Understand the local and regional contributions on air pollution from the view of human health impacts

The source-receptor matrix of PM_(2.5)concentration from local and regional sources in the Beijing-Tianjin-Hebei(BTH)and surrounding provinces has been created in previous studies.However,because the spatial distribution of concentration does not necessarily match with that of the population,such concentration-based source-receptor matrix may not fully reflect the importance of pollutant control effectiveness in reducing the PM_(2.5)-related health impacts.To demonstrate that,we study the source-receptor matrix of the PM_(2.5)-related deaths instead,with inclusion of the spatial correlations between the concentrations and the population.The advanced source apportionment numerical model combined with the integrated exposure-response functions is used for BTH and surrounding regions in 2017.We observed that the relative contribution to PM_(2.5)-related deaths of local emissions was 0.75%to 20.77%larger than that of PM_(2.5)concentrations.Such results address the importance of local emissions control for reducing health impacts of PM_(2.5)particularly for local residents.Contribution of regional transport to PM_(2.5)-related deaths in rural area was 22%larger than that in urban area due to the spatial pattern of regional transport which was more related to the rural population.This resulted in an environmental inequality in the sense that people staying in rural area with access to less educational resources are subjected to higher impacts from regional transport as compared with their more resourceful and knowledgeable urban compatriots.An unexpected benefit from the multi-regional joint controls is suggested for its effectiveness in reducing the regional transport of PM_(2.5)pollution thus mitigating the associated environmental inequality.

Quantifying the contribution of activity patterns to PM_(2.5)exposure inequity between urban and rural residents by a novel method

PM_(2.5)pollution variations in different microenvironments would result in PM_(2.5)exposure inequity between rural and urban residents.In this study,the real-time PM_(2.5)exposure of urban and rural residents in China was examined based on portable PM_(2.5)sensors together with activity patterns derived from questionnaire surveys,with a focus on students and senior citizens who are sensitive to air pollution.The results showed that PM_(2.5)exposure varied significantly among different resident groups,with higher PM_(2.5)exposure of rural residents than those of urban residents.PM_(2.5)exposure peaks mostly occurred during(Accompanied)cooking activities owing to strong emissions.Sleeping and resting were the main activities that affected PM_(2.5)exposures of different resident groups,accounting for 60.7%-94.5%of total daily exposures.Furthermore,the long duration of sleeping makes it the predominant activity contributing to PM 25 exposure inequity.It is necessary to obtain point-to-point respiratory volume(respiratory rate)data when measuring real-time PM_(2.5)exposure data and incorporate respiratory volume(respiratory rate)into the analysis of PM_(2.5)exposure.For the first time,this study quantified the PM_(2.5)exposure inequality based on a novel method and can provide useful information for further studies on the exposure inequity.