Benefits Mapping And Analysis Program-Community Edition Research Articles

Quantifying Multipollutant Health Impacts Using the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE): A Case Study in Atlanta, Georgia.

Air pollution risk assessments do not generally quantify health impacts using multipollutant risk estimates, but instead use results from single-pollutant or copollutant models. Multipollutant epidemiological models account for pollutant interactions and joint effects but can be computationally complex and data intensive. Risk estimates from multipollutant studies are therefore challenging to implement in the quantification of health impacts. Our objective was to conduct a case study using a developmental multipollutant version of the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) to estimate the health impact associated with changes in multiple air pollutants using both a single and multipollutant approach. BenMAP-CE was used to estimate the change in the number of pediatric asthma emergency department (ED) visits attributable to simulated changes in air pollution between 2011 and 2025 in Atlanta, Georgia, applying risk estimates from an epidemiological study that examined short-term single-pollutant and multipollutant (with and without first-order interactions) exposures. Analyses examined individual pollutants (i.e., ozone, fine particulate matter, carbon monoxide, nitrogen dioxide (), sulfur dioxide, and particulate matter components) and combinations of these pollutants meant to represent shared properties or predefined sources (i.e., oxidant gases, secondary pollutants, traffic, power plant, and criteria pollutants). Comparisons were made between multipollutant health impact functions (HIF) and the sum of single-pollutant HIFs for the individual pollutants that constitute the respective pollutant groups. Photochemical modeling predicted large decreases in most of the examined pollutant concentrations between 2011 and 2025 based on sector specific (i.e., source-based) estimates of growth and anticipated controls. Estimated number of avoided asthma ED visits attributable to any given multipollutant group were generally higher when using results from models that included interaction terms in comparison with those that did not. We estimated the greatest number of avoided pediatric asthma ED visits for pollutant groups that include (i. e., criteria pollutants, oxidants, and traffic pollutants). In models that accounted for interaction, year-round estimates for pollutant groups that included ranged from 27.1 [95% confidence interval (CI): 1.6, 52.7; traffic pollutants] to 55.4 (95% CI: 41.8, 69.0; oxidants) avoided pediatric asthma ED visits. Year-round results using multipollutant risk estimates with interaction were comparable to the sum of the single-pollutant results corresponding to most multipollutant groups [e.g., 52.9 (95% CI: 43.6, 62.2) for oxidants] but were notably lower than the sum of the single-pollutant results for some pollutant groups [e.g., 77.5 (95% CI: 66.0, 89.0) for traffic pollutants]. Performing a multipollutant health impact assessment is technically feasible but computationally complex. It requires time, resources, and detailed input parameters not commonly reported in air pollution epidemiological studies. Results estimated using the sum of single-pollutant models are comparable to those quantified using a multipollutant model. Although limited to a single study and location, assessing the trade-offs between a multipollutant and single-pollutant approach is warranted. https://doi.org/10.1289/EHP12969.

Health and economic cost estimates of short-term total and wildfire PM2.5 exposure on work loss: using the consecutive California Health Interview Survey (CHIS) data 2015–2018

InstructionTo help determine the health protectiveness of government regulations and policies for air pollutant control for Americans, our study aimed to investigate the health and economic impacts of work loss...

Health Impact Assessment of Short-Term Exposure to Particulate Matter (PM10) in Northern Thailand.

In northern Thailand, in recent decades, particulate pollution from the burning of biomass has become a serious issue with toxicological implications for human health, especially during the winter months of January to April. The purpose of this study was to explore short-term exposure to particulate matter (PM10) in northern Thailand. The high PM10 concentration in 2012 was used as a case study. We used the EPA's Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) for the health impact assessment, along with ground-based measurement data. The annual average observed PM10 concentration was in the range of 43-61 μg/m3, with a maximum observed PM10 concentration of 300 μg/m3 in March. We then assessed the impacts of PM10 exposure in northern Thailand. When the PM10 concentration was reduced to 120 μg/m3, the undesirable effects on respiratory mortality decreased by 5%-11%. When the concentration of PM10 was reduced to 45 μg/m3, the deleterious effects on respiratory mortality decreased by 11-30%. In conclusion, adherence to the WHO-AQG, particularly for PM10 (45 μg/m3), tends to result in considerable reductions in respiratory disease mortality in northern Thailand.

