空气污染暴露公正评估方法研究进展

Research Progress on Methods of Assessing Air Pollution Exposure Justice

为避免特定区域内环境不公正现象的发生，进行空气污染暴露公正研究有利于合理分配资源，而对其评估方法开展综合性评价必不可少。利用ISI Web of Knowledge、Science Direct．中国期刊网等数据库搜索相关文献，并按空气污染暴露强度评估、社会人口统计数据预处理和统计分析3个方面进行分类整理和评价。结果显示，在空气污染暴露公正的研究中，大气污染扩散模型是精度最优的暴露评估方法；社会人口统计数据分类标准的建立需要顾及数据可获取性和研究目的；在统计分析方法的使用上，基于哑变量的多元线性回归分析和逻辑回归分析方法的解释力最强。针对当前情况，预测未来空气污染暴露公正评价研究集中在评价结果的精度优化、时空变化趋势探测和因果效应分析等方面。

Studies on air pollution exposure justice contribute to reasonably allocating resources, regulating or reducing occurrence of injustice phenomena within a specific geographic region. Considering the uncertainties resulted from diverse methods used by domestic and foreign scholars in researches on air pollution exposure justice, it is very essential to re-evaluate those methods in a review paper. By searching databases including ISI Web of Knowledge, Science Direct and CNKI with air pollution exposure justice related keywords, those searched out references were reclassified into three subtitles, i. e., air pollution exposure intensity assessment, social demographic data pre-processing, and statistic analysis. Results have shown that air dispersion modelling was the optimal method in assessing air pollution exposure intensity in terms of accuracy, standards of reclassifying social demographic data should be established according to the data availability and study objectives, dummy variable based multiple linear regression analysis and logistic regression analysis performed stronger explanations among all the statistic analysis methods. In a sum, future air pollution exposure justice study could focus on improving the precision of results of air pollution exposure justice, detecting its spatial-temporal trends and causality.