Climate change and geo-environmental factors influencing desertification: a critical review.

The problem of desertification (DSF) is one of the most severe environmental disasters which influence the overall condition of the environment. In Rio de Janeiro Earth Summit on Environment and Development (1922), DSF is defined as arid, semi-arid, and dry sub-humid induced LD and that is adopted at the UNEP's Nairobi ad hoc meeting in 1977. It has been seen that there is no variability in the trend of long-term rainfall, but the change has been found in the variability of temperature (avg. temp. 0-5 °C). There is no proof that the air pollution brought on by CO2 and other warming gases is the cause of this rise, which seems to be partially caused by urbanization. The two types of driving factors in DSF-CC (climate change) along with anthropogenic influences-must be compared in order to work and take action to stop DSF from spreading. The proportional contributions of human activity and CC to DSF have been extensively evaluated in this work from "qualitative, semi-quantitative, and quantitative" perspectives. In this study, we have tried to connect the drives of desertification to desertification-induced migration due to loss of biodiversity and agriculture failure. The authors discovered that several of the issues from the earlier studies persisted. The policy-makers should follow the proper SLM (soil and land management) through using the land. The afforestation with social forestry and consciousness among the people can reduce the spreading of the desertification (Badapalli et al. 2023). The green wall is also playing an important role to reduce the desertification. For instance, it was clear that assessments were subjective; they could not be readily replicated, and they always relied on administrative areas rather than being taken and displayed in a continuous space. This research is trying to fulfill the mentioned research gap with the help of the existing literatures related to this field.

Retraction Note: Weather indicators and improving air quality in association with COVID-19 pandemic in India.

[This retracts the article DOI: 10.1007/s00500-021-06012-9.].

Effects of climate change and sea-level rise on coastal habitat: Vulnerability assessment, adaptation strategies and policy recommendations.

On a first-order basis, the global "sea level rise" induced by climate change magnifies coastal land subsidence. Various research related to this discipline is associated with estimated sea level vulnerability in various spatial scales. But the potential impact of climate change on sea level rise and its amalgamated vulnerability to the species remain undiscovered with appropriate procedures. So, in this perspective, our main objective of this research is to estimate the potential impact of climate change on sea level rise and it is associated with vulnerability to coastal habitat. From this research, it is established that the increasing tendency of sea level from the base period to the projected period. The major port city of India has been considered in this research. The qualitative "coastal vulnerability index (CVI)" is based on quantitative estimates to characterize the physical setting, including "geomorphology (G), sea level change (SLC), coastal slope (CS), relative sea-level change (RSLC), mean wave height (MWH), mean tide range (MTR), shoreline change rate (SCR), land use and human activities (LU), and population (P)". The projected sea level rise (SLR) is increasing at the highest rate under the higher RCP (Representative Concentrations Pathways) scenario. This information is very helpful to the decision maker for considering the most appropriate development strategies to maintain the sustainable development of coastal ecology in India.

Weather indicators and improving air quality in association with COVID-19 pandemic in India.

The COVID-19 pandemic enforced nationwide lockdown, which has restricted human activities from March 24 to May 3, 2020, resulted in an improved air quality across India. The present research investigates the connection between COVID-19 pandemic-imposed lockdown and its relation to the present air quality in India; besides, relationship between climate variables and daily new affected cases of Coronavirus and mortality in India during the this period has also been examined. The selected seven air quality pollutant parameters (PM10, PM2.5, CO, NO2, SO2, NH3, and O3) at 223 monitoring stations and temperature recorded in New Delhi were used to investigate the spatial pattern of air quality throughout the lockdown. The results showed that the air quality has improved across the country and average temperature and maximum temperature were connected to the outbreak of the COVID-19 pandemic. This outcomes indicates that there is no such relation between climatic parameters and outbreak and its associated mortality. This study will assist the policy maker, researcher, urban planner, and health expert to make suitable strategies against the spreading of COVID-19 in India and abroad. Supplementary Information: The online version contains supplementary material available at 10.1007/s00500-021-06012-9.

Effect of hydrogeochemical behavior on groundwater resources in Holocene aquifers of moribund Ganges Delta, India: Infusing data-driven algorithms.

