Winter arsenic pollution in 10 forest ecosystems in the mountainous border regions of the Czech Republic

Environmental Science and Pollution Research - Arsenic (As) concentrations and deposition fluxes were measured in snow and rime at 10 mountain-top sites near the borders between the Czech Republic...     

Ecotoxicology of alpine streams in the West Carpathians—Alpine Bullhead (Cottus poecilopus) and high mountain flash flood effects

Environmental Science and Pollution Research - Flash floods represent a serious threat to wildlife, water biota, and human life in pre-alpine regions, particularly in recent historical memory. The...     

How does eliminating mercury from artisanal and small-scale gold mining lead to achieving sustainable development goals?

Artisanal and small-scale gold mining (ASGM) is the principal anthropogenic activity that globally contributes to overloading our environment with mercury. Although the Minamata Convention, led by the United Nations, is a crucial instrument to eliminate its use progressively, novel approaches to accelerate this difficult transition are welcome. This article proposes a framework for policy-making or improvement, fostering the enforcement of mercury elimination through the lens of the 17 Sustainable Development Goals (SDGs), focusing on the excluded artisanal and small-scale gold miners and their dependents. We move forward with a literature review of the Artisanal and Small Mining topic, taking each SDG as a unit of analysis. Understanding the problem as a puzzle of four sets of pieces, namely: (1) social, (2) environmental, (3) economic, and (4) institutional, the paper offers potential opportunities for the decision-makers and practitioners to accelerate the substitution of this heavy metal and develop sustainable futures for the ASGM communities. We conclude by proposing a pragmatic framework that synthesizes the means, actions, and ends to accelerate a sustainable transition.     

2,4-Dichlorophenoxyacetic acid (2,4-D) photodegradation on WO3-TiO2-SBA-15 nanostructured composite

Environmental Science and Pollution Research - A current environmental problem is the uncontrolled use of various pesticides that are harmful to the environment and public health. The herbicide...     

Simultaneous removal of metronidazole and Pb(II) from aqueous solution onto bifunctional activated carbons

Environmental Science and Pollution Research - In this work, it was analyzed the behavior of three commercial activated carbons with different textural and chemical properties to adsorb...     

Larvicidal and pupicidal activities of eco-friendly phenolic lipid products from Anacardium occidentale nutshell against arbovirus vectors

Environmental Science and Pollution Research - Aedes aegypti and Culex quinquefasciatus are vectors of diseases that constitute public health problems. The discovery of products capable of...     

Elevation of biochar application as regulator on denitrification/NH3 volatilization in saline soils

Environmental Science and Pollution Research - Denitrification and NH3 volatilization are the main removal processes of nitrogen in coastal saline soils. In this incubation study, the effects of...     

Systematic review of conservation interventions to promote voluntary behavior change

Understanding human behavior is vital to developing interventions that effectively lead to proenvironmental behavior change, whether the focus is at the individual or societal level. However, interventions in many fields have historically lacked robust forms of evaluation, which makes it hard to be confident that these conservation interventions have successfully helped protect the environment. We conducted a systematic review to assess how effective nonpecuniary and nonregulatory interventions have been in changing environmental behavior. We applied the Office of Health Assessment and Translation systematic review methodology. We started with more than 300,000 papers and reports returned by our search terms and after critical appraisal of quality identified 128 individual studies that merited inclusion in the review. We classified interventions by thematic area, type of intervention, the number of times audiences were exposed to interventions, and the length of time interventions ran. Most studies reported a positive effect (n = 96). The next most common outcome was no effect (n = 28). Few studies reported negative (n = 1) or mixed (n = 3) effects. Education, prompts, and feedback interventions resulted in positive behavior change. Combining multiple interventions was the most effective. Neither exposure duration nor frequency affected the likelihood of desired behavioral change. Comparatively few studies tested the effects of voluntary interventions on non-Western populations (n = 17) or measured actual ecological outcome behavior (n = 1). Similarly, few studies examined conservation devices (e.g., energy-efficient stoves) (n = 9) and demonstrations (e.g., modeling the desired behavior) (n = 5). There is a clear need to both improve the quality of the impact evaluation conducted and the reporting standards for intervention results.     

Air Quality Modeling Using the PSO-SVM-Based Approach,MLP Neural Network,and M5 Model Tree in the Metropolitan Area of Oviedo (Northern Spain)

The main aim of this study was to construct several regression models of air quality using techniques based on the statistical learning, in the metropolitan area of Oviedo, in northern Spain. In this research, a hybrid particle swarm optimization-based evolutionary support vector regression is implemented to predict the air quality from the experimental dataset (specifically, nitrogen oxides, carbon monoxide, sulfur dioxide, ozone, and dust) collected from 2013 to 2015 in the metropolitan area of Oviedo. Furthermore, a multilayer perceptron network (MLP) and the M5 model tree were also fitted to the experimental dataset for comparison purposes. Finally, the predicted results show that the hybrid proposed model is more robust than the MLP and M5 model tree prediction methods in terms of statistical estimators and testing performances.     

Discrete-choice experiments valuing local environmental impacts of renewables: two approaches to a case study in Portugal

Despite the often mentioned environmental benefits associated with transition from fossil fuels to renewable energy sources, their use for electricity production has non-negligible negative environmental impacts. The most commonly mentioned in surveys concern different types of landscape impacts, impacts on the fauna and flora, and noise. These impacts differ by size and location of plants, and by source of energy, rendering the policy decision complex. In addition, there are other welfare issues to take into consideration, as positive and negative environmental impacts are not evenly distributed among population groups. This paper proposes to compare the welfare impacts of renewable energy sources controlling for the type of renewable as well as the specific environmental impact by source. To this end, two discrete-choice experiments are designed and applied to a national sample of the Portuguese population. In one case, only individual negative impacts of renewables are used, and in another case, the negative impacts interact with a specific source. Results show the robustness of discrete-choice experiments as a method to estimate the welfare change induced by the impacts of renewable energy sources. Overall, respondents are willing to pay to reduce the environmental impacts, thus making compensation for local impacts feasible. Moreover, the estimations reveal that respondents are significantly sensitive to the detrimental environmental effects of specific renewable energy sources, being willing to pay more to use these sources of energy relative to others.