Life Cycle Inventory and Impact Analysis Framework for Nonroad Construction Vehicles and Equipment Based Upon In-Use Measurements (TSE03-L)

施工车辆对国家排放有很大贡献；然而，它们的重要性很难用现有的工具来量化。主要假设是：(1)车辆/设备的能源使用和排放具有偶然性；(2)需要使用中的微尺度数据来量化这一点；(3)需要新的模型来解释这些事件，并找出改进的机会；(4)与车辆/设备的直接能源使用和排放相比，燃料循环的能源使用和排放不可忽略；(5)平均排放量存在较大的车辆间变异性和不确定性；(6)面对不确定性，需要一个新的框架来设计建筑实践，以防止排放和减少能源使用（从而产生成本节约）。目标是：(1)表征非道路施工车辆和设备在使用过程中每秒钟的排放和能源使用及其不确定性；(2)制定传统非道路施工车辆和设备的概率生命周期清单；(3)确定并推荐减少能源使用、排放和影响的方法。在任务1中，通过实地研究来补充可用的逐秒使用数据，以填补数据空白。在任务2中，开发了一个微观尺度的建筑在用车辆和设备排放和能源使用模型（CIVEM）。在任务3中开发了建筑设备的概率生命周期清单（LCI）模型。任务4中的详细案例研究演示了该方法的好处。研究结果已纳入建筑和空气质量课程，并分发给区域规划组织。这项工作对建造业、环境规划者和公众都有好处。该行业可以更准确地估计其对排放的贡献，通过修改现行做法确定减少能源使用（成本）和排放的机会，并为未来的监管做好更好的准备，减少因违规或罚款而承担的责任。随着最近对臭氧（氮氧化物和碳氢化合物是其前体）和微粒物质实施新的严格的环境空气质量标准，这些污染物的排放者将面临更大的压力，以防止或控制其排放。在这项工作中发展的改进排放估计的科学基础使区域和国家的有效空气质量战略成为可能。

Construction vehicles contribute substantially to national emissions; however, their importance is difficult to quantify with existing tools. Key hypotheses are that: (1) vehicle/equipment energy use and emissions are episodic in nature; (2) in-use microscale data are required to quantify this; (3) new models are needed to explain such episodes and to identify opportunities for improvements; (4) fuel cycle energy use and emissions are not negligible compared to direct energy use and emissions of the vehicles/equipment; (5) there is substantial inter-vehicle variability and uncertainty in average emissions; and (6) there is a need for a new framework by which to design construction practices in order to prevent emissions and reduce energy use (thereby producing cost savings) in the face of uncertainty. The objectives are to:(1)Characterize second-by-second in-use emissions and energy use of nonroad construction vehicles and equipment and their uncertainty;(2)Develop a probabilistic life cycle inventory of conventional nonroad construction vehicles and equipment;(3)Identify and recommend methods for reducing energy use, emissions, and impacts.In Task 1, available second-by-second in-use data are supplemented by a field study to fill data gaps. In Task 2, a micro-scale Construction In-use Vehicle and Equipment emissions and energy use Model (CIVEM) is developed. A probabilistic life cycle inventory (LCI) model for construction equipment is developed in Task 3. The benefits of the approach are demonstrated via a detailed case study in Task 4. Results of the research are integrated into construction and air quality courses and disseminated to regional planning organizations.This work benefits the construction industry, environmental planners, and the general public. The industry can more accurately estimate its contribution to emissions, identify opportunities for reductions in energy use (cost) and emissions via modifications to current practices, and better prepare for future regulation and reduce exposure to liability for violations or fines. With the recent implementation of new stringent ambient air quality standards for ozone (for which NOx and hydrocarbons are precursors) and particulate matter, there will be more pressure on emitters of these pollutants to prevent or control their emissions. The scientific basis for improved emissions estimation developed in this work enables effective air quality strategies regionally and nationally.