Source contribution and origin of PM10 and arsenic in a complex industrial region (Huelva, SW Spain)

Potential of Coupling Metaheuristics-Optimized-XGBoost and SHAP in Revealing PAHs Environmental Fate

Polycyclic aromatic hydrocarbons (PAHs) refer to a group of several hundred compounds, among which 16 are identified as priority pollutants, due to their adverse health effects, frequency of occurrence, and potential for human exposure. This study is focused on benzo(a)pyrene, being considered an indicator of exposure to a PAH carcinogenic mixture. For this purpose, we have applied the XGBoost model to a two-year database of pollutant concentrations and meteorological parameters, with the aim to identify the factors which were mostly associated with the observed benzo(a)pyrene concentrations and to describe types of environments that supported the interactions between benzo(a)pyrene and other polluting species. The pollutant data were collected at the energy industry center in Serbia, in the vicinity of coal mining areas and power stations, where the observed benzo(a)pyrene maximum concentration for a study period reached 43.7 ngm-3. The metaheuristics algorithm has been used to optimize the XGBoost hyperparameters, and the results have been compared to the results of XGBoost models tuned by eight other cutting-edge metaheuristics algorithms. The best-produced model was later on interpreted by applying Shapley Additive exPlanations (SHAP). As indicated by mean absolute SHAP values, the temperature at the surface, arsenic, PM10, and total nitrogen oxide (NOx) concentrations appear to be the major factors affecting benzo(a)pyrene concentrations and its environmental fate.

From multi to single-particle analysis: A seasonal spectroscopic study of airborne particulate matter in Zaragoza, Spain

It is distinguished that deficient outdoor air quality is responsible for substantial health and climate issues. The aim of our study was to investigate the air quality in the city of Zaragoza (Spain) by characterizing atmospheric particulate matter (PM₁₀) during two seasons (winter and spring). PM₁₀ samples were collected in 2022 in quartz filters through a low-volume sampler and chemically analysed by complementary analytical techniques: Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), Laser Induced Breakdown Spectroscopy (LIBS), Raman Spectroscopy (RS) and Field Emission Scanning Electron Microscopy with Energy-Dispersive X-ray Spectroscopy (FESEM-EDS). Results have revealed, together with a temperature inversion phenomenon in winter, the presence of both natural (Al, Ca, Mg, Ti, Sr, Fe, etc.) and anthropogenic particles. The latter mainly formed by black carbon with an origin on fossil fuel combustion emissions. Additionally, chemical analyses of PM₁₀ filters showed the presence of three types of microplastics suspended in the air of the city: polyethylene terephthalate (PET), polyamides (PA) and polystyrene (PS). The results obtained from this research are of special interest to take into account for future air quality policies, particularly those with the aim of reducing air pollution in cities.

Interaction between arsenic metabolism genes and arsenic leads to a lose-lose situation

Microorganisms are essential for modifying arsenic morphology, mobility, and toxicity. Still, knowledge of the microorganisms responsible for arsenic metabolism in specific arsenic-contaminated fields, such as metallurgical plants is limited. We sampled on-field soils from three depths at 70 day intervals to explore the distribution and transformation of arsenic in the soil. Arsenic-metabolizing microorganisms were identified from the mapped gene sequences. Arsenic metabolism pathways were constructed with metagenomics and AsChip analysis (a high-throughput qPCR chip for arsenic metabolism genes). It has been shown in the result that 350 genera of arsenic-metabolizing microorganisms carrying 17 arsenic metabolism genes in field soils were identified, as relevant to arsenic reduction, arsenic methylation, arsenic respiration, and arsenic oxidation, respectively. Arsenic reduction genes were the only genes shared by the 10 high-ranking arsenic-metabolizing microorganisms. Arsenic reduction genes (arsABCDRT and acr3) accounted for 73.47%-78.11% of all arsenic metabolism genes. Such genes dominated arsenic metabolism, mediating the reduction of 14.11%-19.86% of As(V) to As(III) in 0-100 cm soils. Arsenic reduction disrupts microbial energy metabolism, DNA replication and repair and membrane transport. Arsenic reduction led to a significant decrease in the abundance of 17 arsenic metabolism genes (p < 0.0001). The critical role of arsenic-reducing microorganisms in the migration and transformation of arsenic in metallurgical field soils, was emphasized with such results. These results were of pronounced significance for understanding the transformation behavior of arsenic and the precise regulation of arsenic in field soil.

