Population exposure to multiple air pollutants and its compound episodes in Europe.

Air pollution remains as a substantial health problem, particularly regarding the combined health risks arising from simultaneous exposure to multiple air pollutants. However, understanding these combined exposure events over long periods has been hindered by sparse and temporally inconsistent monitoring data. Here we analyze daily ambient PM2.5, PM10, NO2 and O3 concentrations at a 0.1-degree resolution during 2003-2019 across 1426 contiguous regions in 35 European countries, representing 543 million people. We find that PM10 levels decline by 2.72% annually, followed by NO2 (2.45%) and PM2.5 (1.72%). In contrast, O3 increase by 0.58% in southern Europe, leading to a surge in unclean air days. Despite air quality advances, 86.3% of Europeans experience at least one compound event day per year, especially for PM2.5-NO2 and PM2.5-O3. We highlight the improvements in air quality control but emphasize the need for targeted measures addressing specific pollutants and their compound events, particularly amidst rising temperatures.

Estimation of pan-European, daily total, fine-mode and coarse-mode Aerosol Optical Depth at 0.1° resolution to facilitate air quality assessments.

Aerosol Optical Depth (AOD) data derived from satellites is crucial for estimating spatially-resolved PM concentrations, but existing AOD data over land remain affected by several limitations (e.g., data gaps, coarser resolution, higher uncertainty or lack of size fraction data), which weakens the AOD-PM relationship. We developed a 0.1° resolution daily AOD data set over Europe over the period 2003-2020, based on two-stage Quantile Machine Learning (QML) frameworks. Our approach first fills gaps in satellite AOD data and then constructs three components' models to obtain reliable full-coverage AOD along with Fine-mode AOD (fAOD) and Coarse-mode AOD (cAOD). These models are based on AERONET (AErosol RObotic NETwork) observations, Gap-filled satellite AOD, climate and atmospheric composition reanalyses. Our QML AOD products exhibit better quality with an out-of-sample R2 equal to 0.68 for AOD, 0.66 for fAOD and 0.65 for cAOD, which is 23-92 %, 11-13 % and 115-132 % higher than the corresponding satellite or reanalysis products, respectively. Over 91.6 %, 81.6 %, and 88.9 % of QML AOD, fAOD and cAOD predictions fall within ±20 % Expected Error (EE) envelopes, respectively. Previous studies reported that a weak satellite AOD-PM correlation across Europe (Pearson correlation coefficient (PCC) around 0.1). Our QML products exhibit higher correlations with ground-level PMs, particularly when broadly matched by size: AOD with PM10, fAOD with PM2.5, cAOD with PM coarse (R = 0.41, 0.45 and 0.26, respectively). Different AOD fractions more effectively distinct PM size fractions, than total AOD. Our QML aerosol dataset and models pioneer full-coverage, daily high-resolution monitoring of fine-mode and coarse-mode aerosols, effectively addressing existing AOD challenges for further PMs exposures' estimations. This dataset opens avenues for more in-depth exploration of the impacts of aerosols on human health, climate, visibility, and biogeochemical processes, offering valuable insights for air quality management and environmental health risk assessment.

Assessing ozone abatement scenarios in the framework of the Spanish ozone mitigation plan.

Tropospheric ozone (O3) is a secondary air pollutant that affects human health, vegetation and climate, especially in Mediterranean countries such as Spain. In order to tackle this long-standing issue, the Spanish government recently started to design the Spanish O3 Mitigation Plan. To support this initiative and ultimately provide recommendations, we performed a first ambitious emission and air quality modeling exercise. This study presents the development of different emission scenarios - aligned with or beyond the measures planned for 2030 in Spain - and the modeling of their respective impact on the O3 pollution across Spain (in July 2019) with both MONARCH and WRF-CMAQ air quality models. The modeling experiments include a base case scenario, a so-called planned emission (PE) scenario integrating the expected emission changes related to 2030, and a set of specific emission scenarios in which additional emission changes are applied to specific sectors (on e.g., road transport, maritime traffic) on top of the PE scenario. The planned emission scenario considerably reduces daily 8-h maximum O3 concentrations (-4 µg/m3 on average), with strongest reductions in Madrid region, north of Catalonia, Valencia region, Galicia and Andalusia. The frequency of observed daily exceedances of the 120 µg/m3 daily 8-h maximum target value and 180 µg/m3 hourly information threshold could be reduced by -37 and -77 %, respectively. The results of the specific scenarios highlight road transport and maritime traffic as two key emission sectors contributing to O3 pollution, over the entire country and the Mediterranean coast, respectively, while solvent use and industry emissions have a more limited and localized impact on O3. In any case, even with the implementation of all the emission scenarios, daily exceedances of the aforementioned thresholds will still be recorded over the country.

