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). Although there may be considerable variation in climate indices in terms of absolute values within different products, there is consensus in both long-term trends and inter-annual variability. Analysis shows that even within a small area, there is variability in the magnitude and direction of historic temperature trends. Initially, the data were subjected to rigorous quality control procedures, which involved identifying anomalies. Statistical analysis like trend analysis, employing Mann-Kendall test and Sen's slope estimator, reveal significant (p < 0.05) increase in consecutive dry days (CDD) at 0.03 days/year and decrease in consecutive wet days (CWD) at 0.02 days/year. Notably, the frequency of heavy precipitation occurrences showed an increasing trend. Changes in precipitation in the Western Himalaya are driven by a complex interplay of orographic effects, monsoonal dynamics, atmospheric circulation patterns, climate change, and localized factors such as topography, atmospheric circulation patterns, moisture sources, land-sea temperature contrasts, and anthropogenic influences. Moreover, in case of temperature indices, there is significant increasing trend observed. Temperature indices indicate a significant annual increase in warm nights (TN90p) at 0.06%/year and warm days (TX90p) at 0.11%/year. Extreme temperature events have been trending upward, with monthly daily maximum temperature (TXx) increasing by 1.5 °C yearly. This study enhances our comprehension of the global warming phenomenon and underscores the importance of acknowledging alterations in the water cycle and their repercussions on hydrologic resources, agriculture, and livelihoods in the cold desert of the northwestern Indian Himalaya.

Identification of sources of coarse mode aerosol particles (PM10) 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 PM10 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 PM10 by exploring the inorganic ions, organic functional groups, morphology and elemental characteristics. The pollution load of PM10 was estimated as 63 ± 22 µg m-3; 53 ± 16 µg m-3; 67 ± 26 µg m-3 and 55 ± 11 µg m-3 over Mohal-Kullu, Almora, Nainital and Darjeeling, respectively. ATR-FTIR spectrum analysis revealed the existence of inorganic ions (SiO44-, TiO2, SO42-, SO3-, NO3-, NO2-, CO32-, HCO3-, NH4+) and organic functional groups (C-C, C-H, C=C, C≡C, C=O, N-H, C≡N, C=N, O-H, cyclic rings, aromatic compounds and some heterogeneous groups) in PM10 which may arise from geogenic, biogenic and anthropogenic sources. The morphological and elemental characterization was performed by SEM-EDX, inferring for geogenic origin (Al, Na, K, Ca, Mg and Fe) due to the presence of different morphologies (irregular, spherical, cluster, sheet-like solid deposition and columnar). In contrast, particles having biogenic and anthropogenic origins (K, S and Ba) have primarily spherical with few irregular particles at all the study sites. Also, the statistical analysis ANOVA depicts that among all the detected elements, Na, Al, Si, S and K are site-specific in nature as their mean of aw% significantly varied for all the sites. The trajectory analysis revealed that the Uttarakhand, Jammu and Kashmir, the Thar Desert, Himachal Pradesh, Pakistan, Afghanistan, Nepal, Sikkim, the Indo-Gangetic Plain (IGP) and the Bay of Bengal (BoB) contribute to the increased loading of atmospheric pollutants in various locations within the IHR.

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.7 and other variants of concern have raised global apprehensions. With this context, the discovery of multitarget inhibitors may be proven more comprehensive paradigm than its one-drug-to-one target counterpart. In the current study, a library of 271 phytochemicals from 25 medicinal plants from the Indian Himalayan Region has been virtually screened against SARS-CoV-2 by targeting nine virus proteins, viz., papain-like protease, main protease, nsp12, helicase, nsp14, nsp15, nsp16, envelope, and nucleocapsid for screening of a multi-target inhibitor against the viral replication. Initially, 94 phytochemicals were screened by a hybrid machine learning model constructed by combining 6 confirmatory bioassays against SARS-CoV-2 replication using an instance-based learner lazy k-nearest neighbour classifier. Further, 25 screened compounds with excellent drug-like properties were subjected to molecular docking. The phytochemical Cepharadione A from the plant Piper longum showed binding potential against four proteins with the highest binding energy of -10.90 kcal/mol. The compound has acceptable absorption, distribution, metabolism, excretion, and toxicity properties and exhibits stable binding behaviour in terms of root mean square deviation (0.068 ± 0.05 nm), root-mean-square fluctuation, hydrogen bonds, solvent accessible surface area (83.88-161.89 nm2), and molecular mechanics Poisson-Boltzmann surface area during molecular dynamics simulation of 200 ns with selected target proteins. Concerning the utility of natural compounds in the therapeutics formulation, Cepharadione A could be further investigated as a remarkable lead candidate for the development of therapeutic drugs against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

