Strain-enabled radical spirocyclization cascades: rapid access to spirocyclobutyl lactones and - lactams.

Spirocyclobutane derivatives have gained significant attention in drug discovery programs due to their broad spectrum of biological activities and clinical applications. Ring-strain in organic molecules is a powerful tool to promote reactivity by releasing strain energy, allowing the construction of complex molecules selectively and efficiently. Herein, we report the first strain-enabled radical spirocyclization cascades for the synthesis of functionalized spirocyclobutyl lactones and - lactams, which are finding increasing applications in medicinal chemistry. The reaction of interelement compounds with bicyclobutane (BCB) allyl esters and - amides proceeds with high chemoselectivity under simple, catalyst-free conditions using blue light irradiation. The reaction has been successfully extended to synthesize bis-spirocycles. To introduce a more diverse set of functional groups, we have developed a dual photoredox/nickel catalytic system capable of mediating the carbosulfonylation of BCB allyl amides. The reaction shows broad applicability across various (hetero)aryl halides, aryl sulfinates, and BCB allyl amides, operates under mild conditions and demonstrates excellent functional group compatibility. The functional groups introduced during the cascade reactions served as versatile handles for further synthetic elaboration.

Groundwater Salinity Across India: Predicting Occurrences and Controls by Field-Observations and Machine Learning Modeling.

Elevated groundwater salinity is unsuitable for drinking and harmful to crop production. Thus, it is crucial to determine groundwater salinity distribution, especially where drinking and agricultural water requirements are largely supported by groundwater. This study used field observation (n = 20,994)-based machine learning models to determine the probabilistic distribution of elevated groundwater salinity (electrical conductivity as a proxy, >2000 µS/cm) at 1 km2 across parts of India for near groundwater-table conditions. The final predictions were made by using the best-performing random forest model. The validation performance also demonstrated the robustness of the model (with 77% accuracy). About 29% of the study area (including 25% of entire cropland areas) was estimated to have elevated salinity, dominantly in northwestern and peninsular India. Also, parts of the northwestern and southeastern coasts, adjoining the Arabian Sea and the Bay of Bengal, were assessed with elevated salinity. The climate was delineated as the dominant factor influencing groundwater salinity occurrence, followed by distance from the coast, geology (lithology), and depth of groundwater. Consequently, ∼330 million people, including ∼109 million coastal populations, were estimated to be potentially exposed to elevated groundwater salinity through groundwater-sourced drinking water, thus substantially limiting clean water access.

Modelling of soil erosion susceptibility incorporating sediment connectivity and export at landscape scale using integrated machine learning, InVEST-SDR and Fragstats.

Evaluating the linkage between soil erosion and sediment connectivity for export assessment in different landscape patterns at catchment scale is valuable for optimization of soil and water conservation (SWC) practices. Present research attempts to identify the soil erosion susceptible (SES) sites in Kangsabati River Basin (KRB) using machine learning algorithm (decision trees, decision trees cross validation, CV, Extreme Gradient Boosting, XGB CV and bagging CV) taken thirty five variables, for investigating the linkage between erosion rates and sediment connectivity to assess the sediment export at sub-basin level employing connectivity index (IC) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) sediment delivery ratio (SDR) model. Based on AUC of receiving operating curve in validation test, excellent capacity of extreme Gradient Boosting, XGB CV and bagging CV (0.95, 0.90) than decision tree and decision tree CV (0.78, 0.82), exhibits about 18.58 % of basin areas facing susceptible to very high erosion. Conversely, considering universal soil loss equation (RUSLE) parameters, InVEST-SDR model estimated about 64.24 % of soil loss rate occurred from high SES in where sediment export rate become very high (136.995 t/ha-1/y-1). The IC result show that high sediment connectivity (<-4.4) measured in high SES of laterite and bare land in upper catchment, and double crop agricultural areas in lower catchment, while least connectivity (>-7.1) observed in low SES of dense forest, vegetation cover and settlement built-up areas. Pearson correlation matrix revealed that four landscape indices category i.e. edge metrics (p < 0.01), aggregation metrics (p < 0.001), shape metrics (p < 0.01-0.001) and diversity metrics (p < 0.01) signified the influence of landscape patterns on IC and SES. Accordingly, RUSLE, SDR and landscape matrices reveals that maximum sediment export rate associated with high connective delivery outlet and high SES in laterite, double crop and bare land due to simple landscape and greater homogeneity, whilst minimum export rate related with low connectivity and low SES in dense forest, vegetation cover and settlement built up area causes of fragmented landscape and spatial heterogeneity. Finally, findings could immense useful for formulating the optimizing measures of SWC in the watershed.

