This paper presents the focus on emission estimates in the Italian Regions of the Po-basin obtained by the development of a common air pollutant emission dataset on the Po-basin and Slovenia foreseen in the project LIFE PREPAIR (https://www.lifeprepair.eu/). The objective is to update emission inventories developed by the environmental protection agencies and regions of Lombar-

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:The positive health effects of systematic cycling are weighted against the negative effects due to higher pollutant inhalation in the actual case of the city of Milan in northern Italy. The paper first evaluates the actual use of bikes in the city, and then considers why and how much such an active mobility style can be expanded. Two models are used to compare the outcome of cycling on the specific population sample with the equivalent path travelled by car. The first model computes the long term effects of the physical activity, and the second evaluates the exacerbation of some relevant diseases due to the exposure to high levels of pollutants, in the case at hand, mainly particulate matter with diameter smaller than 10 µm (PM 10 ). According to these two models, the overall balance for public health is always in favour of systematic biking. Even the current level of biking, low in comparison to other European cities, allows a considerable economic advantage on the order of tens of millions euros per year. This may increase to hundreds of millions if the biking level of more bike-friendly cities is reached. Despite being much less relevant from the economic viewpoint, the study also estimates the reduction of pollution and greenhouse gas emissions corresponding to the assumed biking levels.

This paper illustrates the study carried out by ARPA Lombardia to quantify the variation in daily emissions of the main pollutants and their impacts on air quality in Lombardy during the anti-COVID-19 lockdown between the end of February and the end of May 2020. A methodology for emission estimates was developed over Lombardy for this purpose and later was extended to larger areas: the Po-basin, (LIFE PREPAIR 2020) and the entire Italy (PULVIRUS 2021). In this study, the daily emissions estimates were derived by combining data from air emission inventory of Lombardy and a set of indicators that allowed to update the estimates and describe the temporal and spatial variations of the emission sources. The calculation of emission variation was conducted for all the main pollutants (PM 10 , NH 3 , NO x , SO 2 , NMVOC) and the greenhouse gases; then, the impact on air quality concentrations was simulated by the chemical and transport model FARM, that also allows to track secondary particulate and its variability in time and space on the basis of nonlinear processes and weather conditions. The estimated emission reduction, compared to the expected average value in the absence of anti-COVID-19 measures, daily varies depending on pollutants and is mainly affected by reductions in road traffic emissions and an estimated increase in domestic heating emissions. Simulations confirm strong reductions of NO 2 atmospheric average concentrations, slightly variations of PM 10 averages and a potential growth of tropospheric ozone.