Cancer risk estimation from dietary arsenic,a new approach from longitudinal cohort study

Inorganic arsenic is a carcinogen and consumption in low dose may lead to cancer. We estimated the cancer risk of the participants from arsenic endemic regions of West Bengal, India. The probable cancer risk was estimated following the assessment of daily inorganic arsenic intake through drinking water and diets of 20 participants for three consecutive years who had been using low arsenic water in the Indian context (median arsenic concentration in the study Years-I, II and III were 22, 16, 13 µg/l respectively). Probable cancer risk of the population was 2.80 × 10^?4, 2.94 × 10^?4, 3.12 × 10^?4 in the three respective study years (Year-I, II and III); just higher than the US EPA risk level of concern. The arsenic species content of the paired raw, cooked rice and urine was estimated in the as is taken basis. The major diet component, rice contained 72–86% inorganic arsenic whereas urine contains 70% organic arsenic on an average. The cancer risk assessment has been proposed to be modified by inclusion of urine arsenic release, considering the fact of arsenic release through urine. The risk became 1.28 × 10^?5, 1.13 × 10^?5, 1.01 × 10^?5 in the study Year-I, II and III respectively, considering urinary arsenic release, attributed the consideration of urine arsenic release into probable cancer risk estimation.     

Estimation of Biomass Heat Storage Using Thermal Infrared Imagery: Application to a Walnut Orchard

A new method to estimate tree biomass heat storage from thermal infrared (TIR) imaging of biomass surface temperature is presented. TIR images of the canopy are classified into trunk, branches, and leaves. The one-dimensional heat equation in cylindrical coordinates is forced with trunk and branch surface temperatures to simulate the temperature distribution and heat storage in tree trunks and branches. Assuming uniform leaf temperatures, heat storage in leaves is computed from the surface temperature of the leaves separately for the sunlit upper and shaded lower canopy. The sum of trunk, branches, leaf, and air heat storage gives the canopy heat storage. Measurements in a walnut orchard near Davis, California, in early June 2007 showed that biomass heat storage was of the same order as air heat storage and about 1% of daytime and 9% of nighttime net radiation.     

Adaptive neuro-fuzzy inference system to forecast peak gust speed during thunderstorms

The aim of the present study is to develop an adaptive neuro-fuzzy inference system (ANFIS) to forecast the peak gust speed associated with thunderstorms during the pre-monsoon season (April?CMay) over Kolkata (22°32??N, 88°20??E), India. The pre-monsoon thunderstorms during 1997?C2008 are considered in this study to train the model. The input parameters are selected from various stability indices using statistical skill score analysis. The most useful and relevant stability indices are taken to form the input matrix of the model. The forecast through the hybrid ANFIS model is compared with non-hybrid radial basis function network (RBFN), multi layer perceptron (MLP) and multiple linear regression (MLR) models. The forecast error analyses of the models in the test cases reveal that ANFIS provides the best forecast of the peak gust speed with 3.52% error, whereas the errors with RBFN, MLP, and MLR models are 10.48, 11.57, and 12.51%, respectively. During the validation with the 2009 observations of the India Meteorological Department (IMD), the ANFIS model confirms its superiority over other comparative models. The forecast error during the validation of the ANFIS model is observed to be 3.69%, with a lead time of <12?h, whereas the errors with RBFN, MLP, and MLR are 12.25, 13.19, and 14.86%, respectively. The ANFIS model may, therefore, be used as an operational model for forecasting the peak gust speed associated with thunderstorms over Kolkata during the pre-monsoon season.     

Potential CO<Subscript>2</Subscript> Emission Due to Loss of Above Ground Biomass from the Indian Sundarban Mangroves During the Last Four Decades

Sundarban, the largest single patch of mangrove forest of the world is shared by Bangladesh (~ 60 %) and India (~ 40 %). Loss of mangrove biomass and subsequent potential emission of carbon dioxide is reported from different parts of the world. We estimated the loss of above ground mangrove biomass and subsequent potential emission of carbon dioxide in the Indian part of the Sundarban during the last four decades. The loss of mangrove area has been estimated with the help of remotely sensed data and potential emission of carbon dioxide has been evaluated with the help of published above ground biomass data of Indian Sundarban. Total loss of mangrove area was found to be 107 km² between the year 1975 and 2013. Amongst the total loss ~60 % was washed away in the water by erosion, ~ 23 % was converted into barren lands and the rest were anthropogenically transformed into other landforms. The potential carbon dioxide emission due to the degradation of above ground biomass was estimated to be 1567.98 ± 551.69 Gg during this period, which may account to 64.29 million $ in terms of the social cost of carbon. About three-forth of the total mangrove loss was found in the peripheral islands which are much more prone to erosion. Climate induced changes and anthropogenic land use change could be the major driving force behind this loss of ‘blue carbon’.     

