Abstract
A set of exposure⁻response coefficients between fine particulate matter (PM(2.5)) pollution and different health endpoints were determined through the meta-analysis method based on 2254 studies collected from the Web of Science database. With data including remotely-sensed PM(2.5) concentration, demographic data, health data, and survey data, a Poisson regression model was used to assess the health losses and their economic value caused by PM(2.5) pollution in cities of atmospheric pollution transmission channel in the Beijing⁻Tianjin⁻Hebei region, China. The results showed the following: (1) Significant exposure⁻response relationships existed between PM(2.5) pollution and a set of health endpoints, including all-cause death, death from circulatory disease, death from respiratory disease, death from lung cancer, hospitalization for circulatory disease, hospitalization for respiratory disease, and outpatient emergency treatment. Each increase of 10 μg/m³ in PM(2.5) concentration led to an increase of 5.69% (95% CI (confidence interval): 4.12%, 7.85%), 6.88% (95% CI: 4.94%, 9.58%), 4.71% (95% CI: 2.93%, 7.57%), 9.53% (95% CI: 6.84%, 13.28%), 5.33% (95% CI: 3.90%, 7.27%), 5.50% (95% CI: 4.09%, 7.38%), and 6.35% (95% CI: 4.71%, 8.56%) for above-mentioned health endpoints, respectively. (2) PM(2.5) pollution posed a serious threat to residents' health. In 2016, the number of deaths, hospitalizations, and outpatient emergency visits induced by PM(2.5) pollution in cities of atmospheric pollution transmission channel in the Beijing⁻Tianjin⁻Hebei region reached 309,643, 1,867,240, and 47,655,405, respectively, accounting for 28.36%, 27.02% and 30.13% of the total number of deaths, hospitalizations, and outpatient emergency visits, respectively. (3) The economic value of health losses due to PM(2.5) pollution in the study area was approximately $28.1 billion, accounting for 1.52% of the gross domestic product. The economic value of health losses was higher in Beijing, Tianjin, Shijiazhuang, Zhengzhou, Handan, Baoding, and Cangzhou, but lower in Taiyuan, Yangquan, Changzhi, Jincheng, and Hebi.