Little is known about the main sources of ambient particulate matter (PM) in the 22 Eastern Mediterranean Region (EMR) countries. We designed this study to systematically review all published and unpublished source apportionment (SA), identification and characterization studies as well as emission inventories in the EMR. Of 440 articles identified, 82 (11 emission inventory ones) met our inclusion criteria for final analyses. Of 22 EMR countries, Iran with 30 articles had the highest number of studies on source specific PM followed by Pakistan (n = 15 articles) and Saudi Arabia (n = 8 papers). By contrast, there were no studies in Afghanistan, Bahrain, Djibouti, Libya, Somalia, Sudan, Syria, Tunisia, United Arab Emirates and Yemen. Approximately 72% of studies (51) were published within a span of 2015–2021.48 studies identified the sources of PM₂.₅ and its constituents. Positive matrix factorization (PMF), principal component analysis (PCA) and chemical mass balance (CMB) were the most common approaches to identify the source contributions of ambient PM. Both secondary aerosols and dust, with 12–51% and 8–80% (33% and 30% for all EMR countries, on average) had the greatest contributions in ambient PM₂.₅. The remaining sources for ambient PM₂.₅, including mixed sources (traffic, industry and residential (TIR)), traffic, industries, biomass burning, and sea salt were in the range of approximately 4–69%, 4–49%, 1–53%, 7–25% and 3–29%, respectively. For PM₁₀, the most dominant source was dust with 7–95% (49% for all EMR countries, on average). The limited number of SA studies in the EMR countries (one study per approximately 9.6 million people) in comparison to Europe and North America (1 study per 4.3 and 2.1 million people respectively) can be augmented by future studies that will provide a better understanding of emission sources in the urban environment.

Multiwalled carbon nanotubes (MWCNTs) were oxidized using a mixture of H₂SO₄ and HNO₃, and the oxidized MWCNTS were decorated with magnetite (Fe₃O₄). Finally, poly-N-isopropyl acrylamide-co-butyl acrylate (P-NIPAM) was added to obtain P-NIPAM/Fe/MWCNT nanocomposites. The nanosorbents were characterized by various techniques, including X-ray diffraction, transmission electron microscopy, scanning electron microscopy, thermogravimetric analysis, and Brunauer–Emmett–Teller analysis. The P-NIPAM/Fe/MWCNT nanocomposites exhibited increased surface hydrophobicity. Owing to their higher adsorption capacity, their kerosene removal efficiency was 95%; by contrast, the as-prepared, oxidized, and magnetite-decorated MWCNTs had removal efficiencies of 45%, 55%, and 68%, respectively. The P-NIPAM/Fe/MWCNT nanocomposites exhibited a sorbent capacity of 8.1 g/g for kerosene removal from water. The highest kerosene removal efficiency from water was obtained at a process time of 45 min, sorbent dose of 0.005 g, solution temperature of 40 °C, and pH 3.5. The P-NIPAM/Fe/MWCNTs showed excellent stability after four cycles of kerosene removal from water followed by regeneration. The reason may be the increase in the positive charge of the polymer at pH 3.5 and the increased adsorption affinity of the adsorbent toward the kerosene contaminant. The pseudo second-order model was found to be the most suitable model for studying the kinetics of the adsorption reaction.

