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COVID-19 对车辆 PM10 污染等级分布的影响:2020 年与 2018 年的比较。

The effect of COVID-19 on the distribution of PM10 pollution classes of vehicles: Comparison between 2020 and 2018.

机构信息

Scuola di Ingegneria, Università degli Studi della Basilicata, Viale dell'Ateneo Lucano, 10, 85100 Potenza, Italy.

Department of Astronautics, Electrical and Energy Engineering, Sapienza University of Rome, Via Eudossiana, 18, 00184 Rome, Italy.

出版信息

Sci Total Environ. 2022 Mar 10;811:152036. doi: 10.1016/j.scitotenv.2021.152036. Epub 2021 Dec 1.

DOI:10.1016/j.scitotenv.2021.152036
PMID:34863771
Abstract

A recent study by Pini et al. (2021), focusing on year 2018, demonstrated that different strategies should be considered in different Italian cities to mitigate the effects of PM10 pollution produced by circulating cars and commercial vehicles. The current study focuses on year 2020, considering the same ten Italian cities. This new study relies on the estimation of specific indices used to assess the size of the different circulating vehicle fleets (vehicle yearly mileage, diesel-fuel car and LCV fleet dimension, etc.) and their impact on PM10 pollution (Strength of Pollution). Results for 2020, severely affected by vehicular restrictions associated with COVID-19, indicate the need to adopt PM10 pollution reduction strategies for the various cities partially different from those identified earlier. For example, Euro 4 cars is the fleet having the highest impact on PM10 pollution in Rome (emitting 3,3 times more than Euro 6 vehicles), while in Milan the most polluting vehicles are Euro 0 cars (emitting 2 times more than Euro 6 vehicles). In Naples, Euro 0 cars emit 12,5 times more than Euro 6 vehicles. A careful look into the results also reveals that, for all considered cities, the three top fleets in terms of PM10 pollution always include Euro 4 or a higher Euro category fleet and a lower Euro category fleet (Euro 0 or Euro 3). These values were validated based on the use of pollution data from ground monitoring stations, which also allowed estimating the atmospheric mixing layer height. Results from the paper suggest that different incentivization policies have to be considered for the different considered cities. For example, in Naples the allocation of incentives should be ~60% towards new vehicles and ~40% towards recent used (i.e. second-hand) non-diesel vehicles, while in Florence it should be ~90% towards ECVs and ~10% towards recent used non-diesel vehicles.

摘要

最近,皮尼等人(2021 年)的一项研究聚焦于 2018 年,表明在不同的意大利城市应考虑不同的策略来减轻由循环汽车和商用车产生的 PM10 污染的影响。本研究聚焦于 2020 年,考虑了相同的 10 个意大利城市。本项新研究依赖于评估不同循环车辆车队(车辆年里程、柴油车和 LCV 车队规模等)规模及其对 PM10 污染影响(污染强度)的特定指标的估计。受与 COVID-19 相关的车辆限制严重影响的 2020 年结果表明,需要针对不同城市采取部分不同的 PM10 污染减排策略。例如,在罗马,对 PM10 污染影响最大的车队是 Euro 4 汽车(比 Euro 6 车辆多排放 3.3 倍),而在米兰,污染最严重的车辆是 Euro 0 汽车(比 Euro 6 车辆多排放 2 倍)。在那不勒斯,Euro 0 汽车比 Euro 6 车辆多排放 12.5 倍。仔细研究结果还表明,对于所有考虑的城市,PM10 污染排名前三的车队总是包括 Euro 4 或更高的 Euro 类别车队和较低的 Euro 类别车队(Euro 0 或 Euro 3)。这些值是基于使用地面监测站的污染数据验证的,这也允许估计大气混合层高度。该论文的结果表明,对于不同的考虑城市,必须考虑不同的激励政策。例如,在那不勒斯,激励措施的分配应该约 60%用于新车,约 40%用于最近使用的(即二手)非柴油车辆,而在佛罗伦萨,应该约 90%用于 ECV,约 10%用于最近使用的非柴油车辆。

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