Pre-monsoon Season Research Articles

Sea-level rise and mental health among coastal communities: A quantitative survey and conditional process analysis

This is the first large-scale empirical study examining the impact of sea-level rise induced by climate change on mental health outcomes among coastal communities. The study focuses on Bangladesh, a country severely affected by salinity ingress, flood risks, and agricultural damage due to sea-level changes. Participants (n = 1,200) randomly selected from three coastal regions each having high, moderate, or low vulnerability to sea-level rise were surveyed during the pre-monsoon season in 2021. The cross-sectional survey included validated measures of psychological distress, depression, anxiety, stress, environmental stressors, resource loss, and demographics. The results indicated significantly higher levels of psychological distress, depression, anxiety, and stress in residents of high-vulnerability areas compared to moderate or low-vulnerability regions. Resource loss served as a mediating variable between environmental stressors and mental health outcomes. Furthermore, demographic analyses showed that older adults and women reported higher levels of psychological distress. These findings align with the Sendai Framework for Disaster Risk Reduction, highlighting urgent need for targeted mental health interventions and sustainable models of care in coastal areas increasingly threatened by sea-level rise.

Neighbouring effect of land use changes and fire emissions on atmospheric CO2 and CH4 over suburban region of India (Shadnagar)

The present study investigated the effects of land use/land cover (LU/LC) changes on atmospheric carbon dioxide (CO2) and methane (CH4) concentrations over the sub-urban region of India (Shadnagar) using continuous decadal CO2 and CH4in-situ data measured by the greenhouse gas analyser (GGA). Data was collected from 2013 to 2022 at a 1 Hz frequency. Analysis of the current study indicates that during pre-monsoon, the seasonal maximum of CO2 was 409.91 ± 9.26 ppm (μ ± 1σ), while the minimum during monsoon was about 401.64 ± 7.13 ppm. Post-monsoon has a high seasonal mean CH4 concentration of 2.08 ± 0.06 ppm, while monsoon has a low seasonal mean CH4 concentration of 1.88 ± 0.03 ppm. The primary classes, such as forest, crop, and built-up, were considered to estimate the effect of LU/LC changes on atmospheric CO2 and CH4 concentrations. Between 2005 and 2021, the study's results show that the built-up area at radii of 10 km, 20 km, and 50 km increased by 0.17 %, 0.10 %, and 0.4 %, respectively. While other LU/LC categories declined by 30 %, agriculture areas increased by 30 % on average. As a result, the CO2 and CH4 concentrations at the study site are increased by 6 % (26 ppm) and 6.5 % (140 ppb), respectively. The present study utilised the fire-based carbon emissions data from the Global Fire Emissions Database (GFED) to understand the impact on atmospheric CO2 and CH4. Analysis of the present work investigated the influence of transported airmass on CO2 and CH4 during the pre-monsoon and post-monsoon seasons using the HYSPLIT trajectories and found emissions were from the northwest, southeast, and northeast of the study site. Further, in-situ CO2 and CH4 records are compared against the MIROC4-ACTM simulation, and strong agreement was found with bias of 1.80 ppm and 0.98 ppb for CO2 and CH4, respectively.

New evidence for CH4 enhancement in the upper troposphere associated with the Asian summer monsoon

The Asian summer monsoon (ASM) region is a key region transporting air to the upper troposphere (UT), significantly influencing the distribution and concentration of trace gases, including methane (CH4), an important greenhouse gas. We investigate the seasonal enhancement of CH4 in the UT over the ASM region, utilizing retrievals from the Atmospheric Infrared Sounder (AIRS), model simulations and in-situ measurements. Both the AIRS data and model simulation reveal a substantial enhancement in CH4 concentrations within the active monsoon region of up to 3%, referring to the zonal means, and of up to 6% relative to the pre-monsoon season. Notably, the spatial distribution of the CH4 plume demonstrates a southwestward shift in the AIRS retrievals, in contrast to the model simulations, which predict a broader enhancement, including a significant increase to the east. A cross-comparison with in-situ measurements, including AirCore measurements over the Tibetan Plateau and airline sampling across the ASM anticyclone (ASMA), favors the enhancement represented by model simulation. Remarkable CH4 enhancement over the west Pacific is also evidenced by in-situ data and simulation as a dynamical extension of the ASMA. Our findings underscore the necessity for cautious interpretation of satellite-derived CH4 distributions, and highlight the critical role of in-situ data in anchoring the assimilation of CH4.

