Ambient air monitoring plan for Ciudad Acuna and Piedra Negras, Coahuila, Mexico. Final report

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

Winberry, J.; Henning, L.; Crume, R.

1998-01-01

The Cities of Ciudad Acuna and Piedras Negras and the State of Coahuila in Mexico are interested in improving ambient air quality monitoring capabilities in the two cities through the establishment of a network of ambient air monitors. The purpose of the network is to characterize population exposure to potentially harmful air contaminants, possibly including sulfur dioxide (SO{sub 2}), nitrogen oxides (NO{sub x}), ozone (O{sub 3}), carbon monoxide (CO), total suspended particulate matter (TSP), particulate matter with aerodynamic diameter less than 100 micrometers PM-10, and lead. This report presents the results of an evaluation of existing air quality monitoring equipmentmore » and facilities in Ciudad Acuna and Piedras Negras. Additionally, the report presents recommendations for developing an air quality monitoring network for PM-10, SO{sub 2}, lead, and ozone in these cities, using a combination of both new and existing equipment. The human resources currently available and ultimately needed to operate and maintain the network are also discussed.« less

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...

A Hybrid Approach for Estimating Total Deposition in the ...

EPA Pesticide Factsheets

Atmospheric deposition of nitrogen and sulfur causes many deleterious effects on ecosystems including acidification and excess eutrophication. Assessments to support development of strategies to mitigate these effects require spatially and temporally continuous values of nitrogen and sulfur deposition. In the U.S., national monitoring networks exist that provide values of wet and dry deposition at discrete locations. While wet deposition can be interpolated between the monitoring locations, dry deposition cannot. Additionally, monitoring networks do not measure the complete suite of chemicals that contribute to total sulfur and nitrogen deposition. Regional air quality models provide spatially continuous values of deposition of monitored species as well as important unmeasured species. However, air quality modeling values are not generally available for an extended continuous time period. Air quality modeling results may also be biased for some chemical species. We developed a novel approach for estimating dry deposition using data from monitoring networks such as the Clean Air Status and Trends Network (CASTNET), the National Atmospheric Deposition Program (NADP) Ammonia Monitoring Network (AMoN), and the Southeastern Aerosol Research and Characterization (SEARCH) network and modeled data from the Community Multiscale Air Quality (CMAQ) model. These dry deposition values estimates are then combined with wet deposition values from the NADP National Trends Networ

A Novel Hybrid Approach for Estimating Total Deposition in ...

EPA Pesticide Factsheets

Atmospheric deposition of nitrogen and sulfur causes many deleterious effects on ecosystems including acidification and excess eutrophication. Assessments to support development of strategies to mitigate these effects require spatially and temporally continuous values of nitrogen and sulfur deposition. In the U.S., national monitoring networks exist that provide values of wet and dry deposition at discrete locations. While wet deposition can be interpolated between the monitoring locations, dry deposition cannot. Additionally, monitoring networks do not measure the complete suite of chemicals that contribute to total sulfur and nitrogen deposition. Regional air quality models provide spatially continuous values of deposition of monitored species as well as important unmeasured species. However, air quality modeling values are not generally available for an extended continuous time period. Air quality modeling results may also be biased for some chemical species. We developed a novel approach for estimating dry deposition using data from monitoring networks such as the Clean Air Status and Trends Network (CASTNET), the National Atmospheric Deposition Program (NADP) Ammonia Monitoring Network (AMoN), and the Southeastern Aerosol Research and Characterization (SEARCH) network and modeled data from the Community Multiscale Air Quality (CMAQ) model. These dry deposition values estimates are then combined with wet deposition values from the NADP National Trends Networ

A novel hybrid approach for estimating total deposition in the United States

NASA Astrophysics Data System (ADS)

Schwede, Donna B.; Lear, Gary G.

2014-08-01

Atmospheric deposition of nitrogen and sulfur causes many deleterious effects on ecosystems including acidification and excess eutrophication. Assessments to support development of strategies to mitigate these effects require spatially and temporally continuous values of nitrogen and sulfur deposition. In the U.S., national monitoring networks exist that provide values of wet and dry deposition at discrete locations. While wet deposition can be interpolated between the monitoring locations, dry deposition cannot. Additionally, monitoring networks do not measure the complete suite of chemicals that contribute to total sulfur and nitrogen deposition. Regional air quality models provide spatially continuous values of deposition of monitored species as well as important unmeasured species. However, air quality modeling values are not generally available for an extended continuous time period. Air quality modeling results may also be biased for some chemical species. We developed a novel approach for estimating dry deposition using data from monitoring networks such as the Clean Air Status and Trends Network (CASTNET), the National Atmospheric Deposition Program (NADP) Ammonia Monitoring Network (AMoN), and the Southeastern Aerosol Research and Characterization (SEARCH) network and modeled data from the Community Multiscale Air Quality (CMAQ) model. These dry deposition values estimates are then combined with wet deposition values from the NADP National Trends Network (NTN) to develop values of total deposition of sulfur and nitrogen. Data developed using this method are made available via the CASTNET website.

Definition of air quality measurements for monitoring space shuttle launches

NASA Technical Reports Server (NTRS)

Thorpe, R. D.

1978-01-01

A description of a recommended air quality monitoring network to characterize the impact on ambient air quality in the Kennedy Space Center (KSC) (area) of space shuttle launch operations is given. Analysis of ground cloud processes and prevalent meteorological conditions indicates that transient HCl depositions can be a cause for concern. The system designed to monitor HCl employs an extensive network of inexpensive detectors combined with a central analysis device. An acid rain network is also recommended. A quantitative measure of projected minimal long-term impact involves the limited monitoring of NOx and particulates. All recommended monitoring is confined ti KSC property.

40 CFR 58.15 - Annual air monitoring data certification.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Annual air monitoring data certification. 58.15 Section 58.15 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.15 Annual air monitoring data...

40 CFR 58.15 - Annual air monitoring data certification.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 5 2011-07-01 2011-07-01 false Annual air monitoring data certification. 58.15 Section 58.15 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.15 Annual air monitoring data...

Community Air Sensor Network (CAIRSENSE) Project: Lower Cost, Continuous Ambient Monitoring Methods

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 numerous sensors across a small geographic area would have potential benefits to supplement existing monitoring networks and ...

40 CFR 58.13 - Monitoring network completion.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Monitoring network completion. 58.13... (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a) The network of NCore multipollutant sites must be physically established no later than January 1, 2011...

40 CFR 58.13 - Monitoring network completion.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 5 2011-07-01 2011-07-01 false Monitoring network completion. 58.13... (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a) The network of NCore multipollutant sites must be physically established no later than January 1, 2011...

DESIGN OF LARGE-SCALE AIR MONITORING NETWORKS

EPA Science Inventory

The potential effects of air pollution on human health have received much attention in recent years. In the U.S. and other countries, there are extensive large-scale monitoring networks designed to collect data to inform the public of exposure risks to air pollution. A major crit...

Journal Article: EPA's National Dioxin Air Monitoring Network (Ndamn): Design, Implementation, and Final Results

EPA Science Inventory

The U.S. Environmental Protection Agency (U.S. EPA) established the National Dioxin Air Monitoring Network (NDAMN) in June of 1998, and operated it until November of 2004. The objective of NDAMN was to determine background air concentrations of polychlorinated dibenzo-p-dioxins (...

Smoke monitoring network on 2006 Northern California fires

Treesearch

Brenda Belongie; Suraj Ahuja

2007-01-01

Long-duration fire activity during the 2006 northern California fire season presented an excellent opportunity to create a temporary air-quality/smoke-monitoring network in the complex terrain across northwestern California. The network was established through cooperative interagency coordination of Federal officials, the California Air Resources Board (CARB), and...

Micro sensor node for air pollutant monitoring: hardware and software issues.

PubMed

Choi, Sukwon; Kim, Nakyoung; Cha, Hojung; Ha, Rhan

2009-01-01

Wireless sensor networks equipped with various gas sensors have been actively used for air quality monitoring. Previous studies have typically explored system issues that include middleware or networking performance, but most research has barely considered the details of the hardware and software of the sensor node itself. In this paper, we focus on the design and implementation of a sensor board for air pollutant monitoring applications. Several hardware and software issues are discussed to explore the possibilities of a practical WSN-based air pollution monitoring system. Through extensive experiments and evaluation, we have determined the various characteristics of the gas sensors and their practical implications for air pollutant monitoring systems.

Assessment of SRS ambient air monitoring network

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

Abbott, K.; Jannik, T.

Three methodologies have been used to assess the effectiveness of the existing ambient air monitoring system in place at the Savannah River Site in Aiken, SC. Effectiveness was measured using two metrics that have been utilized in previous quantification of air-monitoring network performance; frequency of detection (a measurement of how frequently a minimum number of samplers within the network detect an event), and network intensity (a measurement of how consistent each sampler within the network is at detecting events). In addition to determining the effectiveness of the current system, the objective of performing this assessment was to determine what, ifmore » any, changes could make the system more effective. Methodologies included 1) the Waite method of determining sampler distribution, 2) the CAP88- PC annual dose model, and 3) a puff/plume transport model used to predict air concentrations at sampler locations. Data collected from air samplers at SRS in 2015 compared with predicted data resulting from the methodologies determined that the frequency of detection for the current system is 79.2% with sampler efficiencies ranging from 5% to 45%, and a mean network intensity of 21.5%. One of the air monitoring stations had an efficiency of less than 10%, and detected releases during just one sampling period of the entire year, adding little to the overall network intensity. By moving or removing this sampler, the mean network intensity increased to about 23%. Further work in increasing the network intensity and simulating accident scenarios to further test the ambient air system at SRS is planned« 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.

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.

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.

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.

Journal Article: Atmospheric Measurements of CDDs, CDFs, and Coplanar PCBs in Rural and Remote Locations of the U.S. for the Years 1998-2001 from the National Dioxin Air Monitoring Network (Ndamn)

EPA Science Inventory

The U.S. EPA established a National Dioxin Air Monitoring Network (NDAMN) to determine background air concentrations of PCDDs, PCDFs, and cp-PCBs in rural and remote areas of the United States. Background is defined as average ambient air concentrations inferred from long-term a...

SENSITIVITY ANALYSIS OF THE MULTI-LAYER MODEL USED IN THE CLEAN AIR STATUS AND TRENDS NETWORK (CASTNET)

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) established the Clean Air Status and Trends Network (CASTNET) and its predecessor, the National Dry Deposition Network (NDDN), as national air quality and meteorological monitoring networks. The purpose of CASTNET is to track the pr...

U.S. EPA's National Dioxin Air Monitoring Network: Analytical Issues

EPA Science Inventory

The U.S. EPA has established a National Dioxin Air Monitoring Network (NDAMN) to determine the temporal and geographical variability of atmospheric chlorinated dibenzo-p-dioxins (CDDs), furans (CDFs), and coplanar polychlorinated biphenyls (PCBs) at rural and non-impacted locatio...

A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems

PubMed Central

Yi, Wei Ying; Lo, Kin Ming; Mak, Terrence; Leung, Kwong Sak; Leung, Yee; Meng, Mei Ling

2015-01-01

The air quality in urban areas is a major concern in modern cities due to significant impacts of air pollution on public health, global environment, and worldwide economy. Recent studies reveal the importance of micro-level pollution information, including human personal exposure and acute exposure to air pollutants. A real-time system with high spatio-temporal resolution is essential because of the limited data availability and non-scalability of conventional air pollution monitoring systems. Currently, researchers focus on the concept of The Next Generation Air Pollution Monitoring System (TNGAPMS) and have achieved significant breakthroughs by utilizing the advance sensing technologies, MicroElectroMechanical Systems (MEMS) and Wireless Sensor Network (WSN). However, there exist potential problems of these newly proposed systems, namely the lack of 3D data acquisition ability and the flexibility of the sensor network. In this paper, we classify the existing works into three categories as Static Sensor Network (SSN), Community Sensor Network (CSN) and Vehicle Sensor Network (VSN) based on the carriers of the sensors. Comprehensive reviews and comparisons among these three types of sensor networks were also performed. Last but not least, we discuss the limitations of the existing works and conclude the objectives that we want to achieve in future systems. PMID:26703598

A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems.

PubMed

Yi, Wei Ying; Lo, Kin Ming; Mak, Terrence; Leung, Kwong Sak; Leung, Yee; Meng, Mei Ling

2015-12-12

The air quality in urban areas is a major concern in modern cities due to significant impacts of air pollution on public health, global environment, and worldwide economy. Recent studies reveal the importance of micro-level pollution information, including human personal exposure and acute exposure to air pollutants. A real-time system with high spatio-temporal resolution is essential because of the limited data availability and non-scalability of conventional air pollution monitoring systems. Currently, researchers focus on the concept of The Next Generation Air Pollution Monitoring System (TNGAPMS) and have achieved significant breakthroughs by utilizing the advance sensing technologies, MicroElectroMechanical Systems (MEMS) and Wireless Sensor Network (WSN). However, there exist potential problems of these newly proposed systems, namely the lack of 3D data acquisition ability and the flexibility of the sensor network. In this paper, we classify the existing works into three categories as Static Sensor Network (SSN), Community Sensor Network (CSN) and Vehicle Sensor Network (VSN) based on the carriers of the sensors. Comprehensive reviews and comparisons among these three types of sensor networks were also performed. Last but not least, we discuss the limitations of the existing works and conclude the objectives that we want to achieve in future systems.

Optimal Design of Air Quality Monitoring Network and its Application in an Oil Refinery Plant: An Approach to Keep Health Status of Workers.

PubMed

ZoroufchiBenis, Khaled; Fatehifar, Esmaeil; Ahmadi, Javad; Rouhi, Alireza

2015-01-01

Industrial air pollution is a growing challenge to humane health, especially in developing countries, where there is no systematic monitoring of air pollution. Given the importance of the availability of valid information on population exposure to air pollutants, it is important to design an optimal Air Quality Monitoring Network (AQMN) for assessing population exposure to air pollution and predicting the magnitude of the health risks to the population. A multi-pollutant method (implemented as a MATLAB program) was explored for configur-ing an AQMN to detect the highest level of pollution around an oil refinery plant. The method ranks potential monitoring sites (grids) according to their ability to represent the ambient concentration. The term of cluster of contiguous grids that exceed a threshold value was used to calculate the Station Dosage. Selection of the best configuration of AQMN was done based on the ratio of a sta-tion's dosage to the total dosage in the network. Six monitoring stations were needed to detect the pollutants concentrations around the study area for estimating the level and distribution of exposure in the population with total network efficiency of about 99%. An analysis of the design procedure showed that wind regimes have greatest effect on the location of monitoring stations. The optimal AQMN enables authorities to implement an effective program of air quality management for protecting human health.

Optimal Design of Air Quality Monitoring Network and its Application in an Oil Refinery Plant: An Approach to Keep Health Status of Workers

PubMed Central

ZoroufchiBenis, Khaled; Fatehifar, Esmaeil; Ahmadi, Javad; Rouhi, Alireza

2015-01-01

Background: Industrial air pollution is a growing challenge to humane health, especially in developing countries, where there is no systematic monitoring of air pollution. Given the importance of the availability of valid information on population exposure to air pollutants, it is important to design an optimal Air Quality Monitoring Network (AQMN) for assessing population exposure to air pollution and predicting the magnitude of the health risks to the population. Methods: A multi-pollutant method (implemented as a MATLAB program) was explored for configur­ing an AQMN to detect the highest level of pollution around an oil refinery plant. The method ranks potential monitoring sites (grids) according to their ability to represent the ambient concentration. The term of cluster of contiguous grids that exceed a threshold value was used to calculate the Station Dosage. Selection of the best configuration of AQMN was done based on the ratio of a sta­tion’s dosage to the total dosage in the network. Results: Six monitoring stations were needed to detect the pollutants concentrations around the study area for estimating the level and distribution of exposure in the population with total network efficiency of about 99%. An analysis of the design procedure showed that wind regimes have greatest effect on the location of monitoring stations. Conclusion: The optimal AQMN enables authorities to implement an effective program of air quality management for protecting human health. PMID:26933646

Mapping real-time air pollution health risk for environmental management: Combining mobile and stationary air pollution monitoring with neural network models.

PubMed

Adams, Matthew D; Kanaroglou, Pavlos S

2016-03-01

Air pollution poses health concerns at the global scale. The challenge of managing air pollution is significant because of the many air pollutants, insufficient funds for monitoring and abatement programs, and political and social challenges in defining policy to limit emissions. Some governments provide citizens with air pollution health risk information to allow them to limit their exposure. However, many regions still have insufficient air pollution monitoring networks to provide real-time mapping. Where available, these risk mapping systems either provide absolute concentration data or the concentrations are used to derive an Air Quality Index, which provides the air pollution risk for a mix of air pollutants with a single value. When risk information is presented as a single value for an entire region it does not inform on the spatial variation within the region. Without an understanding of the local variation residents can only make a partially informed decision when choosing daily activities. The single value is typically provided because of a limited number of active monitoring units in the area. In our work, we overcome this issue by leveraging mobile air pollution monitoring techniques, meteorological information and land use information to map real-time air pollution health risks. We propose an approach that can provide improved health risk information to the public by applying neural network models within a framework that is inspired by land use regression. Mobile air pollution monitoring campaigns were conducted across Hamilton from 2005 to 2013. These mobile air pollution data were modelled with a number of predictor variables that included information on the surrounding land use characteristics, the meteorological conditions, air pollution concentrations from fixed location monitors, and traffic information during the time of collection. Fine particulate matter and nitrogen dioxide were both modelled. During the model fitting process we reserved twenty percent of the data to validate the predictions. The models' performances were measured with a coefficient of determination at 0.78 and 0.34 for PM2.5 and NO2, respectively. We apply a relative importance measure to identify the importance of each variable in the neural network to partially overcome the black box issues of neural network models. Copyright © 2015 Elsevier Ltd. All rights reserved.

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...

NETWORK DESIGN FOR OZONE MONITORING

EPA Science Inventory

The potential effects of air pollution on human health have received much attention in recent years. In the U.S. and other countries, there are extensive large-scale monitoring networks designed to collect data to inform the public of exposure risks from air pollution. A major cr...

RadNet Air Data From Honolulu, HI

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Honolulu, HI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Birmingham, AL

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Birmingham, AL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Dallas, TX

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Dallas, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Omaha, NE

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Omaha, NE from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Montgomery, AL

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Montgomery, AL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Burlington, VT

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Burlington, VT from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Washington, DC

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Washington, DC from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Rochester, NY

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Rochester, NY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Tampa, FL

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Tampa, FL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Cincinnati, OH

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Cincinnati, OH from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Fairbanks, AK

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Fairbanks, AL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Yuma, AZ

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Yuma, AZ from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Kalispell, MT

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Kalispell, MT from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Kearney, NE

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Kearney, NE from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Phoenix, AZ

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Phoenix, AZ from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Pierre, SD

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Pierre, SD from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Augusta, GA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Augusta, GA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Syracuse, NY

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Syracuse, NY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Albany, NY

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Albany, NY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Anchorage, AK

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Anchorage, AK from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Philadelphia, PA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Philadelphia, PA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Houston, TX

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Houston, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Duluth, MN

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Duluth, MN from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Raleigh, NC

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Raleigh, NC from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Louisville, KY

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Louisville, KY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Cleveland, OH

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Cleveland, OH from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Carlsbad, NM

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Carlsbad, NM from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Corvallis, OR

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Corvallis, OR from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Orono, ME

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Orono, ME from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Reno, NV

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Reno, NV from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Nashville, TN

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Nashville, TN from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Concord, NH

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Concord, NH from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Paducah, KY

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Paducah, KY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Edison, NJ

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Edison, NJ from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Wilmington, NC

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Wilmington, NC from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Boise, ID

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Boise, ID from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Albuquerque, NM

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Albuquerque, NM from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Fresno, CA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Fresno, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Amarillo, TX

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Amarillo, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Portland, OR

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Portland, OR from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Jacksonville, FL

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Jacksonville, FL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Dover, DE

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Dover, DE from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Baltimore, MD

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Baltimore, MD from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Miami, FL

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Miami, FL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Billings, MT

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Billings, MT from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Providence, RI

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Providence, RI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Knoxville, TN

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Knoxville, TN from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Columbus, OH

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Columbus, OH from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Bloomsburg, PA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Bloomsburg, PA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Shreveport, LA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Shreveport, LA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Laredo, TX

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Laredo, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Bakersfield, CA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Bakersfield, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Portland, ME

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Portland, ME from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Champaign, IL

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Champaign, IL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Tucson, AZ

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Tucson, AZ from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Juneau, AK

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Juneau, AK from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Toledo, OH

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Toledo, OH from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Boston, MA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Boston, MA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Indianapolis, IN

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Indianapolis, IN from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Yaphank, NY

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Yaphank, NY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Anaheim, CA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Anaheim, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Riverside, CA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Riverside, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Detroit, MI

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Detroit, MI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Wichita, KS

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Wichita, KS from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Columbia, SC

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Columbia, SC from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Milwaukee, WI

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Milwaukee, WI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Richmond, VA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Richmond, VA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Tulsa, OK

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Tulsa, OK from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Aurora, IL

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Aurora, IL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Hartford, CT

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Hartford. CT from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Charleston, WV

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Charleston, WV from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Shawano, WI

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Shawano, WI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Harlingen, TX

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Harlingen, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation

RadNet Air Data From Springfield, MO

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Springfield, MO from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Olympia, WA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Olympia, WA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Memphis, TN

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Memphis, TN from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Lubbock, TX

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Lubbock, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Sacramento, CA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Sacramento, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Lockport, NY

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Lockport, NY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Jackson, MS

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Jackson, MS from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Seattle, WA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Seattle, WA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Pittsburgh, PA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Pittsburgh, PA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Madison, WI

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Madison, WI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Ellensburg, WA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Ellensburg, WA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Harrisonburg, VA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Harrisonburg, VA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Bismarck, ND

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Bismarck, ND from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Denver, CO

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Denver, CO from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Charlotte, NC

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Charlotte, NC from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Lexington, KY

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Lexington, KY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Casper, WY

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Casper, WY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Eureka, CA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Eureka, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Lincoln, NE

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Lincoln, NE from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Orlando, FL

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Orlando, FL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Mobile, AL

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Mobile, AL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Spokane, WA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Spokane, WA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Atlanta, GA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Atlanta, GA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Greensboro, NC

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Greensboro, NC from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Chicago, IL

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Chicago, IL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Worcester, MA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Worcester, MA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Austin, TX

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Austin, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

Web Information Systems for Monitoring and Control of Indoor Air Quality at Subway Stations

NASA Astrophysics Data System (ADS)

Choi, Gi Heung; Choi, Gi Sang; Jang, Joo Hyoung

In crowded subway stations indoor air quality (IAQ) is a key factor for ensuring the safety, health and comfort of passengers. In this study, a framework for web-based information system in VDN environment for monitoring and control of IAQ in subway stations is suggested. Since physical variables that describing IAQ need to be closely monitored and controlled in multiple locations in subway stations, concept of distributed monitoring and control network using wireless media needs to be implemented. Connecting remote wireless sensor network and device (LonWorks) networks to the IP network based on the concept of VDN can provide a powerful, integrated, distributed monitoring and control performance, making a web-based information system possible.

Assessment of an air pollution monitoring network to generate urban air pollution maps using Shannon information index, fuzzy overlay, and Dempster-Shafer theory, A case study: Tehran, Iran

NASA Astrophysics Data System (ADS)

Pahlavani, Parham; Sheikhian, Hossein; Bigdeli, Behnaz

2017-10-01

Air pollution assessment is an imperative part of megacities planning and control. Hence, a new comprehensive approach for air pollution monitoring and assessment was introduced in this research. It comprises of three main sections: optimizing the existing air pollutant monitoring network, locating new stations to complete the coverage of the existing network, and finally, generating an air pollution map. In the first section, Shannon information index was used to find less informative stations to be candidate for removal. Then, a methodology was proposed to determine the areas which are not sufficiently covered by the current network. These areas are candidates for establishing new monitoring stations. The current air pollution monitoring network of Tehran was used as a case study, where the air pollution issue has been worsened due to the huge population, considerable commuters' absorption and topographic barriers. In this regard, O3, NO, NO2, NOx, CO, PM10, and PM2.5 were considered as the main pollutants of Tehran. Optimization step concluded that all the 16 active monitoring stations should be preserved. Analysis showed that about 35% of the Tehran's area is not properly covered by monitoring stations and about 30% of the area needs additional stations. The winter period in Tehran always faces the most severe air pollution in the year. Hence, to produce the air pollution map of Tehran, three-month of winter measurements of the mentioned pollutants, repeated for five years in the same period, were selected and extended to the entire area using the kriging method. Experts specified the contribution of each pollutant in overall air pollution. Experts' rankings aggregated by a fuzzy-overlay process. Resulted maps characterized the study area with crucial air pollution situation. According to the maps, more than 45% of the city area faced high pollution in the study period, while only less than 10% of the area showed low pollution. This situation confirms the need for effective plans to mitigate the severity of the problem. In addition, an effort made to investigate the rationality of the acquired air pollution map respect to the urban, cultural, and environmental characteristics of Tehran, which also confirmed the results.

