Nowadays, marine ecosystems are under severe threat from the simultaneous presence of multiple stressors, including microplastics (MPs) and polycyclic aromatic hydrocarbons (PAHs) such as benzo[a]pyrene (B[a]P). In addition to their presence in various marine compartments, there are increasing concerns on the potential capacity of MPs to sorb, concentrate and transfer these pollutants in the environment. Although their ecotoxicological impacts are currently evident, few works have studied the combined effects of these contaminants. Therefore, the major purpose of this work was to assess the toxicity of environmental relevant concentrations of MPs (<30 μm) and B[a]P, alone and in mixture, in the seaworm Hediste diversicolor by exploring their accumulation and hazardous biological effects for 3 and 7 days. Environmental MPs were able to increase B[a]P in a time-dependent manner. The obtained results showed that individual treatments, as well as co-exposure to contaminants, caused cytotoxicity and genotoxicity in the cœlomic fluid cells, while oxidative stress effects were observed at tissue and gene levels associated with alteration in neurotransmission. Overall, our findings provide additional clues about MPs as organic pollutant vectors in the marine environment, and contribute to a clearer understanding of their toxicological risk to aquatic invertebrates.

The concentration of persistent organic pollutants (POPs) makes remarkable difference to environmental fate. In the field of passive sampling, the partition coefficients between polystyrene-divinylbenzene resin (XAD) and air (i.e., KXAD₋A) are indispensable to obtain POPs concentration, and the KXAD₋A is generally thought to be governed by temperature and molecular structure of POPs. However, experimental determination of KXAD₋A is unrealistic for countless and novel chemicals. Herein, the Abraham solute descriptors of poly parameter linear free energy relationship (pp-LFER) and temperature were utilized to develop models, namely pp-LFER-T, for predicting KXAD₋A values. Two linear (MLR and LASSO) and four nonlinear (ANN, SVM, kNN and RF) machine learning algorithms were employed to develop models based on a data set of 307 sample points. For the aforementioned six models, R²ₐdⱼ and Q²ₑₓₜ were both beyond 0.90, indicating distinguished goodness-of-fit and robust generalization ability. By comparing the established models, the best model was observed as the RF model with R²ₐdⱼ = 0.991, Q²ₑₓₜ = 0.935, RMSEₜᵣₐ = 0.271 and RMSEₑₓₜ = 0.868. The mechanism interpretation revealed that the temperature, size of molecules and dipole-type interactions were the predominant factors affecting KXAD₋A values. Concurrently, the developed models with the broad applicability domain provide available tools to fill the experimental data gap for untested chemicals. In addition, the developed models were helpful to preliminarily evaluate the environmental ecological risk and understand the adsorption behavior of POPs between XAD membrane and air.

This study reports the results obtained from toxicological analyses of different types of baits referred to the laboratory of the Toxicology Area (Faculty of Veterinary Medicine, Cáceres, Spain) over a 17-year period (2002–2018). These baits were suspicious materials found in the environment of the region of Extremadura (Western Spain), where such malpractices are a problem to be addressed, as wide livestock farming and hunting activities are combined with a significant wealth of wildlife (especially birds of prey). A total of 246 baits, including 32 commercial chemical products to be used in baits, were analysed. Samples from 183 cases were received and classified according to the material used for their preparation and the toxic substance found. Overall, the most common bait consisted of meat preparations (56.3% of cases) intended to eliminate predators considered ‘annoying’ for livestock and hunting practices, such as carnivores and scavengers. It should be noted that contact baits (as fenthion-impregnated perches) were also detected (7.6%). Regarding the substances detected, anticholinesterase compounds (organophosphates and carbamates) were the most commonly used substances for the preparation of baits (detected in 85.3% of positive baits). Moreover, 8% of the positive baits presented more than one toxic substance in their composition. Due to the types of toxic compounds and the methods used to prepare the baits, this study shows that the malicious use of highly toxic substances in the environment to kill wildlife is a common and current issue and poses a serious risk to different species.

Contaminant vulnerability in the critical zones like groundwater (GW)-seawater (SW) continuum along the entire Gujarat coast was investigated for the first time through an extensive water monitoring survey. The prime focus of the study was to evaluate whether or not: i) seawater intrusion induced metal load translates to toxicity; ii) in the coastal groundwater, metal distribution follows the pattern of other geogenic and anthropogenic contaminants like NO₃- and F-; and iii) what future lies ahead pertaining to metal fate in association with saturation conditions of the coastal aquifers. The spatial distribution of contaminants depicts that the Gulf of Khambhat area is highly contaminated. Ecological risk assessment (ERA) indicates that the Gujarat coast is experiencing a high ecological risk compared to the southeast coast of India. Investigation results revealed that metals, pH, NO₃, and CO₃ are more vulnerable at the SW-GW mixing interface. An increase in pH is reflected in fewer ionic species of metals in the GW. Salinity ingress due to seawater intrusion (SWI) reduces the toxicities of all trace metals except Cu, attributed to the increase of Ca in GW, leading to dissociation of CuCO₃. Reactive species are dominant for Zn and Cd; and M-CO₃ ligands are dominant for Cu and Pb owing to the undersaturation of dolomite and calcite in the aquifer system. SWI tends to increase the metal load but the toxicity of metals varies with the density of industries, anthropogenic activities, changes in the mixing-induced saturation conditions, and intensive salt production across the coast. Multivariate analysis confirmed that the hydrogeochemical processes change due to GW-SW mixing and dictates over natural weathering. The ecological risk index (ERI) for the Arabian sea is experiencing moderate (300 ≥ ERI>150) to high ecological risk (ERI >600). Children population is likely to encounter a high health risk through ingestion and dermal exposure than adults. Overall, the study emphasizes the complexity of toxicity-related health impacts on coastal communities and suggests the dire need for frequent water monitoring along the coastal areas for quick realization of sustainable development goals.

