The consumption of disposable face masks increases greatly because of the outbreak of the COVID-19 pandemic. Inappropriate disposal of wasted face masks has already caused the pollution of the environment. As made from plastic nonwoven fabrics, disposable face masks could be a potential source of microplastics for the environment. In this study, we evaluated the ability of new and used disposable face masks of different types to release microplastics into the water. The microplastic release capacity of the used masks increased significantly from 183.00 ± 78.42 particles/piece for the new masks to 1246.62 ± 403.50 particles/piece. Most microplastics released from the face masks were medium size transparent polypropylene fibers originated from the nonwoven fabrics. The abrasion and aging during the using of face masks enhanced the releasing of microplastics since the increasing of medium size and blue microplastics. The face masks could also accumulate airborne microplastics during use. Our results indicated that used disposable masks without effective disposal could be a critical source of microplastics in the environment. The efficient allocation of mask resources and the proper disposal of wasted masks are not only beneficial to pandemic control but also to environmental safety.

The Menor sea is a coastal lagoon declared by the European Union as a sensitive area to eutrophication due to human activities. To control the deterioration of its water quality, it is necessary to monitor some parameters such as chlorophyll-a (chl-a), which indicates phytoplankton biomass in the water. In the study area, current efforts focus on in-situ measurements to estimate chl-a by means of a few permanent stations and seasonal oceanographic campaigns, however they are expensive and time consuming. In this work, we proposed a machine learning approach based on Sentinel-2 data to estimate chl-a content on the upper part of the water column. Random forest (rf), support vector machine (svmRadial), Artificial Neural Network (ANN) and Deep Neural Network (DNN) algorithms were utilized under three feature selection scenarios, and several spectral indices were used in combination with Sentinel 2 bands. Rf, svmRadial and DNN performed better when all the available predictors were included in the models (RMSE = 0.82, 0.82 and 1.76 mg/m³ respectively), whereas ANN achieved better results under scenario c (principal components). Our results demonstrate the possibility to estimate chl-a concentration in a cost-effective manner and thereby provide near-real time information to monitor the water quality of the Menor sea, what can be of great interest for local authorities, tourism and fishing industry.

Microbial denitrification is a main source of nitrous oxide (N₂O) emissions which have strong greenhouse effect and destroy stratospheric ozone. Though the importance of sulfide driven chemoautotrophic denitrification has been recognized, its contribution to N₂O emissions in nature remains elusive. We built up long-term sulfide-added microcosms with sediments from two freshwater lakes. Chemistry analysis confirmed sulfide could drive nitrate respiration in long term. N₂O accumulated to over 1.5% of nitrate load in both microcosms after long-term sulfide addition, which was up to 12.9 times higher than N₂O accumulation without sulfide addition. Metagenomes were extracted and sequenced during microcosm incubations. 16 S rRNA genes of Thiobacillus and Defluviimonas were gradually enriched. The nitric oxide reductase with c-type cytochromes as electron donors (cNorB) increased in abundance, while the nitric oxide reductase receiving electrons from quinols (qNorB) decreased in abundance. cnorB genes similar to Thiobacillus were enriched in both microcosms. In parallel, enrichment was observed for enzymes involved in sulfur oxidation, which supplied electrons to nitrate respiration, and enzymes involved in Calvin Cycle, which sustained autotrophic cell growth, implying the coupling relationship between carbon, nitrogen and sulfur cycling processes. Our results suggested sulfur pollution considerably increased N₂O emissions in natural environments.

Alberta’s oil sands tailings ponds are suspected to be a source of fugitive emissions of polycyclic aromatic compounds (PACs) to the atmosphere. Here we report, for the first time, fluxes of 6 parent and 21 alkylated PACs based on the measured co-located air and water concentrations using a two-film fugacity-based model (FUG), an inverse dispersion model (DISP) and a simple box model (BOX). Air samples were collected at the Suncor Tailings Pond 2/3 using a high volume air sampler from the “pond” and towards the pond (“non-pond”) directions separately. Mean ∑₂₇PACs in air from the “pond” direction was greater than the “non-pond” direction by a factor of 17. Water-air fugacity ratio of 20 PACs quantifiable in water indicated net volatilization from water. Dispersion and box model results also indicated upward fluxes of 22 PACs. Correlation between the estimated flux results of BOX and DISP model was statistically significant (r = 0.99 and p < 0.05), and correlation between FUG and DISP results ranged from 0.54 to 0.85. In this first-ever assessment of PAC fluxes from tailings pond, the three models confirmed volatilization fluxes of PACs indicating Suncor Tailings Pond 2/3 is a source of PAC emissions to the atmosphere. This study addressed a key data gap identified in the Joint Oil Sands Monitoring Emissions Inventory Compilation Report (Government of Alberta and Canada, 2016) which is the lack of consistent real-world tailings pond fugitive emission monitoring of organic chemicals. Our findings highlight the need for measurements from other tailings ponds to determine their overall contribution in releasing PACs to the atmosphere. This paper presents a practical method for estimating PAC emissions from other tailings ponds, which can provide a better understanding of these fugitive emissions, and thereby help to improve the overall characterization of emissions in the oil sands region.

