Urban airshed modeling of air quality impacts of alternative transportation fuel use in Los Angeles and Atlanta

DOT National Transportation Integrated Search

1997-12-01

This report documents a photochemical modeling study of the potential impacts on air quality of future emissions from alternative fuel vehicles (AFVs). The main objective of the National Renewable Energy Laboratory (NREL) in supporting this study is ...

Cloud processing of gases and aerosols in the Community Multiscale Air Quality (CMAQ) model: Impacts of extended chemistry

EPA Science Inventory

Clouds and fogs can significantly impact the concentration and distribution of atmospheric gases and aerosols through chemistry, scavenging, and transport. This presentation summarizes the representation of cloud processes in the Community Multiscale Air Quality (CMAQ) modeling ...

Impact of inherent meteorology uncertainty on air quality model predictions

EPA Science Inventory

It is well established that there are a number of different classifications and sources of uncertainties in environmental modeling systems. Air quality models rely on two key inputs, namely, meteorology and emissions. When using air quality models for decision making, it is impor...

Using Water Quality Models in Management - A Multiple Model Assessment, Analysis of Confidence, and Evaluation of Climate Change Impacts

NASA Astrophysics Data System (ADS)

Irby, Isaac David

Human impacts on the Chesapeake Bay through increased nutrient run-off as a result of land-use change, urbanization, and industrialization, have resulted in a degradation of water quality over the last half-century. These direct impacts, compounded with human-induced climate changes such as warming, rising sea-level, and changes in precipitation, have elevated the conversation surrounding the future of water quality in the Bay. The overall goal of this dissertation project is to use a combination of models and data to better understand and quantify the impact of changes in nutrient loads and climate on water quality in the Chesapeake Bay. This research achieves that goal in three parts. First, a set of eight water quality models is used to establish a model mean and assess model skill. All models were found to exhibit similar skill in resolving dissolved oxygen concentrations as well as a number of dissolved oxygen-influencing variables (temperature, salinity, stratification, chlorophyll and nitrate) and the model mean exhibited the highest individual skill. The location of stratification within the water column was found to be a limiting factor in the models' ability to adequately simulate habitat compression resulting from low-oxygen conditions. Second, two of the previous models underwent the regulatory Chesapeake Bay pollution diet mandated by the Environmental Protection Agency. Both models exhibited a similar relative improvement in dissolved oxygen concentrations as a result of the reduction of nutrients stipulated in the pollution diet. A Confidence Index was developed to identify the locations of the Bay where the models are in agreement and disagreement regarding the impacts of the pollution diet. The models were least certain in the deep part of the upper main stem of the Bay and the uncertainty primarily stemmed from the post-processing methodology. Finally, by projecting the impacts of climate change in 2050 on the Bay, the potential success of the pollution diet in light of future projections for air temperature, sea level, and precipitation was examined. While a changing climate will reduce the ability of the nutrient reduction to improve oxygen concentrations, that effect is trumped by the improvements in dissolved oxygen stemming from the pollution diet itself. However, climate change still has the potential to cause the current level of nutrient reduction to be inadequate. This is primarily due to the fact that low-oxygen conditions are predicted to start one week earlier, on average, in the future, with the primary changes resulting from the increase in temperature. Overall, this research lends an increased degree of confidence in the water quality modeling of the potential impact of the Chesapeake Bay pollution diet. This research also establishes the efficacy of utilizing a multiple model approach to examining projected changes in water quality while establishing that the pollution diet trumps the impact from climate change. This work will lead directly to advances in scientific understanding of the response of water quality, ecosystem health, and ecological resilience to the impacts of nutrient reduction and climate change.

Modeling crop residue burning experiments and assessing the fire impacts on air quality

EPA Science Inventory

Prescribed burning is a common land management practice that results in ambient emissions of a variety of primary and secondary pollutants with negative health impacts. The community Multiscale Air Quality (CMAQ) model is used to conduct 2 km grid resolution simulations of prescr...

Impact of High Resolution Land-Use Data in Meteorology and Air Quality Modeling Systems

EPA Science Inventory

Accurate land use information is important in meteorology for land surface exchanges, in emission modeling for emission spatial allocation, and in air quality modeling for chemical surface fluxes. Currently, meteorology, emission, and air quality models often use outdated USGS Gl...

Land use impact on water quality: valuing forest services in terms of the water supply sector.

PubMed

Fiquepron, Julien; Garcia, Serge; Stenger, Anne

2013-09-15

The aim of this paper is to quantify the impact of the forest on raw water quality within the framework of other land uses. On the basis of measurements of quality parameters that were identified as being the most problematic (i.e., pesticides and nitrates), we modeled how water quality is influenced by land uses. In order to assess the benefits provided by the forest in terms of improved water quality, we used variations of drinking water prices that were determined by the operating costs of water supply services (WSS). Given the variability of links between forests and water quality, we chose to cover all of France using data observed in each administrative department (France is divided into 95 départements), including a description of WSS and information on land uses. We designed a model that describes the impact of land uses on water quality, as well as the operation of WSS and prices. This bioeconomic model was estimated by the generalized method of moments (GMM) to account for endogeneity and heteroscedasticity issues. We showed that the forest has a positive effect on raw water quality compared to other land uses, with an indirect impact on water prices, making them lower for consumers. Copyright © 2013 Elsevier Ltd. All rights reserved.

Doctors or technicians: assessing quality of medical education

PubMed Central

Hasan, Tayyab

2010-01-01

Medical education institutions usually adapt industrial quality management models that measure the quality of the process of a program but not the quality of the product. The purpose of this paper is to analyze the impact of industrial quality management models on medical education and students, and to highlight the importance of introducing a proper educational quality management model. Industrial quality management models can measure the training component in terms of competencies, but they lack the educational component measurement. These models use performance indicators to assess their process improvement efforts. Researchers suggest that the performance indicators used in educational institutions may only measure their fiscal efficiency without measuring the quality of the educational experience of the students. In most of the institutions, where industrial models are used for quality assurance, students are considered as customers and are provided with the maximum services and facilities possible. Institutions are required to fulfill a list of recommendations from the quality control agencies in order to enhance student satisfaction and to guarantee standard services. Quality of medical education should be assessed by measuring the impact of the educational program and quality improvement procedures in terms of knowledge base development, behavioral change, and patient care. Industrial quality models may focus on academic support services and processes, but educational quality models should be introduced in parallel to focus on educational standards and products. PMID:23745059

Doctors or technicians: assessing quality of medical education.

PubMed

Hasan, Tayyab

2010-01-01

Medical education institutions usually adapt industrial quality management models that measure the quality of the process of a program but not the quality of the product. The purpose of this paper is to analyze the impact of industrial quality management models on medical education and students, and to highlight the importance of introducing a proper educational quality management model. Industrial quality management models can measure the training component in terms of competencies, but they lack the educational component measurement. These models use performance indicators to assess their process improvement efforts. Researchers suggest that the performance indicators used in educational institutions may only measure their fiscal efficiency without measuring the quality of the educational experience of the students. In most of the institutions, where industrial models are used for quality assurance, students are considered as customers and are provided with the maximum services and facilities possible. Institutions are required to fulfill a list of recommendations from the quality control agencies in order to enhance student satisfaction and to guarantee standard services. Quality of medical education should be assessed by measuring the impact of the educational program and quality improvement procedures in terms of knowledge base development, behavioral change, and patient care. Industrial quality models may focus on academic support services and processes, but educational quality models should be introduced in parallel to focus on educational standards and products.

Study of Regional Downscaled Climate and Air Quality in the United States

NASA Astrophysics Data System (ADS)

Gao, Y.; Fu, J. S.; Drake, J.; Lamarque, J.; Lam, Y.; Huang, K.

2011-12-01

Due to the increasing anthropogenic greenhouse gas emissions, the global and regional climate patterns have significantly changed. Climate change has exerted strong impact on ecosystem, air quality and human life. The global model Community Earth System Model (CESM v1.0) was used to predict future climate and chemistry under projected emission scenarios. Two new emission scenarios, Representative Community Pathways (RCP) 4.5 and RCP 8.5, were used in this study for climate and chemistry simulations. The projected global mean temperature will increase 1.2 and 1.7 degree Celcius for the RCP 4.5 and RCP 8.5 scenarios in 2050s, respectively. In order to take advantage of local detailed topography, land use data and conduct local climate impact on air quality, we downscaled CESM outputs to 4 km by 4 km Eastern US domain using Weather Research and Forecasting (WRF) Model and Community Multi-scale Air Quality modeling system (CMAQ). The evaluations between regional model outputs and global model outputs, regional model outputs and observational data were conducted to verify the downscaled methodology. Future climate change and air quality impact were also examined on a 4 km by 4 km high resolution scale.

Impacts of Energy Sector Emissions on PM2.5 Air Quality in Northern India

NASA Astrophysics Data System (ADS)

Karambelas, A. N.; Kiesewetter, G.; Heyes, C.; Holloway, T.

2015-12-01

India experiences high concentrations of fine particulate matter (PM2.5), and several Indian cities currently rank among the world's most polluted cities. With ongoing urbanization and a growing economy, emissions from different energy sectors remain major contributors to air pollution in India. Emission sectors impact ambient air quality differently due to spatial distribution (typical urban vs. typical rural sources) as well as source height characteristics (low-level vs. high stack sources). This study aims to assess the impacts of emissions from three distinct energy sectors—transportation, domestic, and electricity—on ambient PM2.5­­ in northern India using an advanced air quality analysis framework based on the U.S. EPA Community Multi-Scale Air Quality (CMAQ) model. Present air quality conditions are simulated using 2010 emissions from the Greenhouse Gas-Air Pollution Interaction and Synergies (GAINS) model. Modeled PM2.5 concentrations are compared with satellite observations of aerosol optical depth (AOD) from the Moderate Imaging Spectroradiometer (MODIS) for 2010. Energy sector emissions impacts on future (2030) PM2.5 are evaluated with three sensitivity simulations, assuming maximum feasible reduction technologies for either transportation, domestic, or electricity sectors. These simulations are compared with a business as usual 2030 simulation to assess relative sectoral impacts spatially and temporally. CMAQ is modeled at 12km by 12km and include biogenic emissions from the Community Land Model coupled with the Model of Emissions of Gases and Aerosols in Nature (CLM-MEGAN), biomass burning emissions from the Global Fires Emissions Database (GFED), and ERA-Interim meteorology generated with the Weather Research and Forecasting (WRF) model for 2010 to quantify the impact of modified anthropogenic emissions on ambient PM2.5 concentrations. Energy sector emissions analysis supports decision-making to improve future air quality and public health in India.

Water quality modeling in the systems impact assessment model for the Klamath River basin - Keno, Oregon to Seiad Valley, California

USGS Publications Warehouse

Hanna, R. Blair; Campbell, Sharon G.

2000-01-01

This report describes the water quality model developed for the Klamath River System Impact Assessment Model (SIAM). The Klamath River SIAM is a decision support system developed by the authors and other US Geological Survey (USGS), Midcontinent Ecological Science Center staff to study the effects of basin-wide water management decisions on anadromous fish in the Klamath River. The Army Corps of Engineersa?? HEC5Q water quality modeling software was used to simulate water temperature, dissolved oxygen and conductivity in 100 miles of the Klamath River Basin in Oregon and California. The water quality model simulated three reservoirs and the mainstem Klamath River influenced by the Shasta and Scott River tributaries. Model development, calibration and two validation exercises are described as well as the integration of the water quality model into the SIAM decision support system software. Within SIAM, data are exchanged between the water quantity model (MODSIM), the water quality model (HEC5Q), the salmon population model (SALMOD) and methods for evaluating ecosystem health. The overall predictive ability of the water quality model is described in the context of calibration and validation error statistics. Applications of SIAM and the water quality model are described.

Photochemical Grid Modelling Study to Assess Potential Air Quality Impacts Associated with Energy Development in Colorado and Northern New Mexico.

NASA Astrophysics Data System (ADS)

Parker, L. K.; Morris, R. E.; Zapert, J.; Cook, F.; Koo, B.; Rasmussen, D.; Jung, J.; Grant, J.; Johnson, J.; Shah, T.; Pavlovic, T.

2015-12-01

The Colorado Air Resource Management Modeling Study (CARMMS) was funded by the Bureau of Land Management (BLM) to predict the impacts from future federal and non-federal energy development in Colorado and Northern New Mexico. The study used the Comprehensive Air Quality Model with extensions (CAMx) photochemical grid model (PGM) to quantify potential impacts from energy development from BLM field office planning areas. CAMx source apportionment technology was used to track the impacts from multiple (14) different emissions source regions (i.e. field office areas) within one simulation, as well as to assess the cumulative impact of emissions from all source regions combined. The energy development emissions estimates were for the year 2021 for three different development scenarios: (1) low; (2) high; (3) high with emissions mitigation. Impacts on air quality (AQ) including ozone, PM2.5, PM10, NO2, SO2, and air quality related values (AQRVs) such as atmospheric deposition, regional haze and changes in Acid Neutralizing Capacity (ANC) of lakes were quantified, and compared to establish threshold levels. In this presentation, we present a brief summary of the how the emission scenarios were developed, we compare the emission totals for each scenario, and then focus on the ozone impacts for each scenario to assess: (1). the difference in potential ozone impacts under the different development scenarios and (2). to establish the sensitivity of the ozone impacts to different emissions levels. Region-wide ozone impacts will be presented as well as impacts at specific locations with ozone monitors.

Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Johnson, Hoyt; Khan, Maudood

2006-01-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world s population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include business as usual and smart growth scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS lkm land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Remote Sensing and Spatial Growth Modeling Coupled With Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Astrophysics Data System (ADS)

Quattrochi, D. A.; Estes, M. G.; Crosson, W. L.; Johnson, H.; Khan, M.

2006-05-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world's population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta's growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Relevance of Regional Hydro-Climatic Projection Data for Hydrodynamics and Water Quality Modelling of the Baltic Sea

NASA Astrophysics Data System (ADS)

Goldenberg, R.; Vigouroux, G.; Chen, Y.; Bring, A.; Kalantari, Z.; Prieto, C.; Destouni, G.

2017-12-01

The Baltic Sea, located in Northern Europe, is one of the world's largest body of brackish water, enclosed and surrounded by nine different countries. The magnitude of climate change may be particularly large in northern regions, and identifying its impacts on vulnerable inland waters and their runoff and nutrient loading to the Baltic Sea is an important and complex task. Exploration of such hydro-climatic impacts is needed to understand potential future changes in physical, ecological and water quality conditions in the regional coastal and marine waters. In this study, we investigate hydro-climatic changes and impacts on the Baltic Sea by synthesizing multi-model climate projection data from the CORDEX regional downscaling initiative (EURO- and Arctic- CORDEX domains, http://www.cordex.org/). We identify key hydro-climatic variable outputs of these models and assess model performance with regard to their projected temporal and spatial change behavior and impacts on different scales and coastal-marine parts, up to the whole Baltic Sea. Model spreading, robustness and impact implications for the Baltic Sea system are investigated for and through further use in simulations of coastal-marine hydrodynamics and water quality based on these key output variables and their change projections. Climate model robustness in this context is assessed by inter-model spreading analysis and observation data comparisons, while projected change implications are assessed by forcing of linked hydrodynamic and water quality modeling of the Baltic Sea based on relevant hydro-climatic outputs for inland water runoff and waterborne nutrient loading to the Baltic sea, as well as for conditions in the sea itself. This focused synthesis and analysis of hydro-climatically relevant output data of regional climate models facilitates assessment of reliability and uncertainty in projections of driver-impact changes of key importance for Baltic Sea physical, water quality and ecological conditions and their future evolution.

Smart climate ensemble exploring approaches: the example of climate impacts on air pollution in Europe.

NASA Astrophysics Data System (ADS)

Lemaire, Vincent; Colette, Augustin; Menut, Laurent

2016-04-01

Because of its sensitivity to weather patterns, climate change will have an impact on air pollution so that, in the future, a climate penalty could jeopardize the expected efficiency of air pollution mitigation measures. A common method to assess the impact of climate on air quality consists in implementing chemistry-transport models forced by climate projections. However, at present, such impact assessment lack multi-model ensemble approaches to address uncertainties because of the substantial computing cost. Therefore, as a preliminary step towards exploring large climate ensembles with air quality models, we developed an ensemble exploration technique in order to point out the climate models that should be investigated in priority. By using a training dataset from a deterministic projection of climate and air quality over Europe, we identified the main meteorological drivers of air quality for 8 regions in Europe and developed statistical models that could be used to estimate future air pollutant concentrations. Applying this statistical model to the whole EuroCordex ensemble of climate projection, we find a climate penalty for six subregions out of eight (Eastern Europe, France, Iberian Peninsula, Mid Europe and Northern Italy). On the contrary, a climate benefit for PM2.5 was identified for three regions (Eastern Europe, Mid Europe and Northern Italy). The uncertainty of this statistical model challenges limits however the confidence we can attribute to associated quantitative projections. This technique allows however selecting a subset of relevant regional climate model members that should be used in priority for future deterministic projections to propose an adequate coverage of uncertainties. We are thereby proposing a smart ensemble exploration strategy that can also be used for other impacts studies beyond air quality.

Urban airshed modeling of air quality impacts of alternative transportation fuel use in Los Angeles and Atlanta

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

NONE

1997-12-01

The main objective of NREL in supporting this study is to determine the relative air quality impact of the use of compressed natural gas (CNG) as an alternative transportation fuel when compared to low Reid vapor pressure (RVP) gasoline and reformulated gasoline (RFG). A table lists the criteria, air toxic, and greenhouse gas pollutants for which emissions were estimated for the alternative fuel scenarios. Air quality impacts were then estimated by performing photochemical modeling of the alternative fuel scenarios using the Urban Airshed Model Version 6.21 and the Carbon Bond Mechanism Version IV (CBM-IV) (Geary et al., 1988) Using thismore » model, the authors examined the formation and transport of ozone under alternative fuel strategies for motor vehicle transportation sources for the year 2007. Photochemical modeling was performed for modeling domains in Los Angeles, California, and Atlanta, Georgia.« less

Remote Sensing and Spatial Growth Modeling Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Khan, Maudood

2006-01-01

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 80 percent of the world s population will live in cities. Directly aligned with the expansion of cities is urban sprawl. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes. A reduction in air quality over cities is a major result of these impacts. Strategies that can be directly or indirectly implemented to help remediate air quality problems in cities and that can be accepted by political decision makers and the general public are now being explored to help bring down air pollutants and improve air quality. The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how ozone and air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rationale decisions on urban growth and sustainability for the metropolitan area in the future.

Adapting water treatment design and operations to the impacts of global climate change

NASA Astrophysics Data System (ADS)

Clark, Robert M.; Li, Zhiwei; Buchberger, Steven G.

2011-12-01

It is anticipated that global climate change will adversely impact source water quality in many areas of the United States and will therefore, potentially, impact the design and operation of current and future water treatment systems. The USEPA has initiated an effort called the Water Resources Adaptation Program (WRAP) which is intended to develop tools and techniques that can assess the impact of global climate change on urban drinking water and wastewater infrastructure. A three step approach for assessing climate change impacts on water treatment operation and design is being persude in this effort. The first step is the stochastic characterization of source water quality, the second step is the application of the USEPA Water Treatment Plant model and the third step is the application of cost algorithms to provide a metric that can be used to assess the coat impact of climate change. A model has been validated using data collected from Cincinnati's Richard Miller Water Treatment Plant for the USEPA Information Collection Rule (ICR) database. An analysis of the water treatment processes in response to assumed perturbations in raw water quality identified TOC, pH, and bromide as the three most important parameters affecting performance of the Miller WTP. The Miller Plant was simulated using the EPA WTP model to examine the impact of these parameters on selected regulated water quality parameters. Uncertainty in influent water quality was analyzed to estimate the risk of violating drinking water maximum contaminant levels (MCLs).Water quality changes in the Ohio River were projected for 2050 using Monte Carlo simulation and the WTP model was used to evaluate the effects of water quality changes on design and operation. Results indicate that the existing Miller WTP might not meet Safe Drinking Water Act MCL requirements for certain extreme future conditions. However, it was found that the risk of MCL violations under future conditions could be controlled by enhancing existing WTP design and operation or by process retrofitting and modification.

The Effect of Interior Design Improvements on the Quality of Learning for Graduate Level Military Officer Students

DTIC Science & Technology

1991-05-13

for the model classroom. Nevertheless, findings about the impact of interior design improvements 14 on student perceptions about the physical...from the impact of the model classroom interior design improvements on student perceptions about their physical learning environment. Delimitations of...their perceptions about places through personal experience. The intensity and quality of these personal experiences have a greater impact on people’s

Quality Assurance Project Plan - Modeling the Impact of Hydraulic Fracturing on Water Resources Based on Water Acquisition Scenarios

EPA Pesticide Factsheets

This planning document describes the quality assurance/quality control activities and technical requirements that will be used during the research study. The goal of this project is to evaluate the potential impacts of large volume water withdrawals.

The Impact of Globalization on a Country's Quality of Life: Toward an Integrated Model

ERIC Educational Resources Information Center

Sirgy, M. Joseph; Lee, Dong-Jin; Miller, Chad; Littlefield, James E.

2004-01-01

The purpose of the paper is to develop a set of theoretical propositions to explain the impact of globalization on a country's quality of life (QOL). In this paper, we describe how globalization impacts the quality of life of residents of a country by first articulating the globalization construct (in terms of inflows and outflows of goods,…

The Impact of Internet Health Information on Patient Compliance: A Research Model and an Empirical Study.

PubMed

Laugesen, John; Hassanein, Khaled; Yuan, Yufei

2015-06-11

Patients have been increasingly seeking and using Internet health information to become more active in managing their own health in a partnership with their physicians. This trend has both positive and negative effects on the interactions between patients and their physicians. Therefore, it is important to understand the impact that the increasing use of Internet health information has on the patient-physician relationship and patients' compliance with their treatment regimens. This study examines the impact of patients' use of Internet health information on various elements that characterize the interactions between a patient and her/his physician through a theoretical model based on principal-agent theory and the information asymmetry perspective. A survey-based study consisting of 225 participants was used to validate a model through various statistical techniques. A full assessment of the measurement model and structural model was completed in addition to relevant post hoc analyses. This research revealed that both patient-physician concordance and perceived information asymmetry have significant effects on patient compliance, with patient-physician concordance exhibiting a considerably stronger relationship. Additionally, both physician quality and Internet health information quality have significant effects on patient-physician concordance, with physician quality exhibiting a much stronger relationship. Finally, only physician quality was found to have a significant impact on perceived information asymmetry, whereas Internet health information quality had no impact on perceived information asymmetry. Overall, this study found that physicians can relax regarding their fears concerning patient use of Internet health information because physician quality has the greatest impact on patients and their physician coming to an agreement on their medical situation and recommended treatment regimen as well as patient's compliance with their physician's advice when compared to the impact that Internet health information quality has on these same variables. The findings also indicate that agreement between the patient and physician on the medical situation and treatment is much more important to compliance than the perceived information gap between the patient and physician (ie, the physician having a higher level of information in comparison to the patient). In addition, the level of agreement between a patient and their physician regarding the medical situation is more reliant on the perceived quality of their physician than on the perceived quality of Internet health information used. This research found that only the perceived quality of the physician has a significant relationship with the perceived information gap between the patient and their physician and the quality of the Internet health information has no relationship with this perceived information gap.

Modelling the impacts of agricultural management practices on river water quality in Eastern England.

PubMed

Taylor, Sam D; He, Yi; Hiscock, Kevin M

2016-09-15

Agricultural diffuse water pollution remains a notable global pressure on water quality, posing risks to aquatic ecosystems, human health and water resources and as a result legislation has been introduced in many parts of the world to protect water bodies. Due to their efficiency and cost-effectiveness, water quality models have been increasingly applied to catchments as Decision Support Tools (DSTs) to identify mitigation options that can be introduced to reduce agricultural diffuse water pollution and improve water quality. In this study, the Soil and Water Assessment Tool (SWAT) was applied to the River Wensum catchment in eastern England with the aim of quantifying the long-term impacts of potential changes to agricultural management practices on river water quality. Calibration and validation were successfully performed at a daily time-step against observations of discharge, nitrate and total phosphorus obtained from high-frequency water quality monitoring within the Blackwater sub-catchment, covering an area of 19.6 km(2). A variety of mitigation options were identified and modelled, both singly and in combination, and their long-term effects on nitrate and total phosphorus losses were quantified together with the 95% uncertainty range of model predictions. Results showed that introducing a red clover cover crop to the crop rotation scheme applied within the catchment reduced nitrate losses by 19.6%. Buffer strips of 2 m and 6 m width represented the most effective options to reduce total phosphorus losses, achieving reductions of 12.2% and 16.9%, respectively. This is one of the first studies to quantify the impacts of agricultural mitigation options on long-term water quality for nitrate and total phosphorus at a daily resolution, in addition to providing an estimate of the uncertainties of those impacts. The results highlighted the need to consider multiple pollutants, the degree of uncertainty associated with model predictions and the risk of unintended pollutant impacts when evaluating the effectiveness of mitigation options, and showed that high-frequency water quality datasets can be applied to robustly calibrate water quality models, creating DSTs that are more effective and reliable. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Modeling to Evaluate Contribution of Oil and Gas Emissions to Air Pollution.

PubMed

Thompson, Tammy M; Shepherd, Donald; Stacy, Andrea; Barna, Michael G; Schichtel, Bret A

2017-04-01

Oil and gas production in the Western United States has increased considerably over the past 10 years. While many of the still limited oil and gas impact assessments have focused on potential human health impacts, the typically remote locations of production in the Intermountain West suggests that the impacts of oil and gas production on national parks and wilderness areas (Class I and II areas) could also be important. To evaluate this, we utilize the Comprehensive Air quality Model with Extensions (CAMx) with a year-long modeling episode representing the best available representation of 2011 meteorology and emissions for the Western United States. The model inputs for the 2011 episodes were generated as part of the Three State Air Quality Study (3SAQS). The study includes a detailed assessment of oil and gas (O&G) emissions in Western States. The year-long modeling episode was run both with and without emissions from O&G production. The difference between these two runs provides an estimate of the contribution of the O&G production to air quality. These data were used to assess the contribution of O&G to the 8 hour average ozone concentrations, daily and annual fine particulate concentrations, annual nitrogen deposition totals and visibility in the modeling domain. We present the results for the Class I and II areas in the Western United States. Modeling results suggest that emissions from O&G activity are having a negative impact on air quality and ecosystem health in our National Parks and Class I areas. In this research, we use a modeling framework developed for oil and gas evaluation in the western United States to determine the modeled impacts of emissions associated with oil and gas production on air pollution metrics. We show that oil and gas production may have a significant negative impact on air quality and ecosystem health in some national parks and other Class I areas in the western United States. Our findings are of particular interest to federal land managers as well as regulators in states heavy in oil and gas production as they consider control strategies to reduce the impact of development.

Modeling the Impacts of Global Climate and Regional Land Use Change on Regional Climate, Air Quality and Public Health in the New York Metropolitan Region

NASA Astrophysics Data System (ADS)

Rosenthal, J. E.; Knowlton, K. M.; Kinney, P. L.

2002-12-01

There is an imminent need to downscale the global climate models used by international consortiums like the IPCC (Intergovernmental Panel on Climate Change) to predict the future regional impacts of climate change. To meet this need, a "place-based" climate model that makes specific regional projections about future environmental conditions local inhabitants could face is being created by the Mailman School of Public Health at Columbia University, in collaboration with other researchers and universities, for New York City and the 31 surrounding counties. This presentation describes the design and initial results of this modeling study, aimed at simulating the effects of global climate change and regional land use change on climate and air quality over the northeastern United States in order to project the associated public health impacts in the region. Heat waves and elevated concentrations of ozone and fine particles are significant current public health stressors in the New York metropolitan area. The New York Climate and Health Project is linking human dimension and natural sciences models to assess the potential for future public health impacts from heat stress and air quality, and yield improved tools for assessing climate change impacts. The model will be applied to the NY metropolitan east coast region. The following questions will be addressed: 1. What changes in the frequency and severity of extreme heat events are likely to occur over the next 80 years due to a range of possible scenarios of land use and land cover (LU/LC) and climate change in the region? 2. How might the frequency and severity of episodic concentrations of ozone (O3) and airborne particulate matter smaller than 2.5 æm in diameter (PM2.5) change over the next 80 years due to a range of possible scenarios of land use and climate change in the metropolitan region? 3. What is the range of possible human health impacts of these changes in the region? 4. How might projected future human exposures and responses to heat stress and air quality differ as a function of socio-economic status and race/ethnicity across the region? The model systems used for this study are the Goddard Institute for Space Studies (GISS) Global Atmosphere-Ocean Model; the Regional Atmospheric Modeling System (RAMS) and PennState/NCAR MM5 mesoscale meteorological models; the SLEUTH land use model; the Sparse Matrix Operator Kernel Emissions Modeling System (SMOKE); the Community Multiscale Air Quality (CMAQ) and Comprehensive Air Quality Model with Extensions (CAMx) models for simulating regional air quality; and exposure-risk coefficients for assessing population health impacts based on exposure to extreme heat, fine particulates (PM2.5) and ozone. Two different IPCC global emission scenarios and two different regional land use growth scenarios are considered in the simulations, spanning a range of possible futures. In addition to base simulations for selected time periods in the decade 1990 - 2000, the integrated model is used to simulate future scenarios in the 2020s, 2050s, and 2080s. Predictions from both the meteorological models and the air quality models are compared against available observations for the simulations in the 1990s to establish baseline model performance. A series of sensitivity tests will address whether changes in meteorology due to global climate change, changes in regional land use, or changes in emissions have the largest impact on predicted ozone and particulate matter concentrations.

Identification and Assessment of Potential Water Quality Impact Factors for Drinking-Water Reservoirs

PubMed Central

Gu, Qing; Deng, Jinsong; Wang, Ke; Lin, Yi; Li, Jun; Gan, Muye; Ma, Ligang; Hong, Yang

2014-01-01

Various reservoirs have been serving as the most important drinking water sources in Zhejiang Province, China, due to the uneven distribution of precipitation and severe river pollution. Unfortunately, rapid urbanization and industrialization have been continuously challenging the water quality of the drinking-water reservoirs. The identification and assessment of potential impacts is indispensable in water resource management and protection. This study investigates the drinking water reservoirs in Zhejiang Province to better understand the potential impact on water quality. Altogether seventy-three typical drinking reservoirs in Zhejiang Province encompassing various water storage levels were selected and evaluated. Using fifty-two reservoirs as training samples, the classification and regression tree (CART) method and sixteen comprehensive variables, including six sub-sets (land use, population, socio-economy, geographical features, inherent characteristics, and climate), were adopted to establish a decision-making model for identifying and assessing their potential impacts on drinking-water quality. The water quality class of the remaining twenty-one reservoirs was then predicted and tested based on the decision-making model, resulting in a water quality class attribution accuracy of 81.0%. Based on the decision rules and quantitative importance of the independent variables, industrial emissions was identified as the most important factor influencing the water quality of reservoirs; land use and human habitation also had a substantial impact on water quality. The results of this study provide insights into the factors impacting the water quality of reservoirs as well as basic information for protecting reservoir water resources. PMID:24919129

Identification and assessment of potential water quality impact factors for drinking-water reservoirs.

PubMed

Gu, Qing; Deng, Jinsong; Wang, Ke; Lin, Yi; Li, Jun; Gan, Muye; Ma, Ligang; Hong, Yang

2014-06-10

Various reservoirs have been serving as the most important drinking water sources in Zhejiang Province, China, due to the uneven distribution of precipitation and severe river pollution. Unfortunately, rapid urbanization and industrialization have been continuously challenging the water quality of the drinking-water reservoirs. The identification and assessment of potential impacts is indispensable in water resource management and protection. This study investigates the drinking water reservoirs in Zhejiang Province to better understand the potential impact on water quality. Altogether seventy-three typical drinking reservoirs in Zhejiang Province encompassing various water storage levels were selected and evaluated. Using fifty-two reservoirs as training samples, the classification and regression tree (CART) method and sixteen comprehensive variables, including six sub-sets (land use, population, socio-economy, geographical features, inherent characteristics, and climate), were adopted to establish a decision-making model for identifying and assessing their potential impacts on drinking-water quality. The water quality class of the remaining twenty-one reservoirs was then predicted and tested based on the decision-making model, resulting in a water quality class attribution accuracy of 81.0%. Based on the decision rules and quantitative importance of the independent variables, industrial emissions was identified as the most important factor influencing the water quality of reservoirs; land use and human habitation also had a substantial impact on water quality. The results of this study provide insights into the factors impacting the water quality of reservoirs as well as basic information for protecting reservoir water resources.

Differences Between Magnitudes and Health Impacts of BC Emissions Across the United States Using 12 km Scale Seasonal Source Apportionment

EPA Science Inventory

Recent assessments have analyzed the health impacts of PM2.5 from emissions from different locations and sectors using simplified or reduced-form air quality models. Here we present an alternative approach using the adjoint of the Community Multiscale Air Quality (CMAQ) model, wh...

“Impact of CB6 and CB05TU chemical mechanisms on air quality”

EPA Science Inventory

“Impacts of CB6 and CB05TU chemical mechanisms on air quality”In this study, we incorporate the newly developed Carbon Bond chemical mechanism (CB6) into the Community Multiscale Air Quality modeling system (CMAQv5.0.1) and perform air quality model simulations with the CB6 and t...

Impacts of crop growth dynamics on soil quality at the regional scale

NASA Astrophysics Data System (ADS)

Gobin, Anne

2014-05-01

Agricultural land use and in particular crop growth dynamics can greatly affect soil quality. Both the amount of soil lost from erosion by water and soil organic matter are key indicators for soil quality. The aim was to develop a modelling framework for quantifying the impacts of crop growth dynamics on soil quality at the regional scale with test case Flanders. A framework for modelling the impacts of crop growth on soil erosion and soil organic matter was developed by coupling the dynamic crop cover model REGCROP (Gobin, 2010) to the PESERA soil erosion model (Kirkby et al., 2009) and to the RothC carbon model (Coleman and Jenkinson, 1999). All three models are process-based, spatially distributed and intended as a regional diagnostic tool. A geo-database was constructed covering 10 years of crop rotation in Flanders using the IACS parcel registration (Integrated Administration and Control System). Crop allometric models were developed from variety trials to calculate crop residues for common crops in Flanders and subsequently derive stable organic matter fluxes to the soil. Results indicate that crop growth dynamics and crop rotations influence soil quality for a very large percentage. soil erosion mainly occurs in the southern part of Flanders, where silty to loamy soils and a hilly topography are responsible for soil loss rates of up to 40 t/ha. Parcels under maize, sugar beet and potatoes are most vulnerable to soil erosion. Crop residues of grain maize and winter wheat followed by catch crops contribute most to the total carbon sequestered in agricultural soils. For the same rotations carbon sequestration is highest on clay soils and lowest on sandy soils. This implies that agricultural policies that impact on agricultural land management influence soil quality for a large percentage. The coupled REGCROP-PESERA-ROTHC model allows for quantifying the impact of seasonal and year-to-year crop growth dynamics on soil quality. When coupled to a multi-annual crop rotation database both spatial and temporal analysis becomes possible and allows for decision support at both farm and regional level. The framework is therefore suited for further scenario analysis and impact assessment. The research is funded by the Belgian Science Policy Organisation (Belspo) under contract nr SD/RI/03A.

Assessment of impacts of agricultural and climate change scenarios on watershed water quantity and quality, and crop production

NASA Astrophysics Data System (ADS)

Teshager, Awoke D.; Gassman, Philip W.; Schoof, Justin T.; Secchi, Silvia

2016-08-01

Modeling impacts of agricultural scenarios and climate change on surface water quantity and quality provides useful information for planning effective water, environmental and land use policies. Despite the significant impacts of agriculture on water quantity and quality, limited literature exists that describes the combined impacts of agricultural land use change and climate change on future bioenergy crop yields and watershed hydrology. In this study, the soil and water assessment tool (SWAT) eco-hydrological model was used to model the combined impacts of five agricultural land use change scenarios and three downscaled climate pathways (representative concentration pathways, RCPs) that were created from an ensemble of eight atmosphere-ocean general circulation models (AOGCMs). These scenarios were implemented in a well-calibrated SWAT model for the intensively farmed and tiled Raccoon River watershed (RRW) located in western Iowa. The scenarios were executed for the historical baseline, early century, mid-century and late century periods. The results indicate that historical and more corn intensive agricultural scenarios with higher CO2 emissions consistently result in more water in the streams and greater water quality problems, especially late in the 21st century. Planting more switchgrass, on the other hand, results in less water in the streams and water quality improvements relative to the baseline. For all given agricultural landscapes simulated, all flow, sediment and nutrient outputs increase from early-to-late century periods for the RCP4.5 and RCP8.5 climate scenarios. We also find that corn and switchgrass yields are negatively impacted under RCP4.5 and RCP8.5 scenarios in the mid- and late 21st century.

A quality-based cost model for new electronic systems and products

NASA Astrophysics Data System (ADS)

Shina, Sammy G.; Saigal, Anil

1998-04-01

This article outlines a method for developing a quality-based cost model for the design of new electronic systems and products. The model incorporates a methodology for determining a cost-effective design margin allocation for electronic products and systems and its impact on manufacturing quality and cost. A spreadsheet-based cost estimating tool was developed to help implement this methodology in order for the system design engineers to quickly estimate the effect of design decisions and tradeoffs on the quality and cost of new products. The tool was developed with automatic spreadsheet connectivity to current process capability and with provisions to consider the impact of capital equipment and tooling purchases to reduce the product cost.

Air quality and future energy system planning

NASA Astrophysics Data System (ADS)

Sobral Mourao, Zenaida; Konadu, Dennis; Lupton, Rick

2016-04-01

Ambient air pollution has been linked to an increasing number of premature deaths throughout the world. Projected increases in demand for food, energy resources and manufactured products will likely contribute to exacerbate air pollution with an increasing impact on human health, agricultural productivity and climate change. Current events such as tampering emissions tests by VW car manufacturers, failure to comply with EU Air Quality directives and WHO guidelines by many EU countries, the problem of smog in Chinese cities and new industrial emissions regulations represent unique challenges but also opportunities for regulators, local authorities and industry. However current models and practices of energy and resource use do not consider ambient air impacts as an integral part of the planing process. Furthermore the analysis of drivers, sources and impacts of air pollution is often fragmented, difficult to understand and lacks effective visualization tools that bring all of these components together. This work aims to develop a model that links impacts of air quality on human health and ecosystems to current and future developments in the energy system, industrial and agricultural activity and patterns of land use. The model will be added to the ForeseerTM tool, which is an integrated resource analysis platform that has been developed at the University of Cambridge initially with funding from BP and more recently through the EPSRC funded Whole Systems Energy Modeling (WholeSEM) project. The basis of the tool is a set of linked physical models for energy, water and land, including the technologies that are used to transform these resources into final services such as housing, food, transport and household goods. The new air quality model will explore different feedback effects between energy, land and atmospheric systems with the overarching goal of supporting better communication about the drivers of air quality and to incorporate concerns about air quality into energy system planning. Some example applications of this work are: (1) to discover conflicts and synergies between air quality regulations and future developments in the energy system and land use change; (2) to show the drivers of air quality in a given spatial context; (3) to explore effective ways to visualize impacts of different energy, land use and emissions control policies on air quality. An initial test case for the Bay Area in California will be presented, extending the scope of the existing California ForeseerTM tool to identify impacts of different policies within the water-energy-land nexus on local air quality.

78 FR 9703 - Food and Drug Administration/Xavier University PharmaLink Conference-Quality in a Global Supply...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-11

... the Office of the Commissioner on the implementation of the FDA Safety and Innovation Act, Business Impact of Outsourcing, Supplier Management Models that Work, Implementing Quality by Design (QbD... quality and management through the following topics: Beyond our Borders--Maximizing the Impact of FDA's...

Quality Management in Schools: Analysis of Mediating Factors

ERIC Educational Resources Information Center

Díez, Fernando; Iraurgi, Ioseba; Sanchez, Aurelio Villa

2018-01-01

The objective of this study is to contribute to Quality Management Systems (QMS) and their impact on schools in the Basque Country, Spain. Specifically, it analyses two models: the EFQM Excellence Model, which originated in the business world, and the Integrated Quality Project (IQP) Model, which has a humanistic focus and arose from an…

The predicted impact of VOCs from Marijuana cultivation operations on ozone concentrations in great Denver, CO.

NASA Astrophysics Data System (ADS)

Wang, C. T.; Vizuete, W.; Wiedinmyer, C.; Ashworth, K.

2016-12-01

Colorado is the first the marijuana legal states in the United States since 2014. As a result, thousands of legal Marijuana cultivation operations are at great Denver area now. Those Marijuana cultivation operations could be the potential to release a lot of biogenic VOCs, such as monoterpene(C10H16), alpha-pinene, and D-limonene. Those alkene species could rapidly increase the peroxy radicals and chemical reactions in the atmosphere, especially in the urban area which belong to VOC-limited ozone regime. These emissions will increase the ozone in Denver city, where is ozone non-attainment area. Some previous research explained the marijuana smoke and indoor air quality (Martyny, Serrano, Schaeffer, & Van Dyke, 2013) and the smell of marijuana chemical compounds(Rice & Koziel, 2015). However, there have been no studies discuss on identifying and assessing emission rate from marijuana and how those species impact on atmospheric chemistry and ozone concentration, and the marijuana emissions have been not considered in the national emission inventory, either. This research will use air quality model to identify the possibility of ozone impact by marijuana cultivation emission. The Comprehensive Air Quality Model with Extensions, CAMx, are applied for this research to identify the impact of ozone concentration. This model is government regulatory model based on the Three-State Air Quality Modeling Study (3SAQS), which developed by UNC-Chapel Hill and ENVIRON in 2012. This model is used for evaluation and regulate the ozone impact in ozone non-attainment area, Denver city. The details of the 3SAQS model setup and protocol can be found in the 3SAQS report(UNC-IE, 2013). For the marijuana emission study scenarios, we assumed the monoterpene (C10H16) is the only emission species in air quality model and identify the ozone change in the model by the different quantity of emission rate from marijuana cultivation operations.

Environmental impact of geopressure - geothermal cogeneration facility on wetland resources and socioeconomic characteristics in Louisiana Gulf Coast region. Final report, October 10, 1983-September 31, 1984

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

Smalley, A.M.; Saleh, F.M.S.; Fontenot, M.

1984-08-01

Baseline data relevant to air quality are presented. The following are also included: geology and resource assessment, design well prospects in southwestern Louisiana, water quality monitoring, chemical analysis subsidence, microseismicity, geopressure-geothermal subsidence modeling, models of compaction and subsidence, sampling handling and preparation, brine chemistry, wetland resources, socioeconomic characteristics, impacts on wetlands, salinity, toxic metals, non-metal toxicants, temperature, subsidence, and socioeconomic impacts. (MHR)

Urban-rural variations in air quality and health impacts in northern India

NASA Astrophysics Data System (ADS)

Karambelas, A. N.; Holloway, T.; Fiore, A. M.; Kinney, P.; DeFries, R. S.; Kiesewetter, G.; Heyes, C.

2017-12-01

Ambient air pollution in India is a severe problem, contributing to negative health impacts and early death. Ground-based monitors often used to quantify health impacts are often located in urban regions, however approximately 70% of India's population resides in rural areas. We use high-resolution concentrations from the regional Community Multi-scale Air Quality (CMAQ) model over densely-populated northern India to estimate air quality and health impacts due to anthropogenic emission sectors separately for urban and rural regions. Modeled concentrations inform relative risk calculations and exposure estimates as performed in the Global Burden of Disease. Anthropogenic emissions from the International Institute for Applied Systems Analysis (IIASA) Greenhouse Gas-Air Pollution Interactions and Synergies (GAINS) model following version 5a of the Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants project gridding structure are updated to reflect urban- and rural-specific activity information for transportation and residential combustion, and industrial and electrical generating unit location and magnitude information. We estimate 314,000 (95% Confidence Interval: 304,000—323,000) and 58,000 (CI: 39,000—70,000) adults (25 years or older) die prematurely each year from PM2.5 and O3 respectively in northern India, with the greatest impacts along the Indo-Gangetic Plain. Using urban and rural population distributions, we estimate that the majority of premature deaths resulting from PM2.5 and O3 are in rural (292,000) as opposed to urban (79,000) regions. These findings indicate the need for designing monitoring networks and ground-based health studies in rural areas of India to more accurately quantify the true health implications of ambient air pollution, in addition to supporting model evaluation. Using this urban-versus-rural emissions framework, we are assessing anthropogenic contributions to regional air quality and health impacts, and examining mitigation strategies to reduce anthropogenic emissions, improve air quality, and reduce PM2.5 and O3 attributable premature death in the near-term.

Modeled Oil and Gas Atmospheric Impacts in National Parks and Wilderness Areas in the Western US

NASA Astrophysics Data System (ADS)

Thompson, T. M.; Barna, M. G.; Schichtel, B. A.; Vimont, J.; Moore, C. T.

2014-12-01

Oil and gas production in the Western United States has increased considerably over the past 10 years. While many of the still limited oil and gas impact assessments have focused on potential human health impacts, the typically remote locations of production in the Intermountain West suggests that the impacts of oil and gas production on national parks and wilderness areas (class 1&2 areas) could also be important. To evaluate this, we utilize the Comprehensive Air quality Model with Extensions (CAMx) with two year-long modeling episodes representing 2008 and 2011, meteorology and emissions. The model inputs for the 2008 and 2011 episodes were generated as part of the West-wide Jump-start Air Quality Modeling Study (WestJumpAQMS) and Three State Air Quality Study (3SAQS) respectively. Both studies included a detailed assessment of oil and gas (O&G) emissions in Western States for the respective years. Each year-long modeling episode was run both with and without emissions from O&G production. The difference between these two runs provides an estimate of the contribution of the O&G production to air quality. These data were used to assess the contribution of O&G to the 8 hour average ozone concentrations, daily and annual fine particulate concentrations, annual nitrogen deposition totals and visibility in the modeling domain. We present the results for the class 1&2 areas in the Western US. We also present temporal trends of O&G impacts, differentiating between trends in urban and rural areas.

Validation of smoke plume rise models using ground based lidar

Treesearch

Cyle E. Wold; Shawn Urbanski; Vladimir Kovalev; Alexander Petkov; Wei Min Hao

2010-01-01

Biomass fires can significantly degrade regional air quality. Plume rise height is one of the critical factors determining the impact of fire emissions on air quality. Plume rise models are used to prescribe the vertical distribution of fire emissions which are critical input for smoke dispersion and air quality models. The poor state of model evaluation is due in...

A longitudinal study of clinical peer review's impact on quality and safety in U.S. hospitals.

PubMed

Edwards, Marc T

2013-01-01

Clinical peer review is the dominant method of event analysis in U.S. hospitals. It is pivotal to medical staff efforts to improve quality and safety, yet the quality assurance process model that has prevailed for the past 30 years evokes fear and is fundamentally antithetical to a culture of safety. Two prior national studies characterized a quality improvement model that corrects this dysfunction but failed to demonstrate progress toward its adoption despite a high rate of program change between 2007 and 2009. This study's online survey of 470 organizations participating in either of the prior studies further assessed relationships between clinical peer review program factors, including the degree of conformance to the quality improvement model (the QI model score), and subjectively measured program impact variables. Among the 300 hospitals (64%) that responded, the median QI model score was only 60 on a 100-point scale. Scores increased somewhat for the 2007 cohort (mean pair-wise difference of 5.9 [2-10]), but not for the 2009 cohort. The QI model is expanded as the result of the finding that self-reporting of adverse events, near misses, and hazardous conditions--an essential practice in high-reliability organizations--is no longer rare in hospitals. Self-reporting and the quality of case review are additional multivariate predictors of the perceived ongoing impact of clinical peer review on quality and safety, medical staff perceptions of the program, and medical staff engagement in quality and safety initiatives. Hospital leaders and trustees who seek to improve patient outcomes should facilitate the adoption of this best practice model for clinical peer review.

The Impact of Internet Health Information on Patient Compliance: A Research Model and an Empirical Study

PubMed Central

Hassanein, Khaled; Yuan, Yufei

2015-01-01

Background Patients have been increasingly seeking and using Internet health information to become more active in managing their own health in a partnership with their physicians. This trend has both positive and negative effects on the interactions between patients and their physicians. Therefore, it is important to understand the impact that the increasing use of Internet health information has on the patient-physician relationship and patients’ compliance with their treatment regimens. Objective This study examines the impact of patients’ use of Internet health information on various elements that characterize the interactions between a patient and her/his physician through a theoretical model based on principal-agent theory and the information asymmetry perspective. Methods A survey-based study consisting of 225 participants was used to validate a model through various statistical techniques. A full assessment of the measurement model and structural model was completed in addition to relevant post hoc analyses. Results This research revealed that both patient-physician concordance and perceived information asymmetry have significant effects on patient compliance, with patient-physician concordance exhibiting a considerably stronger relationship. Additionally, both physician quality and Internet health information quality have significant effects on patient-physician concordance, with physician quality exhibiting a much stronger relationship. Finally, only physician quality was found to have a significant impact on perceived information asymmetry, whereas Internet health information quality had no impact on perceived information asymmetry. Conclusions Overall, this study found that physicians can relax regarding their fears concerning patient use of Internet health information because physician quality has the greatest impact on patients and their physician coming to an agreement on their medical situation and recommended treatment regimen as well as patient’s compliance with their physician’s advice when compared to the impact that Internet health information quality has on these same variables. The findings also indicate that agreement between the patient and physician on the medical situation and treatment is much more important to compliance than the perceived information gap between the patient and physician (ie, the physician having a higher level of information in comparison to the patient). In addition, the level of agreement between a patient and their physician regarding the medical situation is more reliant on the perceived quality of their physician than on the perceived quality of Internet health information used. This research found that only the perceived quality of the physician has a significant relationship with the perceived information gap between the patient and their physician and the quality of the Internet health information has no relationship with this perceived information gap. PMID:26068214

Impact of reduced mass of light commercial vehicles on fuel consumption, CO2 emissions, air quality, and socio-economic costs.

PubMed

Cecchel, S; Chindamo, D; Turrini, E; Carnevale, C; Cornacchia, G; Gadola, M; Panvini, A; Volta, M; Ferrario, D; Golimbioschi, R

2018-02-01

This study presents a modelling system to evaluate the impact of weight reduction in light commercial vehicles with diesel engines on air quality and greenhouse gas emissions. The PROPS model assesses the emissions of one vehicle in the aforementioned category and its corresponding reduced-weight version. The results serve as an input to the RIAT+ tool, an air quality integrated assessment modelling system. This paper applies the tools in a case study in the Lombardy region (Italy) and discusses the input data pre-processing, the PROPS-RIAT+ modelling system runs, and the results. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantifying Co-benefits of Renewable Energy through Integrated Electricity and Air Quality Modeling

NASA Astrophysics Data System (ADS)

Abel, D.

2016-12-01

This work focuses on the coordination of electricity sector changes with air quality and health improvement strategies through the integration of electricity and air quality models. Two energy models are used to calculate emission perturbations associated with changes in generation technology (20% generation from solar photovoltaics) and demand (future electricity use under a warmer climate). Impacts from increased solar PV penetration are simulated with the electricity model GridView, in collaboration with the National Renewable Energy Laboratory (NREL). Generation results are used to scale power plant emissions from an inventory developed by the Lake Michigan Air Directors Consortium (LADCO). Perturbed emissions and are used to calculate secondary particulate matter with the Community Multiscale Air Quality (CMAQ) model. We find that electricity NOx and SO2 emissions decrease at a rate similar to the total fraction of electricity supplied by solar. Across the Eastern U.S. region, average PM2.5 is reduced 5% over the summer, with highest reduction in regions and on days of greater PM2.5. A similar approach evaluates the air quality impacts of elevated electricity demand under a warmer climate. Meteorology is selected from the North American Regional Climate Change Assessment Program (NARCCAP) and input to a building energy model, eQUEST, to assess electricity demand as a function of ambient temperature. The associated generation and emissions are calculated on a plant-by-plant basis by the MyPower power sector model. These emissions are referenced to the 2011 National Emissions Inventory to be modeled in CMAQ for the Eastern U.S. and extended to health impact evaluation with the Environmental Benefits Mapping and Analysis Program (BenMAP). All results focus on the air quality and health consequences of energy system changes, considering grid-level changes to meet climate and air quality goals.

Impact of Expert Teaching Quality on Novice Academic Performance in the Jigsaw Cooperative Learning Method

ERIC Educational Resources Information Center

Berger, Roland; Hänze, Martin

2015-01-01

We assessed the impact of expert students' instructional quality on the academic performance of novice students in 12th-grade physics classes organized in an expert model of cooperative learning ("jigsaw classroom"). The instructional quality of 129 expert students was measured by a newly developed rating system. As expected, when…

Multiscale predictions of aviation-attributable PM2.5 for U.S. airports modeled using CMAQ with plume-in-grid and an aircraft-specific 1-D emission model

EPA Science Inventory

Aviation activities represent an important and unique mode of transportation, but also impact air quality. In this study, we aim to quantify the impact of aircraft on air quality, focusing on aviation-attributable PM2.5 at scales ranging from local (a few kilometers) to continent...

MODELING ASSESSMENT OF THE IMPACT OF NITROGEN OXIDES EMISSION REDUCTIONS ON OZONE AIR QUALITY IN THE EASTERN UNITED STATES: OFFSETTING INCREASES IN ENERGY USE

EPA Science Inventory

The objective of this study is to examine changes in ambient ozone concentrations estimated by a photochemical air quality model in response to the NOx emission reductions imposed on the utility sector. To accomplish this task, CMAQ air quality model simulations were performe...

Air quality impacts of projections of natural gas-fired distributed generation

NASA Astrophysics Data System (ADS)

Horne, Jeremy R.; Carreras-Sospedra, Marc; Dabdub, Donald; Lemar, Paul; Nopmongcol, Uarporn; Shah, Tejas; Yarwood, Greg; Young, David; Shaw, Stephanie L.; Knipping, Eladio M.

2017-11-01

This study assesses the potential impacts on emissions and air quality from the increased adoption of natural gas-fired distributed generation of electricity (DG), including displacement of power from central power generation, in the contiguous United States. The study includes four major tasks: (1) modeling of distributed generation market penetration; (2) modeling of central power generation systems; (3) modeling of spatially and temporally resolved emissions; and (4) photochemical grid modeling to evaluate the potential air quality impacts of increased DG penetration, which includes both power-only DG and combined heat and power (CHP) units, for 2030. Low and high DG penetration scenarios estimate the largest penetration of future DG units in three regions - New England, New York, and California. Projections of DG penetration in the contiguous United States estimate 6.3 GW and 24 GW of market adoption in 2030 for the low DG penetration and high DG penetration scenarios, respectively. High DG penetration (all of which is natural gas-fired) serves to offset 8 GW of new natural gas combined cycle (NGCC) units, and 19 GW of solar photovoltaic (PV) installations by 2030. In all scenarios, air quality in the central United States and the northwest remains unaffected as there is little to no DG penetration in those states. California and several states in the northeast are the most impacted by emissions from DG units. Peak increases in maximum daily 8-h average ozone concentrations exceed 5 ppb, which may impede attainment of ambient air quality standards. Overall, air quality impacts from DG vary greatly based on meteorological conditions, proximity to emissions sources, the number and type of DG installations, and the emissions factors used for DG units.

Impact of Asian Dust on Climate and Air Quality

NASA Technical Reports Server (NTRS)

Chin, Mian; Tan, Qian; Diehl, Thomas; Yu, Hongbin

2010-01-01

Dust generated from Asian permanent desert and desertification areas can be efficiently transported around the globe, making significant radiative impact through their absorbing and scattering solar radiation and through their deposition on snow and ice to modify the surface albedo. Asian dust is also a major concern of surface air quality not only in the source and immediate downwind regions but also areas thousands of miles away across the Pacific. We present here a global model, GOCART, analysis of data from satellite remote sensing instrument (MODIS, MISR, CALIPSO, OMI) and other observations on Asian dust sources, transport, and deposition, and use the model to assess the Asian dust impact on global climate and air quality.

Trace Gas/Aerosol Boundary Concentrations and their Impacts on Continental-scale AQMEII Modelling Domains

EPA Science Inventory

Over twenty modeling groups are participating in the Air Quality Model Evaluation International Initiative (AQMEII) in which a variety of mesoscale photochemical and aerosol air quality modeling systems are being applied to continental-scale domains in North America and Europe fo...

Recent experience with the CQE{trademark}

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

Harrison, C.D.; Kehoe, D.B.; O`Connor, D.C.

1997-12-31

CQE (the Coal Quality Expert) is a software tool that brings a new level of sophistication to fuel decisions by seamlessly integrating the system-wide effects of fuel purchase decisions on power plant performance, emissions, and power generation costs. The CQE technology, which addresses fuel quality from the coal mine to the busbar and the stack, is an integration and improvement of predecessor software tools including: EPRI`s Coal Quality Information System, EPRI`s Coal Cleaning Cost Model, EPRI`s Coal Quality Impact Model, and EPRI and DOE models to predict slagging and fouling. CQE can be used as a stand-alone workstation or asmore » a network application for utilities, coal producers, and equipment manufacturers to perform detailed analyses of the impacts of coal quality, capital improvements, operational changes, and/or environmental compliance alternatives on power plant emissions, performance and production costs. It can be used as a comprehensive, precise and organized methodology for systematically evaluating all such impacts or it may be used in pieces with some default data to perform more strategic or comparative studies.« less

Assessing Impacts on Unplanned Hospitalisations of Care Quality and Access Using a Structural Equation Method: With a Case Study of Diabetes

PubMed Central

Congdon, Peter

2016-01-01

Background: Enhanced quality of care and improved access are central to effective primary care management of long term conditions. However, research evidence is inconclusive in establishing a link between quality of primary care, or access, and adverse outcomes, such as unplanned hospitalisation. Methods: This paper proposes a structural equation model for quality and access as latent variables affecting adverse outcomes, such as unplanned hospitalisations. In a case study application, quality of care (QOC) is defined in relation to diabetes, and the aim is to assess impacts of care quality and access on unplanned hospital admissions for diabetes, while allowing also for socio-economic deprivation, diabetes morbidity, and supply effects. The study involves 90 general practitioner (GP) practices in two London Clinical Commissioning Groups, using clinical quality of care indicators, and patient survey data on perceived access. Results: As a single predictor, quality of care has a significant negative impact on emergency admissions, and this significant effect remains when socio-economic deprivation and morbidity are allowed. In a full structural equation model including access, the probability that QOC negatively impacts on unplanned admissions exceeds 0.9. Furthermore, poor access is linked to deprivation, diminished QOC, and larger list sizes. Conclusions: Using a Bayesian inference methodology, the evidence from the analysis is weighted towards negative impacts of higher primary care quality and improved access on unplanned admissions. The methodology of the paper is potentially applicable to other long term conditions, and relevant when care quality and access cannot be measured directly and are better regarded as latent variables. PMID:27598184

Assessing Impacts on Unplanned Hospitalisations of Care Quality and Access Using a Structural Equation Method: With a Case Study of Diabetes.

PubMed

Congdon, Peter

2016-09-01

Enhanced quality of care and improved access are central to effective primary care management of long term conditions. However, research evidence is inconclusive in establishing a link between quality of primary care, or access, and adverse outcomes, such as unplanned hospitalisation. This paper proposes a structural equation model for quality and access as latent variables affecting adverse outcomes, such as unplanned hospitalisations. In a case study application, quality of care (QOC) is defined in relation to diabetes, and the aim is to assess impacts of care quality and access on unplanned hospital admissions for diabetes, while allowing also for socio-economic deprivation, diabetes morbidity, and supply effects. The study involves 90 general practitioner (GP) practices in two London Clinical Commissioning Groups, using clinical quality of care indicators, and patient survey data on perceived access. As a single predictor, quality of care has a significant negative impact on emergency admissions, and this significant effect remains when socio-economic deprivation and morbidity are allowed. In a full structural equation model including access, the probability that QOC negatively impacts on unplanned admissions exceeds 0.9. Furthermore, poor access is linked to deprivation, diminished QOC, and larger list sizes. Using a Bayesian inference methodology, the evidence from the analysis is weighted towards negative impacts of higher primary care quality and improved access on unplanned admissions. The methodology of the paper is potentially applicable to other long term conditions, and relevant when care quality and access cannot be measured directly and are better regarded as latent variables.

Assessing Cumulative Impacts of Coal Bed Methane Development on Surface Water Quality and its Suitability for Irrigation in the Powder River Basin

NASA Astrophysics Data System (ADS)

Dawson, H. E.

2003-12-01

This paper presents a mass balance approach to assessing the cumulative impacts of discharge from Coal Bed Methane (CBM) wells on surface water quality and its suitability for irrigation in the Powder River Basin. Key water quality parameters for predicting potential effects of CBM development on irrigated agriculture are sodicity, expressed as sodium adsorption ratio (SAR) and salinity, expressed as electrical conductivity (EC). The assessment was performed with the aid of a spreadsheet model, which was designed to estimate steady-state SAR and EC at gauged stream locations after mixing with CBM produced water. Model input included ambient stream water quality and flow, CBM produced water quality and discharge rates, conveyance loss (quantity of water loss that may occur between the discharge point and the receiving streams), beneficial uses, regulatory thresholds, and discharge allocation at state-line boundaries. Historical USGS data were used to establish ambient stream water quality and flow conditions. The resultant water quality predicted for each stream station included the cumulative discharge of CBM produced water in all reaches upstream of the station. Model output was presented in both tabular and graphical formats, and indicated the suitability of pre- and post-mixing water quality for irrigation. Advantages and disadvantages of the spreadsheet model are discussed. This approach was used by federal agencies to support the development of the January 2003 Environmental Impact Statements (EIS) for the Wyoming and Montana portions of the Powder River Basin.

Can There Ever Be Enough to Impact Water Quality? Evaluating BMPs in Elliot Ditch, Indiana Using the LTHIA-LID Model

NASA Astrophysics Data System (ADS)

Rahman, M. S.; Hoover, F. A.; Bowling, L. C.

2017-12-01

Elliot Ditch is an urban/urbanizing watershed located in the city of Lafayette, IN, USA. The city continues to struggle with stormwater management and combined sewer overflow (CSO) events. Several best-management practices (BMP) such as rain gardens, green roofs, and bioswales have been implemented in the watershed, but the level of adoption needed to achieve meaningful impact is currently unknown. This study's goal is to determine what level of BMP coverage is needed to impact water quality, whether meaningful impact is determined by achieving water quality targets or statistical significance. A power analysis was performed using water quality data for total suspended solids (TSS), E.coli, total phosphorus (TP) and nitrate (NO3-N) from Elliot Ditch from 2011 to 2015. The minimum detectable difference (MDD) was calculated as the percent reduction in load needed to detect a significant change in the watershed. The water quality targets were proposed by stakeholders as part of a watershed management planning process. The water quality targets and the MDD percentages were then compared to simulated load reductions due to BMP implementation using the Long-term Hydrologic Impact Assessment-Low Impact Development (LTHIA-LID) model. Seven baseline model scenarios were simulated by implementing the maximum number of each of six types of BMPs (rain barrels, permeable patios, green roofs, grassed swale/bioswales, bioretention/rain gardens, and porous pavement), as well as all the practices combined in the watershed. These provide the baseline for targeted implementation scenarios designed to determine if statistically and physically meaningful load reductions can be achieved through BMP implementation alone.

Application of Quality by Design to the characterization of the cell culture process of an Fc-Fusion protein.

PubMed

Rouiller, Yolande; Solacroup, Thomas; Deparis, Véronique; Barbafieri, Marco; Gleixner, Ralf; Broly, Hervé; Eon-Duval, Alex

2012-06-01

The production bioreactor step of an Fc-Fusion protein manufacturing cell culture process was characterized following Quality by Design principles. Using scientific knowledge derived from the literature and process knowledge gathered during development studies and manufacturing to support clinical trials, potential critical and key process parameters with a possible impact on product quality and process performance, respectively, were determined during a risk assessment exercise. The identified process parameters were evaluated using a design of experiment approach. The regression models generated from the data allowed characterizing the impact of the identified process parameters on quality attributes. The main parameters having an impact on product titer were pH and dissolved oxygen, while those having the highest impact on process- and product-related impurities and variants were pH and culture duration. The models derived from characterization studies were used to define the cell culture process design space. The design space limits were set in such a way as to ensure that the drug substance material would consistently have the desired quality. Copyright © 2012 Elsevier B.V. All rights reserved.

Coverage and quality: A comparison of Web of Science and Scopus databases for reporting faculty nursing publication metrics.

PubMed

Powell, Kimberly R; Peterson, Shenita R

Web of Science and Scopus are the leading databases of scholarly impact. Recent studies outside the field of nursing report differences in journal coverage and quality. A comparative analysis of nursing publications reported impact. Journal coverage by each database for the field of nursing was compared. Additionally, publications by 2014 nursing faculty were collected in both databases and compared for overall coverage and reported quality, as modeled by Scimajo Journal Rank, peer review status, and MEDLINE inclusion. Individual author impact, modeled by the h-index, was calculated by each database for comparison. Scopus offered significantly higher journal coverage. For 2014 faculty publications, 100% of journals were found in Scopus, Web of Science offered 82%. No significant difference was found in the quality of reported journals. Author h-index was found to be higher in Scopus. When reporting faculty publications and scholarly impact, academic nursing programs may be better represented by Scopus, without compromising journal quality. Programs with strong interdisciplinary work should examine all areas of strength to ensure appropriate coverage. Copyright © 2017 Elsevier Inc. All rights reserved.

Linking Global and Regional Models to Simulate U.S. Air Quality in the Year 2050

EPA Science Inventory

The potential impact of global climate change on future air quality in the United States is investigated with global and regional-scale models. Regional climate model scenarios are developed by dynamically downscaling the outputs from a global chemistry and climate model and are...

Linking Global to Regional Models to Assess Future Climate Impacts on Surface Ozone Concentrations in the United States

EPA Science Inventory

The UCD sectional aerosol model has been coupled to the CMAQ air quality model and used to simulate air quality in Tampa, Florida. Sea salt emissions are parameterized as a function of modeled wind speed and relative humidity. Modeled aerosol sulfate, nitrate, ammonium, sodium,...

Assessment of the emissions and air quality impacts of biomass and biogas use in California.

PubMed

Carreras-Sospedra, Marc; Williams, Robert; Dabdub, Donald

2016-02-01

It is estimated that there is sufficient in-state "technically" recoverable biomass to support nearly 4000 MW of bioelectricity generation capacity. This study assesses the emissions of greenhouse gases and air pollutants and resulting air quality impacts of new and existing bioenergy capacity throughout the state of California, focusing on feedstocks and advanced technologies utilizing biomass resources predominant in each region. The options for bioresources include the production of bioelectricity and renewable natural gas (NG). Emissions of criteria pollutants and greenhouse gases are quantified for a set of scenarios that span the emission factors for power generation and the use of renewable natural gas for vehicle fueling. Emissions are input to the Community Multiscale Air Quality (CMAQ) model to predict regional and statewide temporal air quality impacts from the biopower scenarios. With current technology and at the emission levels of current installations, maximum bioelectricity production could increase nitrogen oxide (NOx) emissions by 10% in 2020, which would cause increases in ozone and particulate matter concentrations in large areas of California. Technology upgrades would achieve the lowest criteria pollutant emissions. Conversion of biomass to compressed NG (CNG) for vehicles would achieve comparable emission reductions of criteria pollutants and minimize emissions of greenhouse gases (GHG). Air quality modeling of biomass scenarios suggest that applying technological changes and emission controls would minimize the air quality impacts of bioelectricity generation. And a shift from bioelectricity production to CNG production for vehicles would reduce air quality impacts further. From a co-benefits standpoint, CNG production for vehicles appears to provide the best benefits in terms of GHG emissions and air quality. This investigation provides a consistent analysis of air quality impacts and greenhouse gas emissions for scenarios examining increased biomass use. Further work involving economic assessment, seasonal or annual emissions and air quality modeling, and potential exposure analysis would help inform policy makers and industry with respect to further development and direction of biomass policy and bioenergy technology alternatives needed to meet energy and environmental goals in California.