Spatio-temporal evaluation of the impact of anthropogenic stressors on physico-chemical characteristics and water quality of the River Ganga using GIS-based approach in the middle Gangetic Plains at Patna, Bihar, India.

The present study aimed to assess the impact of anthropogenic stressors on the physico-chemical characteristics and water quality of the River Ganga employing a GIS-based approach in the middle Gangetic Plain at Patna, India. After the survey, sand mining, bridge construction, and disposal of untreated domestic and sewage wastes were selected as major anthropogenic stressors. A total of 48 samples were collected in pre-monsoon and post-monsoon seasons of 2022 and were analyzed for 16 physico-chemical parameters, namely water temperature (WT), pH, electrical conductivity (EC), total dissolved solids (TDS), turbidity, dissolved oxygen (DO), biological oxygen demand (BOD), total hardness (TH), Ca2+, Mg2+, Na+, K+, Cl- and SO42- ions, following standard protocols. The WQI was calculated using the Weighted Arithmetic Water Quality Index (WAQWI) method and spatial maps were created using ArcGIS software. The result revealed significant seasonal variation in several physico- chemical parameters except for Ca2+, K+ and TA (p > 0.05). ANOVA revealed significant variation for BOD and COD at Ghagha and Triveni, whereas for nitrate at Gai Ghat reference and impact sites, respectively. The Water Quality Index (WQI) revealed a deterioration in water quality by 60% in post-monsoon season. HCA revealed that the WQI was mostly governed by TDS, TH, TA, and EC.

Index Based Irrigation Suitability of Ramsar Sites (Rara and Ghodaghodi) in Western Nepal

The present study highlights the water quality of two important Ramsar sites of western Nepal (Ghodaghodi and Rara lakes) in terms of irrigation use. Based on land use patterns and location accessibility, 13 sites in Ghodaghodi and 18 in Rara were considered and the samplings were performed in the pre-monsoon and post-monsoon seasons. Different physicochemical parameters such as pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness (TH), major cations, and anion (Na+, K+, Ca2+, Mg2+, and HCO3-) were measured. The calculated indices were permeability index percentage (PI), sodium percentage (%Na), sodium adsorption ratio (SAR), magnesium hazard ratio (MAR), residual sodium carbonate (RSC), and Kelly’s index (KI). Major ions were analyzed using ion chromatography including field and procedural blanks to maintain quality standards, whereas on-site parameters were measured by using standard multi-meter probes. The studied irrigation water quality parameters (pH, EC, TDS, TH) and indices (PI, MAR, RSC, KI, SAR, and %Na) fall within the permissible limit in both lakes, indicating the suitability of such water for irrigation purposes. In addition, based on the SAR vs. EC plot, all the results from both lakes fall in the S1 category, signifying low sodium hazard. Concerning EC, most of the samples demonstrate the C1 category and few are in the C2 category (in Ghodaghodi) whereas the C1 category predominates for Rara. According to IWQI, all water samples in both lakes fall in the class I category, which supports the results of other indices indicating the suitability of water for irrigation purposes.

Evaluation of Coastal Sediments for Heavy Metal Contamination, Bhavnagar Coast, Gulf of Khambhat, Gujarat, India

