ABSTRACT
To contain the spread of the COVID-19 pandemic, several governments declared lockdowns. The reduction of human activities linked with mobility restriction caused an unprecedented drop in emissions, especially in the road transport sector. This study aims to evaluate the uncertainty of short-term health effects (i.e. avoided hospital admission (AHA) associated to NO2 ambient concentrations) derived from the change in air quality (AQ) due to lockdown. The CAMx-WRF modelling suite is applied for a series of nested domains using EMEP and Lombardy region emission inventories. The health impact analysis is focused on a 70 × 70 km domain centered on Milan metropolitan area with 1-km resolution, from February 24th 2020 to April 30th 2020. Two simulations, Business as usual (BAU) and lockdown scenario (LOCK), are carried out and results are compared with air quality monitoring data to assess the model uncertainty. Health effects for the difference between LOCK and BAU simulation are evaluated for NO2 following the WHO Health risks of air pollution in Europe (HRAPIE) project recommendation. The combined effect of both modelled concentrations and exposure–response functions (ERF) on the uncertainty of calculated AHA is then evaluated for different air quality station types. We find that the ERF is the major cause for uncertainty for Urban and suburban AQ stations, measured as the size of the 95% confidence interval (CI) of the estimated number of AHA. The AQ uncertainty of the BAU scenario has a lower impact on AHA CI than for the LOCK scenario. When comparing results according to station type, the lowest AHA uncertainty is obtained for urban background stations while the highest for rural background stations. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The Lombardy region was one of the European areas earliest affected by the Coronavirus in 2020, as well as the first area where lockdown measures were enforced. This study aims to investigate the impact of lockdown on air quality for this region of Northern Italy, analyzing a 2 months period. In this work, CAMx and WRF models were used in order to estimate NO2, PM10 and PM2.5 concentrations both during the lockdown and in a business as usual (BAU) situation. NO2, PM10 and PM2.5 concentrations both during the lockdown and in a business as usual (BAU) situation. Model simulations considered two lockdown scenarios, based on different approaches for the assessment of road traffic emissions reduction, in comparison with BAU scenario. The first scenario used emission reduction coefficients computed by the local agency for environmental protection, while the second was based on mobile phone data. We aim to understand whether using these latter data as a proxy could be a promising method for mobility scenario studies.The lockdown offers the opportunity to validate, for the first time ever, modelled scenarios of reduced mobility, proving the reliability of both methods and modelling chain. We take this opportunity by assessing a new approach to support urban mobility, based on a crowdsourcing solution. © 2020 HARMO. All rights reserved.
ABSTRACT
Recent observation and modeling-based studies have shown how air quality has been positively affected by the containment measures enforced due to the COVID-19 outbreak. This work aims to analyze Lombardy's NO2 atmospheric concentration during the spring lockdown. The region of Lombardy is known for having the largest number of residents in Italy and high levels of pollution. It is also the region where the first European confinement measures were imposed by the Italian government. The modeling suite composed of CAMx (Comprehensive Air Quality Model with Extensions) and WRF (Weather Research and Forecasting model) provides the setting to compare the atmospheric NO2 concentration from mid-February to the end of March with a business as usual situation. The main interest in this work is to investigate the response of NO2 atmospheric concentration to increasingly reduced road traffic. We can simulate, for the first time, a real circumstance of progressively reduced mobility, as well as validating it with measured air quality data. Focusing on the city of Milan, we found that the decrease in NO2 concentration reflects progressively reduced traffic contraction. In the case of a large traffic abatement (71%), the concentration level is reduced by one third. We also find that industrial activities have a relevant impact on NO2 atmospheric concentration, especially in the provinces of Brescia and Bergamo. This study provides an overview of how incisive policies must be implemented to achieve the set environmental targets and protect human health.