China’s carbon neutrality: an extensive and profound systemic reform

● China has pledged ambitious carbon peak and neutrality goals for mitigating global climate change. ● Major challenges to achieve carbon neutrality in China are summarized. ● The new opportunities along the pathway of China’s carbon neutrality are discussed from four aspects. ● Five policy suggestions for China are provided. China is the largest developing economy and carbon dioxide emitter in the world, the carbon neutrality goal of which will have a profound influence on the mitigation pathway of global climate change. The transition towards a carbon-neutral society is integrated into the construction of ecological civilization in China, and brings profound implications for China’s socioeconomic development. Here, we not only summarize the major challenges in achieving carbon neutrality in China, but also identify the four potential new opportunities: namely, the acceleration of technology innovations, narrowing regional disparity by reshaping the value of resources, transforming the industrial structure, and co-benefits of pollution and carbon mitigation. Finally, we provide five policy suggestions and highlight the importance of balancing economic growth and carbon mitigation, and the joint efforts among the government, the enterprises, and the residents.     

Twenty years of achievements in China’s implementation of the Stockholm Convention

● China’s implementation of the SC was systematically studied. ● Implementation process of the SC can be roughly divided into three stages. ● DDT and HCH concentrations in the air have been steadily decreasing. ● China has safely disposed of 6352.1 tons of pesticide POPs. Persistent organic pollutants (POPs) are extremely harmful to the environment and human health; the Stockholm Convention on Persistent Organic Pollutants was therefore adopted by the international community in 2001 to eliminate or reduce the production, use, and emissions of POPs. China is the largest developing country that has signed the Stockholm Convention, and thus plays an important role in its implementation. This paper systematically studies the practice and achievements of China since it signed the Stockholm Convention 20 years ago. China has established an implementation guarantee system including institutions, implementation mechanisms, policies, law enforcement, and scientific and technological support. During the 20 years since the implementation of the Stockholm Convention, dichlorodiphenyltrichloroethane (DDT) and hexachlorocyclohexane (HCH) concentrations in the air have been steadily decreasing, and Perfluorooctane sulfonic acid/Perfluorooctane sulfonyl fluoride (PFOS/PFOSF) concentrations in water bodies have decreased. In the past 20 years, China has safely disposed of 6352.1 tons of pesticide persistent organic pollutants and 36998 sets of electrical equipment containing polychlorinated biphenyls (PCBs), with a disposal rate of 100%. In the future, China will further strengthen the construction of persistent organic pollutant monitoring networks, scientific research, publicity, education, and international cooperation to improve environmental quality, providing a reference for other countries to implement the Stockholm Convention.     

Responses of microbial interactions to elevated salinity in activated sludge microbial community

● Salinity led to the elevation of NAR over 99.72%. ● Elevated salinity resulted in a small, complex, and more competitive network. ● Various AOB or denitrifiers responded differently to elevated salinity. ● Putative keystone taxa were dynamic and less abundant among various networks. Biological treatment processes are critical for sewage purification, wherein microbial interactions are tightly associated with treatment performance. Previous studies have focused on assessing how environmental factors (such as salinity) affect the diversity and composition of the microbial community but ignore the connections among microorganisms. Here, we described the microbial interactions in response to elevated salinity in an activated sludge system by performing an association network analysis. It was found that higher salinity resulted in low microbial diversity, and small, complex, more competitive overall networks, leading to poor performance of the treatment process. Subnetworks of major phyla (Proteobacteria, Bacteroidetes, and Chloroflexi) and functional bacteria (such as AOB, NOB and denitrifiers) differed substantially under elevated salinity process. Compared with subnetworks of Nitrosomonadaceae, Nitrosomonas (AOB) made a greater contribution to nitrification under higher salinity (especially 3%) in the activated sludge system. Denitrifiers established more proportion of cooperative relationships with other bacteria to resist 3% salinity stress. Furthermore, identified keystone species playing crucial roles in maintaining process stability were dynamics and less abundant under salinity disturbance. Knowledge gleaned from this study deepened our understanding of microbial interaction in response to elevated salinity in activated sludge systems.     

