School of Environment and Civil Engineering, Dongguan University of Technology, Dongguan, Guangdong 523808, China; Guangdong Provincial Key Lab of Green Chemical Product Technology, South China University of Technology, Guangzhou 510640, China.
School of Environment and Civil Engineering, Dongguan University of Technology, Dongguan, Guangdong 523808, China.
Sci Total Environ. 2019 Jun 10;668:74-83. doi: 10.1016/j.scitotenv.2019.03.019. Epub 2019 Mar 3.
Urban haze has become a severe pollution problem in China. Vehicle emission may be a key factor leading to haze pollution in China's megacities due to the rapid growth of vehicles and corresponding energy consumption. Until now, the haze formation mechanisms in China remain highly uncertain, which have not yet been understood quantitatively. In this work, an efficient modified haze causation system related to vehicle emissions is developed for reliable quantified risk assessment of urban haze in China's megacities. And fuzzy mathematical theory combining with fault tree approach is investigated and employed as the analysis tool/strategy. To provide objective basis for the reliability and practicability of the quantitative assessment results, an efficient data extraction strategy and relevant mathematical models are proposed and developed for the probability determination of basic risk events. Besides, the probability uncertainty of basic risk events during the data extraction is taken into account, where the occurrence probability of basic events is described as triangular fuzzy number, the quantitative analysis results will be more reliable and more tally with the actual situation. After the haze causation system related to vehicle emissions is established along with the identification of all critical risk factors related to vehicle emissions, Beijing and Tianjin are taken as illustrated case studies for the quantified risk assessment of haze causation system related to vehicle emissions in China. All the analysis results demonstrated that this work may provide a useful and effective tool/strategy for efficient quantified risk assessment and risk management of haze causation system relate to vehicle emission in China.
城市霾污染在中国已成为一个严峻的问题。由于车辆的快速增长和相应的能源消耗，车辆排放可能是导致中国特大城市霾污染的一个关键因素。到目前为止，中国霾形成机制仍高度不确定，尚未得到定量理解。在这项工作中，开发了一个有效的改进的与车辆排放有关的霾成因系统，用于可靠地量化评估中国特大城市的城市霾风险。并研究和采用了模糊数学理论与故障树方法相结合作为分析工具/策略。为了提供定量评估结果的可靠性和实用性的客观依据，提出并开发了一种有效的数据提取策略和相关的数学模型，用于确定基本风险事件的概率。此外，还考虑了数据提取过程中基本风险事件的概率不确定性，其中基本事件的发生概率被描述为三角模糊数，定量分析结果将更加可靠，更符合实际情况。在建立了与车辆排放有关的霾成因系统并确定了与车辆排放有关的所有关键风险因素之后，以北京和天津为例，对与车辆排放有关的霾成因系统的量化风险评估进行了实例研究。所有的分析结果表明，这项工作可为中国与车辆排放有关的霾成因系统的有效量化风险评估和风险管理提供有用且有效的工具/策略。