One of the fundamental sustainable development goals has been recognized as having access to clean water for drinking purposes. In the Anthropocene era, rapid urbanization put further stress on water resources, and associated groundwater contamination expanded into a significant global environmental issue. Natural arsenic and related water pollution have already caused a burden issue on groundwater vulnerability and corresponding health hazard in and around the Ganges delta. A field based hydrogeochemical analysis has been carried out in the elevated arsenic prone areas of moribund Ganges delta, West Bengal, a part of western Ganga- Brahmaputra delta (GBD). New data driven heuristic algorithms are rarely used in groundwater vulnerability studies, specifically not yet used in the elevated arsenic prone areas of Ganges delta, India. Therefore, in the current study, emphasis has been given on integration of heuristic algorithms and random forest (RF) i.e., "RF-particle swarm optimization (PSO)", "RF-grey wolf optimizer (GWO)" and "RF-grasshopper optimization algorithm (GOA)", to identify groundwater vulnerable zones on the basis of field based hydrogeochemical parameters. In addition, correspondence health hazard of this area was assessed through human health hazard index. The spatial distribution of groundwater vulnerability revealed that middle-eastern and north-western part of the study area covered by very high and high, whereas central, western and south-western part are covered by very low and low vulnerability zones in outcomes of all the applied models. The evaluation result indicates that RF-GOA (AUC = 0.911) model performed the best considering testing dataset, and thereafter RF-GWO, RF-PSO and RF with AUC value is 0.901, 0.892 and 0.812 respectively. Findings also revealed the groundwater in this study region is quite unfavorable for drinking and irrigation purposes. The suggested models demonstrate their usefulness in foretelling sustainable groundwater resource management in various deltaic regions of the world through taking appropriate measures by policy-makers.

Climate change and groundwater overdraft impacts on agricultural drought in India: Vulnerability assessment, food security measures and policy recommendation.

The problem of drought in India is a major issue in terms of various adverse impacts on livelihood of society. Drought Early Warning System (DEWS), a real-time drought-monitoring tool, has reported that over a fifth of India's geographical area (21.06 %) is suffering drought-like situations. This is 62 % larger than the drought-affected area during the same period last year, which was 7.86 %. Drought affects 21.06 %, with conditions ranging from unusually dry to extremely dry. While 1.63 % and 1.73 % of the area are experiencing 'extreme' or 'exceptional' dry conditions, 2.17 % is experiencing 'severe' dry conditions. Under 'moderate' dry circumstances, up to 8.15 % is possible. In this perspective groundwater vulnerability assessment in the overall country is needed for implementing the sustainable and long-term strategies for escaping from this type of hazardous situation. The main objective of this study is to estimate the drought vulnerability in changing climate which eventually influences the food security of India. The groundwater overdraft is one of the crucial elements in agricultural drought vulnerability. Various related parameters have been selected for estimating the drought vulnerability and its impact to food security in India. Here, MaxEnt (maximum entropy) and ANN (analytical neural network) has been considered in this perspective. The AUC values for the training datasets in the ANN and MaxEnt model are 0.891 and 0.921, respectively. The AUC values in ANN and MaxEnt model for the validation datasets are 0.876 and 0.904, respectively. Here MaxEnt model is most optimal than ANN considering predictive accuracy. From this study analysis it is established that western, south and middle portion of country is very much prone to drought vulnerability. So, special emphases in terms of the regional planning have to be taken into consideration for sustainable planning.

COVID-19 strict lockdown impact on urban air quality and atmospheric temperature in four megacities of India.

COVID-19 pandemic has forced to lockdown entire India starting from 24th March 2020 to 14th April 2020 (first phase), extended up to 3rd May 2020 (second phase), and further extended up to 17th May 2020 (third phase) with limited relaxation in non-hotspot areas. This strict lockdown has severely curtailed human activity across India. Here, aerosol concentrations of particular matters (PM) i.e., PM10, PM2.5, carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2), ammonia (NH3) and ozone (O3), and associated temperature fluctuation in four megacities (Delhi, Mumbai, Kolkata, and Chennai) from different regions of India were investigated. In this pandemic period, air temperature of Delhi, Kolkata, Mumbai and Chennai has decreased about 3 °C, 2.5 °C, 2 °C and 2 °C respectively. Compared to previous years and pre-lockdown period, air pollutants level and aerosol concentration (-41.91%, -37.13%, -54.94% and -46.79% respectively for Delhi, Mumbai, Kolkata and Chennai) in these four megacities has improved drastically during this lockdown period. Emission of PM2.5 has experienced the highest decrease in these megacities, which directly shows the positive impact of restricted vehicular movement. Restricted emissions produce encouraging results in terms of urban air quality and temperature, which may encourage policymakers to consider it in terms of environmental sustainability.

Have any effect of COVID-19 lockdown on environmental sustainability? A study from most polluted metropolitan area of India.