ABSTRACT This research examined heavy metals distribution and potential environmental impact in seven locations along the Bhavnagar coast in Gujarat, India. The study used several analyses, including hierarchical cluster analysis (HCA), principal component analysis (PCA), and correlation analysis to investigate the harmful heavy metals present in the area. To evaluate the possible risk of Cd, Pb, Cr, Zn, Co, Cu, Ni, Mn, and Fe to the marine environment, pollution indices such as contamination factors (Cf), enrichment factor (Ef), geo-accumulation index (Igeo), ecological risk factor (Er), ecological risk index (RI) and sediment quality guidelines (SQGs) applied. Based on the results, the mean concentration of heavy metals was ranked in the following order (mg/kg): Fe (561.4) > Mn (58.9) > Cr (42) > Zn (12.5) > Pb (8.2) > Ni (7) > Cu (5.2) > Co (2.7) > Cd (.3). Compared to the pre-monsoon and post-monsoon seasons, the results showed a diluting impact on heavy metal concentrations during the monsoon season. The spatial distribution of the heavy metals indicated that the geogenic source and anthropogenic source were the primary contributors to pollution in the studied region. Principal component analysis suggests that Cd, Pb, Co and Cr may have come from shipbreaking activities, municipal discharge and industrial operations. Cf, Igeo, and Ef demonstrated no pollution to moderate pollution, with a maximum contribution of Cd, and the coastal sediment poses a minimal ecological risk for all heavy metals investigated. Shipbreaking, urban runoff, salt-marine, and agricultural runoff release toxic metals into the coastal environment. In conclusion, the information obtained from this geochemical characterization could be valuable to policymakers and stakeholders in developing effective management measures for the Bhavnagar coastal region, Gulf of Khambhat, Gujarat, India.

Radiative effect of atmospheric Brown clouds over the Indo-Gangetic plain

Atmospheric brown clouds (ABCs) are widespread hazy accumulation of particles and gases dominant with absorbing nature impacting the air quality, hydrology and climate. The Indo-Gangetic plain (IGP) being an ABCs hotspots is prone to extreme pollution episodes due to anthropogenic activities. However, there is a scarcity of studies that specifically compare episodes of absorbing aerosols (ABCs) and comparatively non-absorbing aerosols (non-ABCs) along with their respective radiative impacts over the IGP. Here, we have used ground-based remote-sensors’ retrieved datasets from AErosol RObotic NETwork (AERONET) to study spatio-temporal variation of ABCs’ frequency and associated radiative properties across the IGP region during 2001–2019. The shortwave aerosol radiative effect (ARE) during ABC and non-ABC episodes is estimated using Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model. Our results show significant spatial variability in the frequency of ABC episodes across the IGP stations with ∼17 ± 5%, ∼19 ± 11% and ∼18 ± 13% average occurrence during winter, pre-monsoon and post-monsoon seasons, respectively. ARE estimations show enhanced surface dimming (ARESRF) and atmospheric warming (AREATM) during ABC episodes as compared to non-ABC episodes. A general increasing trend for ARE is observed as we move from west to east across the IGP due to the meteorological and geographical variations in the region. Our results show day-time averaged ARESRF varying between −142.46 ± 25.13 and −56.66 ± 6.88 W/m2 while AREATM ranging from 58.07 ± 2.58 to 132.69 ± 7.43 W/m2 for ABC episodes. Though ABC episodes show lower aerosol loading as compared to non-ABC episodes in our study, we found higher atmospheric heating during ABC episodes mainly due to distinct chemical composition (lower single scattering albedo) of absorbing aerosols. The upper bound of the difference between atmospheric heating rate during ABC and non-ABC episodes is found to be 0.48 ± 0.27 K/day.

Exploring thermal comfort in rural houses of Chhattisgarh state, India: A comprehensive survey and adaptive model analysis

Thermal comfort studies in India are very much at an emerging stage. According to Indian codes, in the summer, the comfortable temperature range for residential buildings is 23–26 °C. The recommended Indian residential comfort range does not consider the impact of India’s enormous cultural and geographical heterogeneity. Additionally, there seems to be very little effort to conduct a thermal comfort field survey in India’s rural regions. In recent years, houses in rural India have been converted from kutcha (mud houses) to pucca (concrete houses). This work is aimed at proposing an adaptive thermal comfort model for the premonsoon season in the rural area of Raipur, Chhattisgarh, India. The model was achieved using a field study survey conducted in 80 rural area houses in the months of June and July. Regression analysis, the Griffiths method, and the Fanger method have been adopted to analyze thermal comfort. Based on the regression analysis, the comfort band (voting −1 to +1) is established in the range of 28.39 °C to 32.31 °C, with 30.30 °C as the neutral temperature. The study has been carried out to assess the influence of gender, age, controls, and fan usage on thermal comfort perception in rural households.