Quality and price--impact on patient satisfaction.

PubMed

Pantouvakis, Angelos; Bouranta, Nancy

2014-01-01

The purpose of this paper is to synthesize existing quality-measurement models and applies them to healthcare by combining a Nordic service-quality with an American service performance model. Results are based on a questionnaire survey of 1,298 respondents. Service quality dimensions were derived and related to satisfaction by employing a multinomial logistic model, which allows prediction and service improvement. Qualitative and empirical evidence indicates that customer satisfaction and service quality are multi-dimensional constructs, whose quality components, together with convenience and cost, influence the customer's overall satisfaction. The proposed model identifies important quality and satisfaction issues. It also enables transitions between different responses in different studies to be compared.

NUMERICAL MODELS AS ENABLING TOOLS FOR TIDAL-STREAM ENERGY EXTRACTION AND ENVIRONMENTAL IMPACT ASSESSMENT

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

Yang, Zhaoqing; Wang, Taiping

This paper presents a modeling study conducted to evaluate tidal-stream energy extraction and its associated potential environmental impacts using a three-dimensional unstructured-grid coastal ocean model, which was coupled with a water-quality model and a tidal-turbine module.

Evaluating the Contribution of Natural Variability and Climate Model Response to Uncertainty in Projections of Climate Change Impacts on U.S. Air Quality

EPA Science Inventory

We examine the effects of internal variability and model response in projections of climate impacts on U.S. ground-level ozone across the 21st century using integrated global system modeling and global atmospheric chemistry simulations. The impact of climate change on air polluti...

Swimmer illness associated with marine water exposure and water quality indicators: impact of widely used assumptions

EPA Science Inventory

Studies of health risks associated with recreational water exposure require investigators to make choices about water quality indicator averaging techniques, exposure definitions, follow-up periods, and model specifications; but, investigators seldom describe the impact of these ...

Impacts of Residential Biofuel Emissions on Air Quality and Climate

NASA Astrophysics Data System (ADS)

Huang, Y.; Unger, N.; Harper, K.; Storelvmo, T.

2016-12-01

The residential biofuel sector is defined as fuelwood, agricultural residues and dung used for household cooking and heating. Aerosol emissions from this human activity play an important role affecting local, regional and global air quality, climate and public health. However, there are only few studies available that evaluate the net impacts and large uncertainties persist. Here we use the Community Atmosphere Model version 5.3 (CAM v5.3) within the Community Earth System Model version 1.2.2, to quantify the impacts of cook-stove biofuel emissions on air quality and climate. The model incorporates a novel advanced treatment of black carbon (BC) effects on mixed-phase/ice clouds. We update the global anthropogenic emission inventory in CAM v5.3 to a state-of-the-art emission inventory from the Greenhouse Gas-Air Pollution Interactions and Synergies integrated assessment model. Global in-situ and aircraft campaign observations for BC and organic carbon are used to evaluate and validate the model performance. Sensitivity simulations are employed to assess the impacts of residential biofuel emissions on regional and global direct and indirect radiative forcings in the contemporary world. We focus the analyses on several key regions including India, China and Sub-Saharan Africa.

Assessing Concentrations and Health Impacts of Air Quality Management Strategies: Framework for Rapid Emissions Scenario and Health impact ESTimation (FRESH-EST)

PubMed Central

Milando, Chad W.; Martenies, Sheena E.; Batterman, Stuart A.

2017-01-01

In air quality management, reducing emissions from pollutant sources often forms the primary response to attaining air quality standards and guidelines. Despite the broad success of air quality management in the US, challenges remain. As examples: allocating emissions reductions among multiple sources is complex and can require many rounds of negotiation; health impacts associated with emissions, the ultimate driver for the standards, are not explicitly assessed; and long dispersion model run-times, which result from the increasing size and complexity of model inputs, limit the number of scenarios that can be evaluated, thus increasing the likelihood of missing an optimal strategy. A new modeling framework, called the "Framework for Rapid Emissions Scenario and Health impact ESTimation" (FRESH-EST), is presented to respond to these challenges. FRESH-EST estimates concentrations and health impacts of alternative emissions scenarios at the urban scale, providing efficient computations from emissions to health impacts at the Census block or other desired spatial scale. In addition, FRESH-EST can optimize emission reductions to meet specified environmental and health constraints, and a convenient user interface and graphical displays are provided to facilitate scenario evaluation. The new framework is demonstrated in an SO2 non-attainment area in southeast Michigan with two optimization strategies: the first minimizes emission reductions needed to achieve a target concentration; the second minimizes concentrations while holding constant the cumulative emissions across local sources (e.g., an emissions floor). The optimized strategies match outcomes in the proposed SO2 State Implementation Plan without the proposed stack parameter modifications or shutdowns. In addition, the lower health impacts estimated for these strategies suggest the potential for FRESH-EST to identify pollution control alternatives for air quality management planning. PMID:27318620

Hydrological processes and model representation: impact of soft data on calibration

Treesearch

J.G. Arnold; M.A. Youssef; H. Yen; M.J. White; A.Y. Sheshukov; A.M. Sadeghi; D.N. Moriasi; J.L. Steiner; Devendra Amatya; R.W. Skaggs; E.B. Haney; J. Jeong; M. Arabi; P.H. Gowda

2015-01-01

Hydrologic and water quality models are increasingly used to determine the environmental impacts of climate variability and land management. Due to differing model objectives and differences in monitored data, there are currently no universally accepted procedures for model calibration and validation in the literature. In an effort to develop accepted model calibration...

HAWQS (Hydrologic and Water Quality System)

EPA Pesticide Factsheets

A water quantity and quality modeling system to evaluate the impacts of management alternatives, pollution control scenarios, and climate change scenarios on the quantity and quality of water at a national scale.

Relating health and climate impacts to grid-scale emissions using adjoint sensitivity modeling for the Climate and Clean Air Coalition

NASA Astrophysics Data System (ADS)

Henze, D. K.; Lacey, F.; Seltzer, M.; Vallack, H.; Kuylenstierna, J.; Bowman, K. W.; Anenberg, S.; Sasser, E.; Lee, C. J.; Martin, R.

2013-12-01

The Climate and Clean Air Coalition (CCAC) was initiated in 2012 to develop, understand and promote measures to reduce short lived climate forcers such as aerosol, ozone and methane. The Coalition now includes over 30 nations, and as a service to these nations is committed to providing a decision support toolkit that allows member nations to explore the benefits of a range of emissions mitigation measures in terms of the combined impacts on air quality and climate and so help in the development of their National Action Plans. Here we will present recent modeling work to support the development of the CCAC National Action Plans toolkit. Adjoint sensitivity analysis is presented as a means of efficiently relating air quality, climate and crop impacts back to changes in emissions from each species, sector and location at the grid-scale resolution of typical global air quality model applications. The GEOS-Chem adjoint model is used to estimate the damages per ton of emissions of PM2.5 related mortality, the impacts of ozone precursors on crops and ozone-related health effects, and the combined impacts of these species on regional surface temperature changes. We show how the benefits-per-emission vary spatially as a function of the surrounding environment, and how this impacts the overall benefit of sector-specific control strategies. We present initial findings for Bangladesh, as well as Mexico, Ghana and Colombia, some of the first countries to join the CCAC, and discuss general issues related to adjoint-based metrics for quantifying air quality and climate co-benefits.

Modeling prescribed fire impacts on local to regional air quality and potential climate effects

EPA Science Inventory

Biomass burning, including wildfires and prescribed burns, are of increasing concern due to the potential impacts on ambient air quality. The direct and indirect radiative forcings associated the particulate matter from biomass burning are also raising questions regarding the pot...

ANALYSIS OF AIR QUALITY DATA NEAR ROADWAYS USING A DISPERSION MODEL

EPA Science Inventory

A dispersion model was used to analyze measurements made during a field study conducted by the U.S. EPA in July and August 2006, to estimate the impact of highway emissions on air quality at distances of tens of meters from an eight-lane highway. The air quality measurements con...

Modeling the impacts of green infrastructure land use changes on air quality and meteorology case study and sensitivity analysis in Kansas City

EPA Science Inventory

Changes in vegetation cover associated with urban planning efforts may affect regional meteorology and air quality. Here we use a comprehensive coupled meteorology-air quality model (WRF-CMAQ) to simulate the influence of planned land use changes from green infrastructure impleme...

Use of soft data for multi-criteria calibration and validation of APEX: Impact on model simulations

USDA-ARS?s Scientific Manuscript database

It is widely known that the use of soft data and multiple model performance criteria in model calibration and validation is critical to ensuring the model capture major hydrologic and water quality processes. The Agricultural Policy/Environmental eXtender (APEX) is a hydrologic and water quality mod...

VOLATILE ORGANIC COMPOUND EMISSIONS FROM LATEX PAINT-PART 2. TEST HOUSE STUDIES AND INDOOR AIR QUALITY (IAQ) MODELING

EPA Science Inventory

Emission models developed using small chamber data were combined with an Indoor Air Quality (IAQ) model to analyze the impact of volatile organic compound (VOC) emissions from latex paint on indoor environments. Test house experiments were conducted to verify the IAQ model's pred...

VERIFICATION AND USES OF THE ENVIRONMENTAL PROTECTION AGENCY (EPA) INDOOR AIR QUALITY MODEL

EPA Science Inventory

The paper describes a set of experiments used to verify an indoor air quality (IAQ) model for estimating the impact of various pollution sources on IAQ in a multiroom building. he model treats each room as a well-mixed chamber that contains pollution sources and sinks. he model a...

Community Near-Port Modeling System (C-PORT): Briefing for ...

EPA Pesticide Factsheets

What C-PORT is: Screening level tool for assessing port activities and exploring the range of potential impacts that changes to port operations might have on local air quality; Analysis of decision alternatives through mapping of the likely pattern of potential pollutant dispersion and an estimated change in pollutant concentrations for user-designated scenarios; Designed primarily to evaluate the local air quality impacts of proposed port expansion or modernization, as well as to identify options for mitigating any impacts; Currently includes data from 21 US seaports and features a map-based interface similar to the widely used Google Earth; Still under development, C-PORT is designed as an easy-to-use computer modeling tool for users, such as state air quality managers and planners. This is part of our product outreach prior to model public release and to solicit for additional beta testers.

The Impact of Truth Surrogate Variance on Quality Assessment/Assurance in Wind Tunnel Testing

NASA Technical Reports Server (NTRS)

DeLoach, Richard

2016-01-01

Minimum data volume requirements for wind tunnel testing are reviewed and shown to depend on error tolerance, response model complexity, random error variance in the measurement environment, and maximum acceptable levels of inference error risk. Distinctions are made between such related concepts as quality assurance and quality assessment in response surface modeling, as well as between precision and accuracy. Earlier research on the scaling of wind tunnel tests is extended to account for variance in the truth surrogates used at confirmation sites in the design space to validate proposed response models. A model adequacy metric is presented that represents the fraction of the design space within which model predictions can be expected to satisfy prescribed quality specifications. The impact of inference error on the assessment of response model residuals is reviewed. The number of sites where reasonably well-fitted response models actually predict inadequately is shown to be considerably less than the number of sites where residuals are out of tolerance. The significance of such inference error effects on common response model assessment strategies is examined.

Land use change and conversion effects on ground water quality trends: An integration of land change modeler in GIS and a new Ground Water Quality Index developed by fuzzy multi-criteria group decision-making models.

PubMed

Shooshtarian, Mohammad Reza; Dehghani, Mansooreh; Margherita, Ferrante; Gea, Oliveri Conti; Mortezazadeh, Shima

2018-04-01

This study aggregated Land Change Modeller (LCM) as a useful model in GIS with an extended Groundwater Quality Index (GWQI) developed by fuzzy Multi-Criteria Group Decision-Making models to investigate the effect of land use change and conversion on groundwater quality being supplied for drinking. The model's performance was examined through an applied study in Shiraz, Iran, in a five year period (2011 to 2015). Four land use maps including urban, industrial, garden, and bare were employed in LCM model and the impact of change in area and their conversion to each other on GWQI changes was analysed. The correlation analysis indicated that increase in the urban land use area and conversion of bare to the residential/industrial land uses, had a relation with water quality decrease. Integration of LCM and GWQI can accurately and logically provide a numerical analysis of the possible impact of land use change and conversion, as one of the influencing factors, on the groundwater quality. Hence, the methodology could be used in urban development planning and management in macro level. Copyright © 2018. Published by Elsevier Ltd.

Impacts of agricultural land use on biological integrity: A causal analysis

USGS Publications Warehouse

Riseng, C.M.; Wiley, M.J.; Black, R.W.; Munn, M.D.

2011-01-01

Agricultural land use has often been linked to nutrient enrichment, habitat degradation, hydrologic alteration, and loss of biotic integrity in streams. The U.S. Geological Survey's National Water Quality Assessment Program sampled 226 stream sites located in eight agriculture-dominated study units across the United States to investigate the geographic variability and causes of agricultural impacts on stream biotic integrity. In this analysis we used structural equation modeling (SEM) to develop a national and set of regional causal models linking agricultural land use to measured instream conditions. We then examined the direct, indirect, and total effects of agriculture on biotic integrity as it acted through multiple water quality and habitat pathways. In our nation-wide model, cropland affected benthic communities by both altering structural habitats and by imposing water quality-related stresses. Regionspecific modeling demonstrated that geographic context altered the relative importance of causal pathways through which agricultural activities affected stream biotic integrity. Cropland had strong negative total effects on the invertebrate community in the national, Midwest, and Western models, but a very weak effect in the Eastern Coastal Plain model. In theWestern Arid and Eastern Coastal Plain study regions, cropland impacts were transmitted primarily through dissolved water quality contaminants, but in the Midwestern region, they were transmitted primarily through particulate components of water quality. Habitat effects were important in the Western Arid model, but negligible in the Midwest and Eastern Coastal Plain models. The relative effects of riparian forested wetlands also varied regionally, having positive effects on biotic integrity in the Eastern Coastal Plain andWestern Arid region models, but no statistically significant effect in the Midwest. These differences in response to cropland and riparian cover suggest that best management practices and planning for the mitigation of agricultural land use impacts on stream ecosystems should be regionally focused. ?? 2011 by the Ecological Society of America.

The impact of software quality characteristics on healthcare outcome: a literature review.

PubMed

Aghazadeh, Sakineh; Pirnejad, Habibollah; Moradkhani, Alireza; Aliev, Alvosat

2014-01-01

The aim of this study was to discover the effect of software quality characteristics on healthcare quality and efficiency indicators. Through a systematic literature review, we selected and analyzed 37 original research papers to investigate the impact of the software indicators (coming from the standard ISO 9126 quality characteristics and sub-characteristics) on some of healthcare important outcome indicators and finally ranked these software indicators. The results showed that the software characteristics usability, reliability and efficiency were mostly favored in the studies, indicating their importance. On the other hand, user satisfaction, quality of patient care, clinical workflow efficiency, providers' communication and information exchange, patient satisfaction and care costs were among the healthcare outcome indicators frequently evaluated in relation to the mentioned software characteristics. Regression Logistic Method was the most common assessment methodology, and Confirmatory Factor Analysis and Structural Equation Modeling were performed to test the structural model's fit. The software characteristics were considered to impact the healthcare outcome indicators through other intermediate factors (variables).

Variation in Estimated Ozone-Related Health Impacts of Climate Change due to Modeling Choices and Assumptions

PubMed Central

Post, Ellen S.; Grambsch, Anne; Weaver, Chris; Morefield, Philip; Leung, Lai-Yung; Nolte, Christopher G.; Adams, Peter; Liang, Xin-Zhong; Zhu, Jin-Hong; Mahoney, Hardee

2012-01-01

Background: Future climate change may cause air quality degradation via climate-induced changes in meteorology, atmospheric chemistry, and emissions into the air. Few studies have explicitly modeled the potential relationships between climate change, air quality, and human health, and fewer still have investigated the sensitivity of estimates to the underlying modeling choices. Objectives: Our goal was to assess the sensitivity of estimated ozone-related human health impacts of climate change to key modeling choices. Methods: Our analysis included seven modeling systems in which a climate change model is linked to an air quality model, five population projections, and multiple concentration–response functions. Using the U.S. Environmental Protection Agency’s (EPA’s) Environmental Benefits Mapping and Analysis Program (BenMAP), we estimated future ozone (O3)-related health effects in the United States attributable to simulated climate change between the years 2000 and approximately 2050, given each combination of modeling choices. Health effects and concentration–response functions were chosen to match those used in the U.S. EPA’s 2008 Regulatory Impact Analysis of the National Ambient Air Quality Standards for O3. Results: Different combinations of methodological choices produced a range of estimates of national O3-related mortality from roughly 600 deaths avoided as a result of climate change to 2,500 deaths attributable to climate change (although the large majority produced increases in mortality). The choice of the climate change and the air quality model reflected the greatest source of uncertainty, with the other modeling choices having lesser but still substantial effects. Conclusions: Our results highlight the need to use an ensemble approach, instead of relying on any one set of modeling choices, to assess the potential risks associated with O3-related human health effects resulting from climate change. PMID:22796531

Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution

EPA Science Inventory

Aviation is a unique anthropogenic source with four-dimensional varying emissions, peaking at cruise altitudes (9–12 km). Aircraft emission budgets in the upper troposphere lower stratosphere region and their potential impacts on upper troposphere and surface air quality ar...

A Community-Scale Modeling System to Assess Port-Related Air Quality Impacts

EPA Science Inventory

Near-port air pollution has been identified by numerous organizations as a potential public health concern. Based upon multiple near-road and near-source monitoring studies, both busy roadways and large emission sources at the ports may impact local air quality within several hun...

MODELING THE IMPACTS OF FIRE FLOWS ON DISTRIBUTION SYSTEM WATER QUALITY, DESIGN AND OPERATION

EPA Science Inventory

In most water distribution systems, a significant amount of the piping and storage capacity is used to provide adequate quantities of water during fire conditions. This increased capacity results in higher capital costs and potential negative impacts on water quality due to longe...

A framework for modeling contaminant impacts on reservoir water quality

NASA Astrophysics Data System (ADS)

Jeznach, Lillian C.; Jones, Christina; Matthews, Thomas; Tobiason, John E.; Ahlfeld, David P.

2016-06-01

This study presents a framework for using hydrodynamic and water quality models to understand the fate and transport of potential contaminants in a reservoir and to develop appropriate emergency response and remedial actions. In the event of an emergency situation, prior detailed modeling efforts and scenario evaluations allow for an understanding of contaminant plume behavior, including maximum concentrations that could occur at the drinking water intake and contaminant travel time to the intake. A case study assessment of the Wachusett Reservoir, a major drinking water supply for metropolitan Boston, MA, provides an example of an application of the framework and how hydrodynamic and water quality models can be used to quantitatively and scientifically guide management in response to varieties of contaminant scenarios. The model CE-QUAL-W2 was used to investigate the water quality impacts of several hypothetical contaminant scenarios, including hypothetical fecal coliform input from a sewage overflow as well as an accidental railway spill of ammonium nitrate. Scenarios investigated the impacts of decay rates, season, and inter-reservoir transfers on contaminant arrival times and concentrations at the drinking water intake. The modeling study highlights the importance of a rapid operational response by managers to contain a contaminant spill in order to minimize the mass of contaminant that enters the water column, based on modeled reservoir hydrodynamics. The development and use of hydrodynamic and water quality models for surface drinking water sources subject to the potential for contaminant entry can provide valuable guidance for making decisions about emergency response and remediation actions.

Transformation in the pharmaceutical industry: transformation-induced quality risks--a survey.

PubMed

Shafiei, Nader; Ford, James L; Morecroft, Charles W; Lisboa, Paulo J; Taylor, Mark J; Mouzughi, Yusra

2013-01-01

This paper is the fourth in a series that explores ongoing transformation in the pharmaceutical industry and its impact on pharmaceutical quality from the perspective of risk identification. The aim of this paper is to validate proposed quality risks through elicitation of expert opinion and define the resultant quality risk model. Expert opinion was obtained using a questionnaire-based survey with participants with recognized expertise in pharmaceutical regulation, product lifecycle, or technology. The results of the survey validate the theoretical and operational evidence in support of the four main pharmaceutical transformation triggers previously identified. The quality risk model resulting from the survey indicated a firm relationship between the pharmaceutical quality risks and regulatory compliance outcomes during the marketing approval and post-marketing phases of the product lifecycle and a weaker relationship during the pre-market evaluation phase. In this paper through conduct of an expert opinion survey the proposed quality risks carried forward from an earlier part of the research are validated and resultant quality risk model is defined. The survey results validate the theoretical and operational evidence previously identified. The quality risk model indicates that transformation-related risks have a larger regulatory compliance impact during product approval, manufacturing, distribution, and commercial use than during the development phase.

Uncertainty considerations in calibration and validation of hydrologic and water quality models

USDA-ARS?s Scientific Manuscript database

Hydrologic and water quality models (HWQMs) are increasingly used to support decisions on the state of various environmental issues and policy directions on present and future scenarios, at scales varying from watershed to continental levels. Uncertainty associated with such models may impact the ca...

INDOOR AIR QUALITY MODEL VERSION 1.0 DOCUMENTATION

EPA Science Inventory

The report presents a multiroom model for estimating the impact of various sources on indoor air quality (IAQ). The model is written for use on IBM-PC and compatible microcomputers. It is easy to use with a menu-driven user interface. Data are entered using a fill-in-a-form inter...

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

Chen, Longgao; Yang, Xiaoyan; School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116

The implementation of land use planning (LUP) has a large impact on environmental quality. There lacks a widely accepted and consolidated approach to assess the LUP environmental impact using Strategic Environmental Assessment (SEA). In this paper, we developed a state-impact-state (SIS) model employed in the LUP environmental impact assessment (LUPEA). With the usage of Matter-element (ME) and Extenics method, the methodology based on the SIS model was established and applied in the LUPEA of Zoucheng County, China. The results show that: (1) this methodology provides an intuitive and easy understanding logical model for both the theoretical analysis and application ofmore » LUPEA; (2) the spatial multi-temporal assessment from base year, near-future year to planning target year suggests the positive impact on the environmental quality in the whole County despite certain environmental degradation in some towns; (3) besides the spatial assessment, other achievements including the environmental elements influenced by land use and their weights, the identification of key indicators in LUPEA, and the appropriate environmental mitigation measures were obtained; and (4) this methodology can be used to achieve multi-temporal assessment of LUP environmental impact of County or Town level in other areas. - Highlights: • A State-Impact-State model for Land Use Planning Environmental Assessment (LUPEA). • Matter-element (ME) and Extenics methods were embedded in the LUPEA. • The model was applied to the LUPEA of Zoucheng County. • The assessment shows improving environment quality since 2000 in Zoucheng County. • The method provides a useful tool for the LUPEA in the county level.« less

Assessment of the Impacts of Climate Change on Stream Discharge and Water Quality in an Arid, Urbanized Watershed

NASA Astrophysics Data System (ADS)

Ranatunga, T.; Tong, S.; Yang, J.

2011-12-01

Hydrologic and water quality models can provide a general framework to conceptualize and investigate the relationships between climate and water resources. Under a hot and dry climate, highly urbanized watersheds are more vulnerable to changes in climate, such as excess heat and drought. In this study, a comprehensive watershed model, Hydrological Simulation Program FORTRAN (HSPF), is used to assess the impacts of future climate change on the stream discharge and water quality in Las Vegas Wash in Nevada, the only surface water body that drains from the Las Vegas Valley (an area with rapid population growth and urbanization) to Lake Mead. In this presentation, the process of model building, calibration and validation, the generation of climate change scenarios, and the assessment of future climate change effects on stream hydrology and quality are demonstrated. The hydrologic and water quality model is developed based on the data from current national databases and existing major land use categories of the watershed. The model is calibrated for stream discharge, nutrients (nitrogen and phosphorus) and sediment yield. The climate change scenarios are derived from the outputs of the Global Climate Models (GCM) and Regional Climate Models (RCM) simulations, and from the recent assessment reports from the Intergovernmental Panel on Climate Change (IPCC). The Climate Assessment Tool from US EPA's BASINS is used to assess the effects of likely future climate scenarios on the water quantity and quality in Las Vegas Wash. Also the presentation discusses the consequences of these hydrologic changes, including the deficit supplies of clean water during peak seasons of water demand, increased eutrophication potentials, wetland deterioration, and impacts on wild life habitats.

A changing climate: impacts on human exposures to O3 using ...

EPA Pesticide Factsheets

Predicting the impacts of changing climate on human exposure to air pollution requires future scenarios that account for changes in ambient pollutant concentrations, population sizes and distributions, and housing stocks. An integrated methodology to model changes in human exposures due to these impacts was developed by linking climate, air quality, land-use, and human exposure models. This methodology was then applied to characterize changes in predicted human exposures to O3 under multiple future scenarios. Regional climate projections for the U.S. were developed by downscaling global circulation model (GCM) scenarios for three of the Intergovernmental Panel on Climate Change’s (IPCC’s) Representative Concentration Pathways (RCPs) using the Weather Research and Forecasting (WRF) model. The regional climate results were in turn used to generate air quality (concentration) projections using the Community Multiscale Air Quality (CMAQ) model. For each of the climate change scenarios, future U.S. census-tract level population distributions from the Integrated Climate and Land Use Scenarios (ICLUS) model for four future scenarios based on the IPCC’s Special Report on Emissions Scenarios (SRES) storylines were used. These climate, air quality, and population projections were used as inputs to EPA’s Air Pollutants Exposure (APEX) model for 12 U.S. cities. Probability density functions show changes in the population distribution of 8 h maximum daily O3 exposur

Does glycemic variability impact mood and quality of life?

PubMed

Penckofer, Sue; Quinn, Lauretta; Byrn, Mary; Ferrans, Carol; Miller, Michael; Strange, Poul

2012-04-01

Diabetes is a chronic condition that significantly impacts quality of life. Poor glycemic control is associated with more diabetes complications, depression, and worse quality of life. The impact of glycemic variability on mood and quality of life has not been studied. A descriptive exploratory design was used. Twenty-three women with type 2 diabetes wore a continuous glucose monitoring system for 72 h and completed a series of questionnaires. Measurements included (1) glycemic control shown by glycated hemoglobin and 24-h mean glucose, (2) glycemic variability shown by 24-h SD of the glucose readings, continuous overall net glycemic action (CONGA), and Fourier statistical models to generate smoothed curves to assess rate of change defined as "energy," and (3) mood (depression, anxiety, anger) and quality of life by questionnaires. Women with diabetes and co-morbid depression had higher anxiety, more anger, and lower quality of life than those without depression. Certain glycemic variability measures were associated with mood and quality of life. The 24-h SD of the glucose readings and the CONGA measures were significantly associated with health-related quality of life after adjusting for age and weight. Fourier models indicated that certain energy components were significantly associated with depression, trait anxiety, and overall quality of life. Finally, subjects with higher trait anxiety tended to have steeper glucose excursions. Data suggest that greater glycemic variability may be associated with lower quality of life and negative moods. Implications include replication of the study in a larger sample for the assessment of blood glucose fluctuations as they impact mood and quality of life.

Strategic collaborative quality management and employee job satisfaction

PubMed Central

Mosadeghrad, Ali Mohammad

2014-01-01

Background: This study aimed to examine Strategic Collaborative Quality Management (SCQM) impact on employee job satisfaction. Methods: The study presents a case study over six years following the implementation of the SCQM programme in a public hospital. A validated questionnaire was used to measure employees’ job satisfaction. The impact of the intervention was measured by comparing the pre-intervention and post-intervention measures in the hospital. Results: The hospital reported a significant improvement in some dimensions of job satisfaction like management and supervision, organisational policies, task requirement, and working conditions. Conclusion: This paper provides detailed information on how a quality management model implementation affects employees. A well developed, well introduced and institutionalised quality management model can improve employees’ job satisfaction. However, the success of quality management needs top management commitment and stability. PMID:24847482

Strategic collaborative quality management and employee job satisfaction.

PubMed

Mosadeghrad, Ali Mohammad

2014-05-01

This study aimed to examine Strategic Collaborative Quality Management (SCQM) impact on employee job satisfaction. The study presents a case study over six years following the implementation of the SCQM programme in a public hospital. A validated questionnaire was used to measure employees' job satisfaction. The impact of the intervention was measured by comparing the pre-intervention and post-intervention measures in the hospital. The hospital reported a significant improvement in some dimensions of job satisfaction like management and supervision, organisational policies, task requirement, and working conditions. This paper provides detailed information on how a quality management model implementation affects employees. A well developed, well introduced and institutionalised quality management model can improve employees' job satisfaction. However, the success of quality management needs top management commitment and stability.

Patient experiences of burn scars in adults and children and development of a health-related quality of life conceptual model: A qualitative study.

PubMed

Simons, Megan; Price, Nathaniel; Kimble, Roy; Tyack, Zephanie

2016-05-01

The aim of this study was to understand the impact of burn scars on health-related quality of life (HRQOL) from the perspective of adults and children with burn scars, and caregivers to inform the development of a conceptual model of burn scar HRQOL. Twenty-one participants (adults and children) with burn scars and nine caregivers participated in semi-structured, face-to-face interviews between 2012 and 2013. During the interviews, participants were asked to describe features about their (or their child's) burn scars and its impact on everyday life. Two coders conducted thematic analysis, with consensus achieved through discussion and review with a third coder. The literature on HRQOL models was then reviewed to further inform the development of a conceptual model of burn scar HRQOL. Five themes emerged from the qualitative data: 'physical and sensory symptoms', 'impact of burn scar interventions', 'impact of burn scar symptoms', 'personal factors' and 'change over time'. Caregivers offered further insights into family functioning after burn, and the impacts of burn scars and burn scar interventions on family life. In the conceptual model, symptoms (sensory and physical) of burn scars are considered proximal to HRQOL, with distal indicators including functioning (physical, emotional, social, cognitive), individual factors and the environment. Overall quality of life was affected by HRQOL. Understanding the impact of burn scars on HRQOL and the development of a conceptual model will inform future burn scar research and clinical practice. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Health and cost impact of air pollution from biomass burning over the United States

NASA Astrophysics Data System (ADS)

Eslami, E.; Sadeghi, B.; Choi, Y.

2017-12-01

Effective assessment of health and cost effects of air pollution associated with wildfire events is critical for supporting sustainable management and policy analysis to reduce environmental damages. Since biomass burning events result in higher ozone, PM2.5, and NOx concentration values in urban regions due to long-range transport, preliminary results indicated that wildfire events cause a considerable increase in incident estimates and costs. This study aims to evaluate the health and cost impact of biomass burning events over the continental United States using combined air quality and health impact modeling. To meet this goal, a comprehensive air quality modeling scenarios containing biomass burning emissions were conducted using the Community Multiscale Air Quality (CMAQ) modeling system from 2011 to 2014 with a spatial resolution of 12 km. The modeling period includes fire seasons between April and October over the course of four years. By using modeled pollutants concentrations, the USEPA's GIS-based computer program Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) provides an inclusive figure of health and cost impact caused by changing gaseous and particulate air pollution due to fire events. The basis of BenMAP-CE is the use of a damage-function approach to estimate the health impact of an applied change in air quality by comparing a biomass burning scenario (the one that includes wildfire events) with a baseline scenario (without biomass emissions). This approach considers several factors containing population, exposure to the pollutants, adverse health effects of a particular pollutant, and economic costs. Hence, this study made it capable of showing how biomass burning across U.S. influences people's health in different months, seasons, and regions. Besides, the cost impact of the wildfire events during study periods has also been estimated at both national and regional levels. The results of this study demonstrate the BenMAP-CE can be successfully utilized as a proper tool to obtain health and cost impact of biomass burning events.

76 FR 81371 - Approval and Disapproval and Promulgation of Implementation Plans; Texas; Infrastructure and...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-28

... Source Ozone Modeling K. Comments That Address Cumulative Air Quality Impacts IV. Final Action V... (section 110(a)(2)(J)); air quality modeling/data (section 110(a)(2)(K)); permitting fees (section 110(a)(2...

EVALUATION OF THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL VERSION 4.5: UNCERTAINTIES AND SENSITIVITIES IMPACTING MODEL PERFORMANCE: PART I - OZONE

EPA Science Inventory

This study examines ozone (O₃) predictions from the Community Multiscale Air Quality (CMAQ) model version 4.5 and discusses potential factors influencing the model results. Daily maximum 8-hr average O₃ levels are largely underpredicted when observed O_...

Fire Influences on Atmospheric Composition, Air Quality, and Climate

NASA Technical Reports Server (NTRS)

Voulgarakis, Apostolos; Field, Robert D.

2015-01-01

Fires impact atmospheric composition through their emissions, which range from long-lived gases to short-lived gases and aerosols. Effects are typically larger in the tropics and boreal regions but can also be substantial in highly populated areas in the northern mid-latitudes. In all regions, fire can impact air quality and health. Similarly, its effect on large-scale atmospheric processes, including regional and global atmospheric chemistry and climate forcing, can be substantial, but this remains largely unexplored. The impacts are primarily realised in the boundary layer and lower free troposphere but can also be noticeable in upper troposphere/lower stratosphere (UT/LS) region, for the most intense fires. In this review, we summarise the recent literature on findings related to fire impact on atmospheric composition, air quality and climate. We explore both observational and modelling approaches and present information on key regions and on the globe as a whole. We also discuss the current and future directions in this area of research, focusing on the major advances in emission estimates, the emerging efforts to include fire as a component in Earth system modelling and the use of modelling to assess health impacts of fire emissions.

Quantifying Impact of Biofeedstock Production on Hydrology/Water Quality in Midwest USA

NASA Astrophysics Data System (ADS)

Chaubey, Indrajeet; Engel, Bernard; Thomas, Mark; Raj, Cibin; Saraswat, Dharmendra

2010-05-01

The production of biofeedstocks for biofuels is likely to impact the hydrology and water quality of watersheds. Communities potentially impacted are increasingly concerned, and at present, little is known regarding the magnitude of impacts of biofeedstock production on hydrology and water quality. We have initiated a national facilitation project to answer the following questions: What are the unintended environmental consequences of increased corn production to meet biofuel demands? What are the environmental impacts of various second generation biofeedstock production systems to meet cellulosic ethanol demands? Would the management of cropping systems involving corn silage meet cellulosic ethanol demands with minimal environmental impact? What are the broad-scale water quality implications of energy crops, such as switchgrass, grown for bioenergy production on highly erodible soils? This presentation will discuss development of multi-regional agricultural land management practices that can be implemented to mitigate potential negative environmental impacts associated with biofeedstock production while meeting the biofuel production demand. Specifically, we will discuss how watershed scale modeling can be utilized to evaluate the environmental impacts of various biofeedstock production strategies. We will also discuss regional differences in alternative biofeedstock production and associated hydrologic/water quality impacts.

Water quality modelling of an impacted semi-arid catchment using flow data from the WEAP model

NASA Astrophysics Data System (ADS)

Slaughter, Andrew R.; Mantel, Sukhmani K.

2018-04-01

The continuous decline in water quality in many regions is forcing a shift from quantity-based water resources management to a greater emphasis on water quality management. Water quality models can act as invaluable tools as they facilitate a conceptual understanding of processes affecting water quality and can be used to investigate the water quality consequences of management scenarios. In South Africa, the Water Quality Systems Assessment Model (WQSAM) was developed as a management-focussed water quality model that is relatively simple to be able to utilise the small amount of available observed data. Importantly, WQSAM explicitly links to systems (yield) models routinely used in water resources management in South Africa by using their flow output to drive water quality simulations. Although WQSAM has been shown to be able to represent the variability of water quality in South African rivers, its focus on management from a South African perspective limits its use to within southern African regions for which specific systems model setups exist. Facilitating the use of WQSAM within catchments outside of southern Africa and within catchments for which these systems model setups to not exist would require WQSAM to be able to link to a simple-to-use and internationally-applied systems model. One such systems model is the Water Evaluation and Planning (WEAP) model, which incorporates a rainfall-runoff component (natural hydrology), and reservoir storage, return flows and abstractions (systems modelling), but within which water quality modelling facilities are rudimentary. The aims of the current study were therefore to: (1) adapt the WQSAM model to be able to use as input the flow outputs of the WEAP model and; (2) provide an initial assessment of how successful this linkage was by application of the WEAP and WQSAM models to the Buffalo River for historical conditions; a small, semi-arid and impacted catchment in the Eastern Cape of South Africa. The simulations of the two models were compared to the available observed data, with the initial focus within WQSAM on a simulation of instream total dissolved solids (TDS) and nutrient concentrations. The WEAP model was able to adequately simulate flow in the Buffalo River catchment, with consideration of human inputs and outputs. WQSAM was adapted to successfully take as input the flow output of the WEAP model, and the simulations of nutrients by WQSAM provided a good representation of the variability of observed nutrient concentrations in the catchment. This study showed that the WQSAM model is able to accept flow inputs from the WEAP model, and that this approach is able to provide satisfactory estimates of both flow and water quality for a small, semi-arid and impacted catchment. It is hoped that this research will encourage the application of WQSAM to an increased number of catchments within southern Africa and beyond.

Indicators to support the dynamic evaluation of air quality models

NASA Astrophysics Data System (ADS)

Thunis, P.; Clappier, A.

2014-12-01

Air quality models are useful tools for the assessment and forecast of pollutant concentrations in the atmosphere. Most of the evaluation process relies on the “operational phase” or in other words the comparison of model results with available measurements which provides insight on the model capability to reproduce measured concentrations for a given application. But one of the key advantages of air quality models lies in their ability to assess the impact of precursor emission reductions on air quality levels. Models are then used in a dynamic mode (i.e. response to a change in a given model input data) for which evaluation of the model performances becomes a challenge. The objective of this work is to propose common indicators and diagrams to facilitate the understanding of model responses to emission changes when models are to be used for policy support. These indicators are shown to be useful to retrieve information on the magnitude of the locally produced impacts of emission reductions on concentrations with respect to the “external to the domain” contribution but also to identify, distinguish and quantify impacts arising from different factors (different precursors). In addition information about the robustness of the model results is provided. As such these indicators might reveal useful as first screening methodology to identify the feasibility of a given action as well as to prioritize the factors on which to act for an increased efficiency. Finally all indicators are made dimensionless to facilitate the comparison of results obtained with different models, different resolutions, or on different geographical areas.

Enhancing water quality in hydropower system operations

NASA Astrophysics Data System (ADS)

Hayes, Donald F.; Labadie, John W.; Sanders, Thomas G.; Brown, Jackson K.

1998-03-01

The quality of impounded waters often degrades over time because of thermal stratification, sediment oxygen demands, and accumulation of pollutants. Consequently, reservoir releases impact water quality in tailwaters, channels, and other downstream water bodies. Low dissolved oxygen (DO) concentrations in the Cumberland River below Old Hickory dam result from stratification of upstream reservoirs and seasonally low release rates. Operational changes in upstream hydropower reservoirs may be one method to increase DO levels without substantially impacting existing project purposes. A water quality model of the upper Cumberland basin is integrated into an optimal control algorithm to evaluate water quality improvement opportunities through operational modifications. The integrated water quantity/quality model maximizes hydropower revenues, subject to various flow and headwater operational restrictions for satisfying multiple project purposes, as well as maintenance of water quality targets. Optimal daily reservoir release policies are determined for the summer drawdown period which increase DO concentrations under stratification conditions with minimal impact on hydropower production and other project purposes. Appendixes A-D available with entire article on microfiche. Order by mail from AGU, 2000 Florida Ave., N.W., Washington, DC 20009 or by phone at 800-966-2481; $2.50. Document W97-003. Payment must accompany order.

Compartment-based hydrodynamics and water quality modeling of a northern Everglades wetland, Florida, USA

USGS Publications Warehouse

Wang, Hongqing; Meselhe, Ehab A.; Waldon, Michael G.; Harwell, Matthew C.; Chen, Chunfang

2012-01-01

The last remaining large remnant of softwater wetlands in the US Florida Everglades lies within the Arthur R. Marshall Loxahatchee National Wildlife Refuge. However, Refuge water quality today is impacted by pumped stormwater inflows to the eutrophic and mineral-enriched 100-km canal, which circumscribes the wetland. Optimal management is a challenge and requires scientifically based predictive tools to assess and forecast the impacts of water management on Refuge water quality. In this research, we developed a compartment-based numerical model of hydrodynamics and water quality for the Refuge. Using the numerical model, we examined the dynamics in stage, water depth, discharge from hydraulic structures along the canal, and exchange flow among canal and marsh compartments. We also investigated the transport of chloride, sulfate and total phosphorus from the canal to the marsh interior driven by hydraulic gradients as well as biological removal of sulfate and total phosphorus. The model was calibrated and validated using long-term stage and water quality data (1995-2007). Statistical analysis indicates that the model is capable of capturing the spatial (from canal to interior marsh) gradients of constituents across the Refuge. Simulations demonstrate that flow from the eutrophic and mineral-enriched canal impacts chloride and sulfate in the interior marsh. In contrast, total phosphorus in the interior marsh shows low sensitivity to intrusion and dispersive transport. We conducted a rainfall-driven scenario test in which the pumped inflow concentrations of chloride, sulfate and total phosphorus were equal to rainfall concentrations (wet deposition). This test shows that pumped inflow is the dominant factor responsible for the substantially increased chloride and sulfate concentrations in the interior marsh. Therefore, the present day Refuge should not be classified as solely a rainfall-driven or ombrotrophic wetland. The model provides an effective screening tool for studying the impacts of various water management alternatives on water quality across the Refuge, and demonstrates the practicality of similarly modeling other wetland systems. As a general rule, modeling provides one component of a multi-faceted effort to provide technical support for ecosystem management decisions.

The Effect of an Education Program Utilising PRECEDE Model on the Quality of Life in Patients with Type 2 Diabetes

ERIC Educational Resources Information Center

Taghdisi, M. H.; Borhani, M.; Solhi, M.; Afkari, M. E.; Hosseini, F.

2012-01-01

Background and objective: The problems caused by diabetes have direct and indirect impacts on the quality of life of diabetic patients. An increase of these problems means a decrease in a patient's quality of life. This study was conducted to assess the effect of the educational programme based on the precede model in promoting quality of life of…

Evaluation of the impact of SO₂ and NO₂ emissions on the ambient air-quality in the Çan-Bayramiç region of northwest Turkey during 2007-2008.

PubMed

Ozkurt, Nesimi; Sari, Deniz; Akalin, Nuray; Hilmioglu, Bilgin

2013-07-01

The characterization and assessment of air-quality in this region are essential steps for the implementation of the "Clean Air Action Plan" as this is set by the Turkish Regulation on Ambient Air-Quality Assessment and Management. This study area intends to shed a light on use of modeling tools as an alternative method for the assessment of local atmospheric pollution and the determination of the importance of local emissions. This modeling approach can be also used for the consistent geographic representation of air-quality concentration as well as for assessing the future air-quality condition after the implementation of emission reduction measures in a certain area. With this article we evaluate the impact of sulfur dioxide and nitrogen dioxide emissions on the ambient air-quality in the Çan-Bayramiç region of Turkey. The emission rates of sulfur dioxide and nitrogen dioxide were calculated by using the CALPUFF model. The concentration of these pollutants had also been monitored at ten air-quality locations during 2007-2008 in the research area. The measured data were also utilized for testing the model performance. Results showed that the air-quality in this important rural region of Turkey can be evaluated effectively by using the current numerical modeling system. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

The relationship between quality management practices and organisational performance: A structural equation modelling approach

NASA Astrophysics Data System (ADS)

Jamaluddin, Z.; Razali, A. M.; Mustafa, Z.

2015-02-01

The purpose of this paper is to examine the relationship between the quality management practices (QMPs) and organisational performance for the manufacturing industry in Malaysia. In this study, a QMPs and organisational performance framework is developed according to a comprehensive literature review which cover aspects of hard and soft quality factors in manufacturing process environment. A total of 11 hypotheses have been put forward to test the relationship amongst the six constructs, which are management commitment, training, process management, quality tools, continuous improvement and organisational performance. The model is analysed using Structural Equation Modeling (SEM) with AMOS software version 18.0 using Maximum Likelihood (ML) estimation. A total of 480 questionnaires were distributed, and 210 questionnaires were valid for analysis. The results of the modeling analysis using ML estimation indicate that the fits statistics of QMPs and organisational performance model for manufacturing industry is admissible. From the results, it found that the management commitment have significant impact on the training and process management. Similarly, the training had significant effect to the quality tools, process management and continuous improvement. Furthermore, the quality tools have significant influence on the process management and continuous improvement. Likewise, the process management also has a significant impact to the continuous improvement. In addition the continuous improvement has significant influence the organisational performance. However, the results of the study also found that there is no significant relationship between management commitment and quality tools, and between the management commitment and continuous improvement. The results of the study can be used by managers to prioritize the implementation of QMPs. For instances, those practices that are found to have positive impact on organisational performance can be recommended to managers so that they can allocate resources to improve these practices to get better performance.

The Multidimensional Impact of Teachers on Students

ERIC Educational Resources Information Center

Pope, Nolan G.

2017-01-01

For decades, policymakers and researchers have used value-added models that rely solely on student test scores to measure teacher quality. However, since teaching ability is multidimensional, test-score value-added measures of teacher quality may not fully capture the impact of teachers on students. In this paper, we use test-score and…

Modeling Family Adaptation to Fragile X Syndrome

ERIC Educational Resources Information Center

Raspa, Melissa; Bailey, Donald, Jr.; Bann, Carla; Bishop, Ellen

2014-01-01

Using data from a survey of 1,099 families who have a child with Fragile X syndrome, we examined adaptation across 7 dimensions of family life: parenting knowledge, social support, social life, financial impact, well-being, quality of life, and overall impact. Results illustrate that although families report a high quality of life, they struggle…

ASSESSING THE WATER QUALITY IMPACTS OF GLOBAL CLIMATE CHANGE IN SOUTHWESTERN OHIO, U.S.A

EPA Science Inventory

This paper uses a watershed-scale hydrologic model (Soil and Water Assessment Tool) to simulate the water quality impacts of future climate change in the Little Miami River (LMR) watershed in southwestern Ohio. The LMR watershed, the principal source of drinking water for 1.6 mi...

Impacts of forest to urban land conversion and ENSO phase on water quality of a public water supply reservoir

USDA-ARS?s Scientific Manuscript database

We used coupled watershed and reservoir models to evaluate the impacts of deforestation and ENSO phase on drinking water quality. Source water total organic carbon (TOC) is especially important due to the potential for production of carcinogenic disinfection byproducts (DBPs). The Environmental Flui...

Academic Libraries and the Research Quality Framework

ERIC Educational Resources Information Center

Haddow, Gaby

2007-01-01

The Federal Government is introducing a new funding model for research in Australian higher education institutions, the Research Quality Framework (RQF). This paper provides an overview of the RQF and looks at possible impacts of the RQF on academic libraries in Australia. These impacts are drawn from experience at one Australian university,…

On the validity of the incremental approach to estimate the impact of cities on air quality

NASA Astrophysics Data System (ADS)

Thunis, Philippe

2018-01-01

The question of how much cities are the sources of their own air pollution is not only theoretical as it is critical to the design of effective strategies for urban air quality planning. In this work, we assess the validity of the commonly used incremental approach to estimate the likely impact of cities on their air pollution. With the incremental approach, the city impact (i.e. the concentration change generated by the city emissions) is estimated as the concentration difference between a rural background and an urban background location, also known as the urban increment. We show that the city impact is in reality made up of the urban increment and two additional components and consequently two assumptions need to be fulfilled for the urban increment to be representative of the urban impact. The first assumption is that the rural background location is not influenced by emissions from within the city whereas the second requires that background concentration levels, obtained with zero city emissions, are equal at both locations. Because the urban impact is not measurable, the SHERPA modelling approach, based on a full air quality modelling system, is used in this work to assess the validity of these assumptions for some European cities. Results indicate that for PM2.5, these two assumptions are far from being fulfilled for many large or medium city sizes. For this type of cities, urban increments are largely underestimating city impacts. Although results are in better agreement for NO2, similar issues are met. In many situations the incremental approach is therefore not an adequate estimate of the urban impact on air pollution. This poses issues in terms of interpretation when these increments are used to define strategic options in terms of air quality planning. We finally illustrate the interest of comparing modelled and measured increments to improve our confidence in the model results.

Examining the impacts of increased corn production on groundwater quality using a coupled modeling system

EPA Science Inventory

This study demonstrates the value of a coupled chemical transport modeling system for investigating groundwater nitrate contamination responses associated with nitrogen (N) fertilizer application and increased corn production. The coupled Community Multiscale Air Quality Bidirect...

Modeling Cover Crop Effectiveness on Maryland's Eastern Shore

USDA-ARS?s Scientific Manuscript database

The value of watershed-scale, hydrologic/water quality models to ecosystem management is increasingly evident as more programs adopt these tools to evaluate the effectiveness of different management scenarios and their impact on the environment. Quality of precipitation data is critical for appropri...

A spectral method for spatial downscaling

EPA Science Inventory

Complex computer models play a crucial role in air quality research. These models are used to evaluate potential regulatory impacts of emission control strategies and to estimate air quality in areas without monitoring data. For both of these purposes, it is important to calibrat...

Modeling Source Water Threshold Exceedances with Extreme Value Theory

NASA Astrophysics Data System (ADS)

Rajagopalan, B.; Samson, C.; Summers, R. S.

2016-12-01

Variability in surface water quality, influenced by seasonal and long-term climate changes, can impact drinking water quality and treatment. In particular, temperature and precipitation can impact surface water quality directly or through their influence on streamflow and dilution capacity. Furthermore, they also impact land surface factors, such as soil moisture and vegetation, which can in turn affect surface water quality, in particular, levels of organic matter in surface waters which are of concern. All of these will be exacerbated by anthropogenic climate change. While some source water quality parameters, particularly Total Organic Carbon (TOC) and bromide concentrations, are not directly regulated for drinking water, these parameters are precursors to the formation of disinfection byproducts (DBPs), which are regulated in drinking water distribution systems. These DBPs form when a disinfectant, added to the water to protect public health against microbial pathogens, most commonly chlorine, reacts with dissolved organic matter (DOM), measured as TOC or dissolved organic carbon (DOC), and inorganic precursor materials, such as bromide. Therefore, understanding and modeling the extremes of TOC and Bromide concentrations is of critical interest for drinking water utilities. In this study we develop nonstationary extreme value analysis models for threshold exceedances of source water quality parameters, specifically TOC and bromide concentrations. In this, the threshold exceedances are modeled as Generalized Pareto Distribution (GPD) whose parameters vary as a function of climate and land surface variables - thus, enabling to capture the temporal nonstationarity. We apply these to model threshold exceedance of source water TOC and bromide concentrations at two locations with different climate and find very good performance.

Improvements to the Noah Land Surface Model in WRF-CMAQ, and its Application to Future Changes in the Chesapeake Bay Region

EPA Science Inventory

Regional, state, and local environmental regulatory agencies often use Eulerian meteorological and air quality models to investigate the potential impacts of climate, emissions, and land use changes on nutrient loading and air quality. The Noah land surface model in WRF could be...

Impact of length of calibration period on the apex model output simulation performance

USDA-ARS?s Scientific Manuscript database

Datasets from long-term monitoring sites that can be used for calibration and validation of hydrologic and water quality models are rare due to resource constraints. As a result, hydrologic and water quality models are calibrated and, when possible, validated using short-term measured data. A previo...

An Evaluation of carbon monoxide emissions models and mobile source dispersion models applicable to Alaskan cities : final report

DOT National Transportation Integrated Search

1986-01-01

This report describes an investigation of state-of-the-art models for predicting the impact on air quality of additions or changes to a highway system identified by the U.S. Environmental Protection Agency as a "non-attainment area" for air quality s...

A novel integrated modelling framework to assess the impacts of climate and socio-economic drivers on land use and water quality.

PubMed

Zessner, Matthias; Schönhart, Martin; Parajka, Juraj; Trautvetter, Helene; Mitter, Hermine; Kirchner, Mathias; Hepp, Gerold; Blaschke, Alfred Paul; Strenn, Birgit; Schmid, Erwin

2017-02-01

Changes in climatic conditions will directly affect the quality and quantity of water resources. Further on, they will affect them indirectly through adaptation in land use which ultimately influences diffuse nutrient emissions to rivers and therefore potentially the compliance with good ecological status according to the EU Water Framework Directive (WFD). We present an integrated impact modelling framework (IIMF) to track and quantify direct and indirect pollution impacts along policy-economy-climate-agriculture-water interfaces. The IIMF is applied to assess impacts of climatic and socio-economic drivers on agricultural land use (crop choices, farming practices and fertilization levels), river flows and the risk for exceedance of environmental quality standards for determination of the ecological water quality status in Austria. This article also presents model interfaces as well as validation procedures and results of single models and the IIMF with respect to observed state variables such as land use, river flow and nutrient river loads. The performance of the IIMF for calculations of river nutrient loads (120 monitoring stations) shows a Nash-Sutcliffe Efficiency of 0.73 for nitrogen and 0.51 for phosphorus. Most problematic is the modelling of phosphorus loads in the alpine catchments dominated by forests and mountainous landscape. About 63% of these catchments show a deviation between modelled and observed loads of 30% and more. In catchments dominated by agricultural production, the performance of the IIMF is much better as only 30% of cropland and 23% of permanent grassland dominated areas have a deviation of >30% between modelled and observed loads. As risk of exceedance of environmental quality standards is mainly recognized in catchments dominated by cropland, the IIMF is well suited for assessing the nutrient component of the WFD ecological status. Copyright © 2016 British Geological Survey, NERC. Published by Elsevier B.V. All rights reserved.

Beach boundary layer: a framework for addressing recreational water quality impairment at enclosed beaches.

PubMed

Grant, Stanley B; Sanders, Brett F

2010-12-01

Nearshore waters in bays, harbors, and estuaries are frequently contaminated with human pathogens and fecal indicator bacteria. Tracking down and mitigating this contamination is complicated by the many point and nonpoint sources of fecal pollution that can degrade water quality along the shore. From a survey of the published literature, we propose a conceptual and mathematical framework, the "beach boundary layer model", for understanding and quantifying the relative impact of beach-side and bay-side sources of fecal pollution on nearshore water quality. In the model, bacterial concentration in ankle depth water C(ankle) [bacteria L(-3)] depends on the flux m'' [bacteria L(-2) T(-1)] of fecal bacteria from beach-side sources (bather shedding, bird and dog feces, tidal washing of sediments, decaying vegetation, runoff from small drains, and shallow groundwater discharge), a cross-shore mass transfer velocity k [L T(-1)] that accounts for the physics of nearshore transport and mixing, and a background concentration C(bay) [bacteria L(-3)] attributable to bay-side sources of pollution that impact water quality over large regions (sewage outfalls, creeks and rivers): C(ankle) = m''/k + C(bay). We demonstrate the utility of the model for identifying risk factors and pollution sources likely to impact shoreline water quality, and evaluate the model's underlying assumptions using computational fluid dynamic simulations of flow, turbulence, and mass transport in a trapezoidal channel.

Determination of the Acceptable Ambient Light Exposure during Drug Product Manufacturing for Long Term Stability of Monoclonal Antibodies.

PubMed

Luis, Lin M; Hu, Yuzhe; Zamiri, Camellia; Sreedhara, Alavattam

2018-05-31

Monoclonal antibodies (mAbs) are exposed to light during drug product (DP) manufacturing and the acceptable levels of light exposure needs to be determined based on the impact on product quality. In this study, a mild and more representative light model consisting of ambient light instead of stress light as prescribed by ICH Q1B was used to evaluate the impact of light exposure on mAb DP quality. The immediate effect of ambient light exposure on protein drug product quality was determined to be dependent on the amount of light exposure rather than light intensity (up to 5000 lux). The impact on quality of mAbs is product specific due to their differences in light sensitivity, in which mAb II shows larger increases in IEC basic variants and larger decreases in SEC monomer when compared to mAb I after 0.24 million lux hours of light exposure. The acceptable ambient light exposure for mAb II drug product manufacturing was determined to be 0.13 million lux hours, in which no impact on product quality was observed after the short-term light exposure. Additionally, real-time storage (5°C) of the DP after the prescribed ambient light exposure showed no impact to various product quality attributes. The light model used in this study is capable of determining the acceptable amount of ambient light exposure for mAbs, especially during DP manufacturing processes. Copyright © 2018, Parenteral Drug Association.

Predicting fire effects on water quality: a perspective and future needs

NASA Astrophysics Data System (ADS)

Smith, Hugh; Sheridan, Gary; Nyman, Petter; Langhans, Christoph; Noske, Philip; Lane, Patrick

2017-04-01

Forest environments are a globally significant source of drinking water. Fire presents a credible threat to the supply of high quality water in many forested regions. The post-fire risk to water supplies depends on storm event characteristics, vegetation cover and fire-related changes in soil infiltration and erodibility modulated by landscape position. The resulting magnitude of runoff generation, erosion and constituent flux to streams and reservoirs determines the severity of water quality impacts in combination with the physical and chemical composition of the entrained material. Research to date suggests that most post-fire water quality impacts are due to large increases in the supply of particulates (fine-grained sediment and ash) and particle-associated chemical constituents. The largest water quality impacts result from high magnitude erosion events, including debris flow processes, which typically occur in response to short duration, high intensity storm events during the recovery period. Most research to date focuses on impacts on water quality after fire. However, information on potential water quality impacts is required prior to fire events for risk planning. Moreover, changes in climate and forest management (e.g. prescribed burning) that affect fire regimes may alter water quality risks. Therefore, prediction requires spatial-temporal representation of fire and rainfall regimes coupled with information on fire-related changes to soil hydrologic parameters. Recent work has applied such an approach by combining a fire spread model with historic fire weather data in a Monte Carlo simulation to quantify probabilities associated with fire and storm events generating debris flows and fine sediment influx to a reservoir located in Victoria, Australia. Prediction of fire effects on water quality would benefit from further research in several areas. First, more work on regional-scale stochastic modelling of intersecting fire and storm events with landscape zones of erosion vulnerability is required to support quantitative evaluation of water quality risk and the effect of future changes in climate and land management. Second, we underscore previous calls for characterisation of landscape-scale domains to support regionalisation of parameter sets derived from empirical studies. Recent examples include work identifying aridity as a control of hydro-geomorphic response to fire and the use of spectral-based indices to predict spatial heterogeneity in ash loadings. Third, information on post-fire erosion from colluvial or alluvial stores is needed to determine their significance as both sediment-contaminant sinks and sources. Such sediment stores may require explicit spatial representation in risk models for some environments and sediment tracing can be used to determine their relative importance as secondary sources. Fourth, increased dating of sediment archives could provide regional datasets of fire-related erosion event frequency. Presently, the lack of such data hinders evaluation of risk models linking fire and storm events to erosion and water quality impacts.

Measuring the impact of urbanization on scenic quality: land use change in the northeast

Treesearch

Robert O. Brush; James F. Palmer

1979-01-01

The changes in scenic quality resulting from urbanization are explored for a region in the Northeast. The relative contributions to scenic quality of certain landscape features are examined by developing regression models for the region and for town landscapes within that region. The models provide empirical evidence of the importance of trees for maintaining high...

Simulating smoke transport from wildland fires with a regional-scale air quality model: sensitivity to spatiotemporal allocation of fire emissions.

PubMed

Garcia-Menendez, Fernando; Hu, Yongtao; Odman, Mehmet T

2014-09-15

Air quality forecasts generated with chemical transport models can provide valuable information about the potential impacts of fires on pollutant levels. However, significant uncertainties are associated with fire-related emission estimates as well as their distribution on gridded modeling domains. In this study, we explore the sensitivity of fine particulate matter concentrations predicted by a regional-scale air quality model to the spatial and temporal allocation of fire emissions. The assessment was completed by simulating a fire-related smoke episode in which air quality throughout the Atlanta metropolitan area was affected on February 28, 2007. Sensitivity analyses were carried out to evaluate the significance of emission distribution among the model's vertical layers, along the horizontal plane, and into hourly inputs. Predicted PM2.5 concentrations were highly sensitive to emission injection altitude relative to planetary boundary layer height. Simulations were also responsive to the horizontal allocation of fire emissions and their distribution into single or multiple grid cells. Additionally, modeled concentrations were greatly sensitive to the temporal distribution of fire-related emissions. The analyses demonstrate that, in addition to adequate estimates of emitted mass, successfully modeling the impacts of fires on air quality depends on an accurate spatiotemporal allocation of emissions. Copyright © 2014 Elsevier B.V. All rights reserved.

Environmetric data interpretation to assess the water quality of Maritsa River catchment.

PubMed

Papazova, Petia; Simeonova, Pavlina

2013-01-01

Maritsa River is one of the largest rivers flowing on Bulgarian territory. The quality of its waters is of substantial importance for irrigation, industrial, recreation and domestic use. Besides, part of the river is flowing on Turkish territory and the control and management of the Maritsa catchment is of mutual interst for the neighboring countires. Thus, performing interpretation and modeling of the river water quality is a major environmetric problem. Two multivariate statstical methods (Cluster analysis/CA/and Principal components analysis/PCA/) were applied for model assessment of the water quality of Maritsa River on Bulgarian territory. The study used long-term monitoring data from 21 sampling sites characterized by 8 surface water quality indicators. The application of CA to the indicators results in 3 significant clusters showing the impact of biological, anthropogenic and eutrophication sources. For further assessment of the monitoring data, PCA was implemented, which identified, again,three latent factors confirming, in principle, the clustering output. The latent factors were conditionally named "biologic", "anthropogenic" and "eutrophication" source. Their identification coinside correctly to the location of real pollution sources along the Maritsa River catchment. The linkage of the sampling sites along the river flow by CA identified four special patterns separated by specific tracers levels: biological and anthropogenic major impact for pattern 1, euthrophication major impact for pattern 2, background levels for pattern 3 and eutrophication and agricultural major impact for pattern 4. The apportionment models of the pollution determined the contribution of each one of identified pollution factors to the total concentration of each one of the water quality parameters. Thus, a better risk management of the surface water quality is achieved both on local and national level.

A Novel Patient-Derived Conceptual Model of the Impact of Celiac Disease in Adults: Implications for Patient-Reported Outcome and Health-Related Quality-of-Life Instrument Development.

PubMed

Leffler, Daniel A; Acaster, Sarah; Gallop, Katy; Dennis, Melinda; Kelly, Ciarán P; Adelman, Daniel C

2017-04-01

Celiac disease is a chronic inflammatory condition with wide ranging effects on individual's lives caused by a combination of symptoms and the burden of adhering to a gluten-free diet (GFD). To further understand patients' experience of celiac disease, the impact it has on health-related quality of life (HRQOL), and to develop a conceptual model describing this impact. Adults with celiac disease on a GFD reporting symptoms within the previous 3 months were included; patients with refractory celiac disease and confounding medical conditions were excluded. A semistructured discussion guide was developed exploring celiac disease symptoms and impact on patients' HRQOL. An experienced interviewer conducted in-depth interviews. The data set was coded and analyzed using thematic analysis to identify concepts, themes, and the inter-relationships between them. Data saturation was monitored and concepts identified formed the basis of the conceptual model. Twenty-one participants were recruited, and 32 distinct gluten-related symptoms were reported and data saturation was reached. Analysis identified several themes impacting patients' HRQOL: fears and anxiety, day-to-day management of celiac disease, physical functioning, sleep, daily activities, social activities, emotional functioning, and relationships. The conceptual model highlights the main areas of impact and the relationships between concepts. Both symptoms and maintaining a GFD have a substantial impact on patient functioning and HRQOL in adults with celiac disease. The conceptual model derived from these data may help to design future patient-reported outcomes as well as interventions to improve the quality of life in an individual with celiac disease. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Does Glycemic Variability Impact Mood and Quality of Life?

PubMed Central

Quinn, Lauretta; Byrn, Mary; Ferrans, Carol; Miller, Michael; Strange, Poul

2012-01-01

Abstract Background Diabetes is a chronic condition that significantly impacts quality of life. Poor glycemic control is associated with more diabetes complications, depression, and worse quality of life. The impact of glycemic variability on mood and quality of life has not been studied. Methods A descriptive exploratory design was used. Twenty-three women with type 2 diabetes wore a continuous glucose monitoring system for 72 h and completed a series of questionnaires. Measurements included (1) glycemic control shown by glycated hemoglobin and 24-h mean glucose, (2) glycemic variability shown by 24-h SD of the glucose readings, continuous overall net glycemic action (CONGA), and Fourier statistical models to generate smoothed curves to assess rate of change defined as “energy,” and (3) mood (depression, anxiety, anger) and quality of life by questionnaires. Results Women with diabetes and co-morbid depression had higher anxiety, more anger, and lower quality of life than those without depression. Certain glycemic variability measures were associated with mood and quality of life. The 24-h SD of the glucose readings and the CONGA measures were significantly associated with health-related quality of life after adjusting for age and weight. Fourier models indicated that certain energy components were significantly associated with depression, trait anxiety, and overall quality of life. Finally, subjects with higher trait anxiety tended to have steeper glucose excursions. Conclusions Data suggest that greater glycemic variability may be associated with lower quality of life and negative moods. Implications include replication of the study in a larger sample for the assessment of blood glucose fluctuations as they impact mood and quality of life. PMID:22324383

Budget Impact of a Comprehensive Nutrition-Focused Quality Improvement Program for Malnourished Hospitalized Patients

PubMed Central

Sulo, Suela; Feldstein, Josh; Partridge, Jamie; Schwander, Bjoern; Sriram, Krishnan; Summerfelt, Wm. Thomas

2017-01-01

Background Nutrition interventions can alleviate the burden of malnutrition by improving patient outcomes; however, evidence on the economic impact of medical nutrition intervention remains limited. A previously published nutrition-focused quality improvement program targeting malnourished hospitalized patients showed that screening patients with a validated screening tool at admission, rapidly administering oral nutritional supplements, and educating patients on supplement adherence result in significant reductions in 30-day unplanned readmissions and hospital length of stay. Objectives To assess the potential cost-savings associated with decreased 30-day readmissions and hospital length of stay in malnourished inpatients through a nutrition-focused quality improvement program using a web-based budget impact model, and to demonstrate the clinical and fiscal value of the intervention. Methods The reduction in readmission rate and length of stay for 1269 patients enrolled in the quality improvement program (between October 13, 2014, and April 2, 2015) were compared with the pre–quality improvement program baseline and validation cohorts (4611 patients vs 1319 patients, respectively) to calculate potential cost-savings as well as to inform the design of the budget impact model. Readmission rate and length-of-stay reductions were calculated by determining the change from baseline to post–quality improvement program as well as the difference between the validation cohort and the post–quality improvement program, respectively. Results As a result of improved health outcomes for the treated patients, the nutrition-focused quality improvement program led to a reduction in 30-day hospital readmissions and length of stay. The avoided hospital readmissions and reduced number of days in the hospital for the patients in the quality improvement program resulted in cost-savings of $1,902,933 versus the pre–quality improvement program baseline cohort, and $4,896,758 versus the pre–quality improvement program in the validation cohort. When these costs were assessed across the entire patient population enrolled in the quality improvement program, per-patient net savings of $1499 when using the baseline cohort as the comparator and savings per patient treated of $3858 when using the validated cohort as the comparator were achieved. Conclusion The nutrition-focused quality improvement program reduced the per-patient healthcare costs by avoiding 30-day readmissions and through reduced length of hospital stay. These clinical and economic outcomes provide a rationale for merging patient care and financial modeling to advance the delivery of value-based medicine in a malnourished hospitalized population. The use of a novel web-based budget impact model supports the integration of comparative effectiveness analytics and healthcare resource management in the hospital setting to provide optimal quality of care at a reduced overall cost. PMID:28975010

Budget Impact of a Comprehensive Nutrition-Focused Quality Improvement Program for Malnourished Hospitalized Patients.

