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1.
Environ Sci Technol ; 51(4): 2178-2185, 2017 02 21.
Article in English | MEDLINE | ID: mdl-28102073

ABSTRACT

The Gridpoint Statistical Interpolation (GSI) Three-Dimensional Variational (3DVAR) data assimilation system is extended to treat the MOSAIC aerosol model in WRF-Chem, and to be capable of assimilating surface PM2.5 concentrations. The coupled GSI-WRF-Chem system is applied to reproduce aerosol levels over China during an extremely polluted winter month, January 2013. After assimilating surface PM2.5 concentrations, the correlation coefficients between observations and model results averaged over the assimilated sites are improved from 0.67 to 0.94. At nonassimilated sites, improvements (higher correlation coefficients and lower mean bias errors (MBE) and root-mean-square errors (RMSE)) are also found in PM2.5, PM10, and AOD predictions. Using the constrained aerosol fields, we estimate that the PM2.5 concentrations in January 2013 might have caused 7550 premature deaths in Jing-Jin-Ji areas, which are 2% higher than the estimates using unconstrained aerosol fields. We also estimate that the daytime monthly mean anthropogenic aerosol radiative forcing (ARF) to be -29.9W/m2 at the surface, 27.0W/m2 inside the atmosphere, and -2.9W/m2 at the top of the atmosphere. Our estimates update the previously reported overestimations along Yangtze River region and underestimations in North China. This GSI-WRF-Chem system would also be potentially useful for air quality forecasting in China.


Subject(s)
Air Pollutants , Particulate Matter , Aerosols , China , Environmental Monitoring
2.
Environ Res ; 147: 480-96, 2016 May.
Article in English | MEDLINE | ID: mdl-26974362

ABSTRACT

Air pollution poses a critical threat to human health with ambient and household air pollution identified as key health risks in India. While there are many studies investigating concentration, composition, and health effects of air pollution, investigators are only beginning to focus on estimating or measuring personal exposure. Further, the relevance of exposures studies from the developed countries in developing countries is uncertain. This review summarizes existing research on exposure to particulate matter (PM) in India, identifies gaps and offers recommendations for future research. There are a limited number of studies focused on exposure to PM and/or associated health effects in India, but it is evident that levels of exposure are much higher than those reported in developed countries. Most studies have focused on coarse aerosols, with a few studies on fine aerosols. Additionally, most studies have focused on a handful of cities, and there are many unknowns in terms of ambient levels of PM as well as personal exposure. Given the high mortality burden associated with air pollution exposure in India, a deeper understanding of ambient pollutant levels as well as source strengths is crucial, both in urban and rural areas. Further, the attention needs to expand beyond the handful large cities that have been studied in detail.


Subject(s)
Environmental Exposure , Particulate Matter , Air Pollution, Indoor , Humans , India , Vehicle Emissions
3.
Sci Total Environ ; 511: 553-61, 2015 Apr 01.
Article in English | MEDLINE | ID: mdl-25585158

ABSTRACT

Haze is a serious air pollution problem in China, especially in Beijing and surrounding areas, affecting visibility, public health and regional climate. In this study, the Weather Research and Forecasting-Chemistry (WRF-Chem) model was used to simulate PM2.5 (particulate matters with aerodynamic diameter≤2.5 µm) concentrations during the 2013 severe haze event in Beijing, and health impacts and health-related economic losses were calculated based on model results. Compared with surface monitoring data, the model results reflected pollution concentrations accurately (correlation coefficients between simulated and measured PM2.5 were 0.7, 0.4, 0.5 and 0.6 in Beijing, Tianjin, Xianghe and Xinglong stations, respectively). Health impacts assessments show that the PM2.5 concentrations in January might cause 690 (95% confidence interval (CI): (490, 890)) premature deaths, 45,350 (95% CI: (21,640, 57,860)) acute bronchitis and 23,720 (95% CI: (17,090, 29,710)) asthma cases in Beijing area. Results of the economic losses assessments suggest that the haze in January 2013 might lead to 253.8 (95% CI: (170.2, 331.2)) million US$ losses, accounting for 0.08% (95% CI: (0.05%, 0.1%)) of the total 2013 annual gross domestic product (GDP) of Beijing.


