Evaluation of health benefit using BenMAP-CE with an integrated scheme of model and monitor data during Guangzhou Asian Games

Analysis of human health effects under ozone exposure in the oasis area of Hetao Plain

This article, based on OMI data products, utilizes spatial distribution, ozone-sensitive control areas, Pearson correlation methods, and the Ben-MAP model to study the changes in ozone column concentration from 2018 to 2022, along with the influencing factors and the health of populations exposed to ozone. The findings suggest a spatial variation in the ozone column concentration within the study area, with an increasing trend observed from west to east and from south to north. Over time, the ozone column concentration exhibits an initial increase followed by a subsequent decrease, with the peak concentration observed in 2019 at 37.45 DU and the nadir recorded in 2022 at 33.10 DU. The monthly mean distribution exhibits an inverted V-shaped pattern during the warm season from April to September, with a peak in July (46.71 DU) and a trough in April (35.29 DU). The Hetao Plain Oasis area is primarily a NOx control area in sensitive control areas. The concentrations of O3 and precursor HCHO exhibited significant positive correlations with vegetation index and air temperature, while showing significant negative correlations with wind speed and air pressure. The precursor NO2, in contrast, exhibited a significant negative correlation with both the vegetation index and relative humidity. Based on the ground-based monitoring sites and analysis of human health benefits, the study area witnessed 1944.45 deaths attributed to warm season O3 exposure in 2018, with a subsequent reduction in premature deaths by 149.7, 588.2, and 231.75 for the years 2019 to 2021 respectively when compared to the baseline year. In 2021, the observed decrease in warm-season O3 concentration within that region compared to 2018 resulted in a significant reduction, leading to the prevention of 126 premature deaths.

Benefits of Short-term Premature Mortality Reduction Attributed to PM2.5 Pollution: A Case Study in Long an Province, Vietnam

PM2.5 pollution exposure is the leading cause of disease burden globally, especially in low- and middle-income countries, including Vietnam. Therefore, economic damage in this context must be quantified. Long An province in the Southern Key Economic (SKE) region was selected as a research area. This study aimed to evaluate PM2.5-related human health effects causing early deaths attributable to respiratory, cardiovascular, and circulatory diseases in all ages and genders. Health end-points and health impact estimation, economic loss model, groups of PM2.5 concentration data, data of exposed population, data of baseline premature mortality rate, and data of health impact functions were used. Hourly PM2.5 concentration data sets were generated specifically using the coupled Weather Research and Forecasting Model (WRF)/Community Multiscale Air Quality Modelling System (CMAQ) models. Daily PM2.5 pollution levels considered mainly in the dry season (from January to April 2018) resulted in 12.9 (95% CI - 0.6; 18.7) all-cause premature deaths per 100,000 population, of which 7.8 (95% CI 1.1; 7.1), 1.5 (95% CI - 0.2; 3.1), and 3.6 (95% CI - 1.5; 8.5) were due to respiratory diseases (RDs; 60.54%), cardiovascular diseases (CVDs; 11.81%), and circulatory system diseases (CSDs; 27.65%) per 100,000 population, respectively. The total economic losses due to acute PM2.5 exposure-related premature mortality cases reached 62.0 (95% CI - 2.7; 89.6) billion VND, equivalent to 8.3 (95% CI - 0.4; 12.0) million USD. The study outcomes contributed remarkably to the generation and development of data sources for effectively managing ambient air quality in Long An.

Evaluating reduced-form modeling tools for simulating ozone and PM2.5 monetized health impacts

Reduced-form modeling approaches are an increasingly popular way to rapidly estimate air quality and human health impacts related to changes in air pollutant emissions. These approaches reduce computation time by making simplifying assumptions about pollutant source characteristics, transport and chemistry. Two reduced form tools used by the Environmental Protection Agency in recent assessments are source apportionment-based benefit per ton (SA BPT) and source apportionment-based air quality surfaces (SABAQS). In this work, we apply these two reduced form tools to predict changes in ambient summer-season ozone, ambient annual PM2.5 component species and monetized health benefits for multiple sector-specific emission control scenarios: on-road mobile, electricity generating units (EGUs), cement kilns, petroleum refineries, and pulp and paper facilities. We then compare results against photochemical grid and standard health model-based estimates. We additionally compare monetized PM2.5 health benefits to values derived from three reduced form tools available in the literature: the Intervention Model for Air Pollution (InMAP), Air Pollution Emission Experiments and Policy Analysis (APEEP) version 2 (AP2) and Estimating Air pollution Social Impact Using Regression (EASIUR). Ozone and PM2.5 changes derived from SABAQS for EGU scenarios were well-correlated with values obtained from photochemical modeling simulations with spatial correlation coefficients between 0.64 and 0.89 for ozone and between 0.75 and 0.94 for PM2.5. SABAQS ambient ozone and PM2.5 bias when compared to photochemical modeling predictions varied by emissions scenario: SABAQS PM2.5 changes were overpredicted by up to 46% in one scenario and underpredicted by up to 19% in another scenario; SABAQS seasonal ozone changes were overpredicted by 34% to 83%. All tools predicted total PM2.5 benefits within a factor of 2 of the full-form predictions consistent with intercomparisons of reduced form tools available in the literature. As reduced form tools evolve, it is important to continue periodic comparison with comprehensive models to identify systematic biases in estimating air pollution impacts and resulting monetized health benefits.