The long-term lockdown due to COVID-19 has beneficial impact on the natural environment. India has enforced a lockdown on 24th March 2020 and was subsequently extended in various phases. The lockdown due to the sudden spurt of the COVID-19 pandemic has shown a significant decline in concentration of air pollutants across India. The present article dealt with scenarios of air quality concentration of air pollutants, and effect on climatic variability during the COVID-19 lockdown period in Kolkata Metropolitan Area, India. The result showed that the air pollutants are significantly reduced and the air quality index (AQI) was improved during the lockdown months. Aerosol concentrations decreased by - 54.94% from the period of pre-lockdown. The major air pollutants like particulate matters (PM2.5, PM10), sulphur dioxide (SO2), carbon monoxide (CO) and Ozone (O3) were observed the maximum reduction ( - 40 to - 60%) in the COVID-19 lockdown period. The AQI has been improved by 54.94% in the lockdown period. On the other hand, Sen's slope rank and the Mann-Kendal trend test showed the daily decreased of air pollutants rate is - 0.051 to - 1.586 µg /m3. The increasing trend of daily minimum, average, and maximum temperature from the month of March to May in this year (2020s) are 0.091, 0.118, and 0.106 °C which is lowest than the 2016s to 2019s trend. Therefore, this research has an enormous opportunity to explain the effects of the lockdown on air quality and climate variability, and it can also be helpful for policymakers and decision-makers to enact appropriate measures to control air pollution.

Threats of climate change and land use patterns enhance the susceptibility of future floods in India.

The main objective of this work is the future prediction of the floods in India due to climate and land change. Human activity and related carbon emissions are the primary cause of land use and climate change, which has a substantial impact on extreme weather conditions, such as floods. This study presents high-resolution flood susceptibility maps of different future periods (up to 2100) using a combination of remote sensing data and GIS modelling. To quantify the future flood susceptibility various flood causative factors, Global circulation model (GCM) rainfall and land use and land cover (LULC) data are envisaged. The present flood susceptibility model has been evaluated through receiver operating characteristic (ROC) curve, where area under curve (AUC) value shows the 91.57% accuracy of this flood susceptibility model and it can be used for future flood susceptibility modelling. Based on the projected LULC, rainfall and flood susceptibility, the results of the study indicating maximum monthly rainfall will increase by approximately 40-50 mm in 2100, while the conversion of natural vegetation to agricultural and built-up land is about 0.071 million sq. km. and the severe flood event area will increase by up to 122% (0.15 million sq. km) from now on.

Optimization modelling to establish false measures implemented with ex-situ plant species to control gully erosion in a monsoon-dominated region with novel in-situ measurements.

Water dominated gullies formation and associated land degradation are the foremost challenges among the planners for sustainability and optimization of land resources. This type of hazardous phenomenon is utmost vulnerable due to huge loss of surface soil in the sub-tropical developing countries like India. The present study has been carried out in rugged badland topography of Garhbeta-I Community Development (C.D.) Block in eastern India for assessing the gully erosion susceptibility (GES) mapping and optimization of land use planning. The GES mapping is the first and foremost steps towards minimization this adverse affect and attaining sustainable development. In this study we also describe the importance of plantation and alternation of ex-situ tree species with in-situ species for minimizes the erosional activity. To meet our research goal here we used two prediction based machine learning algorithm (MLA) namely random forest (RF) and boosted regression tree (BRT) and one optimization model of Ecogeography based optimization (EBO). The research study also carried out by using a total of 199, in which 139 (70%) and 60 (30%) gully head-cut points were used for training and validation purposes respectively and treated as dependent factors, and twenty gully erosion conditioning factors as independent variables. These models are validated through receiver operating characteristics-area under the curve (ROC-AUC), accuracy (ACC), precision (PRE) and Kappa coefficient index analysis. The validation result showed that EBO model with the highest values of AUC-0.954, ACC-0.85, PRE-0.877 and Kappa-0.646 is the most accurate model for GES followed by BRT and RF. The outcome results should help for the sustainable development of this rugged badland topography.

Improvement in ambient-air-quality reduced temperature during the COVID-19 lockdown period in India.

