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Atmospheric particulate matter with an aerodynamic diameter < 2.5 µm (PM2.5) is associated with adverse effects on the climate system, the human health, vegetation and the ecosystems. The World Health Organization (WHO) lowered the guideline limit for PM2.5 in autumn 2021 and this is exceeded in many regions including rural and remote areas in mainland Europe. Measurements of the chemical composition of PM2.5 is essential to assess the sources which contribute to PM2.5 mass concentrations and to further design meaningful policies to tackle sources at their origin.Here we report 6 years (2014- 2020) of PM2.5 mass and chemical speciation at five remote sites across France belonging to the EMEP network (European Monitoring and Evaluation Programme). The seasonal and spatial variability of aerosol composition and source contributions based on the proximity of sources and long-range transport are discussed. Trends in PM2.5 and the main components at the five locations were evaluated by means of random-forest modelling coupled with a de-weathering algorithm. This approach is advantageous as resulting trends are driven by changes in emission or atmospheric processes and not by changes in weather conditions and/or long-range transport patterns. Random-forest regression modelling was built using meteorological data, backtrajectory information and temporal variables at each site and quantified the most important factors that explain PM2.5 concentrations at remote rural areas in France.All sites observed statistically significant downward trends in PM2.5 at a rate of -4 to -9% year-1 for the period 2014 – 2020. The decrease in PM2.5 concentrations was mostly explained by changes in the secondary inorganic species (sulphate, nitrate and ammonium) and not by changes in primary PM2.5 emissions. The variability in trends in PM2.5 and components observed across the sites is discussed with their implications for policy makers.

Ammonia (NH3) is the major alkaline gas in the atmosphere and the third most abundant N-containing species, after N2 and N2O. It plays an important role in N deposition processes, responsible of several damages on ecosystems, and it is also a precursor of fine particulate matter, known to cause numerous impacts on human health. Despite this, not many countries have implemented long-term monitoring of NH3 in their air quality programs due to the lack of consensus on limit values for ambient levels and a reference method of measuring this gas. In the climate change context, governments and health organizations are increasingly concerned about NH3 and its effects. As a proof, the revision of the EU air quality directives proposes the inclusion of NH3 as a mandatory pollutant for several urban and rural supersites for all member states.Currently, there are only 12 long term programs worldwide dedicated specifically to measure NH3 or including gas-phase measurements of NH3. The longest NH3 time series come from UK and Africa, where measurements start in mid-1990. The rest of locations have started after 2000 and they have lower temporal coverage, between 5 and 22 years. The objectives pursued by these networks are to follow long term spatio-temporal trends, assess the N deposition on sensitive ecosystems, validate emission and/or chemistry transport models and help to understand the effectiveness of air pollution control and mitigation policies. Most of these networks operate using a combination of low-cost samplers with a high spatial density with few collocated sites with high time resolution instrumentation to help calibrate passive samplers and to better monitor the fine temporal variability of NH3. This combined approach has proven to be successful for most of the proposed objectives.However, there are several differences that may difficult harmonizing the information at both the technical and scientific level. At the technical level these include type and number of passive samplers per site, calibration protocol, data control and quality analysis, exposure duration and type of high time resolution sampling method. On the scientific level, increased difficulty understanding the operative parameters and scientific results may come from language barriers (non-English reports), availability of the data (whether it is public or not), and gaps on the knowledge of NH3 levels on a spatial scale due to differences in the implementation of monitoring strategies within the same country.This work aims to review synthetically the world current long-term NH3 networks and provide some insight and recommendations for other countries and supranational programs aiming to establish long term monitoring networks of NH3, based on cost-effective, technical, and operational criteria.

International audience; This paper looks at experiential feedback and the technical and scientific challenges tied to the MERITE-HIPPOCAMPE cruise that took place in the Mediterranean Sea in spring 2019. This cruise proposes an innovative approach to investigate the accumulation and transfer of inorganic and organic contaminants within the planktonic food webs. We present detailed information on how the cruise worked, including 1) the cruise track and sampling stations, 2) the overall strategy, based mainly on the collection of plankton, suspended particles and water at the deep chlorophyll maximum, and the separation of these particles and planktonic organisms into various size fractions, as well as the collection of atmospheric deposition, 3) the operations performed and material used at each station, and 4) the sequence of operations and main parameters analysed. The paper also provides the main environmental conditions that were prevailing during the campaign. Lastly, we present the types of articles produced based on work completed by the cruise that are part of this special issue.

Trajectory-based statistical models (TMs) are widely used to locate source areas responsible for atmospheric pollution at receptor sites. In order to study the influence of long, medium and short-range back-trajectories (BTs) on geographical sources location, an original approach was applied to daily PM10 concentrations measured for 5 years (2009–2013) at 12 receptor sites in the Hauts-de-France (HdF) region bounded on the south by the Paris megacity and on the north by the Benelux countries. The methodology used was based on two complementary TMs, Concentration Field (CF) and Potential Source Contribution Function (PSCF), and included several meaningful constraints in order to improve the spatial representativeness and the statistical significance of the potential source maps. The selection of BTs depending on the occurrence of scavenging precipitations (>1 mm h−1) during the transport of air masses and altitude limitations with respect to the planetary boundary layer height led to more realistic maps. The variability of the density of BT endpoints was accounted for by a weighting function which highlighted medium-distant yet recurring (e.g. Benelux and West of Germany) potential sources of PM10. Investigating the effect of short-range BTs (75% of endpoints within a radius of 500 km from the receptor sites) pointed out at nearby large conurbations (Lille and Paris areas). Comparing our potential source maps with European PM10 emission inventory maps as well as PM10 measurements at European background monitoring stations for similar periods confirmed our results for Central Europe, the Benelux and the East of Germany. This study showed how the combination of several receptor sites enables the determination of potential source areas impacting a whole region. It pointed out also that the fine-tuned parametrization of the CF and PSCF TMs may considerably help improving the knowledge on geographical location of sources related to long, medium and short-range BTs and could be easily implemented for other regions of interest.

Air pollution in trace elements (TE) remains a concern for public health in Europe. For this reasons, networks of air pollution concentrations or exposure are deployed, including a moss bio-monitoring programme in Europe. Spatial determinants of TE concentrations in mosses remain unclear. In this study, the French dataset of TE in mosses is analyzed by spatial autoregressive model to account for spatial structure of the data and several variables proven or suspected to affect TE concentrations in mosses. Such variables include source (atmospheric deposition and soil concentrations), protocol (sampling month, collector, and moss species), and environment (forest type and canopy density, distance to the coast or the highway, and elevation). Modeled atmospheric deposition was only available for Cd and Pb and was one of the main explanatory variables of the concentrations in mosses. Predicted soil content was also an important explanatory variable except for Cr, Ni, and Zn. However, the moss species was the main factor for all the studied TE. The other environmental variables affected differently the TE. In particular, the forest type and canopy density were important in most cases. These results stress the need for further research on the effect of the moss species on the capture and retention of TE, as well as for accounting for several variables and the spatial structure of the data in statistical analyses.