RadNet Air Data From San Juan, PR

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for San Juan, PR from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Grand Rapids, MI

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Grand Rapids, MI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Corpus Christi, TX

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Corpus Christi, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Little Rock, AR

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Little Rock, AR from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Des Moines, IA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Des Moines, IA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Fort Madison, IA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Fort Madison, IA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Fort Wayne, IN

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Fort Wayne, IN from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Navajo Lake, NM

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Navajo Lake, NM from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Las Vegas, NV

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Las Vegas, NV from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From St. George, UT

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for St. George, UT from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Jefferson City, MO

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Jefferson City, MO from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Fort Worth, TX

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Fort Worth, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Kansas City, KS

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Kansas City, KS from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From San Angelo, TX

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for San Angelo, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From San Francisco, CA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for San Francisco, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Oklahoma City, OK

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Oklahoma City, OK from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From San Bernardino, CA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for San Bernardino, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Idaho Falls, ID

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Idaho Falls, ID from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Los Angeles, CA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Los Angeles, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From El Paso, TX

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for El Paso, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Grand Junction, CO

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Grand Junction, CO from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From St. Paul, MN

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for St. Paul, MN from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Virginia Beach, VA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Virginia Beach, VA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From La Crosse, WI

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for La Crosse, WI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From San Diego, CA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for San Diego, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From San Jose, CA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for San Jose, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From San Antonio, TX

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for San Antonio, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Rapid City, SD

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Rapid City, SD from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Dodge City, KS

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Dodge City, KS from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Colorado Springs, CO

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Colorado Springs, CO from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From St. Louis, MO

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for St. Louis, MO from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Bay City, MI

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Bay City, MI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Mason City, IA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Mason City, IA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

Air Quality System (AQS) Metadata

EPA Pesticide Factsheets

The U.S. Environmental Protection Agency compiles air quality monitoring data in the Air Quality System (AQS). Ambient air concentrations are measured at a national network of more than 4,000 monitoring stations and are reported by state, local, and tribal

RadNet Air Data From Fort Smith, AR

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Fort Smith, AR from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Salt Lake City, UT

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Salt Lake City, UT from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From New York City, NY

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for New York City, NY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

a Web Api and Web Application Development for Dissemination of Air Quality Information

NASA Astrophysics Data System (ADS)

Şahin, K.; Işıkdağ, U.

2017-11-01

Various studies have been carried out since 2005 under the leadership of Ministry of Environment and Urbanism of Turkey, in order to observe the quality of air in Turkey, to develop new policies and to develop a sustainable air quality management strategy. For this reason, a national air quality monitoring network has been developed providing air quality indices. By this network, the quality of the air has been continuously monitored and an important information system has been constructed in order to take precautions for preventing a dangerous situation. The biggest handicap in the network is the data access problem for instant and time series data acquisition and processing because of its proprietary structure. Currently, there is no service offered by the current air quality monitoring system for exchanging information with third party applications. Within the context of this work, a web service has been developed to enable location based querying of the current/past air quality data in Turkey. This web service is equipped with up-todate and widely preferred technologies. In other words, an architecture is chosen in which applications can easily integrate. In the second phase of the study, a web-based application was developed to test the developed web service and this testing application can perform location based acquisition of air-quality data. This makes it possible to easily carry out operations such as screening and examination of the area in the given time-frame which cannot be done with the national monitoring network.

Low-cost, high-density sensor network for urban emission monitoring: BEACO2N

NASA Astrophysics Data System (ADS)

Kim, J.; Shusterman, A.; Lieschke, K.; Newman, C.; Cohen, R. C.

2017-12-01

In urban environments, air quality is spatially and temporally heterogeneous as diverse emission sources create a high degree of variability even at the neighborhood scale. Conventional air quality monitoring relies on continuous measurements with limited spatial resolution or passive sampling with high-density and low temporal resolution. Either approach averages the air quality information over space or time and hinders our attempts to understand emissions, chemistry, and human exposure in the near-field of emission sources. To better capture the true spatio-temporal heterogeneity of urban conditions, we have deployed a low-cost, high-density air quality monitoring network in San Francisco Bay Area distributed at 2km horizontal spacing. The BErkeley Atmospheric CO2 Observation Network (BEACO2N) consists of approximately 50 sensor nodes, measuring CO2, CO, NO, NO2, O­3, and aerosol. Here we describe field-based calibration approaches that are consistent with the low-cost strategy of the monitoring network. Observations that allow inference of emission factors and identification of specific local emission sources will also be presented.

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.

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.

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

Monitoring air quality in mountains: Designing an effective network

USGS Publications Warehouse

Peterson, D.L.

2000-01-01

A quantitatively robust yet parsimonious air-quality monitoring network in mountainous regions requires special attention to relevant spatial and temporal scales of measurement and inference. The design of monitoring networks should focus on the objectives required by public agencies, namely: 1) determine if some threshold has been exceeded (e.g., for regulatory purposes), and 2) identify spatial patterns and temporal trends (e.g., to protect natural resources). A short-term, multi-scale assessment to quantify spatial variability in air quality is a valuable asset in designing a network, in conjunction with an evaluation of existing data and simulation-model output. A recent assessment in Washington state (USA) quantified spatial variability in tropospheric ozone distribution ranging from a single watershed to the western third of the state. Spatial and temporal coherence in ozone exposure modified by predictable elevational relationships ( 1.3 ppbv ozone per 100 m elevation gain) extends from urban areas to the crest of the Cascade Range. This suggests that a sparse network of permanent analyzers is sufficient at all spatial scales, with the option of periodic intensive measurements to validate network design. It is imperative that agencies cooperate in the design of monitoring networks in mountainous regions to optimize data collection and financial efficiencies.

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.

Determination of beryllium concentrations in UK ambient air

NASA Astrophysics Data System (ADS)

Goddard, Sharon L.; Brown, Richard J. C.; Ghatora, Baljit K.

2016-12-01

Air quality monitoring of ambient air is essential to minimise the exposure of the general population to toxic substances such as heavy metals, and thus the health risks associated with them. In the UK, ambient air is already monitored under the UK Heavy Metals Monitoring Network for a number of heavy metals, including nickel (Ni), arsenic (As), cadmium (Cd) and lead (Pb) to ensure compliance with legislative limits. However, the UK Expert Panel on Air Quality Standards (EPAQS) has highlighted a need to limit concentrations of beryllium (Be) in air, which is not currently monitored, because of its toxicity. The aim of this work was to analyse airborne particulate matter (PM) sampled onto filter papers from the UK Heavy Metals Monitoring Network for quantitative, trace level beryllium determination and compare the results to the guideline concentration specified by EPAQS. Samples were prepared by microwave acid digestion in a matrix of 2% sulphuric acid and 14% nitric acid, verified by the use of Certified Reference Materials (CRMs). The digested samples were then analysed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The filters from the UK Heavy Metals Monitoring Network were tested using this procedure and the average beryllium concentration across the network for the duration of the study period was 7.87 pg m-3. The highest site average concentration was 32.0 pg m-3 at Scunthorpe Low Santon, which is significantly lower than levels that are thought to cause harm. However the highest levels were observed at sites monitoring industrial point sources, indicating that beryllium is being used and emitted, albeit at very low levels, from these point sources. Comparison with other metals concentrations and data from the UK National Atmospheric Emissions Inventory suggests that current emissions of beryllium may be significantly overestimated.

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...

40 CFR 52.74 - Original identification of plan section.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Governor of Alaska on January 18, 1980 as follows: Volume II. Analysis of Problems, Control Actions Section... requirements of Air Quality Monitoring, 40 CFR part 58, subpart C, § 58.20, as follows: Volume II. Analysis of Problems, Control Actions Section V. Ambient Air Monitoring A. Purpose C. Air Monitoring Network E. Annual...

40 CFR 52.70 - Identification of plan.

Code of Federal Regulations, 2013 CFR

2013-07-01

... submitted by the Governor of Alaska on January 18, 1980 as follows: Volume II. Analysis of Problems, Control... requirements of Air Quality Monitoring, 40 CFR part 58, subpart C, § 58.20, as follows: Volume II. Analysis of Problems, Control Actions Section V. Ambient Air Monitoring A. Purpose C. Air Monitoring Network E. Annual...

An Intercomparison of the Deposition Models Used in the CASTNET and CAPMoN Networks

EPA Science Inventory

To assess long-term trends in atmospheric deposition, the U.S. operates the Clean Air Status and Trends Network (CASTNET) and Canada operates the Canadian Air and Precipitation Monitoring Network (CAPMoN). Both networks use modeled dry deposition velocities and measured atmospher...

Amperometric Gas Sensors as a Low Cost Emerging Technology Platform for Air Quality Monitoring Applications: A Review.

PubMed

Baron, Ronan; Saffell, John

2017-11-22

This review examines the use of amperometric electrochemical gas sensors for monitoring inorganic gases that affect urban air quality. First, we consider amperometric gas sensor technology including its development toward specifically designed air quality sensors. We then review recent academic and research organizations' studies where this technology has been trialed for air quality monitoring applications: early studies showed the potential of electrochemical gas sensors when colocated with reference Air Quality Monitoring (AQM) stations. Spatially dense networks with fast temporal resolution provide information not available from sparse AQMs with longer recording intervals. We review how this technology is being offered as commercial urban air quality networks and consider the remaining challenges. Sensors must be sensitive, selective, and stable; air quality monitors/nodes must be electronically and mechanically well designed. Data correction is required and models with differing levels of sophistication are being designed. Data analysis and validation is possibly the biggest remaining hurdle needed to deliver reliable concentration readings. Finally, this review also considers the roles of companies, urban infrastructure requirements, and public research in the development of this technology.

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.

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

40 CFR 58.14 - System modification.

Code of Federal Regulations, 2010 CFR

2010-07-01

...) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.14 System modification. (a) The State, or where... monitoring network that complies with the findings of the network assessments required every 5 years by § 58... schedule with respect to the SLAMS network are subject to the approval of the EPA Regional Administrator...

40 CFR 58.14 - System modification.

Code of Federal Regulations, 2011 CFR

2011-07-01

...) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.14 System modification. (a) The State, or where... monitoring network that complies with the findings of the network assessments required every 5 years by § 58... schedule with respect to the SLAMS network are subject to the approval of the EPA Regional Administrator...

Large-scale monitoring of air pollution in remote and ecologically important areas

Treesearch

Andrzej Bytnerowicz; Witold Fraczek

2013-01-01

New advances in air quality monitoring techniques, such as passive samplers for nitrogenous (N) or sulphurous (S) pollutants and ozone (O3), have allowed for an improved understanding of concentrations of these pollutants in remote areas. Mountains create special problems with regard to the feasibility of establishing and maintaining air pollution monitoring networks,...

Evaluation of Data Replacement Strategies for CASTNET Dry Deposition Modeling

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) established the Clean Air Status and Trends Network (CASTNET) and its predecessor, the National Dry Deposition Network (NDDN), as national air quality and meteorological monitoring networks. The purpose of CASTNET is to track the pr...

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...

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.

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).

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.

The National Ambient Air Monitoring Stategy: Rethinking the Role of National Networks

EPA Science Inventory

A current re-engineering of the United States routine ambient monitoring networks intended to improve the balance in addressing both regulatory and scientific objectives is addressed in this paper. Key attributes of these network modifications include the addition of collocated ...

National Dioxin Air Monitoring Network (Ndamn) Report of the Results of Atmospheric Measurements of Pcdds, Pcdfs, and Dioxin-Like PCBs in Rural and Remote Areas of the U.S. from June 1998 Through November 2004

EPA Science Inventory

In 1998, the U.S. Environmental Protection Agency (U.S. EPA) established the National Dioxin Air Monitoring Network (NDAMN) to help characterize the ubiquitous presence of dioxins in the environment. This final report represents the 2013 update to NDAMN.

Journal Article: the National Dioxin Air Monitoring Network (Ndamn): Measurements of CDDs, CDFs and Coplanar PCBs at 15 Rural and 6 National Park Areas of the U.S.: June 1998-December 1999.

EPA Science Inventory

The U.S. EPA has established a National Dioxin Air Monitoring Network (NDAMN) to determine the temporal and geographical variability of atmospheric CDDs, CDFs and coplanar PCBs at rural and nonimpacted locations throughout the United States. Currently operating at 32 sampling st...

Journal Article: Average Method Blank Quantities of Dioxin-Like Congeners and Their Relationship to the Detection Limits of the U.S. EPA's National Dioxin Air Monitoring Network (Ndamn)

EPA Science Inventory

The U.S. EPA established a National Dioxin Air Monitoring Network (NDAMN) to determine the temporal and geographical variability of atmospheric CDDs, CDFs and coplanar PCBs throughout the United States. Currently operating at 33 stations, NDAMN has, as one of its tasks, the dete...

Air quality in California forests: current efforts to initiate biomonitoring with lichens.

Treesearch

Sarah Jovan

2002-01-01

The primary objective of the Forest Health Monitoring indicator project is to develop models that use the composition of epiphytic lichen communities to detect and monitor air quality in forests. The designs of existing air quality monitoring networks in California do not provide adequate representation of rural areas to assess impacts to forests. This article is...

Classifying Sources Influencing Indoor Air Quality (IAQ) Using Artificial Neural Network (ANN)

PubMed Central

Mad Saad, Shaharil; Melvin Andrew, Allan; Md Shakaff, Ali Yeon; Mohd Saad, Abdul Rahman; Muhamad Yusof @ Kamarudin, Azman; Zakaria, Ammar

2015-01-01

Monitoring indoor air quality (IAQ) is deemed important nowadays. A sophisticated IAQ monitoring system which could classify the source influencing the IAQ is definitely going to be very helpful to the users. Therefore, in this paper, an IAQ monitoring system has been proposed with a newly added feature which enables the system to identify the sources influencing the level of IAQ. In order to achieve this, the data collected has been trained with artificial neural network or ANN—a proven method for pattern recognition. Basically, the proposed system consists of sensor module cloud (SMC), base station and service-oriented client. The SMC contain collections of sensor modules that measure the air quality data and transmit the captured data to base station through wireless network. The IAQ monitoring system is also equipped with IAQ Index and thermal comfort index which could tell the users about the room’s conditions. The results showed that the system is able to measure the level of air quality and successfully classify the sources influencing IAQ in various environments like ambient air, chemical presence, fragrance presence, foods and beverages and human activity. PMID:26007724

Air quality measurements and monitoring network in the Republic of Latvia

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

Grinman, A.; Lyulko, J.; Dubrovskaja, R.

1996-12-31

The territory of Latvia is covered with a wide environmental monitoring network, that falls under 2 main categories: (1) regional network featuring the region and involved in international monitoring programs, including EMEP, GAW, IM; (2) state network providing for local pollution monitoring of the atmosphere (19 posts), precipitation (5 station) and radioactivity (46 station). In 1994, measurements were made at 20 stationary posts located in Daugavpils (2), Jekabpils (2), Jurmala, (2), Liepaja (2), Nigrande (1), Olaine (1), Rezekne (1), Riga (5), Valn-dera (2), Ventspils (2). This atmospheric air observation network covers mostly towns densely populated with industrial objects and othermore » pollutant emitting sources. Thus, the observation programs encompass measurements of pollutants that have higher concentrations in the ambient air. Results indicate that the annual pollution dynamics are closely connected with concentration fluctuations in the seasons. The sulfur dioxide and nitrogen dioxide concentrations increased during the heating season in Jekabpils, Jurmala and Valmiera, i.e., in the town that have many small heating installations. The data obtained allow to trace a dependence of measurement values upon the location of the observational posts vis-a-vis the pollutant emitting sources.« less

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.

40 CFR 52.70 - Identification of plan.

Code of Federal Regulations, 2011 CFR

2011-07-01

... nonattainment areas submitted by the Governor of Alaska on January 18, 1980 as follows: Volume II. Analysis of...: Volume II. Analysis of Problems, Control Actions Section V. Ambient Air Monitoring A. Purpose C. Air Monitoring Network E. Annual Review (9) Provisions of a State Air Quality Control Plan submitted by the...

40 CFR 52.70 - Identification of plan.

Code of Federal Regulations, 2012 CFR

2012-07-01

... nonattainment areas submitted by the Governor of Alaska on January 18, 1980 as follows: Volume II. Analysis of...: Volume II. Analysis of Problems, Control Actions Section V. Ambient Air Monitoring A. Purpose C. Air Monitoring Network E. Annual Review (9) Provisions of a State Air Quality Control Plan submitted by the...

AMBIENT AIR MONITORING AT GROUND ZERO AND LOWER MANHATTAN FOLLOWING THE COLLAPSE OF THE WORLD TRADE CENTER

EPA Science Inventory

The U.S. EPA National Exposure Research Laboratory (NERL) collaborated with EPA's Regional offices to establish a monitoring network to characterize ambient air concentrations of particulate matter (PM) and air toxics in lower Manhattan following the collapse of the World Trade...

Journal Article: the National Dioxin Air Monitoring Network (Ndamn): Measurements of CDDs, CDFs, and Coplanar PCBs at 18 Rural, 8 National Parks, and 2 Suburban Areas of the U.S.: Results for the Year 2000.

EPA Science Inventory

In June, 1998, the U.S. EPA established the National Dioxin Air Monitoring Network (NDAMN). The primary goal of NDAMN is determine the temporal and geographical variability of atmospheric CDDs, CDFs, and coplanar PCBs at rural and nonimpacted locations throughout the United Stat...

Characterizing Intra-Urban Air Quality Gradients with a Spatially-Distributed Network

NASA Astrophysics Data System (ADS)

Zimmerman, N.; Ellis, A.; Schurman, M. I.; Gu, P.; Li, H.; Snell, L.; Gu, J.; Subramanian, R.; Robinson, A. L.; Apte, J.; Presto, A. A.

2016-12-01

City-wide air pollution measurements have typically relied on regulatory or research monitoring sites with low spatial density to assess population-scale exposure. However, air pollutant concentrations exhibit significant spatial variability depending on local sources and features of the built environment, which may not be well captured by the existing monitoring regime. To better understand urban spatial and temporal pollution gradients at 1 km resolution, a network of 12 real-time air quality monitoring stations was deployed beginning July 2016 in Pittsburgh, PA. The stations were deployed at sites along an urban-rural transect and in urban locations with a range of traffic, restaurant, and tall building densities to examine the impact of various modifiable factors. Measurements from the stationary monitoring stations were further supported by mobile monitoring, which provided higher spatial resolution pollutant measurements on nearby roadways and enabled routine calibration checks. The stationary monitoring measurements comprise ultrafine particle number (Aerosol Dynamics "MAGIC" CPC), PM2.5 (Met One Neighborhood PM Monitor), black carbon (Met One BC 1050), and a new low-cost air quality monitor, the Real-time Affordable Multi-Pollutant (RAMP) sensor package for measuring CO, NO2, SO2, O3, CO2, temperature and relative humidity. High time-resolution (sub-minute) measurements across the distributed monitoring network enable insight into dynamic pollutant behaviour. Our preliminary findings show that our instruments are sensitive to PM2.5 gradients exceeding 2 micro-grams per cubic meter and ultrafine particle gradients exceeding 1000 particles per cubic centimeter. Additionally, we have developed rigorous calibration protocols to characterize the RAMP sensor response and drift, as well as multiple linear regression models to convert sensor response into pollutant concentrations that are comparable to reference instrumentation.

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.

Enhancing wind erosion monitoring and assessment for U.S. rangelands

USGS Publications Warehouse

Webb, Nicholas P.; Van Zee, Justin W.; Karl, Jason W.; Herrick, Jeffrey E.; Courtright, Ericha M.; Billings, Benjamin J.; Boyd, Robert C.; Chappell, Adrian; Duniway, Michael C.; Derner, Justin D.; Hand, Jenny L.; Kachergis, Emily; McCord, Sarah E.; Newingham, Beth A.; Pierson, Frederick B.; Steiner, Jean L.; Tatarko, John; Tedela, Negussie H.; Toledo, David; Van Pelt, R. Scott

2017-01-01

On the GroundWind erosion is a major resource concern for rangeland managers because it can impact soil health, ecosystem structure and function, hydrologic processes, agricultural production, and air quality.Despite its significance, little is known about which landscapes are eroding, by how much, and when.The National Wind Erosion Research Network was established in 2014 to develop tools for monitoring and assessing wind erosion and dust emissions across the United States.The Network, currently consisting of 13 sites, creates opportunities to enhance existing rangeland soil, vegetation, and air quality monitoring programs.Decision-support tools developed by the Network will improve the prediction and management of wind erosion across rangeland ecosystems.

The Longitudinal Effect of Self-Monitoring and Locus of Control on Social Network Position in Friendship Networks

DTIC Science & Technology

2006-03-01

equally essential to examine the antecedents that bring a person to a particular network location. The previous body of knowledge in social networks...Locus of Control on Social Network Position in Friendship Networks THESIS Gary J. Moore, Captain, USAF AFIT/GEM/ENV/06M-11 DEPARTMENT OF THE AIR...THE LONGITUDINAL EFFECTS OF SELF-MONITORING AND LOCUS OF CONTROL ON SOCIAL NETWORK POSITION IN FRIENDSHIP NETWORKS THESIS Presented to the

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.

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?

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.

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)

Forecasting PM10 in metropolitan areas: Efficacy of neural networks.

PubMed

Fernando, H J S; Mammarella, M C; Grandoni, G; Fedele, P; Di Marco, R; Dimitrova, R; Hyde, P

2012-04-01

Deterministic photochemical air quality models are commonly used for regulatory management and planning of urban airsheds. These models are complex, computer intensive, and hence are prohibitively expensive for routine air quality predictions. Stochastic methods are becoming increasingly popular as an alternative, which relegate decision making to artificial intelligence based on Neural Networks that are made of artificial neurons or 'nodes' capable of 'learning through training' via historic data. A Neural Network was used to predict particulate matter concentration at a regulatory monitoring site in Phoenix, Arizona; its development, efficacy as a predictive tool and performance vis-à-vis a commonly used regulatory photochemical model are described in this paper. It is concluded that Neural Networks are much easier, quicker and economical to implement without compromising the accuracy of predictions. Neural Networks can be used to develop rapid air quality warning systems based on a network of automated monitoring stations. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

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)

OXIDIZED NITROGEN DEPOSITION IN THE EASTERN UNITED STATES

EPA Science Inventory

Air quality and selected meteorological parameters have been monitored at rural sites in the United States (US) by EPA's Clean Air Status and Trends Network, (CASTNet) sites. The National Atmospheric Deposition Program (NADP) monitors wet deposition of numerous ions in precip...

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.

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.

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.

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 ...

Journal Article: Quality Assurance Considerations for An Ambient Dioxin Monitoring Network

EPA Science Inventory

The U.S. Environmental Protection Agency initiated the National Dioxin Air Monitoring Network (NDAMN) in 1998. NDAMN has three primary purposes:
1. To provide measurements of background atmospheric levels of dioxin-like compounds in different geographic regions of the Unite...

WSN based indoor air quality monitoring in classrooms

NASA Astrophysics Data System (ADS)

Wang, S. K.; Chew, S. P.; Jusoh, M. T.; Khairunissa, A.; Leong, K. Y.; Azid, A. A.

2017-03-01

Indoor air quality monitoring is essential as the human health is directly affected by indoor air quality. This paper presents the investigations of the impact of undergraduate students' concentration during lecture due to the indoor air quality in classroom. Three environmental parameters such as temperature, relative humidity and concentration of carbon dioxide are measured using wireless sensor network based air quality monitoring system. This simple yet reliable system is incorporated with DHT-11 and MG-811 sensors. Two classrooms were selected to install the monitoring system. The level of indoor air quality were measured and students' concentration was assessed using intelligent test during normal lecturing section. The test showed significant correlation between the collected environmental parameters and the students' level of performances in their study.

An assessment of the performance of Monitor for AeRosols and GAses in ambient air (MARGA): a semi-continuous method for soluble compounds

EPA Science Inventory

Ambient air monitoring as part of the U.S. Environmental Protection Agency’s (U.S. EPA’s) Clean Air Status and Trends Network (CASTNet) currently uses filter packs to measure weekly integrated concentrations. The U.S. EPA is interested in supplementing CASTNet with semi-continuou...

Enhanced data validation strategy of air quality monitoring network.

PubMed

Harkat, Mohamed-Faouzi; Mansouri, Majdi; Nounou, Mohamed; Nounou, Hazem

2018-01-01

Quick validation and detection of faults in measured air quality data is a crucial step towards achieving the objectives of air quality networks. Therefore, the objectives of this paper are threefold: (i) to develop a modeling technique that can be used to predict the normal behavior of air quality variables and help provide accurate reference for monitoring purposes; (ii) to develop fault detection method that can effectively and quickly detect any anomalies in measured air quality data. For this purpose, a new fault detection method that is based on the combination of generalized likelihood ratio test (GLRT) and exponentially weighted moving average (EWMA) will be developed. GLRT is a well-known statistical fault detection method that relies on maximizing the detection probability for a given false alarm rate. In this paper, we propose to develop GLRT-based EWMA fault detection method that will be able to detect the changes in the values of certain air quality variables; (iii) to develop fault isolation and identification method that allows defining the fault source(s) in order to properly apply appropriate corrective actions. In this paper, reconstruction approach that is based on Midpoint-Radii Principal Component Analysis (MRPCA) model will be developed to handle the types of data and models associated with air quality monitoring networks. All air quality modeling, fault detection, fault isolation and reconstruction methods developed in this paper will be validated using real air quality data (such as particulate matter, ozone, nitrogen and carbon oxides measurement). Copyright © 2017 Elsevier Inc. All rights reserved.

The deployment of carbon monoxide wireless sensor network (CO-WSN) for ambient air monitoring.

PubMed

Chaiwatpongsakorn, Chaichana; Lu, Mingming; Keener, Tim C; Khang, Soon-Jai

2014-06-16

Wireless sensor networks are becoming increasingly important as an alternative solution for environment monitoring because they can reduce cost and complexity. Also, they can improve reliability and data availability in places where traditional monitoring methods are difficult to site. In this study, a carbon monoxide wireless sensor network (CO-WSN) was developed to measure carbon monoxide concentrations at a major traffic intersection near the University of Cincinnati main campus. The system has been deployed over two weeks during Fall 2010, and Summer 2011-2012, traffic data was also recorded by using a manual traffic counter and a video camcorder to characterize vehicles at the intersection 24 h, particularly, during the morning and evening peak hour periods. According to the field test results, the 1 hr-average CO concentrations were found to range from 0.1-1.0 ppm which is lower than the National Ambient Air Quality Standards (NAAQS) 35 ppm on a one-hour averaging period. During rush hour periods, the traffic volume at the intersection varied from 2,067 to 3,076 vehicles per hour with 97% being passenger vehicles. Furthermore, the traffic volume based on a 1-h average showed good correlation (R2 = 0.87) with the 1-h average CO-WSN concentrations for morning and evening peak time periods whereas CO-WSN results provided a moderate correlation (R2 = 0.42) with 24 hours traffic volume due to fluctuated changes of meteorological conditions. It is concluded that the performance and the reliability of wireless ambient air monitoring networks can be used as an alternative method for real time air monitoring.

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...

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

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.