Chronic and acute health effects of PM2.5 exposure and the basis of pollution control targets

Ho Chi Minh City (HCMC) is changing and expanding quickly, leading to environmental consequences that seriously threaten human health. PM2.5 pollution is one of the main causes of premature death. In this context, studies have evaluated strategies to control and reduce air pollution; such pollution-control measures need to be economically justified. The objective of this study was to assess the socio-economic damage caused by exposure to the current pollution scenario, taking 2019 as the base year. A methodology for calculating and evaluating the economic and environmental benefits of air pollution reduction was implemented. This study aimed to simultaneously evaluate the impacts of both short-term (acute) and long-term (chronic) PM2.5 pollution exposure on human health, providing a comprehensive overview of economic losses attributable to such pollution. Spatial partitioning (inner-city and suburban) on health risks of PM2.5 and detailed construction of health impact maps by age group and sex on a spatial resolution grid (3.0 km × 3.0 km) was performed. The calculation results show that the economic loss from premature deaths due to short-term exposure (approximately 38.86 trillion VND) is higher than that from long-term exposure (approximately 14.89 trillion VND). As the government of HCMC has been developing control and mitigation solutions for the Air Quality Action Plan towards short- and medium-term goals in 2030, focusing mainly on PM2.5, the results of this study will help policymakers develop a roadmap to reduce the impact of PM2.5 during 2025-2030.

The positive impact of the Omicron pandemic lockdown on air quality and human health in cities around Shanghai

The Omicron pandemic broke out in Shanghai in March 2022, and some infected people spread to some cities in the Yangtze River Delta (YRD) region. To achieve the dynamic zero-COVID target as soon as possible, Shanghai and nine cities that were heavily affected by Shanghai implemented the lockdown measures. This paper aims to quantify the impact of the lockdown on air quality and human health. A difference-in-difference (DID) model was first used to measure the impact of the lockdown on air quality in these ten cities. Based on the results of the DID model, we estimated the PM2.5-related health and economic benefits using the concentration-response function and the value of statistical life method. Results showed that the lockdown has reduced the concentrations of PM2.5, PM10, SO2, NO2, and CO by 9.87 μg/m3, 17.31 μg/m3, 0.75 μg/m3, 9.03 μg/m3, and 0.07 mg/m3, respectively. The number of avoided premature deaths due to PM2.5 reduction was estimated to be 35,342. The resulting economic benefits totaled 18.86 billion US dollars. We investigated the reasons for the air quality improvement in these ten cities and found the "3 + 11" policy has had a great impact on air quality. Compared with the first COVID-19 lockdown in early 2020, the effect of the lockdown in 2022 was smaller. These findings demonstrated that reductions in anthropogenic emissions would achieve substantial air quality improvement and health benefits. This paper re-emphasized continuous efforts to improve air quality are essential to protect public health.

Environmental Regulation and Chronic Conditions: Evidence from China's Air Pollution Prevention and Control Action Plan

In January 2013, a dense haze covered 1.4 million kilometers of China and affected more than 800 million people. Air pollution in China had become a serious threat to the daily lives of people. The State Council of China enacted the "Air Pollution Prevention and Control Action Plan" (APPCAP) in 2013 to lower the particulate matter (PM) level. Between 2013 and 2017, each administrative division established its own environmental preservation strategy in accordance with the APPCAP. We examined the effects of the nationwide air pollution control policy, APPCAP, on chronic health conditions among adults using a nationally representative survey, CFPS, conducted in 2012, 2014, and 2016. We applied a difference-in-differences model, using the time gap when each administrative division implemented the APPCAP. We found that the APPCAP significantly reduced doctor-diagnosed chronic conditions of the respiratory and circulatory systems in the last six months. In respiratory diseases and circulatory system diseases, the treatment effect of the APPCAP was a 34.6% and 11.5% reduction in the sample mean, respectively. The poorest socioeconomic groups and the elderly benefited the most. The stronger the goal, the more positive the effects were on health; the longer the policy intervention, the better the health outcomes were.

Health impact assessment and evaluation of economic costs attributed to PM2.5 air pollution using BenMAP-CE

Air pollution is considered the most prominent public health. Economically, air pollution imposes additional costs on governments. This study aimed to quantify health effects and associated economic values of reducing PM_2.5 air pollution using BenMAP-CE in Qom in 2019. The air quality data were acquired from Qom Province Environmental Protection Agency, and the population data were collected from Qom Province Management and Planning Organization website. The number of deaths due to Stroke, Chronic Obstructive Pulmonary Disease, Lung Cancer, and Ischemic Heart Disease attributable to PM_2.5 were estimated using BenMAP-CE based on two control scenarios, 2.4 and 10 μg/m³, known as scenarios I and II, respectively. The associated economic effect of premature deaths was assessed by value of a statistical life (VSL) approach. The annual average of PM_2.5 concentration was found to be 16.32 μg/m³ (SD: 9.93). A total of 4694.5 and 2475.94 premature deaths in scenarios I and II were found to be attributable to PM_2.5 in overall, respectively. The total associated cost was calculated to be 855.91 and 451.40 million USD in scenarios I and II, respectively. The total years of life lost due to PM_2.5 exposure in 2019 was 158,657.06 and 78,351.51 in scenarios I and II, respectively. The results of both health and economic assessment indicate the importance of solving the air pollution problem in Qom, as well as other big cities in Iran. The elimination of limitations, such as insufficient local data, should be regarded in future studies.

Vehicular Traffic in Urban Areas: Health Burden and Influence of Sustainable Urban Planning and Mobility

Vehicular traffic is one of the major sources of air pollution in European cities. This work aims to understand which characteristics of the urban environment could influence mobility-related air pollution, quantify the health impacts of exposure to traffic-derived PM2.5 and NO2 concentrations, and assess the potential health benefits expected from traffic interventions. The health benefits modeled are intended to provide a set of comparable data to support decision-makers and encourage informed decision-making to design healthier cities. Targeting a large geographical coverage, 12 European cities from 9 countries were comparatively assessed in terms of mean daily traffic volume/area, the number of public transport stops/area, and the percentage of green and outdoor leisure areas, among other urban indicators. This was implemented using an open-source data mining tool, which was seen as a useful engine to identify potential strategies to improve air quality. The comparison of urban indicators in the selected cities evidenced two trends: (a) cities with the most heterogeneous distribution of public transport stops, as an indicator of poor accessibility, are also those with the lowest proportion of km dedicated to cycleways and footways, highlighting the need in these cities for more sustainable mobility management; and (b) the percentage of green and outdoor leisure areas may influence the share of journeys by bicycle, pointing out that promoting the perception of green routes is relevant to enhance the potential of active transport modes. Socioeconomic factors can be key determinants of the urban indicators and would need further consideration. For the health impact assessment (HIA), two baseline scenarios were evaluated and compared. One is based on mean annual traffic contributions to PM2.5 concentrations in each target city (ranging between 1.9 and 13 µg/m3), obtained from the literature, and the second is grounded on mean annual NO2 concentrations at all available traffic and urban background stations within each city (17.2–83.5 µg/m3), obtained from the European Environment Agency database. The intervention scenarios modeled were designed based on traffic mitigation strategies in the literature, and set to ranges of 6–50% in traffic-derived PM2.5 concentrations and of 4–12.5% in NO2 concentrations. These scenarios could result in only a 1.7% (0.6–4%) reduction in premature mortality due to exposure to traffic-derived PM2.5, and 1.0% (0.4–2%) due to exposure to NO2, as the mean for all the cities. This suggests that more ambitious pollution abatement strategies should be targeted.

