Détente from the Air: Monitoring Air Pollution during the Cold War.

PubMed

Rothschild, Rachel

During the period of détente in the 1970s, a Norwegian proposal to construct an air pollution monitoring network for the European continent resulted in the first concrete collaboration between the communist and capitalist blocs after the 1975 Helsinki Accords. Known as the "European-wide monitoring programme" or EMEP, the network earned considerable praise from diplomats for facilitating cooperation across the Iron Curtain. Yet as this article argues, EMEP was strongly influenced by the politics of détente and the constraints of the Cold War even as it helped to decrease tensions. Concerns about national security and sharing data with the enemy shaped both the construction of the monitoring network and the modeling of pollution transport. The article also proposes that environmental monitoring systems like EMEP reveal the ways in which observational technologies can affect conceptions of the natural world and the role of science in public policy.

Air Pollution Monitoring and Mining Based on Sensor Grid in London

PubMed Central

Ma, Yajie; Richards, Mark; Ghanem, Moustafa; Guo, Yike; Hassard, John

2008-01-01

In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a two-layer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm. PMID:27879895

Air Pollution Monitoring and Mining Based on Sensor Grid in London.

PubMed

Ma, Yajie; Richards, Mark; Ghanem, Moustafa; Guo, Yike; Hassard, John

2008-06-01

In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a twolayer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm.

Novel Method for Detection of Air Pollution using Cellular Communication Networks

NASA Astrophysics Data System (ADS)

David, N.; Gao, O. H.

2016-12-01

Air pollution can lead to a wide spectrum of severe and chronic health impacts. Conventional tools for monitoring the phenomenon do not provide a sufficient monitoring solution in a global scale since they are, for example, not representative of the larger space or due to limited deployment as a result of practical limitations, such as: acquisition, installation, and ongoing maintenance costs. Near ground temperature inversions are directly identified with air pollution events since they suppress vertical atmospheric movement and trap pollutants near the ground. Wireless telecommunication links that comprise the data transfer infrastructure in cellular communication networks operate at frequencies of tens of GHz and are affected by different atmospheric phenomena. These systems are deployed near ground level across the globe, including in developing countries such as India, countries in Africa, etc. Many cellular providers routinely store data regarding the received signal levels in the network for quality assurance needs. Temperature inversions cause atmospheric layering, and change the refractive index of the air when compared to standard conditions. As a result, the ducts that are formed can operate, in essence, as atmospheric wave guides, and cause interference (signal amplification / attenuation) in the microwaves measured by the wireless network. Thus, this network is in effect, an existing system of environmental sensors for monitoring temperature inversions and the episodes of air pollution identified with them. This work presents the novel idea, and demonstrates it, in operation, over several events of air pollution which were detected by a standard cellular communication network during routine operation. Reference: David, N. and Gao, H.O. Using cellular communication networks to detect air pollution, Environmental Science & Technology, 2016 (accepted).

Air pollution and climate change effects on health of the Ukrainian forests: monitoring and evalution

Treesearch

Igor F. Buksha; Valentina L. Meshkova; Oleg M. Radchenko; Alexander S. Sidorov

1998-01-01

Forests in the Ukraine are affected by environmental pollution, intensive forestry practice, and recreational uses. These factors make them sensitive to impacts of climate change. Since 1989 Ukraine has participated in the International Cooperative Program on Assessment and Monitoring of Air Pollution Effects on Forests (ICP-Forests). A network of monitoring plots has...

Progress and lessons learned from water-quality monitoring networks

USGS Publications Warehouse

Myers, Donna N.; Ludtke, Amy S.

2017-01-01

Stream-quality monitoring networks in the United States were initiated and expanded after passage of successive federal water-pollution control laws from 1948 to 1972. The first networks addressed information gaps on the extent and severity of stream pollution and served as early warning systems for spills. From 1965 to 1972, monitoring networks expanded to evaluate compliance with stream standards, track emerging issues, and assess water-quality status and trends. After 1972, concerns arose regarding the ability of monitoring networks to determine if water quality was getting better or worse and why. As a result, monitoring networks adopted a hydrologic systems approach targeted to key water-quality issues, accounted for human and natural factors affecting water quality, innovated new statistical methods, and introduced geographic information systems and models that predict water quality at unmeasured locations. Despite improvements, national-scale monitoring networks have declined over time. Only about 1%, or 217, of more than 36,000 US Geological Survey monitoring sites sampled from 1975 to 2014 have been operated throughout the four decades since passage of the 1972 Clean Water Act. Efforts to sustain monitoring networks are important because these networks have collected information crucial to the description of water-quality trends over time and are providing information against which to evaluate future trends.

Water Quality Monitoring Manual.

ERIC Educational Resources Information Center

Mason, Fred J.; Houdart, Joseph F.

This manual is designed for students involved in environmental education programs dealing with water pollution problems. By establishing a network of Environmental Monitoring Stations within the educational system, four steps toward the prevention, control, and abatement of water pollution are proposed. (1) Train students to recognize, monitor,…

Spatiotemporal Patterns, Monitoring Network Design, and Environmental Justice of Air Pollution in the Phoenix Metropolitan Region: A Landscape Approach

NASA Astrophysics Data System (ADS)

Pope, Ronald L.

Air pollution is a serious problem in most urban areas around the world, which has a number of negative ecological and human health impacts. As a result, it's vitally important to detect and characterize air pollutants to protect the health of the urban environment and our citizens. An important early step in this process is ensuring that the air pollution monitoring network is properly designed to capture the patterns of pollution and that all social demographics in the urban population are represented. An important aspect in characterizing air pollution patterns is scale in space and time which, along with pattern and process relationships, is a key subject in the field of landscape ecology. Thus, using multiple landscape ecological methods, this dissertation research begins by characterizing and quantifying the multi-scalar patterns of ozone (O3) and particulate matter (PM10) in the Phoenix, Arizona, metropolitan region. Results showed that pollution patterns are scale-dependent, O3 is a regionally-scaled pollutant at longer temporal scales, and PM10 is a locally-scaled pollutant with patterns sensitive to season. Next, this dissertation examines the monitoring network within Maricopa County. Using a novel multiscale indicator-based approach, the adequacy of the network was quantified by integrating inputs from various academic and government stakeholders. Furthermore, deficiencies were spatially defined and recommendations were made on how to strengthen the design of the network. A sustainability ranking system also provided new insight into the strengths and weaknesses of the network. Lastly, the study addresses the question of whether distinct social groups were experiencing inequitable exposure to pollutants - a key issue of distributive environmental injustice. A novel interdisciplinary method using multi-scalar ambient pollution data and hierarchical multiple regression models revealed environmental inequities between air pollutants and race, ethnicity, age, and socioeconomic classes. The results indicate that changing the scale of the analysis can change the equitable relationship between pollution and demographics. The scientific findings of the scale-dependent relationships among air pollution patterns, network design, and population demographics, brought to light through this study, can help policymakers make informed decisions for protecting the human health and the urban environment in the Phoenix metropolitan region and beyond.

Optimal redistribution of an urban air quality monitoring network using atmospheric dispersion model and genetic algorithm

NASA Astrophysics Data System (ADS)

Hao, Yufang; Xie, Shaodong

2018-03-01

Air quality monitoring networks play a significant role in identifying the spatiotemporal patterns of air pollution, and they need to be deployed efficiently, with a minimum number of sites. The revision and optimal adjustment of existing monitoring networks is crucial for cities that have undergone rapid urban expansion and experience temporal variations in pollution patterns. The approach based on the Weather Research and Forecasting-California PUFF (WRF-CALPUFF) model and genetic algorithm (GA) was developed to design an optimal monitoring network. The maximization of coverage with minimum overlap and the ability to detect violations of standards were developed as the design objectives for redistributed networks. The non-dominated sorting genetic algorithm was applied to optimize the network size and site locations simultaneously for Shijiazhuang city, one of the most polluted cities in China. The assessment on the current network identified the insufficient spatial coverage of SO2 and NO2 monitoring for the expanding city. The optimization results showed that significant improvements were achieved in multiple objectives by redistributing the original network. Efficient coverage of the resulting designs improved to 60.99% and 76.06% of the urban area for SO2 and NO2, respectively. The redistributing design for multi-pollutant including 8 sites was also proposed, with the spatial representation covered 52.30% of the urban area and the overlapped areas decreased by 85.87% compared with the original network. The abilities to detect violations of standards were not improved as much as the other two objectives due to the conflicting nature between the multiple objectives. Additionally, the results demonstrated that the algorithm was slightly sensitive to the parameter settings, with the number of generations presented the most significant effect. Overall, our study presents an effective and feasible procedure for air quality network optimization at a city scale.

Measurement results obtained from air quality monitoring system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turzanski, P.K.; Beres, R.

1995-12-31

An automatic system of air pollution monitoring operates in Cracow since 1991. The organization, assembling and start-up of the network is a result of joint efforts of the US Environmental Protection Agency and the Cracow environmental protection service. At present the automatic monitoring network is operated by the Provincial Inspection of Environmental Protection. There are in total seven stationary stations situated in Cracow to measure air pollution. These stations are supported continuously by one semi-mobile (transportable) station. It allows to modify periodically the area under investigation and therefore the 3-dimensional picture of creation and distribution of air pollutants within Cracowmore » area could be more intelligible.« less

A multi-objective assessment of an air quality monitoring network using environmental, economic, and social indicators and GIS-based models.

PubMed

Pope, Ronald; Wu, Jianguo

2014-06-01

In the United States, air pollution is primarily measured by Air Quality Monitoring Networks (AQMN). These AQMNs have multiple objectives, including characterizing pollution patterns, protecting the public health, and determining compliance with air quality standards. In 2006, the U.S. Environmental Protection Agency issued a directive that air pollution agencies assess the performance of their AQMNs. Although various methods to design and assess AQMNs exist, here we demonstrate a geographic information system (GIS)-based approach that combines environmental, economic, and social indicators through the assessment of the ozone (O3) and particulate matter (PM10) networks in Maricopa County, Arizona. The assessment was conducted in three phases: (1) to evaluate the performance of the existing networks, (2) to identify areas that would benefit from the addition of new monitoring stations, and (3) to recommend changes to the AQMN. A comprehensive set of indicators was created for evaluating differing aspects of the AQMNs' objectives, and weights were applied to emphasize important indicators. Indicators were also classified according to their sustainable development goal. Our results showed that O3 was well represented in the county with some redundancy in terms of the urban monitors. The addition of weights to the indicators only had a minimal effect on the results. For O3, urban monitors had greater social scores, while rural monitors had greater environmental scores. The results did not suggest a need for adding more O3 monitoring sites. For PM10, clustered urban monitors were redundant, and weights also had a minimal effect on the results. The clustered urban monitors had overall low scores; sites near point sources had high environmental scores. Several areas were identified as needing additional PM10 monitors. This study demonstrates the usefulness of a multi-indicator approach to assess AQMNs. Network managers and planners may use this method to assess the performance of air quality monitoring networks in urban regions. The U.S. Environmental Protection Agency issued a directive in 2006 that air pollution agencies assess the performance of their AQMNs; as a result, we developed a GIS-based, multi-objective assessment approach that integrates environmental, economic, and social indicators, and demonstrates its use through assessing the O3 and PM10 monitoring networks in the Phoenix metropolitan area. We exhibit a method of assessing network performance and identifying areas that would benefit from new monitoring stations; also, we demonstrate the effect of adding weights to the indicators. Our study shows that using a multi-indicator approach gave detailed assessment results for the Phoenix AQMN.

Urban air pollution in megacities of the world

NASA Astrophysics Data System (ADS)

Mage, David; Ozolins, Guntis; Peterson, Peter; Webster, Anthony; Orthofer, Rudi; Vandeweerd, Veerle; Gwynne, Michael

Urban air pollution is a major environmental problem in the developing countries of the world. WHO and UNEP created an air pollution monitoring network as part of the Global Environment Monitoring System. This network now covers over 50 cities in 35 developing and developed countries throughout the world. The analyses of the data reported by the network over the past 15-20 yr indicate that the lessons of the prior experiences in the developed countries (U.S.A., U.K.) have not been learned. A study of air pollution in 20 of the 24 megacities of the world (over 10 million people by year 2000) shows that ambient air pollution concentrations are at levels where serious health effects are reported. The expected rise of population in the next century, mainly in the developing countries with a lack of capital for air pollution control, means that there is a great potential that conditions will worsen in many more cities that will reach megacity status. This paper maps the potential for air pollution that cities will experience in the future unless control strategies are developed and implemented during the next several decades.

The expanding scope of air pollution monitoring can facilitate sustainable development.

PubMed

Knox, Andrew; Mykhaylova, Natalia; Evans, Greg J; Lee, Colin J; Karney, Bryan; Brook, Jeffrey R

2013-03-15

This paper explores technologies currently expanding the physical scope of air pollution monitoring and their potential contributions to the assessment of sustainable development. This potential lies largely in the ability of these technologies to address issues typically on the fringe of the air pollution agenda. Air pollution monitoring tends to be primarily focused on human health, and largely neglects other aspects of sustainable development. Sensor networks, with their relatively inexpensive monitoring nodes, allow for monitoring with finer spatiotemporal resolution. This resolution can support more conclusive studies of air pollution's effect on socio-ecological justice and human quality of life. Satellite observation of air pollution allows for wider geographical scope, and in doing so can facilitate studies of air pollution's effects on natural capital and ecosystem resilience. Many air pollution-related aspects of the sustainability of development in human systems are not being given their due attention. Opportunities exist for air pollution monitoring to attend more to these issues. Improvements to the resolution and scale of monitoring make these opportunities realizable. Copyright © 2012 Elsevier B.V. All rights reserved.

Comparison of Remote Sensing and Fixed-Site Monitoring Approaches for Examining Air Pollution and Health in a National Study Population

NASA Technical Reports Server (NTRS)

Prud'homme, Genevieve; Dobbin, Nina A.; Sun, Liu; Burnet, Richard T.; Martin, Randall V.; Davidson, Andrew; Cakmak, Sabit; Villeneuve, Paul J.; Lamsal, Lok N.; vanDonkelaar, Aaron;

A study on exposure assessment for fine dust by using Kriging method: The case of Seoul Metropolitan city

NASA Astrophysics Data System (ADS)

Seo, J. H.; Sohn, J. R.; Mo, R.

2017-12-01

According to the OECD, South Korea is expected to have the highest morality and the biggest economic damage due to the air pollution among OECD members in 2060. Korea's air quality monitoring network is provided by Air Korea of the Korea Environment Corporation under the Ministry of Environment. There are 323 measurement stations installed in 97 different places in Korea. The monitoring network is classified into city atmosphere, roadside, country background concentration, and suburban atmosphere monitoring network, which operate according to each measurement purpose. However, the data from this network shows a large difference in pollutant concentration by region and there is a limit to explain the concentration of pollutants in Seoul, which has a very high population density. The data of the fine dust concentration in Korea University is provided by Seongbuk-gu, but actually Korea University is closer to the measuring station in Dongdaemun-gu. Therefore, a difference will occur if the data from Seongbuk-gu is used to the exposure assessment of residents in nearby Korea University for air pollution. Therefore, this study is aimed to acquire estimated value about areas that have not been measured and implement more precise exposure assessment by comparing it with measured value. On May 8, 2017, when the fine dust concentration was the highest, we calculated the pollutant concentration estimates near Korea University by using measuring network of Seongbukgu and Dongdaemun through Kriging method and compared them with actual measured value which was acquired in this study. Analysis results showed that air pollution concentration near Korea University tends to be overestimated when using the data from Seongbukgu. On the other hand, it showed a similarity to measured value when using data from both Seongbukgu and Dongdaemungu through Kriging method. Therefore, it is necessary to estimate the data about blind spots through Kriging method rather than using the existing national atmospheric monitoring data. In addition, it is required to acquire measured data through government agencies and research institutes in addition to the measurement networking data to calculate more accurate pollution concentration and utilize it for the exposure evaluation.

Monitoring biological effects of contamination in marine fish along French coasts by measurement of ethoxyresorufin-O-deethylase activity.

PubMed

Burgeot, T; Bocquené, G; Pingray, G; Godefroy, D; Legrand, J; Dimeet, J; Marco, F; Vincent, F; Henocque, Y; Jeanneret, H O

1994-11-01

The use of bioindicators to evaluate exposure to the biological effects of chemical pollutants in marine organisms constitutes a new tool in the monitoring field. The establishment of a North Sea monitoring network in 1991, involving such international organizations as the North Sea Task Force, the International Council for the Exploration of the Sea, and the Intergovernmental Oceanography Commission, led French researchers to develop an enzymatic biomarker to monitor biological effects within the National Observation Network. The biomarker, ethoxyresorufin-O-deethylase (EROD), dependent on the CP450 system, has been monitored biannually since 1992 in several species of fish (Callionymus lyra, Limanda limanda, Serranus sp., Mullus barbatus) in two coastal sites particularly exposed to industrial and domestic pollution. A rapid method is used to assay EROD enzymatic activity determined along a pollution gradient, and results are interpreted on a microplate reader. The strategy of this approach is to assess the effects on the marine ecosystem during prolonged exposure to specific pollutants such as polyaromatic hydrocarbons, polychlorinated biphenyls, and dioxins.

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks.

PubMed

Ma, Junjie; Meng, Fansheng; Zhou, Yuexi; Wang, Yeyao; Shi, Ping

2018-02-16

Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths.

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks

PubMed Central

Zhou, Yuexi; Wang, Yeyao; Shi, Ping

2018-01-01

Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths. PMID:29462929

Impact of wildfires on regional air pollution | Science Inventory ...

EPA Pesticide Factsheets

We examine the impact of wildfires and agricultural/prescribed burning on regional air pollution and Air Quality Index (AQI) between 2006 and 2013. We define daily regional air pollution using monitoring sites for ozone (n=1595), PM2.5 collected by Federal Reference Method (n=1058), and constituents of PM2.5 from the Interagency Monitoring of PROtected Visual Environment (IMPROVE) network (n=264) and use satellite image analysis from the NOAA Hazard Mapping System (HMS) to determine days on which visible smoke plumes are detected in the vertical column of the monitoring site. To examine the impact of smoke from these fires on regional air pollution we use a two stage approach, accounting for within site (1st stage) and between site (2nd stage) variations. At the first stage we estimate a monitor-specific plume day effect describing the relative change in pollutant concentrations on the days impacted by smoke plume while accounting for confounding effects of season and temperature_. At the second stage we combine monitor-specific plume day effects with a Bayesian hierarchical model and estimate a pooled nationally-averaged effect. HMS visible smoke plumes were detected on 6% of ozone, 8% of PM2.5 and 6% of IMPROVE network monitoring days. Our preliminary results indicate that the long range transport of air pollutants from wildfires and prescribed burns increase ozone concentration by 11% and PM2.5 mass by 34%. On all of the days where monitoring sites were AQI

Integrated Exposure Assessment Monitoring.

ERIC Educational Resources Information Center

Behar, Joseph V.; And Others

1979-01-01

Integrated Exposure Assessment Monitoring is the coordination of environmental (air, water, land, and crops) monitoring networks to collect systematically pollutant exposure data for a specific receptor, usually man. (Author/BB)

GENASIS national and international monitoring networks for persistent organic pollutants

NASA Astrophysics Data System (ADS)

Brabec, Karel; Dušek, Ladislav; Holoubek, Ivan; Hřebíček, Jiří; Kubásek, Miroslav; Urbánek, Jaroslav

2010-05-01

Persistent organic pollutants (POPs) remain in the centre of scientific attention due to their slow rates of degradation, their toxicity, and potential for both long-range transport and bioaccumulation in living organisms. This group of compounds covers large number of various chemicals from industrial products, such as polychlorinated biphenyls, etc. The GENASIS (Global Environmental Assessment and Information System) information system utilizes data from national and international monitoring networks to obtain as-complete-as-possible set of information and a representative picture of environmental contamination by persistent organic pollutants (POPs). There are data from two main datasets on POPs monitoring: 1.Integrated monitoring of POPs in Košetice Observatory (Czech Republic) which is a long term background site of the European Monitoring and Evaluation Programme (EMEP) for the Central Europe; the data reveals long term trends of POPs in all environmental matrices. The Observatory is the only one in Europe where POPs have been monitored not only in ambient air, but also in wet atmospheric deposition, surface waters, sediments, soil, mosses and needles (integrated monitoring). Consistent data since the year 1996 are available, earlier data (up to 1998) are burdened by high variability and high detection limits. 2.MONET network is ambient air monitoring activities in the Central and Eastern European region (CEEC), Central Asia, Africa and Pacific Islands driven by RECETOX as the Regional Centre of the Stockholm Convention for the region of Central and Eastern Europe under the common name of the MONET networks (MONitoring NETwork). For many of the participating countries these activities generated first data on the atmospheric levels of POPs. The MONET network uses new technologies of air passive sampling, which was developed, tested, and calibrated by RECETOX in cooperation with Environment Canada and Lancaster University, and was originally launched as a model monitoring network providing public administration, private subject, and general public information about air pollution by POPs that had not been previously regularly monitored and whose measurement is further required by global monitoring plan of the Stockholm Convention. The MONET network is international project with many participants. Monitoring in the MONET-CZ network started in 2004 with the pilot project and continues to the current days, MONET CEEC started in 2006 and continues nowadays, MONET Africa started in 2008. The database of the GENASIS systems currently covers MONET-CZ data until the year 2008. The MONET network currently covers 37 countries in the Europe, Asia and Africa with more than 350 sampling sites. The paper will discuss about following topics * Data Fusion in GENASIS: how can GENASIS maximize the value and accuracy of the information gathered from heterogeneous data sources? * Sensor types in GENASIS: which POPs can be measured; what are the physical limitations to achievable accuracy, reliability, and long-term stability of miniaturized sensors; which applications can (not) be realized within these limitations?

PM2.5 monitoring system based on ZigBee wireless sensor network

NASA Astrophysics Data System (ADS)

Lin, Lukai; Li, Xiangshun; Gu, Weiying

2017-06-01

In the view of the haze problem, aiming at improving the deficiency of the traditional PM2.5 monitoring methods, such as the insufficient real-time monitoring, limited transmission distance, high cost and the difficulty to maintain, the atmosphere PM2.5 monitoring system based on ZigBee technology is designed. The system combines the advantages of ZigBee’s low cost, low power consumption, high reliability and GPRS/Internet’s capability of remote transmission of data. Furthermore, it adopts TI’s Z-Stack protocol stack, and selects CC2530 chip and TI’s MSP430 microcontroller as the core, which establishes the air pollution monitoring network that is helpful for the early prediction of major air pollution disasters.

Comparison of remote sensing and fixed-site monitoring approaches for examining air pollution and health in a national study population

NASA Astrophysics Data System (ADS)

Prud'homme, Genevieve; Dobbin, Nina A.; Sun, Liu; Burnett, Richard T.; Martin, Randall V.; Davidson, Andrew; Cakmak, Sabit; Villeneuve, Paul J.; Lamsal, Lok N.; van Donkelaar, Aaron; Peters, Paul A.; Johnson, Markey

2013-12-01

Satellite remote sensing (RS) has emerged as a cutting edge approach for estimating ground level ambient air pollution. Previous studies have reported a high correlation between ground level PM2.5 and NO2 estimated by RS and measurements collected at regulatory monitoring sites. The current study examined associations between air pollution and adverse respiratory and allergic health outcomes using multi-year averages of NO2 and PM2.5 from RS and from regulatory monitoring. RS estimates were derived using satellite measurements from OMI, MODIS, and MISR instruments. Regulatory monitoring data were obtained from Canada's National Air Pollution Surveillance Network. Self-reported prevalence of doctor-diagnosed asthma, current asthma, allergies, and chronic bronchitis were obtained from the Canadian Community Health Survey (a national sample of individuals 12 years of age and older). Multi-year ambient pollutant averages were assigned to each study participant based on their six digit postal code at the time of health survey, and were used as a marker for long-term exposure to air pollution. RS derived estimates of NO2 and PM2.5 were associated with 6-10% increases in respiratory and allergic health outcomes per interquartile range (3.97 μg m-3 for PM2.5 and 1.03 ppb for NO2) among adults (aged 20-64) in the national study population. Risk estimates for air pollution and respiratory/allergic health outcomes based on RS were similar to risk estimates based on regulatory monitoring for areas where regulatory monitoring data were available (within 40 km of a regulatory monitoring station). RS derived estimates of air pollution were also associated with adverse health outcomes among participants residing outside the catchment area of the regulatory monitoring network (p < 0.05). The consistency between risk estimates based on RS and regulatory monitoring as well as the associations between air pollution and health among participants living outside the catchment area for regulatory monitoring suggest that RS can provide useful estimates of long-term ambient air pollution in epidemiologic studies. This is particularly important in rural communities and other areas where monitoring and modeled air pollution data are limited or unavailable.

AN INTEGRATED APPROACH TO AIR QUALITY USING IN SITU, SATELLITE, AND MODELED DATA - FOCUSED ON THE FUTURE OF EARTH OBSERVATIONS SYSTEM (EOS)

EPA Science Inventory

EPA through statutory mandates has monitored air, water, land and human health for the past several decades. The design of the ambient air monitoring networks, for the most part, has been loosely tied single-pollutant networks focused on large urban areas. These networks supply t...

Some applications of remote sensing in atmospheric monitoring programs

NASA Technical Reports Server (NTRS)

Heller, A. N.; Bryson, J. C.; Vasuki, N. C.

1972-01-01

The applications of remote sensing in atmospheric monitoring programs are described. The organization, operations, and functions of an air quality monitoring network at New Castle County, Delaware is discussed. The data obtained by the air quality monitoring network ground stations and the equipment used to obtain atmospheric data are explained. It is concluded that correlation of the information obtained by the network will make it possible to anticipate air pollution problems in the Chesapeake Bay area before a crisis develops.

End-user perspective of low-cost sensors for outdoor air pollution monitoring.

PubMed

Rai, Aakash C; Kumar, Prashant; Pilla, Francesco; Skouloudis, Andreas N; Di Sabatino, Silvana; Ratti, Carlo; Yasar, Ansar; Rickerby, David

2017-12-31

Low-cost sensor technology can potentially revolutionise the area of air pollution monitoring by providing high-density spatiotemporal pollution data. Such data can be utilised for supplementing traditional pollution monitoring, improving exposure estimates, and raising community awareness about air pollution. However, data quality remains a major concern that hinders the widespread adoption of low-cost sensor technology. Unreliable data may mislead unsuspecting users and potentially lead to alarming consequences such as reporting acceptable air pollutant levels when they are above the limits deemed safe for human health. This article provides scientific guidance to the end-users for effectively deploying low-cost sensors for monitoring air pollution and people's exposure, while ensuring reasonable data quality. We review the performance characteristics of several low-cost particle and gas monitoring sensors and provide recommendations to end-users for making proper sensor selection by summarizing the capabilities and limitations of such sensors. The challenges, best practices, and future outlook for effectively deploying low-cost sensors, and maintaining data quality are also discussed. For data quality assurance, a two-stage sensor calibration process is recommended, which includes laboratory calibration under controlled conditions by the manufacturer supplemented with routine calibration checks performed by the end-user under final deployment conditions. For large sensor networks where routine calibration checks are impractical, statistical techniques for data quality assurance should be utilised. Further advancements and adoption of sophisticated mathematical and statistical techniques for sensor calibration, fault detection, and data quality assurance can indeed help to realise the promised benefits of a low-cost air pollution sensor network. Copyright © 2017 Elsevier B.V. All rights reserved.

The Wireless Sensor Network (WSN) Based Coal Ash Impoundments Safety Monitoring System

NASA Astrophysics Data System (ADS)

Sun, E. J.; Nieto, A.; Zhang, X. K.

2017-01-01

Coal ash impoundments are inevitable production of the coal-fired power plants. All coal ash impoundments in North Carolina USA that tested for groundwater contamination are leaking toxic heavy metals and other pollutants. Coal ash impoundments are toxic sources of dangerous pollutants that pose a danger to human and environmental health if the toxins spread to adjacent surface waters and drinking water wells. Coal ash impoundments failures accidents resulted in serious water contamination along with toxic heavy metals. To improve the design and stability of coal ash impoundments, the Development of a Coal Ash Impoundment Safety Monitoring System (CAISM) was proposed based on the implementation of a wireless sensor network (WSN) with the ability to monitor the stability of coal ash impoundments, water level, and saturation levels on-demand and remotely. The monitoring system based on a robust Ad-hoc network could be adapted to different safety conditions.

Air pollution monitoring network on Milan district area structure and results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cavallaro, A.; Gualdi, R.; Tebaldi, G.

1977-01-01

A discussion of air pollution surveillance in the Milan area covers the geographic and winter characteristics of the Milan area; the monitoring network established by the Provincial Laboratory of Hygiene and Prophylaxis, including 25 sulfur dioxide monitors, 3 automatic dust monitors, 6 weather stations, 2 nitrogen oxide monitors, 3 airport noise sensors, and a coordination center; the statistical procedures used to analyze sulfur dioxide concentration data for each month during the period Oct.-Mar. of the winters of 1970-71 through 1974-75; and concludes that the reduction in sulfur dioxide levels is caused by either the reduction in fuel sulfur content (frommore » 1.77Vertical Bar3< to 1.27Vertical Bar3< in the interval under study) or to improved management of heating plants.« less

Identifying exposure disparities in air pollution epidemiology specific to adverse birth outcomes

NASA Astrophysics Data System (ADS)

Geer, Laura A.

2014-10-01

More than 147 million people in the US live in areas where pollutant levels are above regulatory limits and pose a risk to health. Most of the vast network of air pollutant monitors in the US are located in places with higher pollution levels and a higher density of pollutant sources (e.g., point sources from industrial pollution). Vulnerable populations are more likely to live closer to pollutant sources, and thus closer to pollutant monitors. These differential exposures have an impact on maternal and child health; maternal air pollutant exposures have been linked to adverse outcomes such as preterm birth and infant low birth weight. Several studies are highlighted that address methodological approaches in the study of air pollution and health disparities.

Monitoring the effects of air-quality on forests: An overview of the Sierra Ancha Experimental Forest ICP-Level II Site

Treesearch

Peter E. Koestner; Karen A. Koestner; Daniel G. Neary

2012-01-01

The Sierra Ancha International Cooperative Program on Assessment and Monitoring of Air Pollution Effects on Forests study site or (SAEF-ICP II) is part of an international network of cooperative forest monitoring sites spread throughout Europe and the United States. The United Nations Economic Commission for Europe established the ICP II network in 1985 to monitor long...

Summer-time distribution of air pollutants in Sequoia National Park, California

Treesearch

Andrzej Bytnerowicz; Michael Tausz; Rocio Alonso; David Jones; Ronald Johnson; Nancy Grulke

2002-01-01

Concentrations of air pollutants were monitored during the May–November 1999 period on a network of forested sites in Sequoia National Park, California. Measurements were conducted with: (1) active monitors for nitric oxide (NO), nitrogen dioxide (NO2) and ozone (O3); (2) honeycomb denuder/filter pack systems for nitric...

Recognize PM2.5 sources and emission patterns via high-density sensor network: An application case in Beijing

NASA Astrophysics Data System (ADS)

Ba, Yu tao; xian Liu, Bao; Sun, Feng; Wang, Li hua; Zhang, Da wei; Yin, Wen jun

2017-04-01

Beijing suffered severe air pollution during wintertime, 2016, with the unprecedented high level pollutants monitored. As the most dominant pollutant, fine particulate matter (PM2.5) was measured via high-density sensor network (>1000 fixed monitors across 16000 km2 area). This campaign provided precise observations (spatial resolution ≈ 3 km, temporal resolution = 10 min, error of measure < 5 ug/m3) to track potential emission sources. In addition, these observations coupled with WRF-Chem model (Weather Research and Forecasting model coupled with Chemistry) were analyzed to elucidate the effects of atmospheric transportations across regions, both horizontal and vertical, on emission patterns during this haze period. The results quantified the main cause of regional transport and local emission, and highlighted the importance of cross-region cooperation in anti-pollution campaigns.

On the feasibility of measuring urban air pollution by wireless distributed sensor networks.

PubMed

Moltchanov, Sharon; Levy, Ilan; Etzion, Yael; Lerner, Uri; Broday, David M; Fishbain, Barak

2015-01-01

Accurate evaluation of air pollution on human-wellbeing requires high-resolution measurements. Standard air quality monitoring stations provide accurate pollution levels but due to their sparse distribution they cannot capture the highly resolved spatial variations within cities. Similarly, dedicated field campaigns can use tens of measurement devices and obtain highly dense spatial coverage but normally deployment has been limited to short periods of no more than few weeks. Nowadays, advances in communication and sensory technologies enable the deployment of dense grids of wireless distributed air monitoring nodes, yet their sensor ability to capture the spatiotemporal pollutant variability at the sub-neighborhood scale has never been thoroughly tested. This study reports ambient measurements of gaseous air pollutants by a network of six wireless multi-sensor miniature nodes that have been deployed in three urban sites, about 150 m apart. We demonstrate the network's capability to capture spatiotemporal concentration variations at an exceptional fine resolution but highlight the need for a frequent in-situ calibration to maintain the consistency of some sensors. Accordingly, a procedure for a field calibration is proposed and shown to improve the system's performance. Overall, our results support the compatibility of wireless distributed sensor networks for measuring urban air pollution at a sub-neighborhood spatial resolution, which suits the requirement for highly spatiotemporal resolved measurements at the breathing-height when assessing exposure to urban air pollution. Copyright © 2014 Elsevier B.V. All rights reserved.

EPA NetDMR CROMERR System Checklist

EPA Pesticide Factsheets

The Network Disharge Monitoring Report (NetDMR) electronic reporting system is used for the receipt of discharge monitoring reports (DMRs) under the National Pollutant Discharge Elimination System (NPDES) program,

Community Air Sensor Network (CAIRSENSE) project ...

EPA Pesticide Factsheets

Advances in air pollution sensor technology have enabled the development of small and low cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring networks with additional geographic and temporal measurement resolution, if the data quality were sufficient. To understand the capability of emerging air sensor technology, the Community Air Sensor Network (CAIRSENSE) project deployed low cost, continuous and commercially-available air pollution sensors at a regulatory air monitoring site and as a local sensor network over a surrounding ~2 km area in Southeastern U.S. Co-location of sensors measuring oxides of nitrogen, ozone, carbon monoxide, sulfur dioxide, and particles revealed highly variable performance, both in terms of comparison to a reference monitor as well as whether multiple identical sensors reproduced the same signal. Multiple ozone, nitrogen dioxide, and carbon monoxide sensors revealed low to very high correlation with a reference monitor, with Pearson sample correlation coefficient (r) ranging from 0.39 to 0.97, -0.25 to 0.76, -0.40 to 0.82, respectively. The only sulfur dioxide sensor tested revealed no correlation (r 0.5), step-wise multiple linear regression was performed to determine if ambient temperature, relative humidity (RH), or age of the sensor in sampling days could be used in a correction algorihm to im

CASTNET

EPA Pesticide Factsheets

The Clean Air Status and Trends Network (CASTNET) is a national air quality monitoring network designed to provide data to assess trends in air quality, atmospheric deposition, and ecological effects due to changes in air pollutant emissions.

Prediction of air pollutant concentration based on sparse response back-propagation training feedforward neural networks.

PubMed

Ding, Weifu; Zhang, Jiangshe; Leung, Yee

2016-10-01

In this paper, we predict air pollutant concentration using a feedforward artificial neural network inspired by the mechanism of the human brain as a useful alternative to traditional statistical modeling techniques. The neural network is trained based on sparse response back-propagation in which only a small number of neurons respond to the specified stimulus simultaneously and provide a high convergence rate for the trained network, in addition to low energy consumption and greater generalization. Our method is evaluated on Hong Kong air monitoring station data and corresponding meteorological variables for which five air quality parameters were gathered at four monitoring stations in Hong Kong over 4 years (2012-2015). Our results show that our training method has more advantages in terms of the precision of the prediction, effectiveness, and generalization of traditional linear regression algorithms when compared with a feedforward artificial neural network trained using traditional back-propagation.

Transboundary Air Pollution over the Central Himalayas: Monitoring network and Preliminary Results

NASA Astrophysics Data System (ADS)

Zhang, Qianggong; Kang, Shichang

2016-04-01

The Himalayas, stretching over 3000 kms along west-east, separates South Asia continent and the Tibetan Plateau with its extreme high altitudes. The South Asia is being increasingly recognized to be among the hotspots of air pollution, posing multi-effects on regional climate and environment. Recent monitoring and projection have indicated an accelerated decrease of glacier and increasing glacier runoff in the Himalayas, and a remarkable phenomenon has been recognized in the Himalayas that long-range transport atmospheric pollutants (e.g., black carbon and dust) deposited on glacier surface can promote glacier melt, and in turns, may liberate historical contaminant legacy in glaciers into downward ecosystems. To understand the air pollution variation and how they can infiltrate the Himalayas and beyond, we started to operate a coordinated atmospheric pollution monitoring network composing 11 sites with 5 in Nepal and 6 in Tibet since April 2013. Atmospheric total suspended particles ( TSP < 100 μm) are collected for 24h at an interval of 3-6 days at all sites. Black carbon, typical persistent organic pollutants (PAHs) and heavy metals (particulate-bounded mercury) are measured to reveal their spatial and temporal distributions. Results revealed a consistent gradient decrease in almost all analyzed parameters along south-north gradient across the Himalayas, with a clear seasonal variation of higher values in pre-monsoon seasons. Analysis of geochemical signatures of carbonaceous aerosols indicated dominant sources from biomass burning and vehicle exhaust. PAHs concentrations and signatures from soils and aerosols indicated that low-ring PAHs can readily transport across the Himalayas. Integrated analysis of satellite images and air mass trajectories suggested that the transboundary air pollution over the Himalayas is episodic and is likely concentrated in pre-monsoon seasons. Our results emphasis the potential transport and impact of air pollution from South Asia to Himalayas and further inland Tibetan Plateau. The monitoring network will be continuously operated to provide basis for defining the transboundary air pollution and their impact on the environments and ecosystems over the Himalayas and the Tibetan Plateau.

AEROCAN, the Canadian sub-network of AERONET: Aerosol monitoring and air quality applications

NASA Astrophysics Data System (ADS)

Sioris, Christopher E.; Abboud, Ihab; Fioletov, Vitali E.; McLinden, Chris A.

2017-10-01

Previous studies have demonstrated the utility of AERONET (Aerosol Robotic Network) aerosol optical depth (AOD) data for monitoring the spatial variability of particulate matter (PM) in relatively polluted regions of the globe. AEROCAN, a Canadian sub-network of AERONET, was established 20 years ago and currently consists of twenty sites across the country. In this study, we examine whether the AEROCAN sunphotometer data provide evidence of anthropogenic contributions to ambient particulate matter concentrations in relatively clean Canadian locations. The similar weekly cycle of AOD and PM2.5 over Toronto provides insight into the impact of local pollution on observed AODs. High temporal correlations (up to r = 0.78) between daily mean AOD (or its fine-mode component) and PM2.5 are found at southern Ontario AEROCAN sites during May-August, implying that the variability in the aerosol load resides primarily in the boundary layer and that sunphotometers capture day-to-day PM2.5 variations at moderately polluted sites. The sensitivity of AEROCAN AOD data to anthropogenic surface-level aerosol enhancements is demonstrated using boundary-layer wind information for sites near sources of aerosol or its precursors. An advantage of AEROCAN relative to the Canadian in-situ National Air Pollution Surveillance (NAPS) network is the ability to detect free tropospheric aerosol enhancements, which can be large in the case of lofted forest fire smoke or desert dust. These aerosol plumes eventually descend to the surface, sometimes in populated areas, exacerbating air quality. In cases of large AOD (≥0.4), AEROCAN data are also useful in characterizing the aerosol type. The AEROCAN network includes three sites in the high Arctic, a region not sampled by the NAPS PM2.5 monitoring network. These polar sites show the importance of long-range transport and meteorology in the Arctic haze phenomenon. Also, AEROCAN sunphotometers are, by design and due to regular maintenance, the most valuable monitors available for long term aerosol trends. Using a variety of data analysis techniques and timescales, the usefulness of this ground-based remote-sensing sub-network for providing information relevant to air quality is demonstrated.

EXPOSURE MONITORING COMPONENT FOR DETROIT CHILDREN'S HEALTH STUDY ( DCHS )

EPA Science Inventory

Conventional, regulatory-based air monitoring is expensive and, thus, conducted at one or few locations in a city. This provides limited info on intra-urban variability and spatial distribution of air pollution. Research-oriented urban network monitoring has progressed with inc...

Mobile Sensors and Applications for Air Pollutants

EPA Science Inventory

Executive Summary The public has long been interested in understanding what pollutants are in the air they breathe so they can best protect their environmental health and welfare. The current air quality monitoring network consists of discrete stations with expensive equipment ...

EPA scientists develop Federal Reference & Equivalent Methods for measuring key air pollutants

EPA Pesticide Factsheets

EPA operates a nationwide air monitoring network to measure six primary air pollutants: carbon monoxide, lead, sulfur dioxide, ozone, nitrogen dioxide, and particulate matter as part of its mission to protect human health and the environment.

A state of the art regarding urban air quality prediction models

NASA Astrophysics Data System (ADS)

Croitoru, Cristiana; Nastase, Ilinca

2018-02-01

Urban pollution represents an increasing risk to residents of urban regions, particularly in large, over-industrialized cities knowing that the traffic is responsible for more than 25% of air gaseous pollutants and dust particles. Air quality modelling plays an important role in addressing air pollution control and management approaches by providing guidelines for better and more efficient air quality forecasting, along with smart monitoring sensor networks. The advances in technology regarding simulations, forecasting and monitoring are part of the new smart cities which offers a healthy environment for their occupants.

Value of information analysis for groundwater quality monitoring network design Case study: Eocene Aquifer, Palestine

NASA Astrophysics Data System (ADS)

Khader, A.; McKee, M.

2010-12-01

Value of information (VOI) analysis evaluates the benefit of collecting additional information to reduce or eliminate uncertainty in a specific decision-making context. It makes explicit any expected potential losses from errors in decision making due to uncertainty and identifies the “best” information collection strategy as one that leads to the greatest expected net benefit to the decision-maker. This study investigates the willingness to pay for groundwater quality monitoring in the Eocene Aquifer, Palestine, which is an unconfined aquifer located in the northern part of the West Bank. The aquifer is being used by 128,000 Palestinians to fulfill domestic and agricultural demands. The study takes into account the consequences of pollution and the options the decision maker might face. Since nitrate is the major pollutant in the aquifer, the consequences of nitrate pollution were analyzed, which mainly consists of the possibility of methemoglobinemia (blue baby syndrome). In this case, the value of monitoring was compared to the costs of treating for methemoglobinemia or the costs of other options like water treatment, using bottled water or importing water from outside the aquifer. And finally, an optimal monitoring network that takes into account the uncertainties in recharge (climate), aquifer properties (hydraulic conductivity), pollutant chemical reaction (decay factor), and the value of monitoring is designed by utilizing a sparse Bayesian modeling algorithm called a relevance vector machine.

76 FR 17599 - Approval and Promulgation of Implementation Plans; State of Kansas

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-30

... strategies to reduce air pollution. KDHE submits a 5-Year Ambient Air Monitoring Network Assessment to EPA... control of air pollution with the Secretary of Health and Environment (``Secretary''). The Secretary in... pollution is defined in KSA Section 65-3002(c) as the presence in the outdoor atmosphere of one or more air...

Using Mobile Monitoring to Assess Spatial Variability in Urban Air Pollution Levels: Opportunities and Challenges (Invited)

NASA Astrophysics Data System (ADS)

Larson, T.

2010-12-01

Measuring air pollution concentrations from a moving platform is not a new idea. Historically, however, most information on the spatial variability of air pollutants have been derived from fixed site networks operating simultaneously over space. While this approach has obvious advantages from a regulatory perspective, with the increasing need to understand ever finer scales of spatial variability in urban pollution levels, the use of mobile monitoring to supplement fixed site networks has received increasing attention. Here we present examples of the use of this approach: 1) to assess existing fixed-site fine particle networks in Seattle, WA, including the establishment of new fixed-site monitoring locations; 2) to assess the effectiveness of a regulatory intervention, a wood stove burning ban, on the reduction of fine particle levels in the greater Puget Sound region; and 3) to assess spatial variability of both wood smoke and mobile source impacts in both Vancouver, B.C. and Tacoma, WA. Deducing spatial information from the inherently spatio-temporal measurements taken from a mobile platform is an area that deserves further attention. We discuss the use of “fuzzy” points to address the fine-scale spatio-temporal variability in the concentration of mobile source pollutants, specifically to deduce the broader distribution and sources of fine particle soot in the summer in Vancouver, B.C. We also discuss the use of principal component analysis to assess the spatial variability in multivariate, source-related features deduced from simultaneous measurements of light scattering, light absorption and particle-bound PAHs in Tacoma, WA. With increasing miniaturization and decreasing power requirements of air monitoring instruments, the number of simultaneous measurements that can easily be made from a mobile platform is rapidly increasing. Hopefully the methods used to design mobile monitoring experiments for differing purposes, and the methods used to interpret those measurements will keep pace.

Development of wireless sensor network for monitoring indoor air pollutant

NASA Astrophysics Data System (ADS)

Saad, Shaharil Mad; Shakaff, Ali Yeon Md; Saad, Abdul Rahman Mohd; Yusof @ Kamarudin, Azman Muhamad

2015-05-01

The air that we breathe with everyday contains variety of contaminants and particles. Some of these contaminants and particles are hazardous to human health. Most of the people don't realize that the content of air they being exposed to whether it was a good or bad air quality. The air quality whether in indoor or outdoor environment can be influenced by physical factors like dust particles, gaseous pollutants (including carbon dioxide, carbon monoxide and volatile organic compounds) and biological like molds and bacteria growth which largely depend on temperature and humidity condition of a room. These kinds of pollutants can affect human health, physical reaction, comfort or work performance. In this study, a wireless sensor network (WSN) monitoring system for monitor air pollutant in indoor environment was developed. The system was divided into three parts: web-based interface program, sensing module and a base station. The measured data was displayed on the web which is can be accessed by the user. The result shows that the overall measured parameters were meet the acceptable limit, requirement and criteria of indoor air pollution inside the building. The research can be used to improve the indoor air quality level in order to create a comfortable working and healthy environment for the occupants inside the building.

Potential assessment of the "support vector machine" method in forecasting ambient air pollutant trends.

PubMed

Lu, Wei-Zhen; Wang, Wen-Jian

2005-04-01

Monitoring and forecasting of air quality parameters are popular and important topics of atmospheric and environmental research today due to the health impact caused by exposing to air pollutants existing in urban air. The accurate models for air pollutant prediction are needed because such models would allow forecasting and diagnosing potential compliance or non-compliance in both short- and long-term aspects. Artificial neural networks (ANN) are regarded as reliable and cost-effective method to achieve such tasks and have produced some promising results to date. Although ANN has addressed more attentions to environmental researchers, its inherent drawbacks, e.g., local minima, over-fitting training, poor generalization performance, determination of the appropriate network architecture, etc., impede the practical application of ANN. Support vector machine (SVM), a novel type of learning machine based on statistical learning theory, can be used for regression and time series prediction and have been reported to perform well by some promising results. The work presented in this paper aims to examine the feasibility of applying SVM to predict air pollutant levels in advancing time series based on the monitored air pollutant database in Hong Kong downtown area. At the same time, the functional characteristics of SVM are investigated in the study. The experimental comparisons between the SVM model and the classical radial basis function (RBF) network demonstrate that the SVM is superior to the conventional RBF network in predicting air quality parameters with different time series and of better generalization performance than the RBF model.

CitySpace Air Sensor Network Project Conducted to Test New Monitoring Capabilities

EPA Pesticide Factsheets

The CitySpace project is a new research effort by EPA to field test new, lower-cost air pollution sensors in a mid-sized city to understand how this emerging technology can add valuable information on air pollution patterns in neighboorhoods.

Network modeling of PM10 concentration in Malaysia

NASA Astrophysics Data System (ADS)

Supian, Muhammad Nazirul Aiman Abu; Bakar, Sakhinah Abu; Razak, Fatimah Abdul

2017-08-01

Air pollution is not a new phenomenon in Malaysia. The Department of Environment (DOE) monitors the country's ambient air quality through a network of 51 stations. The air quality is measured using the Air Pollution Index (API) which is mainly recorded based on the concentration of particulate matter, PM10 readings. The Continuous Air Quality Monitoring (CAQM) stations are located in various places across the country. In this study, a network model of air quality based on PM10 concen tration for selected CAQM stations in Malaysia has been developed. The model is built using a graph formulation, G = (V, E) where vertex, V is a set of CAQM stations and edges, E is a set of correlation values for each pair of vertices. The network measurements such as degree distributions, closeness centrality, and betweenness centrality are computed to analyse the behaviour of the network. As a result, a rank of CAQM stations has been produced based on their centrality characteristics.

Characteristics and applications of small, portable gaseous air pollution monitors.

PubMed

McKercher, Grant R; Salmond, Jennifer A; Vanos, Jennifer K

2017-04-01

Traditional approaches for measuring air quality based on fixed measurements are inadequate for personal exposure monitoring. To combat this issue, the use of small, portable gas-sensing air pollution monitoring technologies is increasing, with researchers and individuals employing portable and mobile methods to obtain more spatially and temporally representative air pollution data. However, many commercially available options are built for various applications and based on different technologies, assumptions, and limitations. A review of the monitor characteristics of small, gaseous monitors is missing from current scientific literature. A state-of-the-art review of small, portable monitors that measure ambient gaseous outdoor pollutants was developed to address broad trends during the last 5-10 years, and to help future experimenters interested in studying gaseous air pollutants choose monitors appropriate for their application and sampling needs. Trends in small, portable gaseous air pollution monitor uses and technologies were first identified and discussed in a review of literature. Next, searches of online databases were performed for articles containing specific information related to performance, characteristics, and use of such monitors that measure one or more of three criteria gaseous air pollutants: ozone, nitrogen dioxide, and carbon monoxide. All data were summarized into reference tables for comparison between applications, physical features, sensing capabilities, and costs of the devices. Recent portable monitoring trends are strongly related to associated applications and audiences. Fundamental research requires monitors with the best individual performance, and thus the highest cost technology. Monitor networking favors real-time capabilities and moderate cost for greater reproduction. Citizen science and crowdsourcing applications allow for lower-cost components; however important strengths and limitations for each application must be addressed or acknowledged for the given use. Copyright © 2016 Elsevier Ltd. All rights reserved.

Air Pollution Data for Model Evaluation and Application

EPA Science Inventory

One objective of designing an air pollution monitoring network is to obtain data for evaluating air quality models that are used in the air quality management process and scientific discovery.^1.2 A common use is to relate emissions to air quality, including assessing ...

Monitoring Street-Level Spatial-Temporal Variations of Carbon Monoxide in Urban Settings Using a Wireless Sensor Network (WSN) Framework

PubMed Central

Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

2013-01-01

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management. PMID:24287859

Monitoring street-level spatial-temporal variations of carbon monoxide in urban settings using a wireless sensor network (WSN) framework.

PubMed

Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

2013-11-27

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management.

Air quality monitor and acid rain networks

NASA Technical Reports Server (NTRS)

Rudolph, H.

1980-01-01

The air quality monitor program which consists of two permanent air monitor stations (PAMS's) and four mobile shuttle pollutant air monitor stations (SPAMS's) is evaluated. The PAMS measures SO sub X, NO sub X particulates, CO, O3, and nonmethane hydrocarbons. The SPAMS measures O3, SO2, HCl, and particulates. The collection and analysis of data in the rain monitor program are discussed.

Development and field validation of a community-engaged particulate matter air quality monitoring network in Imperial, California, USA.

PubMed

Carvlin, Graeme N; Lugo, Humberto; Olmedo, Luis; Bejarano, Ester; Wilkie, Alexa; Meltzer, Dan; Wong, Michelle; King, Galatea; Northcross, Amanda; Jerrett, Michael; English, Paul B; Hammond, Donald; Seto, Edmund

2017-12-01

The Imperial County Community Air Monitoring Network was developed as part of a community-engaged research study to provide real-time particulate matter (PM) air quality information at a high spatial resolution in Imperial County, California. The network augmented the few existing regulatory monitors and increased monitoring near susceptible populations. Monitors were both calibrated and field validated, a key component of evaluating the quality of the data produced by the community monitoring network. This paper examines the performance of a customized version of the low-cost Dylos optical particle counter used in the community air monitors compared with both PM 2.5 and PM 10 (particulate matter with aerodynamic diameters <2.5 and <10 μm, respectively) federal equivalent method (FEM) beta-attenuation monitors (BAMs) and federal reference method (FRM) gravimetric filters at a collocation site in the study area. A conversion equation was developed that estimates particle mass concentrations from the native Dylos particle counts, taking into account relative humidity. The R 2 for converted hourly averaged Dylos mass measurements versus a PM 2.5 BAM was 0.79 and that versus a PM 10 BAM was 0.78. The performance of the conversion equation was evaluated at six other sites with collocated PM 2.5 environmental beta-attenuation monitors (EBAMs) located throughout Imperial County. The agreement of the Dylos with the EBAMs was moderate to high (R 2 = 0.35-0.81). The performance of low-cost air quality sensors in community networks is currently not well documented. This paper provides a methodology for quantifying the performance of a next-generation Dylos PM sensor used in the Imperial County Community Air Monitoring Network. This air quality network provides data at a much finer spatial and temporal resolution than has previously been possible with government monitoring efforts. Once calibrated and validated, these high-resolution data may provide more information on susceptible populations, assist in the identification of air pollution hotspots, and increase community awareness of air pollution.

Acid Rain

MedlinePlus

... Clean Air Status and Trends Network (CASTNET) Surface Water Monitoring National Atmospheric Deposition Program (NADP) Exit Interstate Air Pollution Transport Contact Us to ask a question, provide ...

ASSESSING TRANSBOUNDARY INFLUENCES IN THE LOWER RIO GRANDE VALLEY

EPA Science Inventory

The Lower Rio Grande Valley Transboundary Air Pollution Project (TAPP) was a U.S.-Mexico Border XXI Program project to assess transboundary air pollution in and near Brownsville, Texas. The study used a three-site air monitoring network very close to the border to capture the d...

Potential assessment of a neural network model with PCA/RBF approach for forecasting pollutant trends in Mong Kok urban air, Hong Kong.

PubMed

Lu, Wei-Zhen; Wang, Wen-Jian; Wang, Xie-Kang; Yan, Sui-Hang; Lam, Joseph C

2004-09-01

The forecasting of air pollutant trends has received much attention in recent years. It is an important and popular topic in environmental science, as concerns have been raised about the health impacts caused by unacceptable ambient air pollutant levels. Of greatest concern are metropolitan cities like Hong Kong. In Hong Kong, respirable suspended particulates (RSP), nitrogen oxides (NOx), and nitrogen dioxide (NO2) are major air pollutants due to the dominant usage of diesel fuel by commercial vehicles and buses. Hence, the study of the influence and the trends relating to these pollutants is extremely significant to the public health and the image of the city. The use of neural network techniques to predict trends relating to air pollutants is regarded as a reliable and cost-effective method for the task of prediction. The works reported here involve developing an improved neural network model that combines both the principal component analysis technique and the radial basis function network and forecasts pollutant tendencies based on a recorded database. Compared with general neural network models, the proposed model features a more simple network architecture, a faster training speed, and a more satisfactory prediction performance. The improved model was evaluated with hourly time series of RSP, NOx and NO2 concentrations monitored at the Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000 and proved to be effective. The model developed is a potential tool for forecasting air quality parameters and is superior to traditional neural network methods.

A black carbon air quality network

NASA Astrophysics Data System (ADS)

Kirchstetter, T.; Caubel, J.; Cados, T.; Preble, C.; Rosen, A.

2016-12-01

We developed a portable, power efficient black carbon sensor for deployment in an air quality network in West Oakland, California. West Oakland is a San Francisco Bay Area residential/industrial community adjacent to regional port and rail yard facilities, and is surrounded by major freeways. As such, the community is affected by diesel particulate matter emissions from heavy-duty diesel trucks, locomotives, and ships associated with freight movement. In partnership with Environmental Defense Fund, the Bay Area Air Quality Management District, and the West Oakland Environmental Indicators Project, we are collaborating with community members to build and operate a 100-sensor black carbon measurement network for a period of several months. The sensor employs the filter-based light transmission method to measure black carbon. Each sensor node in the network transmits data hourly via SMS text messages. Cost, power consumption, and performance are considered in choosing components (e.g., pump) and operating conditions (e.g., sample flow rate). In field evaluation trials over several weeks at three monitoring locations, the sensor nodes provided black carbon concentrations comparable to commercial instruments and ran autonomously for a week before sample filters and rechargeable batteries needed to be replaced. Buildup to the 100-sensor network is taking place during Fall 2016 and will overlap with other ongoing air monitoring projects and monitoring platforms in West Oakland. Sensors will be placed along commercial corridors, adjacent to freeways, upwind of and within the Port, and throughout the residential community. Spatial and temporal black carbon concentration patterns will help characterize pollution sources and demonstrate the value of sensing networks for characterizing intra-urban air pollution concentrations and exposure to air pollution.

Fieldservers and Sensor Service Grid as Real-time Monitoring Infrastructure for Ubiquitous Sensor Networks

PubMed Central

Honda, Kiyoshi; Shrestha, Aadit; Witayangkurn, Apichon; Chinnachodteeranun, Rassarin; Shimamura, Hiroshi

2009-01-01

The fieldserver is an Internet based observation robot that can provide an outdoor solution for monitoring environmental parameters in real-time. The data from its sensors can be collected to a central server infrastructure and published on the Internet. The information from the sensor network will contribute to monitoring and modeling on various environmental issues in Asia, including agriculture, food, pollution, disaster, climate change etc. An initiative called Sensor Asia is developing an infrastructure called Sensor Service Grid (SSG), which integrates fieldservers and Web GIS to realize easy and low cost installation and operation of ubiquitous field sensor networks. PMID:22574018

Using Arc/Info GIS to help implement the National Pollutant Discharge Elimination System (NPDES) stormwater permit for Los Angeles County

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levine, D.A.; Pace, P.J.; Woods, J.A.

1997-06-01

One of Los Angeles County Department of Public Works` many responsibilities is to manage non-point pollution that enters the storm drain network within Los Angeles County. The management of this non-point source pollution is mandated by the NPDES guidelines under the Federal Clean Water Act. These guidelines require the County to monitor the drainage network and the storm water and urban runoff flowing through it. The County covers over 3,117 square miles, with the NPDES Permit covering over 3,100 square miles and over 2500 miles of storm drains. A proposed solution to monitor and manage this vast geographic area ismore » centered upon an Arc/Info GIS. Some of the many concerns which need to be addressed include the administration and evaluation of Best Management Practices (BMP`s), storm drain inspection for illegal connections and illicit discharges, and pollutant load assessment and modeling. The storm drain network and other coverages will be related to external data bases currently used for facility management and planning. This system would be used for query purposes to perform spatial modeling and {open_quotes}what if{close_quotes} scenarios needed to create maps and reports required by the permit and to evaluate various BMP implementation strategies.« less

Ubiquitous Sensor Networking for Development (USN4D): an application to pollution monitoring.

PubMed

Bagula, Antoine; Zennaro, Marco; Inggs, Gordon; Scott, Simon; Gascon, David

2012-01-01

This paper presents a new Ubiquitous Sensor Network (USN) Architecture to be used in developing countries and reveals its usefulness by highlighting some of its key features. In complement to a previous ITU proposal, our architecture referred to as "Ubiquitous Sensor Network for Development (USN4D)" integrates in its layers features such as opportunistic data dissemination, long distance deployment and localisation of information to meet the requirements of the developing world. Besides describing some of the most important requirements for the sensor equipment to be used in a USN4D setting, we present the main features and experiments conducted using the "WaspNet" as one of the wireless sensor deployment platforms that meets these requirements. Furthermore, building upon "WaspNet" platform, we present an application to Air pollution Monitoring in the city of Cape Town, in South Africa as one of the first steps towards building community wireless sensor networks (CSN) in the developing world using off-the-shelf sensor equipment.

Ubiquitous Sensor Networking for Development (USN4D): An Application to Pollution Monitoring

PubMed Central

Bagula, Antoine; Zennaro, Marco; Inggs, Gordon; Scott, Simon; Gascon, David

2012-01-01

This paper presents a new Ubiquitous Sensor Network (USN) Architecture to be used in developing countries and reveals its usefulness by highlighting some of its key features. In complement to a previous ITU proposal, our architecture referred to as “Ubiquitous Sensor Network for Development (USN4D)” integrates in its layers features such as opportunistic data dissemination, long distance deployment and localisation of information to meet the requirements of the developing world. Besides describing some of the most important requirements for the sensor equipment to be used in a USN4D setting, we present the main features and experiments conducted using the “WaspNet” as one of the wireless sensor deployment platforms that meets these requirements. Furthermore, building upon “WaspNet” platform, we present an application to Air pollution Monitoring in the city of Cape Town, in South Africa as one of the first steps towards building community wireless sensor networks (CSN) in the developing world using off-the-shelf sensor equipment. PMID:22368476

Measurement error in time-series analysis: a simulation study comparing modelled and monitored data.

PubMed

Butland, Barbara K; Armstrong, Ben; Atkinson, Richard W; Wilkinson, Paul; Heal, Mathew R; Doherty, Ruth M; Vieno, Massimo

2013-11-13

Assessing health effects from background exposure to air pollution is often hampered by the sparseness of pollution monitoring networks. However, regional atmospheric chemistry-transport models (CTMs) can provide pollution data with national coverage at fine geographical and temporal resolution. We used statistical simulation to compare the impact on epidemiological time-series analysis of additive measurement error in sparse monitor data as opposed to geographically and temporally complete model data. Statistical simulations were based on a theoretical area of 4 regions each consisting of twenty-five 5 km × 5 km grid-squares. In the context of a 3-year Poisson regression time-series analysis of the association between mortality and a single pollutant, we compared the error impact of using daily grid-specific model data as opposed to daily regional average monitor data. We investigated how this comparison was affected if we changed the number of grids per region containing a monitor. To inform simulations, estimates (e.g. of pollutant means) were obtained from observed monitor data for 2003-2006 for national network sites across the UK and corresponding model data that were generated by the EMEP-WRF CTM. Average within-site correlations between observed monitor and model data were 0.73 and 0.76 for rural and urban daily maximum 8-hour ozone respectively, and 0.67 and 0.61 for rural and urban loge(daily 1-hour maximum NO2). When regional averages were based on 5 or 10 monitors per region, health effect estimates exhibited little bias. However, with only 1 monitor per region, the regression coefficient in our time-series analysis was attenuated by an estimated 6% for urban background ozone, 13% for rural ozone, 29% for urban background loge(NO2) and 38% for rural loge(NO2). For grid-specific model data the corresponding figures were 19%, 22%, 54% and 44% respectively, i.e. similar for rural loge(NO2) but more marked for urban loge(NO2). Even if correlations between model and monitor data appear reasonably strong, additive classical measurement error in model data may lead to appreciable bias in health effect estimates. As process-based air pollution models become more widely used in epidemiological time-series analysis, assessments of error impact that include statistical simulation may be useful.

Short-term monitoring of benzene air concentration in an urban area: a preliminary study of application of Kruskal-Wallis non-parametric test to assess pollutant impact on global environment and indoor.

PubMed

Mura, Maria Chiara; De Felice, Marco; Morlino, Roberta; Fuselli, Sergio

2010-01-01

In step with the need to develop statistical procedures to manage small-size environmental samples, in this work we have used concentration values of benzene (C6H6), concurrently detected by seven outdoor and indoor monitoring stations over 12 000 minutes, in order to assess the representativeness of collected data and the impact of the pollutant on indoor environment. Clearly, the former issue is strictly connected to sampling-site geometry, which proves critical to correctly retrieving information from analysis of pollutants of sanitary interest. Therefore, according to current criteria for network-planning, single stations have been interpreted as nodes of a set of adjoining triangles; then, a) node pairs have been taken into account in order to estimate pollutant stationarity on triangle sides, as well as b) node triplets, to statistically associate data from air-monitoring with the corresponding territory area, and c) node sextuplets, to assess the impact probability of the outdoor pollutant on indoor environment for each area. Distributions from the various node combinations are all non-Gaussian, in the consequently, Kruskal-Wallis (KW) non-parametric statistics has been exploited to test variability on continuous density function from each pair, triplet and sextuplet. Results from the above-mentioned statistical analysis have shown randomness of site selection, which has not allowed a reliable generalization of monitoring data to the entire selected territory, except for a single "forced" case (70%); most important, they suggest a possible procedure to optimize network design.

Ambient Greenhouse Gas (GHG) Observations in the San Francisco Bay Area of California Using a Fixed-site Monitoring Network

NASA Astrophysics Data System (ADS)

Martien, P. T.; Guha, A.; Bower, J.; Perkins, I.; Randall, S.; Young, A.; Hilken, H.; Stevenson, E.

2016-12-01

The Bay Area Air Quality Management District is the greater San Francisco Bay metropolitan area's chief air quality regulatory agency. Aligning itself with the Governor's Executive Order S-3-05, the Air District has set a goal to reduce the region's GHG emissions by 80% below 1990 levels by the year 2050. The Air District's 2016 Clean Air Plan will lay out the agency's vision and actions to put the region on a path forward towards achieving the 2050 goal while also reducing air pollution and related health impacts. The 2016 Plan has three overarching objectives: 1) develop a multi-pollutant emissions control strategy, (2) reduce population exposure to harmful air pollutants, especially in vulnerable communities, and (3) protect climate through a comprehensive Regional Climate Protection Strategy. To accomplish one of 2016 Plan's control measures (SL3 - Greenhouse Gas Monitoring and Measurement Network), the Air District has set up a long-term, ambient GHG monitoring network at four sites. The first site is located north and upwind of the urban core at Bodega Bay by the Pacific Coast. It mostly receives clean marine inflow and serves as the regional background site. The other three sites are strategically located at regional exit points for Bay Area plumes that presumably contain well-mixed GHG enhancements from local sources. CO2 and CH4are being measured continuously at the fixed-sites, along with combustion tracer CO and other air pollutants. In the longer term, the network will allow the Air District to monitor ambient concentrations of GHGs and thus evaluate the effectiveness of its policy, regulation and enforcement efforts. We present data trends from the first year of operation of the fixed-site monitoring network including monthly and seasonal patterns, diurnal variations and regional enhancements at individual sites above background concentrations. We also locate an isotopic methane instrument (Picarro, G132-i) for a short duration (a week) at each of the four fixed sites. A comparison of 13C/12C content of ambient CH4 at the downwind sites with the regional background isotopic methane signal at the coastal site provides a valuable top-down assessment of the relative distribution of biogenic versus fossil-fuel based sources of CH4 in the region.

Assessment of water quality monitoring for the optimal sensor placement in lake Yahuarcocha using pattern recognition techniques and geographical information systems.

PubMed

Jácome, Gabriel; Valarezo, Carla; Yoo, Changkyoo

2018-03-30

Pollution and the eutrophication process are increasing in lake Yahuarcocha and constant water quality monitoring is essential for a better understanding of the patterns occurring in this ecosystem. In this study, key sensor locations were determined using spatial and temporal analyses combined with geographical information systems (GIS) to assess the influence of weather features, anthropogenic activities, and other non-point pollution sources. A water quality monitoring network was established to obtain data on 14 physicochemical and microbiological parameters at each of seven sample sites over a period of 13 months. A spatial and temporal statistical approach using pattern recognition techniques, such as cluster analysis (CA) and discriminant analysis (DA), was employed to classify and identify the most important water quality parameters in the lake. The original monitoring network was reduced to four optimal sensor locations based on a fuzzy overlay of the interpolations of concentration variations of the most important parameters.

Atmospheric CO2 Concentrations--The Canadian Background Air Pollution Monitoring Network (1993) (NDP-034)

DOE Data Explorer

Trivett, N. B. A. [Environment Canada, Atmospheric Environment Service, Downsview, Ontario, Canada; Hudec, V. C. [Environment Canada, Atmospheric Environment Service, Downsview, Ontario, Canada; Wong, C. S. [Marine Carbon Research Centre, Institute of Ocean Sciences, Sidney, British Columbia, Canada

1993-01-01

Flask air samples collected at roughly weekly intervals at three Canadian sites [Alert, Northwest Territories (July 1975 through July 1992); Sable Island, Nova Scotia (March 1975 through July 1992); and Cape St. James, British Columbia (May 1979 through July 1992)] were analyzed for CO2 concentration with the measurements directly traceable to the WMO primary CO2 standards. Each record includes the date, atmospheric CO2 concentration, and flask classification code. They provide an accurate record of CO2 concentration levels in Canada during the past two decades. Because these data are directly traceable to WMO standards, this record may be compared with records from other Background Air Pollution Monitoring Network (BAPMoN) stations. The data are in three files (one for each of the monitoring stations) ranging in size from 9.4 to 20.1 kB.

Environmental noise forecasting based on support vector machine

NASA Astrophysics Data System (ADS)

Fu, Yumei; Zan, Xinwu; Chen, Tianyi; Xiang, Shihan

2018-01-01

As an important pollution source, the noise pollution is always the researcher's focus. Especially in recent years, the noise pollution is seriously harmful to the human beings' environment, so the research about the noise pollution is a very hot spot. Some noise monitoring technologies and monitoring systems are applied in the environmental noise test, measurement and evaluation. But, the research about the environmental noise forecasting is weak. In this paper, a real-time environmental noise monitoring system is introduced briefly. This monitoring system is working in Mianyang City, Sichuan Province. It is monitoring and collecting the environmental noise about more than 20 enterprises in this district. Based on the large amount of noise data, the noise forecasting by the Support Vector Machine (SVM) is studied in detail. Compared with the time series forecasting model and the artificial neural network forecasting model, the SVM forecasting model has some advantages such as the smaller data size, the higher precision and stability. The noise forecasting results based on the SVM can provide the important and accuracy reference to the prevention and control of the environmental noise.

Spatial distribution of vehicle emission inventories in the Federal District, Brazil

NASA Astrophysics Data System (ADS)

Réquia, Weeberb João; Koutrakis, Petros; Roig, Henrique Llacer

2015-07-01

Air pollution poses an important public health risk, especially in large urban areas. Information about the spatial distribution of air pollutants can be used as a tool for developing public policies to reduce source emissions. Air pollution monitoring networks provide information about pollutant concentrations; however, they are not available in every urban area. Among the 5570 cities in Brazil, for example, only 1.7% of them have air pollution monitoring networks. In this study we assess vehicle emissions for main traffic routes of the Federal District (state of Brazil) and characterize their spatial patterns. Toward this end, we used a bottom-up method to predict emissions and to characterize their spatial patterns using Global Moran's (Spatial autocorrelation analysis) and Getis-Ord General G (High/Low cluster analysis). Our findings suggested that light duty vehicles are primarily responsible for the vehicular emissions of CO (68.9%), CH4 (93.6%), and CO2 (57.9%), whereas heavy duty vehicles are primarily responsible for the vehicular emissions of NMHC (92.9%), NOx (90.7%), and PM (97.4%). Furthermore, CO2 is the pollutant with the highest emissions, over 30 million tons/year. In the spatial autocorrelation analysis was identified cluster (p < 0.01) for all types of vehicles and for all pollutants. However, we identified high cluster only for the light vehicles.

Implications of different approaches for characterizing ambient air pollutant concentrations within the urban airshed for time-series studies and health benefits analyses.

PubMed

Strickland, Matthew J; Darrow, Lyndsey A; Mulholland, James A; Klein, Mitchel; Flanders, W Dana; Winquist, Andrea; Tolbert, Paige E

2011-05-11

In time-series studies of the health effects of urban air pollutants, decisions must be made about how to characterize pollutant levels within the airshed. Emergency department visits for pediatric asthma exacerbations were collected from Atlanta hospitals. Concentrations of carbon monoxide, nitrogen dioxide, ozone, sulfur dioxide, particulate matter less than 10 microns in diameter (PM10), particulate matter less than 2.5 microns in diameter (PM2.5), and the PM2.5 components elemental carbon, organic carbon, and sulfate were obtained from networks of ambient air quality monitors. For each pollutant we created three different daily metrics. For one metric we used the measurements from a centrally-located monitor; for the second we averaged measurements across the network of monitors; and for the third we estimated the population-weighted average concentration using an isotropic spatial model. Rate ratios for each of the metrics were estimated from time-series models. For pollutants with relatively homogeneous spatial distributions we observed only small differences in the rate ratio across the three metrics. Conversely, for spatially heterogeneous pollutants we observed larger differences in the rate ratios. For a given pollutant, the strength of evidence for an association (i.e., chi-square statistics) tended to be similar across metrics. Given that the chi-square statistics were similar across the metrics, the differences in the rate ratios for the spatially heterogeneous pollutants may seem like a relatively small issue. However, these differences are important for health benefits analyses, where results from epidemiological studies on the health effects of pollutants (per unit change in concentration) are used to predict the health impacts of a reduction in pollutant concentrations. We discuss the relative merits of the different metrics as they pertain to time-series studies and health benefits analyses.

An integrated Bayesian model for estimating the long-term health effects of air pollution by fusing modelled and measured pollution data: A case study of nitrogen dioxide concentrations in Scotland.

PubMed

Huang, Guowen; Lee, Duncan; Scott, Marian

2015-01-01

The long-term health effects of air pollution can be estimated using a spatio-temporal ecological study, where the disease data are counts of hospital admissions from populations in small areal units at yearly intervals. Spatially representative pollution concentrations for each areal unit are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over grid level concentrations from an atmospheric dispersion model. We propose a novel fusion model for estimating spatially aggregated pollution concentrations using both the modelled and monitored data, and relate these concentrations to respiratory disease in a new study in Scotland between 2007 and 2011. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Identifying and closing gaps in environmental monitoring by means of metadata, ecological regionalization and geostatistics using the UNESCO biosphere reserve Rhoen (Germany) as an example.

PubMed

Schröder, Winfried; Pesch, Roland; Schmidt, Gunther

2006-03-01

In Germany, environmental monitoring is intended to provide a holistic view of the environmental condition. To this end the monitoring operated by the federal states must use harmonized, resp., standardized methods. In addition, the monitoring sites should cover the ecoregions without any geographical gaps, the monitoring design should have no gaps in terms of ecologically relevant measurement parameters, and the sample data should be spatially without any gaps. This article outlines the extent to which the Rhoen Biosphere Reserve, occupying a part of the German federal states of Bavaria, Hesse and Thuringia, fulfills the listed requirements. The investigation considered collection, data banking and analysis of monitoring data and metadata, ecological regionalization and geostatistics. Metadata on the monitoring networks were collected by questionnaires and provided a complete inventory and description of the monitoring activities in the reserve and its surroundings. The analysis of these metadata reveals that most of the monitoring methods are harmonized across the boundaries of the three federal states the Rhoen is part of. The monitoring networks that measure precipitation, surface water levels, and groundwater quality are particularly overrepresented in the central ecoregions of the biosphere reserve. Soil monitoring sites are more equally distributed within the ecoregions of the Rhoen. The number of sites for the monitoring of air pollutants is not sufficient to draw spatially valid conclusions. To fill these spatial gaps, additional data on the annual average values of the concentrations of air pollutants from monitoring sites outside of the biosphere reserve had therefore been subject to geostatistical analysis and estimation. This yields valid information on the spatial patterns and temporal trends of air quality. The approach illustrated is applicable to similar cases, as, for example, the harmonization of international monitoring networks.

A decision tree model to estimate the value of information provided by a groundwater quality monitoring network

NASA Astrophysics Data System (ADS)

Khader, A.; Rosenberg, D.; McKee, M.