PubMed

Sulo, Suela; Feldstein, Josh; Partridge, Jamie; Schwander, Bjoern; Sriram, Krishnan; Summerfelt, Wm Thomas

2017-07-01

Nutrition interventions can alleviate the burden of malnutrition by improving patient outcomes; however, evidence on the economic impact of medical nutrition intervention remains limited. A previously published nutrition-focused quality improvement program targeting malnourished hospitalized patients showed that screening patients with a validated screening tool at admission, rapidly administering oral nutritional supplements, and educating patients on supplement adherence result in significant reductions in 30-day unplanned readmissions and hospital length of stay. To assess the potential cost-savings associated with decreased 30-day readmissions and hospital length of stay in malnourished inpatients through a nutrition-focused quality improvement program using a web-based budget impact model, and to demonstrate the clinical and fiscal value of the intervention. The reduction in readmission rate and length of stay for 1269 patients enrolled in the quality improvement program (between October 13, 2014, and April 2, 2015) were compared with the pre-quality improvement program baseline and validation cohorts (4611 patients vs 1319 patients, respectively) to calculate potential cost-savings as well as to inform the design of the budget impact model. Readmission rate and length-of-stay reductions were calculated by determining the change from baseline to post-quality improvement program as well as the difference between the validation cohort and the post-quality improvement program, respectively. As a result of improved health outcomes for the treated patients, the nutrition-focused quality improvement program led to a reduction in 30-day hospital readmissions and length of stay. The avoided hospital readmissions and reduced number of days in the hospital for the patients in the quality improvement program resulted in cost-savings of $1,902,933 versus the pre-quality improvement program baseline cohort, and $4,896,758 versus the pre-quality improvement program in the validation cohort. When these costs were assessed across the entire patient population enrolled in the quality improvement program, per-patient net savings of $1499 when using the baseline cohort as the comparator and savings per patient treated of $3858 when using the validated cohort as the comparator were achieved. The nutrition-focused quality improvement program reduced the per-patient healthcare costs by avoiding 30-day readmissions and through reduced length of hospital stay. These clinical and economic outcomes provide a rationale for merging patient care and financial modeling to advance the delivery of value-based medicine in a malnourished hospitalized population. The use of a novel web-based budget impact model supports the integration of comparative effectiveness analytics and healthcare resource management in the hospital setting to provide optimal quality of care at a reduced overall cost.

Improving the Quality of Positive Datasets for the Establishment of Machine Learning Models for pre-microRNA Detection.

PubMed

Demirci, Müşerref Duygu Saçar; Allmer, Jens

2017-07-28

MicroRNAs (miRNAs) are involved in the post-transcriptional regulation of protein abundance and thus have a great impact on the resulting phenotype. It is, therefore, no wonder that they have been implicated in many diseases ranging from virus infections to cancer. This impact on the phenotype leads to a great interest in establishing the miRNAs of an organism. Experimental methods are complicated which led to the development of computational methods for pre-miRNA detection. Such methods generally employ machine learning to establish models for the discrimination between miRNAs and other sequences. Positive training data for model establishment, for the most part, stems from miRBase, the miRNA registry. The quality of the entries in miRBase has been questioned, though. This unknown quality led to the development of filtering strategies in attempts to produce high quality positive datasets which can lead to a scarcity of positive data. To analyze the quality of filtered data we developed a machine learning model and found it is well able to establish data quality based on intrinsic measures. Additionally, we analyzed which features describing pre-miRNAs could discriminate between low and high quality data. Both models are applicable to data from miRBase and can be used for establishing high quality positive data. This will facilitate the development of better miRNA detection tools which will make the prediction of miRNAs in disease states more accurate. Finally, we applied both models to all miRBase data and provide the list of high quality hairpins.

Impact of length of dataset on streamflow calibration parameters and performance of APEX model

USDA-ARS?s Scientific Manuscript database

Due to resource constraints, long-term monitoring data for calibration and validation of hydrologic and water quality models are rare. As a result, most models are calibrated and, if possible, validated using limited measured data. However, little research has been done to determine the impact of le...

Modeling study of biomass burning plumes and their impact on urban air quality; a case study of Santiago de Chile

NASA Astrophysics Data System (ADS)

Cuchiara, G. C.; Rappenglück, B.; Rubio, M. A.; Lissi, E.; Gramsch, E.; Garreaud, R. D.

2017-10-01

On January 4, 2014, during the summer period in South America, an intense forest and dry pasture wildfire occurred nearby the city of Santiago de Chile. On that day the biomass-burning plume was transported by low-intensity winds towards the metropolitan area of Santiago and impacted the concentration of pollutants in this region. In this study, the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem) is implemented to investigate the biomass-burning plume associated with these wildfires nearby Santiago, which impacted the ground-level ozone concentration and exacerbated Santiago's air quality. Meteorological variables simulated by WRF/Chem are compared against surface and radiosonde observations, and the results show that the model reproduces fairly well the observed wind speed, wind direction air temperature and relative humidity for the case studied. Based on an analysis of the transport of an inert tracer released over the locations, and at the time the wildfires were captured by the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS), the model reproduced reasonably well the transport of biomass burning plume towards the city of Santiago de Chile within a time delay of two hours as observed in ceilometer data. A six day air quality simulation was performed: the first three days were used to validate the anthropogenic and biogenic emissions, and the last three days (during and after the wildfire event) to analyze the performance of WRF/Chem plume-rise model within FINNv1 fire emission estimations. The model presented a satisfactory performance on the first days of the simulation when contrasted against data from the well-established air quality network over the city of Santiago de Chile. These days represent the urban air quality base case for Santiago de Chile unimpacted by fire emissions. However, for the last three simulation days, which were impacted by the fire emissions, the statistical indices showed a decrease in the model performance. While the model showed a satisfactory evidence that wildfires plumes that originated in the vicinity of Santiago de Chile were transported towards the urban area and impacted the air quality, the model still underpredicted some pollutants substantially, likely due to misrepresentation of fire emission sources during those days. Potential uncertainties may include to the land use/land cover classifications and its characteristics, such as type and density of vegetation assigned to the region, where the fire spots are detected. The variability of the ecosystem type during the fire event might also play a role.

The impact of water quality in Narragansett Bay on housing prices

NASA Astrophysics Data System (ADS)

Liu, Tingting; Opaluch, James J.; Uchida, Emi

2017-08-01

We examine the impact of water quality in Narragansett Bay on housing prices in coastal towns and cities using a hedonic housing-price model. Unlike other hedonic studies of water quality, we test whether housing market responds to average water quality or more to extreme events. We also test the spatial and temporal extent of effects of water quality on housing prices. We find that poor coastal water quality, measured in terms of the concentration of chlorophyll, has a negative impact on housing prices that diminishes with distance from the shoreline. Furthermore, our finding suggests that housing prices are most influenced by the extreme environmental conditions, which may be accompanied by unpleasant odors, discoloration, and even fish kills. We further predict potential increases in home values associated under water quality improvement scenarios and find an increase in the values of homes in coastal communities along Narragansett Bay of about 18 million up to 136 million.

Cost-effectiveness and Budget Impact of Routine Use of Fractional Exhaled Nitric Oxide Monitoring for the Management of Adult Asthma Patients in Spain.

PubMed

Sabatelli, L; Seppälä, U; Sastre, J; Crater, G

Fractional exhaled nitric oxide (FeNO) is a marker for type 2 airway inflammation. The objective of this study was to evaluate the cost-effectiveness and budget impact of FeNO monitoring for management of adult asthma in Spain. A cost-effectiveness analysis model was used to evaluate the effect on costs of adding FeNO monitoring to asthma management. Over a 1-year period, the model estimated the incremental cost per quality-adjusted life year and incremental number of exacerbations avoided when FeNO monitoring was added to standard guideline-driven asthma care compared with standard care alone. Univariate and multivariate sensitivity analyses were applied to explore uncertainty in the model. A budget impact model was used to examine the impact of FeNO monitoring on primary care costs across the Spanish health system. The results showed that adding FeNO to standard asthma care saved €62.53 per patient-year in the adult population and improved quality-adjusted life years by 0.026 per patient-year. The budget impact analysis revealed a potential net yearly saving of €129 million if FeNO monitoring had been used in primary care settings in Spain. The present economic model shows that adding FeNO to the treatment algorithm can considerably reduce costs and improve quality of life when used to manage asthma in combination with current treatment guidelines.

Reactive transport modeling of geochemical controls on secondary water quality impacts at a crude oil spill site near Bemidji, MN

USGS Publications Warehouse

Ng, Gene-Hua Crystal.; Bekins, Barbara A.; Cozzarelli, Isabelle M.; Baedecker, Mary Jo; Bennett, Philip C.; Amos, Richard T.; Herkelrath, William N.

2015-01-01

Anaerobic biodegradation of organic amendments and contaminants in aquifers can trigger secondary water quality impacts that impair groundwater resources. Reactive transport models help elucidate how diverse geochemical reactions control the spatiotemporal evolution of these impacts. Using extensive monitoring data from a crude oil spill site near Bemidji, Minnesota (USA), we implemented a comprehensive model that simulates secondary plumes of depleted dissolved O2 and elevated concentrations of Mn2+, Fe2+, CH4, and Ca2+ over a two-dimensional cross section for 30 years following the spill. The model produces observed changes by representing multiple oil constituents and coupled carbonate and hydroxide chemistry. The model includes reactions with carbonates and Fe and Mn mineral phases, outgassing of CH4 and CO2 gas phases, and sorption of Fe, Mn, and H+. Model results demonstrate that most of the carbon loss from the oil (70%) occurs through direct outgassing from the oil source zone, greatly limiting the amount of CH4 cycled down-gradient. The vast majority of reduced Fe is strongly attenuated on sediments, with most (91%) in the sorbed form in the model. Ferrous carbonates constitute a small fraction of the reduced Fe in simulations, but may be important for furthering the reduction of ferric oxides. The combined effect of concomitant redox reactions, sorption, and dissolved CO2 inputs from source-zone degradation successfully reproduced observed pH. The model demonstrates that secondary water quality impacts may depend strongly on organic carbon properties, and impacts may decrease due to sorption and direct outgassing from the source zone.

Reduced order models for prediction of groundwater quality impacts from CO₂ and brine leakage

DOE PAGES

Zheng, Liange; Carroll, Susan; Bianchi, Marco; ...

2014-12-31

A careful assessment of the risk associated with geologic CO₂ storage is critical to the deployment of large-scale storage projects. A potential risk is the deterioration of groundwater quality caused by the leakage of CO₂ and brine leakage from deep subsurface reservoirs. In probabilistic risk assessment studies, numerical modeling is the primary tool employed to assess risk. However, the application of traditional numerical models to fully evaluate the impact of CO₂ leakage on groundwater can be computationally complex, demanding large processing times and resources, and involving large uncertainties. As an alternative, reduced order models (ROMs) can be used as highlymore » efficient surrogates for the complex process-based numerical models. In this study, we represent the complex hydrogeological and geochemical conditions in a heterogeneous aquifer and subsequent risk by developing and using two separate ROMs. The first ROM is derived from a model that accounts for the heterogeneous flow and transport conditions in the presence of complex leakage functions for CO₂ and brine. The second ROM is obtained from models that feature similar, but simplified flow and transport conditions, and allow for a more complex representation of all relevant geochemical reactions. To quantify possible impacts to groundwater aquifers, the basic risk metric is taken as the aquifer volume in which the water quality of the aquifer may be affected by an underlying CO₂ storage project. The integration of the two ROMs provides an estimate of the impacted aquifer volume taking into account uncertainties in flow, transport and chemical conditions. These two ROMs can be linked in a comprehensive system level model for quantitative risk assessment of the deep storage reservoir, wellbore leakage, and shallow aquifer impacts to assess the collective risk of CO₂ storage projects.« less

Assessing concentrations and health impacts of air quality management strategies: Framework for Rapid Emissions Scenario and Health impact ESTimation (FRESH-EST).

PubMed

Milando, Chad W; Martenies, Sheena E; Batterman, Stuart A

2016-09-01

In air quality management, reducing emissions from pollutant sources often forms the primary response to attaining air quality standards and guidelines. Despite the broad success of air quality management in the US, challenges remain. As examples: allocating emissions reductions among multiple sources is complex and can require many rounds of negotiation; health impacts associated with emissions, the ultimate driver for the standards, are not explicitly assessed; and long dispersion model run-times, which result from the increasing size and complexity of model inputs, limit the number of scenarios that can be evaluated, thus increasing the likelihood of missing an optimal strategy. A new modeling framework, called the "Framework for Rapid Emissions Scenario and Health impact ESTimation" (FRESH-EST), is presented to respond to these challenges. FRESH-EST estimates concentrations and health impacts of alternative emissions scenarios at the urban scale, providing efficient computations from emissions to health impacts at the Census block or other desired spatial scale. In addition, FRESH-EST can optimize emission reductions to meet specified environmental and health constraints, and a convenient user interface and graphical displays are provided to facilitate scenario evaluation. The new framework is demonstrated in an SO2 non-attainment area in southeast Michigan with two optimization strategies: the first minimizes emission reductions needed to achieve a target concentration; the second minimizes concentrations while holding constant the cumulative emissions across local sources (e.g., an emissions floor). The optimized strategies match outcomes in the proposed SO2 State Implementation Plan without the proposed stack parameter modifications or shutdowns. In addition, the lower health impacts estimated for these strategies suggest that FRESH-EST could be used to identify potentially more desirable pollution control alternatives in air quality management planning. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cost analysis of impacts of climate change on regional air quality.

PubMed

Liao, Kuo-Jen; Tagaris, Efthimios; Russell, Armistead G; Amar, Praveen; He, Shan; Manomaiphiboon, Kasemsan; Woo, Jung-Hun

2010-02-01

Climate change has been predicted to adversely impact regional air quality with resulting health effects. Here a regional air quality model and a technology analysis tool are used to assess the additional emission reductions required and associated costs to offset impacts of climate change on air quality. Analysis is done for six regions and five major cities in the continental United States. Future climate is taken from a global climate model simulation for 2049-2051 using the Intergovernmental Panel on Climate Change (IPCC) A1B emission scenario, and emission inventories are the same as current ones to assess impacts of climate change alone on air quality and control expenses. On the basis of the IPCC A1B emission scenario and current control technologies, least-cost sets of emission reductions for simultaneously offsetting impacts of climate change on regionally averaged 4th highest daily maximum 8-hr average ozone and yearly averaged PM2.5 (particulate matter [PM] with an aerodynamic diameter less than 2.5 microm) for the six regions examined are predicted to range from $36 million (1999$) yr(-1) in the Southeast to $5.5 billion yr(-1) in the Northeast. However, control costs to offset climate-related pollutant increases in urban areas can be greater than the regional costs because of the locally exacerbated ozone levels. An annual cost of $4.1 billion is required for offsetting climate-induced air quality impairment in 2049-2051 in the five cities alone. Overall, an annual cost of $9.3 billion is estimated for offsetting climate change impacts on air quality for the six regions and five cities examined. Much of the additional expense is to reduce increased levels of ozone. Additional control costs for offsetting the impacts everywhere in the United States could be larger than the estimates in this study. This study shows that additional emission controls and associated costs for offsetting climate impacts could significantly increase currently estimated control requirements and should be considered in developing control strategies for achieving air quality targets in the future.

STAR Measurements and Modeling for Quantifying Air Quality and Climatic Impacts of Residential Biomass or Coal Combustion for Cooking, Heating and Lighting Kick-off Meeting

EPA Pesticide Factsheets

STAR grantees and EPA scientists will discuss progress on their projects which aim to quantify the extent to which interventions for cleaner cooking, heating, or lighting can impact air quality and climate, which in turn affect human health and welfare

IMPACT OF AN OZONE GENERATOR AIR CLEANER ON STYRENE CONCENTRATIONS IN AN INDOOR AIR QUALITY RESEARCH CHAMBER

EPA Science Inventory

The paper gives results of an investigation of the impact of an ozone generator air cleaner on vapor-phase styrene concentrations in a full-scale indoor air quality test chamber. The time history of the concentrations of styrene and ozone is well predicted by a simulation model u...

The Role of Peer Influence and Perceived Quality of Teaching in Faculty Acceptance of Web-Based Learning Management Systems

ERIC Educational Resources Information Center

Salajan, Florin D.; Welch, Anita G.; Ray, Chris M.; Peterson, Claudette

2015-01-01

This study's primary investigation is the impact of "peer influence" and "perceived quality of teaching" on faculty members' usage of web-based learning management systems within the Technology Acceptance Model (TAM) framework. These factors are entered into an extended TAM as external variables impacting on the core constructs…

Drought allocations using the Systems Impact Assessment Model: Klamath River

USGS Publications Warehouse

Flug, M.; Campbell, S.G.

2005-01-01

Water supply and allocation scenarios for the Klamath River, Ore. and Calif., were evaluated using the Systems Impact Assessment Model (SIAM), a decision support system developed by the U.S. Geological Survey. SIAM is a set of models with a graphical user interface that simulates water supply and delivery in a managed river system, water quality, and fish production. Simulation results are presented for drought conditions, one aspect of Klamath River water operations. The Klamath River Basin has experienced critically dry conditions in 1992, 1994, and 2001. Drought simulations are useful to estimate the impacts of specific legal or institutional flow constraints. In addition, simulations help to identify potential adverse water quality consequences including evaluating the potential for reducing adverse temperature impacts on anadromous fish. In all drought simulations, water supply was insufficient to fully meet upstream and downstream targets for endangered species.

IS Success Model in E-Learning Context Based on Students' Perceptions

ERIC Educational Resources Information Center

Freeze, Ronald D.; Alshare, Khaled A.; Lane, Peggy L.; Wen, H. Joseph

2010-01-01

This study utilized the Information Systems Success (ISS) model in examining e-learning systems success. The study was built on the premise that system quality (SQ) and information quality (IQ) influence system use and user satisfaction, which in turn impact system success. A structural equation model (SEM), using LISREL, was used to test the…

The influence of data curation on QSAR Modeling - examining issues of quality versus quantity of data (American Chemical Society)

EPA Science Inventory

This presentation will examine the impact of data quality on the construction of QSAR models being developed within the EPA‘s National Center for Computational Toxicology. We have developed a public-facing platform to provide access to predictive models. As part of the work we ha...

Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model

EPA Science Inventory

Sea spray aerosols (SSA) impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. In this study, the Community Multiscale Air Quality (CMAQ) model is updated to enhance fine mode SSA emissions,...

Modelling Carpool and Transit Park-and-Ride Lots

DOT National Transportation Integrated Search

1997-01-01

Park-and-Ride (PnR) lots are an increasingly common element of many areas plans for air quality conformity. However, few, if any, travel models estimate the impacts of carpool PnR lots, and it is not at all clear that they always improve air quality....

Path Forward for the Air Quality Model Evaluation International Initiative (AQMEII)

EPA Science Inventory

This article lays out the objectives for Phase 2 of the Air Quality Model Evaluation International Initiative (AQMEII). The inhalation of air pollutants such as ozone and fine particles has been linked to adverse impacts on human health, and the atmospheric deposition of pollutan...

Evaluating water quality ecosystem services of wetlands under historic and future climate

NASA Astrophysics Data System (ADS)

Records, R.; Arabi, M.; Fassnacht, S. R.; Duffy, W.; Ahmadi, M.; Hegewisch, K.

2013-12-01

Potential hydrologic effects of climate change have been assessed extensively; however, possible impacts of changing climate on in-stream water quality at the watershed scale have received little study. We assessed potential impacts of climate change on water quantity and quality in the mountainous Sprague River watershed, Oregon, USA, where high total phosphorus (TP) and sediment loads are associated with lake eutrophication and mortality of endangered fish species. Additionally, we analyzed water quality impacts of wetland and riparian zone loss and gain under present-day climate and future climate scenarios. We utilized the hydrologic model Soil and Water Assessment Tool (SWAT) forced with six distinct climate scenarios derived from Coupled Model Intercomparison Project 5 (CMIP5) General Circulation Models to assess magnitude and direction of trends in streamflow, sediment and TP fluxes in the mid-21st century (2030-2059). Model results showed little significant trend in average annual streamflow under most climate scenarios, but trends in annual and monthly streamflow, sediment, and TP fluxes were more pronounced and were generally increasing. Results also suggest that future loss of present-day wetlands and riparian zones under land use or climatic change could result in substantial increases in sediment and TP loads at the Sprague River outlet.

Assessing possible visitor-use impacts on water quality in Yosemite National Park, California

USGS Publications Warehouse

Clow, David W.; Peavler, Rachael S.; Roche, Jim; Panorska, Anna K.; Thomas, James M.; Smith, Steve

2011-01-01

There is concern that visitor-use associated activities, such as bathing, dish washing, wastewater production, and stock animal use near lakes and streams, could cause degradation of water quality in Yosemite National Park. A study was conducted during 2004–2007 to assess patterns in nutrient and Escherichia coli (E. coli) concentrations in the Merced and Tuolumne Rivers and characterize natural background concentrations of nutrients in the park. Results indicated that nutrient and E. coli concentrations were low, even compared to other undeveloped sites in the United States. A multiple linear regression approach was used to model natural background concentrations of nutrients, with basin characteristics as explanatory variables. Modeled nitrogen concentrations increased with elevation, and modeled phosphorus concentrations increased with basin size. Observed concentrations (±uncertainty) were compared to modeled concentrations (±uncertainty) to identify sites that might be impacted by point sources of nutrients, as indicated by large model residuals. Statistically significant differences in observed and modeled concentrations were observed at only a few locations, indicating that most sites were representative of natural background conditions. The empirical modeling approach used in this study can be used to estimate natural background conditions at any point along a study reach in areas minimally impacted by development, and may be useful for setting water-quality standards in many national parks.

Assessing the impacts of climate change and socio-economic changes on flow and phosphorus flux in the Ganga river system.

PubMed

Jin, L; Whitehead, P G; Sarkar, S; Sinha, R; Futter, M N; Butterfield, D; Caesar, J; Crossman, J

2015-06-01

Anthropogenic climate change has impacted and will continue to impact the natural environment and people around the world. Increasing temperatures and altered rainfall patterns combined with socio-economic factors such as population changes, land use changes and water transfers will affect flows and nutrient fluxes in river systems. The Ganga river, one of the largest river systems in the world, supports approximately 10% global population and more than 700 cities. Changes in the Ganga river system are likely to have a significant impact on water availability, water quality, aquatic habitats and people. In order to investigate these potential changes on the flow and water quality of the Ganga river, a multi-branch version of INCA Phosphorus (INCA-P) model has been applied to the entire river system. The model is used to quantify the impacts from a changing climate, population growth, additional agricultural land, pollution control and water transfers for 2041-2060 and 2080-2099. The results provide valuable information about potential effects of different management strategies on catchment water quality.

Integrating Hydrologic and Water Quality Models as a Decision Support Tool for Implementation of Low Impact Development in a Coastal Urban Watershed under Climate Variability and Sea Level Rise

NASA Astrophysics Data System (ADS)

Chang, N. B.

2016-12-01

Many countries concern about development and redevelopment efforts in urban regions to reduce the flood risk by considering hazards such as high-tide events, storm surge, flash floods, stormwater runoff, and impacts of sea level rise. Combining these present and future hazards with vulnerable characteristics found throughout coastal communities such as majority low-lying areas and increasing urban development, create scenarios for increasing exposure of flood hazard. As such, the most vulnerable areas require adaptation strategies and mitigation actions for flood hazard management. In addition, in the U.S., Numeric Nutrient Criteria (NNC) are a critical tool for protecting and restoring the designated uses of a waterbody with regard to nitrogen and phosphorus pollution. Strategies such as low impact development (LID) have been promoted in recent years as an alternative to traditional stormwater management and drainage to control both flooding and water quality impact. LID utilizes decentralized multifunctional site designs and incorporates on-site storm water management practices rather than conventional storm water management approaches that divert flow toward centralized facilities. How to integrate hydrologic and water quality models to achieve the decision support becomes a challenge. The Cross Bayou Watershed of Pinellas County in Tampa Bay, a highly urbanized coastal watershed, is utilized as a case study due to its sensitivity to flood hazards and water quality management within the watershed. This study will aid the County, as a decision maker, to implement its stormwater management policy and honor recent NNC state policy via demonstration of an integrated hydrologic and water quality model, including the Interconnected Channel and Pond Routing Model v.4 (ICPR4) and the BMPTRAIN model as a decision support tool. The ICPR4 can be further coupled with the ADCIRC/SWAN model to reflect the storm surge and seal level rise in coastal regions.

Learning a Continuous-Time Streaming Video QoE Model.

PubMed

Ghadiyaram, Deepti; Pan, Janice; Bovik, Alan C

2018-05-01

Over-the-top adaptive video streaming services are frequently impacted by fluctuating network conditions that can lead to rebuffering events (stalling events) and sudden bitrate changes. These events visually impact video consumers' quality of experience (QoE) and can lead to consumer churn. The development of models that can accurately predict viewers' instantaneous subjective QoE under such volatile network conditions could potentially enable the more efficient design of quality-control protocols for media-driven services, such as YouTube, Amazon, Netflix, and so on. However, most existing models only predict a single overall QoE score on a given video and are based on simple global video features, without accounting for relevant aspects of human perception and behavior. We have created a QoE evaluator, called the time-varying QoE Indexer, that accounts for interactions between stalling events, analyzes the spatial and temporal content of a video, predicts the perceptual video quality, models the state of the client-side data buffer, and consequently predicts continuous-time quality scores that agree quite well with human opinion scores. The new QoE predictor also embeds the impact of relevant human cognitive factors, such as memory and recency, and their complex interactions with the video content being viewed. We evaluated the proposed model on three different video databases and attained standout QoE prediction performance.

Impact of aircraft emissions on air quality in the vicinity of airports. Volume I. Recent airport measurement programs, data analyses, and sub-model development. Final report Jan78-Jul 80

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

Yamartino, R.J.; Smith, D.G.; Bremer, S.A.

1980-07-01

This report documents the results of the Federal Aviation Administration (FAA)/Environmental Protection Agency (EPA) air quality study which has been conducted to assess the impact of aircraft emissions of carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen (NOx) in the vicinity of airports. This assessment includes the results of recent modeling and monitoring efforts at Washington National (DCA), Los Angeles International (LAX), Dulles International (IAD), and Lakeland, Florida airports and an updated modeling of aircraft generated pollution at LAX, John F. Kennedy (JFK) and Chicago O'Hare (ORD) airports. The Airport Vicinity Air Pollution (AVAP) model which was designed formore » use at civil airports was used in this assessment. In addition the results of the application of the military version of the AVAP model the Air Quality Assessment Model (AQAM), are summarized.« less

SWAT Model Application to Assess the Impact of Intensive Corn‐farming on Runoff, Sediments and Phosphorous loss from an Agricultural Watershed in Wisconsin

EPA Science Inventory

The potential future increase in corn-based biofuel may be expected to have a negative impact on water quality in streams and lakes of the Midwestern US due to increased agricultural chemicals usage. This study used the SWAT model to assess the impact of continuous-corn farming o...

Impact of the basic state and MJO representation on MJO Pacific teleconnections in GCMs

NASA Astrophysics Data System (ADS)

Henderson, S. A.; Maloney, E. D.; Son, S. W.

2017-12-01

Teleconnection patterns induced by the Madden-Julian Oscillation (MJO) are known to significantly alter extratropical weather and climate patterns. However, accurate MJO representation has been difficult for many General Circulation Models (GCMs). Furthermore, many GCMs contain large basic state biases. These issues present challenges to the simulation of MJO teleconnections and, in turn, their associated extratropical impacts. This study examines the impacts of basic state quality and MJO representation on the quality of MJO teleconnection patterns in GCMs from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Results suggest that GCMs assessed to have a good MJO but with large basic state biases have similarly low skill in reproducing MJO teleconnections as GCMs with poor MJO representation. In the good MJO models examined, poor teleconnection quality is associated with large errors in the zonal extent of the Pacific subtropical jet. Whereas the horizontal structure of MJO heating in the Indo-Pacific region is found to have modest impacts on the teleconnection patterns, results suggest that MJO heating east of the dateline can alter the teleconnection pattern characteristics over North America. These findings suggest that in order to accurately simulate the MJO teleconnection patterns and associated extratropical impacts, both the MJO and the basic state must be well represented.

Corn stover harvest increases herbicide movement to subsurface drains – Root Zone Water Quality Model simulations

USDA-ARS?s Scientific Manuscript database

BACKGROUND: Removal of crop residues for bioenergy production can alter soil hydrologic properties, but there is little information on its impact on transport of herbicides and their degradation products to subsurface drains. The Root Zone Water Quality Model, previously calibrated using measured fl...

Impact of Rainfall Data Source on Hydrologic and Water Quality Model Response of a Coastal Plain Watershed

USDA-ARS?s Scientific Manuscript database

Hydrologic and water quality models are very sensitive to input parameter values, especially precipitation input data. With several different sources of precipitation data now available, it is quite difficult to determine which source is most appropriate under various circumstances. We used several ...

EUTROPHICATION MODELING CAPABILITIES FOR WATER QUALITY AND INTEGRATION TOWARDS ECOLOGICAL ENDPOINTS

EPA Science Inventory

A primary environmental focus for the use of mathematical models is for characterization of sources of nutrients and sediments and their relative loadings from large river basins, and the impact of land uses from smaller sub-basins on water quality in rivers, lakes, and estuaries...

Impact of Increased Corn Production on Ground Water Quality and Human Health

EPA Science Inventory

In this study, we use a complex coupled modeling system to assess the impacts of increased corn production on groundwater. In particular, we show how the models provide new information on the drivers of contamination in groundwater, and then relate pollutant concentration change...

Modeling crop residue burning experiments to evaluate smoke emissions and plume transport

EPA Science Inventory

Crop residue burning is a common land management practice that results in emissions of a variety of pollutants with negative health impacts. Modeling systems are used to estimate air quality impacts of crop residue burning to support retrospective regulatory assessments and also ...

Rural-Urban Differences in Medicare Quality Outcomes and the Impact of Risk Adjustment.

PubMed

Henning-Smith, Carrie; Kozhimannil, Katy; Casey, Michelle; Prasad, Shailendra; Moscovice, Ira

2017-09-01

There has been considerable debate in recent years about whether, and how, to risk-adjust quality measures for sociodemographic characteristics. However, geographic location, especially rurality, has been largely absent from the discussion. To examine differences by rurality in quality outcomes, and the impact of adjustment for individual and community-level sociodemographic characteristics on quality outcomes. The 2012 Medicare Current Beneficiary Survey, Access to Care module, combined with the 2012 County Health Rankings. All data used were publicly available, secondary data. We merged the 2012 Medicare Current Beneficiary Survey data with the 2012 County Health Rankings data using county of residence. We compared 6 unadjusted quality of care measures for Medicare beneficiaries (satisfaction with care, blood pressure checked, cholesterol checked, flu shot receipt, change in health status, and all-cause annual readmission) by rurality (rural noncore, micropolitan, and metropolitan). We then ran nested multivariable logistic regression models to assess the impact of adjusting for community and individual-level sociodemographic characteristics to determine whether these mediate the rurality difference in quality of care. The relationship between rurality and change in health status was mediated by the inclusion of community-level characteristics; however, adjusting for community and individual-level characteristics caused differences by rurality to emerge in 2 of the measures: blood pressure checked and cholesterol checked. For all quality scores, model fit improved after adding community and individual characteristics. Quality is multifaceted and is impacted by individual and community-level socio-demographic characteristics, as well as by geographic location. Current debates about risk-adjustment procedures should take rurality into account.

Cumulative Impact Assessment: Approaching Environmental Capacity in Development Area Using Environmental Impact Assessment Information

NASA Astrophysics Data System (ADS)

Cho, N.; Lee, M. J.; Maeng, J. H.

2017-12-01

Environmental impact assessment estimates the impact of development as a business unit and establishes mitigation plan. If the development is done, its economic effects can spread to the nearby areas. So that various developments can be distributed at different time intervals. The impact of the new developments can be combined with existing environmental impacts and can have a larger impact. That is, Cumulative impact assessment is needed to consider the environmental capacity of the Nearby area. Cumulative impact assessments require policy tools such as environmental impact assessment information and cumulative impact estimation models. In Korea, environmental information (water quality, air quality, etc.) of the development site is measured for environmental impact assessment and monitored for a certain period (generally 5 years) after the project. In addition, by constructing the environmental information as a spatial database, it is possible to express the environmental impact on a regional basis spatially and to intuitively use it for development site selection. Utilizing a composite model of environmental impact assessment information and Remote Sensing data for cumulative impact estimation, That can be used as a policy decision support tool that provides quantitative information for development area management, such as time series effect and sprawl phenomenon.

PREDICTING THE RELATIVE IMPACTS OF URBAN DEVELOPMENT POLICIES AND ON-ROAD VEHICLE TECHNOLOGIES ON AIR QUALITY IN THE UNITED STATES: MODELING AND ANALYSIS OF A CASE STUDY IN AUSTIN, TEXAS

EPA Science Inventory

Urban development results in changes to land use and land cover and, consequently, to biogenic and anthropogenic emissions, meteorological processes, and processes such as dry deposition that influence future predictions of air quality. This study examines the impacts of alter...

The Impact of Imports and Exports on a Country's Quality of Life

ERIC Educational Resources Information Center

Sirgy, M. Joseph; Lee, Dong-Jin; Miller, Chad; Littlefield, James E.; Atay, Eda Gurel

2007-01-01

This paper is a sequel to Sirgy et al. ("Social Ind. Res." 68(3) (2004) 251), "The Impact of Globalization on a Country's Quality of Life: Toward an Integrated Model" published in "Social Indicators Research." That paper conceptualized globalization in terms of the free flow of four major components: (1) goods and services, (2) people, (3)…

Assessment and economic valuation of air pollution impacts on human health over Europe and the United States as calculated by a multi-model ensemble in the framework of AQMEII3

EPA Science Inventory

The impact of air pollution on human health and the associated external costs in Europe and the United States (US) for the year 2010 are modeled by a multi-model ensemble of regional models in the frame of the third phase of the Air Quality Modelling Evaluation International Init...

Evaluating the impact of AMDAR data quality control in China on the short-range convection forecasts using the WRF model

NASA Astrophysics Data System (ADS)

Wang, Xiaofeng; Jiang, Qin; Zhang, Lei

2016-04-01

A quality control system for the Aircraft Meteorological Data Relay (AMDAR) data has been implemented in China. This system is an extension to the AMDAR quality control system used at the US National Centers for Environmental Prediction. We present a study in which the characteristics of each AMDAR data quality type were examined and the impact of the AMDAR data quality system on short-range convective weather forecasts using the WRF model was investigated. The main results obtained from this study are as follows. (1) The hourly rejection rate of AMDAR data during 2014 was 5.79%, and most of the rejections happened in Near Duplicate Check. (2) There was a significant diurnal variation for both quantity and quality of AMDAR data. Duplicated reports increased with the increase of data quantity, while suspicious and disorderly reports decreased with the increase of data quantity. (3) The characteristics of the data quality were different in each model layer, with the quality problems occurring mainly at the surface as well as at the height where the power or the flight mode of the aircraft underwent adjustment. (4) Assimilating the AMDAR data improved the forecast accuracy, particularly over the region where strong convection occurred. (5) Significant improvements made by assimilating AMDAR data were found after six hours into the model forecast. The conclusion from this study is that the newly implemented AMDAR data quality system can help improve the accuracy of short-range convection forecasts using the WRF model.

Evaluating water management strategies with the Systems Impact Assessment Model: SIAM version 4

USGS Publications Warehouse

Bartholow, John M.; Heasley, John; Hanna, Blair; Sandelin, Jeff; Flug, Marshall; Campbell, Sharon; Henriksen, Jim; Douglas, Aaron

2005-01-01

The apparent disparity between restoration benefits and costs for the Klamath River may suggest to some that water resources on the Klamath be reallocated to environmentally friendly nonmarket uses. The economic analysis rests in part on the information made available to the survey designers by the biological, hydrologic, and water quality data incorporated in The System Impact Assessment Model (SIAM). It is our hope that SIAM can be used to improve the river's water quality and fishery, and strengthen the important regional economy.

NEIGHBORHOOD SCALE AIR QUALITY MODELING IN HOUSTON USING URBAN CANOPY PARAMETERS IN MM5 AND CMAQ WITH IMPROVED CHARACTERIZATION OF MESOSCALE LAKE-LAND BREEZE CIRCULATION

EPA Science Inventory

Advanced capability of air quality simulation models towards accurate performance at finer scales will be needed for such models to serve as tools for performing exposure and risk assessments in urban areas. It is recognized that the impact of urban features such as street and t...

DRAINMOD-GIS: a lumped parameter watershed scale drainage and water quality model

Treesearch

G.P. Fernandez; G.M. Chescheir; R.W. Skaggs; D.M. Amatya

2006-01-01

A watershed scale lumped parameter hydrology and water quality model that includes an uncertainty analysis component was developed and tested on a lower coastal plain watershed in North Carolina. Uncertainty analysis was used to determine the impacts of uncertainty in field and network parameters of the model on the predicted outflows and nitrate-nitrogen loads at the...

Modeling Quality-Adjusted Life Expectancy Loss Resulting from Tobacco Use in the United States

ERIC Educational Resources Information Center

Kaplan, Robert M.; Anderson, John P.; Kaplan, Cameron M.

2007-01-01

Purpose: To describe the development of a model for estimating the effects of tobacco use upon Quality Adjusted Life Years (QALYs) and to estimate the impact of tobacco use on health outcomes for the United States (US) population using the model. Method: We obtained estimates of tobacco consumption from 6 years of the National Health Interview…

The impact of competition on quality and prices in the English care homes market

PubMed Central

Forder, Julien; Allan, Stephen

2014-01-01

This study assesses the impact of competition on quality and price in the English care/nursing homes market. Considering the key institutional features, we use a theoretical model to assess the conditions under which further competition could increase or reduce quality. A dataset comprising the population of 10,000 care homes was used. We constructed distance/travel-time weighted competition measures. Instrumental variable estimations, used to account for the endogeneity of competition, showed quality and price were reduced by greater competition. Further analyses suggested that the negative quality effect worked through the effect on price – higher competition reduces revenue which pushes down quality. PMID:24487075

The impact of competition on quality and prices in the English care homes market.

PubMed

Forder, Julien; Allan, Stephen

2014-03-01

This study assesses the impact of competition on quality and price in the English care/nursing homes market. Considering the key institutional features, we use a theoretical model to assess the conditions under which further competition could increase or reduce quality. A dataset comprising the population of 10,000 care homes was used. We constructed distance/travel-time weighted competition measures. Instrumental variable estimations, used to account for the endogeneity of competition, showed quality and price were reduced by greater competition. Further analyses suggested that the negative quality effect worked through the effect on price - higher competition reduces revenue which pushes down quality. Copyright © 2013 Elsevier B.V. All rights reserved.

An Observational and modeling strategy to investigate the impact of remote sources on local air quality: A Houston, Texas case study from the Second Texas Air Quality Study (TEXAQS II)

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

McMillan, W. W.; Pierce, R.; Sparling, L. C.

2010-01-05

Quantifying the impacts of remote sources on individual air quality exceedances remains a significant challenge for air quality forecasting. One goal of the 2006 Texas Air Quality Study (TEXAQS II) was to assess the impact of distant sources on air quality in east Texas. From 23-30 August 2006, retrievals of tropospheric carbon monoxide (CO) from NASA’s Atmospheric InfraRed Sounder (AIRS) reveal the transport of CO from fires in the United States Pacific Northwest to Houston, Texas. This transport occurred behind a cold front and contributed to the worst ozone exceedance period of the summer in the Houston area. We presentmore » supporting satellite observations from the NASA A-Train constellation of the vertical distribution of smoke aerosols and CO. Ground-based in situ CO measurements in Oklahoma and Texas track the CO plume as it moves south and indicate mixing of the aloft plume to the surface by turbulence in the nocturnal boundary layer and convection during the day. Ground-based aerosol speciation and lidar observations do not find appreciable smoke aerosol transport for this case. However, MODIS aerosol optical depths and model simulations indicate some smoke aerosols were transported from the Pacific Northwest through Texas to the Gulf of Mexico. Chemical transport and forward trajectory models confirm the three major observations: (1) the AIRS envisioned CO transport, (2) the satellite determined smoke plume height, and (3) the timing of the observed surface CO increases. Further, the forward trajectory simulations find two of the largest Pacific Northwest fires likely had the most significant impact.« less

Numerical modeling of chemical spills and assessment of their environmental impacts

USDA-ARS?s Scientific Manuscript database

Chemical spills in surface water bodies often occur in modern societies, which cause significant impacts on water quality, eco-environment and drinking water safety. In this paper, chemical spill contamination in water resources was studied using a depth-integrated computational model, CCHE2D, for p...

Models, Measurements, and Local Decisions: Assessing and Addressing Impacts from Port Expansion and Traffic Activity

EPA Science Inventory

This presentation includes a combination of modeling and measurement results to characterize near-source air quality in Newark, New Jersey with consideration of how this information could be used to inform decision making to reduce risk of health impacts. Decisions could include ...

Modeling the impact of forest biomass change on the subsequent ground level solar energy to enhance the understanding of ecosystem service tradeoffs

EPA Science Inventory

Background/Question/Methods Solar radiation is a significant environmental driver that impacts the quality and resilience of terrestrial and aquatic habitats, yet its spatiotemporal variations are complicated to model accurately at high resolution over large, complex watersheds. ...

Integrated health impact assessment of travel behaviour: model exploration and application to a fuel price increase.

PubMed

Dhondt, Stijn; Kochan, Bruno; Beckx, Carolien; Lefebvre, Wouter; Pirdavani, Ali; Degraeuwe, Bart; Bellemans, Tom; Int Panis, Luc; Macharis, Cathy; Putman, Koen

2013-01-01

Transportation policy measures often aim to change travel behaviour towards more efficient transport. While these policy measures do not necessarily target health, these could have an indirect health effect. We evaluate the health impact of a policy resulting in an increase of car fuel prices by 20% on active travel, outdoor air pollution and risk of road traffic injury. An integrated modelling chain is proposed to evaluate the health impact of this policy measure. An activity-based transport model estimated movements of people, providing whereabouts and travelled kilometres. An emission- and dispersion model provided air quality levels (elemental carbon) and a road safety model provided the number of fatal and non-fatal traffic victims. We used kilometres travelled while walking or cycling to estimate the time in active travel. Differences in health effects between the current and fuel price scenario were expressed in Disability Adjusted Life Years (DALY). A 20% fuel price increase leads to an overall gain of 1650 (1010-2330) DALY. Prevented deaths lead to a total of 1450 (890-2040) Years Life Gained (YLG), with better air quality accounting for 530 (180-880) YLG, fewer road traffic injuries for 750 (590-910) YLG and active travel for 170 (120-250) YLG. Concerning morbidity, mostly road safety led to 200 (120-290) fewer Years Lived with Disability (YLD), while air quality improvement only had a minor effect on cardiovascular hospital admissions. Air quality improvement and increased active travel mainly had an impact at older age, while traffic safety mainly affected younger and middle-aged people. This modelling approach illustrates the feasibility of a comprehensive health impact assessment of changes in travel behaviour. Our results suggest that more is needed than a policy rising car fuel prices by 20% to achieve substantial health gains. While the activity-based model gives an answer on what the effect of a proposed policy is, the focus on health may make policy integration more tangible. The model can therefore add to identifying win-win situations for both transport and health. Copyright © 2012 Elsevier Ltd. All rights reserved.

Modeling procedures for handling qualities evaluation of flexible aircraft

NASA Technical Reports Server (NTRS)

Govindaraj, K. S.; Eulrich, B. J.; Chalk, C. R.

1981-01-01

This paper presents simplified modeling procedures to evaluate the impact of flexible modes and the unsteady aerodynamic effects on the handling qualities of Supersonic Cruise Aircraft (SCR). The modeling procedures involve obtaining reduced order transfer function models of SCR vehicles, including the important flexible mode responses and unsteady aerodynamic effects, and conversion of the transfer function models to time domain equations for use in simulations. The use of the modeling procedures is illustrated by a simple example.

Study on the influence of ground and satellite observations on the numerical air-quality for PM10 over Romanian territory

NASA Astrophysics Data System (ADS)

Dumitrache, Rodica Claudia; Iriza, Amalia; Maco, Bogdan Alexandru; Barbu, Cosmin Danut; Hirtl, Marcus; Mantovani, Simone; Nicola, Oana; Irimescu, Anisoara; Craciunescu, Vasile; Ristea, Alina; Diamandi, Andrei

2016-10-01

The numerical forecast of particulate matter concentrations in general, and PM10 in particular is a theme of high socio-economic relevance. The aim of this study was to investigate the impact of ground and satellite data assimilation of PM10 observations into the Weather Research and Forecasting model coupled with Chemistry (WRF-CHEM) numerical air quality model for Romanian territory. This is the first initiative of the kind for this domain of interest. Assimilation of satellite information - e.g. AOT's in air quality models is of interest due to the vast spatial coverage of the observations. Support Vector Regression (SVR) techniques are used to estimate the PM content from heterogeneous data sources, including EO products (Aerosol Optical Thickness), ground measurements and numerical model data (temperature, humidity, wind, etc.). In this study we describe the modeling framework employed and present the evaluation of the impact from the data assimilation of PM10 observations on the forecast of the WRF-CHEM model. Integrations of the WRF-CHEM model in data assimilation enabled/disabled configurations allowed the evaluation of satellite and ground data assimilation impact on the PM10 forecast performance for the Romanian territory. The model integration and evaluation were performed for two months, one in winter conditions (January 2013) and one in summer conditions (June 2013).

Changes in O3 and NO2 due to emissions from Fracking in the UK.

NASA Astrophysics Data System (ADS)

Archibald, Alexander; Ordonez, Carlos

2016-04-01

Poor air quality is a problem that affects millions of people around the world. Understanding the driving forces behind air pollution is complicated as the precursor gases which combine to produce air pollutants react in a highly non-linear manner and are subject to a range of atmospheric transport mechanisms compounded by the weather. A great deal of money has been spent on mitigating air pollution and so it's important to assess the impacts that new technologies that emit air pollutant precursors may have on local and regional air pollution. One of the most highly discussed new technologies that could impact air quality is the adoption of wide-scale hydraulic fracturing or "fracking" for natural gas. Indeed in regions of the USA where fracking is commonplace large levels of ozone (O3 - a key air pollutant) have been observed and attributed directly to the fracking process. In this study, a numerical modelling framework was used to assess possible impacts of fracking in the UK where at present no large scale fracking facilities are in operation. A number of emissions scenarios were developed for the principle gas phase air pollution precursors: the oxides of nitrogen (NOx) and volatile organic compounds (VOCs). These emissions scenarios were then used in a state-of-the-art numerical air quality model (the UK Met Office operational air quality forecasting model AQUM) to determine potential impacts related to fracking on UK air quality. Comparison of base model results and observations for the year 2013 of NOx, O3 and VOCs from the UK Automatic Urban and Rural Network (AURN) showed that AQUM has good skill at simulating these gas phase air pollutants (O3 r=0.64, NMGE=0.3; NO2 r=0.62, NMGE=0.51). Analysis of the simulations with fracking emissions demonstrate that there are large changes in 1hr max NO2 (11.6±6.6 ppb) with modest increases in monthly mean NO2, throughout the British Isles (150±100 ppt). These results highlight that stringent measures should be applied to prevent deleterious impacts on air quality from emissions related to fracking in the UK.

Information Quality Evaluation of C2 Systems at Architecture Level

DTIC Science & Technology

2014-06-01

based on architecture models of C2 systems, which can help to identify key factors impacting information quality and improve the system capability at the stage of architecture design of C2 system....capability evaluation of C2 systems at architecture level becomes necessary and important for improving the system capability at the stage of architecture ... design . This paper proposes a method for information quality evaluation of C2 system at architecture level. First, the information quality model is

A simulation model of building intervention impacts on indoor environmental quality, pediatric asthma, and costs

PubMed Central

Fabian, Maria Patricia; Adamkiewicz, Gary; Stout, Natasha Kay; Sandel, Megan; Levy, Jonathan Ian

2013-01-01

Background Although indoor environmental conditions can affect pediatric asthmatics, few studies have characterized the impact of building interventions on asthma-related outcomes. Simulation models can evaluate such complex systems but have not been applied in this context. Objective To evaluate the impacts of building interventions on indoor environmental quality and pediatric asthma healthcare utilization, and to conduct cost comparisons between intervention and healthcare costs, and energy savings. Methods We applied our previously developed discrete event simulation model (DEM) to simulate the effect of environmental factors, medication compliance, seasonality, and medical history on: 1) pollutant concentrations indoors, and 2) asthma outcomes in low-income multi-family housing. We estimated healthcare utilization and costs at baseline and subsequent to interventions, and then compared healthcare costs to energy savings and intervention costs. Results Interventions such as integrated pest management and repairing kitchen exhaust fans led to 7–12% reductions in serious asthma events with 1–3 year payback periods. Weatherization efforts targeted solely towards tightening a building envelope led to 20% more serious asthma events, but bundling with repairing kitchen exhaust fans and eliminating indoor sources (e.g. gas stoves or smokers) mitigated this impact. Conclusion Our pediatric asthma model provides a tool to prioritize individual and bundled building interventions based on their impact on health and cost, and highlighting the tradeoffs between weatherization, indoor air quality, and health. Our work bridges the gap between clinical and environmental health sciences by increasing physicians’ understanding of the impact that home environmental changes can have on their patients’ asthma. PMID:23910689

Urban Air Quality Modelling with AURORA: Prague and Bratislava

NASA Astrophysics Data System (ADS)

Veldeman, N.; Viaene, P.; De Ridder, K.; Peelaerts, W.; Lauwaet, D.; Muhammad, N.; Blyth, L.

2012-04-01

The European Commission, in its strategy to protect the health of the European citizens, states that in order to assess the impact of air pollution on public health, information on long-term exposure to air pollution should be available. Currently, indicators of air quality are often being generated using measured pollutant concentrations. While air quality monitoring stations data provide accurate time series information at specific locations, air quality models have the advantage of being able to assess the spatial variability of air quality (for different resolutions) and predict air quality in the future based on different scenarios. When running such air quality models at a high spatial and temporal resolution, one can simulate the actual situation as closely as possible, allowing for a detailed assessment of the risk of exposure to citizens from different pollutants. AURORA (Air quality modelling in Urban Regions using an Optimal Resolution Approach), a prognostic 3-dimensional Eulerian chemistry-transport model, is designed to simulate urban- to regional-scale atmospheric pollutant concentration and exposure fields. The AURORA model also allows to calculate the impact of changes in land use (e.g. planting of trees) or of emission reduction scenario's on air quality. AURORA is currently being applied within the ESA atmospheric GMES service, PASODOBLE (http://www.myair-eu.org), that delivers information on air quality, greenhouse gases, stratospheric ozone, … At present there are two operational AURORA services within PASODOBLE. Within the "Air quality forecast service" VITO delivers daily air quality forecasts for Belgium at a resolution of 5 km and for the major Belgian cities: Brussels, Ghent, Antwerp, Liege and Charleroi. Furthermore forecast services are provided for Prague, Czech Republic and Bratislava, Slovakia, both at a resolution of 1 km. The "Urban/regional air quality assessment service" provides urban- and regional-scale maps (hourly resolution) for air pollution and human exposure statistics for an entire year. So far we concentrated on Brussels, Belgium and the Rotterdam harbour area, The Netherlands. In this contribution we focus on the operational forecast services. Reference Lefebvre W. et al. (2011) Validation of the MIMOSA-AURORA-IFDM model chain for policy support: Modeling concentrations of elemental carbon in Flanders, Atmospheric Environment 45, 6705-6713

A novel approach to support formulation design on twin screw wet granulation technology: Understanding the impact of overarching excipient properties on drug product quality attributes.

PubMed

Willecke, N; Szepes, A; Wunderlich, M; Remon, J P; Vervaet, C; De Beer, T

2018-04-21

The overall objective of this work is to understand how excipient characteristics influence the drug product quality attributes and process performance of a continuous twin screw wet granulation process. The knowledge gained in this study is intended to be used for Quality by Design (QbD)-based formulation design and formulation optimization. Three principal components which represent the overarching properties of 8 selected pharmaceutical fillers were used as factors, whereas factors 4 and 5 represented binder type and binder concentration in a design of experiments (DoE). The majority of process parameters were kept constant to minimize their influence on the granule and drug product quality. 27 DoE batches consisting of binary filler/binder mixtures were processed via continuous twin screw wet granulation followed by tablet compression. Multiple linear regression models were built providing understanding of the impact of filler and binder properties on granule and tablet quality attributes (i.e. 16 DoE responses). The impact of fillers on the granule and tablet responses was more dominant compared to the impact of binder type and concentration. The filler properties had a relevant effect on granule characteristics, such as particle size, friability and specific surface area. Binder type and concentration revealed a relevant influence on granule flowability and friability as well as on the compactability (required compression force during tableting to obtain target hardness). In order to evaluate the DoE models' validity, a verification of the DoE models was performed with new formulations (i.e. a new combination of filler, binder type and binder concentration) which were initially not included in the dataset used to build the DoE models. The combined PCA (principle component analysis)/DoE approach allowed to link the excipient properties with the drug product quality attributes. Copyright © 2018 Elsevier B.V. All rights reserved.

Characterizing the impact of projected changes in climate and air quality on human exposures to ozone.

PubMed

Dionisio, Kathie L; Nolte, Christopher G; Spero, Tanya L; Graham, Stephen; Caraway, Nina; Foley, Kristen M; Isaacs, Kristin K

2017-05-01

The impact of climate change on human and environmental health is of critical concern. Population exposures to air pollutants both indoors and outdoors are influenced by a wide range of air quality, meteorological, behavioral, and housing-related factors, many of which are also impacted by climate change. An integrated methodology for modeling changes in human exposures to tropospheric ozone (O 3 ) owing to potential future changes in climate and demographics was implemented by linking existing modeling tools for climate, weather, air quality, population distribution, and human exposure. Human exposure results from the Air Pollutants Exposure Model (APEX) for 12 US cities show differences in daily maximum 8-h (DM8H) exposure patterns and levels by sex, age, and city for all scenarios. When climate is held constant and population demographics are varied, minimal difference in O 3 exposures is predicted even with the most extreme demographic change scenario. In contrast, when population is held constant, we see evidence of substantial changes in O 3 exposure for the most extreme change in climate. Similarly, we see increases in the percentage of the population in each city with at least one O 3 exposure exceedance above 60 p.p.b and 70 p.p.b thresholds for future changes in climate. For these climate and population scenarios, the impact of projected changes in climate and air quality on human exposure to O 3 are much larger than the impacts of changing demographics. These results indicate the potential for future changes in O 3 exposure as a result of changes in climate that could impact human health.

A self-consistent method to assess air quality co-benefits from U.S. climate policies.

PubMed

Saari, Rebecca K; Selin, Noelle E; Rausch, Sebastian; Thompson, Tammy M

2015-01-01

Air quality co-benefits can potentially reduce the costs of greenhouse gas mitigation. However, whereas many studies of the cost of greenhouse gas mitigation model the macroeconomic welfare impacts of mitigation, most studies of air quality co-benefits do not. We employ a U.S. computable general equilibrium economic model previously linked to an air quality modeling system and enhance it to represent the economy-wide welfare impacts of fine particulate matter. We present a first application of this method to explore the efficiency and distributional implications of a Clean Energy Standard (CES) and a Cap and Trade (CAT) program that both reduce CO₂emissions by 10% in 2030 relative to 2006. We find that co-benefits from fine particulate matter reduction (median $6; $2 to $10/tCO₂) completely offset policy costs by 110% (40% to 190%), transforming the net welfare impact of the CAT into a gain of $1 (-$5 to $7) billion 2005$. For the CES, the corresponding co-benefit (median $8; $3 to $14/tCO₂) is a smaller fraction (median 5%; 2% to 9%) of its higher policy cost. The eastern United States garners 78% and 71% of co-benefits for the CES and CAT, respectively. By representing the effects of pollution-related morbidities and mortalities as an impact to labor and the demand for health services, we find that the welfare impact per unit of reduced pollution varies by region. These interregional differences can enhance the preference of some regions, such as Texas, for a CAT over a CES, or switch the calculation of which policy yields higher co-benefits, compared with an approach that uses one valuation for all regions. This framework could be applied to quantify consistent air quality impacts of other pricing instruments, subnational trading programs, or green tax swaps.

A new instrument for measuring anticoagulation-related quality of life: development and preliminary validation

PubMed Central

Samsa, Greg; Matchar, David B; Dolor, Rowena J; Wiklund, Ingela; Hedner, Ewa; Wygant, Gail; Hauch, Ole; Marple, Cheryl Beadle; Edwards, Roger

2004-01-01

Background Anticoagulation can reduce quality of life, and different models of anticoagulation management might have different impacts on satisfaction with this component of medical care. Yet, to our knowledge, there are no scales measuring quality of life and satisfaction with anticoagulation that can be generalized across different models of anticoagulation management. We describe the development and preliminary validation of such an instrument – the Duke Anticoagulation Satisfaction Scale (DASS). Methods The DASS is a 25-item scale addressing the (a) negative impacts of anticoagulation (limitations, hassles and burdens); and (b) positive impacts of anticoagulation (confidence, reassurance, satisfaction). Each item has 7 possible responses. The DASS was administered to 262 patients currently receiving oral anticoagulation. Scales measuring generic quality of life, satisfaction with medical care, and tendency to provide socially desirable responses were also administered. Statistical analysis included assessment of item variability, internal consistency (Cronbach's alpha), scale structure (factor analysis), and correlations between the DASS and demographic variables, clinical characteristics, and scores on the above scales. A follow-up study of 105 additional patients assessed test-retest reliability. Results 220 subjects answered all items. Ceiling and floor effects were modest, and 25 of the 27 proposed items grouped into 2 factors (positive impacts, negative impacts, this latter factor being potentially subdivided into limitations versus hassles and burdens). Each factor had a high degree of internal consistency (Cronbach's alpha 0.78–0.91). The limitations and hassles factors consistently correlated with the SF-36 scales measuring generic quality of life, while the positive psychological impact scale correlated with age and time on anticoagulation. The intra-class correlation coefficient for test-retest reliability was 0.80. Conclusions The DASS has demonstrated reasonable psychometric properties to date. Further validation is ongoing. To the degree that dissatisfaction with anticoagulation leads to decreased adherence, poorer INR control, and poor clinical outcomes, the DASS has the potential to help identify reasons for dissatisfaction (and positive satisfaction), and thus help to develop interventions to break this cycle. As an instrument designed to be applicable across multiple models of anticoagulation management, the DASS could be crucial in the scientific comparison between those models of care. PMID:15132746

Photochemical model evaluation of the ground-level ozone impacts on ambient air quality and vegetation health in the Alberta oil sands region: Using present and future emission scenarios

NASA Astrophysics Data System (ADS)

Vijayaraghavan, Krish; Cho, Sunny; Morris, Ralph; Spink, David; Jung, Jaegun; Pauls, Ron; Duffett, Katherine

2016-09-01

One of the potential environmental issues associated with oil sands development is increased ozone formation resulting from NOX and volatile organic compound emissions from bitumen extraction, processing and upgrading. To manage this issue in the Athabasca Oil Sands Region (AOSR) in northeast Alberta, a regional multi-stakeholder group, the Cumulative Environmental Management Association (CEMA), developed an Ozone Management Framework that includes a modelling based assessment component. In this paper, we describe how the Community Multi-scale Air Quality (CMAQ) model was applied to assess potential ground-level ozone formation and impacts on ambient air quality and vegetation health for three different ozone precursor cases in the AOSR. Statistical analysis methods were applied, and the CMAQ performance results met the U.S. EPA model performance goal at all sites. The modelled 4th highest daily maximum 8-h average ozone concentrations in the base and two future year scenarios did not exceed the Canada-wide standard of 65 ppb or the newer Canadian Ambient Air Quality Standards of 63 ppb in 2015 and 62 ppb in 2020. Modelled maximum 1-h ozone concentrations in the study were well below the Alberta Ambient Air Quality Objective of 82 ppb in all three cases. Several ozone vegetation exposure metrics were also evaluated to investigate the potential impact of ground-level ozone on vegetation. The chronic 3-months SUM60 exposure metric is within the CEMA baseline range (0-2000 ppb-hr) everywhere in the AOSR. The AOT40 ozone exposure metric predicted by CMAQ did not exceed the United Nations Economic Commission for Europe (UN/ECE) threshold of concern of 3000 ppb-hr in any of the cases but is just below the threshold in high-end future emissions scenario. In all three emission scenarios, the CMAQ predicted W126 ozone exposure metric is within the CEMA baseline threshold of 4000 ppb-hr. This study outlines the use of photochemical modelling of the impact of an industry (oil sands) on ground-level ozone levels as an air quality management tool in the AOSR. It allows an evaluation of the relationships between the pollutants emitted to the atmosphere and potential ground level ozone concentrations throughout the AOSR thereby extending the spatial coverage of the results beyond the monitoring network and also allowing an assessment of the potential impacts of possible future emission cases.

MEGAPOLI: concept and first results of multi-scale modelling of megacity impacts

NASA Astrophysics Data System (ADS)

Baklanov, A. A.; Lawrence, M.; Pandis, S.

2009-09-01

The European FP7 project MEGAPOLI: ‘Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation' (http://megapoli.info), started in October 2008, brings together 27 leading European research groups from 11 countries, state-of-the-art scientific tools and key players from countries outside Europe to investigate the interactions among megacities, air quality and climate. MEGAPOLI bridges the spatial and temporal scales that connect local emissions, air quality and weather with global atmospheric chemistry and climate. The main MEGAPOLI objectives are: 1. to assess impacts of megacities and large air-pollution hot-spots on local, regional and global air quality, 2. to quantify feedbacks among megacity air quality, local and regional climate, and global climate change, 3. to develop improved integrated tools for prediction of air pollution in megacities. In order to achieve these objectives the following tasks are realizing: • Develop and evaluate integrated methods to improve megacity emission data, • Investigate physical and chemical processes starting from the megacity street level, continuing to the city, regional and global scales, • Assess regional and global air quality impacts of megacity plumes, • Determine the main mechanisms of regional meteorology/climate forcing due to megacity plumes, • Assess global megacity pollutant forcing on climate, • Examine feedback mechanisms including effects of climate change on megacity air quality, • Develop integrated tools for prediction of megacity air quality, • Evaluate these integrated tools and use them in case studies, • Develop a methodology to estimate the impacts of different scenarios of megacity development on human health and climate change, • Propose and assess mitigation options to reduce the impacts of megacity emissions. We follow a pyramid strategy of undertaking detailed measurements in one European major city, Paris, performing detailed analysis for 12 megacities with existing air quality datasets and investigate the effects of all megacities on climate and global atmospheric chemistry. The project focuses on the multi-scale modelling of interacting meteorology and air quality, spanning the range from emissions to air quality, effects on climate, and feedbacks and mitigation potentials. Our hypothesis is that megacities around the world have an impact on air quality not only locally, but also regionally and globally and therefore can also influence the climate of our planet. Some of the links between megacities, air quality and climate are reasonably well-understood. However, a complete quantitative picture of these interactions is clearly missing. Understanding and quantifying these missing links is the focus of MEGAPOLI. The current status and modeling results after the first project year on examples of Paris and other European megacities are discussed.

Impacts of climate change and socio-economic scenarios on flow and water quality of the Ganges, Brahmaputra and Meghna (GBM) river systems: low flow and flood statistics.

PubMed

Whitehead, P G; Barbour, E; Futter, M N; Sarkar, S; Rodda, H; Caesar, J; Butterfield, D; Jin, L; Sinha, R; Nicholls, R; Salehin, M

2015-06-01

The potential impacts of climate change and socio-economic change on flow and water quality in rivers worldwide is a key area of interest. The Ganges-Brahmaputra-Meghna (GBM) is one of the largest river basins in the world serving a population of over 650 million, and is of vital concern to India and Bangladesh as it provides fresh water for people, agriculture, industry, conservation and for the delta system downstream. This paper seeks to assess future changes in flow and water quality utilising a modelling approach as a means of assessment in a very complex system. The INCA-N model has been applied to the Ganges, Brahmaputra and Meghna river systems to simulate flow and water quality along the rivers under a range of future climate conditions. Three model realisations of the Met Office Hadley Centre global and regional climate models were selected from 17 perturbed model runs to evaluate a range of potential futures in climate. In addition, the models have also been evaluated using socio-economic scenarios, comprising (1) a business as usual future, (2) a more sustainable future, and (3) a less sustainable future. Model results for the 2050s and the 2090s indicate a significant increase in monsoon flows under the future climates, with enhanced flood potential. Low flows are predicted to fall with extended drought periods, which could have impacts on water and sediment supply, irrigated agriculture and saline intrusion. In contrast, the socio-economic changes had relatively little impact on flows, except under the low flow regimes where increased irrigation could further reduce water availability. However, should large scale water transfers upstream of Bangladesh be constructed, these have the potential to reduce flows and divert water away from the delta region depending on the volume and timing of the transfers. This could have significant implications for the delta in terms of saline intrusion, water supply, agriculture and maintaining crucial ecosystems such as the mangrove forests, with serious implications for people's livelihoods in the area. The socio-economic scenarios have a significant impact on water quality, altering nutrient fluxes being transported into the delta region.

An integrated fuzzy-based advanced eutrophication simulation model to develop the best management scenarios for a river basin.

PubMed

Srinivas, Rallapalli; Singh, Ajit Pratap

2018-03-01

Assessment of water quality status of a river with respect to its discharge has become prerequisite to sustainable river basin management. The present paper develops an integrated model for simulating and evaluating strategies for water quality management in a river basin management by controlling point source pollutant loadings and operations of multi-purpose projects. Water Quality Analysis and Simulation Program (WASP version 8.0) has been used for modeling the transport of pollutant loadings and their impact on water quality in the river. The study presents a novel approach of integrating fuzzy set theory with an "advanced eutrophication" model to simulate the transmission and distribution of several interrelated water quality variables and their bio-physiochemical processes in an effective manner in the Ganges river basin, India. After calibration, simulated values are compared with the observed values to validate the model's robustness. Fuzzy technique of order preference by similarity to ideal solution (F-TOPSIS) has been used to incorporate the uncertainty associated with the water quality simulation results. The model also simulates five different scenarios for pollution reduction, to determine the maximum pollutant loadings during monsoon and dry periods. The final results clearly indicate how modeled reduction in the rate of wastewater discharge has reduced impacts of pollutants in the downstream. Scenarios suggesting a river discharge rate of 1500 m 3 /s during the lean period, in addition to 25 and 50% reduction in the load rate, are found to be the most effective option to restore quality of river Ganges. Thus, the model serves as an important hydrologic tool to the policy makers by suggesting appropriate remediation action plans.

An Integrated Modeling Framework Forecasting Ecosystem Exposure-- A Systems Approach to the Cumulative Impacts of Multiple Stressors

NASA Astrophysics Data System (ADS)

Johnston, J. M.

2013-12-01

Freshwater habitats provide fishable, swimmable and drinkable resources and are a nexus of geophysical and biological processes. These processes in turn influence the persistence and sustainability of populations, communities and ecosystems. Climate change and landuse change encompass numerous stressors of potential exposure, including the introduction of toxic contaminants, invasive species, and disease in addition to physical drivers such as temperature and hydrologic regime. A systems approach that includes the scientific and technologic basis of assessing the health of ecosystems is needed to effectively protect human health and the environment. The Integrated Environmental Modeling Framework 'iemWatersheds' has been developed as a consistent and coherent means of forecasting the cumulative impact of co-occurring stressors. The Framework consists of three facilitating technologies: Data for Environmental Modeling (D4EM) that automates the collection and standardization of input data; the Framework for Risk Assessment of Multimedia Environmental Systems (FRAMES) that manages the flow of information between linked models; and the Supercomputer for Model Uncertainty and Sensitivity Evaluation (SuperMUSE) that provides post-processing and analysis of model outputs, including uncertainty and sensitivity analysis. Five models are linked within the Framework to provide multimedia simulation capabilities for hydrology and water quality processes: the Soil Water Assessment Tool (SWAT) predicts surface water and sediment runoff and associated contaminants; the Watershed Mercury Model (WMM) predicts mercury runoff and loading to streams; the Water quality Analysis and Simulation Program (WASP) predicts water quality within the stream channel; the Habitat Suitability Index (HSI) model scores physicochemical habitat quality for individual fish species; and the Bioaccumulation and Aquatic System Simulator (BASS) predicts fish growth, population dynamics and bioaccumulation of toxic substances. The capability of the Framework to address cumulative impacts will be demonstrated for freshwater ecosystem services and mountaintop mining.