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 (PM_2.5) 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 PM_2.5 and O₃ in China between 2014 and 2018, and then quantified the changes in premature mortality due to PM_2.5 and O₃ using the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) model. The results show that PM_2.5-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 PM_2.5-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 PM_2.5 and O₃. Our results demonstrate that the exposure data source significantly affects mortality estimations and should thus be carefully considered in health burden assessments.

Quantifying spatial heterogeneity of vulnerability to short-term PM2.5 exposure with data fusion framework

The current estimations of the burden of disease (BD) of PM_2.5 exposure is still potentially biased by two factors: ignorance of heterogeneous vulnerabilities at diverse urbanization levels and reliance on the risk estimates from existing literature, usually from different locations. Our objectives are (1) to build up a data fusion framework to estimate the burden of PM_2.5 exposure while evaluating local risks simultaneously and (2) to quantify their spatial heterogeneity, relationship to land-use characteristics, and derived uncertainties when calculating the disease burdens. The feature of this study is applying six local databases to extract PM_2.5 exposure risk and the BD information, including the risks of death, cardiovascular disease (CVD), and respiratory disease (RD), and their spatial heterogeneities through our data fusion framework. We applied the developed framework to Tainan City in Taiwan as a use case estimated the risks by using 2006-2016 emergency department visit data, air quality monitoring data, and land-use characteristics and further estimated the BD caused by daily PM_2.5 exposure in 2013. Our results found that the risks of CVD and RD in highly urbanized areas and death in rural areas could reach 1.20-1.57 times higher than average. Furthermore, we performed a sensitivity analysis to assess the uncertainty of BD estimations from utilizing different data sources, and the results showed that the uncertainty of the BD estimations could be contributed by different PM_2.5 exposure data (20-32%) and risk values (0-86%), especially for highly urbanized areas. In conclusion, our approach for estimating BD based on local databases has the potential to be generalized to the developing and overpopulated countries and to support local air quality and health management plans.

Reduction of air pollutants and associated mortality during and after the COVID-19 lockdown in China: Impacts and implications

Although strict lockdown measurements implemented during the COVID-19 pandemic have dramatically reduced the anthropogenic-based emissions, changes in air quality and its health impacts remain unclear in China. We comprehensively described air pollution during and after the lockdown periods in 2020 compared with 2018-2019, and estimated the mortality burden indicated by the number of deaths and years of life lost (YLL) related to the air pollution changes. The mean air quality index (AQI), PM10, PM2.5, NO2, SO2 and CO concentrations during the lockdown across China declined by 18.2 (21.2%), 27.0 μg/m3 (28.9%), 10.5 μg/m3 (18.3%), 8.4 μg/m3 (44.2%), 13.1 μg/m3 (38.8%), and 0.3 mg/m3 (27.3%) respectively, when compared to the same periods during 2018-2019. We observed an increase in O3 concentration during the lockdown by 5.5 μg/m3 (10.4%), and a slight decrease after the lockdown by 3.4 μg/m3 (4.4%). As a result, there were 51.3 (95%CI: 32.2, 70.1) thousand fewer premature deaths (16.2 thousand during and 35.1 thousand after the lockdown), and 1066.8 (95%CI: 668.7, 1456.8) thousand fewer YLLs (343.3 thousand during and 723.5 thousand after the lockdown) than these in 2018-2019. Our findings suggest that the COVID-19 lockdown has caused substantial decreases in air pollutants except for O3, and that substantial human health benefits can be achieved when strict control measures for air pollution are taken to reduce emissions from vehicles and industries. Stricter tailored policy solutions of air pollution are urgently needed in China and other countries, especially in well-developed industrial regions, such as upgrading industry structure and promoting green transportation.

Health Benefits of Emission Reduction under 1.5 °C Pathways Far Outweigh Climate-Related Variations in China

The 1.5 °C pathways initially promoted by the challenges presented by climate change could bring substantial air quality-related benefits. However, since there is a lack of comprehensive assessment on emissions of air pollutants, meteorology, air quality, and heatwave occurrences under different climate goals, how significant the clean air cobenefits compared with the direct climate-related impact is uncertain. In this study, we assess the cobenefits of 1.5 °C pathways for air quality in China by linking multiple shared socioeconomic pathways, ensembling simulations of regional climate-air quality dynamic downscaling and an air pollution and climate-related health assessment model, and compare different kinds of benefits: the health benefits from direct slowing climate (reduced heatwaves) versus the health cobenefits from air quality improvement (the improved air quality from reduced air pollutants versus meteorological changes). The benefit of reduced air pollution emissions associated with sustainable development under 1.5 °C pathways dominated the overall impact, which could avoid 1 589 000 PM2.5-related and 526 000 O3-related deaths in 2050. Correspondingly, the impact of changed meteorology on air quality would avoid additional 8000 PM2.5-related deaths in 2050 under 1.5 °C pathways yet would lead to 22 000 O3-related deaths. Also, the heatwave-related deaths could be avoided by 7000. The substantial anthropogenic emission reduction cobenefits of 1.5 °C pathways in improving air quality significantly exceed the direct climate (heatwave-related) benefits and completely offset the impact of meteorological changes' impact on air pollution under climate change.

