The removal of antibiotics in subsurface flow constructed wetlands is performed through various removal mechanisms, such as adsorption, hydrolysis, microbial degradation and plant uptake. However, the contribution rates of the removal mechanisms in constructed wetlands are still not well studied. This study conducted a series of experiments and used multivariate statistical analysis to determine contribution rates for substrate adsorption, hydrolysis, and microbial degradation. Multiple stepwise regression analysis indicated that specific surface area and salt content were the main factors influencing sulfonamide adsorption, while temperature and pH were the main factors influencing sulfonamide hydrolysis. Variance partitioning analysis showed that the influence of physical-chemical factors was greater than that of nutrients on the microbial community. Partial least squares path analysis showed that the path coefficients of microbial degradation, adsorption and hydrolysis for sulfonamides removal in vertical subsurface flow constructed wetlands were 0.6339, 0.3608 and 0.0351, respectively, while the corresponding path coefficient were 0.5658, 0.4707 and 0.1079 in horizontal subsurface flow constructed wetlands, respectively. This means that microbial degradation contributes the most to the removal of sulfonamides in subsurface flow constructed wetlands. Enhanced microbial degradation may be a powerful measure to improve the removal of sulfonamides. These results will be helpful for understanding the removal mechanism of antibiotics and will provide a definite direction for pertinently improving sulfonamide removal efficiency in constructed wetlands.

A better understanding of the spatiotemporal dynamics and influencing factors of sulfonamide antibiotic resistance genes (ARGs) distribution in subsurface flow constructed wetlands is essential to improve the ARGs removal efficiency. The spatiotemporal dynamics of sulfonamide ARGs were explored in the vertical upflow subsurface flow constructed wetland (VUSFCW). The results showed that the absolute abundance of ARGs presented a trend of bottom layer > middle layer > top layer. The relative abundance of ARGs decreased significantly from the bottom layer to the middle layer, but increased in the top layer. The bottom layer was the main stage to remove ARGs. The absolute abundance of ARGs at each point in summer was significantly higher than that in winter. Based on the spatiotemporal distribution of ARGs, the internal mechanism of ARGs dynamic change was explored by the partial least square path analysis model. The results showed that physical-chemical factors, microorganisms and antibiotics indirectly affected the spatiotemporal distribution of ARGs mainly through mobile genetic elements. The indirect influence coefficients of physical-chemical factors, microorganisms and antibiotics on the spatiotemporal distribution of ARGs were 0.505, 0.221 and 0.98 respectively. The direct influence coefficient of MGEs on the spatiotemporal distribution of ARGs was 0.895. The results of network analysis showed that the potential host species of ARGs in summer were more abundant than those in winter. The selection mode of sulfonamide ARGs to potential hosts was nonspecific. There is a risk of sulfonamide ARGs infecting pathogens in VUSFCW. Fortunately, VUSFCW has proven effective in reducing the absolute abundance of ARGs and the potential risk of pathogens carrying ARGs. These findings provide a model simulation and theoretical basis for effectively reducing the threat of ARGs.

Understanding the composition and assembly mechanism of waterborne pathogen is essential for preventing the pathogenic infection and protecting the human health. Here, based on 16S rRNA sequencing, we investigated the composition and spatial variation of potentially pathogenic bacteria from different sections of the Pearl River, the most important source of water for human in Southern China. The results showed that the potential pathogen communities consisted of 6 phyla and 64 genera, covering 11 categories of potential pathogens mainly involving animal parasites or symbionts (AniP), human pathogens all (HumPA), and intracellular parasites (IntCelP). Proteobacteria (75.87%) and Chlamydiae (20.56%) were dominant at the phylum level, and Acinetobacter (35.01%) and Roseomonas (8.24%) were dominant at the genus level. Multivariate analysis showed that the potential pathogenic bacterial community was significantly different among the four sections in the Pearl River. Both physicochemical factors (e.g., NO₃–N, and suspended solids) and land use (e.g., urban land and forest) significantly shaped the pathogen community structure. However, spatial effects contributed more to the variation of pathogen community based on variation partitioning and path analysis. Null model based normalized stochasticity ratio analysis further indicated that the stochastic process rather than deterministic process dominated the assembly mechanisms by controlling the spatial patterns of potential pathogens. In conclusion, high-throughput sequencing shows great potential for monitoring the potential pathogens, and provided more comprehensive information on the potentially pathogenic community. Our study highlighted the importance of considering the influences of dispersal-related processes in future risk assessments for the prevention and control of pathogenic bacteria.

