The air pollution tradeoff in India: saving more lives versus reducing the inequality of exposure

Abstract

Chronic exposure to ambient fine particulate matter (PM _2.5 ) represents one of the largest global public health risks, leading to millions of premature deaths annually. For a country facing high and spatially variable exposures, prioritizing where to reduce PM _2.5 concentrations leads to an inherent tradeoff between saving the most lives and reducing inequality of exposure. This tradeoff results from the shape of the concentration–response (C-R) function between exposure to PM _2.5 and mortality, which indicates that the additional lives saved per unit reduction in PM _2.5 declines as concentrations increase, suggesting that more lives can be saved by reducing exposures in clean locations than in dirty locations. We estimated this C-R function for urban areas of India, finding that a 10 µ gm ^−3 reduction in PM _2.5 in already-clean locations will reduce the mortality rate substantially (4.2% for a reduction from 30 to 20 µ gm ^−3 ), while a 10 µ gm ^−3 reduction in the dirtiest locations will reduce mortality only modestly (1.2% for a reduction from 90 to 80 µ gm ^−3 ). Policymakers face a troubling tradeoff between maximizing lives saved and reducing the inequality of exposure. Many air pollution policies impose an upper limit on exposure, thereby cleaning the dirtiest locations and reducing exposure inequality. We explore the implications of this PM _2.5 /mortality relationship by considering a thought experiment. If India had a fixed amount of resources to devote to PM _2.5 concentration reductions across urban areas, what is the lives saved/inequality of exposure tradeoff from three different methods of deploying those resources? Across our three scenarios: (1) which reduces exposures for the dirtiest districts, (2) which reduces exposures everywhere equally, and (3) which reduces exposures to save the most lives—scenario 1 saves 18 000 lives per year while reducing the inequality of exposure by 65%, while scenario 3 saves 126 000 lives per year, but increases inequality by 19%.

Keywords

• air pollution
• India
• pollution inequality
• environmental health