Hydrogeochemical characterization and non-carcinogenic health risk assessment of fluoride and nitrate-affected groundwater in northern parts of Tumkur district, Karnataka, India

Groundwater contamination from geogenic and anthropogenic sources is a significant concern for the public health across the globe. In India, fluoride and nitrate contamination are the most prevalent contaminants in the groundwater. This study evaluated groundwater quality in four over-exploited sub-districts of Tumkur district in Karnataka by collecting 143 samples from post and pre-monsoon seasons and using different hydrogeochemical, statistical and bivariate graphical approaches. Comparison with Drinking Water Standard guidelines revealed elevated levels of fluoride, nitrate, and total dissolved solids (TDS), rendering the groundwater unsuitable for drinking. According to Chadha’s diagram, the predominant groundwater type is Na-Cl, and Gibbs diagram suggested the influence of rock dissolution and weathering. Bivariate plots indicated that hydrogeochemical characteristics were primarily influenced by silicate weathering of minerals, cation ion exchange processes, and anthropogenic factors. A non-carcinogenic health risk assessment was conducted using two different hazard index (HI) approaches from United States Environmental Protection Agency (USEPA) and Agency for Toxic Substances and Disease Registry (ATSDR). It was found that health risk associated with fluoride is more significant than the health risk from nitrate, with children being the most affected, followed by adolescents and adults. A holistic approach to assess cumulative health risks from fluoride and nitrate contamination in groundwater, as demonstrated in this study, promotes the synergistic advancement of SDG 3: Good health and well-being and SDG 6: Clean water and sanitation.

Enhanced prediction of premonsoon thunderstorms over eastern India through assimilation of INSAT‐3D sounding data

AbstractThe present study assesses the impact of Indian National Satellite 3D (INSAT‐3D)‐derived atmospheric (temperature and relative humidity) profiles on the simulation of severe thunderstorms over eastern India during the premonsoon season. Two sets of numerical experiments, without assimilation (CNTL) and with assimilation of INSAT‐3D profiles (INSAT) have been conducted using the three‐dimensional variational data assimilation system of the Weather Research and Forecasting model for 11 thunderstorm events. Analysis increments are positive with INSAT profile assimilation in the lower to middle atmosphere in the thunderstorm region. The errors in the initial fields have been reduced by approx. 50% after the assimilation. After assimilation, the predictions of the surface fields (2‐m temperature, 2‐m relative humidity, and 10‐m wind speed) have been improved at the mature stage (by 37%, 26%, and 15%) compared to the CNTL. Similar improvements are noticed in the vertical profiles of relative humidity and wind speed in the INSAT experiment. The time and magnitude of updrafts and downdrafts improved in INSAT. After assimilation, rainfall intensity improved in nine cases, and time improved in four cases out of 11. The Critical Success Index (False Alarm Rate) of the INSAT ranges from approx. 0.6–0.15 (∼0.37–0.48) for all thresholds, and are higher (lower) than the CNTL. The rainfall area is improved by 25% for light rainfall, 11% for moderate rainfall, and 2% for heavy rainfall in the INSAT over the CNTL experiment. Overall thunderstorm prediction has been improved with the assimilation of INSAT‐3D data. Thus, the study highlights the viability of INSAT‐3D profiles in improving thunderstorm predictions over eastern India.