Selective Metal-Free CO2 Photoreduction in Water Using Porous Nanostructures with Internal Molecular Free Volume.

The conversion of CO2 to a sole carbonaceous product using photocatalysis is a sustainable solution for alleviating the increasing levels of CO2 emissions and reducing our dependence on nonrenewable resources such as fossil fuels. However, developing a photoactive, metal-free catalyst that is highly selective and efficient in the CO2 reduction reaction (CO2RR) without the need for sacrificial agents, cocatalysts, and photosensitizers is challenging. Furthermore, due to the poor solubility of CO2 in water and the kinetically and thermodynamically favored hydrogen evolution reaction (HER), designing a highly selective photocatalyst is challenging. Here, we propose a molecular engineering approach to design a photoactive polymer with high CO2 permeability and low water diffusivity, promoting the mass transfer of CO2 while suppressing HER. We have incorporated a contorted triptycene scaffold with "internal molecular free volume (IMFV)" to enhance gas permeability to the active site by creating molecular channels through the inefficient packing of polymer chains. Additionally, we introduced a pyrene moiety to promote visible-light harvesting capability and charge separation. By leveraging these qualities, the polymer exhibited a high CO generation rate of 77.8 µmol g-1 h-1, with a high selectivity of ∼98% and good recyclability. The importance of IMFV was highlighted by replacing the contorted triptycene unit with a planar scaffold, which led to a selectivity reversal favoring HER over CO2RR in water. In situ electron paramagnetic resonance (EPR), time-resolved photoluminescence spectroscopy (TRPL), and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) techniques, further supported by theoretical calculations, were employed to enlighten the mechanistic insight for metal-free CO2 reduction to exclusively CO in water.

Wurtzite CuGaS2 with an In-Situ-Formed CuO Layer Photocatalyzes CO2 Conversion to Ethylene with High Selectivity.

We present surface reconstruction-induced C-C coupling whereby CO2 is converted into ethylene. The wurtzite phase of CuGaS2. undergoes in situ surface reconstruction, leading to the formation of a thin CuO layer over the pristine catalyst, which facilitates selective conversion of CO2 to ethylene (C2 H4 ). Upon illumination, the catalyst efficiently converts CO2 to C2 H4 with 75.1 % selectivity (92.7 % selectivity in terms of Relectron ) and a 20.6 µmol g-1 h-1 evolution rate. Subsequent spectroscopic and microscopic studies supported by theoretical analysis revealed operando-generated Cu2+ , with the assistance of existing Cu+ , functioning as an anchor for the generated *CO and thereby facilitating C-C coupling. This study demonstrates strain-induced in situ surface reconstruction leading to heterojunction formation, which finetunes the oxidation state of Cu and modulates the CO2 reduction reaction pathway to selective formation of ethylene.

Intrinsic Charge Polarization in Bi19 S27 Cl3 Nanorods Promotes Selective CC Coupling Reaction during Photoreduction of CO2 to Ethanol.