Assessment of health and economic benefits of reducing fine particulate matter (PM2.5) concentration in Ho Chi Minh City, Vietnam

Ambient fine particulate matter (PM2.5) is a growing issue in Ho Chi Minh City (HCMC), the most populous province in Viet Nam. Estimating the benefits of reducing PM2.5 levels has still been sparse in HCMC.The study used the Environmental Benefits Mapping and Analysis Program – Community Edition (BenMAP-CE) to estimate the health, and economic benefits in three controlling scenarios of annual average PM2.5 concentration in 2019 (28.9 µg/m3) rolling back to the World Health Organization's annual average Air Quality Guideline values of 5 µg/m3 (guideline value in 2021), and 10 µg/m3 (guideline value in 2005 which becomes Interim Target 4 of 2021 WHO Air Quality Guideline), and the Vietnamese annual average standard of 25 µg/m3.The annual average concentration of PM2.5 in 2019 was 28.9 µg/m3. Applying BenMAP-CE, the pooled number of avoided deaths of all causes was 3,785 (1,179–6,335), 3,195 (982–5,468), and 1,300 (384–2,386) for three scenarios, respectively. The economic benefits were $ 2.4 (0.8–4.1), $ 2.1 (0.6–3.5), and $ 0.8 (0.2–1.5) billion, using the Value of Statistical Life (VSL) of OECD (the Organization for Economic Cooperation and Development) and $ 3.7 (1.2–6.2), $ 3.1 (1.0–5.4) and $ 1.3 (0.4–2.3) billion, using the VSL of USEPA (the United States Environmental Protection Agency).The annual average PM2.5 concentration in HCMC exceeded the Vietnamese standard and WHO guidelines. Controlling PM2.5 showed massive benefits for health and the economy; thus, the city should have action plans for mitigating the PM2.5 pollution.

Integrated analysis of energy-pollution-health nexus for sustainable energy planning

In recent years, the emission of various pollutants has caused many problems for human life and the ecosystem. The prioritization between different air pollution control scenarios is a challenge between scientists and policy-makers. This study develops an integrated method for sustainable energy planning considering the energy-pollution-health nexus. The paper investigates three main pollutants (i.e., PM2.5, SO2, and NOx) of different emission sources (i.e., industrial, residential, and intra-city and suburban transportations) in twelve scenarios. The American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) is applied to model the air pollution dispersion, and Environmental Benefits Mapping and Analysis Program - Community Edition (BenMAP-CE) is used for the health effect assessment. Also, the health and economic benefits of the scenarios are estimated for a region in Qazvin, I. R. Iran. Finally, the trades-off between the health benefits of cleaner ambient air and the economic benefits of energy scenarios are carefully studied for prioritizing the scenarios. The results show the scenarios of thermal efficiency enhancement of gas heaters and converting 30% of gasoline cars to CNG-burning cars in the intra-city transportation sector are the most appropriate scenarios to reduce pollution according to the net profit (about 8 and 6.3 million USD, respectively) while the scenario of reducing 10% of industrial production is the worst scenario according to this criterion (−46.4 million USD). Accordingly, the results emphasize that the closure of industrial plants to control air pollution should be stopped because it has high economic loss while its health benefit is inconsiderable in the region. The framework and results of the present paper are helpful for policy-makers, managers, and authorities to develop sustainable energy planning.

