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The former mining district of Salsigne is situated in the Orbiel valley. Until the 20th century, it was the first gold mine in Europe and the first arsenic mine in the world. Rehabilitation has been performed during the 20 years that followed closure of the mines and factories, which led to the accumulation of storage of several million tons of waste in this valley. Nevertheless, a detailed description of the air quality of this area is still missing. The goal of the present study is to evaluate atmospheric contamination in the valley and identify the potential sources of this contamination. Active monitors (particulate matter samplers) and passive bioindicators (Tillandsia usneoides) were placed in strategic sites including remote areas. Over the year 2022, we assessed the air quality using microscopic and spectroscopic techniques, as well as environmental risk indicators to report the level of contamination. Results indicate that the overall air quality in the valley is good with PM 10 levels in accordance with EU standards. Elemental concentrations in the exposed plants were lower than reported in the literature. Among the different sites studied, Nartau and La Combe du Saut, corresponding to waste storage and former mining industry sites, were the most affected. Chronic exposure over 1 year was highlighted for Fe, Ni, Cu, Pb, Sb and As. Pollution Load Index and Enrichment Factors, which provided valuable information to assess the environmental condition of the valley's air, suggested that dust and resuspension of anthropogenic materials were the principle sources for most of the elements. Finally, this study also highlights that using T. usneoides could be a convenient approach for biomonitoring of metal (loid)-rich particles in the atmosphere within a former mining area, for at least one year. These results in turn allow to better understand the effects of chronic exposure on the ecosystem., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

This study addressed the scarcity of NH 3 measurements in urban Europe and the diverse monitoring protocols, hindering direct data comparison. Sixty-nine datasets from Finland, France, Italy, Spain, and the UK across various site types, including industrial (IND, 8), traffic (TR, 12), urban (UB, 22), suburban (SUB, 12), and regional background (RB, 15), are analyzed to this study. Among these, 26 sites provided 5, or more, years of data for time series analysis. Despite varied protocols, necessitating future harmonization, the average NH 3 concentration across sites reached 8.0 ± 8.9 μg/m 3 . Excluding farming/agricultural hotspots (FAHs), IND and TR sites had the highest concentrations (4.7 ± 3.2 and 4.5 ± 1.0 μg/m 3 ), followed by UB, SUB, and RB sites (3.3 ± 1.5, 2.7 ± 1.3, and 1.0 ± 0.3 μg/m 3 , respectively) indicating that industrial, traffic, and other urban sources were primary contributors to NH 3 outside FAH regions. When referring exclusively to the FAHs, concentrations ranged from 10.0 ± 2.3 to 15.6 ± 17.2 μg/m 3 , with the highest concentrations being reached in RB sites close to the farming and agricultural sources, and that, on average for FAHs there is a decreasing NH 3 concentration gradient towards the city. Time trends showed that over half of the sites (18/26) observed statistically significant trends. Approximately 50 % of UB and TR sites showed a decreasing trend, while 30 % an increasing one. Meta-analysis revealed a small insignificant decreasing trend for non-FAH RB sites. In FAHs, there was a significant upward trend at a rate of 3.51[0.45,6.57]%/yr. Seasonal patterns of NH 3 concentrations varied, with urban areas experiencing fluctuations influenced by surrounding emissions, particularly in FAHs. Diel variation showed differing patterns at urban monitoring sites, all with higher daytime concentrations, but with variations in peak times depending on major emission sources and meteorological patterns. These results offer valuable insights into the spatio-temporal patterns of gas-phase NH 3 concentrations in urban Europe, contributing to future efforts in benchmarking NH 3 pollution control in urban areas., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

By implementing Principal Component Analysis (PCA) of multitemporal satellite data, this paper presents modeling solutions for air pollutant variation in three scenarios related to COVID-19 lockdown: pre, during, and after lockdown. Tropospheric NO 2 satellite data from Sentinel-5P was used. Two novel PCA-models were developed: Weighted Principal Component Analysis (WPCA) and Rescaled Principal Component Analysis (RPCA). Model results were tested for goodness-of-fit to empirical NO 2 data. The models were used to predict actual near-surface NO 2 concentrations. Model-predicted NO 2 concentrations were validated with NO 2 data acquired at ground monitoring stations. Besides, meteorological bias affecting NO 2 was assessed. It was found that the weather component had substantial impact on NO 2 built-ups, propitiating air pollutant decrease during lockdown and increase after. WPCA and RPCA models well fitted to observed NO 2. Both models accurately estimated near-surface NO 2 concentrations. Modeled NO 2 variation results evidenced the prolongated effect of the total lockdown (up to half a year). Model-predicted NO 2 concentrations were found to highly correlate with monitoring station NO 2 data collected on the ground. It is concluded that PCA is reliable in identifying and predicting air pollution variation patterns. The implementation of PCA is recommended when analyzing other pollutant gases. [Display omitted] • PCA is reliable for identifying and predicting air pollution variation. • WPCA and RPCA models well fitted observed NO 2. • Both models accurately estimated near-surface NO 2 concentrations. • Total lockdown had prolongated effect on NO 2 concentrations. • Weather conditions propitiated air pollutant decrease during lockdown and increase after. [ABSTRACT FROM AUTHOR]

Since 2018, TROPOMI on-board Sentinel-5P provides unprecedented images of NO2 tropospheric columns at a relatively high spatial resolution with a daily revisit. This study aims at assessing the potential of the TROPOMI-PAL data to estimate the national to urban NO x emissions in France from 2019 to 2021, using the variational mode of the recent Community Inversion Framework coupled to the CHIMERE regional transport model at a spatial resolution of 10×10 km2. The seasonal to inter-annual variations of the NO x French emissions are analyzed. A specific attention is paid to the current capability to quantify strong anomalies in the NO x emissions at intra-annual scales such as the ones due to the COVID-19 pandemic, by using TROPOMI NO2 observations. The inversions lead to a decrease of the average emissions over 2019–2021 compared to 2016 of -3 % at national scale, which is lower than the decrease of -14 % between these years in the estimates of the French Technical Center for Air Pollution and Climate Change (CITEPA). This may be linked especially to the limited level of constraint brought by the TROPOMI data, due to the observation coverage and the ratio between the current level of errors in the observation and the chemistry-transport model, and the NO2 signal from the French anthropogenic sources. Focusing on local analysis and selecting the days during which the TROPOMI coverage is good over a specific local source, we compute the reductions in the NO x anthropogenic emission estimates by the inversions from spring 2019 to spring 2020. These reductions are particularly pronounced for the largest French urban areas (e.g., -26 % from April 2019 to April 2020 in the Paris urban area) and along major roadways, consistently with the reduction in the intensity of vehicle traffic reported during the lockdown period. [ABSTRACT FROM AUTHOR]