Obtaining multi-carbon products via CO2  photoreduction is a major catalytic challenge involving multielectron-mediated CC bond formation. Complex design of multicomponent interfaces that are exploited to achieve this chemical transformation, often leads to untraceable deleterious changes in the interfacial chemical environment affecting CO2  conversion efficiency and product selectivity. Alternatively, robust metal centers having asymmetric charge distribution can effectuate CC coupling reaction through the stabilization of intermediates, for desired product selectivity. However, generating inherent charge distribution in a single component catalyst is a difficult material design challenge. Here, a novel photocatalyst, Bi19 S27 Cl3 , is presented which selectively converts CO2  to a C2  product, ethanol, in high yield under visible light irradiation. Structural analysis through transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and X-ray absorption spectroscopy reveals the presence of charge polarized bismuth centers in Bi19 S27 Cl3 . The intrinsic electric field induced by charge polarized bismuth centers renders better separation efficiency of photogenerated electron-hole pair. Furthermore, charge polarized centers yield better adsorption of CO* intermediate and accelerate the rate determining CC coupling step through the formation of OCCOH intermediate. Formation of these intermediates is experimentally mapped by in situ Fourier-transform infrared spectroscopy and further confirmed by theoretical calculation.

Arsenic enriched groundwater discharge to a tropical ocean: Understanding controls and processes.

The role of submarine groundwater discharge (SGD) in transporting terrestrial-sourced arsenic (As) to the global oceans is not well documented. In the present study, executed on a coast adjoining the extensive groundwater As-contaminated Ganges river delta, we hypothesize that As-enriched groundwater discharges to the adjoining Bay of Bengal (BoB) through SGD flow paths. We conducted high-resolution, field-based investigations and thermodynamic modeling to understand the SGD-sourced As discharge and geochemical cycling of As and other redox-sensitive solutes along the discharge path under varying redox conditions and water sediment interactions. The As distribution and other solutes were measured in a series of multi-depth observation wells and sediment cores, extending from the high tide line (HTL) to 100 m toward the sea, for pre- and post-monsoon seasons. Results reveal the presence of a plume carrying up to 30 µg/L dissolved load of As toward the sea. Arsenic is associated with a plume of Fe and exhibits similar shore-perpendicular variability. Arsenic distribution and transport is controlled by the Fe-Mn redox cycle and influenced by terrestrial groundwater discharge. Field-observations and geochemical modeling demonstrate that Fe-hydroxide precipitates in the subterranean estuary and acts as an interim sink for As , which is eventually mobilized on alteration of geochemical conditions with the season. Fluctuating plume size can be attributed to seasonal variation in fresh groundwater input to the site. Estimates indicate up to 55mg/m2/d As is released to BoB from the site. Based on physicochemical observations this study demonstrates the yet to be studied SGD derived As cycles and the role of SGD dynamics in controlling the fate of redox-sensitive contaminants and their discharge into global oceans.

Multifunctional resilience of river health to human service demand in an alluvial quarried reach: a comparison amongst fuzzy logic, entropy, and AHP-based MCDM models.

Riverine ecosystem services to human beings are dynamically evaluated by harmonic relationships; however, over growing human service demands (HSDs) are leading to deteriorate the river health resilience. In this study, an assessment index system of river health involving pressure-state-response (PSR) based on twenty indicators of riparian, channel geomorphic, hydroecological, and social attributes was developed to detect the multifunctional reliability and resilience of river system integrity for HSDs at upper (US), middle (MS), and lower segments (LS) of Kangsabati River using fuzzy logic, analytical hierarchical process (AHP), and entropy weight-based multi-criteria decision matrix (MCDM) methods. Borda integrating MCDM results revealed that overall indicator performance is high health score in US (77), medium score in MS (69), but mostly unhealthy score in LS (34); thus, entropy-MCDM models give highest rank to US, medium rank to MS, and least rank to LS, while AHP and fuzzy MCDM models assigned as high priority rank to MS, medium rank to US, and least rank to LS, respectively. According to model validation performances, entropy-MCDM models (RMSE < 2.48) are rationalized to the harmonic relationship of riverine system, whereas fuzzy and AHP-MCDM models (RMSE < 2.79) are signified to HSDs, and these results are closer to real problems. With the acceptability of AHP-MCDM models through the percentage change (73.89%) and intensity change (17.16) assessment, it points that over HSDs are crucial factors for river health degradation. Moreover, final outcome of the present research helps to find out the sick river health sites for ecological restoration.

