TY - JOUR
T1 - The impact of power generation emissions on ambient PM2.5 pollution and human health in China and India
AU - Gao, Meng
AU - Beig, Gufran
AU - Song, Shaojie
AU - Zhang, Hongliang
AU - Hu, Jianlin
AU - Ying, Qi
AU - Liang, Fengchao
AU - Liu, Yang
AU - Wang, Haikun
AU - Lu, Xiao
AU - Zhu, Tong
AU - Carmichael, Gregory R.
AU - Nielsen, Chris P.
AU - McElroy, Michael B.
PY - 2018/12
Y1 - 2018/12
N2 - Emissions from power plants in China and India contain a myriad of fine particulate matter (PM2.5, PM ≤ 2.5 μm in diameter) precursors, posing significant health risks among large, densely settled populations. Studies isolating the contributions of various source classes and geographic regions are limited in China and India, but such information could be helpful for policy makers attempting to identify efficient mitigation strategies. We quantified the impact of power generation emissions on annual mean PM2.5 concentrations using the state-of-the-art atmospheric chemistry model WRF-Chem (Weather Research Forecasting model coupled with Chemistry) in China and India. Evaluations using nationwide surface measurements show the model performs reasonably well. We calculated province-specific annual changes in mortality and life expectancy due to power generation emissions generated PM2.5 using the Integrated Exposure Response (IER) model, recently updated IER parameters from Global Burden of Disease (GBD) 2015, population data, and the World Health Organization (WHO) life tables for China and India. We estimate that 15 million (95% Confidence Interval (CI): 10 to 21 million) years of life lost can be avoided in China each year and 11 million (95% CI: 7 to 15 million) in India by eliminating power generation emissions. Priorities in upgrading existing power generating technologies should be given to Shandong, Henan, and Sichuan provinces in China, and Uttar Pradesh state in India due to their dominant contributions to the current health risks.
AB - Emissions from power plants in China and India contain a myriad of fine particulate matter (PM2.5, PM ≤ 2.5 μm in diameter) precursors, posing significant health risks among large, densely settled populations. Studies isolating the contributions of various source classes and geographic regions are limited in China and India, but such information could be helpful for policy makers attempting to identify efficient mitigation strategies. We quantified the impact of power generation emissions on annual mean PM2.5 concentrations using the state-of-the-art atmospheric chemistry model WRF-Chem (Weather Research Forecasting model coupled with Chemistry) in China and India. Evaluations using nationwide surface measurements show the model performs reasonably well. We calculated province-specific annual changes in mortality and life expectancy due to power generation emissions generated PM2.5 using the Integrated Exposure Response (IER) model, recently updated IER parameters from Global Burden of Disease (GBD) 2015, population data, and the World Health Organization (WHO) life tables for China and India. We estimate that 15 million (95% Confidence Interval (CI): 10 to 21 million) years of life lost can be avoided in China each year and 11 million (95% CI: 7 to 15 million) in India by eliminating power generation emissions. Priorities in upgrading existing power generating technologies should be given to Shandong, Henan, and Sichuan provinces in China, and Uttar Pradesh state in India due to their dominant contributions to the current health risks.
KW - Air quality modeling
KW - Power generation
KW - China
KW - India
KW - WRF-Chem
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85051147470&partnerID=MN8TOARS
U2 - 10.1016/j.envint.2018.09.015
DO - 10.1016/j.envint.2018.09.015
M3 - Journal article
SN - 0160-4120
VL - 121, Part 1
SP - 250
EP - 259
JO - Environment International
JF - Environment International
ER -