Whilst attention is increasingly being focused on embodied pollutant emissions along supply chains in China, relatively little attention has been paid to dynamic changes in this process. This study utilized environmental extended input-output analysis (EEIOA) and structural path analysis (SPA) to investigate the dynamic variation of the SO2 emissions embodied in 28 economic sectors in Chinese supply chains during 2002–2012. The main conclusions are summarized as follows: (1) The dominant SO2 emission sectors differed under production and consumption perspectives. Electricity and heat production dominated SO2 emissions from the point of view of production, while construction contributed most from the consumption perspective. (2) The embodied SO2 emissions tended to change from the path (staring from consumption side to production side): “Services→Services→Power” in 2002 to the path: “Construction and Manufacturing→Metal and Nonmetal→Power” in 2012. (3) Metal-driven emissions raised dramatically from 15% in 2002 to 22% in 2012, due to increasing demand for metal products in construction and manufacturing activities. (4) Power generation was found to result in the greatest volume of production-based emissions, a burden it tended to transfer to upstream sectors in 2012. Controlling construction activities and cutting down end-of-pipe discharges in the process of power generation represent the most radical interventions in reducing Chinese SO2 emissions. This study shed light on changes in SO2 emissions in the supply chain, providing a range of policy implications from both production and consumption perspectives.

Cadmium (Cd) contamination in soil has posed a great threat to crop safety and yield as well as soil quality. Biochar blended with nitrogen fertilizer have been reported to be effective in remediating Cd-contaminated soil. However, the influence of co-application of biochar and nitrogen fertilizer on the Cd bioavailability, rice yield and soil microbiome remains unclear. In this study, eight different treatments including control (CK), 5% biochar (B), 2.6, 3.5, 4.4 g/pot nitrogen fertilizers (N1, N2 and N3), and co-application of biochar and nitrogen fertilizers (BN1, BN2, BN3) were performed in a pot experiment with paddy soil for observations in an entire rice cycle growth period. Results showed single N increased soil available Cd content and Cd uptake in edible part of rice, while the soil available Cd content significantly decreased by 14.8% and 7.4%–11.1% under the B, BN treatments, and the Cd content in edible part of rice was significantly reduced by 35.1% and 18.5%–26.5%, respectively. Besides, B, N and BN treatments significantly increased the yield of rice by 14.3%–86.6% compared with CK, and the highest yield was gained under BN3 treatment. Soil bacterial diversity indices (Shannon, Chao1, observed species and PD whole tree index) under N2, N3 were generally improved. Cluster analysis indicated that bacterial community structures under BN treatments differed from those of CK and single N treatments. BN treatments enhanced the abundances of key bacterial phylum such as Acidobacteria, positively associated with yield, and increased the abundance of Spirochaetes, negatively correlated to soil available Cd and Cd uptake of rice. Furthermore, the regression path analysis (RPA) revealed that pH, organic matter (OM), alkaline hydrolysis of nitrogen (AHN) and available Cd were the major properties influencing Cd content in edible part of rice. Redundancy analysis (RDA) revealed that pH and available Cd played key role in shaping soil bacterial community. Thus, BN is a feasible practice for the improvements of rice growth and remediation of Cd-polluted soil.

This three-decade long study was conducted in the Pearl River Delta (PRD), a rapidly urbanizing region in southern China. Extensive soil samples for a diverse land uses were collected in 1989 (113), 2005 (1384), 2009 (521), and 2018 (421) for heavy metals of As, Cr, Cd, Cu, Hg, Ni, Pb and Zn. Multiple pollution indices and Structural Equation Models (SEMs) were used in attribution analysis and comprehensive assessments. Data showed that majority of the sampling sites was contaminated by one or more heavy metals, but pollutant concentrations had not reached levels of concerns for food security or human health. There was an increasing trend in heavy metal contamination over time and the variations of soil contamination were site-, time- and pollutant-dependent. Areas with high concentrations of heavy metals overlapped with highly industrialized and populated areas in western part of the study region. A dozen SEMs path analyses were used to compare the relative influences of key environmental factors on soil contamination across space and time. The high or elevated soil contaminations by As, Cr, Ni, Cu and Zn were primarily affected by soil properties during the study period, except 1989–2005, followed by land use patterns. Parent materials had a significant effect on elevated soil contamination of Cd, Cr, Ni, Pb and overall soil pollution during 1989–2005. We hypothesized that other factors not considered in the present study, such as atmospheric deposition, sewage irrigation, and agrochemical uses, may be also important to explain the variability of soil contamination. This study implied that strategies to improve soil physiochemical properties and optimize landscape structures are viable methods to mitigate soil contamination. Future studies should monitor pollutant sources identified by this study to fully understand the causes of heavy metal contamination in rapidly industrialized regions in southern China.