2012-12-01

Nitrate pollution poses a health risk for infants whose freshwater drinking source is groundwater. This risk creates a need to design an effective groundwater monitoring network, acquire information on groundwater conditions, and use acquired information to inform management. These actions require time, money, and effort. This paper presents a method to estimate the value of information (VOI) provided by a groundwater quality monitoring network located in an aquifer whose water poses a spatially heterogeneous and uncertain health risk. A decision tree model describes the structure of the decision alternatives facing the decision maker and the expected outcomes from these alternatives. The alternatives include: (i) ignore the health risk of nitrate contaminated water, (ii) switch to alternative water sources such as bottled water, or (iii) implement a previously designed groundwater quality monitoring network that takes into account uncertainties in aquifer properties, pollution transport processes, and climate (Khader and McKee, 2012). The VOI is estimated as the difference between the expected costs of implementing the monitoring network and the lowest-cost uninformed alternative. We illustrate the method for the Eocene Aquifer, West Bank, Palestine where methemoglobinemia is the main health problem associated with the principal pollutant nitrate. The expected cost of each alternative is estimated as the weighted sum of the costs and probabilities (likelihoods) associated with the uncertain outcomes resulting from the alternative. Uncertain outcomes include actual nitrate concentrations in the aquifer, concentrations reported by the monitoring system, whether people abide by manager recommendations to use/not-use aquifer water, and whether people get sick from drinking contaminated water. Outcome costs include healthcare for methemoglobinemia, purchase of bottled water, and installation and maintenance of the groundwater monitoring system. At current methemoglobinemia and bottled water costs of 150 $/person and 0.6 $/baby/day, the decision tree results show that the expected cost of establishing the proposed groundwater quality monitoring network exceeds the expected costs of the uninformed alternatives and there is not value to the information the monitoring system provides. However, the monitoring system will be preferred to ignoring the health risk or using alternative sources if the methemoglobinemia cost rises to 300 $/person or the bottled water cost increases to 2.3 $/baby/day. Similarly, the monitoring system has value if the system can more accurately report actual aquifer concentrations and the public more fully abides by managers' recommendations to use/not use the aquifer. The system also has value if it will serve a larger population or if its installation costs can be reduced, for example using a smaller number of monitoring wells. The VOI analysis shows how monitoring system design, accuracy, installation and operating costs, public awareness of health risks, costs of alternatives, and demographics together affect the value of implementing a system to monitor groundwater quality.

Combining Community Engagement and Scientific Approaches in Next-Generation Monitor Siting: The Case of the Imperial County Community Air Network.

PubMed

Wong, Michelle; Bejarano, Esther; Carvlin, Graeme; Fellows, Katie; King, Galatea; Lugo, Humberto; Jerrett, Michael; Meltzer, Dan; Northcross, Amanda; Olmedo, Luis; Seto, Edmund; Wilkie, Alexa; English, Paul

2018-03-15

Air pollution continues to be a global public health threat, and the expanding availability of small, low-cost air sensors has led to increased interest in both personal and crowd-sourced air monitoring. However, to date, few low-cost air monitoring networks have been developed with the scientific rigor or continuity needed to conduct public health surveillance and inform policy. In Imperial County, California, near the U.S./Mexico border, we used a collaborative, community-engaged process to develop a community air monitoring network that attains the scientific rigor required for research, while also achieving community priorities. By engaging community residents in the project design, monitor siting processes, data dissemination, and other key activities, the resulting air monitoring network data are relevant, trusted, understandable, and used by community residents. Integration of spatial analysis and air monitoring best practices into the network development process ensures that the data are reliable and appropriate for use in research activities. This combined approach results in a community air monitoring network that is better able to inform community residents, support research activities, guide public policy, and improve public health. Here we detail the monitor siting process and outline the advantages and challenges of this approach.

Combining Community Engagement and Scientific Approaches in Next-Generation Monitor Siting: The Case of the Imperial County Community Air Network

PubMed Central

Wong, Michelle; Bejarano, Esther; Carvlin, Graeme; King, Galatea; Lugo, Humberto; Jerrett, Michael; Northcross, Amanda; Olmedo, Luis; Seto, Edmund; Wilkie, Alexa; English, Paul

2018-01-01

Air pollution continues to be a global public health threat, and the expanding availability of small, low-cost air sensors has led to increased interest in both personal and crowd-sourced air monitoring. However, to date, few low-cost air monitoring networks have been developed with the scientific rigor or continuity needed to conduct public health surveillance and inform policy. In Imperial County, California, near the U.S./Mexico border, we used a collaborative, community-engaged process to develop a community air monitoring network that attains the scientific rigor required for research, while also achieving community priorities. By engaging community residents in the project design, monitor siting processes, data dissemination, and other key activities, the resulting air monitoring network data are relevant, trusted, understandable, and used by community residents. Integration of spatial analysis and air monitoring best practices into the network development process ensures that the data are reliable and appropriate for use in research activities. This combined approach results in a community air monitoring network that is better able to inform community residents, support research activities, guide public policy, and improve public health. Here we detail the monitor siting process and outline the advantages and challenges of this approach. PMID:29543726

Air Pollution over the States

ERIC Educational Resources Information Center

Environmental Science and Technology, 1972

1972-01-01

State plans for implementing air quality standards are evaluated together with problems in modeling procedures and enforcement. Monitoring networks, standards, air quality regions, and industrial problems are also discussed. (BL)

Pollution source localization in an urban water supply network based on dynamic water demand.

PubMed

Yan, Xuesong; Zhu, Zhixin; Li, Tian

2017-10-27

Urban water supply networks are susceptible to intentional, accidental chemical, and biological pollution, which pose a threat to the health of consumers. In recent years, drinking-water pollution incidents have occurred frequently, seriously endangering social stability and security. The real-time monitoring for water quality can be effectively implemented by placing sensors in the water supply network. However, locating the source of pollution through the data detection obtained by water quality sensors is a challenging problem. The difficulty lies in the limited number of sensors, large number of water supply network nodes, and dynamic user demand for water, which leads the pollution source localization problem to an uncertainty, large-scale, and dynamic optimization problem. In this paper, we mainly study the dynamics of the pollution source localization problem. Previous studies of pollution source localization assume that hydraulic inputs (e.g., water demand of consumers) are known. However, because of the inherent variability of urban water demand, the problem is essentially a fluctuating dynamic problem of consumer's water demand. In this paper, the water demand is considered to be stochastic in nature and can be described using Gaussian model or autoregressive model. On this basis, an optimization algorithm is proposed based on these two dynamic water demand change models to locate the pollution source. The objective of the proposed algorithm is to find the locations and concentrations of pollution sources that meet the minimum between the analogue and detection values of the sensor. Simulation experiments were conducted using two different sizes of urban water supply network data, and the experimental results were compared with those of the standard genetic algorithm.

Community Air Sensor Network (CAIRSENSE) project: Evaluation of low-cost sensor performance in a suburban environment in the southeastern United States

EPA Science Inventory

Advances in air pollution sensor technology have enabled the development of small and low cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring n...

The measurement procedure in the SEMONT monitoring system.

PubMed

Djuric, Nikola; Kljajic, Dragan; Kasas-Lazetic, Karolina; Bajovic, Vera

2014-03-01

The measurement procedure of the open area in situ electric field strength is presented, acquiring the real field data for testing of the Serbian electromagnetic field monitoring network (SEMONT) and its Internet portal. The SEMONT monitoring system introduces an advanced approach of wireless sensor network utilization for the continuous supervision of overall and cumulative level of electromagnetic field over the observed area. The aim of the SEMONT system is to become a useful tool for the national and municipal agencies for the environmental protection, regarding the electromagnetic pollution monitoring and the exposure assessment of the general population. Considering the public concern on the potentially harmful effects of the long-term exposure to electromagnetic radiation, as well as the public transparency principle that is incorporated into the Serbian law on non-ionizing radiation protection, the SEMONT monitoring system is designed for the long-term continuous monitoring, presenting real-time measurement results, and corresponding exposure assessment over the public Internet network.

Urban rivers as hotspots of regional nitrogen pollution.

PubMed

Zhang, Xiaohong; Wu, Yiyun; Gu, Baojing

2015-10-01

Excess nitrogen inputs to terrestrial ecosystems via human activities have deteriorated water qualities on regional scales. Urban areas as settlements of over half global population, however, were usually not considered in the analysis of regional water pollution. Here, we used a 72-month monitoring data of water qualities in Hangzhou, China to test the role of urban rives in regional nitrogen pollution and how they response to the changes of human activities. Concentrations of ammonium nitrogen in urban rivers were 3-5 times higher than that in regional rivers. Urban rivers have become pools of reactive nitrogen and hotspots of regional pollution. Moreover, this river pollution is not being measured by current surface water monitoring networks that are designed to measure broader regional patterns, resulting in an underestimation of regional pollution. This is crucial to urban environment not only in China, but also in other countries, where urban rivers are seriously polluted. Copyright © 2015 Elsevier Ltd. All rights reserved.

Requirements for developing a regional monitoring capacity for aerosols in Europe within EMEP.

PubMed

Kahnert, Michael; Lazaridis, Mihalis; Tsyro, Svetlana; Torseth, Kjetil

2004-07-01

The European Monitoring and Evaluation Programme (EMEP) has been established to provide information to Parties to the Convention on Long Range Transboundary Air Pollution on deposition and concentration of air pollutants, as well as on the quantity and significance of long-range transmission of pollutants and transboundary fluxes. To achieve its objectives with the required scientific credibility and technical underpinning, a close integration of the programme's main elements is performed. These elements are emission inventories, chemical transport modelling, and the monitoring of atmospheric chemistry and deposition fluxes, which further are integrated towards abatement policy development. A critical element is the air pollution monitoring that is performed across Europe with a focus not only on health effect aspects and compliance monitoring, but also on process studies and source receptor relationships. Without a strong observational basis a predictive modelling capacity cannot be developed and validated. Thus the modelling success strongly depends on the quality and quantity of available observations. Particulate matter (PM) is a relatively recent addition to the EMEP monitoring programme, and the network for PM mass observations is still evolving. This article presents the current status of EMEP aerosol observations, followed by a critical evaluation in view of EMEP's main objectives and its model development requirements. Specific recommendations are given for improving the PM monitoring programme within EMEP.

Hydrological information system based on on-line monitoring--from strategy to implementation in the Brantas River Basin, East Java, Indonesia.

PubMed

Marini, G W; Wellguni, H

2003-01-01

The worsening environmental situation of the Brantas River, East Java, is addressed by a comprehensive basin management strategy which relies on accurate water quantity and quality data retrieved from a newly installed online monitoring network. Integrated into a Hydrological Information System, the continuously measured indicative parameters allow early warning, control and polluter identification. Additionally, long-term analyses have been initiated for improving modelling applications like flood forecasting, water resource management and pollutant propagation. Preliminary results illustrate the efficiency of the installed system.

On-line dynamic monitoring automotive exhausts: using BP-ANN for distinguishing multi-components

NASA Astrophysics Data System (ADS)

Zhao, Yudi; Wei, Ruyi; Liu, Xuebin

2017-10-01

Remote sensing-Fourier Transform infrared spectroscopy (RS-FTIR) is one of the most important technologies in atmospheric pollutant monitoring. It is very appropriate for on-line dynamic remote sensing monitoring of air pollutants, especially for the automotive exhausts. However, their absorption spectra are often seriously overlapped in the atmospheric infrared window bands, i.e. MWIR (3 5μm). Artificial Neural Network (ANN) is an algorithm based on the theory of the biological neural network, which simplifies the partial differential equation with complex construction. For its preferable performance in nonlinear mapping and fitting, in this paper we utilize Back Propagation-Artificial Neural Network (BP-ANN) to quantitatively analyze the concentrations of four typical industrial automotive exhausts, including CO, NO, NO2 and SO2. We extracted the original data of these automotive exhausts from the HITRAN database, most of which virtually overlapped, and established a mixed multi-component simulation environment. Based on Beer-Lambert Law, concentrations can be retrieved from the absorbance of spectra. Parameters including learning rate, momentum factor, the number of hidden nodes and iterations were obtained when the BP network was trained with 80 groups of input data. By improving these parameters, the network can be optimized to produce necessarily higher precision for the retrieved concentrations. This BP-ANN method proves to be an effective and promising algorithm on dealing with multi-components analysis of automotive exhausts.

Assessment of the environmental significance of nutrients and heavy metal pollution in the river network of Serbia.

PubMed

Dević, Gordana; Sakan, Sanja; Đorđević, Dragana

2016-01-01

In this paper, the data for ten water quality variables collected during 2009 at 75 monitoring sites along the river network of Serbia are considered. The results are alarming because 48% of the studied sites were contaminated by Ni, Mn, Pb, As, and nutrients, which are key factors impairing the water quality of the rivers in Serbia. Special attention should be paid to Zn and Cu, listed in the priority toxic pollutants of US EPA for aquatic life protection. The employed Q-model cluster analysis grouped the data into three major pollution zones (low, moderate, and high). Most sites classified as "low pollution zones" (LP) were in the main rivers, whereas those classified as "moderate and high pollution zones" (MP and HP, respectively) were in the large and small tributaries/hydro-system. Principal component analysis/factor analysis (PCA/FA) showed that the dissolved metals and nutrients in the Serbian rivers varied depending on the river, the heterogeneity of the anthropogenic activities in the basins (influenced primarily by industrial wastewater, agricultural activities, and urban runoff pollution), and natural environmental variability, such as geological characteristics. In LP dominated non-point source pollution, such as agricultural and urban runoff, whereas mixed source pollution dominated in the MP and HP zones. These results provide information to be used for developing better pollution control strategies for the river network of Serbia.

Isotopic Recorders of Pollution in Heterogeneous Urban Areas

NASA Astrophysics Data System (ADS)

Pataki, D. E.; Cobley, L.; Smith, R. M.; Ehleringer, J. R.; Chritz, K.

2017-12-01

A significant difficulty in quantifying urban pollution lies in the extreme spatial and temporal heterogeneity of cities. Dense sources of both point and non-point source pollution as well as the dynamic role of human activities, which vary over very short time scales and small spatial scales, complicate efforts to establish long-term urban monitoring networks that are relevant at neighborhood, municipal, and regional scales. Fortunately, the natural abundance of isotopes of carbon, nitrogen, and other elements provides a wealth of information about the sources and fate of urban atmospheric pollution. In particular, soils and plant material integrate pollution sources and cycling over space and time, and have the potential to provide long-term records of pollution dynamics that extend back before atmospheric monitoring data are available. Similarly, sampling organic material at high spatial resolution can provide "isoscapes" that shed light on the spatial heterogeneity of pollutants in different urban parcels and neighborhoods, along roads of varying traffic density, and across neighborhoods of varying affluence and sociodemographic composition. We have compiled numerous datasets of the isotopic composition of urban organic matter that illustrate the potential for isotopic monitoring of urban areas as a means of understanding hot spots and hot moments in urban atmospheric biogeochemistry. Findings to date already reveal the critical role of affluence, economic activity, demographic change, and land management practices in influencing urban pollution sources and sinks, and suggest an important role of stable isotope and radioisotope measurements in urban atmospheric and biogeochemical monitoring.

Forest fires and air quality issues in southern Europe

Treesearch

Ana Isabel Miranda; Enrico Marchi; Marco Ferretti; Millán M. Millán

2009-01-01

Each summer forest fires in southern Europe emit large quantities of pollutants to the atmosphere. These fires can generate a number of air pollution episodes as measured by air quality monitoring networks. We analyzed the impact of forest fires on air quality of specific regions of southern Europe. Data from several summer seasons were studied with the aim of...

Geohydrology of the Antelope Valley Area, California and design for a ground-water-quality monitoring network

USGS Publications Warehouse

Duell, L.F.

1987-01-01

A basinwide ideal network and an actual network were designed to identify ambient groundwater quality, trends in groundwater quality, and degree of threat from potential pollution sources in Antelope Valley, California. In general, throughout the valley groundwater quality has remained unchanged, and no specific trends are apparent. The main source of groundwater for the valley is generally suitable for domestic, irrigation, and most industrial uses. Water quality data for selected constituents of some network wells and surface-water sites are presented. The ideal network of 77 sites was selected on the basis of site-specific criteria, geohydrology, and current land use (agricultural, residential, and industrial). These sites were used as a guide in the design of the actual network consisting of 44 existing wells. Wells are currently being monitored and were selected whenever possible because of budgetary constraints. Of the remaining ideal sites, 20 have existing wells not part of a current water quality network, and 13 are locations where no wells exist. The methodology used for the selection of sites, constituents monitored, and frequency of analysis will enable network users to make appropriate future changes to the monitoring network. (USGS)

Evaluation of Water Quality Trends in Goodwater Creek Experimental Watershed, Missouri: Implications for Monitoring Strategies and Objective Setting

USDA-ARS?s Scientific Manuscript database

Continued public support for U.S. tax-payer funded programs aimed at reducing agricultural non-point source pollutants depends on clear demonstrations of water quality improvements. Effectiveness of structural BMPs, as well as watershed monitoring networks is an important information need to make f...

Air Pollution Measurements by Citizen Scientists and NASA Satellites: Data Integration and Analysis

NASA Astrophysics Data System (ADS)

Gupta, P.; Maibach, J.; Levy, R. C.; Doraiswamy, P.; Pikelnaya, O.; Feenstra, B.; Polidori, A.

2017-12-01

PM2.5, or fine particulate matter, is a category of air pollutant consisting of solid particles with effective aerodynamic diameter of less than 2.5 microns. These particles are hazardous to human health, as their small size allows them to penetrate deep into the lungs. Since the late 1990's, the US Environmental Protection Agency has been monitoring PM2.5 using a network of ground-level sensors. Due to cost and space restrictions, the EPA monitoring network remains spatially sparse. That is, while the network spans the extent of the US, the distance between sensors is large enough that significant spatial variation in PM concentration can go undetected. To increase the spatial resolution of monitoring, previous studies have used satellite data to estimate ground-level PM concentrations. From imagery, one can create a measure of haziness due to aerosols, called aerosol optical depth (AOD), which then can be used to estimate PM concentrations using statistical and physical modeling. Additionally, previous research has identified a number of meteorological variables, such as relative humidity and mixing height, which aide in estimating PM concentrations from AOD. Although the high spatial resolution of satellite data is valuable alone for forecasting air quality, higher resolution ground-level data is needed to effectively study the relationship between PM2.5 concentrations and AOD. To this end, we discuss a citizen-science PM monitoring network deployed in California. Using low-cost PM sensors, this network achieves higher spatial resolution. We additionally discuss a software pipeline for integrating resulting PM measurements with satellite data, as well as initial data analysis.

Air quality, primary air pollutants and ambient concentrations inventory for Romania

NASA Astrophysics Data System (ADS)

Năstase, Gabriel; Șerban, Alexandru; Năstase, Alina Florentina; Dragomir, George; Brezeanu, Alin Ionuț

2018-07-01

Air pollution is among the greatest risk factors for human health, but it also poses risks to the food security, the economy and the environment. The majority of the pollutants emitted by human activities derive from the production and use of fossil-fuel-based energy. Most energy-related emissions contain sulfur dioxide and nitrogen oxides. The principal source of sulfur dioxide originates from coal, and the main sources of nitrogen oxide emissions are power generation and use of vehicles. Other important pollutants are the inhalable coarse particles (PM10) and the fine particulate matter (PM2.5), which arises from the building sector. Over the last decade, since Romania joined the European Union on the 1st of January 2007, the use of fossil fuels has decreased dramatically, as consumers switched to either natural gas or biomass. This was as a result of the European Commission encouraging the member countries to make use of renewable sources (including biomass). To reduce the PM emissions, in April 2015 EC has extended the EcoDesign Directive to solid-fuel boilers and solid-fuel space heaters. The boilers need to generally meet certain requirements that will be introduced by 1 January 2020. In this article, we are highlighting the fluctuations in air pollution in Romania from the European WebDAB - EMAP database and trends in ambient concentrations of air pollutants using Romania's national air pollution monitoring network. Romania's Air Pollutants/Air Quality Monitoring Network consists of 142 automatic air quality monitoring stations. The results indicate that Romania's annual average mass emissions of CO decreased from 3186 Gg in 1990 to 774 in 2014 (decrease by <76%), SOx decreased from 1311 Gg-176 Gg (decrease by ∼60%), NOx decreased from 546 Gg to 218 (decrease by ∼87%), CO2 decreased from 66.226 Gg/year in 2007 to 38.916 Gg/year in 2014 (decrease by <41%).

Integrated global background monitoring network. Preliminary results from Torres del Paine and Olympic National Parks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wiersma, G.B.; Kohler, A.; Boelcke, C.

1985-10-01

During 1984, a pilot project was initiated for monitoring pollution at Torres del Paine National Park in southern Chile and Olympic National Park in the United States. These are two of three initial sites that are to be established as part of an integrated global backgound monitoring network. Eventually, the plan is to establish a world-wide system of such sites. We collected and analyzed samples of the soil, water, air, and two species of plants (moss and lichen). We also collected and analyzed samples of the forest litter. We compared the samples of soil and vegetation against reference samples. Wemore » also compared samples of soil, vegetation, and of organic material from Torres del Paine against similar samples from Olympic and Sequoia-Kings Canyon National Parks in the United States. Although the data is preliminary, it is in agreement with out initial hypothesis that Torres del Paine and Olympic National Parks are not a polluted sites.« less

A comparative analysis of modeled and monitored ambient hazardous air pollutants in Texas: a novel approach using concordance correlation.

PubMed

Lupo, Philip J; Symanski, Elaine

2009-11-01

Often, in studies evaluating the health effects of hazardous air pollutants (HAPs), researchers rely on ambient air levels to estimate exposure. Two potential data sources are modeled estimates from the U.S. Environmental Protection Agency (EPA) Assessment System for Population Exposure Nationwide (ASPEN) and ambient air pollutant measurements from monitoring networks. The goal was to conduct comparisons of modeled and monitored estimates of HAP levels in the state of Texas using traditional approaches and a previously unexploited method, concordance correlation analysis, to better inform decisions regarding agreement. Census tract-level ASPEN estimates and monitoring data for all HAPs throughout Texas, available from the EPA Air Quality System, were obtained for 1990, 1996, and 1999. Monitoring sites were mapped to census tracts using U.S. Census data. Exclusions were applied to restrict the monitored data to measurements collected using a common sampling strategy with minimal missing values over time. Comparisons were made for 28 HAPs in 38 census tracts located primarily in urban areas throughout Texas. For each pollutant and by year of assessment, modeled and monitored air pollutant annual levels were compared using standard methods (i.e., ratios of model-to-monitor annual levels). Concordance correlation analysis was also used, which assesses linearity and agreement while providing a formal method of statistical inference. Forty-eight percent of the median model-to-monitor values fell between 0.5 and 2, whereas only 17% of concordance correlation coefficients were significant and greater than 0.5. On the basis of concordance correlation analysis, the findings indicate there is poorer agreement when compared with the previously applied ad hoc methods to assess comparability between modeled and monitored levels of ambient HAPs.

Optimization of a Coastal Environmental Monitoring Network Based on the Kriging Method: A Case Study of Quanzhou Bay, China

PubMed Central

Chen, Kai; Ni, Minjie; Wang, Jun; Huang, Dongren; Chen, Huorong; Wang, Xiao; Liu, Mengyang

2016-01-01

Environmental monitoring is fundamental in assessing environmental quality and to fulfill protection and management measures with permit conditions. However, coastal environmental monitoring work faces many problems and challenges, including the fact that monitoring information cannot be linked up with evaluation, monitoring data cannot well reflect the current coastal environmental condition, and monitoring activities are limited by cost constraints. For these reasons, protection and management measures cannot be developed and implemented well by policy makers who intend to solve this issue. In this paper, Quanzhou Bay in southeastern China was selected as a case study; and the Kriging method and a geographic information system were employed to evaluate and optimize the existing monitoring network in a semienclosed bay. This study used coastal environmental monitoring data from 15 sites (including COD, DIN, and PO4-P) to adequately analyze the water quality from 2009 to 2012 by applying the Trophic State Index. The monitoring network in Quanzhou Bay was evaluated and optimized, with the number of sites increased from 15 to 24, and the monitoring precision improved by 32.9%. The results demonstrated that the proposed advanced monitoring network optimization was appropriate for environmental monitoring in Quanzhou Bay. It might provide technical support for coastal management and pollutant reduction in similar areas. PMID:27777951

Optimization of a Coastal Environmental Monitoring Network Based on the Kriging Method: A Case Study of Quanzhou Bay, China.

PubMed

Chen, Kai; Ni, Minjie; Cai, Minggang; Wang, Jun; Huang, Dongren; Chen, Huorong; Wang, Xiao; Liu, Mengyang

2016-01-01

Environmental monitoring is fundamental in assessing environmental quality and to fulfill protection and management measures with permit conditions. However, coastal environmental monitoring work faces many problems and challenges, including the fact that monitoring information cannot be linked up with evaluation, monitoring data cannot well reflect the current coastal environmental condition, and monitoring activities are limited by cost constraints. For these reasons, protection and management measures cannot be developed and implemented well by policy makers who intend to solve this issue. In this paper, Quanzhou Bay in southeastern China was selected as a case study; and the Kriging method and a geographic information system were employed to evaluate and optimize the existing monitoring network in a semienclosed bay. This study used coastal environmental monitoring data from 15 sites (including COD, DIN, and PO 4 -P) to adequately analyze the water quality from 2009 to 2012 by applying the Trophic State Index. The monitoring network in Quanzhou Bay was evaluated and optimized, with the number of sites increased from 15 to 24, and the monitoring precision improved by 32.9%. The results demonstrated that the proposed advanced monitoring network optimization was appropriate for environmental monitoring in Quanzhou Bay. It might provide technical support for coastal management and pollutant reduction in similar areas.

Progress toward a ground-water-quality monitoring network for Idaho

USGS Publications Warehouse

Whitehead, R.L.

1978-01-01

The potential for pollution of the aquifers is expected to be greatest in areas of greatest development. In Idaho, population centers and industries tend to be in areas of privately owned irrigated and arable · land. Therefore, these areas are of primary concern for monitoring ground-water quality. Other areas requiring monitoring include those with second-home development, mining and its related processes, and radioactive-waste disposal.

Monitoring air quality in Southeast Alaska’s National Parks and Forests: Linking atmospheric pollutants with ecological effects

Treesearch

D. Schirokauer; L. Geiser; A. Bytnerowicz; M. Fenn; K. Dillman

2014-01-01

Air quality and air quality related values are important resources to the National Park Service (NPS) units and Wilderness areas in northern Southeast Alaska. Air quality monitoring was prioritized as a high-priority Vital Sign at the Southeast Alaska Network’s (SEAN) Inventory and Monitoring Program’s terrestrial scoping workshop (Derr and Fastie 2006). Air quality...

Pragmatic estimation of a spatio-temporal air quality model with irregular monitoring data

NASA Astrophysics Data System (ADS)

Sampson, Paul D.; Szpiro, Adam A.; Sheppard, Lianne; Lindström, Johan; Kaufman, Joel D.

2011-11-01

Statistical analyses of health effects of air pollution have increasingly used GIS-based covariates for prediction of ambient air quality in "land use" regression models. More recently these spatial regression models have accounted for spatial correlation structure in combining monitoring data with land use covariates. We present a flexible spatio-temporal modeling framework and pragmatic, multi-step estimation procedure that accommodates essentially arbitrary patterns of missing data with respect to an ideally complete space by time matrix of observations on a network of monitoring sites. The methodology incorporates a model for smooth temporal trends with coefficients varying in space according to Partial Least Squares regressions on a large set of geographic covariates and nonstationary modeling of spatio-temporal residuals from these regressions. This work was developed to provide spatial point predictions of PM 2.5 concentrations for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) using irregular monitoring data derived from the AQS regulatory monitoring network and supplemental short-time scale monitoring campaigns conducted to better predict intra-urban variation in air quality. We demonstrate the interpretation and accuracy of this methodology in modeling data from 2000 through 2006 in six U.S. metropolitan areas and establish a basis for likelihood-based estimation.

Wireless Distributed Environmental Sensor Networks for Air Pollution Measurement-The Promise and the Current Reality.

PubMed

Broday, David M

2017-10-02

The evaluation of the effects of air pollution on public health and human-wellbeing requires reliable data. Standard air quality monitoring stations provide accurate measurements of airborne pollutant levels, but, due to their sparse distribution, they cannot capture accurately the spatial variability of air pollutant concentrations within cities. Dedicated in-depth field campaigns have dense spatial coverage of the measurements but are held for relatively short time periods. Hence, their representativeness is limited. Moreover, the oftentimes integrated measurements represent time-averaged records. Recent advances in communication and sensor technologies enable the deployment of dense grids of Wireless Distributed Environmental Sensor Networks for air quality monitoring, yet their capability to capture urban-scale spatiotemporal pollutant patterns has not been thoroughly examined to date. Here, we summarize our studies on the practicalities of using data streams from sensor nodes for air quality measurement and the required methods to tune the results to different stakeholders and applications. We summarize the results from eight cities across Europe, five sensor technologies-three stationary (with one tested also while moving) and two personal sensor platforms, and eight ambient pollutants. Overall, few sensors showed an exceptional and consistent performance, which can shed light on the fine spatiotemporal urban variability of pollutant concentrations. Stationary sensor nodes were more reliable than personal nodes. In general, the sensor measurements tend to suffer from the interference of various environmental factors and require frequent calibrations. This calls for the development of suitable field calibration procedures, and several such in situ field calibrations are presented.

Wireless Distributed Environmental Sensor Networks for Air Pollution Measurement—The Promise and the Current Reality

PubMed Central

2017-01-01

The evaluation of the effects of air pollution on public health and human-wellbeing requires reliable data. Standard air quality monitoring stations provide accurate measurements of airborne pollutant levels, but, due to their sparse distribution, they cannot capture accurately the spatial variability of air pollutant concentrations within cities. Dedicated in-depth field campaigns have dense spatial coverage of the measurements but are held for relatively short time periods. Hence, their representativeness is limited. Moreover, the oftentimes integrated measurements represent time-averaged records. Recent advances in communication and sensor technologies enable the deployment of dense grids of Wireless Distributed Environmental Sensor Networks for air quality monitoring, yet their capability to capture urban-scale spatiotemporal pollutant patterns has not been thoroughly examined to date. Here, we summarize our studies on the practicalities of using data streams from sensor nodes for air quality measurement and the required methods to tune the results to different stakeholders and applications. We summarize the results from eight cities across Europe, five sensor technologies-three stationary (with one tested also while moving) and two personal sensor platforms, and eight ambient pollutants. Overall, few sensors showed an exceptional and consistent performance, which can shed light on the fine spatiotemporal urban variability of pollutant concentrations. Stationary sensor nodes were more reliable than personal nodes. In general, the sensor measurements tend to suffer from the interference of various environmental factors and require frequent calibrations. This calls for the development of suitable field calibration procedures, and several such in situ field calibrations are presented. PMID:28974042

Community Air Sensor Network (CAIRSENSE) project: evaluation of low-cost sensor performance in a suburban environment in the southeastern United States

NASA Astrophysics Data System (ADS)

Jiao, Wan; Hagler, Gayle; Williams, Ronald; Sharpe, Robert; Brown, Ryan; Garver, Daniel; Judge, Robert; Caudill, Motria; Rickard, Joshua; Davis, Michael; Weinstock, Lewis; Zimmer-Dauphinee, Susan; Buckley, Ken

2016-11-01

Advances in air pollution sensor technology have enabled the development of small and low-cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring networks with additional geographic and temporal measurement resolution, if the data quality were sufficient. To understand the capability of emerging air sensor technology, the Community Air Sensor Network (CAIRSENSE) project deployed low-cost, continuous, and commercially available air pollution sensors at a regulatory air monitoring site and as a local sensor network over a surrounding ˜ 2 km area in the southeastern United States. Collocation of sensors measuring oxides of nitrogen, ozone, carbon monoxide, sulfur dioxide, and particles revealed highly variable performance, both in terms of comparison to a reference monitor as well as the degree to which multiple identical sensors produced the same signal. Multiple ozone, nitrogen dioxide, and carbon monoxide sensors revealed low to very high correlation with a reference monitor, with Pearson sample correlation coefficient (r) ranging from 0.39 to 0.97, -0.25 to 0.76, and -0.40 to 0.82, respectively. The only sulfur dioxide sensor tested revealed no correlation (r < 0.5) with a reference monitor and erroneously high concentration values. A wide variety of particulate matter (PM) sensors were tested with variable results - some sensors had very high agreement (e.g., r = 0.99) between identical sensors but moderate agreement with a reference PM2.5 monitor (e.g., r = 0.65). For select sensors that had moderate to strong correlation with reference monitors (r > 0.5), step-wise multiple linear regression was performed to determine if ambient temperature, relative humidity (RH), or age of the sensor in number of sampling days could be used in a correction algorithm to improve the agreement. Maximum improvement in agreement with a reference, incorporating all factors, was observed for an NO2 sensor (multiple correlation coefficient R2adj-orig = 0.57, R2adj-final = 0.81); however, other sensors showed no apparent improvement in agreement. A four-node sensor network was successfully able to capture ozone (two nodes) and PM (four nodes) data for an 8-month period of time and show expected diurnal concentration patterns, as well as potential ozone titration due to nearby traffic emissions. Overall, this study demonstrates the performance of emerging air quality sensor technologies in a real-world setting; the variable agreement between sensors and reference monitors indicates that in situ testing of sensors against benchmark monitors should be a critical aspect of all field studies.

International co-operative program on assessment and monitoring of air pollution effects on forests: The Sierra Ancha Experimental Forest, Arizona

Treesearch

Boris Poff; Daniel G. Neary

2008-01-01

At the end of the 2007 Fiscal Year, the Experimental Forests and Ranges (EFR) Synthesis Network Committee awarded funds to 18 sites to establish a strategic ICP Level II (described below) synthesis network in the United States. Eleven Experimental Forest were selected to be included in the network, as well as seven Long Term Ecological Research (LTER) sites. This will...

Co-occurrence correlations of heavy metals in sediments revealed using network analysis.

PubMed

Liu, Lili; Wang, Zhiping; Ju, Feng; Zhang, Tong

2015-01-01

In this study, the correlation-based study was used to identify the co-occurrence correlations among metals in marine sediment of Hong Kong, based on the long-term (from 1991 to 2011) temporal and spatial monitoring data. 14 stations out of the total 45 marine sediment monitoring stations were selected from three representative areas, including Deep Bay, Victoria Harbour and Mirs Bay. Firstly, Spearman's rank correlation-based network analysis was conducted as the first step to identify the co-occurrence correlations of metals from raw metadata, and then for further analysis using the normalized metadata. The correlations patterns obtained by network were consistent with those obtained by the other statistic normalization methods, including annual ratios, R-squared coefficient and Pearson correlation coefficient. Both Deep Bay and Victoria Harbour have been polluted by heavy metals, especially for Pb and Cu, which showed strong co-occurrence with other heavy metals (e.g. Cr, Ni, Zn and etc.) and little correlations with the reference parameters (Fe or Al). For Mirs Bay, which has better marine sediment quality compared with Deep Bay and Victoria Harbour, the co-occurrence patterns revealed by network analysis indicated that the metals in sediment dominantly followed the natural geography process. Besides the wide applications in biology, sociology and informatics, it is the first time to apply network analysis in the researches of environment pollutions. This study demonstrated its powerful application for revealing the co-occurrence correlations among heavy metals in marine sediments, which could be further applied for other pollutants in various environment systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Comparisons of Spectral Aerosol Single Scattering Albedo in Seoul, South Korea

NASA Technical Reports Server (NTRS)

Mok, Jungbin; Krotkov, Nickolay A.; Torres, Omar; Jethva, Hiren; Loughman, Robert P.; Spinei, Elena; Campanelli, Monica; Li, Zhanqing; Go, Sujung; Labow, Gordon;

Effective Usage of Social Media for Dark Skies Awareness

NASA Astrophysics Data System (ADS)

Hennig, A. J.; Heenatigala, T.; Walker, C. E.

2012-12-01

Social media has become a daily tool in our culture. Networks such as Facebook with 900 million active users and Twitter with 140 million active users make an ideal platform to create awareness. It helps to generate and share new content and enables multi-communication channels. This presentation will address how effectively social media can be used as an education tool to create awareness of light pollution. As a "green" focus becomes more important in our world the topic of light pollution is also rising as an important issue. Light Pollution affects many aspects of our world ranging from flora and fauna to the economic well-being of many industrialized countries. Mixed among the many important pollutants in our world light pollution can fall by the way-side, forgotten, but it is imperative to bring out awareness of this problem, especially since studies are beginning to show how by fighting light pollution we will also be fighting other pollution such as air pollutants. GLOBE at Night has combined social media tools such as Facebook and Twitter with its educational awareness campaign on light pollution to reach out to social media community. Currently our Facebook reaches citizens of twenty separate countries ranging from the Czech Republic and Peru to the United States and the United Kingdom. On Facebook our reach is estimated at over 800,000 friends of our fans. These networks help us to directly answer users' immediate questions and encourage participation in the GLOBE at Night campaigns. Important news on light pollution appearing in cyberspace is monitored regularly using Google Alerts and Twitter hash tags filters which gets posted regularly on our networks. Social media networking has become a tool for users not only for information about GLOBE at Night but also for information about the overall topic of light pollution itself. Many individuals and organizations struggle with the mass content shared in social networks. It is important to know where to look for the right content and what to share with whom. This presentation will highlight on; the importance of engaging in social media to gain and share new content, how to filter the right content, and best uses of social media to create an awareness of light pollution. We will discuss the proper ways to get the most use out of social media networking.

A new air quality monitoring and early warning system: Air quality assessment and air pollutant concentration prediction.

PubMed

Yang, Zhongshan; Wang, Jian

2017-10-01

Air pollution in many countries is worsening with industrialization and urbanization, resulting in climate change and affecting people's health, thus, making the work of policymakers more difficult. It is therefore both urgent and necessary to establish amore scientific air quality monitoring and early warning system to evaluate the degree of air pollution objectively, and predict pollutant concentrations accurately. However, the integration of air quality assessment and air pollutant concentration prediction to establish an air quality system is not common. In this paper, we propose a new air quality monitoring and early warning system, including an assessment module and forecasting module. In the air quality assessment module, fuzzy comprehensive evaluation is used to determine the main pollutants and evaluate the degree of air pollution more scientifically. In the air pollutant concentration prediction module, a novel hybridization model combining complementary ensemble empirical mode decomposition, a modified cuckoo search and differential evolution algorithm, and an Elman neural network, is proposed to improve the forecasting accuracy of six main air pollutant concentrations. To verify the effectiveness of this system, pollutant data for two cities in China are used. The result of the fuzzy comprehensive evaluation shows that the major air pollutants in Xi'an and Jinan are PM 10 and PM 2.5 respectively, and that the air quality of Xi'an is better than that of Jinan. The forecasting results indicate that the proposed hybrid model is remarkably superior to all benchmark models on account of its higher prediction accuracy and stability. Copyright © 2017 Elsevier Inc. All rights reserved.

Using an epiphytic moss to identify previously unknown sources of atmospheric cadmium pollution

Treesearch

Geoffrey H. Donovan; Sarah E. Jovan; Demetrios Gatziolis; Igor Burstyn; Yvonne L. Michael; Michael C. Amacher; Vicente J. Monleon

2016-01-01

Urban networks of air-quality monitors are often too widely spaced to identify sources of air pollutants, especially if they do not disperse far from emission sources. The objectives of this study were to test the use of moss bio-indicators to develop a fine-scale map of atmospherically-derived cadmium and to identify the sources of cadmium in a complex urban setting....

Fractal Analysis of Air Pollutant Concentrations

NASA Astrophysics Data System (ADS)

Cortina-Januchs, M. G.; Barrón-Adame, J. M.; Vega-Corona, A.; Andina, D.

2010-05-01

Air pollution poses significant threats to human health and the environment throughout the developed and developing countries. This work focuses on fractal analysis of pollutant concentration in Salamanca, Mexico. The city of Salamanca has been catalogued as one of the most polluted cities in Mexico. The main causes of pollution in this city are fixed emission sources, such as chemical industry and electricity generation. Sulphur Dioxide (SO2) and Particulate Matter less than 10 micrometer in diameter (PM10) are the most important pollutants in this region. Air pollutant concentrations were investigated by applying the box counting method in time series obtained of the Automatic Environmental Monitoring Network (AEMN). One year of time series of hourly average concentrations were analyzed in order to characterize the temporal structures of SO2 and PM10.

Observational Needs for Four-Dimensional Air Quality Characterization

EPA Science Inventory

Surface-based monitoring programs provide the foundation for associating air pollution and causal effects in human health studies, and they support the development of air quality standards and the preparation of emission reduction strategies. While surface oriented networks remai...

Twenty years of measurement of polycyclic aromatic hydrocarbons (PAHs) in UK ambient air by nationwide air quality networks.

PubMed

Brown, Andrew S; Brown, Richard J C; Coleman, Peter J; Conolly, Christopher; Sweetman, Andrew J; Jones, Kevin C; Butterfield, David M; Sarantaridis, Dimitris; Donovan, Brian J; Roberts, Ian

2013-06-01

The impact of human activities on the health of the population and of the wider environment has prompted action to monitor the presence of toxic compounds in the atmosphere. Toxic organic micropollutants (TOMPs) are some of the most insidious and persistent of these pollutants. Since 1991 the United Kingdom has operated nationwide air quality networks to assess the presence of TOMPs, including polycyclic aromatic hydrocarbons (PAHs), in ambient air. The data produced in 2010 marked 20 years of nationwide PAH monitoring. This paper marks this milestone by providing a novel and critical review of the data produced since nationwide monitoring began up to the end of 2011 (the latest year for which published data is available), discussing how the networks performing this monitoring has evolved, and elucidating trends in the concentrations of the PAHs measured. The current challenges in the area and a forward look to the future of air quality monitoring for PAHs are also discussed briefly.

Regional trend analysis of surface ozone observations from monitoring networks in eastern North America, Europe and East Asia

NASA Astrophysics Data System (ADS)

Chang, K. L.; Petropavlovskikh, I. V.; Cooper, O. R.; Schultz, M.; Wang, T.

2017-12-01

Surface ozone is a greenhouse gas and pollutant detrimental to human health and crop and ecosystem productivity. The Tropospheric Ozone Assessment Report (TOAR) is designed to provide the research community with an up-to-date observation-based overview of tropospheric ozone's global distribution and trends. The TOAR Surface Ozone Database contains ozone metrics at thousands of monitoring sites around the world, densely clustered across mid-latitude North America, western Europe and East Asia. Calculating regional ozone trends across these locations is challenging due to the uneven spacing of the monitoring sites across urban and rural areas. To meet this challenge we conducted a spatial and temporal trend analysis of several TOAR ozone metrics across these three regions for summertime (April-September) 2000-2014, using the generalized additive mixed model (GAMM). Our analysis indicates that East Asia has the greatest human and plant exposure to ozone pollution among investigating regions, with increasing ozone levels through 2014. The results also show that ozone mixing ratios continue to decline significantly over eastern North America and Europe, however, there is less evidence for decreases of daytime average ozone at urban sites. The present-day spatial coverage of ozone monitors in East Asia (South Korea and Japan) and eastern North America is adequate for estimating regional trends by simply taking the average of the individual trends at each site. However the European network is more sparsely populated across its northern and eastern regions and therefore a simple average of the individual trends at each site does not yield an accurate regional trend. This analysis demonstrates that the GAMM technique can be used to assess the regional representativeness of existing monitoring networks, indicating those networks for which a regional trend can be obtained by simply averaging the trends of all individual sites and those networks that require a more sophisticated statistical approach.

Comparison of Calibration Techniques for Low-Cost Air Quality Monitoring

NASA Astrophysics Data System (ADS)

Malings, C.; Ramachandran, S.; Tanzer, R.; Kumar, S. P. N.; Hauryliuk, A.; Zimmerman, N.; Presto, A. A.

2017-12-01

Assessing the intra-city spatial distribution and temporal variability of air quality can be facilitated by a dense network of monitoring stations. However, the cost of implementing such a network can be prohibitive if high-quality but high-cost monitoring systems are used. To this end, the Real-time Affordable Multi-Pollutant (RAMP) sensor package has been developed at the Center for Atmospheric Particle Studies of Carnegie Mellon University, in collaboration with SenSevere LLC. This self-contained unit can measure up to five gases out of CO, SO2, NO, NO2, O3, VOCs, and CO2, along with temperature and relative humidity. Responses of individual gas sensors can vary greatly even when exposed to the same ambient conditions. Those of VOC sensors in particular were observed to vary by a factor-of-8, which suggests that each sensor requires its own calibration model. To this end, we apply and compare two different calibration methods to data collected by RAMP sensors collocated with a reference monitor station. The first method, random forest (RF) modeling, is a rule-based method which maps sensor responses to pollutant concentrations by implementing a trained sequence of decision rules. RF modeling has previously been used for other RAMP gas sensors by the group, and has produced precise calibrated measurements. However, RF models can only predict pollutant concentrations within the range observed in the training data collected during the collocation period. The second method, Gaussian process (GP) modeling, is a probabilistic Bayesian technique whereby broad prior estimates of pollutant concentrations are updated using sensor responses to generate more refined posterior predictions, as well as allowing predictions beyond the range of the training data. The accuracy and precision of these techniques are assessed and compared on VOC data collected during the summer of 2017 in Pittsburgh, PA. By combining pollutant data gathered by each RAMP sensor and applying appropriate calibration techniques, the potentially noisy or biased responses of individual sensors can be mapped to pollutant concentration values which are comparable to those of reference instruments.

Environmental impacts of unmanaged solid waste at a former base metal mining and ore processing site (Kirki, Greece).

PubMed

Liakopoulos, Alexandros; Lemière, Bruno; Michael, Konstantinos; Crouzet, Catherine; Laperche, Valérie; Romaidis, Ioannis; Drougas, Iakovos; Lassin, Arnault

2010-11-01

The Kirki project aimed to identify, among the mining waste abandoned at a mine and processing plant, the most critical potential pollution sources, the exposed milieus and the main pathways for contamination of a littoral area. This was accompanied by the definition of a monitoring network and remedial options. For this purpose, field analytical methods were extensively used to allow a more precise identification of the source, to draw relevant conceptual models and outline a monitoring network. Data interpretation was based on temporal series and on a geographical model. A classification method for mining waste was established, based on data on pollutant contents and emissions, and their long-term pollution potential. Mining waste present at the Kirki mine and plant sites comprises (A) extraction waste, mainly metal sulfide-rich rocks; (B) processing waste, mainly tailings, with iron and sulfides, sulfates or other species, plus residues of processing reagents; and (C) other waste, comprising leftover processing reagents and Pb-Zn concentrates. Critical toxic species include cadmium and cyanide. The stormy rainfall regime and hilly topography favour the flush release of large amounts of pollutants. The potential impacts and remedial options vary greatly. Type C waste may generate immediate and severe chemical hazards, and should be dealt with urgently by careful removal, as it is localised in a few spots. Type B waste has significant acid mine drainage potential and contains significant amounts of bioavailable heavy metals and metalloids, but they may also be released in solid form into the surface water through dam failure. The most urgent action is thus dams consolidation. Type A waste is by far the most bulky, and it cannot be economically removed. Unfortunately, it is also the most prone to acid mine drainage (seepage pH 1 to 2). This requires neutralisation to prevent acid water accelerating heavy metals and metalloids transfer. All waste management options require the implementation of a monitoring network for the design of a remediation plan, efficiency control, and later, community alert in case of accidental failure of mitigation/remediation measures. A network design strategy based on field measurements, laboratory validation and conceptual models is proposed.

Environmental, political, and economic determinants of water quality monitoring in Europe

NASA Astrophysics Data System (ADS)

Beck, Lucas; Bernauer, Thomas; Kalbhenn, Anna

2010-11-01

Effective monitoring is essential for effective pollution control in national and international water systems. To what extent are countries' monitoring choices driven by environmental criteria, as they should be? And to what extent are they also influenced by other factors, such as political and economic conditions? To address these questions, we describe and explain the evolution of one of the most important international environmental monitoring networks in Europe, the one for water quality, in the time period 1965-2004. We develop a geographic information system that contains information on the location of several thousand active monitoring stations in Europe. Using multivariate statistics, we then examine whether and to what extent the spatial and temporal clustering of monitoring intensity is driven by environmental, political, and economic factors. The results show that monitoring intensity is higher in river basins exposed to greater environmental pressure. However, political and economic factors also play a strong role in monitoring decisions: democracy, income, and peer pressure are conducive to monitoring intensity, and monitoring intensity generally increases over time. Moreover, even though monitoring is more intense in international upstream-downstream settings, we observe only a weak bias toward more monitoring downstream of international borders. In contrast, negative effects of European Union (EU) membership and runup to the EU's Water Framework Directive are potential reasons for concern. Our results strongly suggest that international coordination and standardization of water quality monitoring should be intensified. It will be interesting to apply our analytical approach also to other national and international monitoring networks, for instance, the U.S. National Water-Quality Assessment Program or the European Monitoring and Evaluation Program for air pollution.

Use long short-term memory to enhance Internet of Things for combined sewer overflow monitoring

NASA Astrophysics Data System (ADS)

Zhang, Duo; Lindholm, Geir; Ratnaweera, Harsha

2018-01-01

Combined sewer overflow causes severe water pollution, urban flooding and reduced treatment plant efficiency. Understanding the behavior of CSO structures is vital for urban flooding prevention and overflow control. Neural networks have been extensively applied in water resource related fields. In this study, we collect data from an Internet of Things monitoring CSO structure and build different neural network models for simulating and predicting the water level of the CSO structure. Through a comparison of four different neural networks, namely multilayer perceptron (MLP), wavelet neural network (WNN), long short-term memory (LSTM) and gated recurrent unit (GRU), the LSTM and GRU present superior capabilities for multi-step-ahead time series prediction. Furthermore, GRU achieves prediction performances similar to LSTM with a quicker learning curve.

Ecological impacts of atmospheric pollution and interactions with climate change in terrestrial ecosystems of the Mediterranean Basin: Current research and future directions.

PubMed

Ochoa-Hueso, Raúl; Munzi, Silvana; Alonso, Rocío; Arróniz-Crespo, María; Avila, Anna; Bermejo, Victoria; Bobbink, Roland; Branquinho, Cristina; Concostrina-Zubiri, Laura; Cruz, Cristina; Cruz de Carvalho, Ricardo; De Marco, Alessandra; Dias, Teresa; Elustondo, David; Elvira, Susana; Estébanez, Belén; Fusaro, Lina; Gerosa, Giacomo; Izquieta-Rojano, Sheila; Lo Cascio, Mauro; Marzuoli, Riccardo; Matos, Paula; Mereu, Simone; Merino, José; Morillas, Lourdes; Nunes, Alice; Paoletti, Elena; Paoli, Luca; Pinho, Pedro; Rogers, Isabel B; Santos, Arthur; Sicard, Pierre; Stevens, Carly J; Theobald, Mark R

2017-08-01

Mediterranean Basin ecosystems, their unique biodiversity, and the key services they provide are currently at risk due to air pollution and climate change, yet only a limited number of isolated and geographically-restricted studies have addressed this topic, often with contrasting results. Particularities of air pollution in this region include high O 3 levels due to high air temperatures and solar radiation, the stability of air masses, and dominance of dry over wet nitrogen deposition. Moreover, the unique abiotic and biotic factors (e.g., climate, vegetation type, relevance of Saharan dust inputs) modulating the response of Mediterranean ecosystems at various spatiotemporal scales make it difficult to understand, and thus predict, the consequences of human activities that cause air pollution in the Mediterranean Basin. Therefore, there is an urgent need to implement coordinated research and experimental platforms along with wider environmental monitoring networks in the region. In particular, a robust deposition monitoring network in conjunction with modelling estimates is crucial, possibly including a set of common biomonitors (ideally cryptogams, an important component of the Mediterranean vegetation), to help refine pollutant deposition maps. Additionally, increased attention must be paid to functional diversity measures in future air pollution and climate change studies to establish the necessary link between biodiversity and the provision of ecosystem services in Mediterranean ecosystems. Through a coordinated effort, the Mediterranean scientific community can fill the above-mentioned gaps and reach a greater understanding of the mechanisms underlying the combined effects of air pollution and climate change in the Mediterranean Basin. Copyright © 2017 Elsevier Ltd. All rights reserved.

Remote sensing of GHG over Paris megacity and Orléans forest using ground-based QualAir FTS and TCCON-Orléans

NASA Astrophysics Data System (ADS)

Te, Y.; Jeseck, P.; Da Costa, J.; Deutscher, N. M.; Warneke, T.; Notholt, J.

2012-04-01

In a growing world with more than 7 billion inhabitants and big emerging countries such as China, Brazil and India, emissions of anthropogenic pollutants are increasing continuously. Monitoring and control of atmospheric pollutants in megacities have become a major challenge for scientists and public health authorities in environmental research area. The QualAir platform at University Pierre et Marie Curie (UPMC), is an innovating experimental research platform dedicated to survey greenhouse gases (GHGs) and urban air quality. As one of the major instruments of the QualAir platform, the ground-based Fourier transform spectrometer (QualAir FTS, IFS 125HR model) analyses the composition of the urban atmosphere of Paris, which is the third European megacity. The continuous monitoring of atmospheric pollutants is essential to improve the understanding of urban air pollution processes. Associated with a sun-tracker, the QualAir remote sensing FTS operates in solar infrared absorption and enables to monitor many trace gases, and to follow up their variability in the Ile-de-France region. A description of the QualAir FTS will be given. Concentrations of atmospheric GHG, especially CO2 and CH4, are retrieved by the radiative transfer model PROFFIT. Located in the centre of Paris, the QualAir FTS can provide new and complementary urban measurements as compared to unpolluted ground-based stations of existing networks (NDACC and TCCON). The work made by LPMAA to join the TCCON network will also be presented. TCCON-Orléans is a ground-based FTS of the TCCON network located in the forest of Orléans (100 km south of Paris). Preliminary comparisons of GHGs measurements from both sites will be shown. Such ground-based information will help to better characterize regional GHGs, especially regarding anthropogenic emissions and trends.

CASTNet Air Toxics Monitoring Program (CATMP): VOC and carbonyl data for July, 1993 through March, 1994

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harlos, D.P.; Edgerton, E.S.

1994-12-31

The US EPA has, under the auspices of the CASTNet program (Clean Air Status and Trends Network), initiated the CASTNet Air Toxics Monitoring Program (CATMP). Volatile Organic Compounds (VOC) and carbonyls and metals are sampled for 24-hour periods on a 12-day schedule using TO-14 samplers (SUMMA canisters) and dinitrophenylhydrazine-coated (dmph) sorbent cartridges and high volume particle samplers. Sampling was begun at most sites in July of 1993. The sites are operated by state and local air pollution control programs and all analysis is performed by Environmental Science and Engineering (ESE) in Gainesville, Florida. The network currently supports 15 VOC sites,more » of which 7 also sample carbonyls. Three sites sample metals only in Pinellas County, Florida. The limits of detection of 0.05 ppb for VOCs allow routine tracking of a wide range of pollutants including several greenhouse gases, transportation pollutants and photochemically-derived compounds. The sites range from major urban areas (Chicago, St. Louis) to a rural village (Waterbury, Vermont). Results of the first three quarters of VOC and carbonyl data collection are summarized in this presentation.« less

Intra-urban and street scale variability of BTEX, NO 2 and O 3 in Birmingham, UK: Implications for exposure assessment

NASA Astrophysics Data System (ADS)

Vardoulakis, Sotiris; Solazzo, Efisio; Lumbreras, Julio

2011-09-01

Automatic monitoring networks have the ability of capturing air pollution episodes, as well as short- and long-term air quality trends in urban areas that can be used in epidemiological studies. However, due to practical constraints (e.g. cost and bulk of equipment), the use of automatic analysers is restricted to a limited number of roadside and background locations within a city. As a result, certain localised air pollution hotspots may be overlooked or overemphasised, especially near heavily trafficked street canyons and intersections. This has implications for compliance with regulatory standards and may cause exposure misclassification in epidemiological studies. Apart from automatic analysers, low cost passive diffusion tubes can be used to characterise the spatial variability of air pollution in urban areas. In this study, BTEX, NO 2 and O 3 data from a one-year passive sampling survey were used to characterise the intra-urban and street scale spatial variability of traffic-related pollutants in Birmingham (UK). In addition, continuous monitoring of NO 2, NO x, O 3, CO, SO 2, PM 10 and PM 2.5 from three permanent monitoring sites was used to identify seasonal and annual pollution patterns. The passive sampling measurements allowed us to evaluate the representativeness of a permanent roadside monitoring site that has recorded some of the highest NO 2 and PM 10 concentrations in Birmingham in recent years. Dispersion modelling was also used to gain further insight into pollutant sources and dispersion characteristics at this location. The strong spatial concentration gradients observed in busy streets, as well as the differences between roadside and urban background levels highlight the importance of appropriate positioning of air quality monitoring equipment in cities.

A MAC Protocol to Support Monitoring of Underwater Spaces.

PubMed

Santos, Rodrigo; Orozco, Javier; Ochoa, Sergio F; Meseguer, Roc; Eggly, Gabriel; Pistonesi, Marcelo F

2016-06-27

Underwater sensor networks are becoming an important field of research, because of their everyday increasing application scope. Examples of their application areas are environmental and pollution monitoring (mainly oil spills), oceanographic data collection, support for submarine geolocalization, ocean sampling and early tsunamis alert. The challenge of performing underwater communications is well known, provided that radio signals are useless in this medium, and a wired solution is too expensive. Therefore, the sensors in these networks transmit their information using acoustic signals that propagate well under water. This data transmission type not only brings an opportunity, but also several challenges to the implementation of these networks, e.g., in terms of energy consumption, data transmission and signal interference. In order to help advance the knowledge in the design and implementation of these networks for monitoring underwater spaces, this paper proposes a MAC protocol for acoustic communications between the nodes, based on a self-organized time division multiple access mechanism. The proposal was evaluated using simulations of a real monitoring scenario, and the obtained results are highly encouraging.

Trends in atmospheric heavy metals abundances over the Russian part of EMEP region in 1990-2012

NASA Astrophysics Data System (ADS)

Gromov, Sergey A.; Konkova, Elizaveta S.

2016-04-01

The European part of Russia is covered by two atmospheric environment monitoring networks established in the 1970s-1980s to monitor and evaluate anthropogenic pollution of regional/background natural environment. These are EMEP - European Monitoring and Evaluation Program of transboundary atmospheric pollutant transmission (under the UN ECE Convention on Long-Range Transboundary Air Pollution) and IBMoN - Integrated Background Monitoring Network of environmental toxic pollution (prior to 1990 under the UNEP/GEMS supervision, mostly for East European countries). IGCE laboratories operate as analytical centers for both networks. Historically, IBMoN was partly implemented at EMEP sites to support this international program with additional (optional) data. IBMoN datasets were selected for analysis of atmospheric heavy metal trends in the Russian territory of EMEP region for the last twenty three years due to more intensive operation up to now [1, 2]. Atmospheric heavy metals are collected at the remote sites with the air samples of atmospheric aerosols deposited on Petryanov's cellulose acetate filters through high-volume pumping during 24 hours. To measure lead and cadmium content, filters are transferred into the solution to determine total amounts by the Atomic Absorption Spectroscopy (AAS) with flameless atomization. Precipitation samples (collected monthly with acidic preserving) are directly injected into the AAS detection module after filtering. The sampling procedure, special processing and analytical techniques allow us to measure concentrations at substantially low levels [3, 2]. In this study we investigate the long term trends of lead and cadmium in air and precipitation at two stations, viz. Astrakhan Biosphere Reserve (46°N, 49°E) and Danki (Oka-Terrace Biosphere Reserve, 54.9°N, 37.8°E). Following the EMEP general recommendations, the evaluation was done for two continuous periods covering 1990-2001 and 2002-2012, respectively. We apply the common methodology recommended by WMO/EMEP Task Force for trend evaluation, implemented in software developed and distributed by EMEP [4]. This methodology allows approximation of apparent trends using the superposition of the exponential (main) and residual components obtained using the ad hoc trend regression model. We further use so-called reduction parameters to investigate quantitatively the nature of trends: The total over the period (Rtot) and annual average (Rave), with the latter corresponding to increasing trend at negative values. Overall, temporal tendencies of airborne cadmium and lead demonstrate similar behaviour, however on top of different average concentration levels. For both species our analysis confirms the increase in air and precipitation abundances at the regional and remote sites over the European part of Russia for the period of 2002-2012. References: 1. Gromov S.A., and S.G. Paramonov, 2015. Current status and prospects for the development of integrated background monitoring of environmental pollution. Problems of Ecological Monitoring and Ecosystem Modelling, v. XXVI, N 1, p. 205-221. 2. Rovinsky F.Ya. (Ed.), 1989. Analytical review of environmental pollution with heavy metals in background areas of the CMEA member countries (1982-1989). Moscow, Gidrometeoizdat, 88 p. 3. Izrael Yu.A., and F.Ya. Rovinsky, 1991. Integrated background monitoring of environmental pollution in mid-latitude Eurasia. WMO Global Atmospheric Watch No 72, WMO/TD No. 434, 104 p. 4. MSC-East, 2015. Methodology of trend analysis of air quality data (http://www.msceast.org/documents/ Methodology_of_trend_analysis.pdf).

On the Effect of Preferential Sampling in Spatial Prediction

EPA Science Inventory

The choice of the sampling locations in a spatial network is often guided by practical demands. In particular, typically, locations are preferentially chosen to capture high values of a response, for example, air pollution levels in environmental monitoring. Then, model estimatio...

Distributed intelligent urban environment monitoring system

NASA Astrophysics Data System (ADS)

Du, Jinsong; Wang, Wei; Gao, Jie; Cong, Rigang

2018-02-01

The current environmental pollution and destruction have developed into a world-wide major social problem that threatens human survival and development. Environmental monitoring is the prerequisite and basis of environmental governance, but overall, the current environmental monitoring system is facing a series of problems. Based on the electrochemical sensor, this paper designs a small, low-cost, easy to layout urban environmental quality monitoring terminal, and multi-terminal constitutes a distributed network. The system has been small-scale demonstration applications and has confirmed that the system is suitable for large-scale promotion

The Issue of transporting pollutants with atmospheric precipitation

NASA Astrophysics Data System (ADS)

Madibekov, A.; Kogutenko, L.

2018-01-01

A research of the pollution of atmospheric precipitation was conducted. The database of the chemical composition of atmospheric precipitation made by National Monitoring Network of the Republic of Kazakhstan for the period from 2000s to 2011 was generalized and analyzed. The research area covers the big territory of Ile-Balkhash river basin in the South-East Kazakhstan. The research shows that pollutants can be transported over long distances with atmospheric precipitation. Based on the results of the air masses tracking we identified that the main sources of emissions is located in the city of Balkhash.

Low-cost mobile air pollution monitoring in urban environments: a pilot study in Lubbock, Texas.

PubMed

McKercher, Grant R; Vanos, Jennifer K

2018-06-01

The complex nature of air pollution in urban areas prevents traditional monitoring techniques from obtaining measurements representative of true human exposure. The current study assessed the capability of low-cost mobile monitors to acquire useful data in a city without a monitoring network in place (Lubbock, Texas) using a bicycle platform. The monitoring campaign resulted in 30 days of data along a 13.4 km fixed concentric route. Due to high sensitivities to airflow, the apparent wind velocity was accounted for throughout the route. The data were also normalized into percentiles in order to visualize spatial patterns. The highest estimated pollution levels were located near frequently busy intersections and roads; however, sensor issues resulted in lower confidence. Additional research is needed concerning the appropriate use of low-cost metal oxide sensors for citizen science applications, as measurements can be misleading if the user is unaware of sensors specifications. The simultaneous use of several low-cost mobile platforms, rather than a single platform, as well as the use of high-end cases, are recommended to create a more robust spatial analysis. The issues addressed from this research are important to understand for accurate and beneficial application of low-cost gaseous monitors for citizen science.

Prediction of Air Pollutants Concentration Based on an Extreme Learning Machine: The Case of Hong Kong

PubMed Central

Zhang, Jiangshe; Ding, Weifu

2017-01-01

With the development of the economy and society all over the world, most metropolitan cities are experiencing elevated concentrations of ground-level air pollutants. It is urgent to predict and evaluate the concentration of air pollutants for some local environmental or health agencies. Feed-forward artificial neural networks have been widely used in the prediction of air pollutants concentration. However, there are some drawbacks, such as the low convergence rate and the local minimum. The extreme learning machine for single hidden layer feed-forward neural networks tends to provide good generalization performance at an extremely fast learning speed. The major sources of air pollutants in Hong Kong are mobile, stationary, and from trans-boundary sources. We propose predicting the concentration of air pollutants by the use of trained extreme learning machines based on the data obtained from eight air quality parameters in two monitoring stations, including Sham Shui Po and Tap Mun in Hong Kong for six years. The experimental results show that our proposed algorithm performs better on the Hong Kong data both quantitatively and qualitatively. Particularly, our algorithm shows better predictive ability, with R2 increased and root mean square error values decreased respectively. PMID:28125034

Delay/Disruption Tolerant Network-Based Message Forwarding for a River Pollution Monitoring Wireless Sensor Network Application.

PubMed

Velásquez-Villada, Carlos; Donoso, Yezid

2016-03-25

Communications from remote areas that may be of interest is still a problem. Many innovative projects applied to remote sites face communications difficulties. The GOLDFISH project was an EU-funded project for river pollution monitoring in developing countries. It had several sensor clusters, with floating WiFi antennas, deployed along a downstream river's course. Sensor clusters sent messages to a Gateway installed on the riverbank. This gateway sent the messages, through a backhaul technology, to an Internet server where data was aggregated over a map. The communication challenge in this scenario was produced by the antennas' movement and network backhaul availability. Since the antennas were floating on the river, communications could be disrupted at any time. Also, 2G/3G availability near the river was not constant. For non-real-time applications, we propose a Delay/Disruption Tolerant Network (DTN)-based solution where all nodes have persistent storage capabilities and DTN protocols to be able to wait minutes or hours to transmit. A mechanical backhaul will periodically visit the river bank where the gateway is installed and it will automatically collect sensor data to be carried to an Internet-covered spot. The proposed forwarding protocol delivers around 98% of the messages for this scenario, performing better than other well-known DTN routing protocols.

Study of meteorological aspects and urban concentration of SO2 in atmospheric environment of La Plata, Argentina.

PubMed

Ratto, Gustavo; Videla, Fabián; Almandos, J Reyna; Maronna, Ricardo; Schinca, Daniel

2006-10-01

This article presents and discusses SO(2) (ppbv) concentration measurements combined with meteorological data (mainly wind speed and direction) for a five-year campaign (1996 to 2000), in a site near an oil refinery plant close to the city of La Plata and surroundings (aprox. 740.000 inh.), considered one of the six most affected cities by air pollution in the country. Since there is no monitoring network in the area, the obtained results should be considered as medium term accumulated data that enables to determine trends by analyzing together gas concentrations and meteorological parameters. Preliminary characterization of the behaviour of the predominant winds of the region in relation with potential atmospheric gas pollutants from seasonal wind roses is possible to carry out from the data. These results are complemented with monthly averaged SO(2) measurements. In particular, for year 2000, pollutant roses were determined which enable predictions about contamination emission sources. As a general result we can state that there is a clear increase in annual SO(2) concentration and that the selected site should be considered as a key site for future survey monitoring network deployment. Annual SO(2) average concentration and prevailing seasonal winds determined in this work, together with the potential health impact of SO(2) reveals the need for a comprehensive and systematic study involving particulate matter an other basic pollutant gases.

Atlanta Rail Yard Study: Evaluation of local-scale air pollution ...

EPA Pesticide Factsheets

Intermodal rail yards are important nodes in the freight transportation network, where freight is organized and moved from one mode of transport to another, critical equipment is serviced, and freight is routed to its next destination. Rail yard environments are also areas with multiple sources of air pollutant emissions (e.g., heavy-duty vehicles, locomotives, cranes), which may affect local air quality in residential areas nearby. In order to understand emissions and related air quality impacts, two field studies took place over the time span of 2010-2012 to measure air pollution trends in close proximity to the Inman and Tilford rail yard complex in Atlanta, GA. One field study involved long-term stationary monitoring of black carbon, fine particles, and carbon dioxide at two stations nearby the rail yard. In addition, a second field study performed intensive mobile air monitoring for a one month period in the summer of 2012 at a roadway network surrounding the rail yard complex and measured a comprehensive array of pollutants. Real-time mobile particulate measurements included particle counts, extinction coefficient, black carbon via light-absorption and particle incandescence, and particle composition derived by aerosol mass spectrometry. Gas-phase measurements included oxides of nitrogen, sulfur dioxide, carbon dioxide, and air toxics (e.g., benzene). Both sets of measurements determined detectable local influence from rail yard-related emissions.

Use of multi-objective air pollution monitoring sites and online air pollution monitoring system for total health risk assessment in Hyderabad, India.

PubMed

Anjaneyulu, Y; Jayakumar, I; Hima Bindu, V; Sagareswar, G; Mukunda Rao, P V; Rambabu, N; Ramani, K V

2005-08-01

A consensus has been emerging among public health experts in developing countries that air pollution, even at current ambient levels, aggravates respiratory and cardiovascular diseases and leads to premature mortality. Recent studies have also presented well-founded theories concerning the biological mechanisms involved and the groups of people that are probably more susceptible to health effects caused or exacerbated by inhalation of ambient particulate matter (PM.). On the basis of prognostic studies carried out in Center for Environment, JNT University, Hyderabad "it has been estimated that in Hyderabad some 1,700 to 3,000 people per year die prematurely as a result of inhaling PM". These figures reflect only the effects of acute exposure to air pollution. If the long-term effects of chronic exposure are taken into account, 10,000-15,000 people a year could die prematurely in Hyderabad. This estimate of the chronic effects is based on other studies, which are not completely comparable with the Hyderabad situation. While the study designs and analyses in these other studies may indeed be different or irrelevant to Hyderabad, the fact they were carried out in other countries is irrelevant. Taking into account these considerations, a model for total health risk assessment for the city of Hyderabad, and its state of Andhra Pradesh in India has been developed using a multi-objective air pollution monitoring network and online and real time air pollution monitoring stations. For the model studies a number of potential monitoring sites were screened for general and site-specific criteria in a geographic information system (GIS) environment that may, on a local basis, affect the representativeness of the data collected. Local features that may affect either the chemical or meteorological parameters are evaluated to assure a minimum of interference. Finally, for monitoring air pollution, an online and real-time monitoring system was designed using advanced electrochemical sensor systems (sulphur dioxide, oxides of nitrogen, carbon monoxide, hydrocarbons, ozone, mercaptans and hydrogen sulphide) and a particulate matter analyzer (total suspended particulate matter TSPM), PM2.5 and PM10). The sensor and data acquisition systems are programmed to monitor pollution levels at 1/2 hour durations during peak hours and at 1-hour intervals at other times. Presently, extensive statistical and numerical simulations are being carried out at our center to correlate the individuals living in the monitored areas with respiratory infections with air pollution.

Use of Multi-Objective Air Pollution Monitoring Sites and Online Air Pollution Monitoring System for Total Health Risk Assessment in Hyderabad, India

PubMed Central

Anjaneyulu, Y.; Jayakumar, I.; Bindu, V. Hima; Sagareswar, G.; Rao, P.V. Mukunda; Rambabu, N.; Ramani, K. V.

2005-01-01

A consensus has been emerging among public health experts in developing countries that air pollution, even at current ambient levels, aggravates respiratory and cardiovascular diseases and leads to premature mortality. Recent studies have also presented well-founded theories concerning the biological mechanisms involved and the groups of people that are probably more susceptible to health effects caused or exacerbated by inhalation of ambient particulate matter (PM.). On the basis of prognostic studies carried out in Center for Environment, JNT University, Hyderabad “it has been estimated that in Hyderabad some 1,700 to 3,000 people per year die prematurely as a result of inhaling PM”. These figures reflect only the effects of acute exposure to air pollution. If the long-term effects of chronic exposure are taken into account, 10,000–15,000 people a year could die prematurely in Hyderabad. This estimate of the chronic effects is based on other studies, which are not completely comparable with the Hyderabad situation. While the study designs and analyses in these other studies may indeed be different or irrelevant to Hyderabad, the fact they were carried out in other countries is irrelevant. Taking into account these considerations, a model for total health risk assessment for the city of Hyderabad, and its state of Andhra Pradesh in India has been developed using a multi-objective air pollution monitoring network and online and real time air pollution monitoring stations. For the model studies a number of potential monitoring sites were screened for general and site-specific criteria in a geographic information system (GIS) environment that may, on a local basis, affect the representativeness of the data collected. Local features that may affect either the chemical or meteorological parameters are evaluated to assure a minimum of interference. Finally, for monitoring air pollution, an online and real-time monitoring system was designed using advanced electrochemical sensor systems (sulphur dioxide, oxides of nitrogen, carbon monoxide, hydrocarbons, ozone, mercaptans and hydrogen sulphide) and a particulate matter analyzer (total suspended particulate matter TSPM), PM2.5 and PM10). The sensor and data acquisition systems are programmed to monitor pollution levels at ½ hour durations during peak hours and at 1-hour intervals at other times. Presently, extensive statistical and numerical simulations are being carried out at our center to correlate the individuals living in the monitored areas with respiratory infections with air pollution. PMID:16705838

Cluster categorization of urban roads to optimize their noise monitoring.

PubMed

Zambon, G; Benocci, R; Brambilla, G

2016-01-01

Road traffic in urban areas is recognized to be associated with urban mobility and public health, and it is often the main source of noise pollution. Lately, noise maps have been considered a powerful tool to estimate the population exposure to environmental noise, but they need to be validated by measured noise data. The project Dynamic Acoustic Mapping (DYNAMAP), co-funded in the framework of the LIFE 2013 program, is aimed to develop a statistically based method to optimize the choice and the number of monitoring sites and to automate the noise mapping update using the data retrieved from a low-cost monitoring network. Indeed, the first objective should improve the spatial sampling based on the legislative road classification, as this classification is mainly based on the geometrical characteristics of the road, rather than its noise emission. The present paper describes the statistical approach of the methodology under development and the results of its preliminary application to a limited sample of roads in the city of Milan. The resulting categorization of roads, based on clustering the 24-h hourly L Aeqh, looks promising to optimize the spatial sampling of noise monitoring toward a description of the noise pollution due to complex urban road networks more efficient than that based on the legislative road classification.

Space-Time Urban Air Pollution Forecasts

NASA Astrophysics Data System (ADS)

Russo, A.; Trigo, R. M.; Soares, A.

2012-04-01

Air pollution, like other natural phenomena, may be considered a space-time process. However, the simultaneous integration of time and space is not an easy task to perform, due to the existence of different uncertainties levels and data characteristics. In this work we propose a hybrid method that combines geostatistical and neural models to analyze PM10 time series recorded in the urban area of Lisbon (Portugal) for the 2002-2006 period and to produce forecasts. Geostatistical models have been widely used to characterize air pollution in urban areas, where the pollutant sources are considered diffuse, and also to industrial areas with localized emission sources. It should be stressed however that most geostatistical models correspond basically to an interpolation methodology (estimation, simulation) of a set of variables in a spatial or space-time domain. The temporal prediction of a pollutant usually requires knowledge of the main trends and complex patterns of physical dispersion phenomenon. To deal with low resolution problems and to enhance reliability of predictions, an approach based on neural network short term predictions in the monitoring stations which behave as a local conditioner to a fine grid stochastic simulation model is presented here. After the pollutant concentration is predicted for a given time period at the monitoring stations, we can use the local conditional distributions of observed values, given the predicted value for that period, to perform the spatial simulations for the entire area and consequently evaluate the spatial uncertainty of pollutant concentration. To attain this objective, we propose the use of direct sequential simulations with local distributions. With this approach one succeed to predict the space-time distribution of pollutant concentration that accounts for the time prediction uncertainty (reflecting the neural networks efficiency at each local monitoring station) and the spatial uncertainty as revealed by the spatial variograms. The dataset used consists of PM10 concentrations recorded hourly by 12 monitoring stations within the Lisbon's area, for the period 2002-2006. In addition, meteorological data recorded at 3 monitoring stations and boundary layer height (BLH) daily values from the ECMWF (European Centre for Medium Weather Forecast), ERA Interim, were also used. Based on the large-scale standard pressure fields from the ERA40/ECMWF, prevailing circulation patterns at regional scale where determined and used on the construction of the models. After the daily forecasts were produced, the difference between the average maps based on real observations and predicted values were determined and the model's performance was assessed. Based on the analysis of the results, we conclude that the proposed approach shows to be a very promising alternative for urban air quality characterization because of its good results and simplicity of application.