Property-performance relationship of core-shell structured black TiO2 photocatalyst for environmental remediation

● Properties and performance relationship of CSBT photocatalyst were investigated. ● Properties of CSBT were controlled by simply manipulating glycerol content. ● Performance was linked to semiconducting and physicochemical properties. ● CSBT (W:G ratio 9:1) had better performance with lower energy consumption. ● Phenols were reduced by 48.30% at a cost of $2.4127 per unit volume of effluent. Understanding the relationship between the properties and performance of black titanium dioxide with core-shell structure (CSBT) for environmental remediation is crucial for improving its prospects in practical applications. In this study, CSBT was synthesized using a glycerol-assisted sol-gel approach. The effect of different water-to-glycerol ratios (W:G = 1:0, 9:1, 2:1, and 1:1) on the semiconducting and physicochemical properties of CSBT was investigated. The effectiveness of CSBT in removing phenolic compounds (PHCs) from real agro-industrial wastewater was studied. The CSBT synthesized with a W:G ratio of 9:1 has optimized properties for enhanced removal of PHCs. It has a distinct core-shell structure and an appropriate amount of Ti³⁺ cations (11.18%), which play a crucial role in enhancing the performance of CSBT. When exposed to visible light, the CSBT performed better: 48.30% of PHCs were removed after 180 min, compared to only 21.95% for TiO₂ without core-shell structure. The CSBT consumed only 45.5235 kWh/m³ of electrical energy per order of magnitude and cost $2.4127 per unit volume of treated agro-industrial wastewater. Under the conditions tested, the CSBT demonstrated exceptional stability and reusability. The CSBT showed promising results in the treatment of phenols-containing agro-industrial wastewater.     

Technologies for pollutant removal and resource recovery from blackwater: a review

● Blackwater is the main source of organics and nutrients in domestic wastewater. ● Various treatment methods can be applied for resource recovery from blackwater. ● Blackwater treatment systems of high integration and efficiency are the future trend. ● More research is needed for the practical use of blackwater treatment systems. Blackwater (BW), consisting of feces, urine, flushing water and toilet paper, makes up an important portion of domestic wastewater. The improper disposal of BW may lead to environmental pollution and disease transmission, threatening the sustainable development of the world. Rich in nutrients and organic matter, BW could be treated for resource recovery and reuse through various approaches. Aimed at providing guidance for the future development of BW treatment and resource recovery, this paper presented a literature review of BWs produced in different countries and types of toilets, including their physiochemical characteristics, and current treatment and resource recovery strategies. The degradation and utilization of carbon (C), nitrogen (N) and phosphorus (P) within BW are underlined. The performance of different systems was classified and summarized. Among all the treating systems, biological and ecological systems have been long and widely applied for BW treatment, showing their universality and operability in nutrients and energy recovery, but they are either slow or ineffective in removal of some refractory pollutants. Novel processes, especially advanced oxidation processes (AOPs), are becoming increasingly extensively studied in BW treatment because of their high efficiency, especially for the removal of micropollutants and pathogens. This review could serve as an instructive guidance for the design and optimization of BW treatment technologies, aiming to help in the fulfilment of sustainable human excreta management.     

Catalytic reduction of water pollutants: knowledge gaps,lessons learned,and new opportunities

● Advances, challenges, and opportunities for catalytic water pollutant reduction. ● Cases of Pd-based catalysts for nitrate, chlorate, and perchlorate reduction. ● New functionalities developed by screening and design of catalytic metal sites. ● Facile catalyst preparation approaches for convenient catalyst optimization. ● Rational design and non-decorative effort are essential for future work. In this paper, we discuss the previous advances, current challenges, and future opportunities for the research of catalytic reduction of water pollutants. We present five case studies on the development of palladium-based catalysts for nitrate, chlorate, and perchlorate reduction with hydrogen gas under ambient conditions. We emphasize the realization of new functionalities through the screening and design of catalytic metal sites, including (i) platinum group metal (PGM) nanoparticles, (ii) the secondary metals for improving the reaction rate and product selectivity of nitrate reduction, (iii) oxygen-atom-transfer metal oxides for chlorate and perchlorate reduction, and (iv) ligand-enhanced coordination complexes for substantial activity enhancement. We also highlight the facile catalyst preparation approach that brought significant convenience to catalyst optimization. Based on our own studies, we then discuss directions of the catalyst research effort that are not immediately necessary or desirable, including (1) systematic study on the downstream aspects of under-developed catalysts, (2) random integration with hot concepts without a clear rationale, and (3) excessive and decorative experiments. We further address some general concerns regarding using H₂ and PGMs in the catalytic system. Finally, we recommend future catalyst development in both “fundamental” and “applied” aspects. The purpose of this perspective is to remove major misconceptions about reductive catalysis research and bring back significant innovations for both scientific advancements and engineering applications to benefit environmental protection.     

