Executive summary of the study “Source apportionment, health effects and potential reduction of fine particulate matter (PM2.5) in India”, May 2018, by the Air-Weather-Climate (AWC) Research Group Department of Civil and Environmental Engineering Louisiana State University, USA:
In recent years, severe pollution events occurred frequently in India, which are of significant concern of the public. However, limited studies have been conducted to understand the formation, sources and health effects of high pollution and the information for design of effective control strategies is urgently needed. In this work, source-oriented versions of the Community Multiscale Air Quality (CMAQ) model with anthropogenic emissions from Emissions Database for Global Atmospheric Research (EDGAR), biogenic emissions from the Model for Emissions of Gases and Aerosols from Nature (MEGAN) v2.1, and meteorology from the Weather Research and Forecasting (WRF) model were applied to quantify the contributions of eight source types (energy, industry, residential, on-road, off-road, agriculture, open burning and dust) to fine particulate matter (PM2.5) and its major components including primary PM (PPM) and secondary inorganic aerosol (SIA) in India in 2015. Then, the health risks were estimated based on the predicted PM2.5 concentrations and the air quality benefits from potential policy interventions in future were analyzed.
Concentrations of PM2.5 were highest in the Indo-Gangetic region, including northern and eastern India. PM2.5 concentrations were higher during winter and lower during monsoon season. Winter nitrate concentrations were 160-230% higher than yearly average. In contrast, the fraction of sulfate in total PM2.5 was maximum in monsoon and least in winter, due to decrease in temperature and solar radiation intensity in winter. Except in southern India, where sulfate was the major component of PM2.5, primary organic aerosol (POA) fraction in PM2.5 was highest in all regions of the country. Fractions of secondary components were higher on bad days than on good days, indicating the importance of control of precursors for secondary pollutants in India.
PPM mass is dominated by industry and residential activities (> 60%). Energy (~ 39%) and industry (~ 45%) sectors contribute significantly to PPM at south of Delhi, which reach a maximum of 200 µg/m3 during winter. Unlike PPM, SIA concentrations from different sources are more heterogeneous. High SIA concentrations (~ 25 µg/m3 ) at south Delhi and central Uttar Pradesh were mainly attributed to energy, industry and residential sectors. Agriculture is more important for SIA than PPM and contributions of on-road and open burning to SIA are also higher than to PPM. Residential sector contributes highest to total PM2.5 (~ 80 µg/m3), followed by industry (~ 70 µg/m3) in North India. Energy and agriculture contribute ~ 25 µg/m3 and ~ 16 µg/m3 to total PM2.5, while SOA contributes < 5 µg/m3. In Delhi, industry and residential activities contribute to 80% of total PM2.5.
The major source of PPM mass is from within the state. In the selected cities, Chandigarh is the capital of the northern Indian states of Punjab and Haryana, Jaipur is the capital of India’s Rajasthan state, and Lucknow is the capital of the state of Uttar Pradesh and Delhi. About 80% of PPMs are from within the state in these 4 cities. Similar to PPM analysis, 80% of the total ammonia PM concentrations are from within the state, but Delhi have 20% of the total ammonia PMs from the adjacent states: Haryana, Rajasthan, Uttar Pradesh and Uttarakhand. In contrast, the nitrate PM in Delhi comes mainly from 3 sources: within the state, Haryana & Rajasthan and Punjab, Himachal Pradesh and Jammu&Kashmir. Each region contributes ~25% to total nitrate PM in Delhi. In other 3 cities, sources within the state contribution dominates total nitrate PM concentrations. The sulfate is formed mainly through rapid oxidation in emission plumes (40%~70% in Delhi). However, the secondary sulfate PMs are more likely from sources within the state in Lucknow and Jaipur.
Premature mortality associated with PM2.5 exposure was mainly due to cerebrovascular disease (CEV) was the highest in India (0.44 million), followed by ischaemic heart disease (IHD, 0.40 million), chronic obstructive pulmonary disease (COPD, 0.18 million) and lung cancer (LC, 0.01 million), adding up to total morality of 1.04 million. The top states of premature mortality were Uttar Pradesh (0.23 million), Bihar (0.12 million) and West Bengal (0.10 million). The residential sector was the top contributor (55.45%) to total premature mortality with a concentration of ~ 40 µg/m3, followed by industrial sources and power plants (26.5%) and agriculture (11.9%). Notably, in Delhi, the contribution of power plants and industrial sources exceeds residential emissions. With reducing the PM2.5 concentrations to 35 µg/m3, the WHO first interim target, premature mortality in Utter Pradash due to PM2.5 exposure would be reduced by 76%. The total morality would be significantly reduced by lowering current PM2.5 level to the WHO guideline value.
Thirteen scenarios based on different potential emission control strategies towards energy, residential, agriculture, industrial and open burning are simulated and compared with current emissions. If fully implemented, these measures can reduce population weighted average PM2.5 levels by an estimated 38.7% nationwide and avoid 858,900 premature deaths annually. The implementation of new emission standards for thermal power plants can avoid 124,000 premature deaths every year and cancelling the construction of proposed coal-fired power plants not yet under construction can avoid a further 26,000 premature deaths. A 50% reduction in the use of solid fuels by households nationwide could avoid an estimated 177,000 premature deaths annually, completely abandoning crop burning can avoid 55,000 premature deaths, reducing the use of diesel generators by 90% can avoid 30,000 premature deaths per year. The detailed reduction information was listed in the Table below.
Table: Potential reduction of population weighted PM2.5 concentration (µg/m3) and premature mortality (104 deaths) under certain emission scenarios with compliance in future:
The results show that reducing residential emission from solid fuels combustion and reducing power sector emissions affect PM2.5 concentration most, followed by reducing municipal solid waste burning and new emission standards applying in industry sector. In scenarios of thermal power plants emission, concentration increased maximum to more than 9 µg/m3 and decreased greatly in part of north India. From results, residential emission reduction could greatly eliminate PM2.5 concentration, followed by implementing new emission standards in the power sector and introducing new emissions standards for the industrial sector. New emission standards applied in industry sector affect PM2.5 concentration the most, followed by reducing emissions from existing and new thermal power plants, reducing municipal solid waste burning and reducing residential emission from solid fuels combustion and diesel generating sets use.
Click HERE to download full report