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...     

The role of traditional knowledge policies in Egypt: the case of Wadi Allaqi

Environment, Development and Sustainability - Globally, traditional knowledge is at stake, notwithstanding intentions recorded in international policy conventions. Egypt has accepted and ratified...     

Institutional quality,financial development and sustainable economic growth among lower income countries

This article postulates strong endogenous relationships in lower income countries between institutional quality, financial development and sustained economic growth. These associations were investigated using the vector-error correction model (VECM) and Granger causality method for a sample of 79 countries from 2005 to 2022. The findings show that (1) these variables reinforce each other in the short run. (2) In the long run, both institutional quality and financial development can fuel economic growth. (3) The positive effect of institutional quality on economic growth is greater than that of financial development. Policy implications of these findings are that careful attention should be paid to co-development policies to enhance the institutional quality and the financial system in these economies. Policies should also consider economic growth strategies to enable sustainable economic growth rates.     

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.     

Multivariate assessment of outflow water quality in highly urbanized creek system: implication of natural and anthropogenic processes

Environmental Science and Pollution Research - Nutrient source and transport study in tropical creeks adjacent to megacities are sparse on a regional and global scale. High-frequency chemical data...     

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...     

Effect of Anthropogenic Factors on the Ability of Narrow-skulled Voles (Lasiopodomys gregalis) to Adapt to Captive Conditions

Russian Journal of Ecology - To test the hypothesis that animals from habitats exposed to high anthropogenic pressure are more successful in adapting to captivity, immature narrow-skulled voles...     

Performance Evaluation of Multiple Groundwater Flow and Nitrate Mass Transport Numerical Models

Environmental Modeling & Assessment - Benchmarking of different numerical models simulating groundwater flow and contaminant mass transport is the aim of the present study, in order to...     

Auxinic herbicides induce oxidative stress on Cnesterodon decemmaculatus (Pisces: Poeciliidae)

Environmental Science and Pollution Research - Pesticides might increase the production of reactive oxygen species (ROS). Dicamba (DIC) and 2,4-dichlorophenoxyacetic acid (2,4-D) are auxinic...     

A remote sensing tool for near real-time monitoring of harmful algal blooms and turbidity in reservoirs

Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real-time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll-a concentrations (chl-a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real-time monitoring of HABs. Landsat-8 and Sentinel-2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl-a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R² values of 0.75, 0.82, and 0.79 for chl-a, turbidity, and phycocyanin, while multiple regression had R² values of 0.29, 0.51, and 0.46 and SVR had R² values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open-source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality.