Increasing eutrophication poses a considerable threat to freshwater ecosystems, which are closely associated with human well-being. As important functional entities for freshwater ecosystems, submerged macrophytes have suffered rapidly decline with eutrophication. However, it is unclear whether and how submerged macrophytes maintain their ecological functions under increasing eutrophication stress and the underlying patterns in the process. In the current study, we conducted an extensive survey of submerged macrophytes in 49 lakes and reservoirs (67% of them are eutrophic) on the Yunnan-Guizhou Plateau of southwestern China to reveal the relationship between submerged macrophyte biodiversity and ecosystem functioning (BEF) under eutrophication stress. Results showed that submerged macrophytes species richness, functional diversity (FD), and β diversity had positive effects on ecosystem functioning, even under eutrophication. Functional diversity was a stronger predictor of community biomass than species richness and β diversity, while species richness explained higher coverage variability than FD and β diversity. This suggests that species richness was a reliable indicator when valid functional traits cannot be collected in considering specific ecological process. With increasing eutrophication in water bodies, the mechanisms underlying biodiversity-ecosystem functioning evolved from “niche complementarity” to “selection effects”, as evidenced by decreased species turnover and increased nestedness. Furthermore, the relative growth rate, specific leaf area, and ramet size in trade-off of community functional composition became smaller along eutrophication while flowering duration and shoot height became longer. This study contributes to a better understanding of positive BEF in freshwater ecosystems, despite increasing anthropogenic impacts. Protecting the environment remained the effective way to protect biodiversity and corresponding ecological functions and services. We hope focus on specific eco-functioning in future studies so as to effective formulation of management plans.

Arsenic (As) is among the most dangerous metalloids and is harmful to human wellbeing. In this laboratory study, Al(III)-modified kapok fibres (Al-Kapok) were used to remove As(V) from water. The sorbent was characterised using Fourier transform infrared spectroscopy (FT-IR) and scanning electron microscopy (SEM) combined with energy-dispersive X-ray spectroscopy (EDX). Batch experiments were performed to observe the performance of Al-Kapok in the removal of As(V) and to examine the effects of pH, temperature, adsorbent dose, and coexisting ions on the adsorption process. The surface of the sorbent changed after aluminium modification, and the results of the batch experiments showed that the adsorption of As(V) occurred mainly via endothermic-spontaneous chemisorption at the solution and solid interface of Al-Kapok. The As(V) removal efficiency was approximately 76%–84%, and it was slightly affected at pH levels below 8.0. Further study showed that the maximum adsorption capacity of Al-Kapok for As(V) was 118 μg/g at 30 °C and pH 6, and notable adverse effects were caused by the presence of SO42−and PO43−. It was also found that the boundary layer and film diffusion contributed more to As(V) adsorption. After five adsorption/desorption cycles, regeneration recovered approximately 92% of the adsorption capacity of Al-Kapok used. Overall, Al-Kapok appears to be a suitable adsorbent material for the purification of As-contaminated water.

The combination of emerging antibiotic resistance and lack of discovery of new antibiotic classes poses a threat to future human welfare. Antibiotics are administered to livestock at a large scale and these may enter the environment by the spreading of manure on agricultural fields. They may leach to groundwater, especially in the Netherlands which has some of the most intensive livestock farming and corresponding excessive manure spreading in the world. This study investigates the presence of antibiotics in groundwater in two regions with the most intensive livestock farming in the Netherlands. If so, the hydrochemical conditions were further elaborated. Ten multi-level wells with in total 46 filters were sampled, focusing on relatively young, previously age-dated groundwater below agricultural fields. Twenty-two antibiotics were analyzed belonging to the following antibiotic groups: tetracyclines, sulfonamides, trimethoprims, β-lactams, macrolides, lincosamides, quinolones, nitrofurans and chloramphenicol. The samples were analyzed for these antibiotics by LC-MS/MS ESI-POS/NEG (MRM) preceded by solid phase extraction which resulted in importantly low detection limits. Six antibiotics were found above detection limits in 31 filters in seven wells: sulfamethazine, sulfamethoxazole, lincomycin, chloramphenicol, ciprofloxacin, and sulfadiazine. The concentrations range from 0.3 to 18 ng L−1. Sulfonamides were detected at all measured depths down to 23 meters below surface level with apparent groundwater ages up to 40 years old. No antibiotics were detected below the nitrate/iron redox cline, which suggests that the antibiotics might undergo degradation or attenuation under nitrate-reducing redox conditions. This study provides proof that antibiotics are present in groundwater below agricultural areas in the Netherlands due to the spreading of animal manure.