High-Density, High-Resolution, Low-Cost Air Quality Sensor Networks for Urban Air Monitoring

NASA Astrophysics Data System (ADS)

Mead, M. I.; Popoola, O. A.; Stewart, G.; Bright, V.; Kaye, P.; Saffell, J.

2012-12-01

Monitoring air quality in highly granular environments such as urban areas which are spatially heterogeneous with variable emission sources, measurements need to be made at appropriate spatial and temporal scales. Current routine air quality monitoring networks generally are either composed of sparse expensive installations (incorporating e.g. chemiluminescence instruments) or higher density low time resolution systems (e.g. NO2 diffusion tubes). Either approach may not accurately capture important effects such as pollutant "hot spots" or adequately capture spatial (or temporal) variability. As a result, analysis based on data from traditional low spatial resolution networks, such as personal exposure, may be inaccurate. In this paper we present details of a sophisticated, low-cost, multi species (gas phase, speciated PM, meteorology) air quality measurement network methodology incorporating GPS and GPRS which has been developed for high resolution air quality measurements in urban areas. Sensor networks developed in the Centre for Atmospheric Science (University of Cambridge) incorporated electrochemical gas sensors configured for use in urban air quality studies operating at parts-per-billion (ppb) levels. It has been demonstrated that these sensors can be used to measure key air quality gases such as CO, NO and NO2 at the low ppb mixing ratios present in the urban environment (estimated detection limits <4ppb for CO and NO and <1ppb for NO2. Mead et al (submitted Aug., 2012)). Based on this work, a state of the art multi species instrument package for deployment in scalable sensor networks has been developed which has general applicability. This is currently being employed as part of a major 3 year UK program at London Heathrow airport (the Sensor Networks for Air Quality (SNAQ) Heathrow project). The main project outcome is the creation of a calibrated, high spatial and temporal resolution data set for O3, NO, NO2, SO2, CO, CO2, VOCstotal, size-speciated PM, temperature, relative humidity, wind speed and direction. The network incorporates existing GPRS infrastructures for real time sending of data with low overheads in terms of cost, effort and installation. In this paper we present data from the SNAQ Heathrow project as well as previous deployments showing measurement capability at the ppb level for NO, NO2 and CO. We show that variability can be observed and measured quantitatively using these sensor networks over widely differing time scales from individual emission events, diurnal variability associated with traffic and meteorological conditions, through to longer term synoptic weather conditions and seasonal behaviour. This work demonstrates a widely applicable generic capability to urban areas, airports as well as other complex emissions environments making this sensor system methodology valuable for scientific, policy and regulatory issues. We conclude that the low-cost high-density network philosophy has the potential to provide a more complete assessment of the high-granularity air quality structure generally observed in the environment. Further, when appropriately deployed, has the potential to offer a new paradigm in air quality quantification and monitoring.

The use of hierarchical clustering for the design of optimized monitoring networks

NASA Astrophysics Data System (ADS)

Soares, Joana; Makar, Paul Andrew; Aklilu, Yayne; Akingunola, Ayodeji

2018-05-01

Associativity analysis is a powerful tool to deal with large-scale datasets by clustering the data on the basis of (dis)similarity and can be used to assess the efficacy and design of air quality monitoring networks. We describe here our use of Kolmogorov-Zurbenko filtering and hierarchical clustering of NO2 and SO2 passive and continuous monitoring data to analyse and optimize air quality networks for these species in the province of Alberta, Canada. The methodology applied in this study assesses dissimilarity between monitoring station time series based on two metrics: 1 - R, R being the Pearson correlation coefficient, and the Euclidean distance; we find that both should be used in evaluating monitoring site similarity. We have combined the analytic power of hierarchical clustering with the spatial information provided by deterministic air quality model results, using the gridded time series of model output as potential station locations, as a proxy for assessing monitoring network design and for network optimization. We demonstrate that clustering results depend on the air contaminant analysed, reflecting the difference in the respective emission sources of SO2 and NO2 in the region under study. Our work shows that much of the signal identifying the sources of NO2 and SO2 emissions resides in shorter timescales (hourly to daily) due to short-term variation of concentrations and that longer-term averages in data collection may lose the information needed to identify local sources. However, the methodology identifies stations mainly influenced by seasonality, if larger timescales (weekly to monthly) are considered. We have performed the first dissimilarity analysis based on gridded air quality model output and have shown that the methodology is capable of generating maps of subregions within which a single station will represent the entire subregion, to a given level of dissimilarity. We have also shown that our approach is capable of identifying different sampling methodologies as well as outliers (stations' time series which are markedly different from all others in a given dataset).

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

Code of Federal Regulations, 2010 CFR

2010-07-01

... residential district. In this case, one location is representative of a neighborhood of small scale sites and... least one of the required FRM/FEM/ARM monitors is itself a continuous FEM or ARM monitor in which case... studies. 4.7.5Special Network Considerations Required When Using PM2.5 Spatial Averaging Approaches. (a...

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

Code of Federal Regulations, 2012 CFR

2012-07-01

... residential district. In this case, one location is representative of a neighborhood of small scale sites and... least one of the required FRM/FEM/ARM monitors is itself a continuous FEM or ARM monitor in which case... studies. 4.7.5Special Network Considerations Required When Using PM2.5 Spatial Averaging Approaches. (a...

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

Code of Federal Regulations, 2011 CFR

2011-07-01

... residential district. In this case, one location is representative of a neighborhood of small scale sites and... least one of the required FRM/FEM/ARM monitors is itself a continuous FEM or ARM monitor in which case... studies. 4.7.5Special Network Considerations Required When Using PM2.5 Spatial Averaging Approaches. (a...

ENVIRONMENTAL MONITORING AT GROUND ZERO AND LOWER MANHATTAN FOLLOWING THE COLLAPSE OF THE WTC

EPA Science Inventory

The U.S. EPA National Exposure Research Laboratory (NERL), in conjunction with our Regional offices, established a network of air monitoring sites to characterize ambient air concentrations of gases and particles in lower Manhattan following the collapse of the World Trade Cent...

PM2.5 Monitors in New England | Air Quality Planning Unit ...

EPA Pesticide Factsheets

2017-04-10

The New England states are currently operating a network of 58 ambient PM2.5 air quality monitors that meet EPA's Federal Reference Method (FRM) for PM2.5, which is necessary in order for the resultant data to be used for attainment/non-attainment purposes. These monitors collect particles in the ambient air smaller than 2.5 microns in size on a filter, which is weighed prior and post sampling to produce a 24-hour sample concentration.

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 ...

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

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;

MEASUREMENT OF RURAL SULFUR DIOXIDE AND PARTICLE SULFATE: ANALYSIS OF CASTNET DATA, 1987 - 1996

EPA Science Inventory

The Clean Sir Status and Trends Network (CASTNet) was implemented by the U.S. Environmental Protection Agency (EPA) in 1991 in response to Title IX of the Clean Air Amendments of 1990, which mandated the deployment of a national ambient air monitoring network to track progress of...

RadNet Air Quality (Fixed Station) Data

EPA Pesticide Factsheets

RadNet is a national network of monitoring stations that regularly collect air for analysis of radioactivity. The RadNet network, which has stations in each State, has been used to track environmental releases of radioactivity from nuclear weapons tests and nuclear accidents. RadNet also documents the status and trends of environmental radioactivity

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.

Journal Article: the National Dioxin Air Monitoring Network ...

EPA Pesticide Factsheets

The U.S. EPA has established a National Dioxin Air Monitoring Network (NDAMN) to determine the temporal and geographical variability of atmospheric CDDs, CDFs and coplanar PCBs at rural and nonimpacted locations throughout the United States. Currently operating at 32 sampling stations, NDAMN has three primary purposes: (1) to determine the atmospheric levels and occurrences of dioxin-like compounds in rural and agricultural areas where livestock, poultry and animal feed crops are grown; (2) to provide measurements of atmospheric levels of dioxin-like compounds in different geographic regions of the U.S.; and (3) to provide information regarding the long-range transport of dioxin-like compounds in air over the U.S. Designed in 1997, NDAMN has been implemented in phases, with the first phase consisting of 9 monitoring stations. Previously EPA has reported on the preliminary results of monitoring at 9 rural locations from June1998 through June 19991. The one-year measurement at the 9 stations indicated an annual mean TEQDF–WHO98 air concentration of 12 fg m-3. Since this reporting, NDAMN has been extended to include additional stations. The following is intended to be an update to this national monitoring effort. We are reporting the air monitoring results of 22 NDAMN stations operational over 9 sampling moments from June 1998 to December 1999. Fifteen stations are in rural areas, and 6 are located in National Parks. One station is located in suburban Wa

Real-Time ambient carbon monoxide and ultrafine particle concentration mapping in a near-road environment

EPA Science Inventory

Ambient air quality has traditionally been monitored using a network of fixed point sampling sites that are strategically placed to represent regional (e.g., county or town) rather than local (e.g., neighborhood) air quality trends. This type of monitoring data has been used to m...

Spatial Analysis and Land Use Regression of VOCs and NO2 in Dallas, Texas during Two Seasons

EPA Science Inventory

Passive air sampling for nitrogen dioxide (NO₂) and select volatile organic compounds (VOCs) was conducted at 24 fire stations and a compliance monitoring site in Dallas, Texas, USA during summer 2006 and winter 2008. This ambient air monitoring network was established...

SPATIAL ANALYSIS OF VOLATILE ORGANIC COMPOUNDS FROM A COMMUNITY-BASED AIR TOXICS MONITORING NETWORK IN DEER PARK, TEXAS, USA

EPA Science Inventory

This RARE Project with EPA Region 6 was a spatial analysis study of select volatile organic compounds (VOC) collected using passive air monitors at outdoor residential locations in the Deer Park, Texas area near the Houston Ship Channel. Correlation analysis of VOC species confi...

40 CFR 58.11 - Network technical requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Network technical requirements. 58.11... (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.11 Network technical requirements. (a)(1... A to this part when operating the SLAMS networks. (2) Beginning January 1, 2009, State and local...

40 CFR 58.11 - Network technical requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 5 2011-07-01 2011-07-01 false Network technical requirements. 58.11... (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.11 Network technical requirements. (a)(1... A to this part when operating the SLAMS networks. (2) Beginning January 1, 2009, State and local...

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...

The Deployment of Carbon Monoxide Wireless Sensor Network (CO-WSN) for Ambient Air Monitoring

PubMed Central

Chaiwatpongsakorn, Chaichana; Lu, Mingming; Keener, Tim C.; Khang, Soon-Jai

2014-01-01

Wireless sensor networks are becoming increasingly important as an alternative solution for environment monitoring because they can reduce cost and complexity. Also, they can improve reliability and data availability in places where traditional monitoring methods are difficult to site. In this study, a carbon monoxide wireless sensor network (CO-WSN) was developed to measure carbon monoxide concentrations at a major traffic intersection near the University of Cincinnati main campus. The system has been deployed over two weeks during Fall 2010, and Summer 2011–2012, traffic data was also recorded by using a manual traffic counter and a video camcorder to characterize vehicles at the intersection 24 h, particularly, during the morning and evening peak hour periods. According to the field test results, the 1 hr-average CO concentrations were found to range from 0.1–1.0 ppm which is lower than the National Ambient Air Quality Standards (NAAQS) 35 ppm on a one-hour averaging period. During rush hour periods, the traffic volume at the intersection varied from 2,067 to 3,076 vehicles per hour with 97% being passenger vehicles. Furthermore, the traffic volume based on a 1-h average showed good correlation (R2 = 0.87) with the 1-h average CO-WSN concentrations for morning and evening peak time periods whereas CO-WSN results provided a moderate correlation (R2 = 0.42) with 24 hours traffic volume due to fluctuated changes of meteorological conditions. It is concluded that the performance and the reliability of wireless ambient air monitoring networks can be used as an alternative method for real time air monitoring. PMID:24937527

RadNet Map Interface for Near-Real-Time Radiation Monitoring Data

EPA Pesticide Factsheets

RadNet is a national network of monitoring stations that regularly collect air, precipitation, drinking water, and milk samples for analysis of radioactivity. The RadNet network, which has stations in each state, has been used to track environmental releases of radioactivity from nuclear weapons tests and nuclear accidents.

78 FR 54173 - Approval and Promulgation of Air Quality Implementation Plans; Indiana; Maintenance Plan Update...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-03

... direct final rule in the Federal Register informing the public that the rule will not take effect... maintenance period, a commitment to maintain the existing monitoring network, factors and procedures to be... Network Indiana currently operates two SO 2 monitors in Lake County, Indiana. Indiana has committed to...

Environment quality monitoring using ARM processor

NASA Astrophysics Data System (ADS)

Vinaya, C. H.; Krishna Thanikanti, Vamsi; Ramasamy, Sudha

2017-11-01

This paper of air quality monitoring system describes a model of sensors network to continuously monitoring the environment with low cost developed model. At present time all over the world turned into a great revolution in industrial domain and on the other hand environment get polluting in a dangerous value. There are so many technologies present to reduce the polluting contents but still there is no completely reduction of that pollution. Even there are different methods to monitor the pollution content; these are much costly that not everyone can adapt those methods or devices. Now we are proposing a sensors connected network to monitor the environment continuously and displaying the pollutant gases percentage in air surroundings and can transmit the results to our mobiles by message. The advantage of this system is easy to design, establish at area to monitor, maintenance and most cost effective as well.

Quantitative evaluation of an air-monitoring network using atmospheric transport modeling and frequency of detection methods

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

Rood, Arthur S.; Sondrup, A. Jeffrey; Ritter, Paul D.

A methodology to quantify the performance of an air monitoring network in terms of frequency of detection has been developed. The methodology utilizes an atmospheric transport model to predict air concentrations of radionuclides at the samplers for a given release time and duration. Frequency of detection is defined as the fraction of “events” that result in a detection at either a single sampler or network of samplers. An “event” is defined as a release of finite duration that begins on a given day and hour of the year from a facility with the potential to emit airborne radionuclides. Another metricmore » of interest is the network intensity, which is defined as the fraction of samplers in the network that have a positive detection for a given event. The frequency of detection methodology allows for evaluation of short-term releases that include effects of short-term variability in meteorological conditions. The methodology was tested using the U.S. Department of Energy Idaho National Laboratory (INL) Site ambient air monitoring network consisting of 37 low-volume air samplers in 31 different locations covering a 17,630 km 2 region. Releases from six major INL facilities distributed over an area of 1,435 km 2 were modeled and included three stack sources and eight ground-level sources. A Lagrangian Puff air dispersion model (CALPUFF) was used to model atmospheric transport. The model was validated using historical 125Sb releases and measurements. Relevant one-week release quantities from each emission source were calculated based on a dose of 1.9 × 10 –4 mSv at a public receptor (0.01 mSv assuming release persists over a year). Important radionuclides considered include 241Am, 137Cs, 238Pu, 239Pu, 90Sr, and tritium. Results show the detection frequency is over 97.5% for the entire network considering all sources and radionuclides. Network intensities ranged from 3.75% to 62.7%. Evaluation of individual samplers indicated some samplers were poorly situated and add little to the overall effectiveness of the network. As a result, using the frequency of detection methods, optimum sampler placements were simulated that could substantially improve the performance and efficiency of the network.« less

Quantitative evaluation of an air-monitoring network using atmospheric transport modeling and frequency of detection methods

DOE PAGES

Rood, Arthur S.; Sondrup, A. Jeffrey; Ritter, Paul D.

2016-04-01

A methodology to quantify the performance of an air monitoring network in terms of frequency of detection has been developed. The methodology utilizes an atmospheric transport model to predict air concentrations of radionuclides at the samplers for a given release time and duration. Frequency of detection is defined as the fraction of “events” that result in a detection at either a single sampler or network of samplers. An “event” is defined as a release of finite duration that begins on a given day and hour of the year from a facility with the potential to emit airborne radionuclides. Another metricmore » of interest is the network intensity, which is defined as the fraction of samplers in the network that have a positive detection for a given event. The frequency of detection methodology allows for evaluation of short-term releases that include effects of short-term variability in meteorological conditions. The methodology was tested using the U.S. Department of Energy Idaho National Laboratory (INL) Site ambient air monitoring network consisting of 37 low-volume air samplers in 31 different locations covering a 17,630 km 2 region. Releases from six major INL facilities distributed over an area of 1,435 km 2 were modeled and included three stack sources and eight ground-level sources. A Lagrangian Puff air dispersion model (CALPUFF) was used to model atmospheric transport. The model was validated using historical 125Sb releases and measurements. Relevant one-week release quantities from each emission source were calculated based on a dose of 1.9 × 10 –4 mSv at a public receptor (0.01 mSv assuming release persists over a year). Important radionuclides considered include 241Am, 137Cs, 238Pu, 239Pu, 90Sr, and tritium. Results show the detection frequency is over 97.5% for the entire network considering all sources and radionuclides. Network intensities ranged from 3.75% to 62.7%. Evaluation of individual samplers indicated some samplers were poorly situated and add little to the overall effectiveness of the network. As a result, using the frequency of detection methods, optimum sampler placements were simulated that could substantially improve the performance and efficiency of the network.« less

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.

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.

Intercomparison of Clean Air Status and Trends Network (CASTNET) NO3 - and HNO3 Measurements with Data from Other Monitoring Programs

EPA Science Inventory

The EPA Clean Air Status and Trends Network (CASTNET) utilizes an open face filter pack system to measure concentrations of atmospheric sulfur and nitrogen species. The purpose of this study was to estimate the uncertainty in seasonal and annual concentrations of HNO3, NO3 - , ...

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.

INTEGRATION OF SATELLITE-DERIVED AEROSOL DATA INTO THE AIR QUALITY APPLICATIONS

EPA Science Inventory

Historically, the only source of aerosol air quality data available on an ongoing and systematic basis at national levels was generated by ambient air monitoring networks put in place for the US EPA's Air Quality Programs. Over the past several years, the remote sensing of aeros...

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.

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...

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.

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.

Meet EPA Researcher Rachelle Duvall, Ph.D.

EPA Pesticide Factsheets

EPA Research Physical Scientist Dr. Rachelle Duvall works with equipment that measures air pollution—evaluating, testing, and approving of methods that are used in air quality monitoring networks across the U.S.

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.

76 FR 39103 - Science Advisory Board Staff Office Notification of a Public Teleconference of the Air Monitoring...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-05

... draft plans for Photochemical Assessment Monitoring Stations (PAMS) Network Re-engineering. DATES: A... information concerning the EPA CASAC can be found at the EPA CASAC Web site at http://www.epa.gov/casac . Any inquiry regarding EPA's draft plans for PAMS Network Re-engineering should be directed to Mr. Kevin...

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

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.

CrossVit: enhancing canopy monitoring management practices in viticulture.

PubMed

Matese, Alessandro; Vaccari, Francesco Primo; Tomasi, Diego; Di Gennaro, Salvatore Filippo; Primicerio, Jacopo; Sabatini, Francesco; Guidoni, Silvia

2013-06-13

A new wireless sensor network (WSN), called CrossVit, and based on MEMSIC products, has been tested for two growing seasons in two vineyards in Italy. The aims are to evaluate the monitoring performances of the new WSN directly in the vineyard and collect air temperature, air humidity and solar radiation data to support vineyard management practices. The WSN consists of various levels: the Master/Gateway level coordinates the WSN and performs data aggregation; the Farm/Server level takes care of storing data on a server, data processing and graphic rendering; Nodes level is based on a network of peripheral nodes consisting of a MDA300 sensor board and Iris module and equipped with thermistors for air temperature, photodiodes for global and diffuse solar radiation, and an HTM2500LF sensor for relative humidity. The communication levels are: WSN links between gateways and sensor nodes by ZigBee, and long-range GSM/GPRS links between gateways and the server farm level. The system was able to monitor the agrometeorological parameters in the vineyard: solar radiation, air temperature and air humidity, detecting the differences between the canopy treatments applied. The performance of CrossVit, in terms of monitoring and reliability of the system, have been evaluated considering: its handiness, cost-effective, non-invasive dimensions and low power consumption.

CrossVit: Enhancing Canopy Monitoring Management Practices in Viticulture

PubMed Central

Matese, Alessandro; Vaccari, Francesco Primo; Tomasi, Diego; Di Gennaro, Salvatore Filippo; Primicerio, Jacopo; Sabatini, Francesco; Guidoni, Silvia

2013-01-01

A new wireless sensor network (WSN), called CrossVit, and based on MEMSIC products, has been tested for two growing seasons in two vineyards in Italy. The aims are to evaluate the monitoring performances of the new WSN directly in the vineyard and collect air temperature, air humidity and solar radiation data to support vineyard management practices. The WSN consists of various levels: the Master/Gateway level coordinates the WSN and performs data aggregation; the Farm/Server level takes care of storing data on a server, data processing and graphic rendering; Nodes level is based on a network of peripheral nodes consisting of a MDA300 sensor board and Iris module and equipped with thermistors for air temperature, photodiodes for global and diffuse solar radiation, and an HTM2500LF sensor for relative humidity. The communication levels are: WSN links between gateways and sensor nodes by ZigBee, and long-range GSM/GPRS links between gateways and the server farm level. The system was able to monitor the agrometeorological parameters in the vineyard: solar radiation, air temperature and air humidity, detecting the differences between the canopy treatments applied. The performance of CrossVit, in terms of monitoring and reliability of the system, have been evaluated considering: its handiness, cost-effective, non-invasive dimensions and low power consumption. PMID:23765273

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.

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 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.

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.

76 FR 28393 - Proposed Approval of Air Quality Implementation Plan; Ohio and West Virginia; Determinations of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-17

... substituted for missing data. See 40 CFR Part 58, appendix D for network design criteria. EPA has approved the... certified ambient air monitoring data for the 2007-2009 period showing that the areas have monitored attainment of the annual PM 2.5 NAAQS. EPA also evaluated incomplete data from this period from other...

QUALITY ASSURANCE PERFORMANCE AUDIT REPORT FOR THE SECRETARIA DEL MEDIO AMBIENTE CIUDAD DE MEXICO, DF, MEXICO RED AUTOMATICA DE MONITOREO ATMOSFERICO (RAMA) AIR QUALITY MONITORING STATIONS

EPA Science Inventory

The United States Environmental Protection Agency (U.S. EPA) conducted this evaluation of the air monitoring network, known as RAM (Red Automatica de Monitoreo Atmosferico) at the request of the Mexico City Secretariat of the Environment on October 16-27, 2000. This evaluation...

Evaluating Ambient Concentrations and Local Emissions of Greenhouse Gases (GHGs) in the San Francisco Bay Area of California Using a Comprehensive Fixed-site and Mobile Monitoring Network

NASA Astrophysics Data System (ADS)

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

2015-12-01

The Bay Area Air Quality Management District (hence the Air District) is the greater San Francisco Bay metropolitan region's chief air quality regulatory agency. Aligning itself with 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 10-point Climate Action Work Program lays out the agency's priorities, actions and coordination with regional stakeholders. The Program has three core objectives: (1) to develop a technical and monitoring program to document the region's GHG sources and related emissions, (2) to implement a policy and rule-based approach to control and regulate GHG emissions, and finally, (3) to utilize local governance, incentives and partnerships to encourage GHG emissions reductions.As part of the technical program, 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 GHG enhancements from local sources. These stations are at San Martin, located south of the San Jose metropolitan area; at Patterson Pass at the cross section with California's Central Valley; and at Bethel Island at the mouth of the Sacramento-San Joaquin Delta. At all sites, carbon dioxide (CO2) and methane (CH4) are being measured continuously, along with combustion tracer CO and other air pollutants. The GHG measurements are performed with high precision and fast laser instruments (Picarro Inc). 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 from the sites in their first few months of operation and demonstrate the efficacy and utility of this monitoring network. We also present our progress on the design and fabrication of a dedicated mobile GHG measurement platform (a research van) equipped with state of the art analyzers capable of measuring isotopic methane (13C - CH4), CH4, CO2 and also nitrous oxide (N2O) in ambient air at fast temporal rates.

Air-dropped sensor network for real-time high-fidelity volcano monitoring

USGS Publications Warehouse

Song, W.-Z.; Huang, R.; Xu, M.; Ma, A.; Shirazi, B.; LaHusen, R.

2009-01-01

This paper presents the design and deployment experience of an air-dropped wireless sensor network for volcano hazard monitoring. The deployment of five stations into the rugged crater of Mount St. Helens only took one hour with a helicopter. The stations communicate with each other through an amplified 802.15.4 radio and establish a self-forming and self-healing multi-hop wireless network. The distance between stations is up to 2 km. Each sensor station collects and delivers real-time continuous seismic, infrasonic, lightning, GPS raw data to a gateway. The main contribution of this paper is the design and evaluation of a robust sensor network to replace data loggers and provide real-time long-term volcano monitoring. The system supports UTC-time synchronized data acquisition with 1ms accuracy, and is online configurable. It has been tested in the lab environment, the outdoor campus and the volcano crater. Despite the heavy rain, snow, and ice as well as gusts exceeding 120 miles per hour, the sensor network has achieved a remarkable packet delivery ratio above 99% with an overall system uptime of about 93.8% over the 1.5 months evaluation period after deployment. Our initial deployment experiences with the system have alleviated the doubts of domain scientists and prove to them that a low-cost sensor network system can support real-time monitoring in extremely harsh environments. Copyright 2009 ACM.

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.

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

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.

Development of an advanced radioactive airborne particle monitoring system for use in early warning networks.