Activating oxygen deficient TiO2 in the visible region by Bi2MoO6 for CO2 photoreduction to methanol.

Fast photogenerated charge recombination and inappropriate bandgap for visible light driven charge generation hinders the performance of TiO2. In this study, TiO2 was activated for visible light driven CO2 reduction in the presence of Bi2MoO6 as an electron donor. Furthermore, the introduction of oxygen vacancies resulted in enhanced CO2 adsorption and conversion. The best catalyst gives 27.1 µmol g-1 h-1 methanol formation. DRIFTS was used to explain the methanol formation mechanism on oxygen deficient TiO2.

Impact of global-scale hydroclimatic patterns on surface water-groundwater interactions in the climatically vulnerable Ganges river delta of the Sundarbans.

The global climate patterns like El Niño Southern Oscillation (ENSO) cycle and Indian Ocean Dipole (IOD) have impacts on surface water quality and groundwater recharge patterns. But the ENSO and IOD impacts on surface water-groundwater (SW-GW) interaction in terms of quality have not been studied. Therefore, the present study was conducted to delineate the impacts of ENSO and IOD on the SW-GW interaction process-induced groundwater quality of coastal aquifers of Sundarbans, by the application of isotopic signature, salinity content of groundwater and seawater in relation to rainfall variability. Study results revealed that the declining trend of rainfall potentially increases the seawater salinity. The rainfall pattern also positively correlates with the groundwater level (GWL) at a 5% level of significance observed from the wavelet analysis. The deficit in rainfall due to the El Niño is the possible reason for the declining GWL, which is giving rise to groundwater salinity. El Niño also affected the nearshore seawater salinity which was increased from 19 to 24 ppT. The study provides a surrogate understanding of the potential impact of El Niño in one of the most climatically vulnerable parts of the planet, while IOD impacts are not conclusive. In the scenario of depleted rainfall amount, groundwater abstraction practices need to be managed, otherwise, it could create a potential threat to the available drinking water resources in the present and future climate change scenarios.

Quantifying the dynamics of sub-daily to seasonal hydrological interactions of Ganges river with groundwater in a densely populated city: Implications to vulnerability of drinking water sources.

Groundwater resources in South Asian cities are facing immense stress due to over-extraction leading to environmental, social and economic instabilities. The perennial mega rivers of Himalayas form the lifeline for South Asia, underpinning food and water security for a large population both directly and indirectly through exchange with groundwater systems. The present study delineates the spatio-temporal variation in patterns and processes of sub-hourly to annual-scale hydrological exchanges between the Ganges and its adjoining highly exploited aquifer in a urban-peri urban reach. Multivariate statistical analyses established river water-groundwater interaction in this region with ~40% loading of first principal component, i.e river water during monsoon on the shallow aquifer. The part of the aquifer detached from the main confined aquifer show an influence of precipitation (the second principal component) with loading of ~90%. Again the part of the aquifer suffering infiltration of local surface water bodies show effect of precipitation with a second principal loading of ~80%. Fourier transformation is used in the hydrograph to remove influence of heavy urbanization on the hydrographs. This study proves that the phenomenon of infiltrating river water during monsoon plays a primary role in controlling aquifer storage although contaminating the aquifer simultaneously. However, during pre and post-monsoon the flow path reversal helps in maintaining river baseflow. Cross-correlation between the river and piezometric series show increased delay of pressure head propagation of the infiltrating river waterfront, with increasing distance. These observations are also substantiated by stable isotope signatures. The present study provides an understanding of potential groundwater vulnerability resulting from waste water and irrigational contamination through river water intrusion which would eventually lead the government to implement proper water and environmental management policies towards availability of long-term sustainable water resources for the residents.

A study of cluster hypergraphs and its properties.

In this study, cluster hypergraphs are introduced to generalize the concept of hypergraphs, where cluster nodes are allowed. Few related terms and properties on cluster hypergraphs are discussed. Some operations, including the Cartesian product, union, intersection, etc., are studied. Different types of matrix representations and isomorphism are also proposed on cluster hypergraphs. The notion of an effective degree for nodes is introduced to capture the group/ cluster effects. At last, the area of applications and future directions with conclusions is deployed.