Health benefits and cost of using air purifiers to reduce exposure to ambient fine particulate pollution in China

Understanding the cost-effectiveness of possible interventions to reduce air pollution levels is crucial to developing sustainable mitigation and adaption strategies. Although people spend more than 80% of their time indoors, the role of air purifiers in mitigating personal exposure to indoor PM_2.5 of outdoor origin has not yet been quantified, especially in under-developed regions. Here, we performed a comprehensive simulation at the 10 km × 10 km geographical resolution in mainland China to quantify the health benefits and costs of indoor air purification in four intervention scenarios, S1 to S4, where target indoor PM_2.5 concentrations were 35, 25, 15, and 10 μg/m³. In intervention scenarios S1 to S4, 93,200 (95% uncertainty interval 78,900-113,600), 115,300 (97,700-140,800), 163,400 (138,300-198,800), and 207,900 (176,300-251,800) deaths that cost 82, 175, 438, and 798 billion Chinese Yuan can be avoided and 93%, 80%, 53%, and 26% of the cities have a positive net monetary benefit. We found that achieving indoor PM_2.5 concentration of 35 or 25 μg/m³ using air purifiers is cost-effective at reducing PM_2.5 related deaths and PM_2.5 concentration of 25 μg/m³ is a suitable indoor PM_2.5 target for China. Multifaceted efforts are necessary to ensure equitable access to air purifiers and the knowledge to effectively operate them to make sure the benefits reach the whole population.

Coordinated control of PM2.5 and O3 is urgently needed in China after implementation of the "Air pollution prevention and control action plan"

To improve air quality, China formulated the Air Pollution Prevention and Control Action Plan (APPCAP) in 2013. In the present study, the changes in the concentration of air pollutants after the implementation of APPCAP were investigated based on nationwide monitoring data. From the results, it is evident that the annual mean concentrations of PM_2.5, PM₁₀, SO₂, and CO show a significant downward trend over 2015-2018, with decreasing rates of 3.4, 4.1, 3.8, and 70 μg m^-3/year, respectively. However, no significant change was found in NO₂ while maximum daily 8 h average O₃ concentration (MDA8 O₃) was increased by 3.4 μg m^-3/year during the four years. Spatially, the highest decrease in PM_2.5 was found in Beijing-Tianjin-Hebei (BTH), followed by central China and northeast China, while the Pearl River Delta (PRD), Yungui Plateau, and northwest China showed less decreases. MDA8 O₃ had a higher increase in BTH, central China, Yangtze River Delta (YRD), and PRD. With the decrease in PM_2.5 in recent years, cumulative population exposure to PM_2.5 gradually decreased, whereas there was still more than 65% of the population exposing to annual PM_2.5 higher than the standard of 35 μg m^-3 in 2018. In contrast, the health effects of O₃ gradually increased with 13.1%, 14.3%, 20.4%, and 21.7% of the population exposed to unhealthy O₃ levels in summer from 2015 to 2018. O₃ pollution is causing severe health risks with estimated nationwide mortality of 70,024 (95% CI: 55,510-84,501), 79,159 (95% CI: 62,750-95,525), 105,150 (95% CI: 83,378-126,852), and 104,404 (95% CI: 82,784-125,956) in the four years, respectively. This clearly shows that the target of air pollution control in China shifts and coordinated control of PM_2.5 and O₃ is urgently needed after the successful implementation of APPCAP.

Data assimilation of ambient concentrations of multiple air pollutants using an emission-concentration response modeling framework

Data assimilation for multiple air pollutant concentrations has become an important need for modeling air quality attainment, human exposure and related health impacts, especially in China that experiences both PM_2.5 and O₃ pollution. Traditional data assimilation or fusion methods are mainly focused on individual pollutants, and thus cannot support simultaneous assimilation for both PM_2.5 and O₃. To fill the gap, this study proposed a novel multipollutant assimilation method by using an emission-concentration response model (noted as RSM-assimilation). The new method was successfully applied to assimilate precursors for PM_2.5 and O₃ in the 28 cities of the North China Plain (NCP). By adjusting emissions of five pollutants (i.e., NO_x, SO₂, NH₃, VOC and primary PM_2.5) in the 28 cities through RSM-assimilation, the RMSEs (root mean square errors) of O₃ and PM_2.5 were reduced by about 35% and 58% from the original simulations. The RSM-assimilation results small sensitivity to the number of observation sites due to the use of prior knowledge of the spatial distribution of emissions; however, the ability to assimilate concentrations at the edge of the control region is limited. The emission ratios of five pollutants were simultaneously adjusted during the RSM-assimilation, indicating that the emission inventory may underestimate NO₂ in January, April and October, and SO₂ in April, but overestimate NH₃ in April and VOC in January and October. Primary PM_2.5 emissions are also significantly underestimated, particularly in April (dust season in NCP). Future work should focus on expanding the control area and including NH₃ observations to improve the RSM-assimilation performance and emission inventories.

Model for assessing health damage from air pollution in quarrying area - Case study at Tan Uyen quarry, Ho Chi Minh megapolis, Vietnam

Vietnam has a great demand for stone exploitation for the development of the country's infrastructure, reaching 181 million m³ in 2020. Mining activities are always accompanied by environmental pollution, negatively affecting public health. To accurately assess the level of pollution, as well as quantify the effect of air pollution on human health, a number of structures, methods, and models provide tools to assess the benefits of this control for public health and related economic values. However, there has been no research in Vietnam applied specifically to this type of stone exploitation. This study offers a model to evaluate the economic damage caused by dust exposure from activities related to quarrying, overcoming the lack of continuous monitoring data. The area selected for research is Binh Duong province, in the Ho Chi Minh megapolis, Vietnam, which has two construction quarries, Thuong Tan and Tan My, with a current annual production of approximately 4–5 million m³. The calculation results show that the damage to human health is estimated at approximately 9,643 billion dong a year, equivalent to 15.03 million USD. In addition, if the standard criteria are tightened, damage will continue to increase. This study also analyses some of the difficulties and limitations in the modelling process.