The Impact of Residential Combustion Emissions on Air Quality and Human Health in China

NASA Astrophysics Data System (ADS)

Archer-Nicholls, S.; Wiedinmyer, C.; Baumgartner, J.; Brauer, M.; Cohen, A.; Carter, E.; Frostad, J.; Forouzanfar, M.; Xiao, Q.; Liu, Y.; Yang, X.; Hongjiang, N.; Kun, N.

2015-12-01

Solid fuel cookstoves are used heavily in rural China for both residential cooking and heating purposes. Their use contributes significantly to regional emissions of several key pollutants, including carbon monoxide, volatile organic compounds, oxides of nitrogen, and aerosol particles. The residential sector was responsible for approximately 36%, 46% and 81% of China's total primary PM2.5, BC and OC emissions respectively in 2005 (Lei et al., 2011). These emissions have serious consequences for household air pollution, ambient air quality, tropospheric ozone formation, and the resulting population health and climate impacts. This paper presents initial findings from the modeling component of a multi-disciplinary energy intervention study currently being conducted in Sichuan, China. The purpose of this effort is to quantify the impact of residential cooking and heating emissions on regional air quality and human health. Simulations with varying levels of residential emissions have been carried out for the whole of 2014 using the Weather Research and Forecasting model with Chemistry (WRF-Chem), a fully-coupled, "online" regional chemical transport model. Model output is evaluated against surface air quality measurements across China and compared with seasonal (winter and summer) ambient air pollution measurements conducted at the Sichuan study site in 2014. The model output is applied to available exposure—response relationships between PM2.5 and cardiopulmonary health outcomes. The sensitivity in different regions across China to the different cookstove emission scenarios and seasonality of impacts are presented. By estimating the mortality and disease burden risk attributable to residential emissions we demonstrate the potential benefits from large-scale energy interventions. Lei Y, Zhang Q, He KB, Streets DG. 2011. Primary anthropogenic aerosol emission trends for China, 1990-2005. Atmos. Chem. Phys. 11:931-954.

Analysis of parameter sensitivity and identifiability of root zone water quality model (RZWQM) for dryland sugerbeet modeling

USDA-ARS?s Scientific Manuscript database

Sugarbeet is being considered as one of the most viable feedstock alternatives to corn for biofuel production since herbicide resistant energy beets were deregulated by USDA in 2012. Growing sugarbeets for biofuel production may have significant impacts on soil health and water quality in the north-...

The Heartland Region P-Index Conservation Innovation Grant: protecting water quality through improved phosphorus management

USDA-ARS?s Scientific Manuscript database

Reducing phosphorus loss from agricultural land is important for improvement and protection of surface water quality. Agricultural models can be used to determine management impacts on P loss and therefore serve as a guide for recommending best management practices. However, the models must be comp...

(AMD) ANALYSIS OF AIR QUALITY DATA NEAR ROADWAYS USING A DISPERSION MODEL

EPA Science Inventory

We used a dispersion model to analyze measurements made during a field study conducted by the U.S. EPA in July-August 2006, to estimate the impact of traffic emissions on air quality at distances of tens of meters from an 8 lane highway located in Raleigh, North Carolina. The air...

Application of Climate Assessment Tool (CAT) to estimate climate variability impacts on nutrient loading from local watersheds

Treesearch

Ying Ouyang; Prem B. Parajuli; Gary Feng; Theodor D. Leininger; Yongshan Wan; Padmanava Dash

2018-01-01

A vast amount of future climate scenario datasets, created by climate models such as general circulation models (GCMs), have been used in conjunction with watershed models to project future climate variability impact on hydrological processes and water quality. However, these low spatial-temporal resolution datasets are often difficult to downscale spatially and...

Impact of forest fires on particulate matter and ozone levels during the 2003, 2004 and 2005 fire seasons in Portugal.

PubMed

Martins, V; Miranda, A I; Carvalho, A; Schaap, M; Borrego, C; Sá, E

2012-01-01

The main purpose of this work is to estimate the impact of forest fires on air pollution applying the LOTOS-EUROS air quality modeling system in Portugal for three consecutive years, 2003-2005. Forest fire emissions have been included in the modeling system through the development of a numerical module, which takes into account the most suitable parameters for Portuguese forest fire characteristics and the burnt area by large forest fires. To better evaluate the influence of forest fires on air quality the LOTOS-EUROS system has been applied with and without forest fire emissions. Hourly concentration results have been compared to measure data at several monitoring locations with better modeling quality parameters when forest fire emissions were considered. Moreover, hourly estimates, with and without fire emissions, can reach differences in the order of 20%, showing the importance and the influence of this type of emissions on air quality. Copyright © 2011 Elsevier B.V. All rights reserved.

The impact of working memory and the "process of process modelling" on model quality: Investigating experienced versus inexperienced modellers.

PubMed

Martini, Markus; Pinggera, Jakob; Neurauter, Manuel; Sachse, Pierre; Furtner, Marco R; Weber, Barbara

2016-05-09

A process model (PM) represents the graphical depiction of a business process, for instance, the entire process from online ordering a book until the parcel is delivered to the customer. Knowledge about relevant factors for creating PMs of high quality is lacking. The present study investigated the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension, modelling, and reconciliation) were related to PM quality. Our results show that the WM function of relational integration was positively related to PM quality in both modelling groups. The ratio of comprehension phases was negatively related to PM quality in inexperienced modellers and the ratio of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling.

How users adopt healthcare information: An empirical study of an online Q&A community.

PubMed

Jin, Jiahua; Yan, Xiangbin; Li, Yijun; Li, Yumei

2016-02-01

The emergence of social media technology has led to the creation of many online healthcare communities, where patients can easily share and look for healthcare-related information from peers who have experienced a similar problem. However, with increased user-generated content, there is a need to constantly analyse which content should be trusted as one sifts through enormous amounts of healthcare information. This study aims to explore patients' healthcare information seeking behavior in online communities. Based on dual-process theory and the knowledge adoption model, we proposed a healthcare information adoption model for online communities. This model highlights that information quality, emotional support, and source credibility are antecedent variables of adoption likelihood of healthcare information, and competition among repliers and involvement of recipients moderate the relationship between the antecedent variables and adoption likelihood. Empirical data were collected from the healthcare module of China's biggest Q&A community-Baidu Knows. Text mining techniques were adopted to calculate the information quality and emotional support contained in each reply text. A binary logistics regression model and hierarchical regression approach were employed to test the proposed conceptual model. Information quality, emotional support, and source credibility have significant and positive impact on healthcare information adoption likelihood, and among these factors, information quality has the biggest impact on a patient's adoption decision. In addition, competition among repliers and involvement of recipients were tested as moderating effects between these antecedent factors and the adoption likelihood. Results indicate competition among repliers positively moderates the relationship between source credibility and adoption likelihood, and recipients' involvement positively moderates the relationship between information quality, source credibility, and adoption decision. In addition to information quality and source credibility, emotional support has significant positive impact on individuals' healthcare information adoption decisions. Moreover, the relationships between information quality, source credibility, emotional support, and adoption decision are moderated by competition among repliers and involvement of recipients. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The impact of on-site wastewater from high density cluster developments on groundwater quality

NASA Astrophysics Data System (ADS)

Morrissey, P. J.; Johnston, P. M.; Gill, L. W.

2015-11-01

The net impact on groundwater quality from high density clusters of unsewered housing across a range of hydro(geo)logical settings has been assessed. Four separate cluster development sites were selected, each representative of different aquifer vulnerability categories. Groundwater samples were collected on a monthly basis over a two year period for chemical and microbiological analysis from nested multi-horizon sampling boreholes upstream and downstream of the study sites. The field results showed no statistically significant difference between upstream and downstream water quality at any of the study areas, although there were higher breakthroughs in contaminants in the High and Extreme vulnerability sites linked to high intensity rainfall events; these however, could not be directly attributed to on-site effluent. Linked numerical models were then built for each site using HYDRUS 2D to simulate the attenuation of contaminants through the unsaturated zone from which the resulting hydraulic and contaminant fluxes at the water table were used as inputs into MODFLOW MT3D models to simulate the groundwater flows. The results of the simulations confirmed the field observations at each site, indicating that the existing clustered on-site wastewater discharges would only cause limited and very localised impacts on groundwater quality, with contaminant loads being quickly dispersed and diluted downstream due to the relatively high groundwater flow rates. Further simulations were then carried out using the calibrated models to assess the impact of increasing cluster densities revealing little impact at any of the study locations up to a density of 6 units/ha with the exception of the Extreme vulnerability site.

Air quality impacts of distributed power generation in the South Coast Air Basin of California 1: Scenario development and modeling analysis

NASA Astrophysics Data System (ADS)

Rodriguez, M. A.; Carreras-Sospedra, M.; Medrano, M.; Brouwer, J.; Samuelsen, G. S.; Dabdub, D.

Distributed generation (DG) is generally defined as the operation of many small stationary power generators throughout an urban air basin. Although DG has the potential to supply a significant portion of the increased power demands in California and the rest of the United States, it may lead to increased levels of in-basin pollutants and adversely impact urban air quality. This study focuses on two main objectives: (1) the systematic characterization of DG installation in urban air basins, and (2) the simulation of potential air quality impacts using a state-of-the-art three-dimensional computational model. A general and systematic approach is devised to construct five realistic and 21 spanning scenarios of DG implementation in the South Coast Air Basin (SoCAB) of California. Realistic scenarios reflect an anticipated level of DG deployment in the SoCAB by the year 2010. Spanning scenarios are developed to determine the potential impacts of unexpected outcomes. Realistic implementations of DG in the SoCAB result in small differences in ozone and particulate matter concentrations in the basin compared to the baseline simulations. The baseline accounts for population increase, but does not consider any future emissions control measures. Model results for spanning implementations with extra high DG market penetration show that domain-wide ozone peak concentrations increase significantly. Also, air quality impacts of spanning implementations when DG operate during a 6-h period are larger than when the same amount of emissions are introduced during a 24-h period.

A new definition of pharmaceutical quality: assembly of a risk simulation platform to investigate the impact of manufacturing/product variability on clinical performance.

PubMed

Short, Steven M; Cogdill, Robert P; D'Amico, Frank; Drennen, James K; Anderson, Carl A

2010-12-01

The absence of a unanimous, industry-specific definition of quality is, to a certain degree, impeding the progress of ongoing efforts to "modernize" the pharmaceutical industry. This work was predicated on requests by Dr. Woodcock (FDA) to re-define pharmaceutical quality in terms of risk by linking production characteristics to clinical attributes. A risk simulation platform that integrates population statistics, drug delivery system characteristics, dosing guidelines, patient compliance estimates, production metrics, and pharmacokinetic, pharmacodynamic, and in vitro-in vivo correlation models to investigate the impact of manufacturing variability on clinical performance of a model extended-release theophylline solid oral dosage system was developed. Manufacturing was characterized by inter- and intra-batch content uniformity and dissolution variability metrics, while clinical performance was described by a probabilistic pharmacodynamic model that expressed the probability of inefficacy and toxicity as a function of plasma concentrations. Least-squares regression revealed that both patient compliance variables, percent of doses taken and dosing time variability, significantly impacted efficacy and toxicity. Additionally, intra-batch content uniformity variability elicited a significant change in risk scores for the two adverse events and, therefore, was identified as a critical quality attribute. The proposed methodology demonstrates that pharmaceutical quality can be recast to explicitly reflect clinical performance. © 2010 Wiley-Liss, Inc. and the American Pharmacists Association

Development and Evaluation of an Air Quality Modeling Approach to Assess Near-Field Impacts of Lead Emissions from Piston-Engine Aircraft Operating on Leaded Aviation Gasoline

EPA Science Inventory

Since aviation gasoline is now the largest remaining source of lead (Pb) emissions to the air in the United States, there is increased interest by regulatory agencies and the public in assessing the impacts on residents living in close proximity to these sources. An air quality m...

The impact of working memory and the “process of process modelling” on model quality: Investigating experienced versus inexperienced modellers

NASA Astrophysics Data System (ADS)

Martini, Markus; Pinggera, Jakob; Neurauter, Manuel; Sachse, Pierre; Furtner, Marco R.; Weber, Barbara

2016-05-01

A process model (PM) represents the graphical depiction of a business process, for instance, the entire process from online ordering a book until the parcel is delivered to the customer. Knowledge about relevant factors for creating PMs of high quality is lacking. The present study investigated the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension, modelling, and reconciliation) were related to PM quality. Our results show that the WM function of relational integration was positively related to PM quality in both modelling groups. The ratio of comprehension phases was negatively related to PM quality in inexperienced modellers and the ratio of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling.

The impact of working memory and the “process of process modelling” on model quality: Investigating experienced versus inexperienced modellers

PubMed Central

Martini, Markus; Pinggera, Jakob; Neurauter, Manuel; Sachse, Pierre; Furtner, Marco R.; Weber, Barbara

2016-01-01

A process model (PM) represents the graphical depiction of a business process, for instance, the entire process from online ordering a book until the parcel is delivered to the customer. Knowledge about relevant factors for creating PMs of high quality is lacking. The present study investigated the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension, modelling, and reconciliation) were related to PM quality. Our results show that the WM function of relational integration was positively related to PM quality in both modelling groups. The ratio of comprehension phases was negatively related to PM quality in inexperienced modellers and the ratio of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling. PMID:27157858

Geospatial Modeling of Watershed Quality as an Indicator for Environmental Health

NASA Astrophysics Data System (ADS)

Archer, R.

2016-12-01

The impact of urbanization of rural Tennessee counties on environmental quality and human health and wellbeing has not been well studied, especially in the context of water quality. Between 2015 and 2025, Williamson County, TN is projected to see the strongest rate of population growth in the region, expanding by 33.7 percent. Water quality directly affects the condition of soils, vegetation, and other life forms that depend on water for survival, and therefore is a valid indicator of environmental health. Current reliable data is available on less than half (47%) of waterways in Tennessee. GIS is applied to model the impact of urbanization on rural communities within the Mill Creek watershed in Williamson County, Tennessee. Water quality measurements are integrated with data identifying urbanization and other land development influences assessed over a previous decades in order to identify influences of environmental change impacts on the watershed. The study examines the threat of urbanization to soils, vegetation and other related natural resources as well as the distance of farm areas, pasture grazing, cattle access and manure runoff, construction and landscaping to collection systems leading into the watershed. Combining spatial analysis with water quality interpretation helped to identify and display potential causes and sources of Mill Creek Watershed pollution as well as vulnerable locations susceptible to risk of declining environmental health.

Climate change and the impact of increased rainfall variability on sediment transport and catchment scale water quality

NASA Astrophysics Data System (ADS)

Hancock, G. R.; Willgoose, G. R.; Cohen, S.

2009-12-01

Recently there has been recognition that changing climate will affect rainfall and storm patterns with research directed to examine how the global hydrological cycle will respond to climate change. This study investigates the effect of different rainfall patterns on erosion and resultant water quality for a well studied tropical monsoonal catchment that is undisturbed by Europeans in the Northern Territory, Australia. Water quality has a large affect on a range of aquatic flora and fauna and a significant change in sediment could have impacts on the aquatic ecosystems. There have been several studies of the effect of climate change on rainfall patterns in the study area with projections indicating a significant increase in storm activity. Therefore it is important that the impact of this variability be assessed in terms of catchment hydrology, sediment transport and water quality. Here a numerical model of erosion and hydrology (CAESAR) is used to assess several different rainfall scenarios over a 1000 year modelled period. The results show that that increased rainfall amount and intensity increases sediment transport rates but predicted water quality was variable and non-linear but within the range of measured field data for the catchment and region. Therefore an assessment of sediment transport and water quality is a significant and complex issue that requires further understandings of the role of biophysical feedbacks such as vegetation as well as the role of humans in managing landscapes (i.e. controlled and uncontrolled fire). The study provides a robust methodology for assessing the impact of enhanced climate variability on sediment transport and water quality.

Quality-by-design III: application of near-infrared spectroscopy to monitor roller compaction in-process and product quality attributes of immediate release tablets.

PubMed

Kona, Ravikanth; Fahmy, Raafat M; Claycamp, Gregg; Polli, James E; Martinez, Marilyn; Hoag, Stephen W

2015-02-01

The objective of this study is to use near-infrared spectroscopy (NIRS) coupled with multivariate chemometric models to monitor granule and tablet quality attributes in the formulation development and manufacturing of ciprofloxacin hydrochloride (CIP) immediate release tablets. Critical roller compaction process parameters, compression force (CFt), and formulation variables identified from our earlier studies were evaluated in more detail. Multivariate principal component analysis (PCA) and partial least square (PLS) models were developed during the development stage and used as a control tool to predict the quality of granules and tablets. Validated models were used to monitor and control batches manufactured at different sites to assess their robustness to change. The results showed that roll pressure (RP) and CFt played a critical role in the quality of the granules and the finished product within the range tested. Replacing binder source did not statistically influence the quality attributes of the granules and tablets. However, lubricant type has significantly impacted the granule size. Blend uniformity, crushing force, disintegration time during the manufacturing was predicted using validated PLS regression models with acceptable standard error of prediction (SEP) values, whereas the models resulted in higher SEP for batches obtained from different manufacturing site. From this study, we were able to identify critical factors which could impact the quality attributes of the CIP IR tablets. In summary, we demonstrated the ability of near-infrared spectroscopy coupled with chemometrics as a powerful tool to monitor critical quality attributes (CQA) identified during formulation development.

Air quality impacts from prescribed forest fires under different management practices.

PubMed

Tian, Di; Wang, Yuhang; Bergin, Michelle; Hu, Yongtao; Liu, Yongqiang; Russell, Armistead G

2008-04-15

Large amounts of air pollutants are emitted during prescribed forest fires. Such emissions and corresponding air quality impacts can be modulated by different forest management practices. The impacts of changing burning seasons and frequencies and of controlling emissions during smoldering on regional air quality in Georgia are quantified using source-oriented air quality modeling, with modified emissions from prescribed fires reflecting effects of each practice. Equivalent fires in the spring and winter are found to have a greater impact on PM2.5 than those in summer, though ozone impacts are larger from spring and summer fires. If prescribed fires are less frequent more biofuel is burnt in each fire, leading to larger emissions and air quality impacts per fire. For example, emissions from a fire with a 5-year fire return interval (FRI) are 72% larger than those from a fire of the same acreage with a 2-year FRI. However, corresponding long-term regional impacts are reduced with the longer FRI since the annual burned area is reduced. Total emissions for fires in Georgia with a 5-year FRI are 32% less than those with a 2-year FRI. Smoldering emissions can lead to approximately 1.0 or 1.9 microg/m3 of PM2.5 in the Atlanta PM2.5 nonattainment area during March 2002.

Support Center for Regulatory Atmospheric Modeling (SCRAM)

EPA Pesticide Factsheets

This technical site provides access to air quality models (including computer code, input data, and model processors) and other mathematical simulation techniques used in assessing air emissions control strategies and source impacts.

Software cost/resource modeling: Software quality tradeoff measurement

NASA Technical Reports Server (NTRS)

Lawler, R. W.

1980-01-01

A conceptual framework for treating software quality from a total system perspective is developed. Examples are given to show how system quality objectives may be allocated to hardware and software; to illustrate trades among quality factors, both hardware and software, to achieve system performance objectives; and to illustrate the impact of certain design choices on software functionality.

Improvements on NYMTC Data Products

DOT National Transportation Integrated Search

2009-11-11

Just like any other scientific research field, the value of data quality is undisputed in the field of transportation. From policy planning to performance evaluation, from model development to impact studies, good quality data is essential to generat...

Does adoption of electronic health records improve the quality of care management in France? Results from the French e-SI (PREPS-SIPS) study.

PubMed

Plantier, Morgane; Havet, Nathalie; Durand, Thierry; Caquot, Nicolas; Amaz, Camille; Biron, Pierre; Philip, Irène; Perrier, Lionel

2017-06-01

Electronic health records (EHR) are increasingly being adopted by healthcare systems worldwide. In France, the "Hôpital numérique 2012-2017" program was implemented as part of a strategic plan to modernize health information technology (HIT), including the promotion of widespread EHR use. With significant upfront investment costs as well as ongoing operational expenses, it is important to assess this system in terms of its ability to result in improvements in hospital performances. The aim of this study was to evaluate the impact of EHR use on the quality of care management in acute care hospitals throughout France. This retrospective study was based on data derived from three national databases for the year 2011: IPAQSS (indicators of improvement in the quality and the management of healthcare, "IPAQSS"), Hospi-Diag (French hospital performance indicators), and the national accreditation database. Several multivariate models were used to examine the association between the use of EHRs and specific EHR features with four quality indicators: the quality of patient record, the delay in sending information at hospital discharge, the pain status evaluation, and the nutritional status evaluation, while also adjusting for hospital characteristics. The models revealed a significant positive impact of EHR use on the four quality indicators. Additionally, they showed a differential impact according to the functionality of the element of the health record that was computerized. All four quality indicators were also impacted by the type of hospital, the geographical region, and the severity of the pathology. These results suggest that, to improve the quality of care management in hospitals, EHR adoption represents an important lever. They complete previous work dealing with EHR and the organizational performance of hospital surgical units. Copyright © 2017 Elsevier B.V. All rights reserved.

Linking Air Quality and Human Health Effects Models: An Application to the Los Angeles Air Basin

PubMed Central

Stewart, Devoun R; Saunders, Emily; Perea, Roberto A; Fitzgerald, Rosa; Campbell, David E; Stockwell, William R

2017-01-01

Proposed emission control strategies for reducing ozone and particulate matter are evaluated better when air quality and health effects models are used together. The Community Multiscale Air Quality (CMAQ) model is the US Environmental Protection Agency’s model for determining public policy and forecasting air quality. CMAQ was used to forecast air quality changes due to several emission control strategies that could be implemented between 2008 and 2030 for the South Coast Air Basin that includes Los Angeles. The Environmental Benefits Mapping and Analysis Program—Community Edition (BenMAP-CE) was used to estimate health and economic impacts of the different emission control strategies based on CMAQ simulations. BenMAP-CE is a computer program based on epidemiologic studies that link human health and air quality. This modeling approach is better for determining optimum public policy than approaches that only examine concentration changes. PMID:29162976

Linking Air Quality and Human Health Effects Models: An Application to the Los Angeles Air Basin.

PubMed

Stewart, Devoun R; Saunders, Emily; Perea, Roberto A; Fitzgerald, Rosa; Campbell, David E; Stockwell, William R

2017-01-01

Proposed emission control strategies for reducing ozone and particulate matter are evaluated better when air quality and health effects models are used together. The Community Multiscale Air Quality (CMAQ) model is the US Environmental Protection Agency's model for determining public policy and forecasting air quality. CMAQ was used to forecast air quality changes due to several emission control strategies that could be implemented between 2008 and 2030 for the South Coast Air Basin that includes Los Angeles. The Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) was used to estimate health and economic impacts of the different emission control strategies based on CMAQ simulations. BenMAP-CE is a computer program based on epidemiologic studies that link human health and air quality. This modeling approach is better for determining optimum public policy than approaches that only examine concentration changes.

A Framework for Evaluating the Software Product Quality of Pregnancy Monitoring Mobile Personal Health Records.

PubMed

Idri, Ali; Bachiri, Mariam; Fernández-Alemán, José Luis

2016-03-01

Stakeholders' needs and expectations are identified by means of software quality requirements, which have an impact on software product quality. In this paper, we present a set of requirements for mobile personal health records (mPHRs) for pregnancy monitoring, which have been extracted from literature and existing mobile apps on the market. We also use the ISO/IEC 25030 standard to suggest the requirements that should be considered during the quality evaluation of these mPHRs. We then go on to design a checklist in which we contrast the mPHRs for pregnancy monitoring requirements with software product quality characteristics and sub-characteristics in order to calculate the impact of these requirements on software product quality, using the ISO/IEC 25010 software product quality standard. The results obtained show that the requirements related to the user's actions and the app's features have the most impact on the external sub-characteristics of the software product quality model. The only sub-characteristic affected by all the requirements is Appropriateness of Functional suitability. The characteristic Operability is affected by 95% of the requirements while the lowest degrees of impact were identified for Compatibility (15%) and Transferability (6%). Lastly, the degrees of the impact of the mPHRs for pregnancy monitoring requirements are discussed in order to provide appropriate recommendations for the developers and stakeholders of mPHRs for pregnancy monitoring.

The Impact of a Potential Shale Gas Development in Germany and the United Kingdom on Local and Regional Air Quality

NASA Astrophysics Data System (ADS)

Weger, L.; Lupascu, A.; Cremonese, L.; Butler, T. M.

2017-12-01

Numerous countries in Europe that possess domestic shale gas reserves are considering exploiting this unconventional gas resource as part of their energy transition agenda. While natural gas generates less CO2 emissions upon combustion compared to coal or oil, making it attractive as a bridge in the transition from fossil fuels to renewables, production of shale gas leads to emissions of CH4 and air pollutants such as NOx, VOCs and PM. These gases in turn influence the climate as well as air quality. In this study, we investigate the impact of a potential shale gas development in Germany and the United Kingdom on local and regional air quality. This work builds on our previous study in which we constructed emissions scenarios based on shale gas utilization in these counties. In order to explore the influence of shale gas production on air quality, we investigate emissions predicted from our shale gas scenarios with the Weather Research and Forecasting model with chemistry (WRF-Chem) model. In order to do this, we first design a model set-up over Europe and evaluate its performance for the meteorological and chemical parameters. Subsequently we add shale gas emissions fluxes based on the scenarios over the area of the grid in which the shale gas activities are predicted to occur. Finally, we model these emissions and analyze the impact on air quality on both a local and regional scale. The aims of this work are to predict the range of adverse effects on air quality, highlight the importance of emissions control strategies in reducing air pollution, to promote further discussion, and to provide policy makers with information for decision making on a potential shale gas development in the two study countries.

Modeling of Escherichia coli fluxes on a catchment and the impact on coastal water and shellfish quality

USDA-ARS?s Scientific Manuscript database

We coupled the Soil and Water Assessment Tool (SWAT) with a hydrodynamic model in the Daoulas’ catchment and estuary to estimate daily variations in Escherichia coli fluxes due to catchment activities (manure spreading and wastewater treatment plants discharge) and to assess their impact on coastal ...

Examining the Impact of Nitrous Acid Chemistry on Ozone and PM over the Pearl River Delta Region

EPA Science Inventory

The impact of nitrous acid (HONO) chemistry on regional ozone and particulate matter in Pearl River Delta region was investigated using the community multiscale air quality (CMAQ) modeling system and the CB05 mechanism. Model simulations were conducted for a ten-day period in Oct...

The Impact of a Campus-Based 4-H Summer Conference Program on Youth Thriving

ERIC Educational Resources Information Center

Arnold, Mary E.; Davis, Jamie M.; Lundeberg, Roberta

2017-01-01

In 2014 the Oregon 4-H program adopted a new program model to describe and evaluate the impact of 4-H on youths. The model is based on promoting thriving in young people, with an emphasis on high program quality. This article discusses the impact on thriving in 378 youth participants of the 4-H Summer Conference (4-HSC) program. The results of the…

The impact of the board's strategy-setting role on board-management relations and hospital performance.

PubMed

Büchner, Vera Antonia; Schreyögg, Jonas; Schultz, Carsten

2014-01-01

The appropriate governance of hospitals largely depends on effective cooperation between governing boards and hospital management. Governing boards play an important role in strategy-setting as part of their support for hospital management. However, in certain situations, this active strategic role may also generate discord within this relationship. The objective of this study is to investigate the impact of the roles, attributes, and processes of governing boards on hospital performance. We examine the impact of the governing board's strategy-setting role on board-management collaboration quality and on financial performance while also analyzing the interaction effects of board diversity and board activity level. The data are derived from a survey that was sent simultaneously to German hospitals and their associated governing board, combined with objective performance information from annual financial statements and quality reports. We use a structural equation modeling approach to test the model. The results indicate that different board characteristics have a significant impact on hospital performance (R = .37). The strategy-setting role and board-management collaboration quality have a positive effect on hospital performance, whereas the impact of strategy-setting on collaboration quality is negative. We find that the positive effect of strategy-setting on performance increases with decreasing board diversity. When board members have more homogeneous backgrounds and exhibit higher board activity levels, the negative effect of the strategy-setting on collaboration quality also increases. Active strategy-setting by a governing board may generally improve hospital performance. Diverse members of governing boards should be involved in strategy-setting for hospitals. However, high board-management collaboration quality may be compromised if managerial autonomy is too highly restricted. Consequently, hospitals should support board-management collaboration about empowered contrasting board roles.

Differences in aquatic habitat quality as an impact of one- and two-dimensional hydrodynamic model simulated flow variables

NASA Astrophysics Data System (ADS)

Benjankar, R. M.; Sohrabi, M.; Tonina, D.; McKean, J. A.

2013-12-01

Aquatic habitat models utilize flow variables which may be predicted with one-dimensional (1D) or two-dimensional (2D) hydrodynamic models to simulate aquatic habitat quality. Studies focusing on the effects of hydrodynamic model dimensionality on predicted aquatic habitat quality are limited. Here we present the analysis of the impact of flow variables predicted with 1D and 2D hydrodynamic models on simulated spatial distribution of habitat quality and Weighted Usable Area (WUA) for fall-spawning Chinook salmon. Our study focuses on three river systems located in central Idaho (USA), which are a straight and pool-riffle reach (South Fork Boise River), small pool-riffle sinuous streams in a large meadow (Bear Valley Creek) and a steep-confined plane-bed stream with occasional deep forced pools (Deadwood River). We consider low and high flows in simple and complex morphologic reaches. Results show that 1D and 2D modeling approaches have effects on both the spatial distribution of the habitat and WUA for both discharge scenarios, but we did not find noticeable differences between complex and simple reaches. In general, the differences in WUA were small, but depended on stream type. Nevertheless, spatially distributed habitat quality difference is considerable in all streams. The steep-confined plane bed stream had larger differences between aquatic habitat quality defined with 1D and 2D flow models compared to results for streams with well defined macro-topographies, such as pool-riffle bed forms. KEY WORDS: one- and two-dimensional hydrodynamic models, habitat modeling, weighted usable area (WUA), hydraulic habitat suitability, high and low discharges, simple and complex reaches

A Model of Quality of College Life (QCL) of Students in Korea

ERIC Educational Resources Information Center

Yu, Grace (Byung-Hee); Lee, Dong-Jin

2008-01-01

This study develops and tests a model of quality of college life (QCL) of students in Korea. In this study, QCL of students is conceptualized in terms of needs satisfaction and affect balance. It has been hypothesized that satisfaction with education services, administrative services, and facilities have a significant impact on QCL, which in turn…

The objective impact of clinical peer review on hospital quality and safety.

PubMed

Edwards, Marc T

2011-01-01

Despite its importance, the objective impact of clinical peer review on the quality and safety of care has not been studied. Data from 296 acute care hospitals show that peer review program and related organizational factors can explain up to 18% of the variation in standardized measures of quality and patient safety. The majority of programs rely on an outmoded and dysfunctional process model. Adoption of best practices informed by the continuing study of peer review program effectiveness has the potential to significantly improve patient outcomes.

Eco-hydrologic model cascades: Simulating land use and climate change impacts on hydrology, hydraulics and habitats for fish and macroinvertebrates.

PubMed

Guse, Björn; Kail, Jochem; Radinger, Johannes; Schröder, Maria; Kiesel, Jens; Hering, Daniel; Wolter, Christian; Fohrer, Nicola

2015-11-15

Climate and land use changes affect the hydro- and biosphere at different spatial scales. These changes alter hydrological processes at the catchment scale, which impact hydrodynamics and habitat conditions for biota at the river reach scale. In order to investigate the impact of large-scale changes on biota, a cascade of models at different scales is required. Using scenario simulations, the impact of climate and land use change can be compared along the model cascade. Such a cascade of consecutively coupled models was applied in this study. Discharge and water quality are predicted with a hydrological model at the catchment scale. The hydraulic flow conditions are predicted by hydrodynamic models. The habitat suitability under these hydraulic and water quality conditions is assessed based on habitat models for fish and macroinvertebrates. This modelling cascade was applied to predict and compare the impacts of climate- and land use changes at different scales to finally assess their effects on fish and macroinvertebrates. Model simulations revealed that magnitude and direction of change differed along the modelling cascade. Whilst the hydrological model predicted a relevant decrease of discharge due to climate change, the hydraulic conditions changed less. Generally, the habitat suitability for fish decreased but this was strongly species-specific and suitability even increased for some species. In contrast to climate change, the effect of land use change on discharge was negligible. However, land use change had a stronger impact on the modelled nitrate concentrations affecting the abundances of macroinvertebrates. The scenario simulations for the two organism groups illustrated that direction and intensity of changes in habitat suitability are highly species-dependent. Thus, a joined model analysis of different organism groups combined with the results of hydrological and hydrodynamic models is recommended to assess the impact of climate and land use changes on river ecosystems. Copyright © 2015 Elsevier B.V. All rights reserved.

Association between chronic periodontitis and oral health-related quality of life in Sri Lankan adults.

PubMed

Wellapuli, Nimali; Ekanayake, Lilani

2016-12-01

To determine the impact of chronic periodontitis on oral health-related quality of life in Sri Lankan adults. A cross-sectional study was conducted among 1,400 participants, 35-60 years of age, residing in the Colombo district of Sri Lanka. Data were collected using two interviewer-administered questionnaires and an oral examination. The prevalence, extent and severity of oral impacts increased with the increase in severity of chronic periodontitis. The most commonly experienced impacts were within the domain of physical pain. The adjusted Poisson regression model indicated that chronic periodontitis was significantly associated with the prevalence of oral impacts. The prevalence of oral impacts was 48% and 69% higher in those with moderate and severe periodontitis, respectively, compared with those with no/mild periodontitis. Oral health-related quality of life deteriorates with the increase in severity of chronic periodontitis. © 2016 FDI World Dental Federation.

Impact assessment of PM10 cement plants emissions on urban air quality using the SCIPUFF dispersion model.

PubMed

Leone, Vincenzo; Cervone, Guido; Iovino, Pasquale

2016-09-01

The Second-order Closure Integrated Puff (SCIPUFF) model was used to study the impact on urban air quality caused by two cement plants emissions located near the city of Caserta, Italy, during the entire year of 2015. The simulated and observed PM10 concentrations were compared using three monitoring stations located in urban and sub-urban area of Caserta city. Both simulated and observed concentrations are shown to be highest in winter, lower in autumn and spring and lowest in summer. Model results generally follow the pattern of the observed concentrations but have a systematic under-prediction of the concentration values. Measures of the bias, NMSE and RMSE indicate a good correlation between observed and estimated values. The SCIPUFF model data analysis suggest that the cement plants are major sources for the measured PM10 values and are responsible for the deterioration of the urban air quality in the city of Caserta.

CT-based patient modeling for head and neck hyperthermia treatment planning: manual versus automatic normal-tissue-segmentation.

PubMed

Verhaart, René F; Fortunati, Valerio; Verduijn, Gerda M; van Walsum, Theo; Veenland, Jifke F; Paulides, Margarethus M

2014-04-01

Clinical trials have shown that hyperthermia, as adjuvant to radiotherapy and/or chemotherapy, improves treatment of patients with locally advanced or recurrent head and neck (H&N) carcinoma. Hyperthermia treatment planning (HTP) guided H&N hyperthermia is being investigated, which requires patient specific 3D patient models derived from Computed Tomography (CT)-images. To decide whether a recently developed automatic-segmentation algorithm can be introduced in the clinic, we compared the impact of manual- and automatic normal-tissue-segmentation variations on HTP quality. CT images of seven patients were segmented automatically and manually by four observers, to study inter-observer and intra-observer geometrical variation. To determine the impact of this variation on HTP quality, HTP was performed using the automatic and manual segmentation of each observer, for each patient. This impact was compared to other sources of patient model uncertainties, i.e. varying gridsizes and dielectric tissue properties. Despite geometrical variations, manual and automatic generated 3D patient models resulted in an equal, i.e. 1%, variation in HTP quality. This variation was minor with respect to the total of other sources of patient model uncertainties, i.e. 11.7%. Automatically generated 3D patient models can be introduced in the clinic for H&N HTP. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

The behavioral consequences of service quality: an empirical study in the Chinese retail pharmacy industry.

PubMed

Chen, Yuwen; Fu, Frank Q

2015-01-01

This study focuses on the impacts of service quality and examines the mediating effects of customer satisfaction and customer loyalty on willingness to pay more. The authors collected survey data from 479 actual retail pharmacy customers in China and used the structural equation modeling approach to test the hypotheses. The results reveal six dimensions of service quality and the differential impact of these dimensions on customer satisfaction and behavioral intentions. This study contributes to the existing literature by exploring the dimensionality of the service quality construct and mediating effects of customer satisfaction and customer loyalty in a non-Western setting.

A national-scale analysis of the impacts of drought on water quality in UK rivers

NASA Astrophysics Data System (ADS)

Coxon, G.; Howden, N. J. K.; Freer, J. E.; Whitehead, P. G.; Bussi, G.

2015-12-01

Impacts of droughts on water quality qre difficult to quanitify but are essential to manage ecosystems and maintain public water supply. During drought, river water quality is significantly changed by increased residence times, reduced dilution and enhanced biogeochemical processes. But, the impact severity varies between catchments and depends on multiple factors including the sensitivity of the river to drought conditions, anthropogenic influences in the catchment and different delivery patterns of key nutrient, contaminant and mineral sources. A key constraint is data availability for key water quality parameters such that impacts of drought periods on certain determinands can be identified. We use national-scale water quality monitoring data to investigate the impacts of drought periods on water quality in the United Kingdom (UK). The UK Water Quality Sampling Harmonised Monitoring Scheme (HMS) dataset consists of >200 UK sites with weekly to monthly sampling of many water quality variables over the past 40 years. This covers several major UK droughts in 1975-1976, 1983-1984,1989-1992, 1995 and 2003, which cover severity, spatial and temporal extent, and how this affects the temporal impact of the drought on water quality. Several key water quality parameters, including water temperature, nitrate, dissolved organic carbon, orthophosphate, chlorophyll and pesticides, are selected from the database. These were chosen based on their availability for many of the sites, high sampling resolution and importance to the drinking water function and ecological status of the river. The water quality time series were then analysed to investigate whether water quality during droughts deviated significantly from non-drought periods and examined how the results varied spatially, for different drought periods and for different water quality parameters. Our results show that there is no simple conclusion as to the effects of drought on water quality in UK rivers; impacts are diverse both in terms of timing, magnitude and duration. We consider several scenarios in which management interventions may alleviate water quality pressures, and discuss how the many interacting factors need to be better characterised to support detailed mechanistic models to improve our process understanding.

Modeling Aircraft Emissions for Regional-scale Air Quality: Adapting a New Global Aircraft Emissions Database for the U.S

NASA Astrophysics Data System (ADS)

Arunachalam, S.; Baek, B. H.; Vennam, P. L.; Woody, M. C.; Omary, M.; Binkowski, F.; Fleming, G.

2012-12-01

Commercial aircraft emit substantial amounts of pollutants during their complete activity cycle that ranges from landing-and-takeoff (LTO) at airports to cruising in upper elevations of the atmosphere, and affect both air quality and climate. Since these emissions are not uniformly emitted over the earth, and have substantial temporal and spatial variability, it is vital to accurately evaluate and quantify the relative impacts of aviation emissions on ambient air quality. Regional-scale air quality modeling applications do not routinely include these aircraft emissions from all cycles. Federal Aviation Administration (FAA) has developed the Aviation Environmental Design Tool (AEDT), a software system that dynamically models aircraft performance in space and time to calculate fuel burn and emissions from gate-to-gate for all commercial aviation activity from all airports globally. To process in-flight aircraft emissions and to provide a realistic representation of these for treatment in grid-based air quality models, we have developed an interface processor called AEDTproc that accurately distributes full-flight chorded emissions in time and space to create gridded, hourly model-ready emissions input data. Unlike the traditional emissions modeling approach of treating aviation emissions as ground-level sources or processing emissions only from the LTO cycles in regional-scale air quality studies, AEDTproc distributes chorded inventories of aircraft emissions during LTO cycles and cruise activities into a time-variant 3-D gridded structure. We will present results of processed 2006 global emissions from AEDT over a continental U.S. modeling domain to support a national-scale air quality assessment of the incremental impacts of aircraft emissions on surface air quality. This includes about 13.6 million flights within the U.S. out of 31.2 million flights globally. We will focus on assessing spatio-temporal variability of these commercial aircraft emissions, and comparing upper tropospheric budgets of NOx from aircraft and lightning sources in the modeling domain.

Assessing the impacts of land use on downstream water quality using a hydrologically sensitive area concept.

PubMed

Giri, Subhasis; Qiu, Zeyuan; Zhang, Zhen

2018-05-01

Understanding the relationship between land use and water quality is essential to improve water quality through carefully managing landscape change. This study applies a linear mixed model at both watershed and hydrologically sensitive areas (HSAs) scales to assess such a relationship in 28 northcentral New Jersey watersheds located in a rapidly urbanizing region in the United States. Two models differ in terms of the geographic scope used to derive land use matrices that quantify land use conditions. The land use matrices at the watershed and HSAs scales represent the land use conditions in these watersheds and their HSAs, respectively. HSAs are the hydrological "hotspots" in a watershed that are prone to runoff generation during storm events. HSAs are derived using a soil topographic index (STI) that predicts hydrological sensitivity of a landscape based on a variable source area hydrology concept. The water quality indicators in these models are total nitrogen (TN), total phosphorus (TP) and total suspended solids (TSS) concentrations in streams observed at the watershed outlets. The modeling results suggest that presence of low density urban land, agricultural land and wetlands elevate while forest decreases TN, TP and/or TSS concentrations in streams. The watershed scale model tends to emphasize the role of agricultural lands in water quality degradation while the HSA scale model highlights the role of forest in water quality improvement. This study supports the hypothesis that even though HSAs are relatively smaller area compared to watershed, still the land uses within HSAs have similar impacts on downstream water quality as the land uses in entire watersheds, since both models have negligible differences in model evaluation parameters. Inclusion of HSAs brings an interesting perspective to understand the dynamic relationships between land use and water quality. Copyright © 2018 Elsevier Ltd. All rights reserved.

Urbanization and watershed sustainability: Collaborative simulation modeling of future development states

NASA Astrophysics Data System (ADS)

Randhir, Timothy O.; Raposa, Sarah

2014-11-01

Urbanization has a significant impact on water resources and requires a watershed-based approach to evaluate impacts of land use and urban development on watershed processes. This study uses a simulation with urban policy scenarios to model and strategize transferable recommendations for municipalities and cities to guide urban decisions using watershed ecohydrologic principles. The watershed simulation model is used to evaluation intensive (policy in existing built regions) and extensive (policy outside existing build regions) urban development scenarios with and without implementation of Best Management practices (BMPs). Water quantity and quality changes are simulated to assess effectiveness of five urban development scenarios. It is observed that optimal combination of intensive and extensive strategies can be used to sustain urban ecosystems. BMPs are found critical to reduce storm water and water quality impacts on urban development. Conservation zoning and incentives for voluntary adoption of BMPs can be used in sustaining urbanizing watersheds.

Meteorological and air quality impacts of increased urban albedo and vegetative cover in the Greater Toronto Area, Canada

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

Taha, Haider; Hammer, Hillel; Akbari, Hashem

2002-04-30

The study described in this report is part of a project sponsored by the Toronto Atmospheric Fund, performed at the Lawrence Berkeley National Laboratory, to assess the potential role of surface property modifications on energy, meteorology, and air quality in the Greater Toronto Area (GTA), Canada. Numerical models were used to establish the possible meteorological and ozone air-quality impacts of increased urban albedo and vegetative fraction, i.e., ''cool-city'' strategies that can mitigate the urban heat island (UHI), significantly reduce urban energy consumption, and improve thermal comfort, particularly during periods of hot weather in summer. Mitigation is even more important duringmore » critical heat wave periods with possible increased heat-related hospitalization and mortality. The evidence suggests that on an annual basis cool-city strategies are beneficial, and the implementation of such measures is currently being investigated in the U.S. and Canada. We simulated possible scenari os for urban heat-island mitigation in the GTA and investigated consequent meteorological changes, and also performed limited air-quality analysis to assess related impacts. The study was based on a combination of mesoscale meteorological modeling, Lagrangian (trajectory), and photochemical trajectory modeling to assess the potential meteorological and ozone air-quality impacts of cool-city strategies. As available air-quality and emissions data are incompatible with models currently in use at LBNL, our air-quality analysis was based on photochemical trajectory modeling. Because of questions as to the accuracy and appropriateness of this approach, in our opinion this aspect of the study can be improved in the future, and the air-quality results discussed in this report should be viewed as relatively qualitative. The MM5 meteorological model predicts a UHI in the order of 2 to 3 degrees C in locations of maxima, and about 1 degree C as a typical value over most of the urban area. Our si mulations suggest that cool-city strategies can typically reduce local urban air temperature by 0.5-1 degrees C; as more sporadic events, larger decreases (1.5 degrees C, 2.5-2.7 degrees C and 4-6 degrees C) were also simulated. With regard to ozone mixing ratios along the simulated trajectories, the effects of cool-city strategies appear to be on the order of 2 ppb, a typical decrease. The photochemical trajectory model (CIT) also simulates larger decreases (e.g., 4 to 8 ppb), but these are not taken as representative of the potential impacts in this report. A comparison with other simulations suggest very crudely that a decrease of this magnitude corresponds to significant ''equivalent'' decreases in both NOx and VOCs emissions in the region. Our preliminary results suggest that significant UHI control can be achieved with cool-cities strategies in the GTA and is therefore worth further study. We recommend that better input data and more accurate modeling schemes be used to carry out f uture studies in the same direction.« less

Brief alcohol intervention trials conducted by higher prestige authors and published in higher impact factor journals are cited more frequently.

PubMed

Tanner-Smith, Emily E; Polanin, Joshua R

2016-07-01

To examine the relationships between study quality, author prestige, journal impact factors, and citation rates of trials and to examine whether journal impact factors mediated the relationships between study quality and author prestige on citation rates. We used bibliometric data from 128 controlled trials included in a recent meta-analysis on brief alcohol interventions for adolescents and young adults. We obtained the number of citations from ISI Web of Knowledge and Google Scholar; journal impact factors were obtained from ISI Web of Knowledge. Linear regression models were used to examine the direct and indirect effects of interest. The results indicated that studies were published in journals with higher impact factors when first authors had higher h-indices and studies were funded, but this was largely because those studies were of higher quality. Studies were cited more frequently when first authors had higher h-indices and studies were funded, even after adjusting for study quality proxies. The observed associations between study quality and author prestige on citation rates were also partly mediated through journal impact factors. We conclude that studies conducted by more established authors and reported in more prestigious journal outlets are more likely to be cited by other scholars, even after controlling for various proxies of study quality. Copyright © 2016 Elsevier Inc. All rights reserved.

Brief Alcohol Intervention Trials Conducted by Higher Prestige Authors and Published in Higher Impact Factor Journals are Cited More Frequently

PubMed Central

Tanner-Smith, Emily E.; Polanin, Joshua R.

2016-01-01

Objective To examine the relationships between study quality, author prestige, journal impact factors, and citation rates of trials; and to examine whether journal impact factors mediated the relationships between study quality and author prestige on citation rates. Study Design and Setting We used bibliometric data from 128 controlled trials included in a recent meta-analysis on brief alcohol interventions (BAIs) for adolescents and young adults. We obtained the number of citations from ISI Web of Knowledge and Google Scholar; journal impact factors were obtained from ISI Web of Knowledge. Linear regression models were used to examine the direct and indirect effects of interest. Results The results indicated that studies were published in journals with higher impact factors when first authors had higher h-indices and studies were funded, but this was largely because those studies were of higher quality. Studies were cited more frequently when first authors had higher h-indices and studies were funded, even after adjusting for study quality proxies. The observed associations between study quality and author prestige on citation rates were also partly mediated through journal impact factors. Conclusion We conclude that studies conducted by more established authors and reported in more prestigious journal outlets are more likely to be cited by other scholars, even after controlling for various proxies of study quality. PMID:26854420

Switching health insurers: the role of price, quality and consumer information search.

PubMed

Boonen, Lieke H H M; Laske-Aldershof, Trea; Schut, Frederik T

2016-04-01

We examine the impact of price, service quality and information search on people's propensity to switch health insurers in the competitive Dutch health insurance market. Using panel data from annual household surveys and data on health insurers' premiums and quality ratings over the period 2006-2012, we estimate a random effects logit model of people's switching decisions. We find that switching propensities depend on health plan price and quality, and on people's age, health, education and having supplementary or group insurance. Young people (18-35 years) are more sensitive to price, whereas older people are more sensitive to quality. Searching for health plan information has a much stronger impact on peoples' sensitivity to price than to service quality. In addition, searching for health plan information has a stronger impact on the switching propensity of higher than lower educated people, suggesting that higher educated people make better use of available health plan information. Finally, having supplementary insurance significantly reduces older people's switching propensity.

Modeling the impact of watershed management policies on marine ecosystem services with application to Hood Canal, WA, USA

NASA Astrophysics Data System (ADS)

Sutherland, D. A.; Kim, C.; Marsik, M.; Spiridonov, G.; Toft, J.; Ruckelshaus, M.; Guerry, A.; Plummer, M.

2011-12-01

Humans obtain numerous benefits from marine ecosystems, including fish to eat; mitigation of storm damage; nutrient and water cycling and primary production; and cultural, aesthetic and recreational values. However, managing these benefits, or ecosystem services, in the marine world relies on an integrated approach that accounts for both marine and watershed activities. Here we present the results of a set of simple, physically-based, and spatially-explicit models that quantify the effects of terrestrial activities on marine ecosystem services. Specifically, we model the circulation and water quality of Hood Canal, WA, USA, a fjord system in Puget Sound where multiple human uses of the nearshore ecosystem (e.g., shellfish aquaculture, recreational Dungeness crab and shellfish harvest) can be compromised when water quality is poor (e.g., hypoxia, excessive non-point source pollution). Linked to the estuarine water quality model is a terrestrial hydrology model that simulates streamflow and nutrient loading, so land cover and climate changes in watersheds can be reflected in the marine environment. In addition, a shellfish aquaculture model is linked to the water quality model to test the sensitivity of the ecosystem service and its value to both terrestrial and marine activities. The modeling framework is general and will be publicly available, allowing easy comparisons of watershed impacts on marine ecosystem services across multiple scales and regions.

The Impact of ISO Quality Management Systems on Primary and Secondary Schools in Spain

ERIC Educational Resources Information Center

Arribas Díaz, Jorge Antonio; Martínez-Mediano, Catalina

2018-01-01

Purpose: The purpose of this study is to evaluate the application of quality management systems (QMS) based on international standards of quality in education (ISO 9001:2008) and ascertain the influence of this quality model on primary and secondary schools in Spain. Design/methodology/approach: The study was conducted in 26 publicly funded,…

Evaluating the success of an emergency response medical information system.

PubMed

Petter, Stacie; Fruhling, Ann

2011-07-01

STATPack™ is an information system used to aid in the diagnosis of pathogens in hospitals and state public health laboratories. STATPack™ is used as a communication and telemedicine diagnosis tool during emergencies. This paper explores the success of this emergency response medical information system (ERMIS) using a well-known framework of information systems success developed by DeLone and McLean. Using an online survey, the entire population of STATPack™ users evaluated the success of the information system by considering system quality, information quality, system use, intention to use, user satisfaction, individual impact, and organizational impact. The results indicate that the overall quality of this ERMIS (i.e., system quality, information quality, and service quality) has a positive impact on both user satisfaction and intention to use the system. However, given the nature of ERMIS, overall quality does not necessarily predict use of the system. Moreover, the user's satisfaction with the information system positively affected the intention to use the system. User satisfaction, intention to use, and system use had a positive influence on the system's impact on the individual. Finally, the organizational impacts of the system were positively influenced by use of the system and the system's individual impact on the user. The results of the study demonstrate how to evaluate the success of an ERMIS as well as introduce potential changes in how one applies the DeLone and McLean success model in an emergency response medical information system context. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Sustainability analysis of bioenergy based land use change under climate change and variability

NASA Astrophysics Data System (ADS)

Raj, C.; Chaubey, I.; Brouder, S. M.; Bowling, L. C.; Cherkauer, K. A.; Frankenberger, J.; Goforth, R. R.; Gramig, B. M.; Volenec, J. J.

2014-12-01

Sustainability analyses of futuristic plausible land use and climate change scenarios are critical in making watershed-scale decisions for simultaneous improvement of food, energy and water management. Bioenergy production targets for the US are anticipated to impact farming practices through the introduction of fast growing and high yielding perennial grasses/trees, and use of crop residues as bioenergy feedstocks. These land use/land management changes raise concern over potential environmental impacts of bioenergy crop production scenarios, both in terms of water availability and water quality; impacts that may be exacerbated by climate variability and change. The objective of the study was to assess environmental, economic and biodiversity sustainability of plausible bioenergy scenarios for two watersheds in Midwest US under changing climate scenarios. The study considers fourteen sustainability indicators under nine climate change scenarios from World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3). The distributed hydrological model SWAT (Soil and Water Assessment Tool) was used to simulate perennial bioenergy crops such as Miscanthus and switchgrass, and corn stover removal at various removal rates and their impacts on hydrology and water quality. Species Distribution Models (SDMs) developed to evaluate stream fish response to hydrology and water quality changes associated with land use change were used to quantify biodiversity sustainability of various bioenergy scenarios. The watershed-scale sustainability analysis was done in the St. Joseph River watershed located in Indiana, Michigan, and Ohio; and the Wildcat Creek watershed, located in Indiana. The results indicate streamflow reduction at watershed outlet with increased evapotranspiration demands for high-yielding perennial grasses. Bioenergy crops in general improved in-stream water quality compared to conventional cropping systems (maize-soybean). Water quality benefits due to land use change were generally greater than the effects of climate change variability.

Evaluating Organic Aerosol Model Performance: Impact of two Embedded Assumptions

NASA Astrophysics Data System (ADS)

Jiang, W.; Giroux, E.; Roth, H.; Yin, D.

2004-05-01

Organic aerosols are important due to their abundance in the polluted lower atmosphere and their impact on human health and vegetation. However, modeling organic aerosols is a very challenging task because of the complexity of aerosol composition, structure, and formation processes. Assumptions and their associated uncertainties in both models and measurement data make model performance evaluation a truly demanding job. Although some assumptions are obvious, others are hidden and embedded, and can significantly impact modeling results, possibly even changing conclusions about model performance. This paper focuses on analyzing the impact of two embedded assumptions on evaluation of organic aerosol model performance. One assumption is about the enthalpy of vaporization widely used in various secondary organic aerosol (SOA) algorithms. The other is about the conversion factor used to obtain ambient organic aerosol concentrations from measured organic carbon. These two assumptions reflect uncertainties in the model and in the ambient measurement data, respectively. For illustration purposes, various choices of the assumed values are implemented in the evaluation process for an air quality model based on CMAQ (the Community Multiscale Air Quality Model). Model simulations are conducted for the Lower Fraser Valley covering Southwest British Columbia, Canada, and Northwest Washington, United States, for a historical pollution episode in 1993. To understand the impact of the assumed enthalpy of vaporization on modeling results, its impact on instantaneous organic aerosol yields (IAY) through partitioning coefficients is analysed first. The analysis shows that utilizing different enthalpy of vaporization values causes changes in the shapes of IAY curves and in the response of SOA formation capability of reactive organic gases to temperature variations. These changes are then carried into the air quality model and cause substantial changes in the organic aerosol modeling results. In another aspect, using different assumed factors to convert measured organic carbon to organic aerosol concentrations cause substantial variations in the processed ambient data themselves, which are normally used as performance targets for model evaluations. The combination of uncertainties in the modeling results and in the moving performance targets causes major uncertainties in the final conclusion about the model performance. Without further information, the best thing that a modeler can do is to choose a combination of the assumed values from the sensible parameter ranges available in the literature, based on the best match of the modeling results with the processed measurement data. However, the best match of the modeling results with the processed measurement data may not necessarily guarantee that the model itself is rigorous and the model performance is robust. Conclusions on the model performance can only be reached with sufficient understanding of the uncertainties and their impact.

77 FR 62623 - 2017 and Later Model Year Light-Duty Vehicle Greenhouse Gas Emissions and Corporate Average Fuel...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-15

... and their associated effects? 1. Inventory 2. Health Effects of Non-GHG Pollutants 3. Environmental Effects of Non-GHG Pollutants 4. Air Quality Impacts of Non-GHG Pollutants 5. Other Unquantified Health...-Greenhouse Gas Health and Environmental Impacts 8. Energy Security Impacts 9. Additional Impacts 10. Summary...

The Impact of Shame on Health-Related Quality of Life Among HIV-Positive Adults with a History of Childhood Sexual Abuse

PubMed Central

Persons, Elizabeth; Kershaw, Trace; Sikkema, Kathleen J.

2010-01-01

Abstract Childhood sexual abuse is prevalent among people living with HIV, and the experience of shame is a common consequence of childhood sexual abuse and HIV infection. This study examined the role of shame in health-related quality of life among HIV-positive adults who have experienced childhood sexual abuse. Data from 247 HIV-infected adults with a history of childhood sexual abuse were analyzed. Hierarchical linear regression was conducted to assess the impact of shame regarding both sexual abuse and HIV infection, while controlling for demographic, clinical, and psychosocial factors. In bivariate analyses, shame regarding sexual abuse and HIV infection were each negatively associated with health-related quality of life and its components (physical well-being, function and global well-being, emotional and social well-being, and cognitive functioning). After controlling for demographic, clinical, and psychosocial factors, HIV-related, but not sexual abuse-related, shame remained a significant predictor of reduced health-related quality of life, explaining up to 10% of the variance in multivariable models for overall health-related quality of life, emotional, function and global, and social well-being and cognitive functioning over and above that of other variables entered into the model. Additionally, HIV symptoms, perceived stress, and perceived availability of social support were associated with health-related quality of life in multivariable models. Shame is an important and modifiable predictor of health-related quality of life in HIV-positive populations, and medical and mental health providers serving HIV-infected populations should be aware of the importance of shame and its impact on the well-being of their patients. PMID:20718687

Modeling in the quality by design environment: Regulatory requirements and recommendations for design space and control strategy appointment.

PubMed

Djuris, Jelena; Djuric, Zorica

2017-11-30

Mathematical models can be used as an integral part of the quality by design (QbD) concept throughout the product lifecycle for variety of purposes, including appointment of the design space and control strategy, continual improvement and risk assessment. Examples of different mathematical modeling techniques (mechanistic, empirical and hybrid) in the pharmaceutical development and process monitoring or control are provided in the presented review. In the QbD context, mathematical models are predominantly used to support design space and/or control strategies. Considering their impact to the final product quality, models can be divided into the following categories: high, medium and low impact models. Although there are regulatory guidelines on the topic of modeling applications, review of QbD-based submission containing modeling elements revealed concerns regarding the scale-dependency of design spaces and verification of models predictions at commercial scale of manufacturing, especially regarding real-time release (RTR) models. Authors provide critical overview on the good modeling practices and introduce concepts of multiple-unit, adaptive and dynamic design space, multivariate specifications and methods for process uncertainty analysis. RTR specification with mathematical model and different approaches to multivariate statistical process control supporting process analytical technologies are also presented. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling crop residue burning experiments to evaluate smoke emissions and plume transport

Treesearch

Luxi Zhou; Kirk R. Baker; Sergey L. Napelenok; George Pouliot; Robert Elleman; Susan M. O' Neill; Shawn P. Urbanski; David C. Wong

2018-01-01

Crop residue burning is a common land management practice that results in emissions of a variety of pollutants with negative health impacts. Modeling systems are used to estimate air quality impacts of crop residue burning to support retrospective regulatory assessments and also for forecasting purposes. Ground and airborne measurements from a recent field experiment...

Linked Hydrologic-Hydrodynamic Model Framework to Forecast Impacts of Rivers on Beach Water Quality

NASA Astrophysics Data System (ADS)

Anderson, E. J.; Fry, L. M.; Kramer, E.; Ritzenthaler, A.

2014-12-01

The goal of NOAA's beach quality forecasting program is to use a multi-faceted approach to aid in detection and prediction of bacteria in recreational waters. In particular, our focus has been on the connection between tributary loads and bacteria concentrations at nearby beaches. While there is a clear link between stormwater runoff and beach water quality, quantifying the contribution of river loadings to nearshore bacterial concentrations is complicated due to multiple processes that drive bacterial concentrations in rivers as well as those processes affecting the fate and transport of bacteria upon exiting the rivers. In order to forecast potential impacts of rivers on beach water quality, we developed a linked hydrologic-hydrodynamic water quality framework that simulates accumulation and washoff of bacteria from the landscape, and then predicts the fate and transport of washed off bacteria from the watershed to the coastal zone. The framework includes a watershed model (IHACRES) to predict fecal indicator bacteria (FIB) loadings to the coastal environment (accumulation, wash-off, die-off) as a function of effective rainfall. These loadings are input into a coastal hydrodynamic model (FVCOM), including a bacteria transport model (Lagrangian particle), to simulate 3D bacteria transport within the coastal environment. This modeling system provides predictive tools to assist local managers in decision-making to reduce human health threats.

Simulating climate change and socio-economic change impacts on flows and water quality in the Mahanadi River system, India.

PubMed

Jin, Li; Whitehead, Paul G; Rodda, Harvey; Macadam, Ian; Sarkar, Sananda

2018-10-01

Delta systems formed by the deposition of sediments at the mouths of large catchments are vulnerable to sea level rise and other climate change impacts. Deltas often have some of the highest population densities in the world and the Mahanadi Delta in India is one of these, with a population of 39 million. The Mahanadi River is a major river in East Central India and flows through Chattisgarh and Orissa states before discharging into the Bay of Bengal. This study uses an Integrated Catchment Model (INCA) to simulate flow dynamics and water quality (nitrogen and phosphorus) and to analyze the impacts of climate change and socio-economic drivers in the Mahanadi River system. Future flows affected by large population growth, effluent discharge increases and changes in irrigation water demand from changing land uses are assessed under shared socio-economic pathways (SSPs). Model results indicate a significant increase in monsoon flows under the future climates at 2050s (2041-2060) and 2090s (2079-2098) which greatly enhances flood potential. The water availability under low flow conditions will be worsened because of increased water demand from population growth and increased irrigation in the future. Decreased concentrations of nitrogen and phosphorus are expected due to increased flow hence dilution. Socio-economic scenarios have a significant impact on water quality but less impact on the river flow. For example, higher population growth, increased sewage treatment discharges, land use change and enhanced atmospheric deposition would result in the deterioration of water quality, while the upgrade of the sewage treatment works lead to improved water quality. In summary, socio-economic scenarios would change future water quality of the Mahanadi River and alter nutrient fluxes transported into the delta region. This study has serious implications for people's livelihoods in the deltaic area and could impact coastal and Bay of Bengal water ecology. Copyright © 2018 Elsevier B.V. All rights reserved.

Incentives for cooperation in quality improvement among hospitals--the impact of the reimbursement system.

PubMed

Kesteloot, K; Voet, N

1998-12-01

Up to now, few analytical models have studied the incentives for cooperation in quality improvements among hospitals. Only those dealing with reimbursement systems have shown that, from the point of view of individual or competing hospitals, retrospective reimbursement is more likely to encourage quality improvements than prospective financing, while the reverse holds for efficiency improvements. This paper studies the incentives to improve the quality of hospital care, in an analytical model, taking into account the possibility of cooperative agreements, price besides non-price (quality) competition and quality improvements that may simultaneously increase demand, increase or reduce costs and spill over to rival hospitals. In this setting quality improvement efforts rise with the rate of prospective reimbursement, while the impact of the rate of retrospective reimbursement is ambiguous, but likely to be negative for quality improvements that are highly cost-reducting and create large spillovers. Cooperation may lead to more or less quality improvement than non-cooperative conduct, depending on the magnitude of spillovers and the degree of product market competition, relative to the net effect of quality on profits and the share of costs that is reimbursed retrospectively. Finally, the stability of cooperative agreements, supported by grim trigger strategies, is shown to depend upon exactly the opposite interaction between these factors.

Influence of land use on water quality in a tropical landscape: a multi-scale analysis

PubMed Central

Yackulic, Charles B.; Lim, Yili; Arce-Nazario, Javier A.

2015-01-01

There is a pressing need to understand the consequences of human activities, such as land transformations, on watershed ecosystem services. This is a challenging task because different indicators of water quality and yield are expected to vary in their responsiveness to large versus local-scale heterogeneity in land use and land cover (LUC). Here we rely on water quality data collected between 1977 and 2000 from dozens of gauge stations in Puerto Rico together with precipitation data and land cover maps to (1) quantify impacts of spatial heterogeneity in LUC on several water quality indicators; (2) determine the spatial scale at which this heterogeneity influences water quality; and (3) examine how antecedent precipitation modulates these impacts. Our models explained 30–58% of observed variance in water quality metrics. Temporal variation in antecedent precipitation and changes in LUC between measurements periods rather than spatial variation in LUC accounted for the majority of variation in water quality. Urbanization and pasture development generally degraded water quality while agriculture and secondary forest re-growth had mixed impacts. The spatial scale over which LUC influenced water quality differed across indicators. Turbidity and dissolved oxygen (DO) responded to LUC in large-scale watersheds, in-stream nitrogen concentrations to LUC in riparian buffers of large watersheds, and fecal matter content and in-stream phosphorus concentration to LUC at the sub-watershed scale. Stream discharge modulated impacts of LUC on water quality for most of the metrics. Our findings highlight the importance of considering multiple spatial scales for understanding the impacts of human activities on watershed ecosystem services. PMID:26146455

A Framework of the Use of Information in Software Testing

ERIC Educational Resources Information Center

Kaveh, Payman

2010-01-01

With the increasing role that software systems play in our daily lives, software quality has become extremely important. Software quality is impacted by the efficiency of the software testing process. There are a growing number of software testing methodologies, models, and initiatives to satisfy the need to improve software quality. The main…

Influence of air quality model resolution on uncertainty associated with health impacts

NASA Astrophysics Data System (ADS)

Thompson, T. M.; Selin, N. E.

2012-06-01

We use regional air quality modeling to evaluate the impact of model resolution on uncertainty associated with the human health benefits resulting from proposed air quality regulations. Using a regional photochemical model (CAMx), we ran a modeling episode with meteorological inputs representing conditions as they occurred during August through September 2006, and two emissions inventories (a 2006 base case and a 2018 proposed control scenario, both for Houston, Texas) at 36, 12, 4 and 2 km resolution. The base case model performance was evaluated for each resolution against daily maximum 8-h averaged ozone measured at monitoring stations. Results from each resolution were more similar to each other than they were to measured values. Population-weighted ozone concentrations were calculated for each resolution and applied to concentration response functions (with 95% confidence intervals) to estimate the health impacts of modeled ozone reduction from the base case to the control scenario. We found that estimated avoided mortalities were not significantly different between 2, 4 and 12 km resolution runs, but 36 km resolution may over-predict some potential health impacts. Given the cost/benefit analysis requirements of the Clean Air Act, the uncertainty associated with human health impacts and therefore the results reported in this study, we conclude that health impacts calculated from population weighted ozone concentrations obtained using regional photochemical models at 36 km resolution fall within the range of values obtained using fine (12 km or finer) resolution modeling. However, in some cases, 36 km resolution may not be fine enough to statistically replicate the results achieved using 2 and 4 km resolution. On average, when modeling at 36 km resolution, 7 deaths per ozone month were avoided because of ozone reductions resulting from the proposed emissions reductions (95% confidence interval was 2-9). When modeling at 2, 4 or 12 km finer scale resolution, on average 5 deaths were avoided due to the same reductions (95% confidence interval was 2-7). Initial results for this specific region show that modeling at a resolution finer than 12 km is unlikely to improve uncertainty in benefits analysis. We suggest that 12 km resolution may be appropriate for uncertainty analyses in areas with similar chemistry, but that resolution requirements should be assessed on a case-by-case basis and revised as confidence intervals for concentration-response functions are updated.

