Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh Pennsylvania 15213, USA.
Environ Sci Technol. 2009 Dec 15;43(24):9439-44. doi: 10.1021/es901683j.
Hazardous air pollutants or air toxics are pollutants that are known or suspected to cause serious health effects. This paper presents a methodology to quantify source contributions to air toxics health risks. First, a linear, no-threshold risk model was used to identify gas-phase organic air toxics that contribute significantly to cancer risks. Next, Positive Matrix Factorization (PMF) was performed on high time-resolved measurements of these air toxics, and the additive cancer risks associated with each factor was determined. Finally, the PMF factors were linked to sources and source classes (mobile, nonmobile, secondary/background) using a combination of meteorological data and comparisons with published source profiles. The analysis was performed using data from three sites in Pittsburgh, Pennsylvania: a downtown site near a heavily traveled bus route, a residential site adjacent to a heavily industrialized area, and an urban background site. At all three sites emissions from nonmobile sources were the dominant contributors to the cancer risks from air toxics included in the PMF model, including benzene and other air toxics often associated with mobile source emissions. Emissions from both large industrial sources, such as coke works and chemical facilities, and smaller point sources, such as dry cleaners, contributed significantly to the cancer risks at all sites. This method can provide insight for decision makers to prioritize sources for risk reduction.
危害空气污染物或空气毒物是已知或怀疑会导致严重健康影响的污染物。本文提出了一种量化空气毒物健康风险源贡献的方法。首先，使用线性无阈值风险模型来识别对癌症风险有重大贡献的气相有机空气毒物。接下来，对这些空气毒物进行高时间分辨率测量的正矩阵因子化 (PMF)，并确定与每个因子相关的附加癌症风险。最后，使用气象数据和与已发表源谱的比较，将 PMF 因子与源和源类（移动源、非移动源、二次/背景）联系起来。该分析使用宾夕法尼亚州匹兹堡三个地点的数据进行：一个靠近交通繁忙的公共汽车路线的市中心地点，一个毗邻高度工业化地区的住宅地点，以及一个城市背景地点。在所有三个地点，非移动源的排放是 PMF 模型中包含的空气毒物致癌风险的主要贡献者，包括苯和其他通常与移动源排放相关的空气毒物。大型工业源（如炼焦厂和化工厂）和较小的点源（如干洗店）的排放都对所有地点的癌症风险有重大贡献。这种方法可以为决策者提供优先考虑减少风险的来源的见解。