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 21st 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. Of the two climate regimes, one is dominated by the monsoon rainfall and the other by the westerly disturbances. Analysis of tree ring width and climate (monthly temperature and precipitation) data reveals that the spring (March-May) temperature and precipitation affect the growth of deodar negatively and positively, respectively. We used Generalized Least Squares (GLS) regression model to forecast future growth of deodar by taking an ensemble of 40 General Circulation Models (GCMs) for emission scenarios RCP 4.5 and RCP 8.5. Predicted growth trends indicate the decline between 34 % and 38 % under RCP 4.5, and between 29 % and 32 % under RCP 8.5 scenarios, for the low and mid latitude sites. In contrast, a moderate increase in growth was observed in high latitude sites under the both climate scenarios. The study shows more drought stress to deodar trees growing in monsoon areas in mid-and low-latitude sites where less snow melt and low precipitation during the spring season are predicted to increase evapotranspiration. In comparison, in the higher latitude sites where there is a high snowfall due to western disturbances, the growth of deodar is predicted to increase. These findings may be used to take suitable migratory steps for the conservation of deodar in the HKH region.

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. Non-metric multidimensional analysis showed clear distinction in periphytic algal assemblage samples based on sites and potentially some more minor distinction based on seasons rendering the sites into two distinct groups (G1 and G2). The ADONIS test showed that the groups (G1 and G2 sites) do not significantly differ in terms of how communities differ from one another, but there is a difference in species compositions based on seasons. However, the betadisper test indicated that groups (G1 and G2 sites) and seasons present homogeneity among group dispersions (compositions vary similarly) while having significantly different compositions. Geo-physical factors (discharge and altitude) accounted for most variations, while the scraper community played a minor role. This study provides scientific insights related to the ecology of a regulated Himalayan river and may provide information relevant to managing the River Sindh sustainably.

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. Wilk's quotient distribution further showed that ions, nutrients, free carbon dioxide, water temperature, and pH contributed to the formation of clusters. Principle component analysis revealed that the chloride (Cl-), total phosphorus (TP), ortho-phosphorus (PO4-P), nitrate-nitrogen (NO3-N), nitrite-nitrogen (NO2-N), and sulfate ion (SO42-) are significant factors that influence the water quality. Furthermore, our results suggest that diverting water for RoR operation did not significantly raise the WQI value to the point where water in the bypassed reaches could be declared unfit for drinking. Our analysis concluded that inclusive assessments are vital for framing policies on expanding RoR hydropower in the region.