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

Jiang, Like; Kang, Jian, E-mail: j.kang@sheffield.ac.uk; Schroth, Olaf

Large scale transportation projects can adversely affect the visual perception of environmental quality and require adequate visual impact assessment. In this study, we investigated the effects of the characteristics of the road project and the character of the existing landscape on the perceived visual impact of motorways, and developed a GIS-based prediction model based on the findings. An online survey using computer-visualised scenes of different motorway and landscape scenarios was carried out to obtain perception-based judgements on the visual impact. Motorway scenarios simulated included the baseline scenario without road, original motorway, motorways with timber noise barriers, transparent noise barriers andmore » tree screen; different landscape scenarios were created by changing land cover of buildings and trees in three distance zones. The landscape content of each scene was measured in GIS. The result shows that presence of a motorway especially with the timber barrier significantly decreases the visual quality of the view. The resulted visual impact tends to be lower where it is less visually pleasant with more buildings in the view, and can be slightly reduced by the visual absorption effect of the scattered trees between the motorway and the viewpoint. Based on the survey result, eleven predictors were identified for the visual impact prediction model which was applied in GIS to generate maps of visual impact of motorways in different scenarios. The proposed prediction model can be used to achieve efficient and reliable assessment of visual impact of motorways. - Highlights: • Motorways induce significant visual impact especially with timber noise barriers. • Visual impact is negatively correlated with amount of buildings in the view. • Visual impact is positively correlated with percentage of trees in the view. • Perception-based motorway visual impact prediction model using mapped predictors • Predicted visual impacts in different scenarios are mapped in GIS.« less

Scale Issues in Air Quality Modeling

EPA Science Inventory

This presentation reviews past model evaluation studies investigating the impact of horizontal grid spacing on model performance. It also presents several examples of using a spectral decomposition technique to separate the forcings from processes operating on different time scal...

a System Dynamics Model to Study the Importance of Infrastructure Facilities on Quality of Primary Education System in Developing Countries

NASA Astrophysics Data System (ADS)

Pedamallu, Chandra Sekhar; Ozdamar, Linet; Weber, Gerhard-Wilhelm; Kropat, Erik

2010-06-01

The system dynamics approach is a holistic way of solving problems in real-time scenarios. This is a powerful methodology and computer simulation modeling technique for framing, analyzing, and discussing complex issues and problems. System dynamics modeling and simulation is often the background of a systemic thinking approach and has become a management and organizational development paradigm. This paper proposes a system dynamics approach for study the importance of infrastructure facilities on quality of primary education system in developing nations. The model is proposed to be built using the Cross Impact Analysis (CIA) method of relating entities and attributes relevant to the primary education system in any given community. We offer a survey to build the cross-impact correlation matrix and, hence, to better understand the primary education system and importance of infrastructural facilities on quality of primary education. The resulting model enables us to predict the effects of infrastructural facilities on the access of primary education by the community. This may support policy makers to take more effective actions in campaigns.

Interaction of aberrations, diffraction, and quantal fluctuations determine the impact of pupil size on visual quality.

PubMed

Xu, Renfeng; Wang, Huachun; Thibos, Larry N; Bradley, Arthur

2017-04-01

Our purpose is to develop a computational approach that jointly assesses the impact of stimulus luminance and pupil size on visual quality. We compared traditional optical measures of image quality and those that incorporate the impact of retinal illuminance dependent neural contrast sensitivity. Visually weighted image quality was calculated for a presbyopic model eye with representative levels of chromatic and monochromatic aberrations as pupil diameter was varied from 7 to 1 mm, stimulus luminance varied from 2000 to 0.1  cd/m², and defocus varied from 0 to -2 diopters. The model included the effects of quantal fluctuations on neural contrast sensitivity. We tested the model's predictions for five cycles per degree gratings by measuring contrast sensitivity at 5  cyc/deg. Unlike the traditional Strehl ratio and the visually weighted area under the modulation transfer function, the visual Strehl ratio derived from the optical transfer function was able to capture the combined impact of optics and quantal noise on visual quality. In a well-focused eye, provided retinal illuminance is held constant as pupil size varies, visual image quality scales approximately as the square root of illuminance because of quantum fluctuations, but optimum pupil size is essentially independent of retinal illuminance and quantum fluctuations. Conversely, when stimulus luminance is held constant (and therefore illuminance varies with pupil size), optimum pupil size increases as luminance decreases, thereby compensating partially for increased quantum fluctuations. However, in the presence of -1 and -2 diopters of defocus and at high photopic levels where Weber's law operates, optical aberrations and diffraction dominate image quality and pupil optimization. Similar behavior was observed in human observers viewing sinusoidal gratings. Optimum pupil size increases as stimulus luminance drops for the well-focused eye, and the benefits of small pupils for improving defocused image quality remain throughout the photopic and mesopic ranges. However, restricting pupils to <2  mm will cause significant reductions in the best focus vision at low photopic and mesopic luminances.

Modeling study of biomass burning plumes and their impact on urban air quality; a case study of Santiago de Chile

NASA Astrophysics Data System (ADS)

Cuchiara, Gustavo C.; Rappenglück, Bernhard; Angelica Rubio, Maria; Lissi, Eduardo; Gramsch, Ernesto; Garreaud, Rene D.

2017-04-01

Wildfires are a significant direct source of atmospheric pollutants; on a global scale biomass burning is believed to be the largest source of primary fine particles in the atmosphere and the second largest source of trace gases after anthropogenic emission sources. During the summer of 2014, an intense forest and dry pasture wildfire occurred nearby the city of Santiago de Chile. The biomass-burning plume was transported towards the metropolitan area of Santiago and exacerbated the air quality in this region. In this study, we investigated this wildfire event using a forward plume-rise and a chemistry (WRF/Chem) simulation. These data sets provided an opportunity to validate a regional air-quality simulation over Santiago, and a unique case to assess the performance of biomass burning plume modeling in complex topography and validated against an established air quality network. The results from both meteorological and air quality models provide insights about the transport of biomass-burning plumes from the wildfire region towards the metropolitan region of Santiago de Chile. We studied a seven-day period between January 01-07, 2014, and the impact of biomass burning plume emissions estimated by Fire Inventory from NCAR version 1 (FINNv1) on the air quality of Santiago de Chile.

Replacing American Breakfast Foods with Ready-To-Eat (RTE) Cereals Increases Consumption of Key Food Groups and Nutrients among US Children and Adults: Results of an NHANES Modeling Study.

PubMed

Rehm, Colin D; Drewnowski, Adam

2017-09-13

Replacing the typical American breakfast with ready-to-eat cereals (RTECs) may improve diet quality. Our goal was to assess the impact of RTECs on diet quality measures for different age groups, using substitution modeling. Dietary intakes came from the 2007-2010 National Health and Examination Surveys (NHANES; n = 18,112). All breakfast foods, excluding beverages, were replaced on a per calorie basis, with frequency-weighted and age/race specific RTECs. Model 1 replaced foods with RTECs alone; Model 2 replaced foods with RTECs and milk. Diet quality measures were based on desirable food groups and nutrients, Healthy Eating Index (HEI)-2010 scores, and estimated diet costs. Model 1 diets were significantly higher in whole grains (+84.6%), fiber (+14.3%), vitamin D (+14.0%), iron (+54.5%) and folic acid (+104.6%), as compared to observed diets. Model 2 diets were additionally higher in dairy (+15.8%), calcium (+11.3%) and potassium (+3.95%). In Model 1, added sugar increased (+5.0%), but solid fats declined (-10.9%). Energy from solid fats and added sugars declined (-3.2%) in both models. Model 2 offered higher diet quality (57.1 vs. 54.6, p -value < 0.01) at a lower cost ($6.70 vs. $6.92; p < 0.01), compared to observed diets. Substitution modeling of NHANES data can assess the nutritional and economic impact of dietary guidance.

Replacing American Breakfast Foods with Ready-To-Eat (RTE) Cereals Increases Consumption of Key Food Groups and Nutrients among US Children and Adults: Results of an NHANES Modeling Study

PubMed Central

Rehm, Colin D.; Drewnowski, Adam

2017-01-01

Replacing the typical American breakfast with ready-to-eat cereals (RTECs) may improve diet quality. Our goal was to assess the impact of RTECs on diet quality measures for different age groups, using substitution modeling. Dietary intakes came from the 2007–2010 National Health and Examination Surveys (NHANES; n = 18,112). All breakfast foods, excluding beverages, were replaced on a per calorie basis, with frequency-weighted and age/race specific RTECs. Model 1 replaced foods with RTECs alone; Model 2 replaced foods with RTECs and milk. Diet quality measures were based on desirable food groups and nutrients, Healthy Eating Index (HEI)-2010 scores, and estimated diet costs. Model 1 diets were significantly higher in whole grains (+84.6%), fiber (+14.3%), vitamin D (+14.0%), iron (+54.5%) and folic acid (+104.6%), as compared to observed diets. Model 2 diets were additionally higher in dairy (+15.8%), calcium (+11.3%) and potassium (+3.95%). In Model 1, added sugar increased (+5.0%), but solid fats declined (−10.9%). Energy from solid fats and added sugars declined (−3.2%) in both models. Model 2 offered higher diet quality (57.1 vs. 54.6, p-value < 0.01) at a lower cost ($6.70 vs. $6.92; p < 0.01), compared to observed diets. Substitution modeling of NHANES data can assess the nutritional and economic impact of dietary guidance. PMID:28902145

National strategic plan: modeling and data systems for wildland fire and air quality.

Treesearch

David V. Sandberg; Colin C. Hardy; Roger D. Ottmar; J.A. Kendall Snell; Ann Acheson; Janice L. Peterson; Paula Seamon; Peter Lahm; Dale Wade

1999-01-01

This strategic plan is a technical discussion of the implementation and development of models and data systems used to manage the air quality impacts of wildland and prescribed fires. Strategies and priorities in the plan were generated by the Express Team (chartered by the National Wildfire Coordinating Group) and a diverse group of 86 subject matter experts who...

Estimating emissions from fires in North America for air quality modeling.

Treesearch

Christine Wiedinmyer; Brad Quayle; Chris Geron; Angie Belote; Don McKenzie; Xiaoyang Zhang; Susan O' Neill; Kristina Klos Wynne

2006-01-01

Fires contribute substantial emissions of trace gases and particles to the atmosphere. These emissions can impact air quality and even climate. We have developed a modeling framework to estimate the emissions from fires in North and parts of Central America (10-71 ˚N and 55-175 ˚W) by taking advantage of a combination of complementary satellite and...

New approach for optimal electricity planning and dispatching with hourly time-scale air quality and health considerations.

PubMed

Kerl, Paul Y; Zhang, Wenxian; Moreno-Cruz, Juan B; Nenes, Athanasios; Realff, Matthew J; Russell, Armistead G; Sokol, Joel; Thomas, Valerie M

2015-09-01

Integrating accurate air quality modeling with decision making is hampered by complex atmospheric physics and chemistry and its coupling with atmospheric transport. Existing approaches to model the physics and chemistry accurately lead to significant computational burdens in computing the response of atmospheric concentrations to changes in emissions profiles. By integrating a reduced form of a fully coupled atmospheric model within a unit commitment optimization model, we allow, for the first time to our knowledge, a fully dynamical approach toward electricity planning that accurately and rapidly minimizes both cost and health impacts. The reduced-form model captures the response of spatially resolved air pollutant concentrations to changes in electricity-generating plant emissions on an hourly basis with accuracy comparable to a comprehensive air quality model. The integrated model allows for the inclusion of human health impacts into cost-based decisions for power plant operation. We use the new capability in a case study of the state of Georgia over the years of 2004-2011, and show that a shift in utilization among existing power plants during selected hourly periods could have provided a health cost savings of $175.9 million dollars for an additional electricity generation cost of $83.6 million in 2007 US dollars (USD2007). The case study illustrates how air pollutant health impacts can be cost-effectively minimized by intelligently modulating power plant operations over multihour periods, without implementing additional emissions control technologies.

New approach for optimal electricity planning and dispatching with hourly time-scale air quality and health considerations

PubMed Central

Kerl, Paul Y.; Zhang, Wenxian; Moreno-Cruz, Juan B.; Nenes, Athanasios; Realff, Matthew J.; Russell, Armistead G.; Sokol, Joel; Thomas, Valerie M.

2015-01-01

Integrating accurate air quality modeling with decision making is hampered by complex atmospheric physics and chemistry and its coupling with atmospheric transport. Existing approaches to model the physics and chemistry accurately lead to significant computational burdens in computing the response of atmospheric concentrations to changes in emissions profiles. By integrating a reduced form of a fully coupled atmospheric model within a unit commitment optimization model, we allow, for the first time to our knowledge, a fully dynamical approach toward electricity planning that accurately and rapidly minimizes both cost and health impacts. The reduced-form model captures the response of spatially resolved air pollutant concentrations to changes in electricity-generating plant emissions on an hourly basis with accuracy comparable to a comprehensive air quality model. The integrated model allows for the inclusion of human health impacts into cost-based decisions for power plant operation. We use the new capability in a case study of the state of Georgia over the years of 2004–2011, and show that a shift in utilization among existing power plants during selected hourly periods could have provided a health cost savings of $175.9 million dollars for an additional electricity generation cost of $83.6 million in 2007 US dollars (USD2007). The case study illustrates how air pollutant health impacts can be cost-effectively minimized by intelligently modulating power plant operations over multihour periods, without implementing additional emissions control technologies. PMID:26283358

Dynamic modeling of the Ganga river system: impacts of future climate and socio-economic change on flows and nitrogen fluxes in India and Bangladesh.

PubMed

Whitehead, P G; Sarkar, S; Jin, L; Futter, M N; Caesar, J; Barbour, E; Butterfield, D; Sinha, R; Nicholls, R; Hutton, C; Leckie, H D

2015-06-01

This study investigates the potential impacts of future climate and socio-economic change on the flow and nitrogen fluxes of the Ganga river system. This is the first basin scale water quality study for the Ganga considering climate change at 25 km resolution together with socio-economic scenarios. The revised dynamic, process-based INCA model was used to simulate hydrology and water quality within the complex multi-branched river basins. All climate realizations utilized in the study predict increases in temperature and rainfall by the 2050s with significant increase by the 2090s. These changes generate associated increases in monsoon flows and increased availability of water for groundwater recharge and irrigation, but also more frequent flooding. Decreased concentrations of nitrate and ammonia are expected due to increased dilution. Different future socio-economic scenarios were found to have a significant impact on water quality at the downstream end of the Ganga. A less sustainable future resulted in a deterioration of water quality due to the pressures from higher population growth, land use change, increased sewage treatment discharges, enhanced atmospheric nitrogen deposition, and water abstraction. However, water quality was found to improve under a more sustainable strategy as envisaged in the Ganga clean-up plan.

Modelling the impacts of pests and diseases on agricultural systems.

PubMed

Donatelli, M; Magarey, R D; Bregaglio, S; Willocquet, L; Whish, J P M; Savary, S

2017-07-01

The improvement and application of pest and disease models to analyse and predict yield losses including those due to climate change is still a challenge for the scientific community. Applied modelling of crop diseases and pests has mostly targeted the development of support capabilities to schedule scouting or pesticide applications. There is a need for research to both broaden the scope and evaluate the capabilities of pest and disease models. Key research questions not only involve the assessment of the potential effects of climate change on known pathosystems, but also on new pathogens which could alter the (still incompletely documented) impacts of pests and diseases on agricultural systems. Yield loss data collected in various current environments may no longer represent a adequate reference to develop tactical, decision-oriented, models for plant diseases and pests and their impacts, because of the ongoing changes in climate patterns. Process-based agricultural simulation modelling, on the other hand, appears to represent a viable methodology to estimate the impacts of these potential effects. A new generation of tools based on state-of-the-art knowledge and technologies is needed to allow systems analysis including key processes and their dynamics over appropriate suitable range of environmental variables. This paper offers a brief overview of the current state of development in coupling pest and disease models to crop models, and discusses technical and scientific challenges. We propose a five-stage roadmap to improve the simulation of the impacts caused by plant diseases and pests; i) improve the quality and availability of data for model inputs; ii) improve the quality and availability of data for model evaluation; iii) improve the integration with crop models; iv) improve the processes for model evaluation; and v) develop a community of plant pest and disease modelers.

Can editors save peer review from peer reviewers?

PubMed

D'Andrea, Rafael; O'Dwyer, James P

2017-01-01

Peer review is the gold standard for scientific communication, but its ability to guarantee the quality of published research remains difficult to verify. Recent modeling studies suggest that peer review is sensitive to reviewer misbehavior, and it has been claimed that referees who sabotage work they perceive as competition may severely undermine the quality of publications. Here we examine which aspects of suboptimal reviewing practices most strongly impact quality, and test different mitigating strategies that editors may employ to counter them. We find that the biggest hazard to the quality of published literature is not selfish rejection of high-quality manuscripts but indifferent acceptance of low-quality ones. Bypassing or blacklisting bad reviewers and consulting additional reviewers to settle disagreements can reduce but not eliminate the impact. The other editorial strategies we tested do not significantly improve quality, but pairing manuscripts to reviewers unlikely to selfishly reject them and allowing revision of rejected manuscripts minimize rejection of above-average manuscripts. In its current form, peer review offers few incentives for impartial reviewing efforts. Editors can help, but structural changes are more likely to have a stronger impact.

Assessment and prediction of air quality using fuzzy logic and autoregressive models

NASA Astrophysics Data System (ADS)

Carbajal-Hernández, José Juan; Sánchez-Fernández, Luis P.; Carrasco-Ochoa, Jesús A.; Martínez-Trinidad, José Fco.

2012-12-01

In recent years, artificial intelligence methods have been used for the treatment of environmental problems. This work, presents two models for assessment and prediction of air quality. First, we develop a new computational model for air quality assessment in order to evaluate toxic compounds that can harm sensitive people in urban areas, affecting their normal activities. In this model we propose to use a Sigma operator to statistically asses air quality parameters using their historical data information and determining their negative impact in air quality based on toxicity limits, frequency average and deviations of toxicological tests. We also introduce a fuzzy inference system to perform parameter classification using a reasoning process and integrating them in an air quality index describing the pollution levels in five stages: excellent, good, regular, bad and danger, respectively. The second model proposed in this work predicts air quality concentrations using an autoregressive model, providing a predicted air quality index based on the fuzzy inference system previously developed. Using data from Mexico City Atmospheric Monitoring System, we perform a comparison among air quality indices developed for environmental agencies and similar models. Our results show that our models are an appropriate tool for assessing site pollution and for providing guidance to improve contingency actions in urban areas.

GLIMPSE: A decision support tool for simultaneously achieving our air quality management and climate change mitigation goals

NASA Astrophysics Data System (ADS)

Pinder, R. W.; Akhtar, F.; Loughlin, D. H.; Henze, D. K.; Bowman, K. W.

2012-12-01

Poor air quality, ecosystem damages, and climate change all are caused by the combustion of fossil fuels, yet environmental management often addresses each of these challenges separately. This can lead to sub-optimal strategies and unintended consequences. Here we present GLIMPSE -- a decision support tool for simultaneously achieving our air quality and climate change mitigation goals. GLIMPSE comprises of two types of models, (i) the adjoint of the GEOS-Chem chemical transport model, to calculate the relationship between emissions and impacts at high spatial resolution, and (ii) the MARKAL energy system model, to calculate the relationship between energy technologies and emissions. This presentation will demonstrate how GLIMPSE can be used to explore energy scenarios to better achieve both improved air quality and mitigate climate change. Second, this presentation will discuss how space-based observations can be incorporated into GLIMPSE to improve decision-making. NASA satellite products, namely ozone radiative forcing from the Tropospheric Emission Spectrometer (TES), are used to extend GLIMPSE to include the impact of emissions on ozone radiative forcing. This provides a much needed observational constraint on ozone radiative forcing.

Developing a quality by design approach to model tablet dissolution testing: an industrial case study.

PubMed

Yekpe, Ketsia; Abatzoglou, Nicolas; Bataille, Bernard; Gosselin, Ryan; Sharkawi, Tahmer; Simard, Jean-Sébastien; Cournoyer, Antoine

2018-07-01

This study applied the concept of Quality by Design (QbD) to tablet dissolution. Its goal was to propose a quality control strategy to model dissolution testing of solid oral dose products according to International Conference on Harmonization guidelines. The methodology involved the following three steps: (1) a risk analysis to identify the material- and process-related parameters impacting the critical quality attributes of dissolution testing, (2) an experimental design to evaluate the influence of design factors (attributes and parameters selected by risk analysis) on dissolution testing, and (3) an investigation of the relationship between design factors and dissolution profiles. Results show that (a) in the case studied, the two parameters impacting dissolution kinetics are active pharmaceutical ingredient particle size distributions and tablet hardness and (b) these two parameters could be monitored with PAT tools to predict dissolution profiles. Moreover, based on the results obtained, modeling dissolution is possible. The practicality and effectiveness of the QbD approach were demonstrated through this industrial case study. Implementing such an approach systematically in industrial pharmaceutical production would reduce the need for tablet dissolution testing.

Scaling up food production in the Upper Mississippi river basin: modeling impacts on water quality and nutrient cycling

NASA Astrophysics Data System (ADS)

Bowen, E. E.; Martin, P. A.; Schuble, T. J.; Yan, E.; Demissie, Y.

2010-12-01

Agricultural production imposes significant environmental stress on the landscape, both in the intensity and extent of agricultural activities. Among the most significant impacts, agriculture dominates the natural reactive nitrogen cycle, with excess reactive nitrogen leading to the degraded quality of inland and coastal waters. In the U.S., policymakers and stakeholders nationwide continue to debate strategies for decreasing environmental degradation from agricultural lands. Such strategies aim to optimize the balance among competing demands for food, fuel and ecosystem services. One such strategy increasingly discussed in the national debate is that of localizing food production around urban areas, developing what some have recently called “foodsheds”. However, the environmental impacts of localizing food production around population centers are not well-understood given the hard-to-generalize variety seen in management practices currently employed among local farms marketing food crops directly to consumers. As a first, landscape level study of potential impacts from scaling up this type of agriculture, we use the USDA Soil and Water Assessment Tool (SWAT) model to quantify environmental impacts from developing foodsheds for all population centers in the Upper Mississippi river basin. Specifically, we focus on nutrient cycling and water quality impacts determining direct greenhouse gas emissions and changes to nutrient runoff from increased food production in this watershed. We investigate a variety of scenarios in which food production is scaled up to the regional level using different types of farm management practices, ranging from conventional production of fruits and vegetables, to production of these products from small-scale, diversified systems integrating conservation easements. In addition to impacts on nutrient cycling and water quality, we also characterize relative levels of productivity in conjunction with overall demand for food associated with population centers to address one aspect of socio-economic concern.

Impact of Information Technology, Clinical Resource Constraints, and Patient-Centered Practice Characteristics on Quality of Care.

PubMed

Baek, JongDeuk; Seidman, Robert L

2015-01-01

Factors in the practice environment, such as health information technology (IT) infrastructure, availability of other clinical resources, and financial incentives, may influence whether practices are able to successfully implement the patient-centered medical home (PCMH) model and realize its benefits. This study investigates the impacts of those PCMH-related elements on primary care physicians' perception of quality of care. A multiple logistic regression model was estimated using the 2004 to 2005 CTS Physician Survey, a national sample of salaried primary care physicians (n = 1733). The patient-centered practice environment and availability of clinical resources increased physicians' perceived quality of care. Although IT use for clinical information access did enhance physicians' ability to provide high quality of care, a similar positive impact of IT use was not found for e-prescribing or the exchange of clinical patient information. Lack of resources was negatively associated with physician perception of quality of care. Since health IT is an important foundation of PCMH, patient-centered practices are more likely to have health IT in place to support care delivery. However, despite its potential to enhance delivery of primary care, simply making health IT available does not necessarily translate into physicians' perceptions that it enhances the quality of care they provide. It is critical for health-care managers and policy makers to ensure that primary care physicians fully recognize and embrace the use of new technology to improve both the quality of care provided and the patient outcomes.

BASINS Publications

EPA Pesticide Factsheets

Although BASINS has been in use for the past 10 years, there has been limited modeling guidance on its applications for complex environmental problems, such as modeling impacts of hydro modification on water quantity and quality.

Characterizing the impact of projected changes in climate and ...

EPA Pesticide Factsheets

The impact of climate change on human and environmental health is of critical concern. Population exposures to air pollutants both indoors and outdoors are influenced by a wide range of air quality, meteorological, behavioral, and housing-related factors, many of which are also impacted by climate change. An integrated methodology for modeling changes in human exposures to tropospheric ozone (O3) owing to potential future changes in climate and demographics was implemented by linking existing modeling tools for climate, weather, air quality, population distribution, and human exposure. Human exposure results from the Air Pollutants Exposure Model (APEX) for 12 US cities show differences in daily maximum 8-h (DM8H) exposure patterns and levels by sex, age, and city for all scenarios. When climate is held constant and population demographics are varied, minimal difference in O3 exposures is predicted even with the most extreme demographic change scenario. In contrast, when population is held constant, we see evidence of substantial changes in O3 exposure for the most extreme change in climate. Similarly, we see increases in the percentage of the population in each city with at least one O3 exposure exceedance above 60 p.p.b and 70 p.p.b thresholds for future changes in climate. For these climate and population scenarios, the impact of projected changes in climate and air quality on human exposure to O3 are much larger than the impacts of changing demographics.

Impacts of WRF lightning assimilation on offline CMAQ simulations

EPA Science Inventory

Deep convective clouds vertically redistribute trace gases and aerosols and also provide a source for scavenging, aqueous phase chemistry, and wet deposition, making them important to air quality.? Regional air quality simulations are typically driven by meteorological models tha...

A description and evaluation of an air quality model nested within global and regional composition-climate models using MetUM

NASA Astrophysics Data System (ADS)

Neal, Lucy S.; Dalvi, Mohit; Folberth, Gerd; McInnes, Rachel N.; Agnew, Paul; O'Connor, Fiona M.; Savage, Nicholas H.; Tilbee, Marie

2017-11-01

There is a clear need for the development of modelling frameworks for both climate change and air quality to help inform policies for addressing these issues simultaneously. This paper presents an initial attempt to develop a single modelling framework, by introducing a greater degree of consistency in the meteorological modelling framework by using a two-step, one-way nested configuration of models, from a global composition-climate model (GCCM) (140 km resolution) to a regional composition-climate model covering Europe (RCCM) (50 km resolution) and finally to a high (12 km) resolution model over the UK (AQUM). The latter model is used to produce routine air quality forecasts for the UK. All three models are based on the Met Office's Unified Model (MetUM). In order to better understand the impact of resolution on the downscaling of projections of future climate and air quality, we have used this nest of models to simulate a 5-year period using present-day emissions and under present-day climate conditions. We also consider the impact of running the higher-resolution model with higher spatial resolution emissions, rather than simply regridding emissions from the RCCM. We present an evaluation of the models compared to in situ air quality observations over the UK, plus a comparison against an independent 1 km resolution gridded dataset, derived from a combination of modelling and observations, effectively producing an analysis of annual mean surface pollutant concentrations. We show that using a high-resolution model over the UK has some benefits in improving air quality modelling, but that the use of higher spatial resolution emissions is important to capture local variations in concentrations, particularly for primary pollutants such as nitrogen dioxide and sulfur dioxide. For secondary pollutants such as ozone and the secondary component of PM10, the benefits of a higher-resolution nested model are more limited and reasons for this are discussed. This study highlights the point that the resolution of models is not the only factor in determining model performance - consistency between nested models is also important.

Privatization of local public hospitals: effect on budget, medical service quality, and social welfare.

PubMed

Aiura, Hiroshi; Sanjo, Yasuo

2010-09-01

We analyze a duopolistic health care market in which a rural public hospital competes against an urban public hospital on medical quality, by using a Hotelling-type spatial competition model extended into a two-region model. We show that the rural public hospital provides excess quality for each unit of medical service as compared to the first-best quality, and the profits of the rural public hospital are lower than those of the urban public hospital because the provision of excess quality requires larger expenditure. In addition, we investigate the impact of the partial (or full) privatization of local public hospitals.

Predicting the Use of Public Transportation: A Case Study from Putrajaya, Malaysia

PubMed Central

Borhan, Muhamad Nazri; Mohd Akhir, Norliza; Mat Yazid, Muhamad Razuhanafi; Ismail, Amiruddin; Rahmat, Riza Atiq

2014-01-01

Putrajaya is a new federal administrative capital of Malaysia which has been set to achieve a 70% share of all travels by public transport in the city area. However, the current modal split between the public transport and private transport is 15 : 85. In order to understand travelers' willingness to use the public transport, a conceptual model has been developed to determine the factors that affect them to use the public transport instead of travelling in their own cars. Various variables such as service quality, environmental impact, attitude, and behavior intention were analyzed and tested using structural equation model (SEM). Results indicate that the service quality and attitude are found to have positive effects on the behavioral intention of taking the public transport. Other than this, this study also shows that the service quality and environmental impact have some positive influences on the attitude to using the public transport. However, environmental impact has no significant, positive, and direct effect on behavioral intention. The results of this study demonstrate that the model that was developed is useful in predicting the public transport and it could provide a more complete understanding of behavioral intention towards public transport use. PMID:25110744

Predicting the use of public transportation: a case study from Putrajaya, Malaysia.

PubMed

Borhan, Muhamad Nazri; Syamsunur, Deprizon; Akhir, Norliza Mohd; Yazid, Muhamad Razuhanafi Mat; Ismail, Amiruddin; Rahmat, Riza Atiq

2014-01-01

Putrajaya is a new federal administrative capital of Malaysia which has been set to achieve a 70% share of all travels by public transport in the city area. However, the current modal split between the public transport and private transport is 15:85. In order to understand travelers' willingness to use the public transport, a conceptual model has been developed to determine the factors that affect them to use the public transport instead of travelling in their own cars. Various variables such as service quality, environmental impact, attitude, and behavior intention were analyzed and tested using structural equation model (SEM). Results indicate that the service quality and attitude are found to have positive effects on the behavioral intention of taking the public transport. Other than this, this study also shows that the service quality and environmental impact have some positive influences on the attitude to using the public transport. However, environmental impact has no significant, positive, and direct effect on behavioral intention. The results of this study demonstrate that the model that was developed is useful in predicting the public transport and it could provide a more complete understanding of behavioral intention towards public transport use.

Human health impacts of biodiesel use in on-road heavy duty diesel vehicles in Canada.

PubMed

Rouleau, Mathieu; Egyed, Marika; Taylor, Brett; Chen, Jack; Samaali, Mehrez; Davignon, Didier; Morneau, Gilles

2013-11-19

Regulatory requirements for renewable content in diesel fuel have been adopted in Canada. Fatty acid alkyl esters, that is, biodiesel, will likely be used to meet the regulations. However, the impacts on ambient atmospheric pollutant concentrations and human health outcomes associated with the use of biodiesel fuel blends in heavy duty diesel vehicles across Canada have not been evaluated. The objective of this study was to assess the potential human health implications of the widespread use of biodiesel in Canada compared to those from ultralow sulfur diesel (ULSD). The health impacts/benefits resulting from biodiesel use were determined with the Air Quality Benefits Assessment Tool, based on output from the AURAMS air quality modeling system and the MOBILE6.2C on-road vehicle emissions model. Scenarios included runs for ULSD and biodiesel blends with 5 and 20% of biodiesel by volume, and compared their use in 2006 and 2020. Although modeling and data limitations exist, the results of this study suggested that the use of biodiesel fuel blends compared to ULSD was expected to result in very minimal changes in air quality and health benefits/costs across Canada, and these were likely to diminish over time.

Development of risk-based air quality management strategies under impacts of climate change.

PubMed

Liao, Kuo-Jen; Amar, Praveen; Tagaris, Efthimios; Russell, Armistead G

2012-05-01

Climate change is forecast to adversely affect air quality through perturbations in meteorological conditions, photochemical reactions, and precursor emissions. To protect the environment and human health from air pollution, there is an increasing recognition of the necessity of developing effective air quality management strategies under the impacts of climate change. This paper presents a framework for developing risk-based air quality management strategies that can help policy makers improve their decision-making processes in response to current and future climate change about 30-50 years from now. Development of air quality management strategies under the impacts of climate change is fundamentally a risk assessment and risk management process involving four steps: (1) assessment of the impacts of climate change and associated uncertainties; (2) determination of air quality targets; (3) selections of potential air quality management options; and (4) identification of preferred air quality management strategies that minimize control costs, maximize benefits, or limit the adverse effects of climate change on air quality when considering the scarcity of resources. The main challenge relates to the level of uncertainties associated with climate change forecasts and advancements in future control measures, since they will significantly affect the risk assessment results and development of effective air quality management plans. The concept presented in this paper can help decision makers make appropriate responses to climate change, since it provides an integrated approach for climate risk assessment and management when developing air quality management strategies. Development of climate-responsive air quality management strategies is fundamentally a risk assessment and risk management process. The risk assessment process includes quantification of climate change impacts on air quality and associated uncertainties. Risk management for air quality under the impacts of climate change includes determination of air quality targets, selections of potential management options, and identification of effective air quality management strategies through decision-making models. The risk-based decision-making framework can also be applied to develop climate-responsive management strategies for the other environmental dimensions and assess costs and benefits of future environmental management policies.

Dimethylsulfide Chemistry: Annual, Seasonal, and Spatial Impacts on Sulfate

EPA Science Inventory

We incorporated oceanic emissions and atmospheric chemistry of dimethylsulfide (DMS) into the hemispheric Community Multiscale Air Quality model and performed annual model simulations without and with DMS chemistry. The model without DMS chemistry predicts higher concentrations o...

Transport of Aerosols: Regional and Global Implications for Climate, Weather, and Air Quality

NASA Technical Reports Server (NTRS)

Chin, Mian; Diehl, Thomas; Yu, Hongbin; Bian, Huisheng; Remer, Lorraine; Kahn, Ralph

2008-01-01

Long-range transport of atmospheric aerosols can have a significant impact on global climate, regional weather, and local air quality. In this study, we use a global model GOCART together with satellite data and ground-based measurements to assess the emission and transport of pollution, dust, biomass burning, and volcanic aerosols and their implications. In particular, we will show the impact of emissions and long-range transport of aerosols from major pollution and dust source regions to (1) the surface air quality, (2) the atmospheric heating rates, and (3) surface radiation change near the source and downwind regions.

Impact simulation of shrimp farm effluent on BOD-DO in Setiu River

NASA Astrophysics Data System (ADS)

Chong, Michael Sueng Lock; Teh, Su Yean; Koh, Hock Lye

2017-08-01

Release of effluent from intensive aquaculture farms into a river can pollute the receiving river and exert negative impacts on the aquatic ecosystem. In this paper, we simulate the effects of effluent released from a marine shrimp aquaculture farm into Sg Setiu, focusing on two critical water quality parameters i.e. DO (dissolved oxygen) and BOD (biochemical oxygen demand). DO is an important constituent in a river in sustaining water quality, with levels of DO below 5 mg/L deemed undesirable. DO levels can be depressed by the presence of BOD and other organics that consume DO. Water quality simulations in conjunction with management of effluent treatment can suggest mitigation measures for reducing the adverse environmental impact. For this purpose, an in-house two-dimensional water quality simulation model codenamed TUNA-WQ will be used for these simulations. TUNA-WQ has been undergoing regular updates and improvements to broaden the applicability and to improve the robustness. Here, the model is calibrated and verified for simulation of DO and BOD dynamics in Setiu River (Sg Setiu). TUNA-WQ simulated DO and BOD in Setiu River due to the discharge from a marine shrimp aquaculture farm will be presented.

The Impact of Cloud Correction on the Redistribution of Reactive Nitrogen Species

NASA Astrophysics Data System (ADS)

Pour Biazar, A.; McNider, R. T.; Doty, K.; Cameron, R.

2007-12-01

Clouds are particularly important to air quality. Yet, correct prediction of clouds in time and space remains to be a great challenge for the air quality models. One aspect of cloud impact on air quality is the modification of photolysis reaction rates by clouds. Clouds can significantly alter the solar radiation in the wavelengths affecting the photolysis rates. Such modifications significantly impact atmospheric photochemistry and alter the chemical composition of the boundary layer. It also alters the partitioning of chemical compounds by creating a new equilibrium state. Since air quality models are often being used for air quality and emission reduction assessment, understanding the uncertainty caused by inaccurate cloud prediction is imperative. In this study we investigate the radiative impact of clouds in altering the partitioning of nitrogen species in the emission source regions. Such alterations affect the local nitrogen budget and thereby alter the atmospheric composition within the boundary layer. The results from two model simulations, one in which the model predicted clouds are used (control), and the other in which the satellite observed clouds have been assimilated in the model were analyzed. We use satellite retrieved cloud transmissivity, cloud top height, and observed cloud fraction to correct photolysis rates for cloud cover in the Community Multiscale Air Quality (CMAQ) modeling system. The simulations were performed at 4- and 12-km resolution domains over Texas, extending east to Mississippi, for the period of August 24 to August 31, 2000. The results clearly indicate that not using the cloud observations in the model can drastically alter the predicted atmospheric chemical composition within the boundary layer and exaggerate or under-predict the ozone concentrations. Cloud impact is acute and more pronounced over the emission source regions and can lead to drastic errors in the model predictions of ozone and its precursors. Clouds also increased the lifetime of ozone precursors leading to their transport out of the source regions and caused further ozone production downwind. The longer lifetimes for NOx and its transport over regions high in biogenic hydrocarbon emissions (in the eastern part of the domain) led to increased ozone production that was missing in the control simulation. An indirect impact of the clouds in the emission source areas is the alteration in partitioning of nitrogen oxides and the impact on nitrogen budget due to surface removal. This is caused by the disparity between the deposition velocity of NOx and the nitrates that are produced from oxidation of NOx. Under clear skies, NOx undergoes a chemical transformation and produces nitrates such as HNO3 and PAN. In the presence of thick clouds, due to the reduction in the photochemical activities, nitrogen monoxide (NO) rapidly consumes ozone (O3) and produces nitrogen dioxide (NO2) while the production of HNO3 and loss of NOx due to chemical transformation is reduced. Therefore, in one case there is more loss of nitrogen in the vicinity of emission sources. A detailed analysis of two emission source regions, Houston-Galveston and New Orleans area, will be presented. Acknowledgments. This work was accomplished under partial support from Cooperative Agreement between the University of Alabama in Huntsville and the Minerals Management Service on the Gulf of Mexico Issues.

Modeling multi-scale aerosol dynamics and micro-environmental air quality near a large highway intersection using the CTAG model.

PubMed

Wang, Yan Jason; Nguyen, Monica T; Steffens, Jonathan T; Tong, Zheming; Wang, Yungang; Hopke, Philip K; Zhang, K Max

2013-01-15

A new methodology, referred to as the multi-scale structure, integrates "tailpipe-to-road" (i.e., on-road domain) and "road-to-ambient" (i.e., near-road domain) simulations to elucidate the environmental impacts of particulate emissions from traffic sources. The multi-scale structure is implemented in the CTAG model to 1) generate process-based on-road emission rates of ultrafine particles (UFPs) by explicitly simulating the effects of exhaust properties, traffic conditions, and meteorological conditions and 2) to characterize the impacts of traffic-related emissions on micro-environmental air quality near a highway intersection in Rochester, NY. The performance of CTAG, evaluated against with the field measurements, shows adequate agreement in capturing the dispersion of carbon monoxide (CO) and the number concentrations of UFPs in the near road micro-environment. As a proof-of-concept case study, we also apply CTAG to separate the relative impacts of the shutdown of a large coal-fired power plant (CFPP) and the adoption of the ultra-low-sulfur diesel (ULSD) on UFP concentrations in the intersection micro-environment. Although CTAG is still computationally expensive compared to the widely-used parameterized dispersion models, it has the potential to advance our capability to predict the impacts of UFP emissions and spatial/temporal variations of air pollutants in complex environments. Furthermore, for the on-road simulations, CTAG can serve as a process-based emission model; Combining the on-road and near-road simulations, CTAG becomes a "plume-in-grid" model for mobile emissions. The processed emission profiles can potentially improve regional air quality and climate predictions accordingly. Copyright © 2012 Elsevier B.V. All rights reserved.

Regional impacts of oil and gas development on ozone formation in the western United States.

PubMed

Rodriguez, Marco A; Barna, Michael G; Moore, Tom

2009-09-01

The Intermountain West is currently experiencing increased growth in oil and gas production, which has the potential to affect the visibility and air quality of various Class I areas in the region. The following work presents an analysis of these impacts using the Comprehensive Air Quality Model with extensions (CAMx). CAMx is a state-of-the-science, "one-atmosphere" Eulerian photochemical dispersion model that has been widely used in the assessment of gaseous and particulate air pollution (ozone, fine [PM2.5], and coarse [PM10] particulate matter). Meteorology and emissions inventories developed by the Western Regional Air Partnership Regional Modeling Center for regional haze analysis and planning are used to establish an ozone baseline simulation for the year 2002. The predicted range of values for ozone in the national parks and other Class I areas in the western United States is then evaluated with available observations from the Clean Air Status and Trends Network (CASTNET). This evaluation demonstrates the model's suitability for subsequent planning, sensitivity, and emissions control strategy modeling. Once the ozone baseline simulation has been established, an analysis of the model results is performed to investigate the regional impacts of oil and gas development on the ozone concentrations that affect the air quality of Class I areas. Results indicate that the maximum 8-hr ozone enhancement from oil and gas (9.6 parts per billion [ppb]) could affect southwestern Colorado and northwestern New Mexico. Class I areas in this region that are likely to be impacted by increased ozone include Mesa Verde National Park and Weminuche Wilderness Area in Colorado and San Pedro Parks Wilderness Area, Bandelier Wilderness Area, Pecos Wilderness Area, and Wheeler Peak Wilderness Area in New Mexico.

Review of nitrogen fate models applicable to forest landscapes in the Southern U.S.

Treesearch

D. M. Amatya; C. G. Rossi; A. Saleh; Z. Dai; M. A. Youssef; R. G. Williams; D. D. Bosch; G. M. Chescheir; G. Sun; R. W. Skaggs; C. C. Trettin; E. D. Vance; J. E. Nettles; S. Tian

2013-01-01

Assessing the environmental impacts of fertilizer nitrogen (N) used to increase productivity in managed forests is complex due to a wide range of abiotic and biotic factors affecting its forms and movement. Models developed to predict fertilizer N fate (e.g., cycling processes) and water quality impacts vary widely in their design, scope, and potential application. We...

Comparative Evaluation of the Impact of WRF-NMM and WRF-ARW Meteorology on CMAQ Simulations for O3 and Related Species During the 2006 TexAQS/GoMACCS Campaign

EPA Science Inventory

In this paper, impact of meteorology derived from the Weather, Research and Forecasting (WRF)– Non–hydrostatic Mesoscale Model (NMM) and WRF–Advanced Research WRF (ARW) meteorological models on the Community Multiscale Air Quality (CMAQ) simulations for ozone and its related prec...

Insights on the impact of systematic model errors on data assimilation performance in changing catchments

NASA Astrophysics Data System (ADS)

Pathiraja, S.; Anghileri, D.; Burlando, P.; Sharma, A.; Marshall, L.; Moradkhani, H.

2018-03-01

The global prevalence of rapid and extensive land use change necessitates hydrologic modelling methodologies capable of handling non-stationarity. This is particularly true in the context of Hydrologic Forecasting using Data Assimilation. Data Assimilation has been shown to dramatically improve forecast skill in hydrologic and meteorological applications, although such improvements are conditional on using bias-free observations and model simulations. A hydrologic model calibrated to a particular set of land cover conditions has the potential to produce biased simulations when the catchment is disturbed. This paper sheds new light on the impacts of bias or systematic errors in hydrologic data assimilation, in the context of forecasting in catchments with changing land surface conditions and a model calibrated to pre-change conditions. We posit that in such cases, the impact of systematic model errors on assimilation or forecast quality is dependent on the inherent prediction uncertainty that persists even in pre-change conditions. Through experiments on a range of catchments, we develop a conceptual relationship between total prediction uncertainty and the impacts of land cover changes on the hydrologic regime to demonstrate how forecast quality is affected when using state estimation Data Assimilation with no modifications to account for land cover changes. This work shows that systematic model errors as a result of changing or changed catchment conditions do not always necessitate adjustments to the modelling or assimilation methodology, for instance through re-calibration of the hydrologic model, time varying model parameters or revised offline/online bias estimation.

Climate Adaptation Capacity for Conventional Drinking Water Treatment Facilities

NASA Astrophysics Data System (ADS)

Levine, A.; Goodrich, J.; Yang, J.

2013-12-01

Water supplies are vulnerable to a host of climate- and weather-related stressors such as droughts, intense storms/flooding, snowpack depletion, sea level changes, and consequences from fires, landslides, and excessive heat or cold. Surface water resources (lakes, reservoirs, rivers, and streams) are especially susceptible to weather-induced changes in water availability and quality. The risks to groundwater systems may also be significant. Typically, water treatment facilities are designed with an underlying assumption that water quality from a given source is relatively predictable based on historical data. However, increasing evidence of the lack of stationarity is raising questions about the validity of traditional design assumptions, particularly since the service life of many facilities can exceed fifty years. Given that there are over 150,000 public water systems in the US that deliver drinking water to over 300 million people every day, it is important to evaluate the capacity for adapting to the impacts of a changing climate. Climate and weather can induce or amplify changes in physical, chemical, and biological water quality, reaction rates, the extent of water-sediment-air interactions, and also impact the performance of treatment technologies. The specific impacts depend on the watershed characteristics and local hydrological and land-use factors. Water quality responses can be transient, such as erosion-induced increases in sediment and runoff. Longer-term impacts include changes in the frequency and intensity of algal blooms, gradual changes in the nature and concentration of dissolved organic matter, dissolved solids, and modulation of the microbiological community structure, sources and survival of pathogens. In addition, waterborne contaminants associated with municipal, industrial, and agricultural activities can also impact water quality. This presentation evaluates relationships between climate and weather induced water quality variability and the capacity of treatment facilities and supporting water infrastructure to deliver safe drinking water consistently and reliably. Simulation models of water treatment facilities are used to evaluate the outcome of specific source water quality scenarios on treatment system performance and reliability. Modeling results are used to evaluate the process and operational capacity to respond to transient water quality changes and adapt to longer-term variability in water quality and availability. In some cases, changes in temperature and mineral content serve to improve the overall treatment performance. In addition, the integration of microbially enhanced treatment systems such as biological filtration can provide additional capacity. Conversely, changes in the nutrient and temperature dynamics can trigger algal and cyanobacterial blooms that can impair performance. Research needs are identified and the importance of developing more integrated modeling systems is highlighted.

Using the Community Multiscale Air Quality (CMAQ) model to estimate public health impacts of PM2.5 from individual power plants.

PubMed

Buonocore, Jonathan J; Dong, Xinyi; Spengler, John D; Fu, Joshua S; Levy, Jonathan I

2014-07-01

We estimated PM2.5-related public health impacts/ton emitted of primary PM2.5, SO2, and NOx for a set of power plants in the Mid-Atlantic and Lower Great Lakes regions of the United States, selected to include varying emission profiles and broad geographic representation. We then developed a regression model explaining variability in impacts per ton emitted using the population distributions around each plant. We linked outputs from the Community Multiscale Air Quality (CMAQ) model v 4.7.1 with census data and concentration-response functions for PM2.5-related mortality, and monetized health estimates using the value-of-statistical-life. The median impacts for the final set of plants were $130,000/ton for primary PM2.5 (range: $22,000-230,000), $28,000/ton for SO2 (range: $19,000-33,000), and $16,000/ton for NOx (range: $7100-26,000). Impacts of NOx were a median of 34% (range: 20%-75%) from ammonium nitrate and 66% (range: 25%-79%) from ammonium sulfate. The latter pathway is likely from NOx enhancing atmospheric oxidative capacity and amplifying sulfate formation, and is often excluded. Our regression models explained most of the variation in impact/ton estimates using basic population covariates, and can aid in estimating impacts averted from interventions such as pollution controls, alternative energy installations, or demand-side management. Copyright © 2014 Elsevier Ltd. All rights reserved.

Can high quality overcome consumer resistance to restricted provider access? Evidence from a health plan choice experiment.

PubMed

Harris, Katherine M

2002-06-01

To investigate the impact of quality information on the willingness of consumers to enroll in health plans that restrict provider access. A survey administered to respondents between the ages of 25 and 64 in the West Los Angeles area with private health insurance. An experimental approach is used to measure the effect of variation in provider network features and information about the quality of network physicians on hypothetical plan choices. Conditional logit models are used to analyze the experimental choice data. Next, choice model parameter estimates are used to simulate the impact of changes in plan features on the market shares of competing health plans and to calculate the quality level required to make consumers indifferent to changes in provider access. The presence of quality information reduced the importance of provider network features in plan choices as hypothesized. However, there were not statistically meaningful differences by type of quality measure (i.e., consumer assessed versus expert assessed). The results imply that large quality differences are required to make consumers indifferent to changes in provider access. The impact of quality on plan choices depended more on the particular measure and less on the type of measure. Quality ratings based on the proportion of survey respondents "extremely satisfied with results of care" had the greatest impact on plan choice while the proportion of network doctors "affiliated with university medical centers" had the least. Other consumer and expert assessed measures had more comparable effects. Overall the results provide empirical evidence that consumers are willing to trade high quality for restrictions on provider access. This willingness to trade implies that relatively small plans that place restrictions on provider access can successfully compete against less restrictive plans when they can demonstrate high quality. However, the results of this study suggest that in many cases, the level of quality required for consumers to accept access restrictions may be so high as to be unattainable. The results provide empirical support for the current focus of decision support efforts on consumer assessed quality measures. At the same time, however, the results suggest that consumers would also value quality measures based on expert assessments. This finding is relevant given the lack of comparative quality information based on expert judgment and research suggesting that consumers have apprehensions about their ability to meaningfully interpret performance-based quality measures.

Predicting Air Quality Impacts Associated with Oil and Gas Development in the Uinta Basin Using EPA’s Photochemical Air Quality Model

EPA Science Inventory

Rural areas with close proximity to oil and natural gas operations in Utah have experienced winter ozone levels that exceed EPA’s National Ambient Air Quality Standards (NAAQS). Through a collaborative effort, EPA Region 8 – Air Program, ORD, and OAQPS used the Commun...

Parental Sleep Quality and Behavior Problems of Children with Autism

ERIC Educational Resources Information Center

Mihaila, Iulia; Hartley, Sigan L.

2018-01-01

This study explored the impact of parental sleep quality on the experience of behavior problems by children with autism spectrum disorder. A 14-day daily diary was used in a sample of 176 mother-father couples. Dyadic multilevel models were conducted to examine the between-person and within-person effects of previous-night sleep quality on…

The Operation Mechanisms of External Quality Assurance Frameworks of Foreign Higher Education and Implications for Graduate Education

ERIC Educational Resources Information Center

Lin, Mengquan; Chang, Kai; Gong, Le

2016-01-01

The higher education quality evaluation and assurance frameworks and their operating mechanisms of countries such as the United Kingdom, France, and the United States show that higher education systems, traditional culture, and social background all impact quality assurance operating mechanisms. A model analysis of these higher education quality…

Predicting Software Suitability Using a Bayesian Belief Network

NASA Technical Reports Server (NTRS)

Beaver, Justin M.; Schiavone, Guy A.; Berrios, Joseph S.

2005-01-01

The ability to reliably predict the end quality of software under development presents a significant advantage for a development team. It provides an opportunity to address high risk components earlier in the development life cycle, when their impact is minimized. This research proposes a model that captures the evolution of the quality of a software product, and provides reliable forecasts of the end quality of the software being developed in terms of product suitability. Development team skill, software process maturity, and software problem complexity are hypothesized as driving factors of software product quality. The cause-effect relationships between these factors and the elements of software suitability are modeled using Bayesian Belief Networks, a machine learning method. This research presents a Bayesian Network for software quality, and the techniques used to quantify the factors that influence and represent software quality. The developed model is found to be effective in predicting the end product quality of small-scale software development efforts.

Understanding the impact of recent advances in isoprene photooxidation on simulations of regional air quality

EPA Science Inventory

The CMAQ (Community Multiscale Air Quality) us model in combination with observations for INTEX-NA/ICARTT (Intercontinental Chemical Transport Experiment–North America/International Consortium for Atmospheric Research on Transport and Transformation) 2004 are used to evalua...

Assessing the Impacts of Land Use Change from Cotton to Perennial Bioenergy Grasses on Hydrological Fluxes and Water Quality in a Semi-Arid Agricultural Watershed Using the APEX Model

NASA Astrophysics Data System (ADS)

Chen, Y.; Ale, S.; Rajan, N.

2015-12-01

The semi-arid Texas High Plains (THP) region, where cotton (Gossypium hirsutum L.) is grown in vast acreage, has the potential to grow perennial bioenergy grasses. A change in land use from cotton cropping systems to perennial grasses such as Alamo switchgrass (Panicum virgatum L.) and Miscanthus giganteus (Miscanthus sinensis Anderss. [Poaceae]) can significantly affect regional hydrologic cycle and water quality. Assessing the impacts of this potential land use change on hydrology and water quality enables the environmental assessment of feasibility to grow perennial grasses in this region to meet the U.S. national bioenergy target of 2022. The Agricultural Policy/Environmental eXtender (APEX) model was used in this study to assess the impacts of replacing cotton with switchgrass and Miscanthus on water and nitrogen balances in the upstream subwatershed of the Double Mountain Fork Brazos watershed in the THP, which contains 52% cotton land use. The APEX model was initially calibrated against observed streamflow and crop yield data. Since observed data on nitrogen loads in streamflow was not available for this subwatershed, we calibrated the APEX model against the SWAT-simulated nitrogen loads at the outlet of this subwatershed, which were obtained in a parallel study. The calibrated APEX model was used to simulate the impacts of land use change from cotton to Miscanthus and switchgrass on surface and subsurface water and nitrogen balances. Preliminary results revealed that the average (1994-2009) annual surface runoff decreased by 84% and 66% under the irrigated and dryland switchgrass scenarios compared to the baseline scenarios. Average annual percolation increased by 106% and 57% under the irrigated and dryland switchgrass scenarios relative to the baseline scenarios. Preliminary results also indicated Miscanthus and switchgrass appeared to be superior to cotton in terms of better water conservation and water quality, and minimum crop management requirements.

The dual threat of urbanisation and climate change in urbanising catchments - integrated science to meet future challenges - a case study of the Thames catchment, United Kingdom.

NASA Astrophysics Data System (ADS)

Miller, J.; Hutchins, M.; McGrane, S. J.; Kjeldsen, T. R.; Rowland, C.; Hagen-Zanker, A.; Rickards, N. J.; Fidal, J.; Vesuviano, G.; Hitt, O.

2016-12-01

Rapid urbanisation coupled with climate change poses a significant threat of increased flooding in urban locations around the world. In the UK there is a lack of joined up science and monitoring data to support model development and management decisions required for a rapidly growing population. Here, we present the findings from a multi-disciplinary research project entitled POLLCURB involving a combination of both monitoring and modelling approaches, including participatory citizen science, to evaluate impacts of urbanisation and climate change on flooding and water quality in the Thames basin, United Kingdom. Empirical analysis of five years of monitoring data in intensely monitored sub-catchments reveals the degree to which urban land-use impacts upon hydrological and water quality response. Analysis reveals hydrological impacts do not always follow the expected urban gradient due to intra-catchment differences in hydraulic functions. Statistical detection and attribution techniques are used to assess long-term river data, highlighting strong signals of urban growth after climate variability is accounted for. Historical land-use change mapping of the Thames basin using remote sensing shows growth in urban coverage from around 13% (1980's) to 15% (2015) and was used to develop and train a cellular automata model. Projections of a business-as-usual scenario indicates future growth of 12% by 2035. Future potential changes to flooding and water quality are assessed under urbanisation and climate scenarios for the Thames region to provide comparative and cumulative analysis of how these drivers will affect existing and new urban areas within the Thames basin. Results show the relative and cumulative impacts that both urbanisation and climate change have on basin hydrology and water quality, and highlight the improvements in modelling accuracy when utilising high-resolution data. Discussion is made of results in relation to modelling, policy, mitigation options, and implications for further scientific research.

Impact of dental caries on quality of life among preschool children: emphasis on the type of tooth and stages of progression.

PubMed

Ramos-Jorge, Joana; Alencar, Bruna Mota; Pordeus, Isabela Almeida; Soares, Maria Eliza da Consolação; Marques, Leandro Silva; Ramos-Jorge, Maria Letícia; Paiva, Saul Martins

2015-04-01

The aim of this cross-sectional study was to evaluate the impact of dental caries on the quality of life of preschool children and their parents/caretakers, with an emphasis on the type of tooth and stage of progression. A randomly selected sample of preschool children, 3-5 yrs of age, underwent an oral examination for the assessment of dental caries using the International Caries Detection and Assessment System II (ICDAS II) criteria. Parents/caretakers answered two questionnaires, one on the oral health-related quality of life (OHRQoL) of the child [the Early Childhood Oral Health Impact Scale (ECOHIS)], and the other on the socio-economic characteristics of the family. Statistical analyses were performed using the chi-square test, Kruskal-Wallis test, Mann-Whitney U-test, and Poisson regression. A total of 451 preschool children participated in the study. The majority of carious lesions exhibited severe decay (60.6%) and were found in both anterior (incisors/canines) and posterior (molars) teeth. The final Poisson model revealed negative impacts on quality of life from more advanced stages of dental caries, both in incisors/canines and molars. Child's age and household income were also associated with impact on quality of life. Carious lesions in more advanced stages of progression in anterior and posterior teeth were associated with a negative impact on the quality of life of preschool children. © 2014 Eur J Oral Sci.

Integrated impact assessment of climate change, land use, and adaptation policies on water quality in Austria

NASA Astrophysics Data System (ADS)

Trautvetter, Helen; Schoenhart, Martin; Parajaka, Juraj; Schmid, Erwin; Zessner, Matthias

2017-04-01

Climate change is one of the major challenges of our time and adds considerable stress to the human society and environment. A change in climate will not only shift general weather patterns, but might also increase the recurrence of extreme weather events such as drought and heavy rainfall. These changes in climatic conditions will affect the quality and quantity of water resources both directly as well as indirectly through autonomous adaptation by farmers (e.g. cultivar choices, fertilization intensity or soil management). This will influence the compliance with the good ecological and chemical status according to the EU Water Framework Directive. We present results from an integrated impact modelling framework (IIMF) to tackle those direct and indirect impacts and analyze policy options for planned adaptation in agricultural land use and sustainable management of land and water resources until 2040. The IIMF is the result of an interdisciplinary collaboration among economists, agronomists, and hydrologists. It consists of the bio-physical process model EPIC, the regional land use optimization model PASMA[grid], the quantitative precipitation/runoff TUWmodel and the surface water emission model MONERIS. Scenarios have been developed and parameterized in collaboration with stakeholders in order to facilitate multi-actor knowledge transfer. The set of climate change scenarios until 2040 includes three scenarios with equal temperature changes but varying precipitation patterns. They are combined with potential socio-economic and policy development. The latter include water protection measures on fertilization management, soil management, or crop rotation choices. We will presented the development of interfaces among the research, the definition of scenarios and major scenario results for Austria. We will focus on nutrient emissions to surface waters, which are the major link between the different models. The results, available at watershed level indicate the significant impact on future precipitation development on the risk of not achieving nutrient criteria of the good ecological water quality status of surface waters. Policy measures show relatively low impacts for nitrogen, while they may highly affect the phosphorus emissions and hence the compliance with environmental quality standards for phosphate phosphorus.

An Integrated Environmental Assessment Model for Oil Shale Development

NASA Astrophysics Data System (ADS)

Pasqualini, D.; Witkowski, M. S.; Keating, G. N.; Ziock, H.; Wolfsberg, A. V.

2008-12-01

Due to the rising prices of conventional fuel, unconventional fossil fuels such as oil shale, tar sands, and coal to liquid have gained attention as an energy resource. The largest reserve of oil shale in the world is located in the western interior of North America, and includes parts of Colorado, Utah, and Wyoming. Development of oil shale in this area could reduce or eliminate the U.S. dependence on foreign fuel sources. However, oil shale production carries a number of potential environmental impacts. Fuel production associated with oil shale will create increasing competition for limited resources such as water, while potentially negatively impacting air quality, water quality, habitat, and wildlife. Water use, wastewater management, greenhouse gas emissions, air pollution, and land use are the main environmental issues that oil shale production involves. A proper analysis of the interrelationships between these factors and those of the new energy needs required for production is necessary to avoid serious negative impacts to the environment and the economies. We have developed a system dynamics integrated assessment model to evaluate potential fuel production capacity from oil shale within the limits of environmental quality, land use, and economics. Recognizing that the impacts of oil shale development are the outcomes of a complex process that involve water, energy, climate, social pressures, economics, regulations, technical advances, etc., and especially their couplings and feedbacks, we developed our model using the system dynamics (SD) modeling approach. Our SD model integrates all of these components and allows us to analyze the interdependencies among them. Our initial focus has been to address industry, regulator, and stakeholder concerns regarding the quantification and management of carbon and water resources impacts. The model focuses on oil shale production in the Piceance Basin in Colorado, but is inherently designed to be extendable to larger regions, levels of production, and different unconventional fuels.

Development of alternative sulfur dioxide control strategies for a metropolitan area and its environs, utilizing a modified climatological dispersion model

Treesearch

K. J. Skipka; D. B. Smith

1977-01-01

Alternative control strategies were developed for achieving compliance with ambient air quality standards in Portland, Maine, and its environs, using a modified climatological dispersion model (CDM) and manipulating the sulfur content of the fuel oil consumed in four concentric zones. Strategies were evaluated for their impact on ambient air quality, economics, and...

One-dimensional and two-dimensional hydrodynamic modelling derived flow properties: Impacts on aquatic habitat quality predictions

Treesearch

Rohan Benjankar; Daniele Tonina; James McKean

2014-01-01

Studies of the effects of hydrodynamic model dimensionality on simulated flow properties and derived quantities such as aquatic habitat quality are limited. It is important to close this knowledge gap especially now that entire river networks can be mapped at the microhabitat scale due to the advent of point-cloud techniques. This study compares flow properties, such...

Are extreme hydro-meteorological events a prerequisite for extreme water quality impacts? Exploring climate impacts on inland and coastal waters

NASA Astrophysics Data System (ADS)

Michalak, A. M.; Balaji, V.; Del Giudice, D.; Sinha, E.; Zhou, Y.; Ho, J. C.

2017-12-01

Questions surrounding water sustainability, climate change, and extreme events are often framed around water quantity - whether too much or too little. The massive impacts of extreme water quality impairments are equally compelling, however. Recent years have provided a host of compelling examples, with unprecedented harmful algal blooms developing along the West coast, in Utah Lake, in Lake Erie, and off the Florida coast, and huge hypoxic dead zones continuing to form in regions such as Lake Erie, the Chesapeake Bay, and the Gulf of Mexico. Linkages between climate change, extreme events, and water quality impacts are not well understood, however. Several factors explain this lack of understanding, including the relative complexity of underlying processes, the spatial and temporal scale mismatch between hydrologists and climatologists, and observational uncertainty leading to ambiguities in the historical record. Here, we draw on a number of recent studies that aim to quantitatively link meteorological variability and water quality impacts to test the hypothesis that extreme water quality impairments are the result of extreme hydro-meteorological events. We find that extreme hydro-meteorological events are neither always a necessary nor a sufficient condition for the occurrence of extreme water quality impacts. Rather, extreme water quality impairments often occur in situations where multiple contributing factors compound, which complicates both attribution of historical events and the ability to predict the future incidence of such events. Given the critical societal importance of water quality projections, a concerted program of uncertainty reduction encompassing observational and modeling components will be needed to examine situations where extreme weather plays an important, but not solitary, role in the chain of cause and effect.

Project ATLANTA (Atlanta Land use Analysis: Temperature and Air Quality): Use of Remote Sensing and Modeling to Analyze How Urban Land Use Change Affects Meteorology and Air Quality Through Time

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.; Estes, Maurice G., Jr.

1999-01-01

This paper presents an overview of Project ATLANTA (ATlanta Land use ANalysis: Temperature and Air-quality) which is an investigation that seeks to observe, measure, model, and analyze how the rapid growth of the Atlanta, Georgia metropolitan area since the early 1970's has impacted the region's climate and air quality. The primary objectives for this research effort are: (1) To investigate and model the relationships between land cover change in the Atlanta metropolitan, and the development of the urban heat island phenomenon through time; (2) To investigate and model the temporal relationships between Atlanta urban growth and land cover change on air quality; and (3) To model the overall effects of urban development on surface energy budget characteristics across the Atlanta urban landscape through time. Our key goal is to derive a better scientific understanding of how land cover changes associated with urbanization in the Atlanta area, principally in transforming forest lands to urban land covers through time, has, and will, effect local and regional climate, surface energy flux, and air quality characteristics. Allied with this goal is the prospect that the results from this research can be applied by urban planners, environmental managers and other decision-makers, for determining how urbanization has impacted the climate and overall environment of the Atlanta area. Multiscaled remote sensing data, particularly high resolution thermal infrared data, are integral to this study for the analysis of thermal energy fluxes across the Atlanta urban landscape.

Impacts of potential CO2-reduction policies on air quality in the United States.

PubMed

Trail, Marcus A; Tsimpidi, Alexandra P; Liu, Peng; Tsigaridis, Kostas; Hu, Yongtao; Rudokas, Jason R; Miller, Paul J; Nenes, Athanasios; Russell, Armistead G

2015-04-21

Impacts of emissions changes from four potential U.S. CO2 emission reduction policies on 2050 air quality are analyzed using the community multiscale air quality model (CMAQ). Future meteorology was downscaled from the Goddard Institute for Space Studies (GISS) ModelE General Circulation Model (GCM) to the regional scale using the Weather Research Forecasting (WRF) model. We use emissions growth factors from the EPAUS9r MARKAL model to project emissions inventories for two climate tax scenarios, a combined transportation and energy scenario, a biomass energy scenario and a reference case. Implementation of a relatively aggressive carbon tax leads to improved PM2.5 air quality compared to the reference case as incentives increase for facilities to install flue-gas desulfurization (FGD) and carbon capture and sequestration (CCS) technologies. However, less capital is available to install NOX reduction technologies, resulting in an O3 increase. A policy aimed at reducing CO2 from the transportation sector and electricity production sectors leads to reduced emissions of mobile source NOX, thus reducing O3. Over most of the U.S., this scenario leads to reduced PM2.5 concentrations. However, increased primary PM2.5 emissions associated with fuel switching in the residential and industrial sectors leads to increased organic matter (OM) and PM2.5 in some cities.

Assessment of economic and water quality impacts of land use change using a simple bioeconomic model.

PubMed

Bhattarai, Gandhi; Srivastava, Puneet; Marzen, Luke; Hite, Diane; Hatch, Upton

2008-07-01

The objective of this study is to assess the economic and water quality impact of land use change in a small watershed in the Wiregrass region of Alabama. The study compares changes in water quality and revenue from agricultural and timber production due to changes in land use between years 1992 and 2001. The study was completed in two stages. In the first stage, a biophysical model was used to estimate the effect of land use change on nitrogen and phosphorus runoff and sediment deposition in the main channel; in the second stage, farm enterprise budgeting tools were used to estimate the economic returns for the changes in land use condition. Both biophysical and economic results are discussed, and a case for complex optimization to develop a decision support system is presented.

Community Multiscale Air Quality (CMAQ) Modeling for Regional and Hemispheric Scales

EPA Science Inventory

The CMAQ model is a Eulerian model that produces gridded values of atmospheric concentration and deposition. Recent updates to the model are highlighted that impact estimates of dry and wet deposition of nitrogen, sulfur and base cations. Output from the CMAQ model is used in t...

