Monitoring beach plastic contamination across space and time is necessary for understanding its sources and ecological effects, and for guiding mitigation. This is logistically and financially challenging, especially for microplastics. Citizen science represents an option for sampling accessible sites to support long term monitoring, but challenges persist around data validation. Here we test a simple citizen science methodology to monitor visible microplastic contamination on sandy beaches using a standard quadrat unit (50 cm × 50 cm x 5 cm depth) sieved to 1 mm, to support the analysis of microplastic on two islands within the marine protected area of the Galápagos Archipelago, Ecuador (San Cristóbal and Santa Cruz islands). High school and university students undertook supervised sampling of two beaches in 2019–2020 collecting over 7000 particles. A sub-sample of the suspected microplastics collected (n = 2,213, ∼30% total) were analysed using FTIR spectrometry, confirming 93% of particles >1 mm visually identified by students were microplastics or rubber, validating this method as a crowd-sourced indicator for microplastic contamination. These data provide important insights into the plastic contamination of Galápagos, revealing plastic abundances of 0–2524 particles m⁻² over the two beaches (the highest reported in Galápagos). Strong accumulation gradients were measured parallel to the waterline at Punta Pitt (San Cristobal island) and perpendicular to the waterline at Tortuga Bay (Santa Cruz island), where four-fold higher concentrations were recorded at the sea turtle nesting habitat on the back-beach dune. No significant seasonal trends were measured during one year. These results demonstrate the value of citizen science in filling spatiotemporal knowledge gaps of beach contamination to support intervention design and conservation.

Polycyclic aromatic hydrocarbons (PAHs) constitute a significant environmental pollution group that reaches toxic levels with anthropogenic activities. The adverse effects of nanoplastics accumulating in ecosystems with the degradation of plastic wastes are also a growing concern. Previous studies have generally focused on the impact of single PAH or plastic fragments exposure on plants. However, it is well recognized that these contaminants co-exist at varying rates in agricultural soil and water resources. Therefore, it is critical to elucidate the phytotoxicity and interaction mechanisms of mixed pollutants. The current study was designed to comparatively investigate the single and combined effects of anthracene (ANT, 100 mg L⁻¹), fluorene (FLU, 100 mg L⁻¹) and polystyrene nanoplastics (PS, 100 mg L⁻¹) contaminations in wheat. Plants exposed to single ANT, FLU and PS treatments demonstrated decline in growth, water content, high stomatal limitations and oxidative damage. The effect of ANT + FLU on these parameters was more detrimental. In addition, ANT and/or FLU treatments significantly suppressed photosynthetic capacity as determined by carbon assimilation rate (A) and chlorophyll a fluorescence transient. The antioxidant system was not fully activated (decreased superoxide dismutase, peroxidase and glutathione reductase) under ANT + FLU, then hydrogen peroxide (H₂O₂) content (by 2.7-fold) and thiobarbituric acid reactive substances (TBARS) (by 2.8-fold) increased. Interestingly, ANT + PS and FLU + PS improved the growth, water relations and gas exchange parameters. The presence of nanoplastics recovered the adverse effects of ANT and FLU on growth by protecting the photosynthetic photochemistry and reducing oxidative stress. PAH plus PS reduced the ANT and FLU accumulation in wheat leaves. In parallel, the increased antioxidant system, regeneration of ascorbate, glutathione and glutathione redox status observed under ANT + PS and FLU + PS. These findings will provide an information about the phytotoxicity mechanisms of mixed pollutants in the environment.