Impact of the SARS-CoV-2 lockdown measures in Southern Spain on PM10 trace element and gaseous pollutant concentrations

Trace element concentrations within PM10, gaseous pollutants (NO₂ and SO₂), and PM10 levels were studied during the Covid-19 lockdown at a regional level in Southern Spain (Andalusia). Pollutant concentrations were compared considering different mobility periods (pre-lockdown, lockdown, and relaxation) in 2020 and previous years (2013-2016). An acute decrease in NO₂ levels (<50%) was observed as a consequence of traffic diminution during the confinement period. Moreover, a lower reduction in PM10 levels and a non-clear pattern for SO₂ levels were observed. During the lockdown period, PM10 elements released from traffic emissions (Sn and Sb) showed the highest concentration diminution in the study area. Regarding the primary industrial sites, there were no significant differences in V, Ni, La, and Cr concentration reduction during 2020 associated with industrial activity (stainless steel and oil refinery) in Algeciras Bay. Similarly, concentrations of Zn showed the same behaviour at Cordoba, indicating that the Zn-smelter activity was not affected by the lockdown. Nevertheless, stronger reductions of Cu, Zn, and As in Huelva during the confinement period indicated a decrease in the nearby Cu-smelter emissions. Brick factories in Bailen were also influenced by the confinement measures, as corroborated by the marked decrease in concentrations of Ni, V, Cu, and Zn during the lockdown compared to that from previous years. This work has shown the baseline concentrations of trace elements of PM10, which is of great value to air quality managers in order to minimise pollution levels by applying the confinement of the population, affecting both traffic and industrial anthropogenic activities.

Residence in an Area with Environmental Exposure to Heavy Metals and Neurobehavioral Performance in Children 9-11 Years Old: An Explorative Study

We explored the association between residence in an area polluted with metals and neurobehavioral performance in children aged 9 to 11. A cross-sectional study was conducted with thirty boys and thirty girls aged 9 to 11 from public schools in a heavily industrialized area, matched by age (±4 months) and gender with 15 boys and 15 girls from public schools in cities without relevant industrial activity. Neurobehavioral performance was assessed with the Behavioral Assessment and Research System. Linear regression models were used, adjusting for age, sex, social class and multimedia activities to predict each of the neurobehavioral outcome variables. No differences in neurobehavioral performance were found when all children with residence in areas with environmental exposure to metals were classified as exposed and the children from the other provinces as unexposed. However, when we compared children living <1 km from an industrial area with respect to those living more than 1 km away, significant differences were found. Children living <1 km away had lower scores on Finger Tapping (p = 0.03), Symbol-Digit (p = 0.07) and Continuous Performance (p = 0.02) than those living farther away. Our results support the hypothesis that residing close to an area with industrial activity (<1 km) is associated with deficits in neurobehavioral performance among children aged 9 to 11.

Contribution of anthropogenic and natural sources in PM10 during North African dust events in Southern Europe

The influence of North African (NAF) dust events on the air quality at the regional level (12 representative monitoring stations) in Southern Europe during a long time series (2007-2014) was studied. PM10 levels and chemical composition were separated by Atlantic (ATL) and NAF air masses. An increase in the average PM10 concentrations was observed on sampling days with NAF dust influence (42 μg m^-3) when compared to ATL air masses (29 μg m^-3). Major compounds such as crustal components and secondary inorganic compounds (SIC), as well as toxic trace elements derived from industrial emissions, also showed higher concentrations of NAF events. A source contribution analysis using positive matrix factorisation (PMF) 5.0 of the PM10 chemical data, discriminating ATL and NAF air mass origins, allowed the identification of five sources: crustal, sea salt, traffic, regional, and industrial. A higher contribution (74%) of the natural sources to PM10 concentrations was confirmed under NAF episodes compared with ATL. Furthermore, there was an increase in anthropogenic sources during these events (51%), indicating the important influence of the NAF air masses on these sources. The results of this study highlight that environmental managers should take appropriate actions to reduce local emissions during NAF events to ensure good air quality.