Abstract

Traffic is one of the major contributors to PM2.5 in cities worldwide. Quantifying the role of traffic is an important step towards understanding the impact of transport policies on the possibilities to achieve cleaner air and accompanying health benefits. With the aim of estimating potential health benefits of eliminating traffic emissions, we carried out a meta-analysis using the World Health Organisation (WHO) database of source apportionment studies of PM2.5 concentrations. Specifically, we used a Bayesian meta-regression approach, modelling both overall and traffic-related (tailpipe and non-tailpipe) concentrations simultaneously. We obtained the distributions of expected PM2.5 concentrations (posterior densities) of different types for 117 cities worldwide. Using the non-linear Integrated Exposure Response (IER) function of PM2.5, we estimated percent reduction in different disease endpoints for a scenario with complete removal of traffic emissions. We found that eliminating traffic emissions results in achieving the WHO-recommended concentration of PM2.5 only for a handful of cities that already have low concentrations of pollution. The percentage reduction in premature mortality due to cardiovascular and respiratory diseases increases up to a point (30–40 ug/m3), and above this concentration, it flattens off. For diabetes-related mortality, the percentage reduction in mortality decreases with increasing concentrations—a trend that is opposite to other outcomes. For cities with high concentrations of pollution, the results highlight the need for multi-sectoral strategies to reduce pollution. The IER functions of PM2.5 result in diminishing returns of health benefits at high concentrations, and in case of diabetes, there are even negative returns. The results show the significant effect of the shape of IER functions on health benefits. Overall, despite the diminishing results, a significant burden of deaths can be prevented by policies that aim to reduce traffic emissions even at high concentrations of pollution.

Highlights

  • Introduction and backgroundMotorised traffic is growing rapidly in many low- and middle-income countries (LMICs) resulting from increasing ownership of vehicles and rapid urbanisation

  • For the posterior distributions of the expected concentration of non-traffic-related PM2.5, we Potential health benefits of eliminating traffic emissions in urban areas estimated the probability that concentrations remained higher than the World Health Organisation (WHO)-recommended annual concentration of PM2.5 if traffic-related emissions were removed completely

  • We used non-linear Integrated Exposure Response (IER) functions along with the comparative risk assessment approach to estimate population attributable fraction corresponding to this reduction in concentrations

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Summary

Objectives

The primary goal of this research is to estimate the health benefits that can be gained by reduction in traffic emissions

Methods
Results
Conclusion
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