The immense production of plastic polymers combined with their discordancy with nature has led to vast plastic waste contamination across the geosphere, from the oceans to freshwater reservoirs, wetlands, remote snowpacks, sediments, air and multiple other environments. These environmental pollutants include microplastics (MP), typically defined as small and fragmented plastics less than 5 mm in size, and nanoplastics (NP), particles smaller than a micrometer. The formation of micro and nanoplastics in aqueous media to date has been largely attributed to fragmentation of plastics by natural (i.e., abrasion, photolysis, biotic) or industrial processes. We present a novel method to create small microplastics (≲ 5 μm) and nanoplastics in water from a wide variety of plastic materials using a small volume of a solubilizer liquid, such as n-dodecane, in combination with vigorous mixing. When the suspensions or solutions are subjected to ultrasonic mixing, the particle sizes decrease. Small micro- and nanoparticles were made from commercial, real world and waste (aged) polyethylene, polystyrene, polycarbonate and polyethylene terephthalate, in addition to other plastic materials and were analyzed using dark field microscopy, Raman spectroscopy and particle size measurements. The presented method provides a new and simple way to create specific size distributions of micro- and nanoparticles, which will enable expanded research on these plastic particles in water, especially those made from real world and aged plastics. The ease of NP and small MP formation upon initial mixing simulates real world environments, thereby providing further insight into the behavior of plastics in natural settings.

Petroleum hydrocarbon pollution is a global problem. However, the effects of different petroleum pollution levels on soil microbial communities and ecological functions are still not clear. In this study, we analyzed the changes in microbial community structures and carbon and nitrogen transformation functions in oil-contaminated soils at different concentrations by chemical analysis, high-throughput sequencing techniques, cooccurrence networks, and KEGG database comparison functional gene annotation. The results showed that heavy petroleum concentrations (petroleum concentrations greater than 20,000 mg kg⁻¹) significantly decreased soil microbial diversity (p = 0.01), soil microbiome network complexity, species coexistence patterns, and prokaryotic carbon and nitrogen fixation genes. In medium petroleum contamination (petroleum concentrations of between 4000 mg kg⁻¹ and 20,000 mg kg⁻¹), microbial diversity (p > 0.05) and carbon and nitrogen transformation genes showed no evident change but promoted species coexistence patterns. Heavy petroleum contamination increased the Proteobacteria phylum abundance by 3.91%–57.01%, while medium petroleum contamination increased the Actinobacteria phylum abundance by 1.69%–0.26%. The results suggested that petroleum concentrations played a significant role in shifting soil microbial community structures, ecological functions, and species diversities.

Microplastic (MP) contamination is ubiquitous in agricultural soils. As a cost-effective soil amendment, biochar (BC) often coincides with MP exposure. However, little research has been conducted regarding the independent and combined effects of MPs and BC on the soil microbiome and N₂O/CH₄ emissions. Therefore, in this study, polyethylene terephthalate (PET) and wheat straw-derived BC were used, respectively, as representative MP and BC during an entire rice growth period. The high-throughput sequencing results showed that PET alone lowered bacterial diversity by 26.7%, while PET and BC co-existence did not induce apparent change. The relative abundances of some microbes (e.g., Cyanobacteria, Verrucomicrobia, and Bacteroidetes) that are associated with C and N cycling were changed at the phylum and class levels by all the treatments. In comparison with the control, the treatment of BC, PET, and their co-existence reduced the cumulative CH₄ emissions by 50%, 53%, and 61%, respectively. The higher mitigation by BC + PET may be the result of higher soil Eh and a consequently lower methanogenesis functional gene mcrA abundance in the treated soils. In addition, BC and PET alone, as well as their combined treatment, increased the abundance of nitrification genes, enhancing the soil nitrification process. However, the relative contribution of the nitrification process to N₂O emission was possibly lower than that of denitrification, in which the N₂O reductase gene nosZ was found to be the primary gene regulating N₂O emissions. BC alone increased nosZ abundance by 42.3%, thereby showing the potential in suppressing N₂O emission. In contrast, when BC was co-added with PET, the nosZ abundance lowered possibly because of increased soil aeration, and thus its cumulative N₂O emission was 38% higher than the BC treatment. Overall, these results demonstrated that BC and PET function differently in soil ecosystems when they coexisted.

