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.

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.

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.

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.

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.

The COVID-19 pandemic became a challenge to human well-being. The rapid spread of the coronavirus diseases with quarantine measures make people use social media platforms more than before. The bad use of social media platforms affects the mental health of users leading to spread of panic among persons. This study aimed to determine the impact of social media on spreading panic about COVID-19 among adults in Egypt. This was a cross-sectional study that enrolled 2032 participants through online snowball sampling approach conducted during May 2021 to collect data from adults in Egypt. A self-administered questionnaire was used. It consists of three sections as follows: demographic characteristics, the social media platforms employed during the pandemic, the impact of social media on study participants. Nearly half of both sexes believed that spreading news about COVID-19 on social media platforms has a major role in spreading fear among people. More than half of the study participants reported that the level of Egyptian pages on social media covering COVID-19 was not good. A total of 46% females and 30.1% of males; those with primary, preparatory, higher, and postgraduate education; and 46.7% of medical and 32.1% of nonmedical were psychologically affected. The impact of social media on spreading panic among Egyptians varies according to gender, level of education, and occupation. Therefore, social media played an important role in spreading panic during the COVID-19 pandemic.

This paper explores the impact of carbon cap-and-trade policies and consumer low-carbon preferences on the choice of manufacturers’ product lines. We further investigate the optimal decisions of manufacturers under different product line strategies. Moreover, we analyze consumer surplus, environmental impact, and social welfare under different product line strategies. The results show that producing low-carbon and ordinary products is the optimal product line strategy for manufacturers. In addition, we demonstrate that when considering carbon cap-and-trade policies and consumers' low-carbon preferences, the consumer surplus, environmental impact, and social welfare when manufacturers produce low-carbon products are always better than in other scenarios. Furthermore, our research results also show that with the increase of carbon trading prices, the consumer surplus and social welfare when manufacturers choose to produce low-carbon products are always better than in other scenarios. However, we find that the environmental impact is not always outperforming when manufacturers choose a product line that produces low-carbon products than other scenarios.

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.