A low-cost sensing system for cooperative air quality monitoring in urban areas.

PubMed

Brienza, Simone; Galli, Andrea; Anastasi, Giuseppe; Bruschi, Paolo

2015-05-26

Air quality in urban areas is a very important topic as it closely affects the health of citizens. Recent studies highlight that the exposure to polluted air can increase the incidence of diseases and deteriorate the quality of life. Hence, it is necessary to develop tools for real-time air quality monitoring, so as to allow appropriate and timely decisions. In this paper, we present uSense, a low-cost cooperative monitoring tool that allows knowing, in real-time, the concentrations of polluting gases in various areas of the city. Specifically, users monitor the areas of their interest by deploying low-cost and low-power sensor nodes. In addition, they can share the collected data following a social networking approach. uSense has been tested through an in-field experimentation performed in different areas of a city. The obtained results are in line with those provided by the local environmental control authority and show that uSense can be profitably used for air quality monitoring.

Incorpoaration of Geosensor Networks Into Internet of Things for Environmental Monitoring

NASA Astrophysics Data System (ADS)

Habibi, R.; Alesheikh, A. A.

2015-12-01

Thanks to the recent advances of miniaturization and the falling costs for sensors and also communication technologies, Internet specially, the number of internet-connected things growth tremendously. Moreover, geosensors with capability of generating high spatial and temporal resolution data, measuring a vast diversity of environmental data and automated operations provide powerful abilities to environmental monitoring tasks. Geosensor nodes are intuitively heterogeneous in terms of the hardware capabilities and communication protocols to take part in the Internet of Things scenarios. Therefore, ensuring interoperability is an important step. With this respect, the focus of this paper is particularly on incorporation of geosensor networks into Internet of things through an architecture for monitoring real-time environmental data with use of OGC Sensor Web Enablement standards. This approach and its applicability is discussed in the context of an air pollution monitoring scenario.

Simulating the dispersion of NOx and CO2 in the city of Zurich at building resolving scale

NASA Astrophysics Data System (ADS)

Brunner, Dominik; Berchet, Antoine; Emmenegger, Lukas; Henne, Stephan; Müller, Michael

2017-04-01

Cities are emission hotspots for both greenhouse gases and air pollutants. They contribute about 70% of global greenhouse gas emissions and are home to a growing number of people potentially suffering from poor air quality in the urban environment. High-resolution atmospheric transport modelling of greenhouse gases and air pollutants at the city scale has, therefore, several important applications such as air pollutant exposure assessment, air quality forecasting, or urban planning and management. When combined with observations, it also has the potential to quantify emissions and monitor their long-term trends, which is the main motivation for the deployment of urban greenhouse gas monitoring networks. We have developed a comprehensive atmospheric modeling model system for the city of Zurich, Switzerland ( 600,000 inhabitants including suburbs), which is composed of the mesoscale model GRAMM simulating the flow in a larger domain around Zurich at 100 m resolution, and the nested high-resolution model GRAL simulating the flow and air pollutant dispersion in the city at building resolving (5-10 m) scale. Based on an extremely detailed emission inventory provided by the municipality of Zurich, we have simulated two years of hourly NOx and CO2 concentration fields across the entire city. Here, we present a detailed evaluation of the simulations against a comprehensive network of continuous monitoring sites and passive samplers for NOx and analyze the sensitivity of the results to the temporal variability of the emissions. Furthermore, we present first simulations of CO2 and investigate the challenges associated with CO2 sources not covered by the inventory such as human respiration and exchange fluxes with urban vegetation.

Method to Select Metropolitan Areas of Epidemiologic Interest for Enhanced Air Quality Monitoring

EPA Science Inventory

The U.S. Environmental Protection Agency’s current Speciation Trends Network (STN) covers most major U.S. metropolitan areas and a wide range of particulate matter (PM) constituents and gaseous co-pollutants. However, using filter-based methods, most PM constituents are measured ...

MLP based models to predict PM10, O3 concentrations, in Sines industrial area

NASA Astrophysics Data System (ADS)

Durao, R.; Pereira, M. J.

2012-04-01

Sines is an important Portuguese industrial area located southwest cost of Portugal with important nearby protected natural areas. The main economical activities are related with this industrial area, the deep-water port, petrochemical and thermo-electric industry. Nevertheless, tourism is also an important economic activity especially in summer time with potential to grow. The aim of this study is to develop prediction models of pollutant concentration categories (e.g. low concentration and high concentration) in order to provide early warnings to the competent authorities who are responsible for the air quality management. The knowledge in advanced of pollutant high concentrations occurrence will allow the implementation of mitigation actions and the release of precautionary alerts to population. The regional air quality monitoring network consists in three monitoring stations where a set of pollutants' concentrations are registered on a continuous basis. From this set stands out the tropospheric ozone (O3) and particulate matter (PM10) due to the high concentrations occurring in the region and their adverse effects on human health. Moreover, the major industrial plants of the region monitor SO2, NO2 and particles emitted flows at the principal chimneys (point sources), also on a continuous basis,. Therefore Artificial neuronal networks (ANN) were the applied methodology to predict next day pollutant concentrations; due to the ANNs structure they have the ability to capture the non-linear relationships between predictor variables. Hence the first step of this study was to apply multivariate exploratory techniques to select the best predictor variables. The classification trees methodology (CART) was revealed to be the most appropriate in this case.. Results shown that pollutants atmospheric concentrations are mainly dependent on industrial emissions and a complex combination of meteorological factors and the time of the year. In the second step, the Multi-layer perceptron (MLP) have shown to be able to learn the existent complex relationships using different combination of meteorological and emissions variables. Furthermore, MLP models identified what are the meteorological conditions that most affect O3 and PM10 concentrations in the region, namely wind speed and direction, boundary layer height, temperature, sunshine duration, relative humidity and the weather type. The developed MLP models showed good predictive success with model performances between 0.66 and 0.87, indicating a reasonable accuracy for models development and generalization capability. These performance values are obtained using cross entropy error functions. This error functions are only available for classification problems and ensure that the network outputs are true class membership probabilities, which is known to enhance the performance of classification neural networks.

Water toxicity assessment and spatial pollution patterns identification in a Mediterranean River Basin District. Tools for water management and risk analysis.

PubMed

Carafa, Roberta; Faggiano, Leslie; Real, Montserrat; Munné, Antoni; Ginebreda, Antoni; Guasch, Helena; Flo, Monica; Tirapu, Luís; von der Ohe, Peter Carsten

2011-09-15

In compliance with the requirements of the EU Water Framework Directive, monitoring of the ecological and chemical status of Catalan river basins (NE Spain) is carried out by the Catalan Water Agency. The large amount of data collected and the complex relationships among the environmental variables monitored often mislead data interpretation in terms of toxic impact, especially considering that even pollutants at very low concentrations might contribute to the total toxicity. The total dataset of chemical monitoring carried out between 2007 and 2008 (232 sampling stations and 60 pollutants) has been analyzed using sequential advanced modeling techniques. Data on concentrations of contaminants in water were pre-treated in order to calculate the bioavailable fraction, depending on substance properties and local environmental conditions. The resulting values were used to predict the potential impact of toxic substances in complex mixtures on aquatic biota and to identify hot spots. Exposure assessment with Species Sensitivity Distribution (SSD) and mixture toxicity rules were used to compute the multi-substances Potentially Affected Fraction (msPAF). The combined toxicity of the pollutants analyzed in the Catalan surface waters might potentially impact more than 50% of the species in 10% of the sites. In order to understand and visualize the spatial distribution of the toxic risk, Self Organising Map (SOM), based on the Kohonen's Artificial Neural Network (ANN) algorithm, was applied on the output data of these models. Principal Component Analysis (PCA) was performed on top of Neural Network results in order to identify main influential variables which account for the pollution trends. Finally, predicted toxic impacts on biota have been linked and correlated to field data on biological quality indexes using macroinvertebrate and diatom communities (IBMWP and IPS). The methodology presented could represent a suitable tool for water managers in environmental risk assessment and management. Copyright © 2011 Elsevier B.V. All rights reserved.

Challenges of agricultural monitoring: integration of the Open Farm Management Information System into GEOSS and Digital Earth

NASA Astrophysics Data System (ADS)

Řezník, T.; Kepka, M.; Charvát, K.; Charvát, K., Jr.; Horáková, S.; Lukas, V.

2016-04-01

From a global perspective, agriculture is the single largest user of freshwater resources, each country using an average of 70% of all its surface water supplies. An essential proportion of agricultural water is recycled back to surface water and/or groundwater. Agriculture and water pollution is therefore the subject of (inter)national legislation, such as the Clean Water Act in the United States of America, the European Water Framework Directive, and the Law of the People's Republic of China on the Prevention and Control of Water Pollution. Regular monitoring by means of sensor networks is needed in order to provide evidence of water pollution in agriculture. This paper describes the benefits of, and open issues stemming from, regular sensor monitoring provided by an Open Farm Management Information System. Emphasis is placed on descriptions of the processes and functionalities available to users, the underlying open data model, and definitions of open and lightweight application programming interfaces for the efficient management of collected (spatial) data. The presented Open Farm Management Information System has already been successfully registered under Phase 8 of the Global Earth Observation System of Systems (GEOSS) Architecture Implementation Pilot in order to support the wide variety of demands that are primarily aimed at agriculture pollution monitoring. The final part of the paper deals with the integration of the Open Farm Management Information System into the Digital Earth framework.

Non-methane hydrocarbons in the atmosphere of Mexico City: Results of the 2012 ozone-season campaign

NASA Astrophysics Data System (ADS)

Jaimes-Palomera, Mónica; Retama, Armando; Elias-Castro, Gabriel; Neria-Hernández, Angélica; Rivera-Hernández, Olivia; Velasco, Erik

2016-05-01

With the aim to strengthen the verification capabilities of the local air quality management, the air quality monitoring network of Mexico City has started the monitoring of selected non-methane hydrocarbons (NMHCs). Previous information on the NMHC characterization had been obtained through individual studies and comprehensive intensive field campaigns, in both cases restricted to sampling periods of short duration. This new initiative will address the NMHC pollution problem during longer monitoring periods and provide robust information to evaluate the effectiveness of new control measures. The article introduces the design of the monitoring network and presents results from the first campaign carried out during the first six months of 2012 covering the ozone-season (Mar-May). Using as reference data collected in 2003, results show reductions during the morning rush hour (6-9 h) in the mixing ratios of light alkanes associated with the consumption and distribution of liquefied petroleum gas and aromatic compounds related with the evaporation of fossil fuels and solvents, in contrast to olefins from vehicular traffic. The increase in mixing ratios of reactive olefins is of relevance to understand the moderate success in the ozone and fine aerosols abatement in recent years in comparison to other criteria pollutants. In the case of isoprene, the typical afternoon peak triggered by biogenic emissions was clearly observed for the first time within the city. The diurnal profiles of the monitored compounds are analyzed in terms of the energy balance throughout the day as a surrogate of the boundary layer evolution. Particular features of the diurnal profiles and correlation between individual NMHCs and carbon monoxide are used to investigate the influence of specific emission sources. The results discussed here highlight the importance of monitoring NMHCs to better understand the drivers and impacts of air pollution in large cities like Mexico City.

[Research on hyperspectral remote sensing in monitoring snow contamination concentration].

PubMed

Tang, Xu-guang; Liu, Dian-wei; Zhang, Bai; Du, Jia; Lei, Xiao-chun; Zeng, Li-hong; Wang, Yuan-dong; Song, Kai-shan

2011-05-01

Contaminants in the snow can be used to reflect regional and global environmental pollution caused by human activities. However, so far, the research on space-time monitoring of snow contamination concentration for a wide range or areas difficult for human to reach is very scarce. In the present paper, based on the simulated atmospheric deposition experiments, the spectroscopy technique method was applied to analyze the effect of different contamination concentration on the snow reflectance spectra. Then an evaluation of snow contamination concentration (SCC) retrieval methods was conducted using characteristic index method (SDI), principal component analysis (PCA), BP neural network and RBF neural network method, and the estimate effects of four methods were compared. The results showed that the neural network model combined with hyperspectral remote sensing data could estimate the SCC well.

Development of a wireless sensor network for individual monitoring of panels in a photovoltaic plant.

PubMed

Prieto, Miguel J; Pernía, Alberto M; Nuño, Fernando; Díaz, Juan; Villegas, Pedro J

2014-01-30

With photovoltaic (PV) systems proliferating in the last few years due to the high prices of fossil fuels and pollution issues, among others, it is extremely important to monitor the efficiency of these plants and optimize the energy production process. This will also result in improvements related to the maintenance and security of the installation. In order to do so, the main parameters in the plant must be continuously monitored so that the appropriate actions can be carried out. This monitoring should not only be carried out at a global level, but also at panel-level, so that a better understanding of what is actually happening in the PV plant can be obtained. This paper presents a system based on a wireless sensor network (WSN) that includes all the components required for such monitoring as well as a power supply obtaining the energy required by the sensors from the photovoltaic panels. The system proposed succeeds in identifying all the nodes in the network and provides real-time monitoring while tracking efficiency, features, failures and weaknesses from a single cell up to the whole infrastructure. Thus, the decision-making process is simplified, which contributes to reducing failures, wastes and, consequently, costs.

Outlier Detection in Urban Air Quality Sensor Networks.

PubMed

van Zoest, V M; Stein, A; Hoek, G

2018-01-01

Low-cost urban air quality sensor networks are increasingly used to study the spatio-temporal variability in air pollutant concentrations. Recently installed low-cost urban sensors, however, are more prone to result in erroneous data than conventional monitors, e.g., leading to outliers. Commonly applied outlier detection methods are unsuitable for air pollutant measurements that have large spatial and temporal variations as occur in urban areas. We present a novel outlier detection method based upon a spatio-temporal classification, focusing on hourly NO 2 concentrations. We divide a full year's observations into 16 spatio-temporal classes, reflecting urban background vs. urban traffic stations, weekdays vs. weekends, and four periods per day. For each spatio-temporal class, we detect outliers using the mean and standard deviation of the normal distribution underlying the truncated normal distribution of the NO 2 observations. Applying this method to a low-cost air quality sensor network in the city of Eindhoven, the Netherlands, we found 0.1-0.5% of outliers. Outliers could reflect measurement errors or unusual high air pollution events. Additional evaluation using expert knowledge is needed to decide on treatment of the identified outliers. We conclude that our method is able to detect outliers while maintaining the spatio-temporal variability of air pollutant concentrations in urban areas.

Evaluation and intercomparison of five major dry deposition algorithms in North America

EPA Science Inventory

Dry deposition of various pollutants needs to be quantified in air quality monitoring networks as well as in chemical transport models. The inferential method is the most commonly used approach in which the dry deposition velocity (Vd) is empirically parameterized as a function o...

Atlanta Rail Yard Study: Evaluation of local-scale air pollution trends using stationary and mobile monitoring

EPA Science Inventory

Intermodal rail yards are important nodes in the freight transportation network, where freight is organized and moved from one mode of transport to another, critical equipment is serviced, and freight is routed to its next destination. Rail yard environments are also areas with ...

Assessing transboundary influences in the lower Rio Grande Valley

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mukerjee, S.; Shadwick, D.S.; Dean, K.E.

1999-07-01

The Lower Rio Grande Valley Transboundary Air Pollution Project (TAPP) was a US-Mexico Border XXI Program project to assess transboundary air pollution in and near Brownsville, Texas. The study used a three-site air monitoring network very close to the border to capture the direct impact of local sources and transboundary transport. Ambient data included particulate mass and elemental composition, VOCs, PAHs, pesticides, and meteorology. Also, near real-time, PM{sub 2.5} mass measurements captured potential pollutant plume events occurring over 1-h periods. Data collected were compared to screening levels and other monitoring data to assess general air pollution impacts on nearby bordermore » communities. Wind sector analyses, chemical tracer analyses, principal component analyses, and other techniques were used to assess the extent of transboundary transport of air pollutants and identify possible transboundary air pollution sources. Overall, ambient levels were comparable to or lower than other urban and rural areas in Texas and elsewhere. Movement of air pollution across the border did not appear to cause noticeable deterioration of air quality on the US side of the Lower Rio Grande Valley. Dominant southeasterly winds from the Gulf of Mexico were largely responsible for the clean air conditions in the Brownsville airshed. Few observations of pollutants exceeded effects screening levels, almost all being VOCs; these appeared to be due to local events and immediate influences, not regional phenomena or persistent transboundary plumes.« less

Compliance Groundwater Monitoring of Nonpoint Sources - Emerging Approaches

NASA Astrophysics Data System (ADS)

Harter, T.

2008-12-01

Groundwater monitoring networks are typically designed for regulatory compliance of discharges from industrial sites. There, the quality of first encountered (shallow-most) groundwater is of key importance. Network design criteria have been developed for purposes of determining whether an actual or potential, permitted or incidental waste discharge has had or will have a degrading effect on groundwater quality. The fundamental underlying paradigm is that such discharge (if it occurs) will form a distinct contamination plume. Networks that guide (post-contamination) mitigation efforts are designed to capture the shape and dynamics of existing, finite-scale plumes. In general, these networks extend over areas less than one to ten hectare. In recent years, regulatory programs such as the EU Nitrate Directive and the U.S. Clean Water Act have forced regulatory agencies to also control groundwater contamination from non-incidental, recharging, non-point sources, particularly agricultural sources (fertilizer, pesticides, animal waste application, biosolids application). Sources and contamination from these sources can stretch over several tens, hundreds, or even thousands of square kilometers with no distinct plumes. A key question in implementing monitoring programs at the local, regional, and national level is, whether groundwater monitoring can be effectively used as a landowner compliance tool, as is currently done at point-source sites. We compare the efficiency of such traditional site-specific compliance networks in nonpoint source regulation with various designs of regional nonpoint source monitoring networks that could be used for compliance monitoring. We discuss advantages and disadvantages of the site vs. regional monitoring approaches with respect to effectively protecting groundwater resources impacted by nonpoint sources: Site-networks provide a tool to enforce compliance by an individual landowner. But the nonpoint source character of the contamination and its typically large spatial extend requires extensive networks at an individual site to accurately and fairly monitor individual compliance. In contrast, regional networks seemingly fail to hold individual landowners accountable. But regional networks can effectively monitor large-scale impacts and water quality trends; and thus inform regulatory programs that enforce management practices tied to nonpoint source pollution. Regional monitoring networks for compliance purposes can face significant challenges in the implementation due to a regulatory and legal landscape that is exclusively structured to address point sources and individual liability, and due to the non-intensive nature of a regional monitoring program (lack of control of hot spots; lack of accountability of individual landowners).

Comparison of land use regression models for NO2 based on routine and campaign monitoring data from an urban area of Japan.

PubMed

Kashima, Saori; Yorifuji, Takashi; Sawada, Norie; Nakaya, Tomoki; Eboshida, Akira

2018-08-01

Typically, land use regression (LUR) models have been developed using campaign monitoring data rather than routine monitoring data. However, the latter have advantages such as low cost and long-term coverage. Based on the idea that LUR models representing regional differences in air pollution and regional road structures are optimal, the objective of this study was to evaluate the validity of LUR models for nitrogen dioxide (NO 2 ) based on routine and campaign monitoring data obtained from an urban area. We selected the city of Suita in Osaka (Japan). We built a model based on routine monitoring data obtained from all sites (routine-LUR-All), and a model based on campaign monitoring data (campaign-LUR) within the city. Models based on routine monitoring data obtained from background sites (routine-LUR-BS) and based on data obtained from roadside sites (routine-LUR-RS) were also built. The routine LUR models were based on monitoring networks across two prefectures (i.e., Osaka and Hyogo prefectures). We calculated the predictability of the each model. We then compared the predicted NO 2 concentrations from each model with measured annual average NO 2 concentrations from evaluation sites. The routine-LUR-All and routine-LUR-BS models both predicted NO 2 concentrations well: adjusted R 2 =0.68 and 0.76, respectively, and root mean square error=3.4 and 2.1ppb, respectively. The predictions from the routine-LUR-All model were highly correlated with the measured NO 2 concentrations at evaluation sites. Although the predicted NO 2 concentrations from each model were correlated, the LUR models based on routine networks, and particularly those based on all monitoring sites, provided better visual representations of the local road conditions in the city. The present study demonstrated that LUR models based on routine data could estimate local traffic-related air pollution in an urban area. The importance and usefulness of data from routine monitoring networks should be acknowledged. Copyright © 2018 Elsevier B.V. All rights reserved.

Airborne trace element pollution in 11 European cities assessed by exposure of standardised ryegrass cultures

NASA Astrophysics Data System (ADS)

Klumpp, Andreas; Ansel, Wolfgang; Klumpp, Gabriele; Breuer, Jörn; Vergne, Philippe; Sanz, María José; Rasmussen, Stine; Ro-Poulsen, Helge; Ribas Artola, Àngela; Peñuelas, Josep; He, Shang; Garrec, Jean Pierre; Calatayud, Vicent

Within a European biomonitoring programme, Italian ryegrass ( Lolium multiflorum Lam.) was employed as accumulative bioindicator of airborne trace elements (As, Cd, Cr, Cu, Fe, Ni, Pb, Sb, V, Zn) in urban agglomerations. Applying a highly standardised method, grass cultures were exposed for consecutive periods of four weeks each to ambient air at up to 100 sites in 11 cities during 2000-2002. Results of the 2001 exposure experiments revealed a clear differentiation of trace element pollution within and among local monitoring networks. Pollution was influenced particularly by traffic emissions. Especially Sb, Pb, Cr, Fe, and Cu exhibited a very uneven distribution within the municipal areas with strong accumulation in plants from traffic-exposed sites in the city centres and close to major roads, and moderate to low levels in plants exposed at suburban or rural sites. Accumulation of Ni and V was influenced by other emission sources. The biomonitoring sites located in Spanish city centres featured a much higher pollution load by trace elements than those in other cities of the network, confirming previously reported findings obtained by chemical analyses of dust deposition and aerosols. At some heavily-trafficked sites, legal thresholds for Cu, Pb, and V contents in foodstuff and animal feed were reached or even surpassed. The study confirmed that the standardised grass exposure is a useful and reliable tool to monitor and to assess environmental levels of potentially toxic compounds of particulate matter.

Linking Atmospheric Pollution to Cryospheric Changes over the Third Pole

NASA Astrophysics Data System (ADS)

Kang, S.; Zhang, Q.; Ji, Z.; Li, Y.; Chen, J.; Zhang, G.; Li, C.; Cong, Z.; Chen, P.; Guo, J.; Huang, J.; Tripathee, L.; Rupakheti, D.; Li, X.; Zhang, Y.; Panday, A. K.; Rupakheti, M.

2016-12-01

Known as "the Third Pole" (TP), the Tibetan Plateau and surrounding mountains hold the largest aggregate of glaciers outside the pole regions. Recent monitoring and projection indicated an accelerated glacier decline and increasing glacier runoff. The long-range transport of South Asian atmospheric pollutants, including light absorbing impurities (LAIs) such as black carbon (BC) and mineral dust (MD), can absorb the solar radiation in the atmosphere and reduce albedo after being deposited onto the cryosphere, thereby promoting glacier and snow melt. A coordinated atmospheric pollution monitoring network has been launched covering the TP with emphasis on trans-Himalayan transects since 2013. TSP were collected for 24h at an interval of 3-6 days. BC/OC, polycyclic aromatic hydrocarbons (PAHs) and heavy metals were measured. Results reveal a consistent decrease in almost all analyzed parameters from south to north across the Himalayas. Geochemical signatures of carbonaceous aerosols indicate dominant sources of biomass burning and vehicle exhaust, in line with results of PAHs. Integrated analysis of satellite images and air mass trajectories suggest that the trans-boundary air pollution occurred episodically and concentrated in pre-monsoon seasons via upper air circulation, through-valley wind, and local convection. Simulation results showed that carbonaceous aerosols produced positive/negative shortwave radiative forcing in the atmosphere/ground surface. Aerosols increased surface air temperatures by 0.1-0.5° over the TP and decreased temperatures in South Asia during the monsoon season. Surface snow/ice samples were collected from benchmark glaciers to estimate the impacts of LAIs on glacier melt with model assistance. BC (37%) and MD (32%) contribute to the summer melting of Laohugou Glacier in the northern TP. MD (38%) contributed more glacier melt than BC (11%) on Zhadang Glacier in the southern TP. In the southeastern TP, BC and MD contribute to 30% of the total glacier melt, up to 350 mm w.e. yr-1. The monitoring network and ongoing studies point to trans-boundary pollution as an increasing stressor for the TP environment, and highlighted the link between atmospheric pollution and cryospheric changes as well as other surface ecosystems over high mountain regions.

Delay/Disruption Tolerant Network-Based Message Forwarding for a River Pollution Monitoring Wireless Sensor Network Application

PubMed Central

Velásquez-Villada, Carlos; Donoso, Yezid

2016-01-01

Communications from remote areas that may be of interest is still a problem. Many innovative projects applied to remote sites face communications difficulties. The GOLDFISH project was an EU-funded project for river pollution monitoring in developing countries. It had several sensor clusters, with floating WiFi antennas, deployed along a downstream river’s course. Sensor clusters sent messages to a Gateway installed on the riverbank. This gateway sent the messages, through a backhaul technology, to an Internet server where data was aggregated over a map. The communication challenge in this scenario was produced by the antennas’ movement and network backhaul availability. Since the antennas were floating on the river, communications could be disrupted at any time. Also, 2G/3G availability near the river was not constant. For non-real-time applications, we propose a Delay/Disruption Tolerant Network (DTN)-based solution where all nodes have persistent storage capabilities and DTN protocols to be able to wait minutes or hours to transmit. A mechanical backhaul will periodically visit the river bank where the gateway is installed and it will automatically collect sensor data to be carried to an Internet-covered spot. The proposed forwarding protocol delivers around 98% of the messages for this scenario, performing better than other well-known DTN routing protocols. PMID:27023554

Summer-time distribution of air pollutants in Sequoia National Park, California.

PubMed

Bytnerowicz, Andrzej; Tausz, Michael; Alonso, Rocio; Jones, David; Johnson, Ronald; Grulke, Nancy

2002-01-01

Concentrations of air pollutants were monitored during the May November 1999 period on a network of forested sites in Sequoia National Park, California. Measurements were conducted with: (1) active monitors for nitric oxide (NO), nitrogen dioxide (NO2) and ozone (O3); (2) honeycomb denuder/filter pack systems for nitric acid vapor (HNO3), nitrous acid vapor (HNO2), ammonia (NH3), sulfur dioxide (SO2), particulate nitrate (NO3-), ammonium (NH4+), and sulfate (SO4(2-)); and (3) passive samplers for O3, HNO3 and NO2. Elevated concentrations of O3 (seasonal means 41-71 ppb), HNO3 (seasonal means 0.4-2.9 microg/m3), NH3 (seasonal means 1.6-4.5 microg/m3), NO3 (1.1-2.0 microg/m3) and NH4+ (1.0-1.9 microg/m3) were determined. Concentrations of other pollutants were low. With increasing elevation and distance from the pollution source area of O3, NH3 and HNO3 concentrations decreased. Ammonia and NH4+ were dominant N pollutants indicating strong influence of agricultural emissions on forests and other ecosystems of the Sequoia National Park.

One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system

NASA Astrophysics Data System (ADS)

Hu, Jianlin; Chen, Jianjun; Ying, Qi; Zhang, Hongliang

2016-08-01

China has been experiencing severe air pollution in recent decades. Although an ambient air quality monitoring network for criteria pollutants has been constructed in over 100 cities since 2013 in China, the temporal and spatial characteristics of some important pollutants, such as particulate matter (PM) components, remain unknown, limiting further studies investigating potential air pollution control strategies to improve air quality and associating human health outcomes with air pollution exposure. In this study, a yearlong (2013) air quality simulation using the Weather Research and Forecasting (WRF) model and the Community Multi-scale Air Quality (CMAQ) model was conducted to provide detailed temporal and spatial information of ozone (O3), total PM2.5, and chemical components. Multi-resolution Emission Inventory for China (MEIC) was used for anthropogenic emissions and observation data obtained from the national air quality monitoring network were collected to validate model performance. The model successfully reproduces the O3 and PM2.5 concentrations at most cities for most months, with model performance statistics meeting the performance criteria. However, overprediction of O3 generally occurs at low concentration range while underprediction of PM2.5 happens at low concentration range in summer. Spatially, the model has better performance in southern China than in northern China, central China, and Sichuan Basin. Strong seasonal variations of PM2.5 exist and wind speed and direction play important roles in high PM2.5 events. Secondary components have more boarder distribution than primary components. Sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and primary organic aerosol (POA) are the most important PM2.5 components. All components have the highest concentrations in winter except secondary organic aerosol (SOA). This study proves the ability of the CMAQ model to reproduce severe air pollution in China, identifies the directions where improvements are needed, and provides information for human exposure to multiple pollutants for assessing health effects.

A Modular Plug-And-Play Sensor System for Urban Air Pollution Monitoring: Design, Implementation and Evaluation.

PubMed

Yi, Wei-Ying; Leung, Kwong-Sak; Leung, Yee

2017-12-22

Urban air pollution has caused public concern globally because it seriously affects human life. Modern monitoring systems providing pollution information with high spatio-temporal resolution have been developed to identify personal exposures. However, these systems' hardware specifications and configurations are usually fixed according to the applications. They can be inconvenient to maintain, and difficult to reconfigure and expand with respect to sensing capabilities. This paper aims at tackling these issues by adopting the proposed Modular Sensor System (MSS) architecture and Universal Sensor Interface (USI), and modular design in a sensor node. A compact MSS sensor node is implemented and evaluated. It has expandable sensor modules with plug-and-play feature and supports multiple Wireless Sensor Networks (WSNs). Evaluation results show that MSS sensor nodes can easily fit in different scenarios, adapt to reconfigurations dynamically, and detect low concentration air pollution with high energy efficiency and good data accuracy. We anticipate that the efforts on system maintenance, adaptation, and evolution can be significantly reduced when deploying the system in the field.

A Modular Plug-And-Play Sensor System for Urban Air Pollution Monitoring: Design, Implementation and Evaluation

PubMed Central

2017-01-01

Urban air pollution has caused public concern globally because it seriously affects human life. Modern monitoring systems providing pollution information with high spatio-temporal resolution have been developed to identify personal exposures. However, these systems’ hardware specifications and configurations are usually fixed according to the applications. They can be inconvenient to maintain, and difficult to reconfigure and expand with respect to sensing capabilities. This paper aims at tackling these issues by adopting the proposed Modular Sensor System (MSS) architecture and Universal Sensor Interface (USI), and modular design in a sensor node. A compact MSS sensor node is implemented and evaluated. It has expandable sensor modules with plug-and-play feature and supports multiple Wireless Sensor Networks (WSNs). Evaluation results show that MSS sensor nodes can easily fit in different scenarios, adapt to reconfigurations dynamically, and detect low concentration air pollution with high energy efficiency and good data accuracy. We anticipate that the efforts on system maintenance, adaptation, and evolution can be significantly reduced when deploying the system in the field. PMID:29271952

Quality control and gap-filling of PM10 daily mean concentrations with the best linear unbiased estimator.

PubMed

Sozzi, R; Bolignano, A; Ceradini, S; Morelli, M; Petenko, I; Argentini, S

2017-10-15

According to the European Directive 2008/50/CE, the air quality assessment consists in the measurement of the concentration fields, and the evaluation of the mean, number of exceedances, etc. of some chemical species dangerous to human health. The measurements provided by an air quality ground-based monitoring network are the main information source but the availability of these data is often limited by several technical and operational problems. In this paper, the best linear unbiased estimator (BLUE) is proposed to validate the pollutant concentration values and to fill the gaps in the measurement of time series collected by a monitoring network. The BLUE algorithm is tested using the daily mean concentrations of particulate matter having aerodynamic diameter less than 10 μ (PM 10 concentrations) measured by the air quality monitoring sensors operating in the Lazio Region in Italy. The comparison between the estimated and measured data evidences an error comparable with the measurement uncertainty. Due to its simplicity and reliability, the BLUE will be used in the routine quality test procedures of the Lazio air quality monitoring network measurements.

Monitoring groundwater: optimising networks to take account of cost effectiveness, legal requirements and enforcement realities

NASA Astrophysics Data System (ADS)

Allan, A.; Spray, C.

2013-12-01

The quality of monitoring networks and modeling in environmental regulation is increasingly important. This is particularly true with respect to groundwater management, where data may be limited, physical processes poorly understood and timescales very long. The powers of regulators may be fatally undermined by poor or non-existent networks, primarily through mismatches between the legal standards that networks must meet, actual capacity and the evidentiary standards of courts. For example, in the second and third implementation reports on the Water Framework Directive, the European Commission drew attention to gaps in the standards of mandatory monitoring networks, where the standard did not meet the reality. In that context, groundwater monitoring networks should provide a reliable picture of groundwater levels and a ';coherent and comprehensive' overview of chemical status so that anthropogenically influenced long-term upward trends in pollutant levels can be tracked. Confidence in this overview should be such that 'the uncertainty from the monitoring process should not add significantly to the uncertainty of controlling the risk', with densities being sufficient to allow assessment of the impact of abstractions and discharges on levels in groundwater bodies at risk. The fact that the legal requirements for the quality of monitoring networks are set out in very vague terms highlights the many variables that can influence the design of monitoring networks. However, the quality of a monitoring network as part of the armory of environmental regulators is potentially of crucial importance. If, as part of enforcement proceedings, a regulator takes an offender to court and relies on conclusions derived from monitoring networks, a defendant may be entitled to question those conclusions. If the credibility, reliability or relevance of a monitoring network can be undermined, because it is too sparse, for example, this could have dramatic consequences on the ability of a regulator to ensure compliance with legal standards. On the other hand, it can be ruinously expensive to set up a monitoring network in remote areas and regulators must therefore balance the cost effectiveness of these networks against the chance that a court might question their fitness for purpose. This presentation will examine how regulators can balance legal standards for monitoring against the cost of developing and maintaining the requisite networks, while still producing observable improvements in water and ecosystem quality backed by legally enforceable sanctions for breaches. Reflecting the findings from the EU-funded GENESIS project, it will look at case law from around the world to assess how tribunals balance competing models, and the extent to which decisions may be revisited in the light of new scientific understanding. Finally, it will make recommendations to assist regulators in optimising their network designs for enforcement.

INSTRUMENTATION, RECORDING, AND PROCESSING OF METEOROLOGICAL DATA NEAR PORTAGE, WISCONSIN: WISCONSIN POWER PLANT IMPACT STUDY

EPA Science Inventory

As part of the Columbia Power Plant Impact Study meteorological data were collected at a network of monitoring sites from 1972 through 1977. The data were the basis for a series of studies whose purpose was to elucidate the transport of airborne pollutants and to assess the clima...

SEASONAL AND REGIONAL AIR QUALITY AND ATMOSPHERIC DEPOSITION IN THE EASTERN US

EPA Science Inventory

Dry concentration and dry and wet deposition of selected air pollutants monitored over two 5-year periods in the 1990s at or near 34 rural Clean Air Status and Trends Network (CASTNET) sites located in the eastern US are adjusted for known biases, composed into seasonal values, a...

VOC Monitoring to Understand Changes in Secondary Pollution in Mexico City

NASA Astrophysics Data System (ADS)

Velasco, E.; Jaimes-Palomera, M.; Retama, A.; Neria, A.; Rivera, O.; Elias, G.

2015-12-01

Previous studies have documented the distribution, diurnal pattern, magnitude, and reactivity of the volatile organic compounds (VOCs) within and downwind of Mexico City. These studies have provided valuable data, but their duration has been restricted to a few weeks since the majority have been part of intensive field campaigns. With the aim of addressing the VOC pollution problem during longer monitoring periods and evaluating control measures to reduce the production of ozone and secondary aerosols, the environmental authorities of Mexico City through its Air Quality Monitoring Network have developed a program to monitor over 50 VOC species every hour in selected existing air quality monitoring stations inside and outside the urban sprawl. The program started with a testing period of six months in 2012 covering the ozone-season (Mar-May). Results of this first campaign are presented in this paper. Using as reference VOC data collected in 2003, reductions in the mixing ratios of light alkanes associated with the consumption of liquefied petroleum gas and aromatic compounds related with the evaporation of fossil fuels and solvents were observed. In contrast, a clear increase in the mixing ratio of olefins was observed. This increase is of relevance to understand the moderate success in the reduction of ozone and fine aerosols in recent years in comparison to other criteria pollutants, which have substantially decreased. Particular features of the diurnal profiles, reactivity with the hydroxyl radical and correlations between individual VOCs and carbon monoxide are used to investigate the influence of specific emission sources. The results discussed here expect to highlight the importance of monitoring VOCs to better understand the drivers and impacts of secondary pollution in large cities like Mexico City.

Monitoring of persistent organic pollutants in Africa. Part 2: design of a network to monitor the continental and intercontinental background.

PubMed

Lammel, G; Dobrovolný, P; Dvorská, A; Chromá, K; Brázdil, R; Holoubek, I; Hosek, J

2009-11-01

A network for the study of long-term trends of the continental background in Africa and the intercontinental background of persistent organic pollutants as resulting from long-range transport of contaminants from European, South Asian, and other potential source regions, as well as by watching supposedly pristine regions, i.e. the Southern Ocean and Antarctica is designed. The results of a pilot phase sampling programme in 2008 and meteorological and climatological information from the period 1961-2007 was used to apply objective criteria for the selection of stations for the monitoring network: out the original 26 stations six have been rejected because of suggested strong local sources of POPs and three others because of local meteorological effects, which may prevent part of the time long-range transported air to reach the sampling site. Representativeness of the meteorological patterns during the pilot phase with respect to climatology was assessed by comparison of the more local airflow situation as given by climatological vs. observed wind roses and by comparison of backward trajectories with the climatological wind (NCEP/NCAR re-analyses). With minor exceptions advection to nine inspected stations was typical for present-day climate during the pilot phase, 2008. Six to nine stations would cover satisfyingly large and densely populated regions of North-eastern, West and East Africa and its neighbouring seas, the Mediterranean, Northern and Equatorial Atlantic Ocean, the Western Indian Ocean and the Southern Ocean. Among the more densely populated areas Southern Cameroon, parts of the Abessinian plateau and most of the Great Lakes area would not be covered. The potential of the network is not hampered by on-going long-term changes of the advection to the selected stations, as these do hardly affect the coverage of target areas.

Effects of environmental alerts and pre-emergencies on pollutant concentrations in Santiago, Chile

NASA Astrophysics Data System (ADS)

Troncoso, Rodrigo; de Grange, Louis; Cifuentes, Luis A.

2012-12-01

To reduce air pollution levels in Santiago, Chile on days when the weather is expected to create poor ventilation conditions and increased air pollutant concentrations, the responsible authorities impose temporary restrictions on motor vehicles and certain industrial activities. We estimate the impact of these restrictions on the city's air quality using data collected by a network of monitoring stations. The estimates show that the restrictions do reduce the average concentrations of coarse and fine particulate matter, carbon monoxide and nitrogen oxide (both gases are emitted mainly by vehicles). However, no significant changes were found in the sulfur dioxide concentrations, which are primarily the result of industrial processes.

Comparison of Satellite Observations of Aerosol Optical Depth to Surface Monitor Fine Particle Concentration

NASA Technical Reports Server (NTRS)

Kleb, Mary M.; AlSaadi, Jassim A.; Neil, Doreen O.; Pierce, Robert B.; Pippin, Margartet R.; Roell, Marilee M.; Kittaka, Chieko; Szykman, James J.

2004-01-01

Under NASA's Earth Science Applications Program, the Infusing satellite Data into Environmental Applications (IDEA) project examined the relationship between satellite observations and surface monitors of air pollutants to facilitate a more capable and integrated observing network. This report provides a comparison of satellite aerosol optical depth to surface monitor fine particle concentration observations for the month of September 2003 at more than 300 individual locations in the continental US. During September 2003, IDEA provided prototype, near real-time data-fusion products to the Environmental Protection Agency (EPA) directed toward improving the accuracy of EPA s next-day Air Quality Index (AQI) forecasts. Researchers from NASA Langley Research Center and EPA used data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument combined with EPA ground network data to create a NASA-data-enhanced Forecast Tool. Air quality forecasters used this tool to prepare their forecasts of particle pollution, or particulate matter less than 2.5 microns in diameter (PM2.5), for the next-day AQI. The archived data provide a rich resource for further studies and analysis. The IDEA project uses data sets and models developed for tropospheric chemistry research to assist federal, state, and local agencies in making decisions concerning air quality management to protect public health.

A New Black Carbon Sensor for Dense Air Quality Monitoring Networks

PubMed Central

Caubel, Julien J.; Cados, Troy E.; Kirchstetter, Thomas W.

2018-01-01

Low-cost air pollution sensors are emerging and increasingly being deployed in densely distributed wireless networks that provide more spatial resolution than is typical in traditional monitoring of ambient air quality. However, a low-cost option to measure black carbon (BC)—a major component of particulate matter pollution associated with adverse human health risks—is missing. This paper presents a new BC sensor designed to fill this gap, the Aerosol Black Carbon Detector (ABCD), which incorporates a compact weatherproof enclosure, solar-powered rechargeable battery, and cellular communication to enable long-term, remote operation. This paper also demonstrates a data processing methodology that reduces the ABCD’s sensitivity to ambient temperature fluctuations, and therefore improves measurement performance in unconditioned operating environments (e.g., outdoors). A fleet of over 100 ABCDs was operated outdoors in collocation with a commercial BC instrument (Magee Scientific, Model AE33) housed inside a regulatory air quality monitoring station. The measurement performance of the 105 ABCDs is comparable to the AE33. The fleet-average precision and accuracy, expressed in terms of mean absolute percentage error, are 9.2 ± 0.8% (relative to the fleet average data) and 24.6 ± 0.9% (relative to the AE33 data), respectively (fleet-average ± 90% confidence interval). PMID:29494528

A New Black Carbon Sensor for Dense Air Quality Monitoring Networks.

PubMed

Caubel, Julien J; Cados, Troy E; Kirchstetter, Thomas W

2018-03-01

Low-cost air pollution sensors are emerging and increasingly being deployed in densely distributed wireless networks that provide more spatial resolution than is typical in traditional monitoring of ambient air quality. However, a low-cost option to measure black carbon (BC)-a major component of particulate matter pollution associated with adverse human health risks-is missing. This paper presents a new BC sensor designed to fill this gap, the Aerosol Black Carbon Detector (ABCD), which incorporates a compact weatherproof enclosure, solar-powered rechargeable battery, and cellular communication to enable long-term, remote operation. This paper also demonstrates a data processing methodology that reduces the ABCD's sensitivity to ambient temperature fluctuations, and therefore improves measurement performance in unconditioned operating environments (e.g., outdoors). A fleet of over 100 ABCDs was operated outdoors in collocation with a commercial BC instrument (Magee Scientific, Model AE33) housed inside a regulatory air quality monitoring station. The measurement performance of the 105 ABCDs is comparable to the AE33. The fleet-average precision and accuracy, expressed in terms of mean absolute percentage error, are 9.2 ± 0.8% (relative to the fleet average data) and 24.6 ± 0.9% (relative to the AE33 data), respectively (fleet-average ± 90% confidence interval).

Urban-scale mapping of PM2.5 distribution via data fusion between high-density sensor network and MODIS Aerosol Optical Depth

NASA Astrophysics Data System (ADS)

Ba, Yu Tao; xian Liu, Bao; Sun, Feng; Wang, Li hua; Tang, Yu jia; Zhang, Da wei

2017-04-01

High-resolution mapping of PM2.5 is the prerequisite for precise analytics and subsequent anti-pollution interventions. Considering the large variances of particulate distribution, urban-scale mapping is challenging either with ground-based fixed stations, with satellites or via models. In this study, a dynamic fusion method between high-density sensor network and MODIS Aerosol Optical Depth (AOD) was introduced. The sensor network was deployed in Beijing ( > 1000 fixed monitors across 16000 km2 area) to provide raw observations with high temporal resolution (sampling interval < 1 hour), high spatial resolution in flat areas ( < 1 km), and low spatial resolution in mountainous areas ( > 5 km). The MODIS AOD was calibrated to provide distribution map with low temporal resolution (daily) and moderate spatial resolution ( = 3 km). By encoding the data quality and defects (e.g. could, reflectance, abnormal), a hybrid interpolation procedure with cross-validation generated PM2.5 distribution with both high temporal and spatial resolution. Several no-pollutant and high-pollution periods were tested to validate the proposed fusion method for capturing the instantaneous patterns of PM2.5 emission.

Spatial variations of particulate matter and air toxics in communities adjacent to the Port of Oakland.

PubMed

Fujita, Eric M; Campbell, David E; Arnott, W Patrick; Lau, Virginia; Martien, Philip T

2013-12-01

The Bay Area Air Quality Management District (BAAQMD) sponsored the West Oakland Monitoring Study (WOMS) to provide supplemental air quality monitoring that will be used by the BAAQMD to evaluate local-scale dispersion modeling of diesel emissions and other toxic air contaminants for the area within and around the Port of Oakland. The WOMS was conducted during two seasonal periods of 4 weeks in summer 2009 and winter 2009/2010. Monitoring data showed spatial patterns of pollutant concentrations that were generally consistent with proximity to vehicle traffic. Concentrations of directly emitted pollutants were highest on heavily traveled roads with consistently lower concentrations away from the roadways. Pollutants that have higher emission rates from diesel trucks (nitric oxide, black carbon) tended to exhibit sharper gradients than pollutants that are largely associated with gasoline vehicles, such as carbon monoxide and volatile organic compounds, including benzene, toluene, ethylbenzene, and xylenes (BTEX). BTEX concentrations in West Oakland were similar to those measured at the three air toxics monitoring network sites in the Bay Area (San Francisco, Fremont, and San Jose). Aldehyde levels were higher in Fremont and San Jose than in West Oakland, reflecting greater contributions from photo-oxidation of hydrocarbons downwind of the Bay Area. A 2005 modeling-based health risk assessment of diesel particulate matter concentrations is consistent with aerosol carbon concentrations measured during the WOMS after adjusting for recent mitigation measures and improved estimates of heavy-duty truck traffic volumes.

LaSVM-based big data learning system for dynamic prediction of air pollution in Tehran.

PubMed

Ghaemi, Z; Alimohammadi, A; Farnaghi, M

2018-04-20

Due to critical impacts of air pollution, prediction and monitoring of air quality in urban areas are important tasks. However, because of the dynamic nature and high spatio-temporal variability, prediction of the air pollutant concentrations is a complex spatio-temporal problem. Distribution of pollutant concentration is influenced by various factors such as the historical pollution data and weather conditions. Conventional methods such as the support vector machine (SVM) or artificial neural networks (ANN) show some deficiencies when huge amount of streaming data have to be analyzed for urban air pollution prediction. In order to overcome the limitations of the conventional methods and improve the performance of urban air pollution prediction in Tehran, a spatio-temporal system is designed using a LaSVM-based online algorithm. Pollutant concentration and meteorological data along with geographical parameters are continually fed to the developed online forecasting system. Performance of the system is evaluated by comparing the prediction results of the Air Quality Index (AQI) with those of a traditional SVM algorithm. Results show an outstanding increase of speed by the online algorithm while preserving the accuracy of the SVM classifier. Comparison of the hourly predictions for next coming 24 h, with those of the measured pollution data in Tehran pollution monitoring stations shows an overall accuracy of 0.71, root mean square error of 0.54 and coefficient of determination of 0.81. These results are indicators of the practical usefulness of the online algorithm for real-time spatial and temporal prediction of the urban air quality.

Results of Geoenvironmental Studies (2013-2014) Applied to a Monitoring Water Quality Network in Real Time in the Atoyac River (upstream) Puebla, Mexico.

NASA Astrophysics Data System (ADS)

Rodriguez-Espinosa, P. F.; Tavera, E. M.; Morales-Garcia, S. S.; Muñoz-Sevilla, N. P.

2014-12-01

Results of geoenvironment studies, referents to geochemistry, weathering, size, mineral composition, and metals contained in sediments and physicochemical parameters of water in urban rivers associated with dam are presented. Emphasis on the interpretation of these results, was detect environmental susceptibility areas associated at the water quality in Upper basin of Atoyac River, Puebla, Mexico. The environmental sub secretary of the state government of Puebla, Mexico has initiated actions to clean up the urban Atoyac River, with measurements of physicochemical parameters associated of the water quality in real-time monitoring and sampling network along the river. The results identified an important role in the rivers, not only to receive and transport the contaminants associated with sedimentological and geochemical conditions, but magnified the effects of pollutant discharges. A significant concentration of hazardous metals in sediments of the dam, reflecting the geo-environmental conditions of anthropogenic Valsequillo Dam induction was determined. For example, a moderately contaminated Pb contaminated extreme class, and Cu and Zn contaminated with moderate to heavy contaminated under geoenvironment class index. Large concentration of clay minerals with larger surface areas was found there in the study, the minerals are definitely the fittest in nature to accept on their surfaces constitution of metals, metalloids and other contaminants which were reflected in the Geoenvironmental index. The results of the studies performed here enable us to locate monitoring stations and sampling network to physicochemical parameters in real time, in the areas of higher contamination found in geoenvironmental studies Atoyac High River Basin. Similarly, we can elucidate the origin of pollutants and monitoring agents reflected in BOD5 (223 mg / l) and COD (610 mg / l), suspended solids totals (136 mg / l) and dissolved solids totals (840 mg / l), in others. Recent hydrometric data associated with the concentration of pollutants, allow us to report COD transportation charges up to 1690 ton/day and 616 ton/day of BOD5. Where clearly detect the contributions of domestic sewage, industrial and agricultural in non-meteoric water.

Development of a Wireless Sensor Network for Individual Monitoring of Panels in a Photovoltaic Plant

PubMed Central

Prieto, Miguel J.; Pernía, Alberto M.; Nuño, Fernando; Díaz, Juan; Villegas, Pedro J.

2014-01-01

With photovoltaic (PV) systems proliferating in the last few years due to the high prices of fossil fuels and pollution issues, among others, it is extremely important to monitor the efficiency of these plants and optimize the energy production process. This will also result in improvements related to the maintenance and security of the installation. In order to do so, the main parameters in the plant must be continuously monitored so that the appropriate actions can be carried out. This monitoring should not only be carried out at a global level, but also at panel-level, so that a better understanding of what is actually happening in the PV plant can be obtained. This paper presents a system based on a wireless sensor network (WSN) that includes all the components required for such monitoring as well as a power supply obtaining the energy required by the sensors from the photovoltaic panels. The system proposed succeeds in identifying all the nodes in the network and provides real-time monitoring while tracking efficiency, features, failures and weaknesses from a single cell up to the whole infrastructure. Thus, the decision-making process is simplified, which contributes to reducing failures, wastes and, consequently, costs. PMID:24487622

A new scheme for biomonitoring heavy metal concentrations in semi-natural wetlands.

PubMed

Batzias, A F; Siontorou, C G

2008-10-30

This work introduces a semi-natural wetland biomonitoring framework for heavy metal concentrations based on a robust dynamic integration between biological assemblages and relevant biosensors. The cooperative/synergistic scheme developed minimizes uncertainty and monitoring costs and increases reliability of pollution control and abatement. Attention is given to establishing a fully functioning and reliable network approach for monitoring inflows and achieving dose-response relations and calibration of biomonitoring species. The biomonitoring network initially consists of both, biosensors and species, as a validation phase in each wetland of the surveillance area; once the species monitoring efficiency is verified by the biosensors, the biosensor network moves to the next wetland and so on, following a circular pattern until all area wetlands have a fully functional natural monitoring scheme. By means of species recalibration with periodic revisiting of the biosensors, the scheme progressively reaches a quasi steady-state (including seasonality), thus ensuring reliability and robustness. This framework, currently pilot-tested in Voiotia, Greece, for assessing chromium levels, has been built to cover short-, medium- and long-term monitoring requirements. The results gathered so far, support the employment of the proposed scheme in heavy metal monitoring, and, further, arise the need for volunteer involvement to achieve long-term viability.

Establishing of monitoring network on Kosovo Rivers: preliminary measurements on the four main rivers (Drini i Bardhë, Morava e Binqës, Lepenc and Sitnica).

PubMed

Gashi, Fatbardh; Frančišković-Bilinski, Stanislav; Bilinski, Halka; Troni, Naser; Bacaj, Mustafë; Jusufi, Florim

2011-04-01

The main goal of this work was to suggest to authorities concerned a monitoring network on main rivers of Kosovo. We aim to suggest application of WFD (Water Framework Directive) in Kosovo as soon as possible. Our present chemical research could be the first step towards it, giving an opportunity to plan the monitoring network in which pollution locations will be highlighted. In addition to chemical, future ecological studies could be performed. Waters of the rivers Drini i Bardhë, Morava e Binçës, Lepenc and Sitnica, which are of supra-regional interest, are investigated systematically along the river course. Sediments of these rivers were also investigated at the same monitoring points and results have recently been published by us. In this paper we present results of mass concentrations of eco-toxic metals: Cu(II), Pb(II), Cd(II), Zn(II) and Mn(II) in waters of four main rivers of Kosovo, using Anodic Stripping Voltammetry (ASV), Atomic Absorption Spectrophotometry (AAS) and Ultraviolet-Visible (UV-VIS) Spectrometry. Also some physico-chemical parameters are determined: water temperature, electrical conductivity, pH, alkalinity, total hardness and temporary hardness. Results of concentrations of eco-toxic metals in water are compared with concentrations found in sediments at the same locations. Statistical methods are applied to determine anomalous regions Classification of waters at each sampling station of our work was tentatively performed based on metal indicators, using Croatian standards. Our results are showing that concentrations of Zn in all waters are low and pose no risk for living organisms. Exception is water at S5 station, where concentration is above permanent toxic level. Concentrations of Pb and Mn are high at D5 station on Drini i Bardhë River (14 km from boarder to Albania) and at all stations along Sitnica River. Cadmium in high concentrations which is above permanent toxic level is measured in water only at two stations, one (M1) on Morava e Binçës River and the other (S5) on Sitnica River (56 km from boarder to Serbia). Comparison with available results from the past shows that water pollution with respect to toxic elements decreased since 1989, what is explained with closing of heavy industry since then. Continuation of water and sediment monitoring using more than one experimental technique is highly recommended, particularly at locations S2 and S5 with anomalous concentrations of toxic elements, as well as establishing of permanent network of monitoring stations by Kosovo authorities. Remediation of sediments at polluted locations in Sitnica River would be desirable.

Relationship between meteorological phenomena and air pollution in an urbanized and industrialized coastal area in northern France

NASA Astrophysics Data System (ADS)

Gengembre, Cyril; Zhang, Shouwen; Dieudonné, Elsa; Sokolov, Anton; Augustin, Patrick; Riffault, Véronique; Dusanter, Sébastien; Fourmentin, Marc; Delbarre, Hervé

2016-04-01

Impacts of global climate evolution are quite uncertain at regional and local scales, especially on air pollution. Air quality is associated with local atmospheric dynamics at a time scale shorter than a few weeks, while the climate change time scale is on the order of fifty years. To infer consequences of climate evolution on air pollution, it is necessary to fill the gap between these different scales. Another challenge is to understand the effect of global warming on the frequency of meteorological phenomena that influence air pollution. In this work, we classified meteorological events related to air pollution during a one-year long field campaign in Dunkirk (northern France). Owing to its coastal location under urban and industrial exposures, the Dunkirk agglomeration is an interesting area for studying gaseous and aerosols pollutants and their relationship with weather events such as sea breezes, fogs, storms and fronts. The air quality in the northern region of France is also greatly influenced by highly populated and industrialized cities along the coast of the North Sea, and by London and Paris agglomerations. During a field campaign, we used simultaneously a three-dimensional sonic anemometer and a weather station network, along with a scanning Doppler Lidar system to analyse the vertical structure of the atmosphere. An Aerosol Chemical Speciation Monitor enabled investigating the PM1 behaviour during the studied events. Air contaminants such as NOx (NO and NO2) were also measured by the regional pollution monitoring network ATMO Nord Pas-de-Calais. The events were identified by finding specific criteria from meteorological and turbulent parameters. Over a hundred cases of sea breezes, fog periods, stormy days and atmospheric front passages were investigated. Variations of turbulent parameters (vertical sensible heat flux and momentum flux) give estimations on the transport and the dispersal of pollutants. As the fluxes are weak during fogs, an increase of PM1 concentrations was observed, which causes a deposition of the particles. Due to turbulence and horizontal dilution, PM1 concentrations were weak during storms.

Atmospheric mercury concentrations observed at ground-based monitoring sites globally distributed in the framework of the GMOS network

NASA Astrophysics Data System (ADS)

Sprovieri, Francesca; Pirrone, Nicola; Bencardino, Mariantonia; D'Amore, Francesco; Carbone, Francesco; Cinnirella, Sergio; Mannarino, Valentino; Landis, Matthew; Ebinghaus, Ralf; Weigelt, Andreas; Brunke, Ernst-Günther; Labuschagne, Casper; Martin, Lynwill; Munthe, John; Wängberg, Ingvar; Artaxo, Paulo; Morais, Fernando; Barbosa, Henrique de Melo Jorge; Brito, Joel; Cairns, Warren; Barbante, Carlo; Diéguez, María del Carmen; Garcia, Patricia Elizabeth; Dommergue, Aurélien; Angot, Helene; Magand, Olivier; Skov, Henrik; Horvat, Milena; Kotnik, Jože; Read, Katie Alana; Mendes Neves, Luis; Gawlik, Bernd Manfred; Sena, Fabrizio; Mashyanov, Nikolay; Obolkin, Vladimir; Wip, Dennis; Feng, Xin Bin; Zhang, Hui; Fu, Xuewu; Ramachandran, Ramesh; Cossa, Daniel; Knoery, Joël; Marusczak, Nicolas; Nerentorp, Michelle; Norstrom, Claus

2016-09-01

Long-term monitoring of data of ambient mercury (Hg) on a global scale to assess its emission, transport, atmospheric chemistry, and deposition processes is vital to understanding the impact of Hg pollution on the environment. The Global Mercury Observation System (GMOS) project was funded by the European Commission (http://www.gmos.eu) and started in November 2010 with the overall goal to develop a coordinated global observing system to monitor Hg on a global scale, including a large network of ground-based monitoring stations, ad hoc periodic oceanographic cruises and measurement flights in the lower and upper troposphere as well as in the lower stratosphere. To date, more than 40 ground-based monitoring sites constitute the global network covering many regions where little to no observational data were available before GMOS. This work presents atmospheric Hg concentrations recorded worldwide in the framework of the GMOS project (2010-2015), analyzing Hg measurement results in terms of temporal trends, seasonality and comparability within the network. Major findings highlighted in this paper include a clear gradient of Hg concentrations between the Northern and Southern hemispheres, confirming that the gradient observed is mostly driven by local and regional sources, which can be anthropogenic, natural or a combination of both.

Automobile gross emitter screening with remote sensing data using objective-oriented neural network.

PubMed

Chen, Ho-Wen; Yang, Hsi-Hsien; Wang, Yu-Sheng

2009-11-01

One of the costs of Taiwan's massive economic development has been severe air pollution problems in many parts of the island. Since vehicle emissions are the major source of air pollution in most of Taiwan's urban areas, Taiwan's government has implemented policies to rectify the degrading air quality, especially in areas with high population density. To reduce vehicle pollution emissions an on-road remote sensing and monitoring system is used to check the exhaust emissions from gasoline engine automobiles. By identifying individual vehicles with excessive emissions for follow-up inspection and testing, air quality in the urban environment is expected to improve greatly. Because remote sensing is capable of measuring a large number of moving vehicles in a short period, it has been considered as an assessment technique in place of the stationary emission-sampling techniques. However, inherent measurement uncertainty of remote sensing instrumentation, compounded by the indeterminacy of monitoring site selection, plus the vagaries of weather, causes large errors in pollution discrimination and limits the application of the remote sensing. Many governments are still waiting for a novel data analysis methodology to clamp down on heavily emitting vehicles by using remote sensing data. This paper proposes an artificial neural network (ANN), with vehicle attributes embedded, that can be trained by genetic algorithm (GA) based on different strategies to predict vehicle emission violation. Results show that the accuracy of predicting emission violation is as high as 92%. False determinations tend to occur for vehicles aged 7-13 years, peaking at 10 years of age.

The Use of Remote Sensing Data for Modeling Air Quality in the Cities

NASA Astrophysics Data System (ADS)

Putrenko, V. V.; Pashynska, N. M.

2017-12-01

Monitoring of environmental pollution in the cities by the methods of remote sensing of the Earth is actual area of research for sustainable development. Ukraine has a poorly developed network of monitoring stations for air quality, the technical condition of which is deteriorating in recent years. Therefore, the possibility of obtaining data about the condition of air by remote sensing methods is of great importance. The paper considers the possibility of using the data about condition of atmosphere of the project AERONET to assess the air quality in Ukraine. The main pollution indicators were used data on fine particulate matter (PM2.5) and nitrogen dioxide (NO2) content in the atmosphere. The main indicator of air quality in Ukraine is the air pollution index (API). We have built regression models the relationship between indicators of NO2, which are measured by remote sensing methods and ground-based measurements of indicators. There have also been built regression models, the relationship between the data given to the land of NO2 and API. To simulate the relationship between the API and PM2.5 were used geographically weighted regression model, which allows to take into account the territorial differentiation between these indicators. As a result, the maps that show the distribution of the main types of pollution in the territory of Ukraine, were constructed. PM2.5 data modeling is complicated with using existing indicators, which requires a separate organization observation network for PM2.5 content in the atmosphere for sustainable development in cities of Ukraine.

Coupling of ground biosensor networks for water monitoring with satellite observations in assessing Leptospirosis

NASA Astrophysics Data System (ADS)

Skouloudis, A. N.; Rickerby, D. G.

2012-12-01

Leptospirosis became recently a major public-health problem that is closely related with the environment (Nature review Oct 2009, Vol 7, pp 736-747). This disease originates from zoonotic pathogens associated with asymptomatic rodent carriers. Unfortunately, it effects human populations via various direct and indirect routes. This disease can claim many victims with large outbreaks during natural disasters or floods occurring during seasonal conditions. The severity of the illness ranges from subclinical infection to a fulminating fatal disease. Improved water quality monitoring techniques based on biosensor, optical, micro-fluidic and information technologies are leading to radical changes in our ability to perceive and monitor the aquatic environment. Biosensors are capable of providing specific, high spatial resolution information and allow unattended operation that will be particularly useful for water borne related diseases. Current research on biosensors is leading to solutions to problems for several contaminants that were previously irresolvable due to their high degree of complexity. Networking of the sensors enables sensitive monitoring systems allowing real-time monitoring of pollutants and facilitates data transmission between the measurement points and central control stations for continuous surveillance and to provide an early warning capability. The application of intelligent biosensor networks for water quality monitoring and detection of localized sources of pollution are discussed together with the setting up of a methodology that utilizes images from satellite coupled with in-situ sensors for anticipating the zones of potential evolution of this disease and assessing the population at risk. Environmental and climatic conditions that are associated the outbreaks are described and the rational of combining earth observations coupled with advanced in-situ biosensors is explained. The implementation of sensor networks for data collection and exposure mapping is reliant on the identification of location where such networks could be of use. Systematic monitoring from satellite images are utilized for increasing the potential areas of application, for assessing the geographical representativeness on the measurements of the sensors and proposing the methodology on assessing the environmental conditions that are associated with outbreaks of leptospirosis. Unfortunately, several combined deployments of earth observations with ground sensors are required before for the understanding of the connections between hydrology and the human health. Ultimately this will lead to the establishment of early warning system that might investigate the effectiveness of key control measures, including vaccine (when they will become available) and affront the water decontamination, and animal control issues.

Recent Results From the NOAA/ESRL GMD Tall Tower Network

NASA Astrophysics Data System (ADS)

Andrews, A. E.; Tans, P. P.; Peters, W.; Hirsch, A.; Sweeney, C.; Petron, G.; Kofler, J.; Zhao, C.; Masarie, K.; Wofsy, S. C.; Matross, D. M.; Mahadevan, P.; Longo, M.; Gerbig, C.; Lin, J. C.

2006-12-01

We will present a summary of new results from NOAA Earth System Research Laboratory`s Tall Tower greenhouse gas monitoring network. The tower network is operated by the Global Monitoring Division, which also maintains the global Cooperative Air Sampling network and a network of aircraft profiling sites over North America. Tall tower CO2 mixing ratio measurements are sensitive to upwind fluxes over scales of hundreds of kilometers, and the primary objective of the tower network is to obtain regionally representative carbon flux estimates for the North American continent. Mixing ratios of CO2 and CO are measured semi-continuously at the towers, and the KWKT-TV tower site near Moody, TX has recently also been equipped with sensors to measure radon and O3. Daily flask samples are collected at the KWKT tower and analyzed for CO2, CO, CH4, SF6, N2O, H2, stable isotopes of CO2 and CH4, COS, and a variety of halocarbon and hydrocarbon species. Daily flask sampling will be implemented at all tower sites within the next few years. We have used the Stochastic Time Inverted Lagrangian Transport (STILT) model to investigate upwind influences on the tower observations. CO measurements provide an indicator of polluted air masses, and we will present a summary of the frequency and origin of pollution events observed at the towers. We will present an analysis of the primary factors contributing to observed CO2 variability along with average seasonal and diurnal cycles of CO2 at the tower sites. Tower measurements are being used to evaluate atmospheric transport models in the context of the Transcom Continuous experiment and are an important constraint for CO2 data assimilation systems that produce regional to global carbon flux estimates with up to weekly resolution.

Quantitative design of emergency monitoring network for river chemical spills based on discrete entropy theory.

PubMed

Shi, Bin; Jiang, Jiping; Sivakumar, Bellie; Zheng, Yi; Wang, Peng

2018-05-01

Field monitoring strategy is critical for disaster preparedness and watershed emergency environmental management. However, development of such is also highly challenging. Despite the efforts and progress thus far, no definitive guidelines or solutions are available worldwide for quantitatively designing a monitoring network in response to river chemical spill incidents, except general rules based on administrative divisions or arbitrary interpolation on routine monitoring sections. To address this gap, a novel framework for spatial-temporal network design was proposed in this study. The framework combines contaminant transport modelling with discrete entropy theory and spectral analysis. The water quality model was applied to forecast the spatio-temporal distribution of contaminant after spills and then corresponding information transfer indexes (ITIs) and Fourier approximation periodic functions were estimated as critical measures for setting sampling locations and times. The results indicate that the framework can produce scientific preparedness plans of emergency monitoring based on scenario analysis of spill risks as well as rapid design as soon as the incident happened but not prepared. The framework was applied to a hypothetical spill case based on tracer experiment and a real nitrobenzene spill incident case to demonstrate its suitability and effectiveness. The newly-designed temporal-spatial monitoring network captured major pollution information at relatively low costs. It showed obvious benefits for follow-up early-warning and treatment as well as for aftermath recovery and assessment. The underlying drivers of ITIs as well as the limitations and uncertainty of the approach were analyzed based on the case studies. Comparison with existing monitoring network design approaches, management implications, and generalized applicability were also discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

Joint space-time geostatistical model for air quality surveillance

NASA Astrophysics Data System (ADS)

Russo, A.; Soares, A.; Pereira, M. J.

2009-04-01

Air pollution and peoples' generalized concern about air quality are, nowadays, considered to be a global problem. Although the introduction of rigid air pollution regulations has reduced pollution from industry and power stations, the growing number of cars on the road poses a new pollution problem. Considering the characteristics of the atmospheric circulation and also the residence times of certain pollutants in the atmosphere, a generalized and growing interest on air quality issues led to research intensification and publication of several articles with quite different levels of scientific depth. As most natural phenomena, air quality can be seen as a space-time process, where space-time relationships have usually quite different characteristics and levels of uncertainty. As a result, the simultaneous integration of space and time is not an easy task to perform. This problem is overcome by a variety of methodologies. The use of stochastic models and neural networks to characterize space-time dispersion of air quality is becoming a common practice. The main objective of this work is to produce an air quality model which allows forecasting critical concentration episodes of a certain pollutant by means of a hybrid approach, based on the combined use of neural network models and stochastic simulations. A stochastic simulation of the spatial component with a space-time trend model is proposed to characterize critical situations, taking into account data from the past and a space-time trend from the recent past. To identify near future critical episodes, predicted values from neural networks are used at each monitoring station. In this paper, we describe the design of a hybrid forecasting tool for ambient NO2 concentrations in Lisbon, Portugal.

Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation.

PubMed

Li, Xiang; Peng, Ling; Yao, Xiaojing; Cui, Shaolong; Hu, Yuan; You, Chengzeng; Chi, Tianhe

2017-12-01

Air pollutant concentration forecasting is an effective method of protecting public health by providing an early warning against harmful air pollutants. However, existing methods of air pollutant concentration prediction fail to effectively model long-term dependencies, and most neglect spatial correlations. In this paper, a novel long short-term memory neural network extended (LSTME) model that inherently considers spatiotemporal correlations is proposed for air pollutant concentration prediction. Long short-term memory (LSTM) layers were used to automatically extract inherent useful features from historical air pollutant data, and auxiliary data, including meteorological data and time stamp data, were merged into the proposed model to enhance the performance. Hourly PM 2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm) concentration data collected at 12 air quality monitoring stations in Beijing City from Jan/01/2014 to May/28/2016 were used to validate the effectiveness of the proposed LSTME model. Experiments were performed using the spatiotemporal deep learning (STDL) model, the time delay neural network (TDNN) model, the autoregressive moving average (ARMA) model, the support vector regression (SVR) model, and the traditional LSTM NN model, and a comparison of the results demonstrated that the LSTME model is superior to the other statistics-based models. Additionally, the use of auxiliary data improved model performance. For the one-hour prediction tasks, the proposed model performed well and exhibited a mean absolute percentage error (MAPE) of 11.93%. In addition, we conducted multiscale predictions over different time spans and achieved satisfactory performance, even for 13-24 h prediction tasks (MAPE = 31.47%). Copyright © 2017 Elsevier Ltd. All rights reserved.

MACROINVERTEBRATE INVENTORIES OF THE WHITE RIVER, COLORADO AND UTAH: SIGNIFICANCE OF ANNUAL, SEASONAL, AND SPATIAL VARIATION IN THE DESIGN OF BIOMONITORING NETWORKS FOR POLLUTION DETECTION

EPA Science Inventory

An aquatic macroinvertebrate monitoring program is suggested for 'early warning' detection of toxic discharges to streams in oil shale development areas. Changes in stream biota are used to signal need for increasing levels of chemical analyses to identify and quantify toxic poll...

The impact of the 2016 Fort McMurray Horse River Wildfire on ambient air pollution levels in the Athabasca Oil Sands Region, Alberta, Canada

EPA Science Inventory

An unprecedented wildfire impacted the northern Alberta city of Fort McMurray in May 2016 causing a mandatory city wide evacuation and the loss of 2,400 homes and commercial structures. A comprehensive air monitoring network operated by the Wood Buffalo Environmental Association ...

Atlanta Rail Yard Study (ARYS): Evaluation of local-scale air pollution trends and emissions quantification using stationary and mobile monitoring strategies

EPA Science Inventory

Intermodal rail yards are important nodes in the freight transportation network, where freight is organized and moved from one mode of transport to another, critical equipment is serviced, and freight is routed to its next destination. Rail yard environments are also areas with ...

Measurements of Atmospheric NH3, NOy/NOx, and NO2 and Deposition of Total Nitrogen at the Beaufort, NC CASTNET Site (BFT142)

EPA Science Inventory

The Clean Air Status and Trends Network (CASTNET) is a long-term environmental monitoring program that measures trends in ambient air quality and atmospheric dry pollutant deposition across the United States. CASTNET has been operating since 1987 and currently consists of 89 moni...

40 CFR Appendix D to Part 58 - Network Design Criteria for Ambient Air Quality Monitoring

Code of Federal Regulations, 2013 CFR

2013-07-01

... determine the extent of regional pollutant transport among populated areas; and in support of secondary... sources within the area, transport of O3 and its precursors, and the photochemical processes related to O3... precursor concentrations entering the area and will identify those areas which are subjected to transport...

40 CFR Appendix D to Part 58 - Network Design Criteria for Ambient Air Quality Monitoring

Code of Federal Regulations, 2014 CFR

2014-07-01

... determine the extent of regional pollutant transport among populated areas; and in support of secondary... sources within the area, transport of O3 and its precursors, and the photochemical processes related to O3... precursor concentrations entering the area and will identify those areas which are subjected to transport...

Artificial neural networks for modeling time series of beach litter in the southern North Sea.

PubMed

Schulz, Marcus; Matthies, Michael

2014-07-01

In European marine waters, existing monitoring programs of beach litter need to be improved concerning litter items used as indicators of pollution levels, efficiency, and effectiveness. In order to ease and focus future monitoring of beach litter on few important litter items, feed-forward neural networks consisting of three layers were developed to relate single litter items to general categories of marine litter. The neural networks developed were applied to seven beaches in the southern North Sea and modeled time series of five general categories of marine litter, such as litter from fishing, shipping, and tourism. Results of regression analyses show that general categories were predicted significantly moderately to well. Measured and modeled data were in the same order of magnitude, and minima and maxima overlapped well. Neural networks were found to be eligible tools to deliver reliable predictions of marine litter with low computational effort and little input of information. Copyright © 2014 Elsevier Ltd. All rights reserved.

Characterization of water pollution in drainage networks using continuous monitoring data in the Citadel area of Hue City, Vietnam.

PubMed

Nagano, Y; Teraguchi, T; Lieu, P K; Furumai, H

2014-01-01

In the Citadel area of Hue City, drainage systems that include canals and ponds are considerable sources of fecal contaminants to inundated water during the rainy season because canals and ponds receive untreated wastewater. It is important to investigate the characteristics of hydraulics and water pollution in canals and ponds. At the canals and ponds, water sampling was conducted during dry and wet weather periods in order to evaluate fecal contamination and to investigate changes in water pollution caused by runoff inflow. Inundated water was also collected from streets during heavy rainfall. At the canals and ponds, concentrations of Escherichia coli and total coliform exceeded the Vietnamese regulation values for surface water in 23 and 24 out of 27 samples (85 and 89%), respectively. The water samples were categorized based on the characteristics of water pollution using cluster analysis. In the rainy season, continuous monitoring was conducted at the canals and ponds using water depth and electrical conductivity (EC) sensors to investigate the dynamic relationship between water level and water pollution. It is suggested that in the canals, high EC meant water stagnation and low EC signified river water inflow. Therefore, EC might be a good indicator of water flow change in canals.

Sophisticated Clean Air Strategies Required to Mitigate Against Particulate Organic Pollution

NASA Astrophysics Data System (ADS)

Grigas, T.; Ovadnevaite, J.; Ceburnis, D.; Moran, E.; McGovern, F. M.; Jennings, S. G.; O'Dowd, C.

