Exposure of the general population to airborne metals remains poorly estimated despite the potential health risks. Passive moss biomonitoring can proxy air quality at fine resolution over large areas, mainly in rural areas. We adapted the technique to urban areas to develop fine concentration maps for several metals for Constances cohort's participants. We sampled Grimmia pulvinata in 77 and 51 cemeteries within ∼50 km of Paris and Lyon city centers, respectively. We developed land-use regression models for 14 metals including cadmium, lead, and antimony; potential predictors included the amount of urban, agricultural, forest, and water around cemeteries, population density, altitude, and distance to major roads. We used both kriging with external drift and land use regression followed by residual kriging when necessary to derive concentration maps (500 × 500 m) for each metal and region. Both approaches led to similar results. The most frequent predictors were the amount of urban, agricultural, or forest areas. Depending on the metal, the models explained part of the spatial variability, from 6% for vanadium in Lyon to 84% for antimony in Paris, but mostly between 20% and 60%, with better results for metals emitted by human activities. Moss biomonitoring in cemeteries proves efficient for obtaining airborne metal exposures in urban areas for the most common metals.

Microplastics (MPs) have elicited increasing concerns in freshwater systems worldwide. However, little information is available on the MP pollution in the Songhua River, the third largest river in China. And the understanding of the sources and pathways of MPs is limited. In this study, MPs were sampled from river water and wastewater treatment plants in five cities along the Songhua River to investigate the occurrence, spatial distribution, characteristics, and potential sources of MPs. Polyethylene, polypropylene and polystyrene accounted for more than 95% of the total MPs. MP pollution was determined to be spatially heterogeneous. The concentration of MPs in the urban center was always considerably higher than that in the upper reach, and irregular variation was observed from the urban center to the lower reach for each city. Urbanization was one of the primary driving forces of spatial variability. Statistically significant positive correlations (p-value < 0.05) were noted between the average concentration of MPs in river water and population density (p = 0.0023) and number of industrial enterprises above designated size (p = 0.0042) of each city. Line and fiber were the major shapes, and white was the most dominant color. Large (1–5 mm) and small (≤ 1 mm) MP particles accounted for 50% each. Multiple correspondence analysis as a new methodological approach was conducted to elucidate the sources of MPs for the first time. The potential sources of MPs included daily use, fishing, agricultural, and industrial productions. This work provides information about MP contamination for future studies on freshwater systems and new insights into the source apportionment of MPs.

Cooking is an important source of organic aerosols (OA), particularly in urban areas, but it has not been explicitly included in current emission inventories in China. This study estimated the organic aerosol emissions from cooking during winter over the Pearl River Delta (PRD) region, China. Using the retrieved hourly cooking organic aerosol (COA) concentrations at two sites in Hong Kong and Guangzhou, population density, and daily per capita COA emissions, we determined the spatial and temporal distribution of COA emissions over the PRD region based on two approaches by treating COA as non-volatile (NVCOA) and semi-volatile (SVCOA), respectively. By using the estimated COA emissions and the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) model, we reproduced the diurnal cycles of COA concentrations at the PolyU site in Hong Kong and Panyu site in Guangzhou. We also resolved the different patterns of COA between weekdays and weekends. The mean COA concentration during wintertime over the urban areas of the PRD region was 0.7 μg m⁻³ and 0.9 μg m⁻³ for the NVCOA and SVCOA cases, respectively, contributing 5.1% and 6.9% to the urban OA concentrations. The total COA emissions in winter over the PRD region were estimated to be 3.5 × 10⁸ g month⁻¹ and 3.8 × 10⁸ g month⁻¹ for the NVCOA and SVCOA cases, respectively, adding 34.8% and 37.8% to the total primary organic aerosol emissions. Considering COA emissions in the model increased the mean regional OA concentrations by 4.6% and 7.4% for the NVCOA and SVCOA cases, respectively. Our study therefore highlights the importance of cooking activities to OA concentrations in winter over the PRD region.

Microplastics are a pollutant of growing concern, capable of harming aquatic organisms and entering the food web. While freshwater microplastic research has expanded in recent years, much remains unknown regarding the sources and delivery pathways of microplastics in these environments. This review aims to address the scientific literature regarding the spatial and temporal factors affecting global freshwater microplastic distributions and abundances. A total of 75 papers, published through June 2021 and containing an earliest publication date of October 2014, was identified by a Web of Science database search. Microplastic spatial distributions are heavily influenced by anthropogenic factors, with higher concentrations reported in regions characterized by urban land cover, high population density, and wastewater treatment plant effluent. Spatial distributions may also be affected by physical watershed characteristics such as slope and elevation (positive and negative correlations with microplastic concentrations, respectively), although few studies address these factors. Temporal variables of influence include precipitation and stormwater runoff (positive correlations) and water flow/discharge (negative correlations). Despite these overarching trends, variations in study results may be due to differing scales or contributing area delineations. Thus, more rigorous and standardized spatial analytical methods are needed. Future research could simultaneously evaluate both spatial and temporal factors and incorporate finer temporal resolutions into sampling campaigns.