Dimethylsulfide chemistry: annual, seasonal, and spatial impacts on SO_4^(2-)

EPA Science Inventory

We incorporated oceanic emissions and atmospheric chemistry of dimethylsulfide (DMS) into the hemispheric Community Multiscale Air Quality model and performed annual model simulations without and with DMS chemistry. The model without DMS chemistry predicts higher concentrations o...

Photovoltaic Impact Assessment of Smart Inverter Volt-VAR Control on Distribution System Conservation Voltage Reduction and Power Quality

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

Ding, Fei; Nagarajan, Adarsh; Chakraborty, Sudipta

This report presents an impact assessment study of distributed photovoltaic (PV) with smart inverter Volt-VAR control on conservation voltage reduction (CVR) energy savings and distribution system power quality. CVR is a methodology of flattening and lowering a distribution system voltage profile in order to conserve energy. Traditional CVR relies on operating utility voltage regulators and switched capacitors. However, with the increased penetration of distributed PV systems, smart inverters provide the new opportunity to control local voltage and power factor by regulating the reactive power output, leading to a potential increase in CVR energy savings. This report proposes a methodology tomore » implement CVR scheme by operating voltage regulators, capacitors, and autonomous smart inverter Volt-VAR control in order to achieve increased CVR benefit. Power quality is an important consideration when operating a distribution system, especially when implementing CVR. It is easy to measure the individual components that make up power quality, but a comprehensive method to incorporate all of these values into a single score has yet to be undertaken. As a result, this report proposes a power quality scoring mechanism to measure the relative power quality of distribution systems using a single number, which is aptly named the 'power quality score' (PQS). Both the CVR and PQS methodologies were applied to two distribution system models, one obtained from the Hawaiian Electric Company (HECO) and another obtained from Pacific Gas and Electric (PG&E). These two models were converted to the OpenDSS platform using previous model conversion tools that were developed by NREL. Multiple scenarios including various PV penetration levels and smart inverter densities were simulated to analyze the impact of smart inverter Volt-VAR support on CVR energy savings and feeder power quality. In order to analyze the CVR benefit and PQS, an annual simulation was conducted for each scenario.« less

Short-term effects of air quality and thermal stress on non-accidental morbidity-a multivariate meta-analysis comparing indices to single measures.

PubMed

Lokys, Hanna Leona; Junk, Jürgen; Krein, Andreas

2018-01-01

Air quality and thermal stress lead to increased morbidity and mortality. Studies on morbidity and the combined impact of air pollution and thermal stress are still rare. To analyse the correlations between air quality, thermal stress and morbidity, we used a two-stage meta-analysis approach, consisting of a Poisson regression model combined with distributed lag non-linear models (DLNMs) and a meta-analysis investigating whether latitude or the number of inhabitants significantly influence the correlations. We used air pollution, meteorological and hospital admission data from 28 administrative districts along a north-south gradient in western Germany from 2001 to 2011. We compared the performance of the single measure particulate matter (PM10) and air temperature to air quality indices (MPI and CAQI) and the biometeorological index UTCI. Based on the Akaike information criterion (AIC), it can be shown that using air quality indices instead of single measures increases the model strength. However, using the UTCI in the model does not give additional information compared to mean air temperature. Interaction between the 3-day average of air quality (max PM10, max CAQI and max MPI) and meteorology (mean air temperature and mean UTCI) did not improve the models. Using the mean air temperature, we found immediate effects of heat stress (RR 1.0013, 95% CI: 0.9983-1.0043) and by 3 days delayed effects of cold stress (RR: 1.0184, 95% CI: 1.0117-1.0252). The results for air quality differ between both air quality indices and PM10. CAQI and MPI show a delayed impact on morbidity with a maximum RR after 2 days (MPI 1.0058, 95% CI: 1.0013-1.0102; CAQI 1.0068, 95% CI: 1.0030-1.0107). Latitude was identified as a significant meta-variable, whereas the number of inhabitants was not significant in the model.

Short-term effects of air quality and thermal stress on non-accidental morbidity—a multivariate meta-analysis comparing indices to single measures

NASA Astrophysics Data System (ADS)

Lokys, Hanna Leona; Junk, Jürgen; Krein, Andreas

2018-01-01

Air quality and thermal stress lead to increased morbidity and mortality. Studies on morbidity and the combined impact of air pollution and thermal stress are still rare. To analyse the correlations between air quality, thermal stress and morbidity, we used a two-stage meta-analysis approach, consisting of a Poisson regression model combined with distributed lag non-linear models (DLNMs) and a meta-analysis investigating whether latitude or the number of inhabitants significantly influence the correlations. We used air pollution, meteorological and hospital admission data from 28 administrative districts along a north-south gradient in western Germany from 2001 to 2011. We compared the performance of the single measure particulate matter (PM10) and air temperature to air quality indices (MPI and CAQI) and the biometeorological index UTCI. Based on the Akaike information criterion (AIC), it can be shown that using air quality indices instead of single measures increases the model strength. However, using the UTCI in the model does not give additional information compared to mean air temperature. Interaction between the 3-day average of air quality (max PM10, max CAQI and max MPI) and meteorology (mean air temperature and mean UTCI) did not improve the models. Using the mean air temperature, we found immediate effects of heat stress (RR 1.0013, 95% CI: 0.9983-1.0043) and by 3 days delayed effects of cold stress (RR: 1.0184, 95% CI: 1.0117-1.0252). The results for air quality differ between both air quality indices and PM10. CAQI and MPI show a delayed impact on morbidity with a maximum RR after 2 days (MPI 1.0058, 95% CI: 1.0013-1.0102; CAQI 1.0068, 95% CI: 1.0030-1.0107). Latitude was identified as a significant meta-variable, whereas the number of inhabitants was not significant in the model.

Status Update on Translation of Integrated Primary Dental-Medical Care Delivery for Management of Diabetic Patients.

PubMed

Glurich, Ingrid; Nycz, Gregory; Acharya, Amit

2017-06-01

Escalating prevalence of both diabetes and periodontal disease, two diseases associated with bi-directional exacerbation, has been reported. Periodontal disease represents a modifiable risk factor that may reduce diabetes onset or progression, and integrated models of cross-disciplinary care are needed to establish and manage glycemic control in affected patients. An ad-hoc environmental scan of current literature and media sought to characterize factors impacting status of integrated care models based on review of the existing evidence base in literature and media surrounding: (1) current cross-disciplinary practice patterns, (2) epidemiological updates, (3) status on risk assessment and screening for dysglycemia in the dental setting, (4) status on implementation of quality metrics for oral health, (5) care model pilots, and (6) public health perspectives. The survey revealed: escalating prevalence of diabetes and periodontitis globally; greater emphasis on oral health assessment for diabetic patients in recent medical clinical practice guidelines; high knowledgeability surrounding oral-systemic impacts on diabetes and growing receptivity to medical-dental integration among medical and dental providers; increasing numbers of programs/studies reporting on positive impact of emerging integrated dental-medical care models on diabetic patient healthcare access and health outcomes; a growing evidence base for clinically significant rates of undiagnosed dysglycemia among dental patients reported by point-of-care pilot studies; no current recommendation for population-based screening for dysglycemia in dental settings pending a stronger evidence base; improved definition of true periodontitis prevalence in (pre)/diabetics; emerging recognition of the need for oral health quality indicators and tracking; evidence of persistence in dental access disparity; updated status on barriers to integration. The potential benefit of creating clinically-applicable integrated care models to support holistic management of an escalating diabetic population by targeting modifiable risk factors including periodontitis is being recognized by the health industry. Cross-disciplinary efforts supported by high quality research are needed to mitigate previously- and newly-defined barriers of care integration and expedite development and implementation of integrated care models in various practice settings. Implementation of quality monitoring in the dental setting will support definition of the impact and efficacy of interventional clinical care models on patient outcomes. © 2017 Marshfield Clinic.

Use of Structural Equation Modeling to Demonstrate the Differential Impact of Storage and Voiding Lower Urinary Tract Symptoms on Symptom Bother and Quality of Life during Treatment for Lower Urinary Tract Symptoms Associated with Benign Prostatic Hyperplasia.

PubMed

McVary, Kevin T; Peterson, Andrew; Donatucci, Craig F; Baygani, Simin; Henneges, Carsten; Clouth, Johannes; Wong, David; Oelke, Matthias

2016-09-01

Lower urinary tract symptoms associated with benign prostatic hyperplasia typically respond well to medical therapy. While changes in total I-PSS (International Prostate Symptom Score) are generally accepted as measurement for treatment response, I-PSS storage and voiding subscores may not accurately reflect the influence of symptom improvement on patient bother and quality of life. Structural equation modeling was done to evaluate physiological interrelationships measured by I-PSS storage vs voiding subscore questions and measure the magnitude of effects on bother using BII (Benign Prostatic Hyperplasia Impact Index) and quality of life on I-PSS quality of life questions. Pooled data from 4 randomized, controlled trials of tadalafil and placebo in 1,462 men with lower urinary tract symptoms/benign prostatic hyperplasia were used to investigate the relationship of storage vs voiding lower urinary tract symptoms on BII and quality of life. The final structural equation model demonstrated a sufficient fit to model interdependence of storage, voiding, bother and quality of life (probability for test of close fit <0.0001). Storage aspects had a twofold greater effect on voiding vs voiding aspects on storage (0.61 vs 0.28, each p <0.0001). The direct effect of storage on bother was twofold greater than voiding on bother (0.64 vs 0.29, each p <0.0001). Bother directly impacted quality of life by the largest magnitude of (-0.83), largely driven by storage lower urinary tract symptoms (p <0.0001). Total I-PSS is a reliable instrument to assess the therapeutic response in lower urinary tract symptoms/benign prostatic hyperplasia cases. However, an improvement in storage lower urinary tract symptoms is mainly responsible for improved bother and quality of life during treatment. Care should be taken when evaluating the accuracy of I-PSS subscores as indicators of the response to medical therapy. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Storm Water Management Model Reference Manual Volume II ...

EPA Pesticide Factsheets

SWMM is a dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. The runoff component of SWMM operates on a collection of subcatchment areas that receive precipitation and generate runoff and pollutant loads. The routing portion of SWMM transports this runoff through a system of pipes, channels, storage/treatment devices, pumps, and regulators. SWMM tracks the quantity and quality of runoff generated within each subcatchment, and the flow rate, flow depth, and quality of water in each pipe and channel during a simulation period comprised of multiple time steps. The reference manual for this edition of SWMM is comprised of three volumes. Volume I describes SWMM’s hydrologic models, Volume II its hydraulic models, and Volume III its water quality and low impact development models. This document provides the underlying mathematics for the hydraulic calculations of the Storm Water Management Model (SWMM)

Oil Palm expansion over Southeast Asia: land use change and air quality

NASA Astrophysics Data System (ADS)

Silva, S. J.; Heald, C. L.; Geddes, J.; Marlier, M. E.; Austin, K.; Kasibhatla, P. S.

2015-12-01

Over recent decades oil palm plantations have rapidly expanded across Southeast Asia (SEA). Much of this expansion has come at the expense of natural forests and grasslands. Aircraft measurements from a 2008 campaign, OP3, found that oil palm plantations emit as much as 7 times more isoprene than nearby natural forests. Furthermore, SEA is a rapidly developing region, with increasing urban population, and growing air quality concerns. Thus, SEA represents an ideal case study to examine the impacts of land use change on air quality in the region, and whether those changes can be detected from satellite observations of atmospheric composition. We investigate the impacts of historical and future oil palm expansion in SEA using satellite data, high-resolution land maps, and the chemical transport model GEOS-Chem. We examine the impact of palm plantations on surface-atmosphere processes (dry deposition, biogenic emissions). We show the sensitivity of air quality to current and future oil palm expansion scenarios, and discuss the limitations of current satellite measurements in capturing these changes. Our results indicate that while the impact of oil palm expansion on air quality can be significant, the retrieval error and sensitivity of the satellite measurements limit our ability to observe these impacts from space.

Impact of Expert Teaching Quality on Novice Academic Performance in the Jigsaw Cooperative Learning Method

NASA Astrophysics Data System (ADS)

Berger, Roland; Hänze, Martin

2015-01-01

We assessed the impact of expert students' instructional quality on the academic performance of novice students in 12th-grade physics classes organized in an expert model of cooperative learning ('jigsaw classroom'). The instructional quality of 129 expert students was measured by a newly developed rating system. As expected, when aggregating across all four subtopics taught, regression analysis revealed that academic performance of novice students increases with the quality of expert students' instruction. The difficulty of subtopics, however, moderates this effect: higher instructional quality of more difficult subtopics did not lead to better academic performance of novice students. We interpret this finding in the light of Cognitive Load Theory. Demanding tasks cause high intrinsic cognitive load and hindered the novice students' learning.

Impact of chemical lateral boundary conditions in a regional air quality forecast model on surface ozone predictions during stratospheric intrusions

NASA Astrophysics Data System (ADS)

Pendlebury, Diane; Gravel, Sylvie; Moran, Michael D.; Lupu, Alexandru

2018-02-01

A regional air quality forecast model, GEM-MACH, is used to examine the conditions under which a limited-area air quality model can accurately forecast near-surface ozone concentrations during stratospheric intrusions. Periods in 2010 and 2014 with known stratospheric intrusions over North America were modelled using four different ozone lateral boundary conditions obtained from a seasonal climatology, a dynamically-interpolated monthly climatology, global air quality forecasts, and global air quality reanalyses. It is shown that the mean bias and correlation in surface ozone over the course of a season can be improved by using time-varying ozone lateral boundary conditions, particularly through the correct assignment of stratospheric vs. tropospheric ozone along the western lateral boundary (for North America). Part of the improvement in surface ozone forecasts results from improvements in the characterization of near-surface ozone along the lateral boundaries that then directly impact surface locations near the boundaries. However, there is an additional benefit from the correct characterization of the location of the tropopause along the western lateral boundary such that the model can correctly simulate stratospheric intrusions and their associated exchange of ozone from stratosphere to troposphere. Over a three-month period in spring 2010, the mean bias was seen to improve by as much as 5 ppbv and the correlation by 0.1 depending on location, and on the form of the chemical lateral boundary condition.

Impact of Disclosure of HIV Infection on Health-Related Quality of Life Among Children and Adolescents With HIV Infection

PubMed Central

Butler, Anne M.; Williams, Paige L.; Howland, Lois C.; Storm, Deborah; Hutton, Nancy; Seage, George R.

2009-01-01

Background Little is known concerning the impact of HIV status disclosure on quality of life, leaving clinicians and families to rely on research of children with other terminal illnesses. Objectives The purpose of this work was to examine the impact of HIV disclosure on pediatric quality of life and to describe the distribution of age at disclosure in a perinatally infected pediatric population. Methods A longitudinal analysis was conducted of perinatally HIV-infected youth ≥5 years of age enrolled in a prospective cohort study, Pediatric AIDS Clinical Trials Group 219C, with ≥1 study visit before and after HIV disclosure. Age-specific quality-of-life instruments were completed by primary caregivers at routine study visits. The distribution of age at disclosure was summarized. Six quality-of-life domains were assessed, including general health perception, symptom distress, psychological status, health care utilization, physical functioning, and social/role functioning. For each domain, mixed-effects models were fit to estimate the effect of disclosure on quality of life. Results A total of 395 children with 2423 study visits were analyzed (1317 predisclosure visits and 1106 postdisclosure visits). The median age at disclosure was estimated to be 11 years. Older age at disclosure was associated with earlier year of birth. Mean domain scores were not significantly different at the last undisclosed visit compared with the first disclosed visit, with the exception of general health perception. When all of the visits were considered, 5 of 6 mean domain scores were lower after disclosure, although the differences were not significant. In mixed-effects models, disclosure did not significantly impact quality of life for any domain. Conclusions Age at disclosure decreased significantly over time. There were no statistically significant differences between predisclosure and postdisclosure quality of life; therefore, disclosure should be encouraged at an appropriate time. PMID:19255023

Water quality simulation of sewage impacts on the west coast of Mumbai, India.

PubMed

Vijay, R; Khobragade, P J; Sohony, R A

2010-01-01

Most coastal cities use the ocean as a site of waste disposal where pollutant loading degrades the quality of coastal waters. Presently, the west coast of Mumbai receives partially treated effluent from wastewater treatment facilities through ocean outfalls and discharges into creeks as well as wastewater/sewage from various open drains and nallahs which affect the water quality of creek and coastal water. Therefore, the objective of this paper is to simulate and assess the hydrodynamic behaviour and water quality due to impact of sewage and wastewater discharges from the west coast of Mumbai. Hydrodynamics and water quality were simulated based on present conditions and validated by using measured tide, current data and observed DO, BOD and FC. Observed and simulated results indicated non compliance to standards in Malad, Mahim creeks and the impact zones of ocean outfalls. The developed model could be used for generating various conditions of hydrodynamics and water quality considering the improvement in wastewater collection systems, treatment levels and proper disposal for proper planning and management of creeks and coastal environment.

Sentinel site data for model improvement – Definition and characterization

USDA-ARS?s Scientific Manuscript database

Crop models are increasingly being used to assess the impacts of future climate change on production and food security. High quality site-specific data on weather, soils, management, and cultivar are needed for those model applications. Also important, is that model development, evaluation, improvem...

Evaluating impact level of different factors in environmental impact assessment for incinerator plants using GM (1, N) model.

PubMed

Pai, T Y; Chiou, R J; Wen, H H

2008-01-01

In this study, the impact levels in environmental impact assessment (EIA) reports of 10 incinerator plants were quantified and discussed. The relationship between the quantified impact levels and the plant scale factors of BeiTou, LiZe, BaLi, LuTsao, RenWu, PingTung, SiJhou and HsinChu were constructed, and the impact levels of the GangShan (GS) and YongKong (YK) plants were predicted using grey model GM (1, N). Finally, the effects of plant scale factors on impact levels were evaluated using grey model GM (1, N) too. According to the predicted results of GM, the relative errors of topography/geology/soil, air quality, hydrology/water quality, solid waste, noise, terrestrial fauna/flora, aquatic fauna/flora and traffic in the GS plant were 17%, 14%, 15%, 17%, 75%, 16%, 13%, and 37%, respectively. The relative errors of the same environmental items in the YK plant were 1%, 18%, 10%, 40%, 37%, 3%, 25% and 33%, respectively. According to GM (1, N), design capacity (DC) and heat value (HV) were the plant scale factors that affected the impact levels significantly in each environmental item, and thus were the most significant plant scale factors. GM (1, N) was effective in predicting the environmental impact and analyzing the reasonableness of the impact. If there is an EIA for a new incinerator plant to be reviewed in the future, the official committee of the Taiwan EPA could review the reasonableness of impact levels in EIA reports quickly.

Applying air pollution modelling within a multi-criteria decision analysis framework to evaluate UK air quality policies

NASA Astrophysics Data System (ADS)

Chalabi, Zaid; Milojevic, Ai; Doherty, Ruth M.; Stevenson, David S.; MacKenzie, Ian A.; Milner, James; Vieno, Massimo; Williams, Martin; Wilkinson, Paul

2017-10-01

A decision support system for evaluating UK air quality policies is presented. It combines the output from a chemistry transport model, a health impact model and other impact models within a multi-criteria decision analysis (MCDA) framework. As a proof-of-concept, the MCDA framework is used to evaluate and compare idealized emission reduction policies in four sectors (combustion in energy and transformation industries, non-industrial combustion plants, road transport and agriculture) and across six outcomes or criteria (mortality, health inequality, greenhouse gas emissions, biodiversity, crop yield and air quality legal compliance). To illustrate a realistic use of the MCDA framework, the relative importance of the criteria were elicited from a number of stakeholders acting as proxy policy makers. In the prototype decision problem, we show that reducing emissions from industrial combustion (followed very closely by road transport and agriculture) is more advantageous than equivalent reductions from the other sectors when all the criteria are taken into account. Extensions of the MCDA framework to support policy makers in practice are discussed.

Air Quality Improvements of Increased Integration of Renewables: Solar Photovoltaics Penetration Scenarios

NASA Astrophysics Data System (ADS)

Duran, P.; Holloway, T.; Brinkman, G.; Denholm, P.; Littlefield, C. M.

2011-12-01

Solar photovoltaics (PV) are an attractive technology because they can be locally deployed and tend to yield high production during periods of peak electric demand. These characteristics can reduce the need for conventional large-scale electricity generation, thereby reducing emissions of criteria air pollutants (CAPs) and improving ambient air quality with regard to such pollutants as nitrogen oxides, sulfur oxides and fine particulates. Such effects depend on the local climate, time-of-day emissions, available solar resources, the structure of the electric grid, and existing electricity production among other factors. This study examines the air quality impacts of distributed PV across the United States Eastern Interconnection. In order to accurately model the air quality impact of distributed PV in space and time, we used the National Renewable Energy Lab's (NREL) Regional Energy Deployment System (ReEDS) model to form three unique PV penetration scenarios in which new PV construction is distributed spatially based upon economic drivers and natural solar resources. Those scenarios are 2006 Eastern Interconnection business as usual, 10% PV penetration, and 20% PV penetration. With the GridView (ABB, Inc) dispatch model, we used historical load data from 2006 to model electricity production and distribution for each of the three scenarios. Solar PV electric output was estimated using historical weather data from 2006. To bridge the gap between dispatch and air quality modeling, we will create emission profiles for electricity generating units (EGUs) in the Eastern Interconnection from historical Continuous Emissions Monitoring System (CEMS) data. Via those emissions profiles, we will create hourly emission data for EGUs in the Eastern Interconnect for each scenario during 2006. Those data will be incorporated in the Community Multi-scale Air Quality (CMAQ) model using the Sparse Matrix Operator Kernel Emissions (SMOKE) model. Initial results indicate that PV penetration significantly reduces conventional peak electricity production and that, due to reduced emissions during periods of extremely active photochemistry, air quality could see benefits.

Reduced-form air quality modeling for community-scale applications

EPA Science Inventory

Transportation plays an important role in modern society, but its impact on air quality has been shown to have significant adverse effects on public health. Numerous reviews (HEI, CDC, WHO) summarizing findings of hundreds of studies conducted mainly in the last decade, conclude ...

Life cycle air quality impacts of conventional and alternative light-duty transportation in the United States.

PubMed

Tessum, Christopher W; Hill, Jason D; Marshall, Julian D

2014-12-30

Commonly considered strategies for reducing the environmental impact of light-duty transportation include using alternative fuels and improving vehicle fuel economy. We evaluate the air quality-related human health impacts of 10 such options, including the use of liquid biofuels, diesel, and compressed natural gas (CNG) in internal combustion engines; the use of electricity from a range of conventional and renewable sources to power electric vehicles (EVs); and the use of hybrid EV technology. Our approach combines spatially, temporally, and chemically detailed life cycle emission inventories; comprehensive, fine-scale state-of-the-science chemical transport modeling; and exposure, concentration-response, and economic health impact modeling for ozone (O3) and fine particulate matter (PM2.5). We find that powering vehicles with corn ethanol or with coal-based or "grid average" electricity increases monetized environmental health impacts by 80% or more relative to using conventional gasoline. Conversely, EVs powered by low-emitting electricity from natural gas, wind, water, or solar power reduce environmental health impacts by 50% or more. Consideration of potential climate change impacts alongside the human health outcomes described here further reinforces the environmental preferability of EVs powered by low-emitting electricity relative to gasoline vehicles.

Impact of Mother-Daughter Relationship on Hypertension Self-management and Quality of Life: Testing Dyadic Dynamics Using the Actor-Partner Interdependence Model.

PubMed

Shawler, Celeste; Edward, Jean; Ling, Jiying; Crawford, Tim N; Rayens, Mary Kay

Although hypertension (HTN) treatment rates are similar across age groups of women, effective control is significantly worse among older women. Only 20% of hypertensive women aged 70 to 79 years have controlled blood pressure. The purpose of this longitudinal study was to test the effects of the quality of mother-daughter relationship, inner strength, and control on HTN self-management and health-related quality of life (HRQOL) for both members of the dyad at 6 months. The Actor-Partner Interdependence Model was used to examine the direct ("actor") and indirect ("partner") effects of 46 dyads. The mothers' perceived relationship quality with daughters directly impacted their own self-management of HTN and HRQOL while also indirectly affecting their daughters' self-management. Similarly, the daughters' perceived strength of their relationship with their mothers directly influenced their self-management and HRQOL and indirectly affected their mothers' self-management and HRQOL.

Modeling Low Impact Development Alternatives with SWIMM

EPA Science Inventory

The U.S. Environmental Protection Agency’s Office of Water (OW) is actively promoting the use of Low Impact Development (LID) practices to help protect and restore water quality in urban and developing areas. Such practices support the concepts of green infrastructure and sustain...

Integrated analysis of numerical weather prediction and computational fluid dynamics for estimating cross-ventilation effects on inhaled air quality inside a factory

NASA Astrophysics Data System (ADS)

Murga, Alicia; Sano, Yusuke; Kawamoto, Yoichi; Ito, Kazuhide

2017-10-01

Mechanical and passive ventilation strategies directly impact indoor air quality. Passive ventilation has recently become widespread owing to its ability to reduce energy demand in buildings, such as the case of natural or cross ventilation. To understand the effect of natural ventilation on indoor environmental quality, outdoor-indoor flow paths need to be analyzed as functions of urban atmospheric conditions, topology of the built environment, and indoor conditions. Wind-driven natural ventilation (e.g., cross ventilation) can be calculated through the wind pressure coefficient distributions of outdoor wall surfaces and openings of a building, allowing the study of indoor air parameters and airborne contaminant concentrations. Variations in outside parameters will directly impact indoor air quality and residents' health. Numerical modeling can contribute to comprehend these various parameters because it allows full control of boundary conditions and sampling points. In this study, numerical weather prediction modeling was used to calculate wind profiles/distributions at the atmospheric scale, and computational fluid dynamics was used to model detailed urban and indoor flows, which were then integrated into a dynamic downscaling analysis to predict specific urban wind parameters from the atmospheric to built-environment scale. Wind velocity and contaminant concentration distributions inside a factory building were analyzed to assess the quality of the human working environment by using a computer simulated person. The impact of cross ventilation flows and its variations on local average contaminant concentration around a factory worker, and inhaled contaminant dose, were then discussed.

Modeling Study on Air Quality Improvement due to Mobile Source Emission control Plan in Seoul Metropolitan Area

NASA Astrophysics Data System (ADS)

Kim, Y. J.; Sunwoo, Y.; Hwang, I.; Song, S.; Sin, J.; Kim, D.

2015-12-01

A very high population and corresponding high number of vehicles in the Seoul Metropolitan Area (SMA) are aggravating the air quality of this region. The Korean government continues to make concerted efforts to improve air quality. One of the major policies that the Ministry of Environment of Korea enforced is "The Special Act for Improvement of Air Quality in SMA" and "The 1st Air Quality Management Plan of SMA". Mobile Source emission controls are an important part of the policy. Thus, it is timely to evaluate the air quality improvement due to the controls. Therefore, we performed a quantitative analysis of the difference in air quality using the Community Multiscale Air Quality (CMAQ) model and December, 2011 was set as the target period to capture the impact of the above control plans. We considered four fuel-type vehicle emission scenarios and compared the air quality improvement differences between them. The scenarios are as follows: no-control, gasoline vehicle control only, diesel vehicle control only, and control of both; utilizing the revised mobile source emissions from the Clean Air Policy Support System (CAPSS), which is the national emission inventory reflecting current policy.In order to improve the accuracy of the modeling data, we developed new temporal allocation coefficients based on traffic volume observation data and spatially reallocated the mobile source emissions using vehicle flow survey data. Furthermore, we calculated the PM10 and PM2.5 emissions of gasoline vehicles which is omitted in CAPSS.The results of the air quality modeling shows that vehicle control plans for both gasoline and diesel lead to a decrease of 0.65ppb~8.75ppb and 0.02㎍/㎥~7.09㎍/㎥ in NO2 and PM10 monthly average concentrations, respectively. The large percentage decreases mainly appear near the center of the metropolis. However, the largest NO2 decrease percentages are found in the northeast region of Gyeonggi-do, which is the province that surrounds the capital of Seoul. Comparing the results between the different scenarios, diesel vehicle control impact dominates relative to the impact of gasoline control. The diesel-only reduction plan shows that NO2 and PM10 improved by 2.93ppb and 3.32㎍/㎥, respectively.

Impact of Legacy Surface Mining on Water Quality in the Lake Harris Watershed, Tuscaloosa County, Alabama.

NASA Astrophysics Data System (ADS)

Donahoe, R. J.; Hawkins, P. D.

2017-12-01

The Lake Harris watershed was the site of legacy surface mining of coal conducted from approximately 1969 to 1976. The mine site was abandoned and finally reclaimed in 1986. Water quality in the stream draining the mined area is still severely impacted by acid mine drainage (AMD), despite the reclamation effort. Lake Harris is used as a source of industrial water, but shows no negative water quality effects from the legacy mining activities despite receiving drainage from the AMD-impacted stream. Water samples were collected monthly between October 2016 and September 2017 from a first-order stream impacted by acid mine drainage (AMD), a nearby first-order control stream, and Lake Harris. Stream water chemistry was observed to vary both spatially and seasonally, as monitored at five sample stations in each stream over the study period. Comparison of the two streams shows the expected elevated concentrations of AMD-indicator solutes (sulfate and iron), as well as significant increases in conductivity and acidity for the stream draining the reclaimed mine site. In addition, dramatic (1-2 orders of magnitude) increases in major element (Al, Ca, Mg, K), minor element (Mn, Sr) and trace element (Co, Ni) concentrations are also observed for the AMD-impacted stream compared to the control stream. The AMD-impacted stream also shows elevated (2-4 times) levels of other stream water solutes (Cl, Na, Si, Zn), compared to the control stream. As the result of continuing AMD input, the stream draining the reclaimed mine site is essentially sterile, in contrast to the lake and control stream, which support robust aquatic ecosystems. A quantitative model, constrained by isotopic data (δD and δ18O), will be presented that seeks to explain the observed temporal differences in water quality for the AMD-impacted stream as a function of variable meteoric water, groundwater, and AMD inputs. Similar models may be developed for other AMD-impacted streams to better understand and predict temporal variations in water quality parameters and their effect on aquatic ecosystems.

General principles of institutional risks influence on pension systems

NASA Astrophysics Data System (ADS)

Nepp, A. N.; Shilkov, A. A.; Sheveleva, A. Y.; Mamedbakov, M. R.

2016-12-01

This paper examines the tools used to study the influence of institutional factors on investment returns. The research object are the tools used in the evaluation of institutional risks in the pension system, in particular, the correlation model of factors impacting on the `anti-director' index, econometric estimates combining the different determinants of savings, the model of endogenous institutional change, etc. Research work focusing on issues of institutional factors affecting pension systems (authored by La Porta, Guiso, Gianetti, El-Mekkaouide Freitas, Neyapti B., and others) is reviewed. The model is examined in terms of the impact of institutional risks on pension systems, especially with regard to the funded part. The study identified the following factors that affect financial institutions, including pension institutions: management quality, regulation quality, rule of law, political stability, and corruption control.

Stress and family quality of life in parents of children with autism spectrum disorder: parent gender and the double ABCX model.

PubMed

McStay, Rebecca L; Trembath, David; Dissanayake, Cheryl

2014-12-01

Past research has supported the utility of the Double ABCX model of family adaptation for parents raising a child with autism spectrum disorder (ASD). What remains unclear is the impact of family-related variables on outcomes in both mothers and fathers within the same family. We explored the potential predictors of maternal and paternal stress and family quality of life in an Australian sample of 196 parents of children with ASD aged 3-16 years. Using a cross-sectional design, parents completed questionnaires assessing factors within the Double ABCX model attributed to family adaptation. Findings provide further evidence of the negative impact of child externalising behaviours and highlight the importance of family sense of coherence on positive parental outcomes.

Contribution of biomass burning to particles matter smaller than ten microns in Mexico City during April 2013.

NASA Astrophysics Data System (ADS)

Mendoza Campos, Alejandra; Agustin Garcia Reynoso, Jóse; Castro Romero, Telma; Carbajal Perez, Jóse Noel; Gerardo Ruiz Suarez, Luis; Peralta Rosales, Oscar Augusto

2015-04-01

A forest fire is a natural combustion process in a specific geographic area, it's depends on meteorological variables, topography and vegetation type, The wildfires are potential sources of large amounts of pollutants. The main air pollutants emitted in a forest fire are the particles (PM10 and PM2.5) Carbon Monoxide (CO), Nitrogen Oxides (NOx), Volatile Organic Compounds (VOCs) and a negligible amount of Sulfur Dioxide (SO2) (Chow 1995), The study of the impact of air quality in Mexico City for a forest fire occurred on April 14 of 2013 was conducted a duration of 26 hours of grassland burning and consuming an extension of 150 ha, the WRF-Chem, WRF-fire and METv3 models were used to perform the study, for the study two modeling were made, one including emissions from forest fires and the other one no emission-fire, when interpolation is made between the two modeling and obtained the impact of air quality in Mexico City, performing calculating emissions and modeling, the impact on air quality for PM10particles were observed arriving at a concentration of 350 mg/m3 due to wildfire occurred, this issue exceeds the maximum permissible limit of PM10particles governed by NOM-025-SSA1-1993 that establishes a maximum of 120 mg/m3 on average for 24 hours, the modeling results with measured data is corroborated weather Stations the environmental monitoring network of the Mexico City, that alerts an environmental contingency for particles for the post-wildfire day. Until now is review the rule which establishes a maximum of 75 mg/m3 on average for 24 hours, implying greater involvement in air quality.

Modeling sediment transport from an off-road vehicle trail stream crossing using WEPP model

Treesearch

Renee' D. Ayala; Puneet Srivastava; Christian J. Brodbeck; Emily A. Carter; Timothy P. McDonald

2005-01-01

There is a limited information available pertaining to the adverse effects of Off-Road-Vehicle (ORV) use and trail impacts. As a result, this study was initiated in 2003 to (a) quantify water quality impacts of an ORV trail stream crossing through monitoring of total suspended solids, and (b) conduct WEPP (Water Erosion Prediction Project) simulations to determine long...

Revalidation and quality assurance: the application of the MUSIQ framework in independent verification visits to healthcare organisations

PubMed Central

Griffin, Ann; Viney, Rowena; Welland, Trevor; Gafson, Irene

2017-01-01

Objectives We present a national evaluation of the impact of independent verification visits (IVVs) performed by National Health Service (NHS) England as part of quality assuring medical revalidation. Organisational visits are central to NHS quality assurance. They are costly, yet little empirical research evidence exists concerning their impact, and what does exist is conflicting. Setting The focus was on healthcare providers in the NHS (in secondary care) and private sector across England, who were designated bodies (DBs). DBs are healthcare organisations that have a statutory responsibility, via the lead clinician, the responsible officer (RO), to implement medical revalidation. Participants All ROs who had undergone an IVV in England in 2014 and 2015 were invited to participate. 46 ROs were interviewed. Ethnographic data were gathered at 18 observations of the IVVs and 20 IVV post visit reports underwent documentary analysis. Primary and secondary outcome measures Primary outcomes were the findings pertaining to the effectiveness of the IVV system in supporting the revalidation processes at the DBs. Secondary outcomes were methodological, relating to the Model for Understanding Success in Quality (MUSIQ) and how its application to the IVV reveals the relevance of contextual factors described in the model. Results The impact of the IVVs varied by DB according to three major themes: the personal context of the RO; the organisational context of the DB; and the visit and its impact. ROs were largely satisfied with visits which raised the status of appraisal within their organisations. Inadequate or untimely feedback was associated with dissatisfaction. Conclusions Influencing teams whose prime responsibility is establishing processes and evaluating progress was crucial for internal quality improvement. Visits acted as a nudge, generating internal quality review, which was reinforced by visit teams with relevant expertise. Diverse team membership, knowledge transfer and timely feedback made visits more impactful. PMID:28196952

Revalidation and quality assurance: the application of the MUSIQ framework in independent verification visits to healthcare organisations.

PubMed

Griffin, Ann; McKeown, Alex; Viney, Rowena; Rich, Antonia; Welland, Trevor; Gafson, Irene; Woolf, Katherine

2017-02-14

We present a national evaluation of the impact of independent verification visits (IVVs) performed by National Health Service (NHS) England as part of quality assuring medical revalidation. Organisational visits are central to NHS quality assurance. They are costly, yet little empirical research evidence exists concerning their impact, and what does exist is conflicting. The focus was on healthcare providers in the NHS (in secondary care) and private sector across England, who were designated bodies (DBs). DBs are healthcare organisations that have a statutory responsibility, via the lead clinician, the responsible officer (RO), to implement medical revalidation. All ROs who had undergone an IVV in England in 2014 and 2015 were invited to participate. 46 ROs were interviewed. Ethnographic data were gathered at 18 observations of the IVVs and 20 IVV post visit reports underwent documentary analysis. Primary outcomes were the findings pertaining to the effectiveness of the IVV system in supporting the revalidation processes at the DBs. Secondary outcomes were methodological, relating to the Model for Understanding Success in Quality (MUSIQ) and how its application to the IVV reveals the relevance of contextual factors described in the model. The impact of the IVVs varied by DB according to three major themes: the personal context of the RO; the organisational context of the DB; and the visit and its impact. ROs were largely satisfied with visits which raised the status of appraisal within their organisations. Inadequate or untimely feedback was associated with dissatisfaction. Influencing teams whose prime responsibility is establishing processes and evaluating progress was crucial for internal quality improvement. Visits acted as a nudge, generating internal quality review, which was reinforced by visit teams with relevant expertise. Diverse team membership, knowledge transfer and timely feedback made visits more impactful. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Regional air quality impacts of future fire emissions in Sumatra and Kalimantan

NASA Astrophysics Data System (ADS)

Marlier, Miriam E.; DeFries, Ruth S.; Kim, Patrick S.; Gaveau, David L. A.; Koplitz, Shannon N.; Jacob, Daniel J.; Mickley, Loretta J.; Margono, Belinda A.; Myers, Samuel S.

2015-05-01

Fire emissions associated with land cover change and land management contribute to the concentrations of atmospheric pollutants, which can affect regional air quality and climate. Mitigating these impacts requires a comprehensive understanding of the relationship between fires and different land cover change trajectories and land management strategies. We develop future fire emissions inventories from 2010-2030 for Sumatra and Kalimantan (Indonesian Borneo) to assess the impact of varying levels of forest and peatland conservation on air quality in Equatorial Asia. To compile these inventories, we combine detailed land cover information from published maps of forest extent, satellite fire radiative power observations, fire emissions from the Global Fire Emissions Database, and spatially explicit future land cover projections using a land cover change model. We apply the sensitivities of mean smoke concentrations to Indonesian fire emissions, calculated by the GEOS-Chem adjoint model, to our scenario-based future fire emissions inventories to quantify the different impacts of fires on surface air quality across Equatorial Asia. We find that public health impacts are highly sensitive to the location of fires, with emissions from Sumatra contributing more to smoke concentrations at population centers across the region than Kalimantan, which had higher emissions by more than a factor of two. Compared to business-as-usual projections, protecting peatlands from fires reduces smoke concentrations in the cities of Singapore and Palembang by 70% and 40%, and by 60% for the Equatorial Asian region, weighted by the population in each grid cell. Our results indicate the importance of focusing conservation priorities on protecting both forested (intact or logged) peatlands and non-forested peatlands from fire, even after considering potential leakage of deforestation pressure to other areas, in order to limit the impact of fire emissions on atmospheric smoke concentrations and subsequent health effects.

USEEIO: a New and Transparent United States ...

EPA Pesticide Factsheets

National-scope environmental life cycle models of goods and services may be used for many purposes, not limited to quantifying impacts of production and consumption of nations, assessing organization-wide impacts, identifying purchasing hot spots, analyzing environmental impacts of policies, and performing streamlined life cycle assessment. USEEIO is a new environmentally extended input-output model of the United States fit for such purposes and other sustainable materials management applications. USEEIO melds data on economic transactions between 389 industry sectors with environmental data for these sectors covering land, water, energy and mineral usage and emissions of greenhouse gases, criteria air pollutants, nutrients and toxics, to build a life cycle model of 385 US goods and services. In comparison with existing US input-output models, USEEIO is more current with most data representing year 2013, more extensive in its coverage of resources and emissions, more deliberate and detailed in its interpretation and combination of data sources, and includes formal data quality evaluation and description. USEEIO was assembled with a new Python module called the IO Model Builder capable of assembling and calculating results of user-defined input-output models and exporting the models into LCA software. The model and data quality evaluation capabilities are demonstrated with an analysis of the environmental performance of an average hospital in the US. All USEEIO f

Modelling future impacts of air pollution using the multi-scale UK Integrated Assessment Model (UKIAM).

PubMed

Oxley, Tim; Dore, Anthony J; ApSimon, Helen; Hall, Jane; Kryza, Maciej

2013-11-01

Integrated assessment modelling has evolved to support policy development in relation to air pollutants and greenhouse gases by providing integrated simulation tools able to produce quick and realistic representations of emission scenarios and their environmental impacts without the need to re-run complex atmospheric dispersion models. The UK Integrated Assessment Model (UKIAM) has been developed to investigate strategies for reducing UK emissions by bringing together information on projected UK emissions of SO2, NOx, NH3, PM10 and PM2.5, atmospheric dispersion, criteria for protection of ecosystems, urban air quality and human health, and data on potential abatement measures to reduce emissions, which may subsequently be linked to associated analyses of costs and benefits. We describe the multi-scale model structure ranging from continental to roadside, UK emission sources, atmospheric dispersion of emissions, implementation of abatement measures, integration with European-scale modelling, and environmental impacts. The model generates outputs from a national perspective which are used to evaluate alternative strategies in relation to emissions, deposition patterns, air quality metrics and ecosystem critical load exceedance. We present a selection of scenarios in relation to the 2020 Business-As-Usual projections and identify potential further reductions beyond those currently being planned. © 2013.

Foliage Quality and its Effect on Budworm Populations: A Modeller's Viewpoint

Treesearch

Richard A.  Fleming

1983-01-01

Although it may soon be possible to alter stand foliage quality and thus reduce budworm reproductivity, the impact of such changes on the budworm-forest system remains unclear. There are currently a number of hypotheses concerning the key biological mechanisms which drive the budworm-forest system. The possible effects of changes in foliage quality are examined for...

It Takes Two to Tango: How Parents' and Adolescents' Personalities Link to the Quality of Their Mutual Relationship

ERIC Educational Resources Information Center

Denissen, Jaap J. A.; van Aken, Marcel A. G.; Dubas, Judith S.

2009-01-01

According to J. Belsky's (1984) process model of parenting, both adolescents' and parents' personality should exert a significant impact on the quality of their mutual relationship. Using multi-informant, symmetric data on the Big Five personality traits and the relationship quality of mothers, fathers, and two adolescent children, the current…

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...

Green House Adoption and Nursing Home Quality.

PubMed

Afendulis, Christopher C; Caudry, Daryl J; O'Malley, A James; Kemper, Peter; Grabowski, David C

2016-02-01

To evaluate the impact of the Green House (GH) model on nursing home resident-level quality of care measures. Resident-level minimum data set (MDS) assessments merged with Medicare inpatient claims for the period 2005 through 2010. Using a difference-in-differences framework, we compared changes in care quality and outcomes in 15 nursing homes that adopted the GH model relative to changes over the same time period in 223 matched nursing homes that had not adopted the GH model. For individuals residing in GH homes, adoption of the model lowered readmissions and several MDS measures of poor quality, including bedfast residents, catheter use, and pressure ulcers, but these results were not present across the entire GH organization, suggesting possible offsetting effects for residents of non-GH "legacy" units within the GH organization. GH adoption led to improvement in rehospitalizations and certain nursing home quality measures for individuals residing in a GH home. The absence of evidence of a decline in other clinical quality measures in GH nursing homes should reassure anyone concerned that GH might have sacrificed clinical quality for improved quality of life. © Health Research and Educational Trust.

Is the economic value of hydrological forecasts related to their quality? Case study of the hydropower sector.

NASA Astrophysics Data System (ADS)

Cassagnole, Manon; Ramos, Maria-Helena; Thirel, Guillaume; Gailhard, Joël; Garçon, Rémy

2017-04-01

The improvement of a forecasting system and the evaluation of the quality of its forecasts are recurrent steps in operational practice. However, the evaluation of forecast value or forecast usefulness for better decision-making is, to our knowledge, less frequent, even if it might be essential in many sectors such as hydropower and flood warning. In the hydropower sector, forecast value can be quantified by the economic gain obtained with the optimization of operations or reservoir management rules. Several hydropower operational systems use medium-range forecasts (up to 7-10 days ahead) and energy price predictions to optimize hydropower production. Hence, the operation of hydropower systems, including the management of water in reservoirs, is impacted by weather, climate and hydrologic variability as well as extreme events. In order to assess how the quality of hydrometeorological forecasts impact operations, it is essential to first understand if and how operations and management rules are sensitive to input predictions of different quality. This study investigates how 7-day ahead deterministic and ensemble streamflow forecasts of different quality might impact the economic gains of energy production. It is based on a research model developed by Irstea and EDF to investigate issues relevant to the links between quality and value of forecasts in the optimisation of energy production at the short range. Based on streamflow forecasts and pre-defined management constraints, the model defines the best hours (i.e., the hours with high energy prices) to produce electricity. To highlight the link between forecasts quality and their economic value, we built several synthetic ensemble forecasts based on observed streamflow time series. These inputs are generated in a controlled environment in order to obtain forecasts of different quality in terms of accuracy and reliability. These forecasts are used to assess the sensitivity of the decision model to forecast quality. Relationships between forecast quality and economic value are discussed. This work is part of the IMPREX project, a research project supported by the European Commission under the Horizon 2020 Framework programme, with grant No. 641811 (http://www.imprex.eu)

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression.

PubMed

Chen, Qiang; Mei, Kun; Dahlgren, Randy A; Wang, Ting; Gong, Jian; Zhang, Minghua

2016-12-01

As an important regulator of pollutants in overland flow and interflow, land use has become an essential research component for determining the relationships between surface water quality and pollution sources. This study investigated the use of ordinary least squares (OLS) and geographically weighted regression (GWR) models to identify the impact of land use and population density on surface water quality in the Wen-Rui Tang River watershed of eastern China. A manual variable excluding-selecting method was explored to resolve multicollinearity issues. Standard regression coefficient analysis coupled with cluster analysis was introduced to determine which variable had the greatest influence on water quality. Results showed that: (1) Impact of land use on water quality varied with spatial and seasonal scales. Both positive and negative effects for certain land-use indicators were found in different subcatchments. (2) Urban land was the dominant factor influencing N, P and chemical oxygen demand (COD) in highly urbanized regions, but the relationship was weak as the pollutants were mainly from point sources. Agricultural land was the primary factor influencing N and P in suburban and rural areas; the relationship was strong as the pollutants were mainly from agricultural surface runoff. Subcatchments located in suburban areas were identified with urban land as the primary influencing factor during the wet season while agricultural land was identified as a more prevalent influencing factor during the dry season. (3) Adjusted R 2 values in OLS models using the manual variable excluding-selecting method averaged 14.3% higher than using stepwise multiple linear regressions. However, the corresponding GWR models had adjusted R 2 ~59.2% higher than the optimal OLS models, confirming that GWR models demonstrated better prediction accuracy. Based on our findings, water resource protection policies should consider site-specific land-use conditions within each watershed to optimize mitigation strategies for contrasting land-use characteristics and seasonal variations. Copyright © 2016 Elsevier B.V. All rights reserved.

How do you perceive this author? Understanding and modeling authors’ communication quality in social media

PubMed Central

2018-01-01

In this study, we leverage human evaluations, content analysis, and computational modeling to generate a comprehensive analysis of readers’ evaluations of authors’ communication quality in social media with respect to four factors: author credibility, interpersonal attraction, communication competence, and intent to interact. We review previous research on the human evaluation process and highlight its limitations in providing sufficient information for readers to assess authors’ communication quality. From our analysis of the evaluations of 1,000 Twitter authors’ communication quality from 300 human evaluators, we provide empirical evidence of the impact of the characteristics of the reader (demographic, social media experience, and personality), author (profile and social media engagement), and content (linguistic, syntactic, similarity, and sentiment) on the evaluation of an author’s communication quality. In addition, based on the author and message characteristics, we demonstrate the potential for building accurate models that can indicate an author’s communication quality. PMID:29389979

How do you perceive this author? Understanding and modeling authors' communication quality in social media.

PubMed

Han, Kyungsik

2018-01-01

In this study, we leverage human evaluations, content analysis, and computational modeling to generate a comprehensive analysis of readers' evaluations of authors' communication quality in social media with respect to four factors: author credibility, interpersonal attraction, communication competence, and intent to interact. We review previous research on the human evaluation process and highlight its limitations in providing sufficient information for readers to assess authors' communication quality. From our analysis of the evaluations of 1,000 Twitter authors' communication quality from 300 human evaluators, we provide empirical evidence of the impact of the characteristics of the reader (demographic, social media experience, and personality), author (profile and social media engagement), and content (linguistic, syntactic, similarity, and sentiment) on the evaluation of an author's communication quality. In addition, based on the author and message characteristics, we demonstrate the potential for building accurate models that can indicate an author's communication quality.

Investigating the Impact of Marine Ship Emissions on Regional Air Quality using OMI Satellite NO2 Observations and the CMAQ Model

NASA Astrophysics Data System (ADS)

Ring, A.; Canty, T. P.; He, H.; Vinciguerra, T.; Lamsal, L. N.; Dickerson, R. R.; Salawitch, R. J.; Cohen, M.; Montgomery, L. N.; Dreessen, J.

2015-12-01

Commercial marine vessels (CMVs) emit significant amounts of NOx, an ozone precursor, which may contribute to negative health consequences for people living in areas near shipping lanes. In coastal US states, many metropolitan areas such as Baltimore and New York City are located near ports with CMVs. Many studies estimate that ships account for ~15-30% of the global anthropogenic NOx emissions. EPA developed emissions inventories are widely used by states to construct model scenarios for testing air quality attainment strategies. Currently, CMV emissions are generated by simply applying growth factors to aggregated emissions data from much earlier years. Satellite retrievals from the Ozone Monitoring Instrument (OMI) have been successfully used to improve the veracity of marine emissions by incorporating observational data from the inventory year. In this study we use OMI NO2 observations and Community Multiscale Air Quality (CMAQ) model outputs to improve the EPA marine emission estimates for the Mid-Atlantic region. Back trajectories from the NOAA Air Resources Laboratory HYSPLIT model are used to identify days with minimal continental influence on OMI tropospheric column NO2 over shipping lanes. We perform sensitivity analyses to quantify the impact of marine emissions on air quality and suggest strategies to better meet the EPA mandated ozone standard.

Assessing Impact of Aerosol Intercontinental Transport on Regional Air Quality and Climate: What Satellites Can Help

NASA Technical Reports Server (NTRS)

Yu, Hongbin

2011-01-01

Mounting evidence for intercontinental transport of aerosols suggests that aerosols from a region could significantly affect climate and air quality in downwind regions and continents. Current assessment of these impacts for the most part has been based on global model simulations that show large variability. The aerosol intercontinental transport and its influence on air quality and climate involve many processes at local, regional, and intercontinental scales. There is a pressing need to establish modeling systems that bridge the wide range of scales. The modeling systems need to be evaluated and constrained by observations, including satellite measurements. Columnar loadings of dust and combustion aerosols can be derived from the MODIS and MISR measurements of total aerosol optical depth and particle size and shape information. Characteristic transport heights of dust and combustion aerosols can be determined from the CALIPSO lidar and AIRS measurements. CALIPSO liar and OMI UV technique also have a unique capability of detecting aerosols above clouds, which could offer some insights into aerosol lofting processes and the importance of above-cloud transport pathway. In this presentation, I will discuss our efforts of integrating these satellite measurements and models to assess the significance of intercontinental transport of dust and combustion aerosols on regional air quality and climate.

Quality Assurance Decisions with Air Models: A Case Study of ImputatIon of Missing Input Data Using EPA's Multi-Layer Model

EPA Science Inventory

Abstract Environmental models are frequently used within regulatory and policy frameworks to estimate environmental metrics that are difficult or impossible to physically measure. As important decision tools, the uncertainty associated with the model outputs should impact their ...

77 FR 11928 - Approval and Promulgation of Air Quality Implementation Plans; Wisconsin; Regional Haze

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-28

... monitoring, modeling, and scientific knowledge about the relationships between pollutants and visibility... for their BART modeling under the BART Guidelines, below which a BART-eligible source may be... conduct modeling to assess the impact of each of these identified candidate sources. This modeling...

An integrated modeling framework for exploring flow regime and water quality changes with increasing biofuel crop production in the U.S. Corn Belt

NASA Astrophysics Data System (ADS)

Yaeger, Mary A.; Housh, Mashor; Cai, Ximing; Sivapalan, Murugesu

2014-12-01

To better address the dynamic interactions between human and hydrologic systems, we develop an integrated modeling framework that employs a System of Systems optimization model to emulate human development decisions which are then incorporated into a watershed model to estimate the resulting hydrologic impacts. The two models are run interactively to simulate the coevolution of coupled human-nature systems, such that reciprocal feedbacks between hydrologic processes and human decisions (i.e., human impacts on critical low flows and hydrologic impacts on human decisions on land and water use) can be assessed. The framework is applied to a Midwestern U.S. agricultural watershed, in the context of proposed biofuels development. This operation is illustrated by projecting three possible future coevolution trajectories, two of which use dedicated biofuel crops to reduce annual watershed nitrate export while meeting ethanol production targets. Imposition of a primary external driver (biofuel mandate) combined with different secondary drivers (water quality targets) results in highly nonlinear and multiscale responses of both the human and hydrologic systems, including multiple tradeoffs, impacting the future coevolution of the system in complex, heterogeneous ways. The strength of the hydrologic response is sensitive to the magnitude of the secondary driver; 45% nitrate reduction target leads to noticeable impacts at the outlet, while a 30% reduction leads to noticeable impacts that are mainly local. The local responses are conditioned by previous human-hydrologic modifications and their spatial relationship to the new biofuel development, highlighting the importance of past coevolutionary history in predicting future trajectories of change.

A new physically-based windblown dust emission parametrization in CMAQ

EPA Science Inventory

Dust has significant impacts on weather and climate, air quality and visibility, and human health; therefore, it is important to include a windblown dust emission module in atmospheric and air quality models. In this presentation, we summarize our efforts in development of a phys...

MODELING THE IMPACTS OF LAND USE CHANGE ON HYDROLOGY AND WATER QUALITY OF A PACIFIC NORTHWEST WATERSHED

EPA Science Inventory

In many parts of the world, aquatic ecosystems are threatened by hydrological and water quality alterations due to extraction and conversion of natural resources for agriculture, urban development, forestry, mining, transportation, and water resources development. To evaluate the...

BIOWALL’S IMPACT ON INDOOR AIR QUALITY AND ENERGY

EPA Science Inventory

This project will collect data on air quality and energy consumption for a variety of Biowall configurations in a controlled laboratory environment.  This data will be evaluated for statistical significance and used to develop and validate an energy/IAQ model of the Bi...

Computational fluid dynamics modeling to assess the impact of roadside barriers on near-road air quality

EPA Science Inventory

Near-road air quality is an issue of emerging concern, with field studies consistently showing elevated air pollutant concentrations adjacent to major roads, usually decreasing to background levels within several hundred meters. Roadside barriers, both vegetative and structural, ...

Impact of influent data frequency and model structure on the quality of WWTP model calibration and uncertainty.

PubMed

Cierkens, Katrijn; Plano, Salvatore; Benedetti, Lorenzo; Weijers, Stefan; de Jonge, Jarno; Nopens, Ingmar

2012-01-01

Application of activated sludge models (ASMs) to full-scale wastewater treatment plants (WWTPs) is still hampered by the problem of model calibration of these over-parameterised models. This either requires expert knowledge or global methods that explore a large parameter space. However, a better balance in structure between the submodels (ASM, hydraulic, aeration, etc.) and improved quality of influent data result in much smaller calibration efforts. In this contribution, a methodology is proposed that links data frequency and model structure to calibration quality and output uncertainty. It is composed of defining the model structure, the input data, an automated calibration, confidence interval computation and uncertainty propagation to the model output. Apart from the last step, the methodology is applied to an existing WWTP using three models differing only in the aeration submodel. A sensitivity analysis was performed on all models, allowing the ranking of the most important parameters to select in the subsequent calibration step. The aeration submodel proved very important to get good NH(4) predictions. Finally, the impact of data frequency was explored. Lowering the frequency resulted in larger deviations of parameter estimates from their default values and larger confidence intervals. Autocorrelation due to high frequency calibration data has an opposite effect on the confidence intervals. The proposed methodology opens doors to facilitate and improve calibration efforts and to design measurement campaigns.

Hydrologic and water quality impacts of biofuel feedstock production in the Ohio River Basin

DOE PAGES

Demissie, Yonas; Yan, Eugene; Wu, May

2017-07-10

Our study addresses the uncertainties related to potential changes in land use and management and associated impacts on hydrology and water quality resulting from increased production of biofuel from the conventional and cellulosic feedstock. The Soil Water Assessment Tool (SWAT) was then used to assess the impacts on regional and field scale evapotranspiration, soil moisture content, stream flow, sediment, and nutrient loadings in the Ohio River Basin. The model incorporates spatially and temporally detailed hydrologic, climate and agricultural practice data that are pertinent to simulate biofuel feedstock production, watershed hydrology and water quality. Three future biofuel production scenarios in themore » region were considered, including a feedstock projection from the DOE Billion-Ton (BT2) Study, a change in corn rotations to continuous corn, and harvest of 50% corn stover. The impacts were evaluated on the basis of relative changes in hydrology and water quality from historical baseline and future business-as-usual conditions of the basin. The overall impact on water quality is an order of magnitude higher than the impact on hydrology. For all the three future scenarios, the sub-basin results indicated an overall increase in annual evapotranspiration of up to 6%, a decrease in runoff up to 10% and minimal change in soil moisture. The sediment and phosphorous loading at both regional and field levels increased considerably (up to 40–90%) for all the biofuel feedstock scenario considered, while the nitrogen loading increased up to 45% in some regions under the BT2 Study scenario, decreased up to 10% when corn are grown continuously instead of in rotations, and changed minimally when 50% of the stover are harvested. Field level analyses revealed significant variability in hydrology and water quality impacts that can further be used to identify suitable locations for the feedstock productions without causing major impacts on water quantity and quality.« less

Hydrologic and water quality impacts of biofuel feedstock production in the Ohio River Basin

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

Demissie, Yonas; Yan, Eugene; Wu, May

Our study addresses the uncertainties related to potential changes in land use and management and associated impacts on hydrology and water quality resulting from increased production of biofuel from the conventional and cellulosic feedstock. The Soil Water Assessment Tool (SWAT) was then used to assess the impacts on regional and field scale evapotranspiration, soil moisture content, stream flow, sediment, and nutrient loadings in the Ohio River Basin. The model incorporates spatially and temporally detailed hydrologic, climate and agricultural practice data that are pertinent to simulate biofuel feedstock production, watershed hydrology and water quality. Three future biofuel production scenarios in themore » region were considered, including a feedstock projection from the DOE Billion-Ton (BT2) Study, a change in corn rotations to continuous corn, and harvest of 50% corn stover. The impacts were evaluated on the basis of relative changes in hydrology and water quality from historical baseline and future business-as-usual conditions of the basin. The overall impact on water quality is an order of magnitude higher than the impact on hydrology. For all the three future scenarios, the sub-basin results indicated an overall increase in annual evapotranspiration of up to 6%, a decrease in runoff up to 10% and minimal change in soil moisture. The sediment and phosphorous loading at both regional and field levels increased considerably (up to 40–90%) for all the biofuel feedstock scenario considered, while the nitrogen loading increased up to 45% in some regions under the BT2 Study scenario, decreased up to 10% when corn are grown continuously instead of in rotations, and changed minimally when 50% of the stover are harvested. Field level analyses revealed significant variability in hydrology and water quality impacts that can further be used to identify suitable locations for the feedstock productions without causing major impacts on water quantity and quality.« less

The impact of hearing impairment and noise-induced hearing injury on quality of life in the active-duty military population: challenges to the study of this issue.

PubMed

Alamgir, Hasanat; Turner, Caryn A; Wong, Nicole J; Cooper, Sharon P; Betancourt, Jose A; Henry, James; Senchak, Andrew J; Hammill, Tanisha L; Packer, Mark D

2016-01-01

The objectives of this research were to 1) summarize the available evidence on the impact of hearing loss on quality of life (QOL) among U.S. active-duty service members, 2) describe the QOL instruments that have been used to quantify the impact of hearing loss on quality of life, 3) examine national population-level secondary databases and report on their utility for studying the impact of hearing loss on QOL among active-duty service members, and 4) provide recommendations for future studies that seek to quantify the impact of hearing loss in this population. There is a lack of literature that addresses the intersection of hearing impairment, the military population, and quality of life measures. For audiological research, U.S. military personnel offer a unique research population, as they are exposed to noise levels and blast environments that are highly unusual in civilian work settings and can serve as a model population for studying the impact on QOL associated with these conditions. Our team recommends conducting a study on the active-duty service member population using a measurement instrument suitable for determining decreases in QOL specifically due to hearing loss.

What impact might mitigation of diffuse nitrate pollution have on river water quality in a rural catchment?

PubMed

Hutchins, Michael G

2012-10-30

Observations of river flow, river quality and solar radiation were collated to assess the degree to which light and nutrients may be limiting phytoplankton growth at seven sites in the River Ouse catchment in NE England under average conditions. Hydraulic information derived from river network model applications was then used to determine where river water has sufficient residence time above the tidal limit to facilitate bloom development. A nitrate model (NALTRACES) was developed to estimate the impact of land management change on mean river nitrate concentrations. Applications of this model showed that although agricultural activity contributes substantially to nitrate loads in the Ouse it is likely to have little impact on phytoplankton growth, which could still occur extensively in its absence given favourable sunny and dry conditions. As an example of a means of controlling light availability, establishing full riparian tree cover would appear to be a considerably more effective management scenario than suppressing inputs to the river of nitrate or phosphorus. Any actions should be prioritised in headwater areas such as the upper reaches of the Swale and Ure tributaries. These conclusions are in broad agreement with those arising from more detailed simulations at daily resolution using the QUESTOR river quality model. The combination of simple modelling approaches applied here allows an initial identification of suitable spatially-targeted options for mitigating against phytoplankton blooms which can be applied more widely at a regional or national level. Copyright © 2012 Elsevier Ltd. All rights reserved.

Creating a Methodology for Coordinating High-resolution Air Quality Improvement Map and Greenhouse Gas Mitigation Strategies in Pittsburgh City

NASA Astrophysics Data System (ADS)

Shi, J.; Donahue, N. M.; Klima, K.; Blackhurst, M.

2016-12-01

In order to tradeoff global impacts of greenhouse gases with highly local impacts of conventional air pollution, researchers require a method to compare global and regional impacts. Unfortunately, we are not aware of a method that allows these to be compared, "apples-to-apples". In this research we propose a three-step model to compare possible city-wide actions to reduce greenhouse gases and conventional air pollutants. We focus on Pittsburgh, PA, a city with consistently poor air quality that is interested in reducing both greenhouse gases and conventional air pollutants. First, we use the 2013 Pittsburgh Greenhouse Gas Inventory to update the Blackhurst et al. model and conduct a greenhouse gas abatement potentials and implementation costs of proposed greenhouse gas reduction efforts. Second, we use field tests for PM2.5, NOx, SOx, organic carbon (OC) and elemental carbon (EC) data to inform a Land-use Regression Model for local air pollution at a 100m x 100m spatial level, which combined with a social cost of air pollution model (EASIUR) allows us to calculate economic social damages. Third, we combine these two models into a three-dimensional greenhouse gas cost abatement curve to understand the implementation costs and social benefits in terms of air quality improvement and greenhouse gas abatement for each potential intervention. We anticipated such results could provide policy-maker insights in green city development.

Evaluating the Impact of Aerosols on Numerical Weather Prediction

NASA Astrophysics Data System (ADS)

Freitas, Saulo; Silva, Arlindo; Benedetti, Angela; Grell, Georg; Members, Wgne; Zarzur, Mauricio

2015-04-01

The Working Group on Numerical Experimentation (WMO, http://www.wmo.int/pages/about/sec/rescrosscut/resdept_wgne.html) has organized an exercise to evaluate the impact of aerosols on NWP. This exercise will involve regional and global models currently used for weather forecast by the operational centers worldwide and aims at addressing the following questions: a) How important are aerosols for predicting the physical system (NWP, seasonal, climate) as distinct from predicting the aerosols themselves? b) How important is atmospheric model quality for air quality forecasting? c) What are the current capabilities of NWP models to simulate aerosol impacts on weather prediction? Toward this goal we have selected 3 strong or persistent events of aerosol pollution worldwide that could be fairly represented in current NWP models and that allowed for an evaluation of the aerosol impact on weather prediction. The selected events includes a strong dust storm that blew off the coast of Libya and over the Mediterranean, an extremely severe episode of air pollution in Beijing and surrounding areas, and an extreme case of biomass burning smoke in Brazil. The experimental design calls for simulations with and without explicitly accounting for aerosol feedbacks in the cloud and radiation parameterizations. In this presentation we will summarize the results of this study focusing on the evaluation of model performance in terms of its ability to faithfully simulate aerosol optical depth, and the assessment of the aerosol impact on the predictions of near surface wind, temperature, humidity, rainfall and the surface energy budget.

Automated Quality Control of in Situ Soil Moisture from the North American Soil Moisture Database Using NLDAS-2 Products

NASA Astrophysics Data System (ADS)

Ek, M. B.; Xia, Y.; Ford, T.; Wu, Y.; Quiring, S. M.

2015-12-01

The North American Soil Moisture Database (NASMD) was initiated in 2011 to provide support for developing climate forecasting tools, calibrating land surface models and validating satellite-derived soil moisture algorithms. The NASMD has collected data from over 30 soil moisture observation networks providing millions of in situ soil moisture observations in all 50 states as well as Canada and Mexico. It is recognized that the quality of measured soil moisture in NASMD is highly variable due to the diversity of climatological conditions, land cover, soil texture, and topographies of the stations and differences in measurement devices (e.g., sensors) and installation. It is also recognized that error, inaccuracy and imprecision in the data set can have significant impacts on practical operations and scientific studies. Therefore, developing an appropriate quality control procedure is essential to ensure the data is of the best quality. In this study, an automated quality control approach is developed using the North American Land Data Assimilation System phase 2 (NLDAS-2) Noah soil porosity, soil temperature, and fraction of liquid and total soil moisture to flag erroneous and/or spurious measurements. Overall results show that this approach is able to flag unreasonable values when the soil is partially frozen. A validation example using NLDAS-2 multiple model soil moisture products at the 20 cm soil layer showed that the quality control procedure had a significant positive impact in Alabama, North Carolina, and West Texas. It had a greater impact in colder regions, particularly during spring and autumn. Over 433 NASMD stations have been quality controlled using the methodology proposed in this study, and the algorithm will be implemented to control data quality from the other ~1,200 NASMD stations in the near future.

Future shifts in African air quality and the resulting impacts on human health and climate: Design of efficient mitigation strategies.

NASA Astrophysics Data System (ADS)

Lacey, F.; Marais, E. A.; Wiedinmyer, C.; Coffey, E.; Pfotenhauer, D.; Henze, D. K.; Evans, M. J.; Hannigan, M.; Morris, E.; Davila, Y.; Mesenbring, E. C.