Impacts of emissions along the lower Yangtze River on air quality and public health in the Yangtze River delta, China

The area along (and on) the lower Yangtze River is a hotspot in the Yangtze River Delta (YRD) due to intense anthropogenic emissions to both the water and the atmosphere. However, air emissions in the vicinity of the river have received less attention. In this study, the Community Multi-scale Air Quality (CMAQ) model and the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) were applied to quantify the impacts of air emissions in the area within 4 km of the Yangtze River (referred to as the 4 YR area) on the air quality and public health in the YRD in 2017. The 4 YR area had air pollutant emission intensities 1.6–9.6 times higher than the domain-wide averages, and contributed ∼7.5% of the annual PM2.5 concentration across the YRD. Moreover, the emissions led to widespread enhancement of the daily maximum 8-h average (MDA8) O3 concentration in the downwind areas in summer, with an average contribution of 1.5%, while titration of O3 occurred in other seasons. As a result, the emissions increased population-weighted concentration (PWC) of PM2.5 by up to 11.5 μg m−3 near the river, leading to premature mortality of ∼17,000 in the YRD. Additionally, the mortality in terms of O3 exposure was less substantial, due to the lower PWC of O3 at distances of less than 40 km from the river. The emissions were responsible for mortality of ∼6000 due to higher exposure to NO2. The results suggest that it is beneficial to public health to reduce emissions in the 4 YR area.

Spatiotemporal variation of ozone pollution and health effects in China.

With the rapid urbanization and industrialization in China, ozone pollution has become increasingly serious and poses a greater threat to human health. In this study, the spatiotemporal distribution of ozone pollution in China's cities and urban agglomerations from 2015 to 2019 was analyzed. The health effects and health economic costs of ozone pollution in China were estimated by applying the environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) model. The results are as follows: (1) ozone pollution was more serious in Chinese urban agglomerations from 2015 to 2019; (2) the hot spots of ozone concentration mainly distributed in the North China Plain, expanding from north to south; the cold spots decreased year by year and were located in the northeast, northwest, and southwest of China, shifting from northwest to southwest; (3) the seasonal average of ozone concentration in China was the highest in summer, followed by spring and autumn, and the lowest in winter; (4) the number of all-cause premature deaths of ozone pollution in China increased slowly from 2015 to 2019, and the average of urban agglomerations was significantly higher than cities, with similar spatial distribution characteristics as ozone concentration; (5) the health economic costs of ozone pollution from 2015 to 2019 slowly expanded to surrounding cities with Beijing, Shanghai, Xi'an, and Chongqing as the centers of high values, while the low value areas decreased year by year and were mainly concentrated in southwest and northeast China. The health economic costs of ozone pollution at urban agglomerations scale were higher in the eastern coastal regions and lower in the northwest inland regions. Thus, this study presents policy recommendations to provide decision-making reference for realizing the inter-regional prevention and control of ozone pollution.

Estimating Mortality Related to O3 and PM2.5 under Changing Climate and Emission in Continental Southeast Asia

Air pollution causes adverse effects not only on the environment but also on human health. This study evaluated the excess mortalities in continental Southeast Asia that are related to future O3 and PM2.5 ambient concentration changes attributed to future climate change and emission change. The Environmental Benefits Mapping and Analysis Program - Community Edition (BenMAP-CE) was applied as a health impact assessment tool. In BenMAP-CE simulations, baseline scenarios presenting for the present year (2014) were compared against the control scenarios presenting for the future year (2050). The air pollutant concentrations for the simulations were collected from modeled data. The future population data and baseline incidence rates were as same as the 2014 levels. In four calculating countries namely Laos, Cambodia, Thailand, and Vietnam, on average, impacted by climate change alone, the avoided mortalities of -1164 and -3358 under Representative Concentration Pathway (RCP) 4.5 scenario and the additional mortalities of +758 and +2562 under RCP8.5 scenario were calculated for O3 and PM2.5, respectively. Future emission change alone under Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants current legislation (ECLIPSE CLE) scenario induces +7113 and +11072 additional O3 and PM2.5 related mortalities, respectively. Combined change in climate and emission produces additional O3 and PM2.5 related mortalities of +6067 and +7830 under RCP4.5 and ECLIPSE CLE combined scenario and +8763 and +14580 under RCP8.5 and ECLIPSE CLE combined scenario, respectively. The results of this study provided meaningful information for understanding the public health attributed to air pollution in the region.

