Cover illustration
Front Cover Story (See: Hailong Yin, Yiyuan Lin, Huijin Zhang, Ruibin Wu, Zuxin Xu , 2023, 17(7): 85)
Water quality restoration in rivers requires identification of the locations and discharges of pollution sources, and a reliable mathematical model to cost-effectively accomplish this identification is essential. A hydrodynamic-Bayesian inference model was developed to inversely estimate pollution sources for both accidental preparedness and normal management of the a
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● A better risk assessment can combine the improved non-target analysis method. ● Multi-evidence is advised in molecular determination and risk-based prioritization. ● Combining omics, multi-endpoint EDA, and machine learning to assess product risks.
The continuous input of various emerging contaminants (ECs) has inevitably introduced large amounts of transformation products (TPs) in natural and engineering water scenarios. Structurally similar to the precursor species, the TPs are expected to possess comparative, if not more serious, environmental properties and risks. This review summarizes the state-of-the-art knowledge regarding the integrated risk assessment frameworks of TPs of ECs, mainly involving the exposure- and effect-driven analysis. The inadequate information within existing frameworks that was essential and critical for developing a better risk assessment framework was discussed. The main strategic improvements include (1) non-targeted product analysis in both laboratory and field samples, (2) omics-based high-throughput toxicity assessment, (3) multichannel-driven mode of action in conjugation with effect-directed analysis, and (4) machine learning technology. Overall, this review provides a concise but comprehensive insight into the optimized strategy for evaluating the environmental risks and screening the key toxic products from the cocktail mixtures of ECs and their TPs in the global water cycle. This facilitates deciphering the mode of toxicity in complex chemical mixtures and prioritizing the regulated TPs among the unknown products, which have the potential to be considered a class of novel “ECs” of great concern.
● Monthly hospitalization expenses are sensitive to increases in PM2.5 exposure. ● The increased PM2.5 causes patients with CHD and LRI to stay longer in the hospital. ● The impact of PM2.5 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 PM2.5 has adverse health effects and causes economic losses. This study investigated the economic impact of exposure to PM2.5 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 PM2.5 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 PM2.5 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.
● Application of the MOF-composite membranes in adsorption was discussed. ● Recent application of MOFs-membranes for separation was summarized. ● Separation and degradation for emerging organic contaminants were described.
Presence of emerging organic contaminants (EOCs) in water is one of the major threats to water safety. In recent decades, an increasing number of studies have investigated new approaches for their effective removal. Among them, metal-organic frameworks (MOFs) have attracted increasing attention since their first development thanks to their tunable metal nodes and versatile, functional linkers. However, whether or not MOFs have a promising future for practical application in emerging contaminants-containing wastewater is debatable. This review summarizes recent studies about the removal of EOCs using MOFs-related material. The synthesis strategies of both MOF particles and composites, including thin-film nanocomposite and mixed matrix membranes, are critically reviewed, as well as various characterization technologies. The application of the MOF-based composite membranes in adsorption, separation (nanofiltration and ultrafiltration), and catalytic degradation are discussed. Overall, literature survey shows that MOFs-based composite could play a crucial role in eliminating EOCs in the future. In particular, modified membranes that realize separation and degradation might be the most promising materials for such application.
● A novel VMD-IGOA-LSTM model has proposed for the prediction of water quality. ● Improved model quickly converges to the global optimal fitness and remains stable. ● The prediction accuracy of water quality parameters is significantly improved.
Water quality prediction is vital for solving water pollution and protecting the water environment. In terms of the characteristics of nonlinearity, instability, and randomness of water quality parameters, a short-term water quality prediction model was proposed based on variational mode decomposition (VMD) and improved grasshopper optimization algorithm (IGOA), so as to optimize long short-term memory neural network (LSTM). First, VMD was adopted to decompose the water quality data into a series of relatively stable components, with the aim to reduce the instability of the original data and increase the predictability, then each component was input into the IGOA-LSTM model for prediction. Finally, each component was added to obtain the predicted values. In this study, the monitoring data from Dayangzhou Station and Shengmi Station of the Ganjiang River was used for training and prediction. The experimental results showed that the prediction accuracy of the VMD-IGOA-LSTM model proposed was higher than that of the integrated model of Ensemble Empirical Mode Decomposition (EEMD), the integrated model of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Nonlinear Autoregressive Network with Exogenous Inputs (NARX), Recurrent Neural Network (RNN), as well as other models, showing better performance in short-term prediction. The current study will provide a reliable solution for water quality prediction studies in other areas.