Variation in water quality can directly affect the composition of benthic assemblages on coral reefs. Yet, few studies have directly quantified nutrient and suspended particulate matter (SPM) to examine their potential impacts on benthic community structure, especially around high oceanic islands. We assessed the spatio-temporal variation of nutrients and SPM across six sites in American Samoa over a 12-month period and used exploratory path analysis to relate dissolved inorganic nutrients, land use, and natural and anthropogenic drivers to benthic assemblages on adjacent shallow reefs. Multivariate analyses showed clear gradients in nutrient concentrations, sediment accumulation and composition, and benthic structure across watersheds. Instream nutrients and land uses positively influenced reef flat nutrient concentrations, while benthic assemblages were best predicted by wave exposure, runoff, stream phosphate and dissolved inorganic nitrogen loads. Identifying locality-specific drivers of water quality and benthic condition can support targeted management in American Samoa and in other high islands.

Developing the wind energy industry (WEI) has been a long-term strategy in China for responding to the energy crisis and greenhouse gas emissions. However, China’s WEI faces various barriers despite its favorable prospects. This paper aims to propose a path analysis approach for exploring the best methods and timing for overcoming diverse barriers in developing WEI systematically, especially in terms of revealing in which phases these barriers should take priority. A multidimensional barrier set categorized by institutional, economic and financial, social, technical, and market factors is identified via the integration of a literature review and empirical interviews. A path analysis approach based on the grey group DEMATEL-NK model is constructed, where the causalities and intensities among barriers are extracted to design a path simulation algorithm with heuristics. The optimal path for overcoming barriers in developing the WEI is generated through a simulation of the search and optimization process used to climb to the fitness landscape peak. The results show that the different barriers to completing the legal and regulatory framework should be prioritized to reach adequate financial incentives and coordination among stakeholders, and that an efficient talent cultivation system should be developed and industry-academic cooperation should be strengthened to increase technical and R&D capabilities in the short term. The optimal path presents a strategic instrument for managers to use to better develop sustainable and clean wind energy systems from the novel insights of prioritizing to overcome barriers.

The impact of COVID-19 has revamped all aspects of human life including education sector, and it has completely changed the educational environment across the globe. Due to the pandemic, the methodical functions of educational institutions have stopped, and new phases have started like online class, online evaluation, and indoor activities. Students are the vital players in education sector, and their opinions play an indispensable role while formulating the policies by the government. In the pandemic, students’ perspective on education environment finds new dimension. Therefore, this paper has made an honest attempt to know the coastal Karnataka students’ stance on college educational environment. In this study, six major components of education environment are considered, namely (1) online class, (2) teaching and learning, (3) evaluation, (4) college administration, (5) extracurricular activities, and (6) teachers. The study is descriptive in nature, and data was collected from 347 college students of Coastal Karnataka. To support the main objective, a hypothesis has been developed with the help of review of literature and is tested by using ANOVA and independent t-test. The path analysis is used to analyze the casual relationships among components of college educational environment, overall perception, and student performance. The result of the study found that the college students have positive perception towards online class (M=3.14), teaching and learning (M=3.704), evaluation (M=3.38), college and administration (M=3.83), extracurricular activities (M=3.87), and teachers (M=3.63). The result of the hypothesis testing revealed that there is no significant difference in the student perception towards various components of college education system. Path analysis results show that there is relation and effect between components of college education, overall perception, and students’ performance. The study concludes that students agree with policies and actions taken by colleges to carry out classes during COVID-19 pandemic irrespective of demographic and educational difference.