Intra-urban pollution monitoring requires fine particulate (PM₂.₅) concentration mapping at ultrahigh-resolution (dozens to hundreds of meters). However, current PM₂.₅ concentration estimation, which is mainly based on aerosol optical depth (AOD) and meteorological data, usually had a low spatial resolution (kilometers) and severe spatial missing problem, cannot be applied to intra-urban pollution monitoring. To solve these problems, top-of-atmosphere reflectance (TOAR), which contains both the information about land and atmosphere and has high resolution and large spatial coverage, may be efficiently used for PM₂.₅ estimation. This study aims to systematically evaluate the feasibility of retrieving ultrahigh-resolution PM₂.₅ concentration at a large scale (national level) from TOAR. Firstly, we make a detailed discussion about several important but unsolved theoretic problems on TOAR-based PM₂.₅ retrieval, including the band selection, scale effect, cloud impact, and mapping quality evaluation. Secondly, four types and eight retrieval models are compared in terms of quantitative accuracy, mapping quality, model generalization, and model efficiency, with the pros and cons of each type summarized. Deep neural network (DNN) model shows the highest retrieval accuracy, and linear models were the best in efficiency and generalization. As a compromise, ensemble learning shows the best overall performance. Thirdly, using the highly accurate DNN model (cross-validated R² equals 0.93) and through combining Landsat 8 and Sentinel 2 images, a 90 m and ∼4-day resolution PM₂.₅ product was generated. The retrieved maps were used for analyzing the fine-scale interannual pollution change inner the city and the pollution variations during novel coronavirus disease 2019 (COVID-19). Results of this study proves that ultrahigh resolution can bring new findings of intra-urban pollution change, which cannot be observed at previous coarse resolution. Lastly, some suggestions for future ultrahigh-resolution PM₂.₅ mapping research were given.

Reliable long-horizon PM₂.₅ forecasts are crucial and beneficial for health protection through early warning against air pollution. However, the dynamic nature of air quality makes PM₂.₅ forecasts at long horizons very challenging. This study proposed a novel machine learning-based model (MCNN-BP) that fused multiple convolutional neural networks (MCNN) with a back-propagation neural network (BPNN) for making spatiotemporal PM₂.₅ forecasts for the next 72 h at 74 stations covering the whole Taiwan simultaneously. Model configuration involved an ensemble of massive hourly air quality and meteorological monitoring datasets and the existing publicly-available PM₂.₅ simulated (forecasted) datasets from an atmospheric chemical transport (ACT) model. The proposed methodology collaboratively constructed two CNNs to mine the observed data (the past) and the forecasted data from ACT (the future) separately. The results showed that the MCNN-BP model could significantly improve the accuracy of spatiotemporal PM₂.₅ forecasts and substantially reduce the forecast biases of the ACT model. We demonstrated that the proposed MCNN-BP model with effective feature extraction and good denoising ability could overcome the curse of dimensionality and offer satisfactory regional long-horizon PM₂.₅ forecasts. Moreover, the MCNN-BP model has considerably shorter computational time (5 min) and lower computational load than the compute-intensive ACT model. The proposed approach hits a milestone in multi-site and multi-horizon forecasting, which significantly contributes to early warning against regional air pollution.

The application of exogenous biodegradation strains in pesticide-polluted soils encounters the challenges of migration and persistence of inoculants. In this study, the degradation characteristics, vertical migration capacity, and microbial ecological risk assessment of an enhanced green fluorescent protein (EGFP)-tagged 2-Methyl-4-chlorophenoxyacetic acid (MCPA)-degrading strain Cupriavidus gilardii T1 (EGFP) were investigated in the laboratory and field soils. The optimum remediation conditions for T1 (EGFP) was characterized in soils. Meanwhile, leaching experiments showed that T1 (EGFP) migrated vertically downwards in soil and contribute to the degradation of MCPA at different depths. After inoculation with T1 (EGFP), a high expression levels of EGFP gene was observed at 28 d in the laboratory soil and at 45 d in the field soil. The degradation rates of MCPA were ≥ 60% in the laboratory soil and ≥ 48% in the field soil, indicating that T1 (EGFP) can efficiently and continuously remove MCPA in both laboratory and field conditions. In addition, the inoculation of T1 (EGFP) not only showed no significant impact on the soil microbial community structure but also can alleviate the negative effects induced by MCPA to some extent. Overall, our findings suggested that T1 (EGFP) strain is an ecologically safe resource for the in situ bioremediation of MCPA-contaminated soils.