Solute exchanges between multi-depth groundwater and surface water of climatically vulnerable Gangetic delta front aquifers of Sundarbans.

The coastal aquifers of Sundarbans, an UNESCO world biodiversity heritage site, are highly vulnerable due to changing climatic conditions, intensification and increasing frequency of extreme climate events and uncontrolled abstraction of groundwater. The exchange of solutes between hydraulically connective shallow and deep aquifers, the seawater intrusion and the role of growing population are poorly understood in the Sundarbans. This study aims to address the solute exchange (Cl-, Sr2+, and salinity) process between surface water and groundwater (SW-GW) at local to regional scale under variable hydraulic head conditions, where annual rainfall is declining and population density is increasing [population 573 (1991) to 819 (2011)/Km2]. Electrical resistivity tomography (ERT) in combination with salinity and δ18O data was used to address the exchange of solutes between SW-GW in a hydraulic continuation. The results revealed that regionally, the Cl- concentration of Sundarbans shows an increasing trend (average 329-351 mg/L) with declining groundwater levels (⁓3 m). Local, depth-dependent study depicting there is a predominant exchange of Sr2+ between shallow depth [D1: 14-25 and D2: 30-50 m below ground level (m bgl)] with seawater (Sr2+: 30-85 µM), which is possibly absent at greater depths (D3:115 and D4: 333 m bgl). The recorded Sr2+ content ranged from 25 to 102 and 16 to 78 µM for shallow depth D1 and D2, respectively, whereas, the Sr2+ concentrations ranged from 1.4 to 6.8 and 1.2 to 5.7 µM for D3 and D4, respectively. The ERT data showed progressively increasing resistivity with increasing depth, similar to high salinity and enriched δ18O at shallow depths and depleted δ18O with low salinity at higher depth reflects the continuous distribution of solutes, which is possibly a result of local downward migration of contaminated shallow brackish water within this physically disconnected zone. The lateral and vertical transportation of solutes in variable hydraulic head conditions would be a measure of drinking water threat in present-day and in imminent future for millions of inhabitants near the coastal area.

Self-Assembly and Cascade Catalysis by a Soft-Oxometalate (SOM) System.

Cascade catalysis has gained importance due to its various applications. In this work, cascade catalysis was performed using a self-assembled soft-oxometalate (SOM) as a model system. At first, we synthesized an oxometalate (OM) hybrid with a polymerizable organic cation, namely tetrakis(4-aminophenyl)methane, and an OM, K8[SiW11O39]. The hybrid in turn was converted into SOM in water, DMSO mixture, and characterized by different techniques, ranging from electron microscopy to DLS. The SOM state is endowed with the ability to polymerize the aniline based counter ions associated with it in the presence of UV-light. This polymerization is possible due to the presence of photocatalytic OMs (oxometalates) in the SOMs. The polymer-SOM hybrid in cascade oxidizes selectively aniline to nitrobenzene and nitrite to nitrate owing to the residual oxidizing property of the OM constituents in it. This is the first example of cascade catalysis in SOM chemistry.

Achieving Sustainable Development Goal for Clean Water in India: Influence of Natural and Anthropogenic Factors on Groundwater Microbial Pollution.

Worldwide, >2 billion people (~1/3 world population), mostly living in economically stressed areas of Africa and South Asia, still do not have access to basic sanitation, and ~1 billion still practice open defecation. Water pollution due to open defecation may primarily be linked to economy, and other factors such as social and hygiene practices, land use and hydrogeological parameters could also have sufficient influence. The present study describes the effect of human development index (HDI, 2001-2015) and economic development (NL, 1992-2013) on groundwater microbial pollution (FC, 2002-2017) across India. Economic development pattern suggested discernable inverse relationship with FC in most areas, although areas with inferior water quality, improper human practices were found to outweigh economic development. Vulnerability modelling, using these data, along with measured FC in groundwater-sourced drinking water locations (n = 235) demonstrated the heterogeneity of FC distribution potential in areas of homogenous economy, social practices, and land use. High-resolution numerical modelling of the advective transport of the hypothetical FC particles in the aquifers, suggest up to ~24 times faster movement of pollutants under irrigation-induced pumping regimes. Hence, the results of our study highlight and quantify the potential pitfalls that are possible hindrance for achieving the United Nations sustainable development goal, despite social and economic development, across the spatial scales.

