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.

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.

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 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.

Choosing pollution control instrument is an important environmental policy decision. Carbon taxes and subsidies for emissions reductions are two commonly used environmental policies. In practice, the government may be restricted to use only one policy instrument. In this paper, we compare the social welfare effect between policies of a carbon tax and a subsidy. We show that as the marginal environmental damage of the high carbon product increases, the control instrument should change from a subsidy policy to a carbon tax policy. It also turns out that Bertrand competition does not always incur a higher social welfare than Cournot competition when the government intervenes with a pollution control policy.

Output growth uncertainty is a key issue in climate economics, involving the full range of impacts from emissions, through temperature changes to economic damage. The current study introduces output growth uncertainty into the EZ climate model, in which the predicted global carbon emissions under output growth uncertainty are used as weighted input. The objective of the present study is to calculate the future carbon prices represented by marginal abatement cost (MAC), to maximize social welfare. Moreover, the sensitivity of the two output growth uncertainty parameters, namely population growth rate and per capita output growth rate, is analyzed. Lastly, the significance and influence of output uncertainty for carbon price are also discussed. The results exhibit that (1) the optimal prices of per ton CO₂e emission permits in the years 2020, 2030, 2060, 2080, and 2095 are $294.9, $285.3, $238.0, $143.3, and $15.4, respectively. (2) Population growth rate and per capita output growth rate both positively increase the future carbon prices, while the per capita output growth rate has a greater effect. (3) Compared with the performance under output certainty, carbon prices are estimated to be lower with output uncertainty; the high degree of uncertainty about carbon price is also primarily due to the high degree of output uncertainty. These results highlight the importance of research on output growth uncertainty, thus underpinning the EZ climate model for reducing carbon price and improving policymaking.

This study aims to address the economic, social, and environmental wellbeing issues simultaneously by measuring the carbon intensity of wellbeing (CIWB) of Asian economies employing Prais-Winsten and pooled OLS estimator. The measure of CIWB is made taking into account a ratio of the two indicators—CO₂ emissions per capita and life expectancy at birth. There is a paucity of studies that concentrate on human and social wellbeing indicators (i.e., water, sanitation, life expectancy) together applying the Environmental Kuznets Curve (EKC) hypothesis. Therefore, we have also investigated the EKC hypothesis as this theory hypothesizes the link involving human and environmental wellbeing and development. The findings utilizing the two econometric techniques indicate that in both the estimation models urban population access to an improved water source and total population access to improved water source has consistently negative and significant effects on CIWB. The fertility rate and prevalence of HIV pose no threat to CIWB. These findings demonstrate that social and human wellbeing indicators of the Asian economies are sustainable to this moment as they are lowering CIWB which is desirable. Contrary, GDP per capita, exports as a percent of GDP, and urban population have a significant and positive impact on CIWB which poses a challenge for the sustainability issue. We also have found the existence of the EKC hypothesis indicating environmental quality will increase past a turning point. The findings of the paper are well matched with the view of the “Economic and ecological modernization” theory and “human ecology” theory.

In Shanxi, a major energy province in China, environmental pollution caused by coal gangue accumulation is becoming an increasingly serious problem. In addition, crops are the first trophic level in the human food chain, and the security and production of crops are closely related to human well-being. The objective of this study was to estimate the phytotoxicities of agricultural soil samples contaminated by coal gangue accumulation using maize (Zea mays L.) as a model organism. Finally, a tolerant maize cultivar was screened for coal gangue stacking areas. Seven cultivars of maize seeds were treated with agricultural soil leachate around the coal gangue stacking area at various concentrations of 0, 1:27, 1:9, 1:3, and 1:1. The results revealed that the agricultural soil leachate treatment could inhibit seed germination and the growth of roots and shoots and that the soil leachate-induced phytotoxicities were cultivar-dependent. At the same exposure concentration, tolerant maize cultivar displayed lower toxicity symptoms than sensitive maize cultivar in terms of growth inhibition, oxidative damage, and DNA damage. Stronger activities of antioxidant enzymes were observed in the tolerant maize cultivar than in the sensitive maize cultivar, indicating that the difference between cultivars in antioxidant capacity is one reason for the difference in plant tolerance. Our study provides experimental evidence for the ecological risk assessment of soil and the selection of maize cultivars with high environmental pollutant tolerance for use in coal gangue stacking areas.

Since 1970, numerous governments have established strategic petroleum reserves (SPRs) in relation to oil supply interruptions. In this study, important oil reserves, physical oil supply disruption and social welfare losses due to physical distribution of oil supply have been measured. The physical oil supply disruption has been measured in the form of oil supply vulnerability index and oil volatility index of the South Asian economies. Analysis reveals that the accumulation and drawdown of important national crude oil strategic petroleum reserves where the state wants to optimize individual social welfare while individuals hold over stock optimize their earnings levels. The monetary deciding factors utilize the government’s optimum important stockpile policy and simultaneously the amount and economic factors vital for the nongovernment market to actuate the optimum accumulation and nonaccumulation of important fossil fuels stockpile. Additionally, findings show that India is the lowest crude oil insecure country while Afghanistan and Bangladesh are the highest insecure countries in terms of oil supply. India’s topmost mark shows a bigger possibility to alter the fossil fuels producers while Afghanistan, Bangladesh, Bhutan and Nepal have the minimum mark corroborating the group as the utmost producer risk exposed nations.