Combining biochar with irrigation management to alter the microbial community is a sustainable method for remediating soils contaminated by heavy metals. However, studies on how these treatments promote Cr(VI) reduction are limited, and the corresponding microbial mechanisms are unclear. Therefore, we conducted a pot experiment to explore the responses of soil microbial communities to combined biochar amendment and irrigation management strategies and their involvement in Cr transformation in paddy soils. Six treatments were established using varying concentrations of biochar (0, 1, and 2% [w/w]) combined with two irrigation management strategies (continuous flooding [CF] and dry–wet alternation [DWA]). The results showed that the combined biochar addition and irrigation management strategy significantly altered soil pH, redox potential, organic matter content, and Fe(II) and sulfide concentrations. In addition, the Cr(VI) concentration under CF irrigation management was conspicuously lower (48.2–54.4%) than that under DWA irrigation management. Biochar amendment also resulted in a substantial reduction (8.8–27.4%) in Cr(VI) concentration. Moreover, the changes in soil physicochemical properties remarkably affected the soil microbial community. The microbial diversity and abundance significantly increased with biochar amendment. Furthermore, the combined biochar amendment and CF strategy stimulated the growth of Geobacter- and Anaeromyxobacter-related Fe(III)-reducing bacteria, Gallionella-related Fe(II)-oxidizing bacteria, and Desulfovibro- and Clostridium-related sulfate-reducing bacteria, which simultaneously facilitated the generation of Fe(II) and sulfide, thereby enhancing Cr(VI) reduction. Consequently, our results suggest that the effectively increased abundance of Fe-reducing/oxidizing bacteria and sulfate-reducing bacteria via combined CF irrigation management and biochar addition may be a key factor in reducing Cr(VI) in paddy soil. The keystone genera responsible for Cr(VI) reduction were Geobacter, Anaeromyxobacter, Gallionella, Desulfovibro, and Clostridium. This study provides novel insights into the coupling mechanism of the Fe/S/Cr transformation mediated by Fe-reducing/oxidizing bacteria and sulfate-reducing bacteria.

Bisphenol A (BPA) is pervasive in the environment, and exposure to BPA may increase the incidence of noncommunicable diseases like autoimmune diseases and cancer. Although BPA causes immunological problems at the cellular level, no system-level research has been conducted on this. Hence, in this study, we aimed to gain a better understanding of the biological response to BPA exposure and its association with immunological disorders. For that, we explored the transcriptome and the proteomic modifications at the systems and cellular levels following BPA exposure. Our integrated multi-omics data showed the alteration of the T cell receptor (TCR) signaling pathway at both levels. The proportion of enlarged T cells increased with upregulation of CD69, a surface marker of early T cell activation, even though the number of T cells reduced after BPA exposure. Additionally, on BPA exposure, the levels of pLCK and pSRC increased in T cells, while that of pLAT decreased. Following BPA exposure, we investigated cytokine profiles and discovered that chitinase 3 Like 1 and matrix metalloproteinase 9 were enriched in T cells. These results indicated that T cells were hyperactivated by CD69 stimulation, and phosphorylation of SRC accelerated on BPA exposure. Hence, alteration in the TCR signaling pathway during development and differentiation due to BPA exposure could lead to insufficient and hasty activation of TCR signaling in T cells, which could modify cytokine profiles, leading to increased environmental susceptibility to chronic inflammation or diseases, increasing the chance of autoimmune diseases and cancer. This study enhances our understanding of the effects of environmental perturbations on immunosuppression at molecular, cellular, and systematic levels following pubertal BPA exposure, and may help develop better predictive, preventative, and therapeutic techniques.

Pyrethroids are a class of widely used insecticides. Our recent epidemiological study of Chinese women reported that pyrethroid exposure was positively associated with the risk of primary ovarian insufficiency (POI). In this study, we utilized cypermethrin (CP), the most frequently detected pyrethroid in the environment, to recognize how lifelong and low-dose exposure to pyrethroids affects ovarian functions and the underlying mechanism(s). Female mice were exposed to CP at doses of human dietary intake of 6.7 μg/kg/day, an acceptable daily intake (ADI) of 20 μg/kg/day, or the chronic reference dose (RfD) of 60 μg/kg/day, starting from gestational day 0.5 until 44-week-old. We assessed effects on fertility, serum hormone levels, ovarian follicular development and ovarian transcriptomic profiles. Chronic exposure to CP at doses of ADI and RfD caused a significant reduction in the size of the primordial follicle pool on postnatal day (PND) 5 and the number of all types of follicles in 44-week-old mice, lower estrogen and higher gonadotropin levels, as well as decreased fertility. Significant increase in apoptosis and decrease in cell proliferation were observed in CP-exposed ovarian follicles from PND 5 and 44-week-old mice. Ovarian transcriptomic data showed that the pro-apoptotic protein BMF and the cell cycle inhibitor p27 were significantly up-regulated in CP-exposed ovaries. Cyp17a1, Cyp19a1 and Hsd17b1 genes involved in the key steps of steroidogenesis were down-regulated in the ovaries of female mice exposed to CP. This study first reported that lifelong exposure to CP at doses of ADI or RfD caused an ovarian phenotype similar to human POI in female mice and provided a mechanistic explanation. Our findings suggest that lifelong exposure to pyrethroids of low doses, which are recommended as ‘safe’ dosages, may have a significant impact on the ovarian health of female mammals and humans.

