Refine Health Benefit Prior-Evaluation of Emergency Response Measures Under Heavy Pollution Weather

Abstract

In a realistic scenario people move and get exposed to different microenvironment (ME) with varying PM2.5 levels. While the traditional health impacts assessment directly overlaid static population with ambient PM2.5 concentrations, without considering diverse individual Activity Patterns (AP), bringing great uncertainties in PM2.5-related mortality burden assessment.So to refine exposure assessment considering AP, and applied it to the assessment of the Emergency Response Measures (ERMs) for heavy pollution weather. We carried out Activity Pattern Survey (APS) to investigate the time spent in certain ME and on certain activity types. Based on population density maps and APS data, the Random Forest Model and Agent Based Model were used to establish the rules of individual activity decisions and simulate the Population Distribution Embedded with AP (PD-AP), respectively. Then, indoor/outdoor PM2.5 concentration ratios of ME were summarized through literature research and were applied to calculate the ME PM2.5 levels by modifying the ambient PM2.5 levels. Finally, based on PD-AP, ME PM2.5 levels, and doses-response relationship, we used the Relative Risk Model to evaluate PM2.5 attributed deaths under 8 ERMs. And we also compared results under PD-AP, Uniform Population Distribution (UPD) and Static Population Distribution (SPD), to figure out the importance of improving simulation ability of the real distribution of population.The traditional UDP and SDP methods overestimated PM2.5 attributed deaths, and this overestimation was far greater than changes of attributed deaths caused by choosing different ERMs. Therefore, it is of great importance of considering diversities of population AP for improving accuracy of PM2.5 exposures assessment. Among 8 ERMs, Intensified Control Scenario in Jiangsu should be selected to deal with heavy pollution weather for its maneuverability and good performance of reducing attributed deaths especially in highly polluted areas.