Evaluating ozone levels at high resolutions and accuracy is crucial for understanding the spatiotemporal characteristics of ozone distribution and assessing ozone exposure levels in epidemiological studies. The national models with high spatiotemporal resolutions to predict ground ozone concentrations are limited in China so far. In this study, we aimed to develop a random forest model by combining ground ozone measurements from fixed stations, ozone simulations from the Community Multiscale Air Quality (CMAQ) modeling system, meteorological parameters, population density, road length, and elevation to predict ground maximum daily 8-h average (MDA8) ozone concentrations at a daily level and 1 km × 1 km spatial resolution. The model cross-validation R² and root mean squared error (RMSE) were 0.80 and 20.93 μg/m³ at daily level in 2013–2019, respectively. CMAQ ozone simulations and near-surface temperature played vital roles in predicting ozone concentrations among all predictors. The population-weighted median concentrations of predicted MDA8 ozone were 89.34 μg/m³ in mainland China in 2013, and reached 100.96 μg/m³ in 2019. However, the long-term temporal variations among regions were heterogeneous. Central and Eastern China, as well as the Southeast Coastal Area, suffered higher ozone pollution and higher increased rates of ozone concentrations from 2013 to 2019. The seasonal pattern of ozone pollution varied spatially. The peak-season ozone pollution with the highest 6-month ozone concentrations occurred in different months among regions, with more than half domain in April–September. The predictions showed that not only the annual mean concentrations but also the percentages of grid-days with MDA8 ozone concentrations higher than 100/160 μg/m³ have been increasing in the past few years in China; meanwhile, majority areas in mainland China suffered peak-season ozone concentrations higher than the air quality guidelines launched by the World Health Organization in September 2021. The proposed model and ozone predictions with high spatiotemporal resolution and full coverage could provide health studies with flexible choices to evaluate ozone exposure levels at multiple spatiotemporal scales in the future.

While the increasing accumulation of anthropogenic litter in the marine environment has received considerable attention over the last decade, litter occurrence and distribution in rivers, the main source of marine litter, have been comparatively less investigated. Moreover, little information is available about the amount and typology of Riverine Anthropogenic Macro-litter (RAM) entering marine environments from intermittent rivers in low populated areas of the Mediterranean basin. To provide insights on this issue, we investigated density and composition of RAM accumulated over a total of 133 riverbanks, belonging to 37 river basins in the Sardinia Island (Mediterranean Sea). We report here that plastics, especially single-use items, represent the most frequent and abundant RAM category in all investigated basins. Statistical modelling revealed that occurrence of lightweight RAM (especially plastic) is mostly explained by levels of urban (12.3% of the relative contribution) and agricultural (12%) land use of the territory, whereas the proximity of bridges to the sampling point (21%) and the local population density (19.8%) are best predictors of heavy weighted RAM items (i.e., large metal items, appliances) occurrence. Our results confirm that plastics represent an important component of RAM and pinpoint that, beside plastic reduction policies and better waste management, actions aimed at abating and monitoring litter contamination should be localized on the proximity of bridges, whatever the local population density. Finally, to fill existing knowledge gaps in understanding the severity of litter discharge and accumulation in the Mediterranean Sea, land-to-sea systematic monitoring campaigns at appropriate spatial and temporal scales should be put in place.

Varroa mite is one of the major adverse factors causing honey bee population decline. In this study, Varroa destructor-infested and uninfested honey bee colonies were established by selective applying miticide (Apivar® amitraz). Mite population was monitored monthly (April–October 2016), and deformed wing virus (DWV) loading was detected seasonally (April, July, and October). Four immunity- and two physiology-related gene expressions, natural mortality, and susceptibility to five insecticides were comparatively and seasonally examined in field-collected honey bee workers. Results showed that Apivar-treated bee colonies had minor or undetectable mite and DWV (using RT-qPCR) infestations in whole bee season, while untreated colonies had substantially higher mite and DWV infestations. In untreated colonies, Varroa mite population irregularly fluctuated over the bee season with higher mite counts in Jun (318 ± 89 mites dropped in 48 h) or August (302) than that (25 ± 4 or 34) in October, and mite population density was not dynamically or closely correlated with the seasonal shift of honey bee natural mortality (regression slope = −0.5212). Unlike mite, DWV titer in untreated colonies progressively increased over the bee season, and it was highly correlated (R² = 1) with the seasonal increase of honey bee natural mortality. Significantly lower gene expressions of dor, PPO, mfe, potentially PPOa and eat as well, in untreated colonies also indicated an association of increased DWV infestation with decreased physiological and immunity-related functions in late-season honey bees. Furthermore, bees with lower mite/DWV infestations exhibited generally consistently lower susceptibilities (contact and oral toxicities) to five representative insecticides than the bees without Apivar treatment. All of these data from this study consistently indicated an interaction of Varroa/viral infestations with insecticide susceptibilities in honey bees, potentially through impairing bee's physiology and immunity, emphasizing the importance of mite control in order to minimize honey bee decline.