Sub-basin prioritization for assessment of soil erosion susceptibility in Kangsabati, a plateau basin: A comparison between MCDM and SWAT models.

Kangsabati basin located in tropical plateau region faces multiple problems of soil erosion susceptibility (SES), soil fertility deterioration, and sedimentation in reservoirs. Hence, identification of SES zones in thirty-eight sub-basins (SB) for basin prioritization is necessary. The present research addressed the issue by using four multi-criteria decision-making (MCDM) models: VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR), technique for order preference by similarity to ideal solution (TOPSIS), simple additive weighing (SAW), compound factor (CF). To determine the best fitted method from MCDM for erosion susceptibility (ES), a comparison has been made with Soil and Water Assessment Tool (SWAT), where fifteen morphometric parameters were considered for MCDM, and meteorological data, soil, slope and land use land cover (LULC) were considered for SWAT model. Two validation indices of percentage change and intensity change were used for evaluation and comparison of MCDM results. With SWAT model performance, SWAT calibration and uncertainty analysis programs (CUP) was used for sensitive analysis of SWAT parameters on flow discharge and sediment load simulation. The results showed that 23, 16, 18 SB have high ES; therefore they were given 1 to 3 ranks, whereas 31, 37, 21SB have low ES, hence given 38 to 36 rank as predicted by MCDM methods and SWAT. MCDM validation results depict that VIKOR and CF methods are more acceptable than TOPSIS and SAW. Calibration (flow discharge R2 0.86, NSE 0.75; sediment load R2 0.87, NSE 0.69) and validation (flow discharge R2 0.79, NSE 0.55; sediment load R2 0.79, NSE 0.76) of SWAT model indicated that simulated results are well fitted with observed data. Therefore, VIKOR reflects the significant role of morphometric parameters on ES, whereas SWAT reflects the significant role of LULC, slope, and soil on ES. However, it could be concluded that VIKOR is more effective MCDM method in comparison to SWAT prediction.

Sub-basin prioritization for assessment of soil erosion susceptibility in Kangsabati, a plateau basin: A comparison between MCDM and SWAT models.

Kangsabati basin located in tropical plateau region faces multiple problems of soil erosion susceptibility (SES), soil fertility deterioration, and sedimentation in reservoirs. Hence, identification of SES zones in thirty-eight sub-basins (SB) for basin prioritization is necessary. The present research addressed the issue by using four multi-criteria decision-making (MCDM) models: VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR), technique for order preference by similarity to ideal solution (TOPSIS), simple additive weighing (SAW), compound factor (CF). To determine the best fitted method from MCDM for erosion susceptibility (ES), a comparison has been made with Soil and Water Assessment Tool (SWAT), where fifteen morphometric parameters were considered for MCDM, and meteorological data, soil, slope and land use land cover (LULC) were considered for SWAT model. Two validation indices of percentage change and intensity change were used for evaluation and comparison of MCDM results. With SWAT model performance, SWAT calibration and uncertainty analysis programs (CUP) was used for sensitive analysis of SWAT parameters on flow discharge and sediment load simulation. The results showed that 23, 16, 18 SB have high ES; therefore they were given 1 to 3 ranks, whereas 31, 37, 21SB have low ES, hence given 38 to 36 rank as predicted by MCDM methods and SWAT. MCDM validation results depict that VIKOR and CF methods are more acceptable than TOPSIS and SAW. Calibration (flow discharge R2 0.86, NSE 0.75; sediment load R2 0.87, NSE 0.69) and validation (flow discharge R2 0.79, NSE 0.55; sediment load R2 0.79, NSE 0.76) of SWAT model indicated that simulated results are well fitted with observed data. Therefore, VIKOR reflects the significant role of morphometric parameters on ES, whereas SWAT reflects the significant role of LULC, slope, and soil on ES. However, it could be concluded that VIKOR is more effective MCDM method in comparison to SWAT prediction.

