The objective of the current study is to investigate the performance of the inclined solar panel basin still (ISPBS) incorporated with a spiral tube collector (STC) for various mass flow rates of water (mf). The maximum potable water yield of 8.1, 6.9, and 6.1 kg is obtained for different mass flow rates of 1.8, 3.2, and 4.7 kg/h in each instance. Also, for mf of 1.8, 3.2, and 4.7 kg per hour, the daily average energy and exergy efficiency of the ISPBS is recorded to be 47.9, 39.3, and 31.02 % and 9.8, 7.9, and 5.6 %, in each instance. The average electrical, thermal, and exergy efficiency of the PV panel is noted to be 6.5, 7.1, and 7.5 %; 15.67, 17.1, and 18.04 %; and 20.03, 22.21, and 23.36 % for mf of 1.8, 3.2, and 4.7 kg/h in each instance. The rise in mf causes a drop in the fresh water production yield; thermal, exergy, and overall thermal effectiveness; and an enhancement in the power production of the panel, electrical, thermal, exergy, and overall exergy efficiency of the system. Also, the cost of yield production is noted to be low-cost in AISS at minimum mf of 1.8 kg per hour (0.019 $/l) when compared to the other two mf of 3.2 and 4.7 kg per hour (0.022 and 0.025 $/l).

Low-carbon economic development and energy transition are interactively linked. The synergetic development of the two subsystems is important to achieve the “double carbon” goal of sustainable development. First, this study proposes a model to measure the current synergy level of China’s economy–energy low-carbon transition. Second, an optimization model is developed to improve industry and energy synergy levels through structure optimization. The synergy degree (SD) level of China’s economy–energy low-carbon transition increased from 0 to 0.98 between 2005 and 2017. Furthermore, 69.2% of the periods are in a state of asynergy (SD < 0.6). By implementing the industry and energy structure optimization (OPT) scenario, the synergy level by 2035 can be 27.8% higher than the business-as-usual (BAU) scenario. Moreover, light synergy (0.6 ≤ SD < 0.8) could be achieved by 2025, and high-quality synergy (0.9 ≤ SD ≤ 1) by 2033 in the OPT scenario. Conversely, the synergy level can only achieve light synergy until 2035 in the BAU scenario. Compared to energy structure optimization, the low carbonization of the economic structure plays a more significant role in improving the synergy level of the transaction. These findings can provide support for China’s policy-making regarding economic and energy transition.

Plastic waste and its ubiquity in the oceans represent a growing problem for marine life worldwide. Microplastics (MPs) are ubiquitous in the sea and easily enter food webs. Xyrichtys novacula L. is one of the main target species of recreational fishing in the Balearic Islands, Spain. In the present study, the quantity of MPs in gastrointestinal tracts of X. novacula from two different areas (a marine protected area (MPA) and a non-protected area) of Eivissa Island (in the Balearic archipelago) has been assessed, as well as MPs evaluation within the sediment of both areas. The results showed that over 80% of sampled individuals had MPs in their gut with an average of 3.9 ± 4.3 plastic items/individual. Eighty percent of these plastics were fibres, while the rest were fragments. Although the sediment of the non-protected area had a significant higher presence of MPs, no significant differences in the number of MPs were observed in X. novacula from both areas. The µ-FT-IR analysis showed that the main polymers in the sediments were polycarbonate (PC) and polypropylene (PP), whereas in the digestive tract of fish PC, PP, polyethylene, polystyrene and polyester. In conclusion, practically all X. novacula specimens presented MPs in their digestive tract regardless if the capture zone was in a MPAs or not. These results highlight the ubiquity of MPs in coastal marine areas, and further studies might be necessary to evaluate further implications of MP presence in this species.

