Lippmann Morton
New York University School of Medicine, Tuxedo, New York 10987, USA.
J Expo Sci Environ Epidemiol. 2009 Mar;19(3):235-47. doi: 10.1038/jes.2008.65. Epub 2008 Oct 29.
One of the most urgent needs for future progress in reducing the substantial impacts of ambient air particulate matter (PM) on human health is to determine which of its components are having the greatest effects. The EPA's Speciation Trends Network (STN) has been operating since 2000. It generates 24-h average fine PM component concentrations for sulfate and nitrate ions, elemental and organic carbon (EC/OC), and many elements on an every third or sixth day basis for one or a few sites in most large US cities. To date, a small number of research studies, summarized in this paper, have used available STN and other supplemental data to identify and quantify the influences of specific components or source-related mixtures on measures of health-related impacts. These pioneering studies have demonstrated the potential utility of using such data in analyses that can provide a sound basis for guiding future research and control activities on those PM sources that have the greatest public health relevance. Unfortunately, the STN data collection methods used are expensive, and data have therefore been too sparse for studies of short-term health effects, where semi-continuous data, or at least daily 24-h concentration data are needed, as well as for regional concentration distributions that are needed for definitive analyses. Furthermore, because of cost considerations, there is virtually no prospect of collecting the data needed by the health researchers for more definitive analyses as long as there is continued reliance on current FRM sampling and analysis methodologies. At the second EPA-HEI Workshop on "Air Quality and Health Researchers Working Together" in RTP, NC on 16 and 17 April 2008, many participants concluded that it was both desirable, and possibly technically and economically feasible, to re-equip the STN sites with an automated system of semi-continuous monitors for sulfate, nitrate, EC, OC, and semi-continuous multistage PM samplers for non-volatile elements, providing continuous records of PM components with an averaging time of approximately 6 h for both thoracic coarse mode PM, fine PM, and perhaps ultrafine PM as well. The availability of such data would greatly accelerate the accumulation of knowledge on PM component exposure-response relationships that would provide a sound basis more targeted air quality standards and pollution control measures.
为了减少环境空气中颗粒物（PM）对人类健康的重大影响，未来取得进展的最迫切需求之一是确定其哪些成分产生的影响最大。美国环境保护局（EPA）的物种趋势网络（STN）自2000年以来一直在运行。它每三天或六天为美国大多数大城市的一个或几个监测点生成一次24小时平均细颗粒物成分浓度数据，包括硫酸根和硝酸根离子、元素碳和有机碳（EC/OC）以及许多元素。迄今为止，本文总结的少数研究已经利用现有的STN数据和其他补充数据来识别和量化特定成分或与源相关的混合物对健康相关影响指标的影响。这些开创性研究已经证明了在分析中使用此类数据的潜在效用，这些分析可以为指导未来针对那些对公众健康最具相关性的PM源的研究和控制活动提供坚实基础。不幸的是，所使用的STN数据收集方法成本高昂，因此数据对于短期健康影响研究来说过于稀疏，短期健康影响研究需要半连续数据，或者至少是每日24小时浓度数据，同时对于确定性分析所需的区域浓度分布研究也是如此。此外，出于成本考虑，只要继续依赖当前的联邦参考方法（FRM）采样和分析方法，就几乎没有可能收集健康研究人员进行更确定性分析所需的数据。在2008年4月16日和17日于北卡罗来纳州三角研究园（RTP）举行的第二届EPA - 健康效应研究所（HEI）“空气质量与健康研究人员合作”研讨会上，许多与会者得出结论，用一个用于硫酸根、硝酸根、EC、OC的半连续监测自动系统以及用于非挥发性元素的半连续多级PM采样器重新装备STN监测点是既可取的，而且在技术和经济上可能也是可行的，这样可以提供PM成分的连续记录，对于胸段粗模式PM、细PM以及可能的超细PM，平均时间约为6小时。此类数据的可得性将极大地加速关于PM成分暴露 - 反应关系知识的积累，这将为更具针对性的空气质量标准和污染控制措施提供坚实基础。