2017-03-01

Since the 1980’s, measures mitigating the impact of transboundary air pollution have been implemented successfully as evidenced in the 1980-2014 record of atmospheric sulphur pollution over the NE-Atlantic, a key region for monitoring background northern-hemisphere pollution levels. The record reveals a 72-79% reduction in annual-average airborne sulphur pollution (SO4 and SO2, respectively) over the 35-year period. The NE-Atlantic, as observed from the Mace Head research station on the Irish coast, can be considered clean for 64% of the time during which sulphate dominates PM1 levels, contributing 42% of the mass, and for the remainder of the time, under polluted conditions, a carbonaceous (organic matter and Black Carbon) aerosol prevails, contributing 60% to 90% of the PM1 mass and exhibiting a trend whereby its contribution increases with increasing pollution levels. The carbonaceous aerosol is known to be diverse in source and nature and requires sophisticated air pollution policies underpinned by sophisticated characterisation and source apportionment capabilities to inform selective emissions-reduction strategies. Inauspiciously, however, this carbonaceous concoction is not measured in regulatory Air Quality networks.

Sophisticated Clean Air Strategies Required to Mitigate Against Particulate Organic Pollution.

PubMed

Grigas, T; Ovadnevaite, J; Ceburnis, D; Moran, E; McGovern, F M; Jennings, S G; O'Dowd, C

2017-03-17

Since the 1980's, measures mitigating the impact of transboundary air pollution have been implemented successfully as evidenced in the 1980-2014 record of atmospheric sulphur pollution over the NE-Atlantic, a key region for monitoring background northern-hemisphere pollution levels. The record reveals a 72-79% reduction in annual-average airborne sulphur pollution (SO 4 and SO 2 , respectively) over the 35-year period. The NE-Atlantic, as observed from the Mace Head research station on the Irish coast, can be considered clean for 64% of the time during which sulphate dominates PM 1 levels, contributing 42% of the mass, and for the remainder of the time, under polluted conditions, a carbonaceous (organic matter and Black Carbon) aerosol prevails, contributing 60% to 90% of the PM 1 mass and exhibiting a trend whereby its contribution increases with increasing pollution levels. The carbonaceous aerosol is known to be diverse in source and nature and requires sophisticated air pollution policies underpinned by sophisticated characterisation and source apportionment capabilities to inform selective emissions-reduction strategies. Inauspiciously, however, this carbonaceous concoction is not measured in regulatory Air Quality networks.

Nonlinear dynamics of the atmospheric pollutants in Mexico City

NASA Astrophysics Data System (ADS)

Muñoz-Diosdado, Alejandro; Barrera-Ferrer, Amilcar; Angulo-Brown, Fernando

2014-05-01

The atmospheric pollution in the Metropolitan Zone of Mexico City (MZMC) is a serious problem with social, economical and political consequences, in virtue that it is the region which concentrates both the greatest country population and a great part of commercial and industrial activities. According to the World Health Organization, maximum permissible concentrations of atmospheric pollutants are exceeded frequently. In the MZMC, the environmental monitoring has been limited to criteria pollutants, named in this way due to when their levels are measured in the atmosphere, they indicate in a precise way the air quality. The Automatic Atmospheric Monitoring Network monitors and registers the values of pollutants concentration in air in the MZMC. Actually, it is integrated by approximately 35 automatic-equipped remote stations, which report an every-hour register. Local and global invariant quantities have been widely used to describe the fractal properties of diverse time series. In the study of certain time series, many times it is assumed that they are monofractal, which means that they can be described only with one fractal dimension. But this hypothesis is unrealistic because a lot of time series are heterogeneous and non stationary, so their scaling properties are not the same throughout time and therefore they may require more fractal dimensions for their description. Complexity of the atmospheric pollutants dynamics suggests us to analyze its time series of hourly concentration registers with the multifractal formalism. So, in this work, air concentration time series of MZMC criteria pollutants were studied with the proposed method. The chosen pollutants to perform this analysis are ozone, sulfur dioxide, carbon monoxide, nitrogen dioxide and PM10 (particles less than 10 micrometers). We found that pollutants air concentration time series are multifractal. When we calculate the degree of multifractality for each time series we know that while more multifractal are the time series, there is more complexity both in the time series and in the system from which the measurements were obtained. We studied the variation of the degree of multifractality over time, by calculating the multifractal spectra of the time series for each year; we see the variation in each monitoring station from 1990 until 2013. Multifractal analysis can tell us what kinds of correlations are present in the time series, and it is interesting to consider how these correlations vary over time. Our results show that for all the pollutants and all the monitoring stations the time series have long range correlations and they are highly persistent.

"What We Breathe Impacts Our Health: Improving Understanding of the Link between Air Pollution and Health".

PubMed

West, J Jason; Cohen, Aaron; Dentener, Frank; Brunekreef, Bert; Zhu, Tong; Armstrong, Ben; Bell, Michelle L; Brauer, Michael; Carmichael, Gregory; Costa, Dan L; Dockery, Douglas W; Kleeman, Michael; Krzyzanowski, Michal; Künzli, Nino; Liousse, Catherine; Lung, Shih-Chun Candice; Martin, Randall V; Pöschl, Ulrich; Pope, C Arden; Roberts, James M; Russell, Armistead G; Wiedinmyer, Christine

2016-05-17

Air pollution contributes to the premature deaths of millions of people each year around the world, and air quality problems are growing in many developing nations. While past policy efforts have succeeded in reducing particulate matter and trace gases in North America and Europe, adverse health effects are found at even these lower levels of air pollution. Future policy actions will benefit from improved understanding of the interactions and health effects of different chemical species and source categories. Achieving this new understanding requires air pollution scientists and engineers to work increasingly closely with health scientists. In particular, research is needed to better understand the chemical and physical properties of complex air pollutant mixtures, and to use new observations provided by satellites, advanced in situ measurement techniques, and distributed micro monitoring networks, coupled with models, to better characterize air pollution exposure for epidemiological and toxicological research, and to better quantify the effects of specific source sectors and mitigation strategies.

An efficient approach to imaging underground hydraulic networks

NASA Astrophysics Data System (ADS)

Kumar, Mohi

2012-07-01

To better locate natural resources, treat pollution, and monitor underground networks associated with geothermal plants, nuclear waste repositories, and carbon dioxide sequestration sites, scientists need to be able to accurately characterize and image fluid seepage pathways below ground. With these images, scientists can gain knowledge of soil moisture content, the porosity of geologic formations, concentrations and locations of dissolved pollutants, and the locations of oil fields or buried liquid contaminants. Creating images of the unknown hydraulic environments underfoot is a difficult task that has typically relied on broad extrapolations from characteristics and tests of rock units penetrated by sparsely positioned boreholes. Such methods, however, cannot identify small-scale features and are very expensive to reproduce over a broad area. Further, the techniques through which information is extrapolated rely on clunky and mathematically complex statistical approaches requiring large amounts of computational power.

Design of a water quality monitoring network for the Limpopo River Basin in Mozambique

NASA Astrophysics Data System (ADS)

Chilundo, M.; Kelderman, P.; O´keeffe, J. H.

The measurement of chemical, physical and biological parameters is important for the characterization of streams health. Thus, cost-effective and targeted water quality (WQ) monitoring programmes are required for proper assessment, restoration and protection of such systems. This research proposes a WQ monitoring network for the Limpopo River Basin (LRB) in Mozambique located in Southern Africa, a region prone to severe droughts. In this Basin both anthropogenic and natural driven processes, exacerbated by the increased water demand by the four riparian countries (Botswana, South Africa, Zimbabwe and Mozambique) are responsible for the degradation of surface waters, impairing their downstream use, either for aquatic ecosystem, drinking, industrial or irrigation. Hence, physico-chemical, biological and microbiological characteristics at 23 sites within the basin were studied in November 2006 and January 2007. The physico-chemical and microbiological samples were analyzed according to American Public Health Association (APHA) standard methods, while the biological monitoring working party method (BMWP) was used for biological assessment. The assessment of the final WQ condition at sampled points was done taking into account appropriate indexes, the Mozambican standards for receiving waters and the WHO guidelines for drinking WQ. The assessed data indicated that sites located at proximities to the border with upstream countries were contaminated with heavy metals. The Elephants subcatchment was found with a relatively better WQ, whereas the Changane subcatchment together with the effluent point discharges in the basin were found polluted as indicated by the low dissolved oxygen and high total dissolved solids, electric conductivity, total hardness, sodium adsorption ratio and low benthic macroinvertebrates taxa. Significant differences ( p < 0.05) were found for some parameters when the concentrations recorded in November and January were tested, therefore, indicating possible need for monthly monitoring of WQ. From this study it was concluded that a systematic WQ monitoring network composed of 16 stations would fit the conditions of the LRB. Ambient, earl warning, operational and effluents are the main monitoring types recommended. Additional research at a Basin scale was also recommended to identify the major sources of pollution, their transport and impacts to the downstream ecosystem.

Calibration of low-cost gas sensors for an urban air quality monitoring network

NASA Astrophysics Data System (ADS)

Scott, A.; Kelley, C.; He, C.; Ghugare, P.; Lehman, A.; Benish, S.; Stratton, P.; Dickerson, R. R.; Zuidema, C.; Azdoud, Y.; Ren, X.

2017-12-01

In a warming world, environmental pollution may be exacerbated by anthropogenic activities, such as climate change and the urban heat island effect, as well as natural phenomena such as heat waves. However, monitoring air pollution at federal reference standards (approximately 1 part per billion or ppb for ambient ozone) is cost-prohibitive in heterogeneous urban areas as many expensive devices are required to fully capture a region's geo-spatial variability. Innovation in low-cost sensors provide a potential solution, yet technical challenges remain to overcome possible imprecision in the data. We present the calibrations of ozone and nitrous dioxide from a low-cost air quality monitoring device designed for the Baltimore Open Air Project. The sensors used in this study are commercially available thin film electrochemical sensors from SPEC Sensor, which are amperometric, meaning they generate current proportional to volumetric fraction of gas. The results of sensor calibrations in the laboratory and field are presented.

Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone?

PubMed

Morawska, Lidia; Thai, Phong K; Liu, Xiaoting; Asumadu-Sakyi, Akwasi; Ayoko, Godwin; Bartonova, Alena; Bedini, Andrea; Chai, Fahe; Christensen, Bryce; Dunbabin, Matthew; Gao, Jian; Hagler, Gayle S W; Jayaratne, Rohan; Kumar, Prashant; Lau, Alexis K H; Louie, Peter K K; Mazaheri, Mandana; Ning, Zhi; Motta, Nunzio; Mullins, Ben; Rahman, Md Mahmudur; Ristovski, Zoran; Shafiei, Mahnaz; Tjondronegoro, Dian; Westerdahl, Dane; Williams, Ron

2018-07-01

Over the past decade, a range of sensor technologies became available on the market, enabling a revolutionary shift in air pollution monitoring and assessment. With their cost of up to three orders of magnitude lower than standard/reference instruments, many avenues for applications have opened up. In particular, broader participation in air quality discussion and utilisation of information on air pollution by communities has become possible. However, many questions have been also asked about the actual benefits of these technologies. To address this issue, we conducted a comprehensive literature search including both the scientific and grey literature. We focused upon two questions: (1) Are these technologies fit for the various purposes envisaged? and (2) How far have these technologies and their applications progressed to provide answers and solutions? Regarding the former, we concluded that there is no clear answer to the question, due to a lack of: sensor/monitor manufacturers' quantitative specifications of performance, consensus regarding recommended end-use and associated minimal performance targets of these technologies, and the ability of the prospective users to formulate the requirements for their applications, or conditions of the intended use. Numerous studies have assessed and reported sensor/monitor performance under a range of specific conditions, and in many cases the performance was concluded to be satisfactory. The specific use cases for sensors/monitors included outdoor in a stationary mode, outdoor in a mobile mode, indoor environments and personal monitoring. Under certain conditions of application, project goals, and monitoring environments, some sensors/monitors were fit for a specific purpose. Based on analysis of 17 large projects, which reached applied outcome stage, and typically conducted by consortia of organizations, we observed that a sizable fraction of them (~ 30%) were commercial and/or crowd-funded. This fact by itself signals a paradigm change in air quality monitoring, which previously had been primarily implemented by government organizations. An additional paradigm-shift indicator is the growing use of machine learning or other advanced data processing approaches to improve sensor/monitor agreement with reference monitors. There is still some way to go in enhancing application of the technologies for source apportionment, which is of particular necessity and urgency in developing countries. Also, there has been somewhat less progress in wide-scale monitoring of personal exposures. However, it can be argued that with a significant future expansion of monitoring networks, including indoor environments, there may be less need for wearable or portable sensors/monitors to assess personal exposure. Traditional personal monitoring would still be valuable where spatial variability of pollutants of interest is at a finer resolution than the monitoring network can resolve. Copyright © 2018 Elsevier Ltd. All rights reserved.

Evaluation and intercomparison of five major dry deposition ...

EPA Pesticide Factsheets

Dry deposition of various pollutants needs to be quantified in air quality monitoring networks as well as in chemical transport models. The inferential method is the most commonly used approach in which the dry deposition velocity (Vd) is empirically parameterized as a function of meteorological and biological conditions and pollutant species’ chemical properties. Earlier model intercomparison studies suggested that existing dry deposition algorithms produce quite different Vd values, e.g., up to a factor of 2 for monthly to annual average values for ozone, and sulfur and nitrogen species (Flechard et al., 2011; Schwede et al., 2011; Wu et al., 2011). To further evaluate model discrepancies using available flux data, this study compared the five dry deposition algorithms commonly used in North America and evaluated the models using five-year Vd(O3) and Vd(SO2) data generated from concentration gradient measurements above a temperate mixed forest in Canada. The five algorithms include: (1) the one used in the Canadian Air and Precipitation Monitoring Network (CAPMoN) and several Canadian air quality models based on Zhang et al. (2003), (2) the one used in the US Clean Air Status and Trends Network (CASTNET) based on Meyers et al. (1998), (3) the one used in the Community Multiscale Air Quality (CMAQ) model described in Pleim and Ran (2011), (4) the Noah land surface model coupled with a photosynthesis-based Gas Exchange Model (Noah-GEM) described in Wu et a

Regional and transported aerosols during DRAGON-Japan experiment

NASA Astrophysics Data System (ADS)

Sano, I.; Holben, B. N.; Mukai, S.; Nakata, M.; Nakaguchi, Y.; Sugimoto, N.; Hatakeyama, S.; Nishizawa, T.; Takamura, T.; Takemura, T.; Yonemitsu, M.; Fujito, T.; Schafer, J.; Eck, T. F.; Sorokin, M.; Kenny, P.; Goto, M.; Hiraki, T.; Iguchi, N.; Kouzai, K.; KUJI, M.; Muramatsu, K.; Okada, Y.; Sadanaga, Y.; Tohno, S.; Toyazaki, Y.; Yamamoto, K.

2013-12-01

Aerosol properties over Japan have been monitored by AERONET sun / sky photometers since 2000. These measurements provides us with long term information of local aerosols, which are influenced by transported aerosols, such as Asian dusts or anthropogenic pollutants due to rapid increasing of energy consumption in Asian countries. A new aerosol monitoring experiment, Distributed Regional Aerosol Gridded Observation Networks (DRAGON) - Japan is operated in spring of 2012. The main instrument of DRAGON network is AERONET sun/sky radiometers. Some of them are sparsely set along the Japanese coast and some others make a dense network in Osaka, which is the second-largest city in Japan and famous for manufacturing town. Several 2ch NIES-LIDAR systems are also co-located with AERONET instrument to monitor Asian dusts throughout the campaign. The objects of Dragon-Japan are to characterize local aerosols as well as transported ones from the continent of China, and to acquire the detailed aerosol information for validating satellite data with high resolved spatial scale. This work presents the comprehensive results of aerosol properties with respect to regional- and/or transported- scale during DRAGON-Japan experiments.

Pollution monitoring using networks of honey bees

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bromenshenk, J.J.; Dewart, M.L.; Thomas, J.M.

1983-08-01

Each year thousands of chemicals in large quantities are introduced into the global environment and the need for effective methods of monitoring these substances has steadily increased. Most monitoring programs rely upon instrumentation to measure specific contaminants in air, water, or soil. However, it has become apparent that humans and their environment are exposed to complex mixtures of chemicals rather than single entities. As our ability to detect ever smaller quantities of pollutants has increased, the biological significance of these findings has become more uncertain. Also, it is clear that monitoring efforts should shift from short-term studies of easily identifiablemore » sources in localized areas to long-term studies of multiple sources over widespread regions. Our investigations aim at providing better tools to meet these exigencies. Honey bees are discussed as an effective, long-term, self-sustaining system for monitoring environmental impacts. Our results indicate that the use of regional, and possibly national or international, capability can be realized with the aid of beekeepers in obtaining samples and conducting measurements. This approach has the added advantage of public involvement in environmental problem solving and protection of human health and environmental quality.« less

The statistical evaluation and comparison of ADMS-Urban model for the prediction of nitrogen dioxide with air quality monitoring network.

PubMed

Dėdelė, Audrius; Miškinytė, Auksė

2015-09-01

In many countries, road traffic is one of the main sources of air pollution associated with adverse effects on human health and environment. Nitrogen dioxide (NO2) is considered to be a measure of traffic-related air pollution, with concentrations tending to be higher near highways, along busy roads, and in the city centers, and the exceedances are mainly observed at measurement stations located close to traffic. In order to assess the air quality in the city and the air pollution impact on public health, air quality models are used. However, firstly, before the model can be used for these purposes, it is important to evaluate the accuracy of the dispersion modelling as one of the most widely used method. The monitoring and dispersion modelling are two components of air quality monitoring system (AQMS), in which statistical comparison was made in this research. The evaluation of the Atmospheric Dispersion Modelling System (ADMS-Urban) was made by comparing monthly modelled NO2 concentrations with the data of continuous air quality monitoring stations in Kaunas city. The statistical measures of model performance were calculated for annual and monthly concentrations of NO2 for each monitoring station site. The spatial analysis was made using geographic information systems (GIS). The calculation of statistical parameters indicated a good ADMS-Urban model performance for the prediction of NO2. The results of this study showed that the agreement of modelled values and observations was better for traffic monitoring stations compared to the background and residential stations.

Estimating Ground-Level PM2.5 by Fusing Satellite and Station Observations: A Geo-Intelligent Deep Learning Approach

NASA Astrophysics Data System (ADS)

Li, Tongwen; Shen, Huanfeng; Yuan, Qiangqiang; Zhang, Xuechen; Zhang, Liangpei

2017-12-01

Fusing satellite observations and station measurements to estimate ground-level PM2.5 is promising for monitoring PM2.5 pollution. A geo-intelligent approach, which incorporates geographical correlation into an intelligent deep learning architecture, is developed to estimate PM2.5. Specifically, it considers geographical distance and spatiotemporally correlated PM2.5 in a deep belief network (denoted as Geoi-DBN). Geoi-DBN can capture the essential features associated with PM2.5 from latent factors. It was trained and tested with data from China in 2015. The results show that Geoi-DBN performs significantly better than the traditional neural network. The out-of-sample cross-validation R2 increases from 0.42 to 0.88, and RMSE decreases from 29.96 to 13.03 μg/m3. On the basis of the derived PM2.5 distribution, it is predicted that over 80% of the Chinese population live in areas with an annual mean PM2.5 of greater than 35 μg/m3. This study provides a new perspective for air pollution monitoring in large geographic regions.

A Flexible Spatio-Temporal Model for Air Pollution with Spatial and Spatio-Temporal Covariates.

PubMed

Lindström, Johan; Szpiro, Adam A; Sampson, Paul D; Oron, Assaf P; Richards, Mark; Larson, Tim V; Sheppard, Lianne

2014-09-01

The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system (GIS) covariates. The model presented in this paper has been implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of NO x in the Los Angeles area during a ten year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated R 2 of approximately 0.7 at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy.

Transfer of European Approach to Groundwater Monitoring in China

NASA Astrophysics Data System (ADS)

Zhou, Y.

2007-12-01

Major groundwater development in North China has been a key factor in the huge economic growth and the achievement of self sufficiency in food production. Groundwater accounts for more than 70 percent of urban water supply and provides important source of irrigation water during dry period. This has however caused continuous groundwater level decline and many associated problems: hundreds of thousands of dry wells, dry river beds, land subsidence, seawater intrusion and groundwater quality deterioration. Groundwater levels in the shallow unconfined aquifers have fallen 10m up to 50m, at an average rate of 1m/year. In the deep confined aquifers groundwater levels have commonly fallen 30m up to 90m, at an average rate of 3 to 5m/year. Furthermore, elevated nitrate concentrations have been found in shallow groundwater in large scale. Pesticides have been detected in vulnerable aquifers. Urgent actions are necessary for aquifer recovery and mitigating groundwater pollution. Groundwater quantity and quality monitoring plays a very important role in formulating cost-effective groundwater protection strategies. In 2000 European Union initiated a Water Framework Directive (2000/60/EC) to protect all waters in Europe. The objective is to achieve good water and ecological status by 2015 cross all member states. The Directive requires monitoring surface and groundwater in all river basins. A guidance document for monitoring was developed and published in 2003. Groundwater monitoring programs are distinguished into groundwater level monitoring and groundwater quality monitoring. Groundwater quality monitoring is further divided into surveillance monitoring and operational monitoring. The monitoring guidance specifies key principles for the design and operation of monitoring networks. A Sino-Dutch cooperation project was developed to transfer European approach to groundwater monitoring in China. The project aims at building a China Groundwater Information Centre. Case studies in 3 pilot areas have been conducted to build research capacities of the central and provincial groundwater information centers in providing groundwater information services to decision makers and public. Groundwater regime zoning and pollution risk maps were used to lay-out groundwater quantity and quality monitoring networks, respectively. Automatic groundwater recorders were installed in selected observation wells. ArcGIS based regional groundwater information systems were constructed and used to create groundwater regime zoning and pollution risk maps. Steady state groundwater models have been constructed and calibrated. Transient groundwater models are under calibration. Groundwater resources development scenarios were formulated. The model will be used to predict what will be consequences in next 20 years if current situation continues as business as usual. Possibilities of reducing groundwater abstraction and opportunities of artificially enhanced groundwater recharge will be analyzed. Combination of decreasing abstraction and increasing recharge may lead to a sustainable plan of future groundwater resources development.

An Overview of the 3C-STAR project

NASA Astrophysics Data System (ADS)

Zhang, Y.

2009-04-01

Over the past three decades, city clusters have played a leading role in the economic growth of China, owing to their collective economic capacity and interdependency. However, pollution prevention lags behind the economic boom, led to a general decline in air quality in city clusters. As a result, industrial emissions and traffic exhausts together contribute to high levels of ozone (O3) and fine particulate matter (PM2.5) pollution problems ranging from urban to regional scale. Such high levels of both primary and secondary airborne pollutants lead to the development of a (perhaps typically Chinese) "air pollution complex" concept. Air pollution complex is particularly true and significant in Beijing-Tianjin area, Pearl River Delta (PRD) and Yangtze River Delta. The concurrent high concentrations of O3 and PM2.5 in PRD as well as in other China city clusters have led to rather unique pollution characteristics due to interactions between primary emissions and photochemical processes, between gaseous compounds and aerosol phase species, and between local and regional scale processes. The knowledge and experience needed to find solutions to the unique pollution complex in China are still lacking. Starting from 2007, we launch a major project "Synthesized Prevention Techniques for Air Pollution Complex and Integrated Demonstration in Key City-Cluster Region" (3C-STAR) to address those problems scientifically and technically. The purpose of the project is to build up the capacity of regional air pollution control and to establish regional coordination mechanism for joint implementation of pollution control. The project includes a number of key components technically: regional air quality monitoring network and super-sites, regional dynamic emission inventory of multi-pollutants, regional ensemble air quality forecasting model system, and regional management system supported by decision making platform. The 3C-STAR project selected PRD as a core area to have technical demonstration, and thus provide opportunities as well as challenges for PRD to improve its regional air quality. An integrated field measurement campaign 3C-STAR2008 was organized during October 15-November 19, 2008, including 3-D regional air quality monitoring network, two super-sites, and in-site meteorological and air quality forecasting. With the efforts of more than 100 scientists and students from 12 research institutes, the 3C-STAR2008 was conducted with great success. A great amount of data with rigorous QA/QC procedures has been obtained and data analysis is underway. In this talk, an overview of the 3C-STAR project will be presented, together with major findings from previous PRD campaigns (PRD2004 and PRD2006).

Multi-scale modeling of urban air pollution: development and application of a Street-in-Grid model (v1.0) by coupling MUNICH (v1.0) and Polair3D (v1.8.1)

NASA Astrophysics Data System (ADS)

Kim, Youngseob; Wu, You; Seigneur, Christian; Roustan, Yelva

2018-02-01

A new multi-scale model of urban air pollution is presented. This model combines a chemistry-transport model (CTM) that includes a comprehensive treatment of atmospheric chemistry and transport on spatial scales down to 1 km and a street-network model that describes the atmospheric concentrations of pollutants in an urban street network. The street-network model is the Model of Urban Network of Intersecting Canyons and Highways (MUNICH), which consists of two main components: a street-canyon component and a street-intersection component. MUNICH is coupled to the Polair3D CTM of the Polyphemus air quality modeling platform to constitute the Street-in-Grid (SinG) model. MUNICH is used to simulate the concentrations of the chemical species in the urban canopy, which is located in the lowest layer of Polair3D, and the simulation of pollutant concentrations above rooftops is performed with Polair3D. Interactions between MUNICH and Polair3D occur at roof level and depend on a vertical mass transfer coefficient that is a function of atmospheric turbulence. SinG is used to simulate the concentrations of nitrogen oxides (NOx) and ozone (O3) in a Paris suburb. Simulated concentrations are compared to NOx concentrations measured at two monitoring stations within a street canyon. SinG shows better performance than MUNICH for nitrogen dioxide (NO2) concentrations. However, both SinG and MUNICH underestimate NOx. For the case study considered, the model performance for NOx concentrations is not sensitive to using a complex chemistry model in MUNICH and the Leighton NO-NO2-O3 set of reactions is sufficient.

Multi-perspective analysis and spatiotemporal mapping of air pollution monitoring data.

PubMed

Kolovos, Alexander; Skupin, André; Jerrett, Michael; Christakos, George

2010-09-01

Space-time data analysis and assimilation techniques in atmospheric sciences typically consider input from monitoring measurements. The input is often processed in a manner that acknowledges characteristics of the measurements (e.g., underlying patterns, fluctuation features) under conditions of uncertainty; it also leads to the derivation of secondary information that serves study-oriented goals, and provides input to space-time prediction techniques. We present a novel approach that blends a rigorous space-time prediction model (Bayesian maximum entropy, BME) with a cognitively informed visualization of high-dimensional data (spatialization). The combined BME and spatialization approach (BME-S) is used to study monthly averaged NO2 and mean annual SO4 measurements in California over the 15-year period 1988-2002. Using the original scattered measurements of these two pollutants BME generates spatiotemporal predictions on a regular grid across the state. Subsequently, the prediction network undergoes the spatialization transformation into a lower-dimensional geometric representation, aimed at revealing patterns and relationships that exist within the input data. The proposed BME-S provides a powerful spatiotemporal framework to study a variety of air pollution data sources.

Contamination Event Detection with Multivariate Time-Series Data in Agricultural Water Monitoring †

PubMed Central

Mao, Yingchi; Qi, Hai; Ping, Ping; Li, Xiaofang

2017-01-01

Time series data of multiple water quality parameters are obtained from the water sensor networks deployed in the agricultural water supply network. The accurate and efficient detection and warning of contamination events to prevent pollution from spreading is one of the most important issues when pollution occurs. In order to comprehensively reduce the event detection deviation, a spatial–temporal-based event detection approach with multivariate time-series data for water quality monitoring (M-STED) was proposed. The M-STED approach includes three parts. The first part is that M-STED adopts a Rule K algorithm to select backbone nodes as the nodes in the CDS, and forward the sensed data of multiple water parameters. The second part is to determine the state of each backbone node with back propagation neural network models and the sequential Bayesian analysis in the current timestamp. The third part is to establish a spatial model with Bayesian networks to estimate the state of the backbones in the next timestamp and trace the “outlier” node to its neighborhoods to detect a contamination event. The experimental results indicate that the average detection rate is more than 80% with M-STED and the false detection rate is lower than 9%, respectively. The M-STED approach can improve the rate of detection by about 40% and reduce the false alarm rate by about 45%, compared with the event detection with a single water parameter algorithm, S-STED. Moreover, the proposed M-STED can exhibit better performance in terms of detection delay and scalability. PMID:29207535

Modelling the photochemical pollution over the metropolitan area of Porto Alegre, Brazil

NASA Astrophysics Data System (ADS)

Borrego, C.; Monteiro, A.; Ferreira, J.; Moraes, M. R.; Carvalho, A.; Ribeiro, I.; Miranda, A. I.; Moreira, D. M.

2010-01-01

The main purpose of this study is to evaluate the photochemical pollution over the Metropolitan Area of Porto Alegre (MAPA), Brazil, where high concentrations of ozone have been registered during the past years. Due to the restricted spatial coverage of the monitoring air quality network, a numerical modelling technique was selected and applied to this assessment exercise. Two different chemistry-transport models - CAMx and CALGRID - were applied for a summer period, driven by the MM5 meteorological model. The meteorological model performance was evaluated comparing its results to available monitoring data measured at the Porto Alegre airport. Validation results point out a good model performance. It was not possible to evaluate the chemistry models performance due to the lack of adequate monitoring data. Nevertheless, the model intercomparison between CAMx and CALGRID shows a similar behaviour in what concerns the simulation of nitrogen dioxide, but some discrepancies concerning ozone. Regarding the fulfilment of the Brazilian air quality targets, the simulated ozone concentrations surpass the legislated value in specific periods, mainly outside the urban area of Porto Alegre. The ozone formation is influenced by the emission of pollutants that act as precursors (like the nitrogen oxides emitted at Porto Alegre urban area and coming from a large refinery complex) and by the meteorological conditions.

Comparison of Satellite Observations of Nitrogen Dioxide to Surface Monitor Nitrogen Dioxide Concentration

NASA Technical Reports Server (NTRS)

Kleb, Mary M.; Pippin, Margaret R.; Pierce, R. Bradley; Neil, Doreen O.; Lingenfelser, Gretchen; Szykman, James J.

2006-01-01

Nitrogen dioxide is one of the U. S. EPA s criteria pollutants, and one of the main ingredients needed for the production of ground-level ozone. Both ozone and nitrogen dioxide cause severe public health problems. Existing satellites have begun to produce observational data sets for nitrogen dioxide. Under NASAs Earth Science Applications Program, we examined the relationship between satellite observations and surface monitor observations of this air pollutant to examine if the satellite data can be used to facilitate a more capable and integrated observing network. This report provides a comparison of satellite tropospheric column nitrogen dioxide to surface monitor nitrogen dioxide concentration for the period from September 1996 through August 1997 at more than 300 individual locations in the continental US. We found that the spatial resolution and observation time of the satellite did not capture the variability of this pollutant as measured at ground level. The tools and processes developed to conduct this study will be applied to the analysis of advanced satellite observations. One advanced instrument has significantly better spatial resolution than the measurements studied here and operates with an afternoon overpass time, providing a more representative distribution for once-per-day sampling of this photochemically active atmospheric constituent.

Sophisticated Clean Air Strategies Required to Mitigate Against Particulate Organic Pollution

PubMed Central

Grigas, T.; Ovadnevaite, J.; Ceburnis, D.; Moran, E.; McGovern, F. M.; Jennings, S. G.; O’Dowd, C.

2017-01-01

Since the 1980’s, measures mitigating the impact of transboundary air pollution have been implemented successfully as evidenced in the 1980–2014 record of atmospheric sulphur pollution over the NE-Atlantic, a key region for monitoring background northern-hemisphere pollution levels. The record reveals a 72–79% reduction in annual-average airborne sulphur pollution (SO4 and SO2, respectively) over the 35-year period. The NE-Atlantic, as observed from the Mace Head research station on the Irish coast, can be considered clean for 64% of the time during which sulphate dominates PM1 levels, contributing 42% of the mass, and for the remainder of the time, under polluted conditions, a carbonaceous (organic matter and Black Carbon) aerosol prevails, contributing 60% to 90% of the PM1 mass and exhibiting a trend whereby its contribution increases with increasing pollution levels. The carbonaceous aerosol is known to be diverse in source and nature and requires sophisticated air pollution policies underpinned by sophisticated characterisation and source apportionment capabilities to inform selective emissions-reduction strategies. Inauspiciously, however, this carbonaceous concoction is not measured in regulatory Air Quality networks. PMID:28303958

Putting Man in the Machine: Exploiting Expertise to Enhance Multiobjective Design of Water Supply Monitoring Network

NASA Astrophysics Data System (ADS)

Bode, F.; Nowak, W.; Reed, P. M.; Reuschen, S.

2016-12-01

Drinking-water well catchments need effective early-warning monitoring networks. Groundwater water supply wells in complex urban environments are in close proximity to a myriad of potential industrial pollutant sources that could irreversibly damage their source aquifers. These urban environments pose fiscal and physical challenges to designing monitoring networks. Ideal early-warning monitoring networks would satisfy three objectives: to detect (1) all potential contaminations within the catchment (2) as early as possible before they reach the pumping wells, (3) while minimizing costs. Obviously, the ideal case is nonexistent, so we search for tradeoffs using multiobjective optimization. The challenge of this optimization problem is the high number of potential monitoring-well positions (the search space) and the non-linearity of the underlying groundwater flow-and-transport problem. This study evaluates (1) different ways to effectively restrict the search space in an efficient way, with and without expert knowledge, (2) different methods to represent the search space during the optimization and (3) the influence of incremental increases in uncertainty in the system. Conductivity, regional flow direction and potential source locations are explored as key uncertainties. We show the need and the benefit of our methods by comparing optimized monitoring networks for different uncertainty levels with networks that seek to effectively exploit expert knowledge. The study's main contributions are the different approaches restricting and representing the search space. The restriction algorithms are based on a point-wise comparison of decision elements of the search space. The representation of the search space can be either binary or continuous. For both cases, the search space must be adjusted properly. Our results show the benefits and drawbacks of binary versus continuous search space representations and the high potential of automated search space restriction algorithms for high-dimensional, highly non-linear optimization problems.

Organization of long range transport of air pollution monitoring in Europe

Treesearch

Brynjulf Ottar

1976-01-01

In the 1950's a network of stations for observation of the chemical composition of air and precipitation was established in Europe. Analysing these data, Odén in 1968, was able to show that a central area in Europe with highly acid precipitation was expanding from year to year. This was further substantiated by Granat in 1972, and the explanation is the...

Assessing the Performance of a Network of Low Cost Particulate Matter Sensors Deployed in Sacramento, California

NASA Astrophysics Data System (ADS)

Mukherjee, A. D.; Brown, S. G.; McCarthy, M. C.

2017-12-01

A new generation of low cost air quality sensors have the potential to provide valuable information on the spatial-temporal variability of air pollution - if the measurements have sufficient quality. This study examined the performance of a particulate matter sensor model, the AirBeam (HabitatMap Inc., Brooklyn, NY), over a three month period in the urban environment of Sacramento, California. Nineteen AirBeam sensors were deployed at a regulatory air monitoring site collocated with meteorology measurements and as a local network over an 80 km2 domain in Sacramento, CA. This study presents the methodology to evaluate the precision, accuracy, and reliability of the sensors over a range of meteorological and aerosol conditions. The sensors demonstrated a robust degree of precision during collocated measurement periods (R2 = 0.98 - 0.99) and a moderate degree of correlation against a Beta Attenuation Monitor PM2.5 monitor (R2 0.6). A normalization correction is applied during the study period so that each AirBeam sensor in the network reports a comparable value. The role of the meteorological environment on the accuracy of the sensor measurements is investigated, along with the possibility of improving the measurements through a meteorology weighted correction. The data quality of the network of sensors is examined, and the spatial variability of particulate matter through the study domain derived from the sensor network is presented.

The rise of low-cost sensing for managing air pollution in cities.

PubMed

Kumar, Prashant; Morawska, Lidia; Martani, Claudio; Biskos, George; Neophytou, Marina; Di Sabatino, Silvana; Bell, Margaret; Norford, Leslie; Britter, Rex

2015-02-01

Ever growing populations in cities are associated with a major increase in road vehicles and air pollution. The overall high levels of urban air pollution have been shown to be of a significant risk to city dwellers. However, the impacts of very high but temporally and spatially restricted pollution, and thus exposure, are still poorly understood. Conventional approaches to air quality monitoring are based on networks of static and sparse measurement stations. However, these are prohibitively expensive to capture tempo-spatial heterogeneity and identify pollution hotspots, which is required for the development of robust real-time strategies for exposure control. Current progress in developing low-cost micro-scale sensing technology is radically changing the conventional approach to allow real-time information in a capillary form. But the question remains whether there is value in the less accurate data they generate. This article illustrates the drivers behind current rises in the use of low-cost sensors for air pollution management in cities, while addressing the major challenges for their effective implementation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evaluation of Observation-Fused Regional Air Quality Model Results for Population Air Pollution Exposure Estimation

PubMed Central

Chen, Gang; Li, Jingyi; Ying, Qi; Sherman, Seth; Perkins, Neil; Rajeshwari, Sundaram; Mendola, Pauline

2014-01-01

In this study, Community Multiscale Air Quality (CMAQ) model was applied to predict ambient gaseous and particulate concentrations during 2001 to 2010 in 15 hospital referral regions (HRRs) using a 36-km horizontal resolution domain. An inverse distance weighting based method was applied to produce exposure estimates based on observation-fused regional pollutant concentration fields using the differences between observations and predictions at grid cells where air quality monitors were located. Although the raw CMAQ model is capable of producing satisfying results for O3 and PM2.5 based on EPA guidelines, using the observation data fusing technique to correct CMAQ predictions leads to significant improvement of model performance for all gaseous and particulate pollutants. Regional average concentrations were calculated using five different methods: 1) inverse distance weighting of observation data alone, 2) raw CMAQ results, 3) observation-fused CMAQ results, 4) population-averaged raw CMAQ results and 5) population-averaged fused CMAQ results. It shows that while O3 (as well as NOx) monitoring networks in the HRR regions are dense enough to provide consistent regional average exposure estimation based on monitoring data alone, PM2.5 observation sites (as well as monitors for CO, SO2, PM10 and PM2.5 components) are usually sparse and the difference between the average concentrations estimated by the inverse distance interpolated observations, raw CMAQ and fused CMAQ results can be significantly different. Population-weighted average should be used to account spatial variation in pollutant concentration and population density. Using raw CMAQ results or observations alone might lead to significant biases in health outcome analyses. PMID:24747248

An assessment of air pollutant exposure methods in Mexico City, Mexico.

PubMed

Rivera-González, Luis O; Zhang, Zhenzhen; Sánchez, Brisa N; Zhang, Kai; Brown, Daniel G; Rojas-Bracho, Leonora; Osornio-Vargas, Alvaro; Vadillo-Ortega, Felipe; O'Neill, Marie S

2015-05-01

Geostatistical interpolation methods to estimate individual exposure to outdoor air pollutants can be used in pregnancy cohorts where personal exposure data are not collected. Our objectives were to a) develop four assessment methods (citywide average (CWA); nearest monitor (NM); inverse distance weighting (IDW); and ordinary Kriging (OK)), and b) compare daily metrics and cross-validations of interpolation models. We obtained 2008 hourly data from Mexico City's outdoor air monitoring network for PM10, PM2.5, O3, CO, NO2, and SO2 and constructed daily exposure metrics for 1,000 simulated individual locations across five populated geographic zones. Descriptive statistics from all methods were calculated for dry and wet seasons, and by zone. We also evaluated IDW and OK methods' ability to predict measured concentrations at monitors using cross validation and a coefficient of variation (COV). All methods were performed using SAS 9.3, except ordinary Kriging which was modeled using R's gstat package. Overall, mean concentrations and standard deviations were similar among the different methods for each pollutant. Correlations between methods were generally high (r=0.77 to 0.99). However, ranges of estimated concentrations determined by NM, IDW, and OK were wider than the ranges for CWA. Root mean square errors for OK were consistently equal to or lower than for the IDW method. OK standard errors varied considerably between pollutants and the computed COVs ranged from 0.46 (least error) for SO2 and PM10 to 3.91 (most error) for PM2.5. OK predicted concentrations measured at the monitors better than IDW and NM. Given the similarity in results for the exposure methods, OK is preferred because this method alone provides predicted standard errors which can be incorporated in statistical models. The daily estimated exposures calculated using these different exposure methods provide flexibility to evaluate multiple windows of exposure during pregnancy, not just trimester or pregnancy-long exposures. Many studies evaluating associations between outdoor air pollution and adverse pregnancy outcomes rely on outdoor air pollution monitoring data linked to information gathered from large birth registries, and often lack residence location information needed to estimate individual exposure. This study simulated 1,000 residential locations to evaluate four air pollution exposure assessment methods, and describes possible exposure misclassification from using spatial averaging versus geostatistical interpolation models. An implication of this work is that policies to reduce air pollution and exposure among pregnant women based on epidemiologic literature should take into account possible error in estimates of effect when spatial averages alone are evaluated.

Application of Frequency of Detection Methods in Design and Optimization of the INL Site Ambient Air Monitoring Network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rood, Arthur S.; Sondrup, A. Jeffrey

This report presents an evaluation of a hypothetical INL Site monitoring network and the existing INL air monitoring network using frequency of detection methods. The hypothetical network was designed to address the requirement in 40 CFR Part 61, Subpart H (2006) that “emissions of radionuclides to ambient air from U.S. DOE facilities shall not exceed those amounts that would cause any member of the public to receive in any year an effective dose equivalent exceeding 10 mrem/year.” To meet the requirement for monitoring only, “radionuclide releases that would result in an effective dose of 10% of the standard shall bemore » readily detectable and distinguishable from background.” Thus, the hypothetical network consists of air samplers placed at residence locations that surround INL and at other locations where onsite livestock grazing takes place. Two exposure scenarios were used in this evaluation: a resident scenario and a shepherd/rancher scenario. The resident was assumed to be continuously present at their residence while the shepherd/rancher was assumed to be present 24-hours at a fixed location on the grazing allotment. Important radionuclides were identified from annual INL radionuclide National Emission Standards for Hazardous Pollutants reports. Important radionuclides were defined as those that potentially contribute 1% or greater to the annual total dose at the radionuclide National Emission Standards for Hazardous Pollutants maximally exposed individual location and include H-3, Am-241, Pu-238, Pu 239, Cs-137, Sr-90, and I-131. For this evaluation, the network performance objective was set at achieving a frequency of detection greater than or equal to 95%. Results indicated that the hypothetical network for the resident scenario met all performance objectives for H-3 and I-131 and most performance objectives for Cs-137 and Sr-90. However, all actinides failed to meet the performance objectives for most sources. The shepherd/rancher scenario showed that air samplers placed around the facilities every 22.5 degrees were very effective in detecting releases, but this arrangement is not practical or cost effective. However, it was shown that a few air samplers placed in the prevailing wind direction around each facility could achieve the performance objective of a frequency of detection greater than or equal to 95% for the shepherd/rancher scenario. The results also indicate some of the current sampler locations have little or no impact on the network frequency of detection and could be removed from the network with no appreciable deterioration of performance. Results show that with some slight modifications to the existing network (i.e., additional samplers added north and south of the Materials and Fuels Complex and ineffective samplers removed), the network would achieve performance objectives for all sources for both the resident and shepherd/rancher scenario.« less

Evaluation of the spatial and temporal measurement requirements of remote sensors for monitoring regional air pollution episodes

NASA Technical Reports Server (NTRS)

Burke, H. H. K.; Bowley, C. J.; Barnes, J. C.

1979-01-01

The spatial and temporal measurement requirements of satellite sensors for monitoring regional air pollution episodes were evaluated. Use was made of two sets of data from the Sulfate Regional Experiment (SURE), which provided the first ground-based aerosol measurements from a regional-scale station network. The sulfate data were analyzed for two air pollution episode cases. The results of the analysis indicate that the key considerations required for episode mapping from satellite sensors are the following: (1) detection of sulfate levels exceeding 20 micron-g/cu m; (2) capability to view a broad area (of the order of 1500 km swath) because of regional extent of pollution episodes; (3) spatial resolution sufficient to detect variations in sulfate levels of greater than 10 micron-g/cu m over distances of the order of 50 to 75 km; (4) repeat coverage at least on a daily basis; and (5) satellite observations during the mid to late morning local time, when the sulfate levels have begun to increase after the early morning minimum levels, and convective-type cloud cover has not yet increased to the amount reached later in the afternoon. Analysis of the satellite imagery shows that convective clouds can obscure haze patterns. Additional parameters based on spectral analysis include wavelength and bandwidth requirements.

A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring

NASA Astrophysics Data System (ADS)

Zimmerman, Naomi; Presto, Albert A.; Kumar, Sriniwasa P. N.; Gu, Jason; Hauryliuk, Aliaksei; Robinson, Ellis S.; Robinson, Allen L.; Subramanian, R.

2018-01-01

Low-cost sensing strategies hold the promise of denser air quality monitoring networks, which could significantly improve our understanding of personal air pollution exposure. Additionally, low-cost air quality sensors could be deployed to areas where limited monitoring exists. However, low-cost sensors are frequently sensitive to environmental conditions and pollutant cross-sensitivities, which have historically been poorly addressed by laboratory calibrations, limiting their utility for monitoring. In this study, we investigated different calibration models for the Real-time Affordable Multi-Pollutant (RAMP) sensor package, which measures CO, NO2, O3, and CO2. We explored three methods: (1) laboratory univariate linear regression, (2) empirical multiple linear regression, and (3) machine-learning-based calibration models using random forests (RF). Calibration models were developed for 16-19 RAMP monitors (varied by pollutant) using training and testing windows spanning August 2016 through February 2017 in Pittsburgh, PA, US. The random forest models matched (CO) or significantly outperformed (NO2, CO2, O3) the other calibration models, and their accuracy and precision were robust over time for testing windows of up to 16 weeks. Following calibration, average mean absolute error on the testing data set from the random forest models was 38 ppb for CO (14 % relative error), 10 ppm for CO2 (2 % relative error), 3.5 ppb for NO2 (29 % relative error), and 3.4 ppb for O3 (15 % relative error), and Pearson r versus the reference monitors exceeded 0.8 for most units. Model performance is explored in detail, including a quantification of model variable importance, accuracy across different concentration ranges, and performance in a range of monitoring contexts including the National Ambient Air Quality Standards (NAAQS) and the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. A key strength of the RF approach is that it accounts for pollutant cross-sensitivities. This highlights the importance of developing multipollutant sensor packages (as opposed to single-pollutant monitors); we determined this is especially critical for NO2 and CO2. The evaluation reveals that only the RF-calibrated sensors meet the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. We also demonstrate that the RF-model-calibrated sensors could detect differences in NO2 concentrations between a near-road site and a suburban site less than 1.5 km away. From this study, we conclude that combining RF models with carefully controlled state-of-the-art multipollutant sensor packages as in the RAMP monitors appears to be a very promising approach to address the poor performance that has plagued low-cost air quality sensors.

Comprehensive model-based prediction of micropollutants from diffuse sources in the Swiss river network

NASA Astrophysics Data System (ADS)

Strahm, Ivo; Munz, Nicole; Braun, Christian; Gälli, René; Leu, Christian; Stamm, Christian

2014-05-01

Water quality in the Swiss river network is affected by many micropollutants from a variety of diffuse sources. This study compares, for the first time, in a comprehensive manner the diffuse sources and the substance groups that contribute the most to water contamination in Swiss streams and highlights the major regions for water pollution. For this a simple but comprehensive model was developed to estimate emission from diffuse sources for the entire Swiss river network of 65 000 km. Based on emission factors the model calculates catchment specific losses to streams for more than 15 diffuse sources (such as crop lands, grassland, vineyards, fruit orchards, roads, railways, facades, roofs, green space in urban areas, landfills, etc.) and more than 130 different substances from 5 different substance groups (pesticides, biocides, heavy metals, human drugs, animal drugs). For more than 180 000 stream sections estimates of mean annual pollutant loads and mean annual concentration levels were modeled. This data was validated with a set of monitoring data and evaluated based on annual average environmental quality standards (AA-EQS). Model validation showed that the estimated mean annual concentration levels are within the range of measured data. Therefore simulations were considered as adequately robust for identifying the major sources of diffuse pollution. The analysis depicted that in Switzerland widespread pollution of streams can be expected. Along more than 18 000 km of the river network one or more simulated substances has a concentration exceeding the AA-EQS. In single stream sections it could be more than 50 different substances. Moreover, the simulations showed that in two-thirds of small streams (Strahler order 1 and 2) at least one AA-EQS is always exceeded. The highest number of substances exceeding the AA-EQS are in areas with large fractions of arable cropping, vineyards and fruit orchards. Urban areas are also of concern even without considering wastewater treatment plants. Only a small number of problematic substances are expected from grassland. Landfills and roadways are insignificant within the entire Swiss river network, but may locally lead to considerable water pollution. Considering all substance groups, pesticides and some heavy metals are the main polluters. Many pesticides are expected to exceed AA-EQS and in a substantial percentage of the river network. Modeling a large number of substances from many sources and a huge quantity of stream sections is only possible with a simple model. Nevertheless conclusions are robust and may indicate where and for what kind of substance groups additional efforts for water quality improvements should be undertaken.

International Conference on Environmental Sensing and Assessment, Las Vegas, Nev., September 14-19, 1975, Proceedings. Volumes 1 & 2

NASA Technical Reports Server (NTRS)

1976-01-01

The papers deal with the detection of hazardous environmental pollutants, the development of emission control plans, and the design of compliance monitoring systems. Topics include remote sensing techniques in environmental pollution monitoring, monitoring of atmospheric particulate matter, air pollution due to sulfur dioxide and other inorganic compounds, marine pollution, atmospheric aerosols, industrial pollution, and legal aspects of pollution monitoring. Other papers examine the toxic effects of heavy metals and halogenated hydrocarbons, pollution associated with waste-disposal processes, pesticide residues in soil and groundwater, evaluations of groundwater quality, and monitoring of nuclear wastes. The interaction of climate and pollution is also discussed along with global pollutant transport, environmental modeling, ambient environmental air quality, aircraft and ground-vehicle emissions, and pollution associated with energy extraction and utilization processes. Individual items are announced in this issue.

Offshore platform sourced pollution monitoring using space-borne fully polarimetric C and X band synthetic aperture radar.

PubMed

Singha, Suman; Ressel, Rudolf

2016-11-15

Use of polarimetric SAR data for offshore pollution monitoring is relatively new and shows great potential for operational offshore platform monitoring. This paper describes the development of an automated oil spill detection chain for operational purposes based on C-band (RADARSAT-2) and X-band (TerraSAR-X) fully polarimetric images, wherein we use polarimetric features to characterize oil spills and look-alikes. Numbers of near coincident TerraSAR-X and RADARSAT-2 images have been acquired over offshore platforms. Ten polarimetric feature parameters were extracted from different types of oil and 'look-alike' spots and divided into training and validation dataset. Extracted features were then used to develop a pixel based Artificial Neural Network classifier. Mutual information contents among extracted features were assessed and feature parameters were ranked according to their ability to discriminate between oil spill and look-alike spots. Polarimetric features such as Scattering Diversity, Surface Scattering Fraction and Span proved to be most suitable for operational services. Copyright © 2016 Elsevier Ltd. All rights reserved.

Artificial neural network model for ozone concentration estimation and Monte Carlo analysis

NASA Astrophysics Data System (ADS)

Gao, Meng; Yin, Liting; Ning, Jicai

2018-07-01

Air pollution in urban atmosphere directly affects public-health; therefore, it is very essential to predict air pollutant concentrations. Air quality is a complex function of emissions, meteorology and topography, and artificial neural networks (ANNs) provide a sound framework for relating these variables. In this study, we investigated the feasibility of using ANN model with meteorological parameters as input variables to predict ozone concentration in the urban area of Jinan, a metropolis in Northern China. We firstly found that the architecture of network of neurons had little effect on the predicting capability of ANN model. A parsimonious ANN model with 6 routinely monitored meteorological parameters and one temporal covariate (the category of day, i.e. working day, legal holiday and regular weekend) as input variables was identified, where the 7 input variables were selected following the forward selection procedure. Compared with the benchmarking ANN model with 9 meteorological and photochemical parameters as input variables, the predicting capability of the parsimonious ANN model was acceptable. Its predicting capability was also verified in term of warming success ratio during the pollution episodes. Finally, uncertainty and sensitivity analysis were also performed based on Monte Carlo simulations (MCS). It was concluded that the ANN could properly predict the ambient ozone level. Maximum temperature, atmospheric pressure, sunshine duration and maximum wind speed were identified as the predominate input variables significantly influencing the prediction of ambient ozone concentrations.

Deployment Considerations for Low-cost Air Quality Sensor Networks; Examining Spatial Variability of Gas-Phase Pollutants Around a Building in Los Angeles

NASA Astrophysics Data System (ADS)

Collier-Oxandale, A. M.; Hannigan, M.; Casey, J. G.; Johnston, J.; Coffey, E.; Thorson, J.

2017-12-01

The field of low-cost air quality sensing technologies is growing rapidly through the continual development of new sensors, increased research into sensor performance, and more and more community groups utilizing sensors to investigate local issues. However, as this technology is still in an exploratory phase, there are few `best-practices' available to serve as guidelines for these projects and the standardization of some procedures could benefit the research community as a whole. For example, deployment considerations such as where and how to place a monitor at a given location are often determined by accessibility and safety, power-requirements, and what is an ideal for sampling the target pollutant. Using data from multiple gas-phase sensors, we will examine the importance of siting considerations for low-cost monitoring systems. During a sampling campaign in Los Angeles, a subset of monitors was deployed at one field site to explore the variability in air quality sensor data around a single building. The site is a three story, multi-family housing unit in a primarily residential neighborhood that is near two major roadways and other potential sources of pollution. Five low-cost monitors were co-located prior to and following the field deployment. During the approximately 2.5-month deployment, these monitors were placed at various heights above street level, on different sides of the building, and on the roof. In our analysis, we will examine how monitor placement affects a sensor's ability to detect local verses more regional trends and how this building-scale spatial variability changes over time. Additionally, examining data from VOC sensors (quantified for methane and total non-methane hydrocarbon signals) and O3 sensors will allow us to compare the variability of primary and secondary pollutants. An outcome of this analysis may include guidelines or `best practices' for siting sensors that could aid in ensuring the collection of high quality field data. These may be particularly useful in community-based projects where monitor siting is typically a collaborative process.

Multi-scale modeling of urban air pollution: development of a Street-in-Grid model

NASA Astrophysics Data System (ADS)

Kim, Youngseob; Wu, You; Seigneur, Christian; Roustan, Yelva

2016-04-01

A new multi-scale model of urban air pollution is presented. This model combines a chemical-transport model (CTM) that includes a comprehensive treatment of atmospheric chemistry and transport at spatial scales greater than 1 km and a street-network model that describes the atmospheric concentrations of pollutants in an urban street network. The street-network model is based on the general formulation of the SIRANE model and consists of two main components: a street-canyon component and a street-intersection component. The street-canyon component calculates the mass transfer velocity at the top of the street canyon (roof top) and the mean wind velocity within the street canyon. The estimation of the mass transfer velocity depends on the intensity of the standard deviation of the vertical velocity at roof top. The effect of various formulations of this mass transfer velocity on the pollutant transport at roof-top level is examined. The street-intersection component calculates the mass transfer from a given street to other streets across the intersection. These mass transfer rates among the streets are calculated using the mean wind velocity calculated for each street and are balanced so that the total incoming flow rate is equal to the total outgoing flow rate from the intersection including the flow between the intersection and the overlying atmosphere at roof top. In the default option, the Leighton photostationary cycle among ozone (O3) and nitrogen oxides (NO and NO2) is used to represent the chemical reactions within the street network. However, the influence of volatile organic compounds (VOC) on the pollutant concentrations increases when the nitrogen oxides (NOx) concentrations are low. To account for the possible VOC influence on street-canyon chemistry, the CB05 chemical kinetic mechanism, which includes 35 VOC model species, is implemented in this street-network model. A sensitivity study is conducted to assess the uncertainties associated with the use of the Leighton cycle chemistry. The street-network model is coupled to the CTM Polair3D of the Polyphemus air quality modeling platform to constitute a Street-in-Grid (SinG) model. The street-network model is used to simulate the concentrations of the chemical species in the lowest layer in the urban area and the simulation for the upper layers is then performed by Polair3D. Interactions between the street-network model and the host CTM occur at roof-top and depend on the vertical mass transfer described above. The SinG model is used to simulate the concentrations of gas-phase pollutants (O3 and NOx) in a Paris suburb. The emission data for each street that are needed for the street-network model were obtained from a dynamic traffic model. Topographic data, such as street length/width and building height, were obtained from a geographic database (BD TOPO). Simulated concentrations are compared to concentrations measured at two monitoring stations that were located on each side of a large avenue.

Assessing community exposure to hazardous air pollutants by combining optical remote sensing and "low-cost" sensor technologies

NASA Astrophysics Data System (ADS)

Pikelnaya, O.; Polidori, A.; Wimmer, R.; Mellqvist, J.; Samuelsson, J.; Marianne, E.; Andersson, P.; Brohede, S.; Izos, O.

2017-12-01

Industrial facilities such as refineries and oil processing facilities can be sources of chemicals adversely affecting human health, for example aromatic hydrocarbons and formaldehyde. In an urban setting, such as the South Coast Air Basin (SCAB), exposure to harmful air pollutants (HAP's) for residents of communities neighboring such facilities is of serious concern. Traditionally, exposure assessments are performed by modeling a community exposure using emission inventories and data collected at fixed air monitoring sites. However, recent field measurements found that emission inventories may underestimate HAP emissions from refineries; and HAP measurements data from fixed sites is lacking spatial resolution; as a result, the impact of HAP emissions on communities is highly uncertain. The next generation air monitoring technologies can help address these challenges. For example, dense "low-cost" sensors allow continuous monitoring of concentrations of pollutants within communities with high temporal- and spatial- resolution, and optical remote sensing (ORS) technologies offer measurements of emission fluxes and real-time ground-concentration mapping of HAPs. South Coast Air Quality Management District (SCAQMD) is currently conducting a multi-year study using ORS methods and "low-cost" Volatile Organic Compounds (VOCs) sensors to monitor HAP emissions from selected industrial facilities in the SCAB and their ambient concentrations in neighboring communities. For this purpose, quarterly mobile ORS surveys are conducted to quantify facility-wide emissions for VOCs, aromatic hydrocarbons and HCHO, and to collect ground-concentration profiles of these pollutants inside neighboring communities. Additionally, "low-cost" sensor nodes for deployment in neighborhood(s) downwind of the facilities have been developed in order to obtain long-term, granular data on neighborhood VOC concentrations, During this presentation we will discuss initial results of quarterly ORS surveys and pilot "low-cost" sensor deployments. We will also outline benefits of using a combination of mobile ORS surveys and "low-cost" sensor networks for community exposure monitoring.

Estimating spatio-temporal dynamics of stream total phosphate concentration by soft computing techniques.

PubMed

Chang, Fi-John; Chen, Pin-An; Chang, Li-Chiu; Tsai, Yu-Hsuan

2016-08-15

This study attempts to model the spatio-temporal dynamics of total phosphate (TP) concentrations along a river for effective hydro-environmental management. We propose a systematical modeling scheme (SMS), which is an ingenious modeling process equipped with a dynamic neural network and three refined statistical methods, for reliably predicting the TP concentrations along a river simultaneously. Two different types of artificial neural network (BPNN-static neural network; NARX network-dynamic neural network) are constructed in modeling the dynamic system. The Dahan River in Taiwan is used as a study case, where ten-year seasonal water quality data collected at seven monitoring stations along the river are used for model training and validation. Results demonstrate that the NARX network can suitably capture the important dynamic features and remarkably outperforms the BPNN model, and the SMS can effectively identify key input factors, suitably overcome data scarcity, significantly increase model reliability, satisfactorily estimate site-specific TP concentration at seven monitoring stations simultaneously, and adequately reconstruct seasonal TP data into a monthly scale. The proposed SMS can reliably model the dynamic spatio-temporal water pollution variation in a river system for missing, hazardous or costly data of interest. Copyright © 2016 Elsevier B.V. All rights reserved.

Baseline results from the Lichen Community Indicator Program in the Pacific Northwest: Air quality patterns and evidence of a nitrogen pollution problem

Treesearch

Sarah Jovan

2009-01-01

Why Are Epiphytic Lichen Communities Important? Lichens are one of the bioindicators used by the Forest Inventory and Analysis (FIA) Program to monitor forest health. To obtain data for use in its Lichen Community Indicator Program, FIA samples a regular network of permanent field plots to determine the composition of epiphytic, i.e., tree dwelling, lichen communities...

USGS Tracks Acid Rain

USGS Publications Warehouse

Gordon, John D.; Nilles, Mark A.; Schroder, LeRoy J.

1995-01-01

The U.S. Geological Survey (USGS) has been actively studying acid rain for the past 15 years. When scientists learned that acid rain could harm fish, fear of damage to our natural environment from acid rain concerned the American public. Research by USGS scientists and other groups began to show that the processes resulting in acid rain are very complex. Scientists were puzzled by the fact that in some cases it was difficult to demonstrate that the pollution from automobiles and factories was causing streams or lakes to become more acidic. Further experiments showed how the natural ability of many soils to neutralize acids would reduce the effects of acid rain in some locations--at least as long as the neutralizing ability lasted (Young, 1991). The USGS has played a key role in establishing and maintaining the only nationwide network of acid rain monitoring stations. This program is called the National Atmospheric Deposition Program/National Trends Network (NADP/NTN). Each week, at approximately 220 NADP/NTN sites across the country, rain and snow samples are collected for analysis. NADP/NTN site in Montana. The USGS supports about 72 of these sites. The information gained from monitoring the chemistry of our nation's rain and snow is important for testing the results of pollution control laws on acid rain.

Black Carbon Measurements From Ireland's Transboundary Network (TXB)

NASA Astrophysics Data System (ADS)

Spohn, T. K.; Martin, D.; O'Dowd, C. D. D.

2017-12-01

Black Carbon (BC) is carbonaceous aerosol formed by incomplete fossil fuel combustion. Named for its light absorbing properties, it acts to trap heat in the atmosphere, thus behaving like a greenhouse gas, and is considered a strong, short-lived climate forcer by the International Panel on Climate Change (IPCC). Carbonaceous aerosols from biomass burning (BB) such as forest fires and residential wood burning, also known as brown carbon, affect the ultra violet (UV) light absorption in the atmosphere as well. In 2016 a three node black carbon monitoring network was established in Ireland as part of a Transboundary Monitoring Network (TXB). The three sites (Mace Head, Malin Head, and Carnsore Point) are coastal locations on opposing sides of the country, and offer the opportunity to assess typical northern hemispheric background concentrations as well national and European pollution events. The instruments deployed in this network (Magee Scientific AE33) facilitate elimination of the changes in response due to `aerosol loading' effects; and a real-time calculation of the `loading compensation' parameter which offers insights into aerosol optical properties. Additionally, these instruments have an inbuilt algorithm, which estimates the difference in absorption in the ultraviolet wavelengths (mostly by brown carbon) and the near infrared wavelengths (only by black carbon).Presented here are the first results of the BC measurements from the three Irish stations, including instrument validation, seasonal variation as well as local, regional, and transboundary influences based on air mass trajectories as well as concurrent in-situ observations (meteorological parameters, particle number, and aerosol composition). A comparison of the instrumental algorithm to off-line sensitivity calculations will also be made to assess the contribution of biomass burning to BC pollution events.

A Proposed Community Network For Monitoring Volcanic Emissions In Saint Lucia, Lesser Antilles

NASA Astrophysics Data System (ADS)

Joseph, E. P.; Beckles, D. M.; Robertson, R. E.; Latchman, J. L.; Edwards, S.

2013-12-01

Systematic geochemical monitoring of volcanic systems in the English-speaking islands of the Lesser Antilles was initiated by the UWI Seismic Research Centre (SRC) in 2000, as part of its volcanic surveillance programme for the English-speaking islands of the Lesser Antilles. This programme provided the first time-series observations used for the purpose of volcano monitoring in Dominica and Saint Lucia, permitted the characterization of the geothermal fluids associated with them, and established baseline studies for understanding of the hydrothermal systems during periods of quiescence (Joseph et al., 2011; Joseph et al., 2013). As part of efforts to improve and expand the capacity of SRC to provide volcanic surveillance through its geothermal monitoring programme, it is necessary to develop economically sustainable options for the monitoring of volcanic emissions/pollutants. Towards this effort we intend to work in collaboration with local authorities in Saint Lucia, to develop a monitoring network for quantifying the background exposure levels of ambient concentrations of volcanic pollutants, SO2 in air and As in waters (as health significant marker elements in the geothermal emissions) that would serve as a model for the emissions monitoring network for other volcanic islands. This programme would facilitate the building of local capacity and training to monitor the hazardous exposure, through the application and transfer of a regionally available low-cost and low-technology SO2 measurement/detection system in Saint Lucia. Existing monitoring technologies to inform evidence based health practices are too costly for small island Caribbean states, and no government policies or health services measures currently exist to address/mitigate these influences. Gases, aerosols and toxic elements from eruptive and non-eruptive volcanic activity are known to adversely affect human health and the environment (Baxter, 2000; Zhang et al., 2008). Investigations into the impact of volcanic emissions on health have been almost exclusively focused on acute responses, or the effects of one-off eruptions (Horwell and Baxter, 2006). However, little attention has been paid to any long-term impacts on human health in the population centers around volcanoes as a result of exposure to passive emissions from active geothermal systems. The role of volcano tourism is also recognized as an important contributor to the economy of volcanic islands in the Lesser Antilles. However, if it is to be promoted as a sustainable sector of the tourism industry tourists, tour guides, and vendors must be made aware of the potential health hazards facing them in volcanic environments.

Developing a Composite Aquifer Vulnerability Assessment Model Combining DRASTIC with Agricultural Land Use in Choushui River Alluvial Fan, Central Taiwan

NASA Astrophysics Data System (ADS)

Chen, Shih-Kai; Hsieh, Chih-Heng; Tsai, Cheng-Bin

2017-04-01

Aquifer vulnerability assessment is considered to be an effective tool in controlling potential pollution which is critical for groundwater management. The Choushui River alluvial fan, located in central Taiwan, is an agricultural area with complex crop patterns and various irrigation schemes, which increased the difficulties in groundwater resource management. The aim of this study is to propose an integrated methodology to assess shallow groundwater vulnerability by including land-use impact on groundwater potential pollution. The original groundwater vulnerability methodology, DRASTIC, was modified by adding a land-use parameter in order to assess groundwater vulnerability under intense agricultural activities. To examine the prediction capacity of pollution for the modified DRASTIC model, various risk categories of contamination potentials were compared with observed nitrate-N obtained from groundwater monitoring network. It was found that for the original DRASTIC vulnerability map, some areas with low nitrate-N concentrations are covered within the high vulnerability areas, especially in the northern part of mid-fan areas, where rice paddy is the main crop and planted for two crop seasons per year. The low nitrate-N contamination potential of rice paddies may be resulted from the denitrification in the reduced root zone. By reducing the rating for rice paddies, the modified model was proved to be capable of increasing the precise of prediction in study area. The results can provide a basis for groundwater monitoring network design and effective preserve measures formulation in the mixed agricultural area. Keyword:Aquifer Vulnerability, Groundwater, DRASTIC, Nitrate-N

Effectiveness of traffic-related elements in tree bark and pollen abortion rates for assessing air pollution exposure on respiratory mortality rates.

PubMed

Carvalho-Oliveira, Regiani; Amato-Lourenço, Luís F; Moreira, Tiana C L; Silva, Douglas R Rocha; Vieira, Bruna D; Mauad, Thais; Saiki, Mitiko; Saldiva, Paulo H Nascimento

2017-02-01

The majority of epidemiological studies correlate the cardiorespiratory effects of air pollution exposure by considering the concentrations of pollutants measured from conventional monitoring networks. The conventional air quality monitoring methods are expensive, and their data are insufficient for providing good spatial resolution. We hypothesized that bioassays using plants could effectively determine pollutant gradients, thus helping to assess the risks associated with air pollution exposure. The study regions were determined from different prevalent respiratory death distributions in the Sao Paulo municipality. Samples of tree flower buds were collected from twelve sites in four regional districts. The genotoxic effects caused by air pollution were tested through a pollen abortion bioassay. Elements derived from vehicular traffic that accumulated in tree barks were determined using energy-dispersive X-ray fluorescence spectrometry (EDXRF). Mortality data were collected from the mortality information program of Sao Paulo City. Principal component analysis (PCA) was applied to the concentrations of elements accumulated in tree barks. Pearson correlation and exponential regression were performed considering the elements, pollen abortion rates and mortality data. PCA identified five factors, of which four represented elements related to vehicular traffic. The elements Al, S, Fe, Mn, Cu, and Zn showed a strong correlation with mortality rates (R 2 >0.87) and pollen abortion rates (R 2 >0.82). These results demonstrate that tree barks and pollen abortion rates allow for correlations between vehicular traffic emissions and associated outcomes such as genotoxic effects and mortality data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Exposure of Paris taxi drivers to automobile air pollutants within their vehicles

PubMed Central

Zagury, E.; Le Moullec, Y.; Momas, I.

2000-01-01

OBJECTIVES—To study the exposure of Parisian taxi drivers to automobile air pollutants during their professional activity.
METHODS—A cross sectional study was carried out from 27 January to 27 March 1997, with measurements performed in the vehicles of 29 randomly selected drivers. Carbon monoxide (CO) content was measured over an 8 hour period by a CO portable monitor. The fine suspended particles were measured according to the black smoke index (BS), with a flow controlled portable pump provided with a cellulose filter. The nitrogen oxides, NO and NO2 were measured with a passive sampler.
RESULTS—These drivers are exposed during their professional activity to relatively high concentrations of pollutants (mean, median (SD) 3.8, 2 (1.7) ppm for CO, 168, 164 (53) µg/m3 for BS, 625, 598 (224) µg/m3 for NO, and 139, 131 (43) µg/m3 for NO2.) For CO the concentrations were clearly lower than the threshold values recommended by the World Health Organisation. The situation is less satisfactory for the other pollutants, especially for the BS index. All concentrations of pollutants recorded were noticeably higher than concentrations in air recorded by the ambient Parisian air monitoring network and were close to, or slightly exceeded, the concentrations measured at the fixed stations close to automobile traffic. Pollutant concentrations were also influenced greatly by weather conditions.
CONCLUSION—This first French study conducted in taxi drivers shows that they are highly exposed to automobile pollutants. The results would justify a medical follow up of this occupational group.


Keywords: taxi drivers; exposure assessment PMID:10810130

Quantitative Assessment of Detection Frequency for the INL Ambient Air Monitoring Network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sondrup, A. Jeffrey; Rood, Arthur S.

A quantitative assessment of the Idaho National Laboratory (INL) air monitoring network was performed using frequency of detection as the performance metric. The INL air monitoring network consists of 37 low-volume air samplers in 31 different locations. Twenty of the samplers are located on INL (onsite) and 17 are located off INL (offsite). Detection frequencies were calculated using both BEA and ESER laboratory minimum detectable activity (MDA) levels. The CALPUFF Lagrangian puff dispersion model, coupled with 1 year of meteorological data, was used to calculate time-integrated concentrations at sampler locations for a 1-hour release of unit activity (1 Ci) formore » every hour of the year. The unit-activity time-integrated concentration (TICu) values were calculated at all samplers for releases from eight INL facilities. The TICu values were then scaled and integrated for a given release quantity and release duration. All facilities modeled a ground-level release emanating either from the center of the facility or at a point where significant emissions are possible. In addition to ground-level releases, three existing stacks at the Advanced Test Reactor Complex, Idaho Nuclear Technology and Engineering Center, and Material and Fuels Complex were also modeled. Meteorological data from the 35 stations comprising the INL Mesonet network, data from the Idaho Falls Regional airport, upper air data from the Boise airport, and three-dimensional gridded data from the weather research forecasting model were used for modeling. Three representative radionuclides identified as key radionuclides in INL’s annual National Emission Standards for Hazardous Air Pollutants evaluations were considered for the frequency of detection analysis: Cs-137 (beta-gamma emitter), Pu-239 (alpha emitter), and Sr-90 (beta emitter). Source-specific release quantities were calculated for each radionuclide, such that the maximum inhalation dose at any publicly accessible sampler or the National Emission Standards for Hazardous Air Pollutants maximum exposed individual location (i.e., Frenchman’s Cabin) was no more than 0.1 mrem yr–1 (i.e., 1% of the 10 mrem yr–1 standard). Detection frequencies were calculated separately for the onsite and offsite monitoring network. As expected, detection frequencies were generally less for the offsite sampling network compared to the onsite network. Overall, the monitoring network is very effective at detecting the potential releases of Cs-137 or Sr-90 from all sources/facilities using either the ESER or BEA MDAs. The network was less effective at detecting releases of Pu-239. Maximum detection frequencies for Pu-239 using ESER MDAs ranged from 27.4 to 100% for onsite samplers and 3 to 80% for offsite samplers. Using BEA MDAs, the maximum detection frequencies for Pu-239 ranged from 2.1 to 100% for onsite samplers and 0 to 5.9% for offsite samplers. The only release that was not detected by any of the samplers under any conditions was a release of Pu-239 from the Idaho Nuclear Technology and Engineering Center main stack (CPP-708). The methodology described in this report could be used to improve sampler placement and detection frequency, provided clear performance objectives are defined.« less

Using Google Location History to track personal exposure to air pollution

NASA Astrophysics Data System (ADS)

Marais, E. A.; Wiedinmyer, C.

2017-12-01

Big data is increasingly used in air pollution research to monitor air quality and develop mitigation strategies. Google Location History provides an archive of geolocation and time information from mobile devices that can be used to track personal exposure to air pollution. Here we demonstrate the utility of Google Location History for assessing true exposure of individuals to air pollution hazardous to human health in an increasingly mobile world. We use the GEOS-Chem chemical transport model at coarse resolution (2° × 2.5°; latitude × longitude) to calculate and sample surface concentrations of fine particle mass (PM2.5) and ozone concentrations at the same time and location of each of six volunteers for 2 years (June 2015 to May 2017) and compare this to annual mean PM2.5 and ozone estimated at their postal addresses. The latter is synonymous with Global Burden of Disease studies that use a static population distribution map. We find that mobile PM2.5 is higher than static PM2.5 for most (five out of six) volunteers and can lead to a 10% increase in the risk for ischemic heart disease and stroke mortality. The difference may be more if instead a high resolution CTM or an abundant air quality monitoring network is used. There is tremendous potential to exploit geolocation and time data from mobile devices for cohort health studies and to determine best practices for limiting personal exposure to air pollution.

Operational evaluation of the RLINE dispersion model for studies of traffic-related air pollutants

NASA Astrophysics Data System (ADS)

Milando, Chad W.; Batterman, Stuart A.

2018-06-01

Exposure to traffic-related air pollutants (TRAP) remains a key public health issue, and improved exposure measures are needed to support health impact and epidemiologic studies and inform regulatory responses. The recently developed Research LINE source model (RLINE), a Gaussian line source dispersion model, has been used in several epidemiologic studies of TRAP exposure, but evaluations of RLINE's performance in such applications have been limited. This study provides an operational evaluation of RLINE in which predictions of NOx, CO and PM2.5 are compared to observations at air quality monitoring stations located near high traffic roads in Detroit, MI. For CO and NOx, model performance was best at sites close to major roads, during downwind conditions, during weekdays, and during certain seasons. For PM2.5, the ability to discern local and particularly the traffic-related portion was limited, a result of high background levels, the sparseness of the monitoring network, and large uncertainties for certain processes (e.g., formation of secondary aerosols) and non-mobile sources (e.g., area, fugitive). Overall, RLINE's performance in near-road environments suggests its usefulness for estimating spatially- and temporally-resolved exposures. The study highlights considerations relevant to health impact and epidemiologic applications, including the importance of selecting appropriate pollutants, using appropriate monitoring approaches, considering prevailing wind directions during study design, and accounting for uncertainty.