PubMed

Baeza, A; Corbacho, J A; Caballero, J M; Ontalba, M A; Vasco, J; Valencia, D

2017-09-25

Automatic real-time warning networks are essential for the almost immediate detection of anomalous levels of radioactivity in the environment. In the case of Extremadura region (SW Spain), a radiological network (RARE) has been operational in the vicinity of the Almaraz nuclear power plant and in other areas farther away since 1992. There are ten air monitoring stations equipped with Geiger-Müller counters in order to evaluate the external ambient gamma dose rate. Four of these stations have a commercial system that provides estimates of the total artificial alpha and beta activity concentrations in aerosols, and of the 131 I activity (gaseous fraction). Despite experience having demonstrated the benefits and robustness of these commercial systems, important improvements have been made to one of these air monitoring systems. In this paper, the analytical and maintenance shortcomings of the original commercial air monitoring system are described first; the new custom-designed advanced air monitoring system is then presented. This system is based mainly on the incorporation of gamma spectrometry using two scintillation detectors, one of NaI:Tl and the other of LaBr 3 :Ce, and compact multichannel analysers. Next, a comparison made of the results provided by the two systems operating simultaneously at the same location for three months shows the advantages of the new advanced air monitoring system. As a result, the gamma spectrometry analysis allows passing from global alpha and beta activity determinations due to artificial radionuclides in aerosols, and the inaccurate measurement of the gaseous 131 I activity concentration, to the possibility of identifying a large number of radionuclides and quantifying each of their activity concentrations. Moreover, the new station's dual capacity is designed to work in early warning monitoring mode and surveillance monitoring mode. This is based on custom developed software that includes an intelligent system to issue the necessary warnings when radiological anomalies or technical problems are identified. Implicitly, for the construction of the advanced station, substantial mechanical and electronic developments have been required. They have essentially consisted of integrating a new replacement device, whose operation has reduced the maintenance tasks.

40 CFR 58.12 - Operating schedules.

Code of Federal Regulations, 2010 CFR

2010-07-01

...) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.12 Operating schedules. State and local... part. Area-specific PAMS operating schedules must be included as part of the PAMS network description... remains once every six days. No less frequently than as part of each 5-year network assessment, the most...

40 CFR 58.12 - Operating schedules.

Code of Federal Regulations, 2011 CFR

2011-07-01

...) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.12 Operating schedules. State and local... part. Area-specific PAMS operating schedules must be included as part of the PAMS network description... remains once every six days. No less frequently than as part of each 5-year network assessment, the most...

40 CFR 58.16 - Data submittal and archiving requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... Other Federal agencies may request access to filters for purposes of supporting air quality management... PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.16 Data submittal and..., via AQS all ambient air quality data and associated quality assurance data for SO2; CO; O3; NO2; NO...

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...

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...

Use of Whatman-41 filters in air quality sampling networks (with applications to elemental analysis)

NASA Technical Reports Server (NTRS)

Neustadter, H. E.; Sidik, S. M.; King, R. B.; Fordyce, J. S.; Burr, J. C.

1974-01-01

The operation of a 16-site parallel high volume air sampling network with glass fiber filters on one unit and Whatman-41 filters on the other is reported. The network data and data from several other experiments indicate that (1) Sampler-to-sampler and filter-to-filter variabilities are small; (2) hygroscopic affinity of Whatman-41 filters need not introduce errors; and (3) suspended particulate samples from glass fiber filters averaged slightly, but not statistically significantly, higher than from Whatman-41-filters. The results obtained demonstrate the practicability of Whatman-41 filters for air quality monitoring and elemental analysis.

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.

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.

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.

Prediction of Indoor Air Exposure from Outdoor Air Quality Using an Artificial Neural Network Model for Inner City Commercial Buildings.

PubMed

Challoner, Avril; Pilla, Francesco; Gill, Laurence

2015-12-01

NO₂ and particulate matter are the air pollutants of most concern in Ireland, with possible links to the higher respiratory and cardiovascular mortality and morbidity rates found in the country compared to the rest of Europe. Currently, air quality limits in Europe only cover outdoor environments yet the quality of indoor air is an essential determinant of a person's well-being, especially since the average person spends more than 90% of their time indoors. The modelling conducted in this research aims to provide a framework for epidemiological studies by the use of publically available data from fixed outdoor monitoring stations to predict indoor air quality more accurately. Predictions are made using two modelling techniques, the Personal-exposure Activity Location Model (PALM), to predict outdoor air quality at a particular building, and Artificial Neural Networks, to model the indoor/outdoor relationship of the building. This joint approach has been used to predict indoor air concentrations for three inner city commercial buildings in Dublin, where parallel indoor and outdoor diurnal monitoring had been carried out on site. This modelling methodology has been shown to provide reasonable predictions of average NO₂ indoor air quality compared to the monitored data, but did not perform well in the prediction of indoor PM2.5 concentrations. Hence, this approach could be used to determine NO₂ exposures more rigorously of those who work and/or live in the city centre, which can then be linked to potential health impacts.

US EPA's National Dioxin Air Monitoring Network: Analytical ...

EPA Pesticide Factsheets

The U.S. EPA has established a National Dioxin Air Monitoring Network (NDAMN) to determine the temporal and geographical variability of atmospheric chlorinated dibenzo-p-dioxins (CDDs), furans (CDFs), and coplanar polychlorinated biphenyls (PCBs) at rural and non-impacted locations throughout the United States. Currently operating at 32 sampling stations, NDAMN has three primary purposes: (1) to determine the atmospheric levels and occurrences of dioxin-like compounds in rural and agricultural areas where livestock, poultry, and animal feed crops are grown; (2) to provide measurements of atmospheric levels in different geographic regions of the U.S.; and (3) to provide information regarding the long-range transport of dioxin-like compounds in air over the U.S. Designed in 1997, NDAMN has been implemented in phases, with the first phase consisting of 9 monitoring stations and is achieving congener-specific detection lmits of 0.1 fg/m3 for 2,3,7,8-TCDD and 10 fg/m3 for OCDD. With respect to coplanar PCBs, the detection limits are generally higher due to the presence of background levels in the air during the preparation and processing of the samples. Achieving these extremely low levels of detection present a host of analytical issues. Among these issues are the methods used to establish ultra-trace detection limits, measures to ensure against and monitor for breakthrough of native analytes when sampling large volumes of air, and procedures for handling and e

Measuring NO, NO2, CO2 and O3 with low-cost sensors

NASA Astrophysics Data System (ADS)

Müller, Michael; Graf, Peter; Hüglin, Christoph

2017-04-01

Inexpensive sensors measuring ambient gas concentrations can be integrated in sensor units forming dense sensor networks. The utilized sensors have to be sufficiently accurate as the value of such networks directly depends on the information they provide. Thus, thorough testing of sensors before bringing them into service and the application of effective strategies for performance monitoring and adjustments during service are key elements for operating the low-cost sensors that are currently available on the market. We integrated several types of low-cost sensors into sensor units (Alphasense NO2 B4/B42F/B43F, Alphasense NO B4, SensAir CO2 LP8, Aeroqual O3 SM50), run them in the field next to instruments of air quality monitoring stations and performed tests in the laboratory. The poster summarizes our findings regarding the achieved sensor accuracy, methods to improve sensor performance as well as strategies to monitor the current state of the sensor (drifts, sensitivity) within a sensor network.

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...

Replacing the AMOR with the miniDOAS in the ammonia monitoring network in the Netherlands

NASA Astrophysics Data System (ADS)

Berkhout, Augustinus J. C.; Swart, Daan P. J.; Volten, Hester; Gast, Lou F. L.; Haaima, Marty; Verboom, Hans; Stefess, Guus; Hafkenscheid, Theo; Hoogerbrugge, Ronald

2017-11-01

In this paper we present the continued development of the miniDOAS, an active differential optical absorption spectroscopy (DOAS) instrument used to measure ammonia concentrations in ambient air. The miniDOAS has been adapted for use in the Dutch National Air Quality Monitoring Network. The miniDOAS replaces the life-expired continuous-flow denuder ammonia monitor (AMOR). From September 2014 to December 2015, both instruments measured in parallel before the change from AMOR to miniDOAS was made. The instruments were deployed at six monitoring stations throughout the Netherlands. We report on the results of this intercomparison. Both instruments show a good uptime of ca. 90 %, adequate for an automatic monitoring network. Although both instruments produce 1 min values of ammonia concentrations, a direct comparison on short timescales such as minutes or hours does not give meaningful results because the AMOR response to changing ammonia concentrations is slow. Comparisons between daily and monthly values show good agreement. For monthly averages, we find a small average offset of 0.65 ± 0.28 µg m-3 and a slope of 1.034 ± 0.028, with the miniDOAS measuring slightly higher than the AMOR. The fast time resolution of the miniDOAS makes the instrument suitable not only for monitoring but also for process studies.

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...

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.

The design of tea garden environmental monitoring system based on WSN

NASA Astrophysics Data System (ADS)

Chen, Huajun; Yuan, Lina

2018-01-01

Through the application of wireless sensor network (WSN) in tea garden, it can realize the change of traditional tea garden to the modern ones, and effectively improves the comprehensive productive capacity of tea garden. According to the requirement of real-time remote in agricultural information collection and monitoring and the power supply affected by environmental limitations, based on WSN, this paper designs a set of tea garden environmental monitoring system, which achieves the monitoring nodes with ad-hoc network as well as automatic acquisition and transmission to the tea plantations of air temperature, light intensity, soil temperature and humidity.

The Alaska Volcano Observatory - Expanded Monitoring of Volcanoes Yields Results

USGS Publications Warehouse

Brantley, Steven R.; McGimsey, Robert G.; Neal, Christina A.

2004-01-01

Recent explosive eruptions at some of Alaska's 52 historically active volcanoes have significantly affected air traffic over the North Pacific, as well as Alaska's oil, power, and fishing industries and local communities. Since its founding in the late 1980s, the Alaska Volcano Observatory (AVO) has installed new monitoring networks and used satellite data to track activity at Alaska's volcanoes, providing timely warnings and monitoring of frequent eruptions to the aviation industry and the general public. To minimize impacts from future eruptions, scientists at AVO continue to assess volcano hazards and to expand monitoring networks.

40 CFR 58.14 - System modification.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 6 2012-07-01 2012-07-01 false System modification. 58.14 Section 58.14 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.14 System modification. (a) The State, or where...

40 CFR 58.14 - System modification.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 6 2014-07-01 2014-07-01 false System modification. 58.14 Section 58.14 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.14 System modification. (a) The State, or where...

REVIEW OF THE RADNET AIR MONITORING NETWORK UPGRADE AND EXPANSION

EPA Science Inventory

RadNet, formerly known as ERAMS, has been operating since the 1970's, monitoring environmental radiation across the country, supporting responses to radiological emergencies, and providing important information on background levels of radiation in the environment. The original ...

Community Air Monitoring for Pesticide Drift Using Pesticide Action Network's (PAN) Drift Catcher

NASA Astrophysics Data System (ADS)

Marquez, E.

2016-12-01

Community air monitoring projects for pesticides in the air have been conducted by PAN in collaboration with community members and locally based groups engaged around pesticide issues. PAN is part of an international network working to promote a just, thriving food system and replace the use of hazardous pesticides with ecologically sound alternatives. The Drift Catcher is an air-monitoring device with a design based on the California Air Resource Board's air monitoring equipment, and has been used in community-based projects in 11 states. Observations of pesticide drift made by community members cannot always be confirmed by regulatory agencies—if an inspection is made hours or days after a drift incident, the evidence may no longer be present. The Drift Catcher makes it possible to collect scientific evidence of pesticide drift in areas where people live, work, and play. One of the most recent Drift Catcher projects was done in California, in partnership with the Safe Strawberry Coalition and led by the statewide coalition Californians for Pesticide Reform. The data were used to support a call for stronger mitigation rules for the fumigant chloropicrin and to support a campaign asking for stronger pesticide rules to protect children attending school in close proximity to agricultural fields. The Drift Catcher data are used by organizers and community members to engage policymakers with the intention of making policy change on a local and/or statewide level. On the national level, PAN's Drift Catcher data has helped win regulatory recognition of volatilization drift for pesticides other than fumigants. Lessons learned from conducting community-based research projects will also be discussed. PAN is also currently assessing other community-based monitoring tools, such as community surveys and drift questionnaires that may allow communities to collect data that can also support the campaign work.

Vital signs monitoring plan for the Klamath Network: Phase I report

USGS Publications Warehouse

Sarr, Daniel; Odion, Dennis; Truitt, Robert E.; Beever, Erik A.; Shafer, Sarah; Duff, Andrew; Smith, Sean B.; Bunn, Windy; Rocchio, Judy; Sarnat, Eli; Alexander, John; Jessup, Steve

2004-01-01

This report chronicles the Phase 1 stage of the vital signs monitoring program for the Klamath Network. It consists of two chapters and eleven appendixes. The purposes of Chapter One are to 1) describe the network administrative structure and approach to planning; 2) introduce the Klamath Network parks, their resources, and environmental settings; 3) explain the need for monitoring changes in resources and supporting environments; 4) identify key information gaps that limit understanding of how to best achieve these monitoring goals. The purpose of Chapter Two is to develop the descriptive information provided in Chapter One into a conceptual basis for vital signs monitoring and to present the Network’s initial suite of conceptual models. The Report Appendices provide in-depth information on a variety of topics researched in preparation of the report, including: detailed natural resource profiles for each park, supporting policies and guidelines, regional fire regimes, vegetation types of the parks, exotic species threats, interagency monitoring programs, air issues, water quality (Phase 1 Report), Network vital signs (Scoping Summary Report), rare species, and rare habitats of the parks.

DEVELOPMENT OF QUALITY ASSURANCE AND QUALITY CONTROL GUIDANCE FOR GROUND-BASED REMOTE SENSORS FOR USE IN REGULATORY MONITORING

EPA Science Inventory

The U.S. Environmental Protection Agency's (EPA) authority for enhanced monitoring activities is provided for in Title I, Section 182 of the Clean Air Act Amendment of 1990. or example, the Photochemical Assessment Monitoring Station (PAMS) network is one such program which requi...

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...

40 CFR 58.16 - Data submittal and archiving requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 5 2011-07-01 2011-07-01 false Data submittal and archiving requirements. 58.16 Section 58.16 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.16 Data submittal and...

Community Air Sensor Network (CAIRSENSE) Project: Lower Cost, Continuous Ambient Monitoring Methods

EPA Pesticide Factsheets

CAIRSENSE Project presentation was given at the 108th Annual Meeting of the Air & Waste Management Associate in June 2015. The presentation provides an overview of the CAIRSENSE Project and general info about the sensors used in the CAIRSENSE Project.

ADVANCEMENTS IN SOURCE-TO-DOSE ANALYSIS OF POPULATION EXPOSURES TO OZONE

EPA Science Inventory

The current study takes advantage of the observations from regional air quality monitoring networks, the data from the NE-OPS (North East Oxidant and Particulate Study) Project in the Philadelphia region, and regional photochemical air quality model predictions to obtain and co...

Prediction of Indoor Air Exposure from Outdoor Air Quality Using an Artificial Neural Network Model for Inner City Commercial Buildings

PubMed Central

Challoner, Avril; Pilla, Francesco; Gill, Laurence

2015-01-01

NO2 and particulate matter are the air pollutants of most concern in Ireland, with possible links to the higher respiratory and cardiovascular mortality and morbidity rates found in the country compared to the rest of Europe. Currently, air quality limits in Europe only cover outdoor environments yet the quality of indoor air is an essential determinant of a person’s well-being, especially since the average person spends more than 90% of their time indoors. The modelling conducted in this research aims to provide a framework for epidemiological studies by the use of publically available data from fixed outdoor monitoring stations to predict indoor air quality more accurately. Predictions are made using two modelling techniques, the Personal-exposure Activity Location Model (PALM), to predict outdoor air quality at a particular building, and Artificial Neural Networks, to model the indoor/outdoor relationship of the building. This joint approach has been used to predict indoor air concentrations for three inner city commercial buildings in Dublin, where parallel indoor and outdoor diurnal monitoring had been carried out on site. This modelling methodology has been shown to provide reasonable predictions of average NO2 indoor air quality compared to the monitored data, but did not perform well in the prediction of indoor PM2.5 concentrations. Hence, this approach could be used to determine NO2 exposures more rigorously of those who work and/or live in the city centre, which can then be linked to potential health impacts. PMID:26633448

Final Regulatory Impact Analysis (RIA) for the NO2 National Ambient Air Quality Standards (NAAQS)

EPA Pesticide Factsheets

This RIA provides illustrative estimates, as of January 2010, of the incremental costs and monetized human health benefits of attaining the revised NO2 NAAQS within the the existing community-wide monitoring network of 409 monitors.

TRENDS IN RURAL SULFUR CONCENTRATIONS

EPA Science Inventory

This paper presents an analysis of regional trends in atmospheric concentrations in sulfur dioxide (502) and particulate sulfate (50~- ) at rural monitoring sites in the Clean Air Act Status and Trends Monitoring Network (CAsTNet) from 1990 to 1999. A two-stage approach is used t...

Pollen and spore monitoring in the world.

PubMed

Buters, J T M; Antunes, C; Galveias, A; Bergmann, K C; Thibaudon, M; Galán, C; Schmidt-Weber, C; Oteros, J

2018-01-01

Ambient air quality monitoring is a governmental duty that is widely carried out in order to detect non-biological ("chemical") components in ambient air, such as particles of < 10 µm (PM 10 , PM 2.5 ), ozone, sulphur dioxide, and nitrogen oxides. These monitoring networks are publicly funded and air quality data are open to the public. The situation for biological particles that have detrimental effects on health, as is the case of pollen and fungal spores, is however very different. Most pollen and spore monitoring networks are not publicly funded and data are not freely available. The information regarding which biological particle is being monitored, where and by whom, is consequently often not known, even by aerobiologists themselves. This is a considerable problem, as local pollen data are an important tool for the prevention of allergic symptoms. The aim of this study was to review pollen monitoring stations throughout the world and to create an interactive visualization of their distribution. The method employed to collect information was based on: (a) a review of the recent and historical bibliography related to pollen and fungal spore monitoring, and (b) personal surveys of the managers of national and regional monitoring networks. The interactive application was developed using the R programming language. We have created an inventory of the active pollen and spore monitoring stations in the world. There are at least 879 active pollen monitoring stations in the world, most of which are in Europe (> 500). The prevalent monitoring method is based on the Hirst principle (> 600 stations). The inventory is visualised as an interactive and on-line map. It can be searched, its appearance can be adjusted to the users' needs and it is updated regularly, as new stations or changes to those that already exist can be submitted online. The map shows the current situation of pollen and spore monitoring and facilitates collaboration among those individuals who are interested in pollen and spore counts. It might also help to improve the monitoring of biological particles up to the current level employed for non-biological components.

Journal Article: the National Dioxin Air Monitoring Network ...

EPA Pesticide Factsheets

In June, 1998, the U.S. EPA established the National Dioxin Air Monitoring Network (NDAMN). The primary goal of NDAMN is determine the temporal and geographical variability of atmospheric CDDs, CDFs, and coplanar PCBs at rural and nonimpacted locations throughout the United States. Currently operating at 32 sampling stations, NDAMN has three primary purposes: (1) to determine the atmospheric levels and occurrences of dioxin-like compounds in rural and agricultural areas where livestock, poultry and animal feed crops are grown; (2) to provide measurements of atmospheric levels of dioxin-like compounds in different geographic regions of the U.S.; and (3) to provide information regarding the long-range transport of dioxin-like compounds in air over the U.S. At Dioxin 2000, we reported on the preliminary results of monitoring at 9 rural locations from June 1998 through June 1999. By the end of 1999, NDAMN had expanded to 21 sampling stations. Then, at Dioxin 2001, we reported the results of the first 18 months of operation of NDAMN at 15 rural and 6 National Park stations in the United States. The following is intended to be an update to this national monitoring effort. We are reporting the air monitoring results of 17 rural and 8 National Park NDAMN stations operational over 4 sampling moments during calendar year 2000. Two stations located in suburban Washington DC and San Francisco, CA are more urban in character and serve as an indicator of CDD/F and cop

Condition monitoring of an electro-magnetic brake using an artificial neural network

NASA Astrophysics Data System (ADS)

Gofran, T.; Neugebauer, P.; Schramm, D.

2017-10-01

This paper presents a data-driven approach to Condition Monitoring of Electromagnetic brakes without use of additional sensors. For safe and efficient operation of electric motor a regular evaluation and replacement of the friction surface of the brake is required. One such evaluation method consists of direct or indirect sensing of the air-gap between pressure plate and magnet. A larger gap is generally indicative of worn surface(s). Traditionally this has been accomplished by the use of additional sensors - making existing systems complex, cost- sensitive and difficult to maintain. In this work a feed-forward Artificial Neural Network (ANN) is learned with the electrical data of the brake by supervised learning method to estimate the air-gap. The ANN model is optimized on the training set and validated using the test set. The experimental results of estimated air-gap with accuracy of over 95% demonstrate the validity of the proposed approach.

Real-time indoor monitoring system based on wireless sensor networks

NASA Astrophysics Data System (ADS)

Wu, Zhengzhong; Liu, Zilin; Huang, Xiaowei; Liu, Jun

2008-10-01

Wireless sensor networks (WSN) greatly extend our ability to monitor and control the physical world. It can collaborate and aggregate a huge amount of sensed data to provide continuous and spatially dense observation of environment. The control and monitoring of indoor atmosphere conditions represents an important task with the aim of ensuring suitable working and living spaces to people. However, the comprehensive air quality, which includes monitoring of humidity, temperature, gas concentrations, etc., is not so easy to be monitored and controlled. In this paper an indoor WSN monitoring system was developed. In the system several sensors such as temperature sensor, humidity sensor, gases sensor, were built in a RF transceiver board for monitoring indoor environment conditions. The indoor environmental monitoring parameters can be transmitted by wireless to database server and then viewed throw PC or PDA accessed to the local area networks by administrators. The system, which was also field-tested and showed a reliable and robust characteristic, is significant and valuable to people.

EVALUATION OF THE FILTER PACK FOR LONG-DURATION SAMPLING OF AMBIENT AIR

EPA Science Inventory

A 14-week filter pack (FP) sampler evaluation field study was conducted at a site near Bondville, IL to investigate the impact of weekly sampling duration. Simultaneous samples were collected using collocated filter packs (FP) from two independent air quality monitoring networks...

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.

REGIONAL TRENDS IN RURAL SULFUR CONCENTRATIONS

EPA Science Inventory

This paper presents an analysis of trends in atmospheric concentrations of sulfur dioxide (SO,) and particulate sulfate (SO42-) at rural monitoring sites in the Clean Air Act Status and Trends Monitoring Network (CASTNet) from 1990 to 1999. A two-stage approach is used to estimat...

Oceanographic Research Towers in European Waters

DTIC Science & Technology

1992-12-01

equipped with an air - conditioner ). Precipitation and fog occurrence are 5 percent and I percent of the time. High humidity is frequent in summer. Water...salinity, temperature; existence of biological systems; air temperature; winds; other weather parameters, etc. "* Accommodation of instruments, support...monitoring network as employed by Rijkwaterstaat. It carries a meteorological station providing information on wind speed and direction, air pressure

THE USE OF MICROMETEROLOGICAL PARAMETERS IN THE ESTABLISHMENT OF A VOC MONITORING NETWORK

EPA Science Inventory

This report is part of the National Network for Environmental Management Studies Program conducted under the auspices of the Office of Cooperative Environmental Management - U.S. Environmental Protection Agency. As part of an ongoing volatile organic compounds (VOC) ambient air s...

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.

Home medical monitoring network based on embedded technology

NASA Astrophysics Data System (ADS)

Liu, Guozhong; Deng, Wenyi; Yan, Bixi; Lv, Naiguang

2006-11-01

Remote medical monitoring network for long-term monitoring of physiological variables would be helpful for recovery of patients as people are monitored at more comfortable conditions. Furthermore, long-term monitoring would be beneficial to investigate slowly developing deterioration in wellness status of a subject and provide medical treatment as soon as possible. The home monitor runs on an embedded microcomputer Rabbit3000 and interfaces with different medical monitoring module through serial ports. The network based on asymmetric digital subscriber line (ADSL) or local area network (LAN) is established and a client - server model, each embedded home medical monitor is client and the monitoring center is the server, is applied to the system design. The client is able to provide its information to the server when client's request of connection to the server is permitted. The monitoring center focuses on the management of the communications, the acquisition of medical data, and the visualization and analysis of the data, etc. Diagnosing model of sleep apnea syndrome is built basing on ECG, heart rate, respiration wave, blood pressure, oxygen saturation, air temperature of mouth cavity or nasal cavity, so sleep status can be analyzed by physiological data acquired as people in sleep. Remote medical monitoring network based on embedded micro Internetworking technology have advantages of lower price, convenience and feasibility, which have been tested by the prototype.

UTILIZING SATELLITE OBSERVATIONS TO EXPAND EPA'S AIR MONITORING NETWORK: A NEW PARTNERSHIP BETWEEN NASA AND EPA

EPA Science Inventory

Over the next decade, data requirements to inform air quality management decisions and policies will need to be expanded to large spatial domains to accommodate decisions which more frequently cross geo-political boundaries; from urban (local) and regional scales to regional, sup...

CONCENTRATIONS AND SPECIATION OF PM AT GROUND ZERO AND LOWER MANHATTAN FOLLOWING THE COLLAPSE OF THE WTC

EPA Science Inventory

The U.S. EPA National Exposure Research Laboratory (NERL), in conjunction with our Regional offices, established a network of air monitoring sites to characterize ambient air concentrations of gases and particles in lower Manhattan following the collapse of the World Trade Cent...

CONCENTRATIONS AND COMPOSITION OF PM AT GROUND ZERO AND LOWER MANHATTAN FOLLOWING THE COLLAPSE OF THE WTC

EPA Science Inventory

The U.S. EPA National Exposure Research Laboratory (NERL), in conjunction with our Regional offices, established a network of air monitoring sites to characterize ambient air concentrations of gases and particles in lower Manhattan following the collapse of the World Trade Cent...

Evaluation of land use regression models (LURs) for nitrogen dioxide and benzene in four U.S. Cities.

EPA Science Inventory

Spatial analysis studies have included application of land use regression models (LURs) for health and air quality assessments. Recent LUR studies have collected nitrogen dioxide (NO2) and volatile organic compounds (VOCs) using passive samplers at urban air monitoring networks ...

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

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.