2017-12-01

Population in Africa is currently projected to double by 2050, which will have significant impacts on anthropogenic emissions and in turn the ambient air quality, especially near population centers. Recent research has also shown that the emissions factors used for global inventories are misrepresented when compared to field measurements in Africa, which leads to inaccuracies in the magnitude and spatial distribution of emissions throughout the continent. As the population in Africa increases, the combination of anthropogenic and biogenic emissions in many regions will lead to changes in atmospheric pollutant concentrations, including particulate matter (PM2.5) and ozone. Combining updated emissions estimates created using measured emissions factors reported from field studies in Africa with the Community Earth System Model (CESM2) improves predictions of the present day ambient air quality; validated based on available observations from field measurements and satellite data. We use these tools to quantify the impacts of anthropogenic emissions on both climate and human health, shown here as estimated premature deaths from chronic exposure to pollutants. Sensitivities derived from model source attribution calculations using the GEOS-Chem adjoint model are then used to examine the impacts of changes in population distribution and shifts in technology moving to the mid-21st century. With these results, we are able to identify efficient mitigation pathways that target specific regions and anthropogenic activities. These targeted control measures include shifts from traditional to modern cooking technologies, as well as other sector-specific interventions that represent feasible adoptions in Africa over the next several decades. This work provides a potential roadmap towards improved air quality to both government and non-governmental organizations as Africa transitions through this period of rapid growth.

Modelling the impacts of global change on concentrations of Escherichia coli in an urban river

NASA Astrophysics Data System (ADS)

Jalliffier-Verne, Isabelle; Leconte, Robert; Huaringa-Alvarez, Uriel; Heniche, Mourad; Madoux-Humery, Anne-Sophie; Autixier, Laurène; Galarneau, Martine; Servais, Pierre; Prévost, Michèle; Dorner, Sarah

2017-10-01

Discharges of combined sewer system overflows (CSOs) affect water quality in drinking water sources despite increasing regulation and discharge restrictions. A hydrodynamic model was applied to simulate the transport and dispersion of fecal contaminants from CSO discharges and to quantify the impacts of climate and population changes on the water quality of the river used as a drinking water source in Québec, Canada. The dispersion model was used to quantify Escherichia coli (E. coli) concentrations at drinking water intakes. Extreme flows during high and low water events were based on a frequency analysis in current and future climate scenarios. The increase of the number of discharges was quantified in current and future climate scenarios with regards to the frequency of overflows observed between 2009 and 2012. For future climate scenarios, effects of an increase of population were estimated according to current population growth statistics, independently of local changes in precipitation that are more difficult to predict than changes to regional scale hydrology. Under ;business-as-usual; scenarios restricting increases in CSO discharge frequency, mean E. coli concentrations at downstream drinking water intakes are expected to increase by up to 87% depending on the future climate scenario and could lead to changes in drinking water treatment requirements for the worst case scenarios. The greatest uncertainties are related to future local discharge loads. Climate change adaptation with regards to drinking water quality must focus on characterizing the impacts of global change at a local scale. Source water protection planning must consider the impacts of climate and population change to avoid further degradation of water quality.

Evaluating the impact of chemical boundary conditions on near surface ozone in regional climate-air quality simulations over Europe

NASA Astrophysics Data System (ADS)

Akritidis, D.; Zanis, P.; Katragkou, E.; Schultz, M. G.; Tegoulias, I.; Poupkou, A.; Markakis, K.; Pytharoulis, I.; Karacostas, Th.

2013-12-01

A modeling system based on the air quality model CAMx driven off-line by the regional climate model RegCM3 is used for assessing the impact of chemical lateral boundary conditions (LBCs) on near surface ozone over Europe for the period 1996-2000. The RegCM3 and CAMx simulations were performed on a 50 km × 50 km grid over Europe with RegCM3 driven by the NCEP meteorological reanalysis fields and CAMx with chemical LBCs from ECHAM5/MOZART global model. The recent past period (1996-2000) was simulated in three experiments. The first simulation was forced using time and space invariant LBCs, the second was based on ECHAM5/MOZART chemical LBCs fixed for the year 1996 and the third was based on ECHAM5/MOZART chemical LBCs with interannual variability. Anthropogenic and biogenic emissions were kept identical for the three sensitivity runs.

Impact of combustion products from Space Shuttle launches on ambient air quality

NASA Technical Reports Server (NTRS)

Dumbauld, R. K.; Bowers, J. F.; Cramer, H. E.

1974-01-01

The present work describes some multilayer diffusion models and a computer program for these models developed to predict the impact of ground clouds formed during Space Shuttle launches on ambient air quality. The diffusion models are based on the Gaussian plume equation for an instantaneous volume source. Cloud growth is estimated on the basis of measurable meteorological parameters: standard deviation of the wind azimuth angle, standard deviation of wind elevation angle, vertical wind-speed shear, vertical wind-direction shear, and depth of the surface mixing layer. Calculations using these models indicate that Space Shuttle launches under a variety of meteorological regimes at Kennedy Space Center and Vandenberg AFB are unlikely to endanger the exposure standards for HCl; similar results have been obtained for CO and Al2O3. However, the possibility that precipitation scavenging of the ground cloud might result in an acidic rain that could damage vegetation has not been investigated.

Diabetes-related quality of life is enhanced by glycaemic improvement in older people.

PubMed

Abbatecola, A M; Spazzafumo, L; Fabbietti, P; Testa, R; Rabini, R A; Bonfigli, A R; Corsonello, A; Lattanzio, F; Paolisso, G

2015-02-01

To investigate the validity and reliability of the Audit of Diabetes-Dependent Quality of Life instrument in older Italians with diabetes and to test the association of diabetes-related quality of life with glycaemic control over time. A total of 558 outpatients with Type 2 diabetes from the Diabetic Unit of the Italian National Research Centre on Aging Hospital in Ancona were enrolled to complete questionnaires (Audit of Diabetes-Dependent Quality of Life-19 and the Short-Form-12), and to undergo clinical and biochemical testing at baseline and at 12 months of follow-up. The overall impact of diabetes using the average weighted impact score from the Audit of Diabetes-Dependent Quality of Life questionnaire was calculated. Participants were categorized according to this score as having either less or more negative diabetes-related quality of life. Participants had a mean ± SD age of 67.7 ± 9.2 years and 51.8% were male. Factor analysis and Cronbach's coefficient of internal consistency (Cronbach's α = 0.931) confirmed that the 19 domain-specific Audit of Diabetes-Dependent Quality of Life items could be combined into a single scale in this Italian population. The impact score correlated with the physical (r = 0.275; P < 0.001) and mental components (r = 0.291; P < 0.001) of the Short-Form-12 questionnaire. Significant differences were found according to diabetic complications in specific Audit of Diabetes-Dependent Quality of Life items and impact scores. Insulin use had a greater association with a more negative quality of life compared with other antidiabetic agents. A multivariate linear regression model with restricted linear spline application showed that the relationship between HbA1c and impact score was not linear and that the change in the impact score was associated with improved glycaemic control in those with a less negative diabetes-related quality of life at 12 months. The Audit of Diabetes-Dependent Quality of Life-19 is a valid tool for measuring the impact of diabetes on quality of life in older Italians. Perception of diabetes-related quality of life is associated with glycaemic control over time. © 2014 The Authors. Diabetic Medicine © 2014 Diabetes UK.

Integrated Assessment of Health-related Economic Impacts of U.S. Air Pollution Policy

NASA Astrophysics Data System (ADS)

Saari, R. K.; Rausch, S.; Selin, N. E.

2012-12-01

We examine the environmental impacts, health-related economic benefits, and distributional effects of new US regulations to reduce smog from power plants, namely: the Cross-State Air Pollution Rule. Using integrated assessment methods, linking atmospheric and economic models, we assess the magnitude of economy-wide effects and distributional consequences that are not captured by traditional regulatory impact assessment methods. We study the Cross-State Air Pollution Rule, a modified allowance trading scheme that caps emissions of nitrogen oxides and sulfur dioxide from power plants in the eastern United States and thus reduces ozone and particulate matter pollution. We use results from the regulatory regional air quality model, CAMx (the Comprehensive Air Quality Model with extensions), and epidemiologic studies in BenMAP (Environmental Benefits Mapping and Analysis Program), to quantify differences in morbidities and mortalities due to this policy. To assess the economy-wide and distributional consequences of these health impacts, we apply a recently developed economic and policy model, the US Regional Energy and Environmental Policy Model (USREP), a multi-region, multi-sector, multi-household, recursive dynamic computable general equilibrium economic model of the US that provides a detailed representation of the energy sector, and the ability to represent energy and environmental policies. We add to USREP a representation of air pollution impacts, including the estimation and valuation of health outcomes and their effects on health services, welfare, and factor markets. We find that the economic welfare benefits of the Rule are underestimated by traditional methods, which omit economy-wide impacts. We also quantify the distribution of benefits, which have varying effects across US regions, income groups, and pollutants, and we identify factors influencing this distribution, including the geographic variation of pollution and population as well as underlying economic conditions.

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.

Global trends in milk quality: implications for the Irish dairy industry

PubMed Central

2009-01-01

The quality of Irish agricultural product will become increasingly important with the ongoing liberalisation of international trade. This paper presents a review of the global and Irish dairy industries; considers the impact of milk quality on farm profitability, food processing and human health, examines global trends in quality; and explores several models that are successfully being used to tackle milk quality concerns. There is a growing global demand for dairy products, fuelled in part by growing consumer wealth in developing countries. Global dairy trade represents only 6.2% of global production and demand currently outstrips supply. Although the Irish dairy industry is small by global standards, approximately 85% of annual production is exported annually. It is also the world's largest producer of powdered infant formula. Milk quality has an impact on human health, milk processing and on-farm profitability. Somatic cell count (SCC) is a key measure of milk quality, with a SCC not exceeding 400,000 cells/ml (the EU milk quality standard) generally accepted as the international export standard. There have been ongoing improvements in milk quality among both established and emerging international suppliers. A number of countries have developed successful industry-led models to tackle milk quality concerns. Based on international experiences, it is likely that problems with effective translation of knowledge to practice, rather than incomplete knowledge per se, are the more important constraints to national progress towards improved milk quality. PMID:22081986

Students worry about the impact of alcohol on quality of life: Roles of frequency of binge drinking and drinker self-concept.

PubMed

Luquiens, A; Falissard, B; Aubin, H J

2016-10-01

The aim of this study was to clarify the impact of binge drinking, its intensity and frequency, and drinker self-concept on health-related quality-of-life (HRQOL) in students. This cross-sectional online survey included 16,930 students. We collected sociodemographics, environmental data, and drinking behaviors. We assessed HRQOL using the Alcohol Quality-of-Life scale, which explicitly explores the subjective negative impact on quality of life one attributes to his relationship with alcohol and the degree to which drinking is a part of an individual's self-concept. Data analyses were performed in 2015 and 2016. We described and compared binge drinkers and non-binge drinkers. Using a regression model we identified the independent factors associated with HRQOL. The impact on HRQOL attributed to alcohol was significantly greater among binge drinkers. Factors of impact on HRQOL subjectively attributed to alcohol by students were: AUDIT-C score, interaction between gender and AUDIT-C score, strong individual identity as a drinker, binge-drinking frequency, financial difficulties, being a foreigner, fewer years since diploma, chronic condition, recent use of cannabis, psychostimulant, poppers or gambling. Sleep quality, ability to work, expenditure on alcohol, shame, and health-related concerns were the most strongly impacted quality of life areas. Binge-drinking frequency should be considered as an important target in prevention programs. In addition, integrating findings on students' subjective perceptions of impairment of HRQOL by alcohol could enable the development of more acceptable and more relevant prevention messages. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Influence of air quality model resolution on uncertainty associated with health impacts

NASA Astrophysics Data System (ADS)

Thompson, T. M.; Selin, N. E.

2012-10-01

We use regional air quality modeling to evaluate the impact of model resolution on uncertainty associated with the human health benefits resulting from proposed air quality regulations. Using a regional photochemical model (CAMx), we ran a modeling episode with meteorological inputs simulating conditions as they occurred during August through September 2006 (a period representative of conditions leading to high ozone), and two emissions inventories (a 2006 base case and a 2018 proposed control scenario, both for Houston, Texas) at 36, 12, 4 and 2 km resolution. The base case model performance was evaluated for each resolution against daily maximum 8-h averaged ozone measured at monitoring stations. Results from each resolution were more similar to each other than they were to measured values. Population-weighted ozone concentrations were calculated for each resolution and applied to concentration response functions (with 95% confidence intervals) to estimate the health impacts of modeled ozone reduction from the base case to the control scenario. We found that estimated avoided mortalities were not significantly different between the 2, 4 and 12 km resolution runs, but the 36 km resolution may over-predict some potential health impacts. Given the cost/benefit analysis requirements motivated by Executive Order 12866 as it applies to the Clean Air Act, the uncertainty associated with human health impacts and therefore the results reported in this study, we conclude that health impacts calculated from population weighted ozone concentrations obtained using regional photochemical models at 36 km resolution fall within the range of values obtained using fine (12 km or finer) resolution modeling. However, in some cases, 36 km resolution may not be fine enough to statistically replicate the results achieved using 2, 4 or 12 km resolution. On average, when modeling at 36 km resolution, an estimated 5 deaths per week during the May through September ozone season are avoided because of ozone reductions resulting from the proposed emissions reductions (95% confidence interval was 2-8). When modeling at 2, 4 or 12 km finer scale resolution, on average 4 deaths are avoided due to the same reductions (95% confidence interval was 1-7). Study results show that ozone modeling at a resolution finer than 12 km is unlikely to reduce uncertainty in benefits analysis for this specific region. We suggest that 12 km resolution may be appropriate for uncertainty analyses of health impacts due to ozone control scenarios, in areas with similar chemistry, meteorology and population density, but that resolution requirements should be assessed on a case-by-case basis and revised as confidence intervals for concentration-response functions are updated.

Leadership and globalization: research in health management education.

PubMed

West, Daniel J; Ramirez, Bernardo; Filerman, Gary

2012-01-01

The impact of globalization on graduate health care management education is evident, yet challenging to quantify. The Commission on Healthcare Management Education (CAHME) recently authorized two research studies to gather specific information and answer important questions about accredited graduate programs in the USA and Canada. Two surveys provided the most comprehensive data impacting international health management education efforts by 70 programs. An inventory was made of 22 countries; information was compiled on 21 accrediting or quality improvement organizations. Observations on leadership and the demand for qualified health care professionals is discussed in terms of accreditation, certification, competency models, outcome assessment, improving quality, and the impact of globalization on higher education.

Experimental investigation and modelling approach of the impact of urban wastewater on a tropical river; a case study of the Nhue River, Hanoi, Viet Nam

NASA Astrophysics Data System (ADS)

Duc, Trinh Anh; Vachaud, Georges; Bonnet, Marie Paule; Prieur, Nicolas; Loi, Vu Duc; Anh, Le Lan

2007-02-01

SummaryAnalyses of water quality and flow regime in combination with laboratory studies and ecological modelling were used to assess the water quality impact of pollution from to To Lich River that drains through Hanoi City and greatly contaminates the Nhue River. With an average discharge of 26.2 m 3/s, the Nhue River receives about 5.8 m 3/s of untreated domestic water from the city's main open-air-sewer - the To Lich River. The studies during 2002-2003 showed high concentrations of BOD (70 mg O 2/l), DOC (15 mg C/l), coliform (2.4e 6 MNP/100 ml), total phosphorus (3.5 mg P/l), and total nitrogen (31.6 mg N/l) in the To Lich, while DO level was less than 1 mg O 2/l. Such high loads of untreated wastewater impacted water quality in the Nhue River where DO decreased at times to as low as 1 mg O 2/l. The accumulation of particulate organic matter and micro-organisms in the sediments of the Nhue represented substantial sources of nutrients and sinks for DO. They are also considerable production of dissolved carbon dioxide at concentrations up to two orders of magnitude higher than pressure. Such pressures ( EpCO 2) are expected in polluted environments, but the results presented here are new for Vietnam and much of developing countries. A number of factors linked to field monitoring and laboratory measurements clearly indicate the importance of autotrophic over heterotrophic biological processes and sediments. An ecological model for management purposes has been developed that reliably estimates of the pollutant loads. An opportunity was taken to examine the changing impacts and processes when the To Lich was diverted from the Nhue. The monitoring and modelling of this opportunity showed low dissolved oxygen levels even if the impact from the To Lich was lessened. Alternatives are proposed to alleviate problems of water quality in the Nhue. It is concluded that the treatment of the To Lich River's water is highly recommended; otherwise a reduction to one third of current wastewater discharge is needed to bring water quality back to the environmental standard.

Impact of rain gauge quality control and interpolation on streamflow simulation: an application to the Warwick catchment, Australia

NASA Astrophysics Data System (ADS)

Liu, Shulun; Li, Yuan; Pauwels, Valentijn R. N.; Walker, Jeffrey P.

2017-12-01

Rain gauges are widely used to obtain temporally continuous point rainfall records, which are then interpolated into spatially continuous data to force hydrological models. However, rainfall measurements and interpolation procedure are subject to various uncertainties, which can be reduced by applying quality control and selecting appropriate spatial interpolation approaches. Consequently, the integrated impact of rainfall quality control and interpolation on streamflow simulation has attracted increased attention but not been fully addressed. This study applies a quality control procedure to the hourly rainfall measurements obtained in the Warwick catchment in eastern Australia. The grid-based daily precipitation from the Australian Water Availability Project was used as a reference. The Pearson correlation coefficient between the daily accumulation of gauged rainfall and the reference data was used to eliminate gauges with significant quality issues. The unrealistic outliers were censored based on a comparison between gauged rainfall and the reference. Four interpolation methods, including the inverse distance weighting (IDW), nearest neighbors (NN), linear spline (LN), and ordinary Kriging (OK), were implemented. The four methods were firstly assessed through a cross-validation using the quality-controlled rainfall data. The impacts of the quality control and interpolation on streamflow simulation were then evaluated through a semi-distributed hydrological model. The results showed that the Nash–Sutcliffe model efficiency coefficient (NSE) and Bias of the streamflow simulations were significantly improved after quality control. In the cross-validation, the IDW and OK methods resulted in good interpolation rainfall, while the NN led to the worst result. In term of the impact on hydrological prediction, the IDW led to the most consistent streamflow predictions with the observations, according to the validation at five streamflow-gauged locations. The OK method performed second best according to streamflow predictions at the five gauges in the calibration period (01/01/2007–31/12/2011) and four gauges during the validation period (01/01/2012–30/06/2014). However, NN produced the worst prediction at the outlet of the catchment in the validation period, indicating a low robustness. While the IDW exhibited the best performance in the study catchment in terms of accuracy, robustness and efficiency, more general recommendations on the selection of rainfall interpolation methods need to be further explored.

Impact of rain gauge quality control and interpolation on streamflow simulation: an application to the Warwick catchment, Australia

NASA Astrophysics Data System (ADS)

Liu, Shulun; Li, Yuan; Pauwels, Valentijn R. N.; Walker, Jeffrey P.

2018-01-01

Rain gauges are widely used to obtain temporally continuous point rainfall records, which are then interpolated into spatially continuous data to force hydrological models. However, rainfall measurements and interpolation procedure are subject to various uncertainties, which can be reduced by applying quality control and selecting appropriate spatial interpolation approaches. Consequently, the integrated impact of rainfall quality control and interpolation on streamflow simulation has attracted increased attention but not been fully addressed. This study applies a quality control procedure to the hourly rainfall measurements obtained in the Warwick catchment in eastern Australia. The grid-based daily precipitation from the Australian Water Availability Project was used as a reference. The Pearson correlation coefficient between the daily accumulation of gauged rainfall and the reference data was used to eliminate gauges with significant quality issues. The unrealistic outliers were censored based on a comparison between gauged rainfall and the reference. Four interpolation methods, including the inverse distance weighting (IDW), nearest neighbors (NN), linear spline (LN), and ordinary Kriging (OK), were implemented. The four methods were firstly assessed through a cross-validation using the quality-controlled rainfall data. The impacts of the quality control and interpolation on streamflow simulation were then evaluated through a semi-distributed hydrological model. The results showed that the Nash–Sutcliffe model efficiency coefficient (NSE) and Bias of the streamflow simulations were significantly improved after quality control. In the cross-validation, the IDW and OK methods resulted in good interpolation rainfall, while the NN led to the worst result. In term of the impact on hydrological prediction, the IDW led to the most consistent streamflow predictions with the observations, according to the validation at five streamflow-gauged locations. The OK method performed second best according to streamflow predictions at the five gauges in the calibration period (01/01/2007–31/12/2011) and four gauges during the validation period (01/01/2012–30/06/2014). However, NN produced the worst prediction at the outlet of the catchment in the validation period, indicating a low robustness. While the IDW exhibited the best performance in the study catchment in terms of accuracy, robustness and efficiency, more general recommendations on the selection of rainfall interpolation methods need to be further explored.

Urban Landscape Characterization Using Remote Sensing Data For Input into Air Quality Modeling

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William; Khan, Maudood

2005-01-01

The urban landscape is inherently complex and this complexity is not adequately captured in air quality models that are used to assess whether urban areas are in attainment of EPA air quality standards, particularly for ground level ozone. This inadequacy of air quality models to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well these models predict ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to meteorological and air quality models focusing on the Atlanta, Georgia metropolitan area as a case study. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the Community Multiscale Air Quality (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality.

Using proxies to explore ensemble uncertainty in climate impact studies: the example of air pollution

NASA Astrophysics Data System (ADS)

Lemaire, V. E. P.; Colette, A.; Menut, L.

2015-10-01

Because of its sensitivity to unfavorable weather patterns, air pollution is sensitive to climate change so that, in the future, a climate penalty could jeopardize the expected efficiency of air pollution mitigation measures. A common method to assess the impact of climate on air quality consists in implementing chemistry-transport models forced by climate projection. However, the computing cost of such method requires optimizing ensemble exploration techniques. By using a training dataset of deterministic projection of climate and air quality over Europe, we identified the main meteorological drivers of air quality for 8 regions in Europe and developed simple statistical models that could be used to predict air pollutant concentrations. The evolution of the key climate variables driving either particulate or gaseous pollution allows concluding on the robustness of the climate impact on air quality. The climate benefit for PM2.5 was confirmed -0.96 (±0.18), -1.00 (±0.37), -1.16 ± (0.23) μg m-3, for resp. Eastern Europe, Mid Europe and Northern Italy and for the Eastern Europe, France, Iberian Peninsula, Mid Europe and Northern Italy regions a climate penalty on ozone was identified 10.11 (±3.22), 8.23 (±2.06), 9.23 (±1.13), 6.41 (±2.14), 7.43 (±2.02) μg m-3. This technique also allows selecting a subset of relevant regional climate model members that should be used in priority for future deterministic projections.

Negligible impact of differential item functioning between Black and White dialysis patients on the Kidney Disease Quality of Life 36-item short form survey (KDQOLTM-36).

PubMed

Peipert, John D; Bentler, Peter; Klicko, Kristi; Hays, Ron D

2018-05-14

Black dialysis patients report better health-related quality of life (HRQOL) than White patients, which may be explained if Black and White patients respond systematically differently to HRQOL survey items. We examined differential item functioning (DIF) of the Kidney Disease Quality of Life 36-item (KDQOL TM -36) Burden of Kidney Disease, Symptoms and Problems with Kidney Disease, and Effects of Kidney Disease scales between Black (n = 18,404) and White (n = 21,439) dialysis patients. We fit multiple group confirmatory factor analysis models with increasing invariance: a Configural model (invariant factor structure), a Metric model (invariant factor loadings), and a Scalar model (invariant intercepts). Criteria for invariance included non-significant χ 2 tests, > 0.002 difference in the models' CFI, and > 0.015 difference in RMSEA and SRMR. Next, starting with a fully invariant model, we freed loadings and intercepts item-by-item to determine if DIF impacted estimated KDQOL TM -36 scale means. ΔCFI was 0.006 between the metric and scalar models but was reduced to 0.001 when we freed intercepts for the burdens and symptoms and problems of kidney disease scales. In comparison to standardized means of 0 in the White group, those for the Black group on the Burdens, Symptoms and Problems, and Effects of Kidney Disease scales were 0.218, 0.061, and 0.161, respectively. When loadings and thresholds were released sequentially, differences in means between models ranged between 0.001 and 0.048. Despite some DIF, impacts on KDQOL TM -36 responses appear to be minimal. We conclude that the KDQOL TM -36 is appropriate to make substantive comparisons of HRQOL between Black and White dialysis patients.

Assessing Receiving Water Quality Impacts due to Flow Path Alteration in Residential Catchments, using the Stormwater and Wastewater Management Model

NASA Astrophysics Data System (ADS)

Wolosoff, S. E.; Duncan, J.; Endreny, T.

2001-05-01

The Croton water supply system, responsible for supplying approximately 10% of New York City's water, provides an opportunity for exploration into the impacts of significant terrestrial flow path alteration upon receiving water quality. Natural flow paths are altered during residential development in order to allow for construction at a given location, reductions in water table elevation in low lying areas and to provide drainage of increased overland flow volumes. Runoff conducted through an artificial drainage system, is prevented from being attenuated by the natural environment, thus the pollutant removal capacity inherent in most natural catchments is often limited to areas where flow paths are not altered by development. By contrasting the impacts of flow path alterations in two small catchments in the Croton system, with different densities of residential development, we can begin to identify appropriate limits to the re-routing of runoff in catchments draining into surface water supplies. The Stormwater and Wastewater Management Model (SWMM) will be used as a tool to predict the runoff quantity and quality generated from two small residential catchments and to simulate the potential benefits of changes to the existing drainage system design, which may improve water quality due to longer residence times.

Impact of a Novel, Anti-microbial Dressing on In Vivo, Pseudomonas aeruginosa Wound Biofilm: Quantitative Comparative Analysis using a Rabbit Ear Model

DTIC Science & Technology

2014-12-01

previously pub- lished in vivo, wound biofilm model.19 Rabbits were anesthe- tized with intramuscular injection of a ketamine (22.5 mg/kg) and xylazine (3.5...22: 12–16. 3. Krasner D. Painful venous ulcers: themes and stories about their impact on quality of life. Ostomy Wound Manage 1998; 44: 38–49. 4

Prevention of Spacecraft Anomalies: The Role of Space Climate and Space Weather Models

NASA Technical Reports Server (NTRS)

Barth, Janet L.

2003-01-01

Space-based systems are developing into critical infrastructure to support the quality of life on Earth. Mission requirements along with rapidly evolving technologies have outpaced efforts to accommodate detrimental space environment impacts on systems. This chapter describes approaches to accommodate space climate and space weather impacts on systems and notes areas where gaps in model development limit our ability to prevent spacecraft anomalies.

Anthropogenic activities impact on atmospheric environmental quality in a gas-flaring community: application of fuzzy logic modelling concept.

PubMed

Akintola, Olayiwola Akin; Sangodoyin, Abimbola Yisau; Agunbiade, Foluso Oyedotun

2018-05-24

We present a modelling concept for evaluating the impacts of anthropogenic activities suspected to be from gas flaring on the quality of the atmosphere using domestic roof-harvested rainwater (DRHRW) as indicator. We analysed seven metals (Cu, Cd, Pb, Zn, Fe, Ca, and Mg) and six water quality parameters (acidity, PO 4 3- , SO 4 2- , NO 3 - , Cl - , and pH). These were used as input parameters in 12 sampling points from gas-flaring environments (Port Harcourt, Nigeria) using Ibadan as reference. We formulated the results of these input parameters into membership function fuzzy matrices based on four degrees of impact: extremely high, high, medium, and low, using regulatory limits as criteria. We generated indices that classified the degree of anthropogenic activity impact on the sites from the product membership function matrices and weight matrices, with investigated (gas-flaring) environment as between medium and high impact compared to those from reference (residential) environment that was classified as between low and medium impact. Major contaminants of concern found in the harvested rainwater were Pb and Cd. There is also the urgent need to stop gas-flaring activities in Port Harcourt area in particular and Niger Delta region of Nigeria in general, so as to minimise the untold health hazard that people living in the area are currently faced with. The fuzzy methodology presented has also indicated that the water cannot safely support potable uses and should not be consumed without purification due to the impact of anthropogenic activities in the area but may be useful for other domestic purposes.

Using NEXRAD and Rain Gauge Precipitation Data for Hydrologic Calibration of SWAT in a Northeastern Watershed

USDA-ARS?s Scientific Manuscript database

The value of watershed-scale, hydrologic/water quality models to ecosystem management is increasingly evident as more programs adopt these tools to evaluate the effectiveness of different management scenarios and their impact on the environment. Quality of precipitation data is critical for appropri...

Global Atmosphere Watch Workshop on Measurement-Model Fusion for Global Total Atmospheric Deposition (MMF-GTAD)

EPA Science Inventory

The World Meteorological Organization’s (WMO) Global Atmosphere Watch (GAW) Programme coordinates high-quality observations of atmospheric composition from global to local scales with the aim to drive high-quality and high-impact science while co-producing a new generation of pro...

Compartment-based hydrodynamics and water quality modeling of a NorthernEverglades Wetland, Florida, USA

EPA Science Inventory

The last remaining large remnant of softwater wetlands in the US Florida Everglades lies within the Arthur R. Marshall Loxahatchee National Wildlife Refuge. However, Refuge water quality today is impacted by pumped stormwater inflows to the eutrophic and mineral-enriched 100-km c...

IMPACTS OF CLIMATE-INDUCED CHANGES IN EXTREME EVENTS ON OZONE AND PARTICULATE MATTER AIR QUALITY

EPA Science Inventory

Historical data records of air pollution meteorology from multiple datasets will be compiled and analyzed to identify possible trends in extreme events. Changes in climate and air quality between 2010 and 2050 will be simulated with a suite of models. The consequential effe...

Educational transformation in upper-division physics: The Science Education Initiative model, outcomes, and lessons learned

NASA Astrophysics Data System (ADS)

Chasteen, Stephanie V.; Wilcox, Bethany; Caballero, Marcos D.; Perkins, Katherine K.; Pollock, Steven J.; Wieman, Carl E.

2015-12-01

[This paper is part of the Focused Collection on Upper Division Physics Courses.] In response to the need for a scalable, institutionally supported model of educational change, the Science Education Initiative (SEI) was created as an experiment in transforming course materials and faculty practices at two institutions—University of Colorado Boulder (CU) and University of British Columbia. We find that this departmentally focused model of change, which includes an explicit focus on course transformation as supported by a discipline-based postdoctoral education specialist, was generally effective in impacting courses and faculty across the institution. In CU's Department of Physics, the SEI effort focused primarily on upper-division courses, creating high-quality course materials, approaches, and assessments, and demonstrating an impact on student learning. We argue that the SEI implementation in the CU Physics Department, as compared to that in other departments, achieved more extensive impacts on specific course materials, and high-quality assessments, due to guidance by the physics education research group—but with more limited impact on the departmental faculty as a whole. We review the process and progress of the SEI Physics at CU and reflect on lessons learned in the CU Physics Department in particular. These results are useful in considering both institutional and faculty-led models of change and course transformation.

The Impacts of Policies To Meet The UK Climate Change Act Target on Air Quality - An Explicit Modelling Study

NASA Astrophysics Data System (ADS)

Williams, M.; Beevers, S.; Lott, M. C.; Kitwiroon, N.

2016-12-01

This paper presents a preliminary analysis of different pathways to meet the UK Climate Change Act target for 2050, of an 80% reduction in carbon dioxide equivalent emissions on a base year of 1990. The pathways can result in low levels of air pollution emissions through the use of renewables and nuclear power. But large increases in biomass burning and the continued use of diesel cars they can result in larger air quality impacts. The work evaluated the air quality impacts in several pathways using an energy system optimisation model (UK TIMES) and a chemical transport model (CMAQ). The work described in this paper goes beyond the `damage cost' approach where only emissions in each are assessed. In this work we used scenarios produced by the UK TIMES model which we converted into air pollution emissions. Emissions of ammonia from agriculture are not attributed to the energy system and are thus not captured by energy system models, yet are crucial in forming PM2.5, acknowledged to be currently the most important pollutant associated with premature deaths. Our model includes these emissions and other non-energy sources of hydrocarbons which lead to the formation of ozone, another significant cause of air pollution health impacts. A key policy issue is how much biogenic hydrocarbons contribute to ozone formation compared with man-made emissions. We modelled pollution concentrations at a resolution of 7 km across the UK and at 2km in urban areas. These results allow us to estimate changes in premature mortality and morbidity associated with the changes in air pollution and subsequently the economic cost of the impacts on public health. The work shows that in the `clean' scenario, urban exposures to particles (PM2.5) and NO2 could decrease by very large amounts, but ozone exposures are likely to increase without further significant reductions world-wide. Large increases in biomass use however could lead to increases in urban levels of carcinogens and primary PM.

78 FR 49516 - Agency Information Collection Activities: Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-14

... experiment with and evaluate several promising ideas related to improving the quality of children's health... evaluate the impact of a model pediatric electronic health record. Category E grantees are testing other... descriptive and inferential techniques appropriate to answering questions about outcomes and impacts...

Evaluating the Impacts of Transboundary Air pollution from China on Air Quality in the U.S. Using a Regression Framework

NASA Astrophysics Data System (ADS)

Ngo, N. S.; Bao, X.; Zhong, N.

2014-12-01

China is the largest emitter of anthropogenic air pollution in the world and previous work has shown the environmental impacts of the long-range transport (LRT) of air pollution from China to the U.S. via chemical transport models, in situ observations, isentropic back trajectories, and to a lesser extent statistical models. However, these studies generally focus on a narrow time period due to data constraints. In this study, we build upon the literature using econometric techniques to isolate the impacts on U.S. air quality from the LRT of air pollution from China. We use a unique daily data set of China's air pollution index (API) and PM10 concentrations at the city level and merge these information with daily monitor data in California (CA) between 2000 and 2013. We first employ a distributed lag model to examine daily patterns, and then exploit a "natural experiment." In the latter methodology, since air pollution is rarely randomly assigned, we examine the impacts of specific events that affect air quality in China, but are plausibly uncorrelated to factors affecting air pollution in CA. For example, Chinese New Year (CNY) is a major week-long holiday and we show pollution levels in China decrease during this time period, likely from reductions in industrial production. CNY varies each calendar year since it is based off the lunar new year, so the timing of this pollution reduction could be considered "as good as random" or exogenous to factors affecting air quality in CA. Using a regression framework including weather, seasonal and geographic controls, we can potentially isolate the impact of the LRT of air pollution to CA. First, results from the distributed lag model suggest that in the Spring, when LRT peaks, a 1 μg/m3 increase in daily PM10 from China between 10 and 14 days ago is associated with an increase in today's PM2.5 in CA of 0.022 μg/m3 (mean daily PM2.5 in CA is 12 μg/m3). Second, we find that if CNY occurred 5 to 9 days ago, today's PM2.5 in CA decreases by 3 μg/m3. We also conduct other tests and sensitivity checks, like observing impacts from individual cities in China or other events, and using daily leads as a falsification test. Our results have important policy implications regarding the consequences of foreign pollution sources and suggest a causal relationship between pollution from China and air quality in CA.

Potential Impacts of two SO2 oxidation pathways on regional sulfate concentrations: acqueous-hase oxidation by NO2 and gas-phase oxidation by Stabilized Criegee Intermediates

EPA Science Inventory

We examine the potential impacts of two additional sulfate production pathways using the Community Multiscale Air Quality modeling system. First we evaluate the impact of the aqueous-phase oxidation of S(IV) by nitrogen dioxide using two published rate constants, differing by 1-2...

Source partitioning of anthropogenic groundwater nitrogen in a mixed-use landscape, Tutuila, American Samoa

NASA Astrophysics Data System (ADS)

Shuler, Christopher K.; El-Kadi, Aly I.; Dulai, Henrietta; Glenn, Craig R.; Fackrell, Joseph

2017-12-01

This study presents a modeling framework for quantifying human impacts and for partitioning the sources of contamination related to water quality in the mixed-use landscape of a small tropical volcanic island. On Tutuila, the main island of American Samoa, production wells in the most populated region (the Tafuna-Leone Plain) produce most of the island's drinking water. However, much of this water has been deemed unsafe to drink since 2009. Tutuila has three predominant anthropogenic non-point-groundwater-pollution sources of concern: on-site disposal systems (OSDS), agricultural chemicals, and pig manure. These sources are broadly distributed throughout the landscape and are located near many drinking-water wells. Water quality analyses show a link between elevated levels of total dissolved groundwater nitrogen (TN) and areas with high non-point-source pollution density, suggesting that TN can be used as a tracer of groundwater contamination from these sources. The modeling framework used in this study integrates land-use information, hydrological data, and water quality analyses with nitrogen loading and transport models. The approach utilizes a numerical groundwater flow model, a nitrogen-loading model, and a multi-species contaminant transport model. Nitrogen from each source is modeled as an independent component in order to trace the impact from individual land-use activities. Model results are calibrated and validated with dissolved groundwater TN concentrations and inorganic δ15N values, respectively. Results indicate that OSDS contribute significantly more TN to Tutuila's aquifers than other sources, and thus should be prioritized in future water-quality management efforts.

Modeling the impacts of winter cover crops on water quality in two adjacent sub-watersheds within the Chesapeake Bay Watershed, Maryland, USA

USDA-ARS?s Scientific Manuscript database

The Choptank River on Maryland’s Eastern Shore has been designated by the USEPA as “impaired waters” under Section 303(d) of the Federal Clean Water Act of 1972, mainly because of significant nutrient loads that resulted in not meeting the EPA water quality standards. This water quality deteriorati...

Tamoxifen for breast cancer risk reduction: impact of alternative approaches to quality-of-life adjustment on cost-effectiveness analysis.

PubMed

Melnikow, Joy; Birch, Stephen; Slee, Christina; McCarthy, Theodore J; Helms, L Jay; Kuppermann, Miriam

2008-09-01

In cost-effectiveness analysis (CEA), the effects of health-care interventions on multiple health dimensions typically require consideration of both quantity and quality of life. To explore the impact of alternative approaches to quality-of-life adjustment using patient preferences (utilities) on the outcome of a CEA on use of tamoxifen for breast cancer risk reduction. A state transition Markov model tracked hypothetical cohorts of women who did or did not take 5 years of tamoxifen for breast cancer risk reduction. Incremental quality-adjusted effectiveness and cost-effectiveness ratios (ICERs) for models including and excluding a utility adjustment for menopausal symptoms were compared with each other and to a global utility model. Two hundred fifty-five women aged 50 and over with estimated 5-year breast cancer risk >or=1.67% participated in utility assessment interviews. Standard gamble utilities were assessed for specified tamoxifen-related health outcomes, current health, and for a global assessment of possible outcomes of tamoxifen use. Inclusion of a utility for menopausal symptoms in the outcome-specific models substantially increased the ICER; at the threshold 5-year breast cancer risk of 1.67%, tamoxifen was dominated. When a global utility for tamoxifen was used in place of outcome-specific utilities, tamoxifen was dominated under all circumstances. CEAs may be profoundly affected by the types of outcomes considered for quality-of-life adjustment and how these outcomes are grouped for utility assessment. Comparisons of ICERs across analyses must consider effects of different approaches to using utilities for quality-of-life adjustment.

Impact of Performance Obstacles on Intensive Care Nurses‘ Workload, Perceived Quality and Safety of Care, and Quality of Working Life

PubMed Central

Gurses, Ayse P; Carayon, Pascale; Wall, Melanie

2009-01-01

Objectives To study the impact of performance obstacles on intensive care nurses‘ workload, quality and safety of care, and quality of working life (QWL). Performance obstacles are factors that hinder nurses‘ capacity to perform their job and that are closely associated with their immediate work system. Data Sources/Study Setting Data were collected from 265 nurses in 17 intensive care units (ICUs) between February and August 2004 via a structured questionnaire, yielding a response rate of 80 percent. Study Design A cross-sectional study design was used. Data were analyzed by correlation analyses and structural equation modeling. Principal Findings Performance obstacles were found to affect perceived quality and safety of care and QWL of ICU nurses. Workload mediated the impact of performance obstacles with the exception of equipment-related issues on perceived quality and safety of care as well as QWL. Conclusions Performance obstacles in ICUs are a major determinant of nursing workload, perceived quality and safety of care, and QWL. In general, performance obstacles increase nursing workload, which in turn negatively affect perceived quality and safety of care and QWL. Redesigning the ICU work system to reduce performance obstacles may improve nurses‘ work. PMID:19207589

Multiscale predictions of aviation-attributable PM2.5 for US ...

EPA Pesticide Factsheets

Aviation activities represent an important and unique mode of transportation, but also impact air quality. In this study, we aim to quantify the impact of aircraft on air quality, focusing on aviation-attributable PM2.5 at scales ranging from local (a few kilometers) to continental (spanning hundreds of kilometers) using the Community Multiscale Air Quality-Advanced Plume Treatment (CMAQ-APT) model. In our CMAQ-APT simulations, a plume scale treatment is applied to aircraft emissions from 99 major U.S. airports over the contiguous U.S. in January and July 2005. In addition to the plume scale treatment, we account for the formation of non-traditional secondary organic aerosols (NTSOA) from the oxidation of semivolatile and intermediate volatility organic compounds (S/IVOCs) emitted from aircraft, and utilize alternative emission estimates from the Aerosol Dynamics Simulation Code (ADSC). ADSC is a 1-D plume scale model that estimates engine specific PM and S/IVOC emissions at ambient conditions, accounting for relative humidity and temperature. We estimated monthly and contiguous U.S. average aviation-attributable PM2.5 to be 2.7 ng m−3 in January and 2.6 ng m−3 in July using CMAQ-APT with ADSC emissions. This represents an increase of 40% and 12% in January and July, respectively, over impacts using traditional modeling approaches (traditional emissions without APT). The maximum fine scale (subgrid scale) hourly impacts at a major airport were 133.6 μg m−

The impacts of reactive terpene emissions from plants on air quality in Las Vegas, Nevada

NASA Astrophysics Data System (ADS)

Papiez, Maria R.; Potosnak, Mark J.; Goliff, Wendy S.; Guenther, Alex B.; Matsunaga, Sou N.; Stockwell, William R.

A three-part study was conducted to quantify the impact of landscaped vegetation on air quality in a rapidly expanding urban area in the arid southeastern United States. The study combines in situ, plant-level measurements, a spatial emissions inventory, and a photochemical box model. Maximum plant-level basal emission rates were moderate: 18.1 μgC gdw -1 h -1 ( Washingtonia spp., palms) for isoprene and 9.56 μgC gdw -1 h -1 ( Fraxinus velutina, Arizona ash) for monoterpenes. Sesquiterpene emission rates were low for plant species selected in this study, with no measurement exceeding 0.1 μgC gdw -1 h -1. The high ambient temperatures combined with moderate plant-level emission factors resulted in landscape emission factors that were low (250-640 μgC m -2 h -1) compared to more mesic environments (e.g., the southeastern United States). The Regional Atmospheric Chemistry Mechanism (RACM) was modified to include a new reaction pathway for ocimene. Using measured concentrations of anthropogenic hydrocarbons and other reactive air pollutants (NO x, ozone), the box model employing the RACM mechanism revealed that these modest emissions could have a significant impact on air quality. For a suburban location that was downwind of the urban core (high NO x; low anthropogenic hydrocarbons), biogenic terpenes increased time-dependent ozone production rates by a factor of 50. Our study demonstrates that low-biomass density landscapes emit sufficient biogenic terpenes to have a significant impact on regional air quality.

Impact of the 2008 Global Recession on Air Quality over the United States: Implications for Surface Ozone Levels from Changes in NOx Emissions

NASA Technical Reports Server (NTRS)

Tong, Daniel; Pan, Li; Chen, Weiwei; Lamsal, Lok; Lee, Pius; Tang, Youhua; Kim, Hyuncheol; Kondragunta, Shobha; Stajner, Ivanka

2016-01-01

Satellite and ground observations detected large variability in nitrogen oxides (NOx) during the 2008 economic recession, but the impact of the recession on air quality has not been quantified. This study combines observed NOx trends and a regional chemical transport model to quantify the impact of the recession on surface ozone (O3) levels over the continental United States. The impact is quantified by simulating O3 concentrations under two emission scenarios: business-as-usual (BAU) and recession. In the BAU case, the emission projection from the Cross-State Air Pollution Rule is used to estimate the would-be NOx emission level in 2011. In the recession case, the actual NO2 trends observed from Air Quality System ground monitors and the Ozone Monitoring Instrument on the Aura satellite are used to obtain realistic changes in NOx emissions. The model prediction with the recession effect agrees better with ground O3 observations over time and space than the prediction with the BAU emission. The results show that the recession caused a 12ppbv decrease in surface O3 concentration over the eastern United States, a slight increase (0.51ppbv) over the Rocky Mountain region, and mixed changes in the Pacific West. The gain in air quality benefits during the recession, however, could be quickly offset by the much slower emission reduction rate during the post-recession period.

Global Air Quality and Climate Impacts of Mitigating Short-lived Climate Pollution in China

NASA Astrophysics Data System (ADS)

Harper, K.; Unger, N.; Heyes, C.; Kiesewetter, G.; Klimont, Z.; Schoepp, W.; Wagner, F.

2014-12-01

China is a major emitter of harmful air pollutants, including the short-lived climate pollutants (SLCPs) and their precursors. Implementation of pollution control technologies provides a mechanism for simultaneously protecting human and ecosystem health and achieving near-term climate co-benefits; however, predicting the outcomes of technical and policy interventions is challenging because the SLCPs participate in both climate warming and cooling and share many common emission sources. Here, we present the results of a combined regional integrated assessment and global climate modeling study aimed at quantifying the near-term climate and air quality co-benefits of selective control of Chinese air pollution emissions. Results from IIASA's Greenhouse Gas - Air Pollution Interactions and Synergies (GAINS) integrated assessment model indicate that methane emission reductions make up > 75% of possible CO2-equivalent emission reductions of the SLCPs and their precursors in China in 2030. A multi-pollutant emission reduction scenario incorporating the 2030 Chinese pollution control measures with the highest potential for future climate impact is applied to the NASA ModelE2 - Yale Interactive Terrestrial Biosphere (NASA ModelE2-YIBs) global carbon - chemistry - climate model to assess the regional and long-range impacts of Chinese SLCP mitigation measures. Using model simulations that incorporate dynamic methane emissions and photosynthesis-dependent isoprene emissions, we quantify the impacts of Chinese reductions of the short-lived air pollutants on radiative forcing and on surface ozone and particulate air pollution. Present-day modeled methane mole fractions are evaluated against SCIAMACHY methane columns and NOAA ESRL/GMD surface flask measurements.

Impact of Apex Model parameterization strategy on estimated benefit of conservation practices

USDA-ARS?s Scientific Manuscript database

Three parameterized Agriculture Policy Environmental eXtender (APEX) models for corn-soybean rotation on clay pan soils were developed with the objectives, 1. Evaluate model performance of three parameterization strategies on a validation watershed; and 2. Compare predictions of water quality benefi...

The Impact of Spatial Correlation and Incommensurability on Model Evaluation

EPA Science Inventory

Standard evaluations of air quality models rely heavily on a direct comparison of monitoring data matched with the model output for the grid cell containing the monitor’s location. While such techniques may be adequate for some applications, conclusions are limited by such facto...

Better Water Demand and Pipe Description Improve the Distribution Network Modeling Results

EPA Science Inventory

Distribution system modeling simplifies pipe network in skeletonization and simulates the flow and water quality by using generalized water demand patterns. While widely used, the approach has not been examined fully on how it impacts the modeling fidelity. This study intends to ...

UNCERTAINTY AND THE JOHNSON-ETTINGER MODEL FOR VAPOR INTRUSION CALCULATIONS

EPA Science Inventory

The Johnson-Ettinger Model is widely used for assessing the impacts of contaminated vapors on residential air quality. Typical use of this model relies on a suite of estimated data, with few site-specific measurements. Software was developed to provide the public with automate...

The impact of past and future climate change on global human mortality due to ozone and PM2.5 outdoor air pollution

NASA Astrophysics Data System (ADS)

Silva, R.; West, J.; Anenberg, S.; Lamarque, J.; Shindell, D. T.; Bergmann, D. J.; Berntsen, T.; Cameron-Smith, P. J.; Collins, B.; Ghan, S. J.; Josse, B.; Nagashima, T.; Naik, V.; Plummer, D.; Rodriguez, J. M.; Szopa, S.; Zeng, G.

2012-12-01

Climate change can adversely affect air quality, through changes in meteorology, atmospheric chemistry, and emissions. Future changes in air pollutant emissions will also profoundly influence air quality. These changes in air quality can affect human health, as exposure to ground-level ozone and fine particulate matter (PM2.5) has been associated with premature human mortality. Here we will quantify the global mortality impacts of past and future climate change, considering the effects of climate change on air quality isolated from emission changes. The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) has simulated the past and future surface concentrations of ozone and PM2.5 from each of several GCMs, for emissions from 1850 ("preindustrial") to 2000 ("present-day"), and for the IPCC AR5 Representative Concentration Pathways (RCPs) scenarios to 2100. We will use ozone and PM2.5 concentrations from simulations from five or more global models of atmospheric dynamics and chemistry, for a base year (present-day), pre-industrial conditions, and future scenarios, considering changes in climate and emissions. We will assess the mortality impacts of past climate change by using one simulation ensemble with present emissions and climate and one with present emissions but 1850 climate. We will similarly quantify the potential impacts of future climate change under the four RCP scenarios in 2030, 2050 and 2100. All model outputs will be regridded to the same resolution to estimate multi-model medians and range in each grid cell. Resulting premature deaths will be calculated using these medians along with epidemiologically-derived concentration-response functions, and present-day or future projections of population and baseline mortality rates, considering aging and transitioning disease rates over time. The spatial distributions of current and future global premature mortalities due to ozone and PM2.5 outdoor air pollution will be presented separately. These results will strengthen our understanding of the impacts of climate change today, and in future years considering different plausible scenarios.

A comparison of methods for the assessment of odor impacts on air quality: Field inspection (VDI 3940) and the air dispersion model CALPUFF

NASA Astrophysics Data System (ADS)

Ranzato, Laura; Barausse, Alberto; Mantovani, Alice; Pittarello, Alberto; Benzo, Maurizio; Palmeri, Luca

2012-12-01

Unpleasant odors are a major cause of public complaints concerning air quality and represent a growing social problem in industrialized countries. However, the assessment of odor pollution is still regarded as a difficult task, because olfactory nuisance can be caused by many different chemical compounds, often found in hard-to-detect concentrations, and the perception of odors is influenced by subjective thresholds; moreover, the impact of odor sources on air quality is mediated by complex atmospheric dispersion processes. The development of standardized assessment approaches to odor pollution and proper international regulatory tools are urgently needed. In particular, comparisons of the methodologies commonly used nowadays to assess odor impacts on air quality are required. Here, we assess the olfactory nuisance caused by an anaerobic treatment plant for municipal solid waste by means of two alternative techniques: the field inspection procedure and the atmospheric dispersion model CALPUFF. Our goal was to compare rigorously their estimates of odor nuisance, both qualitatively (spatial extent of odor impact) and quantitatively (intensity of odor nuisance). To define the impact of odors, we referred to the German standards, based on the frequency of odor episodes in terms of odor hours. We report a satisfying, although not perfect agreement between the estimates provided by the two techniques. For example, they assessed similar spatial extents of odor pollution, but different frequencies of odor episodes in locations where the odor nuisance was highest. The comparison highlights strengths and weaknesses for both approaches. CALPUFF is a cheaper methodology which can be used predictively, but fugitive emissions are difficult to model reliably, because of uncertainty regarding timing, location and emission rate. Field inspection takes into account the role of human perception, but unlike the model it does not always characterize precisely the extent of the odor nuisance caused by a single source when other odors are present, because only the most unpleasant odor is reported. We conclude that these two assessment methods provide reasonable estimates of odor nuisance.

Can High Quality Overcome Consumer Resistance to Restricted Provider Access? Evidence from a Health Plan Choice Experiment

PubMed Central

Harris, Katherine M

2002-01-01

Objective To investigate the impact of quality information on the willingness of consumers to enroll in health plans that restrict provider access. Data Sources and Setting A survey administered to respondents between the ages of 25 and 64 in the West Los Angeles area with private health insurance. Study Design An experimental approach is used to measure the effect of variation in provider network features and information about the quality of network physicians on hypothetical plan choices. Conditional logit models are used to analyze the experimental choice data. Next, choice model parameter estimates are used to simulate the impact of changes in plan features on the market shares of competing health plans and to calculate the quality level required to make consumers indifferent to changes in provider access. Principal Findings The presence of quality information reduced the importance of provider network features in plan choices as hypothesized. However, there were not statistically meaningful differences by type of quality measure (i.e., consumer assessed versus expert assessed). The results imply that large quality differences are required to make consumers indifferent to changes in provider access. The impact of quality on plan choices depended more on the particular measure and less on the type of measure. Quality ratings based on the proportion of survey respondents “extremely satisfied with results of care” had the greatest impact on plan choice while the proportion of network doctors “affiliated with university medical centers” had the least. Other consumer and expert assessed measures had more comparable effects. Conclusions Overall the results provide empirical evidence that consumers are willing to trade high quality for restrictions on provider access. This willingness to trade implies that relatively small plans that place restrictions on provider access can successfully compete against less restrictive plans when they can demonstrate high quality. However, the results of this study suggest that in many cases, the level of quality required for consumers to accept access restrictions may be so high as to be unattainable. The results provide empirical support for the current focus of decision support efforts on consumer assessed quality measures. At the same time, however, the results suggest that consumers would also value quality measures based on expert assessments. This finding is relevant given the lack of comparative quality information based on expert judgment and research suggesting that consumers have apprehensions about their ability to meaningfully interpret performance-based quality measures. PMID:12132595

Simulating the Response of Urban Water Quality to Climate and Land Use Change in Partially Urbanized Basins

NASA Astrophysics Data System (ADS)

Sun, N.; Yearsley, J. R.; Nijssen, B.; Lettenmaier, D. P.

2014-12-01

Urban stream quality is particularly susceptible to extreme precipitation events and land use change. Although the projected effects of extreme events and land use change on hydrology have been resonably well studied, the impacts on urban water quality have not been widely examined due in part to the scale mismatch between global climate models and the spatial scales required to represent urban hydrology and water quality signals. Here we describe a grid-based modeling system that integrates the Distributed Hydrology Soil Vegetation Model (DHSVM) and urban water quality module adpated from EPA's Storm Water Management Model (SWMM) and Soil and water assessment tool (SWAT). Using the model system, we evaluate, for four partially urbanized catchments within the Puget Sound basin, urban water quality under current climate conditions, and projected potential changes in urban water quality associated with future changes in climate and land use. We examine in particular total suspended solids, toal nitrogen, total phosphorous, and coliform bacteria, with catchment representations at the 150-meter spatial resolution and the sub-daily timestep. We report long-term streamflow and water quality predictions in response to extreme precipitation events of varying magnitudes in the four partially urbanized catchments. Our simulations show that urban water quality is highly sensitive to both climatic and land use change.

Desktop microsimulation: a tool to improve efficiency in the medical office practice.

PubMed

Montgomery, James B; Linville, Beth A; Slonim, Anthony D

2013-01-01

Because the economic crisis in the United States continues to have an impact on healthcare organizations, industry leaders must optimize their decision making. Discrete-event computer simulation is a quality tool with a demonstrated track record of improving the precision of analysis for process redesign. However, the use of simulation to consolidate practices and design efficiencies into an unfinished medical office building was a unique task. A discrete-event computer simulation package was used to model the operations and forecast future results for four orthopedic surgery practices. The scenarios were created to allow an evaluation of the impact of process change on the output variables of exam room utilization, patient queue size, and staff utilization. The model helped with decisions regarding space allocation and efficient exam room use by demonstrating the impact of process changes in patient queues at check-in/out, x-ray, and cast room locations when compared to the status quo model. The analysis impacted decisions on facility layout, patient flow, and staff functions in this newly consolidated practice. Simulation was found to be a useful tool for process redesign and decision making even prior to building occupancy. © 2011 National Association for Healthcare Quality.

The Impact of Visit Frequency on the Relationship between Service Quality and Outpatient Satisfaction: A South Korean Study

PubMed Central

Cho, Woo Hyun; Lee, Hanjoon; Kim, Chankon; Lee, Sunhee; Choi, Kui-Son

2004-01-01

Objective To examine the relative impact of four service quality dimensions on outpatient satisfaction and to test the invariance of the structural relationships between the service quality dimensions and satisfaction across three patient groups of varying numbers of prior visits to the same hospital as outpatients. Data Sources/Study Setting Survey of 557 outpatients using a self-administered questionnaire over a 10-day period at a general hospital in Sungnam, South Korea. Data Collection Patients answered questions related to two main constructs, patient satisfaction and health care service quality. The health care service quality measures (30 items) were developed based on the results of three focus group interviews and the SERVQUAL scale, while satisfaction (3 items) was measured using a previously validated scale. Study Design Confirmatory factor analysis was used to assess the construct validity of the service quality scale by testing convergent and divergent validity. A structural equation model specifying the four service quality dimensions as exogenous variables and patient satisfaction as an endogenous variable was estimated to assess the relative impact of each of the service quality dimensions on satisfaction. This was followed by a multigroup LISREL analysis that tested the invariance of structural coefficients across three groups with different frequencies of outpatient visits to the hospital. Principal Findings Findings support the causal relationship between service quality and satisfaction in the context of the South Korean health care environment. The four service quality dimensions showed varying patterns of impact on patient satisfaction across the three different outpatient groups. Conclusion The hospital management needs to be aware of the relative importance of each of the service quality dimensions in satisfaction formation of outpatients, which varies across different hospital utilization groups, and use this in strategic considerations. PMID:14965075

Do competition and managed care improve quality?

PubMed

Sari, Nazmi

2002-10-01

In recent years, the US health care industry has experienced a rapid growth of managed care, formation of networks, and an integration of hospitals. This paper provides new insights about the quality consequences of this dynamic in US hospital markets. I empirically investigate the impact of managed care and hospital competition on quality using in-hospital complications as quality measures. I use random and fixed effects, and instrumental variable fixed effect models using hospital panel data from up to 16 states in the 1992-1997 period. The paper has two important findings: First, higher managed care penetration increases the quality, when inappropriate utilization, wound infections and adverse/iatrogenic complications are used as quality indicators. For other complication categories, coefficient estimates are statistically insignificant. These findings do not support the straightforward view that increases in managed care penetration are associated with decreases in quality. Second, both higher hospital market share and market concentration are associated with lower quality of care. Hospital mergers have undesirable quality consequences. Appropriate antitrust policies towards mergers should consider not only price and cost but also quality impacts. Copyright 2002 John Wiley & Sons, Ltd.

A Modeling Investigation of Human Exposure to Select Traffic-Related Air Pollutants in the Tampa Area: Spatiotemporal Distributions of Concentrations, Social Distributions of Exposures, and Impacts of Urban Design on Both

NASA Astrophysics Data System (ADS)

Yu, Haofei

Increasing vehicle dependence in the United States has resulted in substantial emissions of traffic-related air pollutants that contribute to the deterioration of urban air quality. Exposure to urban air pollutants trigger a number of public health concerns, including the potential of inequality of exposures and health effects among population subgroups. To better understand the impact of traffic-related pollutants on air quality, exposure, and exposure inequality, modeling methods that can appropriately characterize the spatiotemporally resolved concentration distributions of traffic-related pollutants need to be improved. These modeling methods can then be used to investigate the impacts of urban design and transportation management choices on air quality, pollution exposures, and related inequality. This work will address these needs with three objectives: 1) to improve modeling methods for investigating interactions between city and transportation design choices and air pollution exposures, 2) to characterize current exposures and the social distribution of exposures to traffic-related air pollutants for the case study area of Hillsborough County, Florida, and 3) to determine expected impacts of urban design and transportation management choices on air quality, air pollution exposures, and exposure inequality. To achieve these objectives, the impacts of a small-scale transportation management project, specifically the '95 Express' high occupancy toll lane project, on pollutant emissions and nearby air quality was investigated. Next, a modeling method capable of characterizing spatiotemporally resolved pollutant emissions, concentrations, and exposures was developed and applied to estimate the impact of traffic-related pollutants on exposure and exposure inequalities among several population subgroups in Hillsborough County, Florida. Finally, using these results as baseline, the impacts of sprawl and compact urban forms, as well as vehicle fleet electrification, on air quality, pollution exposure, and exposure inequality were explored. Major findings include slightly higher pollutant emissions, with the exception of hydrocarbons, due to the managed lane project. Results also show that ambient concentration contributions from on-road mobile sources are disproportionate to their emissions. Additionally, processes not captured by the CALPUFF model, such as atmospheric formation, contribute substantially to ambient concentration levels of the secondary pollutants such as acetaldehyde and formaldehyde. Exposure inequalities for NOx, 1,3-butadiene, and benzene air pollution were found for black, Hispanic, and low income (annual household income less than $20,000) subgroups at both short-term and long-term temporal scales, which is consistent with previous findings. Exposure disparities among the subgroups are complex, and sometimes reversed for acetaldehyde and formaldehyde, due primarily to their distinct concentration distributions. Compact urban form was found to result in lower average NOx and benzene concentrations, but higher exposure for all pollutants except for NOx when compared to sprawl urban form. Evidence suggests that exposure inequalities differ between sprawl and compact urban forms, and also differ by pollutants, but are generally consistent at both short and long-term temporal scales. In addition, vehicle fleet electrification was found to result in generally lower average pollutant concentrations and exposures, except for NOx. However, the elimination of on-road mobile source emissions does not substantially reduce exposure inequality. Results and findings from this work can be applied to assist transportation infrastructure and urban planning. In addition, method developed here can be applied elsewhere for better characterization of air pollution concentrations, exposure and related inequalities.

Environmental Flow for Sungai Johor Estuary

NASA Astrophysics Data System (ADS)

Adilah, A. Kadir; Zulkifli, Yusop; Zainura, Z. Noor; Bakhiah, Baharim N.

2018-03-01

Sungai Johor estuary is a vital water body in the south of Johor and greatly affects the water quality in the Johor Straits. In the development of the hydrodynamic and water quality models for Sungai Johor estuary, the Environmental Fluid Dynamics Code (EFDC) model was selected. In this application, the EFDC hydrodynamic model was configured to simulate time varying surface elevation, velocity, salinity, and water temperature. The EFDC water quality model was configured to simulate dissolved oxygen (DO), dissolved organic carbon (DOC), chemical oxygen demand (COD), ammoniacal nitrogen (NH3-N), nitrate nitrogen (NO3-N), phosphate (PO4), and Chlorophyll a. The hydrodynamic and water quality model calibration was performed utilizing a set of site specific data acquired in January 2008. The simulated water temperature, salinity and DO showed good and fairly good agreement with observations. The calculated correlation coefficients between computed and observed temperature and salinity were lower compared with the water level. Sensitivity analysis was performed on hydrodynamic and water quality models input parameters to quantify their impact on modeling results such as water surface elevation, salinity and dissolved oxygen concentration. It is anticipated and recommended that the development of this model be continued to synthesize additional field data into the modeling process.

Experiments with data assimilation in comprehensive air quality models: Impacts on model predictions and observation requirements (Invited)

NASA Astrophysics Data System (ADS)

Mathur, R.

2009-12-01

Emerging regional scale atmospheric simulation models must address the increasing complexity arising from new model applications that treat multi-pollutant interactions. Sophisticated air quality modeling systems are needed to develop effective abatement strategies that focus on simultaneously controlling multiple criteria pollutants as well as use in providing short term air quality forecasts. In recent years the applications of such models is continuously being extended to address atmospheric pollution phenomenon from local to hemispheric spatial scales over time scales ranging from episodic to annual. The need to represent interactions between physical and chemical atmospheric processes occurring at these disparate spatial and temporal scales requires the use of observation data beyond traditional in-situ networks so that the model simulations can be reasonably constrained. Preliminary applications of assimilation of remote sensing and aloft observations within a comprehensive regional scale atmospheric chemistry-transport modeling system will be presented: (1) A methodology is developed to assimilate MODIS aerosol optical depths in the model to represent the impacts long-range transport associated with the summer 2004 Alaskan fires on surface-level regional fine particulate matter (PM2.5) concentrations across the Eastern U.S. The episodic impact of this pollution transport event on PM2.5 concentrations over the eastern U.S. during mid-July 2004, is quantified through the complementary use of the model with remotely-sensed, aloft, and surface measurements; (2) Simple nudging experiments with limited aloft measurements are performed to identify uncertainties in model representations of physical processes and assess the potential use of such measurements in improving the predictive capability of atmospheric chemistry-transport models. The results from these early applications will be discussed in context of uncertainties in the model and in the remote sensing data and needs for defining a future optimum observing strategy.

Impacts of Participatory Modeling on Climate Change-related Water Management Impacts in Sonora, Mexico

NASA Astrophysics Data System (ADS)

Halvorsen, K. E.; Kossak, D. J.; Mayer, A. S.; Vivoni, E. R.; Robles-Morua, A.; Gamez Molina, V.; Dana, K.; Mirchi, A.

2013-12-01

Climate change-related impacts on water resources are expected to be particularly severe in the arid developing world. As a result, we conducted a series of participatory modeling workshops on hydrologic and water resources systems modeling in the face of climate change in Sonora, Mexico. Pre-surveys were administered to participants on Day 1 of a series of four workshops spaced out over three months in 2013. Post-surveys repeated many pre-survey questions and included questions assessing the quality of the workshops and models. We report on significant changes in participant perceptions of water resource models and problems and their assessment of the workshops. These findings will be of great value to future participatory modeling efforts, particularly within the developing world.

The International development of PROQOL-HCV: An instrument to assess the health-related quality of life of patients treated for Hepatitis C virus.

PubMed

Armstrong, Andrew Richard; Herrmann, Susan Elizabeth; Chassany, Olivier; Lalanne, Christophe; Da Silva, Mariliza Henrique; Galano, Eliana; Carrieri, Patrizia M; Estellon, Vincent; Sogni, Philippe; Duracinsky, Martin

2016-08-23

Hepatitis C virus (HCV) compromises Health-related Quality of Life (HRQL) with detriments to Physical, Mental and Social health domains. Treatment with interferon and ribavirin is associated with side effects which further impair HRQL. New treatments appear potent, effective and tolerable. However, Patient Reported Outcomes instruments that capture the impact on HRQL for people with hepatitis C are largely non-specific and will be needed in the new treatment era. Therefore, we developed a conceptually valid multidimensional model of HCV-specific quality of life and pilot survey instrument, the Patient Reported Outcome Quality of Life survey for HCV (PROQOL-HCV). HCV patients from France (n = 30), Brazil (n = 20) and Australia (n = 20) were interviewed to investigate HCV-HRQL issues raised in the scientific literature and by treatment specialists. Interviews were recorded, transcribed and translated into English and French. Fifteen content dimensions were derived from the qualitative analysis, refined and fitted to four domains: (1) Physical Health included: fatigue, pain, sleep, sexual impairment and physical activity; (2) Mental Health: psychological distress, psychosocial impact, and cognition; (3) Social Health: support, stigma, social activity, substance use; (4) TREATMENT: management, side effects, and fear of treatment failure. The impact of some dimensions extended beyond their primary domain including: physical activity, cognition, sleep, sexual impairment, and the three treatment dimensions. A bank of 300 items was constructed to reflect patient reports and, following expert review, reduced to a 72-item pilot questionnaire. We present a conceptually valid multidimensional model of HCV-specific quality of life and the pilot survey instrument, PROQOL-HCV. The model is widely inclusive of the experience of hepatitis C and the first to include the treatment dimension.

Modelling the cost-effectiveness of impact-absorbing flooring in Swedish residential care facilities.

PubMed

Ryen, Linda; Svensson, Mikael

2016-06-01

Fall-related injuries among the elderly, specifically hip fractures, cause significant morbidity and mortality as well as imposing a substantial financial cost on the health care system. Impact-absorbing flooring has been advocated as an effective method for preventing hip fractures resulting from falls. This study identifies the cost-effectiveness of impact-absorbing flooring compared to standard flooring in residential care facilities for the elderly in a Swedish setting. An incremental cost-effectiveness analysis was performed comparing impact-absorbing flooring to standard flooring using a Markov decision model. A societal perspective was adopted and incremental costs were compared to incremental gains in quality-adjusted life years (QALYs). Data on costs, probability transitions and health-related quality of life measures were retrieved from the published literature and from Swedish register data. Probabilistic sensitivity analysis was performed through a Monte Carlo simulation. The base-case analysis indicates that the impact-absorbing flooring reduces costs and increases QALYs. When allowing for uncertainty we find that 60% of the simulations indicate that impact-absorbing flooring is cost-saving compared to standard flooring and an additional 20% that it has a cost per QALY below a commonly used threshold value : Using a modelling approach, we find that impact-absorbing flooring is a dominant strategy at the societal level considering that it can save resources and improve health in a vulnerable population. © The Author 2015. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

GIS based procedure of cumulative environmental impact assessment.

