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Sci Total Environ ; 811: 152036, 2022 Mar 10.
Article in English | MEDLINE | ID: covidwho-1550060

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.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , Cities , Environmental Monitoring , Humans , Particulate Matter/analysis , SARS-CoV-2 , Vehicle Emissions/analysis
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