Longitudinal assessment of extreme climate events in Kinnaur district, Himachal Pradesh, north-western Himalaya, India.

It is vital to keep an eye on changes in climatic extremes because they set the stage for current and potential future climate, which usually have a reasonable adverse impact on ecosystems and society. The present study examines the variability and trends in precipitation and temperature across seasons in the Kinnaur district, offering valuable insights into the complex dynamics of the Himalayan climate. Using Climatic Research Unit gridded Time Series (CRU TS) datasets from 1951 to 2021, the study analyzes the data to produce 28 climate indices based on India Meteorological Department (IMD) convention indices and Expert Team on Climate Change Detection and Indices (ETCCDI).

Identification of sources of coarse mode aerosol particles (PM) using ATR-FTIR and SEM-EDX spectroscopy over the Himalayan Region of India.

This study attempts to examine the morphological, elemental and physical characteristics of PM over the Indian Himalayan Region (IHR) using FTIR and scanning electron microscopy-energy dispersive X-ray (SEM-EDX) analysis. The study aimed at source identification of PM by exploring the inorganic ions, organic functional groups, morphology and elemental characteristics. The pollution load of PM was estimated as 63 ± 22 μg m; 53 ± 16 μg m; 67 ± 26 μg m and 55 ± 11 μg m over Mohal-Kullu, Almora, Nainital and Darjeeling, respectively.

Potent multi-target natural inhibitors against SARS-CoV-2 from medicinal plants of the Himalaya: a discovery from hybrid machine learning, chemoinformatics, and simulation assisted screening.

The emergence and immune evasion ability of SARS-CoV-2 Omicron strains, mainly BA.5.2 and BF.

Is survival of Himalayan Cedar (Cedrus deodara) threatened? An evaluation based on predicted scenarios of its growth trend under future climate change.

Global warming is likely to become one of the significant drivers of forest losses in the Hindu-Kush Himalaya (HKH) during the 21 century. Better understanding of how forest ecosystem will respond to global warming requires a precise knowledge of site and species specific responses to climate change. We applied dendrochronological technique to quantify and predict future growth trend of Himalayan cedar (Cedrus deodara), a tree of high commercial importance, and explored its spatial growth variability under two different climatic regimes from 17 deodar sites in the HKH.

Understanding the role of natural and anthropogenic forcings in structuring the periphytic algal assemblages in a regulated river ecosystem.

Periphytic algal assemblages in the River Sindh of Kashmir Himalaya were studied in relation to environmental factors and anthropogenic alterations like flow regulation for Run-of-River hydropower plants to understand their ecology in a regulated river ecosystem. Sites were sampled from unregulated, regulated, and downstream reaches along the river on a seasonal basis from the year 2017 to 2019. A total of 48 species were identified, spread over 31 genera.

Impact evaluation of the run-of-river hydropower projects on the water quality dynamics of the Sindh River in the Northwestern Himalayas.

As the run-of-river (RoR) hydropower projects remain understudied, we conducted this study to understand how these projects affect the hydro-chemical dynamics and water quality index (WQI) of the Sindh River in the Kashmir Himalayas. We used multivariate statistical techniques and WQI to identify the spatiotemporal dynamics of 18 physico-chemical parameters from 11 sampling stations distributed along the length of river Sindh from December 2017 to December 2019. The dataset was classified into three groups using hierarchical cluster analysis based on similarities between hydro-chemical characteristics, and the results were confirmed by discriminant analysis.

Dayara bugyal restoration model in the alpine and subalpine region of the Central Himalaya: a step toward minimizing the impacts.

Eco-restoration initiative work in the high altitude Dayara pastureland (3501 m) from the Indian Himalayan Region has been considered to be one of the successful field demonstration against both natural and anthropogenic degradation. The present study therefore attempts to assess the implications of entire eco-restoration model as practiced by Department of Forest, Government of Uttarakhand in 2019. Its assessment was done by calculating restoration success index by way of considering three categories, viz.

Virtual screening of anti-HIV1 compounds against SARS-CoV-2: machine learning modeling, chemoinformatics and molecular dynamics simulation based analysis.

COVID-19 caused by the SARS-CoV-2 is a current global challenge and urgent discovery of potential drugs to combat this pandemic is a need of the hour. 3-chymotrypsin-like cysteine protease (3CLpro) enzyme is the vital molecular target against the SARS-CoV-2. Therefore, in the present study, 1528 anti-HIV1compounds were screened by sequence alignment between 3CLpro of SARS-CoV-2 and avian infectious bronchitis virus (avian coronavirus) followed by machine learning predictive model, drug-likeness screening and molecular docking, which resulted in 41 screened compounds.

Efficacy of a novel sequential enzymatic hydrolysis of lignocellulosic biomass and inhibition characteristics of monosugars.

Efficient production of sugar monomers from lignocellulose is often hampered by serious bottle-necks in biomass hydrolysis. The present study reveals that ultra-sonication assisted pretreatment following autoclaving, termed as combined pretreatment, can lead to more efficient delignification of lignocellulosic biomass and an open, deformed polysaccharide matrix, found favorable for subsequent enzymatic hydrolysis, is formed. The pattern of inhibition for the enzymatic hydrolysis reaction on combined-pretreated saw dust is identified.

Stable carbon and nitrogen isotopic composition of PM over Indo-Gangetic Plains (IGP), adjoining regions and Indo-Himalayan Range (IHR) during a winter 2014 campaign.

For source identification, a field campaign involving simultaneous sampling of particulate matter (PM) was conducted at eight sampling sites in the Indian mainland during winter 2014. The sampling sites include Delhi (upper IGP), Lucknow (middle IGP), and Kolkata (lower IGP) in the Indo-Gangetic Plains (IGP); Mohal-Kullu and Darjeeling in the Indo-Himalayan Range (IHR). In addition, Ajmer, located upwind of the IGP in NW-India and Giridih and Bhubaneswar, in the downwind to the IGP has also been chosen.

Loss of crop yields in India due to surface ozone: an estimation based on a network of observations.

Surface ozone is mainly produced by photochemical reactions involving various anthropogenic pollutants, whose emissions are increasing rapidly in India due to fast-growing anthropogenic activities. This study estimates the losses of wheat and rice crop yields using surface ozone observations from a group of 17 sites, for the first time, covering different parts of India. We used the mean ozone for 7 h during the day (M7) and accumulated ozone over a threshold of 40 ppbv (AOT40) metrics for the calculation of crop losses for the northern, eastern, western and southern regions of India.