A hybrid modeling framework to estimate pollutant concentrations and exposures in near road environments
A hybrid modeling framework to estimate pollutant concentrations and exposures in near road environments
复制标题
用于估计道路附近环境中污染物浓度和暴露的混合建模框架
DOI：
10.1016/j.scitotenv.2019.01.218
复制
发表时间：
2019
影响因子：
9.8
通讯作者：
Wagstrom, Kristina
中科院分区：
文献类型：
--
作者：
Parvez, Fatema;Wagstrom, Kristina
与交通有关的空气污染是对大多数城市人口构成挑战的主要地方污染源之一。现有的空气质量模拟方法只能估计区域或区域尺度上的空气污染物浓度，但不能同时从区域和区域尺度的区域源和局部源的组合中有效地估计空气污染物的浓度。这项研究描述了一个混合模拟框架HYCAMR，它结合了区域模式CAMX和局地尺度扩散模式R-LINE，在高时间(小时)和空间(40 m)分辨率下估计初级和次生物种的浓度。HYCAMR利用CAMX和颗粒物来源分配技术(PSAT)工具提供的所有化学和物理过程来估计道路和非道路排放源的浓度。HYCAMR使用R-LINE，以高分辨率估计来自道路排放源、主要道路和次要道路的归一化污染物质量扩散。应用R线，每月一天，利用日均气象，以较低的计算成本产生季节分辨的空间弥散廓线。将R线空间弥散分布与CAMX浓度估计值相结合，可在高空间和时间分辨率上估计一系列污染物的组合浓度。在康涅狄格州的三个主要城市，HYCAMR在NOx、PM2.5和元素碳(EC)浓度方面显示出强烈的时间和季节变化。这项研究评估了HYCAMR 2011年对NO2和PM2.5的估计，并参考了两个来源：基于卫星的粗略分辨率估计和人口普查区组分辨率的回归模型估计。在这项评价中，HYCAMR与区域CAMX估计相比，显示出与土地利用回归模型更好的一致性，与基于卫星的估计混合一致。
Traffic related air pollution is one of the major local sources of pollution challenging most urban populations. Current air quality modeling approaches can estimate the concentrations of air pollutants on either regional or local scales but cannot effectively estimate concentrations from the combination of regional and local sources at both local and regional scales simultaneously. This study describes a hybrid modeling framework, HYCAMR, combining a regional model, CAMx, and a local-scale dispersion model, R-LINE, to estimate concentrations of both primary and secondary species at high temporal (hourly) and spatial (40 m) resolution. HYCAMR utilizes all the chemical and physical processes available in CAMx and the Particulate Matter Source Apportionment Technology (PSAT) tool to estimate concentrations from both onroad and nonroad emission sources. HYCAMR employs R-LINE, to estimate the normalized dispersion of pollutant mass from onroad emission sources, from primary and secondary roads, at high resolution. Applying R-LINE for one day per month using average daily meteorology yields seasonally-resolved spatial dispersion profiles at low computational cost. Combining the R-LINE spatial dispersion profile with CAMx concentration estimates yields an estimate of the combined concentrations for a range of pollutants at high spatial and temporal resolution. In three major cities in Connecticut, HYCAMR shows strong temporal and seasonal variability in NOx, PM2.5, and elemental carbon (EC) concentrations. This study evaluates HYCAMR year 2011 estimates of NO2and PM2.5against two sources: satellite-based estimates at coarse resolution and regression model estimates at census block group resolution. In this evaluation, HYCAMR demonstrates improved agreement with the land-use regression modeling and mixed agreement with satellite-based estimates when compared to the regional CAMx estimates.