● Organic solvent extracted fewer Cd/Pb in rapeseed oil than physical pressing. ● Brassica rapa transferred fewer Cd and Pb from seed to oil than Brassica napus . ● Carcinogenic risk mainly from Cd and worth more concern than noncarcinogenic risk. ● Organic solvent specially SLB pose less heath risk for oil than physical pressing. ● Rapeseed oil posed higher carcinogenic risk for rural residents than urban.
Substitute planting with rapeseed offers promise for safely using large areas of Cd/Pb-contaminated farmland. Cd/Pb distributions during rapeseed oil production were investigated and health risks posed by the oil were assessed. Tests were performed using three cultivars (Brassica rapa SYH and ZS100 and Brassica napus QY-1) and four oil extraction techniques (mechanical and low-temperature pressing and n-hexane and subcritical low-temperature butane extraction). The amounts of Cd and Pb in oil were 0.73%–8.44% and 3.14%–11.76%, respectively, of the amounts in rapeseed and were strongly affected by the cultivar and oil extraction technique. The heavy metal (HM) concentrations were lower in solvent-extracted oil (particularly subcritical low-temperature butane extracted oil, in which HMs were not detected) than mechanically pressed oil. The Cd and Pb transfer indices were lower (meaning larger proportions of HMs were retained by the rapeseed meal) for B. rapa than B. napus. This was attributed to a high HM binding protein content of B. rapa seed. Health risks to humans were assessed using a probabilistic risk assessment model. The carcinogenic risk was mainly (97.1%–99.9%) caused by Cd and poses more concern than non-carcinogenic risk. Stronger health risks are posed by mechanically pressed than solvent-extracted oil, and higher carcinogenic risks are posed to people living in rural areas than urban areas. Substitute planting with B. rapa and extracting oil with organic solvent (preferably subcritical low-temperature butane) are optimal for safely utilizing Cd/Pb-contaminated soil. Attention should be paid to the health risks posed by Cd in oil to rural populations.
● 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.
● A hydrodynamic-Bayesian inference model was developed for water pollution tracking. ● Model is not stuck in local optimal solutions for high-dimensional problem. ● Model can estimate source parameters accurately with known river water levels. ● Both sudden spill incident and normal sewage inputs into the river can be tracked. ● Model is superior to the traditional approaches based on the test cases.
Water quality restoration in rivers requires identification of the locations and discharges of pollution sources, and a reliable mathematical model to accomplish this identification is essential. In this paper, an innovative framework is presented to inversely estimate pollution sources for both accident preparedness and normal management of the allowable pollutant discharge. The proposed model integrates the concepts of the hydrodynamic diffusion wave equation and an improved Bayesian-Markov chain Monte Carlo method (MCMC). The methodological framework is tested using a designed case of a sudden wastewater spill incident (i.e., source location, flow rate, and starting and ending times of the discharge) and a real case of multiple sewage inputs into a river (i.e., locations and daily flows of sewage sources). The proposed modeling based on the improved Bayesian-MCMC method can effectively solve high-dimensional search and optimization problems according to known river water levels at pre-set monitoring sites. It can adequately provide accurate source estimation parameters using only one simulation through exploration of the full parameter space. In comparison, the inverse models based on the popular random walk Metropolis (RWM) algorithm and microbial genetic algorithm (MGA) do not produce reliable estimates for the two scenarios even after multiple simulation runs, and they fall into locally optimal solutions. Since much more water level data are available than water quality data, the proposed approach also provides a cost-effective solution for identifying pollution sources in rivers with the support of high-frequency water level data, especially for rivers receiving significant sewage discharges.