In the face of the rapid increase of carbon emissions, climate warming, and an epidemic situation, low-carbon economy is attracting growing attention. Using bibliometric analysis and machine learning methods, the paper conducts a systematic review in the low-carbon economy. Using the Web of Science Core Collection database, 1433 articles from 1990 to 2021 were selected for review. We find that the trajectories of the low-carbon economy research can be divided into four phases: exploration, fermentation, rising, and flourishing. The low-carbon economy research can be categorized into five clusters: low-carbon energy policy, carbon footprint and carbon trading, energy–economy–environment system, energy efficiency and its decomposition, and carbon emission drivers. The findings of this review study shed light on the role and effects of low-carbon economic policies on energy futures.

Heavy metals are persistent and bio-accumulative, and pose potential risk to human health and ecosystem. We reviewed the current state of heavy metal contamination, the ecotoxicological and human health risk of heavy metals reported in urban road dust from various cities in different continents (Asia, Europe, Africa, America, and Australia). We compared and synthesized the findings on the methods related to sample collection, extraction, analytical tools of heavy metals, their concentrations, level of contamination, ecological risk, non-carcinogenic risk, and carcinogenic risk in road dust. Concentrations of Pb, Zn, Cu, Ni, Cd, Cr, Mn, and Fe were found to be higher than their background values in soil. As expected, the contamination levels of the heavy metals varied extensively among cities, countries, continents, and periods. A high level of contamination is observed for Pb and Cd in road dust due to operating leaded gasoline and the old vehicle population. The highest Zn contamination was observed from road dust in Europe, followed by Asia, Africa, Australia, and America (North America and South America). Cu contamination and the pollution load index (PLI) is found to be the highest in Europe and lowest in Africa, with in-between values of PLI in American and African cities. The potential ecological risk on different continents was observed highest in Asia, followed by Europe, Australia, America, and Africa. A comparative assessment of non-carcinogenic risk for children indicated that Australia is the most susceptible country due to high heavy metal exposure in road dust, followed by Asia. However, there is no susceptible risk in European, African, and American cities. We did not observe any potential risk to adults due to non-carcinogenic metals. Carcinogenic risk to all age groups was within the threshold limit range for all the regions worldwide.

Roughness is an important parameter in hydrodynamic and water quality modelling; it has direct effects on bottom shear stress which relied on sediment and vegetation. The varied roughness caused by spatial heterogeneity of sediment and vegetation may lead to uncertain simulation results. To investigate the effect of roughness uncertainty on the performance of hydrodynamic water quality models, a typical large shallow lake in China (Lake Taihu) was divided into eight areas for illustrating the effect of spatial variation of roughness on hydrodynamics and water quality. Total nitrogen (TN) was selected as the variable to calculate the uncertainty interval, and sensitive positions greatly affected by roughness as well as the appropriate range of roughness were explored by means of regional sensitive analysis (RSA). The results showed that roughness had the most significant effect on the bottom velocity. The uncertainty for water quality caused by roughness presented a striking spatial difference; the uncertainty interval for TN could be up to 1.3 mg/L. The posterior distribution of roughness was given to further narrowed the range of roughness, and the updated roughness range manifested that roughness value should be set higher in the area with thick sediment and abundant vegetation. It is of utmost importance to consider the comprehensive effects of sediment and vegetation in the determination of roughness. For certain lake areas with great water quality simulation error, the error could be effectively reduced by setting spatial distributed roughness. The optimization scheme was provided for the reasonable determination of roughness, so that the dynamic characteristic at the sediment-water interface could be represented synthetically. In this paper, the uncertainty and sensitivity of roughness in hydrodynamic water quality model are analyzed to provide reference for parameter setting of large shallow water lake model. For large scale lakes, parameters need to be modified according to the actual condition due to the spatial difference of friction coefficient at the bottom.

