The applicability of wastewater-based epidemiology (WBE) has been extensively studied throughout the world with remarkable findings. This study reports the presence and reduction of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at two wastewater treatment plants (WWTPs) of Nepal, along with river water, hospital wastewater (HWW), and wastewater from sewer lines collected between July 2020 and February 2021. SARS-CoV-2 RNA was detected in 50%, 54%, 100%, and 100% of water samples from WWTPs, river hospitals, and sewer lines, respectively, by at least one of four quantitative PCR assays tested (CDC-N1, CDC-N2, NIID_2019-nCOV_N, and N_Sarbeco). The CDC-N2 assay detected SARS-CoV-2 RNA in the highest number of raw influent samples of both WWTPs. The highest concentration was observed for an influent sample of WWTP A (5.5 ± 1.0 log 10 genome copies/L) by the N_Sarbeco assay. SARS-CoV-2 was detected in 47% (16/34) of the total treated effluents of WWTPs, indicating that biological treatments installed at the tested WWTPs are not enough to eliminate SARS-CoV-2 RNA. One influent sample was positive for N501Y mutation using the mutation-specific qPCR, highlighting a need for further typing of water samples to detect Variants of Concern. Furthermore, crAssphage-normalized SARS-CoV-2 RNA concentrations in raw wastewater did not show any significant association with the number of new coronavirus disease 2019 (COVID-19) cases in the whole district where the WWTPs were located, suggesting a need for further studies focusing on suitability of viral as well as biochemical markers as a population normalizing factor. Detection of SARS-CoV-2 RNA before, after, and during the peaking in number of COVID-19 cases suggests that WBE is a useful tool for COVID-19 case estimation in developing countries.
The hydrogeochemical and stable isotopes of water (δD and δ18O) were combined to investigate the deep groundwater recharge processes in the geologically complex intermountain basin (Kathmandu Valley). Results of the stable isotopic composition of the deep groundwater compared with global and local meteoric water lines and d-excess showed the deep groundwater as a meteoric water origin which is insignificantly affected by evaporation. The analysis suggests the deep groundwater was recharged during high rainfall periods (wet season). Additionally, the control of seasonal variation was absent in the deep groundwater and in the spring water samples. The large range of isotopic composition distribution was due to the altitude affect, whereas variations are from the various geological settings of the infiltration encountered during the recharge processes. The tri-linear diagram showed Na-K-HCO3 and Ca-Mg-HCO3 as the two major water types. The distribution of water types in this intermountain basin was found to be unique compared to other basins. Ionic concentration of the samples was found to be higher in the central part than in the periphery due to the ion exchange processes. This study determines the spatial distribution of various recharge processes that depends upon the environment during rainfall and the geological settings.
Rapid Urbanization, and other anthropogenic activities, have amplified the change in land-use transition from green space to heat emission in built-up areas globally. As a result, there has been an increase in the land surface temperature (LST) causing the Urban Heat Island (UHI) effect, particularly in large cities. The UHI effect poses a serious risk to human health and well-being, magnified in large developing cities with limited resources to cope with such issues. This study focuses on understanding the UHI effect in Kathmandu Valley (KV), Delhi, and Dhaka, three growing cities in South Asia. The UHI effect was evaluated by analyzing the UHI intensity of the city with respect to the surroundings. We found that the central urban area, of all three cities, experienced more heat zones compared to the peri-urban areas. The estimated average surface temperature ranged from 21.1 ∘C in March 2014 to 32.0 ∘C in June 2015 in KV, while Delhi and Dhaka experienced surface temperature variation from 29.7 ∘C in June 2017 to 40.2 ∘C in June 2019 and 23.6 ∘C in March 2017 to 33.2 ∘C in March 2014, respectively. Based on magnitude and variation of LST, highly built-up central KV showed heat island characteristics. In both Delhi and Dhaka, the western regions showed the UHI effect. Overall, this study finds that the UHI zones are more concentrated near the urban business centers with high population density. The results suggest that most areas in these cities have a rising LST trend and are on the verge of being UHI regions. Therefore, it is essential that further detailed assessment is conducted to understand and abate the impact of the temperature variations.
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