This study aims to investigate the effect of transportation infrastructure on the decrease of NO₂ air pollution during three COVID-19-induced lockdowns in a vast region of France. For this purpose, using Sentinel-5P satellite data, the relative change in tropospheric NO₂ air pollution during the three lockdowns was calculated. The estimation of regional infrastructure intensity was performed using Kernel Density Estimation, being the predictor variable. By performing hotspot–coldspot analysis on the relative change in NO₂ air pollution, significant spatial clusters of decreased air pollution during the three lockdowns were identified. Based on the clusters, a novel spatial index, the Clustering Index (CI) was developed using its Coldspot Clustering Index (CCI) variant as a predicted variable in the regression model between infrastructure intensity and NO₂ air pollution decline. The analysis revealed that during the three lockdowns there was a strong and statistically significant relationship between the transportation infrastructure and the decline index, CCI (r = 0.899, R² = 0.808). The results showed that the largest decrease in NO₂ air pollution was recorded during the first lockdown, and in this case, there was the strongest inverse correlation with transportation infrastructure (r = −0.904, R² = 0.818). Economic and population predictors also explained with good fit the decrease in NO₂ air pollution during the first lockdown: GDP (R² = 0.511), employees (R² = 0.513), population density (R² = 0.837). It is concluded that not only economic-population variables determined the reduction of near-surface air pollution but also the transportation infrastructure. Further studies are recommended to investigate other pollutant gases as predicted variables.

Microplastic pollution is currently one of the most intensely studied ecological issues. Numerous studies have estimated the distribution and concentration of microplastics in various environments and determine how they affect their inhabitants. Much less effort has been place on assessing the possible effects of microplastics on interactions between organisms, including interspecific competition. Our aim was to test the hypothesis that the presence of microplastics affects the proportion of individuals of coexisting species and the elimination rate of the inferior competitor. The hypothesis was tested in competitive experiments done in the absence and presence of spherical non-biodegradable polystyrene and polyethylene and biodegradable polyhydroxybutyrate in environmentally relevant densities. In each of the experiments, we used three different pairs of closely related planktonic species of the genus Daphnia composed of the superior and inferior competitor: D. pulex and D. magna, D. magna and D. galeata, D. pulex and D. galeata. The results support our hypothesis and demonstrate each microplastic type had a different effect on the density of the competing species. The presence of polystyrene and polyethylene lowered the density of the superior competitor in each of the three pairs, at least partially due to a reduction in the number of gravid females, but not their fecundity. The presence of the polyhydroxybutyrate, in turn, increased the population density of D. magna in the variants with each of the two remaining species. Moreover, the presence of microplastics affected the elimination rate of the inferior competitor, i.e. polystyrene expedited the exclusion of D. magna by D. pulex, and polyhydroxybutyrate hampered the exclusion of D. magna by D. pulex. Our results suggest that long-term exposure to environmentally relevant densities of both non-biodegradable and biodegradable microplastics may affect the relative abundance of co-occurring species in zooplankton communities, and thus the functioning of aquatic ecosystems.

This study investigated whether lead (Pb), at concentrations allowed for soil, affects the community of insects that live in the aerial part of plants. We evaluated the effect of Pb concentrations on accumulated species richness, composition, and abundance of different functional groups of insects. Kale plants were grown in soil experimentally contaminated with four concentrations of lead nitrate: 0 (control), 144 (T1), 360 (T2), and 600 (T3) mg/kg of soil. The experiment was conducted in an open greenhouse for the natural colonization of insects. Insects were collected twice using trap bags attached to the plant leaf and by direct removal. The concentration of Pb in the stem and leaf samples increased with the increased soil contamination, even showing values above the limit allowed by the legislation for this plant species. Control plants showed a higher richness of accumulated insect species. In addition, the treatments had an effect on the community composition, in which Diaeretiella rapae (primary parasitoid) was found as an indicator of the control + T1 treatments and the top species Pachyneuron sp. (parasitoid of predators) was associated with the control. The abundance of chewing and sucking herbivores, their respective parasitoids, predators, and parasitoids of predators were negatively affected. Hyperparasitoid abundance was not affected, but their accumulated species richness was. This study was innovative in demonstrating that soil contamination by different concentrations of a heavy metal (Pb) can negatively affect the community of plant-associated insects, even at concentrations allowed for soil, reflecting possible damage to the ecosystem.