SMART Infrastructure Facility, University of Wollongong, Wollongong, NSW, Australia.
SMART Infrastructure Facility, University of Wollongong, Wollongong, NSW, Australia.
Environ Pollut. 2018 Oct;241:775-786. doi: 10.1016/j.envpol.2018.06.019. Epub 2018 Jun 13.
Traffic emissions are a complex and variable cocktail of toxic chemicals. They are the major source of atmospheric pollution in the parts of cities where people live, commute and work. Reducing exposure requires information about the distribution and nature of emissions. Spatially and temporally detailed data are required, because both the rate of production and the composition of emissions vary significantly with time of day and with local changes in wind, traffic composition and flow. Increasing computer processing power means that models can accept highly detailed inputs of fleet, fuels and road networks. The state of the science models can simulate the behaviour and emissions of all the individual vehicles on a road network, with resolution of a second and tens of metres. The chemistry of the simulated emissions is also highly resolved, due to consideration of multiple engine processes, fuel evaporation and tyre wear. Good results can be achieved with both commercially available and open source models. The extent of a simulation is usually limited by processing capacity; the accuracy by the quality of traffic data. Recent studies have generated real time, detailed emissions data by using inputs from novel traffic sensing technologies and data from intelligent traffic systems (ITS). Increasingly, detailed pollution data is being combined with spatially resolved demographic or epidemiological data for targeted risk analyses.
交通排放物是一种复杂且多变的有毒化学物质混合物。它们是城市中人们居住、通勤和工作的区域大气污染的主要来源。减少接触需要有关排放物分布和性质的信息。需要具有空间和时间细节的数据，因为排放物的产生速率和组成随时间和当地的风向、交通组成和流量的变化而显著变化。计算机处理能力的提高意味着模型可以接受车队、燃料和道路网络的高度详细输入。科学模型的状态可以模拟道路网络上所有单个车辆的行为和排放，分辨率为秒和数十米。由于考虑了多个发动机过程、燃料蒸发和轮胎磨损，模拟排放物的化学性质也具有高度分辨率。商业上可用的和开源模型都可以取得良好的结果。模拟的范围通常受到处理能力的限制，而准确性则受到交通数据质量的限制。最近的研究通过使用新型交通感应技术的输入和智能交通系统（ITS）的数据生成了实时、详细的排放数据。越来越多的详细污染数据与空间分辨率的人口统计学或流行病学数据相结合，用于有针对性的风险分析。