Effect of ambient polycyclic aromatic hydrocarbons and nicotine on the structure of Aβ42 protein

● B[a]P, nicotine and phenanthrene molecules altered the secondary structure of Aβ₄₂. ● β-content of the peptide was significantly enhanced in the presence of the PAHs. ● Nicotine made stable cluster with Aβ₄₂ peptide via hydrogen bonds. ● Phenanthrene due to its small size, interfered with the Aβ₄₂ monomer more strongly. Recent studies have correlated the chronic impact of ambient environmental pollutants like polycyclic aromatic hydrocarbons (PAHs) with the progression of neurodegenerative disorders, either by using statistical data from various cities, or via tracking biomarkers during in-vivo experiments. Among different neurodegenerative disorders, PAHs are known to cause increased risk for Alzheimer’s disease, related to the development of amyloid beta (Aβ) peptide oligomers. However, the complex molecular interactions between peptide monomers and organic pollutants remains obscured. In this work, we performed an atomistic molecular dynamics study via GROMACS to investigate the structure of Aβ₄₂ peptide monomer in the presence of benzo[a]pyrene, nicotine, and phenanthrene. Interestingly the results revealed strong hydrophobic, and hydrogen-bond based interactions between Aβ peptides and these environmental pollutants that resulted in the formation of stable intermolecular clusters. The strong interactions affected the secondary structure of the Aβ₄₂ peptide in the presence of the organic pollutants, with almost 50 % decrease in the α-helix and 2 %–10 % increase in the β-sheets of the peptide. Overall, the undergoing changes in the secondary structure of the peptide monomer in the presence of the pollutants under the study indicates an enhanced formation of Aβ peptide oligomers, and consequent progression of Alzheimer’s disease.     

Evaluating the impact of sulfamethoxazole on hydrogen production during dark anaerobic sludge fermentation

● SMX promotes hydrogen production from dark anaerobic sludge fermentation. ● SMX significantly enhances the hydrolysis and acidification processes. ● SMX suppresses the methanogenesis process in order to reduce hydrogen consumption. ● SMX enhances the relative abundance of hydrogen-VFAs producers. ● SMX brings possible environmental risks due to the enrichment of ARGs. The impact of antibiotics on the environmental protection and sludge treatment fields has been widely studied. The recovery of hydrogen from waste activated sludge (WAS) has become an issue of great interest. Nevertheless, few studies have focused on the impact of antibiotics present in WAS on hydrogen production during dark anaerobic fermentation. To explore the mechanisms, sulfamethoxazole (SMX) was chosen as a representative antibiotic to evaluate how SMX influenced hydrogen production during dark anaerobic fermentation of WAS. The results demonstrated SMX promoted hydrogen production. With increasing additions of SMX from 0 to 500 mg/kg TSS, the cumulative hydrogen production elevated from 8.07 ± 0.37 to 11.89 ± 0.19 mL/g VSS. A modified Gompertz model further verified that both the maximum potential of hydrogen production (P_m) and the maximum rate of hydrogen production (R_m) were promoted. SMX did not affected sludge solubilization, but promoted hydrolysis and acidification processes to produce more hydrogen. Moreover, the methanogenesis process was inhibited so that hydrogen consumption was reduced. Microbial community analysis further demonstrated that the introduction of SMX improved the abundance of hydrolysis bacteria and hydrogen-volatile fatty acids (VFAs) producers. SMX synergistically influenced hydrolysis, acidification and acetogenesis to facilitate the hydrogen production.     

Collaborative control of fine particles and ozone required in China for health benefit