In arid and semi-arid regions, water-quality problems are crucial to local social demand and human well-being. However, the conventional remote sensing-based direct detection of water quality parameters, especially using spectral reflectance of water, must satisfy certain preconditions (e.g., flat water surface and ideal radiation geometry). In this study, we hypothesized that drone-borne hyperspectral imagery of emergent plants could be better applied to retrieval total nitrogen (TN) concentration in water regardless of preconditions possibly due to the spectral responses of emergent plants on nitrogen removal and water purification. To test this hypothesis, a total of 200 groups of bootstrap samples were used to examine the relationship between the extracted TN concentrations from the drone-borne hyperspectral imagery of emergent plants and the experimentally measured TN concentrations in Ebinur Lake Oasis using four machine learning (ML) models (Partial Least Squares (PLS), Random Forest (RF), Extreme Learning Machine (ELM), and Gaussian Process (GP)). Through the introduction of the fractional order derivative (FOD), we build a decision-level fusion (DLF) model to minimize the regression results’ biases of individual ML models. For individual ML model, GP performed the best. Still, the amount of uncertainty in individual ML models renders their performance to be subpar. The introduction of the DLF model greatly minimizes the regression results’ biases. The DLF model allows to reduce potential uncertainties without sacrificing accuracy. In conclusion, the spectral response caused by nitrogen removal and water purification on emergent plants could be used to retrieve TN concentration in water with a DLF model framework. Our study offers a new perspective and a basic scientific support for water quality monitoring in arid regions.

The marine environment is a complex system formed by interactions between ecological structure and functioning, physico-chemical processes and socio-economic systems. An increase in competing marine uses and users requires a holistic approach to marine management which considers the environmental, economic and societal impacts of all activities. If managed sustainably, the marine environment will deliver a range of ecosystem services which lead to benefits for society. In order to understand the complexity of the system, the DPSIR (Driver-Pressure-State-Impact-Response) approach has long been a valuable problem-structuring framework used to assess the causes, consequences and responses to change in a holistic way. Despite DPSIR being used for a long time, there is still confusion over the definition of its terms and so to be appropriate for current marine management, we contend that this confusion needs to be addressed. Our viewpoint advocates that DPSIR should be extended to DAPSI(W)R(M) (pronounced dap-see-worm) in which Drivers of basic human needs require Activities which lead to Pressures. The Pressures are the mechanisms of State change on the natural system which then leads to Impacts (on human Welfare). Those then require Responses (as Measures). Furthermore, because of the complexity of any managed sea area in terms of multiple Activities, there is the need for a linked-DAPSI(W)R(M) framework, and then the connectivity between marine ecosystems and ecosystems in the catchment and further at sea, requires an interlinked, nested-DAPSI(W)R(M) framework to reflect the continuum between adjacent ecosystems. Finally, the unifying framework for integrated marine management is completed by encompassing ecosystem structure and functioning, ecosystem services and societal benefits. Hence, DAPSI(W)R(M) links the socio-ecological system of the effects of changes to the natural system on the human uses and benefits of the marine system. However, to deliver these sustainably in the light of human activities requires a Risk Assessment and Risk Management framework; the ISO-compliant Bow-Tie method is used here as an example. Finally, to secure ecosystem health and economic benefits such as Blue Growth, successful, adaptive and sustainable marine management Responses (as Measures) are delivered using the 10-tenets, a set of facets covering all management disciplines and approaches.

The flows of ecosystem services (ESs) from ecological patches (EPs) are being severely challenged due to global change. However, the evaluation of nexus between tribal society and ecological units with focus of tribal livelihood was not a subject of enquiry until recent past. Present study hypothesized that the different EPs has differential nexus in terms of delivery of ESs in Barind region, Eastern India. Dependency and prominence of l livelihood on ESs was evaluated through developing ES dependency index (ESDI) and ecosystem services prominence index (ESPI). Five sub-components (comprising 25 indicators) and ten dominant provisioning ecosystem services (PES) were considered to develop ESDI and ESPI respectively. The seasonal variations of availability of ESs from EPs were also assessed-based five-point Likert scale. The findings of the study showed that (i) the households were highly dependent on PES for their livelihood strategies; (ii) agricultural crops (main foods), housing materials, fuel woods, water, livestock, and medical plants were the dominant ESs; (iii) forests, agricultural lands, water bodies, and homesteads were the main EPs from which ESs were collected; (iv) there was positive correlation between ESDI and ESPI. Moreover, there was substantial variation on dependency of ESs across villages was observed and seasonal variation in ESs was noted in terms of availability and dependency with maximum contribution during the monsoon season. The result clearly suggests that there is a strong nexus between livelihood strategies and ESs in the region. Therefore, diversification of livelihood strategies must be integrated with ESs for human well-being (HWB) as well as environmental sustainability.