Facing the challenge of global microplastics (MPs) pollution, full characterization of MPs biohazards is urgent. Recent intensive studies revealed that the toxicity depends on the material, size, and exposure concentration of MP. To better elucidate MPs biohazards, we investigated the impact of polystyrene-MPs of size 0.1 μm at a low dose of 50 μg/L on the neuromuscular, retinal, and reproductive phenotypes of fruit fly model, by voltage-clamped electrophysiology, electroretinogram, and reproductive assay, respectively. We found that MPs decreased the frequency of spontaneous junction currents of synapse and altered the receptor potential amplitude of the retina. Furthermore, MPs lowered the rate of embryo-laying of fruit flies. The differential gene expression of ligand-receptor interaction, endocytosis, phototransduction, and Toll/Imd signaling pathways might underlie these MPs-induced phenotypes. These findings call for further investigation on the potential biohazards of low-dose MPs.

Plastic pollution is a serious problem in the global marine environment because it can produce negative effects at the biological and ecological levels. Due to large surface-area-to-volume ratio and inherent hydrophobicity, nanoplastics can serve as carriers of contaminants, and may affect their fate and toxicity in marine environments. However, the combined effects of nanoplastics and mercury (Hg) in marine organisms have not been well characterized. In this study, after verifying the ingestion of polystyrene nano-size plastics (PS NPs, 50 nm) by the copepod Tigriopus japonicus and adsorption of Hg to PS NPs, we investigated the effects of PS NPs and Hg exposure (alone or in combination) for 48 h on the copepods. Specifically, a 72-h depuration was performed after 48 h exposure. The results showed that after 48 h exposure, the copepod's Hg concentration was significantly increased in the combined exposure group compared to that in the Hg treatment group, but these differences did not persist following 24 h of depuration. Therefore, PS NPs transported Hg into the copepods but did not promote Hg bioaccumulation. Treatment with PS NPs alone did not induce toxicity in T. japonicus, but co-exposure to PS NPs and Hg resulted in elevated transcription of genes related to energy production, antioxidant response, and detoxification/stress defense when compared with Hg treatment alone, demonstrating the synergistic interaction between PS NPs and Hg. Our findings contribute to a comprehensive understanding about the combined toxicity of nanoplastics and metals and the potential ecological risks of associated with these effects in marine environments.

Poor air quality is becoming a critical environmental concern in different countries over the last several years. Most of the air pollutants have serious consequences on human health and wellbeing. In this context, efficient forecasting of air pollutants is currently crucial to predict future events with a view to taking corrective actions and framing effective environmental policies. Although deep learning (DL) as well as statistical forecasting models are investigated in the literature, they have rarely used in air pollutant-specific optimal model building for long-term forecasting. In this paper, our aim is to develop the pollutant-specific optimal forecasting models for the phases spanning from preprocessing to model building by investigating a set of predictive techniques. In this regard, this paper presents a methodology for long-term forecasting of some important air pollutants. More specifically, a total of eight best performing models such as stacked LSTM, LSTM auto-encoder, Bi-LSTM, convLSTM, Holt-Winters, auto-regressive (AR), SARIMA, and Prophet are investigated for developing pollutant-specific optimal forecasting models. The study is carried out based on the real-world data obtained from government-run air quality monitoring units in Kolkata over a period of 4 years. The models such as Holt-Winters, Bi-LSTM, and ConvLSTM achieve high forecasting accuracy with respect to MAE and RMSE values for majority of the pollutants.

Currently, the evidence of the ingestion of microplastics (MPs) by organisms or the accumulation in different environmental compartments has been achieved using several methodological procedures. However, its uses have not been standardized across studies. In this study, we aim to assess and validate a protocol that can be useful for optimizing the identification and quantification procedures of polyethylene microplastics (PE MPs) in biological samples. Initially, considering that numerous studies filter samples previously digested in cellulosic membranes for isolation and analysis of MPs, we evaluated whether washing these membranes with different reagents could contribute to the complete detachment of particles, as well as to their dispersion in the obtained solutions. However, none of the tested reagents (dimethyl sulfoxide, acetone, ethyl alcohol and chloroform), including purified water, was able to completely remove the MPs adhered to the membranes or facilitate their dispersion in the solutions. On the other hand, we observed that the digestion of the membranes by acetonitrile constituted a procedure that prevents the loss of particles due to adherence, in addition to promoting good dispersion of MPs. Subsequently, we evaluated the use of Neubauer chambers for the quantification of MPs, having observed a good recovery rate (>92%) and results with insignificant variation, in PE MPs solutions with different concentrations (0.15; 0.075 and 0.0375 mg/mL). Ultimately, the validation of the proposed procedures took place from the evaluation of the accumulation of PE MPs in Astyanax spp. juveniles, having demonstrated the efficiency and sensitivity of the method proposed for this purpose. Subsequently, our study provides a methodological alternative that can optimize MPs quantifications in biological samples and reduce the generation of biased or unreliable results.