Recently, with the rapid development of China's economy, the pollution of trace metal(loid)s (TMs) in soils has become increasingly severe and attracted widespread attention. Based on 1,402 published papers from 2000 to 2021, this study aimed to analyze the pollution intensity, ecological risk and driving factors for eight TMs (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) in Chinese soils. Results showed that the average concentrations of eight TMs in Chinese soils all exceeded background values, and the pollution of Cd and Hg was the most serious. Based on Principal component analysis of pollution intensity and ecological risk, the priority control TMs were identified for the heavily polluted provinces. The results of Geo-detector model suggested that Urban development factors contributed most to the TM accumulation in Chinese soils. Further, spatial analysis using bivariate Moran's I indicated that industrial activities contributed most to soil TM accumulation in the middle and lower reaches of the Yangtze River, while soil TM pollution in the southwest and northwest provinces was mainly caused by mining and metal smelting. This study investigated the relationship between soil TM pollution and anthropogenic activities, thus providing a scientific basis for controlling soil TM pollution at a large-scale level.

DO₃SE (Deposition of Ozone for Stomatal Exchange), is a dry deposition model, designed to assess tropospheric ozone risk to vegetation, and is based on two alternative algorithms to estimate stomatal conductance: multiplicative and photosynthetic. The multiplicative model has been argued to perform better for leaf-level and regional-level application. In this study, we demonstrate that the photosynthetic model is superior to the multiplicative model even for leaf-level studies using measurements performed on Mangifera indica. We find that the multiplicative model overestimates the daytime stomatal conductance, when compared with measured stomatal conductance and prescribes zero conductance at night while measurements show an average conductance of 100 mmol(H₂O)m⁻²s⁻¹ between 9 p.m. and 4 a.m. The daytime overestimation of the multiplicative model can be significantly reduced when the model is modified to include a response function for ozone-induced stomatal closure. However, nighttime pollutant uptake fluxes can only be accurately assessed with the photosynthetic model which includes the stomatal opening at night during respiration and is capable of reproducing the measured nighttime stomatal conductance. At our site, the nocturnal flux contributes 64%, 39%, 46%, and 88% of the total for NO₂ uptake in winter, summer, monsoon, and post-monsoon, respectively. For SO₂, nocturnal uptake amounts to 35%, 28%, 28%, and 44% in winter, summer, monsoon, and post-monsoon, respectively while for ozone the nighttime uptake contributes 30%, 17%, 18%, and 29% of the total stomatal uptake in winter, summer, monsoon, and post-monsoon respectively.

Mangroves play a vital role in protecting the coastal community from the climate change effect and in the restoration of the coastal ecosystem. This research has been designed to determine the spatial and seasonal changes of potentially toxic elements’ (PTEs) concentration in sediments and their potential source contribution among the different human-driven processes in Sundarbans, Bangladesh. Different pollution evaluation indices, random forest (RF) model, conditional inference tree (CIT), self-organizing map (SOM), geographical information system (GIS), and principal component analysis (PCA) were used for the interpretation of sources and risk assessment of PTEs. The mean concentration of PTEs both in winter and monsoon seasons has fallen below the threshold effect level but exceeded the rare effect level of marine sediments quality standards. Results showed that the PTEs were significantly enriched (EF > 1.00 < 70.00) in sediments, whereas the Cd enrichment (7.00% samples) was very alarming (EF = 60–70). Except for Zn and Cd, other PTEs were enriched in 30–60% samples. The highest geoaccumulation and contamination factors for Cd were observed in 46–72% of samples. The ecological risk (ER) factors showed similar results where Cd showed strong to very strong factors (ER = 110–2218) in 80% of samples. The CIT explained the natural/geogenic and anthropogenic sources of pollution, where the higher CIT values for Cd indicated industrial, aquaculture, and coal-based thermal powerplant. The RF model provided that shrimp firms, power plants, industry, and seaport were recognized as the influential sources for Zn, Pb, Cr, Cd, and As in sediments. Though Pb and As were found as the most significant pollutants, Cd was identified as a severe threat to ecology and public health. Based on CIT, RF, SOM and PCA the order of PTEs in mangroves sediment were:industrial/urban > aquaculture/shrimpfirm > powerplant > seaportoperation > tourism > geogenic/natural. The present study will help the policymakers for effective and sustainable management of the mangrove ecosystem.