Effects of using different exposure data to estimate changes in premature mortality attributable to PM2.5 and O3 in China

The assessment of premature mortality associated with the dramatic changes in fine particulate matter (PM2.5) and ozone (O3) has important scientific significance and provides valuable information for future emission control strategies. Exposure data are particularly vital but may cause great uncertainty in health burden assessments. This study, for the first time, used six methods to generate the concentration data of PM2.5 and O3 in China between 2014 and 2018, and then quantified the changes in premature mortality due to PM2.5 and O3 using the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) model. The results show that PM2.5-related premature mortality in China decreases by 263 (95% confidence interval (CI95): 142–159) to 308 (CI95: 213–241) thousands from 2014 to 2018 by using different concentration data, while O3-related premature mortality increases by 67 (CI95: 26–104) to 103 (CI95: 40–163) thousands. The estimated mean changes are up to 40% different for the PM2.5-related mortality, and up to 30% for the O3-related mortality if different exposure data are chosen. The most significant difference due to the exposure data is found in the areas with a population density of around 103 people/km2, mostly located in Central China, for both PM2.5 and O3. Our results demonstrate that the exposure data source significantly affects mortality estimations and should thus be carefully considered in health burden assessments.

Estimating daily high-resolution PM2.5 concentrations over Texas: Machine Learning approach

PM2.5 is an important atmospheric constituent associated to human health. Therefore, the capability of estimating PM2.5 concentrations at high spatiotemporal resolutions, particularly in places with no ground stations, would be invaluable. Although several studies have involved the estimation of PM2.5, few have estimated PM2.5 concentrations at high spatial resolutions. In this study, we leverage the aerosol optical depth (AOD) and random forest (RF) algorithm to estimate daily 1-km PM2.5 concentrations over Texas from 2014 to 2018. For this purpose, we use collection 6 Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD products from the Moderate Resolution Imaging Spectroradiometer (MODIS). To address the different sources and speciation of PM2.5 over Texas, we use several important control parameters. As a result, the accuracy of RF remains consistent throughout the study area. After estimating ground-level PM2.5 levels, we apply a ten-fold cross-validation approach to obtain a correlation coefficient (R) of 0.83–0.90 and a mean absolute bias (MAB) of 1.47–1.77 μg/m3. Our results show that RF is highly capable of estimating ground-level PM2.5 concentrations. In addition to the RF model, we also compare the capability of commonly used models, including multiple linear regression (MLR) and mixed effects model (MEM), for estimating the PM2.5 concentrations of global regions. Results indicate that RF, compared to the other models, has the highest accuracy, MEM the second-highest, and MLR the third. We also leverage the USEPA Environmental Benefits Mapping and Analysis Program Community Edition (BenMAP-CE) to estimate the impact of changes in PM2.5 levels on the number of respiratory-related premature mortalities in Texas in 2014–2018. Considering 2014 as the baseline year, the BenMAP analyses reveal that PM2.5 reductions could have prevented a large number of premature mortalities, particularly among adults aged 25–99, from 2014 to 2018 in Texas.

Comprehensive study of a long-lasting severe haze in Seoul megacity and its impacts on fine particulate matter and health

A long-lasting severe haze event was observed over the Seoul metropolitan region (SMR: Seoul, Incheon, and Gyeonggi-do), South Korea, in the winter of 2013 (January 12–16). We comprehensively investigated the atmospheric processes affecting particulate matter (PM) distributions during the haze event, as well as its impact on human health in the study area. These analyses were performed based on meteorological and PM observations and numerical modeling, which included the WRF-CMAQ modeling system and the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE). High PM10 concentrations during the haze event were mostly observed in the western and southern parts of the SMR. Significant differences (60–70 μg m−3) in the mean PM2.5 concentrations for haze and non-haze days were predicted mainly in the west-northwest areas of SMR. This might be primarily due to the pollutant transport (horizontal and vertical) from large emission sources (e.g., Chinese emissions) and, in part, their local accumulation (by local emissions) under high-pressure conditions and slow-moving air flows (i.e., blocking effect) around SMR. In addition, the enhanced PM2.5 concentrations in the study area during the haze event led to an increase in the number of premature deaths.

