Impact of NO x and NH 3 Emission Reduction on Particulate Matter across Po Valley: A LIFE-IP-PREPAIR Study.

Autor: Veratti, Giorgio, Stortini, Michele, Amorati, Roberta, Bressan, Lidia, Giovannini, Giulia, Bande, Stefano, Bissardella, Francesca, Ghigo, Stefania, Angelino, Elisabetta, Colombo, Loris, Fossati, Giuseppe, Malvestiti, Giulia, Marongiu, Alessandro, Dalla Fontana, Alberto, Intini, Barbara, Pillon, Silvia
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Zdroj: Atmosphere; May2023, Vol. 14 Issue 5, p762, 25p
Abstrakt: Air quality in Europe continues to remain poor in many areas, with regulation limits often exceeded by many countries. The EU Life-IP PREPAIR Project, involving administrations and environmental protection agencies of eight regions and three municipalities in Northern Italy and Slovenia, was designed to support the implementation of the regional air quality plans in the Po Valley, one of the most critical areas in Europe in terms of pollution levels. In this study, four air quality modelling systems, based on three chemical transport models (CHIMERE, FARM and CAMx) were applied over the Po Valley to assess the sensitivity of PM2.5 concentrations to NOx and NH3 emission reductions. These two precursors were reduced (individually and simultaneously) from 25% up to 75% for a total of 10 scenarios, aimed at identifying the most efficient emission reduction strategies and to assess the non-linear response of PM2.5 concentrations to precursor changes. The multi-model analysis shows that reductions across multiple emission sectors are necessary to achieve optimal results. In addition, the analysis of non-linearities revealed that during the cold season, the efficiency of PM2.5 abatement tends to increase by increasing the emission reductions, while during summertime, the same efficiency remains almost constant, or slightly decreases towards higher reduction strengths. Since the concentrations of PM2.5 are greater in winter than in summer, it is reasonable to infer that significant emission reductions should be planned to maximise reduction effectiveness. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index