Emerging evidence witnesses the association of air pollution exposure with sleep disorders or the risk of obstructive sleep apnea (OSA); however, the results are not consistent. OSA patients with or without a low arousal threshold (LAT) have different pathology and therapeutic schemes. No study has evaluated the potential diverse effects of air pollution on the phenotypes of OSA. The current study aimed to evaluate the associations of short-term and long-term exposure to air pollution with sleep-disordered measures and OSA phenotypes. This cross-sectional study consisted of 4634 participants from a sleep center in Taipei from January 2015 to April 2019. The personal exposure to ambient PM₂.₅ and NO₂ was assessed by a spatial-temporal model. Overnight polysomnography was used to measure the sleep parameters. According to a developed clinical tool, we defined the low arousal threshold (LAT) and identified the OSA patients with or without LAT. We applied a generalized linear model and multinomial logistic regression model to estimate the change of sleep measures and risk of the OSA phenotypes, respectively, associated with an interquartile range (IQR) increment of personal pollution exposure after adjusting for the essential confounders. In the single-pollutant model, we observed the associations of NO₂ with sleep-disordered measures by decreasing the total sleep time, sleep efficiency, extending the time of wake after sleep onset, and the association of NO₂ with the increased risk of LAT OSA by around 15%. The two-pollutant model with both long-term and short-term exposures confirmed the most robust associations of long-term NO₂ exposure with sleep measures. An IQR increment of NO₂ averaged over the past year (6.0 ppb) decreased 3.32 min of total sleep time and 0.85% of sleep efficiency. Mitigating exposure to air pollution may improve sleep quality and reduce the risk of LAT OSA.

Predicting the toxicity of effluent exposures, which vary in duration, composition, and concentration, poses a challenge for ecological risk assessments. Effluent discharges may frequently result in the exposure of aquatic organisms to high concentrations of mixed contaminants for short durations. In the receiving environment effluents will undergo dilution and physical or chemical processes that further reduce contaminant concentrations at varying rates. To date, most studies comparing toxicity risks of continuous and pulsed contaminant exposures have focused on individual contaminants. In this study, the toxicity to the tropical euryhaline copepod Acartia sinjiensis of two complex effluents was assessed, comparing 6- and 18-h pulses and 78-h continuous exposures. Observations of larval development success and population size were completed after a 78-h incubation period, to observe for latent effects after pulse exposures. The chemical compositions of the effluents were assessed over time and different contaminants (i.e., metals, ammonia or organics) declined at differing rates. These were characterized as either a minimal, steady, or rapid decline. Nauplii development and population after 78 h were more impacted by effluent exposures following an 18-h pulse, compared to a 6-h pulse. Based on pulse-exposure concentrations, the 50% effect concentrations (EC50) were similar for continuous and 18-h exposures but up to 3-fold greater (lower toxicity) for the shorter 6-h exposures. Time-weighted average concentrations did not accurately predict toxicity from pulse exposures of the effluents. Concentration-addition toxicity modelling using toxicity data from pulse exposures of single contaminants was useful for predicting the toxicity of chemical mixtures exposed for varying durations. Recommendations for modified approaches to assessing risks of short-term effluent discharges are discussed.

The epidemiological evidence supporting putative associations between air pollution and health-related outcomes continues to grow at an accelerated pace with a considerable heterogeneity and with varying consistency based on the outcomes assessed, the examined surveillance system, and the geographic region. We aimed to evaluate the strength of this evidence base, to identify robust associations as well as to evaluate effect variation. An overview of reviews (umbrella review) methodology was implemented. PubMed and Scopus were systematically screened (inception-3/2020) for systematic reviews and meta-analyses examining the association between air pollutants, including CO, NOX, NO₂, O₃, PM₁₀, PM₂.₅, and SO₂ and human health outcomes. The quality of systematic reviews was evaluated using AMSTAR. The strength of evidence was categorized as: strong, highly suggestive, suggestive, or weak. The criteria included statistical significance of the random-effects meta-analytical estimate and of the effect estimate of the largest study in a meta-analysis, heterogeneity between studies, 95% prediction intervals, and bias related to small study effects. Seventy-five systematic reviews of low to moderate methodological quality reported 548 meta-analyses on the associations between outdoor air quality and human health. Of these, 57% (N = 313) were not statistically significant. Strong evidence supported 13 associations (2%) between elevated PM₂.₅, PM₁₀, NO₂, and SO₂ concentrations and increased risk of cardiorespiratory or pregnancy/birth-related outcomes. Twenty-three (4%) highly suggestive associations were identified on elevated PM₂.₅, PM₁₀, O₃, NO₂, and SO₂ concentrations and increased risk of cardiorespiratory, kidney, autoimmune, neurodegenerative, cancer or pregnancy/birth-related outcomes. Sixty-seven (12%), and 132 (24%) meta-analyses were graded as suggestive, and weak, respectively. Despite the abundance of research on the association between outdoor air quality and human health, the meta-analyses of epidemiological studies in the field provide evidence to support robust associations only for cardiorespiratory or pregnancy/birth-related outcomes.