Measuring The Impact Of Air Pollution On Health Care Costs.

Air pollution contributes to the development of numerous adverse human health outcomes. The Environmental Protection Agency's Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) tool is widely used in estimating the health care costs of air pollution and in the development of federal and state regulations and policy. Its default features consider only the costs of hospital and emergency department admissions. A more complete accounting of the chain of costs would include ambulatory and other care. In this article we use employer health insurance claims data to infer additional costs that accompany hospitalizations but are not included in BenMAP-CE. Including additional categories increases BenMAP-CE health care cost estimates by approximately 40percent for respiratory and cardiovascular patients. That is, for each dollar of health care costs captured by BenMAP-CE, a more complete accounting would include an additional 40 cents. These results suggest that because such air pollution costs are underestimated, the health care benefits associated with reducing air pollution may be much larger than previously estimated.

Health benefits of achieving fine particulate matter standards in India – A nationwide assessment

BackgroundAmbient fine particulate matter (PM2.5) is one of the leading risk factors in India. The elevated levels of PM2.5 exposure concentration in India are related to higher premature mortality. However, health benefits or avoidable premature mortality by reducing PM2.5 concentration is uncertain. ObjectivesHere we simulated the health benefits by assuming the achievement of 1) National Ambient Air Quality Standards of India (PM2.5 annual average = 40 μg m−3), 2) National Clean Air Programme policy (30% reduction) and 3) World Health Organization standard (10 μg m−3). MethodologyUsing Environmental Benefits Mapping and Analysis Program – Community Edition (BenMAP-CE), the health benefits are estimated at national, state and district levels for various health endpoints viz., all-cause, ischaemic heart disease (IHD), chronic obstructive pulmonary disease (COPD), lung cancer and stroke. PM2.5 data, concentration-response coefficient, population, and baseline incidence rate are specified as input data in BenMAP–CE. ResultsAt the national level, all-cause health benefits in three simulations range from 0.79 to 2.1 million cases during 2019. Similarly, IHD, COPD, lung cancer, and stroke related health benefits are in the range of 0.28–0.68, 0.17–0.39, 0.01–0.03, and 0.14–0.34 million cases, respectively. State-level estimates showed that Uttar Pradesh, Bihar, and West Bengal are having maximum health benefits whereas north-eastern states are found with lowest estimates. Districts such as Allahabad, Lucknow, Muzaffarpur, Patna, and Sultanpur are estimated to have highest health benefits. States and districts with higher PM2.5 concentration and exposed population are found with maximum health benefits. Among the three simulations, achievement of the World Health Organization standard resulted in highest estimates. Further, the limitations and sensitivity of input parameters used in this study are discussed in detail. ConclusionStudy results highlighted the need for state and district-specific air quality management measures to increase PM2.5 related health benefits.

Impact of regional versus local resolution air quality modeling on particulate matter exposure health impact assessment

As much of the population lives in close proximity to high-traffic roads, there is the potential for health impact assessments based on regional air quality modeling to underpredict health impacts. We compare the estimated health impacts from fine particulate matter (PM2.5) using local (0.04 × 0.04 km upscaled to census block group resolution) compared to regional (12 × 12 km resolution) modeled concentrations for three locations in Connecticut: Hartford, New Haven, and Willimantic. We use concentration estimates from the Comprehensive Air Quality Model with Extensions (CAMx) regional model and a hybrid model combining CAMx with a near road model (HYCAMR) in the Environmental Benefits Mapping and Analysis Program—Community Edition (BenMAP-CE) to calculate the difference in estimated human health impacts using different resolution air quality estimates from PM2.5 exposure including mortality, emergency room visits, hospitalizations, and asthma exacerbation. This provides an estimate of the potential underprediction of health impacts resulting from not accounting for the sharp concentration gradients in near road environments in urban areas. The fine-scale estimates capture the elevated concentrations near the roadways leading to increased estimates of overall mortality and morbidity in the population. We find an increase in the estimated likelihood of emergency department visits and mortality in the urban core. We also compare the impact of model resolution on the health impact estimates for different demographic groups. Of the locations investigated, we see the largest differences between demographic groups in Willimantic, CT. Our results indicate that using regional air pollutant concentrations may lead to an underprediction of human health impacts from air pollution exposure.

