Abstract
The current socio-economic and political scenario is posing serious challenges to energy usage, mobility, residential and industrial activities, which may impact local emission patterns, fossil fuel vs alternative fuels usage and air quality in unknown ways. On top of this, winter 2022-23 is being exceptionally warm across the European continent.The investigation of the interactions between air quality, meteorological factors and emissions sources at high spatio-temporal resolution plays a crucial role to detect areas and periods characterized by critical conditions, especially in complex urban environments. Data at such fine resolution can today be obtained through dense low-cost sensor networks integrating sparse official air quality stations. This research aims to assess meteorological forcing, emission proxies (i.e., population density, CO2 local enhancement, land-use) and particulate matter concentrations (PMs) for the last three winter seasons (2020-2023) characterized by contrasting conditions. The study was focused on the Lucca plain (central Italy), an area characterized by heterogeneous emission sources and classified among the most polluted in the region. Sixteen low-cost stations (“AirQino”), equipped with high-frequency sensors to detect PM10, PM2.5, air-temperature, relative humidity (RH), and CO2 concentration were installed on an area spanning approximately 10 x 20 km. Local land use surrounding the measurement stations was obtained from the Corine Land Cover. Mixing Layer Height (Hmix) and wind data were obtained from a WRF-CALMET coupled model. Population density was computed with demographic data from the Global Human Settlement database. For CO2 data, the nocturnal enhancement normalized by wind speed with respect the minimum midday values was used as an emission proxy (ΔCO2). Population density and land use including fractions of residential, industrial, and agricultural areas were computed in a 1-km radius surrounding each station.Preliminary comparisons between winter 2021/2022 and 2022/23 were performed to assess the effects of energy crisis and climatic conditions on air-quality. Different multivariate regression models were developed to investigate the inference between Hmix, air-temperature, RH, ΔCO2, population density, land use and PMs concentrations.Most recent analysis shows a consistent and robust positive air temperature anomaly in November-December 2022 vs 2021 (+ 1.25 °C). CO2 enhancements were on average 20% lower (-19.0 to +3.7 ppm in 2022 vs 2021 respectively) suggesting a relevant emission reduction occurring at the landscape scale. However, these reductions did not always translate into PM10 and PM2.5 reductions and air quality improvements. Among the 16 stations, 11 exhibited a decrease in PM2.5 concentration (-21.60 % on average) and only 9 in PM10 (-21.55 % on average). The locations where air quality did not improve or was even worse this year are characterized by the lowest population density and lowest presence of residential neighborhoods, being mostly in rural or rural/industrial contexts. This suggests that alternative fuels such as wood biomass are likely replacing natural gas in peri-urban areas for domestic heating, generating a negative impact on air quality that could be much worst when usual lower temperature conditions will be met. A complete multivariate analysis to confirm these patterns will be presented.
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