Dynamic effects of fiscal and monetary policy instruments on environmental pollution in ASEAN

Environmental Science and Pollution Research - This study aims to re-examine the impacts of monetary and fiscal policy on environmental quality in ASEAN countries from 1990 to 2019. We utilized the...     

Prospects and challenges of conservation agriculture in Bangladesh for sustainable sugarcane cultivation

Environment, Development and Sustainability - Sugarcane is an industrial crop globally used for producing biofuels and bioproducts and is the only source of white sugar in Bangladesh. However,...     

Dynamics of Tree and Shrub Vegetation in the Eastern Sayan Mountain Tundra

Russian Journal of Ecology - Climate change entails shifts in the ranges of woody plants along both latitudinal and altitudinal gradients in the boreal forest biome. In this study,...     

Immunohistochemical,histopathological, and biochemical studies of the NF-ҡB P65 marker in rat ovaries experimentally intoxicated by cadmium and the protective effect of the purslane plant extract

Environmental Science and Pollution Research - The aim of this study is to describe the existence of the inflammatory marker nuclear factor kappa light chain B lymphocyte protein (NF-?B P65)...     

Lithium extraction from salt lake brines with high magnesium/lithium ratio: a review

Environmental Chemistry Letters - The demand for lithium is growing rapidly with the increase in electric vehicles, batteries and electronic equipments. Lithium can be extracted from brines, yet...     

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.     

Investigation of long-term river water quality variations using different urbanization indices and assessment of common scientific perspectives of urbanization on water quality

This study investigated the water quality variation spanning 30 years (1986–2017) in 16 catchments of Hong Kong against different urbanization indices, namely, built area fraction; population; and product of population and built area fraction. Pearson correlations of three different periods of time (1988–1990, 1998–2000, and 2015–2017) indicated that water quality trends were dependent on the urbanization index. Total solids, nitrite-nitrogen, total phosphorus, electrical conductivity, dissolved oxygen, and flow rate had significant deteriorative trends (Pearson r > 0.5 and p < 0.05) with population and product of built area and population. Results also interpreted that built area fraction and product of built area and population were the worst and best indices that represented urbanization and/or its impacts, respectively. Mann-Kendall test for the entire 30 year period showed that water quality had improved with time with respect to certain water quality parameters (e.g., dissolved oxygen, ammoniacal nitrogen and total suspended solids). The results portrayed that although the urbanization of catchments had increased with time, the river water quality with respect to many parameters showed signs of improvement and the legislative measures implemented seemed to be effective in controlling pollution.     

Sulfonated graphene nanomaterials for membrane antifouling,pollutant removal,and production of chemicals from biomass: a review

Water pollution and the unsustainable use of fossil fuel derivatives require advanced catalytic methods to clean waters and to produce fine chemicals from modern biomass. Classical homogeneous catalysts such as sulfuric, phosphoric, and hydrochloric acid are highly corrosive and non-recyclable, whereas heterogeneous catalysts appear promising for lignocellulosic waste depolymerization, pollutant degradation, and membrane antifouling. Here, we review the use of sulfonated graphene and sulfonated graphene oxide nanomaterials for improving membranes, pollutant adsorption and degradation, depolymerization of lignocellulosic waste, liquefaction of biomass, and production of fine chemicals. We also discuss the economy of oil production from biomass. Sulfonated graphene and sulfonated graphene oxide display an unusual large theoretical specific surface area of 2630 m²/g, allowing the reactants to easily enter the internal surface of graphene nanosheets and to reach active acid sites. Sulfonated graphene oxide is hydrophobic and has hydrophilic groups, such as hydroxyl, carboxyl, and epoxy, thus creating cavities on the graphene nanosheet’s surface. The adsorption capacity approached 2.3–2.4 mmol per gram for naphthalene and 1-naphthol. Concerning membranes, we observe an improvement of hydrophilicity, salt rejection, water flux, antifouling properties, and pollutant removal. The nanomaterials can be reused several times without losing catalytic activity due to the high stability originating from the stable carbon–sulfur bond between graphene and the sulfonic group.

     

AI-based runoff simulation based on remote sensing observations: A case study of two river basins in the United States and Canada

Data-driven techniques are used extensively for hydrologic time-series prediction. We created various data-driven models (DDMs) based on machine learning: long short-term memory (LSTM), support vector regression (SVR), extreme learning machines, and an artificial neural network with backpropagation, to define the optimal approach to predicting streamflow time series in the Carson River (California, USA) and Montmorency (Canada) catchments. The moderate resolution imaging spectroradiometer (MODIS) snow-coverage dataset was applied to improve the streamflow estimate. In addition to the DDMs, the conceptual snowmelt runoff model was applied to simulate and forecast daily streamflow. The four main predictor variables, namely snow-coverage (S-C), precipitation (P), maximum temperature (T_max), and minimum temperature (T_min), and their corresponding values for each river basin, were obtained from National Climatic Data Center and National Snow and Ice Data Center to develop the model. The most relevant predictor variable was chosen using the support vector machine-recursive feature elimination feature selection approach. The results show that incorporating the MODIS snow-coverage dataset improves the models' prediction accuracies in the snowmelt-dominated basin. SVR and LSTM exhibited the best performances (root mean square error = 8.63 and 9.80) using monthly and daily snowmelt time series, respectively. In summary, machine learning is a reliable method to forecast runoff as it can be employed in global climate forecasts that require high-volume data processing.     

Ingestion and egestion of microplastic by aquatic insects in Egypt wastewater

Microplastics (MPs) are frequently regarded as environmental and biota contaminants. Yet, research on the accumulation of MPs in living entities, particularly aquatic insects that serve as food resources in the aquatic food chain, is limited. This study to investigate the accumulation of MPs in aquatic insects from water and sediment in an Egyptian wastewater basin. Four typical freshwater insect groups were used. The highest MP load per gram wet weight was reported by collector-gatherers (Chironomus sp. and Hydrophilus sp.), followed by collector-filterers (Culex sp.) with the second highest MP load. However, Predators (Aeshna sp.) had the lowest values. Also, the present results showed a reduction in the number of MPs in all insect taxa tested after a 24 h depuration time, with differences in the observed egestion ability. The mean number of MPs per individual significantly reduced after 24 h in both Chironomus sp. and Culex sp. larvae, where 53% and 40% of MPs particles were ejected from them, respectively. However, the ability of MP egestion decreases in Aeshna sp. nymph (25%), and the lowest proportion of ejection was observed in Hydrophilus sp. adults (9%). Polyethylene terephthalate fibers were the most abundant type of MP in both sediment and water, followed by fragments (polyethylene and polypropylene). Yet, only polyester fibers were detected in the various insect species. The average length of fibers in the various insects was somewhat shorter than in the surrounding environment. The current study reveals that MP ingestion by aquatic insects is not always related to levels of pollution in the environment, since other factors such as feeding strategies may play a role in MP ingestion. Based on these observations, further studies should be carried out on studies on toxicological impacts of MPs on freshwater/aquatic biota.