The benefits of lower ozone due to air pollution emission reductions (2002–2011) in the Eastern United States during extreme heat

ABSTRACTUsing the Community Multiscale Air Quality (CMAQ) model and the Benefits Mapping and Analysis Program – Community Edition (BenMAP-CE) tool, we estimate the benefits of anthropogenic emission reductions between 2002 and 2011 in the Eastern United States (US) with respect to surface ozone concentrations and ozone-related health and economic impacts, during a month of extreme heat, July 2011. Based on CMAQ simulations using emissions appropriate for 2002 and 2011, we estimate that emission reductions since 2002 likely prevented 10– 15 ozone exceedance days (using the 2011 maximum 8-hr average ozone standard of 75 ppbv) throughout the Ohio River Valley and 5– 10 ozone exceedance days throughout the Washington, DC – Baltimore, MD metropolitan area during this extremely hot month. CMAQ results were fed into the BenMAP-CE tool to determine the health and health-related economic benefits of anthropogenic emission reductions between 2002 and 2011. We estimate that the concomitant health benefits from the ozone reductions were significant for this anomalous month: 160–800 mortalities (95% confidence interval (CI): 70–1,010) were avoided in July 2011 in the Eastern U.S, saving an estimated $1.3–$6.6 billion (CI: $174 million–$15.5 billion). Additionally, we estimate that emission reductions resulted in 950 (CI: 90–2,350) less hospital admissions from respiratory symptoms, 370 (CI: 180–580) less hospital admissions for pneumonia, 570 (CI: 0–1650) less Emergency Room (ER) visits from asthma symptoms, 922,020 (CI: 469,960–1,370,050) less minor restricted activity days (MRADs), and 430,240 (CI: −280,350–963,190) less symptoms of asthma exacerbation during July 2011.Implications: We estimate the benefits of air pollution emission reductions on surface ozone concentrations and ozone-related impacts on human health and the economy between 2002 and 2011 during an extremely hot month, July 2011, in the eastern United States (US) using the CMAQ and BenMAP-CE models. Results suggest that, during July 2011, emission reductions prevented 10-15 ozone exceedance days in the Ohio River Valley and 5-10 ozone exceedance days in the Mid Atlantic; saved 160-800 lives in the Eastern US, saving $1.3 - $6.5 billion; and resulted in 950 less hospital admissions for respiratory symptoms, 370 less hospital admissions for pneumonia, 570 less Emergency Room visits for asthma symptoms, 922,020 less minor restricted activity days, and 430,240 less symptoms of asthma exacerbation.

Estimation of health and economic benefits based on ozone exposure level with high spatial-temporal resolution by fusing satellite and station observations

In recent years, ozone pollution has become more and more serious in China. Several epidemiological studies have demonstrated the correlation between short-term ozone exposure and several health risks including all-cause mortality, cardiovascular mortality, and respiratory mortality. In this study, the daily ozone exposure levels with 10 km × 10 km resolution were estimated based on satellite data derived from Ozone Monitoring Instrument (OMI) and the monitoring data. The health impacts for potential decrease in the daily ozone concentration and the corresponding economic benefits in 2016 were estimated by applying the environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) model. By reducing the daily maximum 8-h average concentration of ozone to 100 μg/m3, the estimated avoided all-cause mortalities were 120 × 103 (95% confidence interval (CI): 67 × 103, 160 × 103) cases and the correspondingly economic benefits ranged from 36 to 64 billion CNY using amended human capital (AHC) and willingness to pay (WTP) method in 2016. If the daily maximum 8-h average concentration of ozone were rolled back to 70 μg/m3, the estimated avoided all-cause mortalities were 160 × 103 (95% CI: 98 × 103, 230 × 103) cases and economic benefits ranged from 54 to 95 billion CNY based on AHC and WTP methods.

