The contribution of emission sources to the future air pollution disease burden in China

Abstract

Air pollution exposure is a leading public health problem in China. Despite recent air quality improvements, fine particulate matter (PM2.5) exposure remains large, the associated disease burden is substantial, and population ageing is projected to increase the susceptibility to disease. Here, we used emulators of a regional chemical transport model to quantify the impacts of future emission scenarios on air pollution exposure in China. We estimated how key emission sectors contribute to these future health impacts from air pollution exposure. We found that PM2.5 exposure declines in all scenarios across China over 2020–2050, with reductions of 15% under current air quality legislation, 36% when exploiting the full potential of air pollutant emission reduction technologies, and 39% when that technical mitigation potential is combined with emission controls for climate mitigation. However, population ageing means that the PM2.5 disease burden under current legislation increases by 17% in 2050 relative to 2020. In comparison to current legislation in 2050, the application of the best air pollution technologies provides substantial health benefits, reducing the PM2.5 disease burden by 16%, avoiding 536,600 (95% uncertainty interval, 95UI: 497,800–573,300) premature deaths per year. These public health benefits are mainly due to reductions in industrial (43%) and residential (30%) emissions. Climate mitigation efforts combined with the best air pollution technologies leads to an additional 2% reduction in the PM2.5 disease burden, avoiding 57,000 (95UI: 52,800–61,100) premature deaths per year. Up to 90% of the 2020–2050 reductions in PM2.5 exposure are already achieved by 2030, assuming efficient implementation and enforcement of currently committed air quality policies in key sectors. Achieving reductions in PM2.5 exposure and the associated disease burden after 2030 will require further tightening of emission limits for regulated sectors, addressing other sources including agriculture and waste management, and international coordinated action to mitigate air pollution across Asia.

The Air Pollution Human Health Burden in Different Future Scenarios That Involve the Mitigation of Near‐Term Climate Forcers, Climate and Land‐Use

“…The corrected data is then re-gridded to match the horizontal resolution of the population data (0.125°) to create population-weighted mean values. This then provides a new present-day baseline of air pollutant concentrations, which are derived from observations as far as possible to eliminate some of these known biases in surface concentrations in a similar way to other recent air pollution health assessments (Chowdhury et al, 2020;Conibear et al, 2022;Shaddick et al, 2020), and makes the present day exposure values suitable for use in the calculation of the health response. Future changes in concentrations simulated by UKESM1 in each of the scenarios are then applied on top of this corrected baseline (see Text S1 in Supporting Information S1).…”

Inequalities in Air Pollution Exposure and Attributable Mortality in a Low Carbon Future

“…We performed an air pollution health impact assessment to estimate the future premature mortality burden attributable to long‐term exposure to ambient PM 2.5 concentrations under the different model scenarios, using population attributable fractions of relative risk following Conibear, Reddington, Silver, Arnold, et al. (2022). The relative risk for a specific PM 2.5 exposure and population age group was estimated using the Global Exposure Mortality Model (GEMM) (Burnett et al., 2018).…”

“…We chose to use the GEMM in our health impact assessment framework as it is based only on cohort studies of exposure to ambient PM 2.5 concentrations and has been used in several recent studies to quantify future PM 2.5 ‐attributable mortality burdens under different scenarios (Conibear, Reddington, Silver, Arnold, et al., 2022; Shindell et al., 2022; Turnock et al., 2023; Wang et al., 2022; Yang et al., 2023). For completeness, the results calculated in this study using the GEMM are compared with those calculated using the recent function from Weichenthal et al.…”

“…A number of specific measures that would likely yield the largest co‐benefits for climate and air quality have been highlighted in recent reports (Royal Society, 2021; UNEP, 2019; UNESCAP, 2023). Overall, the greatest health benefits are likely to result from implementation of climate mitigation policies in combination with stringent air pollution control measures (Amann et al., 2020; Conibear, Reddington, Silver, Arnold, et al., 2022; Harmsen et al., 2020; Likhvar et al., 2015; Partanen et al., 2018; Rafaj et al., 2021; Rao et al., 2016; Shim et al., 2021).…”

A hybrid deep learning framework for air quality prediction with spatial autocorrelation during the COVID-19 pandemic

“…Air pollution has long been a major matter of concern in China 1 . Exposure to harmful air pollution for a long time will result in a range of respiratory ailments, cardiovascular diseases, and even lung cancer in humans 2 . Furthermore, high concentrations of air pollutants harm food production and imperil animal survival 3 .…”