PubMed

Balakrishna Reddy, M; Blah, Baiantimon

2009-07-01

Scale and spatial limits of impact assessment study in a GIS platform are two very important factors that could have a bearing on the genuineness and quality of impact assessment. While effect of scale has been documented and well understood, no significant study has been carried out on spatial considerations in an impact assessment study employing GIS technique. A novel technique of impact assessment demonstrable through GIS approach termed hereby as 'spatial data integrated GIS impact assessment method (SGIAM)' is narrated in this paper. The technique makes a fundamental presumption that the importance of environmental impacts is dependent, among other things, on spatial distribution of the effects of the proposed action and of the affected receptors in a study area. For each environmental component considered (e.g., air quality), impact indices are calculated through aggregation of impact indicators which are measures of the severity of the impact. The presence and spread of environmental descriptors are suitably quantified through modeling techniques and depicted. The environmental impact index is calculated from data exported from ArcINFO, thus giving significant importance to spatial data in the impact assessment exercise.

A cost-efficiency and health benefit approach to improve urban air quality.

PubMed

Miranda, A I; Ferreira, J; Silveira, C; Relvas, H; Duque, L; Roebeling, P; Lopes, M; Costa, S; Monteiro, A; Gama, C; Sá, E; Borrego, C; Teixeira, J P

2016-11-01

When ambient air quality standards established in the EU Directive 2008/50/EC are exceeded, Member States are obliged to develop and implement Air Quality Plans (AQP) to improve air quality and health. Notwithstanding the achievements in emission reductions and air quality improvement, additional efforts need to be undertaken to improve air quality in a sustainable way - i.e. through a cost-efficiency approach. This work was developed in the scope of the recently concluded MAPLIA project "Moving from Air Pollution to Local Integrated Assessment", and focuses on the definition and assessment of emission abatement measures and their associated costs, air quality and health impacts and benefits by means of air quality modelling tools, health impact functions and cost-efficiency analysis. The MAPLIA system was applied to the Grande Porto urban area (Portugal), addressing PM10 and NOx as the most important pollutants in the region. Four different measures to reduce PM10 and NOx emissions were defined and characterized in terms of emissions and implementation costs, and combined into 15 emission scenarios, simulated by the TAPM air quality modelling tool. Air pollutant concentration fields were then used to estimate health benefits in terms of avoided costs (external costs), using dose-response health impact functions. Results revealed that, among the 15 scenarios analysed, the scenario including all 4 measures lead to a total net benefit of 0.3M€·y(-1). The largest net benefit is obtained for the scenario considering the conversion of 50% of open fire places into heat recovery wood stoves. Although the implementation costs of this measure are high, the benefits outweigh the costs. Research outcomes confirm that the MAPLIA system is useful for policy decision support on air quality improvement strategies, and could be applied to other urban areas where AQP need to be implemented and monitored. Copyright © 2016. Published by Elsevier B.V.

Applying a two-dimensional morphodynamic model to assess impacts to Chinook salmon spawning habitat from dam removal

NASA Astrophysics Data System (ADS)

Lee, A. A.; Crosato, A.; Omer, A. Y. A.; Bregoli, F.

2017-12-01

The need for accurate and robust predictive methods of assessing fluvial ecosystems is highlighted by the accelerating practice of dam removal. Dam removal can be a restorative measure, but the sudden release of impounded sediment and change in flow regime may negatively impact aquatic biota and their habitat. This study assesses the performance of a quasi-three-dimensional morphodynamic numerical model, coupled with habitat suitability indices, to predict short-term impacts to Chinook salmon (Oncorhynchus tshawytscha) spawning habitat from dam removal. The 2007 removal of Marmot Dam on the Sandy River (Oregon, U.S.A.) is used as a case study. Delft3D-FLOW is employed to simulate changes in river channel topography, sediment composition and hydrodynamic conditions for a 20-kilometer reach of the Sandy River. The transport of non-uniform sediment and three-dimensional flow effects are included in the model. Output parameters such as flow depth, velocity and substrate are processed to evaluate habitat quality in the year following the Marmot Dam removal. Impacts are evaluated across four life-stages of Chinook salmon. As a hindcast analysis, the morphodynamic model sufficiently reproduces the evolution of river morphology at the reach-scale while requiring only a low level of calibration. The model performs well in predicting impacts to fish passage, but carries more uncertainty for developing life stages. By coupling flow-sediment-biota interactions, this method shows strong potential for habitat assessment in unsteady and non-uniform environments. Computation time is a primary constraint, as it limits grid-cell resolution, modelling of suspended sediment and capacity to characterize the sediment grain size distribution. Research on the effects of suspended sediment on habitat quality is ongoing, and further research is recommended for modelling reservoir erosion processes numerically.

Environment, Health and Climate: Impact of African aerosols

NASA Astrophysics Data System (ADS)

Liousse, C.; Doumbia, T.; Assamoi, E.; Galy-Lacaux, C.; Baeza, A.; Penner, J. E.; Val, S.; Cachier, H.; Xu, L.; Criqui, P.

2012-12-01

Fossil fuel and biofuel emissions of particles in Africa are expected to significantly increase in the near future, particularly due to rapid growth of African cities. In addition to biomass burning emissions prevailing in these areas, air quality degradation is then expected with important consequences on population health and climatic/radiative impact. In our group, we are constructing a new integrated methodology to study the relations between emissions, air quality and their impacts. This approach includes: (1) African combustion emission characterizations; (2) joint experimental determination of aerosol chemistry from ultrafine to coarse fractions and health issues (toxicology and epidemiology). (3) integrated environmental, health and radiative modeling. In this work, we show some results illustrating our first estimates of African anthropogenic emission impacts: - a new African anthropogenic emission inventory adapted to regional specificities on traffic, biofuel and industrial emissions has been constructed for the years 2005 and 2030. Biomass burning inventories were also improved in the frame of AMMA (African Monsoon) program. - carbonaceous aerosol radiative impact in Africa has been modeled with TM5 model and Penner et al. (2011) radiative code for these inventories for 2005 and 2030 and for two scenarios of emissions : a reference scenario, with no further emission controls beyond those achieved in 2003 and a ccc* scenario including planned policies in Kyoto protocol and regulations as applied to African emission specificities. In this study we will show that enhanced heating is expected with the ccc* scenarios emissions in which the OC fraction is relatively lower than in the reference scenario. - results of short term POLCA intensive campaigns in Bamako and Dakar in terms of aerosol chemical characterization linked to specific emissions sources and their inflammatory impacts on the respiratory tract through in vitro studies. In this study, organic carbon particles have appeared quite biologically active. Quite importantly, air quality improvement obtained through regulations in the ccc* scenario are accompanied by stronger heating impact.

75 FR 72705 - Approval and Promulgation of Implementation Plans; Idaho

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-26

... other states, WG relied on an additional study entitled the ``Uinta Basin Air Quality Study (UBAQS... of a modeling analysis to assess ozone impacts prior to authorizing oil and gas development projects... Agencies on assessing impacts of oil and gas development projects.\\18\\ WG questioned why EPA's...

Regional photochemical air quality modeling in the Mexico-US border area

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

Mendoza, A.; Russell, A.G.; Mejia, G.M.

1998-12-31

The Mexico-United States border area has become an increasingly important region due to its commercial, industrial and urban growth. As a result, environmental concerns have risen. Treaties like the North American Free Trade Agreement (NAFTA) have further motivated the development of environmental impact assessment in the area. Of particular concern are air quality, and how the activities on both sides of the border contribute to its degradation. This paper presents results of applying a three-dimensional photochemical airshed model to study air pollution dynamics along the Mexico-United States border. In addition, studies were conducted to assess how size resolution impacts themore » model performance. The model performed within acceptable statistic limits using 12.5 x 12.5 km{sup 2} grid cells, and the benefits using finer grids were limited. Results were further used to assess the influence of grid-cell size on the modeling of control strategies, where coarser grids lead to significant loss of information.« less

Coupled impacts of climate and land use change across a river-lake continuum: insights from an integrated assessment model of Lake Champlain’s Missisquoi Basin, 2000-2040

NASA Astrophysics Data System (ADS)

Zia, Asim; Bomblies, Arne; Schroth, Andrew W.; Koliba, Christopher; Isles, Peter D. F.; Tsai, Yushiou; Mohammed, Ibrahim N.; Bucini, Gabriela; Clemins, Patrick J.; Turnbull, Scott; Rodgers, Morgan; Hamed, Ahmed; Beckage, Brian; Winter, Jonathan; Adair, Carol; Galford, Gillian L.; Rizzo, Donna; Van Houten, Judith

2016-11-01

Global climate change (GCC) is projected to bring higher-intensity precipitation and higher-variability temperature regimes to the Northeastern United States. The interactive effects of GCC with anthropogenic land use and land cover changes (LULCCs) are unknown for watershed level hydrological dynamics and nutrient fluxes to freshwater lakes. Increased nutrient fluxes can promote harmful algal blooms, also exacerbated by warmer water temperatures due to GCC. To address the complex interactions of climate, land and humans, we developed a cascading integrated assessment model to test the impacts of GCC and LULCC on the hydrological regime, water temperature, water quality, bloom duration and severity through 2040 in transnational Lake Champlain’s Missisquoi Bay. Temperature and precipitation inputs were statistically downscaled from four global circulation models (GCMs) for three Representative Concentration Pathways. An agent-based model was used to generate four LULCC scenarios. Combined climate and LULCC scenarios drove a distributed hydrological model to estimate river discharge and nutrient input to the lake. Lake nutrient dynamics were simulated with a 3D hydrodynamic-biogeochemical model. We find accelerated GCC could drastically limit land management options to maintain water quality, but the nature and severity of this impact varies dramatically by GCM and GCC scenario.

76 FR 34000 - Approval and Promulgation of Air Quality Implementation Plans; Pennsylvania; Revisions to...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-10

... nonattainment area in Allegheny County by incorporating Federal modeling requirements. EPA is approving these... for sources locating in or impacting a nonattainment area by incorporating Federal modeling... incorporating the modeling requirements from 40 CFR part 51, subpart I, entitled ``Review of New Sources and...

Life cycle air quality impacts of conventional and alternative light-duty transportation in the United States

DOE PAGES

Tessum, Christopher W.; Hill, Jason D.; Marshall, Julian D.

2014-12-30

Commonly considered strategies for reducing the environmental impact of light-duty transportation include using alternative fuels and improving vehicle fuel economy. We evaluate the air quality-related human health impacts of 10 such options, including the use of liquid biofuels, diesel, and compressed natural gas (CNG) in internal combustion engines; the use of electricity from a range of conventional and renewable sources to power electric vehicles (EVs); and the use of hybrid EV technology. Our approach combines spatially, temporally, and chemically detailed life cycle emission inventories; comprehensive, fine-scale state-of-the-science chemical transport modeling; and exposure, concentration–response, and economic health impact modeling for ozonemore » (O 3) and fine particulate matter (PM 2.5). We find that powering vehicles with corn ethanol or with coal-based or “grid average” electricity increases monetized environmental health impacts by 80% or more relative to using conventional gasoline. Conversely, EVs powered by low-emitting electricity from natural gas, wind, water, or solar power reduce environmental health impacts by 50% or more. Consideration of potential climate change impacts alongside the human health outcomes described here further reinforces the environmental preferability of EVs powered by low-emitting electricity relative to gasoline vehicles.« less

Life cycle air quality impacts of conventional and alternative light-duty transportation in the United States

PubMed Central

Hill, Jason D.; Marshall, Julian D.

2014-01-01

Commonly considered strategies for reducing the environmental impact of light-duty transportation include using alternative fuels and improving vehicle fuel economy. We evaluate the air quality-related human health impacts of 10 such options, including the use of liquid biofuels, diesel, and compressed natural gas (CNG) in internal combustion engines; the use of electricity from a range of conventional and renewable sources to power electric vehicles (EVs); and the use of hybrid EV technology. Our approach combines spatially, temporally, and chemically detailed life cycle emission inventories; comprehensive, fine-scale state-of-the-science chemical transport modeling; and exposure, concentration–response, and economic health impact modeling for ozone (O3) and fine particulate matter (PM2.5). We find that powering vehicles with corn ethanol or with coal-based or “grid average” electricity increases monetized environmental health impacts by 80% or more relative to using conventional gasoline. Conversely, EVs powered by low-emitting electricity from natural gas, wind, water, or solar power reduce environmental health impacts by 50% or more. Consideration of potential climate change impacts alongside the human health outcomes described here further reinforces the environmental preferability of EVs powered by low-emitting electricity relative to gasoline vehicles. PMID:25512510

Impact of air quality in Mexico City due to particles smaller than ten microns (PM10) by wildland fire in "Cumbres del Ajusco Park" for the year 2013

NASA Astrophysics Data System (ADS)

Mendoza, A.; Garcia-Reynoso, J. A.; Ruiz-Suárez, L. G.; Torres, R.; Castro, T.; Peralta, O.; Padilla Barrera, Z. V.; Mar, B.; Carbajal, J. N.

2014-12-01

A forest fire is a natural process of combustion in a specific geographical area, its occurrence depends on meteorological variables, topography and vegetation type, the wildland fires are potential sources of large amounts of pollutants. The main air pollutants are in a wildland fires particles (PM10 and PM2.5) Carbon Monoxide (CO), nitrogen oxides (NOx), volatile organic compounds (VOC's) and a negligible amount of sulfur dioxide (SO2) (Chow 1995), Was performed a study of the environmental impact on air quality in Mexico city for a wildland fire. The fire was presented in Cumbres del Ajusco Park on April 14 for the year 2013, with a duration of 26 hours and consuming an extension 150 ha of pasture, WRF-Chem and WRF-fire model were used to conduct the study, two modeling scenarios were made, one including emissions from wildfire and other without emission-fire, comparison is made between the two modeling scenarios in order to calculate on air quality in Mexico cityPM10 concentrations have a larger impact on the air quality of Mexico city, when fire emission were included, a plume of PM10 coming from fire increase ambient concentration up to 350ug/m3 and it was obtained by modeling similar to the concentration measured by a monitoring station (320ug/m3).The current limit is 120ug/m3 24 hours average. (Mexican standard NOM-025-SSA1-1993)This system for setting emissions from fire is working properly whoever further development is required.

Contribution of Optical Zone Decentration and Pupil Dilation on the Change of Optical Quality After Myopic Photorefractive Keratectomy in a Cat Model

PubMed Central

Bühren, Jens; Yoon, Geunyoung; MacRae, Scott; Huxlin, Krystel

2010-01-01

PURPOSE To simulate the simultaneous contribution of optical zone decentration and pupil dilation on retinal image quality using wavefront error data from a myopic photorefractive keratectomy (PRK) cat model. METHODS Wavefront error differences were obtained from five cat eyes 19±7 weeks (range: 12 to 24 weeks) after spherical myopic PRK for −6.00 diopters (D) (three eyes) and −10.00 D (two eyes). A computer model was used to simulate decentration of a 6-mm sub-aperture relative to the measured wavefront error difference. Changes in image quality (visual Strehl ratio based on the optical transfer function [VSOTF]) were computed for simulated decentrations from 0 to 1500 μm over pupil diameters of 3.5 to 6.0 mm in 0.5-mm steps. For each eye, a bivariate regression model was applied to calculate the simultaneous contribution of pupil dilation and decentration on the pre- to postoperative change of the log VSOTF. RESULTS Pupil diameter and decentration explained up to 95% of the variance of VSOTF change (adjusted R2=0.95). Pupil diameter had a higher impact on VSOTF (median β=−0.88, P<.001) than decentration (median β= −0.45, P<.001). If decentration-induced lower order aberrations were corrected, the impact of decentration further decreased (β= −0.26) compared to the influence of pupil dilation (β= −0.95). CONCLUSIONS Both pupil dilation and decentration of the optical zone affected the change of retinal image quality (VSOTF) after myopic PRK with decentration exerting a lower impact on VSOTF change. Thus, under physiological conditions pupil dilation is likely to have more effect on VSOTF change after PRK than optical zone decentration. PMID:20229950

Contribution of optical zone decentration and pupil dilation on the change of optical quality after myopic photorefractive keratectomy in a cat model.

PubMed

Bühren, Jens; Yoon, Geunyoung; MacRae, Scott; Huxlin, Krystel

2010-03-01

To simulate the simultaneous contribution of optical zone decentration and pupil dilation on retinal image quality using wavefront error data from a myopic photorefractive keratectomy (PRK) cat model. Wavefront error differences were obtained from five cat eyes 19+/-7 weeks (range: 12 to 24 weeks) after spherical myopic PRK for -6.00 diopters (D) (three eyes) and -10.00 D (two eyes). A computer model was used to simulate decentration of a 6-mm sub-aperture relative to the measured wavefront error difference. Changes in image quality (visual Strehl ratio based on the optical transfer function [VSOTF]) were computed for simulated decentrations from 0 to 1500 mum over pupil diameters of 3.5 to 6.0 mm in 0.5-mm steps. For each eye, a bivariate regression model was applied to calculate the simultaneous contribution of pupil dilation and decentration on the pre- to postoperative change of the log VSOTF. Pupil diameter and decentration explained up to 95% of the variance of VSOTF change (adjusted R(2)=0.95). Pupil diameter had a higher impact on VSOTF (median beta=-0.88, P<.001) than decentration (median beta=-0.45, P<.001). If decentration-induced lower order aberrations were corrected, the impact of decentration further decreased (beta=-0.26) compared to the influence of pupil dilation (beta=-0.95). Both pupil dilation and decentration of the optical zone affected the change of retinal image quality (VSOTF) after myopic PRK with decentration exerting a lower impact on VSOTF change. Thus, under physiological conditions pupil dilation is likely to have more effect on VSOTF change after PRK than optical zone decentration. Copyright 2010, SLACK Incorporated.

IMPROVE EMISSION INVENTORIES THROUGH ADVANCES IN METHODS AND MODELS

EPA Science Inventory

Emission inventories are the foundation of cost-effective air quality management strategies. The emission inventory must be complete, accurate, timely, transparent, and affordable. The general approach is to identify the largest uncertainties that can impact model outputs and a...

MODELING UNCERTAINTY OF RUNOFF AND SEDIMENT YIELD IN TWO EXPERIMENTAL WATERSHEDS

EPA Science Inventory

Sediment loading from agriculture is adversely impacting surface water quality and ecological conditions. In this regard, the use of distributed hydrologic models has gained acceptance in management of soil erosion and sediment yield from agricultural watersheds. Soil infiltrati...

LOUISIANA ENVIRONMENTAL MODELING SYSTEM FOR HYPOXIA RELATED ISSUES

EPA Science Inventory

An environmental assessment tool to evaluate the impacts of nonpoint source (NPS) pollutants discharged from Mississippi River basins into the Gulf of Mexico and to assess their effects on receiving water quality will be described. This system (Louisiana Environmental Modeling S...

The Impact of the Aerosol Direct Radiative Forcing on Deep Convection and Air Quality in the Pearl River Delta Region

NASA Astrophysics Data System (ADS)

Liu, Z.; Yim, Steve H. L.; Wang, C.; Lau, N. C.

2018-05-01

Literature has reported the remarkable aerosol impact on low-level cloud by direct radiative forcing (DRF). Impacts on middle-upper troposphere cloud are not yet fully understood, even though this knowledge is important for regions with a large spatial heterogeneity of emissions and aerosol concentration. We assess the aerosol DRF and its cloud response in June (with strong convection) in Pearl River Delta region for 2008-2012 at cloud-resolving scale using an air quality-climate coupled model. Aerosols suppress deep convection by increasing atmospheric stability leading to less evaporation from the ground. The relative humidity is reduced in middle-upper troposphere due to induced reduction in both evaporation from the ground and upward motion. The cloud reduction offsets 20% of the aerosol DRF. The weaker vertical mixing further increases surface aerosol concentration by up to 2.90 μg/m3. These findings indicate the aerosol DRF impact on deep convection and in turn regional air quality.

Impact of aircraft emissions on air quality in the vicinity of airports. Volume II. An updated model assessment of aircraft generated air pollution at LAX, JFK, and ORD. Final report Jan 1978-Jul 1980

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

Yamartino, R.J.; Smith, D.G.; Bremer, S.A.

1980-07-01

This report documents the results of the Federal Aviation Administration (FAA)/Environmental Protection Agency (EPA) air quality study which has been conducted to assess the impact of aircraft emissions of carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen (NOx) in the vicinity of airports. This assessment includes the results of recent modeling and monitoring efforts at Washington National (DCA), Los Angeles International (LAX), Dulles International (IAD), and Lakeland, Florida airports and an updated modeling of aircraft generated pollution at LAX, John F. Kennedy (JFK) and Chicago O'Hare (ORD) airports. The Airport Vicinity Air Pollution (AVAP) model which was designed formore » use at civil airports was used in this assessment. In addition the results of the application of the military version of the AVAP model the Air Quality Assessment Model (AQAM), are summarized. Both the results of the pollution monitoring analyses in Volume I and the modeling studies in Volume II suggest that: maximum hourly average CO concentrations from aircraft are unlikely to exceed 5 parts per million (ppm) in areas of public exposure and are thus small in comparison to the National Ambient Air Quality Standard of 35 ppm; maximum hourly HC concentrations from aircraft can exceed 0.25 ppm over an area several times the size of the airport; and annual average NO2 concentrations from aircraft are estimated to contribute only 10 to 20 percent of the NAAQS limit level.« less

The impact on air quality of energy saving measures in the major cities signatories of the Covenant of Mayors initiative.

PubMed

Monforti-Ferrario, Fabio; Kona, Albana; Peduzzi, Emanuela; Pernigotti, Denise; Pisoni, Enrico

2018-06-08

This study is a first attempt to evaluate how the major efforts made by several European cities in the frame of the Covenant of Mayors (CoM) initiative can impact the air pollution levels in the participating cities. CoM is by no mean one of the major cities initiatives aimed at mitigating climate change, supporting local authorities in the implementation of their climate action plans. Energy savings measures reported in the CoM cities' action plans have been analysed from the air quality perspective in order to find quantitative relations in the way local authorities deal with mitigation and how these practices are expected to have consequences on the air quality at urban level and finally positively impacting the citizens' health. In the paper, the air quality 2713 energy saving measures proposed by 146 cities located in 23 countries in the frame of the CoM are selected and their co-benefits for air quality and public health estimated by means of SHERPA, a fast modelling tool that mimics the behaviour of a full physically-based Chemical Transport Model. Besides evaluating the overall benefits of this subset of mitigation measures for the air quality, the study also investigates the relevance of some factors such as the implementation sector, the city size and the pollution levels in achieving the highest possible co-benefits. The results presented refer to the special field covered by the study, i.e. energy saving measures and are not automatically referable to other types of measures. Nevertheless, they clearly show how climate mitigation and air quality policies are deeply interconnected at the urban level. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Breast cancer screening services: trade-offs in quality, capacity, outreach, and centralization.

PubMed

Güneş, Evrim D; Chick, Stephen E; Akşin, O Zeynep

2004-11-01

This work combines and extends previous work on breast cancer screening models by explicitly incorporating, for the first time, aspects of the dynamics of health care states, program outreach, and the screening volume-quality relationship in a service system model to examine the effect of public health policy and service capacity decisions on public health outcomes. We consider the impact of increasing standards for minimum reading volume to improve quality, expanding outreach with or without decentralization of service facilities, and the potential of queueing due to stochastic effects and limited capacity. The results indicate a strong relation between screening quality and the cost of screening and treatment, and emphasize the importance of accounting for service dynamics when assessing the performance of health care interventions. For breast cancer screening, increasing outreach without improving quality and maintaining capacity results in less benefit than predicted by standard models.

Factors associated with severe impact of lipodystrophy on the quality of life of patients infected with HIV-1.

PubMed

Blanch, Jordi; Rousaud, Araceli; Martinez, Esteban; De Lazzari, Elisa; Milinkovic, Ana; Peri, Josep-Maria; Blanco, José-Luis; Jaen, Jesús; Navarro, Victor; Massana, Guillem; Gatell, Josep-Maria

2004-05-15

A standardized questionnaire was used to assess the impact of lipodystrophy (LD) on quality of life (QoL). Eighty-four consecutive asymptomatic human immunodeficiency virus type 1 (HIV-1)-infected outpatients with clinical LD completed a modified version of the Dermatology Life Quality Index (DLQI) survey to measure the impact of body fat changes on their QoL. Body changes influenced dressing for 55 patients (65%), produced feelings of shame for 41 (49%), and disrupted sexual life for 23 (27%). There was a greater impact on the DLQI due to body changes among women, injection drug users, patients with abdominal or breast lipoaccumulation, and patients with a high number of non-LD side effects. Multivariate proportional odds model analysis showed that the severity of non-LD-associated side effects and the presence of breast lipoaccumulation were associated with impaired psychosocial functioning. Specific characteristics of patients, antiretroviral-based side effects, and breast lipoaccumulation exert a greater impact on QoL in HIV-1-infected patients with LD.

Air quality co-benefits and costs under state, regional, or national cooperation to regulate CO2 from existing power plants

NASA Astrophysics Data System (ADS)

Saari, R.; Selin, N. E.

2015-12-01

We examine the effect of state, regional, and national cooperation on the costs and air quality co-benefits of a policy to limit the carbon intensity of existing electricity generation. Electricity generation is a significant source of both greenhouse gases and air pollutant emissions that harm human health. Previous studies have shown that air quality co-benefits can be substantial compared to the costs of limiting carbon emissions in the energy system. The EPA's proposed Clean Power Plan seeks to impose carbon intensity limits for each state, but allows states to cooperate in order to meet combined limits. We explore how such cooperation might produce trade-offs between lower costs, widespread pollution reductions, and local reductions. We employ a new state-level model of the US energy system and economy to examine the costs and emissions as states reduce demand or deploy cleaner generation. We use an advanced air quality impacts modeling system, including SMOKE, CAMx, and BenMAP, to estimate health-related air quality co-benefits and compare these to costs under different levels of cooperation. We draw conclusions about the potential impacts of cooperation on economic welfare at various scales.

Piloted Simulation Assessment of the Impact of Flexible Structures on Handling Qualities of Generic Supersonic Aircraft

NASA Technical Reports Server (NTRS)

Stringer, Mary T.; Cowen, Brandon; Hoffler, Keith D.; Couch, Jesse C.; Ogburn, Marilyn E.; Diebler, Corey G.

2013-01-01

The NASA Langley Research Center Cockpit Motion Facility (CMF) was used to conduct a piloted simulation assessment of the impact of flexible structures on flying qualities. The CMF was used because of its relatively high bandwidth, six degree-of-freedom motion capability. Previous studies assessed and attempted to mitigate the effects of multiple dynamic aeroservoelastic modes (DASE). Those results indicated problems existed, but the specific cause and effect was difficult to ascertain. The goal of this study was to identify specific DASE frequencies, damping ratios, and gains that cause degradation in handling qualities. A generic aircraft simulation was developed and designed to have Cooper-Harper Level 1 handling qualities when flown without DASE models. A test matrix of thirty-six DASE modes was implemented. The modes had frequencies ranging from 1 to 3.5 Hz and were applied to each axis independently. Each mode consisted of a single axis, frequency, damping, and gain, and was evaluated individually by six subject pilots with test pilot backgrounds. Analysis completed to date suggests that a number of the DASE models evaluated degrade the handling qualities of this class of aircraft to an uncontrollable condition.

Understanding Intention to Use Electronic Information Resources: A Theoretical Extension of the Technology Acceptance Model (TAM)

PubMed Central

Tao, Donghua

2008-01-01

This study extended the Technology Acceptance Model (TAM) by examining the roles of two aspects of e-resource characteristics, namely, information quality and system quality, in predicting public health students’ intention to use e-resources for completing research paper assignments. Both focus groups and a questionnaire were used to collect data. Descriptive analysis, data screening, and Structural Equation Modeling (SEM) techniques were used for data analysis. The study found that perceived usefulness played a major role in determining students’ intention to use e-resources. Perceived usefulness and perceived ease of use fully mediated the impact that information quality and system quality had on behavior intention. The research model enriches the existing technology acceptance literature by extending TAM. Representing two aspects of e-resource characteristics provides greater explanatory information for diagnosing problems of system design, development, and implementation. PMID:18999300

Understanding intention to use electronic information resources: A theoretical extension of the technology acceptance model (TAM).

PubMed

Tao, Donghua

2008-11-06

This study extended the Technology Acceptance Model (TAM) by examining the roles of two aspects of e-resource characteristics, namely, information quality and system quality, in predicting public health students' intention to use e-resources for completing research paper assignments. Both focus groups and a questionnaire were used to collect data. Descriptive analysis, data screening, and Structural Equation Modeling (SEM) techniques were used for data analysis. The study found that perceived usefulness played a major role in determining students' intention to use e-resources. Perceived usefulness and perceived ease of use fully mediated the impact that information quality and system quality had on behavior intention. The research model enriches the existing technology acceptance literature by extending TAM. Representing two aspects of e-resource characteristics provides greater explanatory information for diagnosing problems of system design, development, and implementation.

The impact of maternal depressive symptoms on health-related quality of life in children with epilepsy: a prospective study of family environment as mediators and moderators.

PubMed

Ferro, Mark A; Avison, William R; Campbell, M Karen; Speechley, Kathy N

2011-02-01

To examine the impact of maternal depressive symptoms (DS) on health-related quality of life (HRQL) in children with new-onset epilepsy and to identify family factors that moderate and mediate this relationship during the first 24 months after epilepsy diagnosis. A sample of 339 mother-child dyads recruited from pediatric neurologists across Canada in the Health-related Quality of Life in Children with Epilepsy Study. Mothers' and neurologists' reports were collected at four times during the 24-month follow-up. Mothers' DS were measured using the Center for Epidemiological Studies Depression Scale (CES-D) and children's HRQL using the Quality of Life in Childhood Epilepsy (QOLCE). Data were modeled using individual growth curve modeling. Maternal DS were observed to have a negative impact on QOLCE scores at 24 months (β = -0.47, p < 0.0001) and the rate of change in QOLCE scores during follow-up (β = -0.04, p = 0.0250). This relationship was moderated by family resources (β = 0.25, p = 0.0243), and the magnitude of moderation varied over time (β = 0.09, p = 0.0212). Family functioning and demands partially mediated the impact of maternal DS on child HRQL (β = -0.07, p = 0.0007; β = -0.12, p = 0.0006). Maternal DS negatively impact child HRQL in new-onset epilepsy during the first 24 months after diagnosis. This relationship is moderated by family resources and mediated by family functioning and demands. By adopting family centered approaches, health care professionals may be able to intervene at the maternal or family level to promote more positive outcomes in children. Wiley Periodicals, Inc. © 2010 International League Against Epilepsy.

Adherence to National Dietary Guidelines in Association with Oral Health Impact on Quality of Life.

PubMed

Andreeva, Valentina A; Kesse-Guyot, Emmanuelle; Galan, Pilar; Feron, Gilles; Hercberg, Serge; Hennequin, Martine; Sulmont-Rossé, Claire

2018-04-24

We aimed to assess the association between oral health, in terms of its impact on quality of life, and diet quality expressed as adherence to dietary guidelines. We analyzed cross-sectional data from the French NutriNet-Santé general population-based e-cohort (N = 18,263 adults; mean age = 56.5 ± 13.8 years). The main independent variable, oral health-related quality of life, was assessed in 2016 with the GOHAI instrument (maximum score = 60). The main dependent variable, diet’s nutritional quality, was assessed with the mPNNS-GS score (maximum score = 13.5) measuring adherence to French dietary guidelines and computed on the basis of repeated 24-h dietary records. Multivariable linear regression models were fit. Mean GOHAI score was 54.5 ± 4.3 and mean mPNNS-GS score was 7.7 ± 1.6. Among participants aged 18⁻64 years, those scoring ≤50 on GOHAI (poor oral health with a detrimental impact on quality of life) were less likely to adhere to dietary guidelines than participants scoring 57⁻60 points (good oral health) (beta = −0.18, 95% CI: −0.26, −0.09; p < 0.0001). Among participants aged 65+ years, those scoring 51⁻56 points on GOHAI (average oral health with some negative impact on quality of life) were less likely to adhere to dietary guidelines than were participants scoring in the range 57⁻60 (beta = −0.23, 95% CI: −0.33, −0.13; p < 0.0001). The findings suggested modest age-dependent associations between oral health-related quality of life and diet quality. Confirmation is needed longitudinally with representative samples and accounting for diet quality evolution.

Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution

NASA Astrophysics Data System (ADS)

Vennam, L. P.; Vizuete, W.; Talgo, K.; Omary, M.; Binkowski, F. S.; Xing, J.; Mathur, R.; Arunachalam, S.

2017-12-01

Aviation is a unique anthropogenic source with four-dimensional varying emissions, peaking at cruise altitudes (9-12 km). Aircraft emission budgets in the upper troposphere lower stratosphere region and their potential impacts on upper troposphere and surface air quality are not well understood. Our key objective is to use chemical transport models (with prescribed meteorology) to predict aircraft emissions impacts on the troposphere and surface air quality. We quantified the importance of including full-flight intercontinental emissions and increased horizontal grid resolution. The full-flight aviation emissions in the Northern Hemisphere contributed 1.3% (mean, min-max: 0.46, 0.3-0.5 ppbv) and 0.2% (0.013, 0.004-0.02 μg/m3) of total O3 and PM2.5 concentrations at the surface, with Europe showing slightly higher impacts (1.9% (O3 0.69, 0.5-0.85 ppbv) and 0.5% (PM2.5 0.03, 0.01-0.05 μg/m3)) than North America (NA) and East Asia. We computed seasonal aviation-attributable mass flux vertical profiles and aviation perturbations along isentropic surfaces to quantify the transport of cruise altitude emissions at the hemispheric scale. The comparison of coarse (108 × 108 km2) and fine (36 × 36 km2) grid resolutions in NA showed 70 times and 13 times higher aviation impacts for O3 and PM2.5 in coarser domain. These differences are mainly due to the inability of the coarse resolution simulation to capture nonlinearities in chemical processes near airport locations and other urban areas. Future global studies quantifying aircraft contributions should consider model resolution and perhaps use finer scales near major aviation source regions.

Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution

PubMed Central

Vennam, L. P.; Vizuete, W.; Talgo, K.; Omary, M.; Binkowski, F. S.; Xing, J.; Mathur, R.; Arunachalam, S.

2018-01-01

Aviation is a unique anthropogenic source with four-dimensional varying emissions, peaking at cruise altitudes (9–12 km). Aircraft emission budgets in the upper troposphere lower stratosphere region and their potential impacts on upper troposphere and surface air quality are not well understood. Our key objective is to use chemical transport models (with prescribed meteorology) to predict aircraft emissions impacts on the troposphere and surface air quality. We quantified the importance of including full-flight intercontinental emissions and increased horizontal grid resolution. The full-flight aviation emissions in the Northern Hemisphere contributed ~1.3% (mean, min–max: 0.46, 0.3–0.5 ppbv) and 0.2% (0.013, 0.004–0.02 μg/m3) of total O3 and PM2.5 concentrations at the surface, with Europe showing slightly higher impacts (1.9% (O3 0.69, 0.5–0.85 ppbv) and 0.5% (PM2.5 0.03, 0.01–0.05 μg/m3)) than North America (NA) and East Asia. We computed seasonal aviation-attributable mass flux vertical profiles and aviation perturbations along isentropic surfaces to quantify the transport of cruise altitude emissions at the hemispheric scale. The comparison of coarse (108 × 108 km2) and fine (36 × 36 km2) grid resolutions in NA showed ~70 times and ~13 times higher aviation impacts for O3 and PM2.5 in coarser domain. These differences are mainly due to the inability of the coarse resolution simulation to capture nonlinearities in chemical processes near airport locations and other urban areas. Future global studies quantifying aircraft contributions should consider model resolution and perhaps use finer scales near major aviation source regions. PMID:29707471

The impact of illness-related shame on psychological health and social relationships: Testing a mediational model in students with chronic illness.

PubMed

Trindade, Inês A; Duarte, Joana; Ferreira, Cláudia; Coutinho, Mariana; Pinto-Gouveia, José

2018-05-01

This study explores the impact of illness-related shame on the quality of social relationships and psychological health in chronic patients. We aimed to examine the roles of fear of receiving compassion from others and experiential avoidance as potential mediators of this relationship. Although some studies have demonstrated the negative impact of chronic illness-related shame on psychological functioning, the mechanisms that may underlie this link remain understudied. The sample was comprised by 115 college students, which had been diagnosed with at least 1 chronic illness. Participants completed self-report measures on an online platform. This study's design was cross-sectional. A path analysis was conducted using structural equation modelling. Results showed that the impact of illness-related shame on both psychological health (R 2  = .45) and the quality of social relationships (R 2  = .33) was fully accounted by fear of compassion from others and experiential avoidance. This model revealed an excellent fit. Fear of receiving compassion from others was the main mediator of the illness-related shame link with the quality of social relationships (β = -.22). The main mediator of the association between shame-related chronic illness and psychological health was experiential avoidance (β = -.21).This study shed light on possible psychological mechanisms linking feelings of shame associated with having a chronic condition and impaired social relationships and mental health. On one hand, resisting feelings of compassion and care from others and, on the other hand, avoiding difficult internal experiences and situations that might trigger them seem to underlie the impact of shame on psychological and social functioning in chronic patients. Copyright © 2018 John Wiley & Sons, Ltd.

Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution.

PubMed

Vennam, L P; Vizuete, W; Talgo, K; Omary, M; Binkowski, F S; Xing, J; Mathur, R; Arunachalam, S

2017-01-01

Aviation is a unique anthropogenic source with four-dimensional varying emissions, peaking at cruise altitudes (9-12 km). Aircraft emission budgets in the upper troposphere lower stratosphere region and their potential impacts on upper troposphere and surface air quality are not well understood. Our key objective is to use chemical transport models (with prescribed meteorology) to predict aircraft emissions impacts on the troposphere and surface air quality. We quantified the importance of including full-flight intercontinental emissions and increased horizontal grid resolution. The full-flight aviation emissions in the Northern Hemisphere contributed ~1.3% (mean, min-max: 0.46, 0.3-0.5 ppbv) and 0.2% (0.013, 0.004-0.02 μg/m 3 ) of total O 3 and PM 2.5 concentrations at the surface, with Europe showing slightly higher impacts (1.9% (O 3 0.69, 0.5-0.85 ppbv) and 0.5% (PM 2.5 0.03, 0.01-0.05 μg/m 3 )) than North America (NA) and East Asia. We computed seasonal aviation-attributable mass flux vertical profiles and aviation perturbations along isentropic surfaces to quantify the transport of cruise altitude emissions at the hemispheric scale. The comparison of coarse (108 × 108 km 2 ) and fine (36 × 36 km 2 ) grid resolutions in NA showed ~70 times and ~13 times higher aviation impacts for O 3 and PM 2.5 in coarser domain. These differences are mainly due to the inability of the coarse resolution simulation to capture nonlinearities in chemical processes near airport locations and other urban areas. Future global studies quantifying aircraft contributions should consider model resolution and perhaps use finer scales near major aviation source regions.

Quality evaluation of health information system's architectures developed using the HIS-DF methodology.

PubMed

López, Diego M; Blobel, Bernd; Gonzalez, Carolina

2010-01-01

Requirement analysis, design, implementation, evaluation, use, and maintenance of semantically interoperable Health Information Systems (HIS) have to be based on eHealth standards. HIS-DF is a comprehensive approach for HIS architectural development based on standard information models and vocabulary. The empirical validity of HIS-DF has not been demonstrated so far. Through an empirical experiment, the paper demonstrates that using HIS-DF and HL7 information models, semantic quality of HIS architecture can be improved, compared to architectures developed using traditional RUP process. Semantic quality of the architecture has been measured in terms of model's completeness and validity metrics. The experimental results demonstrated an increased completeness of 14.38% and an increased validity of 16.63% when using the HIS-DF and HL7 information models in a sample HIS development project. Quality assurance of the system architecture in earlier stages of HIS development presumes an increased quality of final HIS systems, which supposes an indirect impact on patient care.

Determining the Uncertainties in Prescribed Burn Emissions Through Comparison of Satellite Estimates to Ground-based Estimates and Air Quality Model Evaluations in Southeastern US

NASA Astrophysics Data System (ADS)

Odman, M. T.; Hu, Y.; Russell, A. G.

2016-12-01

Prescribed burning is practiced throughout the US, and most widely in the Southeast, for the purpose of maintaining and improving the ecosystem, and reducing the wildfire risk. However, prescribed burn emissions contribute significantly to the of trace gas and particulate matter loads in the atmosphere. In places where air quality is already stressed by other anthropogenic emissions, prescribed burns can lead to major health and environmental problems. Air quality modeling efforts are under way to assess the impacts of prescribed burn emissions. Operational forecasts of the impacts are also emerging for use in dynamic management of air quality as well as the burns. Unfortunately, large uncertainties exist in the process of estimating prescribed burn emissions and these uncertainties limit the accuracy of the burn impact predictions. Prescribed burn emissions are estimated by using either ground-based information or satellite observations. When there is sufficient local information about the burn area, the types of fuels, their consumption amounts, and the progression of the fire, ground-based estimates are more accurate. In the absence of such information satellites remain as the only reliable source for emission estimation. To determine the level of uncertainty in prescribed burn emissions, we compared estimates derived from a burn permit database and other ground-based information to the estimates by the Biomass Burning Emissions Product derived from a constellation of NOAA and NASA satellites. Using these emissions estimates we conducted simulations with the Community Multiscale Air Quality (CMAQ) model and predicted trace gas and particulate matter concentrations throughout the Southeast for two consecutive burn seasons (2015 and 2016). In this presentation, we will compare model predicted concentrations to measurements at monitoring stations and evaluate if the differences are commensurate with our emission uncertainty estimates. We will also investigate if spatial and temporal patterns in the differences reveal the sources of the uncertainty in the prescribed burn emission estimates.

Impact on air quality of measures to reduce CO2 emissions from road traffic in Basel, Rotterdam, Xi'an and Suzhou

NASA Astrophysics Data System (ADS)

Keuken, M. P.; Jonkers, S.; Verhagen, H. L. M.; Perez, L.; Trüeb, S.; Okkerse, W.-J.; Liu, J.; Pan, X. C.; Zheng, L.; Wang, H.; Xu, R.; Sabel, C. E.

2014-12-01

Two traffic scenarios to reduce CO2 emissions from road traffic in two European cities (Basel and Rotterdam) and two Chinese cities (Xi'an and Suzhou) were evaluated in terms of their impact on air quality. The two scenarios, one modelling a reduction of private vehicle kilometres driven by 10% on urban streets and the other modelling the introduction of 50% electric-powered private vehicle kilometres on urban streets, were both compared to a scenario following “business-as-usual”: 2020-BAU. The annual average concentrations of NO2, PM2.5, PM10 and elemental carbon (EC) were modelled separately in busy street canyons, near urban motorways and in the remainder of the urban area. It was concluded that traffic-related CO2 emissions in 2020-BAU could be expected to remain at the levels of 2010 in Basel and Rotterdam, while in Xi'an and Suzhou to increase 30-50% due to growth in the traffic volume. Traffic-related CO2 emissions may be reduced by up to 5% and 25%, respectively using the first and second scenarios. Air pollution in the Chinese cities is a factor 3 to 5 higher than in the European cities in 2010 and 2020-BAU. The impact of both CO2 reduction scenarios on air quality in 2020-BAU is limited. In Europe, due to implementation of stringent emission standards in all sectors, air quality is expected to improve at both the urban background and near busy road traffic. In China, the regional background is expected to improve for EC, stabilize for PM2.5 and PM10, and decrease for NO2. The urban background follows this regional trend, while near busy road traffic, air pollution will remain elevated due to the considerable growth in traffic volume. A major constraint for modelling air quality in China is access to the input data required and lack of measurements at ground level for validation.

Water Quality Assessment in the Vouga Catchment (Portugal) through the Integration of Hydrologic Modeling, Economic Valuation, and Optimization Methods

NASA Astrophysics Data System (ADS)

Hawtree, Daniel; Julich, Stefan; Rocha, João; Roebeling, Peter; Feger, Karl-Heinz

2016-04-01

Hydrologic model assessments of the impacts of land-cover / use change (LCLUC) are fundamental for the development of catchment management plans, which are increasingly needed for meeting water quality standards (i.e. Water Framework Directive). These assessments can be difficult to conduct at the spatial scale required for such plans, due to data limitations and the challenge of up-scaling from field / small scale studies to larger regions. Furthermore, such hydrologic assessments are of limited practical use if the financial impacts of any potential land-cover / management changes on local stakeholders are adequately quantified and taken into planning consideration. To address these challenges, this study presents an approach that integrates hydrologic modeling, economic valuation, and landscape optimization methods. This approach is applied to the Vouga catchment, a large (2,298 km^2) mixed land-use catchment in north-central Portugal. The Vouga has high nutrient (nitrogen and phosphorus) impacts in a number of reaches, which have negative impacts on downstream wetlands and groundwater supplies. To examine potential improvements to water quality, the Soil and Water Assessment Tool (SWAT) was calibrated over a five period (2002 - 2007) to establish the baseline hydrologic and nutrient fluxes. This calibration relies upon the up-scaling of findings from previous field studies (on vegetation and soils), hydrologic assessments, and modeling studies. The agricultural income for local stakeholders was estimated from existing land-cover and management approaches is made, to establish the baseline financial conditions. An optimization algorithm is then applied to the baseline scenario using both the biophysical and financial information, which seeks to determine various (most) optimal states. The preliminary results from this work are presented, and the advantages and challenges of using such an approach for scenario analysis for catchment management are discussed

CONSTRAINING URBAN-TO-GLOBAL SCALE ESTIMATES OF BLACK CARBON DISTRIBUTIONS, SOURCES, REGIONAL CLIMATE IMPACTS, AND CO-BENEFIT METRICS WITH ADVANCED COUPLED DYNAMIC - CHEMICAL TRANSPORT - ADJOINT MODELS

EPA Science Inventory

This project will provide an unprecedented and much-needed identification and ranking of the sources of uncertainty in BC, its effects on climate, and the impacts of policy actions to reduce its impact on air quality and climate. The estimates of process and emissions uncertai...

Quality by Design approach for studying the impact of formulation and process variables on product quality of oral disintegrating films.

PubMed

Mazumder, Sonal; Pavurala, Naresh; Manda, Prashanth; Xu, Xiaoming; Cruz, Celia N; Krishnaiah, Yellela S R

2017-07-15

The present investigation was carried out to understand the impact of formulation and process variables on the quality of oral disintegrating films (ODF) using Quality by Design (QbD) approach. Lamotrigine (LMT) was used as a model drug. Formulation variable was plasticizer to film former ratio and process variables were drying temperature, air flow rate in the drying chamber, drying time and wet coat thickness of the film. A Definitive Screening Design of Experiments (DoE) was used to identify and classify the critical formulation and process variables impacting critical quality attributes (CQA). A total of 14 laboratory-scale DoE formulations were prepared and evaluated for mechanical properties (%elongation at break, yield stress, Young's modulus, folding endurance) and other CQA (dry thickness, disintegration time, dissolution rate, moisture content, moisture uptake, drug assay and drug content uniformity). The main factors affecting mechanical properties were plasticizer to film former ratio and drying temperature. Dissolution rate was found to be sensitive to air flow rate during drying and plasticizer to film former ratio. Data were analyzed for elucidating interactions between different variables, rank ordering the critical materials attributes (CMA) and critical process parameters (CPP), and for providing a predictive model for the process. Results suggested that plasticizer to film former ratio and process controls on drying are critical to manufacture LMT ODF with the desired CQA. Published by Elsevier B.V.

The Impact of Marketing Actions on Relationship Quality in the Higher Education Sector in Jordan

ERIC Educational Resources Information Center

Al-Alak, Basheer A. M.

2006-01-01

This field/analytical study examined the marketing actions (antecedents) and performance (consequences) of relationship quality in a higher education setting. To analyze data collected from a random sample of 271 undergraduate students at AL-Zaytoonah Private University of Jordan, the linear structural relationship (LISREL) model was used to…

A Systems Approach to Manage Drinking Water Quality through Integrated Model Projections, Adaptive Monitoring and Process Optimization - abstract

EPA Science Inventory

Drinking water supplies can be vulnerable to impacts from short-term weather events, long-term changes in land-use and climate, and water quality controls in treatment and distribution. Disinfection by-product (DBP) formation in drinking water is a prominent example to illustrate...

A Systems Approach to Manage Drinking Water Quality through Integrated Model Projections, Adaptive Monitoring and Process Optimization

EPA Science Inventory

Drinking water supplies can be vulnerable to impacts from short-term weather events, long-term changes in land-use and climate, and water quality controls in treatment and distribution. Disinfection by-product (DBP) formation in drinking water is a prominent example to illustrate...

Writing Week-Journals to Improve the Writing Quality of Fourth-Graders' Compositions

ERIC Educational Resources Information Center

Rosário, Pedro; Högemann, Julia; Núñez, José Carlos; Vallejo, Guillermo; Cunha, Jennifer; Oliveira, Vera; Fuentes, Sonia; Rodrigues, Celestino

2017-01-01

Students' writing problems are a global educational concern and is in need of particular attention. This study aims to examine the impact of providing extra writing opportunities (i.e., writing journals) on the quality of writing compositions. A longitudinal cluster-randomized controlled design using a multilevel modeling analysis with 182 fourth…

Mining Information form a Coupled Air Quality Model to Examine the Impacts of Agricultural Management Practices on Air and Groundwater Quality

EPA Science Inventory

Attributing nitrogen (N) in the environment to emissions from agricultural management practices is difficult because of the complex and inter-related chemical and biological reactions associated with N and its cascading effects across land, air and water. Such analyses are criti...

Application of a tablet film coating model to define a process-imposed transition boundary for robust film coating.

PubMed

van den Ban, Sander; Pitt, Kendal G; Whiteman, Marshall

2018-02-01

A scientific understanding of interaction of product, film coat, film coating process, and equipment is important to enable design and operation of industrial scale pharmaceutical film coating processes that are robust and provide the level of control required to consistently deliver quality film coated product. Thermodynamic film coating conditions provided in the tablet film coating process impact film coat formation and subsequent product quality. A thermodynamic film coating model was used to evaluate film coating process performance over a wide range of film coating equipment from pilot to industrial scale (2.5-400 kg). An approximate process-imposed transition boundary, from operating in a dry to a wet environment, was derived, for relative humidity and exhaust temperature, and used to understand the impact of the film coating process on product formulation and process control requirements. This approximate transition boundary may aid in an enhanced understanding of risk to product quality, application of modern Quality by Design (QbD) based product development, technology transfer and scale-up, and support the science-based justification of critical process parameters (CPPs).

Predictors of burnout, work engagement and nurse reported job outcomes and quality of care: a mixed method study.

PubMed

Van Bogaert, Peter; Peremans, Lieve; Van Heusden, Danny; Verspuy, Martijn; Kureckova, Veronika; Van de Cruys, Zoë; Franck, Erik

2017-01-01

High levels of work-related stress, burnout, job dissatisfaction, and poor health are common within the nursing profession. A comprehensive understanding of nurses' psychosocial work environment is necessary to respond to complex patients' needs. The aims of this study were threefold: (1) To retest and confirm two structural equation models exploring associations between practice environment and work characteristics as predictors of burnout (model 1) and engagement (model 2) as well as nurse-reported job outcome and quality of care; (2) To study staff nurses' and nurse managers' perceptions and experiences of staff nurses' workload; (3) To explain and interpret the two models by using the qualitative study findings. This mixed method study is based on an explanatory sequential study design. We first performed a cross-sectional survey design in two large acute care university hospitals. Secondly, we conducted individual semi-structured interviews with staff nurses and nurse managers assigned to medical or surgical units in one of the study hospitals. Study data was collected between September 2014 and June 2015. Finally, qualitative study results assisted in explaining and interpreting the findings of the two models. The two models with burnout and engagement as mediating outcome variables fitted sufficiently to the data. Nurse-reported job outcomes and quality of care explained variances between 52 and 62%. Nurse management at the unit level and workload had a direct impact on outcome variables with explained variances between 23 and 36% and between 12 and 17%, respectively. Personal accomplishment and depersonalization had an explained variance on job outcomes of 23% and vigor of 20%. Burnout and engagement had a less relevant direct impact on quality of care (≤5%). The qualitative study revealed various themes such as organisation of daily practice and work conditions; interdisciplinary collaboration, communication and teamwork; staff nurse personal characteristics and competencies; patient centeredness, quality and patient safety. Respondents' statements corresponded closely to the models' associations. A deep understanding of various associations and impacts on studied outcome variables such as risk factors and protective factors was gained through the retested models and the interviews with the study participants. Besides the softer work characteristics - such as decision latitude, social capital and team cohesion - more insight and knowledge of the hard work characteristic workload is essential.

Evaluation of model-predicted hazardous air pollutants (HAPs) near a mid-sized U.S. airport

NASA Astrophysics Data System (ADS)

Vennam, Lakshmi Pradeepa; Vizuete, William; Arunachalam, Saravanan

2015-10-01

Accurate modeling of aircraft-emitted pollutants in the vicinity of airports is essential to study the impact on local air quality and to answer policy and health-impact related issues. To quantify air quality impacts of airport-related hazardous air pollutants (HAPs), we carried out a fine-scale (4 × 4 km horizontal resolution) Community Multiscale Air Quality model (CMAQ) model simulation at the T.F. Green airport in Providence (PVD), Rhode Island. We considered temporally and spatially resolved aircraft emissions from the new Aviation Environmental Design Tool (AEDT). These model predictions were then evaluated with observations from a field campaign focused on assessing HAPs near the PVD airport. The annual normalized mean error (NME) was in the range of 36-70% normalized mean error for all HAPs except for acrolein (>70%). The addition of highly resolved aircraft emissions showed only marginally incremental improvements in performance (1-2% decrease in NME) of some HAPs (formaldehyde, xylene). When compared to a coarser 36 × 36 km grid resolution, the 4 × 4 km grid resolution did improve performance by up to 5-20% NME for formaldehyde and acetaldehyde. The change in power setting (from traditional International Civil Aviation Organization (ICAO) 7% to observation studies based 4%) doubled the aircraft idling emissions of HAPs, but led to only a 2% decrease in NME. Overall modeled aircraft-attributable contributions are in the range of 0.5-28% near a mid-sized airport grid-cell with maximum impacts seen only within 4-16 km from the airport grid-cell. Comparison of CMAQ predictions with HAP estimates from EPA's National Air Toxics Assessment (NATA) did show similar annual mean concentrations and equally poor performance. Current estimates of HAPs for PVD are a challenge for modeling systems and refinements in our ability to simulate aircraft emissions have made only incremental improvements. Even with unrealistic increases in HAPs aviation emissions the model could not match observed concentrations near the runway airport site. Our results suggest other uncertainties in the modeling system such as meteorology, HAPs chemistry, or other emission sources require increased scrutiny.

[Weight parameters of water quality impact and risk grade determination of water environmental sensitive spots in Jiashan].

PubMed

Xie, Rong-Rong; Pang, Yong; Zhang, Qian; Chen, Ke; Sun, Ming-Yuan

2012-07-01

For the safety of the water environment in Jiashan county in Zhejiang Province, one-dimensional hydrodynamic and water quality models are established based on three large-scale monitoring of hydrology and water quality in Jiashan county, three water environmental sensitive spots including Hongqitang dam Chijia hydrological station and Luxie pond are selected to investigate weight parameters of water quality impact and risk grade determination. Results indicate as follows (1) Internal pollution impact in Jiashan areas was greater than the external, the average weight parameters of internal chemical oxygen demand (COD) pollution is 55.3%, internal ammonia nitrogen (NH(4+)-N) is 67.4%, internal total phosphor (TP) is 63.1%. Non-point pollution impact in Jiashan areas was greater than point pollution impact, the average weight parameters of non-point COD pollutions is 53.7%, non-point NH(4+)-N is 65.9%, non-point TP is 57.8%. (2) The risk of Hongqitang dam and Chijia hydrological station are in the middle risk. The risk of Luxie pond is also in the middle risk in August, and in April and December the risk of Luxie pond is low. The strategic decision will be suggested to guarantee water environment security and social and economic security in the study.

A systematic quality assessment of Environmental Impact Statements in the oil and gas industry.

PubMed

Anifowose, B; Lawler, D M; van der Horst, D; Chapman, L

2016-12-01

The global economy relies heavily on oil and gas resources. However, hydrocarbon exploitation projects can cause significant impacts on the environment. But despite the production of numerous Environmental Impact Statements (EISs) to identify/mitigate such impacts, no study has specifically assessed the quality of EISs for both onshore and offshore oil and gas projects, with tested hypotheses. To address this research gap, our paper, for the first time, develops a modified Lee and Colley evaluation model to assess the quality of 19 sampled oil and gas project EISs produced from 1998 to 2008 in Nigeria. Our findings show that Project Description and Communication of Results are the main areas of strength. However, Environmental Impact Prediction, and Project Decommissioning, were among the key areas requiring attention. A key finding, though, is that Mann-Whitney tests suggest that there is no evidence that the quality of EISs for the latter period (2004-2008) is higher than that of the earlier period (1998-2004). We suggest that periodic systematic review of the quality of submitted/approved EISs (c. every 3-5years) should be established to monitor trends in EIS quality and identify strong and weak areas. This would help to drive continual improvement in both the EIA processes and the resultant EISs of technical engineering projects. Such reviews have the potential to illuminate some of the underlying problems of, and solutions to, oil and gas exploration, production and transportation, and their related environmental impacts. This suggested change would also be useful internationally, including for the burgeoning exploration and production of unconventional hydrocarbon resources. Copyright © 2016 Elsevier B.V. All rights reserved.

Air Emissions Inventories

EPA Pesticide Factsheets

This site provides access to emissions data, regulations and guidance, electronic system access, resources and tools to support trends analysis, regional, and local scale air quality modeling, regulatory impact assessments.

Critical appraisal of assumptions in chains of model calculations used to project local climate impacts for adaptation decision support—the case of Baakse Beek

NASA Astrophysics Data System (ADS)

van der Sluijs, Jeroen P.; Arjan Wardekker, J.

2015-04-01

In order to enable anticipation and proactive adaptation, local decision makers increasingly seek detailed foresight about regional and local impacts of climate change. To this end, the Netherlands Models and Data-Centre implemented a pilot chain of sequentially linked models to project local climate impacts on hydrology, agriculture and nature under different national climate scenarios for a small region in the east of the Netherlands named Baakse Beek. The chain of models sequentially linked in that pilot includes a (future) weather generator and models of respectively subsurface hydrogeology, ground water stocks and flows, soil chemistry, vegetation development, crop yield and nature quality. These models typically have mismatching time step sizes and grid cell sizes. The linking of these models unavoidably involves the making of model assumptions that can hardly be validated, such as those needed to bridge the mismatches in spatial and temporal scales. Here we present and apply a method for the systematic critical appraisal of model assumptions that seeks to identify and characterize the weakest assumptions in a model chain. The critical appraisal of assumptions presented in this paper has been carried out ex-post. For the case of the climate impact model chain for Baakse Beek, the three most problematic assumptions were found to be: land use and land management kept constant over time; model linking of (daily) ground water model output to the (yearly) vegetation model around the root zone; and aggregation of daily output of the soil hydrology model into yearly input of a so called ‘mineralization reduction factor’ (calculated from annual average soil pH and daily soil hydrology) in the soil chemistry model. Overall, the method for critical appraisal of model assumptions presented and tested in this paper yields a rich qualitative insight in model uncertainty and model quality. It promotes reflectivity and learning in the modelling community, and leads to well informed recommendations for model improvement.

Assessment of predictors of the impact of fibromyalgia on health-related quality of life 12 months after the end of an interdisciplinary treatment.

PubMed

Martín, Josune; Torre, Fernando; Aguirre, Urko; Padierna, Angel; Matellanes, Begoña; Quintana, José M

2017-01-15

Fibromyalgia is a chronic pain disorder with a range of comorbid symptoms, including anxiety. We aimed to prospectively identify predictors of the long-term impact of fibromyalgia on health-related quality of life after the end of an interdisciplinary intervention. 138 patients with fibromyalgia, selected from a hospital pain management unit, participated in a 6-week interdisciplinary treatment that combined coordinated psychological, medical, educational, and physiotherapeutic interventions. Participants completed the Fibromyalgia Impact Questionnaire and the Hospital Anxiety and Depression Scale at baseline and 6 weeks, 6 months, and 12 months after the intervention. Multivariable generalized linear mixed models were developed, using the Fibromyalgia Impact Questionnaire score as a continuous variable. Variables that were significant predictors of the long-term impact of fibromyalgia on health-related quality of life in patients who completed a 6-week interdisciplinary treatment were marital status, the number of concurrent conditions, years since the onset of pain, and symptoms of anxiety. In the longitudinal analysis, patients with symptoms of anxiety had lower rates of improvement than those without symptoms of anxiety. Our results suggest that patients with lower level of anxiety have less impact on their HRQoL. The results also provide evidence that starting interventions as soon as possible is an important factor for improving health-related quality of life. Copyright © 2016 Elsevier B.V. All rights reserved.

The Impact of Long-Term Climate Change on Nitrogen Runoff at the Watershed Scale.

NASA Astrophysics Data System (ADS)

Dorley, J.; Duffy, C.; Arenas Amado, A.

2017-12-01

The impact of agricultural runoff is a major concern for water quality of mid-western streams. This concern is largely due to excessive use of agricultural fertilizer, a major source of nutrients in many Midwestern watersheds. In order to improve water quality in these watersheds, understanding the long-term trends in nutrient concentration and discharge is an important water quality problem. This study attempts to analyze the role of long-term temperature and precipitation on nitrate runoff in an agriculturally dominated watershed in Iowa. The approach attempts to establish the concentration-discharge (C-Q) signature for the watershed using time series analysis, frequency analysis and model simulation. The climate data is from the Intergovernmental Panel on Climate Change (IPCC), model GFDL-CM3 (Geophysical Fluid Dynamic Laboratory Coupled Model 3). The historical water quality data was made available by the IIHR-Hydroscience & Engineering at the University of Iowa for the clear creek watershed (CCW). The CCW is located in east-central Iowa. The CCW is representative of many Midwestern watersheds with humid-continental climate with predominantly agricultural land use. The study shows how long-term climate changes in temperature and precipitation affects the C-Q dynamics and how a relatively simple approach to data analysis and model projections can be applied to best management practices at the site.

Public reporting in health care: how do consumers use quality-of-care information? A systematic review.

PubMed

Faber, Marjan; Bosch, Marije; Wollersheim, Hub; Leatherman, Sheila; Grol, Richard

2009-01-01

One of the underlying goals of public reporting is to encourage the consumer to select health care providers or health plans that offer comparatively better quality-of-care. To review the weight consumers give to quality-of-care information in the process of choice, to summarize the effect of presentation formats, and to examine the impact of quality information on consumers' choice behavior. The evidence is organized in a theoretical consumer choice model. English language literature was searched in PubMed, the Cochrane Clinical Trial, and the EPOC Databases (January 1990-January 2008). Study selection was limited to randomized controlled trails, controlled before-after trials or interrupted time series. Included interventions focused on choice behavior of consumers in health care settings. Outcome measures referred to one of the steps in a consumer choice model. The quality of the study design was rated, and studies with low quality ratings were excluded. All 14 included studies examine quality information, usually CAHPS, with respect to its impact on the consumer's choice of health plans. Easy-to-read presentation formats and explanatory messages improve knowledge about and attitude towards the use of quality information; however, the weight given to quality information depends on other features, including free provider choice and costs. In real-world settings, having seen quality information is a strong determinant for choosing higher quality-rated health plans. This review contributes to an understanding of consumer choice behavior in health care settings. The small number of included studies limits the strength of our conclusions.

The impact of local surface changes in Borneo on atmospheric composition at wider spatial scales: coastal processes, land-use change and air quality

PubMed Central

Pyle, J. A.; Warwick, N. J.; Harris, N. R. P.; Abas, Mohd Radzi; Archibald, A. T.; Ashfold, M. J.; Ashworth, K.; Barkley, Michael P.; Carver, G. D.; Chance, K.; Dorsey, J. R.; Fowler, D.; Gonzi, S.; Gostlow, B.; Hewitt, C. N.; Kurosu, T. P.; Lee, J. D.; Langford, S. B.; Mills, G.; Moller, S.; MacKenzie, A. R.; Manning, A. J.; Misztal, P.; Nadzir, Mohd Shahrul Mohd; Nemitz, E.; Newton, H. M.; O'Brien, L. M.; Ong, Simon; Oram, D.; Palmer, P. I.; Peng, Leong Kok; Phang, Siew Moi; Pike, R.; Pugh, T. A. M.; Rahman, Noorsaadah Abdul; Robinson, A. D.; Sentian, J.; Samah, Azizan Abu; Skiba, U.; Ung, Huan Eng; Yong, Sei Eng; Young, P. J.

2011-01-01

We present results from the OP3 campaign in Sabah during 2008 that allow us to study the impact of local emission changes over Borneo on atmospheric composition at the regional and wider scale. OP3 constituent data provide an important constraint on model performance. Treatment of boundary layer processes is highlighted as an important area of model uncertainty. Model studies of land-use change confirm earlier work, indicating that further changes to intensive oil palm agriculture in South East Asia, and the tropics in general, could have important impacts on air quality, with the biggest factor being the concomitant changes in NOx emissions. With the model scenarios used here, local increases in ozone of around 50 per cent could occur. We also report measurements of short-lived brominated compounds around Sabah suggesting that oceanic (and, especially, coastal) emission sources dominate locally. The concentration of bromine in short-lived halocarbons measured at the surface during OP3 amounted to about 7 ppt, setting an upper limit on the amount of these species that can reach the lower stratosphere. PMID:22006963

The impact of local surface changes in Borneo on atmospheric composition at wider spatial scales: coastal processes, land-use change and air quality.

PubMed

Pyle, J A; Warwick, N J; Harris, N R P; Abas, Mohd Radzi; Archibald, A T; Ashfold, M J; Ashworth, K; Barkley, Michael P; Carver, G D; Chance, K; Dorsey, J R; Fowler, D; Gonzi, S; Gostlow, B; Hewitt, C N; Kurosu, T P; Lee, J D; Langford, S B; Mills, G; Moller, S; MacKenzie, A R; Manning, A J; Misztal, P; Nadzir, Mohd Shahrul Mohd; Nemitz, E; Newton, H M; O'Brien, L M; Ong, Simon; Oram, D; Palmer, P I; Peng, Leong Kok; Phang, Siew Moi; Pike, R; Pugh, T A M; Rahman, Noorsaadah Abdul; Robinson, A D; Sentian, J; Samah, Azizan Abu; Skiba, U; Ung, Huan Eng; Yong, Sei Eng; Young, P J

2011-11-27

We present results from the OP3 campaign in Sabah during 2008 that allow us to study the impact of local emission changes over Borneo on atmospheric composition at the regional and wider scale. OP3 constituent data provide an important constraint on model performance. Treatment of boundary layer processes is highlighted as an important area of model uncertainty. Model studies of land-use change confirm earlier work, indicating that further changes to intensive oil palm agriculture in South East Asia, and the tropics in general, could have important impacts on air quality, with the biggest factor being the concomitant changes in NO(x) emissions. With the model scenarios used here, local increases in ozone of around 50 per cent could occur. We also report measurements of short-lived brominated compounds around Sabah suggesting that oceanic (and, especially, coastal) emission sources dominate locally. The concentration of bromine in short-lived halocarbons measured at the surface during OP3 amounted to about 7 ppt, setting an upper limit on the amount of these species that can reach the lower stratosphere.