Health benefit assessment of PM2.5 reduction in Pearl River Delta region of China using a model-monitor data fusion approach

The Pearl River Delta (PRD), one of the most polluted and populous regions of China, experienced a 28% reduction in fine particulate matter (PM2.5) concentration between 2013 (47 μg/m3) and 2015 (34 μg/m3) under a stringent national policy known as the Air Pollution Prevention and Control Action Plan (hereafter Action Plan). In this study, the health and economic benefits associated with PM2.5 reductions in PRD during 2013–2015 were estimated using the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) software. To create reliable gridded PM2.5 surfaces for BenMAP-CE calculations, a data fusion tool which incorporates the accuracy of monitoring data and the spatial coverage of predictions from the Community Multiscale Air Quality (CMAQ) model has been developed. The population-weighted average PM2.5 concentration over PRD was predicted to decline by 24%. PM2.5-related mortality was estimated to decrease by more than 3800 due to decreases in stroke (48%), ischemic heart disease (IHD) (35%), chronic obstructive pulmonary disease (COPD) (10%), and lung cancer (LC) (7%). A 13% reduction in PM2.5-related premature deaths from these four causes yielded a large economic benefit of about 1300 million US dollars. Our research suggests that the Action Plan played a major role in reducing emissions and additional measures should be implemented to further reduce PM2.5 pollution and protect public health in the future.

Spatial Patterns of Satellite-Retrieved PM2.5 and Long-Term Exposure Assessment of China from 1998 to 2016.

Previous studies have shown that particulate matter with an aerodynamic diameter of less than 2.5 micrometers (PM2.5) is tightly associated with adverse effects on human health, i.e., morbidity and mortality. Based on long-term satellite-derived PM2.5 datasets, this study analyzed the spatial patterns and temporal trends of PM2.5 concentrations in China from 1998 to 2016 using standard deviational ellipse and statistical analyses. A long-term assessment of exposure and health impacts due to PM2.5 was undertaken by the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) model. The results show that concentrations of PM2.5 increased nonlinearly in most areas of China from 1998 to 2016. Higher concentrations were found in eastern China and western Tarim Basin, and most areas exceeded the World Health Organization’s (WHO) annual PM2.5 standards. The median center of average PM2.5 concentration of the country shifted to the southeast and then returned during the examined time period. The proportion of the population exposed to equal PM2.5 concentrations increased at first, then trended downward. The proportion of the population exposed to PM2.5 over WHO Interim Target-1 (35 µg/m3) increased 20.6%, which was the largest growth compared with other WHO standard levels. The extent of health risk in China increased and expanded from 1998 to 2016, especially in the Beijing-Tianjin-Hebei region, the Yangtze River Delta, and the Pearl River Delta, which are China’s top three urban areas. The implementation of the Air Pollution Prevention and Control Action Plan has gradually paid off. If the government can achieve long-term adherence to its plan, great economic and health benefits will be gotten through the BenMAP-CE model analysis.

Estimating the Health and Economic Impacts of Changes in Local Air Quality.

To demonstrate the benefits-mapping software Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE), which integrates local air quality data with previously published concentration-response and health-economic valuation functions to estimate the health effects of changes in air pollution levels and their economic consequences. We illustrate a local health impact assessment of ozone changes in the 10-county nonattainment area of the Dallas-Fort Worth region of Texas, estimating the short-term effects on mortality predicted by 2 scenarios for 3 years (2008, 2011, and 2013): an incremental rollback of the daily 8-hour maximum ozone levels of all area monitors by 10 parts per billion and a rollback-to-a-standard ambient level of 65 parts per billion at only monitors above that level. Estimates of preventable premature deaths attributable to ozone air pollution obtained by the incremental rollback method varied little by year, whereas those obtained by the rollback-to-a-standard method varied by year and were sensitive to the choice of ordinality and the use of preloaded or imported data. BenMAP-CE allows local and regional public health analysts to generate timely, evidence-based estimates of the health impacts and economic consequences of potential policy options in their communities.

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

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.