Quantifying the impact of particle matter on mortality and hospitalizations in four Brazilian metropolitan areas

Air quality management involves investigating areas where pollutant concentrations are above guideline or standard values to minimize its effect on human health. Particulate matter (PM) is one of the most studied pollutants, and its relationship with health has been widely outlined. To guide the construction and improvement of air quality policies, the impact of PM on the four Brazilian southeast metropolitan areas was investigated. One-year long modeling of PM₁₀ and PM_2.5 was performed with the WRF-Chem model for 2015 to quantify daily and annual PM concentrations in 102 cities. Avoidable mortality due to diverse causes and morbidity due to respiratory and circular system diseases were estimated concerning WHO guidelines, which was adopted in Brazil as a final standard to be reached in the future; although there is no deadline set for its implementation yet. Results showed satisfactory representation of meteorology and ambient PM concentrations. An overestimation in PM concentrations for some monitoring stations was observed, mainly in São Paulo metropolitan area. Cities around capitals with high modelled annual PM_2.5 concentrations do not monitor this pollutant. The total avoidable deaths estimated for the region, related to PM_2.5, were 32,000 ± 5,300 due to all-cause mortality, between 16,000 ± 2,100 and 51,000 ± 3,000 due non-accidental causes, between 7,300 ± 1,300 and 16,700 ± 1,500 due to cardiovascular disease, between 4,750 ± 900 and 10,950 ± 870 due ischemic heart diseases and 1,220 ± 330 avoidable deaths due to lung cancer. Avoidable respiratory hospitalizations were greater for PM_2.5 among 'children' age group than for PM₁₀ (all age group) except in São Paulo metropolitan area. For circulatory system diseases, 9,840 ± 3,950 avoidable hospitalizations in the elderly related to a decrease in PM_2.5 concentrations were estimated. This study endorses that more restrictive air quality standards, human exposure, and health effects are essential factors to consider in urban air quality management.

Large-scale optimization of multi-pollutant control strategies in the Pearl River Delta region of China using a genetic algorithm in machine learning

A scientifically sound integrated assessment modeling (IAM) system capable of providing optimized cost-benefit analysis is essential in effective air quality management and control strategy development. Yet scenario optimization for large-scale applications is limited by the computational expense of optimization over many control factors. In this study, a multi-pollutant cost-benefit optimization system based on a genetic algorithm (GA) in machine learning has been developed to provide cost-effective air quality control strategies for large-scale applications (e.g., solution spaces of ~1035). The method was demonstrated by providing optimal cost-benefit control pathways to attain air quality goals for fine particulate matter (PM2.5) and ozone (O3) over the Pearl River Delta (PRD) region of China. The GA was found to be >99% more efficient than the commonly used grid searching method while providing the same combination of optimized multi-pollutant control strategies. The GA method can therefore address air quality management problems that are intractable using the grid searching method. The annual attainment goals for PM2.5 (< 35 μg m-3) and O3 (< 80 ppb) can be achieved simultaneously over the PRD region and surrounding areas by reducing NOx (22%), volatile organic compounds (VOCs, 12%), and primary PM (30%) emissions. However, to attain stricter PM2.5 goals, SO2 reductions (> 9%) are needed as well. The estimated benefit-to-cost ratio of the optimal control strategy reached 17.7 in our application, demonstrating the value of multi-pollutant control for cost-effective air quality management in the PRD region.

PM2.5-Related Health Economic Benefits Evaluation Based on Air Improvement Action Plan in Wuhan City, Middle China

On the basis of PM_2.5 data of the national air quality monitoring sites, local population data, and baseline all-cause mortality rate, PM_2.5-related health economic benefits of the Air Improvement Action Plan implemented in Wuhan in 2013–2017 were investigated using health-impact and valuation functions. Annual avoided premature deaths driven by the average concentration of PM_2.5 decrease were evaluated, and the economic benefits were computed by using the value of statistical life (VSL) method. Results showed that the number of avoided premature deaths in Wuhan are 21,384 (95% confidence interval (CI): 15,004 to 27,255) during 2013–2017, due to the implementation of the Air Improvement Action Plan. According to the VSL method, the obtained economic benefits of Huangpi, Wuchang, Hongshan, Xinzhou, Jiang’an, Hanyang, Jiangxia, Qiaokou, Jianghan, Qingshan, Caidian, Dongxihu, and Hannan District were 8.55, 8.19, 8.04, 7.39, 5.78, 4.84, 4.37, 4.04, 3.90, 3.30, 2.87, 2.42, and 0.66 billion RMB (1 RMB = 0.1417 USD On 14 October 2019), respectively. These economic benefits added up to 64.35 billion RMB (95% CI: 45.15 to 82.02 billion RMB), accounting for 4.80% (95% CI: 3.37% to 6.12%) of the total GDP of Wuhan in 2017. Therefore, in the process of formulating a regional air quality improvement scheme, apart from establishing hierarchical emission-reduction standards and policies, policy makers should give integrated consideration to the relationship between regional economic development, environmental protection and residents’ health benefits. Furthermore, for improving air quality, air quality compensation mechanisms can be established on the basis of the status quo and trends of air quality, population distribution, and economic development factors.

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

OBJECTIVES

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Evaluation of hexavalent chromium concentration in water and its health risk with a system dynamics model

This study is the first to use reliable data sources to establish a reasonable mass balance of Cr(VI) contamination in river water, sediment, and farmland soil. A system dynamics model was used to establish the interrelationships among water, Cr(VI) contamination, and health effects in the Wu River watershed (between Taichung city and Changhua county) between 2018 and 2048 (30 years). The results show very little Cr(VI) contamination in rivers; most flowed downstream or settled in sediment, and the accumulation of Cr(VI) in the sediment increased throughout the study period. The highest Cr(VI) concentrations in farmland soil (338.46 mg/kg) were reached in Changhua county as a result of greater Cr(VI) contamination from upstream and local factories. This Cr(VI) contamination led to gastric cancer risks of 5.24 × 10^-4 and 4.38 × 10^-6 in Changhua county and Taichung city, respectively. Although most of the Cr(VI) contamination was discharged from Taichung City, greater health risks and losses occurred downstream in Changhua county; medical costs were 55 times higher. For total quality control, a reduction rate of at least 68% should be reached in the study area. These findings will be helpful in predicting the transmission of Cr(VI) contamination over long study periods with a systematic model.