SAMIRA - SAtellite based Monitoring Initiative for Regional Air quality

NASA Astrophysics Data System (ADS)

Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nicolae, Doina; Stachlewska, Iwona; Zehner, Claus

2016-04-01

Here, we present a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellites, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. Despite considerable improvements in the past decades, Europe is still far from achieving levels of air quality that do not pose unacceptable hazards to humans and the environment. Main concerns in Europe are exceedances of particulate matter (PM), ground-level ozone, benzo(a)pyrene (BaP) and nitrogen dioxide (NO2). While overall sulfur dioxide (SO2) emissions have decreased in recent years, regional concentrations can still be high in some areas. The objectives of SAMIRA are to improve algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from SEVIRI, and to develop robust methods for deriving column- and near-surface PM maps for the study area by combining satellite AOD with information from regional models. The benefit to existing monitoring networks (in situ, models, satellite) by combining these datasets using data fusion methods will be tested for satellite-based NO2, SO2, and PM/AOD. Furthermore, SAMIRA will test and apply techniques for downscaling air quality-related EO products to a spatial resolution that is more in line with what is generally required for studying urban and regional scale air quality. This will be demonstrated for a set of study sites that include the capitals of the four countries and the highly polluted areas along the border of Poland and the Czech Republic, and the Gorj County in Romania. All data products shall undergo a quality control, i.e. robust and independent validation. The SAMIRA consortium will further work towards a pre-operational system for improved PM10 forecasts using observational (in situ and satellite) data assimilation. SAMIRA aims to maximize project benefits by liaison with national and regional environmental protection agencies and health institutions, as well as related ESA and European initiatives such as the Copernicus Atmospheric Monitoring Services (CAMS).

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.

40 CFR Appendix N to Part 50 - Interpretation of the National Ambient Air Quality Standards for PM2.5

Code of Federal Regulations, 2013 CFR

2013-07-01

... monitors utilize the same specific sampling and analysis method. Combined site data record is the data set... monitors are suitable monitors designated by a state or local agency in their annual network plan (and in... appendix. Seasonal sampling is the practice of collecting data at a reduced frequency during a season of...

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.

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).

Wet deposition monitoring and modelling in New Brunswick — An area dominated by wet deposition due to long-range transport

NASA Astrophysics Data System (ADS)

Davis, Claude S.

Two wet deposition monitoring networks, the Coleson Cove Precipitation Monitoring Network (CCPMN) (12 stations) located in the Coleson Cove-Saint John area of south New Brunswick, and the Expanded New Brunswick Precipitation Monitoring Network (ENBPMN) (6 stations) covering the remainder of the province, were established in May 1988. The monitoring networks and a complementary modelling study were implemented to assess the relative contributions of local and distant sources to wet deposition in New Brunswick. Quality assurance/quality control activities for the networks included independent external audits, collocated samplers at one site and comparisons of weekly measurements at the ENBPMN sampler and the Canadian Air and Precipitation Monitoring Network (CAPMoN) sampler which makes daily measurements. The intercomparisons provided reassurance that the networks provided high quality data. Analysis of 2 years (June 1988-May 1990) data from the networks included routine statistical analyses for acid rain chemistry as well as analysis of 1 year of daily back trajectory data from Harcourt, New Brunswick. Three-day back trajectories determined at 12-h intervals from Harcourt on days with precipitatio showed that air masses originate mainly from regions in Quebec, Ontario and northeast U.S.A. which are known to have high sulphur oxide emissions. Some 18 trajectories were associated with 50% of the wet sulphate deposition and over 200 trajectories with 75% of the deposition in the 1-year period ending 31 May 1989. The MESOPUFF model, applied to an 800 km by 800 km domain that included the entire province of New Brunswick, was used to make predictions of wet sulphate and nitrate deposition at each of the wet deposition monitoring stations for a 2-year period, 1 June 1988-31 May 1990. Model predictions averaged over all receptors due to all sources in the model domain accounted for 7-25% of the measured seasonal average wet sulphate deposition and less than 3% of the measured wet nitrate deposition at all monitoring stations. Wet deposition in New Brunswick is thus dominated by distant sources through long-range transport. The model estimated that the oil-fired Coleson Cove thermal generating station contributed between 7% and 16% to the seasonal wet sulphur deposition and less than 3% of the seasonal wet nitrogen deposition at monitoring stations in the Coleson Cove-Saint John area. The estimates for wet nitrogen deposition are limited by the NO χ emissions information which is considered less reliable than SO 2 emissions information.

75 FR 43062 - Approval and Promulgation of Air Quality Implementation Plans; Texas; Revisions to Emissions...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-23

... ozone precursor gases during the winter and summer months, respectively. The revisions also allow for... dioxide, ozone, lead (Pb), particulate matter (PM), and sulfur dioxide (SO 2 ). A SIP is a set of air... supporting information such as emissions inventories, monitoring networks, and modeling demonstrations. Each...

Development of hybrid genetic-algorithm-based neural networks using regression trees for modeling air quality inside a public transportation bus.

PubMed

Kadiyala, Akhil; Kaur, Devinder; Kumar, Ashok

2013-02-01

The present study developed a novel approach to modeling indoor air quality (IAQ) of a public transportation bus by the development of hybrid genetic-algorithm-based neural networks (also known as evolutionary neural networks) with input variables optimized from using the regression trees, referred as the GART approach. This study validated the applicability of the GART modeling approach in solving complex nonlinear systems by accurately predicting the monitored contaminants of carbon dioxide (CO2), carbon monoxide (CO), nitric oxide (NO), sulfur dioxide (SO2), 0.3-0.4 microm sized particle numbers, 0.4-0.5 microm sized particle numbers, particulate matter (PM) concentrations less than 1.0 microm (PM10), and PM concentrations less than 2.5 microm (PM2.5) inside a public transportation bus operating on 20% grade biodiesel in Toledo, OH. First, the important variables affecting each monitored in-bus contaminant were determined using regression trees. Second, the analysis of variance was used as a complimentary sensitivity analysis to the regression tree results to determine a subset of statistically significant variables affecting each monitored in-bus contaminant. Finally, the identified subsets of statistically significant variables were used as inputs to develop three artificial neural network (ANN) models. The models developed were regression tree-based back-propagation network (BPN-RT), regression tree-based radial basis function network (RBFN-RT), and GART models. Performance measures were used to validate the predictive capacity of the developed IAQ models. The results from this approach were compared with the results obtained from using a theoretical approach and a generalized practicable approach to modeling IAQ that included the consideration of additional independent variables when developing the aforementioned ANN models. The hybrid GART models were able to capture majority of the variance in the monitored in-bus contaminants. The genetic-algorithm-based neural network IAQ models outperformed the traditional ANN methods of the back-propagation and the radial basis function networks. The novelty of this research is the development of a novel approach to modeling vehicular indoor air quality by integration of the advanced methods of genetic algorithms, regression trees, and the analysis of variance for the monitored in-vehicle gaseous and particulate matter contaminants, and comparing the results obtained from using the developed approach with conventional artificial intelligence techniques of back propagation networks and radial basis function networks. This study validated the newly developed approach using holdout and threefold cross-validation methods. These results are of great interest to scientists, researchers, and the public in understanding the various aspects of modeling an indoor microenvironment. This methodology can easily be extended to other fields of study also.

A Modular IoT Platform for Real-Time Indoor Air Quality Monitoring.

PubMed

Benammar, Mohieddine; Abdaoui, Abderrazak; Ahmad, Sabbir H M; Touati, Farid; Kadri, Abdullah

2018-02-14

The impact of air quality on health and on life comfort is well established. In many societies, vulnerable elderly and young populations spend most of their time indoors. Therefore, indoor air quality monitoring (IAQM) is of great importance to human health. Engineers and researchers are increasingly focusing their efforts on the design of real-time IAQM systems using wireless sensor networks. This paper presents an end-to-end IAQM system enabling measurement of CO₂, CO, SO₂, NO₂, O₃, Cl₂, ambient temperature, and relative humidity. In IAQM systems, remote users usually use a local gateway to connect wireless sensor nodes in a given monitoring site to the external world for ubiquitous access of data. In this work, the role of the gateway in processing collected air quality data and its reliable dissemination to end-users through a web-server is emphasized. A mechanism for the backup and the restoration of the collected data in the case of Internet outage is presented. The system is adapted to an open-source Internet-of-Things (IoT) web-server platform, called Emoncms, for live monitoring and long-term storage of the collected IAQM data. A modular IAQM architecture is adopted, which results in a smart scalable system that allows seamless integration of various sensing technologies, wireless sensor networks (WSNs) and smart mobile standards. The paper gives full hardware and software details of the proposed solution. Sample IAQM results collected in various locations are also presented to demonstrate the abilities of the system.

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 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".

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.

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 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.

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 ...

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...

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.

Measurements of Rural Sulfur Dioxide and Particle Sulfate: Analysis of CASTNet Data, 1987 through 1996.

PubMed

Baumgardner, Ralph E; Isil, Selma S; Bowser, Jon J; Fitzgerald, Kelley M

1999-11-01

The Clean Air Status and Trends Network (CASTNet) was implemented by the U.S. Environmental Protection Agency (EPA) in 1991 in response to Title IX of the Clean Air Amendments of 1990, which mandated the deployment of a national ambient air monitoring network to track progress of the implementation of emission reduction programs in terms of deposition, air quality, and changes to affected ecosystems. CASTNet evolved from the National Dry Deposition Network (NDDN). CASTNet currently consists of 45 sites in the eastern United States and 28 sites in the West. Each site measures sulfur dioxide (SO 2 ), nitric acid (HNO 3 ), particle sulfate (SO 4 = ), particle nitrate (NO 3 - ), and ozone. Nineteen sites collect precipitation samples. NDDN/CASTNet uses a uniform set of site-selection criteria which provides the data user with consistent measures to compare each site. These criteria also ensure that, to the extent possible, CASTNet sites are located away from local emission sources. This paper presents an analysis of SO 2 and SO 4 = concentration data collected from 1987 through 1996 at rural NDDN/CASTNet sites. Annual and seasonal variability is examined. Gradients of SO 2 and SO 4 = are discussed. The variability of the atmospheric mix of SO 2 and SO 4 = is explored spatially and seasonally. Data from CASTNet are also compared to SO 2 and SO 4 = data from concurrent monitoring studies in rural areas.

Atmospheric Carbon Dioxide Mixing Ratios from the NOAA CMDL Carbon Cycle Cooperative Global Air Sampling Network (2009)

DOE Data Explorer

Conway, Thomas [NOAA Climate Monitoring and Diagnostics Laboratory, Boulder, CO (USA); Tans, Pieter [NOAA Climate Monitoring and Diagnostics Laboratory, Boulder, CO (USA)

2009-01-01

The National Oceanic and Atmospheric Administration's Climate Monitoring and Diagnostics Laboratory (NOAA/CMDL) has measured CO2 in air samples collected weekly at a global network of sites since the late 1960s. Atmospheric CO2 mixing ratios reported in these files were measured by a nondispersive infrared absorption technique in air samples collected in glass flasks. All CMDL flask samples are measured relative to standards traceable to the World Meteorological Organization (WMO) CO2 mole fraction scale. These measurements constitute the most geographically extensive, carefully calibrated, internally consistent atmospheric CO2 data set available and are essential for studies aimed at better understanding the global carbon cycle budget.

Monitoring industrial facilities using principles of integration of fiber classifier and local sensor networks

NASA Astrophysics Data System (ADS)

Korotaev, Valery V.; Denisov, Victor M.; Rodrigues, Joel J. P. C.; Serikova, Mariya G.; Timofeev, Andrey V.

2015-05-01

The paper deals with the creation of integrated monitoring systems. They combine fiber-optic classifiers and local sensor networks. These systems allow for the monitoring of complex industrial objects. Together with adjacent natural objects, they form the so-called geotechnical systems. An integrated monitoring system may include one or more spatially continuous fiber-optic classifiers based on optic fiber and one or more arrays of discrete measurement sensors, which are usually combined in sensor networks. Fiber-optic classifiers are already widely used for the control of hazardous extended objects (oil and gas pipelines, railways, high-rise buildings, etc.). To monitor local objects, discrete measurement sensors are generally used (temperature, pressure, inclinometers, strain gauges, accelerometers, sensors measuring the composition of impurities in the air, and many others). However, monitoring complex geotechnical systems require a simultaneous use of continuous spatially distributed sensors based on fiber-optic cable and connected local discrete sensors networks. In fact, we are talking about integration of the two monitoring methods. This combination provides an additional way to create intelligent monitoring systems. Modes of operation of intelligent systems can automatically adapt to changing environmental conditions. For this purpose, context data received from one sensor (e.g., optical channel) may be used to change modes of work of other sensors within the same monitoring system. This work also presents experimental results of the prototype of the integrated monitoring system.

FIELD EVALUATION OF SAMPLERS FOR EPA'S NATIONAL PM 2.5 CHEMICAL SPECIATION NETWORK-PRELIMINARY RESULTS FROM ATLANTA

EPA Science Inventory

The US EPA bas established a national network at nearly 1100 sites to monitor PM2.5 mass for testing compliance with the PM2.5 National Ambient Air Quality Standards. The objective of the field evaluation is to determine the performance characteristics for the collection of the...

Results of hydrologic monitoring on landslide-prone coastal bluffs near Mukilteo, Washington

USGS Publications Warehouse

Smith, Joel B.; Baum, Rex L.; Mirus, Benjamin B.; Michel, Abigail R.; Stark, Ben

2017-08-31

A hydrologic monitoring network was installed to investigate landslide hazards affecting the railway corridor along the eastern shore of Puget Sound between Seattle and Everett, near Mukilteo, Washington. During the summer of 2015, the U.S. Geological Survey installed monitoring equipment at four sites equipped with instrumentation to measure rainfall and air temperature every 15 minutes. Two of the four sites are installed on contrasting coastal bluffs, one landslide scarred and one vegetated. At these two sites, in addition to rainfall and air temperature, volumetric water content, pore pressure, soil suction, soil temperature, and barometric pressure were measured every 15 minutes. The instrumentation was designed to supplement landslide-rainfall thresholds developed by the U.S. Geological Survey with a long-term goal of advancing the understanding of the relationship between landslide potential and hydrologic forcing along the coastal bluffs. Additionally, the system was designed to function as a prototype monitoring system to evaluate criteria for site selection, instrument selection, and placement of instruments. The purpose of this report is to describe the monitoring system, present the data collected since installation, and describe significant events represented within the dataset, which is published as a separate data release. The findings provide insight for building and configuring larger, modular monitoring networks.

1990 Environmental monitoring report, Tonopah Test Range, Tonopah, Nevada

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

Hwang, A.; Phelan, J.; Wolff, T.

1991-05-01

There is no routine radioactive emission from Sandia National Laboratories, Tonopah Test Range (SNL, TTR). However, based on the types of test activities such as air drops, gun firings, ground- launched rockets, air-launched rockets, and other explosive tests, possibilities exist that small amounts of depleted uranium (DU) (as part of weapon components) may be released to the air or to the ground because of unusual circumstances (failures) during testing. Four major monitoring programs were used in 1990 to assess radiological impact on the public. The EPA Air Surveillance Network (ASN) found that the only gamma ({gamma}) emitting radionuclide on themore » prefilters was beryllium-7 ({sup 7}Be), a naturally-occurring spallation product formed by the interaction of cosmic radiation with atmospheric oxygen and nitrogen. The weighted average results were consistent with the area background concentrations. The EPA Thermoluminescent Dosimetry (TLD) Network and Pressurized Ion Chamber (PIC) reported normal results. In the EPA Long-Term Hydrological Monitoring Program (LTHMP), analytical results for tritium ({sup 3}H) in well water were reported and were well below DOE-derived concentration guides (DCGs). In the Reynolds Electrical and Engineering Company (REECo) Drinking Water Sampling Program, analytical results for {sup 3}H, gross alpha ({alpha}), beta ({beta}), and {gamma} scan, strontium-90 ({sup 90}Sr) and plutonium-239 ({sup 239}Pu) were within the EPA's primary drinking water standards. 29 refs., 5 figs., 15 tabs.« less

78 FR 57631 - Information Collection Request Submitted to OMB for Review and Approval; Comment Request; Ambient...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-19

..., tribal entities, environmental groups, academic institutions, industrial groups) use the ambient air... System (AQS) database. Quality assurance/quality control records and monitoring network documentation are...

Unattended wireless proximity sensor networks for counterterrorism, force protection, littoral environments, PHM, and tamper monitoring ground applications

NASA Astrophysics Data System (ADS)

Forcier, Bob

2003-09-01

This paper describes a digital-ultrasonic ground network, which forms an unique "unattended mote sensor system" for monitoring the environment, personnel, facilities, vehicles, power generation systems or aircraft in Counter-Terrorism, Force Protection, Prognostic Health Monitoring (PHM) and other ground applications. Unattended wireless smart sensor/tags continuously monitor the environment and provide alerts upon changes or disruptions to the environment. These wireless smart sensor/tags are networked utilizing ultrasonic wireless motes, hybrid RF/Ultrasonic Network Nodes and Base Stations. The network is monitored continuously with a 24/7 remote and secure monitoring system. This system utilizes physical objects such as a vehicle"s structure or a building to provide the media for two way secure communication of key metrics and sensor data and eliminates the "blind spots" that are common in RF solutions because of structural elements of buildings, etc. The digital-ultrasonic sensors have networking capability and a 32-bit identifier, which provide a platform for a robust data acquisition (DAQ) for a large amount of sensors. In addition, the network applies a unique "signature" of the environment by comparing sensor-to-sensor data to pick up on minute changes, which would signal an invasion of unknown elements or signal a potential tampering in equipment or facilities. The system accommodates satellite and other secure network uplinks in either RF or UWB protocols. The wireless sensors can be dispersed by ground or air maneuvers. In addition, the sensors can be incorporated into the structure or surfaces of vehicles, buildings, or clothing of field personnel.

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...

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.

Historical Prediction Modeling Approach for Estimating Long-Term Concentrations of PM2.5 in Cohort Studies before the 1999 Implementation of Widespread Monitoring.

PubMed

Kim, Sun-Young; Olives, Casey; Sheppard, Lianne; Sampson, Paul D; Larson, Timothy V; Keller, Joshua P; Kaufman, Joel D

2017-01-01

Recent cohort studies have used exposure prediction models to estimate the association between long-term residential concentrations of fine particulate matter (PM2.5) and health. Because these prediction models rely on PM2.5 monitoring data, predictions for times before extensive spatial monitoring present a challenge to understanding long-term exposure effects. The U.S. Environmental Protection Agency (EPA) Federal Reference Method (FRM) network for PM2.5 was established in 1999. We evaluated a novel statistical approach to produce high-quality exposure predictions from 1980 through 2010 in the continental United States for epidemiological applications. We developed spatio-temporal prediction models using geographic predictors and annual average PM2.5 data from 1999 through 2010 from the FRM and the Interagency Monitoring of Protected Visual Environments (IMPROVE) networks. Temporal trends before 1999 were estimated by using a) extrapolation based on PM2.5 data in FRM/IMPROVE, b) PM2.5 sulfate data in the Clean Air Status and Trends Network, and c) visibility data across the Weather Bureau Army Navy network. We validated the models using PM2.5 data collected before 1999 from IMPROVE, California Air Resources Board dichotomous sampler monitoring (CARB dichot), the Children's Health Study (CHS), and the Inhalable Particulate Network (IPN). In our validation using pre-1999 data, the prediction model performed well across three trend estimation approaches when validated using IMPROVE and CHS data (R2 = 0.84-0.91) with lower R2 values in early years. Model performance using CARB dichot and IPN data was worse (R2 = 0.00-0.85) most likely because of fewer monitoring sites and inconsistent sampling methods. Our prediction modeling approach will allow health effects estimation associated with long-term exposures to PM2.5 over extended time periods ≤ 30 years. Citation: Kim SY, Olives C, Sheppard L, Sampson PD, Larson TV, Keller JP, Kaufman JD. 2017. Historical prediction modeling approach for estimating long-term concentrations of PM2.5 in cohort studies before the 1999 implementation of widespread monitoring. Environ Health Perspect 125:38-46; http://dx.doi.org/10.1289/EHP131.

A Modular IoT Platform for Real-Time Indoor Air Quality Monitoring

PubMed Central

Abdaoui, Abderrazak; Ahmad, Sabbir H.M.; Touati, Farid; Kadri, Abdullah

2018-01-01

The impact of air quality on health and on life comfort is well established. In many societies, vulnerable elderly and young populations spend most of their time indoors. Therefore, indoor air quality monitoring (IAQM) is of great importance to human health. Engineers and researchers are increasingly focusing their efforts on the design of real-time IAQM systems using wireless sensor networks. This paper presents an end-to-end IAQM system enabling measurement of CO2, CO, SO2, NO2, O3, Cl2, ambient temperature, and relative humidity. In IAQM systems, remote users usually use a local gateway to connect wireless sensor nodes in a given monitoring site to the external world for ubiquitous access of data. In this work, the role of the gateway in processing collected air quality data and its reliable dissemination to end-users through a web-server is emphasized. A mechanism for the backup and the restoration of the collected data in the case of Internet outage is presented. The system is adapted to an open-source Internet-of-Things (IoT) web-server platform, called Emoncms, for live monitoring and long-term storage of the collected IAQM data. A modular IAQM architecture is adopted, which results in a smart scalable system that allows seamless integration of various sensing technologies, wireless sensor networks (WSNs) and smart mobile standards. The paper gives full hardware and software details of the proposed solution. Sample IAQM results collected in various locations are also presented to demonstrate the abilities of the system. PMID:29443893

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%).

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

Determining Usability Versus Cost and Yields of a Regional Transport

NASA Technical Reports Server (NTRS)

Gvozdenovic, Slobodan

1999-01-01

Regional transports are designed to operate on air networks having the basic characteristics of short trip distances and low density passengers/cargo, i.e. small numbers of passengers per flight. Regional transports passenger capacity is from 10 to 100 seats and operate on routes from 350 to 1000 nautical miles (nm). In order to meet passenger requirements providing low fares and high or required number of frequencies, airlines must constantly monitor operational costs and keep them low. It is obvious that costs of operating aircraft must be lower than yield obtained by transporting passengers and cargo. The requirement to achieve favorable yield/cost ratio must provide the answer to the question of which aircraft will best meet a specific air network (Simpson, 1972). An air network is defined by the number of services, the trip distance of each service, and the number of flights (frequencies) per day and week.

Wearable sensors for health monitoring

NASA Astrophysics Data System (ADS)

Suciu, George; Butca, Cristina; Ochian, Adelina; Halunga, Simona

2015-02-01

In this paper we describe several wearable sensors, designed for monitoring the health condition of the patients, based on an experimental model. Wearable sensors enable long-term continuous physiological monitoring, which is important for the treatment and management of many chronic illnesses, neurological disorders, and mental health issues. The system is based on a wearable sensors network, which is connected to a computer or smartphone. The wearable sensor network integrates several wearable sensors that can measure different parameters such as body temperature, heart rate and carbon monoxide quantity from the air. After the portable sensors measuring parameter values, they are transmitted by microprocessor through the Bluetooth to the application developed on computer or smartphone, to be interpreted.

Networking of Icelandic Earth Infrastructures - Natural laboratories and Volcano Supersites

NASA Astrophysics Data System (ADS)

Vogfjörd, K. S.; Sigmundsson, F.; Hjaltadóttir, S.; Björnsson, H.; Arason, Ø.; Hreinsdóttir, S.; Kjartansson, E.; Sigbjörnsson, R.; Halldórsson, B.; Valsson, G.

2012-04-01

The back-bone of Icelandic geoscientific research infrastructure is the country's permanent monitoring networks, which have been built up to monitor seismic and volcanic hazard and deformation of the Earth's surface. The networks are mainly focussed around the plate boundary in Iceland, particularly the two seismic zones, where earthquakes of up to M7.3 have occurred in centuries past, and the rift zones with over 30 active volcanic systems where a large number of powerful eruptions have occurred, including highly explosive ones. The main observational systems are seismic, strong motion, GPS and bore-hole strain networks, with the addition of more recent systems like hydrological stations, permanent and portable radars, ash-particle counters and gas monitoring systems. Most of the networks are owned by a handful of Icelandic institutions, but some are operated in collaboration with international institutions and universities. The networks have been in operation for years to decades and have recorded large volumes of research quality data. The main Icelandic infrastructures will be networked in the European Plate Observing System (EPOS). The plate boundary in the South Iceland seismic zone (SISZ) with its book-shelf tectonics and repeating major earthquakes sequences of up to M7 events, has the potential to be defined a natural laboratory within EPOS. Work towards integrating multidisciplinary data and technologies from the monitoring infrastructures in the SISZ with other fault regions has started in the FP7 project NERA, under the heading of Networking of Near-Fault Observatories. The purpose is to make research-quality data from near-fault observatories available to the research community, as well as to promote transfer of knowledge and techical know-how between the different observatories of Europe, in order to create a network of fault-monitoring networks. The seismic and strong-motion systems in the SISZ are also, to some degree, being networked nationally to strengthen their early warning capabilities. In response to the far-reaching dispersion of ash from the 2010 Eyjafjallajökull eruption and subsequent disturbance to European air-space, the instrumentation of the Icelandic volcano observatory was greatly improved in number and capability to better monitor sub-surface volcanic processes as well as the air-borne products of eruptions. This infrastructure will also be networked with other European volcano observatories in EPOS. Finally the Icelandic EPOS team, together with other European collaborators, has responded to an FP7 call for the establishment of an Icelandic volcano supersite, where land- and space-based data will be made available to researchers and hazard managers, in line with the implementation plan of the GEO. The focus of the Icelandic volcano supersite are the active volcanoes in Iceland's Eastern volcanic zone.

Atmospheric Carbon Monoxide Mixing Ratios NOAA Climate Monitoring and Diagnostics Laboratory Cooperative Air Sampling Network (1988-1993) (DB1011)

DOE Data Explorer

Novelli, P. C.; Masarie, K. A.

1994-01-01

Individual site files provide CO mixing ratios in parts per billion (ppb) (ppb = parts in 109 by mole fraction) based on measurements from the NOAA/CMDL Cooperative Air Sampling Network beginning 1988. Data are provided through June 1993 for stations at which the first sample was collected before July 1991. All samples were analyzed for CO at the NOAA/CMDL laboratory in Boulder by gas chromatography with mercuric oxide reduction detection, and all measurements are referenced to the CMDL CO scale (Novelli et al., 1991, Novelli et al., 1994).