● Increased DAAO offsets 3/4 of the decrease of DAAP in 2013–2020. ● DAAO increases are mainly due to O₃ concentration increase and population aging. ● Health benefit from PM_2.5 reduction after 2017 is larger than that before 2017. ● Reducing PM_2.5 concentration by 1% results in 0.6% reduction of DAAP. ● Reducing O₃ concentration by 1% results in 2% reduction of DAAO. PM_2.5 concentration declined significantly nationwide, while O₃ concentration increased in most regions in China in 2013–2020. Recent evidences proved that peak season O₃ is related to increased death risk from non-accidental and respiratory diseases. Based on these new evidences, we estimate excess deaths associated with long-term exposure to ambient PM_2.5 and O₃ in China following the counterfactual analytic framework from Global Burden Disease. Excess deaths from non-accidental diseases associated with long-term exposure to ambient O₃ in China reaches to 579 (95% confidential interval (CI): 93, 990) thousand in 2020, which has been significantly underestimated in previous studies. In addition, the increased excess deaths associated with long-term O₃ exposure (234 (95% CI: 177, 282) thousand) in 2013–2020 offset three quarters of the avoided excess deaths (302 (95% CI: 244, 366) thousand) mainly due to PM_2.5 exposure reduction. In key regions (the North China Plain, the Yangtze River Delta and the Fen-Wei Plain), the former is even larger than the latter, particularly in 2017–2020. Health benefit of PM_2.5 concentration reduction offsets the adverse effects of population growth and aging on excess deaths attributed to PM_2.5 exposure. Increase of excess deaths associated with O₃ exposure is mainly due to the strong increase of O₃ concentration, followed by population aging. Considering the faster population aging process in the future, collaborative control, and faster reduction of PM_2.5 and O₃ are needed to reduce the associated excess deaths.     

PM2.5 concentration declining saves health expenditure in China

● Monthly hospitalization expenses are sensitive to increases in PM_2.5 exposure. ● The increased PM_2.5 causes patients with CHD and LRI to stay longer in the hospital. ● The impact of PM_2.5 on total expenses for stroke is greater in southern China. ● Males may be more sensitive to air pollution than females. Air pollution has been a severe issue in China. Exposure to PM_2.5 has adverse health effects and causes economic losses. This study investigated the economic impact of exposure to PM_2.5 pollution using monthly city-level data covering 88.5 million urban employees in 2016 and 2017. This study mainly focused on three expenditure indicators to measure the economic impact considering lower respiratory infections (LRIs), coronary heart disease (CHD), and stroke. The results show that a 10 µg/m³ increase in PM_2.5 would cause total monthly expenses of LRIs, CHD, and stroke to increase by 0.226%, 0.237%, and 0.374%, respectively. We also found that LRI, CHD, and stroke hospital admissions increased significantly by 10%, 8.42%, and 5.64%, respectively. Furthermore, the total hospital stays of LRIs, CHDs, and strokes increased by 2.49%, 2. 51%, and 1.64%, respectively. Our findings also suggest heterogeneous impacts of PM_2.5 exposures by sex and across regions, but no statistical evidence shows significant differences between the older and younger adult subgroups. Our results provide several policy implications for reducing unequal public health expenditures in overpolluted countries.     

Adsorption behavior of imidacloprid pesticide on polar microplastics under environmental conditions: critical role of photo-aging

● Small molecular chains formed on photo-aged polylactic acid microplastics (MPs). ● Oxygen-containing functional groups generated on photo-aged polyamide MPs. ● Photo-aging has the opposite influence on the imidacloprid adsorption on two MPs. ● Electrostatic interactions and hydrogen bonds were the main mechanisms. ● High pH value and low ionic strength increase the adsorption capacity. The photo-aging behavior of microplastics (MPs) in natural environment has become a global concern. The ultraviolet radiation has enough energy to change the polymer structure and physical-chemical properties of MPs. Less attention has focused on the interactions of the photo-aged polar and biodegradable MPs with organic pollutants. This work investigated the structural properties of aged polar polyamide (PA) MPs and biodegradable polylactic acid (PLA) MPs exposed to ultraviolet irradiation and their adsorption behavior and mechanism for neonicotinoid insecticide imidacloprid (IMI). The results showed that the MPs had extensive changes in surface morphology and chemical properties after photo-aging. The C–N bond of PA MPs was disrupted to form more carbonyl groups. The oxygen-containing functional groups on the surface of aged PLA MPs were broken and generated relatively smaller molecules. The adsorption capacity of IMI on PA MPs decreased by 19.2 %, while the adsorption capacity of IMI on PLA MPs increased by 41.2 % after photo-aging. This depended on the natural structure of the MPs and their ability to absorb ultraviolet light. The electrostatic interactions, hydrogen bonds, van der Waals interactions, and polar-polar interactions were the main adsorption mechanisms of IMI on MPs. High initial solution pH and low ionic strength favored the adsorption of IMI by altering charge distribution on the MPs surface. The formation of the humic acid-IMI complexes decreased the concentration of IMI in the water phase and further decreased the adsorption on MPs. These results are enlightening for a scientific comprehension of the environmental behavior of the polar MPs.     