Estimated Contributions of Emissions Controls, Meteorological Factors, Population Growth, and Changes in Baseline Mortality to Reductions in Ambient [Formula: see text] and [Formula: see text]-Related Mortality in China, 2013-2017

BACKGROUND

In 2013, China released the Air Pollution Prevention and Control Action Plan (Action Plan), which set the roadmap for national air pollution control actions for the period of 2013 to 2017. A decrease in the fine particulate matter with aerodynamic diameter [Formula: see text] ([Formula: see text]) concentration may lead to a substantial benefit for human health.

OBJECTIVE

We aimed to quantify the relative contributions four factors: emission reductions, changed meteorology, population growth, and a change in baseline mortality rates to the reduced [Formula: see text]-related mortality ([Formula: see text]-mortality) during the 2013-2017 period and evaluate the importance of emission controls for human health protection in China.

METHODS

The integrated exposure-response function was adopted to estimate the chronic health effects of [Formula: see text]. The annual [Formula: see text] concentrations were estimated from chemical transport model simulations combined with surface observations for 2013 and 2017. Relative contributions to [Formula: see text]-mortality from emission reductions and the three factors were individually quantified through scenario analysis.

RESULTS

The estimated total [Formula: see text]-mortality in China was 1.389 million [95% confidence interval (CI): 1.005 million, 1.631 million] in 2013 but was substantially reduced to 1.102 million (95% CI: 0.755 million, 1.337 million) in 2017. Emission controls contributed 88.7% to this reduction in [Formula: see text]-mortality, while changed meteorology, the change in baseline mortality rates, and population growth during 2013-2017 contributed 9.6, 3.8, and [Formula: see text], respectively.

CONCLUSIONS

The implementation of the Action Plan has significantly reduced the [Formula: see text] concentration in regions of China where population density is high, dominating the decline in [Formula: see text]-mortality during 2013-2017. However, the health burden of [Formula: see text] pollution in China is still extremely high compared with that in other developed countries. An aggressive air pollution control strategy should be implemented in densely populated areas to further reduce the health burden. https://doi.org/10.1289/EHP4157.

Interventions to reduce ambient particulate matter air pollution and their effect on health

BACKGROUND

Ambient air pollution is associated with a large burden of disease in both high-income countries (HICs) and low- and middle-income countries (LMICs). To date, no systematic review has assessed the effectiveness of interventions aiming to reduce ambient air pollution.

OBJECTIVES

To assess the effectiveness of interventions to reduce ambient particulate matter air pollution in reducing pollutant concentrations and improving associated health outcomes.

SEARCH METHODS

We searched a range of electronic databases with diverse focuses, including health and biomedical research (CENTRAL, Cochrane Public Health Group Specialised Register, MEDLINE, Embase, PsycINFO), multidisciplinary research (Scopus, Science Citation Index), social sciences (Social Science Citation Index), urban planning and environment (Greenfile), and LMICs (Global Health Library regional indexes, WHOLIS). Additionally, we searched grey literature databases, multiple online trial registries, references of included studies and the contents of relevant journals in an attempt to identify unpublished and ongoing studies, and studies not identified by our search strategy. The final search date for all databases was 31 August 2016.

SELECTION CRITERIA

Eligible for inclusion were randomized and cluster randomized controlled trials, as well as several non-randomized study designs, including controlled interrupted time-series studies (cITS-EPOC), interrupted time-series studies adhering to EPOC standards (ITS-EPOC), interrupted time-series studies not adhering to EPOC standards (ITS), controlled before-after studies adhering to EPOC standards (CBA-EPOC), and controlled before-after studies not adhering to EPOC standards (CBA); these were classified as main studies. Additionally, we included uncontrolled before-after studies (UBA) as supporting studies. We included studies that evaluated interventions to reduce ambient air pollution from industrial, residential, vehicular and multiple sources, with respect to their effect on mortality, morbidity and several air pollutant concentrations. We did not restrict studies based on the population, setting or comparison.

DATA COLLECTION AND ANALYSIS

After a calibration exercise among the author team, two authors independently assessed studies for inclusion, extracted data and assessed risk of bias. We conducted data extraction, risk of bias assessment and evidence synthesis only for main studies; we mapped supporting studies with regard to the types of intervention and setting. To assess risk of bias, we used the Graphic Appraisal Tool for Epidemiological studies (GATE) for correlation studies, as modified and employed by the Centre for Public Health Excellence at the UK National Institute for Health and Care Excellence (NICE). For each intervention category, i.e. those targeting industrial, residential, vehicular and multiple sources, we synthesized evidence narratively, as well as graphically using harvest plots.

MAIN RESULTS

We included 42 main studies assessing 38 unique interventions. These were heterogeneous with respect to setting; interventions were implemented in countries across the world, but most (79%) were implemented in HICs, with the remaining scattered across LMICs. Most interventions (76%) were implemented in urban or community settings.We identified a heterogeneous mix of interventions, including those aiming to address industrial (n = 5), residential (n = 7), vehicular (n = 22), and multiple sources (n = 4). Some specific interventions, such as low emission zones and stove exchanges, were assessed by several studies, whereas others, such as a wood burning ban, were only assessed by a single study.Most studies assessing health and air quality outcomes used routine monitoring data. Studies assessing health outcomes mostly investigated effects in the general population, while few studies assessed specific subgroups such as infants, children and the elderly. No identified studies assessed unintended or adverse effects.The judgements regarding the risk of bias of studies were mixed. Regarding health outcomes, we appraised eight studies (47%) as having no substantial risk of bias concerns, five studies (29%) as having some risk of bias concerns, and four studies (24%) as having serious risk of bias concerns. Regarding air quality outcomes, we judged 11 studies (31%) as having no substantial risk of bias concerns, 16 studies (46%) as having some risk of bias concerns, and eight studies (23%) as having serious risk of bias concerns.The evidence base, comprising non-randomized studies only, was of low or very low certainty for all intervention categories and primary outcomes. The narrative and graphical synthesis showed that evidence for effectiveness was mixed across the four intervention categories. For interventions targeting industrial, residential and multiple sources, a similar pattern emerged for both health and air quality outcomes, with essentially all studies observing either no clear association in either direction or a significant association favouring the intervention. The evidence base for interventions targeting vehicular sources was more heterogeneous, as a small number of studies did observe a significant association favouring the control. Overall, however, the evidence suggests that the assessed interventions do not worsen air quality or health.