Wireless Sensor Platform for Cultural Heritage Monitoring and Modeling System

PubMed Central

Bermudez, Sergio A.; Schrott, Alejandro G.; Tsukada, Masahiko; Kargere, Lucretia; Marianno, Fernando; Hamann, Hendrik F.; López, Vanessa; Leona, Marco

2017-01-01

Results from three years of continuous monitoring of environmental conditions using a wireless sensor platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, are presented. The platform comprises more than 200 sensors that were distributed in five galleries to assess temperature and air flow and to quantify microclimate changes using physics-based and statistical models. The wireless sensor network data shows a very stable environment within the galleries, while the dense monitoring enables localized monitoring of subtle changes in air quality trends and impact of visitors on the microclimate conditions. The high spatial and temporal resolution data serves as a baseline study to understand the impact of visitors and building operations on the long-term preservation of art objects. PMID:28858223

Wireless Sensor Platform for Cultural Heritage Monitoring and Modeling System.

PubMed

Klein, Levente J; Bermudez, Sergio A; Schrott, Alejandro G; Tsukada, Masahiko; Dionisi-Vici, Paolo; Kargere, Lucretia; Marianno, Fernando; Hamann, Hendrik F; López, Vanessa; Leona, Marco

2017-08-31

Results from three years of continuous monitoring of environmental conditions using a wireless sensor platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, are presented. The platform comprises more than 200 sensors that were distributed in five galleries to assess temperature and air flow and to quantify microclimate changes using physics-based and statistical models. The wireless sensor network data shows a very stable environment within the galleries, while the dense monitoring enables localized monitoring of subtle changes in air quality trends and impact of visitors on the microclimate conditions. The high spatial and temporal resolution data serves as a baseline study to understand the impact of visitors and building operations on the long-term preservation of art objects.

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.

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.

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.

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.

Air-Sense: indoor environment monitoring evaluation system based on ZigBee network

NASA Astrophysics Data System (ADS)

Huang, Yang; Hu, Liang; Yang, Disheng; Liu, Hengchang

2017-08-01

In the modern life, people spend most of their time indoors. However, indoor environmental quality problems have always been affecting people’s social activities. In general, indoor environmental quality is also related to our indoor activities. Since most of the organic irritants and volatile gases are colorless, odorless and too tiny to be seen, because we have been unconsciously overlooked indoor environment quality. Consequently, our body suffer a great health problem. In this work, we propose Air-Sense system which utilizes the platform of ZigBee Network to collect and detect the real-time indoor environment quality. What’s more, Air-Sense system can also provide data analysis, and visualizing the results of the indoor environment to the user.

The meteorological monitoring system for the Kennedy Space Center/Cape Canaveral Air Station

NASA Technical Reports Server (NTRS)

Dianic, Allan V.

1994-01-01

The Kennedy Space Center (KSC) and Cape Canaveral Air Station (CCAS) are involved in many weather-sensitive operations. Manned and unmanned vehicle launches, which occur several times each year, are obvious example of operations whose success and safety are dependent upon favorable meteorological conditions. Other operations involving NASA, Air Force, and contractor personnel, including daily operations to maintain facilities, refurbish launch structures, prepare vehicles for launch, and handle hazardous materials, are less publicized but are no less weather-sensitive. The Meteorological Monitoring System (MMS) is a computer network which acquires, processes, disseminates, and monitors near real-time and forecast meteorological information to assist operational personnel and weather forecasters with the task of minimizing the risk to personnel, materials, and the surrounding population. CLIPS has been integrated into the MMS to provide quality control analysis and data monitoring. This paper describes aspects of the MMS relevant to CLIPS including requirements, actual implementation details, and results of performance testing.

Remote Monitoring of Post-eruption Volcano Environment Based-On Wireless Sensor Network (WSN): The Mount Sinabung Case

NASA Astrophysics Data System (ADS)

Soeharwinto; Sinulingga, Emerson; Siregar, Baihaqi

2017-01-01

An accurate information can be useful for authorities to make good policies for preventive and mitigation after volcano eruption disaster. Monitoring of environmental parameters of post-eruption volcano provides an important information for authorities. Such monitoring system can be develop using the Wireless Network Sensor technology. Many application has been developed using the Wireless Sensor Network technology, such as floods early warning system, sun radiation mapping, and watershed monitoring. This paper describes the implementation of a remote environment monitoring system of mount Sinabung post-eruption. The system monitor three environmental parameters: soil condition, water quality and air quality (outdoor). Motes equipped with proper sensors, as components of the monitoring system placed in sample locations. The measured value from the sensors periodically sends to data server using 3G/GPRS communication module. The data can be downloaded by the user for further analysis.The measurement and data analysis results generally indicate that the environmental parameters in the range of normal/standard condition. The sample locations are safe for living and suitable for cultivation, but awareness is strictly required due to the uncertainty of Sinabung status.

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.

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...

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.

77 FR 45965 - Determination of Attainment for the Paul Spur/Douglas PM10

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-02

... plans, and based on the findings of our technical system audit report, ADEQ's monitoring network meets... to EPA's Air Quality System (AQS) database as quality- assured. Next, we reviewed the ambient PM 10...

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.

Design of a monitoring network over France in case of a radiological accidental release

NASA Astrophysics Data System (ADS)

Abida, Rachid; Bocquet, Marc; Vercauteren, Nikki; Isnard, Olivier

The Institute of Radiation Protection and Nuclear Safety (France) is planning the set-up of an automatic nuclear aerosol monitoring network over the French territory. Each of the stations will be able to automatically sample the air aerosol content and provide activity concentration measurements on several radionuclides. This should help monitor the French and neighbouring countries nuclear power plants set. It would help evaluate the impact of a radiological incident occurring at one of these nuclear facilities. This paper is devoted to the spatial design of such a network. Here, any potential network is judged on its ability to extrapolate activity concentrations measured on the network stations over the whole domain. The performance of a network is quantitatively assessed through a cost function that measures the discrepancy between the extrapolation and the true concentration fields. These true fields are obtained through the computation of a database of dispersion accidents over one year of meteorology and originating from 20 French nuclear sites. A close to optimal network is then looked for using a simulated annealing optimisation. The results emphasise the importance of the cost function in the design of a network aimed at monitoring an accidental dispersion. Several choices of norm used in the cost function are studied and give way to different designs. The influence of the number of stations is discussed. A comparison with a purely geometric approach which does not involve simulations with a chemistry-transport model is performed.

Comparison for Air Kerma from Radiation Protection Gamma-ray Beams with Brazilian Network - 2016/2017

NASA Astrophysics Data System (ADS)

Cabral, TS; da Silva, CNM; Potiens, MPA; Soares, CMA; Silveira, RR; Khoury, H.; Saito, V.; Fernandes, E.; Cardoso, WF; de Oliveira, HPS; Pires, MA; de Amorim, AS; Balthar, M.

2018-03-01

The results of the comparison involving 9 laboratories in Brazil are reported. The measured quantity was the air kerma in 137Cs and 60Co, at the level of radioprotection. The comparison was conducted by the National Laboratory Metrology of Ionizing Radiation (LNMRI/IRD) from October 2016 to March 2017. The largest deviation between the calibration coefficients was 0.8% for 137Cs and 0.7% for 60Co. This proficiency exercise proved the technical capacity of the Brazilian calibration network in radiation monitors and the results were used by some in the implementation of the standard ISO/IEC 17025.

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.

THE US EPA'S SUPERSITES PROGRAM

EPA Science Inventory

The PM2.5 monitoring program is dominated by gravimetric measurements (over 1000 mass samplers nationwide) specific for mass, where the primary objective is comparisons with the PMZ 5 National Ambient Air Quality Standards (NAAQS). The other major component of the network is th...

MONITORING ENVIRONMENTAL RADIATION IN THE UNITED STATES(RADNET)

EPA Science Inventory

Operate a national network of sampling stations that regularly submit environmental samples of air, precipitation and drinking water; analyze all samples for radiation at the laboratory; and report data to the public and the radiation protection community. During national radiat...

Monitoring Climate Variability and Change in Northern Alaska: Updates to the U.S. Geological Survey (USGS) Climate and Permafrost Monitoring Network

NASA Astrophysics Data System (ADS)

Urban, F. E.; Clow, G. D.; Meares, D. C.

2004-12-01

Observations of long-term climate and surficial geological processes are sparse in most of the Arctic, despite the fact that this region is highly sensitive to climate change. Instrumental networks that monitor the interplay of climatic variability and geological/cryospheric processes are a necessity for documenting and understanding climate change. Improvements to the spatial coverage and temporal scale of Arctic climate data are in progress. The USGS, in collaboration with The Bureau of Land Management (BLM) and The Fish and Wildlife Service (FWS) currently maintains two types of monitoring networks in northern Alaska: (1) A 15 site network of continuously operating active-layer and climate monitoring stations, and (2) a 21 element array of deep bore-holes in which the thermal state of deep permafrost is monitored. Here, we focus on the USGS Alaska Active Layer and Climate Monitoring Network (AK-CLIM). These 15 stations are deployed in longitudinal transects that span Alaska north of the Brooks Range, (11 in The National Petroleum Reserve Alaska, (NPRA), and 4 in The Arctic National Wildlife Refuge (ANWR)). An informative overview and update of the USGS AK-CLIM network is presented, including insight to current data, processing and analysis software, and plans for data telemetry. Data collection began in 1998 and parameters currently measured include air temperature, soil temperatures (5-120 cm), snow depth, incoming and reflected short-wave radiation, soil moisture (15 cm), wind speed and direction. Custom processing and analysis software has been written that calculates additional parameters such as active layer thaw depth, thawing-degree-days, albedo, cloudiness, and duration of seasonal snow cover. Data from selected AK-CLIM stations are now temporally sufficient to begin identifying trends, anomalies, and inter-annual variability in the climate of northern Alaska.

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....

Respirable particulate monitoring with remote sensors. (Public health ecology: Air pollution)

NASA Technical Reports Server (NTRS)

Severs, R. K.

1974-01-01

The feasibility of monitoring atmospheric aerosols in the respirable range from air or space platforms was studied. Secondary reflectance targets were located in the industrial area and near Galveston Bay. Multichannel remote sensor data were utilized to calculate the aerosol extinction coefficient and thus determine the aerosol size distribution. Houston Texas air sampling network high volume data were utilized to generate computer isopleth maps of suspended particulates and to establish the mass loading of the atmosphere. In addition, a five channel nephelometer and a multistage particulate air sampler were used to collect data. The extinction coefficient determined from remote sensor data proved more representative of wide areal phenomena than that calculated from on site measurements. It was also demonstrated that a significant reduction in the standard deviation of the extinction coefficient could be achieved by reducing the bandwidths used in remote sensor.

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.

Source attribution and quantification of benzene event emissions in a Houston ship channel community based on real-time mobile monitoring of ambient air.

PubMed

Olaguer, Eduardo P; Erickson, Matthew H; Wijesinghe, Asanga; Neish, Bradley S

2016-02-01

A mobile laboratory equipped with a proton transfer reaction mass spectrometer (PTR-MS) operated in Galena Park, Texas, near the Houston Ship Channel during the Benzene and other Toxics Exposure Study (BEE-TEX). The mobile laboratory measured transient peaks of benzene of up to 37 ppbv in the afternoon and evening of February 19, 2015. Plume reconstruction and source attribution were performed using the four-dimensional (4D) variational data assimilation technique and a three-dimensional (3D) micro-scale forward and adjoint air quality model based on mobile PTR-MS data and nearby stationary wind measurements at the Galena Park Continuous Air Monitoring Station (CAMS). The results of inverse modeling indicate that significant pipeline emissions of benzene may at least partly explain the ambient concentration peaks observed in Galena Park during BEE-TEX. Total pipeline emissions of benzene inferred within the 16-km(2) model domain exceeded point source emissions by roughly a factor of 2 during the observational episode. Besides pipeline leaks, the model also inferred significant benzene emissions from marine, railcar, and tank truck loading/unloading facilities, consistent with the presence of a tanker and barges in the Kinder Morgan port terminal during the afternoon and evening of February 19. Total domain emissions of benzene exceeded corresponding 2011 National Emissions Inventory (NEI) estimates by a factor of 2-6. Port operations involving petrochemicals may significantly increase emissions of air toxics from the transfer and storage of materials. Pipeline leaks, in particular, can lead to sporadic emissions greater than in emission inventories, resulting in higher ambient concentrations than are sampled by the existing monitoring network. The use of updated methods for ambient monitoring and source attribution in real time should be encouraged as an alternative to expanding the conventional monitoring network.

Historical Prediction Modeling Approach for Estimating Long-Term Concentrations of PM2.5 in Cohort Studies before the 1999 Implementation of Widespread Monitoring

PubMed Central

Kim, Sun-Young; Olives, Casey; Sheppard, Lianne; Sampson, Paul D.; Larson, Timothy V.; Keller, Joshua P.; Kaufman, Joel D.

2016-01-01

Introduction: Recent cohort studies have used exposure prediction models to estimate the association between long-term residential concentrations of fine particulate matter (PM2.5) and health. Because these prediction models rely on PM2.5 monitoring data, predictions for times before extensive spatial monitoring present a challenge to understanding long-term exposure effects. The U.S. Environmental Protection Agency (EPA) Federal Reference Method (FRM) network for PM2.5 was established in 1999. Objectives: We evaluated a novel statistical approach to produce high-quality exposure predictions from 1980 through 2010 in the continental United States for epidemiological applications. Methods: We developed spatio-temporal prediction models using geographic predictors and annual average PM2.5 data from 1999 through 2010 from the FRM and the Interagency Monitoring of Protected Visual Environments (IMPROVE) networks. Temporal trends before 1999 were estimated by using a) extrapolation based on PM2.5 data in FRM/IMPROVE, b) PM2.5 sulfate data in the Clean Air Status and Trends Network, and c) visibility data across the Weather Bureau Army Navy network. We validated the models using PM2.5 data collected before 1999 from IMPROVE, California Air Resources Board dichotomous sampler monitoring (CARB dichot), the Children’s Health Study (CHS), and the Inhalable Particulate Network (IPN). Results: In our validation using pre-1999 data, the prediction model performed well across three trend estimation approaches when validated using IMPROVE and CHS data (R2 = 0.84–0.91) with lower R2 values in early years. Model performance using CARB dichot and IPN data was worse (R2 = 0.00–0.85) most likely because of fewer monitoring sites and inconsistent sampling methods. Conclusions: Our prediction modeling approach will allow health effects estimation associated with long-term exposures to PM2.5 over extended time periods ≤ 30 years. Citation: Kim SY, Olives C, Sheppard L, Sampson PD, Larson TV, Keller JP, Kaufman JD. 2017. Historical prediction modeling approach for estimating long-term concentrations of PM2.5 in cohort studies before the 1999 implementation of widespread monitoring. Environ Health Perspect 125:38–46; http://dx.doi.org/10.1289/EHP131 PMID:27340825

GCOS reference upper air network (GRUAN): Steps towards assuring future climate records

NASA Astrophysics Data System (ADS)

Thorne, P. W.; Vömel, H.; Bodeker, G.; Sommer, M.; Apituley, A.; Berger, F.; Bojinski, S.; Braathen, G.; Calpini, B.; Demoz, B.; Diamond, H. J.; Dykema, J.; Fassò, A.; Fujiwara, M.; Gardiner, T.; Hurst, D.; Leblanc, T.; Madonna, F.; Merlone, A.; Mikalsen, A.; Miller, C. D.; Reale, T.; Rannat, K.; Richter, C.; Seidel, D. J.; Shiotani, M.; Sisterson, D.; Tan, D. G. H.; Vose, R. S.; Voyles, J.; Wang, J.; Whiteman, D. N.; Williams, S.

2013-09-01

The observational climate record is a cornerstone of our scientific understanding of climate changes and their potential causes. Existing observing networks have been designed largely in support of operational weather forecasting and continue to be run in this mode. Coverage and timeliness are often higher priorities than absolute traceability and accuracy. Changes in instrumentation used in the observing system, as well as in operating procedures, are frequent, rarely adequately documented and their impacts poorly quantified. For monitoring changes in upper-air climate, which is achieved through in-situ soundings and more recently satellites and ground-based remote sensing, the net result has been trend uncertainties as large as, or larger than, the expected emergent signals of climate change. This is more than simply academic with the tropospheric temperature trends issue having been the subject of intense debate, two international assessment reports and several US congressional hearings. For more than a decade the international climate science community has been calling for the instigation of a network of reference quality measurements to reduce uncertainty in our climate monitoring capabilities. This paper provides a brief history of GRUAN developments to date and outlines future plans. Such reference networks can only be achieved and maintained with strong continuing input from the global metrological community.

REVIEW OF THE RADNET AIR MONITORING NETWORK ...

EPA Pesticide Factsheets

RadNet, formerly known as ERAMS, has been operating since the 1970's, monitoring environmental radiation across the country, supporting responses to radiological emergencies, and providing important information on background levels of radiation in the environment. The original purpose of the system was to monitor fallout from weapons testing. Even though upgrades to and reconfiguration of the system have been planned for some time, the events of 9/11/01 gave impetus to a thorough upgrade of RadNet, primarily directed at providing more timely data and covering a larger portion of the nation's population. Moreover, the demands upon RadNet are now based upon homeland security support in addition to existing EPA monitoring responsibilities. Beginning in FY05 and continuing into FY13 up to135 near real-time air monitors will be put into operation across the country to provide decision making-data to EPA officials. Data will be transmitted from the monitors in all 50 states to a central database at the National Air and Radiation Environmental Laboratory (NAREL) in Montgomery, Alabama. The data will then be assessed and verified and made available to federal and state officials and, eventually, the public. A data flow model is being constructed to provide the most effective and efficient use of verified data obtained from the new radNet system The objective of the near-real time air monitoring component of RadNet is to provide verified decision-making data to fed

A framework for visualization of battlefield network behavior

NASA Astrophysics Data System (ADS)

Perzov, Yury; Yurcik, William

2006-05-01

An extensible network simulation application was developed to study wireless battlefield communications. The application monitors node mobility and depicts broadcast and unicast traffic as expanding rings and directed links. The network simulation was specially designed to support fault injection to show the impact of air strikes on disabling nodes. The application takes standard ns-2 trace files as an input and provides for performance data output in different graphical forms (histograms and x/y plots). Network visualization via animation of simulation output can be saved in AVI format that may serve as a basis for a real-time battlefield awareness system.

Regulatory Impact Analysis (RIA) for the Proposed Revisions to the Sulfur Dioxide National Ambient Air Quality Standards (NAAQS)

EPA Pesticide Factsheets

This Regulatory Impact Analysis (RIA) provides estimates of the incremental costs and monetized human health benefits of attaining a revised short‐term Sulfur Dioxide (SO2) NAAQS within the current monitoring network.

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...

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.

Transient states of air parameters after a stoppage and re-start of the main fan / Stany przejściowe parametrów powietrza po postoju i załączeniu wentylatora głównego

NASA Astrophysics Data System (ADS)

Wasilewski, Stanisław

2012-12-01

A stoppage of the main ventilation fan constitutes a disturbance of ventilation conditions of a deepmine and its effects can cause serious hazards by generating transient states of air and gas flow. Main ventilation fans are the basic deep-mine facilities; therefore, under mining regulations it is only allowed to stop them with the consent and under the conditions specified by the mine maintenance manager. The stoppage of the main ventilation fan may be accompanied by transient air parameters, including the air pressure and flow patterns. There is even the likelihood of reversing the direction of air flow, which, in case of methane mines, can pose a major hazard, particularly in sections of the mine with fire fields or large goaf areas. At the same time, stoppages of deep-mine main ventilation fans create interesting research conditions, which if conducted under the supervision of the monitoring systems, can provide much information about the transient processes of pressure, air and gas flow in underground workings. This article is a discussion of air parameter observations in mine workings made as part of such experiments. It also presents the procedure of the experiments, conducted in three mines. They involved the observation of transient processes of mine air parameters, and most interestingly, the recording of pressure and air and gas flow in the workings of the mine ventilation networks by mine monitoring systems and using specialist recording instruments. In mining practice, both in Poland and elsewhere, software tools and computer modelling methods are used to try and reproduce the conditions prior to and during disasters based on the existing network model and monitoring system data. The use of these tools to simulate the alternatives of combating and liquidation of the gas-fire hazard after its occurrence is an important issue. Measurement data collected during the experiments provides interesting research material for the verification and validation of the software tools used for the simulation of processes occurring in deep-mine ventilation systems.

How to most effectively expand the global surface ozone observing network

NASA Astrophysics Data System (ADS)

Sofen, E. D.; Bowdalo, D.; Evans, M. J.

2016-02-01

Surface ozone observations with modern instrumentation have been made around the world for more than 40 years. Some of these observations have been made as one-off activities with short-term, specific science objectives and some have been made as part of wider networks which have provided a foundational infrastructure of data collection, calibration, quality control, and dissemination. These observations provide a fundamental underpinning to our understanding of tropospheric chemistry, air quality policy, atmosphere-biosphere interactions, etc. brought together eight of these networks to provide a single data set of surface ozone observations. We investigate how representative this combined data set is of global surface ozone using the output from a global atmospheric chemistry model. We estimate that on an area basis, 25 % of the globe is observed (34 % land, 21 % ocean). Whereas Europe and North America have almost complete coverage, other continents, Africa, South America, Australia, and Asia (12-17 %) show significant gaps. Antarctica is surprisingly well observed (78 %). Little monitoring occurs over the oceans, with the tropical and southern oceans particularly poorly represented. The surface ozone over key biomes such as tropical forests and savanna is almost completely unmonitored. A chemical cluster analysis suggests that a significant number of observations are made of polluted air masses, but cleaner air masses whether over the land or ocean (especially again in the tropics) are significantly under-observed. The current network is unlikely to see the impact of the El Niño-Southern Oscillation (ENSO) but may be capable of detecting other planetary-scale signals. Model assessment and validation activities are hampered by a lack of observations in regions where the models differ substantially, as is the ability to monitor likely changes in surface ozone over the next century. Using our methodology we are able to suggest new sites which would help to close the gap in our ability to measure global surface ozone. An additional 20 surface ozone monitoring sites (a 20 % increase in the World Meteorological Organization Global Atmosphere Watch (WMO GAW) ozone sites or a 1 % increase in the total background network) located on 10 islands and in 10 continental regions would almost double the area observed. The cost of this addition to the network is small compared to other expenditure on atmospheric composition research infrastructure and would provide a significant long-term benefit to our understanding of the composition of the atmosphere, information which will also be available for consideration by air quality control managers and policy makers.

Determining Usability Versus Cost and Yields of a Regional Transport

NASA Technical Reports Server (NTRS)

Gvozdenovic, Slobodan

1999-01-01

Regional transports are designed to operate on air networks having the basic characteristics of short trip distances and low density passengers/cargo, i.e. small numbers of passengers per flight. Regional transports passenger capacity is from 10 to 100 seats and operate on routes from 350 to 1000 nautical miles (nm). An air network operated by regional transports has the following characteristics: (1) connecting regional centers; (2) operating on low density passengers/cargo flow services with minimum two frequencies per day; (3) operating on high density passengers/cargo flow with more than two frequencies per day; and (4) operating supplemental services whenever market demands in order to help bigger capacity aircraft already operating the same routes. In order to meet passenger requirements providing low fares and high or required number of frequencies, airlines must constantly monitor operational costs and keep them low. It is obvious that costs of operating aircraft must be lower than yield obtained by transporting passengers and cargo. The requirement to achieve favorable yield/cost ratio must provide the answer to the question of which aircraft will best meet a specific air network. An air network is defined by the number of services, the trip distance of each service, and the number of flights (frequencies) per day and week.

Evaluation of multisectional and two-section particulate matter photochemical grid models in the Western United States.

PubMed

Morris, Ralph; Koo, Bonyoung; Yarwood, Greg

2005-11-01

Version 4.10s of the comprehensive air-quality model with extensions (CAMx) photochemical grid model has been developed, which includes two options for representing particulate matter (PM) size distribution: (1) a two-section representation that consists of fine (PM2.5) and coarse (PM2.5-10) modes that has no interactions between the sections and assumes all of the secondary PM is fine; and (2) a multisectional representation that divides the PM size distribution into N sections (e.g., N = 10) and simulates the mass transfer between sections because of coagulation, accumulation, evaporation, and other processes. The model was applied to Southern California using the two-section and multisection representation of PM size distribution, and we found that allowing secondary PM to grow into the coarse mode had a substantial effect on PM concentration estimates. CAMx was then applied to the Western United States for the 1996 annual period with a 36-km grid resolution using both the two-section and multisection PM representation. The Community Multiscale Air Quality (CMAQ) and Regional Modeling for Aerosol and Deposition (REMSAD) models were also applied to the 1996 annual period. Similar model performance was exhibited by the four models across the Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network monitoring networks. All four of the models exhibited fairly low annual bias for secondary PM sulfate and nitrate but with a winter overestimation and summer underestimation bias. The CAMx multisectional model estimated that coarse mode secondary sulfate and nitrate typically contribute <10% of the total sulfate and nitrate when averaged across the more rural IMPROVE monitoring network.

Why a Network Energy Monitoring and Control System?

DTIC Science & Technology

1985-01-01

years to complete as they were modified to work with existing, frequently very old, buildings. The benefits derived from those systems that did work were...or groups of workstations, then certain of the occupants could be tasked to turn off their respective lighting. The advantage is the increased...units. Duty Cycle (Strategy J) This strategy takes advantage of the oversizing of the air handling unit. The air handling unit is sized for a peak load

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.

Position estimation of transceivers in communication networks

DOEpatents

Kent, Claudia A [Pleasanton, CA; Dowla, Farid [Castro Valley, CA

2008-06-03

This invention provides a system and method using wireless communication interfaces coupled with statistical processing of time-of-flight data to locate by position estimation unknown wireless receivers. Such an invention can be applied in sensor network applications, such as environmental monitoring of water in the soil or chemicals in the air where the position of the network nodes is deemed critical. Moreover, the present invention can be arranged to operate in areas where a Global Positioning System (GPS) is not available, such as inside buildings, caves, and tunnels.

Downsizing a long-term precipitation network: Using a quantitative approach to inform difficult decisions.