● This study explored the long-term association by double robust additive models. ● Individual exposure concentrations were assessed by integrating GAM, LUR and BPNN. ● PM2.5, SO2 and NO2 are positively associated with cerebrovascular disease. ● CO could reduce the risk of cerebrovascular disease with the highest robustness. ● The elderly, women and people with normal BMI are at higher risk for air pollution.
The relationship between air pollution and cerebrovascular disease has become a popular topic, yet research findings are highly heterogeneous. This study aims to investigate this association based on detailed individual health data and a precise evaluation of their exposure levels. The integrated models of generalized additive model, land use regression model and back propagation neural network were used to evaluate the exposure concentrations. And doubly robust additive model was conducted to explore the association between cerebrovascular disease and air pollution after adjusted for demographic characteristics, physical examination, disease information, geographic and socioeconomic status. A total of 25097 subjects were included in the Beijing Health Management Cohort from 2013 to 2018. With a 1 μg/m3 increase in the concentrations of PM2.5, SO2 and NO2, the incidence risk of cerebrovascular disease increased by 1.02 (95% CI: 1.008–1.034), 1.06 (95% CI: 1.034–1.095) and 1.02 (95% CI: 1.010–1.029) respectively. Whereas CO exposure could decrease the risk, with an odds ratio of 0.38 (95% CI: 0.212–0.626). In the subgroup analysis, individuals under the age of 50 with normal BMI were at higher risk caused by PM2.5, and SO2 was considered more hazardous to women. Meanwhile, the protective effect of CO on women and those with normal BMI was stronger. Successful reduction of long-term exposure to PM2.5, SO2 and NO2 would lead to substantial benefits for decrease the risk of cerebrovascular disease especially for the health of the susceptible individuals.
● 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.
● Abundance of MAGs carrying ARG-VF pairs unchanged in rivers after WWTP upgrade. ● Upgrade of WWTPs significantly reduced diversity of pathogenic genera in rivers. ● Upgrade of WWTPs reduced most VF (ARG) types carried by potential pathogens in rivers. ● Upgrade of WWTPs narrowed the pathogenic host ranges of ARGs and VFs in rivers.
Wastewater treatment plants (WWTPs) with additional tertiary ultrafiltration membranes and ozonation treatment can improve water quality in receiving rivers. However, the impacts of WWTP upgrade (WWTP-UP) on pathogens carrying antibiotic resistance genes (ARGs) and virulence factors (VFs) in rivers remain poorly understood. In this study, ARGs, VFs, and their pathogenic hosts were investigated in three rivers impacted by large-scale WWTP-UP. A five-year sampling campaign covered the periods before and after WWTP-UP. Results showed that the abundance of total metagenome-assembled genomes (MAGs) containing both ARGs and VFs in receiving rivers did not decrease substantially after WWTP-UP, but the abundance of MAGs belonging to pathogenic genera that contain both ARGs and VFs (abbreviated as PAVs) declined markedly. Genome-resolved metagenomics further revealed that WWTP-UP not only reduced most types of VFs and ARGs in PAVs, but also effectively eliminated efflux pump and nutritional VFs carried by PAVs in receiving rivers. WWTP-UP narrowed the pathogenic host ranges of ARGs and VFs and mitigated the co-occurrence of ARGs and VFs in receiving rivers. These findings underline the importance of WWTP-UP for the alleviation of pathogens containing both ARGs and VFs in receiving rivers.
● The main and added effect from heat co-existed in China. ● Both of the main and added effect could increase the mortality risk of population. ● Females, the elderly, the less educated and inland residents were more vulnerable.
