Net effect of air pollution controls on health risk in the Beijing-Tianjin-Hebei region during the 2022 winter Olympics and Paralympics

Due to the non-linearity in ozone(O_(3))formation,reducing the emission of nitrogen oxides(NO_(x))may increase O_(3) concentration.Given the counteractive O_(3) response to NO_(x) reduction,overall impact of air pollution controls can be ambiguous when the assessments focus on the changes in pollutant concentrations.In this study,a risk-based method was used to gauge the net effect of air pollution controls on mortality risk in the Beijing–Tianjin–Hebei(BTH)region during the 2022 Winter Olympics and Paralympics(WOP).This mega-event presents a unique opportunity to investigate the efficacy of deep cuts in pollutant emissions.Results show that O_(3) concentrations greatly increased as nitrogen dioxide(NO_(2))concentrations decreased in the BTH.Due to the active photochemical formations,O_(3) became the dominant pollutant that affected human health during the WOP.Despite the substantial O_(3) increases,the health benefits of NO_(2) reductions overwhelmed the adverse health effects of O_(3) increases in most regions of the BTH(at 81 out of 112 stations).After considering the impacts of particulate matter,the integrated health risk of air pollution mixtures declined almost everywhere in the BTH.Our results underscore the great necessity of changing the assessment paradigm of pollution control from using concentration-based methods to using risk-based methods.Together with the carbon neutrality policy,stringent control of NO_(x)emission from combustion sources is a promising way to achieve synergistic control solutions for air pollution and climate change.

Impacts of pollution heterogeneity on population exposure in dense urban areas using ultra-fine resolution air quality data

Traditional air quality data have a spatial resolution of 1 km or above, making it challenging to resolve detailed air pollution exposure in complex urban areas. Combining urban morphology, dynamic traffic emission, regional and local meteorology, physicochemical transformations in air quality models using big data fusion technology, an ultra-fine resolution modeling system was developed to provide air quality data down to street level. Based on one-year ultra-fine resolution data, this study investigated the effects of pollution heterogeneity on the individual and population exposure to particulate matter(PM_(2.5)and PM_(10)),nitrogen dioxide(NO_(2)), and ozone(O_(3)) in Hong Kong, one of the most densely populated and urbanized cities. Sharp fine-scale variabilities in air pollution were revealed within individual city blocks. Using traditional 1 km average to represent individual exposure resulted in a positively skewed deviation of up to 200% for high-end exposure individuals. Citizens were disproportionally affected by air pollution, with annual pollutant concentrations varied by factors of 2 to 5 among 452 District Council Constituency Areas(DCCAs) in Hong Kong, indicating great environmental inequities among the population. Unfavorable city planning resulted in a positive spatial coincidence between pollution and population, which increased public exposure to air pollutants by as large as 46% among districts in Hong Kong. Our results highlight the importance of ultra-fine pollutant data in quantifying the heterogeneity in pollution exposure in the dense urban area and the critical role of smart urban planning in reducing exposure inequities.