Simon Heather, Baker Kirk R, Sellers Jennifer, Amend Meredith, Penn Stefani L, Bankert Joshua, Chan Elizabeth A W, Fann Neal, Jang Carey, McKinley Gobeail, Zawacki Margaret, Roman Henry
US Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC.
Industrial Economics, Incorporated, Cambridge, MA.
Environ Sci Atmos. 2023 Jul 27;19(227):1-13. doi: 10.1039/d3ea00092c.
Reduced-form modeling approaches are an increasingly popular way to rapidly estimate air quality and human health impacts related to changes in air pollutant emissions. These approaches reduce computation time by making simplifying assumptions about pollutant source characteristics, transport and chemistry. Two reduced form tools used by the Environmental Protection Agency in recent assessments are source apportionment-based benefit per ton (SA BPT) and source apportionment-based air quality surfaces (SABAQS). In this work, we apply these two reduced form tools to predict changes in ambient summer-season ozone, ambient annual PM component species and monetized health benefits for multiple sector-specific emission control scenarios: on-road mobile, electricity generating units (EGUs), cement kilns, petroleum refineries, and pulp and paper facilities. We then compare results against photochemical grid and standard health model-based estimates. We additionally compare monetized PM health benefits to values derived from three reduced form tools available in the literature: the Intervention Model for Air Pollution (InMAP), Air Pollution Emission Experiments and Policy Analysis (APEEP) version 2 (AP2) and Estimating Air pollution Social Impact Using Regression (EASIUR). Ozone and PM changes derived from SABAQS for EGU scenarios were well-correlated with values obtained from photochemical modeling simulations with spatial correlation coefficients between 0.64 and 0.89 for ozone and between 0.75 and 0.94 for PM. SABAQS ambient ozone and PM bias when compared to photochemical modeling predictions varied by emissions scenario: SABAQS PM changes were overpredicted by up to 46% in one scenario and underpredicted by up to 19% in another scenario; SABAQS seasonal ozone changes were overpredicted by 34% to 83%. All tools predicted total PM benefits within a factor of 2 of the full-form predictions consistent with intercomparisons of reduced form tools available in the literature. As reduced form tools evolve, it is important to continue periodic comparison with comprehensive models to identify systematic biases in estimating air pollution impacts and resulting monetized health benefits.
简化形式建模方法是一种越来越流行的方式，用于快速估算与空气污染物排放变化相关的空气质量和人类健康影响。这些方法通过对污染物源特征、传输和化学过程做出简化假设来减少计算时间。美国环境保护局在近期评估中使用的两种简化形式工具是基于源分配的每吨效益（SA BPT）和基于源分配的空气质量表面（SABAQS）。在这项工作中，我们应用这两种简化形式工具来预测夏季环境臭氧、年度环境颗粒物成分物种的变化以及多种特定行业排放控制情景下的货币化健康效益：道路移动源、发电单位（EGU）、水泥窑、炼油厂和纸浆造纸设施。然后，我们将结果与光化学网格模型和基于标准健康模型的估计值进行比较。我们还将货币化的颗粒物健康效益与文献中可用的三种简化形式工具得出的值进行比较：空气污染干预模型（InMAP）、空气污染排放实验与政策分析（APEEP）第2版（AP2）以及使用回归估计空气污染社会影响（EASIUR）。对于EGU情景，从SABAQS得出的臭氧和颗粒物变化与光化学建模模拟获得的值具有良好的相关性，臭氧的空间相关系数在0.64至0.89之间，颗粒物的空间相关系数在0.75至0.94之间。与光化学建模预测相比，SABAQS环境臭氧和颗粒物偏差因排放情景而异：在一种情景中，SABAQS颗粒物变化被高估了高达46%，而在另一种情景中被低估了高达19%；SABAQS季节性臭氧变化被高估了34%至83%。所有工具预测的总颗粒物效益在全形式预测的2倍范围内，这与文献中简化形式工具的相互比较结果一致。随着简化形式工具的不断发展，继续定期与综合模型进行比较以识别在估算空气污染影响和由此产生的货币化健康效益方面的系统偏差非常重要。