The COVID-19 pandemic forced India as a whole to lockdown from 24 March 2020 to 14 April 2020 (first phase), extended to 3 May 2020 (second phase) and further extended to 17 May 2020 (third phase) and 31 May 2020 (fourth phase) with only some limited relaxation in non-hot spot areas. This lockdown has strictly controlled human activities in the entire India. Although this long lockdown has had a serious impact on the social and economic fronts, it has many positive impacts on environment. During this lockdown phase, a drastic fall in emissions of major pollutants has been observed throughout all the parts of India. Therefore, in this research study we have tried to establish a relationship among the fall in emission of pollutants and their impact on reducing regional temperature. This analysis was tested through the application of Mann-Kendall and Sen's slope statistical index with air quality index and temperature data for several stations across the country, during the lockdown period. After the analysis, it has been observed that daily emissions of pollutants (PM10, PM2.5, CO, NO2, SO2 and NH3) decreased by - 1- - 2%, allowing to reduce the average daily temperature by 0.3 °C compared with the year of 2019. Moreover, this lockdown period reduces overall emissions of pollutants by - 51- - 72% on an average and hence decreases the average monthly temperature by 2 °C. The same findings have been found in the four megacities in India, i.e., Delhi, Kolkata, Mumbai and Chennai; the rate of temperature fall in the aforementioned megacities is close to 3 °C, 2.5 °C, 2 °C and 2 °C, respectively. It is a clear indicator that a major change occurs in air quality, and as a result it reduced lower atmospheric temperature due to the effect of lockdown. It is also a clear indicator that a major change in air quality and favorable temperature can be expected if the strict implementations of several pollution management measures have been implemented by the concern authority in the coming years.

Significant decrease of lightning activities during COVID-19 lockdown period over Kolkata megacity in India.

The outbreak of COVID-19 has now created the largest pandemic and the World health organization (WHO) has declared social distancing as the key precaution to confront such type of infections. Most of the countries have taken protective measures by the nationwide lockdown. The purpose of this study is to understand the effect of lockdown on air pollutants and to analyze pre-monsoon (April and May) cloud-to-ground and inter-cloud lightning activity in relation to air pollutants i.e. suspended Particulate matter (PM10), Nitrogen dioxides (NO2) Sulfur dioxide (SO2), Ozone (O3) and Aerosol concentration (AC) in a polluted tropical urban megacities like Kolkata. After the strict lockdown the pollutants rate has reduced by more than 40% from the pre-lockdown period in the Kolkata megacity. So, decreases of PM10, NO2, SO2, O3 and AC have a greater effect on cloud lightning flashes in the pre-monsoon period. In the previous year (2019), the pre-monsoon average result shows a strong positive relation between the lightning and air pollutants; PM10 (R2 = 0.63), NO2 (R2 = 0.63), SO2 (R2 = 0.76), O3 (R2 = 0.68) and AC (R2 = 0.83). The association was relatively low during the lock-down period (pre-monsoon 2020) and the R2 values were 0.62, 0.60, 0.71, 0.64 and 0.80 respectively. Another thing is that the pre-monsoon (2020) lightning strikes decreased by 49.16% compared to the average of previous years (2010 to 2019). The overall study shows that the reduction of surface pollution in the thunderstorm environment is strongly related to the reduction of lightning activity where PM10 and AC are the key pollutants in the Kolkata megacity.

Antimicrobial properties of Kalanchoe blossfeldiana: a focus on drug resistance with particular reference to quorum sensing-mediated bacterial biofilm formation.

OBJECTIVES: This study attempts to investigate the antimicrobial properties of Kalanchoe blossfeldiana with a particular reference to quorum sensing (QS)-mediated biofilm formation. METHODS: The methanol extract of K. blossfeldiana leaves (MEKB) was evaluated for antimicrobial properties including QS-controlled production of biofilm (including virulence factor, motility and lactone formation) in Pseudomonas aeruginosa. Methanol extract of K. blossfeldiana was also evaluated for anti-cytokine (tumour necrosis factor-alpha, interleukin-6 and interleukin-1 beta) properties in peripheral blood mononuclear cells (PBMC). KEY FINDINGS: Methanol extract of K. blossfeldiana exhibited antimicrobial effect on clinical isolates, as well as standard reference strains. Pseudomonas aeruginosa exposed to MEKB (subminimum inhibitory concentration (MIC)) displayed reduced biofilm formation, whereas supra-MIC produced destruction of preformed biofilms. Methanol extract of K. blossfeldiana reduced the secretion of virulence factors (protease and pyoverdin) along with generation of acyl homoserine lactone (AHL). Confocal laser scanning microscopy images indicate reduction of biofilm thickness. The extract also reduced cytokine formation in lipopolysaccharide-stimulated PBMC. CONCLUSIONS: Kalanchoe blossfeldiana was found to interfere with AHL production, which in turn may be responsible for downregulating QS-mediated production of biofilm and virulence. This first report on the antibiofilm and anticytokine properties of this plant may open up new vistas for future exploration of this plant for combating biofilm-related resistant infections.

Pharmacological studies on Buchanania lanzan Spreng.- a focus on wound healing with particular reference to anti-biofilm properties.