PubMed

Green, Mark B; Campbell, John L; Yanai, Ruth D; Bailey, Scott W; Bailey, Amey S; Grant, Nicholas; Halm, Ian; Kelsey, Eric P; Rustad, Lindsey E

2018-01-01

The design of a precipitation monitoring network must balance the demand for accurate estimates with the resources needed to build and maintain the network. If there are changes in the objectives of the monitoring or the availability of resources, network designs should be adjusted. At the Hubbard Brook Experimental Forest in New Hampshire, USA, precipitation has been monitored with a network established in 1955 that has grown to 23 gauges distributed across nine small catchments. This high sampling intensity allowed us to simulate reduced sampling schemes and thereby evaluate the effect of decommissioning gauges on the quality of precipitation estimates. We considered all possible scenarios of sampling intensity for the catchments on the south-facing slope (2047 combinations) and the north-facing slope (4095 combinations), from the current scenario with 11 or 12 gauges to only 1 gauge remaining. Gauge scenarios differed by as much as 6.0% from the best estimate (based on all the gauges), depending on the catchment, but 95% of the scenarios gave estimates within 2% of the long-term average annual precipitation. The insensitivity of precipitation estimates and the catchment fluxes that depend on them under many reduced monitoring scenarios allowed us to base our reduction decision on other factors such as technician safety, the time required for monitoring, and co-location with other hydrometeorological measurements (snow, air temperature). At Hubbard Brook, precipitation gauges could be reduced from 23 to 10 with a change of <2% in the long-term precipitation estimates. The decision-making approach illustrated in this case study is applicable to the redesign of monitoring networks when reduction of effort seems warranted.

Understanding sources of organic aerosol during CalNex-2010 using the CMAQ-VBS

EPA Science Inventory

Community Multiscale Air Quality (CMAQ) model simulations utilizing the traditional organic aerosol (OA) treatment (CMAQ-AE6) and a volatility basis set (VBS) treatment for OA (CMAQ-VBS) were evaluated against measurements collected at routine monitoring networks (Chemical Specia...

MARSnet: Mission-aware Autonomous Radar Sensor Network for Future Combat Systems

DTIC Science & Technology

2007-05-03

34Parameter estimation for 3-parameter log-logistic distribution (LLD3) by Porne ", Parameter estimation for 3-parameter log-logistic distribu- tion...section V we physical security, air traffic control, traffic monitoring, andvidefaconu s cribedy. video surveillance, industrial automation etc. Each

75 FR 54773 - Approval and Promulgation of Air Quality Implementation Plans; Minnesota; Carbon Monoxide (CO...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-09

.... Monitoring Network and Verification of Continued Attainment 4. Contingency Plan 5. Conformity Determination... Continued Attainment, Contingency Plan, and Conformity Determinations Under Limited Maintenance Plans. These.../Verification of Continued Attainment, Contingency Plan, and Conformity Determination Under Limited Maintenance...

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.

Real-Time Alpine Measurement System Using Wireless Sensor Networks

PubMed Central

2017-01-01

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra’s wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape. PMID:29120376

Real-Time Alpine Measurement System Using Wireless Sensor Networks.

PubMed

Malek, Sami A; Avanzi, Francesco; Brun-Laguna, Keoma; Maurer, Tessa; Oroza, Carlos A; Hartsough, Peter C; Watteyne, Thomas; Glaser, Steven D

2017-11-09

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra's wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km 2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape.

A Great Lakes atmospheric mercury monitoring network: evaluation and design

USGS Publications Warehouse

Risch, Martin R.; Kenski, Donna M.; ,; David, A.

2014-01-01

As many as 51 mercury (Hg) wet-deposition-monitoring sites from 4 networks were operated in 8 USA states and Ontario, Canada in the North American Great Lakes Region from 1996 to 2010. By 2013, 20 of those sites were no longer in operation and approximately half the geographic area of the Region was represented by a single Hg-monitoring site. In response, a Great Lakes Atmospheric Mercury Monitoring (GLAMM) network is needed as a framework for regional collaboration in Hg-deposition monitoring. The purpose of the GLAMM network is to detect changes in regional atmospheric Hg deposition related to changes in Hg emissions. An optimized design for the network was determined to be a minimum of 21 sites in a representative and approximately uniform geographic distribution. A majority of the active and historic Hg-monitoring sites in the Great Lakes Region are part of the National Atmospheric Deposition Program (NADP) Mercury Deposition Network (MDN) in North America and the GLAMM network is planned to be part of the MDN. To determine an optimized network design, active and historic Hg-monitoring sites in the Great Lakes Region were evaluated with a rating system of 21 factors that included characteristics of the monitoring locations and interpretations of Hg data. Monitoring sites were rated according to the number of Hg emissions sources and annual Hg emissions in a geographic polygon centered on each site. Hg-monitoring data from the sites were analyzed for long-term averages in weekly Hg concentrations in precipitation and weekly Hg-wet deposition, and on significant temporal trends in Hg concentrations and Hg deposition. A cluster analysis method was used to group sites with similar variability in their Hg data in order to identify sites that were unique for explaining Hg data variability in the Region. The network design included locations in protected natural areas, urban areas, Great Lakes watersheds, and in proximity to areas with a high density of annual Hg emissions and areas with high average weekly Hg wet deposition. In a statistical analysis, relatively strong, positive correlations in the wet deposition of Hg and sulfate were shown for co-located NADP Hg-monitoring and acid-rain monitoring sites in the Region. This finding indicated that efficiency in regional Hg monitoring can be improved by adding new Hg monitoring to existing NADP acid-rain monitoring sites. Implementation of the GLAMM network design will require Hg-wet-deposition monitoring to be: (a) continued at 12 MDN sites active in 2013 and (b) restarted or added at 9 NADP sites where it is absent in 2013. Ongoing discussions between the states in the Great Lakes Region, the Lake Michigan Air Directors Consortium (a regional planning entity), the NADP, the U.S. Environmental Protection Agency, and the U.S. Geological Survey are needed for coordinating the GLAMM network.

Multi-terminal remote monitoring and warning system using Micro Air Vehicle for dangerous environment

NASA Astrophysics Data System (ADS)

Yu, Yanan; Wang, Xiaoxun; He, Chengcheng; Lai, Chenlong; Liu, Yuanchao

2015-11-01

For overcoming the problems such as remote operation and dangerous tasks, multi-terminal remote monitoring and warning system based on STC89C52 Micro Control Unit and wireless communication technique was proposed. The system with MCU as its core adopted multiple sets of sensor device to monitor environment parameters of different locations, such as temperature, humidity, smoke other harmful gas concentration. Data information collected was transmitted remotely by wireless transceiver module, and then multi-channel data parameter was processed and displayed through serial communication protocol between the module and PC. The results of system could be checked in the form of web pages within a local network which plays a wireless monitoring and warning role. In a remote operation, four-rotor micro air vehicle which fixed airborne data acquisition device was utilized as a middleware between collecting terminal and PC to increase monitoring scope. Whole test system has characteristics of simple construction, convenience, real time ability and high reliability, which could meet the requirements of actual use.

Monitoring of heavy metal concentrations in home outdoor air using moss bags.

PubMed

Rivera, Marcela; Zechmeister, Harald; Medina-Ramón, Mercedes; Basagaña, Xavier; Foraster, Maria; Bouso, Laura; Moreno, Teresa; Solanas, Pascual; Ramos, Rafael; Köllensperger, Gunda; Deltell, Alexandre; Vizcaya, David; Künzli, Nino

2011-04-01

One monitoring station is insufficient to characterize the high spatial variation of traffic-related heavy metals within cities. We tested moss bags (Hylocomium splendens), deployed in a dense network, for the monitoring of metals in outdoor air and characterized metals' long-term spatial distribution and its determinants in Girona, Spain. Mosses were exposed outside 23 homes for two months; NO₂ was monitored for comparison. Metals were not highly correlated with NO₂ and showed higher spatial variation than NO₂. Regression models explained 61-85% of Cu, Cr, Mo, Pb, Sb, Sn, and Zn and 72% of NO₂ variability. Metals were strongly associated with the number of bus lines in the nearest street. Heavy metals are an alternative traffic-marker to NO₂ given their toxicological relevance, stronger association with local traffic and higher spatial variability. Monitoring heavy metals with mosses is appealing, particularly for long-term exposure assessment, as mosses can remain on site many months without maintenance. Copyright © 2010 Elsevier Ltd. All rights reserved.

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.

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.

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 Project: Lower Cost, Continuous Ambient Monitoring Methods

EPA Science Inventory

This is an extended abstract that will be part of the peer-reviewed proceedings of the AWMA annual meeting in 2015. The extended abstract covers preliminary results from the CAIRSENSE project, which involves testing low cost sensors at an NCore site in Atlanta, GA.

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 ...

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

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.

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.

Spatial and temporal air quality pattern recognition using environmetric techniques: a case study in Malaysia.

PubMed

Syed Abdul Mutalib, Sharifah Norsukhairin; Juahir, Hafizan; Azid, Azman; Mohd Sharif, Sharifah; Latif, Mohd Talib; Aris, Ahmad Zaharin; Zain, Sharifuddin M; Dominick, Doreena

2013-09-01

The objective of this study is to identify spatial and temporal patterns in the air quality at three selected Malaysian air monitoring stations based on an eleven-year database (January 2000-December 2010). Four statistical methods, Discriminant Analysis (DA), Hierarchical Agglomerative Cluster Analysis (HACA), Principal Component Analysis (PCA) and Artificial Neural Networks (ANNs), were selected to analyze the datasets of five air quality parameters, namely: SO2, NO2, O3, CO and particulate matter with a diameter size of below 10 μm (PM10). The three selected air monitoring stations share the characteristic of being located in highly urbanized areas and are surrounded by a number of industries. The DA results show that spatial characterizations allow successful discrimination between the three stations, while HACA shows the temporal pattern from the monthly and yearly factor analysis which correlates with severe haze episodes that have happened in this country at certain periods of time. The PCA results show that the major source of air pollution is mostly due to the combustion of fossil fuel in motor vehicles and industrial activities. The spatial pattern recognition (S-ANN) results show a better prediction performance in discriminating between the regions, with an excellent percentage of correct classification compared to DA. This study presents the necessity and usefulness of environmetric techniques for the interpretation of large datasets aiming to obtain better information about air quality patterns based on spatial and temporal characterizations at the selected air monitoring stations.

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.

A Novel Cloud-Based Service Robotics Application to Data Center Environmental Monitoring

PubMed Central

Russo, Ludovico Orlando; Rosa, Stefano; Maggiora, Marcello; Bona, Basilio

2016-01-01

This work presents a robotic application aimed at performing environmental monitoring in data centers. Due to the high energy density managed in data centers, environmental monitoring is crucial for controlling air temperature and humidity throughout the whole environment, in order to improve power efficiency, avoid hardware failures and maximize the life cycle of IT devices. State of the art solutions for data center monitoring are nowadays based on environmental sensor networks, which continuously collect temperature and humidity data. These solutions are still expensive and do not scale well in large environments. This paper presents an alternative to environmental sensor networks that relies on autonomous mobile robots equipped with environmental sensors. The robots are controlled by a centralized cloud robotics platform that enables autonomous navigation and provides a remote client user interface for system management. From the user point of view, our solution simulates an environmental sensor network. The system can easily be reconfigured in order to adapt to management requirements and changes in the layout of the data center. For this reason, it is called the virtual sensor network. This paper discusses the implementation choices with regards to the particular requirements of the application and presents and discusses data collected during a long-term experiment in a real scenario. PMID:27509505

A Fleet of Low-Cost Sensor Based Air Quality Monitors Is Used to Measure Carbon Dioxide and Carbon Monoxide in Two Settings: In the Ambient Environment to Explore the Regional-Scale Spatial Variability of These Compounds Via a Distributed Network, and in Homes to Investigate How Heating during Winter Months can Impact Indoor Air Quality.

NASA Astrophysics Data System (ADS)

Casey, J. G.; Hannigan, M.; Collier, A. M.; Coffey, E.; Piedrahita, R.

2016-12-01

Affordable, small, portable, quiet tools to measure atmospheric trace gases and air quality enable novel experimental design and new findings. Members of the Hannigan Lab at the University of Colorado in Boulder have been working over the last few years to integrate emerging affordable gas sensors into such an air quality monitor. Presented here are carbon monoxide (CO) and carbon dioxide (CO2) measurements from two field experiments that utilized these tools. In the first experiment, ten air quality monitors were located northeast of Boulder throughout the Denver Julesburg oil and gas basin. The Colorado Department of Health and Environment has several air quality monitoring sites in this broader region, each in an Urban center. One goal of the experiment was to determine whether or not significant spatial variability of EPA criteria pollutants like CO, exists on a sub-regulatory monitoring grid scale. Another goal of the experiment was to compare rural sampling locations with urban sites. The monitors collected continuous data (sampling every 15 seconds) at each location over the course of several months. Our sensor calibration procedures are presented along with our observations and an analysis of the spatial and temporal variability in CO and CO2. In the second experiment, we used eight of our air quality monitors to better understand how home heating fuel type can impact indoor air quality in two communities on the Navajo Nation. We sought to compare air quality in homes using one of four different fuels for heat (wood, wood plus coal, pellet, and gas). There are many factors that contribute to indoor air quality and the impact of an emission source, like a woodstove, within a home. Having multiple, easily deployable, air quality monitors allowed us to account for many of these factors. We sampled four homes at a time, aiming for one home from each of our fuel groups in each sampling period. We sampled inside and outside of each home for a period of 3-4 days. In this way, we hoped to account for possible weather and outdoor air quality biases. CO and CO2 were measured and are put into context with acceptable levels. During periods when there were no emissions of CO and CO2, we used their rates of decay to calculate the home's air exchange rate via the tracer gas technique. The air exchange rate was then used to calculate emission rates for CO.

An agronomic field-scale sensor network for monitoring soil water and temperature variation

NASA Astrophysics Data System (ADS)

Brown, D. J.; Gasch, C.; Brooks, E. S.; Huggins, D. R.; Campbell, C. S.; Cobos, D. R.

2014-12-01

Environmental sensor networks have been deployed in a variety of contexts to monitor plant, air, water and soil properties. To date, there have been relatively few such networks deployed to monitor dynamic soil properties in cropped fields. Here we report on experience with a distributed soil sensor network that has been deployed for seven years in a research farm with ongoing agronomic field operations. The Washington State University R. J. Cook Agronomy Farm (CAF), Pullman, WA, USA has recently been designated a United States Department of Agriculture (USDA) Long-Term Agro-Ecosystem Research (LTAR) site. In 2007, 12 geo-referenced locations at CAF were instrumented, then in 2009 this network was expended to 42 locations distributed across the 37-ha farm. At each of this locations, Decagon 5TE probes (Decagon Devices Inc., Pullman, WA, USA) were installed at five depths (30, 60, 90, 120, and 150 cm), with temperature and volumetric soil moisture content recorded hourly. Initially, data loggers were wirelessly connected to a data station that could be accessed through a cell connection, but due to the logistics of agronomic field operations, we later buried the dataloggers at each site and now periodically download data via local radio transmission. In this presentation, we share our experience with the installation, maintenance, calibration and data processing associated with an agronomic soil monitoring network. We also present highlights of data derived from this network, including seasonal fluctuations of soil temperature and volumetric water content at each depth, and how these measurements are influenced by crop type, soil properties, landscape position, and precipitation events.

A Community Network of 100 Black Carbon Sensors

NASA Astrophysics Data System (ADS)

Preble, C.; Kirchstetter, T.; Caubel, J.; Cados, T.; Keeling, C.; Chang, S.

2017-12-01

We developed a low-cost black carbon sensor, field tested its performance, and then built and deployed a network of 100 sensors in West Oakland, California. We operated the network for 100 days beginning mid-May 2017 to measure spatially resolved black carbon concentrations throughout the community. West Oakland is a San Francisco Bay Area mixed residential and industrial community that is adjacent to regional port and rail yard facilities and 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 deployed the black carbon monitoring network outside of residences and business, along truck routes and arterial streets, and at upwind locations. The sensor employs the filter-based light transmission method to measure black carbon and has good precision and correspondence with current commercial black carbon instruments. Throughout the 100-day period, each of the 100 sensors transmitted data via a cellular network. A MySQL database was built to receive and manage the data in real-time. The database included diagnostic features to monitor each sensor's operational status and facilitate the maintenance of the network. Spatial and temporal patterns in black carbon concentrations will be presented, including patterns around industrial facilities, freeways, and truck routes, as well as the relationship between neighborhood concentrations and the BAAQMD's monitoring site. Lessons learned during this first of its kind black carbon monitoring network will also be shared.

[Evaluation of environmental conditions: air, water and soil in areas of mining activity in Boyacá, Colombia].

PubMed

Agudelo-Calderón, Carlos A; Quiroz-Arcentales, Leonardo; García-Ubaque, Juan C; Robledo-Martínez, Rocío; García-Ubaque, Cesar A

2016-02-01

Objectives To determine concentrations of PM10, mercury and lead in indoor air of homes, water sources and soil in municipalities near mining operations. Method 6 points were evaluated in areas of influence and 2 in control areas. For measurements of indoor air, we used the NIOSH 600 method (PM10), NIOSH 6009 (mercury) and NIOSH 7300 (lead). For water analysis we used the IDEAM Guide for monitoring discharges. For soil analysis, we used the cold vapor technique (mercury) and atomic absorption (lead). Results In almost all selected households, the average PM10 and mercury concentrations in indoor air exceeded applicable air quality standards. Concentrations of lead were below standard levels. In all water sources, high concentrations of lead were found and in some places within the mining areas, high levels of iron, aluminum and mercury were also found. In soil, mercury concentrations were below the detection level and for lead, differences between the monitored points were observed. Conclusions The results do not establish causal relationships between mining and concentration of these pollutants in the evaluated areas because of the multiplicity of sources in the area. However, such studies provide important information, useful to agents of the environmental health system and researchers. Installation of networks for environmental monitoring to obtain continuous reports is suggested.

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...

76 FR 42549 - Approval and Promulgation of Air Quality Implementation Plans; Louisiana; Section 110(a)(2...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-19

..., including emissions inventories, monitoring, and modeling to assure attainment and maintenance of the... of the Louisiana Environmental Action Network (LEAN, hereinafter referred to as ``the commenter... action'' subject to review by the Office of Management and Budget under Executive Order 12866 (58 FR...

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 ...

40 CFR 52.2565 - Original identification of plan.

Code of Federal Regulations, 2013 CFR

2013-07-01

...) Amended Regulations VI and VII, and an Identification and Analysis of the Impact of the 1979 West Virginia... State of West Virginia on November 4, 1983 which establishes an Ambient Air Quality Monitoring Network...) Revision to the State implementation plan consisting of a good engineering practice (GEP) for stack heights...

40 CFR 52.2565 - Original identification of plan.

Code of Federal Regulations, 2011 CFR

2011-07-01

...) Amended Regulations VI and VII, and an Identification and Analysis of the Impact of the 1979 West Virginia... State of West Virginia on November 4, 1983 which establishes an Ambient Air Quality Monitoring Network...) Revision to the State implementation plan consisting of a good engineering practice (GEP) for stack heights...

40 CFR 52.2565 - Original identification of plan.

Code of Federal Regulations, 2010 CFR

2010-07-01

...) Amended Regulations VI and VII, and an Identification and Analysis of the Impact of the 1979 West Virginia... State of West Virginia on November 4, 1983 which establishes an Ambient Air Quality Monitoring Network...) Revision to the State implementation plan consisting of a good engineering practice (GEP) for stack heights...

40 CFR 52.2565 - Original identification of plan.

Code of Federal Regulations, 2012 CFR

2012-07-01

...) Amended Regulations VI and VII, and an Identification and Analysis of the Impact of the 1979 West Virginia... State of West Virginia on November 4, 1983 which establishes an Ambient Air Quality Monitoring Network...) Revision to the State implementation plan consisting of a good engineering practice (GEP) for stack heights...

Impacts of a large boreal wildfire on ground level atmospheric concentrations of PAHs, VOCs and ozone

EPA Science Inventory

During May 2016 a very large boreal wildfire burned throughout the Athabasca Oil Sands Region (AOSR) in central Canada, and in close proximity to an extensive air quality monitoring network. This study examines speciated 24-h integrated polycyclic aromatic hydrocarbon (PAH) and v...

Microfluidics-based integrated airborne pathogen detection systems

NASA Astrophysics Data System (ADS)

Northrup, M. Allen; Alleman-Sposito, Jennifer; Austin, Todd; Devitt, Amy; Fong, Donna; Lin, Phil; Nakao, Brian; Pourahmadi, Farzad; Vinas, Mary; Yuan, Bob

2006-09-01

Microfluidic Systems is focused on building microfluidic platforms that interface front-end mesofluidics to handle real world sample volumes for optimal sensitivity coupled to microfluidic circuitry to process small liquid volumes for complex reagent metering, mixing, and biochemical analysis, particularly for pathogens. MFSI is the prime contractor on two programs for the US Department of Homeland Security: BAND (Bioagent Autonomous Networked Detector) and IBADS (Instantaneous Bio-Aerosol Detection System). The goal of BAND is to develop an autonomous system for monitoring the air for known biological agents. This consists of air collection, sample lysis, sample purification, detection of DNA, RNA, and toxins, and a networked interface to report the results. For IBADS, MFSI is developing the confirmatory device which must verify the presence of a pathogen with 5 minutes of an air collector/trigger sounding an alarm. Instrument designs and biological assay results from both BAND and IBADS will be presented.

76 FR 54293 - Review of National Ambient Air Quality Standards for Carbon Monoxide

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-31

...This rule is being issued at this time as required by a court order governing the schedule for completion of this review of the air quality criteria and the national ambient air quality standards (NAAQS) for carbon monoxide (CO). Based on its review, the EPA concludes the current primary standards are requisite to protect public health with an adequate margin of safety, and is retaining those standards. After review of the air quality criteria, EPA further concludes that no secondary standard should be set for CO at this time. EPA is also making changes to the ambient air monitoring requirements for CO, including those related to network design, and is updating, without substantive change, aspects of the Federal reference method.

GuMNet - A high altitude monitoring network in the Sierra de Guadarrama (Madrid, Spain)

NASA Astrophysics Data System (ADS)

Santolaria-Canales, Edmundo

2016-04-01

The Guadarrama Monitoring Network (GuMNet) is an observational infrastructure focused on monitoring the state of the atmosphere and the ground in the Sierra de Guadarrama, 50 km NW of the city of Madrid. The network is composed of10 stations ranging from low altitude (900 m a.s.l.) to high mountain climate (2400 m a.s.l.). The atmospheric instrumentation includes sensors for air temperature, air humidity, 4-component net radiation, precipitation, snow height and wind speed and direction. The surface and subsurface infrastructure includes temperature and humidity sensors distributed in 9 trenches up to a maximum of 1 m depth and additionally temperature sensors in 15 PVC cased boreholes down to 20 m and 2 m with a higher vertical resolution close to the surface. All stations are located in exposed open areas except for one site that is in a forested area for measuring air-ground fluxes under forest conditions. High altitude sites are focused on periglacial areas and lower altitude sites have emphasis on pastures. One of the low altitude sites is equipped with a 10 m high tower with 3D sonic anemometers and a CO2/H2O analyzer that will allow the sampling of wind profiles and H2O and CO2 eddy covariance fluxes, important for estimation of CO2 and energy exchanges over complex vegetated surfaces. The network is connected via general packet radio service to the central lab in the Campus of Excellence of Moncloa and management software has been developed to handle the operation of the infrastructure. The data provided by GuMNet will help to improve the characterization of atmospheric variability from turbulent scales to meteorology and climate at high mountain areas, as well as land-atmosphere interactions. The network information aims at meeting the needs of accuracy to be used for biological, agricultural, hydrological, meteorological and climatic investigations in this area with relevance for ecosystem oriented studies. This setup will complement the broader network of meteorological stations of the Spanish National Meteorological Agency(AEMET), mostly distributed in the lower latitude range. This initiative is supported and developed by research groups integrating the GuMNet Consortium from the Complutense and Polytechnical Universities of Madrid (UCM and UPM), the Energetic Environmental and Technological Research Centre (CIEMAT), AEMET, and the National Park Sierra de Guadarrama (PNSG) which provided the initial foundations of this network. GuMNet will be operational in 2016. Web: http://www.ucm.es/gumnet/ Contact: edmundo.santolaria@ucm.es

Integration of Satellite, Modeled, and Ground Based Aerosol Data for use in Air Quality and Public Health Applications

NASA Astrophysics Data System (ADS)

Garcia, V.; Kondragunta, S.; Holland, D.; Dimmick, F.; Boothe, V.; Szykman, J.; Chu, A.; Kittaka, C.; Al-Saadi, J.; Engel-Cox, J.; Hoff, R.; Wayland, R.; Rao, S.; Remer, L.

2006-05-01

Advancements in remote sensing over the past decade have been recognized by governments around the world and led to the development of the international Global Earth Observation System of Systems 10-Year Implementation Plan. The plan for the U.S. contribution to GEOSS has been put forth in The Strategic Plan for the U.S. Integrated Earth Observation System (IEOS) developed under IWGEO-CENR. The approach for the development of the U.S. IEOS is to focus on specific societal benefits that can be achieved by integrating the nation's Earth observation capabilities. One such challenge is our ability to understand the impact of poor air quality on human health and well being. Historically, the air monitoring networks put in place for the Nations air quality programs provided the only aerosol air quality data on an ongoing and systematic basis at national levels. However, scientific advances in the remote sensing of aerosols from space have improved dramatically. The MODIS sensor and GOES Imager aboard NASA and NOAA satellites, respectively, provide synoptic-scale measurements of aerosol optical depth (AOD) which have been demonstrated to correlate with high levels of PM10 and PM2.5 at the surface. The MODIS sensor has been shown to be capable of a 1 km x 1 km (at nadir) AOD product, while the GOES Imager can provide AOD at 4 km x 4 km every 30 minutes. Within the next several years NOAA and EPA will begin to issue PM2.5 air quality forecasts over the entire domain of the eastern United States, eventually extending to national coverage. These forecasts will provide continuous estimated values of PM2.5 on a daily basis. A multi-agency collaborative project among government and academia is underway to improve the spatial prediction of fine particulate matter through the integration of multi-sensor and multi-platform aerosol observations (MODIS and GOES), numerical model output, and air monitoring data. By giving more weight to monitoring data in monitored areas and relying on adjusted model output and satellite data in non-monitored areas, a Bayesian hierarchical space-time model will be used to improve the accuracy of prediction and associated prediction errors. The improved spatial predictions will be tested as estimates of exposure for input to modeling relationships between air quality and asthma/other respiratory diseases through CDC under the Environmental Public Health Tracking Network. We will also focus on the use of the predictive spatial maps within the EPA AIRNow program which provides near real-time spatial maps of daily average PM2.5 concentrations across the US. We will present the overall project plan and preliminary results with emphasis on how GEOSS framework is facilitating this effort.