For the first time, we used targeted metabolome to investigate the effects of pH-aluminum (Al) interactions on energy-rich compounds and their metabolites (ECMs) and phytohormones in sweet orange (Citrus sinensis) roots. The concentration of total ECMs (TECMs) was reduced by Al-toxicity in 4.0-treated roots, but unaffected significantly in pH 3.0-treated roots. However, the concentrations of most ECMs and TECMs were not lower in pH 4.0 + 1.0 mM Al-treated roots (P4AR) than in pH 3.0 + 1.0 mM Al-treated roots (P3AR). Increased pH improved the adaptability of ECMs to Al-toxicity in roots. For example, increased pH improved the utilization efficiency of ECMs and the conversion of organic phosphorus (P) from P-containing ECMs into available phosphate in Al-treated roots. We identified upregulated cytokinins (CKs), downregulated jasmonic acid (JA), methyl jasmonate (MEJA) and jasmonates (JAs), and unaltered indole-3-acetic acid (IAA) and salicylic acid (SA) in P3AR vs pH 3.0 + 0 mM Al-treated roots (P3R); upregulated JA, JAs and IAA, downregulated total CKs, and unaltered MEJA and SA in P4AR vs pH 4.0 + 0 mM Al-treated roots (P4R); and upregulated CKs, downregulated JA, MEJA, JAs and SA, and unaltered IAA in P3AR vs P4AR. Generally viewed, raised pH-mediated increments of JA, MEJA, total JAs, SA and IAA concentrations and reduction of CKs concentration in Al-treated roots might help to maintain nutrient homeostasis, increase Al-toxicity-induced exudation of organic acid anions and the compartmentation of Al in vacuole, and reduce oxidative stress and Al uptake, thereby conferring root Al-tolerance. In short, elevated pH-mediated mitigation of root Al-stress involved the regulation of ECMs and phytohormones.

Synthetic microfibers have been identified as the most prevalent type of microplastic in samples from aquatic, atmospheric, and terrestrial environments across the globe. Apparel washing has shown to be a major source of microfiber pollution. We used California as a case study to estimate the magnitude and fate of microfiber emissions, and to evaluate potential mitigation approaches. First, we quantified synthetic microfiber emissions and fate from apparel washing in California by developing a material flow model which connects California-specific data on synthetic fiber consumption, apparel washing, microfiber generation, and wastewater and biosolid management practices. Next, we used the model to assess the effectiveness of different interventions to reduce microfiber emissions to natural environments. We estimate that in 2019 as much as 2.2 kilotons (kt) of synthetic microfibers were generated by apparel washing in California, a 26% increase since 2008. The majority entered terrestrial environments (1.6 kt), followed by landfills (0.4 kt), waterbodies (0.1 kt), and incineration (0.1 kt). California's wastewater treatment network was estimated to divert 95% of microfibers from waterbodies, mainly to terrestrial environments and primarily via land application of biosolids. Our analysis also reveals that application of biosolids on agricultural lands facilitates a directional flow of microfibers from higher-income urban counties to lower-income rural communities. Without interventions, annual synthetic microfiber emissions to California's natural environments are expected to increase by 17% to 2.1 kt by 2026. Further increasing the microfiber retention efficiency at the wastewater treatment plant would increase emissions to terrestrial environments, which suggests that microfibers should be removed before entering the wastewater system. In our model, full adoption of in-line filters in washing machines decreased annual synthetic microfiber emissions to natural environments by 79% to 0.5 kt and offered the largest reduction of all modeled scenarios.

Mine waste classification preceding mining constitutes a proactive solution to classify and segregate mine waste into geo-environmental domains based upon the magnitude of their environmental risks. However, upstream classification requires multi-disciplinary and integrated approaches. This study integrates geological modeling and kinetic modeling to inform upstream mine waste classification based on the pH generated from the main acid-generating and acid-neutralizing reactions once the mine solid waste is stored in oxidizing conditions. Geological models were used to depict the ante-mining spatial distribution of the main reactive minerals: pyrite, albite and calcite. Subsequently, the corresponding block models were created. The dimension of the elementary voxels for each block model was set at 40х40х40 m for this study. The kinetic modeling approach was performed using PHREEQC and VS2DRTI to consider unsaturated conditions. The kinetic modeling simulated a 1D column for each voxel. The column simulates the excavated state of the hosting rock involving kinetic reactions and unsaturated flow under highly oxidizing conditions. Subsequently, the resulting pH for different intervals of time was assigned to its respective voxel. The outcome consists of a spatio-temporal visualization of the pH defining ante-mining geo-environmental domains, thereby providing the opportunity for formulating proactive management measures regarding the hazardous geo-environmental domains.

