Impact of regional versus local resolution air quality modeling on particulate matter exposure health impact assessment
Impact of regional versus local resolution air quality modeling on particulate matter exposure health impact assessment
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DOI：
10.1007/s11869-019-00786-6
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发表时间：
2020-02-07
影响因子：
5.1
通讯作者：
Wagstrom, Kristina
中科院分区：
文献类型：
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作者：
Parvez, Fatema;Wagstrom, Kristina
由于许多人口居住在交通繁忙的道路附近，因此基于区域空气质量模型进行健康影响评估有可能低估健康影响。我们比较了康涅狄格州哈特福德、纽黑文和威利曼蒂克三个地点的当地（0.04 x 0.04 公里升级至人口普查区块组分辨率）和区域（12 x 12 公里分辨率）模拟浓度对细颗粒物 (PM2.5) 的健康影响的估计。我们使用环境效益绘图和分析计划社区版 (BenMAP-CE) 中的综合空气质量模型扩展 (CAMx) 区域模型以及将 CAMx 与近路模型 (HYCAMR) 相结合的混合模型 (HYCAMR) 中的浓度估计值，使用 PM2.5 暴露的不同分辨率空气质量估计值（包括死亡率、急诊室就诊、住院治疗和哮喘恶化）来计算估计的人类健康影响的差异。这提供了对因未考虑城市地区道路附近环境中的急剧浓度梯度而导致的健康影响的潜在低估的估计。精细估计捕获了道路附近浓度升高的情况，从而提高了对人口总体死亡率和发病率的估计。我们发现，在市中心，急诊就诊和死亡率的估计可能性有所增加。我们还比较了模型分辨率对不同人口群体健康影响估计的影响。在调查的地点中，我们发现康涅狄格州威利曼蒂克的人口群体之间的差异最大。我们的结果表明，使用区域空气污染物浓度可能会导致低估空气污染暴露对人类健康的影响。
As much of the population lives in close proximity to high-traffic roads, there is the potential for health impact assessments based on regional air quality modeling to underpredict health impacts. We compare the estimated health impacts from fine particulate matter (PM2.5) using local (0.04 x 0.04 km upscaled to census block group resolution) compared to regional (12 x 12 km resolution) modeled concentrations for three locations in Connecticut: Hartford, New Haven, and Willimantic. We use concentration estimates from the Comprehensive Air Quality Model with Extensions (CAMx) regional model and a hybrid model combining CAMx with a near road model (HYCAMR) in the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) to calculate the difference in estimated human health impacts using different resolution air quality estimates from PM2.5 exposure including mortality, emergency room visits, hospitalizations, and asthma exacerbation. This provides an estimate of the potential underprediction of health impacts resulting from not accounting for the sharp concentration gradients in near road environments in urban areas. The fine-scale estimates capture the elevated concentrations near the roadways leading to increased estimates of overall mortality and morbidity in the population. We find an increase in the estimated likelihood of emergency department visits and mortality in the urban core. We also compare the impact of model resolution on the health impact estimates for different demographic groups. Of the locations investigated, we see the largest differences between demographic groups in Willimantic, CT. Our results indicate that using regional air pollutant concentrations may lead to an underprediction of human health impacts from air pollution exposure.