The spatiotemporal inhomogeneity of pollutant concentrations and its dependence on regional weather conditions in a coastal city of China.

PubMed

Zhou, Baohua; Yu, Lejiang; Zhong, Shiyuan; Bian, Xindi

2018-04-02

Hourly data for sulfur dioxide (SO 2 ), nitrogen oxides (NO x ), and inhalable particulate matter (PM 10 ) over a 33-month period from a network of air quality monitoring stations across Qingdao, a major coastal city in eastern China, along with surface and upper-air meteorological data, are used to characterize the spatiotemporal variability of these pollutants in the region and the role of meteorological conditions play in pollution episodes. Large differences in the concentrations of all three pollutants are found between densely populated or industrial areas and suburban commercial or residential or coastal tourist areas, but the differences are relatively small between older and newer parts of the residential-commercial areas and between old and newly developed industrial areas. Wavelet analyses revealed a strong seasonal cycle for all three pollutants, introseasonal variability with a periodicity depending on pollutant and location, and diurnal and a semi-diurnal variability with season-dependent amplitude and phase. Low wind speed is found to be the leading factor for pollution buildup in the region. These results may prove useful for urban planning and development and implementation of effective air pollution control strategies for other coastal regions with economic development similar to Qingdao.

Assessment of regional air quality by a concentration-dependent Pollution Permeation Index

PubMed Central

Liang, Chun-Sheng; Liu, Huan; He, Ke-Bin; Ma, Yong-Liang

2016-01-01

Although air quality monitoring networks have been greatly improved, interpreting their expanding data in both simple and efficient ways remains challenging. Therefore, needed are new analytical methods. We developed such a method based on the comparison of pollutant concentrations between target and circum areas (circum comparison for short), and tested its applications by assessing the air pollution in Jing-Jin-Ji, Yangtze River Delta, Pearl River Delta and Cheng-Yu, China during 2015. We found the circum comparison can instantly judge whether a city is a pollution permeation donor or a pollution permeation receptor by a Pollution Permeation Index (PPI). Furthermore, a PPI-related estimated concentration (original concentration plus halved average concentration difference) can be used to identify some overestimations and underestimations. Besides, it can help explain pollution process (e.g., Beijing’s PM2.5 maybe largely promoted by non-local SO2) though not aiming at it. Moreover, it is applicable to any region, easy-to-handle, and able to boost more new analytical methods. These advantages, despite its disadvantages in considering the whole process jointly influenced by complex physical and chemical factors, demonstrate that the PPI based circum comparison can be efficiently used in assessing air pollution by yielding instructive results, without the absolute need for complex operations. PMID:27731344

Preliminary results of the aerosol optical depth retrieval in Johor, Malaysia

NASA Astrophysics Data System (ADS)

Lim, H. Q.; Kanniah, K. D.; Lau, A. M. S.

2014-02-01

Monitoring of atmospheric aerosols over the urban area is important as tremendous amounts of pollutants are released by industrial activities and heavy traffic flow. Air quality monitoring by satellite observation provides better spatial coverage, however, detailed aerosol properties retrieval remains a challenge. This is due to the limitation of aerosol retrieval algorithm on high reflectance (bright surface) areas. The aim of this study is to retrieve aerosol optical depth over urban areas of Iskandar Malaysia; the main southern development zone in Johor state, using Moderate Resolution Imaging Spectroradiometer (MODIS) 500 m resolution data. One of the important steps is the aerosol optical depth retrieval is to characterise different types of aerosols in the study area. This information will be used to construct a Look Up Table containing the simulated aerosol reflectance and corresponding aerosol optical depth. Thus, in this study we have characterised different aerosol types in the study area using Aerosol Robotic Network (AERONET) data. These data were processed using cluster analysis and the preliminary results show that the area is consisting of coastal urban (65%), polluted urban (27.5%), dust particles (6%) and heavy pollution (1.5%) aerosols.

Estimation of Chinese surface NO2 concentrations combining satellite data and Land Use Regression

NASA Astrophysics Data System (ADS)

Anand, J.; Monks, P.

2016-12-01

Monitoring surface-level air quality is often limited by in-situ instrument placement and issues arising from harmonisation over long timescales. Satellite instruments can offer a synoptic view of regional pollution sources, but in many cases only a total or tropospheric column can be measured. In this work a new technique of estimating surface NO2 combining both satellite and in-situ data is presented, in which a Land Use Regression (LUR) model is used to create high resolution pollution maps based on known predictor variables such as population density, road networks, and land cover. By employing a mixed effects approach, it is possible to take advantage of the spatiotemporal variability in the satellite-derived column densities to account for daily and regional variations in surface NO2 caused by factors such as temperature, elevation, and wind advection. In this work, surface NO2 maps are modelled over the North China Plain and Pearl River Delta during high-pollution episodes by combining in-situ measurements and tropospheric columns from the Ozone Monitoring Instrument (OMI). The modelled concentrations show good agreement with in-situ data and surface NO2 concentrations derived from the MACC-II global reanalysis.

A Comparative Study of Three Spatial Interpolation Methodologies for the Analysis of Air Pollution Concentrations in Athens, Greece

NASA Astrophysics Data System (ADS)

Deligiorgi, Despina; Philippopoulos, Kostas; Thanou, Lelouda; Karvounis, Georgios

2010-01-01

Spatial interpolation in air pollution modeling is the procedure for estimating ambient air pollution concentrations at unmonitored locations based on available observations. The selection of the appropriate methodology is based on the nature and the quality of the interpolated data. In this paper, an assessment of three widely used interpolation methodologies is undertaken in order to estimate the errors involved. For this purpose, air quality data from January 2001 to December 2005, from a network of seventeen monitoring stations, operating at the greater area of Athens in Greece, are used. The Nearest Neighbor and the Liner schemes were applied to the mean hourly observations, while the Inverse Distance Weighted (IDW) method to the mean monthly concentrations. The discrepancies of the estimated and measured values are assessed for every station and pollutant, using the correlation coefficient, the scatter diagrams and the statistical residuals. The capability of the methods to estimate air quality data in an area with multiple land-use types and pollution sources, such as Athens, is discussed.

National review of ambient air toxics observations.

PubMed

Strum, Madeleine; Scheffe, Richard

2016-02-01

Ambient air observations of hazardous air pollutant (HAPs), also known as air toxics, derived from routine monitoring networks operated by states, local agencies, and tribes (SLTs), are analyzed to characterize national concentrations and risk across the nation for a representative subset of the 187 designated HAPs. Observations from the National Air Toxics Trend Sites (NATTS) network of 27 stations located in most major urban areas of the contiguous United States have provided a consistent record of HAPs that have been identified as posing the greatest risk since 2003 and have also captured similar concentration patterns of nearly 300 sites operated by SLTs. Relatively high concentration volatile organic compounds (VOCs) such as benzene, formaldehyde, and toluene exhibit the highest annual average concentration levels, typically ranging from 1 to 5 µg/m(3). Halogenated (except for methylene chloride) and semivolatile organic compounds (SVOCs) and metals exhibit concentrations typically 2-3 orders of magnitude lower. Formaldehyde is the highest national risk driver based on estimated cancer risk and, nationally, has not exhibited significant changes in concentration, likely associated with the large pool of natural isoprene and formaldehyde emissions. Benzene, toluene, ethylbenzene, and 1,3-butadiene are ubiquitous VOC HAPs with large mobile source contributions that continue to exhibit declining concentrations over the last decade. Common chlorinated organic compounds such as ethylene dichloride and methylene chloride exhibit increasing concentrations. The variety of physical and chemical attributes and measurement technologies across 187 HAPs result in a broad range of method detection limits (MDLs) and cancer risk thresholds that challenge confidence in risk results for low concentration HAPs with MDLs near or greater than risk thresholds. From a national monitoring network perspective, the ability of the HAPs observational database to characterize the multiple pollutant and spatial scale patterns influencing exposure is severely limited and positioned to benefit by leveraging a variety of emerging measurement technologies. Ambient air toxics observation networks have limited ability to characterize the broad suite of hazardous air pollutants (HAPs) that affect exposures across multiple spatial scales. While our networks are best suited to capture major urban-scale signals of ubiquitous volatile organic compound HAPs, incorporation of sensing technologies that address regional and local-scale exposures should be pursued to address major gaps in spatial resolution. Caution should be exercised in interpreting HAPs observations based on data proximity to minimum detection limit and risk thresholds.

Cyclist route choice, traffic-related air pollution, and lung function: a scripted exposure study

PubMed Central

2013-01-01

Background A travel mode shift to active transportation such as bicycling would help reduce traffic volume and related air pollution emissions as well as promote increased physical activity level. Cyclists, however, are at risk for exposure to vehicle-related air pollutants due to their proximity to vehicle traffic and elevated respiratory rates. To promote safe bicycle commuting, the City of Berkeley, California, has designated a network of residential streets as “Bicycle Boulevards.” We hypothesized that cyclist exposure to air pollution would be lower on these Bicycle Boulevards when compared to busier roads and this elevated exposure may result in reduced lung function. Methods We recruited 15 healthy adults to cycle on two routes – a low-traffic Bicycle Boulevard route and a high-traffic route. Each participant cycled on the low-traffic route once and the high-traffic route once. We mounted pollutant monitors and a global positioning system (GPS) on the bicycles. The monitors were all synced to GPS time so pollutant measurements could be spatially plotted. We measured lung function using spirometry before and after each bike ride. Results We found that fine and ultrafine particulate matter, carbon monoxide, and black carbon were all elevated on the high-traffic route compared to the low-traffic route. There were no corresponding changes in the lung function of healthy non-asthmatic study subjects. We also found that wind-speed affected pollution concentrations. Conclusions These results suggest that by selecting low-traffic Bicycle Boulevards instead of heavily trafficked roads, cyclists can reduce their exposure to vehicle-related air pollution. The lung function results indicate that elevated pollutant exposure may not have acute negative effects on healthy cyclists, but further research is necessary to determine long-term effects on a more diverse population. This study and broader field of research have the potential to encourage policy-makers and city planners to expand infrastructure to promote safe and healthy bicycle commuting. PMID:23391029

Cyclist route choice, traffic-related air pollution, and lung function: a scripted exposure study.

PubMed

Jarjour, Sarah; Jerrett, Michael; Westerdahl, Dane; de Nazelle, Audrey; Hanning, Cooper; Daly, Laura; Lipsitt, Jonah; Balmes, John

2013-02-07

A travel mode shift to active transportation such as bicycling would help reduce traffic volume and related air pollution emissions as well as promote increased physical activity level. Cyclists, however, are at risk for exposure to vehicle-related air pollutants due to their proximity to vehicle traffic and elevated respiratory rates. To promote safe bicycle commuting, the City of Berkeley, California, has designated a network of residential streets as "Bicycle Boulevards." We hypothesized that cyclist exposure to air pollution would be lower on these Bicycle Boulevards when compared to busier roads and this elevated exposure may result in reduced lung function. We recruited 15 healthy adults to cycle on two routes - a low-traffic Bicycle Boulevard route and a high-traffic route. Each participant cycled on the low-traffic route once and the high-traffic route once. We mounted pollutant monitors and a global positioning system (GPS) on the bicycles. The monitors were all synced to GPS time so pollutant measurements could be spatially plotted. We measured lung function using spirometry before and after each bike ride. We found that fine and ultrafine particulate matter, carbon monoxide, and black carbon were all elevated on the high-traffic route compared to the low-traffic route. There were no corresponding changes in the lung function of healthy non-asthmatic study subjects. We also found that wind-speed affected pollution concentrations. These results suggest that by selecting low-traffic Bicycle Boulevards instead of heavily trafficked roads, cyclists can reduce their exposure to vehicle-related air pollution. The lung function results indicate that elevated pollutant exposure may not have acute negative effects on healthy cyclists, but further research is necessary to determine long-term effects on a more diverse population. This study and broader field of research have the potential to encourage policy-makers and city planners to expand infrastructure to promote safe and healthy bicycle commuting.

Advances in Satellite Remote Sensing of Particulate Air Pollution: From MISR to MAIA

NASA Astrophysics Data System (ADS)

Diner, D. J.; Burke, K.; Xu, F.; Garay, M. J.; Kalashnikova, O. V.; Liu, Y.; Meng, X.; Wang, J.; Martin, R.; Ostro, B.

2017-12-01

Airborne particulate matter (PM) is a well-known cause of cardiovascular and respiratory disease. To estimate human exposure to PM pollution, satellite instruments such as the Terra Multi-angle Imaging SpectroRadiometer (MISR) and the Moderate resolution Imaging Spectroradiometer (MODIS) have been used in conjunction with surface monitors to map near-surface PM concentrations. The relative toxicity of different size and compositional mixtures of PM is not well understood. To address this, we are developing the Multi-Angle Imager for Aerosols (MAIA) investigation. The satellite instrument extends MISR's multiangular visible and near-infrared (VNIR) spectral coverage to 14 bands in the ultraviolet, VNIR, and shortwave IR; three of the bands are polarimetric to enhance sensitivity to aerosol size and composition. To constrain the retrievals, the observations will be combined with data from surface monitors and the WRF-Chem and GEOS-Chem chemical transport models. Existing surface PM speciation monitors will be supplemented by adding new stations to the Surface PARTiculate mAtter Network (SPARTAN). Unlike MISR, MAIA is a targeting instrument. Primary areas of interest include metropolitan areas in North and South America, Europe, the Middle East, Africa, India, and East Asia. PM retrieval algorithms are being developed using data from MISR and the high-altitude Airborne Multiangle SpectroPolarimetric Imager (AirMSPI). Epidemiologists on the MAIA science team will use the derived PM data products and birth, death, and hospital records to investigate adverse health impacts of different types of airborne particulates. MAIA's earliest possible launch date is mid-2020, making it possible for the data to be complemented by global observations from Terra as well as high temporal resolution atmospheric chemistry measurements from TEMPO (Tropospheric Emissions: Monitoring Pollution), GEMS (Geostationary Environment Monitoring Spectrometer), and Sentinel-4.

The investigation of using 5G millimeter-wave communications links for environmental monitoring

NASA Astrophysics Data System (ADS)

Han, Congzheng

2017-04-01

There has been significantly increasing recognition that millimeter waves from 30 GHz to 300 GHz as carriers for future 5G cellular networks. This is good for high speed, line-of-sight communication, potentially using very densely deployed infrastructure involving many small cells. High resolution, continuous and accurate monitoring of environmental conditions, such as rainfall and water vapor are of great important to meteorology, hydrology (e.g. flood warning), agriculture, environmental policy (e.g. pollution regulation) and weather forecasting. We have built a 28GHz measurement link at our research institute in central Beijing, China. This work will study the potential of using millimeter wave based wireless links to monitor environmental conditions including rainfall and water vapor.

Spectrally encoded optical fibre sensor systems and their application in process control, environmental and structural monitoring

NASA Astrophysics Data System (ADS)

Willsch, Reinhardt; Ecke, Wolfgang; Schwotzer, Gunter

2005-09-01

Different types of advanced optical fibre sensor systems using similar spectral interrogation principles and potential low-cost polychromator optoelectronic signal processing instrumentation will be presented, and examples of their industrial application are demonstrated. These are such sensors as multimode fibre based humidity, temperature, and pressure sensors with extrinsic microoptical Fabry-Perot transducers for process control in gas industry, UV absorption evanescent field sensors for organic pollution monitoring in groundwater, and single mode fibre Bragg grating (FBG) multiplexed strain & vibration and temperature sensor networks for structural health monitoring applications in electric power facilities, aerospace, railways, geotechnical and civil engineering. Recent results of current investigations applying FBGs and microstructured fibres for chemical sensing will be discussed.

Five Years of BEACO2N: First Results and Lessons Learned

NASA Astrophysics Data System (ADS)

Shusterman, A.; Cohen, R. C.

2017-12-01

The BErkeley Atmospheric CO2 Observation Network (BEACO2N) is an ongoing greenhouse gas and air quality monitoring campaign based in the San Francisco Bay Area of Northern California. BEACO2N is a distributed network instrument consisting of low- to moderate-cost commercial sensors for CO2 and other pollutants installed on top of schools, museums, and other outreach-minded institutions. The reduced cost of each individual sensor "node" enables the deployment of a larger volume of total nodes, resulting in a web of approximately 50 sites with an average node-to-node distance of 2 km. Operating in some variation of this configuration since 2012, BEACO2N offers greater spatio-temporal coverage than any other fixed CO2 monitoring network to date. This high-resolution information allows us to faithfully represent the true heterogeneity of urban emission processes and distinguish between specific sources that are often regulated independently, but typically treated en masse by sparser, conventional surface monitors. However, maintaining and appropriately interpreting a network of BEACO2N's size presents a number of unique data quality and data coverage challenges. Here we describe the quantitative capabilities of the BEACO2N platform, first results from initial attempts at constraining greenhouse gas emission estimates, as well as other lessons learned over the first five years of operation.

The development of an ecological approach to manage the pollution risk from highway runoff.

PubMed

Crabtree, B; Dempsey, P; Johnson, I; Whitehead, M

2009-01-01

In the UK, the Highways Agency is responsible for operating, maintaining and improving the strategic road network in England. One focus of the Highways Agency's ongoing research into the nature and impact of highway runoff is aimed at ensuring that the Highways Agency will meet the requirements of the EU Water Framework Directive. A research programme, undertaken in partnership with the Environment Agency, is in progress to develop a better understanding of pollutants in highway runoff and their ecological impact. The paper presents the outcome of a study to: (1) monitor pollutants in highway runoff under different climate and traffic conditions; (2) develop standards to assess potential ecological risks from soluble pollutants in highway runoff; and (3) develop a model to predict pollutant concentrations in highway runoff. The model has been embedded in a design tool incorporating risk assessment procedures and receiving water standards for soluble and insoluble pollutants--the latter has been developed elsewhere in another project within the research programme. The design tool will be used to support improved guidance on where, and to what level, treatment of runoff is required for highway designers to manage the risk of ecological impact from highway runoff.

National-scale exposure prediction for long-term concentrations of particulate matter and nitrogen dioxide in South Korea.

PubMed

Kim, Sun-Young; Song, Insang

2017-07-01

The limited spatial coverage of the air pollution data available from regulatory air quality monitoring networks hampers national-scale epidemiological studies of air pollution. The present study aimed to develop a national-scale exposure prediction model for estimating annual average concentrations of PM 10 and NO 2 at residences in South Korea using regulatory monitoring data for 2010. Using hourly measurements of PM 10 and NO 2 at 277 regulatory monitoring sites, we calculated the annual average concentrations at each site. We also computed 322 geographic variables in order to represent plausible local and regional pollution sources. Using these data, we developed universal kriging models, including three summary predictors estimated by partial least squares (PLS). The model performance was evaluated with fivefold cross-validation. In sensitivity analyses, we compared our approach with two alternative approaches, which added regional interactions and replaced the PLS predictors with up to ten selected variables. Finally, we predicted the annual average concentrations of PM 10 and NO 2 at 83,463 centroids of residential census output areas in South Korea to investigate the population exposure to these pollutants and to compare the exposure levels between monitored and unmonitored areas. The means of the annual average concentrations of PM 10 and NO 2 for 2010, across regulatory monitoring sites in South Korea, were 51.63 μg/m3 (SD = 8.58) and 25.64 ppb (11.05), respectively. The universal kriging exposure prediction models yielded cross-validated R 2 s of 0.45 and 0.82 for PM 10 and NO 2 , respectively. Compared to our model, the two alternative approaches gave consistent or worse performances. Population exposure levels in unmonitored areas were lower than in monitored areas. This is the first study that focused on developing a national-scale point wise exposure prediction approach in South Korea, which will allow national exposure assessments and epidemiological research to answer policy-related questions and to draw comparisons among different countries. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessing the Value of Enhancing AirNow Data with NASA Satellite Data

NASA Astrophysics Data System (ADS)

Pasch, A. N.; Burke, B.; Huang, S.; Dye, T.; Dawes, S. S.; DeWinter, J. L.; Zahn, P. H.; Haderman, M.; Szykman, J.; White, J. E.; Dickerson, P.; van Donkelaar, A.; Martin, R.

2013-12-01

We will describe the methodology and findings from a study that addressed how satellite-enhanced air quality information provided through the U.S. Environmental Protection Agency's (EPA) AirNow Satellite Data Processor (ASDP) program could contribute to greater socioeconomic benefits. This study was funded by the National Aeronautics and Space Administration (NASA) and conducted, in partnership with the EPA, by the Center for Technology in Government at the University at Albany (CTG) and Sonoma Technology, Inc. (STI). AirNow is the national repository of real-time air quality data and forecasts for the United States. While mainly a public outreach and awareness tool, AirNow relies on the same network of ground-based air quality monitors that is used by federal, state, local, and tribal governments throughout the United States. Extensive as the monitoring network is, considerable gaps exist in certain parts of the United States. Even areas with monitors considered adequate for regulatory purposes can lack information needed to resolve localized air quality issues or give forecasters sufficient confidence about the potential air quality impact of specific events. Monitors are expensive to deploy and maintain; thus, EPA is seeking other ways to improve coverage and detail. Satellite-estimated data can provide information for many places where ground monitors do not exist, and supplement ground monitors, providing additional information for use in analysis and forecasting. ASDP uses satellite-derived estimates for fine-particle pollution (PM2.5) and provides coverage for a small window of time during the day. As satellite capabilities improve in terms of different types of sensors and increased coverage throughout the day, the ASDP program is prepared to extend its scope to additional pollutants and provide greater enhancements to the ground-based networks. In this study, CTG assessed the socioeconomic benefits of air quality data at a community level through three case studies in the Denver, Atlanta, and Kansas City regions by interviewing people at EPA regional offices, state environmental and public health agencies, local public health authorities, regional planning and non-profit outreach organizations, and universities. The interviews focused on the existing uses of air quality information and the potential value of incorporating NASA satellite-enhanced AirNow data to support and enhance the missions of the organizations interviewed. STI analyzed the economic benefit of using satellite data to fill in gaps in the current air quality monitoring network used to provide information to the public. This presentation will discuss how the findings can be used to improve estimation of the socioeconomic benefits derived from Earth observation science in policy and management decisions.

Air quality mapping using GIS and economic evaluation of health impact for Mumbai City, India.

PubMed

Kumar, Awkash; Gupta, Indrani; Brandt, Jørgen; Kumar, Rakesh; Dikshit, Anil Kumar; Patil, Rashmi S

2016-05-01

Mumbai, a highly populated city in India, has been selected for air quality mapping and assessment of health impact using monitored air quality data. Air quality monitoring networks in Mumbai are operated by National Environment Engineering Research Institute (NEERI), Maharashtra Pollution Control Board (MPCB), and Brihanmumbai Municipal Corporation (BMC). A monitoring station represents air quality at a particular location, while we need spatial variation for air quality management. Here, air quality monitored data of NEERI and BMC were spatially interpolated using various inbuilt interpolation techniques of ArcGIS. Inverse distance weighting (IDW), Kriging (spherical and Gaussian), and spline techniques have been applied for spatial interpolation for this study. The interpolated results of air pollutants sulfur dioxide (SO2), nitrogen dioxide (NO2) and suspended particulate matter (SPM) were compared with air quality data of MPCB in the same region. Comparison of results showed good agreement for predicted values using IDW and Kriging with observed data. Subsequently, health impact assessment of a ward was carried out based on total population of the ward and air quality monitored data within the ward. Finally, health cost within a ward was estimated on the basis of exposed population. This study helps to estimate the valuation of health damage due to air pollution. Operating more air quality monitoring stations for measurement of air quality is highly resource intensive in terms of time and cost. The appropriate spatial interpolation techniques can be used to estimate concentration where air quality monitoring stations are not available. Further, health impact assessment for the population of the city and estimation of economic cost of health damage due to ambient air quality can help to make rational control strategies for environmental management. The total health cost for Mumbai city for the year 2012, with a population of 12.4 million, was estimated as USD8000 million.

Characterization of traffic-related air pollutant metrics at four schools in El Paso, Texas, USA: Implications for exposure assessment and siting schools in urban areas

NASA Astrophysics Data System (ADS)

Raysoni, Amit U.; Stock, Thomas H.; Sarnat, Jeremy A.; Montoya Sosa, Teresa; Ebelt Sarnat, Stefanie; Holguin, Fernando; Greenwald, Roby; Johnson, Brent; Li, Wen-Whai

2013-12-01

Children spend substantial amount of time within school microenvironments; therefore, assessing school-based exposures is essential for characterizing and preventing children's health risks to air pollutants. Indeed, the importance of characterizing children's exposures in schools is recognized by the US Environmental Protection Agency's recent initiative to promote outdoor air monitoring networks near schools. As part of a health effects study investigating the impact of traffic-related air pollution on asthmatic children along the US-Mexico border, this research examines children's exposures to, and spatio-temporal heterogeneity in concentrations of, traffic-related air pollutants at four elementary schools in El Paso, Texas. Three schools were located in an area of high traffic density and one school in an area of low traffic density. Paired indoor and outdoor concentrations of 48-h fine and coarse particulate matter (PM2.5 and PM10-2.5), 48-h black carbon (BC), 96-h nitrogen dioxide (NO2), and 96-h volatile organic compounds (VOCs) were measured for 13 weeks at each school. Outdoor concentrations of PM, NO2, BC, and BTEX (benzene, toluene, ethylbenzene, m,p-xylene, o-xylene) compounds were similar among the three schools in the high-traffic zone in contrast to the school in the low-traffic zone. Results from this study and previous studies in this region corroborate the fact that PM pollution in El Paso is dominated by coarse PM (PM10-2.5) and fine fraction (PM2.5) accounts for only 25-30% of the total PM mass in PM10. BTEX species and BC are better surrogates for traffic air pollution in this region. Correlation analyses indicate a range of association between indoor and outdoor pollutant concentrations due to uncontrollable factors like student foot traffic and varying building and ventilation configurations across the four schools. Results suggest the need of micro-scale monitoring for children's exposure assessment, which may not be adequately characterized by the measurements from a centralized monitoring site.

Multi-criteria anomaly detection in urban noise sensor networks.

PubMed

Dauwe, Samuel; Oldoni, Damiano; De Baets, Bernard; Van Renterghem, Timothy; Botteldooren, Dick; Dhoedt, Bart

2014-01-01

The growing concern of citizens about the quality of their living environment and the emergence of low-cost microphones and data acquisition systems triggered the deployment of numerous noise monitoring networks spread over large geographical areas. Due to the local character of noise pollution in an urban environment, a dense measurement network is needed in order to accurately assess the spatial and temporal variations. The use of consumer grade microphones in this context appears to be very cost-efficient compared to the use of measurement microphones. However, the lower reliability of these sensing units requires a strong quality control of the measured data. To automatically validate sensor (microphone) data, prior to their use in further processing, a multi-criteria measurement quality assessment model for detecting anomalies such as microphone breakdowns, drifts and critical outliers was developed. Each of the criteria results in a quality score between 0 and 1. An ordered weighted average (OWA) operator combines these individual scores into a global quality score. The model is validated on datasets acquired from a real-world, extensive noise monitoring network consisting of more than 50 microphones. Over a period of more than a year, the proposed approach successfully detected several microphone faults and anomalies.

An investigation of wash-off controlling parameters at urban and commercial monitoring sites.

PubMed

Berretta, C; Gnecco, I; Lanza, L G; La Barbera, P

2007-01-01

The relationship between the parameters of the wash-off function and the controlling hydrologic variables are investigated in this paper, assuming that the pollutant generation process basically depends on the watershed rainfall-runoff response characteristics. Data collected during an intense monitoring program carried out by the Department of Environmental Engineering of the University of Genova (Italy) within a residential area, an auto dismantler facility, a tourism terminal and a urban waste truck depot are used to this aim. The observed runoff events are classified into different TSS mass delivery processes and the occurrence of the first flush phenomenon is also investigated. The correlation between the mathematical parameters describing the exponential process and the hydrological parameters of the corresponding rainfall-runoff event is analysed: runoff parameters and in particular the maximum flow discharge over the time of concentration of the drainage network are proposed as the controlling factor for the total mass of pollutant that is made available for wash-off during each runoff event.

40 CFR 58.61 - Monitoring other pollutants.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Monitoring other pollutants. 58.61 Section 58.61 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Federal Monitoring § 58.61 Monitoring other pollutants. The...

Monitoring Indoor Air Quality for Enhanced Occupational Health.

PubMed

Pitarma, Rui; Marques, Gonçalo; Ferreira, Bárbara Roque

2017-02-01

Indoor environments are characterized by several pollutant sources. Because people spend more than 90% of their time in indoor environments, several studies have pointed out the impact of indoor air quality on the etiopathogenesis of a wide number of non-specific symptoms which characterizes the "Sick Building Syndrome", involving the skin, the upper and lower respiratory tract, the eyes and the nervous system, as well as many building related diseases. Thus, indoor air quality (IAQ) is recognized as an important factor to be controlled for the occupants' health and comfort. The majority of the monitoring systems presently available is very expensive and only allow to collect random samples. This work describes the system (iAQ), a low-cost indoor air quality monitoring wireless sensor network system, developed using Arduino, XBee modules and micro sensors, for storage and availability of monitoring data on a web portal in real time. Five micro sensors of environmental parameters (air temperature, humidity, carbon monoxide, carbon dioxide and luminosity) were used. Other sensors can be added for monitoring specific pollutants. The results reveal that the system can provide an effective indoor air quality assessment to prevent exposure risk. In fact, the indoor air quality may be extremely different compared to what is expected for a quality living environment. Systems like this would have benefit as public health interventions to reduce the burden of symptoms and diseases related to "sick buildings".

Monitoring of Air Quality in Passenger Cabins of the Athens Metro

NASA Astrophysics Data System (ADS)

Tsairidi, Evangelia; Assimakopoulos, Vasiliki D.; Assimakopoulos, Margarita-Niki; Barbaresos, Nicolaos; Karagiannis, Athanassios

2013-04-01

The air pollution induced by various transportation means combines the emission of pollutants with the simultaneous presence of people. In this respect, the scientific community has focused its efforts in studying both the air quality within busy streets and inside cars, buses and the underground railway network in order to identify the pollutants' sources and levels as well as the human exposure. The impact of the air pollution on commuters of the underground may be more severe because it is a confined space, extended mostly under heavily trafficked urban streets, relies on mechanical ventilation for air renewal and gathers big numbers of passengers. The purpose of the present work is to monitor the air quality of the city of Athens Metro Network cabins and platforms during the unusually hot summer of 2012. For that cause particulate matter (PM10, PM2.5, PM1), carbon dioxide (CO2), the number of commuters along with temperature (T) and humidity (RH) were recorded inside the Athens Metro Blue Line trains (covering a route from the centre of Athens (Aigaleo) to the Athens International Airport) and on the platforms of a central (Syntagma) and a suburban-traffic (Doukissis Plakentias) station between June and August. The data collection included six different experiments that took place for 2 consecutive working days each, for a time period of 6 weeks from 6:30 am too 7:00 pm in order to account for different outdoor climatic conditions and for morning and evening rush hours respectively. Measurements were taken in the middle car of the moving trains and the platform end of the selected stations. The results show PM concentrations to be higher (approximately 2 to 5 times) inside the cabins and o the platforms of the underground network as compared to the outdoor levels monitored routinely by the Ministry of Environment. Moreover, PM1, PM2.5 and PM10 average concentrations recorded at the Syntagma Station Platform were almost constantly higher reaching 11 μg m-3 47 μg m-3 and 246 μg m-3 respectively on July 11th, as opposed to the ones at Doukissis Plakentias (4 μg m-3, 15 μg m-3and 97 μg m-3 respectively). Interestingly enough, inside the trains PM1, PM2.5 and PM10 average concentrations were significantly lower compared to the Syntagma Station Platform, reaching 8 μg m-3, 27 μg m-3 and 90 μg m-3 . It was also observed that particulate levels were higher over the extent of the central part of the train route. Finally, as expected CO2 levels where found to be higher inside the trains compared to the platforms and in some cases surpassed the 1,000 ppm limit during the hottest days of the experimental campaign. Temperature and humidity remained relatively stable on the platforms whereas measurements inside the cabin fluctuated depending on the trains track locations reaching 34.8° C at the central sector of the route. KEYWORDS: Particulate pollution, Athens underground, indoor air quality, urban pollution, transportation

An early warning system for groundwater pollution based on the assessment of groundwater pollution risks.

NASA Astrophysics Data System (ADS)

Zhang, Weihong.; Zhao, Yongsheng; Hong, Mei; Guo, Xiaodong

2009-04-01

Groundwater pollution usually is complex and concealed, remediation of which is difficult, high cost, time-consuming, and ineffective. An early warning system for groundwater pollution is needed that detects groundwater quality problems and gets the information necessary to make sound decisions before massive groundwater quality degradation occurs. Groundwater pollution early warning were performed by considering comprehensively the current groundwater quality, groundwater quality varying trend and groundwater pollution risk . The map of the basic quality of the groundwater was obtained by fuzzy comprehensive evaluation or BP neural network evaluation. Based on multi-annual groundwater monitoring datasets, Water quality state in sometime of the future was forecasted using time-sequenced analyzing methods. Water quality varying trend was analyzed by Spearman's rank correlative coefficient.The relative risk map of groundwater pollution was estimated through a procedure that identifies, cell by cell,the values of three factors, that is inherent vulnerability, load risk of pollution source and contamination hazard. DRASTIC method was used to assess inherent vulnerability of aquifer. Load risk of pollution source was analyzed based on the potential of contamination and pollution degree. Assessment index of load risk of pollution source which involves the variety of pollution source, quantity of contaminants, releasing potential of pollutants, and distance were determined. The load risks of all sources considered by GIS overlay technology. Early warning model of groundwater pollution combined with ComGIS technology organically, the regional groundwater pollution early-warning information system was developed, and applied it into Qiqiha'er groundwater early warning. It can be used to evaluate current water quality, to forecast water quality changing trend, and to analyze space-time influencing range of groundwater quality by natural process and human activities. Keywords: groundwater pollution, early warning, aquifer vulnerability, pollution load, pollution risk, ComGIS

Remote sensing techniques in monitoring areas affected by forest fire

NASA Astrophysics Data System (ADS)

Karagianni, Aikaterini Ch.; Lazaridou, Maria A.

2017-09-01

Forest fire is a part of nature playing a key role in shaping ecosystems. However, fire's environmental impacts can be significant, affecting wildlife habitat and timber, human settlements, man-made technical constructions and various networks (road, power networks) and polluting the air with emissions harmful to human health. Furthermore, fire's effect on the landscape may be long-lasting. Monitoring the development of a fire occurs as an important aspect at the management of natural hazards in general. Among the used methods for monitoring, satellite data and remote sensing techniques can be proven of particular importance. Satellite remote sensing offers a useful tool for forest fire detection, monitoring, management and damage assessment. Especially for fire scars detection and monitoring, satellite data derived from Landsat 8 can be a useful research tool. This paper includes critical considerations of the above and concerns in particular an example of the Greek area (Thasos Island). This specific area was hit by fires several times in the past and recently as well (September 2016). Landsat 8 satellite data are being used (pre and post fire imagery) and digital image processing techniques are applied (enhancement techniques, calculation of various indices) for fire scars detection. Visual interpretation of the example area affected by the fires is also being done, contributing to the overall study.

Air quality impact assessment of multiple open pit coal mines in northern Colombia.

PubMed

Huertas, José I; Huertas, María E; Izquierdo, Sebastián; González, Enrique D

2012-01-01

The coal mining region in northern Colombia is one of the largest open pit mining regions of the world. In 2009, there were 8 mining companies in operation with an approximate coal production of ∼70 Mtons/year. Since 2007, the Colombian air quality monitoring network has reported readings that exceed the daily and annual air quality standards for total suspended particulate (TSP) matter and particles with an equivalent aerodynamic diameter smaller than 10 μm (PM₁₀) in nearby villages. This paper describes work carried out in order to establish an appropriate clean air program for this region, based on the Colombian national environmental authority requirement for modeling of TSP and PM(10) dispersion. A TSP and PM₁₀ emission inventory was initially developed, and topographic and meteorological information for the region was collected and analyzed. Using this information, the dispersion of TSP was modeled in ISC3 and AERMOD using meteorological data collected by 3 local stations during 2008 and 2009. The results obtained were compared to actual values measured by the air quality monitoring network. High correlation coefficients (>0.73) were obtained, indicating that the models accurately described the main factors affecting particle dispersion in the region. The model was then used to forecast concentrations of particulate matter for 2010. Based on results from the model, areas within the modeling region were identified as highly, fairly, moderately and marginally polluted according to local regulations. Additionally, the contribution particulate matter to the pollution at each village was estimated. Using these predicted values, the Colombian environmental authority imposed new decontamination measures on the mining companies operating in the region. These measures included the relocation of three villages financed by the mine companies based on forecasted pollution levels. Copyright © 2011. Published by Elsevier Ltd.

Local-Scale Air Quality Modeling in Support of Human Health and Exposure Research (Invited)

NASA Astrophysics Data System (ADS)

Isakov, V.

2010-12-01

Spatially- and temporally-sparse information on air quality is a key concern for air-pollution-related environmental health studies. Monitor networks are sparse in both space and time, are costly to maintain, and are often designed purposely to avoid detecting highly localized sources. Recent studies have shown that more narrowly defining the geographic domain of the study populations and improvements in the measured/estimated ambient concentrations can lead to stronger associations between air pollution and hospital admissions and mortality records. Traditionally, ambient air quality measurements have been used as a primary input to support human health and exposure research. However, there is increasing evidence that the current ambient monitoring network is not capturing sharp gradients in exposure due to the presence of high concentration levels near, for example, major roadways. Many air pollutants exhibit large concentration gradients near large emitters such as major roadways, factories, ports, etc. To overcome these limitations, researchers are now beginning to use air quality models to support air pollution exposure and health studies. There are many advantages to using air quality models over traditional approaches based on existing ambient measurements alone. First, models can provide spatially- and temporally-resolved concentrations as direct input to exposure and health studies and thus better defining the concentration levels for the population in the geographic domain. Air quality models have a long history of use in air pollution regulations, and supported by regulatory agencies and a large user community. Also, models can provide bidirectional linkages between sources of emissions and ambient concentrations, thus allowing exploration of various mitigation strategies to reduce risk to exposure. In order to provide best estimates of air concentrations to support human health and exposure studies, model estimates should consider local-scale features, regional-scale transport, and photochemical transformations. Since these needs are currently not met by a single model, hybrid air quality modeling has recently been developed to combine these capabilities. In this paper, we present the results of two studies where we applied the hybrid modeling approach to provide spatial and temporal details in air quality concentrations to support exposure and health studies: a) an urban-scale air quality accountability study involving near-source exposures to multiple ambient air pollutants, and b) an urban-scale epidemiological study involving human health data based on emergency department visits.

Space time modelling of air quality for environmental-risk maps: A case study in South Portugal

NASA Astrophysics Data System (ADS)

Soares, Amilcar; Pereira, Maria J.

2007-10-01

Since the 1960s, there has been a strong industrial development in the Sines area, on the southern Atlantic coast of Portugal, including the construction of an important industrial harbour and of, mainly, petrochemical and energy-related industries. These industries are, nowadays, responsible for substantial emissions of SO2, NOx, particles, VOCs and part of the ozone polluting the atmosphere. The major industries are spatially concentrated in a restricted area, very close to populated areas and natural resources such as those protected by the European Natura 2000 network. Air quality parameters are measured at the emissions' sources and at a few monitoring stations. Although air quality parameters are measured on an hourly basis, the lack of representativeness in space of these non-homogeneous phenomena makes even their representativeness in time questionable. Hence, in this study, the regional spatial dispersion of contaminants is also evaluated, using diffusive-sampler (Radiello Passive Sampler) campaigns during given periods. Diffusive samplers cover the entire space extensively, but just for a limited period of time. In the first step of this study, a space-time model of pollutants was built, based on a stochastic simulation-direct sequential simulation-with local spatial trend. The spatial dispersion of the contaminants for a given period of time-corresponding to the exposure time of the diffusive samplers-was computed by ordinary kriging. Direct sequential simulation was applied to produce equiprobable spatial maps for each day of that period, using the kriged map as a spatial trend and the daily measurements of pollutants from the monitoring stations as hard data. In the second step, the following environmental risk and costs maps were computed from the set of simulated realizations of pollutants: (i) maps of the contribution of each emission to the pollutant concentration at any spatial location; (ii) costs of badly located monitoring stations.

Biomagnetic Monitoring of Atmospheric Pollution: A Review of Magnetic Signatures from Biological Sensors.

PubMed

Hofman, Jelle; Maher, Barbara A; Muxworthy, Adrian R; Wuyts, Karen; Castanheiro, Ana; Samson, Roeland

2017-06-20

Biomagnetic monitoring of atmospheric pollution is a growing application in the field of environmental magnetism. Particulate matter (PM) in atmospheric pollution contains readily measurable concentrations of magnetic minerals. Biological surfaces, exposed to atmospheric pollution, accumulate magnetic particles over time, providing a record of location-specific, time-integrated air quality information. This review summarizes current knowledge of biological material ("sensors") used for biomagnetic monitoring purposes. Our work addresses the following: the range of magnetic properties reported for lichens, mosses, leaves, bark, trunk wood, insects, crustaceans, mammal and human tissues; their associations with atmospheric pollutant species (PM, NO x , trace elements, PAHs); the pros and cons of biomagnetic monitoring of atmospheric pollution; current challenges for large-scale implementation of biomagnetic monitoring; and future perspectives. A summary table is presented, with the aim of aiding researchers and policy makers in selecting the most suitable biological sensor for their intended biomagnetic monitoring purpose.

Air Pollution Monitoring and Use of Nanotechnology Based Solid State Gas Sensors in Greater Cairo Area, Egypt

NASA Astrophysics Data System (ADS)

Ramadan, A. B. A.

Air pollution is a serious problem in thickly populated and industrialized areas in Egypt, especially in greater Cairo area. Economic growth and industrialization are proceeding at a rapid pace, accompanied by increasing emissions of air polluting sources. Furthermore, though the variety and quantities of polluting sources have increased dramatically, the development of a suitable method for monitoring the pollution causing sources has not followed at the same pace. Environmental impacts of air pollutants have impact on public health, vegetation, material deterioration etc. To prevent or minimize the damage caused by atmospheric pollution, suitable monitoring systems are urgently needed that can rapidly and reliably detect and quantify polluting sources for monitoring by regulating authorities in order to prevent further deterioration of the current pollution levels. Consequently, it is important that the current real-time air quality monitoring system, controlled by the Egyptian Environmental Affairs Agency (EEAA), should be adapted or extended to aid in alleviating this problem. Nanotechnology has been applied to several industrial and domestic fields, for example, applications for gas monitoring systems, gas leak detectors in factories, fire and toxic gas detectors, ventilation control, breath alcohol detectors, and the like. Here we report an application example of studying air quality monitoring based on nanotechnology `solid state gas sensors'. So as to carry out air pollution monitoring over an extensive area, a combination of ground measurements through inexpensive sensors and wireless GIS will be used for this purpose. This portable device, comprising solid state gas sensors integrated to a Personal Digital Assistant (PDA) linked through Bluetooth communication tools and Global Positioning System (GPS), will allow rapid dissemination of information on pollution levels at multiple sites simultaneously.

Accidental spills at sea--risk, impact, mitigation and the need for co-ordinated post-incident monitoring.

PubMed

Kirby, Mark F; Law, Robin J

2010-06-01

A fully integrated and effective response to an oil or chemical spill at sea must include a well planned and executed post-incident assessment of environmental contamination and damage. While salvage, rescue and clean-up operations are generally well considered, including reviews and exercises, the expertise, resources, networks and logistical planning required to achieve prompt and effective post-spill impact assessment and monitoring are not generally well established. The arrangement and co-ordination of post-incident monitoring and impact assessment need to consider sampling design, biological effects, chemical analysis and collection/interpretation of expert local knowledge. This paper discusses the risks, impacts and mitigation options associated with accidental spills and considers the importance of pre-considered impact assessment and monitoring programmes in the wider response cycle. The PREMIAM (Pollution Response in Emergencies: Marine Impact Assessment and Monitoring; www.premiam.org) project is considered as an example of an improved approach to the planning, co-ordination and conduct of post-incident monitoring.

Monitoring Instrument Performance in Regional Broadband Seismic Network Using Ambient Seismic Noise

NASA Astrophysics Data System (ADS)

Ye, F.; Lyu, S.; Lin, J.

2017-12-01

In the past ten years, the number of seismic stations has increased significantly, and regional seismic networks with advanced technology have been gradually developed all over the world. The resulting broadband data help to improve the seismological research. It is important to monitor the performance of broadband instruments in a new network in a long period of time to ensure the accuracy of seismic records. Here, we propose a method that uses ambient noise data in the period range 5-25 s to monitor instrument performance and check data quality in situ. The method is based on an analysis of amplitude and phase index parameters calculated from pairwise cross-correlations of three stations, which provides multiple references for reliable error estimates. Index parameters calculated daily during a two-year observation period are evaluated to identify stations with instrument response errors in near real time. During data processing, initial instrument responses are used in place of available instrument responses to simulate instrument response errors, which are then used to verify our results. We also examine feasibility of the tailing noise using data from stations selected from USArray in different locations and analyze the possible instrumental errors resulting in time-shifts used to verify the method. Additionally, we show an application that effects of instrument response errors that experience pole-zeros variations on monitoring temporal variations in crustal properties appear statistically significant velocity perturbation larger than the standard deviation. The results indicate that monitoring seismic instrument performance helps eliminate data pollution before analysis begins.

A novel mobile monitoring approach to characterize spatial and temporal variation in traffic-related air pollutants in an urban community

NASA Astrophysics Data System (ADS)

Yu, Chang Ho; Fan, Zhihua; Lioy, Paul J.; Baptista, Ana; Greenberg, Molly; Laumbach, Robert J.

2016-09-01

Air concentrations of traffic-related air pollutants (TRAPs) vary in space and time within urban communities, presenting challenges for estimating human exposure and potential health effects. Conventional stationary monitoring stations/networks cannot effectively capture spatial characteristics. Alternatively, mobile monitoring approaches became popular to measure TRAPs along roadways or roadsides. However, these linear mobile monitoring approaches cannot thoroughly distinguish spatial variability from temporal variations in monitored TRAP concentrations. In this study, we used a novel mobile monitoring approach to simultaneously characterize spatial/temporal variations in roadside concentrations of TRAPs in urban settings. We evaluated the effectiveness of this mobile monitoring approach by performing concurrent measurements along two parallel paths perpendicular to a major roadway and/or along heavily trafficked roads at very narrow scale (one block away each other) within short time period (<30 min) in an urban community. Based on traffic and particulate matter (PM) source information, we selected 4 neighborhoods to study. The sampling activities utilized real-time monitors, including battery-operated PM2.5 monitor (SidePak), condensation particle counter (CPC 3007), black carbon (BC) monitor (Micro-Aethalometer), carbon monoxide (CO) monitor (Langan T15), and portable temperature/humidity data logger (HOBO U12), and a GPS-based tracker (Trackstick). Sampling was conducted for ∼3 h in the morning (7:30-10:30) in 7 separate days in March/April and 6 days in May/June 2012. Two simultaneous samplings were made at 5 spatially-distributed locations on parallel roads, usually distant one block each other, in each neighborhood. The 5-min averaged BC concentrations (AVG ± SD, [range]) were 2.53 ± 2.47 [0.09-16.3] μg/m3, particle number concentrations (PNC) were 33,330 ± 23,451 [2512-159,130] particles/cm3, PM2.5 mass concentrations were 8.87 ± 7.65 [0.27-46.5] μg/m3, and CO concentrations were 1.22 ± 0.60 [0.22-6.29] ppm in the community. The traffic-related air pollutants, BC and PNC, but not PM2.5 or CO, varied spatially depending on proximity to local stationary/mobile sources. Seasonal differences were observed for all four TRAPs, significantly higher in colder months than in warmer months. The coefficients of variation (CVs) in concurrent measurements from two parallel routes were calculated around 0.21 ± 0.17, and variations were attributed by meteorological variation (25%), temporal variability (19%), concentration level (6%), and spatial variability (2%), respectively. Overall study findings suggest this mobile monitoring approach could effectively capture and distinguish spatial/temporal characteristics in TRAP concentrations for communities impacted by heavy motor vehicle traffic and mixed urban air pollution sources.

Long-term trends in airborne SO2 in an air quality monitoring station in Seoul, Korea, from 1987 to 2013.

PubMed

Khan, Azmatullah; Kim, Ki-Hyun; Szulejko, Jan E; Brown, Richard J C; Jeon, Eui-Chan; Oh, Jong-Min; Shin, Yong Soon; Adelodun, Adedeji A

2017-08-01

Atmospheric concentration of sulfur dioxide (SO 2 ) was intermittently measured at an air quality monitoring (AQM) station in the Yong-san district of Seoul, Korea, between 1987 and 2013. The SO 2 level was compared with other important pollutants concurrently measured, including methane (CH 4 ), carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO 2 ), ozone (O 3 ), and particulate matter (PM 10 ). If split into three different periods (period 1, 1987-1988, period 2, 1999-2000, and period 3, 2004-2013), the respective mean [SO 2 ] values (6.57 ± 4.29, 6.30 ± 2.44, and 5.29 ± 0.63 ppb) showed a slight reduction across the entire study period. The concentrations of SO 2 are found to be strongly correlated with other pollutants such as CO (r = 0.614, p = 0.02), which tracked reductions in reported emissions due to tighter emissions standards enacted by the South Korean government. There was also a clear seasonal trend in the SO 2 level, especially in periods 2 and 3, reflecting the combined effects of domestic heating by coal briquettes and meteorological conditions. Although only a 16% concentration reduction was achieved during the 27-year study duration, this is significant if one considers rapid urbanization, an 83.2% increase in population, and rapid industrialization that took place during that period. Since 1970, a network of air quality monitoring (AQM) stations has been operated by the Korean Ministry of Environment (KMOE) for routine nationwide monitoring of air pollutant concentrations in urban/suburban areas. To date, the information obtained from these stations has provided a platform for analyzing long-term trends of major pollutant species. In this study, we examined the long-term trends of SO 2 levels and relevant environmental parameters monitored continuously in the Yong-san district of Seoul between 1987 and 2013. The data were analyzed over various time scales (i.e., monthly, seasonal, and annual intervals). The results obtained from this study will allow us to assess the effectiveness of abatement strategy and to predict future concentrations trends in association with future abatement strategies and technologies.

Involvement of stakeholders in the water quality monitoring and surveillance system: The case of Mzingwane Catchment, Zimbabwe

NASA Astrophysics Data System (ADS)

Nare, Lerato; Love, David; Hoko, Zvikomborero

Stakeholder participation is viewed as critical in the current water sector reforms taking place in the Southern African region. In Zimbabwe, policies and legislation encourage stakeholder participation. A study was undertaken to determine the extent of stakeholder participation in water quality monitoring and surveillance at the operational level, and also to assess indigenous knowledge and practices in water quality monitoring. Two hundred and forty one questionnaires were administered in Mzingwane Catchment, the portion of the Limpopo Basin that falls within Zimbabwe. The focus was on small users in rural communities, whose experiences were captured using a questionnaire and focus group discussions. Extension workers, farmers and NGOs and relevant sector government ministries and departments were also interviewed and a number of workshops held. Results indicate that there is very limited stakeholder participation despite the presence of adequate supportive structures and organisations. For the Zimbabwe National Water Authority (ZINWA), stakeholders are the paying permit holders to whom feedback is given following analysis of samples. However, the Ministry of Health and Child Welfare generally only releases information to rural communities when it is deemed necessary for their welfare. There are no guidelines on how a dissatisfied member of the public can raise a complaint - although some stakeholders carry such complaints to Catchment Council meetings. With regard to water quality, the study revealed widespread use of indigenous knowledge and practice by communities. Such knowledge is based on smell, taste, colour and odour perceptions. Residents are generally more concerned about the physical parameters than the bacteriological quality of water. They are aware of what causes water pollution and the effects of pollution on human health, crops, animals and aquatic ecology. They have ways of preventing pollution and appropriate interventions to take when a source of water is polluted, such as boiling water for human consumption, laundry and bathing, or abandoning a water source in extreme cases. Stakeholder participation and ownership of resources needs to be encouraged through participatory planning, and integration between the three government departments (water, environment and health). Local knowledge systems could be integrated into the formal water quality monitoring systems, in order to complement the conventional monitoring networks.

Making Sense of Remotely Sensed Ultra-Spectral Infrared Data

NASA Technical Reports Server (NTRS)

2001-01-01

NASA's Jet Propulsion Laboratory (JPL), Pasadena, California, Earth Observing System (EOS) programs, the Deep Space Network (DSN), and various Department of Defense (DOD) technology demonstration programs, combined their technical expertise to develop SEASCRAPE, a software program that obtains data when thermal infrared radiation passes through the Earth's atmosphere and reaches a sensor. Licensed by the California Institute of Technology (Caltech), SEASCRAPE automatically inverts complex infrared data and makes it possible to obtain estimates of the state of the atmosphere along the ray path. Former JPL staff members created a small entrepreneurial firm, Remote Sensing Analysis Systems, Inc., of Altadena, California, to commercialize the product. The founders believed that a commercial version of the software was needed for future U.S. government missions and the commercial monitoring of pollution. With the inversion capability of this software and remote sensing instrumentation, it is possible to monitor pollution sources from safe and secure distances on a noninterfering, noncooperative basis. The software, now know as SEASCRAPE_Plus, allows the user to determine the presence of pollution products, their location and their abundance along the ray path. The technology has been cleared by the Department of Commerce for export, and is currently used by numerous research and engineering organizations around the world.

The relationship between changes in daily air pollution and hospitalizations in Perth, Australia 1992-1998: a case-crossover study.

PubMed

Hinwood, A L; De Klerk, N; Rodriguez, C; Jacoby, P; Runnion, T; Rye, P; Landau, L; Murray, F; Feldwick, M; Spickett, J

2006-02-01

A case-crossover study was undertaken to investigate the relationship between daily air pollutant concentrations and daily hospitalizations for selected disease categories in Perth, Western Australia. Daily measurements of particles (measured by nephelometry and PM2.5), photochemical oxidants (measured as ozone), nitrogen dioxide (NO2) and carbon monoxide (CO) concentrations were obtained from 1992 to 1998 via a metropolitan network of monitoring stations. Daily PM2.5 concentrations were estimated using monitored data, modelling and interpolation. Hospital morbidity data for respiratory, cardiovascular (CVD), gastrointestinal (GI) diseases, chronic obstructive pulmonary diseases (COPD) excluding asthma; pneumonia/influenza diseases; and asthma were obtained and categorized into all ages, less than 15 years and greater than 65 years. Gastrointestinal morbidity was used as a control disease. The data were analyzed using conditional logistic regression. The results showed a small number of significant associations for daily changes in particle concentrations, nitrogen dioxide and carbon monoxide for the respiratory diseases, CODP, pneumonia, asthma and CVD hospitalizations. Changes in ozone concentrations were not significantly associated with any disease outcomes. These data provide useful information on the potential health impacts of air pollution in an airshed with very low sulphur dioxide concentrations and lower nitrogen dioxide concentrations commonly found in many other cities.

The Mediterranean Decision Support System for Marine Safety dedicated to oil slicks predictions

NASA Astrophysics Data System (ADS)

Zodiatis, G.; De Dominicis, M.; Perivoliotis, L.; Radhakrishnan, H.; Georgoudis, E.; Sotillo, M.; Lardner, R. W.; Krokos, G.; Bruciaferri, D.; Clementi, E.; Guarnieri, A.; Ribotti, A.; Drago, A.; Bourma, E.; Padorno, E.; Daniel, P.; Gonzalez, G.; Chazot, C.; Gouriou, V.; Kremer, X.; Sofianos, S.; Tintore, J.; Garreau, P.; Pinardi, N.; Coppini, G.; Lecci, R.; Pisano, A.; Sorgente, R.; Fazioli, L.; Soloviev, D.; Stylianou, S.; Nikolaidis, A.; Panayidou, X.; Karaolia, A.; Gauci, A.; Marcati, A.; Caiazzo, L.; Mancini, M.

2016-11-01

In the Mediterranean sea the risk from oil spill pollution is high due to the heavy traffic of merchant vessels for transporting oil and gas, especially after the recent enlargement of the Suez canal and to the increasing coastal and offshore installations related to the oil industry in general. The basic response to major oil spills includes different measures and equipment. However, in order to strengthen the maritime safety related to oil spill pollution in the Mediterranean and to assist the response agencies, a multi-model oil spill prediction service has been set up, known as MEDESS-4MS (Mediterranean Decision Support System for Marine Safety). The concept behind the MEDESS-4MS service is the integration of the existing national ocean forecasting systems in the region with the Copernicus Marine Environmental Monitoring Service (CMEMS) and their interconnection, through a dedicated network data repository, facilitating access to all these data and to the data from the oil spill monitoring platforms, including the satellite data ones, with the well established oil spill models in the region. The MEDESS-4MS offer a range of service scenarios, multi-model data access and interactive capabilities to suite the needs of REMPEC (Regional Marine Pollution Emergency Response Centre for the Mediterranean Sea) and EMSA-CSN (European Maritime Safety Agency-CleanseaNet).

Characterizing air quality data from complex network perspective.

PubMed

Fan, Xinghua; Wang, Li; Xu, Huihui; Li, Shasha; Tian, Lixin

2016-02-01

Air quality depends mainly on changes in emission of pollutants and their precursors. Understanding its characteristics is the key to predicting and controlling air quality. In this study, complex networks were built to analyze topological characteristics of air quality data by correlation coefficient method. Firstly, PM2.5 (particulate matter with aerodynamic diameter less than 2.5 μm) indexes of eight monitoring sites in Beijing were selected as samples from January 2013 to December 2014. Secondly, the C-C method was applied to determine the structure of phase space. Points in the reconstructed phase space were considered to be nodes of the network mapped. Then, edges were determined by nodes having the correlation greater than a critical threshold. Three properties of the constructed networks, degree distribution, clustering coefficient, and modularity, were used to determine the optimal value of the critical threshold. Finally, by analyzing and comparing topological properties, we pointed out that similarities and difference in the constructed complex networks revealed influence factors and their different roles on real air quality system.

Consistent Steering System using SCTP for Bluetooth Scatternet Sensor Network

NASA Astrophysics Data System (ADS)

Dhaya, R.; Sadasivam, V.; Kanthavel, R.

2012-12-01

Wireless communication is the best way to convey information from source to destination with flexibility and mobility and Bluetooth is the wireless technology suitable for short distance. On the other hand a wireless sensor network (WSN) consists of spatially distributed autonomous sensors to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants. Using Bluetooth piconet wireless technique in sensor nodes creates limitation in network depth and placement. The introduction of Scatternet solves the network restrictions with lack of reliability in data transmission. When the depth of the network increases, it results in more difficulties in routing. No authors so far focused on the reliability factors of Scatternet sensor network's routing. This paper illustrates the proposed system architecture and routing mechanism to increase the reliability. The another objective is to use reliable transport protocol that uses the multi-homing concept and supports multiple streams to prevent head-of-line blocking. The results show that the Scatternet sensor network has lower packet loss even in the congestive environment than the existing system suitable for all surveillance applications.

An International Haze-Monitoring Network for Students.

NASA Astrophysics Data System (ADS)

Mims, Forrest M., III

1999-07-01

The Global Learning and Observations to Benefit the Environment (GLOBE) Program is an international network of schools in 71 countries that monitors up to 20 environmental parameters. Recently GLOBE added a haze-monitoring program to its measurement protocols. This network has the potential of providing important data about changes in the aerosol optical depth of the atmosphere caused by weather fronts, industrial and automobile pollution, and smoke from forest and brush fires and volcanic eruptions. Initially, monitoring will be conducted with an inexpensive, single-channel (520 nm) sun photometer. Unlike conventional sun photometers that use interference filters that are subject to unpredictable and rapid degradation, the GLOBE instrument uses a common light-emitting diode (LED) as a spectrally selective detector. Annual calibrations of two LED sun photometers at Mauna Loa Observatory since 1992 show that these instruments have insignificant degradation when compared to filter sun photometers. Some 175 prototype versions of a kit LED sun photometer have been assembled and tested by students from 16 countries at the University of the Nations and by more than 130 high school teachers in various pilot studies. These studies have demonstrated that even inexperienced students and teachers can quickly assemble a sun photometer from a kit of parts and perform a reliable angley calibration. The pilot studies have also demonstrated that sun photometery provides a convenient means for allowing students to perform hands-on science while they learn about various topics in history, electronics, algebra, statistics, graphing, and meteorology.

Calculation and analysis of the non-point source pollution in the upstream watershed of the Panjiakou Reservoir, People's Republic of China

NASA Astrophysics Data System (ADS)

Zhang, S.; Tang, L.

2007-05-01

Panjiakou Reservoir is an important drinking water resource in Haihe River Basin, Hebei Province, People's Republic of China. The upstream watershed area is about 35,000 square kilometers. Recently, the water pollution in the reservoir is becoming more serious owing to the non-point pollution as well as point source pollution on the upstream watershed. To effectively manage the reservoir and watershed and develop a plan to reduce pollutant loads, the loading of non-point and point pollution and their distribution on the upstream watershed must be understood fully. The SWAT model is used to simulate the production and transportation of the non-point source pollutants in the upstream watershed of the Panjiakou Reservoir. The loadings of non-point source pollutants are calculated for different hydrologic years and the spatial and temporal characteristics of non-point source pollution are studied. The stream network and topographic characteristics of the stream network and sub-basins are all derived from the DEM by ArcGIS software. The soil and land use data are reclassified and the soil physical properties database file is created for the model. The SWAT model was calibrated with observed data of several hydrologic monitoring stations in the study area. The results of the calibration show that the model performs fairly well. Then the calibrated model was used to calculate the loadings of non-point source pollutants for a wet year, a normal year and a dry year respectively. The time and space distribution of flow, sediment and non-point source pollution were analyzed depending on the simulated results. The comparison of different hydrologic years on calculation results is dramatic. The loading of non-point source pollution in the wet year is relatively larger but smaller in the dry year since the non-point source pollutants are mainly transported through the runoff. The pollution loading within a year is mainly produced in the flood season. Because SWAT is a distributed model, it is possible to view model output as it varies across the basin, so the critical areas and reaches can be found in the study area. According to the simulation results, it is found that different land uses can yield different results and fertilization in rainy season has an important impact on the non- point source pollution. The limitations of the SWAT model are also discussed and the measures of the control and prevention of non- point source pollution for Panjiakou Reservoir are presented according to the analysis of model calculation results.

Numerical simulation the pollutants transport in the Lake base on remote sensing image with Lattice Boltzmann Method

NASA Astrophysics Data System (ADS)

Qiao, Y.

2013-12-01

As China's economic development, water pollution incidents happened frequently. For example, the cyanobacterial bloom events repeatedly occur in Taihu Lake. In this research, we investigate the pollutants solute transport start at different points, such as the eutrophication substances Nitrogen and Phosphorus et al, with the Lattice Boltzmann Method (LBM) performed on real pore geometries. The LBM has emerged as a powerful tool for simulating the behaviour of multi-component fluid systems in complex pore networks. We will build a quick response simulation system, which is base on the high resolution GIS figure, using the LBM numerical method.When the start two deferent points at the Meiliang Bay nearby the Wuxi City, it is shown that the pollutants solute can't transport out of the bay to influence the Taihu Lake and the diffusion areas are similar. On the other hand, when the start point at central region of the Taihu Lake, it is found that the pollutants solute covered the almost whole area of the lake and the cyanobacterial bloom with good condition. In the same way, if the cyanobacterial bloom transport in the central area, then it will pollute the whole Taihu Lake. Therefore, when we monitor and deal with the eutrophication substances, we need to focus on the central area of lake.

Control of Pollutants in the Trans-Boundary Area of Taihu Basin, Yangtze Delta.

PubMed

Wang, Xiao; Katopodes, Nikolaos; Shen, Chunqi; Wang, Hua; Pang, Yong; Zhou, Qi

2016-12-17

This work focuses on pollution control in the trans-boundary area of Taihu Basin. Considering the unique characteristics of the river network in the study area, a new methodology of pollution control is proposed aiming at improving the water quality in the trans-boundary area and reducing conflicts between up and downstream regions. Based on monitoring data and statistical analysis, important trans-boundary cross sections identified by the regional government were selected as important areas for consideration in developing management objectives; using a 1-D mathematicmodel and an effective weight evaluation model, the trans-boundary effective control scope (TECS) of the study area was identified as the scope for pollutant control; the acceptable pollution load was then estimated using an established model targeting bi-directional flow. The results suggest that the water environmental capacity for chemical oxygen demand (COD), in order to guarantee reaching the target water quality standard in the TECS, is 160,806 t/year, and amounts to 16,098 t/year, 3493 t/year, and 39,768 t/year for ammonia nitrogen, total nitrogen, and total phosphorus, respectively. Our study method and results have been incorporated into the local government management project, and have been proven to be useful in designing a pollution control strategy and management policy.

Control of Pollutants in the Trans-Boundary Area of Taihu Basin, Yangtze Delta

PubMed Central

Wang, Xiao; Katopodes, Nikolaos; Shen, Chunqi; Wang, Hua; Pang, Yong; Zhou, Qi

2016-01-01

This work focuses on pollution control in the trans-boundary area of Taihu Basin. Considering the unique characteristics of the river network in the study area, a new methodology of pollution control is proposed aiming at improving the water quality in the trans-boundary area and reducing conflicts between up and downstream regions. Based on monitoring data and statistical analysis, important trans-boundary cross sections identified by the regional government were selected as important areas for consideration in developing management objectives; using a 1-D mathematicmodel and an effective weight evaluation model, the trans-boundary effective control scope (TECS) of the study area was identified as the scope for pollutant control; the acceptable pollution load was then estimated using an established model targeting bi-directional flow. The results suggest that the water environmental capacity for chemical oxygen demand (COD), in order to guarantee reaching the target water quality standard in the TECS, is 160,806 t/year, and amounts to 16,098 t/year, 3493 t/year, and 39,768 t/year for ammonia nitrogen, total nitrogen, and total phosphorus, respectively. Our study method and results have been incorporated into the local government management project, and have been proven to be useful in designing a pollution control strategy and management policy. PMID:27999331

[Explore the spatial and temporal patterns of water pollution in the Yincungang canal of the Lake Taihu basin, China].

PubMed

Yang, Xiao-Ying; Luo, Xing-Zhang; Zheng, Zheng; Fang, Shu-Bo

2012-09-01

Two high-density snap-shot samplings were conducted along the Yincungang canal, one important tributary of the Lake Tai, in April (low flow period) and June (high flow period) of 2010. Geostatistical analysis based on the river network distance was used to analyze the spatial and temporal patterns of the pollutant concentrations along the canal with an emphasis on chemical oxygen demand (COD) and total nitrogen (TN). Study results have indicated: (1) COD and TN concentrations display distinctly different spatial and temporal patterns between the low and high flow periods. COD concentration in June is lower than that in April, while TN concentration has the contrary trend. (2) COD load is relatively constant during the period between the two monitoring periods. The spatial correlation structure of COD is exponential for both April and June, and the change of COD concentration is mainly influenced by hydrological conditions. (3) Nitrogen load from agriculture increased significantly during the period between the two monitoring periods. Large amount of chaotic fertilizing by individual farmers has led to the loss of the spatial correlation among the observed TN concentrations. Hence, changes of TN concentration in June are under the dual influence of agricultural fertilizing and hydrological conditions. In the view of the complex hydrological conditions and serious water pollution in the Lake Taihu region, geostatistical analysis is potentially a useful tool for studying the characteristics of pollutant distribution and making predictions in the region.

Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks

PubMed Central

Artuñedo, Antonio; del Toro, Raúl M.; Haber, Rodolfo E.

2017-01-01

Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller (TLC) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks. PMID:28445398

Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks.

PubMed

Artuñedo, Antonio; Del Toro, Raúl M; Haber, Rodolfo E

2017-04-26

Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller ( TLC ) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks.

A national scale monitoring network for nutrients in agriculture dominated headwaters in the Netherlands

NASA Astrophysics Data System (ADS)

Broers, H. P.; Rozemeijer, J.; Klein, J.

2012-04-01

Although specific monitoring networks exist in the Netherlands which assess the leaching of nutrients to surface waters and groundwater, none of them was capable to quantify the effects of nutrient reduction schemes to agriculture dominated headwaters. Thus, an important link was missing which relates the nutrient concentrations measured in shallow groundwater at farm scale to nutrient concentrations measured at the scale of Water Framework Directive water bodies. A new network was composed using existing monitoring locations and water quality time series owned by the 24 water boards in the Netherlands. Only monitoring locations were selected where no other pollution sources , such as water sewage treatment plants were influencing water quality. Eventually, 168 monitoring locations were selected to assess compliance to environmental standards and 80 for trend analysis. Compliance was tested applying environmental quality standards (EQS) based on summer averaged concentrations, which are set by the water boards and which are water type and location dependent. Compliance was strongly weather dependent, and only 24% of the locations complied for N and P under all weather conditions. Trends were assessed using a combination of seasonal Mann-Kendall tests and Theil-Sen robust lines for individual time series, and aggregating those trends to acquire median and average trend slopes for the sand, clay and peat regions in the Netherlands. Significant downward trends were demonstrated for N and P over the whole period (slopes between -0,55 mgN/l and -0.015 and 0.02 mg P/l per 10 year). Slopes were even more pronounced for winter concentrations of N (-0.89 mg N/l per 10 year). The slopes were relevant and environmentally significant in relation to the height of the EQS and were attributed to the effective reduction of nutrient leaching as the result of adapted farming practices. The presentation will highlight and evaluate choices in the design of the newly composed network, including the use of existing monitoring data and its probable effect on the outcomes of the network.

Design of an Air Pollution Monitoring Campaign in Beijing for Application to Cohort Health Studies.

PubMed

Vedal, Sverre; Han, Bin; Xu, Jia; Szpiro, Adam; Bai, Zhipeng

2017-12-15

No cohort studies in China on the health effects of long-term air pollution exposure have employed exposure estimates at the fine spatial scales desirable for cohort studies with individual-level health outcome data. Here we assess an array of modern air pollution exposure estimation approaches for assigning within-city exposure estimates in Beijing for individual pollutants and pollutant sources to individual members of a cohort. Issues considered in selecting specific monitoring data or new monitoring campaigns include: needed spatial resolution, exposure measurement error and its impact on health effect estimates, spatial alignment and compatibility with the cohort, and feasibility and expense. Sources of existing data largely include administrative monitoring data, predictions from air dispersion or chemical transport models and remote sensing (specifically satellite) data. New air monitoring campaigns include additional fixed site monitoring, snapshot monitoring, passive badge or micro-sensor saturation monitoring and mobile monitoring, as well as combinations of these. Each of these has relative advantages and disadvantages. It is concluded that a campaign in Beijing that at least includes a mobile monitoring component, when coupled with currently available spatio-temporal modeling methods, should be strongly considered. Such a campaign is economical and capable of providing the desired fine-scale spatial resolution for pollutants and sources.

Design of an Air Pollution Monitoring Campaign in Beijing for Application to Cohort Health Studies

PubMed Central

Vedal, Sverre; Han, Bin; Szpiro, Adam; Bai, Zhipeng

2017-01-01

No cohort studies in China on the health effects of long-term air pollution exposure have employed exposure estimates at the fine spatial scales desirable for cohort studies with individual-level health outcome data. Here we assess an array of modern air pollution exposure estimation approaches for assigning within-city exposure estimates in Beijing for individual pollutants and pollutant sources to individual members of a cohort. Issues considered in selecting specific monitoring data or new monitoring campaigns include: needed spatial resolution, exposure measurement error and its impact on health effect estimates, spatial alignment and compatibility with the cohort, and feasibility and expense. Sources of existing data largely include administrative monitoring data, predictions from air dispersion or chemical transport models and remote sensing (specifically satellite) data. New air monitoring campaigns include additional fixed site monitoring, snapshot monitoring, passive badge or micro-sensor saturation monitoring and mobile monitoring, as well as combinations of these. Each of these has relative advantages and disadvantages. It is concluded that a campaign in Beijing that at least includes a mobile monitoring component, when coupled with currently available spatio-temporal modeling methods, should be strongly considered. Such a campaign is economical and capable of providing the desired fine-scale spatial resolution for pollutants and sources. PMID:29244738

How representative is pesticide monitoring in Swiss streams?

NASA Astrophysics Data System (ADS)

Munz, Nicole; Wittmer, Irene; Strahm, Ivo; Leu, Christian; Stamm, Christian

2013-04-01

The surveillance of surface water quality in Switzerland is the task of the 26 cantons. This includes the assessment of the level of pesticide pollution. Each of the cantons may follow different procedures, which makes a comparison difficult and cumbersome. Nevertheless, in this study presents the main results of the first nation-wide compilation and interpretation of cantonal and federal monitoring data as well as results from specific research projects on agricultural and urban pesticides are presented. Overall, more than 345'000 concentration data of 281 biocidal compounds have been analyzed. This set of substances includes 203 compounds that have been registered either only as agricultural plant protection (N = 149) product or only as urban biocide (N = 18), but also some (N = 36) which were registered for both uses. This data set contains 70 out of the 100 most sold agricultural plant protection products in 2010. A comparable assessment for the representativeness of the biocide data is hardly possible due to a lack of systematic use data. The data stem from 565 measuring sites. However, these sites are not representative for all size classes of the Swiss stream network. While about 75% of the total length of the stream network is made up by small streams (Strahler order 1 and 2), only 28% of the measuring sites are located on such streams. In combination with the sampling strategies that have been used - about 50% grab samples and 50% composite samples - it can be concluded that the 2% of measured values > 100 ng L-1 most probably severely underestimates the true level of pesticide pollution in the Swiss stream network. In the future, more emphasis has to be put on small streams, where higher concentrations are expected and thus also actual ecological effects.

Self Calibrated Wireless Distributed Environmental Sensory Networks

PubMed Central

Fishbain, Barak; Moreno-Centeno, Erick

2016-01-01

Recent advances in sensory and communication technologies have made Wireless Distributed Environmental Sensory Networks (WDESN) technically and economically feasible. WDESNs present an unprecedented tool for studying many environmental processes in a new way. However, the WDESNs’ calibration process is a major obstacle in them becoming the common practice. Here, we present a new, robust and efficient method for aggregating measurements acquired by an uncalibrated WDESN, and producing accurate estimates of the observed environmental variable’s true levels rendering the network as self-calibrated. The suggested method presents novelty both in group-decision-making and in environmental sensing as it offers a most valuable tool for distributed environmental monitoring data aggregation. Applying the method on an extensive real-life air-pollution dataset showed markedly more accurate results than the common practice and the state-of-the-art. PMID:27098279

Monitoring urban air quality using a high-density network of low-cost sensor nodes in Oslo, Norway.