Ecophysiological evaluation of tree species for biomonitoring of air quality and identification of air pollution-tolerant species.

Identification of tree species that can biologically monitor air pollution and can endure air pollution is very much important for a sustainable green belt development around any polluted place. To ascertain the species, ten tree species were selected on the basis of some previous study from the campus of the University of Burdwan and were studied in the pre-monsoon and post-monsoon seasons. The study has been designed to investigate biochemical and physiological activities of selected tree species as the campus is presently exposed to primary air pollutants and their impacts on plant community were observed through the changes in several physical and biochemical constituents of plant leaves. As the plant species continuously exchange different gaseous pollutants in and out of the foliar system and are very sensitive to gaseous pollutants, they serve as bioindicators. Due to air pollution, foliar surface undergoes different structural and functional changes. In the selected plant species, it was observed that the concentration of primary air pollutants, proline content, pH, relative water holding capacity, photosynthetic rate, and respiration rate were higher in the pre-monsoon than the post-monsoon season, whereas the total chlorophyll, ascorbic acid, sugar, and conductivity were higher in the post-monsoon season. From the entire study, it was observed that the concentration of sulfur oxide (SO x ), nitrogen oxide (NO x ), and suspended particulate matter (SPM) all are reduced in the post-monsoon season than the pre-monsoon season. In the pre-monsoon season, SO x , NO x , and SPM do not have any significant correlation with biochemical as well as physiological parameters. SPM shows a negative relationship with chlorophyll 'a' (r = -0.288), chlorophyll 'b' (r = -0.267), and total chlorophyll (r = -0.238). Similarly, chlorophyll a, chlorophyll b, and the total chlorophyll show negative relations with SO x and NO x (p < 0.005) during the post-monsoon season. Proline shows a positive relationship with SO x in the pre-monsoon season whereas in the post-monsoon season proline content shows a positive relationship with both SO x and NO x . The present study facilitates to screen eight sensitive and two moderately tolerant tree species according to their air pollution tolerance index (APTI) values.

Dental fluorosis and urinary fluoride concentration as a reflection of fluoride exposure and its impact on IQ level and BMI of children of Laxmisagar, Simlapal Block of Bankura District, W.B., India.

There has been growing public concern about intellectual performance of children at high levels of fluoride exposure. A cross-sectional study was conducted in Simlapal Block of Bankura District, West Bengal, to find out the relationship between fluoride (F) exposure as exposure dose (ED) with dental fluorosis (DF), urinary fluoride concentration (UF), intelligence quotient (IQ) and body mass index (BMI). Fifty groundwater samples were collected from the target area. One hundred forty-nine children belonging to age group 6 to 18 years were considered for this study. Experimental results reveal that mean F(-) concentration of that area is 2.11 mg/L (±SD 1.64). On the basis of F concentration in groundwater and water consumption pattern, ED was calculated to explore the impact of F(-) on DF, UF, IQ, and BMI. Paired t test results suggest that exposure rate of F does not show any significant differences (<0.05) among the children of 12 different places. As a result of F exposure, DF cases are mostly found in the order of moderate > severe > mild > very mild > questionable > normal conditions. The highest UF concentration was recorded as 17 mg/L, but the status of DF in the affected children was recorded as moderate. The results also reveal that ED has a positive correlation with DF (r = 0.299, P < 0.01) and UF (r = 0.513, P < 0.01) and a negative correlation with IQ (r = -0.343, P < 0.01) along with BMI (r = 0.083, non-significant). Therefore, from this study, it may be concluded that UF and DF concentration could act as a biomarker of fluoride toxicity.