Production of Bauxite Certified Reference Material (BARC-B1201) for Nine Property Values (Al2O3, Fe2O3, SiO2, TiO2, V2O5, MnO,Cr2O3, MgO and LOI) Traceable to SI Units

The National Centre for Compositional Characterisation of Materials (NCCCM) / Bhabha Atomic Research Centre (BARC) and National Aluminium Company Limited (NALCO), India have produced an Indian origin bauxite certified reference material (CRM), referred to as BARC-B1201, certified for major (Al₂O₃, Fe₂O₃, SiO₂, TiO₂, loss on ignition - LOI) and trace contents (V₂O₅, MnO, Cr₂O₃, MgO). Characterisation was undertaken by strict adherence to ISO Guides. A method previously developed and validated in our laboratory, using single step bauxite dissolution and subsequent quantitation (of Al₂O₃, Fe₂O₃, SiO₂, TiO₂, V₂O_5, MnO, Cr₂O₃ and MgO) by ICP-AES (SSBD ICP-AES) was used for homogeneity studies and an inter-laboratory comparison exercise (ILCE) of the candidate CRM. LOI was determined by thermo-gravimetric analysis. Property values were assigned after an ILCE with participation from seventeen reputed government and private sector laboratories in India. The CRM was certified for nine property values: Al₂O₃, Fe₂O₃, SiO₂, TiO₂, V₂O_5, MnO, Cr₂O₃, MgO and LOI, which are traceable to SI units.     

Influence of natural and anthropogenic activities on UV Index variations – a study over tropical urban region using ground based observations and satellite data

Measurements of total ozone column and solar UV radiation under different atmospheric conditions are needed to define variations of both UV and ozone and to study the impact of ozone depletion at the Earth’s surface. In this study, spectral and broadband measurements of UV-B irradiance were obtained along with total ozone observations and aerosol optical depth measurements in the tropical urban region of Hyderabad, south India. We specifically used an Ultra-Violet Multifilter Rotating Shadow band Radiometer (UVMFR-SR), to measure UV irradiance in time and space. To assess the aerosol and O₃ effects on ground-reaching UV irradiance, we used measurements from a Microtops II sun photometer in addition to the Tropospheric Ultraviolet Visible radiation (TUV) model. We also assessed the Defense Meteorological Satellite Program – Operational Line Scanner (DMSP-OLS) night time satellite data for inferring biomass burning fires during the study period. Results clearly suggested a negative correlation between the DMSP-OLS satellite derived fire count data and UVMFR-SR data suggesting that aerosols from biomass burning are directly attenuating UV irradiance in the study region. Also, correlation analysis between UV index and ozone measurements from sun photometer and TOMS-Ozone Mapping Instrument (OMI) indicated a clear decrease in ground reaching UV-B irradiance during higher ozone conditions. The higher levels are attributed to photochemical production of O₃ during the oxidation of trace gases emitted from biomass burning. Results also suggested a relatively high attenuation in UV irradiance (~6% higher) from smoke particles than dust. We also found a relatively good agreement between the modeled (TUV) and measured UV irradiance spectra for different atmospheric conditions. Our results highlight the factors affecting UV irradiance in a tropical urban environment, south India.     

Variations in CO,O<Subscript>3</Subscript> and black carbon aerosol mass concentrations associated with planetary boundary layer (PBL) over tropical urban environment in India

Carbon monoxide (CO), Ozone (O₃) and Black Carbon (BC) aerosol mass concentrations in relation to planetary boundary layer (PBL) height measurements were analyzed from January–December, 2008 over tropical urban environment of Hyderabad, India. DMSP-OLS night-time satellite data were analyzed for fire occurrence over the region and its correlation with pollution concentrations over the urban region. Results of the study suggested considerable increase in CO and BC concentrations during early morning hours. Higher concentration of BC, CO and ozone was observed during pre-monsoon, post-monsoon and winter and lowest concentrations exhibited during monsoon season. NCEP/NCAR reanalysis winds suggested long range transport of aerosols and trace gases from forest fires are enhancing the pollutant concentrations over the study area.     

