Moving beyond Fine Particle Mass: High-Spatial Resolution Exposure to Source-Resolved Atmospheric Particle Number and Chemical Mixing State
Moving beyond Fine Particle Mass: High-Spatial Resolution Exposure to Source-Resolved Atmospheric Particle Number and Chemical Mixing State
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DOI：
10.1289/ehp5311
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发表时间：
2020-01-01
影响因子：
10.4
通讯作者：
Presto, Albert A.
中科院分区：
文献类型：
--
作者：
Ye, Qing;Li, Hugh Z.;Presto, Albert A.
背景：大多数流行病学研究都使用基于质量的测量作为暴露替代物来解决大气颗粒物 (PM) 的健康影响。然而，这种方法忽略了单个大气颗粒的许多关键物理化学特性。这些特性控制着颗粒在人肺中的沉积以及可能的毒性；此外，它们可能比 PM 质量具有更大的空间变异性。 目的：本研究旨在量化人口稠密的城市地区单个颗粒的数量、大小、来源和化学混合状态的空间变异性。我们量化了暴露于这些详细颗粒特性的人群，并将其与基于质量的暴露进行了比较。方法：我们使用先进的单颗粒质谱仪进行移动采样，以测量宾夕法尼亚州匹兹堡源分辨 50-1,000 nm 颗粒的数量浓度和颗粒混合状态的空间变异性。我们建立了土地利用回归（LUR）模型来估计其空间模式，并将其与人口统计数据相结合来估计人口暴露情况。结果：城市内颗粒数量浓度的空间变异性比质量浓度大得多。交通和烹饪中新排放的颗粒导致颗粒数量的变化，但质量浓度主要由二次材料组成的老化背景颗粒主导。此外，暴露在大气颗粒物数量浓度升高的人们也会暴露于更多的外部混合颗粒物。 结论：我们先进的测量技术提供了一种新的暴露图像，解决了人口稠密的城市地区交通和烹饪颗粒物数量浓度的巨大城内空间异质性问题。与成分的批量测量相比，我们的结果提供了补充和更详细的视角。此外，考虑到颗粒混合状态对肺部颗粒沉积等性质的影响，化学混合状态的大空间梯度可能会显着：影响细颗粒物的健康效应。
BACKGROUND: Most epidemiological studies address health effects of atmospheric particulate matter (PM) using mass-based measurements as exposure surrogates. However, this approach ignores many critical physiochemical properties of individual atmospheric particles. These properties control the deposition of particles in the human lung and likely their toxicity; in addition, they likely have larger spatial variability than PM mass.OBJECTIVES: This study was designed to quantify the spatial variability in number, size, source, and chemical mixing state of individual particles in a populous urban area. We quantified the population exposure to these detailed particle properties and compared them to mass-based exposures.METHODS: We performed mobile sampling using an advanced single-particle mass spectrometer to measure the spatial variability of number concentration of source-resolved 50-1,000 nm particles and particle mixing state in Pittsburgh, Pennsylvania. We built land-use regression (LUR) models to estimate their spatial patterns and coupled them with demographic data to estimate population exposure.RESULTS: Particle number concentration had a much larger spatial variability than mass concentration within the city. Freshly emitted particles from traffic and cooking drive the variability in particle number, but mass concentrations are dominated by aged background particles composed of secondary materials. In addition, people exposed to elevated number concentrations of atmospheric particles are also exposed to more externally mixed particles.CONCLUSIONS: Our advanced measurement technique provides a new exposure picture that resolves the large infra-city spatial heterogeneity in traffic and cooking particle number concentrations in the populous urban area. Our results provide a complementary and more detailed perspective compared with bulk measurements of composition. In addition, given the influence of particle mixing state on properties such as particle deposition in the lung, the large spatial gradients of chemical mixing state may significantly: influence the health effects of fine PM.