Seasonal to decadal dynamics of supraglacial lakes on debris-covered glaciers in the Khumbu region, Nepal

Abstract. Supraglacial lakes (SGLs) play an important role in debris-covered glacier (DCG) systems by enabling efficient interactions between the supraglacial, englacial, and subglacial environments. Developing a better understanding of the short-term and long-term development of these features is needed to constrain DCG evolution and the hazards posed to downstream communities, ecosystems, and infrastructure from rapid drainage. In this study, we present an analysis of supraglacial lakes on eight DCGs in the Khumbu region of Nepal by automating SGL identification in PlanetScope, Sentinel-2, and Landsat 5–9 images. We identify a regular annual cycle in SGL area, with lakes covering approximately twice as much area during their maximum annual extent (in the pre-monsoon season) than their minimum annual extent (in the post-monsoon season). The high spatiotemporal resolution of PlanetScope imagery (∼ daily, 3 m) shows that this cycle is driven by the appearance and expansion of small lakes in the upper debris-covered regions of these glaciers throughout the winter. Decadal-scale expansion of large, near-terminus lakes was identified on four of the glaciers (Khumbu, Lhotse, Nuptse, and Ambulapcha), while the remaining four showed no significant increases over the study period. The seasonal variation in SGL area is of comparable or greater magnitude as decadal-scale changes, highlighting the importance of accounting for this seasonality when interpreting long-term records of SGL changes from sparse observations. The complex spatiotemporal patterns revealed in our analysis are not captured in existing regional-scale glacial lake databases, suggesting that more targeted efforts are needed to capture the true variability of SGLs on large scales.

Sustainable water management in rice cultivation reduces arsenic contamination, increases productivity, microbial molecular response, and profitability

Arsenic (As) and silicon (Si) are two structurally competitive natural elements where Si minimises As accumulation in rice plants, and based on this two-year field trial, the study proposes adopting alternating wetting and drying (AWD) irrigation as a sustainable water management strategy allowing greater Si availability. This field-based project is the first report on AWD's impact on As-Si distribution in fluvio-alluvial soils of the entire Ganga valley (24 study sites, six divisions), seasonal variance (pre-monsoon and monsoon), rice plant anatomy and productivity, soil microbial diversity, microbial gene ontology profiling and associated metabolic pathways. Under AWD to flooded and pre-monsoon to monsoon cultivations, respectively, greater Si availability was achieved and As-bioavailability was reduced by 8.7 ± 0.01–9.2 ± 0.02% and 25.7 ± 0.09–26.1 ± 0.01%. In the pre-monsoon and monsoon seasons, the physiological betterment of rice plants led to the high rice grain yield under AWD improved by 8.4 ± 0.07% and 10.0 ± 0.07%, proving the economic profitability. Compared to waterlogging, AWD evidences as an optimal soil condition for supporting soil microbial communities in rice fields, allowing diverse metabolic activities, including As-resistance, and active expression of As-responsive genes and gene products. Greater expressions of gene ontological terms and complex biochemical networking related to As metabolism under AWD proved better cellular, genetic and environmental responsiveness in microbial communities. Finally, by implementing AWD, groundwater usage can be reduced, lowering the cost of pumping and field management and generating an economic profit for farmers. These combined assessments prove the acceptability of AWD for the establishment of multiple sustainable development goals (SDGs).

Forest fire estimation and risk prediction using multispectral satellite images: Case study

IntroductionForest fires are increasing in terms of number, size, and extent which have a growing influence on the achievement of the Sustainable Development Goals (SDGs). The economy and ecology of Northeast India have been seriously impacted by forest fires in many places, it is important to comprehend the region's spatiotemporal distribution, severity, and future projections for forest fires in light of climate change. MethodsGeographical information systems (GIS) integrating with remote sensing (RS) were used to understand the role of different parameters in all four bioclimatic zones of the region. Resultsand discussion: Most of the fires were restricted to pre-monsoon season (93 %), alone 62 % in March. The forest fire in the present scenario was highest in the Lawngtlai district, followed by Dhalai and Ri-Bhoi. The Lawngtlai and Dhalai districts are at the highest risk (greater than 70 %) for future forest fires. Categorically, among the protected areas, Lengteng WLS has the highest (86.6 %) future forest fire risk followed by Tawi WLS (86.5 %), Ngengpui WLS (84.9 %), and Pualreng WLS (84.6 %). ConclusionThe results suggest that underground biomass in the lower elevated forest needs to be managed effectively at the onset of the fire season to reduce the occurrence of forest fires. There is a need for a well-defined framework supported by geospatial technology to predict, identify, and prioritize the fire potential zone with synergic strategies supported by the local community to mitigate the fire impact on the forests.