NASA Astrophysics Data System (ADS)

Castell, Nuria; Schneider, Philipp; Vogt, Matthias; Dauge, Franck R.; Lahoz, William; Bartonova, Alena

2017-04-01

Urban air quality represents a major public health burden and is a long-standing concern to citizens. Air pollution is associated with a range of diseases, symptoms and conditions that impair health and quality of life. In Oslo, traffic, especially exhaust from heavy-duty and private diesel vehicles and dust resuspension from studded tyres, together with wood burning in winter, are the main sources of pollution. Norway, as part of the European Economic Area, is obliged to comply with the European air quality regulations and ensure clean air. Despite this, Oslo has exceeded both the NO2 and PM10 thresholds for health protection defined in the Directive 2008/50/EC. The air quality in the Oslo area is continuously monitored in 12 compliance monitoring stations. These stations provide reliable and accurate data but their density is too low to provide a detailed spatial distribution of air quality. The emergence of low-cost nodes enables observations at high spatial resolution, providing the opportunity to enhance existing monitoring systems. However, the data generated by these nodes is significantly less accurate and precise than the data provided by reference equipment. We have conducted an evaluation of low-cost nodes to monitor NO2 and PM10, comparing the data collected with low-cost nodes against CEN (European Standardization Organization) reference analysers. During January and March 2016, a network of 24 nodes was deployed in Oslo. During January, high NO2 levels were observed for several days in a row coinciding with the formation of a thermal inversion. During March, we observed an episode with high PM10 levels due to road dust resuspension. Our results show that there is a major technical challenge associated with current commercial low-cost sensors, regarding the sensor robustness and measurement repeatability. Despite this, low-cost sensor nodes are able to reproduce the NO2 and PM10 variability. The data from the sensors was employed to generate detailed NO2 and PM10 air quality maps using a data fusion technique. This way we were able to offer localized air quality information for the city of Oslo. The outlook for commercial low-cost sensors is promising, and our results show that currently some sensors are already capable of providing coarse information about air quality, indicating if the air quality is good, moderate or if the air is heavily polluted. This type of information could be suitable for applications that aim to raise awareness, or engage the community by monitoring local air quality, as such applications do not require the same accuracy as scientific or regulatory monitoring.

40 CFR 63.864 - Monitoring requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... that uses an air pollution control system other than an ESP, wet scrubber, RTO, or fabric filter must... unit equipped with an alternative air pollution control system and monitoring operating parameters... affected source or process unit equipped with an alternative air pollution control system and monitoring...

40 CFR 63.864 - Monitoring requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... that uses an air pollution control system other than an ESP, wet scrubber, RTO, or fabric filter must... unit equipped with an alternative air pollution control system and monitoring operating parameters... affected source or process unit equipped with an alternative air pollution control system and monitoring...

40 CFR 63.864 - Monitoring requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... that uses an air pollution control system other than an ESP, wet scrubber, RTO, or fabric filter must... unit equipped with an alternative air pollution control system and monitoring operating parameters... affected source or process unit equipped with an alternative air pollution control system and monitoring...

Air quality measurements-From rubber bands to tapping the rainbow.

PubMed

Hidy, George M; Mueller, Peter K; Altshuler, Samuel L; Chow, Judith C; Watson, John G

2017-06-01

It is axiomatic that good measurements are integral to good public policy for environmental protection. The generalized term for "measurements" includes sampling and quantitation, data integrity, documentation, network design, sponsorship, operations, archiving, and accessing for applications. Each of these components has evolved and advanced over the last 200 years as knowledge of atmospheric chemistry and physics has matured. Air quality was first detected by what people could see and smell in contaminated air. Gaseous pollutants were found to react with certain materials or chemicals, changing the color of dissolved reagents such that their light absorption at selected wavelengths could be related to both the pollutant chemistry and its concentration. Airborne particles have challenged the development of a variety of sensory devices and laboratory assays for characterization of their enormous range of physical and chemical properties. Advanced electronics made possible the sampling, concentration, and detection of gases and particles, both in situ and in laboratory analysis of collected samples. Accurate and precise measurements by these methods have made possible advanced air quality management practices that led to decreasing concentrations over time. New technologies are leading to smaller and cheaper measurement systems that can further expand and enhance current air pollution monitoring networks. Ambient air quality measurement systems have a large influence on air quality management by determining compliance, tracking trends, elucidating pollutant transport and transformation, and relating concentrations to adverse effects. These systems consist of more than just instrumentation, and involve extensive support efforts for siting, maintenance, calibration, auditing, data validation, data management and access, and data interpretation. These requirements have largely been attained for criteria pollutants regulated by National Ambient Air Quality Standards, but they are rarely attained for nonroutine measurements and research studies.

Air quality impacted by local pollution sources and beyond - Using a prominent petro-industrial complex as a study case.

PubMed

Chen, Sheng-Po; Wang, Chieh-Heng; Lin, Wen-Dian; Tong, Yu-Huei; Chen, Yu-Chun; Chiu, Ching-Jui; Chiang, Hung-Chi; Fan, Chen-Lun; Wang, Jia-Lin; Chang, Julius S

2018-05-01

The present study combines high-resolution measurements at various distances from a world-class gigantic petrochemical complex with model simulations to test a method to assess industrial emissions and their effect on local air quality. Due to the complexity in wind conditions which were highly seasonal, the dominant wind flow patterns in the coastal region of interest were classified into three types, namely northeast monsoonal (NEM) flows, southwest monsoonal (SEM) flows and local circulation (LC) based on six years of monitoring data. Sulfur dioxide (SO 2 ) was chosen as an indicative pollutant for prominent industrial emissions. A high-density monitoring network of 12 air-quality stations distributed within a 20-km radius surrounding the petrochemical complex provided hourly measurements of SO 2 and wind parameters. The SO 2 emissions from major industrial sources registered by the monitoring network were then used to validate model simulations and to illustrate the transport of the SO 2 plumes under the three typical wind patterns. It was found that the coupling of observations and modeling was able to successfully explain the transport of the industrial plumes. Although the petrochemical complex was seemingly the only major source to affect local air quality, multiple prominent sources from afar also played a significant role in local air quality. As a result, we found that a more complete and balanced assessment of the local air quality can be achieved only after taking into account the wind characteristics and emission factors of a much larger spatial scale than the initial (20 km by 20 km) study domain. Copyright © 2018 Elsevier Ltd. All rights reserved.

CAIRSENSE Study: Real-world evaluation of low cost sensors ...

EPA Pesticide Factsheets

Low-cost air pollution sensors are a rapidly developing field in air monitoring. In recent years, numerous sensors have been developed that can provide real-time concentration data for different air pollutants at costs accessible to individuals and non-regulatory groups. Additionally, these sensors have the potential to improve the spatial resolution of monitoring networks and provide a better understanding of neighborhood- and local-scale air quality and sources. However, many new sensors have not been evaluated to determine their long-term performance and capabilities. In this study, nine different low-cost sensor models, including O3, NO2 and particle sensors, were deployed in Denver, CO from September 2015 to February 2016. Three sensors of each type were deployed to evaluate instrument precision and consistency over the time period. Sensors were co-located with reference monitors at the Denver NCore site in order to evaluate sensor accuracy and precision. Denver was chosen as the location for this study to evaluate sensor performance in dry, high altitude, and low winter temperatures. Sensors were evaluated for data completeness, performance over time, and comparison with regulatory monitors. This presentation will also address challenges and approaches to data logging and processing. Preliminary analysis revealed that most sensors had high data completeness when data loggers were operational (e.g., the Aeroqual O3 sensor ranged from 94-100%), and exhibited

Joint Conference on Sensing of Environmental Pollutants, 4th, New Orleans, La., November 6-11, 1977, Proceedings

NASA Technical Reports Server (NTRS)

1978-01-01

Papers are presented on such topics as environmental chemistry, the effects of sulfur compounds on air quality, the prediction and monitoring of biological effects caused by environmental pollutants, environmental indicators, the satellite remote sensing of air pollution, weather and climate modification by pollution, and the monitoring and assessment of radioactive pollutants. Consideration is also given to empirical and quantitative modeling of air quality, disposal of hazardous and nontoxic materials, sensing and assessment of water quality, pollution source monitoring, and assessment of some environmental impacts of fossil and nuclear fuels.

Assessment of Near-Source Air Pollution at a Fine Spatial Scale Utilizing Mobile Monitoring Approach

EPA Science Inventory

Mobile monitoring is an emerging strategy to characterize spatially and temporally variable air pollution in areas near sources. EPA’s Geospatial Monitoring of Air Pollution (GMAP) vehicle – an all-electric vehicle measuring real-time concentrations of partic...

Calibration of an electronic nose for poultry farm

NASA Astrophysics Data System (ADS)

Abdullah, A. H.; Shukor, S. A.; Kamis, M. S.; Shakaff, A. Y. M.; Zakaria, A.; Rahim, N. A.; Mamduh, S. M.; Kamarudin, K.; Saad, F. S. A.; Masnan, M. J.; Mustafa, H.

2017-03-01

Malodour from the poultry farms could cause air pollution and therefore potentially dangerous to humans' and animals' health. This issue also poses sustainability risk to the poultry industries due to objections from local community. The aim of this paper is to develop and calibrate a cost effective and efficient electronic nose for poultry farm air monitoring. The instrument main components include sensor chamber, array of specific sensors, microcontroller, signal conditioning circuits and wireless sensor networks. The instrument was calibrated to allow classification of different concentrations of main volatile compounds in the poultry farm malodour. The outcome of the process will also confirm the device's reliability prior to being used for poultry farm malodour assessment. The Multivariate Analysis (HCA and KNN) and Artificial Neural Network (ANN) pattern recognition technique was used to process the acquired data. The results show that the instrument is able to calibrate the samples using ANN classification model with high accuracy. The finding verifies the instrument's performance to be used as an effective poultry farm malodour monitoring.

FY 2013 Request for Proposals for the Pollution Prevention Information Network Grants Program

EPA Pesticide Factsheets

The Pollution Prevention Information Network (PPIN) grant program funds regional centers that serve both unique regional pollution prevention (P2) information needs and national audience needs for information on source reduction and related P2 practices.

Assessment of Near-Source Air Pollution at a Fine Spatial Scale Utilizing Mobile Monitoring Approach

EPA Science Inventory

Mobile monitoring is an emerging strategy to characterize spatially and temporally variable air pollution in areas near sources. EPA’s Geospatial Monitoring of Air Pollution (GMAP) vehicle – an all-electric vehicle measuring real-time concentrations of particulate and gaseous po...

Assessment of Near-Source Air Pollution at a Fine Spatial Scale Utilizing a Mobile Monitoring Approach

EPA Science Inventory

Mobile monitoring is an emerging strategy to characterize spatially and temporally variable air pollution in areas near sources. EPA’s Geospatial Monitoring of Air Pollution (GMAP) vehicle – an all-electric vehicle measuring real-time concentrations of particulate and gaseous po...

40 CFR 63.6655 - What records must I keep?

Code of Federal Regulations, 2010 CFR

2010-07-01

... equipment) or the air pollution control and monitoring equipment. (3) Records of performance tests and... on the air pollution control and monitoring equipment. (5) Records of actions taken during periods of... malfunctioning process and air pollution control and monitoring equipment to its normal or usual manner of...

40 CFR 63.6655 - What records must I keep?

Code of Federal Regulations, 2013 CFR

2013-07-01

... equipment) or the air pollution control and monitoring equipment. (3) Records of performance tests and... on the air pollution control and monitoring equipment. (5) Records of actions taken during periods of... malfunctioning process and air pollution control and monitoring equipment to its normal or usual manner of...

Updated methods for assessing the impacts of nearby gas drilling and production on neighborhood air quality and human health.

PubMed

Olaguer, Eduardo P; Erickson, Matthew; Wijesinghe, Asanga; Neish, Brad; Williams, Jeff; Colvin, John

2016-02-01

An explosive growth in natural gas production within the last decade has fueled concern over the public health impacts of air pollutant emissions from oil and gas sites in the Barnett and Eagle Ford shale regions of Texas. Commonly acknowledged sources of uncertainty are the lack of sustained monitoring of ambient concentrations of pollutants associated with gas mining, poor quantification of their emissions, and inability to correlate health symptoms with specific emission events. These uncertainties are best addressed not by conventional monitoring and modeling technology, but by increasingly available advanced techniques for real-time mobile monitoring, microscale modeling and source attribution, and real-time broadcasting of air quality and human health data over the World Wide Web. The combination of contemporary scientific and social media approaches can be used to develop a strategy to detect and quantify emission events from oil and gas facilities, alert nearby residents of these events, and collect associated human health data, all in real time or near-real time. The various technical elements of this strategy are demonstrated based on the results of past, current, and planned future monitoring studies in the Barnett and Eagle Ford shale regions. Resources should not be invested in expanding the conventional air quality monitoring network in the vicinity of oil and gas exploration and production sites. Rather, more contemporary monitoring and data analysis techniques should take the place of older methods to better protect the health of nearby residents and maintain the integrity of the surrounding environment.

Using neural networks for prediction of air pollution index in industrial city

NASA Astrophysics Data System (ADS)

Rahman, P. A.; Panchenko, A. A.; Safarov, A. M.

2017-10-01

This scientific paper is dedicated to the use of artificial neural networks for the ecological prediction of state of the atmospheric air of an industrial city for capability of the operative environmental decisions. In the paper, there is also the described development of two types of prediction models for determining of the air pollution index on the basis of neural networks: a temporal (short-term forecast of the pollutants content in the air for the nearest days) and a spatial (forecast of atmospheric pollution index in any point of city). The stages of development of the neural network models are briefly overviewed and description of their parameters is also given. The assessment of the adequacy of the prediction models, based on the calculation of the correlation coefficient between the output and reference data, is also provided. Moreover, due to the complexity of perception of the «neural network code» of the offered models by the ordinary users, the software implementations allowing practical usage of neural network models are also offered. It is established that the obtained neural network models provide sufficient reliable forecast, which means that they are an effective tool for analyzing and predicting the behavior of dynamics of the air pollution in an industrial city. Thus, this scientific work successfully develops the urgent matter of forecasting of the atmospheric air pollution index in industrial cities based on the use of neural network models.

Quality Control of The Norwegian Uv Monitoring Network.

NASA Astrophysics Data System (ADS)

Johnsen, B.; Mikkelborg, O.; Dahlback, A.; Høiskar, B. A.; Kylling, A.; Edvardsen, K.; Olseth, J. A.; Kjeldstad, B.; Ørbæk, J. B.

A Norwegian UV-monitoring network of GUV multiband radiometers has been operating at locations between 59°N to 79°N since 1995-96. The purpose of the network is to obtain data of high scientific quality, to be used in further assessments related to health- and environmental issues. Maintenance of measurement quality is given priority. Spectral response functions, crucial for calibrations, have been obtained for each instrument. Calibrations are traceable to the Nordic intercomparison of UV radiometers held in Sweden in June 2000. Instruments are inspected daily or weekly. Once a year the instruments are compared to travelling standards operating side by side to the local network radiometers. This enables determination of the longterm drift in instrument responses. For the six years period of operation, the steadiest instrument performed stable within +/-3%, whereas the least steady had a response drop by 23%. Comparisons with a true cosine performing spectroradiometer demonstrate close agreement (+/- 2%) for solar zenith angles less than 80°. Good cosine performance, high spectral sensitivity and weatherproof design demonstrate that the GUV radiometers are particularly suitable for UV monitoring at high latitudes. Complete records of corrected daily CIE-effective doses and online measurements are presented on http://uvnett.nrpa.no/. Gaps in measurement series have been corrected for with a clear sky radiative transfer model and hourly UV sky transmittances estimated from pyranometer data. Measurement data and information about the monitoring network may be found by visiting websites at respectively NRPA, NILU and The University of Oslo; http://www.nrpa.no, http://www.nilu.no/uv, http://www.fys.uio.no/plasma/ozone/. At this stage the quality of the network has reached a satisfactory level and it is possible to move on using UV data in further assessments. Trend analyses and UV forecasting are topics for future work. The network is supported by the ministries of Health and Environment and is administered by The Norwegian Radiation Protection Authority and The Norwegian Pollution Control Authority, the latter through The Norwegian Institute for Air Research.

Implementing wireless sensor networks for architectural heritage conservation

NASA Astrophysics Data System (ADS)

Martínez-Garrido, M. I.; Aparicio, S.; Fort, R.; Izquierdo, M. A. G.; Anaya, J. J.

2012-04-01

Preventive conservation in architectural heritage is one of the most important aims for the development and implementation of new techniques to assess decay, lending to reduce damage before it has occurred and reducing costs in the long term. For that purpose, it is necessary to know all aspects influencing in decay evolution depending on the material under study and its internal and external conditions. Wireless sensor networks are an emerging technology and a minimally invasive technique. The use of these networks facilitates data acquisition and monitoring of a large number of variables that could provoke material damages, such as presence of harmful compounds like salts, dampness, etc. The current project presents different wireless sensors networks (WSN) and sensors used to fulfill the requirements for a complete analysis of main decay agents in a Renaissance church of the 16th century in Madrid (Spain). Current typologies and wireless technologies are studied establishing the most suitable system and the convenience of each one. Firstly, it is very important to consider that microclimate is in close correlation with material deterioration. Therefore a temperature(T) and relative humidity (RH)/moisture network has been developed, using ZigBee wireless communications protocols, and monitoring different points along the church surface. These points are recording RH/T differences depending on the height and the sensor location (inside the material or on the surface). On the other hand, T/RH button sensors have been used, minimizing aesthetical interferences, and concluding which is the most advisable way for monitoring these specific parameters. Due to the fact that microclimate is a complex phenomenon, it is necessary to examine spatial distribution and time evolution at the same time. This work shows both studies since the development expects a long term monitoring. A different wireless network has been deployed to study the effects of pollution caused by other active systems such as a forced-air heating system, the parishioners presence or feasts and other ventilation conditions. Finally weather conditions are registered through a weather station. Outside and inside conditions are compared to incorporate data to the network for a later decay modeling.

The risk assessment of sudden water pollution for river network system under multi-source random emission

NASA Astrophysics Data System (ADS)

Li, D.

2016-12-01

Sudden water pollution accidents are unavoidable risk events that we must learn to co-exist with. In China's Taihu River Basin, the river flow conditions are complicated with frequently artificial interference. Sudden water pollution accident occurs mainly in the form of a large number of abnormal discharge of wastewater, and has the characteristics with the sudden occurrence, the uncontrollable scope, the uncertainty object and the concentrated distribution of many risk sources. Effective prevention of pollution accidents that may occur is of great significance for the water quality safety management. Bayesian networks can be applied to represent the relationship between pollution sources and river water quality intuitively. Using the time sequential Monte Carlo algorithm, the pollution sources state switching model, water quality model for river network and Bayesian reasoning is integrated together, and the sudden water pollution risk assessment model for river network is developed to quantify the water quality risk under the collective influence of multiple pollution sources. Based on the isotope water transport mechanism, a dynamic tracing model of multiple pollution sources is established, which can describe the relationship between the excessive risk of the system and the multiple risk sources. Finally, the diagnostic reasoning algorithm based on Bayesian network is coupled with the multi-source tracing model, which can identify the contribution of each risk source to the system risk under the complex flow conditions. Taking Taihu Lake water system as the research object, the model is applied to obtain the reasonable results under the three typical years. Studies have shown that the water quality risk at critical sections are influenced by the pollution risk source, the boundary water quality, the hydrological conditions and self -purification capacity, and the multiple pollution sources have obvious effect on water quality risk of the receiving water body. The water quality risk assessment approach developed in this study offers a effective tool for systematically quantifying the random uncertainty in plain river network system, and it also provides the technical support for the decision-making of controlling the sudden water pollution through identification of critical pollution sources.

Integrating smart-phone based momentary location tracking with fixed site air quality monitoring for personal exposure assessment.

PubMed

Su, Jason G; Jerrett, Michael; Meng, Ying-Ying; Pickett, Melissa; Ritz, Beate

2015-02-15

Epidemiological studies investigating relationships between environmental exposures from air pollution and health typically use residential addresses as a single point for exposure, while environmental exposures in transit, at work, school or other locations are largely ignored. Personal exposure monitors measure individuals' exposures over time; however, current personal monitors are intrusive and cannot be operated at a large scale over an extended period of time (e.g., for a continuous three months) and can be very costly. In addition, spatial locations typically cannot be identified when only personal monitors are used. In this paper, we piloted a study that applied momentary location tracking services supplied by smart phones to identify an individual's location in space-time for three consecutive months (April 28 to July 28, 2013) using available Wi-Fi networks. Individual exposures in space-time to the traffic-related pollutants Nitrogen Oxides (NOX) were estimated by superimposing an annual mean NOX concentration surface modeled using the Land Use Regression (LUR) modeling technique. Individual's exposures were assigned to stationary (including home, work and other stationary locations) and in-transit (including commute and other travel) locations. For the individual, whose home/work addresses were known and the commute route was fixed, it was found that 95.3% of the time, the individual could be accurately identified in space-time. The ambient concentration estimated at the home location was 21.01 ppb. When indoor/outdoor infiltration, indoor sources of air pollution and time spent outdoors were taken into consideration, the individual's cumulative exposures were 28.59 ppb and 96.49 ppb, assuming a respective indoor/outdoor ratio of 1.33 and 5.00. Integrating momentary location tracking services with fixed-site field monitoring, plus indoor-outdoor air exchange calibration, makes exposure assessment of a very large population over an extended time period feasible. Copyright © 2014 Elsevier B.V. All rights reserved.

Assessment of air pollution impacts on vegetation in South Africa

DOE Office of Scientific and Technical Information (OSTI.GOV)

Botha, A.T.

1989-01-01

Field surveys and biomonitoring network experiments were conducted in selected areas in South Africa to assess possible air pollution damage to vegetation. During field surveys, atmospheric fluoride was identified as an important pollutant that damaged vegetation in residential areas north of Cape Town. Gaseous air pollutants, including acid deposition and acidic mist, probably play a major role in the development of characteristic air pollution injury symptoms observed on pine trees in the Eastern Transvaal area. The impact of urban air pollution in the Cape Town area was evaluated by exposing bio-indicator plants in a network of eight biomonitoring network stationsmore » from June 1985 to May 1988. Sensitive Freesia and Gladiolus cultivars were used to biomonitor atmospheric fluoride, while a green bean cultivar was used as a biomonitor of atmospheric sulfur dioxide and ozone. At one location, bio-indicator plants were simultaneously exposed in a biomonitoring network station, open-top chambers, as well as in open plots. The responses of plants grown under these different conditions were compared.« less

A Decade of Change in NO2 and SO2 over the Canadian Oil Sands As Seen from Space

NASA Technical Reports Server (NTRS)

Mclinden, Chris A.; Fioletov, Vitali; Krotkov, Nickolay A.; Li, Can; Boersma, K. Folkert; Adams, Cristen

2015-01-01

A decade (20052014) of observations from the Ozone Monitoring Instrument (OMI) were used to examine trends in nitrogen dioxide(NO2) and sulfur dioxide (SO2) over a large region of western Canada and the northern United States, with a focus on the Canadian oil sands. In the oil sands, primarily over an area of intensive surface mining, NO2 tropospheric vertical column densities (VCDs) are seen to be increasing by as much as 10year, with the location of the largest trends in a newly developing NO2 lobe well removed from surface monitoring stations. SO2 VCDs in the oil sands have remained approximately constant. The only other significant increase in the region was seen in NO2 over Bakken gas fields in North Dakota which showed increases of up to5yr. By contrast, other locations in the region show substantial declines in both pollutants, providing strong evidence to the efficacy of environmental pollution control measures implemented by both nations. The OMI-derived trends were found to be consistent with those from the Canadian surface monitoring network, although in the case of SO2, it was necessary to apply a correction in order to remove the residual signal from volcanic eruptions present in the OMI data.

Watershed monitoring and modelling and USA regulatory compliance.

PubMed

Turner, B G; Boner, M C

2004-01-01

The aim of the Columbus program was to implement a comprehensive watershed monitoring-network including water chemistry, aquatic biology and alternative sensors to establish water environment health and methods for determining future restoration progress and early warning for protection of drinking water supplies. The program was implemented to comply with USA regulatory requirements including Total Maximum Daily Load (TMDL) rules of the Clean Water Act (CWA) and Source Water Assessment and Protection (SWAP) rules under the Safe Drinking Water Act (SDWA). The USEPA Office of Research and Development and the Water Environment Research Foundation provided quality assurance oversight. The results obtained demonstrated that significant wet weather data is necessary to establish relationships between land use, water chemistry, aquatic biology and sensor data. These measurements and relationships formed the basis for calibrating the US EPA BASINS Model, prioritizing watershed health and determination of compliance with water quality standards. Conclusions specify priorities of cost-effective drainage system controls that attenuate stormwater flows and capture flushed pollutants. A network of permanent long-term real-time monitoring using combination of continuous sensor measurements, water column sampling and aquatic biology surveys and a regional organization is prescribed to protect drinking water supplies and measure progress towards water quality targets.

40 CFR 60.1365 - What records must I keep for continuously monitored pollutants or parameters?

Code of Federal Regulations, 2010 CFR

2010-07-01

... diluent gas, document the relationship between oxygen and carbon dioxide, as specified in § 60.1255. (h... continuously monitored pollutants or parameters? 60.1365 Section 60.1365 Protection of Environment... Recordkeeping § 60.1365 What records must I keep for continuously monitored pollutants or parameters? You must...

40 CFR 60.1365 - What records must I keep for continuously monitored pollutants or parameters?

Code of Federal Regulations, 2011 CFR

2011-07-01

... diluent gas, document the relationship between oxygen and carbon dioxide, as specified in § 60.1255. (h... continuously monitored pollutants or parameters? 60.1365 Section 60.1365 Protection of Environment... Recordkeeping § 60.1365 What records must I keep for continuously monitored pollutants or parameters? You must...

40 CFR 60.1365 - What records must I keep for continuously monitored pollutants or parameters?

Code of Federal Regulations, 2013 CFR

2013-07-01

... diluent gas, document the relationship between oxygen and carbon dioxide, as specified in § 60.1255. (h... continuously monitored pollutants or parameters? 60.1365 Section 60.1365 Protection of Environment... Recordkeeping § 60.1365 What records must I keep for continuously monitored pollutants or parameters? You must...

40 CFR 60.1365 - What records must I keep for continuously monitored pollutants or parameters?

Code of Federal Regulations, 2012 CFR

2012-07-01

... diluent gas, document the relationship between oxygen and carbon dioxide, as specified in § 60.1255. (h... continuously monitored pollutants or parameters? 60.1365 Section 60.1365 Protection of Environment... Recordkeeping § 60.1365 What records must I keep for continuously monitored pollutants or parameters? You must...

40 CFR 60.1365 - What records must I keep for continuously monitored pollutants or parameters?

Code of Federal Regulations, 2014 CFR

2014-07-01

... diluent gas, document the relationship between oxygen and carbon dioxide, as specified in § 60.1255. (h... continuously monitored pollutants or parameters? 60.1365 Section 60.1365 Protection of Environment... Recordkeeping § 60.1365 What records must I keep for continuously monitored pollutants or parameters? You must...

Air Pollution in the World's Megacities.

ERIC Educational Resources Information Center

Richman, Barbara T., Ed.

1994-01-01

Reports findings of the Global Environment Monitoring System study concerning air pollution in the world's megacities. Discusses sources of air pollution, air pollution impacts, air quality monitoring, air quality trends, and control strategies. Provides profiles of the problem in Beijing, Los Angeles, Mexico City, India, Cairo, Sao Paulo, and…

Changing regional emissions of airborne pollutants reflected in the chemistry of snowpacks and wetfall in the Rocky Mountain region, USA, 1993–2012

USGS Publications Warehouse

Ingersoll, George P.; Miller, Debra C.; Morris, Kristi H.; McMurray, Jill A.; Port, Garrett M.; Caruso, Brian

2016-01-01

Wintertime precipitation sample data from 55 Snowpack sites and 17 National Atmospheric Deposition Program (NADP)/National Trends Network Wetfall sites in the Rocky Mountain region were examined to identify long-term trends in chemical concentration, deposition, and precipitation using Regional and Seasonal Kendall tests. The Natural Resources Conservation Service snow-telemetry (SNOTEL) network provided snow-water-equivalent data from 33 sites located near Snowpack- and NADP Wetfall-sampling sites for further comparisons. Concentration and deposition of ammonium, calcium, nitrate, and sulfate were tested for trends for the period 1993–2012. Precipitation trends were compared between the three monitoring networks for the winter seasons and downward trends were observed for both Snowpack and SNOTEL networks, but not for the NADP Wetfall network. The dry-deposition fraction of total atmospheric deposition, relative to wet deposition, was shown to be considerable in the region. Potential sources of regional airborne pollutant emissions were identified from the U.S. Environmental Protection Agency 2011 National Emissions Inventory, and from long-term emissions data for the period 1996–2013. Changes in the emissions of ammonia, nitrogen oxides, and sulfur dioxide were reflected in significant trends in snowpack and wetfall chemistry. In general, ammonia emissions in the western USA showed a gradual increase over the past decade, while ammonium concentrations and deposition in snowpacks and wetfall showed upward trends. Emissions of nitrogen oxides and sulfur dioxide declined while regional trends in snowpack and wetfall concentrations and deposition of nitrate and sulfate were downward.

Status of marine pollution research in South Africa (1960-present).

PubMed

Wepener, V; Degger, N

2012-07-01

The published literature on marine pollution monitoring research in South Africa from 1960 to present was evaluated. There has been a general decline in the number of papers from the 1980s and this can be linked to the absence of a marine pollution monitoring programme in South Africa. General trends observed were that contaminant exposure monitoring of metals predominates the research conducted to date. Monitoring results indicate that there has been a general decrease in metal concentrations in South African coastal waters and concentrations of metals and most organics in mussels are lower than in other industrialised nations. This is reflected in the general pristine nature and high biodiversity of the South African coastline. The establishment of a national marine pollution monitoring framework would stimulate marine pollution research. Copyright © 2012 Elsevier Ltd. All rights reserved.

CityAir app: Mapping air-quality perception using people as sensors

NASA Astrophysics Data System (ADS)

Castell, Nuria; Fredriksen, Mirjam; Cole-Hunter, Thomas; Robinson, Johanna; Keune, Hans; Nieuwenhuijsen, Mark; Bartonova, Alena

2016-04-01

Outdoor air pollution is a major environmental health problem affecting all people in developed and developing countries alike. Ambient (outdoor) air pollution in both cities and rural areas was estimated to cause 3.7 million premature deaths worldwide in 2012. In modern society, people are expending an increasing amount of time in polluted urban environments, thus increasing their exposure and associated health responses. Some cities provide information about air pollution levels to their citizens using air quality monitoring networks. However, due to their high cost and maintenance, the density of the monitoring networks is very low and not capable to capture the high temporal and spatial variability of air pollution. Thus, the citizen lacks a specific answer to the question of "how the air quality is in our surroundings". In the framework of the EU-funded CITI-SENSE project the innovative concept of People as Sensors is being applied to the field of outdoor air pollution. This is being done in eight European cities, including Barcelona, Belgrade, Edinburgh, Haifa, Ljubljana, Oslo, Ostrava and Vienna. People as Sensors defines a measurement model, in which measurements are not only taken by hardware sensors, but in which also humans can contribute with their individual "measurements" such as their subjective perception of air quality and other personal observations. In order to collect the personal observations a mobile app, CityAir, has been developed. CityAir allows citizens to rate the air quality in their surroundings with colour at their current location: green if air quality is very good, yellow if air quality is good, orange if air quality is poor and red if air quality is very poor. The users have also the possibility of indicating the source of pollution (i.e. traffic, industry, wood burning) and writing a comment. The information is on-line and accessible for other app users, thus contributing to create an air-quality map based on citizens' perception. Currently, 400 + Android OS and 180+ iOS smartphone users in 12+ countries have downloaded, installed and used CityAir. The central advantage of the People as Sensors approach is that it can complement costly physical sensor networks. The observations made in smartphones are shared and other persons can consult those to take decisions as for instance choosing a cleaner route to bicycle to work or avoid exercising in certain areas that day. The drawbacks are limited comparability and interpretability, and the inherent uncertainty. CityAir can be seen as a democratic platform for empowering citizens to contribute to environmental governance, facilitating the communication between the citizen and the decision makers. Citizens are encouraged to participate in sharing their perception on the air quality in their city. Citizens become agents of change by uncovering and sharing their perception of air quality in a place that matters to them. We discuss the current challenges: how to involve citizens in the use of the app and how to communicate and visualize the information in a way that is useful for the citizens; point out possible solutions, and pin-point directions for future research.

The Significance of Forest Monitoring Programmes: the Finnish Perspective

NASA Astrophysics Data System (ADS)

Merila, P.; Derome, J.; Lindgren, M.

2007-12-01

Finland has been participating in the ICP Forests programme (the International Co-operative Programme on the Assessment and Monitoring of Air Pollution Effects on Forests) based on international agreements on the long- range transportation of air pollutants (LRTAP) and other associated monitoring programmes (e.g. Forest Focus, ICP Integrated Monitoring, ICP Vegetation) since 1985. The knowledge gained during the years has greatly increased our understanding of the overall condition of our forests and the factors affecting forest condition, the processes underlying forest ecosystem functioning, and the potential threats to our forests posed by human activities, both at home and abroad. The success of the monitoring activities in Finland is largely based on the experience gained during the early 1980's with our own national acidification project and, during the late 1980's and early 1990"s, in a number of regional monitoring projects. Finland's membership of the European Union (entry in 1996) has enabled us to further develop the infrastructure and coverage of both our extensive and intensive level networks. This broadening of our ecological understanding and development of international collaboration are now providing us with an invaluable basis for addressing the new monitoring challenges (biodiversity, climate change). The results gained in our monitoring activities clearly demonstrate the value of long-term monitoring programmes. The main results have been regularly reported both at the European (e.g. http://www.icp- forests.org/Reports.htm) and national level (e.g. http://www.metla.fi/julkaisut/workingpapers/2007/mwp045- en.htm). However, the datasets have not been intensively explored and exploited, and few of the important methodological and ecological findings have been published in peer-reviewed scientific journals. This has, understandably, not been the first priority of the international monitoring programmes. A number of the intensive forest monitoring plots in Finland have recently been included in LTER platforms, thus potentially increasing scientific collaboration between researchers across different governmental institutes and education bodies.

Impact to lung health of haze from forest fires: the Singapore experience.

PubMed

Emmanuel, S C

2000-06-01

From late July to the beginning of October 1997, countries of Southeast Asia experienced severe smoke haze pollution from uncontrolled forest fires mainly in the Indonesian states of Kalimantan and Sumatra. In Singapore, the impact of the 1997 haze was felt in the period from the end of August to the first week of November 1997 as a result of prevailing winds. The Ministry of the Environment monitors ambient air quality by a country-wide telemetric air quality monitoring and management network, with 15 stations located throughout the island, linked via a public telephone network to a central control station at the Environment Building. The monitoring methods used are the United States Environmental Protection Agency (USEPA) reference methods. The Pollutant Standards Index (PSI) developed by the USEPA is used for the reporting of daily air pollution concentrations. Intervals on the PSI scale are related to the potential health effects of the daily measured concentrations of the five major air pollutants: sulfur dioxide, particulate matter (PM10), nitrogen dioxide, ozone and carbon monoxide. Public sector health facilities which come under the Ministry of Health, have computerized patient care systems which enable the routine ongoing surveillance of disease conditions for the period of the haze. Attention during the period of the haze was focused on conditions related to health effects of the haze. Data sources for the monitoring of the lung health effects of the haze included morbidity from public sector outpatient care facilities, accidents and emergency departments, public sector inpatient care facilities and national mortality data. Findings from the health impact of the haze showed that there was a 30% increase in outpatient attendance for haze-related conditions. An increase in PM10 levels from 50 microg/m3 to 150 microg/m3 was significantly associated with increases of 12% of upper respiratory tract illness, 19% asthma and 26% rhinitis. Supplementary findings from scanning the electron microscopic sizing of the haze particles showed that 94% of the particles in the haze were below 2.5 microm in diameter. This was consistent with emissions from combustion sources originating over 500 km from Singapore. This has been of some concern because particles smaller than 2.5 microm in diameter can easily bypass normal body defence metabolism and penetrate deeply into the alveoli of the lungs. During the same period, there was also an increase in accident and emergency attendance for haze-related conditions. There was no significant increase in hospital admissions or in mortality. The present study found that the health effects from the 1997 smoke haze in Singapore were generally mild.

Inter-annual variability of air mass and acidified pollutants transboundary exchange in the north-eastern part of the EANET region

NASA Astrophysics Data System (ADS)

Gromov, Sergey A.; Trifonova-Yakovleva, Alisa; Gromov, Sergey S.

2016-04-01

Anthropogenic emissions, be it exhaust gases or aerosols, stem from multitude of sources and may survive long-range transport within the air masses they were emitted into. So they follow regional and global transport pathways varying under different climatological regimes. Transboundary transfer of pollutants occurs this way and has a significant impact on the ecological situation of the territories neighbouring those of emission sources, as found in a few earlier studies examining the environmental monitoring data [1]. In this study, we employ a relatively facile though robust technique for estimating the transboundary air and concomitant pollutant fluxes using actual or climatological meteorological and air pollution monitoring data. Practically, we assume pollutant transfer being proportional to the horizontal transport of air enclosed in the lower troposphere and to the concentration of the pollutant of interest. The horizontal transport, in turn, is estimated using the mean layer wind direction and strength, or their descriptive statistics at the individual transects of the boundary of interest. The domain of our interest is the segment of Russian continental border in East Asia spanning from 88° E (southern Middle Siberia) to 135° E (Far East at Pacific shore). The data on atmospheric pollutants concentration are available from the Russian monitoring sites of the region-wide Acid Deposition Monitoring Network in East Asia (EANET, http://www.eanet.asia/) Mondy (Baikal area) and Primorskaya (near Vladivostok). The data comprises multi-year continuous measurement of gas-phase and particulate species abundances in air with at least biweekly sampling rate starting from 2000. In the first phase of our study, we used climatological dataset on winds derived from the aerological soundings at Russian stations along the continental border for the 10-year period (1961-1970) by the Research Institute of Hydrometeorological Information - World Data Centre (RIHMI-WDC) [3]. This dataset provides comprehensive monthly statistics on the wind meteorological regime at the stations of interest in a given range of altitudes. Based on long-term source observational data, the dataset is assumed being representative up to date, which allowed us to estimate monthly pollutant fluxes for the years 2006-2008 over segments of the Russian border and its whole [4]. In the current phase of our study, we calculate the inter-annual variations in the transboundary pollutant fluxes for 2000-2012 using longer-term EANET data and transient changes in air mass fluxes derived from the meteorological wind fields from ERA INTERIM re-analysis [5]. We gauge similar average air transport terms and dynamics from the statistical and reanalysis data, which bolsters our earlier findings. The reanalysis data, being naturally more variable, convolutes the variations in net air fluxes and pollutant concentrations into several episodes we emphasise, in addition to the integral pollutant transfer terms we estimate. At last, we discuss on the possibility of climate change effect on the flux strength and dynamics together with regional air quality tendencies in North-East Asia countries. References: Izrael, Yu.A., et al.: Monitoring of the Transboundary Air Pollution Transport. Gidrometeoizdat, Leningrad, 303 p., 187 (in Russian). Akimoto H., et al.: Periodic Report of the State of Acid Deposition in East Asia. Part I: Regional Assessment. EANET-UNEP/RRC.AP-ADORC, 258 p., 2006. Brukhan, F.F.: Aeroclimatic Characteristics of the Mean Winds over USSR (ed. Ignatjushina E.N.). Gidrometeoizdat, Moscow, 54 p., 1984 (in Russian). Gromov S.A., et al.: First-order evaluation of transboundary pollution fluxes in areas of EANET stations in Eastern Siberia and the Russian Far East. EANET Science Bulletin, vol. 3, pp. 195-203, 2013. Dee, D. P., et al.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Quart. J. Royal Met. Soc., 137, 553-597, doi: 10.1002/qj.828, 2011.

Background Mole Fractions of Hydrocarbons in North America Determined from NOAA Global Reference Network Data

NASA Astrophysics Data System (ADS)

Mielke-Maday, I.

2015-12-01

The National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Division (GMD) maintains a global reference network for over 50 trace gas species and analyzes discrete air samples collected by this network throughout the world at the Earth System Research Laboratory in Boulder, Colorado. In particular, flask samples are analyzed for a number of hydrocarbons with policy and health relevance such as ozone precursors, greenhouse gases, and hazardous air pollutants. Because this global network's sites are remote and therefore minimally influenced by local anthropogenic emissions, these data yield information about background ambient mole fractions and can provide a context for observations collected in intensive field campaigns, such as the Front Range Air Pollution and Photochemistry Experiment (FRAPPE), the Southeast Nexus (SENEX) study, and the DISCOVER-AQ deployments. Information about background mole fractions during field campaigns is critical for calculating hydrocarbon enhancements in the region of study and for assessing the extent to which a particular region's local emissions sources contribute to these enhancements. Understanding the geographic variability of the background and its contribution to regional ambient mole fractions is also crucial for the development of realistic regulations. We present background hydrocarbon mole fractions and their ratios in North America using data from air samples collected in the planetary boundary layer at tall towers and aboard aircraft from 2008 to 2014. We discuss the spatial and seasonal variability in these data. We present trends over the time period of measurements and propose possible explanations for these trends.

MLP based LOGSIG transfer function for solar generation monitoring

NASA Astrophysics Data System (ADS)

Hashim, Fakroul Ridzuan; Din, Muhammad Faiz Md; Ahmad, Shahril; Arif, Farah Khairunnisa; Rizman, Zairi Ismael

2018-02-01

Solar panel is one of the renewable energy that can reduce the environmental pollution and have a wide potential of application. The exact solar prediction model will give a big impact on the management of solar power plants and the design of solar energy systems. This paper attempts to use Multilayer Perceptron (MLP) neural network based transfer function. The MLP network can be used to calculate the temperature module (TM) in Malaysia. This can be done by simulating the collected data of four weather variables which are the ambient temperature (TA), local wind speed (VW), solar radiation flux (GT) and the relative humidity (RH) as the input into the neural network. The transfer function will be applied to the 14 types of training. Finally, an equation from the best training algorithm will be deduced to calculate the temperature module based on the input of weather variables in Malaysia.

WaterNet:The NASA Water Cycle Solutions Network

NASA Astrophysics Data System (ADS)

Belvedere, D. R.; Houser, P. R.; Pozzi, W.; Imam, B.; Schiffer, R.; Schlosser, C. A.; Gupta, H.; Martinez, G.; Lopez, V.; Vorosmarty, C.; Fekete, B.; Matthews, D.; Lawford, R.; Welty, C.; Seck, A.

2008-12-01

Water is essential to life and directly impacts and constrains society's welfare, progress, and sustainable growth, and is continuously being transformed by climate change, erosion, pollution, and engineering. Projections of the effects of such factors will remain speculative until more effective global prediction systems and applications are implemented. NASA's unique role is to use its view from space to improve water and energy cycle monitoring and prediction, and has taken steps to collaborate and improve interoperability with existing networks and nodes of research organizations, operational agencies, science communities, and private industry. WaterNet is a Solutions Network, devoted to the identification and recommendation of candidate solutions that propose ways in which water-cycle related NASA research results can be skillfully applied by partner agencies, international organizations, state, and local governments. It is designed to improve and optimize the sustained ability of water cycle researchers, stakeholders, organizations and networks to interact, identify, harness, and extend NASA research results to augment Decision Support Tools that address national needs.

Monitoring-well network and sampling design for ground-water quality, Wind River Indian Reservation, Wyoming

USGS Publications Warehouse

Mason, Jon P.; Sebree, Sonja K.; Quinn, Thomas L.

2005-01-01

The Wind River Indian Reservation, located in parts of Fremont and Hot Springs Counties, Wyoming, has a total land area of more than 3,500 square miles. Ground water on the Wind River Indian Reservation is a valuable resource for Shoshone and Northern Arapahoe tribal members and others who live on the Reservation. There are many types of land uses on the Reservation that have the potential to affect the quality of ground-water resources. Urban areas, rural housing developments, agricultural lands, landfills, oil and natural gas fields, mining, and pipeline utility corridors all have the potential to affect ground-water quality. A cooperative study was developed between the U.S. Geological Survey and the Wind River Environmental Quality Commission to identify areas of the Reservation that have the highest potential for ground-water contamination and develop a comprehensive plan to monitor these areas. An arithmetic overlay model for the Wind River Indian Reservation was created using seven geographic information system data layers representing factors with varying potential to affect ground-water quality. The data layers used were: the National Land Cover Dataset, water well density, aquifer sensitivity, oil and natural gas fields and petroleum pipelines, sites with potential contaminant sources, sites that are known to have ground-water contamination, and National Pollutant Discharge Elimination System sites. A prioritization map for monitoring ground-water quality on the Reservation was created using the model. The prioritization map ranks the priority for monitoring ground-water quality in different areas of the Reservation as low, medium, or high. To help minimize bias in selecting sites for a monitoring well network, an automated stratified random site-selection approach was used to select 30 sites for ground-water quality monitoring within the high priority areas. In addition, the study also provided a sampling design for constituents to be monitored, sampling frequency, and a simple water-table level observation well network.

IOC/WMO Workshop on Marine Pollution Monitoring (3rd, New Delhi, India, February 11-15, 1980). Summary Report. Workshop Report No. 22.

ERIC Educational Resources Information Center

United Nations Educational, Scientific, and Cultural Organization, Paris (France). Intergovernmental Oceanographic Commission.

Provided is a summary report of the third IOC/WMO (Intergovernmental Oceanographic Commission/World Meteorological Organization) workshop of marine pollution monitoring. Summaries are presented in nine sections, including: (1) workshop opening; (2) welcoming addresses; (3) reports on the Marine Pollution (Petroleum) Monitoring Pilot Project…

Perfluorooctane sulfonate (PFOS) contamination of fish in urban lakes: a prioritization methodology for lake management.

PubMed

Xiao, Feng; Gulliver, John S; Simcik, Matt F

2013-12-15

The contamination of urban lakes by anthropogenic pollutants such as perfluorooctane sulfonate (PFOS) is a worldwide environmental problem. Large-scale, long-term monitoring of urban lakes requires careful prioritization of available resources, focusing efforts on potentially impaired lakes. Herein, a database of PFOS concentrations in 304 fish caught from 28 urban lakes was used for development of an urban-lake prioritization framework by means of exploratory data analysis (EDA) with the aid of a geographical information system. The prioritization scheme consists of three main tiers: preliminary classification, carried out by hierarchical cluster analysis; predictor screening, fulfilled by a regression tree method; and model development by means of a neural network. The predictive performance of the newly developed model was assessed using a training/validation splitting method and determined by an external validation set. The application of the model in the U.S. state of Minnesota identified 40 urban lakes that may contain elevated levels of PFOS; these lakes were not previously considered in PFOS monitoring programs. The model results also highlight ongoing industrial/commercial activities as a principal determinant of PFOS pollution in urban lakes, and suggest vehicular traffic as an important source and surface runoff as a primary pollution carrier. In addition, the EDA approach was further compared to a spatial interpolation method (kriging), and their advantages and disadvantages were discussed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Monitoring Light Pollution on the Starlight Reserve of Montsec

NASA Astrophysics Data System (ADS)

Ribas, S. J.; Paricio, S.; Canal-Domingo, R.; Gustems, L.; Calvo, C. O.

2015-05-01

Montsec Mountains are a special protected place in Catalonia (NE of Iberian Peninsula). Since 2013 the site has been declared Starlight Reserve and Touristic Destination. In the last three years different projects took place in Montsec to evaluate the quality of night sky and the effects of Light Pollution of nearby (and not so nearby) municipalities. Using SQM techniques in RoadRunner configuration (installed on a car) we have evaluated all the region (1 600 km^2) and we determined the distribution of night sky brightness detecting some excellent areas with values around 21.5--22.0 mags. In addition we have evaluated the effects of the closest big city (Lleida with around 200 000 inhabitants) and we have estimated long distance effects of this city on the natural sky. The effect is detected on zenith up to 25 km away from the city. These data show the critical problem of the long-distance effects of LP on protected areas. To complete the monitoring of the region, a new SQM network is ongoing in cooperation with Parc Astronòmic Montsec and Catalan Service against Light Pollution. During 2014 six SQM permanent detectors are starting their measurements around the area of Montsec and major cities that affects this protected area. This data could be combined with meteorological data (clouds, humidity, etc) in some of the evaluation sites.

Developing a methodology to predict PM10 concentrations in urban areas using generalized linear models.

PubMed

Garcia, J M; Teodoro, F; Cerdeira, R; Coelho, L M R; Kumar, Prashant; Carvalho, M G

2016-09-01

A methodology to predict PM10 concentrations in urban outdoor environments is developed based on the generalized linear models (GLMs). The methodology is based on the relationship developed between atmospheric concentrations of air pollutants (i.e. CO, NO2, NOx, VOCs, SO2) and meteorological variables (i.e. ambient temperature, relative humidity (RH) and wind speed) for a city (Barreiro) of Portugal. The model uses air pollution and meteorological data from the Portuguese monitoring air quality station networks. The developed GLM considers PM10 concentrations as a dependent variable, and both the gaseous pollutants and meteorological variables as explanatory independent variables. A logarithmic link function was considered with a Poisson probability distribution. Particular attention was given to cases with air temperatures both below and above 25°C. The best performance for modelled results against the measured data was achieved for the model with values of air temperature above 25°C compared with the model considering all ranges of air temperatures and with the model considering only temperature below 25°C. The model was also tested with similar data from another Portuguese city, Oporto, and results found to behave similarly. It is concluded that this model and the methodology could be adopted for other cities to predict PM10 concentrations when these data are not available by measurements from air quality monitoring stations or other acquisition means.

Diseases Burden of Chronic Obstructive Pulmonary Disease (COPD) Attributable to Ground-Level Ozone in Thailand: Estimates Based on Surface Monitoring Measurements Data.

PubMed

Pinichka, Chayut; Bundhamcharoen, Kanitta; Shibuya, Kenji

2015-05-14

Ambient ozone (O3) pollution has increased globally since preindustrial times. At present, O3 is one of the major air pollution concerns in Thailand, and is associated with health impacts such as chronic obstructive pulmonary disease (COPD). The objective of our study is to estimate the burden of disease attributed to O3 in 2009 in Thailand based on empirical evidence. We estimated disability-adjusted life years (DALYs) attributable to O3 using the comparative risk assessment framework in the Global Burden of Diseases (GBD) study. We quantified the population attributable fraction (PAF), integrated from Geographic Information Systems (GIS)-based spatial interpolation, the population distribution of exposure, and the exposure-response coefficient to spatially characterize exposure to ambient O3 pollution on a national scale. Exposure distribution was derived from GIS-based spatial interpolation O3 exposure model using Pollution Control Department Thailand (PCD) surface air pollution monitor network sources. Relative risk (RR) and population attributable fraction (PAF) were determined using health impact function estimates for O3. PAF (%) of COPD attributable to O3 were determined by region: at approximately, Northern=2.1, Northeastern=7.1, Central=9.6, Eastern=1.75, Western=1.47 and Southern=1.74. The total COPD burden attributable to O3 for Thailand in 2009 was 61,577 DALYs. Approximately 0.6% of the total DALYs in Thailand is male: 48,480 DALYs; and female: 13,097 DALYs. This study provides the first empirical evidence on the health burden (DALYs) attributable to O3 pollution in Thailand. Varying across regions, the disease burden attributable to O3 was 0.6% of the total national burden in 2009. Better empirical data on local specific sites, e.g. urban and rural areas, alternative exposure assessment, e.g. land use regression (LUR), and a local concentration-response coefficient are required for future studies in Thailand.

Development of improved wildfire smoke exposure estimates for health studies in the western U.S.

NASA Astrophysics Data System (ADS)

Ivey, C.; Holmes, H.; Loria Salazar, S. M.; Pierce, A.; Liu, C.

2016-12-01

Wildfire smoke exposure is a significant health concern in the western U.S. because large wildfires have increased in size and frequency over the past four years due to drought conditions. The transport phenomena in complex terrain and timing of the wildfire emissions make the smoke plumes difficult to simulate using conventional air quality models. Monitoring data can be used to estimate exposure metrics, but in rural areas the monitoring networks are too sparse to calculate wildfire exposure metrics for the entire population in a region. Satellite retrievals provide global, spatiotemporal air quality information and are used to track pollution plumes, estimate human exposures, model emissions, and determine sources (i.e., natural versus anthropogenic) in regulatory applications. Particulate matter (PM) exposures can be estimated using columnar aerosol optical depth (AOD), where satellite AOD retrievals serve as a spatial surrogate to simulate surface PM gradients. These exposure models have been successfully used in health effects studies in the eastern U.S. where complex mountainous terrain and surface reflectance do not limit AOD retrival from satellites. Using results from a chemical transport model (CTM) is another effective method to determine spatial gradients of pollutants. However, the CTM does not adequately capture the temporal and spatial distribution of wildfire smoke plumes. By combining the spatiotemporal pollutant fields from both satellite retrievals and CTM results with ground based pollutant observations the spatial wildfire smoke exposure model can be improved. This work will address the challenge of understanding the spatiotemporal distributions of pollutant concentrations to model human exposures of wildfire smoke in regions with complex terrain, where meteorological conditions as well as emission sources significantly influence the spatial distribution of pollutants. The focus will be on developing models to enhance exposure estimates of elevated PM and ozone concentrations from wildfire smoke plumes in the western U.S.

Organic micropollutants discharged by combined sewer overflows - Characterisation of pollutant sources and stormwater-related processes.

PubMed

Launay, Marie A; Dittmer, Ulrich; Steinmetz, Heidrun

2016-11-01

To characterise emissions from combined sewer overflows (CSOs) regarding organic micropollutants, a monitoring study was undertaken in an urban catchment in southwest Stuttgart, Germany. The occurrence of 69 organic micropollutants was assessed at one CSO outfall during seven rain events as well as in the sewage network at the influent of the wastewater treatment plant (WWTP) and in the receiving water. Several pollutant groups like pharmaceuticals and personal care products (PPCPs), urban biocides and pesticides, industrial chemicals, organophosphorus flame retardants, plasticisers and polycyclic aromatic hydrocarbons (PAHs) were chosen for analysis. Out of the 69 monitored substances, 60 were detected in CSO discharges. The results of this study show that CSOs represent an important pathway for a wide range of organic micropollutants from wastewater systems to urban receiving waters. For most compounds detected in CSO samples, event mean concentrations varied between the different events in about one order of magnitude range. When comparing CSO concentrations with median wastewater concentrations during dry weather, two main patterns could be observed depending on the source of the pollutant: (i) wastewater is diluted by stormwater; (ii) stormwater is the most important source of a pollutant. Both wastewater and stormwater only play an important role in pollutant concentration for a few compounds. The proportion of stormwater calculated with the conductivity is a suitable indicator for the evaluation of emitted loads of dissolved wastewater pollutants, but not for all compounds. In fact, this study demonstrates that remobilisation of in-sewer deposits contributed from 10% to 65% to emissions of carbamazepine in CSO events. The contribution of stormwater to CSO emitted loads was higher than 90% for all herbicides as well as for PAHs. Regarding the priority substance di(2-ethylhexyl)phthalate (DEHP), this contribution varied between 39% and 85%. The PAH concentrations found along the river indicate environmental risk, especially during rainfall events. Copyright © 2016 Elsevier Ltd. All rights reserved.

Air quality remote sensing over alpine regions with METEOSAT SEVIRI

NASA Astrophysics Data System (ADS)

Emili, E.; Popp, C.; Petitta, M.; Riffler, M.; Wunderle, S.

2009-04-01

It is well demonstrated that small aerosol particles or particulate matter (PM10 and PM2.5) affect air quality and can have severe effects on human's health. Hence, it is of great interest for public institutions to have an efficient PM monitoring network. In the last decades this data has been provided from ground-based instruments. Moreover, due to the fast development of space-borne remote sensing instruments, we can now be able to take advantage of air pollution measurements from space, which bears the potential to fill up the gap of spatial coverage from ground-based networks. This also improves the capability to assess air pollutants transport properties together with a better implementation in forecasting data assimilation procedures. In this study we examine the possibility of using data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI), on-board of the geostationary Meteosat Second Generation (MSG) platform, to provide PM concentrations values over Switzerland. SEVIRI's high temporal resolution (15 minutes) could be very useful in investigating the daily behaviour of air pollutants and therefore be a good complement to measurements from polar orbiting sensors (e.g. MODIS). Switzerland is of particular interest because of its mountainous orography that hampers pollutants dispersion. Further, major transalpine connection routes, often characterised by high traffic load, act as a significant air pollution source. The south of Switzerland is also occasionally influenced by pollutants transported from the highly industrialised Po Valley in northern Italy. We investigate the existence of a linear relation between the SEVIRI retrieved AOD (Aerosol Optical Depth) and the PM concentration obtained from the ground-based air quality network NABEL (Nationales Beobachtungsnetz fuer Luftfremdstoffe). The temporal trend of this two quantities shows a significant relationship over various locations. The correlation coefficient is in some cases higher than 0.6, indicating the possibility of estimating PM concentrations from SEVIRI AOD with a reasonable uncertainty using a statistical empirical linear model. The quality of this approach is highly influenced by the seasonal variability and by the meteorological conditions. We also include meteorological data in order to investigate the observed correlation and to improve the statistical empirical model. Finally, the possible sources of errors for this approach are examined.

Modeling urban air pollution in Budapest using WRF-Chem model

NASA Astrophysics Data System (ADS)

Kovács, Attila; Leelőssy, Ádám; Lagzi, István; Mészáros, Róbert

2017-04-01

Air pollution is a major problem for urban areas since the industrial revolution, including Budapest, the capital and largest city of Hungary. The main anthropogenic sources of air pollutants are industry, traffic and residential heating. In this study, we investigated the contribution of major industrial point sources to the urban air pollution in Budapest. We used the WRF (Weather Research and Forecasting) nonhydrostatic mesoscale numerical weather prediction system online coupled with chemistry (WRF-Chem, version 3.6).The model was configured with three nested domains with grid spacings of 15, 5 and 1 km, representing Central Europe, the Carpathian Basin and Budapest with its surrounding area. Emission data was obtained from the National Environmental Information System. The point source emissions were summed in their respective cells in the second nested domain according to latitude-longitude coordinates. The main examined air pollutants were carbon monoxide (CO) and nitrogen oxides (NOx), from which the secondary compound, ozone (O3) forms through chemical reactions. Simulations were performed under different weather conditions and compared to observations from the automatic monitoring site of the Hungarian Air Quality Network. Our results show that the industrial emissions have a relatively weak role in the urban background air pollution, confirming the effect of industrial developments and regulations in the recent decades. However, a few significant industrial sources and their impact area has been demonstrated.

PM10 and gaseous pollutants trends from air quality monitoring networks in Bari province: principal component analysis and absolute principal component scores on a two years and half data set

PubMed Central

2014-01-01

Background The chemical composition of aerosols and particle size distributions are the most significant factors affecting air quality. In particular, the exposure to finer particles can cause short and long-term effects on human health. In the present paper PM10 (particulate matter with aerodynamic diameter lower than 10 μm), CO, NOx (NO and NO2), Benzene and Toluene trends monitored in six monitoring stations of Bari province are shown. The data set used was composed by bi-hourly means for all parameters (12 bi-hourly means per day for each parameter) and it’s referred to the period of time from January 2005 and May 2007. The main aim of the paper is to provide a clear illustration of how large data sets from monitoring stations can give information about the number and nature of the pollutant sources, and mainly to assess the contribution of the traffic source to PM10 concentration level by using multivariate statistical techniques such as Principal Component Analysis (PCA) and Absolute Principal Component Scores (APCS). Results Comparing the night and day mean concentrations (per day) for each parameter it has been pointed out that there is a different night and day behavior for some parameters such as CO, Benzene and Toluene than PM10. This suggests that CO, Benzene and Toluene concentrations are mainly connected with transport systems, whereas PM10 is mostly influenced by different factors. The statistical techniques identified three recurrent sources, associated with vehicular traffic and particulate transport, covering over 90% of variance. The contemporaneous analysis of gas and PM10 has allowed underlining the differences between the sources of these pollutants. Conclusions The analysis of the pollutant trends from large data set and the application of multivariate statistical techniques such as PCA and APCS can give useful information about air quality and pollutant’s sources. These knowledge can provide useful advices to environmental policies in order to reach the WHO recommended levels. PMID:24555534

Open hardware, low cost, air quality stations for monitoring ozone in coastal area

NASA Astrophysics Data System (ADS)

Lima, Marco; Donzella, Davide; Pintus, Fabio; Fedi, Adriano; Ferrari, Daniele; Massabò, Marco

2014-05-01

Ozone concentrations in urban and coastal area are a great concern for citizens and, consequently regulator. In the last 20 years the Ozone concentration is almost doubled and it has attracted the public attention because of the well know harmful impacts on human health and biosphere in general. Official monitoring networks usually comprise high precision, high accuracy observation stations, usually managed by public administrations and environmental agency; unfortunately due to their high costs of installation and maintenance, the monitoring stations are relatively sparse. This kind of monitoring networks have been recognized to be unsuitable to effectively characterize the high variability of air quality, especially in areas where pollution sources are various and often not static. We present a prototype of a low cost station for air quality monitoring, specifically developed for complementing the official monitoring stations improving the representation of air quality spatial distribution. We focused on a semi-professional product that could guarantee the highest reliability at the lowest possible cost, supported by a consistent infrastructure for data management. We test two type of Ozone sensor electrochemical and metal oxide. This work is integrated in the ACRONET Paradigm ® project: an open-hardware platform strongly oriented on environmental monitoring. All software and hardware sources will be available on the web. Thus, a computer and a small amount of work tools will be sufficient to create new monitoring networks, with the only constraint to share all the data obtained. It will so possible to create a real "sensing community". The prototype is currently able to measure ozone level, temperature and relative humidity, but soon, with the upcoming changes, it will be able also to monitor dust, carbon monoxide and nitrogen dioxide, always through the use of commercial sensors. The sensors are grouped in a compact board that interfaces with a data-logger able to transmit data to a dedicated server through a GPRS module (no ad hoc radio infrastructure needed). Due to the GPRS low latency transmission the data are transmitted in near-real time. The prototype has an independent power supply. The sensors outputs are directly compared with the measurement of the official fixed monitoring stations. We present preliminary tests of a ozone level assessment obtained without laboratory calibration during a first field campaign in Savona (Italy); the preliminary verification and test show reasonable agreement between low cost sensors and fixed monitoring station ozone level trends (low cost sensors detect gas concentration at ppb level). The preliminary results are promising for complementing the fixed official monitoring networks with low-cost sensors.

Spatiotemporal distribution of airborne elements monitored with the moss bags technique in the Greater Thriasion Plain, Attica, Greece.

PubMed

Saitanis, C J; Frontasyeva, M V; Steinnes, E; Palmer, M W; Ostrovnaya, T M; Gundorina, S F

2013-01-01

The well-known moss bags technique was applied in the heavily polluted Thriasion Plain region, Attica, Greece, in order to study the spatiotemporal distribution, in the atmosphere, of the following 32 elements: Na, Al, Cl, Ca, Sc, Ti, V, Cr, Mn, Fe, Ni, Co, Zn, As, Se, Br, Sr, Mo, Sb, I, Ba, La, Ce, Sm, Tb, Dy, Yb, Hf, Ta, Hg, Th, and U. The moss bags were constituted of Sphagnum girgensohnii materials. The bags were exposed to ambient air in a network of 12 monitoring stations scattered throughout the monitoring area. In order to explore the temporal variation of the pollutants, four sets of moss bags were exposed for 3, 6, 9, and 12 months. Instrumental neutral activation analysis was used for the determinations of the elements. The data were analyzed using the Pearson correlations, the partial redundancy analysis, and the biplot statistical methods. Some pairs of elements were highly correlated indicating a probable common source of origin. The levels of the measured pollutants were unevenly distributed throughout the area and different pollutants exhibited different spatial patterns. In general, higher loads were observed in the stations close to and within the industrial zone. Most of the measured elements (e.g., Al, Ca, Ni, I, Zn, Cr, and As) exhibited a monotonic accumulation trend over time. Some elements exhibited different dynamics. The elements Mn, Mo, and Hg showed a decreasing trend, probably due to leaching and/or volatilization processes over time. Na and Br initially showed an increasing trend during the winter and early spring periods but decreased drastically during the late warm period. The results further suggest that the moss bags technique would be considered valuable for the majority of elements but should be used with caution in the cases of elements vulnerable to leaching and/or volatilization. It also suggests that the timing and the duration of the exposure of moss materials should be considered in the interpretation of the results.

Polycyclic Aromatic Hydrocarbons (PAHs) and Hopanes in Plastic Resin Pellets as Markers of Oil Pollution via International Pellet Watch Monitoring.

PubMed

Yeo, Bee Geok; Takada, Hideshige; Hosoda, Junki; Kondo, Atsuko; Yamashita, Rei; Saha, Mahua; Maes, Thomas

2017-08-01

Oil pollution in the marine environment is an unavoidable problem due to chronic input from local sources, particularly in urban areas and oil spills. Oil pollution not only causes immediate physical damages to surrounding wildlife but also some components, including higher molecular weight PAHs, can persist in the environment for many years and pose insidious threats to the ecosystem. Long-term and nontargeted monitoring of oil pollution is important. This paper examines the ability of International Pellet Watch (IPW) for initial identification and monitoring of oil pollution by analysing PAHs and hopanes in plastic pellet samples collected globally by volunteers. PAH concentrations with the sum of 28 parent and methyl PAHs vary geographically, ranging from 0.035 to 24.4 µg/g-pellet, in line with the presence or absence of local oil pollution sources, such as oil refineries or oil spill sites. This suggests that PAHs can be used to monitor petroleum pollution in IPW. A colour-coded categorization for PAH concentrations within IPW monitoring also is established to facilitate data presentation and understanding. PAH concentrations are generally higher in Western Europe, especially around the North Sea shorelines, moderate in East Asia and North America, and lower in South East Asia, Oceania, South America, and Africa. Hopane concentrations, with a smaller spatial variation (1.7-101 µg/g-pellet), showed no spatial pattern. This result and the poor correlation between hopanes and PAHs suggest that hopane concentrations alone are unsuited to identify petroleum pollution. However, hopane compositions can be used for fingerprinting sources of oil pollution. Thus, both PAHs and hopanes in IPW allow for low cost, remote monitoring of global oil pollution.

Air quality concerns of unconventional oil and natural gas production.

PubMed

Field, R A; Soltis, J; Murphy, S

2014-05-01

Increased use of hydraulic fracturing ("fracking") in unconventional oil and natural gas (O & NG) development from coal, sandstone, and shale deposits in the United States (US) has created environmental concerns over water and air quality impacts. In this perspective we focus on how the production of unconventional O & NG affects air quality. We pay particular attention to shale gas as this type of development has transformed natural gas production in the US and is set to become important in the rest of the world. A variety of potential emission sources can be spread over tens of thousands of acres of a production area and this complicates assessment of local and regional air quality impacts. We outline upstream activities including drilling, completion and production. After contrasting the context for development activities in the US and Europe we explore the use of inventories for determining air emissions. Location and scale of analysis is important, as O & NG production emissions in some US basins account for nearly 100% of the pollution burden, whereas in other basins these activities make up less than 10% of total air emissions. While emission inventories are beneficial to quantifying air emissions from a particular source category, they do have limitations when determining air quality impacts from a large area. Air monitoring is essential, not only to validate inventories, but also to measure impacts. We describe the use of measurements, including ground-based mobile monitoring, network stations, airborne, and satellite platforms for measuring air quality impacts. We identify nitrogen oxides, volatile organic compounds (VOC), ozone, hazardous air pollutants (HAP), and methane as pollutants of concern related to O & NG activities. These pollutants can contribute to air quality concerns and they may be regulated in ambient air, due to human health or climate forcing concerns. Close to well pads, emissions are concentrated and exposure to a wide range of pollutants is possible. Public health protection is improved when emissions are controlled and facilities are located away from where people live. Based on lessons learned in the US we outline an approach for future unconventional O & NG development that includes regulation, assessment and monitoring.

[Characteristics and loads of key sources of pollutions discharged into Beishi River, Changzhou City].

PubMed

Li, Chun-Ping; Jiang, Jian-Guo; Chen, Ai-Mei; Wu, Jia-Ling; Fan, Xiu-Juan; Ye, Bin

2010-11-01

Choosing the Beishi river, Changzhou City as the study area, the sewage generation, pollutants characteristics and sewage discharge in catchment area of Beishi river were conducted, detailed investigated and monitored. After using pollution coefficients, the yearly loads of all sources of pollutions were calculated to determine the highest sewage. The results showed that: except pH, the high concentration of SS, COD, BOD5, ammonia nitrogen, TN and TP discharged from MSW collecting houses, MSW transfer stations, public toilets and dining in Changzhou city far exceeded the "Integrated Wastewater Discharge Standard" (GB 8978-1996) and "Effluent Discharged into the City Sewer Water Quality Standards" (CJ 3082-1999). Among which: the highest concentration of COD discharged from MSW transfer stations was up to 51 700 mg/L, while the ammonia nitrogen and TN were as high as 1 616 mg/L and 2 044 mg/L in the toilet wastewater. In addition to this, the ratio of wastewater discharged directly into the river through storm water pipe network was higher from MSW houses, MSW transfer stations, public toilets, dining and other waste in Changzhou city. The 125.2 t/a of COD and 40.53 t/a of BOD5 were the two highest concentrations of various sources of pollution. The highest annual polluting loads discharged into Beishi river is dining, followed by the sanitation facilities. Therefore, cutting pollution control of food and sanitation facilities along the river is particularly urgent.

A MEMS approach to determine the biochemical oxygen demand (BOD) of wastewaters

NASA Astrophysics Data System (ADS)

Recoules, L.; Migaou, A.; Dollat, X.; Thouand, G.; Gue, A. M.; Boukabache, A.

2017-07-01

A MEMS approach to obtain an efficient tool for the evaluation of the biochemical oxygen demand (BOD) of wastewaters is introduced. Its operating principle is based on the measurement of oxygen concentration in water samples containing organic pollutants and specific bacteria. The microsystem has been designed to perform multiple and parallel measurements in a poly-wells microfluidic device. The monitoring of the bacterial activity is ensured by optical sensors incorporated in each well of the fluidic network. By using an optode sensor, it is hereby demonstrated that this approach is efficient to measure organic pollutants by testing different Luria Bertani buffer dilutions. These results also show that it is possible to reduce the duration of measurements from 5 d (BOD5) of the standard approach to few hours, typically 3 h-5 h.

Characterization of air pollution in Mexico City by remote sensing

NASA Astrophysics Data System (ADS)

Grutter, Michel; Arellano, Josue; Bezanilla, Alejandro; Friedrich, Martina; Plaza, Eddy; Rivera, Claudia; Stremme, Wolfgang

2014-05-01

Megacities, like the Mexico City Metropolitan Area, are home to a large fraction of the population of the world and a consequence is that they are one of the biggest sources of contaminants and greenhouse gases emitted to the atmosphere. The pollution is visible form space through remote sensing instruments, however, satellite observations like those with NADIR viewing geometries have decreased sensitivity near the Earth's surface and the analytical algorithms are in generally optimized to detect pollution plumes in the free troposphere or above. Ground-based observations are thus necessary in order to reduce uncertainties from satellite products. As we will show, Mexico City and its surroundings is well characterized by ground-based remote sensing measurements like from two stations with solar-absorption FTIR spectrometers and a newly formed network of MAX-DOAS and LIDAR instruments. Examples will be provided of how the evolution of the mixing-layer height is characterized and the vertical column densities and profiles of gases in and outside the urban area are continuously monitored. The combination of ground-based and space-borne measurements are used to improve the current knowledge in the spatial and temporal distribution of key pollutants from this megacity.

Aspects regarding the use of the INFREP network for identifying possible seismic precursors

NASA Astrophysics Data System (ADS)

Dolea, Paul; Cristea, Octavian; Dascal, Paul Vladut; Moldovan, Iren-Adelina; Biagi, Pier Francesco

In the last decades, one of the main research directions in identifying seismic precursors involved monitoring VLF (Very Low Frequency) and LF (Low Frequency) radio waves and analysing their propagation characteristics. Essentially this method consists of monitoring different available VLF and LF transmitters from long distance reception points. The received signal has two major components: the ground wave and the sky wave, where the sky wave propagates by reflection on the lower layers of the ionosphere. It is assumed that before and during major earthquakes, unusual changes may occur in the lower layers of the ionosphere, such as the modification of the charged particles number density and the altitude of the reflection zone. Therefore, these unusual changes in the ionosphere may generate unusual variations in the received signal level. The International Network for Frontier Research on Earthquake Precursors (INFREP) was developed starting with 2009 and consists of several dedicated VLF and LF radio receivers used for monitoring various radio transmitters located throughout Europe. The receivers' locations were chosen so that the propagation path from these VLF/LF stations would pass over high seismicity regions while others were chosen to obtain different control paths. The monitoring receivers are capable of continuously measuring the received signal amplitude from the VLF/LF stations of interest. The recorded data is then stored and sent to an INFREP database, which is available on the Internet for scientific researchers. By processing and analysing VLF and LF data samples, collected at different reception points and at different periods of the year, one may be able to identify some distinct patterns in the envelope of the received signal level over time. Significant deviations from these patterns may have local causes such as the electromagnetic pollution at the monitoring point, regional causes like existing electrical storms over the propagation path or even global causes generated by high-intensity solar flares. As a consequence, classifying these perturbations and minimizing them (when possible) would represent an important step towards identifying significant pattern deviations caused by seismic activities. Taken into consideration some of the issues mentioned above, this paper intends to present some aspects meant to improve the overall performance of the existing INFREP network. The signal-to-noise ratio improvement of the monitoring receiver may be achieved by relocating the antenna (or even the entire monitoring system if possible) in areas with less electromagnetic pollution within the VLF and LF bands. Other solution may involve replacing the existing electric ;whip; antennas with magnetic loop antennas. Regarding the measuring method, long-term averaging of the received signal to reduce the electromagnetic noise should be carefully applied. If the averaging time is too long, there is a risk that, during a seismic event, the details of the received signal envelope would be lost. Moreover, this may reduce the possibility of making correlations between the monitored stations and INFREP receivers in case of sudden ERP (Effective Radiated Power) variations of the VLF/LF stations. For the same reason, the time synchronization of the recorded data using (for instance) GPS technology is highly recommended. Other aspects related to the overall performance improvement of the INFREP network consist of monitoring other VLF/LF stations such as the Krasnodar station (south of Russia), part of the ALPHA/RSDN-20 VLF navigation system, or the 77.5 kHz DCF77 time signal transmitter (near Frankfurt am Main, Germany). Moreover, the installation of a new reception point in Romania (near Cluj-Napoca) for monitoring the Vrancea area (within the Carpathians Mountains) and the Adriatic region will provide complementary scientific data within the network.

Review of air pollution and health impacts in Malaysia.

PubMed

Afroz, Rafia; Hassan, Mohd Nasir; Ibrahim, Noor Akma

2003-06-01

In the early days of abundant resources and minimal development pressures, little attention was paid to growing environmental concerns in Malaysia. The haze episodes in Southeast Asia in 1983, 1984, 1991, 1994, and 1997 imposed threats to the environmental management of Malaysia and increased awareness of the environment. As a consequence, the government established Malaysian Air Quality Guidelines, the Air Pollution Index, and the Haze Action Plan to improve air quality. Air quality monitoring is part of the initial strategy in the pollution prevention program in Malaysia. Review of air pollution in Malaysia is based on the reports of the air quality monitoring in several large cities in Malaysia, which cover air pollutants such as Carbon monoxide (CO), Sulphur Dioxide (SO2), Nitrogen Dioxide (NO2), Ozone (O3), and Suspended Particulate Matter (SPM). The results of the monitoring indicate that Suspended Particulate Matter (SPM) and Nitrogen Dioxide (NO2) are the predominant pollutants. Other pollutants such as CO, O(x), SO2, and Pb are also observed in several big cities in Malaysia. The air pollution comes mainly from land transportation, industrial emissions, and open burning sources. Among them, land transportation contributes the most to air pollution. This paper reviews the results of the ambient air quality monitoring and studies related to air pollution and health impacts.