Subject(s)
Air Pollutants/analysis , Air Pollution/statistics & numerical data , Environmental Exposure/statistics & numerical data , Air Pollution/economics , China , Environmental Exposure/economics , Humans , Particulate Matter/analysis , Public Health
4.
Environ Monit Assess ; 185(7): 5585-93, 2013 Jul.
Article in English | MEDLINE | ID: mdl-23132755

ABSTRACT

Air quality in Hyderabad, India, often exceeds the national ambient air quality standards, especially for particulate matter (PM), which, in 2010, averaged 82.2 ± 24.6, 96.2 ± 12.1, and 64.3 ± 21.2 µg/m(3) of PM10, at commercial, industrial, and residential monitoring stations, respectively, exceeding the national ambient standard of 60 µg/m(3). In 2005, following an ordinance passed by the Supreme Court of India, a source apportionment study was conducted to quantify source contributions to PM pollution in Hyderabad, using the chemical mass balance (version 8.2) receptor model for 180 ambient samples collected at three stations for PM10 and PM2.5 size fractions for three seasons. The receptor modeling results indicated that the PM10 pollution is dominated by the direct vehicular exhaust and road dust (more than 60%). PM2.5 with higher propensity to enter the human respiratory tracks, has mixed sources of vehicle exhaust, industrial coal combustion, garbage burning, and secondary PM. In order to improve the air quality in the city, these findings demonstrate the need to control emissions from all known sources and particularly focus on the low-hanging fruits like road dust and waste burning, while the technological and institutional advancements in the transport and industrial sectors are bound to enhance efficiencies. Andhra Pradesh Pollution Control Board utilized these results to prepare an air pollution control action plan for the city.


Subject(s)
Air Pollutants/analysis , Air Pollution/statistics & numerical data , Models, Chemical , Particulate Matter/analysis , Environmental Monitoring , India
5.
Environ Monit Assess ; 184(5): 3199-211, 2012 May.
Article in English | MEDLINE | ID: mdl-21713474

ABSTRACT

The winters in megacity Delhi are harsh, smoggy, foggy, and highly polluted. The pollution levels are approximately two to three times those monitored in the summer months, and the severity is felt not only in the health department but also in the transportation department, with regular delays at airport operations and series of minor and major accidents across the road corridors. The impacts felt across the city are both manmade (due to the fuel burning) and natural (due to the meteorological setting), and it is hard to distinguish their respective proportions. Over the last decade, the city has gained from timely interventions to control pollution, and yet, the pollution levels are as bad as the previous year, especially for the fine particulates, the most harmful of the criteria pollutants, with a daily 2009 average of 80 to 100 µg/m(3). In this paper, the role of meteorology is studied using a Lagrangian model called Atmospheric Transport Modeling System in tracer mode to better understand the seasonality of pollution in Delhi. A clear conclusion is that irrespective of constant emissions over each month, the estimated tracer concentrations are invariably 40% to 80% higher in the winter months (November, December, and January) and 10% to 60% lower in the summer months (May, June, and July), when compared to annual average for that year. Along with monitoring and source apportionment studies, this paper presents a way to communicate complex physical characteristics of atmospheric modeling in simplistic manner and to further elaborate linkages between local meteorology and pollution.


Subject(s)
Air Pollutants/analysis , Air Pollution/statistics & numerical data , Cities/statistics & numerical data , Weather , Atmosphere/chemistry , Environmental Monitoring , India , Meteorology , Seasons
6.
J Environ Manage ; 70(1): 49-62, 2004 Jan.
Article in English | MEDLINE | ID: mdl-15125545

ABSTRACT

Urban development in the mega-cities of Asia has caused detrimental effects on the human health of its inhabitants through air pollution. However, averting these health damages by investing in clean energy and industrial technologies and measures can be expensive. Many cities do not have the capital to make such investments or may prefer to invest that capital elsewhere. In this article, we examine the city of Shanghai, China, and perform an illustrative cost/benefit analysis of air pollution control. Between 1995 and 2020 we expect that Shanghai will continue to grow rapidly. Increased demands for energy will cause increased use of fossil fuels and increased emissions of air pollutants. In this work, we examine emissions of particles smaller than 10 microm in diameter (PM10), which have been associated with inhalation health effects. We hypothesize the establishment of a new technology strategy for coal-fired power generation after 2010 and a new industrial coal-use policy. The health benefits of pollution reduction are compared with the investment costs for the new strategies. The study shows that the benefit-to-cost ratio is in the range of 1-5 for the power-sector initiative and 2-15 for the industrial-sector initiative. Thus, there appear to be considerable net benefits for these strategies, which could be very large depending on the valuation of health effects in China today and in the future. This study therefore provides economic grounds for supporting investments in air pollution control in developing cities like Shanghai.


Subject(s)
Air Pollution/economics , Air Pollution/prevention & control , Population Dynamics , Public Health , China , Cost-Benefit Analysis , Humans , Particle Size , Urban Population
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