Inferring the impacts of climate extreme in the Kabul River Basin

The increasing temperature and variability in precipitation, in terms of both frequency and intensity, are affecting different sectors in the Himalayan region. This study aims to quantify the future scenario and related extremes in the Kabul River Basin (KRB) of the western Himalaya using high-resolution climate datasets. We selected four representative General Circulation Model (GCM) runs from Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios, based on future projections, climatic extremes and their abilities to represent the historical climate cycle (1981–2010) of KRB. The seasonal analysis of precipitation shows decreasing pattern during the winter and pre-monsoon seasons and annual mean temperature will increase consistently by 3 to 5 °C in RCP4.5 and 8.5 scenarios. Ten indices were selected to study climatic extremes pertaining to the health, agriculture and water resources sectors. The extremes, like consecutive summer days, warm days and heatwaves, will increase, whereas the frost days, cold nights, cold waves and extreme precipitation days will decrease towards the end of this century. Besides, the extremes are not homogenous in time and space. Based on the results of this study, there is a need for prompt climate actions in order to increase the adaptive capacity against these extreme changes and to build resilient livelihoods in the KRB.

Quantifying effects of long-range transport of NO2 over Delhi using back trajectories and satellite data

Abstract. Exposure to air pollution is a leading public health risk factor in India, especially over densely populated Delhi and the surrounding Indo-Gangetic Plain. During the post-monsoon seasons, the prevailing north-westerly winds are known to influence aerosol pollution events in Delhi by advecting pollutants from agricultural fires as well as from local sources. Here we investigate the year-round impact of meteorology on gaseous nitrogen oxides (NOx=NO+NO2). We use bottom-up NOx emission inventories (anthropogenic and fire) and high-resolution satellite measurement based tropospheric column NO2 (TCNO2) data, from S5P aboard TROPOMI, alongside a back-trajectory model (ROTRAJ) to investigate the balance of local and external sources influencing air pollution changes in Delhi, with a focus on different emissions sectors. Our analysis shows that accumulated emissions (i.e. integrated along the trajectory path, allowing for chemical loss) are highest under westerly, north-westerly and northerly flow during pre-monsoon (February–May) and post-monsoon (October–February) seasons. According to this analysis, during the pre-monsoon season, the highest accumulated satellite TCNO2 trajectories come from the east and north-west of Delhi. TCNO2 is elevated within Delhi and the Indo-Gangetic Plain (IGP) to the east of city. The accumulated NOx emission trajectories indicate that the transport and industry sectors together account for more than 80 % of the total accumulated emissions, which are dominated by local sources (>70 %) under easterly winds and north-westerly winds. The high accumulated emissions estimated during the pre-monsoon season under north-westerly wind directions are likely to be driven by high NOx emissions locally and in nearby regions (since NOx lifetime is reduced and the boundary layer is relatively deeper in this season). During the post-monsoon season the highest accumulated satellite TCNO2 trajectories are advected from Punjab and Haryana, where satellite TCNO2 is elevated, indicating the potential for the long-range transport of agricultural burning emissions to Delhi. However, accumulated NOx emissions indicate local (70 %) emissions from the transport sector are the largest contributor to the total accumulated emissions. High local emissions, coupled with a relatively long NOx atmospheric lifetime and shallow boundary layer, aid the build-up of emissions locally and along the trajectory path. This indicates the possibility that fire emissions datasets may not capture emissions from agricultural waste burning in the north-west sufficiently to accurately quantify their influence on Delhi air quality (AQ). Analysis of daily ground-based NO2 observations indicates that high-pollution episodes (>90th percentile) occur predominantly in the post-monsoon season, and more than 75 % of high-pollution events are primarily caused by local sources. But there is also a considerable influence from non-local (30 %) emissions from the transport sector during the post-monsoon season. Overall, we find that in the post-monsoon season, there is substantial accumulation of high local NOx emissions from the transport sector (70 % of total emissions, 70 % local), alongside the import of NOx pollution into Delhi (30 % non-local). This work indicates that both high local NOx emissions from the transport sector and the advection of highly polluted air originating from outside Delhi are of concern for the population. As a result, air quality mitigation strategies need to be adopted not only in Delhi but in the surrounding regions to successfully control this issue. In addition, our analysis suggests that the largest benefits to Delhi NOx air quality would be seen with targeted reductions in emissions from the transport and agricultural waste burning sectors, particularly during the post-monsoon season.