Biological Monitoring of Air Pollutants and Its Influence on Human Beings

PubMed Central

Cen, Shihong

2015-01-01

Monitoring air pollutants via plants is an economic, convenient and credible method compared with the traditional ways. Plants show different damage symptoms to different air pollutants, which can be used to determine the species of air pollutants. Besides, pollutants mass concentration scope can be estimated by the damage extent of plants and the span of polluted time. Based on the domestic and foreign research, this paper discusses the principles, mechanism, advantages and disadvantages of plant-monitoring, and exemplifies plenty of such plants and the minimum mass concentration and pollution time of the plants showing damage symptoms. Finally, this paper introduced the human health effects of air pollutants on immune function of the body, such as decrease of the body's immune function, decline of lung function, respiratory and circulatory system changes, inducing and promoting human allergic diseases, respiratory diseases and other diseases. PMID:26628931

Moball-Buoy Network: A Near-Real-Time Ground-Truth Distributed Monitoring System to Map Ice, Weather, Chemical Species, and Radiations, in the Arctic

NASA Astrophysics Data System (ADS)

Davoodi, F.; Shahabi, C.; Burdick, J.; Rais-Zadeh, M.; Menemenlis, D.

2014-12-01

The work had been funded by NASA HQ's office of Cryospheric Sciences Program. Recent observations of the Arctic have shown that sea ice has diminished drastically, consequently impacting the environment in the Arctic and beyond. Certain factors such as atmospheric anomalies, wind forces, temperature increase, and change in the distribution of cold and warm waters contribute to the sea ice reduction. However current measurement capabilities lack the accuracy, temporal sampling, and spatial coverage required to effectively quantify each contributing factor and to identify other missing factors. Addressing the need for new measurement capabilities for the new Arctic regime, we propose a game-changing in-situ Arctic-wide Distributed Mobile Monitoring system called Moball-buoy Network. Moball-buoy Network consists of a number of wind-propelled self-powered inflatable spheres referred to as Moball-buoys. The Moball-buoys are self-powered. They use their novel mechanical control and energy harvesting system to use the abundance of wind in the Arctic for their controlled mobility and energy harvesting. They are equipped with an array of low-power low-mass sensors and micro devices able to measure a wide range of environmental factors such as the ice conditions, chemical species wind vector patterns, cloud coverage, air temperature and pressure, electromagnetic fields, surface and subsurface water conditions, short- and long-wave radiations, bathymetry, and anthropogenic factors such as pollutions. The stop-and-go motion capability, using their novel mechanics, and the heads up cooperation control strategy at the core of the proposed distributed system enable the sensor network to be reconfigured dynamically according to the priority of the parameters to be monitored. The large number of Moball-buoys with their ground-based, sea-based, satellite and peer-to-peer communication capabilities would constitute a wireless mesh network that provides an interface for a global control system. This control system will ensure arctic-wide coverage, will optimize Moball-buoys monitoring efforts according to their available resources and the priority of local areas of high scientific value within the Arctic region. Moball-buoy Network is expected to be the first robust and persistent Arctic-wide environment monitoring system capable of providing reliable readings in near real time

40 CFR 63.1250 - Applicability.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., including associated air pollution control equipment and monitoring equipment, in a manner consistent with safety and good air pollution control practices for minimizing emissions. The general duty to minimize... were caused by a sudden, infrequent, and unavoidable failure of air pollution control and monitoring...

40 CFR 63.1250 - Applicability.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., including associated air pollution control equipment and monitoring equipment, in a manner consistent with safety and good air pollution control practices for minimizing emissions. The general duty to minimize... were caused by a sudden, infrequent, and unavoidable failure of air pollution control and monitoring...

40 CFR 63.1250 - Applicability.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., including associated air pollution control equipment and monitoring equipment, in a manner consistent with safety and good air pollution control practices for minimizing emissions. The general duty to minimize... were caused by a sudden, infrequent, and unavoidable failure of air pollution control and monitoring...

40 CFR 63.1250 - Applicability.

Code of Federal Regulations, 2013 CFR

2013-07-01

..., including associated air pollution control equipment and monitoring equipment, in a manner consistent with safety and good air pollution control practices for minimizing emissions. The general duty to minimize... were caused by a sudden, infrequent, and unavoidable failure of air pollution control and monitoring...

Next-generation air monitoring

EPA Science Inventory

Air pollution measurement technology is advancing rapidly towards smaller-scale and wireless devices, with a potential to significantly change the landscape of air pollution monitoring. EPA is evaluating and developing a range of next-generation air monitoring (NGAM) technologie...

Coordinated profiling of stratospheric intrusions and transported pollution by the Tropospheric Ozone Lidar Network (TOLNet) and NASA Alpha Jet experiment (AJAX): Observations and comparison to HYSPLIT, RAQMS, and FLEXPART

NASA Astrophysics Data System (ADS)

Langford, A. O.; Alvarez, R. J.; Brioude, J.; Evan, S.; Iraci, L. T.; Kirgis, G.; Kuang, S.; Leblanc, T.; Newchurch, M. J.; Pierce, R. B.; Senff, C. J.; Yates, E. L.

2018-02-01

Ground-based lidars and ozonesondes belonging to the NASA-supported Tropospheric Ozone Lidar Network (TOLNet) are used in conjunction with the NASA Alpha Jet Atmospheric eXperiment (AJAX) to investigate the transport of stratospheric ozone and entrained pollution into the lower troposphere above the United States on May 24-25, 2013. TOLNet and AJAX measurements made in California, Nevada, and Alabama are compared to tropospheric ozone retrievals from the Atmospheric Infrared Sounder (AIRS), to back trajectories from the NOAA Air Resources Laboratory (ARL) Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, and to analyses from the NOAA/NESDIS Real-time Air Quality Modeling System (RAQMS) and FLEXPART particle dispersion model. The measurements and model analyses show much deeper descent of ozone-rich upper tropospheric/lower stratospheric air above the Desert Southwest than above the Southeast, and comparisons to surface measurements from regulatory monitors reporting to the U.S. EPA Air Quality System (AQS) suggest that there was a much greater surface impact in the Southwest including exceedances of the 2008 National Ambient Air Quality Standard (NAAQS) of 0.075 ppm in both Southern California and Nevada. Our analysis demonstrates the potential benefits to be gained by supplementing the existing surface ozone network with coordinated upper air observations by TOLNet.

Characterization (environmental Signature) and Function of the Main Instrumented (monitoring Water Quality Network in Real Time) Rivers Atoyac and Zahuapan in High Atoyac Basin; in Dry, Rain and Winter Season 2013-2014; Puebla-Tlaxcala Mexico

NASA Astrophysics Data System (ADS)

Tavera, E. M.; Rodriguez-Espinosa, P. F.; Morales-Garcia, S. S.; Muñoz-Sevilla, N. P.

2014-12-01

The Zahuapan and Atoyac rivers were characterized in the Upper Atoyac through the integration of physical and chemical parameters (environmental firm) determining the behavior and function of the basin as a tool for measuring and monitoring the quality and management of water resources of the water in one of the most polluted rivers in Mexico. For the determination of the environmental signature proceeded to characterize the water through 11 physicochemical parameters: temperature (T), potential hydrogen (pH), dissolved oxygen (DO), spectral absorption coefficient (SAC), the reduction of oxide potential (ORP), turbidity (Turb), conductivity (l), biochemical oxygen demand in 5 days (BOD5), chemical oxygen demand (COD), total suspended solids (TSS) and total dissolved solids (TDS ), which were evaluated in 49 sites in the dry season, 47 for the rainy season and 23 for the winter season in the basin and Atoyac Zahuapan Alto Atoyac, Puebla-Tlaxcala, Mexico river; finding a mathematical algorithm to assimilate and better represent the information obtained. The algorithm allows us to estimate correlation greater than 0.85. The results allow us to propose the algorithm used in the monitoring stations for purposes of processing information assimilated form.This measurement and monitoring of water quality supports the project, the monitoring network in real time and the actions to clean up Atoyac River, in the urban area of the city of Puebla.

Water quality assessment of a highly polluted Mediterranean River - Oued Fez (Morocco)

NASA Astrophysics Data System (ADS)

Perrin, J.-L.; Bellarbi, M.; Raïs, N.; Chahinian, N.; Moulin, P.; Ijjaali, M.

2012-04-01

In the South of the Mediterranean basin, many rivers are characterized by an alternation of very long dry periods only cut by short flood events. Currently, the socio-economical development of these zones is limited by water scarcity and poor quality of the water resources. Indeed human activities, generally concentrated in overpopulated cities, generate large quantity of domestic and industrial effluents which are directly rejected in the environment without any treatment. In Morocco, the well known city of Fez illustrates perfectly this situation, observed in most developing countries. The oued Fez receives continuously the non-treated domestic and industrial effluents (90.000 m3/day) of the city and pollutes all the downstream water bodies. Indeed, it is a tributary of the Sebou River, a major body of great economical importance used for irrigation and freshwater supply. This study aims at characterising and quantifying the pollutant concentrations and fluxes in various points of oued Fez's hydrological network and assessing its impact on the Sebou River; this river's preservation being considered a national priority in Morocco. A coupled water quality-water quantity monitoring scheme has been implemented on oued Fez since 2008. In addition to basic hydrological data, water quality samples are collected at regular intervals at 8 locations where discharge is simultaneously measured using an Acoustic Doppler Current Profiler (ADCP). Water samples are analysed for different forms of nitrogen (nitrates, nitrites, ammonium and total nitrogen), phosphorus (soluble reactive phosphorus and total phosphorus) but also total chromium which is used in the leather tanning processes, one of the most important industrial production of the city of Fez, using a photospectrometer (Hach Lange DR 2800 VIS-photometer (Germany). The results of 17 sampling campaigns, carried out over 3 hydrological years, indicate that the rural areas contribute mostly to baseflow during the wet period while non-treated anthropogenic inputs constitute most of the flow during the dry period. The pollution levels are very high as the mean values reach 39 mg/l N, 5 mg/l P, 0.2mg/l Cr, for total nitrogen, total phosphorus and total chromium respectively at the most polluted sites. Even if the hydrological conditions induce important concentration variations, the pollution levels remain high all along the year. The nitrogen, phosphorus and chromium fluxes calculated for steady state conditions, show that more than 500 kg/hour of nitrogen, 60 kg/hour of phosphorus and 2.5 kg/hour of chromium are flushed by the oued Sebou downstream of its confluence with the oued Fez. These fluxes are due to human activities and do not vary significantly with the hydrological conditions. This study shows that a relatively limited observation network allows the characterization of the temporal and spatial variability of the pollution levels if the monitoring points are selected by taking into account the main pollution sources and the specificity of the hydrological conditions.

Comparison of spatiotemporal prediction models of daily exposure of individuals to ambient nitrogen dioxide and ozone in Montreal, Canada.

PubMed

Buteau, Stephane; Hatzopoulou, Marianne; Crouse, Dan L; Smargiassi, Audrey; Burnett, Richard T; Logan, Travis; Cavellin, Laure Deville; Goldberg, Mark S

2017-07-01

In previous studies investigating the short-term health effects of ambient air pollution the exposure metric that is often used is the daily average across monitors, thus assuming that all individuals have the same daily exposure. Studies that incorporate space-time exposures of individuals are essential to further our understanding of the short-term health effects of ambient air pollution. As part of a longitudinal cohort study of the acute effects of air pollution that incorporated subject-specific information and medical histories of subjects throughout the follow-up, the purpose of this study was to develop and compare different prediction models using data from fixed-site monitors and other monitoring campaigns to estimate daily, spatially-resolved concentrations of ozone (O 3 ) and nitrogen dioxide (NO 2 ) of participants' residences in Montreal, 1991-2002. We used the following methods to predict spatially-resolved daily concentrations of O 3 and NO 2 for each geographic region in Montreal (defined by three-character postal code areas): (1) assigning concentrations from the nearest monitor; (2) spatial interpolation using inverse-distance weighting; (3) back-extrapolation from a land-use regression model from a dense monitoring survey, and; (4) a combination of a land-use and Bayesian maximum entropy model. We used a variety of indices of agreement to compare estimates of exposure assigned from the different methods, notably scatterplots of pairwise predictions, distribution of differences and computation of the absolute agreement intraclass correlation (ICC). For each pairwise prediction, we also produced maps of the ICCs by these regions indicating the spatial variability in the degree of agreement. We found some substantial differences in agreement across pairs of methods in daily mean predicted concentrations of O 3 and NO 2 . On a given day and postal code area the difference in the concentration assigned could be as high as 131ppb for O 3 and 108ppb for NO 2 . For both pollutants, better agreement was found between predictions from the nearest monitor and the inverse-distance weighting interpolation methods, with ICCs of 0.89 (95% confidence interval (CI): 0.89, 0.89) for O 3 and 0.81 (95%CI: 0.80, 0.81) for NO 2 , respectively. For this pair of methods the maximum difference on a given day and postal code area was 36ppb for O 3 and 74ppb for NO 2 . The back-extrapolation method showed a higher degree of disagreement with the nearest monitor approach, inverse-distance weighting interpolation, and the Bayesian maximum entropy model, which were strongly constrained by the sparse monitoring network. The maps showed that the patterns of agreement differed across the postal code areas and the variability depended on the pair of methods compared and the pollutants. For O 3 , but not NO 2 , postal areas showing greater disagreement were mostly located near the city centre and along highways, especially in maps involving the back-extrapolation method. In view of the substantial differences in daily concentrations of O 3 and NO 2 predicted by the different methods, we suggest that analyses of the health effects from air pollution should make use of multiple exposure assessment methods. Although we cannot make any recommendations as to which is the most valid method, models that make use of higher spatially resolved data, such as from dense exposure surveys or from high spatial resolution satellite data, likely provide the most valid estimates. Copyright © 2017 Elsevier Inc. All rights reserved.

Novel Approaches for Estimating Human Exposure to Air Pollutants

EPA Science Inventory

Numerous health studies have used measurements from a few central-site ambient monitors to characterize air pollution exposures. Relying on solely on central-site ambient monitors does not account for the spatial-heterogeneity of ambient air pollution patterns, the temporal varia...

Ozone levels in the Spanish Sierra de Guadarrama mountain range are above the thresholds for plant protection: analysis at 2262, 1850, and 995 m a.s.l.

PubMed

Elvira, S; González-Fernández, I; Alonso, R; Sanz, J; Bermejo-Bermejo, V

2016-10-01

The Sierra de Guadarrama mountain range, located at 60 km from Madrid City (Spain), includes high valuable ecosystems following an altitude gradient, some of them protected under the Sierra de Guadarrama National Park. The characteristic Mediterranean climatic conditions and the precursors emitted from Madrid favor a high photochemical production of ozone (O 3 ) in the region. However, very little information is available about the patterns and levels of O 3 and other air pollutants in the high elevation areas and their potential effects on vegetation. Ozone levels were monitored at three altitudes (2262, 1850, and 995 m a.s.l.) for at least 3 years within the 2005-2011 period. NO x and SO 2 were also recorded at the highest and lowest altitude sites. Despite the inter-annual and seasonal variations detected in the O 3 concentrations, the study revealed that SG is exposed to a chronic O 3 pollution. The two high elevation sites showed high O 3 levels even in winter and at nighttime, having low correlation with local meteorological variables. At the lower elevation site, O 3 levels were more related with local meteorological and pollution conditions. Ozone concentrations at the three sites exceeded the thresholds for the protection of human health and vegetation according to the European Air Quality Directive (EU/50/2008) and the thresholds for vegetation protection of the CLRTAP. Ozone should be considered as a stress factor for the health of the Sierra de Guadarrama mountain ecosystems. Furthermore, since O 3 levels at foothills differ from concentration in high elevation, monitoring stations in mountain ranges should be incorporated in regional air quality monitoring networks.

Laser-Based and Ultra-Portable Gas Sensor for Indoor and Outdoor Formaldehyde (HCHO) Monitoring

NASA Astrophysics Data System (ADS)

Shutter, J. D.; Allen, N.; Paul, J.; Thiebaud, J.; So, S.; Scherer, J. J.; Keutsch, F. N.

2017-12-01

While used as a key tracer of oxidative chemistry in the atmosphere, formaldehyde (HCHO) is also a known human carcinogen and is listed and regulated by the United States EPA as a hazardous air pollutant. Combustion processes and photochemical oxidation of volatile organic compounds (VOCs) are the major outdoor sources of HCHO, and building materials and household products are ubiquitous sources of indoor HCHO. Due to the ease with which humans can be exposed to HCHO, it is imperative to monitor levels of both indoor and outdoor HCHO exposure in both short and long-term studies.High-quality direct and indirect methods of quantifying HCHO mixing ratios exist, but instrument size and user-friendliness can make them cumbersome or impractical for certain types of indoor and long-term outdoor measurements. In this study, we present urban HCHO measurements by using a new, commercially-available, ppbv-level accurate HCHO gas sensor (Aeris Technologies' MIRA Pico VOC Laser-Based Gas Analyzer) that is highly portable (29 cm x 20 cm x 10 cm), lightweight (3 kg), easy-to-use, and has low power (15 W) consumption. Using an ultra-compact multipass cell, an absorption path length of 13 m is achieved, resulting in a sensor capable of achieving ppbv/s sensitivity levels with no significant spectral interferences.To demonstrate the utility of the gas sensor for emissions measurements, a GPS was attached to the sensor's housing in order to map mobile HCHO measurements in real-time around the Boston, Massachusetts, metro area. Furthermore, the sensor was placed in residential and industrial environments to show its usefulness for indoor and outdoor pollution measurements. Lastly, we show the feasibility of using the HCHO sensor (or a network of them) in long-term monitoring stations for hazardous air pollutants.

A Coupled model for ERT monitoring of contaminated sites

NASA Astrophysics Data System (ADS)

Wang, Yuling; Zhang, Bo; Gong, Shulan; Xu, Ya

2018-02-01

The performance of electrical resistivity tomography (ERT) system is usually investigated using a fixed resistivity distribution model in numerical simulation study. In this paper, a method to construct a time-varying resistivity model by coupling water transport, solute transport and constant current field is proposed for ERT monitoring of contaminated sites. Using the proposed method, a monitoring model is constructed for a contaminated site with a pollution region on the surface and ERT monitoring results at different time is calculated by the finite element method. The results show that ERT monitoring profiles can effectively reflect the increase of the pollution area caused by the diffusion of pollutants, but the extent of the pollution is not exactly the same as the actual situation. The model can be extended to any other case and can be used to scheme design and results analysis for ERT monitoring.

Assessment of Near-Source Air Pollution at a Fine Spatial ...

EPA Pesticide Factsheets

Mobile monitoring is an emerging strategy to characterize spatially and temporally variable air pollution in areas near sources. EPA’s Geospatial Monitoring of Air Pollution (GMAP) vehicle – an all-electric vehicle measuring real-time concentrations of particulate and gaseous pollutants – was used to map air pollution levels near the Port of Charleston in South Carolina. High-resolution monitoring was performed along driving routes near several port terminals and rail yard facilities, recording geospatial coordinates and concentrations of pollutants including black carbon, size-resolved particle count ranging from ultrafine to coarse (6 nm to 20 um), carbon monoxide, carbon dioxide, and nitrogen dioxide. Additionally, a portable meteorological station was used to characterize local conditions. The primary objective of this work is to characterize the impact of port facilities on local scale air quality. It is found that elevated concentration measurements of Black Carbon and PM correlate to periods of increased port activity and a significant elevation in concentration is observed downwind of ports. However, limitations in study design prevent a more complete analysis of the port effect. As such, we discuss the ways in which this study is limited and how future work could be improved. Mobile monitoring is an emerging strategy to characterize spatially and temporally variable air pollution in areas near sources. EPA’s Geospatial Monitoring of Air Pollut

40 CFR 60.1230 - What continuous emission monitoring systems must I install for gaseous pollutants?

Code of Federal Regulations, 2012 CFR

2012-07-01

... according to the “Monitoring Requirements” in § 60.13. (c) You must monitor the oxygen (or carbon dioxide... systems must I install for gaseous pollutants? 60.1230 Section 60.1230 Protection of Environment... Continuous Emission Monitoring § 60.1230 What continuous emission monitoring systems must I install for...

40 CFR 60.1230 - What continuous emission monitoring systems must I install for gaseous pollutants?

Code of Federal Regulations, 2014 CFR

2014-07-01

... according to the “Monitoring Requirements” in § 60.13. (c) You must monitor the oxygen (or carbon dioxide... systems must I install for gaseous pollutants? 60.1230 Section 60.1230 Protection of Environment... Continuous Emission Monitoring § 60.1230 What continuous emission monitoring systems must I install for...

40 CFR 60.1230 - What continuous emission monitoring systems must I install for gaseous pollutants?

Code of Federal Regulations, 2013 CFR

2013-07-01

... according to the “Monitoring Requirements” in § 60.13. (c) You must monitor the oxygen (or carbon dioxide... systems must I install for gaseous pollutants? 60.1230 Section 60.1230 Protection of Environment... Continuous Emission Monitoring § 60.1230 What continuous emission monitoring systems must I install for...

Multitemporal Monitoring of the Air Quality in Bulgaria by Satellite Based Instruments

NASA Astrophysics Data System (ADS)

Nikolov, Hristo; Borisova, Denitsa

2015-04-01

Nowadays the effect on climate changes on the population and environment caused by air pollutants at local and regional scale by pollution concentrations higher than allowed is undisputable. Main sources of gas releases are due to anthropogenic emissions caused by the economic and domestic activities of the inhabitants, and to less extent having natural origin. Complementary to pollutants emissions the local weather parameters such as temperature, precipitation, wind speed, clouds, atmospheric water vapor, and wind direction control the chemical reactions in the atmosphere. It should be noted that intrinsic property of the air pollution is its "transboundary-ness" and this is why the air quality (AQ) is not affecting the population of one single country only. This why the exchange of information concerning AQ at EU level is subject to well established legislation and one of EU flagship initiatives for standardization in data exchange, namely INSPIRE, has to cope with. It should be noted that although good reporting mechanism with regard to AQ is already established between EU member states national networks suffer from a serious disadvantage - they don't form a regular grid which is a prerequisite for verification of pollutants transport modeling. Alternative sources of information for AQ are the satellite observations (i.e. OMI, TOMS instruments) providing daily data for ones of the major contributors to air pollution such as O3, NOX and SO2. Those data form regular grids and are processed the same day of the acquisition so they could be used in verification of the outputs generated by numerical modeling of the AQ and pollution transfer. In this research we present results on multitemporal monitoring of several regional "hot spots" responsible for greenhouse gases emissions in Bulgaria with emphasis on satellite-based instruments. Other output from this study is a method for validation of the AQ forecasts and also providing feedback to the service that prepares them. The following sources of in-situ data for the different types of gases and dust particles have been used - the National Institute of Meteorology and Hydrology of Bulgaria (NIMH) and National System for Environmental Monitoring managed by Bulgarian Executive Environmental Agency (ExEA). Both authorities provide data for concentration of several gases just to mention CO, CO2, NO2, SO2, and fine suspended dust (PM10, PM2.5) on monthly (for some data on daily) basis. Considered satellite-based instruments for data provision are OMI instrument aboard EOS-Aura satellite and from TROPOMI instrument which is basic payload for the future Sentinel-5P mission.

Online monitoring and conditional regression tree test: Useful tools for a better understanding of combined sewer network behavior.

PubMed

Bersinger, T; Bareille, G; Pigot, T; Bru, N; Le Hécho, I

2018-06-01

A good knowledge of the dynamic of pollutant concentration and flux in a combined sewer network is necessary when considering solutions to limit the pollutants discharged by combined sewer overflow (CSO) into receiving water during wet weather. Identification of the parameters that influence pollutant concentration and flux is important. Nevertheless, few studies have obtained satisfactory results for the identification of these parameters using statistical tools. Thus, this work uses a large database of rain events (116 over one year) obtained via continuous measurement of rainfall, discharge flow and chemical oxygen demand (COD) estimated using online turbidity for the identification of these parameters. We carried out a statistical study of the parameters influencing the maximum COD concentration, the discharge flow and the discharge COD flux. In this study a new test was used that has never been used in this field: the conditional regression tree test. We have demonstrated that the antecedent dry weather period, the rain event average intensity and the flow before the event are the three main factors influencing the maximum COD concentration during a rainfall event. Regarding the discharge flow, it is mainly influenced by the overall rainfall height but not by the maximum rainfall intensity. Finally, COD discharge flux is influenced by the discharge volume and the maximum COD concentration. Regression trees seem much more appropriate than common tests like PCA and PLS for this type of study as they take into account the thresholds and cumulative effects of various parameters as a function of the target variable. These results could help to improve sewer and CSO management in order to decrease the discharge of pollutants into receiving waters. Copyright © 2017 Elsevier B.V. All rights reserved.

Dry Particulate Nitrate Deposition in China.

PubMed

Liu, Lei; Zhang, Xiuying; Zhang, Yan; Xu, Wen; Liu, Xuejun; Zhang, Xiaomin; Feng, Junlan; Chen, Xinrui; Zhang, Yuehan; Lu, Xuehe; Wang, Shanqian; Zhang, Wuting; Zhao, Limin

2017-05-16

A limited number of ground measurements of dry particulate nitrate deposition (NO 3 - ) makes it difficult and challenging to fully know the status of the spatial and temporal variations of dry NO 3 - depositions over China. This study tries to expand the ground measurements of NO 3 - concentrations at monitoring sites to a national scale, based on the Ozone Monitoring Instrument (OMI) NO 2 columns, NO 2 profiles from an atmospheric chemistry transport model (Model for Ozone and Related chemical Tracers, version 4, MOZART-4) and monitor-based sources, and then estimates the NO 3 - depositions on a regional scale based on an inferred model. The ground NO 2 concentrations were first derived from NO 2 columns and the NO 2 profiles, and then the ground NO 3 - concentrations were derived from the ground NO 2 concentrations and the relationship between NO 2 and NO 3 - based on Chinese Nationwide Nitrogen Deposition Monitoring Network (NNDMN). This estimated dry NO 3 - depositions over China will be helpful in determining the magnitude and pollution status in regions without ground measurements, supporting the construction plan of environmental monitoring in future.

Trends of NOx, NO2 and O3 concentrations at three different types of air quality monitoring stations in Athens, Greece

NASA Astrophysics Data System (ADS)

Mavroidis, I.; Ilia, M.

2012-12-01

This work presents a systematic analysis and evaluation of the historic and current levels of atmospheric pollution in the Athens metropolitan region, regarding nitrogen oxides (NOx = NO + NO2), ozone (O3) and the NO2/NOx and NO/NO2 concentration ratios. Hourly, daily, monthly, seasonal and annual pollutant variations are examined and compared, using the results of concentration time series from three different stations of the national network for air pollution monitoring, one urban-traffic, one urban-background and one suburban-background. Concentration data are also related to meteorological parameters. The results show that the traffic affected station of Patission Street presents the higher NOx values and the lower concentrations of O3, while it is the station with the highest number of NO2 limit exceedances. The monitoring data suggest, inter alia, that there is a change in the behaviour of the suburban-background station of Liossia at about year 2000, indicating that the exact location of this station may need to be reconsidered. Comparison of NOx concentrations in Athens with concentrations in urban areas of other countries reveal that the Patission urban-traffic station records very high NOx concentrations, while remarkably high is the ratio of NO2 concentrations recorded at the urban-traffic vs. the urban-background station in Athens, indicating the overarching role of vehicles and traffic congestion on NO2 formation. The NO2/NOx ratio in the urban-traffic station appears to be almost constant with time, while it has been increasing in other urban areas, such as London and Seoul, suggesting an increased effect of primary NO2 in these areas. Diesel passenger cars were only recently allowed in Athens and, therefore, NO2 trends should be carefully monitored since a possible increase in primary NO2 may affect compliance with NO2 air quality standards.

A versatile and interoperable network sensors for water resources monitoring

NASA Astrophysics Data System (ADS)

Ortolani, Alberto; Brandini, Carlo; Costantini, Roberto; Costanza, Letizia; Innocenti, Lucia; Sabatini, Francesco; Gozzini, Bernardo

2010-05-01

Monitoring systems to assess water resources quantity and quality require extensive use of in-situ measurements, that have great limitations like difficulties to access and share data, and to customise and easy reconfigure sensors network to fulfil end-users needs during monitoring or crisis phases. In order to address such limitations Sensor Web Enablement technologies for sensors management have been developed and applied to different environmental context under the EU-funded OSIRIS project (Open architecture for Smart and Interoperable networks in Risk management based on In-situ Sensors, www.osiris-fp6.eu). The main objective of OSIRIS was to create a monitoring system to manage different environmental crisis situations, through an efficient data processing chain where in-situ sensors are connected via an intelligent and versatile network infrastructure (based on web technologies) that enables end-users to remotely access multi-domain sensors information. Among the project application, one was focused on underground fresh-water monitoring and management. With this aim a monitoring system to continuously and automatically check water quality and quantity has been designed and built in a pilot test, identified as a portion of the Amiata aquifer feeding the Santa Fiora springs (Grosseto, Italy). This aquifer present some characteristics that make it greatly vulnerable under some conditions. It is a volcanic aquifer with a fractured structure. The volcanic nature in Santa Fiora causes levels of arsenic concentrations that normally are very close to the threshold stated by law, but that sometimes overpass such threshold for reasons still not fully understood. The presence of fractures makes the infiltration rate very inhomogeneous from place to place and very high in correspondence of big fractures. In case of liquid-pollutant spills (typically hydrocarbons spills from tanker accidents or leakage from house tanks containing fuel for heating), these fractures can act as shortcuts to the heart of the aquifer, causing water contamination much faster than what inferable from average infiltration rates. A new system has been set up, upgrading a legacy sensor network with new sensors to address the monitoring and emergency phase management. Where necessary sensors have been modified in order to manage the whole sensor network through SWE services. The network manage sensors for water parameters (physical and chemical) and for atmospheric ones (for supporting the management of accidental crises). A main property of the developed architecture is that it can be easily reconfigured to pass from the monitoring to the alert phase, by changing sampling frequencies of interesting parameters, or deploying specific additional sensors on identified optimal positions (as in case of the hydrocarbon spill). A hydrogeological model, coupled through a hydrological interface to the atmospheric forcing, has been implemented for the area. Model products (accessed through the same web interface than sensors) give a fundamental added value to the upgraded sensors network (e.g. for data merging procedures). Together with the available measurements, it is shown how the model improves the knowledge of the local hydrogeological system, gives a fundamental support to eventually reconfigure the system (e.g. support on transportable sensors position). The network, basically conceived for real-time monitoring, allow to accumulate an unprecedent amount of information for the aquifer. The availability of such a large set of data (in terms of continuously measured water levels, fluxes, precipitation, concentrations, etc.) from the system, gives a unique opportunity for studying the influences of hydrogeological and geopedological parameters on arsenic and concentrations of other chemicals that are naturally present in water.

Applications of MODIS satellite data and products for monitoring air quality in the state of Texas

NASA Astrophysics Data System (ADS)

Hutchison, Keith D.

The Center for Space Research (CSR), in conjunction with the Monitoring Operations Division (MOD) of the Texas Commission on Environmental Quality (TCEQ), is evaluating the use of remotely sensed satellite data to assist in monitoring and predicting air quality in Texas. The challenges of meeting air quality standards established by the US Environmental Protection Agency (US EPA) are impacted by the transport of pollution into Texas that originates from outside our borders and are cumulative with those generated by local sources. In an attempt to quantify the concentrations of all pollution sources, MOD has installed ground-based monitoring stations in rural regions along the Texas geographic boundaries including the Gulf coast, as well as urban regions that are the predominant sources of domestic pollution. However, analysis of time-lapse GOES satellite imagery at MOD, clearly demonstrates the shortcomings of using only ground-based observations for monitoring air quality across Texas. These shortcomings include the vastness of State borders, that can only be monitored with a large number of ground-based sensors, and gradients in pollution concentration that depend upon the location of the point source, the meteorology governing its transport to Texas, and its diffusion across the region. With the launch of NASA's MODerate resolution Imaging Spectroradiometer (MODIS), the transport of aerosol-borne pollutants can now be monitored over land and ocean surfaces. Thus, CSR and MOD personnel have applied MODIS data to several classes of pollution that routinely impact Texas air quality. Results demonstrate MODIS data and products can detect and track the migration of pollutants. This paper presents one case study in which continental haze from the northeast moved into the region and subsequently required health advisories to be issued for 150 counties in Texas. It is concluded that MODIS provides the basis for developing advanced data products that will, when used in conjunction with ground-based observations, create a cost-effective and accurate pollution monitoring system for the entire state of Texas.

Adapting an ambient monitoring program to the challenge of managing emerging pollutants in the San Francisco Estuary.

PubMed

Hoenicke, Rainer; Oros, Daniel R; Oram, John J; Taberski, Karen M

2007-09-01

While over seven million organic and inorganic compounds that have been indexed by the American Chemical Society's Chemical Abstracts Service in their CAS Registry are commercially available, most pollution monitoring programs focus only on those chemical stressors for which regulatory benchmarks exist, and have been traditionally considered responsible for the most significant human and environmental health risks. Until the late 1990s, the San Francisco Estuary Regional Monitoring Program was no exception in that regard. After a thorough external review, the monitoring program responded to the need for developing a pro-active surveillance approach for emerging pollutants in recognition of the fact that the potential for the growing list of widely used chemical compounds to alter the integrity of water is high. We describe (1) the scientific and analytical bases underlying a new surveillance monitoring approach; (2) summarize approaches used and results obtained from a forensic retrospective; (3) present the growing data set on emerging pollutants from surveillance monitoring and related efforts in the San Francisco Bay Area to characterize newly targeted compounds in wastewater streams, sediment, storm water runoff, and biota; and (4) suggest next steps in monitoring program development and applied research that could move beyond traditional approaches of pollutant characterization. Based on the forensic analysis of archived chromatograms and chemical and toxicological properties of candidate compounds, we quantified a variety of synthetic organic compounds which had previously not been targeted for analysis. Flame retardant compounds, pesticides and insecticide synergists, insect repellents, pharmaceuticals, personal care product ingredients, plasticizers, non-ionic surfactants, and other manufacturing ingredients were detected in water, sediment, and/or biological tissue samples. Several of these compounds, especially polybrominated diphenyl ether flame retardants, exhibited concentrations of environmental concern. We also describe environmental management challenges associated with emerging pollutants and how pro-active surveillance monitoring might assist in implementing a more holistic approach to pollution prevention and control before emerging pollutants become a burden on future generations.

Polycyclic aromatic hydrocarbons and polychlorinated biphenyls in soils of Mayabeque, Cuba.

PubMed

Sosa, Dayana; Hilber, Isabel; Faure, Roberto; Bartolomé, Nora; Fonseca, Osvaldo; Keller, Armin; Schwab, Peter; Escobar, Arturo; Bucheli, Thomas D

2017-05-01

Cuba is a country in transition with a considerable potential for economic growth. Soils are recipients and integrators of chemical pollution, a frequent negative side effect of increasing industrial activities. Therefore, we established a soil monitoring network to monitor polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) in soils of Mayabeque, a Cuban province southeast of Havana. Concentrations of the sum of the 16 US EPA PAHs and of the seven IRMM PCBs in soils from 39 locations ranged from 20 to 106 μg kg -1 and from 1.1 to 7.6 μg kg -1 , respectively. While such concentrations can be considered as low overall, they were in several cases correlated with the distance of sampling sites to presumed major emission sources, with some of the concomitantly investigated source diagnostic PAH ratios, and with black carbon content. The presented data adds to the limited information on soil pollution in the Caribbean region and serves as a reference time point before the onset of a possible further industrial development in Cuba. It also forms the basis to set up and adapt national environmental standards.

GIS-based spatial regression and prediction of water quality in river networks: A case study in Iowa

USGS Publications Warehouse

Yang, X.; Jin, W.

2010-01-01

Nonpoint source pollution is the leading cause of the U.S.'s water quality problems. One important component of nonpoint source pollution control is an understanding of what and how watershed-scale conditions influence ambient water quality. This paper investigated the use of spatial regression to evaluate the impacts of watershed characteristics on stream NO3NO2-N concentration in the Cedar River Watershed, Iowa. An Arc Hydro geodatabase was constructed to organize various datasets on the watershed. Spatial regression models were developed to evaluate the impacts of watershed characteristics on stream NO3NO2-N concentration and predict NO3NO2-N concentration at unmonitored locations. Unlike the traditional ordinary least square (OLS) method, the spatial regression method incorporates the potential spatial correlation among the observations in its coefficient estimation. Study results show that NO3NO2-N observations in the Cedar River Watershed are spatially correlated, and by ignoring the spatial correlation, the OLS method tends to over-estimate the impacts of watershed characteristics on stream NO3NO2-N concentration. In conjunction with kriging, the spatial regression method not only makes better stream NO3NO2-N concentration predictions than the OLS method, but also gives estimates of the uncertainty of the predictions, which provides useful information for optimizing the design of stream monitoring network. It is a promising tool for better managing and controlling nonpoint source pollution. ?? 2010 Elsevier Ltd.

Applications of measures of cumulative exposure to assessing air pollution health effects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abbey, D.E.; Euler, G.L.; Magie, A.R.

A method for assessing the health effects of long-term cumulative exposures to air pollutants or other environmental exposures is proposed and illustrated using self-reported symptoms of chronic obstructive pulmonary disease (COPD) for a population of 7,343 non-smokers. Using zip code by month, residence histories, and interpolated exposure estimates from the network of California air monitoring stations, two alternative exposure indices were calculated to estimate cumulative exposure over an 11-yr period above different threshold levels for each of four pollutants. The indices were used with multiple logistic regression models to form dose-response curves for relative risks adjusting for covariates. Statistically significantmore » effects were noted for total suspended particulates, total oxidants, sulfur dioxide, and passive smoking. A description is also given of how the indices are currently being used in a 10-yr follow-up of the study population. This follow-up study is utilizing data collected by the National Cancer Institute-funded Adventist Health Study and has mortality, cancer incidence, heart disease incidence, and change in self-reported COPD symptoms as outcomes.« less

40 CFR 62.14595 - What are the operator training and qualification requirements?

Code of Federal Regulations, 2010 CFR

2010-07-01

... charging, and shutdown procedures. (iv) Combustion controls and monitoring. (v) Operation of air pollution... the incinerator and air pollution control devices. (vii) Actions to correct malfunctions or conditions... requirements. (xiii) Methods to continuously monitor CISWI unit and air pollution control device operating...

40 CFR 62.14595 - What are the operator training and qualification requirements?

Code of Federal Regulations, 2011 CFR

2011-07-01

... charging, and shutdown procedures. (iv) Combustion controls and monitoring. (v) Operation of air pollution... the incinerator and air pollution control devices. (vii) Actions to correct malfunctions or conditions... requirements. (xiii) Methods to continuously monitor CISWI unit and air pollution control device operating...

A statistical framework for the validation of a population exposure model based on personal exposure data

NASA Astrophysics Data System (ADS)

Rodriguez, Delphy; Valari, Myrto; Markakis, Konstantinos; Payan, Sébastien

2016-04-01

Currently, ambient pollutant concentrations at monitoring sites are routinely measured by local networks, such as AIRPARIF in Paris, France. Pollutant concentration fields are also simulated with regional-scale chemistry transport models such as CHIMERE (http://www.lmd.polytechnique.fr/chimere) under air-quality forecasting platforms (e.g. Prev'Air http://www.prevair.org) or research projects. These data may be combined with more or less sophisticated techniques to provide a fairly good representation of pollutant concentration spatial gradients over urban areas. Here we focus on human exposure to atmospheric contaminants. Based on census data on population dynamics and demographics, modeled outdoor concentrations and infiltration of outdoor air-pollution indoors we have developed a population exposure model for ozone and PM2.5. A critical challenge in the field of population exposure modeling is model validation since personal exposure data are expensive and therefore, rare. However, recent research has made low cost mobile sensors fairly common and therefore personal exposure data should become more and more accessible. In view of planned cohort field-campaigns where such data will be available over the Paris region, we propose in the present study a statistical framework that makes the comparison between modeled and measured exposures meaningful. Our ultimate goal is to evaluate the exposure model by comparing modeled exposures to monitor data. The scientific question we address here is how to downscale modeled data that are estimated on the county population scale at the individual scale which is appropriate to the available measurements. To assess this question we developed a Bayesian hierarchical framework that assimilates actual individual data into population statistics and updates the probability estimate.

Spatial Investigation of Columnar AOD and Near-Surface PM2.5 Concentrations During the 2013 American and Yosemite Rim Fires

NASA Astrophysics Data System (ADS)

Loria Salazar, S. M.; Holmes, H.; Arnott, W. P.; Moosmuller, H.; Liming, A.; Echevarria, B.

2014-12-01

The study of aerosol pollution transport and optical properties in the western U.S. is a challenge due to the complex terrain, bright surfaces, presence of anthropogenic and biogenic emissions, secondary organic aerosol formation, and smoke from wild fires. In addition, the complex terrain influences transport phenomena by recirculating mountain air from California to Nevada, where air pollution from the Sierra Nevada Mountains (SNM) is mixed with urban air from the Central Valley in California. Previous studies in Reno hypothesize that elevated aerosol concentrations aloft, above the convective boundary layer height, make air quality monitoring in Reno challenging with MODIS products. Here, we analyze data from August 2013 as a case study for wildfire smoke plumes in California and Nevada. During this time period, northern California was impacted by large wild fires known as the American and Yosemite Rim fires. Thousands of acres burned, generating large quantities of aerosol pollutants that were transported downwind. The aim of the present work is to investigate the fire plume behavior and transport phenomena using ground level PM2.5 concentrations from routine monitoring networks and aerosol optical properties from AERONET, both at multiple locations in California and Nevada. In addition, the accuracy of MODIS (Collection 6) and VIIRS aerosol satellite products will be evaluated. The multispectral photoacoustic instruments and reciprocal nephelometers located in Reno support the estimation of approximated aerosol height. The objectives are to investigate the impact of the vertical distribution of PM concentrations on satellite aerosol optical depth (AOD) retrievals; assess the ability to estimate ground level PM2.5 mass concentrations for wildfire smoke plumes from satellite remote sensing; and investigate the influence of complex terrain on the transport of pollutants, convective boundary layer depth, and aerosol optical height.

Measuring PM and related air pollutants using low-cost ...

EPA Pesticide Factsheets

Emerging air quality sensors may play a key role in better characterizing levels of air pollution in a variety of settings There are a wide range of low-cost (< $500 US) sensors on the market, but few have been characterized. If accurate, this new generation of inexpensive sensors can potentially allow larger fleets of monitors to be deployed to better study the spatial and temporal variability of pollutants. The small size and light weight of these sensors also allows for the possibility of wearable or drone applications. Sensor networks will very likely play a key role in future estimates of human health impacts of pollutants, in particular particulate matter (PM), and will allow for the better characterization of pollutant sources and source regions.We will present measurements from an assortment of sensors, costing $20-$700, that have been used to measure air pollution in the US, India, and China with a focus on estimating PM concentrations. Their performance has been evaluated in these very different settings with low concentrations seen in the US (up to approximately 20 ug m-3) and much higher concentrations measured in India and China (up to approximately 300 ug m-3). Based on these studies the optimal concentration ranges of these sensors have been determined. Used in conjunction with data from a carbon dioxide sensor, emissions factors were estimated in some of the locations. In addition temperature and humidity sensors can be used to calculate c

The use of alternative pollutant metrics in time-series studies of ambient air pollution and respiratory emergency department visits.

PubMed

Darrow, Lyndsey A; Klein, Mitchel; Sarnat, Jeremy A; Mulholland, James A; Strickland, Matthew J; Sarnat, Stefanie E; Russell, Armistead G; Tolbert, Paige E

2011-01-01

Various temporal metrics of daily pollution levels have been used to examine the relationships between air pollutants and acute health outcomes. However, daily metrics of the same pollutant have rarely been systematically compared within a study. In this analysis, we describe the variability of effect estimates attributable to the use of different temporal metrics of daily pollution levels. We obtained hourly measurements of ambient particulate matter (PM₂.₅), carbon monoxide (CO), nitrogen dioxide (NO₂), and ozone (O₃) from air monitoring networks in 20-county Atlanta for the time period 1993-2004. For each pollutant, we created (1) a daily 1-h maximum; (2) a 24-h average; (3) a commute average; (4) a daytime average; (5) a nighttime average; and (6) a daily 8-h maximum (only for O₃). Using Poisson generalized linear models, we examined associations between daily counts of respiratory emergency department visits and the previous day's pollutant metrics. Variability was greatest across O₃ metrics, with the 8-h maximum, 1-h maximum, and daytime metrics yielding strong positive associations and the nighttime O₃ metric yielding a negative association (likely reflecting confounding by air pollutants oxidized by O₃). With the exception of daytime metric, all of the CO and NO₂ metrics were positively associated with respiratory emergency department visits. Differences in observed associations with respiratory emergency room visits among temporal metrics of the same pollutant were influenced by the diurnal patterns of the pollutant, spatial representativeness of the metrics, and correlation between each metric and copollutant concentrations. Overall, the use of metrics based on the US National Ambient Air Quality Standards (for example, the use of a daily 8-h maximum O₃ as opposed to a 24-h average metric) was supported by this analysis. Comparative analysis of temporal metrics also provided insight into underlying relationships between specific air pollutants and respiratory health.

Pollution monitoring using bees: a new service provided by honey bees

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bromenshenk, J.J.; Thomas, J.M.; Simpson, J.C.

1983-10-01

The objectives are to provide a tool for assessing pollutant distributions and the effects of pollutants on living systems. The potential of bees as pollution monitors was studied by examining bees exposed to toxic metals near a smelter in Montana and bees in the area surrounding a hazardous waste disposal site near Puget Sound, Washington. Levels of toxic metals in the bees and brood survival were examined. It was concluded bees were, indeed, suitable indicators of pollution levels. (ACR)

40 CFR Table 3 to Subpart Bbbbbb... - Applicability of General Provisions

Code of Federal Regulations, 2012 CFR

2012-07-01

... Maintain monitoring system in a manner consistent with good air pollution control practices Yes. § 63.8(c...) Maintenance records Recordkeeping of maintenance on air pollution control and monitoring equipment Yes. § 63... (CONTINUED) AIR PROGRAMS (CONTINUED) NATIONAL EMISSION STANDARDS FOR HAZARDOUS AIR POLLUTANTS FOR SOURCE...

40 CFR 63.7113 - What are my monitoring installation, operation, and maintenance requirements?

Code of Federal Regulations, 2014 CFR

2014-07-01

... monitor an add-on air pollution control device, you must meet the requirements in paragraphs (g)(1) and (2... PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) NATIONAL EMISSION STANDARDS FOR HAZARDOUS AIR POLLUTANTS FOR SOURCE CATEGORIES (CONTINUED) National Emission Standards for Hazardous Air Pollutants for...

40 CFR 63.7113 - What are my monitoring installation, operation, and maintenance requirements?

Code of Federal Regulations, 2012 CFR

2012-07-01

... monitor an add-on air pollution control device, you must meet the requirements in paragraphs (g)(1) and (2... PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) NATIONAL EMISSION STANDARDS FOR HAZARDOUS AIR POLLUTANTS FOR SOURCE CATEGORIES (CONTINUED) National Emission Standards for Hazardous Air Pollutants for...

40 CFR 63.7113 - What are my monitoring installation, operation, and maintenance requirements?

Code of Federal Regulations, 2011 CFR

2011-07-01

... monitor an add-on air pollution control device, you must meet the requirements in paragraphs (g)(1) and (2... PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) NATIONAL EMISSION STANDARDS FOR HAZARDOUS AIR POLLUTANTS FOR SOURCE CATEGORIES (CONTINUED) National Emission Standards for Hazardous Air Pollutants for...

40 CFR 63.7113 - What are my monitoring installation, operation, and maintenance requirements?

Code of Federal Regulations, 2013 CFR

2013-07-01

... monitor an add-on air pollution control device, you must meet the requirements in paragraphs (g)(1) and (2... PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) NATIONAL EMISSION STANDARDS FOR HAZARDOUS AIR POLLUTANTS FOR SOURCE CATEGORIES (CONTINUED) National Emission Standards for Hazardous Air Pollutants for...

40 CFR Table 3 to Subpart Bbbbbb... - Applicability of General Provisions

Code of Federal Regulations, 2011 CFR

2011-07-01

... Maintain monitoring system in a manner consistent with good air pollution control practices Yes. § 63.8(c...) Maintenance records Recordkeeping of maintenance on air pollution control and monitoring equipment Yes. § 63... (CONTINUED) AIR PROGRAMS (CONTINUED) NATIONAL EMISSION STANDARDS FOR HAZARDOUS AIR POLLUTANTS FOR SOURCE...

40 CFR Table 3 to Subpart Bbbbbb... - Applicability of General Provisions

Code of Federal Regulations, 2014 CFR

2014-07-01

... Maintain monitoring system in a manner consistent with good air pollution control practices Yes. § 63.8(c...) Maintenance records Recordkeeping of maintenance on air pollution control and monitoring equipment Yes. § 63... (CONTINUED) AIR PROGRAMS (CONTINUED) NATIONAL EMISSION STANDARDS FOR HAZARDOUS AIR POLLUTANTS FOR SOURCE...

Pollution Analyzing and Monitoring Instruments.

ERIC Educational Resources Information Center

1972

Compiled in this book is basic, technical information useful in a systems approach to pollution control. Descriptions and specifications are given of what is available in ready made, on-the-line commercial equipment for sampling, monitoring, measuring and continuously analyzing the multitudinous types of pollutants found in the air, water, soil,…

Assessment of near-source air pollution at a fine spatial scale utilizing a mobile measurement platform approach

EPA Science Inventory

Mobile monitoring is an emerging strategy to characterize spatially and temporally variable air pollution in areas near sources. EPA’s Geospatial Monitoring of Air Pollution (GMAP) vehicle, an all-electric vehicle measuring real-time concentrations of particulate and gaseous poll...

Air pollution and watershed research in the central Sierra Nevada of California: nitrogen and ozone.

PubMed

Hunsaker, Carolyn; Bytnerowicz, Andrzej; Auman, Jessica; Cisneros, Ricardo

2007-03-21

Maintaining healthy forests is the major objective for the Forest Service scientists and managers working for the U.S. Department of Agriculture. Air pollution, specifically ozone (O3) and nitrogenous (N) air pollutants, may severely affect the health of forest ecosystems in the western U.S. Thus, the monitoring of air pollution concentration and deposition levels, as well as studies focused on understanding effects mechanisms, are essential for evaluation of risks associated with their presence. Such information is essential for development of proper management strategies for maintaining clean air, clean water, and healthy ecosystems on land managed by the Forest Service. We report on two years of research in the central Sierra Nevada of California, a semi-arid forest at elevations of 1100-2700 m. Information on O3 and N air pollutants is obtained from a network of 18 passive samplers. We relate the atmospheric N concentration to N concentrations in streams, shallow soil water, and bulk deposition collectors within the Kings River Experimental Watershed. This watershed also contains an intensive site that is part of a recent Forest Service effort to calculate critical loads for N, sulfur, and acidity to forest ecosystems. The passive sampler design allows for extensive spatial measurements while the watershed experiment provides intensive spatial data for future analysis of ecosystem processes.

Near-Port Air Quality Assessment Utilizing a Mobile Monitoring Approach

EPA Science Inventory

Mobile monitoring is an emerging strategy to characterize spatially and temporally variable air pollution in areas near sources. EPA’s Geospatial Monitoring of Air Pollution (GMAP) vehicle – an all-electric vehicle measuring real-time concentrations of particulate and gaseous po...

Assessing the air quality impact of nitrogen oxides and benzene from road traffic and domestic heating and the associated cancer risk in an urban area of Verona (Italy)

NASA Astrophysics Data System (ADS)

Schiavon, Marco; Redivo, Martina; Antonacci, Gianluca; Rada, Elena Cristina; Ragazzi, Marco; Zardi, Dino; Giovannini, Lorenzo

2015-11-01

Simulations of emission and dispersion of nitrogen oxides (NOx) are performed in an urban area of Verona (Italy), characterized by street canyons and typical sources of urban pollutants. Two dominant source categories are considered: road traffic and, as an element of novelty, domestic heaters. Also, to assess the impact of urban air pollution on human health and, in particular, the cancer risk, simulations of emission and dispersion of benzene are carried out. Emissions from road traffic are estimated by the COPERT 4 algorithm, whilst NOx emission factors from domestic heaters are retrieved by means of criteria provided in the technical literature. Then maps of the annual mean concentrations of NOx and benzene are calculated using the AUSTAL2000 dispersion model, considering both scenarios representing the current situation, and scenarios simulating the introduction of environmental strategies for air pollution mitigation. The simulations highlight potentially critical situations of human exposure that may not be detected by the conventional network of air quality monitoring stations. The proposed methodology provides a support for air quality policies, such as planning targeted measurement campaigns, re-locating monitoring stations and adopting measures in favour of better air quality in urban planning. In particular, the estimation of the induced cancer risk is an important starting point to conduct zoning analyses and to detect the areas where population is more directly exposed to potential risks for health.

Incorporating wind availability into land use regression modelling of air quality in mountainous high-density urban environment.

PubMed

Shi, Yuan; Lau, Kevin Ka-Lun; Ng, Edward

2017-08-01

Urban air quality serves as an important function of the quality of urban life. Land use regression (LUR) modelling of air quality is essential for conducting health impacts assessment but more challenging in mountainous high-density urban scenario due to the complexities of the urban environment. In this study, a total of 21 LUR models are developed for seven kinds of air pollutants (gaseous air pollutants CO, NO 2 , NO x , O 3 , SO 2 and particulate air pollutants PM 2.5 , PM 10 ) with reference to three different time periods (summertime, wintertime and annual average of 5-year long-term hourly monitoring data from local air quality monitoring network) in Hong Kong. Under the mountainous high-density urban scenario, we improved the traditional LUR modelling method by incorporating wind availability information into LUR modelling based on surface geomorphometrical analysis. As a result, 269 independent variables were examined to develop the LUR models by using the "ADDRESS" independent variable selection method and stepwise multiple linear regression (MLR). Cross validation has been performed for each resultant model. The results show that wind-related variables are included in most of the resultant models as statistically significant independent variables. Compared with the traditional method, a maximum increase of 20% was achieved in the prediction performance of annual averaged NO 2 concentration level by incorporating wind-related variables into LUR model development. Copyright © 2017 Elsevier Inc. All rights reserved.

Characterisation of an urban bus network for environmental purposes.

PubMed

André, Michel; Villanova, André

2004-12-01

Since pollutant emissions are closely related to the operating conditions of vehicles, their evaluation usually involves studying these operating conditions (through bus instrumentation and monitoring under actual operation), the design of representative driving or engine test cycles and the measurement of pollutant emissions. A preliminary characterisation of the routes on a bus network should make it possible to identify typical routes, the driving conditions and pollutant emissions of which are then studied. Two approaches are envisaged and applied to the Paris area, for which a wealth of information is available, which should be transferable to other bus networks. Both approaches are based on factorial analysis and automatic clustering, to allow optimum description and the identification of a pertinent typology of the bus routes in several classes. The first attempt at characterisation is based on statistics relating to bus operations: route characteristics (length, dedicated bus lanes, number of stops, location of stops: schools, tourist sites, hospitals, railways or underground stations), travel time, commercial speed, annual statistics (number of passengers, number of vehicles per hour, total kilometres), the irregularity of travel (variation of travel times, injuries, congestion.), as well as information on the problems encountered (congestion, distribution of the passenger load, junctions, bends). A second approach is based on the analysis of the "urban context" in which buses are driven. Population, employment, housing, road network, traffic and places that generate or disturb traffic (schools, railway stations, shopping areas, etc.) are calculated for the Ile de France region, by cells of 100 x 100 m, and collected in a geographical information system (GIS). Statistical analyses enable a typology of these urban cells to be established, the main parameters being density, type of housing, road types and traffic levels. The bus routes are then analysed according to their itineraries across these typical areas (distances travelled in each type of area) using a similar approach. A comparison of the typologies obtained from operational data and from urban data highlights the advantages and disadvantages of the two approaches. The first result from these typologies is the selection of routes which are representative of the different classes, in order to instrument buses and record driving patterns. This method should also make it possible to link driving conditions and urban characteristics, and then to allocate pollutant emission factors to given geographical situations, in particular, in the context of emission inventories or impact studies.

Evaluating A Priori Ozone Profile Information Used in TEMPO Tropospheric Ozone Retrievals

NASA Technical Reports Server (NTRS)

Johnson, Matthew S.; Sullivan, John T.; Liu, Xiong; Newchurch, Mike; Kuang, Shi; McGee, Thomas J.; Langford, Andrew O'Neil; Senff, Christoph J.; Leblanc, Thierry; Berkoff, Timothy;

Evaluating a Priori Ozone Profile Information Used in TEMPO Tropospheric Ozone Retrievals

NASA Technical Reports Server (NTRS)

Johnson, Matthew S.; Sullivan, John; Liu, Xiong; Newchurch, Mike; Kuang, Shi; McGee, Thomas; Langford, Andrew; Senff, Chris; Leblanc, Thierry; Berkoff, Timothy;

Evaluating A Priori Ozone Profile Information Used in TEMPO Tropospheric Ozone Retrievals

NASA Astrophysics Data System (ADS)

Johnson, M. S.; Sullivan, J. T.; Liu, X.; Newchurch, M.; Kuang, S.; McGee, T. J.; Langford, A. O.; Senff, C. J.; Leblanc, T.; Berkoff, T.; Gronoff, G.; Chen, G.; Strawbridge, K. B.

2016-12-01

Ozone (O3) is a greenhouse gas and toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is primarily conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address these limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product. TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME, GOME-2, and OMI. This algorithm uses a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB) O3 climatology). It has been shown that satellite O3 retrievals are sensitive to a priori O3 profiles and covariance matrices. During this work we investigate the climatological data to be used in TEMPO algorithms (TB O3) and simulated data from the NASA GMAO Goddard Earth Observing System (GEOS-5) Forward Processing (FP) near-real-time (NRT) model products. These two data products will be evaluated with ground-based lidar data from the Tropospheric Ozone Lidar Network (TOLNet) at various locations of the US. This study evaluates the TB climatology, GEOS-5 climatology, and 3-hourly GEOS-5 data compared to lower tropospheric observations to demonstrate the accuracy of a priori information to potentially be used in TEMPO O3 algorithms. Here we present our initial analysis and the theoretical impact on TEMPO retrievals in the lower troposphere.

Assessment of the use of space technology in the monitoring of oil spills and ocean pollution: Executive summary

NASA Technical Reports Server (NTRS)

Alvarado, U. R. (Editor)

1980-01-01

The adequacy of current technology in terms of stage of maturity, of sensing, support systems, and information extraction was assessed relative to oil spills, waste pollution, and inputs to pollution trajectory models. Needs for advanced techniques are defined and the characteristics of a future satellite system are determined based on the requirements of U.S. agencies involved in pollution monitoring.

Instrumentation for Air Pollution Monitoring

ERIC Educational Resources Information Center

Hollowell, Craig D.; McLaughlin, Ralph D.

1973-01-01

Describes the techniques which form the basis of current commercial instrumentation for monitoring five major gaseous atmospheric pollutants (sulfur dioxide, oxides of nitrogen, oxidants, carbon monoxide, and hydrocarbons). (JR)

Integrated evaluation of aerogenic pollution by air-transported heavy metals (Pb, Cd, Ni, Zn, Mn and Cu) in the analysis of the main deposit media.

PubMed

Baltrėnaitė, Edita; Baltrėnas, Pranas; Lietuvninkas, Arvydas; Serevičienė, Vaida; Zuokaitė, Eglė

2014-01-01

The composition of the ambient air is constantly changing; therefore, the monitoring of ambient air quality to detect the changes caused by aerogenic pollutants makes the essential part of general environmental monitoring. To achieve more effective improvement of the ambient air quality, the Directive 2008/50/EC on 'Ambient Air Quality and Cleaner Air for Europe' was adopted by the European Parliament and the European Council. It informed the public and enterprises about a negative effect of pollution on humans, animals and plants, as well as about the need for monitoring aerogenic pollutants not only at the continuous monitoring stations but also by using indicator methods, i.e. by analysing natural deposit media. The problem of determining the relationship between the accumulation level of pollutants by a deposit medium and the level of air pollution and its risks is constantly growing in importance. The paper presents a comprehensive analysis of the response of the main four deposit media, i.e. snow cover, soil, pine bark and epigeic mosses, to the long-term pollution by aerogenic pollutants which can be observed in the area of oil refinery influence. Based on the quantitative expressions of the amounts of the accumulated pollutants in the deposit media, the territory of the oil refinery investigated in this paper has been referred to the areas of mild or moderate pollution.

SWARMs Ontology: A Common Information Model for the Cooperation of Underwater Robots.

PubMed

Li, Xin; Bilbao, Sonia; Martín-Wanton, Tamara; Bastos, Joaquim; Rodriguez, Jonathan

2017-03-11

In order to facilitate cooperation between underwater robots, it is a must for robots to exchange information with unambiguous meaning. However, heterogeneity, existing in information pertaining to different robots, is a major obstruction. Therefore, this paper presents a networked ontology, named the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs) ontology, to address information heterogeneity and enable robots to have the same understanding of exchanged information. The SWARMs ontology uses a core ontology to interrelate a set of domain-specific ontologies, including the mission and planning, the robotic vehicle, the communication and networking, and the environment recognition and sensing ontology. In addition, the SWARMs ontology utilizes ontology constructs defined in the PR-OWL ontology to annotate context uncertainty based on the Multi-Entity Bayesian Network (MEBN) theory. Thus, the SWARMs ontology can provide both a formal specification for information that is necessarily exchanged between robots and a command and control entity, and also support for uncertainty reasoning. A scenario on chemical pollution monitoring is described and used to showcase how the SWARMs ontology can be instantiated, be extended, represent context uncertainty, and support uncertainty reasoning.

Rocky Mountain snowpack chemistry network; history, methods, and the importance of monitoring mountain ecosystems

USGS Publications Warehouse

Ingersoll, George P.; Turk, John T.; Mast, M. Alisa; Clow, David W.; Campbell, Donald H.; Bailey, Zelda C.

2002-01-01

Because regional-scale atmospheric deposition data in the Rocky Mountains are sparse, a program was designed by the U.S. Geological Survey to more thoroughly determine the quality of precipitation and to identify sources of atmospherically deposited pollution in a network of high-elevation sites. Depth-integrated samples of seasonal snowpacks at 52 sampling sites, in a network from New Mexico to Montana, were collected and analyzed each year since 1993. The results of the first 5 years (1993?97) of the program are discussed in this report. Spatial patterns in regional data have emerged from the geographically distributed chemical concentrations of ammonium, nitrate, and sulfate that clearly indicate that concentrations of these acid precursors in less developed areas of the region are lower than concentrations in the heavily developed areas. Snowpacks in northern Colorado that lie adjacent to both the highly developed Denver metropolitan area to the east and coal-fired powerplants to the west had the highest overall concentrations of nitrate and sulfate in the network. Ammonium concentrations were highest in northwestern Wyoming and southern Montana.

Estimations of pollution emissions by the Moscow megapolis basing on in-situ measurements and optical remote sensing

NASA Astrophysics Data System (ADS)

Elansky, N.; Postylyakov, O.; Verevkin, Y.; Volobuev, L.; Ponomarev, N.

2017-11-01

By the present a large amount of data has been accumulated on direct measurements of the pollution and thermodynamic state of the atmosphere in the Moscow region, which was obtained at stations of Roshydromet, Mosecomonitoring, A.M.Obukhov Institute of Atmospheric Physics (OIAP), M.V. Lomonosov Moscow State University, NPO Typhoon, what allows estimating pollution emissions based on measurements and correcting existing emission inventories, which are evaluated mainly on indirect data connected with population density, fuel consumption, etc. Within the framework of the project, the whole volume of data on the concentration of ground contaminants CO, NOx, SO2, CH4, obtained at regularly operated Moscow Ecological Monitoring stations and at OIAP stations from 2005 to 2014, was systematized. Observation data on pollution concentrations are supplemented by measurements of their integral content in the atmospheric boundary layer, obtained by differential spectroscopy methods (MAX DOAS, ZDOAS) at stationary stations and by passing Moscow with DOAS-equipped car. The paper present preliminary estimates of pollution emissions in the Moscow region, obtained on the basis of the collected array of experimental data. The estimations of pollutant emissions from Moscow were obtained experimentally in a few ways: (1) on the basis of network observations of surface concentrations, (2) on the basis of measurements in the atmospheric layer 0-348 m at Ostankino TV tower, (3) on the basis of the integral pollutant (NO2) content in ABL obtained by DOAS technique from stationary stations, and (4) using a car with DOAS equipment traveling over the closed route around Moscow (for NO2). All experimental approaches yielded close values of pollution emissions for Moscow. Trends in emissions of CO, NOx, and CH4 are negative, and the trend of SO2 emission is positive from 2005 to 2014.

Spatio-temporal modelling for assessing air pollution in Santiago de Chile

NASA Astrophysics Data System (ADS)

Nicolis, Orietta; Camaño, Christian; Mařın, Julio C.; Sahu, Sujit K.

2017-01-01

In this work, we propose a space-time approach for studying the PM2.5 concentration in the city of Santiago de Chile. In particular, we apply the autoregressive hierarchical model proposed by [1] using the PM2.5 observations collected by a monitoring network as a response variable and numerical weather forecasts from the Weather Research and Forecasting (WRF) model as covariate together with spatial and temporal (periodic) components. The approach is able to provide short-term spatio-temporal predictions of PM2.5 concentrations on a fine spatial grid (at 1km × 1km horizontal resolution.)

Two Methods to Derive Ground-level Concentrations of PM2.5 with Improved Accuracy in the North China, Calibrating MODIS AOD and CMAQ Model Predictions

NASA Astrophysics Data System (ADS)

Lyu, Baolei; Hu, Yongtao; Chang, Howard; Russell, Armistead; Bai, Yuqi

2016-04-01

Reliable and accurate characterizations of ground-level PM2.5 concentrations are essential to understand pollution sources and evaluate human exposures etc. Monitoring network could only provide direct point-level observations at limited locations. At the locations without monitors, there are generally two ways to estimate the pollution levels of PM2.5. One is observations of aerosol properties from the satellite-based remote sensing, such as Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD). The other one is from deterministic atmospheric chemistry models, such as the Community Multi-Scale Air Quality Model (CMAQ). In this study, we used a statistical spatio-temporal downscaler to calibrate the two datasets to monitor observations to derive fine-scale ground-level concentrations of PM2.5 with improved accuracy. We treated both MODIS AOD and CMAQ model predictions as biased proxy estimations of PM2.5 pollution levels. The downscaler proposed a Bayesian framework to model the spatially and temporally varying coefficients of the two types of estimations in the linear regression setting, in order to correct biases. Especially for calibrating MODIS AOD, a city-specific linear model was established to fill the missing AOD values, and a novel interpolation-based variable, i.e. PM2.5 Spatial Interpolator, was introduced to account for the spatial dependence among grid cells. We selected the heavy polluted and populated North China as our study area, in a grid setting of 81×81 12-km cells. For the evaluation of calibration performance for retrieved MODIS AOD, the R2 was 0.61 by the full model with PM2.5 Spatial Interpolator being presented, and was 0.48 with PM2.5 Spatial Interpolator not being presented. The constructed AOD values effectively predicted PM2.5 concentrations under our model structure, with R2=0.78. For the evaluation of calibrated CMAQ predictions, the R2 was 0.51, a little less than that of calibrated AOD. Finally we obtained two sets of calibrated estimations of ground-level PM2.5 concentrations with complete spatial coverage. By comparing the two datasets, we found that the prediction from AOD have a little smoother texture than that from CMAQ. The former also predicted larger heavy pollution area in the southern Hebei province than the latter, but in a small margin. In general, they have pretty similar spatial patterns, indicating the reliability of our data fusion method. In summary, the statistical spatio-temporal downscaler could provide improvements on MODIS AOD and CMAQ's predictions on PM2.5 pollution levels. Future work would focus on fusing three datasets, as aforementioned monitor observations, MODIS AOD and CMAQ predictions, to derive predictions of ground-level PM2.5 pollution levels with even increased accuracy.

Intraregional links between the trends in air pollutants observed at the EANET network sites for 2000-2014

NASA Astrophysics Data System (ADS)

Gromov, Sergey A.; Trifonova-Yakovleva, Alisa; Gromov, Sergey S.

2016-04-01

Recent changes in economic development tendencies and environmental protection policies in the East Asian countries raise hopes for improvement of regional air quality in this vast region populated by more than 3 billion people. To recognize anticipated changes in atmospheric pollutants levels, deposition rates and impact on the environment, the Acid Deposition Monitoring Network in East Asia (EANET, http://www.eanet.asia/) is regularly operating region-wide since 2000 in 13 countries. The network provides continuous monitoring data on the air quality and precipitation (including gas-phase and particulate chemistry) at 55 monitoring sites, including 20 remote and 14 rural sites. Observation of soil and inland water environments are performed at more than 30 monitoring sites [1]. In this study we focus on 1) the data quality assessment and preparation and 2) analysis of temporal trends of compositions observed at selected 26 non-urban EANET stations. Speciation includes gas-phase (SO2, HNO3, HCl, NH3) and particulate matter (SO42-, NO3-, Cl-, NH4+, Na+, K+, Mg2+, Ca2+) abundances analysed in samples collected using filterpack technique with sampling duration/frequency of one-two weeks. Data quality assessment (distribution test and manual inspection) allowed us to remove/repair random and operator errors. Wrong sample timing was found for 0.37% (severe) and 34% (mild inconsistency) of the total of 7630 samples regarded. Erroneous data flagging (e.g. missing or below the detection limit) was repaired for 9.3%, respectively. Some 1.8% of severely affected data were corrected (where possible) or removed. Thus refined 15-year dataset is made available for the scientific community. For convenience, we also provide data in netCDF format (per station or in an assembly). Based on this refined dataset, we performed trend analysis using several statistical approaches including quantile regression which provides robust results against outliers and better understanding of trend origins. Our calculations indicate that about half of the median trends at EANET stations are significant, derived either for the entire observational period or for a given season, however not for the same species. The proportions of decreasing and increasing trends are comparable. The latter is the case for SO2, HCl, Cl-, NO3 (except for Russia), while marked decrease in K+ abundances is prevailing at all stations. Most unsystematic trends are seen for nitrogenated compounds, particularly HNO3, which calls for deeper data quality analysis. Interestingly, about the same statistic (half of significant trends) is obtained for the upper (0.9) quantile of the dataset, suggesting that trends pertain to the upper part of the data distribution usually linked to emission dynamics (i.e. bearing winter/spring compositions). We further apply an ad hoc cluster analysis to infer spatial patterns and colocation of the trends across the East Asian region. Finally, we provide a brief comparison of results with an evaluation of changes in major acidic compounds over EMEP region for the 1990-2012 provided by EMEP in its trend assessment for the UN ECE CLRTAP earlier this year [2]. References: 1. EANET: Data Report 2014. Network Center for EANET (ACAP), November 2015, 314 p. (http://www.eanet.asia/product/datarep/datarep14/datarep14.pdf) 2. EMEP: Air Pollution Trends in the EMEP region between 1990 and 2012. WMO/EMEP TFMM Trend Assessment Report. UN ECE Convention on LRTAP, 2016, 54 p.

Citizen-sensor-networks to confront government decision-makers: Two lessons from the Netherlands.

PubMed

Carton, Linda; Ache, Peter

2017-07-01

This paper presents one emerging social-technical innovation: The evolution of citizen-sensor-networks where citizens organize themselves from the 'bottom up', for the sake of confronting governance officials with measured information about environmental qualities. We have observed how citizen-sensor-networks have been initiated in the Netherlands in cases where official government monitoring and business organizations leave gaps. The formed citizen-sensor-networks collect information about issues that affect the local community in their quality-of-living. In particular, two community initiatives are described where the sensed environmental information, on noise pollution and gas-extraction induced earthquakes respectively, is published through networked geographic information methods. Both community initiatives pioneered in developing an approach that comprises the combined setting-up of sensor data flows, real-time map portals and community organization. Two particular cases are analyzed to trace the emergence and network operation of such 'networked geo-information tools' in practice: (1) The Groningen earthquake monitor, and (2) The Airplane Monitor Schiphol. In both cases, environmental 'externalities' of spatial-economic activities play an important role, having economic dimensions of national importance (e.g. gas extraction and national airport development) while simultaneously affecting the regional community with environmental consequences. The monitoring systems analyzed in this paper are established bottom-up, by citizens for citizens, to serve as 'information power' in dialogue with government institutions. The goal of this paper is to gain insight in how these citizen-sensor-networks come about: how the idea for establishing a sensor network originated, how their value gets recognized and adopted in the overall 'system of governance'; to what extent they bring countervailing power against vested interests and established discourses to the table and influence power-laden conflicts over environmental pressures; and whether or not they achieve (some form of) institutionalization and, ultimately, policy change. We find that the studied-citizen-sensor networks gain strength by uniting efforts and activities in crowdsourcing data, providing factual, 'objectivized data' or 'evidence' of the situation 'on the ground' on a matter of local community-wide concern. By filling an information need of the local community, a process of 'collective sense-making' combined with citizen empowerment could grow, which influenced societal discourse and challenged prevailing truth-claims of public institutions. In both cases similar, 'competing' web-portals were developed in response, both by the gas-extraction company and the airport. But with the citizen-sensor-networks alongside, we conclude there is a shift in power balance involved between government and affected communities, as the government no longer has information monopoly on environmental measurements. Copyright © 2017 Elsevier Ltd. All rights reserved.

40 CFR 50.14 - Treatment of air quality monitoring data influenced by exceptional events.

Code of Federal Regulations, 2010 CFR

2010-07-01

... specific air pollution concentration at a particular air quality monitoring location. (2) Demonstration to... exceptional event caused a specific air pollution concentration in excess of one or more national ambient air... specific air pollution concentration in excess of one or more national ambient air quality standards at a...

Comparison between air pollution concentrations measured at the nearest monitoring station to the delivery hospital and those measured at stations nearest the residential postal code regions of pregnant women in Fukuoka.

PubMed

Michikawa, Takehiro; Morokuma, Seiichi; Nitta, Hiroshi; Kato, Kiyoko; Yamazaki, Shin

2017-06-13

Numerous earlier studies examining the association of air pollution with maternal and foetal health estimated maternal exposure to air pollutants based on the women's residential addresses. However, residential addresses, which are personally identifiable information, are not always obtainable. Since a majority of pregnant women reside near their delivery hospitals, the concentrations of air pollutants at the respective delivery hospitals may be surrogate markers of pollutant exposure at home. We compared air pollutant concentrations measured at the nearest monitoring station to Kyushu University Hospital with those measured at the closest monitoring stations to the respective residential postal code regions of pregnant women in Fukuoka. Aggregated postal code data for the home addresses of pregnant women who delivered at Kyushu University Hospital in 2014 was obtained from Kyushu University Hospital. For each of the study's 695 women who resided in Fukuoka Prefecture, we assigned pollutant concentrations measured at the nearest monitoring station to Kyushu University Hospital and pollutant concentrations measured at the nearest monitoring station to their respective residential postal code regions. Among the 695 women, 584 (84.0%) resided in the proximity of the nearest monitoring station to hospital or one of the four other stations (as the nearest stations to their respective residential postal code region) in Fukuoka city. Pearson's correlation for daily mean concentrations among the monitoring stations in Fukuoka city was strong for fine particulate matter (PM 2.5 ), suspended particulate matter (SPM), and photochemical oxidants (Ox) (coefficients ≥0.9), but moderate for coarse particulate matter (the result of subtracting the PM 2.5 from the SPM concentrations), nitrogen dioxide, and sulphur dioxide. Hospital-based and residence-based concentrations of PM 2.5 , SPM, and Ox were comparable. For PM 2.5 , SPM, and Ox, exposure estimation based on the delivery hospital is likely to approximate that based on the home of pregnant women.

