A multicity study of wintertime inversions and acute cardiorespiratory health events in the western U.S.

摘要 确定空气污染源对于制定保护人类健康的缓解战略至关重要。许多城市 在美国西部，PM2.5短期升高，由异质PM2.5混合物组成， 季节性变化。PM2.5是主要PM2.5（直接从源排放的气溶胶）和次要PM2.5的混合物 （气溶胶在大气中形成的反应涉及主要污染物，前体排放物和大气 过程）。虽然源解析模型可用于追踪污染物的排放源，但所有 传统的源解析模型有一个共同的局限性：只对主要的PM2.5进行了解析。 在西部较冷的月份，气象因素对空气污染浓度的上升起着重要作用。 美国在典型的气象条件下，气温随着海拔的升高而降低。在反转期间， 相反的关系-温暖的空气被保持在较冷的空气之上-导致环境空气污染物，如PM2.5，被捕获 接近地面。包括1952年伦敦“大烟雾”在内的几次重大历史空气污染事件都是由 通过倒置。在美国西部寒冷的月份里，PM2.5总量的80%以上是二次污染， PM2.5。为了制定有效的法规来保护这些城市的人类健康，空气质量管理人员必须了解 二次PM2.5的来源。由于在较冷的月份，二次PM2.5占主导地位， 分配模式无法可靠地确定哪些排放源应作为缓解战略的优先事项。 我们建议通过开发一个创新的空气质量模型来解决这个公共卫生问题， 原发性和继发性PM2.5，并使用该模型的估计在一个大型的12个城市的流行病学研究。 我们将开发一种新的数据融合方法，将空气质量模型结果与PM2.5观测结果相结合， 为主要和次要PM2.5物种创建季节性、特定位置的源概况。这些新来源 将在多年源分配模型中使用剖面，以估计 博伊西、湖城普罗沃、奥格登、丹佛、里诺、拉斯维加斯、萨克拉门托、弗雷斯诺、莫德斯托、 贝克斯菲尔德和维萨利亚。来自这些城市的急诊室就诊数据将用于估计 PM2.5源浓度估计值与心肺急诊就诊之间的差异。 我们的项目直接解决了现有源解析方法的主要局限性， 二次PM2.5的分配方法。我们的多城市流行病学分析将通过以下方式为文献做出独特贡献： 提供针对具体来源的健康关联，全面解释原发性和继发性PM2.5 从一个给定的来源。我们专注于美国西部城市PM2.5的重大公共卫生问题， 逆温和伴随的PM2.5峰值，但我们的新的源解析方法可以很容易地应用 其他地区和研究。我们的研究结果将对空气质量和公共卫生产生直接影响 我们的工作是向利益相关者提供信息，为政策制定提供信息，以减少高污染天数并保护公众健康。

ABSTRACT Identifying air pollution sources is critical for developing mitigation strategies to protect human health. Many cities in the western United States experience elevated short-term PM2.5, composed of heterogeneous PM2.5 mixtures that vary seasonally. PM2.5 is a mixture of primary PM2.5 (aerosols emitted directly from a source) and secondary PM2.5 (aerosols formed in the atmosphere from reactions involving primary pollutants, precursor emissions, and atmospheric processes). Although source apportionment models can be applied to trace pollutants back to their emission sources, all conventional source apportionment models share a common limitation: only the primary PM2.5 is apportioned. Meteorology plays a significant role in elevated air pollution concentrations during colder months in the western U.S. Under typical meteorological conditions, temperature decreases as altitude increases. During an inversion, this relationship is inverted – warm air is held above cooler air – causing ambient air pollutants, such as PM2.5, to be trapped near ground level. Several major historical air pollution events, including the 1952 London “Great Smog,” were caused by inversions. During colder months in the western U.S., it is common for over 80% of the total PM2.5 to be secondary PM2.5. To create effective regulations to protect human health in these cities, air quality managers must understand the origin of secondary PM2.5. Given the predominance of secondary PM2.5 during colder months, existing source apportionment models cannot reliably identify which source(s) should be prioritized for mitigation strategies. We propose to address this public health problem by developing an innovative air quality model that apportions both primary and secondary PM2.5, and to use the estimates from this model in a large 12-city epidemiologic study. We will develop a new data fusion method that combines air quality model results and speciated PM2.5 observations to create seasonal, location-specific source profiles for both primary and secondary PM2.5 species. These new source profiles will be used in a multi-year source apportionment model to estimate daily PM2.5 source concentrations during colder months for Boise, Salt Lake City, Provo, Ogden, Denver, Reno, Las Vegas, Sacramento, Fresno, Modesto, Bakersfield, and Visalia. Emergency department visit data from these cities will be used to estimate associations between the PM2.5 source concentration estimates and cardiorespiratory emergency visits. Our project directly addresses major limitations in existing source apportionment approaches by developing methods to apportion secondary PM2.5. Our multicity epidemiologic analyses will uniquely contribute to the literature by providing source-specific health associations that comprehensively account for both primary and secondary PM2.5 originating from a given source. We focus on the significant public health problem of PM2.5 in western U.S. cities prone to inversions and accompanying PM2.5 spikes, but our novel source apportionment methodologies can be readily applied to other regions and studies. Findings from our study will be of immediate interest to air quality and public health stakeholders, informing policy development to reduce high pollution days and protect public health.