The practices of the joint prevention and control of air pollution (JPCAP) present two disadvantages: the low enthusiasm of governance subjects and an unsatisfactory governance effect. Revealing the existing problems and exploring their causes has been a key issue for promoting JPCAP. Given this, we especially establish a two-stage dynamic game model for air pollution control to explore the advantages and dilemmas of JPCAP by analyzing changes in environmental tax rate and social welfare. The results show that the unfair distribution of social welfare among cities is a key reason for the unsatisfactory effect of JPCAP. Therefore, we improve JPCAP by considering both production-oriented and consumption-oriented pollutions based on environmental justice. In the improved JPCAP mode, the social welfare of each city is higher than that of non-joint control of air pollution (NJCAP), in which the increased degree is positively related to the city’s negotiation ability. In addition, the consumption tax rate is negatively correlated with the negotiation ability of the central city and the trade transfer coefficient. This study not only provides a theoretical and methodological reference for formulating effective planning and compensation scheme for JPCAP but also can be extended to the practice and theoretical analysis of other cross-regional public issues.

Urban heat island (UHI) has a great influence on human wellbeing in urban areas. Previous studies have investigated impact on environment, ecosystem, and human health of UHI. To investigate economic impact of UHI is a lack of research. In this study, spatial-econometric hedonic housing price models are developed for estimating the marginal value of summer UHI in Beijing, China. The results showed that UHI effects in Beijing became severe from 2015 to 2017. The heat islands showed a mix of high and sub-high land surface temperature (LST). The spatial Durbin model estimates that one-unit increase of UHI intensity (UHII) would lower the housing value by 3.91%. Regarding the different districts, households had different attitudes to the UHI effect. Specifically, households regarded UHI effect as amenity in the four suburban districts with hills and relatively low LSTs; however, in most urban districts and their surroundings, households were willing to pay to avoid UHI effects with 13.0 dollars to 826.3 dollars for one-degree UHII decrease. This study highlights the urgent need for planners and decision-makers to consider urban expansion, UHI effect, and their economic impact in future urban planning.

As global warming has severely threatened the ecosystem and sustainable development of human beings, carbon trading scheme is introduced to mitigate global warming and consumer environmental awareness (CEA) is gradually enhanced. Government regulation and consumer supervision have required firms to seek efficient strategies of product rollover and emission abatement in order to sustain and increase market share. This paper constructs a two-period analytical model in the context of intertemporal carbon emission regulation to investigate how carbon emission regulations and CEA affect the optimal strategies of product rollover, emission abatement, and social welfare. The results reveal that without consumer supervision, the firm prefers to adopt dual product rollover strategy and the optimal product rollover strategy depends on costs and benefits when product recycling is considered. When CEA is high, welfare and emission abatement regulated by hybrid policy is lower than those regulated by carbon trading scheme. When CEA is low, emission abatement under hybrid policy is superior to those regulated by carbon trading scheme. These findings help provide implications for improving carbon emission management efficiency and prompting sustainable development.

Product competition and pollution control are closely related to watershed environmental management, but existing literature rarely investigates them in an identical framework. Therefore, this paper develops a multiple differential game model to analyze product market competition and ecological compensation games between watershed regions based on the assumption that a region can choose four strategies to regulate its manufacturers while cooperating with other regions in the basin. Then, we solve the model and obtain a simultaneous equilibrium between the governments and manufacturers for the first time. The results show that the combination of emissions tax and ecological compensation results in the highest social welfare and water ecology for all regions in a basin. Furthermore, the ecological compensation rate independent of emissions tax policy and ecological compensation does not shift investment from downstream to upstream, but it can induce the upstream region to increase investment in management. In addition, if the governments impose an emissions tax, manufacturers’ output in both regions decreases, and the upstream region is higher than in the downstream region.