Spatial prediction of soil contamination based on machine learning: a review

● A review of machine learning (ML) for spatial prediction of soil contamination. ● ML have achieved significant breakthroughs for soil contamination prediction. ● A structured guideline for using ML in soil contamination is proposed. ● The guideline includes variable selection, model evaluation, and interpretation. Soil pollution levels can be quantified via sampling and experimental analysis; however, sampling is performed at discrete points with long distances owing to limited funding and human resources, and is insufficient to characterize the entire study area. Spatial prediction is required to comprehensively investigate potentially contaminated areas. Consequently, machine learning models that can simulate complex nonlinear relationships between a variety of environmental conditions and soil contamination have recently become popular tools for predicting soil pollution. The characteristics, advantages, and applications of machine learning models used to predict soil pollution are reviewed in this study. Satisfactory model performance generally requires the following: 1) selection of the most appropriate model with the required structure; 2) selection of appropriate independent variables related to pollutant sources and pathways to improve model interpretability; 3) improvement of model reliability through comprehensive model evaluation; and 4) integration of geostatistics with the machine learning model. With the enrichment of environmental data and development of algorithms, machine learning will become a powerful tool for predicting the spatial distribution and identifying sources of soil contamination in the future.     

A critical review of the emerging research on the detection and assessment of microplastics pollution in the coastal,marine, and urban Bangladesh

● Coastal and marine regions are the most studied for microplastic pollution. ● Tourism is a major cause of microplastic pollution in coastal regions. ● Sediments contain larger microplastics while fish ingest smaller microplastics. ● Inland lakes, rivers, and freshwater fish are impacted by microplastic pollution. ● Microplastics are found in edible salts, however, presence is less in refined salt. The research on the extent and effects of microplastics pollution in the Global South is only getting started. Bangladesh is a South Asian country with one of the fastest growing economies in the world, however, such exponential economic growth has also increased the pollution threats to its natural and urban environment. In this paper, we reviewed the recent primary research on the assessment of the extent of microplastics pollution in Bangladesh. From the online databases, we developed a compilation of emerging research articles that detected and quantified microplastics in different coastal, marine, and urban environments in Bangladesh. Most of the studies focused on the coastal environment (e.g., beach sediment) and marine fish, while limited data were available for the urban environment. We also discussed the relationship of the type of anthropogenic activities with the observed microplastic pollution. The Cox’s Bazar sea beach in south-east Bangladesh experienced microplastics pollution due to tourism activities, while fishing and other anthropogenic activities led to microplastics pollution in the Bay of Bengal. While microplastics larger than 1 mm were prevalent in the beach sediments, smaller microplastics with size below 0.5 mm were prevalent in marine fish samples. Moreover, the differences in microplastic abundance, size, shape, color, and polymer type found were depended on the sampling sites and relevant anthropogenic activities. It is imperative to identify major sources of microplastics pollution in both natural and urban environment, determine potential environmental and human health effects, and develop mitigating and prevention strategies for reducing microplastics pollution.     

Differences in distributions,assembly mechanisms,and putative interactions of AOB and NOB at a large spatial scale

● Nitrifiers in WWTP were investigated at large spatial scale. ● AOB populations varied greatly but NOB populations were similar among cities. ● Drift dominated both AOB and NOB assembling processes. ● DO did not show a significant effect on NOB. ● NOB tended to cooperate with AOB and non-nitrifying microorganisms. Ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) play crucial roles in removing nitrogen from sewage in wastewater treatment plants (WWTPs) to protect water resources. However, the differences in ecological properties and putative interactions of AOB and NOB in WWTPs at a large spatial scale remain unclear. Hence, 132 activated sludge (AS) samples collected from 11 cities across China were studied by utilizing 16S rRNA gene sequencing technology. Results indicated that Nitrosomonas and Nitrosospira accounted for similar ratios of the AOB community and might play nearly equal roles in ammonia oxidation in AS. However, Nitrospira greatly outnumbered other NOB genera, with proportions varying from 94.7% to 99.9% of the NOB community in all WWTPs. Similar compositions and, hence, a low distance–decay turnover rate of NOB (0.035) across China were observed. This scenario might have partly resulted from the high proportions of homogenizing dispersal (~13%). Additionally, drift presented dominant roles in AOB and NOB assembling mechanisms (85.2% and 81.6% for AOB and NOB, respectively). The partial Mantel test illustrated that sludge retention time and temperature were the primary environmental factors affecting AOB and NOB communities. Network results showed that NOB played a leading role in maintaining module structures and node connections in AS. Moreover, most links between NOB and other microorganisms were positive, indicating that NOB were involved in complex symbioses with bacteria in AS.     

