Estimation of Heavy Metal Concentrations in the Water of Urban Lakes in the Russian Arctic (Murmansk)

This article presents the results of the analysis and estimation of the seasonal variation of heavy metals in the water of urban lakes and the assessment of their environmental state based on the chemical data. The research covered seven lakes in Murmansk, subject to various levels of anthropogenic load. Field studies were conducted in 2019–2020. Water samples were taken both in summer and in winter/spring seasons. The most polluted lake was Lake Ledovoe, where the highest concentrations of V, Cr, Co, Ni, Cu, W, and Mn were found. Lake Yuzhnoe, which is characterized by the lowest concentrations of studied heavy metals, was the least subject to anthropogenic load. In total, V, Ni, Zn, Fe, and Mn were above the background levels in the lakes of Murmansk. The analysis of the seasonal variation showed that the highest concentrations of heavy metals were found in winter/spring season and reached their maximum during the period of melt water intake from the catchment area. The research showed the impact of the urban environment on the chemical composition of the Murmansk lakes.

COVID-19 lockdown effects on water turbidity of a highly polluted lake in Dhaka city, Bangladesh

Highly polluted lake water turbidity was analyzed to detect the changes during COVID-19 lockdown. Total eight Sentinel-2 Multispectral Instrument (MSI) and Landsat-8 Operational Land Imager (OLI) satellite imageries are used to observe the qualitative change of lake water turbidity for pre, during and post lockdown period. The imageries from January to June, and September and October were analyzed for change detections. Cloud free imageries have been chosen for analysis. The water pixels and turbidity are assessed by the Normalized Difference Water Index (NDWI) and Normalized Difference Turbidity Index (NDTI), respectively. The blue, red and NIR band reflectance indicates that most of the lake water becomes clearer than before the lockdown period except May. The turbidity index shows low pollution after the lockdown period. High turbidity was observed evenly distributed from January to June. In September and October, high turbidity only found the upper part of the lake. This probably indicates the floating pollutants in the lake. The qualitative study of lake water turbidity using a remote sensing approach indicates that the COVID-19 lockdown improves the water quality in city lake water.

Effective removal of Cu2+ ions from polluted water using new bio-adsorbents

Sorbents derived from stem powders of Feronia limonia (FLSP), Amorphophallus paeoniifolius (APSP) and Pumpkin (Cucurbitapepo) (PSP) plants are investigated for the removal of Cu2+ ions from polluted water by adopting batch methods of extraction. Extraction conditions are optimized for the effective removal of Cu2+ ions. High sorption capacities are observed: 175.5 mg/g for FLSP; 140.4 mg/g for APSP; 130.0 mg/g for PSP. Effective pH ranges are: 5 to 10 for FLSP; 6 to 10 for APSP and 7 to 10 for PSP. The three spent adsorbents can be regenerated and used. Thermodynamic parameters indicate that the adsorption process is spontaneous, endothermic and have positive change in entropy values. As ΔH values are more than 25.0 kJ/mole, the adsorption may be due to surface complex formation between Cu2+ ions and functional groups of the adsorbents viz., -OH, -COOH etc. in the effective pH ranges. The good adsorption behaviour of FLSP even in acidic pHs may be due to the ion-exchange of Cu2+ ions for H+ ions of the functional groups of the adsorbent. The Langmuir adsorption isotherm and pseudo second-order model describe well the adsorption process. The sorbents are effectively applied to treat effluents from Cu-based industries and polluted lake water.