As tracers, rare earth elements (REEs) can reflect the influence of human activities on the environmental changes in aquatic systems. To reveal the geochemical behavior of REEs in a water–sediment system influenced by human activities, the contents of REEs in the surface water and sediment in the Chaohu Lake Basin were measured by inductively coupled plasma mass spectrometry (ICP–MS). The results show that the ΣREE contents in the surface water are 0.10–0.850 μg L⁻¹, the ΣREE contents in the sediments are 71.14–210.01 μg g⁻¹, and the average contents are 0.24 μg L⁻¹ and 126.72 μg g⁻¹, respectively. Almost all water and sediment samples have obvious light REE (LREE) enrichment, which is the result of the input of LREE-rich substances released by natural processes and human activities (industrial and agricultural production). Under the alkaline water quality conditions of Chaohu Lake, REEs (especially LREEs) are easily removed from water by adsorption/coprecipitation reactions with suspended colloidal particles, which leads to the enrichment of LREEs in sediments. The Ce anomaly of the water–sediment system is related to the oxidation environment, while the Eu anomaly is related to the plagioclase crystallization. Significant Gd anomalies was observed in the downstream of rivers flowing through urban areas, which was related to the anthropogenic Gd wastewater discharged by hospitals. The ∑REE–δEu and provenance index (PI) discrimination results are consistent, indicating that the sediments in Chaohu Lake mainly come from rivers flowing through the southwest farmland. Furthermore, the spatial distribution of REEs shows that these tributaries are significantly affected by agricultural activities. The distribution and accumulation of REEs in Chaohu Lake are the result of the interaction of natural and human processes. The results can provide a scientific reference for the distribution and environmental behavior of REEs in aquatic environments disturbed by human beings.

Iron (III) co-precipitation with dissolved organic matter (DOM) is pervasive in many natural environments. However, the effects of DOM on the formation of Fe(III) hydroxysulfate (FHS) and its environmental implications are poorly understood. In this study, fulvic acid (FA) was used as a model DOM compound, and experiments were devised to investigate the effects of FA on the formation of FHS. In addition, the Pb(II) adsorption capabilities of FHSs biosynthesized under various FA dosages, including kinetics and sorption isotherm experiments, were conducted. These experiments showed that co-precipitation of FA promoted the formation of Fe-FA composites, FA-doped schwertmannite, and small particles of jarosite. Co-precipitates are more enriched in carboxyl (–COOH) functional groups due to their preferential binding with FHS. The adsorption kinetics, isotherms and mechanisms of Pb onto the biosynthesized FHSs were then comprehensively characterized and modeled. Though the specific surface area decreased with increasing FA loading, the introduction of FA into FHSs increased Pb(II) adsorption, with the highest concentration of FA addition improving the removal capacity of Pb(II) to 91.54%. Kinetics studies and intra-particle diffusion models indicated that the adsorption of Pb(II) onto the FHSs was correlated with the number of active sites, and two adsorption steps: surface adsorption and the diffusion of Pb(II) in channels inside the biosynthesized FHSs, are suggested. The adsorption mechanism was attributed to cation exchange between Pb(II) and –OH and –COOH functional groups, and the co-precipitated FA provided additional sites for Pb(II) adsorption by FHS.