Traffic exhaust is a main source of fine particulate matter (PM₂.₅) in cities. Heavy-duty diesel trucks (HDDTs), the primary mode of freight transport, contribute significantly to PM₂.₅, posing a great threat to public health. However, existing research based on dispersion models to simulate pollutant concentrations lacks high-spatiotemporal-resolution emission inventories of HDDTs as input data, and the public health effects of such emissions in different populations have not been thoroughly assessed. To fill this gap, we focused on Beijing as the research area and developed a high-resolution PM₂.₅ emission inventory for HDDTs based on Global Navigation Satellite System-equipped vehicle trajectory data. We then simulated the fine-scale spatial distribution of diesel-related PM₂.₅ and assessed the population exposure by integrating the dispersion model and population distributions. Further, we quantified the mortality attributable to noncommunicable diseases (NCDs) plus lower respiratory infections (LRIs) related to PM₂.₅ emissions from HDDTs. Results showed that 3.3% of Beijing people lived in areas with high PM₂.₅ HDDT emissions, which were near intercity highways. Furthermore, the estimated number of NCD + LRI annual premature deaths attributed to PM₂.₅ HDDT emissions in Beijing was 339 (95% CI: 276–401). The NCD + LRI mortality increased with age, and deaths were more frequent in males than females. Our results aid the identification of HDDT PM₂.₅ emission exposure hotspots for the formulation of effective mitigation measures and provide important insights into the adverse health impacts of HDDT emissions.

Understanding the differences in the approaches used to assess household air pollution (HAP) is crucial for evaluating HAP-related health effects and interpreting the effectiveness of stove-fuel interventions. Our review aims to understand how exposure to HAP from solid fuels was measured in epidemiological studies in children under five. We conducted a search of PubMed, EMBASE, Cochrane Central Register of Controlled Trials, Global Health Library, Web of Science, and CINAHL to identify English-language research articles published between January 1, 2000 and April 30, 2022. Two researchers applied the inclusion and exclusion criteria independently. Study region, type of measurement, study design, health outcomes, and other key characteristics were extracted from each article and analyzed descriptively. Our search strategy yielded 2229 records, of which 185 articles were included. A large proportion was published between 2018 and 2022 (42.1%), applied a cross-sectional study design (47.6%), and took place in low- or lower middle-income countries. Most studies (130/185, 70.3%) assessed HAP using questionnaires/interviews, most frequently posing questions on cooking fuel type, followed by household ventilation and cooking location. Cooking frequency/duration and children's location while cooking was less commonly considered. About 28.6% (53/185) used monitors, but the application of personal portable samplers was limited (particulate matter [PM]: 12/40, 30.0%; carbon monoxide [CO]: 13/34, 38.2%). Few studies used biomarkers or modeling approaches to estimate HAP exposure among children under five. More studies that report household and behavioral characteristics and children's location while cooking, apply personal exposure samplers, and perform biomarker analysis are needed to advance our understandings of HAP exposure among infants and young children, who are particularly susceptible to HAP-related health effects.

Environmental pollutants such as heavy metals, nano/microparticles, and organic compounds have been detected in a wide range of environmental media, causing long-term exposure in various organisms and even humans through breathing, contacting, ingestion, and other routes. Long-term exposure to environmental pollutants in organisms or humans promotes exposure of offspring to parental and environmental pollutants, and subsequently results in multiple biological defects in the offspring. This review dialectically summarizes and discusses the existing studies using Caenorhabditis elegans (C. elegans) as a model organism to explore the multi/transgenerational toxicity and potential underlying molecular mechanisms induced by environmental pollutants following parental or successive exposure patterns. Parental and successive exposure to environmental pollutants induces various biological defects in C. elegans across multiple generations, including multi/transgenerational developmental toxicity, neurotoxicity, reproductive toxicity, and metabolic disturbances, which may be transmitted to progeny through reactive oxygen species-induced damage, epigenetic mechanisms, insulin/insulin-like growth factor-1 signaling pathway. This review aims to arouse researchers’ interest in the multi/transgenerational toxicity of pollutants and hopes to explore the possible long-term effects of environmental pollutants on organisms and even humans, as well as to provide constructive suggestions for the safety and management of emerging alternatives.