Due to the large-scale outbreak of Corona Virus Disease (2019), amounts of disinfecting agents was regularly used in public environments and their potential toxicity towards organisms needed to be appreciated. Thus, one mostly used cationic disinfectant, benzalkonium chlorides (BAC(C12)), was selected to assess its potential toxicity one common cyanobacteria Microcystis aeruginosa (M. aeruginosa) in this study. The aims were to explore the toxic effect and mechanism of BAC (C12) on M. aeruginosa growth within 96 h via morphological, physiological, and the relative and absolute quantification (iTRAQ)-based quantitative proteomics variations. The results found that BAC(C12) significantly inhibited cell density of M. aeruginosa at concentrations from 1 mg/L to 10 mg/L, and the 96-h EC₅₀ value was identified to be 3.61 mg/L. Under EC₅₀ concentration, BAC(C12) depressed the photosynthesis activities of M. aeruginosa exhibited by 36% decline of the maximum quantum yield for primary photochemistry (Fv/Fm) value and denaturation of photosynthetic organelle, caused oxidative stress response displayed by the increase of three indexes including superoxide dismutase (SOD), malondialdehyde (MDA), and the intracellular reactive oxygen species (ROS), and destroyed the integrity of cell membranes demonstrated by TEM images and the increase of ex-cellular substances. Then, the iTRAQ-based proteomic analysis demonstrated that BAC(C12) depressed photosynthesis activities through inhibiting the expressions of photosynthetic protein and photosynthetic electron transport related proteins. The suppression of electron transport also led to the increase of superoxide radicals and then posed oxidative stress on cell. Meantime, the 63.63% ascent of extracellular microcystin production of M. aeruginosa was observed, attributing to the high expression of microcystin synthesis proteins and the damage of cell membrane. In sum, BAC(C12) exposure inhibited the growth of M. aeruginosa mainly by depressing photosynthesis, inducing oxidative stress, and breaking the cell membrane. And, it enhanced the release of microcystin from the cyanobacterial cells via up-regulating the microcystin synthesis proteins and inducing the membrane damage, which could enlarge its toxicity to aquatic species.

Slaughter wastewater is an important and wide range of environmental issues, and even threaten human health through meat production. A high efficiency and stability microsphere-immobilized Bacillus velezensis strain was designed to remove organic matter and inhibit the growth of harmful bacteria in process of slaughter wastewater. Bacillus velezensis was immobilized on the surface of sodium alginate (SA)/Polyvinyl alcohol (PVA)/Nano Zinc Oxide (Nano-ZnO) microsphere with the adhesion to bio-carrier through direct physical adsorption. Results indicated that SA/PVA/ZnO and SA/ZnO microspheres could inhibit E.coli growth with adding 0.15 g/L nano-ZnO and not affect Bacillus velezensis strain, and the removal the chemical oxygen demand (COD) rates of SA/PVA/ZnO microsphere immobilized cells are 16.99%, followed by SA/ZnO (13.69%) and free bacteria (7.61%) from 50% concentration slaughter wastewater within 24 h at 37 °C, pH 7.0, and 120 rpm, a significant difference was found between the microsphere and control group. Moreover, when the processing time reaches 36 h, COD degradation of SA/PVA/ZnO microsphere is obviously higher than other groups (SA/PVA/ZnO:SA/ZnO:control vs 18.535 : 15.446: 10.812). Similar results were obtained from 30% concentration slaughter wastewater. Moreover, protein degradation assay was detected, and there are no significant difference (SA/PVA/ZnO:SA/ZnO:control vs 35.4 : 34.4: 36.0). The design of this strategy could greatly enhance the degradation efficiency, inhibit the growth of other bacteria and no effect on the activity of protease in slaughter wastewater. These findings suggested that the nano-ZnO hydrogel immobilization Bacillus velezensis system wastewater treatment is a valuable alternative method for the remediation of pollutants from slaughter wastewater with a novel and eco-friendly with low-cost investment as an advantage.