This study investigated soil microbial community in a typical gathering area of antimony mining and smelting in South China. The physical and chemical properties of different soils (mining waste dumps, flotation tailings, and smelting slag) and depths (0–20 cm, 40–60 cm, and 80–100 cm) were compared. The results showed that antimony (Sb) and arsenic (As) were the main pollutants, and their concentrations were 5524.7 mg/kg and 3433.7 mg/kg, respectively. Xanthates were found in the flotation tailings and smelting slag, and the highest concentration was 585.1 mg/kg. The microbial communities were analyzed by high-throughput sequencing, and it was shown that Proteobacteria, Acidobacteria, Chlorobacterium, Bacteroides, and Actinomycetes were the dominant taxa at the phylum level. There were obvious differences in microbial community structure in different sites. The dominant microorganism in the mining site was Chujaibacter. Subgroup_2_unclassified and Gemmatimonadaceae_unclassified were the prevalent microorganisms in the flotation and smelting sites, respectively. As, Sb, and xanthates were the main factors affecting the diversity and composition of bacteria in the flotation tailings and smelting slag areas. Therefore, this study provides experimental guidance and a theoretical basis for soil antimony pollution quality assessment, biological treatment, and environmental remediation.

Renewable energy consumption (REC) holds the key to sustainable development. Therefore, many studies have considered the role of REC. However, the factors influencing the REC share in total energy usage (SREC) are not well investigated. Especially, the factors of China’s fast-shrinking SREC are understudied. This research void on the world’s largest renewable energy producer and consumer, i.e., China’s decreasing SREC, is alarming and requires thorough investigation. Our study intends to fill this gap by analyzing the factors of China’s decreasing SREC. The study uses both the conventional (descriptive and directional correlational analyses) and some unconventional (automatic linear modeling (ALM) and Artificial neural network (ANN) multilayer perceptron (MLP)) approach to investigate the factors of China’s decreasing SREC. The initial hypothesis testing and most reliable model validation were achieved via directional correlational (Pearson and Spearman) and ALM analyses. The ANN MLP (two hidden layers) indicated that the most critical factor is “Combustible renewables and waste,” with a 100% normalized importance. It was followed by “urbanization (64.2%), gross savings (56.1%), and alternative and nuclear energy (38%),” respectively. It is suggested that the Chinese government and private investors prioritize their investments based on factors’ importance ranking.

The association of hydrological extremes to a specific season provides a perception that the extraction of dominant patterns of seasonal precipitation variability can be useful to identify the hidden pathways of oceanic-atmospheric mechanisms behind these extremes. The native objective of this study is to find the empirical orthogonal function (EOF) patterns of seasonal precipitation using daily gridded precipitation data over the study region. The spatio-temporal variability of monthly precipitation reveals that over the entire study region precipitation occurs throughout the year with less in November and more in August. We found two dominant EOF patterns of precipitation for summer (JJA) and fall (SON) that have captured all the observed floods from 1901 to 2018. The PC of the dominant pattern of summer season precipitation variability (EOF3) shows a significant negative correlation with the El Niño-Southern Oscillation (ENSO) index (Niño 3.4) depicting that global teleconnection influences the variability of JJA precipitation over this region, while the PC of the dominant pattern of SON season precipitation variability (EOF2) has captured the 2014 deadliest flood which is positively correlated with ENSO at < 5% significance level and can be considered a positive domain response of SON precipitation to the variability of SST over the tropical Pacific Ocean (ENSO). The study will find its applicability in predicting the response of hydrological extremes to global teleconnections and hence can be applied in disaster mitigation and decision-making for the water resource management over the study region.

Methane, as the second most emitted greenhouse gas (GHG), has a warming potential of approximately 86 times that of carbon dioxide within 20 years. Quantifying methane emissions is helpful to the country’s emission reduction efforts. However, currently, there is a lack of measurement data of methane emissions from natural gas fueling stations in China. In this study, a downwind quantification approach was employed to directly measure the methane emissions of nine compressed natural gas (CNG) fueling stations in East China according to the Environmental Protection Agency’s Other Test Method 33A (OTM 33A). Moreover, methane concentrations were also measured near the nozzle of the refueling dispenser and the process equipment in the station. The methane emissions of the nine stations lied within the range of 0.11–0.83 kg/h, and the distribution of the emission rate was skewed. It was found that the emissions from gas fueling stations could be divided into intermittent emissions and continuous emissions, of which the intermittent emissions were the main source of methane.