AUTHORS' CONCLUSIONS

Given the heterogeneity across interventions, outcomes, and methods, it was difficult to derive overall conclusions regarding the effectiveness of interventions in terms of improved air quality or health. Most included studies observed either no significant association in either direction or an association favouring the intervention, with little evidence that the assessed interventions might be harmful. The evidence base highlights the challenges related to establishing a causal relationship between specific air pollution interventions and outcomes. In light of these challenges, the results on effectiveness should be interpreted with caution; it is important to emphasize that lack of evidence of an association is not equivalent to evidence of no association.We identified limited evidence for several world regions, notably Africa, the Middle East, Eastern Europe, Central Asia and Southeast Asia; decision-makers should prioritize the development and implementation of interventions in these settings. In the future, as new policies are introduced, decision-makers should consider a built-in evaluation component, which could facilitate more systematic and comprehensive evaluations. These could assess effectiveness, but also aspects of feasibility, fidelity and acceptability.The production of higher quality and more uniform evidence would be helpful in informing decisions. Researchers should strive to sufficiently account for confounding, assess the impact of methodological decisions through the conduct and communication of sensitivity analyses, and improve the reporting of methods, and other aspects of the study, most importantly the description of the intervention and the context in which it is implemented.

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 (PM_2.5) 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 PM_2.5 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 PM_2.5 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 PM_2.5 concentration over PRD was predicted to decline by 24%. PM_2.5-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 PM_2.5-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 PM_2.5 pollution and protect public health in the future.

Temporal variations in ambient particulate matter reduction associated short-term mortality risks in Guangzhou, China: A time-series analysis (2006-2016)

Numerous studies have reported associations between ambient particulate matter (PM) and daily mortality; however, little is known about temporal variations in ambient air pollution associated mortality risks, particularly in developing countries with limited long time-series air monitoring data. In present study, we assessed the associations and temporal relationships between ambient PM and daily mortality in Guangzhou, China, during 2006-2016. With this unique 11-year dataset, we related daily concentrations of PM with aerodynamic diameter < 2.5 μm (PM_2.5), between 2.5 and 10 μm (PM_10-2.5) and <10 μm (PM₁₀) to daily mortality in Guangzhou. We applied overdispersed Poisson regression with adjustment for time trend and potential confounding factors. Multiple level sensitivity analyses were conducted to examine the robustness of main results. Between 2006 and 2016, annual concentrations of PM_2.5 decreased by 50.8% to 27.0 μg/m³, of PM_10-2.5 by 27.6% to 16.2 μg/m³, and of PM₁₀ by 44.1% to 43.3 μg/m³ in Guangzhou. In this study, per 10 μg/m³ increases in mean concentrations at current day and 6 prior days of death (lag06), we observed increases in total mortality risks of 0.55% (95% Confidence Interval (CI): 0.24%, 0.86%) for PM_2.5, 0.99% (95%CI: 0.48%, 1.50%) for PM_10-2.5, and 0.44% (95%CI: 0.22%, 0.65%) for PM₁₀. Stronger associations were observed for ambient PM on cardio-respiratory mortality and people at age ≥ 65 years. Despite drastic reductions in annual PM levels, PM_2.5 associated cardiovascular and respiratory mortality risks remained significant at 1.26% (95%CI: 0.19%, 2.35%) and 1.91% (95%CI: 0.25%, 3.60%) during 2014-2016. Further, PM_2.5 and PM₁₀ associated respiratory mortality risks showed increasing trend over time (p-value = 0.03 for PM_2.5). In summary, though ambient PM levels decreased substantially in Guangzhou in recent years, PM_2.5 and PM₁₀ associated cardio-respiratory mortality risks remained significant and respiratory mortality risks even increased. Our findings provide strong rationale for continuation of ambient air pollution control effort for public health protection in the future.

Air quality improvement and health benefit of PM2.5 reduction from the coal cap policy in the Beijing-Tianjin-Hebei (BTH) region, China

Large amounts of air pollutants emitted from massive coal combustion result in the air quality deterioration and threaten public health in China. To improve air quality, the Chinese government released the coal cap policy to reduce coal consumption. So it is important and necessary to understand the possible environmental impact and relevant health benefits from the coal cap policy. The purpose of this paper is to quantify the air quality improvement and to evaluate the health benefits from the implementation of the coal cap policy, with the Beijing-Tianjin-Hebei (BTH) region as the study area. The results showed that the emissions of SO₂, NOx, CO, VOCs, PM₁₀, and PM_2.5 could be reduced by 20-40% in the BTH region in 2020 and all pollutants from industrial boilers notably decreased. Under the coal cap policy, the PM_2.5 concentration in the whole region would fall by 11.27%, and the total economic benefit from health impacts could achieve 26.61 (13.29 to 39.14) billion RMB (3.9 billion USD) in the BTH region in 2020, accounting for 0.43% (0.21 to 0.63%) of regional GDP in 2013. This study demonstrated the quantification of environmental effect and health benefit from the coal cap policy, which could be used for the complete cost-benefit analysis and provide the sufficient support for policy makers to implement the coal cap policy in the BTH region and other areas of China.