Predictability of landfall location and surge height of tropical cyclones over North Indian Ocean (NIO)

Natural Hazards - Forecasting, with precision, the location of landfall and the height of surge of cyclonic storms prevailing over any ocean basin is very important to cope with the associated...     

Comparison of tropical and midlatitude thunderstorm characteristics anchored in thermodynamic and dynamic aspects

Thunderstorms prevailing over tropics and midlatitudes depict dissimilar features relating to the thermodynamic and dynamic aspects. The identification of the physical characteristics of the tropical and midlatitude thunderstorms is the main objective of the present study. The stations Kolkata (22.6°N, 88.4°E) and Denver (39.47°N, 104.32°W) are selected from the tropics and midlatitudes for the comparative analyses. The study reveals that the average storm relative helicity (SRH) and the lapse rate between 700 and 500 hPa level is much higher over Denver compared to Kolkata during thunderstorm days. The study further reveals that the surface to mid troposphere (upto 500 hPa) become drier (～2 times) over Denver than Kolkata prior to the occurrence of thunderstorms while the upper tropospheric (300–100 hPa) humidity remains comparable for both the locations.     

Uncertainty of soil erosion modelling using open source high resolution and aggregated DEMs

Digital Elevation Model (DEM) is one of the important parameters for soil erosion assessment. Notable uncertainties are observed in this study while using three high resolution open source DEMs. The Revised Universal Soil Loss Equation (RUSLE) model has been applied to analysis the assessment of soil erosion uncertainty using open source DEMs (SRTM, ASTER and CARTOSAT) and their increasing grid space (pixel size) from the actual. The study area is a part of the Narmada river basin in Madhya Pradesh state, which is located in the central part of India and the area covered 20,558 km². The actual resolution of DEMs is 30 m and their increasing grid spaces are taken as 90, 150, 210, 270 and 330 m for this study. Vertical accuracy of DEMs has been assessed using actual heights of the sample points that have been taken considering planimetric survey based map (toposheet). Elevations of DEMs are converted to the same vertical datum from WGS 84 to MSL (Mean Sea Level), before the accuracy assessment and modelling. Results indicate that the accuracy of the SRTM DEM with the RMSE of 13.31, 14.51, and 18.19 m in 30, 150 and 330 m resolution respectively, is better than the ASTER and the CARTOSAT DEMs. When the grid space of the DEMs increases, the accuracy of the elevation and calculated soil erosion decreases. This study presents a potential uncertainty introduced by open source high resolution DEMs in the accuracy of the soil erosion assessment models. The research provides an analysis of errors in selecting DEMs using the original and increased grid space for soil erosion modelling.     

Assessment of fire danger vulnerability using McArthur’s forest and grass fire danger indices

We present a field survey and a number of simulations of the local Persian Gulf tsunami of 19 March 2017 at Bandar Dayyer, Iran, which resulted in one death, five persons missing and significant damage to the port. The field survey defined the inundated area as extending \(\sim\, 40\) km along the coast, with major effects concentrated on an \(\sim\, 8\) km stretch immediately west of Dayyer, a maximum run-up of 3 m and maximum inundation reaching 600 m. In the absence of significant earthquakes on that day, we first test the possibility of generation of a landslide; however, our simulations for legitimate sources fail to reproduce the distribution of run-up along the coast. We prefer the model of a meteorological tsunami, triggered by Proudman resonance with a hypothetical weather front moving at 10 m/s in a NNW azimuth, which could be an ancillary phenomenon to a major shamal wind system present over the Persian Gulf on that day. More detailed simulations of the Dayyer tsunami would require an improved bathymetric grid in the vicinity of the relevant coastal segment.     

Geochemistry of Harappan potteries from Kalibangan and sediments in the Ghaggar River: Clues for a dying river

The ephemeral Ghaggar-Hakra River of northwestern India has always been considered to be the remnant of an ancient perennial glacier-fed river(Vedic Saraswati). The exact reason and timing of major hydrological change of this river remains speculative. The river's purported association with the zenith of the Harappan civilisation remains a conjecture because the timings of its fluvial past are still being debated. In this study we have made an attempt to resolve this issue using geochemical provenance of sediments from some dated horizons in the Ghaggar flood plain and that of the material used in the potteries from the Mature Harappan period(4600-3900 yr BP) at Kalibangan. Sampled sedimentary horizons were dated by radiocarbon and optically stimulated luminescence(OSL) methods. Results of our study from the Ghaggar alluvium indicate that the river did have glacial sources during the early Holocene. However, the data from the potteries suggest that during the Mature Harappan period, the sediments in the Ghaggar as used by the potters did not have a higher Himalayan provenance and hence, were not derived from glaciated Himalayas.These findings imply that during the time of the Mature Harappans the Ghaggar had already become a foothill-fed river.