Weakened black carbon trans-boundary transport to the Tibetan Plateau during the COVID-19 pandemic

The lockdowns implemented during the coronavirus disease 2019 (COVID-19) pandemic provide a unique opportunity to investigate the impact of emission sources and meteorological conditions on the trans-boundary transportation of black carbon (BC) aerosols to the Tibetan Plateau (TP). In this study, we conducted an integrative analysis, including in-situ observational data, reanalysis datasets, and numerical simulations, and found a significant reduction in the trans-boundary transport of BC to the TP during the 2020 pre-monsoon season as a result of the lockdowns and restrictive measures. Specifically, we observed a decrease of 0.0211 μgm−3 in surface BC concentration over the TP compared to the 2016 pre-monsoon period. Of this reduction, approximately 6.04 % can be attributed to the decrease in emissions during the COVID-19 pandemic, surpassing the 4.47 % decrease caused by changes in meteorological conditions. Additionally, the emission reductions have weakened the trans-boundary transport of South Asia BC to the TP by 0.0179 μgm−2s−1; indicating that the recurring spring atmospheric pollution from South Asia to the TP will be alleviated through the reduction of anthropogenic emissions. Moreover, it is important to note that BC deposition on glaciers contributes significantly to glacier melting due to its enrichment, posing a threat to the water sustainability of the TP. Therefore, urgent measures are needed to reduce emissions from adjacent regions to preserve the TP as the “Asian Water Tower.”

Evaluation of groundwater quality by adopting a multivariate statistical approach and indexing of water quality in Sagar Island, West Bengal, India.

In the vicinity of the coast, predominantly groundwater is the sole reliable resource for potable purposes as the surface water sources are highly saline and unfit for human consumption. However, the groundwater in Sagar Island is highly vulnerable to saltwater intrusion. The majority of drinking water comes from government-owned hand pump-equipped tube wells. But during the summer season, many of these tube wells yield significantly less water. Hence, in the current scenario, water quality assessment has become important to the quantity available. Total of 31 samples of deep tube wells (groundwater) are collected at variegated locations during pre-monsoon season throughout Sagar, and then, the physical and chemical quality parameters of these water samples are analysed. Furthermore, a multivariate statistical technique is executed with the aid of the SPSS program. The hydro-chemical parameters that are taken into account for the quality analysis are pH, salinity, electrical conductivity (EC), total dissolved solids (TDS), total hardness, aluminium, arsenic, bi-carbonate, cadmium, iron, chloride, copper, chromium, cobalt, lead, magnesium, manganese, nickel, potassium, sulphate, zinc, and sodium. Then, the analysed data evaluates the water quality index (WQI). Five components are identified through the principal component analysis (PCA) technique, and 82.642% total variance is found. The outcomes of the quality assessment study illustrate that about 54.84% of collected samples come in the "excellent" water quality class when calculated by the "weighted arithmetic WQI method," and 90.32% of collected groundwater samples come in the "good" water quality class when computed using the "modified weighted arithmetic WQI method." This study helps for the interpretation of WQI to assess groundwater quality.

Unravelling blue landscape fragmentation effects on ecosystem services in urban agglomerations