Increases in ambient temperatures and the frequency of extreme heat events constitute important burdens on global public health. However, evidence on their effects on public health is limited and inconclusive in China. In this study, data on daily deaths recorded in 33 Chinese cities from 2007 to 2013 was used to evaluate the effect of heat on mortality in China. In addition to the definition of a heatwave established by the China Meteorological Administration, we combined four city-specific relative thresholds (90th, 92.5th, 95th, and 97.5th percentiles) of the daily mean temperature during the study period and three durations of ≥ 2, ≥ 3, and ≥ 4 days, from which 13 heatwave definitions were developed. Then, we estimated the main and added effects of heat at the city level using a quasi-Poisson generalized additive model combined with a distributed lag nonlinear model. Next, the estimates for the effects were pooled at the national level using a multivariable meta-analysis. Subgroup analysis was performed according to sex, age, educational attainment, and spatially stratified heterogeneity. The results showed that the mortality risk increased from 22.3% to 37.1% due to the effects of the different heatwave definitions. The added effects were much lower, with the highest increase of 3.9% (95% CI: 1.7%–6.1%) in mortality risk. Females, the elderly, populations with low educational levels, and populations living inland in China were found to be the most vulnerable to the detrimental effects of heat. These findings have important implications for the improvement of early warning systems for heatwaves.
● The main direct seal up carbon options and challenges are reviewed. ● Ocean-based CO2 replacement for CH4/oil exploitation is presented. ● Scale-advantage of offshore CCS hub is discussed.
Carbon capture and storage (CCS) technology is an imperative, strategic, and constitutive method to considerably reduce anthropogenic CO2 emissions and alleviate climate change issues. The ocean is the largest active carbon bank and an essential energy source on the Earth’s surface. Compared to oceanic nature-based carbon dioxide removal (CDR), carbon capture from point sources with ocean storage is more appropriate for solving short-term climate change problems. This review focuses on the recent state-of-the-art developments in offshore carbon storage. It first discusses the current status and development prospects of CCS, associated with the challenges and uncertainties of oceanic nature-based CDR. The second section outlines the mechanisms, sites, advantages, and ecologic hazards of direct offshore CO2 injection. The third section emphasizes the mechanisms, schemes, influencing factors, and recovery efficiency of ocean-based CO2-CH4 replacement and CO2-enhanced oil recovery are reviewed. In addition, this review discusses the economic aspects of offshore CCS and the preponderance of offshore CCS hubs. Finally, the upsides, limitations, and prospects for further investigation of offshore CO2 storage are presented.
● Heavy metals and organic toxins may persist in legacy sites for a long time. ● Contaminants pose potential harms to the nearby community (HI > 1). ● PCDD/Fs had the risk of endocrine disruption and reproductive risk. ● Further intervention is needed to reduce pollution and related risks.
Informal electronic-waste (e-waste) recycling sites pose substantial health risks to surrounding environments and populations, yet they are not properly regulated. In this study, the soil levels of copper, lead, cadmium, eight polybrominated diphenyl ethers (PBDEs), and 18 polychlorinated dibenzo-dioxins/furans (PCDD/Fs) were measured at two e-waste recycling sites in South China between 2014 and 2019. Both sites have been abandoned for natural restoration. Our results indicate that the mean Cd and PCDD/F levels at Site A in 2019 were higher than those recommended by current safety guidelines. Meanwhile, the highest exposure among children was 1.36 × 10−2 mg/(kg·d) for Cu, followed by 5.05 × 10−3 mg/(kg·d) for Pb, 9.71 ng/(kg·d) for PBDEs, and 6.82 ng TEQ/(kg·d) for PCDD/Fs. Children were at elevated risk for health problem posed by Pb and Cu exposure at both sites (hazard quotient > 1) and by PCDD/Fs at Site A. Further risk assessment was conducted on the target organs and endpoints of heavy metals and PCDD/Fs. The hazard index (HI) for the target organ mixed-risk of heavy metals was high (HI = 1.27), as was that of PCDD/Fs (HI = 1.66), which can disrupt endocrine function and pose a risk of reproductive toxicity in children. Owing to incomplete cleaning, contaminants persist in soils over long periods and may harm nearby environments and communities. Our study demonstrates that heavy metal, PBDE, and PCDD/F contamination have not yet been remediated, and intervention is needed to reduce pollution and associated risks in areas affected by e-waste.