A growing number of studies report associations between air pollution and COVID-19 mortality. Most were ecological studies at the county or regional level which disregard important local variability and relied on data from only the first few months of the pandemic. Using COVID-19 deaths identified from death certificates in California, we evaluated whether long-term ambient air pollution was related to weekly COVID-19 mortality at the census tract-level during the first ∼12 months of the pandemic. Weekly COVID-19 mortality for each census tract was calculated based on geocoded death certificate data. Annual average concentrations of ambient particulate matter <2.5 μm (PM₂.₅) and <10 μm (PM₁₀), nitrogen dioxide (NO₂), and ozone (O₃) over 2014–2019 were assessed for all census tracts using inverse distance-squared weighting based on data from the ambient air quality monitoring system. Negative binomial mixed models related weekly census tract COVID-19 mortality counts to a natural cubic spline for calendar week. We included adjustments for potential confounders (census tract demographic and socioeconomic factors), random effects for census tract and county, and an offset for census tract population. Data were analyzed as two study periods: Spring/Summer (March 16-October 18, 2020) and Winter (October 19, 2020–March 7, 2021). Mean (standard deviation) concentrations were 10.3 (2.1) μg/m³ for PM₂.₅, 25.5 (7.1) μg/m³ for PM₁₀, 11.3 (4.0) ppb for NO₂, and 42.8 (6.9) ppb for O₃. For Spring/Summer, adjusted rate ratios per standard deviation increase were 1.13 (95% confidence interval: 1.09, 1.17) for PM₂.₅, 1.16 (1.11, 1.21) for PM₁₀, 1.06 (1.02, 1.10) for NO₂, and 1.09 (1.04, 1.14) for O₃. Associations were replicated in Winter, although they were attenuated for PM₂.₅ and PM₁₀. Study findings support a relation between long-term ambient air pollution exposure and COVID-19 mortality. Communities with historically high pollution levels might be at higher risk of COVID-19 mortality.

Soil contamination by potentially toxic elements (PTEs) is one of the greatest threats to environmental degradation. Knowing where PTEs accumulated in soil can mitigate their adverse effects on plants, animals, and human health. We evaluated the potential of using long-term remote sensing images that reveal the bare soils, to detect and map PTEs in agricultural fields. In this study, 360 soil samples were collected at the superficial layer (0–20 cm) in a 2574 km² agricultural area located in São Paulo State, Brazil. We tested the Soil Synthetic Image (SYSI) using Landsat TM/ETM/ETM+, Landsat OLI, and Sentinel 2 images. The three products have different spectral, temporal, and spatial resolutions. The time series multispectral images were used to reveal areas with bare soil and their spectra were used as predictors of soil chromium, iron, nickel, and zinc contents. We observed a strong linear relationship (−0.26 > r > −0.62) between the selected PTEs and the near infrared (NIR) and shortwave infrared (SWIR) bands of Sentinel (ensemble of 4 years of data), Landsat TM (35 years data), and Landsat OLI (4 years data). The clearest discrimination of soil PTEs was obtained from SYSI using a long term Landsat 5 collection over 35 years. Satellite data could efficiently detect the contents of PTEs in soils due to their relation with soil attributes and parent materials. Therefore, distinct satellite sensors could map the PTEs on tropics and assist in understanding their spatial dynamics and environmental effects.

Understanding the arsenic (As) enrichment mechanisms in the subsurface environment relies on a systematic investigation of As valence species and their partitioning with the Fe (oxyhydr)oxide phases in the subsoil profile. The present study explored the distribution, speciation, partitioning, and (im)mobilization of As associated with Fe in four subsoil cores (∼30 m depth) from Hong Kong using sequential chemical extraction and X-ray absorption near edge spectroscopy. The subsoil profiles exhibited relatively high concentrations of As at 26.1–982 mg/kg (median of 112 mg/kg), and the As was dominated by As(V) (85–96%) and primarily associated with the residual fraction (50.7–94.7%). A small amount of As (0.002–13.2 mg/kg) was easily mobilized from the four subsoil profiles, and a concentration of water-soluble As higher than 100 μg/L was observed for only some subsoil layers. The molar ratios of As:Fe in the oxalate-extractable Fe fraction ranged from 1.2 to 76.5 mmol/mol (median of 11.1 mmol/mol), revealing the participation of poorly crystalline Fe (oxyhydr)oxides in immobilizing most of the high geogenic As. The primary phases of ferric (oxyhydr)oxides were characterized as ferrihydrite (16–53%), lepidocrocite (0–32%), and goethite (0–62%), and these phases contributed to the sufficient ability of the subsoil to sequester 45.3–100% (median of 98.8%) of the exogenous As(V) (1.0 mg/L) in adsorption experiments. In contrast to As(V), exogenous As(III) showed a lower removal percentage (3.9–79.1%, median of 45.1%). The study revealed that the chemical speciation of As and Fe in the subsoil profiles is useful for predicting the immobilization of high geogenic As in the region, which is also helpful for the safe utilization of As-containing soil during land development worldwide.