Prediction and cause investigation of ozone based on a double-stage attention mechanism recurrent neural network

● Used a double-stage attention mechanism model to predict ozone. ● The model can autonomously select the appropriate time series for forecasting. ● The model outperforms other machine learning models and WRF-CMAQ. ● We used the model to analyze the driving factors of VOCs that cause ozone pollution. Ozone is becoming a significant air pollutant in some regions, and VOCs are essential for ozone prediction as necessary ozone precursors. In this study, we proposed a recurrent neural network based on a double-stage attention mechanism model to predict ozone, selected an appropriate time series for prediction through the input attention and temporal attention mechanisms, and analyzed the cause of ozone generation according to the contribution of feature parameters. The experimental data show that our model had an RMSE of 7.71 μg/m³ and a mean absolute error of 5.97 μg/m³ for 1-h predictions. The DA-RNN model predicted ozone closer to observations than the other models. Based on the importance of the characteristics, we found that the ozone pollution in the Jinshan Industrial Zone mainly comes from the emissions of petrochemical enterprises, and the good generalization performance of the model is proved through testing multiple stations. Our experimental results demonstrate the validity and promising application of the DA-RNN model in predicting atmospheric pollutants and investigating their causes.     

Target the neglected VOCs emission from iron and steel industry in China for air quality improvement

● Haze formation in China is highly correlated with iron and steel industry. ● VOCs generated in sinter process were neglected under current emission standard. ● Co-elimination removal of sinter flue gas complex pollutants are timely needed. Recent years have witnessed significant improvement in China’s air quality. Strict environmental protection measures have led to significant decreases in sulfur dioxide (SO₂), nitrogen oxides (NO_x), and particulate matter (PM) emissions since 2013. But there is no denying that the air quality in 135 cities is inferior to reaching the Ambient Air Quality Standards (GB 3095–2012) in 2020. In terms of temporal, geographic, and historical aspects, we have analyzed the potential connections between China’s air quality and the iron and steel industry. The non-target volatile organic compounds (VOCs) emissions from iron and steel industry, especially from the iron ore sinter process, may be an underappreciated index imposing a negative effect on the surrounding areas of China. Therefore, we appeal the authorities to pay more attention on VOCs emission from the iron and steel industry and establish new environmental standards. And different iron steel flue gas pollutants will be eliminated concurrently with the promotion and application of new technology.     

The role of lipids in fermentative propionate production from the co-fermentation of lipid and food waste

● Lipid can promote PA production on a target from food waste. ● PA productivity reached 6.23 g/(L∙d) from co-fermentation of lipid and food waste. ● Lipid promoted the hydrolysis and utilization of protein in food waste. ● Prevotella , Veillonella and norank _f _Propioni bacteriaceae were enriched. ● Main pathway of PA production was the succinate pathway. Food waste (FW) is a promising renewable low-cost biomass substrate for enhancing the economic feasibility of fermentative propionate production. Although lipids, a common component of food waste, can be used as a carbon source to enhance the production of volatile fatty acids (VFAs) during co-fermentation, few studies have evaluated the potential for directional propionate production from the co-fermentation of lipids and FW. In this study, co-fermentation experiments were conducted using different combinations of lipids and FW for VFA production. The contributions of lipids and FW to propionate production, hydrolysis of substrates, and microbial composition during co-fermentation were evaluated. The results revealed that lipids shifted the fermentation type of FW from butyric to propionic acid fermentation. Based on the estimated propionate production kinetic parameters, the maximum propionate productivity increased significantly with an increase in lipid content, reaching 6.23 g propionate/(L∙d) at a lipid content of 50%. Propionate-producing bacteria Prevotella, Veillonella, and norank_f_Propionibacteriaceae were enriched in the presence of lipids, and the succinate pathway was identified as a prominent fermentation route for propionate production. Moreover, the Kyoto Encyclopedia of Genes and Genomes functional annotation revealed that the expression of functional genes associated with amino acid metabolism was enhanced by the presence of lipids. Collectively, these findings will contribute to gaining a better understanding of targeted propionate production from FW.     