A review on health cost accounting of air pollution in China

Over the last three decades, rapid industrialization in China has generated an unprecedentedly high level of air pollution and associated health problems. Given that China accounts for one-fifth of the world population and suffers from severe air pollution, a comprehensive review of the indicators accounting for the health costs in relation to air pollution will benefit evidence-based and health-related environmental policy-making. This paper reviews the conventional static and the new dynamic approach adopted for air pollution-related health cost accounting in China and analyzes the difference between the two in estimating GDP loss. The advantages of adopting the dynamic approach for health cost accounting in China, with conditions guaranteeing its optimal performance are highlighted. Guidelines on how one can identify an appropriate approach for health cost accounting in China are put forward. Further, we outline and compare the globally-applicable and China-specific indicators adopted by different accounting methodologies, with their pros and cons being discussed. A comprehensive account of the available databases and methodologies for health cost accounting in China are outlined. Future directions to guide health cost accounting in China are provided. Our work provides valuable insights into future health cost accounting research in China. Our study has strengthen the view that the dynamic approach is comparatively more preferred than the static approach for health cost accounting in China, if more data is available to train the dynamic models and improve the robustness of the parameters employed. In addition, future dynamic model should address the socio-economic impacts, including benefits or losses of air pollution polices, to provide a more robust policy picture. Our work has laid the key principles and guidelines for selecting proper econometric approaches and parameters. We have also identified a proper estimation method for the Value of Life in China, and proposed the integration of engineering approaches, such as the use of deep learning and big data analysis for health cost accounting at the fine-grained level (city-district or sub-regional level). Our work has also identified the gap for more accurate health cost accounting at the fine-grained level in China, which will subsequently affect the quality of health-related air pollution policy decision-making at such levels, and the health-related quality of life of the citizens in China.

Health impact of China's Air Pollution Prevention and Control Action Plan: an analysis of national air quality monitoring and mortality data

BACKGROUND

To mitigate the serious levels of air pollution in China, the State Council of China issued the Air Pollution Prevention and Control Action Plan (APPCAP) in 2013. This policy is a milestone in air quality control in China. We aimed to evaluate the effects of the APPCAP on long-term air quality management and the related health impacts in China.

METHODS

We did an analysis of national air quality monitoring and mortality data to estimate the health impact of the APPCAP from 2013 to 2017 in 74 key cities in China. Changes in mortality and in years of life lost (YLL), an indicator that considers life expectancy at death, were calculated to assess the health impact of air quality management during the 5-year period.

FINDINGS

Between 2013 and 2017, annual average concentrations of PM_2·5 decreased by 33·3% (95% CI 16·3-50·3), PM₁₀ by 27·8% (8·0-47·5), sulphur dioxide by 54·1% (28·2-80·0), and carbon monoxide by 28·2% (3·1-53·3) in the 74 key cities. However, no significant change was seen in annual average concentrations of nitrogen dioxide (9·7% reduction; 95% CI -23·0 to 42·4) or ozone (20·4% increase; -30·1 to 71·0). In 2017, as a result of substantial improvements in air quality, there were 47 240 (95% CI 25 870-69 990) fewer deaths and 710 020 (420 230-1 025 460) fewer YLL in the 74 key cities in China than in 2013.

INTERPRETATION

Substantial reductions in mortality and YLL related to control of ambient air pollution were achieved from 2013 to 2017 in China, indicating appreciable effectiveness of China's APPCAP. However, emissions control efforts for ozone and nitrogen dioxide should be strengthened in the future.

FUNDING

National Natural Science Foundation of China and the National Key Research and Development Program of China.

Application of an Original Wildfire Smoke Health Cost Benefits Transfer Protocol to the Western US, 2005-2015

Recent growth in the frequency and severity of US wildfires has led to more wildfire smoke and increased public exposure to harmful air pollutants. Populations exposed to wildfire smoke experience a variety of negative health impacts, imposing economic costs on society. However, few estimates of smoke health costs exist and none for the entire Western US, in particular, which experiences some of the largest and most intense wildfires in the US. The lack of cost estimates is troublesome because smoke health impacts are an important consideration of the overall costs of wildfire. To address this gap, this study provides the first time series estimates of PM2.5 smoke costs across mortality and several morbidity measures for the Western US over 2005-2015. This time period includes smoke from several megafires and includes years of record-breaking acres burned. Smoke costs are estimated using a benefits transfer protocol developed for contexts when original health data are not available. The novelty of our protocol is that it synthesizes the literature on choices faced by researchers when conducting a smoke cost benefit transfer. On average, wildfire smoke in the Western US creates $165 million in annual morbidity and mortality health costs.

Quantifying public health benefits of environmental strategy of PM2.5 air quality management in Beijing-Tianjin-Hebei region, China

In 2013, China issued "Air Pollution Prevention and Control Action Plan (Action Plan)" to improve air quality. To assess the benefits of this program in Beijing-Tianjin-Hebei (BTH) region, where the density of population and emissions vary greatly, we simulated the air quality benefit based on BenMAP to satisfy the Action Plan. In this study, we estimate PM_2.5 concentration using Voronoi spatial interpolation method on a grid with a spatial resolution of 1×1km². Combined with the exposure-response function between PM_2.5 concentration and health endpoints, health effects of PM_2.5 exposure are analyzed. The economic loss is assessed by using the willingness to pay (WTP) method and human capital (HC) method. When the PM_2.5 concentration falls by 25% in BTH and reached 60μg/m³ in Beijing, the avoiding deaths will be in the range of 3175 to 14051 based on different functions each year. Of the estimated mortality attributable to all causes, 3117 annual deaths were due to lung cancer, 1924 - 6318 annual deaths were due to cardiovascular, and 343 - 1697 annual deaths were due to respiratory. Based on WTP, the estimated monetary values for the avoided cases of all cause mortality, cardiovascular mortality, respiratory mortality and lung cancer ranged from 1110 to 29632, 673 to 13325, 120 to 3579, 1091 to 6574 million yuan, respectively. Based on HC, the corresponding values for the avoided cases of these four mortalities were 267 to 1178, 161 to 529, 29 to 143 and 261 million yuan, respectively.

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.