OBJECTIVE: To evaluate the wound healing activity of the methanolic root extract of Buchanania lanzan Spreng. (B. lanzan), with a focus on antimicrobial and anti-biofilm properties. METHODS: The extract was evaluated for its wound healing properties (excision and incision models) as evident from the analysis of tensile strength and wound contraction. The extract was also screened for antibacterial properties against different Gram positive and Gram negative bacterial strains. B. lanzan was also studied for its effect on biofilm formation and disruption of preformed biofilms. The synergistic effect of B. lanzan was determined in combination with gentamicin. RESULTS: Topical application of B. lanzan (10% w/w ointment) significantly increased (40.84%) the tensile strength in the incision wound model. B. lanzan also showed significant wound healing activity in excision model and such significant activity was observed from the 9th day. Whereas Soframycin displayed significant wound healing activity from the 6th day. It was found that root extracts of B. lanzan revealed significant inhibition against all tested pathogens. B. lanzan displayed antimicrobial activity against Gram positive (MIC 0.625 mg/mL) and Gram negative (MIC 0.625-1.25 mg/mL). B. lanzan was able to reduce biofilm formation and also caused disruption of preformed biofilms in a manner similar to ciprofloxacin. However, gentamicin was found to be ineffective against biofilms formed by Gram negative organism. According to the fractional inhibitory concentration index, B. lanzan displayed synergistic activity when it was combined with gentamicin. CONCLUSIONS: From this study it may be concluded that the root extract of B. lanzan revealed significant wound healing potential, which was supported and well correlated with pronounced antibacterial activity of the tested plant parts.

Pharmacological studies on Buchanania lanzan Spreng.-A focus on wound healing with particular reference to anti-biofilm properties

Objective:To evaluate the wound healing activity of the methanolic root extract of Buchanania lanzan Spreng. (B. lanzan), with a focus on antimicrobial and anti-biofilm properties. Methods: The extract was evaluated for its wound healing properties (excision and incision models) as evident from the analysis of tensile strength and wound contraction. The extract was also screened for antibacterial properties against different Gram positive and Gram negative bacterial strains. B. lanzan was also studied for its effect on biofilm formation and disruption of preformed biofilms. The synergistic effect of B. lanzan was determined in combination with gentamicin. Results:Topical application of B. lanzan (10%w/w ointment) significantly increased (40.84%) the tensile strength in the incision wound model. B. lanzan also showed significant wound healing activity in excision model and such significant activity was observed from the 9th day. Whereas Soframycin displayed significant wound healing activity from the 6th day. It was found that root extracts of B. lanzan revealed significant inhibition against all tested pathogens. B. lanzan displayed antimicrobial activity against Gram positive (MIC 0.625 mg/mL) and Gram negative (MIC 0.625-1.25 mg/mL). B. lanzan was able to reduce biofilm formation and also caused disruption of preformed biofilms in a manner similar to ciprofloxacin. However, gentamicin was found to be ineffective against biofilms formed by Gram negative organism. According to the fractional inhibitory concentration index, B. lanzan displayed synergistic activity when it was combined with gentamicin. Conclusions:From this study it may be concluded that the root extract of B. lanzan revealed significant wound healing potential, which was supported and well correlated with pronounced antibacterial activity of the tested plant parts.

Deliberate Self-harm: A Search for Distinct Group of Suicide.

OBJECTIVE: Some persons attempt suicide with a strong intention to die and some are not. Presently, no distinctive grouping has been done on the basis of the suicidal intention, though there is a significant variation in the psycho-socio-demographic profile, suicidal ideation, and intent within the persons making suicidal attempt. The aim of our study was to find the psycho-socio-demographic profile, suicide intent in survivors of suicide attempt, categorizing them by suicide intent, and finally to define the deliberate self-harm (DSH) group. MATERIALS AND METHODS: It was a cross-sectional study. Two hundred patients who survived suicide attempt were evaluated by a psychiatrist. The data were recorded for sociodemographic variables, psychiatric disorder, suicide intent, and lethality of suicide attempt. Grouping was done by using suicide intent as the determining dimension. The DSH group was defined by psycho-socio-demographic characteristics of the patient. RESULTS: The mean age of the DSH group was 26.72 years, mostly females (50.5%), semiskilled workers (43.43%) and housewives (32.32%), from nuclear family (60.6%) with no psychiatric disorder (35.35%). Most of them attempted a nonlethal suicide attempt (87.87%) by organophosphorus poisoning (87.87%). CONCLUSIONS: The DSH group is a distinct group among suicide attempters, having different psycho-socio-demographic characteristics.