Adsorption of herring sperm DNA onto pine sawdust biochar: Thermodynamics and site energy distribution

● Adsorption of environmental deoxyribonucleic acid on biochar was studied. ● π−π interaction and electrostatic repulsion worked in the adsorption. ● Thermodynamics indicated the adsorption was spontaneous and endothermic. Environmental deoxyribonucleic acid (eDNA), which includes antibiotic resistance genes, is ubiquitous in the environment. The interactions between eDNA and biochar, a promising material widely used in soil amendment and water treatment, greatly affect the environmental behavior of eDNA. Hitherto few experimental evidences are available yet, especially on the information of thermodynamics and energy distribution to explains the interactions between biochar and eDNA. This study investigated the adsorption of herring sperm DNA (hsDNA) on pine sawdust biochar, with a specific emphasis on the adsorption thermodynamics and site energy distribution. The adsorption of hsDNA on biochar was enhanced by an increase in the pyrolysis and adsorption temperatures. The higher surface area, stronger π−π interaction, and weaker electrostatic repulsion between hsDNA and biochars prepared at high pyrolysis temperatures facilitated the adsorption of hsDNA. The thermodynamics indicated that the adsorption of hsDNA on biochar was spontaneous and endothermic. Therefore, higher temperature was beneficial for the adsorption of hsDNA on biochar; this was well explained by the increase in E^* and F(E^*) with the adsorption temperature. These results are useful for evaluating the migration and transformation of eDNA in the presence of biochar.     

Discovery of emerging organic pollutants in the atmosphere through an omics approach

● We review the framework of discovering emerging pollutants through an omics approach. ● High-resolution MS can digitalize atmospheric samples to full-component data. ● Chemical features and databases can help to translate untargeted data to compounds. ● Biological effect-directed untargeted analyses consider both existence and toxicity. Ambient air pollution, containing numerous known and hitherto unknown compounds, is a major risk factor for public health. The discovery of harmful components is the prerequisite for pollution control; however, this raises a great challenge on recognizing previously unknown species. Here we systematically review the analytical techniques on air pollution in the framework of an omics approach, with a brief introduction on sample preparation and analysis, and in more detail, compounds prioritization and identification. Through high-resolution mass spectrometry (HRMS, typically coupled with chromatography), the complicated environmental matrix can be digitalized into “full-component” data. A key step to discover emerging compounds is the prioritization of compounds from massive data. Chemical fingerprints, suspect lists and biological effects are the most vital untargeted strategies for comprehensively screening critical and hazardous substances. Afterward, compressed data of compounds can be identified at various confidence levels according to exact mass and the derived molecular formula, MS libraries, and authentic standards. Such an omics approach on full-component data provides a paradigm for discovering emerging air pollutants; nonetheless, new technological advancements of instruments and databases are warranted for further tracking the environmental behaviors, hence to evaluate the health risk of key pollutants.     

Source identification and prediction of nitrogen and phosphorus pollution of Lake Taihu by an ensemble machine learning technique

● A machine learning model was used to identify lake nutrient pollution sources. ● XGBoost model showed the best performance for lake water quality prediction. ● Model feature size was reduced by screening the key features with the MIC method. ● TN and TP concentrations of Lake Taihu are mainly affected by endogenous sources. ● Next-month lake TN and TP concentrations were predicted accurately. Effective control of lake eutrophication necessitates a full understanding of the complicated nitrogen and phosphorus pollution sources, for which mathematical modeling is commonly adopted. In contrast to the conventional knowledge-based models that usually perform poorly due to insufficient knowledge of pollutant geochemical cycling, we employed an ensemble machine learning (ML) model to identify the key nitrogen and phosphorus sources of lakes. Six ML models were developed based on 13 years of historical data of Lake Taihu’s water quality, environmental input, and meteorological conditions, among which the XGBoost model stood out as the best model for total nitrogen (TN) and total phosphorus (TP) prediction. The results suggest that the lake TN is mainly affected by the endogenous load and inflow river water quality, while the lake TP is predominantly from endogenous sources. The prediction of the lake TN and TP concentration changes in response to these key feature variations suggests that endogenous source control is a highly desirable option for lake eutrophication control. Finally, one-month-ahead prediction of lake TN and TP concentrations (R² of 0.85 and 0.95, respectively) was achieved based on this model with sliding time window lengths of 9 and 6 months, respectively. Our work demonstrates the great potential of using ensemble ML models for lake pollution source tracking and prediction, which may provide valuable references for early warning and rational control of lake eutrophication.