Trade-offs between short-term mortality attributable to NO2 and O3 changes during the COVID-19 lockdown across major Spanish cities.

The emergence of the COVID-19 pandemic forced most countries to put in place lockdown measures to slow down the transmission of the virus. These lockdowns have led to temporal improvements in air quality. Here, we evaluate the changes in NO2 and O3 levels along with the associated impact upon premature mortality during the COVID-19 lockdown and deconfinement periods along the first epidemic wave across the provincial capital cities of Spain. We first quantify the change in pollutants solely due to the lockdown as the difference between business-as-usual (BAU) pollution levels, estimated with a machine learning-based meteorological normalization technique, and observed concentrations. Second, instead of using exposure-response functions between the pollutants and mortality reported in the literature, we fit conditional quasi-Poisson regression models to estimate city-specific associations between daily pollutant levels and non-accidental mortality during the period 2010-2018. Significant relative risk values are observed at lag 1 for NO2 (1.0047 [95% CI: 1.0014 to 1.0081]) and at lag 0 for O3 (1.0039 [1.0013 to 1.0065]). On average NO2 changed by -51% (intercity range -65.7 to -30.9%) and -36.4% (-53.7 to -11.6%), and O3 by -1.1% (-20.2 to 23.8%) and 0.6% (-12.4 to 23.0%), during the lockdown (57 days) and deconfinement (42 days) periods, respectively. We obtain a reduction in attributable mortality associated with NO2 changes of -119 (95% CI: -273 to -24) deaths over the lockdown, and of -53 (-114 to -10) deaths over the deconfinement. This was partially compensated by an increase in the attributable number of deaths, 14 (-72 to 99) during the lockdown, and 8 (-27 to 50) during the deconfinement, associated with the rise in O3 levels in the most populous cities during the analysed period, despite the overall small average reductions. Our study shows that the potential trade-offs between multiple air pollutants should be taken into account when evaluating the health impacts of environmental exposures.

Lessons from the COVID-19 air pollution decrease in Spain: Now what?

We offer an overview of the COVID-19 -driven air quality changes across 11 metropolises in Spain with the focus on lessons learned on how continuing abating pollution. Traffic flow decreased by up to 80% during the lockdown and remained relatively low during the full relaxation (June and July). After the lockdown a significant shift from public transport to private vehicles (+21% in Barcelona) persisted due to the pervasive fear that using public transport might increase the risk of SARS-CoV-2 infection, which need to be reverted as soon as possible. NO2 levels fell below 50% of the WHO annual air quality guidelines (WHOAQGs), but those of PM2.5 were reduced less than expected due to the lower contributions from traffic, increased contributions from agricultural and domestic biomass burning, or meteorological conditions favoring high secondary aerosol formation yields. Even during the lockdown, the annual PM2.5 WHOAQG was exceeded in cities within the NE and E regions with high NH3 emissions from farming and agriculture. Decreases in PM10 levels were greater than in PM2.5 due to reduced emissions from road dust, vehicle wear, and construction/demolition. Averaged O3 daily maximum 8-h (8hDM) experienced a generalized decrease in the rural receptor sites in the relaxation (June-July) with -20% reduced mobility. For urban areas O3 8hDM responses were heterogeneous, with increases or decreases depending on the period and location. Thus, after canceling out the effect of meteorology, 5 out of 11 cities experienced O3 decreases during the lockdown, while the remaining 6 either did not experience relevant reductions or increased. During the relaxation period and coinciding with the growing O3 season (June-July), most cities experienced decreases. However, the O3 WHOAQG was still exceeded during the lockdown and full relaxation periods in several cities. For secondary pollutants, such as O3 and PM2.5, further chemical and dispersion modeling along with source apportionment techniques to identify major precursor reduction targets are required to evaluate their abatement potential.