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首页> 外文期刊>Atmospheric environment >Source apportionment of PM2.5 at multiple Northwest US sites: Assessing regional winter wood smoke impacts from residential wood combustion
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Source apportionment of PM2.5 at multiple Northwest US sites: Assessing regional winter wood smoke impacts from residential wood combustion

机译：美国西北部多个站点的PM2.5来源分配：评估住宅木材燃烧对区域冬季木材烟雾的影响

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Wood smoke from residential wood combustion is a significant source of elevated PM2.5 in many communities across the Northwest U.S. Accurate representation of residential wood combustion in source-oriented regional scale air quality models is challenging because of multiple uncertainties. As an alternative to source-oriented source apportionment, this work provides, through receptor-oriented source apportionment, an assessment of winter residential wood combustion impacts at multiple Northwest U.S. locations. Source apportionment was performed on chemically speciated PM2.5 from 19 monitoring sites using the Positive Matrix Factorization (PMF) receptor model. Each site was modeled independently, but a common data preparation and modeling protocol was used so that results were as comparable as possible across sites. Model solutions had from 4 to 8 PMF factors, depending on the site. PMF factors at each site were associated with a source classification (e.g., primary wood smoke), a dominant chemical composition (e.g., ammonium nitrate), or were some mixture. 15 different sources or chemical compositions were identified as contributing to PM2.5 across the 19 sites. The 6 most common were; aged wood smoke and secondary organic carbon, motor vehicles, primary wood smoke, ammonium nitrate, ammonium sulfate, and fugitive dust. Wood smoke was identified at every site, with both aged and primary wood smoke identified at most sites. Wood smoke contributions to PM2.5 were averaged for the two winter months of December and January, the months when wood smoke in the Northwest U.S. is mainly from residential wood combustion. The total contribution of residential wood combustion, that from primary plus aged smoke, ranged from 11.4% to 92.7% of average December and January PM2.5 depending on the site, with the highest percent contributions occurring in smaller towns that have fewer expected sources of winter PM2.5. Receptor modeling at multiple sites, such as that conducted in this work, provided some significant advantages over modeling a single or small number of sites. Analysis at multiple sites allowed common factor chemical compositions to be identified, making it easier to evaluate when a PMF factor at a particular site represents a mix of sources versus a single source. The identification of similar PMF factors across multiple sites also allowed average chemical profiles to be established for the 6 the most commonly identified PM2.5 sources or compositions in this study. These average profiles have the potential to be used as source profile inputs in future Chemical Mass Balance receptor modeling, when a limited number of samples may restrict the ability to conduct PMF receptor modeling, or when the availability of local source profiles is limited. Receptor modeling results spanning a range of community sizes and source compositions, as in this study, could be used to evaluate and improve the representation of wood smoke and other specific sources in source-oriented regional scale air quality models by providing an independent source impact assessment. Published by Elsevier Ltd.
机译：在美国西北部的许多社区中，居民用木材燃烧产生的木烟是PM2.5升高的重要来源。由于存在许多不确定性，在以源为导向的区域空气质量模型中准确表示住宅用木材燃烧是一项挑战。作为面向源的源分配的替代方法，这项工作通过面向受体的源分配提供了对美国西北部多个地点的冬季住宅木材燃烧影响的评估。使用正矩阵分解（PMF）受体模型对来自19个监测点的化学特定PM2.5进行了源分配。每个站点都是独立建模的，但是使用了通用的数据准备和建模协议，因此跨站点的结果尽可能具有可比性。模型解决方案的PMF因子为4到8，具体取决于站点。每个站点的PMF因子都与来源分类（例如，主要的木烟），主要的化学成分（例如，硝酸铵）或某种混合物相关。在这19个站点中，发现了15种不同的来源或化学成分对PM2.5的贡献。最常见的6种是：老化的木烟和二次有机碳，机动车，木柴的烟，硝酸铵，硫酸铵和扬尘。在每个站点都可以识别出木烟，在大多数站点都可以识别出老化的和原始的木烟。在12月和1月的两个冬季月份，木材烟雾对PM2.5的贡献是平均的，这两个月份在美国西北部的木材烟雾主要来自住宅木材燃烧。取决于地点，住宅用木燃烧的总贡献（包括主要烟雾和老烟）占平均12月和1月PM2.5的11.4％至92.7％，具体取决于地点，其中贡献百分比最高的是较小城镇，其预期来源较少。冬季PM2.5。与对单个或少量站点进行建模相比，在多个站点进行的受体建模（例如在本工作中进行的建模）具有一些明显的优势。通过在多个位置进行分析，可以识别出公共因子的化学成分，从而更容易评估特定位置的PMF因子代表的是混合污染源还是单一污染源。跨多个站点的类似PMF因子的鉴定还允许建立本研究中6种最常鉴定的PM2.5来源或组成的平均化学谱。当有限数量的样本可能会限制进行PMF受体建模的能力时，或者当本地源轮廓的可用性受到限制时，这些平均轮廓可能会在将来的“化学物质平衡”受体建模中用作源轮廓输入。如本研究中所述，涵盖范围广泛的社区规模和排放源组成的受体建模结果可用于通过提供独立的排放源影响评估来评估和改善面向排放源的区域尺度空气质量模型中木烟和其他特定排放源的表示。由Elsevier Ltd.发布

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