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Network-Based Simulation of Air Pollution Emissions Associated with Truck Operations

机译：基于网络的卡车操作相关的空气污染排放模拟

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摘要

Estimating greenhouse gases (GHGs) and other emissions (especially diesel particulates) is an increasingly important basis for regional policy analysis. According to the EPA (2010a), the transportation sector contributed 27.2% of total GHG emissions in 2008, and 50% of these were from truck operations. This research focuses on estimating GHGs and other emissions (e.g., PM) from freight movements on roads in California as well as the concurrent effects of various mitigation scenarios. The study demonstrates that interregional freight flow data, along with FAF data can be important data sources for emission models. The results are useful not only for estimating GHGs and other emissions based on estimated freight flows, but also for evaluating area-specific environmental impacts of policy alternatives. The analysis shows that emissions impacts vary by study area as well as by policy. A policy alternative that has a significant impact in a specific area may have a trivial impact in a broader region. Also, an emissions reduction in one area may be because of emissions increases in another area. Therefore, it is important to simulate possible emissions impacts by applying a spatially disaggregated model to help decision makers weigh alternatives. The study can also be applied for analyzing environmental justice when the emission results are disaggregated into small areas.
机译：估算温室气体（GHG）和其他排放物（尤其是柴油颗粒物）是区域政策分析越来越重要的基础。根据EPA（2010a）的数据，运输部门在2008年占了温室气体总排放量的27.2％，其中50％来自卡车运营。这项研究的重点是估算加利福尼亚道路货运活动产生的温室气体和其他排放物（例如PM），以及各种缓解方案的同时影响。研究表明，区域间货运量数据以及FAF数据可以成为排放模型的重要数据来源。该结果不仅可用于根据估计的货运量估算温室气体和其他排放量，而且还可用于评估政策替代方案对特定地区的环境影响。分析表明，排放影响因研究领域和政策而异。在特定领域产生重大影响的政策替代方案可能在更广泛的地区产生微不足道的影响。同样，一个区域的排放减少可能是由于另一区域的排放增加。因此，重要的是通过应用空间分解模型来模拟可能的排放影响，以帮助决策者权衡替代方案。当排放结果分为小区域时，该研究还可用于分析环境公正性。

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