The blue landscape (BL), which refers to the wetlands, rivers, lakes, and other bodies of water, is of immense importance for a sustainable environment. It provides a variety of ecosystem services, including carbon sequestration, water purification, soil fertility, and habitat for diverse flora and fauna. These services are crucial for sustaining the livelihoods of local communities and maintaining the health of the environment. In megacities like Kolkata, India, the BL is often subjected to fragmentation and degradation due to rapid urbanisation, industrialization, and other human activities. This has serious implications for ecosystem services and the overall health of the environment. This study is intended to value ecosystem service losses over the last 25 years and assess the influence of blue landscape fragmentation on ecosystem services in Kolkata, India. To accomplish this goal, satellite data was collected from 1994 to 2019 for both pre-monsoon and post-monsoon seasons. The results of the study showed that significant losses in ecosystem services were observed over this time period, primarily due to the decline of the East Kolkata Wetland and its conversion for settlement and agricultural purposes. Despite the existence of some policies aimed at protecting the wetland, more robust restrictions and remedial strategies are required to conserve and restore the blue landscape in Kolkata. This work adds to the corpus of research on the value of blue landscapes (BLs) and the environmental services they provide. The findings of this study highlight the need for increased attention to the conservation and management of BLs in India and provide a valuable foundation for future research and policy development. Furthermore, this research introduces the innovative concept of urban BLs as a nature-based framework for understanding urban landscape fragmentation, a novel contribution that fills a gap in the existing literature on this topic.

Human health risk assessment model associated with PM2.5 bound metals in paradip port township, India

This study aimed to assess the environmental risk and human health risks associated with PM2.5-bound metals in Paradip city between January 2019 and December 2021. The seasonal average concentrations of PM2.5 were measured 91.43 ± 70.18 μg m−3, 103.40 ± 60.80 μg m−3, 124.74 ± 62.37 μg m−3, and 159.37 ± 77.88 μg m−3 in pre-monsoon, monsoon, post-monsoon, and winter season respectively. The highest and lowest concentrations are estimated in the winter and pre-monsoon season. Paradip city experienced tropical weather conditions with a hot and humid climate. The wind pattern shows that the predominant wind direction was observed from the south-south-west (SSW) direction. The metals in PM2.5 were analysed using an atomic absorption spectrophotometer (AAS) by air-acetylene flame using a hollow cathode lamp. The average metal concentration decreased in the order of Fe > Al > Zn > Pb > Cr > Mn > Ni > Cu > Co > Cd > As. The value of the geo-accumulation index (Igeo) was evaluated >1 for Cd, Fe, and Zn elements. The health risk assessment (HRA) results showed that non-carcinogenic risk (NCR) was higher through the inhalation route followed by ingestion and dermal contact. The cumulative NCR, which is expressed in terms of the hazard index (HI), is greater than 1 for infant (2.78E+00), child (2.53E+00), and adult (1.04E+00) via inhalation pathway. The total carcinogenic risk (TCR) for infants, children, and adults was estimated at 1.45E-04, 7.24E-05 and 1.25E-05, respectively, which exceeded the acceptable limit of 1.00E-06. Our comprehensive research plays an important role in both policymakers and relevant stakeholders for the preparation of city action plans concerning ambient air pollution, which can improve the air quality in and around Paradip city, India.

Red-necked Falcons Falco chicquera track changing environments by shifting their trophic niche during the rainy monsoon season

ABSTRACT Capsule Red-necked Falcons Falco chicquera shift their trophic niche, from eating birds to bats, during the rainy monsoon season. Aims To explore seasonal changes in prey weight, diet composition, and mobbing interactions of the globally Near Threatened Red-necked Falcon in Bangladesh. Methods We analysed long-term direct observations of 19 adult pairs feeding on prey between 2002 and 2019, exploring changes in mean prey weight, prey group, and mobbing interactions throughout the cool dry winter, hot pre-monsoon, and rainy monsoon seasons. Results The probability of bats being present within the diet increased over time, from 16% in the cool dry winter and 11% in the pre-monsoon hot season, to 48% in the rainy monsoon season. This coincided with a significant decline in mean prey weight and biomass consumed during the rainy monsoon season. Probabilities of falcons being mobbed during feeding varied throughout the seasons, depending on mobbing species. Conclusion Red-necked Falcons appeared to track changing environments by shifting their trophic niche during the rainy monsoon season. This may be due to: (a) an optimal foraging response to bat population fluxes, itself a response to weather-induced increases in flying insect abundances, (b) opportunistic hunting of bats during periods of crepuscular activity peaks, and/or (c) the energetic demands of fledglings during the rainy monsoon season.