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,...     

A comprehensive review on green buildings research: bibliometric analysis during 1998–2018

Environmental Science and Pollution Research - Buildings account for nearly 2/5ths of global energy expenditure. Due to this figure, the 90s witnessed the rise of green buildings (GBs) that were...     

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)...     

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.     

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.     

Assessment of the impacts of climate change and variability on water resources and use,food security,and economic welfare in Iran

Climate change influences the agricultural sector by reducing available water resources, thereby influencing income, consumer and producer surplus, and crop prices. So, it is necessary to have a comprehensive integrated method to measure the effects of these changes on natural resources and social conditions. The present study aims to use the positive mathematical programming method to discover the trend and conditions of groundwater resources, agricultural water use, food security, and economic welfare of the agricultural sector in Iran. To this end, data for the period 2000–2015 was used under four different scenarios of normal climate change, climate change, climate variability, and concurrent climate change The results showed that the mean agricultural water use will amount to 35,103.6, 26,533.8, 35,216, and 26,510.7 million m³ and the mean decline in the reserves of aquifers will amount to 4422.22, 11,165.6, 4438.25, and 11,267.4 million m³ under the scenarios, respectively. With respect to food security, the net farm revenue will be 314,560, 248,753, 315,427, and 248,574 billion IRR, respectively. The mean crop price per ton will reach 905.3, 1141.8, 904, and 1142.8 million IRR, respectively. The mean consumer surplus will be 172,107.7, 166,450, 172,024, and 166,403 billion IRR and the mean producer surplus will be 419,959.2, 395,380, 419,751, and 395,204 billion IRR, respectively. Based on the results, to reduce the adverse impacts of climate change on different studied aspects, it is necessary to change policymaking in the water and agricultural sectors, especially regarding the shift from traditional agricultural water allocation to its market-based allocation and to change planting pattern.

     

Impact of green trust and green perceived quality on green purchase intentions: a moderation study

Environment, Development and Sustainability - The current study explores the role of green trust, green perceived risk and green perceived quality in changing green purchase intention....     

The Anthropogenic Impact on the True Seals (Carnivora: Phocidae) at the Mouth of Piltun Bay (Sakhalin Island,Russia)

Russian Journal of Ecology - A study of the anthropogenic impacts on the on-shore aggregation of true seals was carried out at a haul-out located at the mouth of Piltun Bay (the northeastern part...