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., direct management measure (M), environmental desirability (E) and socio-economic feasibility (SE) considering 22 individual variables. 'M' comprised both biotic and abiotic pressures. Grazing and tourism were biotic, while abiotic pressure was considered mainly soil erosion in alpine area due to topographic fragility. Above ground vegetation profile and below ground soil nutrient profile (N, P, K, pH and water holding capacity) were analyzed in 'E' component. In the last but not least, 'SE' was analyzed to assess the social acceptability of the local communities and stakeholders who are supposed to be ultimate beneficiary of alike interventions. Direct management measure was found with the variable index score of 0.8 indicating the higher score as compared to environmental desirability (0.56). Under direct management measure, grazing and tourists' carrying capacity of the area was analyzed with high management needs to call the region sustainable in terms of availability of bio-resources. The ecosystem index score was evaluated for the reference (81.94), treated (64.5) and untreated zones (52.03), wherein increasing profile of these values were found. The outcomes like improved vegetation profile in terms of total herb density, soil nutrient profile of the restored area along with soil pH (4.96) and water holding capacity (49.85%) were found to be restored significantly along with controlling 169.64 tonne year-1 soil erosion from draining. The assessment of grazing pattern of 118 migratory Cow Unit (CU) (76 horse/mule and 18 sheep/goat, already controlled), 318 local CU (30 horse/mule and 187 sheep/goat) were calculated and recommended to be controlled. Tourists' carrying capacity of 274 tourists per day and manual removal of Rumex nepalensis at the shepherd camping site were found to be worth to apply in the area. Use of biodegradable but locally sourced material and engaging local villagers in this endeavor were also found to be in harmony with SDG Goal 1 (no poverty). Therefore, the restoration and its evaluation model could have its future prospects to prove as a successful restoration practice. This restoration practice could not only be worth in high altitude degraded alpine pastures of the Indian Himalayan Region but also to other mountain alpine and sub-alpine ecosystems.

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. These 41 compounds were re-screened by deep learning model constructed considering the IC50 values of known inhibitors which resulted in 22 hit compounds. Further, screening was done by structural activity relationship mapping which resulted in two structural clefts. Thereafter, functional group analysis was also done, where cluster 2 showed the presence of several essential functional groups having pharmacological importance. In the final stage, Cluster 2 compounds were re-docked with four different PDB structures of 3CLpro, and their depth interaction profile was analyzed followed by molecular dynamics simulation at 100 ns. Conclusively, 2 out of 1528 compounds were screened as potential hits against 3CLpro which could be further treated as an excellent drug against SARS-CoV-2.

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. Two main inhibition models (competitive and noncompetitive) are proposed and a better fit of experimental values with the theoretical values for the competitive inhibition model validates the proposition that in the present experiment, glucose inhibits the enzymes competitively. Additionally, accuracy of the inhibitory kinetics based models is estimated over a series of enzyme and substrate concentrations.

Stable carbon and nitrogen isotopic composition of PM10 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 (PM10) 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. To characterize the sources of the ambient PM10, stable isotope ratios of carbon (δ13CTC) and nitrogen (δ15NTN) for the total carbon (TC) and total nitrogen (TN) fractions have been considered. Ancillary chemical parameters, such as organic carbon (OC), elemental carbon (EC), and water-soluble ionic components (WSIC) mass concentrations are also presented in this paper. There was very small variation in the daily average δ13CTC ratios (- 24.8 to - 25.9‰) among the sites. Comparison with end-member stable C isotopic signatures of major typical sources suggests that the PM10 at the sites was mainly from fossil fuel and biofuel and biomass combustion. Daily average δ15NTN ratios were not observed to vary much between sites either (8.3 to 11.0‰), and the low δ15NTN levels also indicate substantial contributions from biofuel and biomass burning of primarily C3 andC4 plant matter. Graphical abstract Scatter plot of the average (± 1 standard deviation (SD)) δ13CTC (‰) compared to δ15NTN (‰) at the sampling sites.

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. Our estimates show the highest annual loss of wheat (about 9 million ton) in the northern India, one of the most polluted regions in India, and that of rice (about 2.6 million ton) in the eastern region. The total all India annual loss of 4.0-14.2 million ton (4.2-15.0%) for wheat and 0.3-6.7 million ton (0.3-6.3%) for rice are estimated. The results show lower crop loss for rice than that of wheat mainly due to lower surface ozone levels during the cropping season after the Indian summer monsoon. These estimates based on a network of observation sites show lower losses than earlier estimates based on limited observations and much lower losses compared to global model estimates. However, these losses are slightly higher compared to a regional model estimate. Further, the results show large differences in the loss rates of both the two crops using the M7 and AOT40 metrics. This study also confirms that AOT40 cannot be fit with a linear relation over the Indian region and suggests for the need of new metrics that are based on factors suitable for this region.