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.

A Networked Sensor System for the Analysis of Plot-Scale Hydrology.

PubMed

Villalba, German; Plaza, Fernando; Zhong, Xiaoyang; Davis, Tyler W; Navarro, Miguel; Li, Yimei; Slater, Thomas A; Liang, Yao; Liang, Xu

2017-03-20

This study presents the latest updates to the Audubon Society of Western Pennsylvania (ASWP) testbed, a $50,000 USD, 104-node outdoor multi-hop wireless sensor network (WSN). The network collects environmental data from over 240 sensors, including the EC-5, MPS-1 and MPS-2 soil moisture and soil water potential sensors and self-made sap flow sensors, across a heterogeneous deployment comprised of MICAz, IRIS and TelosB wireless motes. A low-cost sensor board and software driver was developed for communicating with the analog and digital sensors. Innovative techniques (e.g., balanced energy efficient routing and heterogeneous over-the-air mote reprogramming) maintained high success rates (>96%) and enabled effective software updating, throughout the large-scale heterogeneous WSN. The edaphic properties monitored by the network showed strong agreement with data logger measurements and were fitted to pedotransfer functions for estimating local soil hydraulic properties. Furthermore, sap flow measurements, scaled to tree stand transpiration, were found to be at or below potential evapotranspiration estimates. While outdoor WSNs still present numerous challenges, the ASWP testbed proves to be an effective and (relatively) low-cost environmental monitoring solution and represents a step towards developing a platform for monitoring and quantifying statistically relevant environmental parameters from large-scale network deployments.

A Networked Sensor System for the Analysis of Plot-Scale Hydrology

PubMed Central

Villalba, German; Plaza, Fernando; Zhong, Xiaoyang; Davis, Tyler W.; Navarro, Miguel; Li, Yimei; Slater, Thomas A.; Liang, Yao; Liang, Xu

2017-01-01

This study presents the latest updates to the Audubon Society of Western Pennsylvania (ASWP) testbed, a $50,000 USD, 104-node outdoor multi-hop wireless sensor network (WSN). The network collects environmental data from over 240 sensors, including the EC-5, MPS-1 and MPS-2 soil moisture and soil water potential sensors and self-made sap flow sensors, across a heterogeneous deployment comprised of MICAz, IRIS and TelosB wireless motes. A low-cost sensor board and software driver was developed for communicating with the analog and digital sensors. Innovative techniques (e.g., balanced energy efficient routing and heterogeneous over-the-air mote reprogramming) maintained high success rates (>96%) and enabled effective software updating, throughout the large-scale heterogeneous WSN. The edaphic properties monitored by the network showed strong agreement with data logger measurements and were fitted to pedotransfer functions for estimating local soil hydraulic properties. Furthermore, sap flow measurements, scaled to tree stand transpiration, were found to be at or below potential evapotranspiration estimates. While outdoor WSNs still present numerous challenges, the ASWP testbed proves to be an effective and (relatively) low-cost environmental monitoring solution and represents a step towards developing a platform for monitoring and quantifying statistically relevant environmental parameters from large-scale network deployments. PMID:28335534

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.

The Satellite based Monitoring Initiative for Regional Air quality (SAMIRA): Project summary and first results

NASA Astrophysics Data System (ADS)

Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nemuc, Anca; Stachlewska, Iwona; Zehner, Claus

2017-04-01

We present a summary and some first results of a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellite instruments, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. The primary goal of SAMIRA is to demonstrate the usefulness of existing and future satellite products of air quality for improving monitoring and mapping of air pollution at the regional scale. A total of six core activities are being carried out in order to achieve this goal: Firstly, the project is developing and optimizing algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard of Meteosat Second Generation. As a second activity, SAMIRA aims to derive particulate matter (PM2.5) estimates from AOD data by developing robust algorithms for AOD-to-PM conversion with the support from model- and Lidar data. In a third activity, we evaluate the added value of satellite products of atmospheric composition for operational European-scale air quality mapping using geostatistics and auxiliary datasets. The additional benefit of satellite-based monitoring over existing monitoring techniques (in situ, models) is tested by combining these datasets using geostatistical methods and demonstrated for nitrogen dioxide (NO2), sulphur dioxide (SO2), and aerosol optical depth/particulate matter. As a fourth activity, the project is developing novel algorithms for downscaling coarse-resolution satellite products of air quality with the help of high-resolution model information. This will add value to existing earth observation products of air quality by bringing them to spatial scales that are more in line with what is generally required for studying urban and regional scale air quality. In a fifth activity, we implement robust and independent validation schemes for evaluating the quality of the generated products. Finally, in a sixth activity the consortium is working towards a pre-operational system for improved PM forecasts using observational (in situ and satellite) data assimilation. SAMIRA aims to maximize project benefits by liaison with national and regional environmental protection agencies and health institutions, as well as related ESA and European initiatives such as the Copernicus Atmosphere Monitoring Service (CAMS).

National Trends in Trace Metals Concentrations in Ambient Particulate Matter

NASA Astrophysics Data System (ADS)

McCarthy, M. C.; Hafner, H. R.; Charrier, J. G.

2007-12-01

Ambient measurements of trace metals identified as hazardous air pollutants (HAPs, air toxics) collected in the United States from 1990 to 2006 were analyzed for long-term trends. Trace metals analyzed include lead, manganese, arsenic, chromium, nickel, cadmium, and selenium. Visual and statistical analyses were used to identify and quantify temporal variations in air toxics at national and regional levels. Trend periods were required to be at least five years. Lead particles decreased in concentration at most monitoring sites, but trends in other metals were not consistent over time or spatially. In addition, routine ambient monitoring methods had method detection limits (MDLs) too high to adequately measure concentrations for trends analysis. Differences between measurement methods at urban and rural sites also confound trends analyses. Improvements in MDLs, and a better understanding of comparability between networks, are needed to better quantify trends in trace metal concentrations in the future.

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

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.

Remote detection of riverine traffic using an ad hoc wireless sensor network

NASA Astrophysics Data System (ADS)

Athan, Stephan P.

2005-05-01

Trafficking of illegal drugs on riverine and inland waterways continues to proliferate in South America. While there has been a successful joint effort to cut off overland and air trafficking routes, there exists a vast river network and Amazon region consisting of over 13,000 water miles that remains difficult to adequately monitor, increasing the likelihood of narcotics moving along this extensive river system. Hence, an effort is underway to provide remote unattended riverine detection in lieu of manned or attended detection measures.

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.

2012 Nitrogen Dioxide Monitoring Site Design Values

EPA Pesticide Factsheets

A design value is a statistic that describes the air quality status of a given location relative to the level of the National Ambient Air Quality Standards (NAAQS). Design values are defined to be consistent with the individual NAAQS as described in CFR Part 50. They are typically used to designate and classify nonattainment areas, as well as to assess progress towards meeting the NAAQS. To view a list of areas designated nonattainment, see EPA's Green Book site. Design values are computed and published annually by EPA's Office of Air Quality Planning and Standards and reviewed in conjunction with the EPA Regional Offices. Some of these design values can change after the date of publication for a variety of reasons, including but not limited to: 1) EPA agreement that certain data were influenced by exceptional events and therefore not subject for comparison with the NAAQS, 2) States retroactively entering or changing erroneous data based on later findings, and/or 3) notification of a monitoring issue (e.g. network design, site combination, change in the regulatory status of a monitor) that would prompt a revision.

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

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.

Atmospheric Methane Mixing Ratios--The NOAA/CMDL Global Cooperative Air Sampling Network\\, 1983-1993

DOE Data Explorer

Dlugokencky, E. J. [National Oceanic and Atmospheric Administration, Boulder, Colorado (USA); Lang, P. M. [National Oceanic and Atmospheric Administration, Boulder, Colorado (USA); Masarie, K. A. [National Oceanic and Atmospheric Administration, Boulder, Colorado (USA); Steele, L. P. [Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria, Australia

1994-01-01

This data base presents atmospheric methane (CH4) mixing ratios from flask air samples collected over the period 1983-1993 by the National Oceanic and Atmospheric Administration, Climate Monitoring and Diagnostics Laboratory's (NOAA/CMDL's) global cooperative air sampling network. Air samples were collected approximately once per week at 44 fixed sites (37 of which were still active at the end of 1993). Samples were also collected at 5 degree latitude intervals along shipboard cruise tracks in the Pacific Ocean between North America and New Zealand (or Australia) and at 3 degree latitude intervals along cruise tracks in the South China Sea between Singapore and Hong Kong. The shipboard measurements were made approximately every 3 weeks per latitude zone by each of two ships in the Pacific Ocean and approximately once every week per latitude zone in the South China Sea. All samples were analyzed for CH4 at the NOAA/CMDL laboratory in Boulder, Colorado, by gas chromatography with flame ionization detection, and each aliquot was referenced to the NOAA/CMDL methane standard scale. In addition to providing the complete set of atmospheric CH4 measurements from flask air samples collected at the NOAA/CMDL network sites, this data base also includes files which list monthly mean mixing ratios derived from the individual flask air measurements. These monthly summary data are available for 35 of the fixed sites and 21 of the shipboard sampling sites.

Importance of a Priori Vertical Ozone Profiles for TEMPO Air Quality Retrievals

NASA Technical Reports Server (NTRS)

Johnson, Matthew S.; Sullivan, John; Liu, Xiong; Zoogman, Peter; Newchurch, Mike; Kuang, Shi; McGee, Thomas; Leblanc, Thierry

2017-01-01

Ozone (O3) is a toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is 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 the 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 (Global Ozone Monitoring Experiment), GOME-2, and OMI (Ozone Monitoring Instrument). This algorithm is suggested to use a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB-Clim) O3 climatology). This study evaluates the TB-Clim dataset and model simulated O3 profiles, which could potentially serve as a priori O3 profile information in TEMPO retrievals, from near-real-time data assimilation model products (NASA GMAO's (Global Modeling and Assimilation Office) operational GEOS-5 (Goddard Earth Observing System, Version 5) FP (Forecast Products) model and reanalysis data from MERRA2 (Modern-Era Retrospective analysis for Research and Applications, Version 2)) and a full chemical transport model (CTM), GEOS-Chem. In this study, vertical profile products are evaluated with surface (0-2 kilometers) and tropospheric (0-10 kilometers) TOLNet (Tropospheric Ozone Lidar Network) observations and the theoretical impact of individual a priori profile sources on the accuracy of TEMPO O3 retrievals in the troposphere and at the surface are presented. Results indicate that while the TB-Clim climatological dataset can replicate seasonally-averaged tropospheric O3 profiles, model-simulated profiles from a full CTM resulted in more accurate tropospheric and surface-level O3 retrievals from TEMPO when compared to hourly and daily-averaged TOLNet observations. Furthermore, it is shown that when large surface O3 mixing ratios are observed, TEMPO retrieval values at the surface are most accurate when applying CTM a priori profile information compared to all other data products.

Neural network analysis on the effect of heat fluxes on greenhouse gas emissions from anaerobic swine waste treatment lagoon

USDA-ARS?s Scientific Manuscript database

In this study, we examined the various meteorological factors (i.e., air temperatures, solar radiation, and heat fluxes) that potentially affect greenhouse gas (GHG) emissions from swine waste lagoon. GHG concentrations (methane, carbon dioxide, and nitrous oxide) were monitored using a photoacous...

77 FR 65656 - Determination of Attainment for the Nogales Nonattainment Area for the 2006 Fine Particle...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-30

...\\ Furthermore, we concluded in our Technical System Audit Report concerning ADEQ's ambient air quality... Monitoring Network Plan: For the Year 2011''). \\7\\ Technical System Audit Report transmitted via... an ``anonymous access'' system, and EPA will not know your identity or contact information unless you...

40 CFR 52.1100 - Original identification of plan section.

Code of Federal Regulations, 2012 CFR

2012-07-01

... establish an Ambient Air Quality Monitoring Network. (45) Recodification of the Maryland Regulations... Practice (GEP) Stack Height Regulations, COMAR 10.18.01.08 (Determination of Ground Level Concentrations... consumption analysis. The amendments to COMAR 26.11.01.01, 26.11.02.10 (C)(9), and 26.11.06.14 were effective...

78 FR 57496 - Approval and Promulgation of Air Quality Implementation Plans; State of Colorado Second Ten-Year...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-19

... FURTHER INFORMATION CONTACT section to view the hard copy of the docket. You may view the hard copy of the... to illustrate your concerns, and suggest alternatives. g. Explain your views as clearly as possible..., Maintenance Demonstration, Monitoring Network/Verification of Continued Attainment, Contingency Plan, and...

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.

Complex monitoring and alert network for electromagnetic, infrasound, acoustic seismotectonic phenomena

NASA Astrophysics Data System (ADS)

-Emilian Toader, Victorin; Moldovan, Iren-Adelina; Constantin, Ionescu

2014-05-01

The Romanian seismicity recorded in 2013 three important events: the largest seismic "silence", the shortest sequence of two earthquakes greater than 4.8R in less than 14 days after the "Romanian National Institute for Earth Physics" (NIEP) developed a digital network, and a very high crustal activity in Galati area. We analyze the variations of the telluric currents and local magnetic field, variations of the atmospheric electrostatic field, infrasound, temperature, humidity, wind speed and direction, atmospheric pressure, variations in the earth crust with inclinometers and animal behavior. The general effect is the first high seismic energy discontinuity that could be a precursor factor. Since 1977 Romania did not register any important earthquake that would generate a sense of fear among the population. In parallel with the seismic network NIEP developed a magneto-telluric, bioseismic, VLF and acoustic network. A large frequency spectrum is covered for mechanical vibration, magnetic and electric field with ground and air sensors. Special software was designed for acquisition, analysis and real time alert using internet direct connection, web page, email and SMS. Many examples show the sensitivity of telluric current, infrasound, acoustic records (from air-ground), and the effect of tectonic stress on the magnetic field or ground deformation. The next update of the multidisciplinary monitoring network will include measurement of ionization, radon emission, sky color, solar radiation and extension of infrasound and VL/LF equipment. NOAA Space Weather satellites transmit solar activity magnetic field data, X ray flux, electron, and proton flux information useful for complex analysis.

High Electricity Demand in the Northeast U.S.: PJM Reliability Network and Peaking Unit Impacts on Air Quality.

PubMed

Farkas, Caroline M; Moeller, Michael D; Felder, Frank A; Henderson, Barron H; Carlton, Annmarie G

2016-08-02

On high electricity demand days, when air quality is often poor, regional transmission organizations (RTOs), such as PJM Interconnection, ensure reliability of the grid by employing peak-use electric generating units (EGUs). These "peaking units" are exempt from some federal and state air quality rules. We identify RTO assignment and peaking unit classification for EGUs in the Eastern U.S. and estimate air quality for four emission scenarios with the Community Multiscale Air Quality (CMAQ) model during the July 2006 heat wave. Further, we population-weight ambient values as a surrogate for potential population exposure. Emissions from electricity reliability networks negatively impact air quality in their own region and in neighboring geographic areas. Monitored and controlled PJM peaking units are generally located in economically depressed areas and can contribute up to 87% of hourly maximum PM2.5 mass locally. Potential population exposure to peaking unit PM2.5 mass is highest in the model domain's most populated cities. Average daily temperature and national gross domestic product steer peaking unit heat input. Air quality planning that capitalizes on a priori knowledge of local electricity demand and economics may provide a more holistic approach to protect human health within the context of growing energy needs in a changing world.

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

High density ozone monitoring using gas sensitive semi-conductor sensors in the Lower Fraser Valley, British Columbia.

PubMed

Bart, Mark; Williams, David E; Ainslie, Bruce; McKendry, Ian; Salmond, Jennifer; Grange, Stuart K; Alavi-Shoshtari, Maryam; Steyn, Douw; Henshaw, Geoff S

2014-04-01

A cost-efficient technology for accurate surface ozone monitoring using gas-sensitive semiconducting oxide (GSS) technology, solar power, and automated cell-phone communications was deployed and validated in a 50 sensor test-bed in the Lower Fraser Valley of British Columbia, over 3 months from May-September 2012. Before field deployment, the entire set of instruments was colocated with reference instruments for at least 48 h, comparing hourly averaged data. The standard error of estimate over a typical range 0-50 ppb for the set was 3 ± 2 ppb. Long-term accuracy was assessed over several months by colocation of a subset of ten instruments each at a different reference site. The differences (GSS-reference) of hourly average ozone concentration were normally distributed with mean -1 ppb and standard deviation 6 ppb (6000 measurement pairs). Instrument failures in the field were detected using network correlations and consistency checks on the raw sensor resistance data. Comparisons with modeled spatial O3 fields demonstrate the enhanced monitoring capability of a network that was a hybrid of low-cost and reference instruments, in which GSS sensors are used both to increase station density within a network as well as to extend monitoring into remote areas. This ambitious deployment exposed a number of challenges and lessons, including the logistical effort required to deploy and maintain sites over a summer period, and deficiencies in cell phone communications and battery life. Instrument failures at remote sites suggested that redundancy should be built into the network (especially at critical sites) as well as the possible addition of a "sleep-mode" for GSS monitors. At the network design phase, a more objective approach to optimize interstation distances, and the "information" content of the network is recommended. This study has demonstrated the utility and affordability of the GSS technology for a variety of applications, and the effectiveness of this technology as a means substantially and economically to extend the coverage of an air quality monitoring network. Low-cost, neighborhood-scale networks that produce reliable data can be envisaged.

Journal Article: EPA's National Dioxin Air Monitoring Network ...

EPA Pesticide Factsheets

The U.S. Environmental Protection Agency (U.S. EPA) established the National Dioxin Air Monitoring Network (NDAMN) in June of 1998, and operated it until November of 2004. The objective of NDAMN was to determine background air concentrations of polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), and dioxin-like polychlorinated biphenyls (dl-PCBs). NDAMN started with 10 sampling sites, adding more over time until the final count of 34 sites was reached by the beginning of 2003. Samples were taken quarterly, and the final sample count was 685. All samples were measured for 17 PCDD/PCDF congeners, 8 PCDD/PCDF homologue groups, and 7 dl-PCBs (note: 5 additional dl-PCBs were added for samples starting in the summer of 2002; 317 samples had measurements of 12 dl-PCBs). The overall average total toxic equivalent (TEQ) concentration in the United States was 11.2 fg TEQ m−3 with dl-PCBs contributing 0.8 fg TEQ m−3 (7%) to this total. The archetype dioxin and furan background air congener profile was seen in the survey averages and in most individual samples. This archetype profile is characterized by low and similar concentrations for tetra – through hexa PCDD/PCDF congeners, with elevations in four congeners – a hepta dioxin and furan congener, and both octa congeners. Sites were generally categorized as urban (4 sites), rural (23 sites), or remote (7 sites). The average TEQ concentrations over all sites and samples within these cat

Technical report: The design and evaluation of a basin-scale wireless sensor network for mountain hydrology

NASA Astrophysics Data System (ADS)

Zhang, Ziran; Glaser, Steven D.; Bales, Roger C.; Conklin, Martha; Rice, Robert; Marks, Danny G.

2017-05-01

A network of sensors for spatially representative water-balance measurements was developed and deployed across the 2000 km2 snow-dominated portion of the upper American River basin, primarily to measure changes in snowpack and soil-water storage, air temperature, and humidity. This wireless sensor network (WSN) consists of 14 sensor clusters, each with 10 measurement nodes that were strategically placed within a 1 km2 area, across different elevations, aspects, slopes, and canopy covers. Compared to existing operational sensor installations, the WSN reduces hydrologic uncertainty in at least three ways. First, redundant measurements improved estimation of lapse rates for air and dew-point temperature. Second, distributed measurements captured local variability and constrained uncertainty in air and dew-point temperature, snow accumulation, and derived hydrologic attributes important for modeling and prediction. Third, the distributed relative-humidity measurements offer a unique capability to monitor upper-basin patterns in dew-point temperature and characterize elevation gradient of water vapor-pressure deficit across steep, variable topography. Network statistics during the first year of operation demonstrated that the WSN was robust for cold, wet, and windy conditions in the basin. The electronic technology used in the WSN-reduced adverse effects, such as high current consumption, multipath signal fading, and clock drift, seen in previous remote WSNs.

Concept of Complex Environmental Monitoring Network - Vardzia Rock Cut City Case Study

NASA Astrophysics Data System (ADS)

Elashvili, Mikheil; Vacheishvili, Nikoloz; Margottini, Claudio; Basilaia, Giorgi; Chkhaidze, Davit; Kvavadze, Davit; Spizzichino, Daniele; Boscagli, Franceso; Kirkitadze, Giorgi; Adikashvili, Luka; Navrozashvili, Levan

2016-04-01

Vardzia represents an unique cultural heritage monument - rock cut city, which unites architectural monument and Natural-Geological complex. Such monuments are particularly vulnerable and their restoration and conservation requires complex approach. It is curved in various layers of volcanic tuffs and covers several hectares of area, with chronologically different segments of construction. This monument, as many similar monuments worldwide, is subjected to slow but permanent process of destruction, expressed in following factors: surface weathering of rock, active tectonics (aseismic displacement along the active faults and earthquakes), interaction between lithologically different rock layers, existence of major cracks and associated complex block structure, surface rainwater runoff and infiltrated ground water, temperature variations, etc. During its lifetime, Vardzia was heavily damaged by Historical Earthquake of 1283 and only partly restored afterwards. The technological progress together with the increased knowledge about ongoing environmental processes, established the common understanding that the complex monitoring of the environment represents the essential component for resolving such a principal issues, as: Proper management and prevention of natural disasters; Modeling of environmental processes, their short and long term prognosis; Monitoring of macro and micro climate; Safe functioning and preservation of important constructions. Research Center of Cultural Heritage and Environment of Ilia State University in cooperation with Experts from ISPRA, with the funding from the State agency of Cultural Heritage, has developed a concept of Vardzia complex monitoring network. Concept of the network includes: monitoring local meteorological conditions (meteorological station), monitoring microclimate in caves (temperature and humidity in the air and rock), monitoring microtremors and ambient seismic noise in Vardzia (local strong motion network), monitoring displacement and deformation of Vardzia cliff by means of Ground-based SAR (GBSAR) interferometry, continuous photo fixation of ongoing destruction. Works were started in 2014 from the development of network concept and at the end of year 2015 installation of all major components were accomplished. Special Wi-Fi network was installed, using 5.8 GHz frequency to online connect all the station to the central data center in Tbilisi and the same time avoiding complex network of wires on cultural monument. Acquired Data and network status can be seen online on Vardzia.IliaUni.edu.ge. For the management of considerable data flow special Internet Of Thing (IOT) server was developed. First streams of data are already collected and processing started, initial results already obtained and given in current presentation. It should be outlined that Vardzia complex monitoring network does not represent unitary technical or conceptual solution, but it is a constantly developing model to be farther extended by adding more monitoring points and/or increasing monitored parameters. It is extremely important to test and validate given approach in reality, enabling use of these technologies in the study and conservation projects of other, similar monuments.

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.

Expanding NevCAN capabilities: monitoring cold air drainage flow along a narrow wash within a Montane to PJ ecotone

NASA Astrophysics Data System (ADS)

Bird, B. M.; Devitt, D.

2012-12-01

Cold air drainage flows are a naturally occurring physical process of mountain systems. Plant communities that exist in cold air drainage basins respond to these localized cold air trends, and have been shown to be decoupled from larger global climate weather systems. The assumption that air temperature decreases with altitude is violated within these systems and climate model results based on this assumption would ultimately be inaccurate. In arid regions, high radiation loads lead to significant long wave radiation being emitted from the ground later in the day. As incoming radiation ceases, the surface very quickly loses energy through radiative processes, leading to surface inversions and enhanced cold air drainage opportunities. This study is being conducted in the Mojave desert on Sheep Mountain located between sites 3 and 4 of the NSF EPSCoR network. Monitoring of cold air drainage was initiated in September of 2011within a narrow ravine located between the 2164 and 2350 meter elevation. We have installed 25 towers (5 towers per location situated at the central low point in a ravine and at equal distances up the sides of the ravine on both the N and S facing slopes) to assess air temperatures from 0.1 meters to a height of 3 meters at 25m intervals. Our goal is to better understand the connection between cold air movement and plant physiological response. The species monitored in this study include: Pinus ponderosa (common name: Ponderosa Pine), Pinus pinyon (Pinyon Pine), Juniperus osteosperma (Utah juniper), Cercocarpus intricatus (Mountain Mahogany) and Symphoricarpos (snowberry). Hourly air temperature measurements within the wash are being captured from 100 ibuttons placed within PVC solar radiation shields. We are also developing a modeling approach to assess the three dimensional movement of cold air over time by incorporating wind vectors captured from 5 2D sonic anemometers. Wind velocities will be paired with air temperatures to better understand the thermal dynamics of cold air drainage. Granier probes were installed in the five test species to monitor transpirational flow relative to cold air movement. Mid day soil - plant - water measurements are also being taken on a monthly basis during the growing season at all locations. Measurements include: leaf xylem water potential, stomata conductance, chlorophyll index readings, canopy minus ambient temperatures and surface soil moisture contents. To date the monitoring system has revealed cold air drainage occurring during periods of every month. We will report the physiological response of the five plant species, with emphasis on assessing the linkages with cold air movement.

3D Air Quality and the Clean Air Interstate Rule: Lagrangian Sampling of CMAQ Model Results to Aid Regional Accountability Metrics

NASA Technical Reports Server (NTRS)

Fairlie, T. D.; Szykman, Jim; Pierce, Robert B.; Gilliland, A. B.; Engel-Cox, Jill; Weber, Stephanie; Kittaka, Chieko; Al-Saadi, Jassim A.; Scheffe, Rich; Dimmick, Fred;