The robust and eco-friendly super-hydrophobic sponge with remarkable performances has been potential adsorption material for the treatment of offshore oil spills. In this work, the durable PDMS@SiO₂@WS₂ sponge was fabricated via a green and facile one-step dipping method. The mixed tungsten disulfide (WS₂) microparticles and hydrophobic SiO₂ nanoparticles were immobilized on the sponge by non-toxic polydimethylsiloxane (PDMS) glue tier, which featured the hierarchical structure and extreme water repellency with the water contact angle of 158.8 ± 1.4°. The obtained PDMS@SiO₂@WS₂ sponge exhibits high oil adsorption capacity with 12–112 times of its own weight, and oil/water selectivity with separation efficiency over 99.85%. Notably, when subjected to the complex marine environment including high temperature, corrosive condition, insolation, and strong wind and waves, the modified sponge can maintain sable super-hydrophobicity with water contact angle over 150°. Moreover, it possesses superior mechanical stability for sustainable reusability and oil recovery. The sponge fabricated by non-toxic modifiers along with its sable super-hydrophobicity in complex marine environment makes it a potential material for practical applications.

Acid mine drainage (AMD) is generated by the bio-oxidation of sulfide minerals. To understand the AMD formation and evolution, it is necessary to determine the composition and variation of acidophilic community, and their role in AMD ecosystem. In this study, we compared seasonal variations of geochemistry and microbial composition of two adjacent AMD lakes with different formation histories in Anhui Province, China. Lake Paitu (PT) formed in 1970s near a mine dump and the pH was in the range of 3.01–3.16, with the lowest in spring and summer while the highest in winter. The main ions in PT were Al and SO₄²⁻, whereas Fe concentration was relatively low. The concentrations of these ions were the lowest in summer and the highest in winter. Lake Tafang (TF) formed in around 2013 in a pit was more acidic (pH 2.43–2.75), but the seasonal variation of pH was the same as PT. Compared with Lake PT, TF had higher Fe, lower Al and SO₄²⁻ concentrations, and showed no significant seasonal changes. Despite salient seasonal variations of prokaryotic composition in Lake PT, Ferrovum was the major iron-oxidizing bacterium in most seasons. Furthermore, Lake PT was also rich in heterotrophic bacteria (48.6 ± 15.9%). Both prokaryotic diversity and evenness of Lake TF were lower than PT, and chemolithotrophic iron-oxidizing bacteria (71.7 ± 25.4%) were dominant in almost all samples. Besides Ferrovum, more acid tolerant iron-oxidizer Leptospirillum and Acidithiobacillus were also abundant in Lake TF. Chlamydomonas was the major eukaryote in Lake PT and it flourished repeatedly at the end of December, causing an extremely high chlorophyll a concentration (587 μg/L) at one sampling site in 2016, which provided rich nutrients for heterotrophic bacteria. The main alga in Lake TF was Chrysonebula, but its concentration was low, apparently because of the strong acidity and dark red color of lake water.

Cadmium (Cd) is a toxic heavy metal that initiates diverse chronic diseases through food chains. Developing a biotechnology for manipulating Cd uptake in plants is beneficial to reduce environmental and health risks. Here, we identified a novel epigenetic mechanism underlying Cd accumulation regulated by an uncharacterized metallochaperone namely Heavy Metal Responsive Protein (HMP) in rice plants. OsHMP resides in cytoplasm and nucleus, dominantly induced by Cd stress and binds directly to Cd ions. OsHMP overexpression enhanced the rice growth under Cd stress but accumulated more Cd, whereas knockout or knockdown of OsHMP showed a contrasting effect. The enhanced Cd accumulation in the transgenic lines was confirmed by a long-term experiment with rice growing at the environmentally realistic Cd concentration in soil. The bisulfite sequencing and chromatin immunoprecipitation assessments revealed that Cd stress reduced significantly the DNA methylation at CpG (Cytosine-Guanine) and histone H3K9me2 marks in the upstream of OsHMP. By identifying a couple of mutants defective in DNA methylation and histone modification (H3K9me2) such as Osmet1 (methylatransfease1) and Ossdg714 (kryptonite), we found that the Cd-induced epigenetic hypomethylation at the region was associated with OsHMP overexpression, which consequently led to Cd detoxification in rice. The causal relationship was confirmed by the GUS reporter gene coupled with OsHMP and OsMET1 whereby OsMET1 repressed directly the OsHMP expression. Our work signifies that expression of OsHMP is required for Cd detoxification in rice plants, and the Cd-induced hypomethylation in the specific region is responsible for the enhanced OsHMP expression. In summary, this study gained an insight into the epigenetic mechanism for additional OsHMP expression which consequently ensures rice adaptation to the Cd-contaminated environment.

