Department of Civil and Environmental Engineering, University of California, One Shields Avenue, Davis, California 95616, United States.
Environ Sci Technol. 2011 Jul 1;45(13):5846-52. doi: 10.1021/es103660r. Epub 2011 May 24.
Estimates of fuel use and air pollutant emissions from freight rail currently rely highly on aggregate methods and largely obsolete data which offer little insight into contemporary air quality problems. Because the freight industry is for the most part privately held and data are closely guarded for competitive reasons, the challenge is to produce robust estimates using current reporting requirements, while accurately portraying the spatial nature of freight rail impacts. This research presents a new spatially resolved model for estimating air pollutant emissions (hydrocarbons, carbon monoxide, nitrogen oxides, particulate matter less than 10 μm in diameter, sulfur dioxide, and carbon dioxide) from locomotives. Emission estimates are based on track segment level data including track grade, type of train traffic (bulk, intermodal, or manifest) and the local locomotive fleet (EPA tier certification level and fuel efficiency). We model the California Class I freight rail system and compare our results to regional estimates from the California Air Resources Board and to estimates following U.S. Environmental Protection Agency guidance. We find that our results vary considerably from the other methods depending on the region or corridor analyzed. We also find large differences in fuel and emission intensity for individual rail corridors.
目前，货运铁路的燃料使用和空气污染物排放估算高度依赖于综合方法和基本过时的数据，这些方法和数据几乎无法深入了解当代的空气质量问题。由于货运行业基本上是私营的，而且出于竞争原因，数据受到严密保护，因此，挑战在于使用当前的报告要求来生成稳健的估算，同时准确描述货运铁路影响的空间性质。本研究提出了一种新的、空间分辨率高的模型，用于估算机车产生的空气污染物排放（碳氢化合物、一氧化碳、氮氧化物、直径小于 10μm 的颗粒物、二氧化硫和二氧化碳）。排放估算基于包括轨道坡度、列车交通类型（散货、多式联运或直达）和当地机车车队（美国环保署的 tier 认证级别和燃油效率）在内的轨道段级别数据。我们对加州一级货运铁路系统进行建模，并将我们的结果与加州空气资源委员会的区域估算以及美国环境保护署指南的估算进行比较。我们发现，根据分析的区域或走廊的不同，我们的结果与其他方法有很大差异。我们还发现，个别铁路走廊的燃料和排放强度存在很大差异。