Mobility and bio-availability of heavy metals in anthropogenically contaminated alluvial (deluvial) meadow soils (EUTRIC FLUVISOLS)

NASA Astrophysics Data System (ADS)

Dinev, Nikolai; Hristova, Mariana; Tzolova, Venera

2015-04-01

The total content of heavy metals is not sufficient to assess the pollution and the risk for environment as it does not provide information for the type and solubility of heavy metals' compounds in soils. The purpose was to study and determine the mobility of heavy metals in anthropogenically contaminated alluvial (delluvial) meadow soils spread around the non-ferrous plant near the town of Asenovgrad in view of risk assessment for environment pollution. Soil samples from monitoring network (1x1 km) was used. The sequential extraction procedure described by Zein and Brummer (1989) was applied. Results showed that the easily mobilizable cadmium compounds predominate in both contaminated and not contaminated soils. The stable form of copper (associated with silicate minerals, carbonates or amorphous and crystalline oxide compounds) predominates only in non polluted soils and reviles the risk of the environment contamination. Lead spreads and accumulates as highly soluble (mobile) compounds and between 72.3 and 99.6 percent of the total lead is bioavailable in soils. The procedure is very suitable for studying the mobility of technogenic lead and copper in alluvial soils with neutral medium reaction and in particular at the high levels of cadmium contamination. In soils with alkaline reaction - polluted and unpolluted the error of analysis increases for all studied elements.

Air quality assessment of Estarreja, an urban industrialized area, in a coastal region of Portugal.

PubMed

Figueiredo, M L; Monteiro, A; Lopes, M; Ferreira, J; Borrego, C

2013-07-01

Despite the increasing concern given to air quality in urban and industrial areas in recent years, particular emphasis on regulation, control, and reduction of air pollutant emissions is still necessary to fully characterize the chain emissions-air quality-exposure-dose-health effects, for specific sources. The Estarreja region was selected as a case study because it has one of the largest chemical industrial complexes in Portugal that has been recently expanded, together with a growing urban area with an interesting location in the Portuguese coastland and crossed by important road traffic and rail national networks. This work presents the first air quality assessment for the region concerning pollutant emissions and meteorological and air quality monitoring data analysis, over the period 2000-2009. This assessment also includes a detailed investigation and characterization of past air pollution episodes for the most problematic pollutants: ozone and PM10. The contribution of different emission sources and meteorological conditions to these episodes is investigated. The stagnant meteorological conditions associated with local emissions, namely industrial activity and road traffic, are the major contributors to the air quality degradation over the study region. A set of measures to improve air quality--regarding ozone and PM10 levels--is proposed as an air quality management strategy for the study region.

Analysis of Mexico City urban air pollution using nitrogen dioxide column density measurements from UV/Visible spectroscopy

NASA Astrophysics Data System (ADS)

Garcia Payne, D. G.; Grutter, M.; Melamed, M. L.

2010-12-01

The differential optical absorption spectroscopy method (DOAS) was used to get column densities of nitrogen dioxide (NO2) from the analysis of zenith sky UV/visible spectra. Since the optical path length provides critical information in interpreting NO2 column densities, in conjunction with NO2 column densities, the oxygen dimer (O4) column density was retrieved to give insight into the optical path length. We report observations of year round NO2 and O4 column densities (from august 2009 to september 2010) from which the mean seasonal levels and the daily evolution, as well as the occurrence of elevated pollution episodes are examined. Surface nitric oxide (NO) and NO2 from the local monitoring network, as well as wind data and the vertical aerosol density from continuous Lidar measurements are used in the analysis to investigate specific events in the context of local emissions from vehicular traffic, photochemical production and transport from industrial emissions. The NO2 column density measurements will enhance the understanding Mexico City urban air pollution. Recent research has begun to unravel the complexity of the air pollution problem in Mexico City and its effects not only locally but on a regional and global scale as well.

Monitoring of Hazardous Air Pollutant Surrogates Using Resonance Enhanced Multiphoton Ionization/Time of Flight Mass Spectrometry

EPA Science Inventory

EPA’s preferred approach for regulatory emissions compliance is based upon real-time monitoring of individual hazardous air pollutants (HAPs). Real-time, continuous monitoring not only provides the most comprehensive assurance of emissions compliance, but also can serve as...

Water Quality & Pollutant Source Monitoring: Field and Laboratory Procedures. Training Manual.

ERIC Educational Resources Information Center

Office of Water Program Operations (EPA), Cincinnati, OH. National Training and Operational Technology Center.

This training manual presents material on techniques and instrumentation used to develop data in field monitoring programs and related laboratory operations concerned with water quality and pollution monitoring. Topics include: collection and handling of samples; bacteriological, biological, and chemical field and laboratory methods; field…

Temporal trends of Persistent Organic Pollutants (POPs) in arctic air: 20 years of monitoring under the Arctic Monitoring and Assessment Programme (AMAP).

PubMed

Hung, Hayley; Katsoyiannis, Athanasios A; Brorström-Lundén, Eva; Olafsdottir, Kristin; Aas, Wenche; Breivik, Knut; Bohlin-Nizzetto, Pernilla; Sigurdsson, Arni; Hakola, Hannele; Bossi, Rossana; Skov, Henrik; Sverko, Ed; Barresi, Enzo; Fellin, Phil; Wilson, Simon

2016-10-01

Temporal trends of Persistent Organic Pollutants (POPs) measured in Arctic air are essential in understanding long-range transport to remote regions and to evaluate the effectiveness of national and international chemical control initiatives, such as the Stockholm Convention (SC) on POPs. Long-term air monitoring of POPs is conducted under the Arctic Monitoring and Assessment Programme (AMAP) at four Arctic stations: Alert, Canada; Stórhöfði, Iceland; Zeppelin, Svalbard; and Pallas, Finland, since the 1990s using high volume air samplers. Temporal trends observed for POPs in Arctic air are summarized in this study. Most POPs listed for control under the SC, e.g. polychlorinated biphenyls (PCBs), dichlorodiphenyltrichloroethanes (DDTs) and chlordanes, are declining slowly in Arctic air, reflecting the reduction of primary emissions during the last two decades and increasing importance of secondary emissions. Slow declining trends also signifies their persistence and slow degradation under the Arctic environment, such that they are still detectable after being banned for decades in many countries. Some POPs, e.g. hexachlorobenzene (HCB) and lighter PCBs, showed increasing trends at specific locations, which may be attributable to warming in the region and continued primary emissions at source. Polybrominated diphenyl ethers (PBDEs) do not decline in air at Canada's Alert station but are declining in European Arctic air, which may be due to influence of local sources at Alert and the much higher historical usage of PBDEs in North America. Arctic air samples are screened for chemicals of emerging concern to provide information regarding their environmental persistence (P) and long-range transport potential (LRTP), which are important criteria for classification as a POP under SC. The AMAP network provides consistent and comparable air monitoring data of POPs for trend development and acts as a bridge between national monitoring programs and SC's Global Monitoring Plan (GMP). Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Using remote sensing imagery to monitoring sea surface pollution cause by abandoned gold-copper mine

NASA Astrophysics Data System (ADS)

Kao, H. M.; Ren, H.; Lee, Y. T.

2010-08-01

The Chinkuashih Benshen mine was the largest gold-copper mine in Taiwan before the owner had abandoned the mine in 1987. However, even the mine had been closed, the mineral still interacts with rain and underground water and flowed into the sea. The polluted sea surface had appeared yellow, green and even white color, and the pollutants had carried by the coast current. In this study, we used the optical satellite images to monitoring the sea surface. Several image processing algorithms are employed especial the subpixel technique and linear mixture model to estimate the concentration of pollutants. The change detection approach is also applied to track them. We also conduct the chemical analysis of the polluted water to provide the ground truth validation. By the correlation analysis between the satellite observation and the ground truth chemical analysis, an effective approach to monitoring water pollution could be established.

Spatial and temporal trends from an air quality sensor network near a heavily trafficked intersection

NASA Astrophysics Data System (ADS)

Orlando, P.; Vo, D.; Giossi, C.; George, L.

2017-12-01

With the world-wide increase in urbanization and the increasing usage of combustion vehicles in urban areas, traffic-related air pollution is a growing health hazard. However, there are limited studies that examine the spatial and temporal impacts of traffic-related pollutants within cities. In particular, there are few studies that look at traffic management and its potential for pollution mitigation. In a previous study we examined roadway pollution and traffic parameters with one roadway station instrumented with standard measurement instruments. With the advent of low-cost air pollution sensors, we have expanded our work by observing multiple sites within a neighborhood to understand spatial and temporal exposures. We have deployed a high-density sensor network around urban arterial corridors in SE Portland, Oregon. This network consisted of ten nodes measuring CO, NO, NO2 and O3, and ten nodes measuring CO, CO2, VOC and PM2.5. The co-location of standard measurement instruments provided insight towards the utility of our low-cost sensor network, as the different nodes varied in cost, and potentially in quality. We have identified near-real-time temporal trends and local-scale spatial patterns during the summer of 2017. Meteorological and traffic data were included to further characterize these patterns, exploring the potential for pollution mitigation.

Detecting volcanic sulfur dioxide plumes in the Northern Hemisphere using the Brewer spectrophotometers, other networks, and satellite observations

NASA Astrophysics Data System (ADS)

Zerefos, Christos S.; Eleftheratos, Kostas; Kapsomenakis, John; Solomos, Stavros; Inness, Antje; Balis, Dimitris; Redondas, Alberto; Eskes, Henk; Allaart, Marc; Amiridis, Vassilis; Dahlback, Arne; De Bock, Veerle; Diémoz, Henri; Engelmann, Ronny; Eriksen, Paul; Fioletov, Vitali; Gröbner, Julian; Heikkilä, Anu; Petropavlovskikh, Irina; Jarosławski, Janusz; Josefsson, Weine; Karppinen, Tomi; Köhler, Ulf; Meleti, Charoula; Repapis, Christos; Rimmer, John; Savinykh, Vladimir; Shirotov, Vadim; Siani, Anna Maria; Smedley, Andrew R. D.; Stanek, Martin; Stübi, René

2017-01-01

This study examines the adequacy of the existing Brewer network to supplement other networks from the ground and space to detect SO2 plumes of volcanic origin. It was found that large volcanic eruptions of the last decade in the Northern Hemisphere have a positive columnar SO2 signal seen by the Brewer instruments located under the plume. It is shown that a few days after the eruption the Brewer instrument is capable of detecting significant columnar SO2 increases, exceeding on average 2 DU relative to an unperturbed pre-volcanic 10-day baseline, with a mean close to 0 and σ = 0.46, as calculated from the 32 Brewer stations under study. Intercomparisons with independent measurements from the ground and space as well as theoretical calculations corroborate the capability of the Brewer network to detect volcanic plumes. For instance, the comparison with OMI (Ozone Monitoring Instrument) and GOME-2 (Global Ozone Monitoring Experiment-2) SO2 space-borne retrievals shows statistically significant agreement between the Brewer network data and the collocated satellite overpasses in the case of the Kasatochi eruption. Unfortunately, due to sparsity of satellite data, the significant positive departures seen in the Brewer and other ground networks following the Eyjafjallajökull, Bárðarbunga and Nabro eruptions could not be statistically confirmed by the data from satellite overpasses. A model exercise from the MACC (Monitoring Atmospheric Composition and Climate) project shows that the large increases in SO2 over Europe following the Bárðarbunga eruption in Iceland were not caused by local pollution sources or ship emissions but were clearly linked to the volcanic eruption. Sulfur dioxide positive departures in Europe following Bárðarbunga could be traced by other networks from the free troposphere down to the surface (AirBase (European air quality database) and EARLINET (European Aerosol Research Lidar Network)). We propose that by combining Brewer data with that from other networks and satellites, a useful tool aided by trajectory analyses and modelling could be created which can also be used to forecast high SO2 values both at ground level and in air flight corridors following future eruptions.

Continuous monitoring of water flow and solute transport using vadose zone monitoring technology

NASA Astrophysics Data System (ADS)

Dahan, O.

2009-04-01

Groundwater contamination is usually attributed to pollution events that initiate on land surface. These may be related to various sources such as industrial, urban or agricultural, and may appear as point or non point sources, through a single accidental event or a continuous pollution process. In all cases, groundwater pollution is a consequence of pollutant transport processes that take place in the vadose zone above the water table. Attempts to control pollution events and prevent groundwater contamination usually involve groundwater monitoring programs. This, however, can not provide any protection against contamination since pollution identification in groundwater is clear evidence that the groundwater is already polluted and contaminants have already traversed the entire vadose zone. Accordingly, an efficient monitoring program that aims at providing information that may prevent groundwater pollution has to include vadose-zone monitoring systems. Such system should provide real-time information on the hydrological and chemical properties of the percolating water and serve as an early warning system capable of detecting pollution events in their early stages before arrival of contaminants to groundwater. Recently, a vadose-zone monitoring system (VMS) was developed to allow continuous monitoring of the hydrological and chemical properties of percolating water in the deep vadose zone. The VMS includes flexible time-domain reflectometry (FTDR) probes for continuous tracking of water content profiles, and vadose-zone sampling ports (VSPs) for frequent sampling of the deep vadose pore water at multiple depths. The monitoring probes and sampling ports are installed through uncased slanted boreholes using a flexible sleeve that allows attachment of the monitoring devices to the borehole walls while achieving good contact between the sensors and the undisturbed sediment column. The system has been successfully implemented in several studies on water flow and contaminant transport in various hydrological and geological setups. These include floodwater infiltration in arid environments, land use impact on groundwater quality, and control of remediation process in a contaminated vadose zone. The data which is collected by the VMS allows direct measurements of flow velocities and fluxes in the vadose zone while continuously monitoring the chemical evolution of the percolating water. While real time information on the hydrological and chemical properties of the percolating water in the vadose is essential to prevent groundwater contamination it is also vital for any remediation actions. Remediation of polluted soils and aquifers essentially involves manipulation of surface and subsurface hydrological, physical and biochemical conditions to improve pollutant attenuation. Controlling the biochemical conditions to enhance biodegradation often includes introducing degrading microorganisms, applying electron donors or acceptors, or adding nutrients that can promote growth of the desired degrading organisms. Accordingly real time data on the hydrological and chemical properties of the vadose zone may be used to select remediation strategies and determine its efficiency on the basis of real time information.

Analysis of feature selection with Probabilistic Neural Network (PNN) to classify sources influencing indoor air quality

NASA Astrophysics Data System (ADS)

Saad, S. M.; Shakaff, A. Y. M.; Saad, A. R. M.; Yusof, A. M.; Andrew, A. M.; Zakaria, A.; Adom, A. H.

2017-03-01

There are various sources influencing indoor air quality (IAQ) which could emit dangerous gases such as carbon monoxide (CO), carbon dioxide (CO2), ozone (O3) and particulate matter. These gases are usually safe for us to breathe in if they are emitted in safe quantity but if the amount of these gases exceeded the safe level, they might be hazardous to human being especially children and people with asthmatic problem. Therefore, a smart indoor air quality monitoring system (IAQMS) is needed that able to tell the occupants about which sources that trigger the indoor air pollution. In this project, an IAQMS that able to classify sources influencing IAQ has been developed. This IAQMS applies a classification method based on Probabilistic Neural Network (PNN). It is used to classify the sources of indoor air pollution based on five conditions: ambient air, human activity, presence of chemical products, presence of food and beverage, and presence of fragrance. In order to get good and best classification accuracy, an analysis of several feature selection based on data pre-processing method is done to discriminate among the sources. The output from each data pre-processing method has been used as the input for the neural network. The result shows that PNN analysis with the data pre-processing method give good classification accuracy of 99.89% and able to classify the sources influencing IAQ high classification rate.

Fast notification architecture for wireless sensor networks

NASA Astrophysics Data System (ADS)

Lee, Dong-Hahk

2013-03-01

In an emergency, since it is vital to transmit the message to the users immediately after analysing the data to prevent disaster, this article presents the deployment of a fast notification architecture for a wireless sensor network. The sensor nodes of the proposed architecture can monitor an emergency situation periodically and transmit the sensing data, immediately to the sink node. We decide on the grade of fire situation according to the decision rule using the sensing values of temperature, CO, smoke density and temperature increasing rate. On the other hand, to estimate the grade of air pollution, the sensing data, such as dust, formaldehyde, NO2, CO2, is applied to the given knowledge model. Since the sink node in the architecture has a ZigBee interface, it can transmit the alert messages in real time according to analysed results received from the host server to the terminals equipped with a SIM card-type ZigBee module. Also, the host server notifies the situation to the registered users who have cellular phone through short message service server of the cellular network. Thus, the proposed architecture can adapt an emergency situation dynamically compared to the conventional architecture using video processing. In the testbed, after generating air pollution and fire data, the terminal receives the message in less than 3 s. In the test results, this system can also be applied to buildings and public areas where many people gather together, to prevent unexpected disasters in urban settings.

Sulfur Dioxide Pollution Monitor.

ERIC Educational Resources Information Center

National Bureau of Standards (DOC), Washington, DC.

The sulfur dioxide pollution monitor described in this document is a government-owed invention that is available for licensing. The background of the invention is outlined, and drawings of the monitor together with a detailed description of its function are provided. A sample stream of air, smokestack gas or the like is flowed through a…

40 CFR 60.1720 - What continuous emission monitoring systems must I install for gaseous pollutants?

Code of Federal Regulations, 2014 CFR

2014-07-01

... systems must I install for gaseous pollutants? 60.1720 Section 60.1720 Protection of Environment... or Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1720 What continuous..., maintain, and operate continuous emission monitoring systems for oxygen (or carbon dioxide), sulfur dioxide...

40 CFR 60.1720 - What continuous emission monitoring systems must I install for gaseous pollutants?

Code of Federal Regulations, 2012 CFR

2012-07-01

... systems must I install for gaseous pollutants? 60.1720 Section 60.1720 Protection of Environment... or Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1720 What continuous..., maintain, and operate continuous emission monitoring systems for oxygen (or carbon dioxide), sulfur dioxide...

40 CFR 60.1720 - What continuous emission monitoring systems must I install for gaseous pollutants?

Code of Federal Regulations, 2013 CFR

2013-07-01

... systems must I install for gaseous pollutants? 60.1720 Section 60.1720 Protection of Environment... or Before August 30, 1999 Model Rule-Continuous Emission Monitoring § 60.1720 What continuous..., maintain, and operate continuous emission monitoring systems for oxygen (or carbon dioxide), sulfur dioxide...

Generating high-accuracy urban distribution map for short-term change monitoring based on convolutional neural network by utilizing SAR imagery

NASA Astrophysics Data System (ADS)

Iino, Shota; Ito, Riho; Doi, Kento; Imaizumi, Tomoyuki; Hikosaka, Shuhei

2017-10-01

In the developing countries, urban areas are expanding rapidly. With the rapid developments, a short term monitoring of urban changes is important. A constant observation and creation of urban distribution map of high accuracy and without noise pollution are the key issues for the short term monitoring. SAR satellites are highly suitable for day or night and regardless of atmospheric weather condition observations for this type of study. The current study highlights the methodology of generating high-accuracy urban distribution maps derived from the SAR satellite imagery based on Convolutional Neural Network (CNN), which showed the outstanding results for image classification. Several improvements on SAR polarization combinations and dataset construction were performed for increasing the accuracy. As an additional data, Digital Surface Model (DSM), which are useful to classify land cover, were added to improve the accuracy. From the obtained result, high-accuracy urban distribution map satisfying the quality for short-term monitoring was generated. For the evaluation, urban changes were extracted by taking the difference of urban distribution maps. The change analysis with time series of imageries revealed the locations of urban change areas for short-term. Comparisons with optical satellites were performed for validating the results. Finally, analysis of the urban changes combining X-band, L-band and C-band SAR satellites was attempted to increase the opportunity of acquiring satellite imageries. Further analysis will be conducted as future work of the present study

Air Emissions Monitoring for Permits

EPA Pesticide Factsheets

Operating permits document how air pollution sources will demonstrate compliance with emission limits and also how air pollution sources will monitor, either periodically or continuously, their compliance with emission limits and all other requirements.

New problems and opportunities of oil spill monitoring systems

NASA Astrophysics Data System (ADS)

Barenboim, G. M.; Borisov, V. M.; Golosov, V. N.; Saveca, A. Yu.

2015-04-01

Emergency oil and oil products spills represent a great danger to the environment, including ecosystems, and to the population. New problems of such dangerous spills and methods of early detection are discussed in this paper. It is proposed to conduct assessment of biological hazards of such spills on the basis of data on the distribution of individual oil hydrocarbons within the column of the water body and computer predictions of their toxicity. Oil radioactivity, which is associated with uranium and thorium, is seen as the important aspect of the oil spill danger, especially in watercourses. The need for an automated monitoring system for the early detection of oil spills in water bodies is analysed. The proposed system consists of three subsystems. The first remote sensing subsystem is based on powerful fluorescent lidars; experimental results on lidar registration of oil pollution of water are reported. The second subsystem uses a network of automatic monitoring stations with contact detectors. The third subsystem is the combined sensor system based on remote and contact technologies.

JPRS report: Science and technology. Central Eurasia

NASA Astrophysics Data System (ADS)

1994-08-01

Translated articles cover the following topics: boronizing laser treatment of titanium alloys; argon-arc welding-on titanium dowels to inserts for aircraft structures made of composite materials; method of reducing level of thermally stressed state of gas turbine engine blades by selecting optimum thickness distribution of ceramic heat shield coating; certifying modern ceramics for mechanical properties; superplastic ceramic: possibilities for application in modeling pressworking manufacturing processes; monitoring strength of ceramics by acoustic emission; physical and mechanical properties of Al2O3 + ZrO2:Y2O3 composite produced by directional crystallization from melt; influence that microalloying with rare earth elements has on resistance of steels to deformation and fracture under alternating elastic-plastic loading; conceptions of constructing information management networks for distributed objects; concept of a document information system based on an object-oriented subject-area model; underground future of rocket technologies; geoinformation approach to organizing automated information systems for regional-local monitoring of atmospheric pollutants; and possibility of using lidar wind sounding in climatic-ecologic monitoring of limited areas.

Predictive monitoring and diagnosis of periodic air pollution in a subway station.

PubMed

Kim, YongSu; Kim, MinJung; Lim, JungJin; Kim, Jeong Tai; Yoo, ChangKyoo

2010-11-15

The purpose of this study was to develop a predictive monitoring and diagnosis system for the air pollutants in a subway system using a lifting technique with a multiway principal component analysis (MPCA) which monitors the periodic patterns of the air pollutants and diagnoses the sources of the contamination. The basic purpose of this lifting technique was to capture the multivariate and periodic characteristics of all of the indoor air samples collected during each day. These characteristics could then be used to improve the handling of strong periodic fluctuations in the air quality environment in subway systems and will allow important changes in the indoor air quality to be quickly detected. The predictive monitoring approach was applied to a real indoor air quality dataset collected by telemonitoring systems (TMS) that indicated some periodic variations in the air pollutants and multivariate relationships between the measured variables. Two monitoring models--global and seasonal--were developed to study climate change in Korea. The proposed predictive monitoring method using the lifted model resulted in fewer false alarms and missed faults due to non-stationary behavior than that were experienced with the conventional methods. This method could be used to identify the contributions of various pollution sources. Copyright © 2010 Elsevier B.V. All rights reserved.

Appraising city-scale pollution monitoring capabilities of multi-satellite datasets using portable pollutant monitors

NASA Astrophysics Data System (ADS)

Aliyu, Yahaya A.; Botai, Joel O.

2018-04-01

The retrieval characteristics for a city-scale satellite experiment was explored over a Nigerian city. The study evaluated carbon monoxide and aerosol contents in the city atmosphere. We utilized the MSA Altair 5× gas detector and CW-HAT200 particulate counter to investigate the city-scale monitoring capabilities of satellite pollution observing instruments; atmospheric infrared sounder (AIRS), measurement of pollution in the troposphere (MOPITT), moderate resolution imaging spectroradiometer (MODIS), multi-angle imaging spectroradiometer (MISR) and ozone monitoring instrument (OMI). To achieve this, we employed the Kriging interpolation technique to collocate the satellite pollutant estimations over 19 ground sample sites for the period of 2015-2016. The portable pollutant devices were validated using the WHO air filter sampling model. To determine the city-scale performance of the satellite datasets, performance indicators: correlation coefficient, model efficiency, reliability index and root mean square error, were adopted as measures. The comparative analysis revealed that MOPITT carbon monoxide (CO) and MODIS aerosol optical depth (AOD) estimates are the appropriate satellite measurements for ground equivalents in Zaria, Nigeria. Our findings were within the acceptable limits of similar studies that utilized reference stations. In conclusion, this study offers direction to Nigeria's air quality policy organizers about available alternative air pollution measurements for mitigating air quality effects within its limited resource environment.

EPMOSt: An Energy-Efficient Passive Monitoring System for Wireless Sensor Networks

PubMed Central

Garcia, Fernando P.; Andrade, Rossana M. C.; Oliveira, Carina T.; de Souza, José Neuman

2014-01-01

Monitoring systems are important for debugging and analyzing Wireless Sensor Networks (WSN). In passive monitoring, a monitoring network needs to be deployed in addition to the network to be monitored, named the target network. The monitoring network captures and analyzes packets transmitted by the target network. An energy-efficient passive monitoring system is necessary when we need to monitor a WSN in a real scenario because the lifetime of the monitoring network is extended and, consequently, the target network benefits from the monitoring for a longer time. In this work, we have identified, analyzed and compared the main passive monitoring systems proposed for WSN. During our research, we did not identify any passive monitoring system for WSN that aims to reduce the energy consumption of the monitoring network. Therefore, we propose an Energy-efficient Passive MOnitoring SysTem for WSN named EPMOSt that provides monitoring information using a Simple Network Management Protocol (SNMP) agent. Thus, any management tool that supports the SNMP protocol can be integrated with this monitoring system. Experiments with real sensors were performed in several scenarios. The results obtained show the energy efficiency of the proposed monitoring system and the viability of using it to monitor WSN in real scenarios. PMID:24949639

Wavelength dependent light absorption as a cost effective, real-time surrogate for ambient concentrations of polycyclic aromatic hydrocarbons

NASA Astrophysics Data System (ADS)

Brown, Richard J. C.; Butterfield, David M.; Goddard, Sharon L.; Hussain, Delwar; Quincey, Paul G.; Fuller, Gary W.

2016-02-01

Many monitoring stations used to assess ambient air concentrations of pollutants regulated by European air quality directives suffer from being expensive to establish and operate, and from their location being based on the results of macro-scale modelling exercises rather than measurement assessments in candidate locations. To address these issues for the monitoring of polycyclic aromatic hydrocarbons (PAHs), this study has used data from a combination of the ultraviolet and infrared channels of aethalometers (referred to as UV BC), operated as part of the UK Black Carbon Network, as a surrogate measurement. This has established a relationship between concentrations of the PAH regulated in Europe, benzo[a]pyrene (B[a]P), and the UV BC signal at locations where these measurements have been made together from 2008 to 2014. This relationship was observed to be non-linear. Relationships for individual site types were used to predict measured concentrations with, on average, 1.5% accuracy across all annual averages, and with only 1 in 36 of the predicted annual averages deviating from the measured annual average by more than the B[a]P data quality objective for uncertainty of 50% (at -65%, with the range excluding this value between + 38% and -37%). These relationships were then used to predict B[a]P concentrations at stations where UV BC measurement are made, but PAH measurements are not. This process produced results which reflected expectations based on knowledge of the pollution climate at these stations gained from the measurements of other air quality networks, or from nearby stations. The influence of domestic solid fuel heating was clear using this approach which highlighted Strabane in Northern Ireland as a station likely to be in excess of the air quality directive target value for B[a]P.

Water Pollution Search | ECHO | US EPA

EPA Pesticide Factsheets

The Water Pollution Search within the Water Pollutant Loading Tool gives users options to search for pollutant loading information from Discharge Monitoring Report (DMR) and Toxic Release Inventory (TRI) data.

Estimating PM2.5 concentrations in China from 1957 to 2014 using meteorological visibility data

NASA Astrophysics Data System (ADS)

Ma, Z.; Liu, M.; Wen, T.; Bi, J.

2017-12-01

PM2.5 is a major air pollutant that has caused severe adverse health impacts in China. It was not until late 2012 that China established its ground PM2.5 monitoring network. The lack of ground PM2.5 measurements before 2013 makes it difficult to assess the long-term trends of PM2.5 and its health impacts in China. PM2.5 has been widely recognized as an air pollutant that would cause visibility degradation. Given the facts that the visibility data has been available since 1950s in most major cities in China, it provides a potential way to figure out the long-term ground PM2.5 concentrations. In this work, we developed a national-scale spatiotemporal linear mixed effects model to estimate the long-term PM2.5 concentrations in China from 1957 to 2014 using ground visibility monitoring data as the primary predictor. We used the 2014 data to develop the model. The overall model-fitting and cross-validation R2 is 0.74 and 0.72, suggesting that the model is not over-fitted. Validation beyond the model year (2014) indicated that the model could generate accurate historical PM2.5 concentrations at the monthly (R2 = 0.72) level. Results show that air pollution is not a new environmental issue that occurs in the recent decades but a problem existing in a longer time before 1980. The PM2.5 concentrations have reached 60-80 µg/m3 in the north part of North China Plain during 1950s-1960s and increased to generally higher than 90 µg/m3 during 1970s. The results also show that the entire China experienced an overall increasing trend (0.20 µg/m3/yr, P<0.001) in PM2.5 concentrations from 1957 to 2014 with fluctuations among different periods. This study demonstrated that the visibility data allow us to preliminarily understand the spatiotemporal characteristics of PM2.5 pollution in China in a longer time scale when ground monitoring and satellite remote sensing data are unavailable.

Towards an agent based traffic regulation and recommendation system for the on-road air quality control.

PubMed

Sadiq, Abderrahmane; El Fazziki, Abdelaziz; Ouarzazi, Jamal; Sadgal, Mohamed

2016-01-01

This paper presents an integrated and adaptive problem-solving approach to control the on-road air quality by modeling the road infrastructure, managing traffic based on pollution level and generating recommendations for road users. The aim is to reduce vehicle emissions in the most polluted road segments and optimizing the pollution levels. For this we propose the use of historical and real time pollution records and contextual data to calculate the air quality index on road networks and generate recommendations for reassigning traffic flow in order to improve the on-road air quality. The resulting air quality indexes are used in the system's traffic network generation, which the cartography is represented by a weighted graph. The weights evolve according to the pollution indexes and path properties and the graph is therefore dynamic. Furthermore, the systems use the available pollution data and meteorological records in order to predict the on-road pollutant levels by using an artificial neural network based prediction model. The proposed approach combines the benefits of multi-agent systems, Big data technology, machine learning tools and the available data sources. For the shortest path searching in the road network, we use the Dijkstra algorithm over Hadoop MapReduce framework. The use Hadoop framework in the data retrieve and analysis process has significantly improved the performance of the proposed system. Also, the agent technology allowed proposing a suitable solution in terms of robustness and agility.

Preliminary assessment of a water-quality monitoring program for total maximum daily loads in Johnson County, Kansas, January 2015 through June 2016

USGS Publications Warehouse

Rasmussen, Teresa J.; Paxson, Chelsea R.

2017-08-25

Municipalities in Johnson County in northeastern Kansas are required to implement stormwater management programs to reduce pollutant discharges, protect water quality, and comply with applicable water-quality regulations in accordance with National Pollutant Discharge Elimination System permits for stormwater discharge. To this end, municipalities collect grab samples at streams entering and leaving their jurisdiction to determine levels of excessive nutrients, sediment, and fecal bacteria to characterize pollutants and understand the factors affecting them.In 2014, the U.S. Geological Survey and the Johnson County Stormwater Management Program, with input from the Kansas Department of Health and Environment, initiated a 5-year monitoring program to satisfy minimum sampling requirements for each municipality as described by new stormwater permits issued to Johnson County municipalities. The purpose of this report is to provide a preliminary assessment of the monitoring program. The monitoring program is described, a preliminary assessment of the monitoring program design is provided using water-quality data collected during the first 2 years of the program, and the ability of the current monitoring network and sampling plan to provide data sufficient to quantify improvements in water quality resulting from implemented and planned best management practices is evaluated. The information in this initial report may be used to evaluate changes in data collection methods while data collection is still ongoing that may lead to improved data utility.Discrete water-quality samples were collected at 27 sites and analyzed for nutrients, Escherichia coli (E. coli) bacteria, total suspended solids, and suspended-sediment concentration. In addition, continuous water-quality data (water temperature, pH, dissolved oxygen, specific conductance, turbidity, and nitrate plus nitrite) were collected at one site to characterize variability and provide a basis for comparison to discrete data. Base flow samples indicated that point sources are likely affecting nutrient concentrations and E. coli bacteria densities at several sites. Concentrations of all analytes in storm runoff samples were characterized by substantial variability among sites and samples. About one-half of the sites, representing different watersheds, had storm runoff samples with nitrogen concentrations greater than 10 milligrams per liter. About one-third of the sites, representing different watersheds, had storm runoff samples with total phosphorus concentrations greater than 3 milligrams per liter. Six sites had samples with E. coli densities greater than 100,000 colonies per 100 milliliters of water. Total suspended solids concentrations of about 12,000 milligrams per liter or greater occurred in samples from three sites.Data collected for this monitoring program may be useful for some general assessment purposes but may also be limited in potential to fully inform stormwater management activities. Valuable attributes of the monitoring program design included incorporating many sites across the county for comparisons among watersheds and municipalities, using fixed-stage samplers to collect multiple samples during single events, collection of base flow samples in addition to storm samples to isolate possible point sources from stormwater sources, and use of continuous monitors to characterize variability. Limiting attributes of the monitoring program design included location of monitoring sites along municipal boundaries to satisfy permit requirements rather than using watershed-based criteria such as locations of tributaries, potential pollutant sources, and implemented management practices. Additional limiting attributes include having a large number of widespread sampling locations, which presented logistical challenges for predicting localized rainfall and collecting and analyzing samples during short timeframes associated with storms, and collecting storm samples at fixed-stage elevations only during the rising limb of storms, which does not characterize conditions over the storm hydrograph. The small number of samples collected per site resulted in a sample size too small to be representative of site conditions, including seasonal and hydrologic variability, and insufficient for meaningful statistical analysis or site-specific modeling.Several measures could be taken to improve data utility and include redesigning the monitoring network according to watershed characteristics, incorporating a nested design in which data are collected at different scales (watershed, subwatershed, and best management practices), increasing sampling frequency, and combining different methods to allow for flexibility to focus on areas and conditions of particular interest. A monitoring design that would facilitate most of these improvements would be to focus efforts on a limited number of watersheds for several years, then cycle to the next set of watersheds for several years, eventually returning to previously monitored watersheds to document changes.Redesign of the water-quality monitoring program requires considerable effort and commitment from municipalities of Johnson County. However, the long-term benefit likely is a monitoring program that results in improved stream conditions and more effective management practices and efficient expenditure of resources.

Next-generation air monitoring – an overview of EPA research to develop real-time instrumentation packages for stationary and mobile monitoring

EPA Science Inventory

Abstract. Air pollution measurement technology is advancing rapidly towards small-scale, real-time, wireless detectors, with a potential to significantly change the landscape of air pollution monitoring. The U.S. EPA Office of Research and Development is evaluating and developi...

Pollution Prevention Information Network (PPIN) Grant Summaries 2014

EPA Pesticide Factsheets

The Office of Pollution Prevention and Toxics is responsible for overseeing several grant programs for tribes and states which promote pollution prevention through source reduction and resource conservation.

An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning

PubMed Central

Jo, ByungWan

2018-01-01

The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH4, CO, SO2, and H2S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R2 and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality. PMID:29561777

An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning.

PubMed

Jo, ByungWan; Khan, Rana Muhammad Asad

2018-03-21

The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH₄, CO, SO₂, and H₂S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R ² and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality.

A study of impact of Asian dusts and their transport pathways to Hong Kong using multiple AERONET data, trajectory, and in-situ measurements

NASA Astrophysics Data System (ADS)

Wong, Man Sing; Nichol, Janet Elizabeth; Lee, Kwon Ho

2010-10-01

Hong Kong, a commercial and financial city located in south-east China has suffered serious air pollution for the last decade due largely to rapid urban and industrial expansion of the cities of mainland China. However, the potential sources and pathways of aerosols transported to Hong Kong have not been well researched due to the lack of air quality monitoring stations in southern China. Here, an integrated method combining the AErosol RObotic NETwork (AERONET) data, trajectory and Potential Source Contribution Function (PSCF) modeling is used to identify the potential transport pathways and contribution of sources from four characteristic aerosol types. Four characteristic aerosol types were defined using a total of 730 AERONET data measurements between 2005 and 2008. They are coastal urban, polluted urban, dust (likely to be long distance desert dust), and heavy pollution. Results show that the sources of polluted urban and heavy pollution are associated with industrial emissions in southern China, whereas coastal urban aerosols have been affected both from natural marine aerosol and emissions. The PSCF map of dust shows a wide range of pathways followed by east- and south-eastwards trajectories from northwest China to Hong Kong. Although the contribution from dust sources is small compared to the anthropogenic aerosols, a serious recent dust outbreak has been observed in Hong Kong with an elevation of the Air Pollution Index to 500, compared with 50-100 on normal days. Therefore, the combined use of clustered AERONET data, trajectory and the PSCF models can help to resolve the longstanding issue about source regions and characteristics of pollutants carried to Hong Kong.

Sensor Placement Optimization using Chama

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klise, Katherine A.; Nicholson, Bethany L.; Laird, Carl Damon

Continuous or regularly scheduled monitoring has the potential to quickly identify changes in the environment. However, even with low - cost sensors, only a limited number of sensors can be deployed. The physical placement of these sensors, along with the sensor technology and operating conditions, can have a large impact on the performance of a monitoring strategy. Chama is an open source Python package which includes mixed - integer, stochastic programming formulations to determine sensor locations and technology that maximize monitoring effectiveness. The methods in Chama are general and can be applied to a wide range of applications. Chama ismore » currently being used to design sensor networks to monitor airborne pollutants and to monitor water quality in water distribution systems. The following documentation includes installation instructions and examples, description of software features, and software license. The software is intended to be used by regulatory agencies, industry, and the research community. It is assumed that the reader is familiar with the Python Programming Language. References are included for addit ional background on software components. Online documentation, hosted at http://chama.readthedocs.io/, will be updated as new features are added. The online version includes API documentation .« less

Interpolation of extensive routine water pollution monitoring datasets: methodology and discussion of implications for aquifer management.

PubMed

Yuval, Yuval; Rimon, Yaara; Graber, Ellen R; Furman, Alex

2014-08-01

A large fraction of the fresh water available for human use is stored in groundwater aquifers. Since human activities such as mining, agriculture, industry and urbanisation often result in incursion of various pollutants to groundwater, routine monitoring of water quality is an indispensable component of judicious aquifer management. Unfortunately, groundwater pollution monitoring is expensive and usually cannot cover an aquifer with the spatial resolution necessary for making adequate management decisions. Interpolation of monitoring data is thus an important tool for supplementing monitoring observations. However, interpolating routine groundwater pollution data poses a special problem due to the nature of the observations. The data from a producing aquifer usually includes many zero pollution concentration values from the clean parts of the aquifer but may span a wide range of values (up to a few orders of magnitude) in the polluted areas. This manuscript presents a methodology that can cope with such datasets and use them to produce maps that present the pollution plumes but also delineates the clean areas that are fit for production. A method for assessing the quality of mapping in a way which is suitable to the data's dynamic range of values is also presented. A local variant of inverse distance weighting is employed to interpolate the data. Inclusion zones around the interpolation points ensure that only relevant observations contribute to each interpolated concentration. Using inclusion zones improves the accuracy of the mapping but results in interpolation grid points which are not assigned a value. The inherent trade-off between the interpolation accuracy and coverage is demonstrated using both circular and elliptical inclusion zones. A leave-one-out cross testing is used to assess and compare the performance of the interpolations. The methodology is demonstrated using groundwater pollution monitoring data from the coastal aquifer along the Israeli shoreline. The implications for aquifer management are discussed.

COVARIATE-ADAPTIVE CLUSTERING OF EXPOSURES FOR AIR POLLUTION EPIDEMIOLOGY COHORTS*

PubMed Central

Keller, Joshua P.; Drton, Mathias; Larson, Timothy; Kaufman, Joel D.; Sandler, Dale P.; Szpiro, Adam A.

2017-01-01

Cohort studies in air pollution epidemiology aim to establish associations between health outcomes and air pollution exposures. Statistical analysis of such associations is complicated by the multivariate nature of the pollutant exposure data as well as the spatial misalignment that arises from the fact that exposure data are collected at regulatory monitoring network locations distinct from cohort locations. We present a novel clustering approach for addressing this challenge. Specifically, we present a method that uses geographic covariate information to cluster multi-pollutant observations and predict cluster membership at cohort locations. Our predictive k-means procedure identifies centers using a mixture model and is followed by multi-class spatial prediction. In simulations, we demonstrate that predictive k-means can reduce misclassification error by over 50% compared to ordinary k-means, with minimal loss in cluster representativeness. The improved prediction accuracy results in large gains of 30% or more in power for detecting effect modification by cluster in a simulated health analysis. In an analysis of the NIEHS Sister Study cohort using predictive k-means, we find that the association between systolic blood pressure (SBP) and long-term fine particulate matter (PM2.5) exposure varies significantly between different clusters of PM2.5 component profiles. Our cluster-based analysis shows that for subjects assigned to a cluster located in the Midwestern U.S., a 10 μg/m3 difference in exposure is associated with 4.37 mmHg (95% CI, 2.38, 6.35) higher SBP. PMID:28572869

Restless roosts: Light pollution affects behavior, sleep, and physiology in a free-living songbird.

PubMed

Ouyang, Jenny Q; de Jong, Maaike; van Grunsven, Roy H A; Matson, Kevin D; Haussmann, Mark F; Meerlo, Peter; Visser, Marcel E; Spoelstra, Kamiel

2017-11-01

The natural nighttime environment is increasingly polluted by artificial light. Several studies have linked artificial light at night to negative impacts on human health. In free-living animals, light pollution is associated with changes in circadian, reproductive, and social behavior, but whether these animals also suffer from physiologic costs remains unknown. To fill this gap, we made use of a unique network of field sites which are either completely unlit (control), or are artificially illuminated with white, green, or red light. We monitored nighttime activity of adult great tits, Parus major, and related this activity to within-individual changes in physiologic indices. Because altered nighttime activity as a result of light pollution may affect health and well-being, we measured oxalic acid concentrations as a biomarker for sleep restriction, acute phase protein concentrations and malaria infection as indices of immune function, and telomere lengths as an overall measure of metabolic costs. Compared to other treatments, individuals roosting in the white light were much more active at night. In these individuals, oxalic acid decreased over the course of the study. We also found that individuals roosting in the white light treatment had a higher probability of malaria infection. Our results indicate that white light at night increases nighttime activity levels and sleep debt and affects disease dynamics in a free-living songbird. Our study offers the first evidence of detrimental effects of light pollution on the health of free-ranging wild animals. © 2017 John Wiley & Sons Ltd.

Reducing urban diffuse pollution and surface water flooding using retrofit street trees

NASA Astrophysics Data System (ADS)

Rothwell, James; Stringer, Pete; Causer, Katherine; Ryan, Matt; Mangan, Steve; Appleton, Ian; Savage, Mike

2016-04-01

Nature-based solutions for the management of urban stormwater have been growing in popularity, but there is a lack of empirical performance data for field-scale installations, especially in a UK context. To address this deficiency, a novel retrofit street tree demonstration project was commissioned in the City of Salford, near Manchester (UK). Three fifteen year-old London Plane trees were planted within a large roadside tree trench on an urban residential street. The DeepRoot Silvia Cell modular suspended pavement system was used to maximise soil volume, avoid compaction and support large tree growth. Road runoff is directed to the tree trench via AKO Slot Kerbs. Water is then distributed evenly throughout the whole system via a perforated pipe. Excess water is conveyed out of the system via an underdrain, which is subsequently connected to the sewer network. The tree trench is lined with an impermeable membrane. Access chambers are positioned on the inflow and outflow of the tree trench to facilitate hydrological and water quality monitoring. Installation was completed in autumn 2015 and monitoring will be conducted over a three year period. This paper will provide an overview of the installation process and present initial results on the pollutant removal performance and hydrological functioning of the system.

Bayesian maximum entropy integration of ozone observations and model predictions: an application for attainment demonstration in North Carolina.

PubMed

de Nazelle, Audrey; Arunachalam, Saravanan; Serre, Marc L

2010-08-01

States in the USA are required to demonstrate future compliance of criteria air pollutant standards by using both air quality monitors and model outputs. In the case of ozone, the demonstration tests aim at relying heavily on measured values, due to their perceived objectivity and enforceable quality. Weight given to numerical models is diminished by integrating them in the calculations only in a relative sense. For unmonitored locations, the EPA has suggested the use of a spatial interpolation technique to assign current values. We demonstrate that this approach may lead to erroneous assignments of nonattainment and may make it difficult for States to establish future compliance. We propose a method that combines different sources of information to map air pollution, using the Bayesian Maximum Entropy (BME) Framework. The approach gives precedence to measured values and integrates modeled data as a function of model performance. We demonstrate this approach in North Carolina, using the State's ozone monitoring network in combination with outputs from the Multiscale Air Quality Simulation Platform (MAQSIP) modeling system. We show that the BME data integration approach, compared to a spatial interpolation of measured data, improves the accuracy and the precision of ozone estimations across the state.

Biofilm as a bioindicator of Cr VI pollution in the Lotic Ecosystems

NASA Astrophysics Data System (ADS)

Kurniawan, A.; Sukandar; Satriya, C.; Guntur

2018-04-01

Biofilm is ubiquitous in aquatic ecosystems such as river. Biofilm have been reported to have high sorption capacities that promote the accumulation of nutrient ions inside biofilm matrix. The ion that can be accumulated inside the biofilm is not only nutrient ions but also other ions such as heavy metal ions. The pollution of heavy metal ions emerge as one of the biggest aquatic ecosystem problems. Thus, the effort to monitor the heavy metal pollution in the aquatic ecosystem in the aquatic ecosystems is needed. The difficulty to monitor the water pollution particularly in the lotic ecosystems is mainly related to the water flow. Therefore, the utilization of indicator of pollution in such ecosystem is fundamentally important. The present study investigated the accumulation of Cr VI inside biofilm matrices in the river ecosystems in order to develop biofilm as a bioindicator for pollution in the lotic ecosystems. The result indicates that biofilm can accumulate Cr VI from the surrounding water and reserve the ion. According to the result of this study, biofilm is a promising bioindicator to monitor the Cr VI pollution in the lotic ecosystems.

Tehran Air Pollutants Prediction Based on Random Forest Feature Selection Method

NASA Astrophysics Data System (ADS)

Shamsoddini, A.; Aboodi, M. R.; Karami, J.

2017-09-01

Air pollution as one of the most serious forms of environmental pollutions poses huge threat to human life. Air pollution leads to environmental instability, and has harmful and undesirable effects on the environment. Modern prediction methods of the pollutant concentration are able to improve decision making and provide appropriate solutions. This study examines the performance of the Random Forest feature selection in combination with multiple-linear regression and Multilayer Perceptron Artificial Neural Networks methods, in order to achieve an efficient model to estimate carbon monoxide and nitrogen dioxide, sulfur dioxide and PM2.5 contents in the air. The results indicated that Artificial Neural Networks fed by the attributes selected by Random Forest feature selection method performed more accurate than other models for the modeling of all pollutants. The estimation accuracy of sulfur dioxide emissions was lower than the other air contaminants whereas the nitrogen dioxide was predicted more accurate than the other pollutants.

Forecasting air quality time series using deep learning.

PubMed

Freeman, Brian S; Taylor, Graham; Gharabaghi, Bahram; Thé, Jesse

2018-04-13

This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of identifying population exposure to airborne pollutants and determining compliance with local ambient air standards. In this paper, 8 hr averaged surface ozone (O 3 ) concentrations were predicted using deep learning consisting of a recurrent neural network (RNN) with long short-term memory (LSTM). Hourly air quality and meteorological data were used to train and forecast values up to 72 hours with low error rates. The LSTM was able to forecast the duration of continuous O 3 exceedances as well. Prior to training the network, the dataset was reviewed for missing data and outliers. Missing data were imputed using a novel technique that averaged gaps less than eight time steps with incremental steps based on first-order differences of neighboring time periods. Data were then used to train decision trees to evaluate input feature importance over different time prediction horizons. The number of features used to train the LSTM model was reduced from 25 features to 5 features, resulting in improved accuracy as measured by Mean Absolute Error (MAE). Parameter sensitivity analysis identified look-back nodes associated with the RNN proved to be a significant source of error if not aligned with the prediction horizon. Overall, MAE's less than 2 were calculated for predictions out to 72 hours. Novel deep learning techniques were used to train an 8-hour averaged ozone forecast model. Missing data and outliers within the captured data set were replaced using a new imputation method that generated calculated values closer to the expected value based on the time and season. Decision trees were used to identify input variables with the greatest importance. The methods presented in this paper allow air managers to forecast long range air pollution concentration while only monitoring key parameters and without transforming the data set in its entirety, thus allowing real time inputs and continuous prediction.

Using geo-targeted social media data to detect outdoor air pollution

NASA Astrophysics Data System (ADS)

Jiang, W.; Wang, Y.; Tsou, M. H.; Fu, X.

2016-06-01

Outdoor air pollution has become a more and more serious issue over recent years (He, 2014). Urban air quality is measured at air monitoring stations. Building air monitoring stations requires land, incurs costs and entails skilled technicians to maintain a station. Many countries do not have any monitoring stations and even lack any means to monitor air quality. Recent years, the social media could be used to monitor air quality dynamically (Wang, 2015; Mei, 2014). However, no studies have investigated the inter-correlations between real-space and cyberspace by examining variation in micro-blogging behaviors relative to changes in daily air quality. Thus, existing methods of monitoring AQI using micro-blogging data shows a high degree of error between real AQI and air quality as inferred from social media messages. In this paper, we introduce a new geo-targeted social media analytic method to (1) investigate the dynamic relationship between air pollution-related posts on Sina Weibo and daily AQI values; (2) apply Gradient Tree Boosting, a machine learning method, to monitor the dynamics of AQI using filtered social media messages. Our results expose the spatiotemporal relationships between social media messages and real-world environmental changes as well suggesting new ways to monitor air pollution using social media.

A real-time monitoring and assessment method for calculation of total amounts of indoor air pollutants emitted in subway stations.

PubMed

Oh, TaeSeok; Kim, MinJeong; Lim, JungJin; Kang, OnYu; Shetty, K Vidya; SankaraRao, B; Yoo, ChangKyoo; Park, Jae Hyung; Kim, Jeong Tai

2012-05-01

Subway systems are considered as main public transportation facility in developed countries. Time spent by people in indoors, such as underground spaces, subway stations, and indoor buildings, has gradually increased in the recent past. Especially, operators or old persons who stay in indoor environments more than 15 hr per day usually influenced a greater extent by indoor air pollutants. Hence, regulations on indoor air pollutants are needed to ensure good health of people. Therefore, in this study, a new cumulative calculation method for the estimation of total amounts of indoor air pollutants emitted inside the subway station is proposed by taking cumulative amounts of indoor air pollutants based on integration concept. Minimum concentration of individual air pollutants which naturally exist in indoor space is referred as base concentration of air pollutants and can be found from the data collected. After subtracting the value of base concentration from data point of each data set of indoor air pollutant, the primary quantity of emitted air pollutant is calculated. After integration is carried out with these values, adding the base concentration to the integration quantity gives the total amount of indoor air pollutant emitted. Moreover the values of new index for cumulative indoor air quality obtained for 1 day are calculated using the values of cumulative air quality index (CAI). Cumulative comprehensive indoor air quality index (CCIAI) is also proposed to compare the values of cumulative concentrations of indoor air pollutants. From the results, it is clear that the cumulative assessment approach of indoor air quality (IAQ) is useful for monitoring the values of total amounts of indoor air pollutants emitted, in case of exposure to indoor air pollutants for a long time. Also, the values of CCIAI are influenced more by the values of concentration of NO2, which is released due to the use of air conditioners and combustion of the fuel. The results obtained in this study confirm that the proposed method can be applied to monitor total amounts of indoor air pollutants emitted, inside apartments and hospitals as well. Nowadays, subway systems are considered as main public transportation facility in developed countries. Time spent by people in indoors, such as underground spaces, subway stations, and indoor buildings, has gradually increased in the recent past. Especially, operators or old persons who stay in the indoor environments more than 15 hr per day usually influenced a greater extent by indoor air pollutants. Hence, regulations on indoor air pollutants are needed to ensure good health of people. Therefore, this paper presents a new methodology for monitoring and assessing total amounts of indoor air pollutants emitted inside underground spaces and subway stations. A new methodology for the calculation of cumulative amounts of indoor air pollutants based on integration concept is proposed. The results suggest that the cumulative assessment approach of IAQ is useful for monitoring the values of total amounts of indoor air pollutants, if indoor air pollutants accumulated for a long time, especially NO2 pollutants. The results obtained here confirm that the proposed method can be applied to monitor total amounts of indoor air pollutants emitted, inside apartments and hospitals as well.

Next Generation Air Monitoring

EPA Science Inventory

Abstract. Air pollution measurement technology is advancing rapidly towards smaller-scale and wireless devices, with a potential to significantly change the landscape of air pollution monitoring. The U.S. EPA Office of Research and Development is evaluating and developing a rang...

Monitor-based evaluation of pollutant load from urban stormwater runoff in Beijing.

PubMed

Liu, Y; Che, W; Li, J

2005-01-01

As a major pollutant source to urban receiving waters, the non-point source pollution from urban runoff needs to be well studied and effectively controlled. Based on monitoring data from urban runoff pollutant sources, this article describes a systematic estimation of total pollutant loads from the urban areas of Beijing. A numerical model was developed to quantify main pollutant loads of urban runoff in Beijing. A sub-procedure is involved in this method, in which the flush process influences both the quantity and quality of stormwater runoff. A statistics-based method was applied in computing the annual pollutant load as an output of the runoff. The proportions of pollutant from point-source and non-point sources were compared. This provides a scientific basis for proper environmental input assessment of urban stormwater pollution to receiving waters, improvement of infrastructure performance, implementation of urban stormwater management, and utilization of stormwater.

Total Nitrogen Concentrations in Surface Water of Typical Agro- and Forest Ecosystems in China, 2004-2009

PubMed Central

Xu, Zhiwei; Zhang, Xinyu; Xie, Juan; Yuan, Guofu; Tang, Xinzhai; Sun, Xiaomin; Yu, Guirui

2014-01-01

We assessed the total nitrogen (N) concentrations of 28 still surface water (lake and pond), and 42 flowing surface water (river), monitoring sites under 29 typical terrestrial ecosystems of the Chinese Ecosystem Research Network (CERN) using monitoring data collected between 2004 and 2009. The results showed that the median total N concentrations of still surface water were significantly higher in the agro- (1.5 mg·L−1) and oasis agro- ecosystems (1.8 mg·L−1) than in the forest ecosystems (1.0 mg·L−1). This was also the case for flowing surface water, with total N concentrations of 2.4 mg·L−1, 1.8 mg·L−1 and 0.5 mg·L−1 for the agro-, oasis agro- and forest ecosystems, respectively. In addition, more than 50% of the samples in agro- and oasis agro- ecosystems were seriously polluted (>1.0 mg·L−1) by N. Spatial analysis showed that the total N concentrations in northern and northwestern regions were higher than those in the southern region for both still and flowing surface waters under agro- and oasis agro- ecosystems, with more than 50% of samples exceeding 1.0 mg·L−1 (the Class III limit of the Chinese National Quality Standards for Surface Waters) in surface water in the northern region. Nitrogen pollution in agro- ecosystems is mainly due to fertilizer applications, while the combination of fertilizer and irrigation exacerbates nitrogen pollution in oasis agro- ecosystems. PMID:24667701

Plastic Free Belize: People, Plastic, and Pollution in a developing Caribbean nation

NASA Astrophysics Data System (ADS)

Bennett-Martin, P. A.; Longobardi, P.

2016-02-01

The accumulation of non-organic debris from humans is a growing environmental concern in coastal Belize. This study used a variety of methods to inventory and categorize debris types, to assess the spatial distribution of debris and used GIS to catalog and analyze data. Marine debris included glass, metal, styrofoam, fishing debris, and plastics. Plastics were the most abundant marine debris observed, and are a common pollutant in the marine ecosystem throughout Belize. The study also used ethnographic techniques engaging members of three coastal communities to assess practices for managing the debris. In 2015, we worked with over 146 individuals in different capacities in the communities of Belize City, Blackbird Caye, and Caye Caulker to determine their involvement and activities with marine debris. The participatory observation process discovered a network of individuals who are committed to managing and reducing waste, especially plastic pollution. This research establishes a baseline framework for participatory monitoring and adaptive governance for addressing coastal marine debris issues at varying scales: individuals, communities, NGOs, and government. These data allow for use of critical cartographic representations that will be beneficial to coastal communities of Belize for awareness and governance purposes related to future management of marine debris issues.

"Total Deposition (TDEP) Maps" | Science Inventory | US EPA

EPA Pesticide Factsheets

The presentation provides an update on the use of a hybrid methodology that relies on measured values from national monitoring networks and modeled values from CMAQ to produce of maps of total deposition for use in critical loads and other ecological assessments. Additionally, comparisons of the deposition values from the hybrid approach are compared with deposition estimates from other methodologies. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.

40 CFR 63.1505 - Emission standards for affected sources and emission units.

Code of Federal Regulations, 2010 CFR

2010-07-01

...-on air pollution control device if a continuous opacity monitor (COM) or visible emissions monitoring... percent opacity from any PM add-on air pollution control device if a COM is chosen as the monitoring.../delacquering kiln/decoating kiln is equipped with an afterburner having a design residence time of at least 1...

40 CFR 60.1230 - What continuous emission monitoring systems must I install for gaseous pollutants?

Code of Federal Regulations, 2010 CFR

2010-07-01

... systems for oxygen (or carbon dioxide), sulfur dioxide, and carbon monoxide. If you operate a Class I... sulfur dioxide, nitrogen oxides, and oxygen (or carbon dioxide) at the outlet of the air pollution... according to the “Monitoring Requirements” in § 60.13. (c) You must monitor the oxygen (or carbon dioxide...

40 CFR 60.1230 - What continuous emission monitoring systems must I install for gaseous pollutants?

Code of Federal Regulations, 2011 CFR

2011-07-01

... systems for oxygen (or carbon dioxide), sulfur dioxide, and carbon monoxide. If you operate a Class I... sulfur dioxide, nitrogen oxides, and oxygen (or carbon dioxide) at the outlet of the air pollution... according to the “Monitoring Requirements” in § 60.13. (c) You must monitor the oxygen (or carbon dioxide...

Optimal Control of Connected and Automated Vehicles at Roundabouts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Liuhui; Malikopoulos, Andreas; Rios-Torres, Jackeline

Connectivity and automation in vehicles provide the most intriguing opportunity for enabling users to better monitor transportation network conditions and make better operating decisions to improve safety and reduce pollution, energy consumption, and travel delays. This study investigates the implications of optimally coordinating vehicles that are wirelessly connected to each other and to an infrastructure in roundabouts to achieve a smooth traffic flow without stop-and-go driving. We apply an optimization framework and an analytical solution that allows optimal coordination of vehicles for merging in such traffic scenario. The effectiveness of the efficiency of the proposed approach is validated through simulationmore » and it is shown that coordination of vehicles can reduce total travel time by 3~49% and fuel consumption by 2~27% with respect to different traffic levels. In addition, network throughput is improved by up to 25% due to elimination of stop-and-go driving behavior.« less

Pollution Prevention Information Network (PPIN) Grant Summaries for 2011 and 2013

EPA Pesticide Factsheets

The Office of Pollution Prevention and Toxics is responsible for overseeing several grant programs for tribes and states which promote pollution prevention through source reduction and resource conservation.

[Application of lysosomal detection in marine pollution monitoring: research progress].

PubMed

Weng, You-Zhu; Fang, Yong-Qiang; Zhang, Yu-Sheng

2013-11-01

Lysosome is an important organelle existing in eukaryotic cells. With the development of the study on the structure and function of lysosome in recent years, lysosome is considered as a target of toxic substances on subcellular level, and has been widely applied abroad in marine pollution monitoring. This paper summarized the biological characteristics of lysosomal marker enzyme, lysosome-autophagy system, and lysosomal membrane, and introduced the principles and methods of applying lysosomal detection in marine pollution monitoring. Bivalve shellfish digestive gland and fish liver are the most sensitive organs for lysosomal detection. By adopting the lysosomal detection techniques such as lysosomal membrane stability (LMS) test, neutral red retention time (NRRT) assay, morphological measurement (MM) of lysosome, immunohistochemical (Ih) assay of lysosomal marker enzyme, and electron microscopy (EM), the status of marine pollution can be evaluated. It was suggested that the lysosome could be used as a biomarker for monitoring marine environmental pollution. The advantages and disadvantages of lysosomal detection and some problems worthy of attention were analyzed, and the application prospects of lysosomal detection were discussed.

Statewide water-quality network for Massachusetts

USGS Publications Warehouse

Desimone, Leslie A.; Steeves, Peter A.; Zimmerman, Marc James

2001-01-01

A water-quality monitoring program is proposed that would provide data to meet multiple information needs of Massachusetts agencies and other users concerned with the condition of the State's water resources. The program was designed by the U.S. Geological Survey and the Massachusetts Department of Environmental Protection, Division of Watershed Management, with input from many organizations involved in water-quality monitoring in the State, and focuses on inland surface waters (streams and lakes). The proposed monitoring program consists of several components, or tiers, which are defined in terms of specific monitoring objectives, and is intended to complement the Massachusetts Watershed Initiative (MWI) basin assessments. Several components were developed using the Neponset River Basin in eastern Massachusetts as a pilot area, or otherwise make use of data from and sampling approaches used in that basin as part of a MWI pilot assessment in 1994. To guide development of the monitoring program, reviews were conducted of general principles of network design, including monitoring objectives and approaches, and of ongoing monitoring activities of Massachusetts State agencies.Network tiers described in this report are primarily (1) a statewide, basin-based assessment of existing surface-water-quality conditions, and (2) a fixed-station network for determining contaminant loads carried by major rivers. Other components, including (3) targeted programs for hot-spot monitoring and other objectives, and (4) compliance monitoring, also are discussed. Monitoring programs for the development of Total Maximum Daily Loads for specific water bodies, which would constitute another tier of the network, are being developed separately and are not described in this report. The basin-based assessment of existing conditions is designed to provide information on the status of surface waters with respect to State water-quality standards and designated uses in accordance with the reporting requirements [Section 305(b)] of the Clean Water Act (CWA). Geographic Information System (GIS)-based procedures were developed to inventory streams and lakes in a basin for these purposes. Several monitoring approaches for this tier and their associated resource requirements were investigated. Analysis of the Neponset Basin for this purpose demonstrated that the large number of sites needed in order for all the small streams in a basin to be sampled (about half of stream miles in the basin were headwater or first-order streams) pose substantial resource-based problems for a comprehensive assessment of existing conditions. The many lakes pose similar problems. Thus, a design is presented in which probabilistic monitoring of small streams is combined with deterministic or targeted monitoring of large streams and lakes to meet CWA requirements and to provide data for other information needs of Massachusetts regulatory agencies and MWI teams.The fixed-station network is designed to permit the determination of contaminant loads carried by the State's major rivers to sensitive inland and coastal receiving waters and across State boundaries. Sampling at 19 proposed sites in 17 of the 27 major basins in Massachusetts would provide information on contaminant loads from 67 percent of the total land area of the State; unsampled areas are primarily coastal areas drained by many small streams that would be impossible to sample within realistic resource limitations. Strategies for hot-spot monitoring, a targeted monitoring program focused on identifying contaminant sources, are described with reference to an analysis of the bacteria sampling program of the 1994 Neponset Basin assessment. Finally, major discharge sites permitted under the National Pollutant Discharge Elimination System (NPDES) were evaluated as a basis for ambient water-quality monitoring. The discharge sites are well distributed geographically among basins, but are primarily on large rivers (two-thirds or more

40 CFR 63.548 - Monitoring requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 63.548 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) NATIONAL EMISSION STANDARDS FOR HAZARDOUS AIR POLLUTANTS FOR SOURCE CATEGORIES National Emission Standards for Hazardous Air Pollutants from Secondary Lead Smelting § 63.548 Monitoring requirements. (a) Owners...

Tracking hazardous air pollutants from a refinery fire by applying on-line and off-line air monitoring and back trajectory modeling.

PubMed

Shie, Ruei-Hao; Chan, Chang-Chuan

2013-10-15

The air monitors used by most regulatory authorities are designed to track the daily emissions of conventional pollutants and are not well suited for measuring hazardous air pollutants that are released from accidents such as refinery fires. By applying a wide variety of air-monitoring systems, including on-line Fourier transform infrared spectroscopy, gas chromatography with a flame ionization detector, and off-line gas chromatography-mass spectrometry for measuring hazardous air pollutants during and after a fire at a petrochemical complex in central Taiwan on May 12, 2011, we were able to detect significantly higher levels of combustion-related gaseous and particulate pollutants, refinery-related hydrocarbons, and chlorinated hydrocarbons, such as 1,2-dichloroethane, vinyl chloride monomer, and dichloromethane, inside the complex and 10 km downwind from the fire than those measured during the normal operation periods. Both back trajectories and dispersion models further confirmed that high levels of hazardous air pollutants in the neighboring communities were carried by air mass flown from the 22 plants that were shut down by the fire. This study demonstrates that hazardous air pollutants from industrial accidents can successfully be identified and traced back to their emission sources by applying a timely and comprehensive air-monitoring campaign and back trajectory air flow models. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Understanding and improving mitigation strategies for reducing catchment scale nutrient loads using high resolution observations and uncertainty analysis approaches

NASA Astrophysics Data System (ADS)

Collins, A.; Lloyd, C.; Freer, J. E.; Johnes, P.; Stirling, M.

2012-12-01

One of the biggest challenges in catchment water quality management is tackling the problem of reducing water pollution from agriculture whilst ensuring food security nationally. Improvements to catchment management plans are needed if we are to enhance biodiversity and maintain good ecological status in freshwater ecosystems, while producing enough food to support a growing global population. In order to plan for a more sustainable and secure future, research needs to quantify the uncertainties and understand the complexities in the source-mobilisation-delivery-impact continuum of pollution and nutrients at all scales. In the UK the Demonstration Test Catchment (DTC) project has been set up to improve water quality specifically from diffuse pollution from agriculture by enhanced high resolution monitoring and targeted mitigation experiments. The DTC project aims to detect shifts in the baseline trend of the most ecologically-significant pollutants resulting from targeted on-farm measures at field to farm scales and assessing their effects on ecosystem function. The DTC programme involves three catchments across the UK that are indicative of three different typologies and land uses. This paper will focus on the Hampshire Avon DTC, where a total of 12 parameters are monitored by bank-side stations at two sampling sites, including flow, turbidity, phosphate and nitrate concentrations at 30 min resolution. This monitoring is supported by daily resolution sampling at 5 other sites and storm sampling at all locations. Part of the DTC project aims to understand how observations of water quality within river systems at different temporal resolutions and types of monitoring strategies enable us to understand and detect changes over and above the natural variability. Baseline monitoring is currently underway and early results show that high-resolution data is essential at this sub-catchment scale to understand important process dynamics. This is critical if we are to design cost efficient and effective management strategies. The high-resolution dataset means that there are new opportunities to explore the associated uncertainties in monitoring water quality and assessing ecological status and how that relates to current monitoring networks. For example, concurrent grab samples at the high-resolution sampling stations allow the assessment of the uncertainties which would be generated through coarser sampling strategies. This is just the beginning of the project, however, as the project progresses, the high resolution dataset will provide higher statistical power compared with previous data collection schemes and allow the employment of more complex methods such as signal decomposition e.g. wavelet analysis, which can allow us to start to decipher the complex interactions occurring at sub-catchment scale which may not be immediately detectable in bulk signals. In this paper we outline our methodological approach, present some of the initial findings of this research and how we can quantify changes to nutrient loads whilst taking account the main uncertainties and the inherent natural variability.

Uncertainty in the relationship between criteria pollutants and low birth weight in Chicago

NASA Astrophysics Data System (ADS)

Kumar, Naresh

2012-03-01

Using the data on all live births (˜400,000) and criteria pollutants from the Chicago Metropolitan Statistical Area (MSA) between 2000 and 2004, this paper empirically demonstrates how mismatches in the spatiotemporal scales of health and air pollution data can result in inconsistency and uncertainty in the linkages between air pollution and birth outcomes. This paper suggests that the risks of low birth weight associated with air pollution exposure changes significantly as the distance interval (around the monitoring stations) used for exposure estimation changes. For example, when the analysis was restricted within 3 miles distance of the monitoring stations the odds of LBW (births <2500 g) increased by a factor of 1.045 (±0.0285 95% CI) with a unit increase in the average daily exposure to PM10 (in μg m-3) during the gestation period; the value dropped to 1.028 when the analysis was restricted within 6 miles distance of air pollution monitoring stations. The effect of PM10 exposure on LBW became null when controlled for confounders. But PM2.5 exposure showed a significant association with low birth weight when controlled for confounders. These results must be interpreted with caution, because the distance to monitoring station does not influence the risks of adverse birth outcomes, but uncertainty in exposure increases with the increase in distance from the monitoring stations, especially for coarse particles such as PM10 that settle with gravity within short distance and time interval. The results of this paper have important implications for the research design of environmental epidemiological studies, and the way air pollution (and potentially other environmental) and health data are collocated to compute exposure. While this paper challenges the findings of pervious epidemiological studies that have relied on coarse resolution air pollution data (such as county level aggregated data), the paper also calls for time-space resolved estimate of air pollution to minimize uncertainty in exposure estimation.

Research to Support California Greenhouse Gas Reduction Programs

NASA Astrophysics Data System (ADS)

Croes, B. E.; Charrier-Klobas, J. G.; Chen, Y.; Duren, R. M.; Falk, M.; Franco, G.; Gallagher, G.; Huang, A.; Kuwayama, T.; Motallebi, N.; Vijayan, A.; Whetstone, J. R.

2016-12-01

Since the passage of the California Global Warming Solutions Act in 2006, California state agencies have developed comprehensive programs to reduce both long-lived and short-lived climate pollutants. California is already close to achieving its goal of reducing greenhouse (GHG) emissions to 1990 levels by 2020, about a 30% reduction from business as usual. In addition, California has developed strategies to reduce GHG emissions another 40% by 2030, which will put the State on a path to meeting its 2050 goal of an 80% reduction. To support these emission reduction goals, the California Air Resources Board (CARB) and the California Energy Commission have partnered with NASA's Carbon Monitoring System (CMS) program on a comprehensive research program to identify and quantify the various GHG emission source sectors in the state. These include California-specific emission studies and inventories for carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) emission sources; a Statewide GHG Monitoring Network for these pollutants integrated with the Los Angeles Megacities Carbon Project funded by several federal agencies; efforts to verify emission inventories using inversion modeling and other techniques; mobile measurement platforms and flux chambers to measure local and source-specific emissions; and a large-scale statewide methane survey using a tiered monitoring and measurement program, which will include satellite, airborne, and ground-level measurements of the various regions and source sectors in the State. In addition, there are parallel activities focused on black carbon (BC) and fluorinated gases (F-gases) by CARB. This presentation will provide an overview of results from inventory, monitoring, data analysis, and other research efforts on Statewide, regional, and local sources of GHG emissions in California.

Trace metal concentrations in forest and lawn soils of Paris region (France) along a gradient of urban pressure

NASA Astrophysics Data System (ADS)

Ludovic, Foti

2017-04-01

Urban soils differ greatly from natural ones as they are located in areas of intense anthropogenic activity (e.g. pollution, physical disturbance, surface transformation). Urban soils are a crucial component of urban ecosystems, especially in public green spaces, and contribute to many ecosystem services from the mitigation of urban heat island to recreational services. In the last decade, the study of urban soils has emerged as an important frontier in environmental research, at least because of their impact on the quality of life of urban populations, because of the services they deliver and because they are more and more recognized as a valuable resource. One of the key issues is the pollution of urban soils because they receive a variety of deposits from local (vehicle emissions, industrial discharges, domestic heating, waste incineration and other anthropogenic activities) and from remote sources (through atmospheric transport). Typical contaminants include persistent toxic substances, such as trace metals (TMs) that have drawn wide attention due to their long persistence in the environment, their tendency to bioaccumulate in the food chain and their toxicity for humans and other organisms. Concentrations, spatial distributions, dynamics, impacts and sources of TMs (e.g. industry or fossil fuels combustion) have attracted a global interest in urban soils and are the subject of ongoing research (e.g. ecotoxicological urban ecology). Some studies have already documented soil pollution with TMs at both the town and regional scales. So far, several monitoring programs (e.g. National Network for the long term Monitoring of Forest Ecosystem, Regional Monitoring Quality of Soil in France) and studies have been carried out on a national scale to measure the ranges of TM concentrations and natural background values in French soils. These studies have focused on French agricultural and forest soils and have not tackled urban soils. No study has described TM concentrations and subsequent risks in soils of Paris and Paris region (Île-de-France). Our study aims at filling this knowledge gap, focusing on contamination and pollution by TMs in lawns and forests that constitute the main types of vegetation in urban areas of Paris region. Considering the rational described above, the aims of the present study were (i) to examine the concentration of eight selected TMs (As, Cd, Cr, Cu, Fe, Ni, Pb, Zn) in soils of two land-uses (public lawns and woods) along an urban pressure gradient in Paris region, (ii) to distinguish origins and sources of contamination or pollution, (iii) to evaluate the individual and overall TM contamination degree as well as the individual and overall TM pollution degree, (iiii) to use soil characteristics to better understand soil origins and histories along the urban pressure gradient and the relationship between these characteristics and TM concentrations. Ultimately, this study provides a baseline TM assessment for the long-term monitoring of the evolution of TM soil contents in urban area of the Paris region.

Design and implementation air quality monitoring robot

NASA Astrophysics Data System (ADS)

Chen, Yuanhua; Li, Jie; Qi, Chunxue

2017-01-01

Robot applied in environmental protection can break through the limitations in working environment, scope and mode of the existing environmental monitoring and pollution abatement equipments, which undertake the innovation and improvement in the basin, atmosphere, emergency and pollution treatment facilities. Actually, the relevant technology is backward with limited research and investment. Though the device companies have achieved some results in the study on the water quality monitoring, pipeline monitoring and sewage disposal, this technological progress on the whole is still much slow, and the mature product has not been formed. As a result, the market urges a demand of a new type of device which is more suitable for environmental protection on the basis of robot successfully applied in other fields. This paper designs and realizes a tracked mobile robot of air quality monitoring, which can be used to monitor air quality for the pollution accident in industrial parks and regular management.

Possibilities of observing air pollution from orbital altitudes

NASA Technical Reports Server (NTRS)

Barringer, A.

1972-01-01

Research carried out over a number of years has indicated the feasibility of monitoring global air pollution from orbiting satellites. Optical methods show considerable promise of measuring the burdens of pollution, both gaseous and particulates. Important pollution gases, such as sulfur dioxide, nitrogen dioxide, carbon monoxide, and ozone, as well as some hydrocarbon vapors, appear amenable to optical remote sensing. Satellite platforms for carrying out this work would not compete with ground monitoring stations but rather supplement them with a different type of data which could be integrated with ground level measurements to provide an all-embracing picture of pollution buildup, mass migration, and dissipation.