In this study, a novel biosorbent is prepared from the pods of Bauhinia variegata is used for defluoridation of the fluoride contaminated water. It is an eco-friendly and economically feasible material. Comparison of adsorption capacity of Physically Treated Bauhinia (PTB) and Chemically Treated Bauhinia (CTB) are carried in this work. Characterization studies like SEM, EDS, FTIR, and XRD are executed to analyze surface morphology and functional groups in PTB and CTB. The experimental procedure was implemented in a batch process where the operating constraints such as dosage, pH, initial fluoride concentration, time, and temperature are varied to attain optimized efficiency. PTB and CTB yield an adsorption capacities of 10.90 mg/g and 15.45 mg/g respectively in the batch process. PTB adheres fluoride in monolayer formation whereas CTB forms multilayer adsorption. The adsorption process was described by the Pseudo first-order model to state the mechanism of physisorption. The negative values of thermodynamic parameters indicate spontaneity and favorable conditions for adsorption process. As CTB has a higher adsorption capacity than PTB, the batch study has been extended to column adsorption. Bed depth, initial fluoride concentration, and flow rate are the experimental variables used to acquire breakthrough curves. Simplified column models like Adam-Bohart, Thomas, and Yoon-Nelson models were analyzed. In column studies, Yoon-Nelson model fitted well in describing the process of adsorption. The maximum adsorption capacity acquired during the column process was found to be 1.176 mg/g with a bed depth of 5 cm and a flow rate of 5 ml/min. Thus, the innocuous and sustainable adsorbent is developed and serves as an excellent defluoridation agent.

To better understand air quality issues in South Korea, it is essential to identify the main contributors of air pollution and to quantify the effects of transboundary transport. In this study, geostationary satellite measurements were used to assess the effects of aerosol transport on air quality in South Korea. This study proposes a method to define the long-range transport (LRT) of aerosols into the Korean Peninsula using remote sensing obervations and back-trajectories and estimates the LRT effects on air quality in Seoul using in-situ particulate matter (PM) measurements. Aerosol optical depths (AODs) are obtained from the Geostationary Ocean Color Imager (GOCI), and the back-trajectories are from the National Ocean and Atmospheric Administration (NOAA) HYbrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. For LRT events, satellite observations showed high AOD plumes over the Yellow Sea, a pathway between Eastern China and South Korea, and the movements of aerosol plumes transported to South Korea were also detected. PM₂.₅ concentrations, PM₁₀ concentrations, and AOD during LRT increased by 52%, 49%, and 81%, respectively, relative to their average values for 2015–2018. To quantitatively characterize the LRT of aerosols, the effects of LRT on PM₂.₅ concentrations were estimated for each PM concentration category. The contribution of LRT to PM₂.₅ concentrations was estimated to be 33% during 2015–2018. When high concentrations of PM₂.₅ were observed in Seoul, they were likely to be associated with LRT events.

It has not been well understood that the binding affinity and potential toxicity of different chemical forms of selenite (Se(IV)), which are predominant forms of selenium with plant availability. The influences of pH and major anions on Se(IV) toxicity to wheat root elongation were determined in solutions and modeled based on the biotic ligand model (BLM) and free ion activity model (FIAM) concepts. Results showed that EC50[Se(IV)]T values increased from 164 to 273 μM as the pH raised from 4.5 to 8.0, indicating the increase of pH induced weakened Se(IV) toxicity. The EC50{SeO₃²⁻} values increased from 0.019 to 71.3 μM while the EC50{H₂SeO₃} values sharply decreased from 2.08 μM to 0.760 nM with the pH increasing from 4.5 to 8.0. The effect of pH on Se(IV) toxicity could be explained by the changes of Se(IV) species in different pH solutions as H₂SeO₃, HSeO₃⁻ and SeO₃²⁻ were differently toxic to wheat root elongation. The toxicity of Se(IV) decreased with increasing H₂PO₄⁻ activity but not for SO₄²⁻, NO₃⁻ and Cl⁻ activities, indicating that only H₂PO₄⁻ had a competitive effect with Se(IV) on the binding sites. A site-specific BLM was developed to count in effects of pH and H₂PO₄⁻, and stability constants of H₂SeO₃, HSeO₃⁻, SeO₃²⁻ and H₂PO₄⁻ to the binding sites were obtained: logKH2SeO3BL = 4.96, logKHSeO3BL = 3.47, logKSeO3BL = 2.56 and logKH2PO4BL = 2.00. Results implied that BLM performed much better than FIAM in the wheat root elongation prediction when coupling toxic species H₂SeO₃, HSeO₃⁻, SeO₃²⁻, and the competitions of H₂PO₄⁻ for the binding sites while developing the Se(IV)-BLM.