[论文解读] Absentee and Economic Impact of Low-Level Fine Particulate Matter and Ozone Exposure in K-12 Students

Daniel Mendoza, C.S. Pirozzi+7 more|arXiv (Cornell University)|Jan 1, 2020

Air Quality and Health Impacts参考文献 43被引用 3

一句话总结

本研究利用密集传感器网络获取的高分辨率空气质量数据，对2015–2018年间盐湖城市36所K-12学校中的PM2.5和臭氧暴露水平进行了建模。研究发现，即使污染水平低于美国监管标准，仍与学校缺勤率显著升高相关，导致每年经济损失和生产力损失达45.2万美元，尤其对弱势学校影响更为严重。

ABSTRACT

High air pollution levels are associated with school absences. However, low level pollution impact on individual school absences are under-studied. We modelled PM2.5 and ozone concentrations at 36 schools from July 2015 to June 2018 using data from a dense, research grade regulatory sensor network. We determined exposures and daily absences at each school. We used generalized estimating equations model to retrospectively estimate rate ratios for association between outdoor pollutant concentrations and school absences. We estimated lost school revenue, productivity, and family economic burden. PM2.5 and ozone concentrations and absence rates vary across the School District. Pollution exposure were associated with as high a rate ratio of 1.02 absences per ug/m$^3$ and 1.01 per ppb increase for PM2.5 and ozone, respectively. Significantly, even PM2.5 and ozone exposure below regulatory standards (<12.1 ug/m$^3$ and <55 ppb) was associated with positive rate ratios of absences: 1.04 per ug/m$^3$ and 1.01 per ppb increase, respectively. Granular local measurements enabled demonstration of air pollution impacts that varied between schools undetectable with averaged pollution levels. Reducing pollution by 50% would save $452,000 per year districtwide. Pollution reduction benefits would be greatest in schools located in socioeconomically disadvantaged areas. Exposures to air pollution, even at low levels, are associated with increased school absences. Heterogeneity in exposure, disproportionately affecting socioeconomically disadvantaged schools, points to the need for fine resolution exposure estimation. The economic cost of absences associated with air pollution is substantial even excluding indirect costs such as hospital visits and medication. These findings may help inform decisions about recess during severe pollution events and regulatory considerations for localized pollution sources.

研究动机与目标

• 评估K-12学生中低水平PM2.5和臭氧暴露与缺勤率之间的关联。
• 评估空气污染相关缺勤在学区层面造成的经济负担。
• 考察不同社会经济背景学校之间污染暴露及其影响的空间异质性。
• 提供精细化、本地化的暴露估计，以改善污染事件期间的学校决策。
• 通过识别社会经济弱势学校所承受的不成比例影响，为环境正义考量提供依据。

提出的方法

• 利用密集的监管型和移动式空气质量传感器网络（包括安装在轻轨列车上的传感器）以5分钟间隔采集PM2.5和臭氧数据。
• 采用反距离加权法（IDW），基于监测站点与学校的距离估算各校的污染物浓度。
• 采用广义估计方程（GEE）建模每日污染物浓度与缺勤率之间的关联，同时调整时间趋势和学校层面的协变量。
• 通过估算每起缺勤造成的学校收入损失、家庭生产力成本及间接成本，计算经济影响。
• 开展滞后暴露分析，评估污染对缺勤的延迟效应。
• 按学校层级和经济地位（Title I资格）比较结果，以评估不平等差异。

实验结果

研究问题

• RQ1 低水平PM2.5和臭氧暴露是否与K-12学生缺勤率显著升高存在关联？
• RQ2 空气污染对缺勤的影响是否因学校的社会经济特征不同而有所差异？
• RQ3 在学区层面，环境PM2.5和臭氧暴露导致的缺勤经济成本是多少？
• RQ4 与区域平均污染数据相比，精细化的学校级暴露估计在预测缺勤方面表现如何？
• RQ5 若学区范围内PM2.5和臭氧浓度降低50%，将带来多大的经济效益？

主要发现

• 即使PM2.5和臭氧水平低于美国国家环境空气质量标准（分别为12.1 µg/m³和55 ppb），仍与缺勤率上升显著相关，每µg/m³和每ppb的率比（rate ratio）分别为1.04和1.01。
• PM2.5的最高率比出现在小学，表明年幼儿童因呼吸系统尚未发育完全，可能更为脆弱。
• 若学区范围内PM2.5和臭氧浓度降低50%，预计每年可节省45.2万美元的学校收入损失和生产力损失。
• 污染减排的经济效益在服务社会经济弱势社区的学校中预计最高。
• 学区范围内暴露水平差异显著，不同学校间PM2.5浓度差异超过6 µg/m³，凸显了区域平均值的局限性。
• 本研究表明，基于单一监测站点的现行课间休息政策可能无法充分反映局部污染暴露情况，尤其是在空间变异性较高的区域。