Technical Challenges to In-situ Remediation of Polluted Sites

Throughout the world, subsurface contamination has become a widespread and pervasive problem. Toxic chemicals such as heavy metals and organic compounds are commonly used in a myriad of industries. However, largely through inadvertent or accidental release, these chemicals are presently polluting sites across the United States. In order to protect public health and the environment, further pollution must be prevented and sites with existing contamination urgently need remediation. Unfortunately, remediating subsurface contamination has proved to be a daunting task. Heavy metals and organic compounds often coexist and their distribution within the subsurface is highly dependent on particle and macro-scale heterogeneities. Vast resources have been invested to develop efficient remediation technologies, yet very few of these technologies have been successful. In-situ remediation is often preferred due to minimal site disturbance, safety, simplicity, and cost-effectiveness. The effectiveness of in-situ remediation technologies depends largely on the contaminant chemistry and subsurface heterogeneities (including particle-scale heterogeneities such as fine-grained soils, soils with reactive minerals, and/or soils rich in organic matter as well as macro-scale heterogeneities such as irregular soil layers and/or lenses). Under such heterogeneous conditions, integrated electrokinetic remediation technology has great potential. As a safe and economical remedial option for so many contaminated sites, the application of integrated electrokinetic remediation offers enormous public health, environmental, and financial benefits.     

Long-Term Variability of Nutrients and Chlorophyll in the Chesapeake Bay: A Retrospective Analysis, 1985–2008

A retrospective analysis of freshwater discharge, riverine dissolved nutrient loads, dissolved nutrients, and chlorophyll in the Chesapeake Bay from 1985 to 2008 is presented. It is evident that each field displays an interannual variability averaged over the Bay. The N and P loads peaked in 1997 and have fluctuated with a decreasing trend since early 2004. Dissolved nutrient concentrations in the Bay appear to be largely controlled by riverine nutrient loads. The temporal variability of chlorophyll is positively correlated with nutrient loads and concentrations. Over the study period, N:P (DIN:DIP) molar ratios were consistently higher than the Redfield ratio (N:P?=?16:1) and strongly correlated with river discharge (R ²?=?0.68, p??16:1), and N is the limiting nutrient in summer and early autumn (N:P?4 from anoxic sediments. Long-term climate indices, such as El Niño Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO), appear to exert only a moderate control over the riverine discharge to the Bay or over the ecosystem response in terms of chlorophyll in the Bay. While not all related mechanisms can be inferred from available data, this analysis should help in determining future data needs for monitoring water quality and human and climate influence on the health of the Bay.     

Simulation of heavy rainfall events over Indian monsoon region using WRF-3DVAR data assimilation system

We present the results of the impact of the 3D variational data assimilation (3DVAR) system within the Weather Research and Forecasting (WRF) model to simulate three heavy rainfall events (25–28 June 2005, 29–31 July 2004, and 7–9 August 2002) over the Indian monsoon region. For each event, two numerical experiments were performed. In the first experiment, namely the control simulation (CNTL), the low-resolution global analyses are used as the initial and boundary conditions of the model. In the second experiment (3DV-ANA), the model integration was carried out by inserting additional observations in the model’s initial conditions using the 3DVAR scheme. The 3DVAR used surface weather stations, buoy, ship, radiosonde/rawinsonde, and satellite (oceanic surface wind, cloud motion wind, and cloud top temperature) observations obtained from the India Meteorological Department (IMD). After the successful inclusion of additional observational data using the 3DVAR data assimilation technique, the resulting reanalysis was able to successfully reproduce the structure of convective organization as well as prominent synoptic features associated with the mid-tropospheric cyclones (MTC). The location and intensity of the MTC were better simulated in the 3DV-ANA as compared to the CNTL. The results demonstrate that the improved initial conditions of the mesoscale model using 3DVAR enhanced the location and amount of rainfall over the Indian monsoon region. Model verification and statistical skill were assessed with the help of available upper-air sounding data. The objective verification further highlighted the efficiency of the data assimilation system. The improvements in the 3DVAR run are uniformly better as compared to the CNTL run for all the three cases. The mesoscale 3DVAR data assimilation system is not operational in the weather forecasting centers in India and a significant finding in this study is that the assimilation of Indian conventional and non-conventional observation datasets into numerical weather forecast models can help improve the simulation accuracy of meso-convective activities over the Indian monsoon region. Results from the control experiments also highlight that weather and regional climate model simulations with coarse analysis have high uncertainty in simulating heavy rain events over the Indian monsoon region and assimilation approaches, such as the 3DVAR can help reduce this uncertainty.     

Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud

ABSTRACT

The South Asia (India, Pakistan, Bangladesh, Nepal, Sri Lanka and Bhutan) has a staggering 900 million people (~43% of the population) who face food insecurity or severe food insecurity as per United Nations, Food and Agriculture Organization’s (FAO) the Food Insecurity Experience Scale (FIES). The existing coarse-resolution (≥250-m) cropland maps lack precision in geo-location of individual farms and have low map accuracies. This also results in uncertainties in cropland areas calculated from such products. Thereby, the overarching goal of this study was to develop a high spatial resolution (30-m or better) baseline cropland extent product of South Asia for the year 2015 using Landsat satellite time-series big-data and machine learning algorithms (MLAs) on the Google Earth Engine (GEE) cloud computing platform. To eliminate the impact of clouds, 10 time-composited Landsat bands (blue, green, red, NIR, SWIR1, SWIR2, Thermal, EVI, NDVI, NDWI) were derived for each of the three time-periods over 12 months (monsoon: Days of the Year (DOY) 151–300; winter: DOY 301–365 plus 1–60; and summer: DOY 61–150), taking the every 8-day data from Landsat-8 and 7 for the years 2013–2015, for a total of 30-bands plus global digital elevation model (GDEM) derived slope band. This 31-band mega-file big data-cube was composed for each of the five agro-ecological zones (AEZ’s) of South Asia and formed a baseline data for image classification and analysis. Knowledge-base for the Random Forest (RF) MLAs were developed using spatially well spread-out reference training data (N = 2179) in five AEZs. The classification was performed on GEE for each of the five AEZs using well-established knowledge-base and RF MLAs on the cloud. Map accuracies were measured using independent validation data (N = 1185). The survey showed that the South Asia cropland product had a producer’s accuracy of 89.9% (errors of omissions of 10.1%), user’s accuracy of 95.3% (errors of commission of 4.7%) and an overall accuracy of 88.7%. The National and sub-national (districts) areas computed from this cropland extent product explained 80-96% variability when compared with the National statistics of the South Asian Countries. The full-resolution imagery can be viewed at full-resolution, by zooming-in to any location in South Asia or the world, at www.croplands.org and the cropland products of South Asia downloaded from The Land Processes Distributed Active Archive Center (LP DAAC) of National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS): https://lpdaac.usgs.gov/products/gfsad30saafgircev001/.     

Isotopic evolution of common lead

The isotopic composition of lead from galenas and feldspars of granitic rocks covering a time span of 3600 m.y. is reviewed. Hew data are combined with data from the literature, all ratios being normalized to a fixed value for the isotopic composition of lead in an inter-laboratory reference sample. Comparison of feldspar and galena results show that the isotopic composition of initial lead in granitic rocks may be identical to, or more radiogenic than, that in coeval stratiform (or ‘single stage’) ore deposits. The isotopic evolution of terrestrial lead over the past 3600 m.y. deduced from the stratiform ore data does not fit the closed system source. The data are best fitted to evolution models in which the value of μ (U²³⁸/Pb²⁰⁴ normalized to the present day) in the source has increased either over approximately the past 3.6 billion years or since the time of formation of the Earth. A limited number of high precision data for strontium likewise indicate open system isotopic evolution. In this system the Rb/Sr ratio appears to have decreased as a function of time. Physical models that explain the data are presented. Either mantle differentiation or crustal contamination processes could account for the change in μ in the source for the lead. The strontium data and some detailed studies of the isotopic composition of lead in oceanic volcanic rocks support mantle differentiation rather than crustal contamination. The exact nature of the mantle differentiation process cannot be specified, although empirical data favoring the existence of such a process are given. The best estimate of the age of the Earth, calculated with the data from 2750 and 3290 m.y.-old lead ores, is 4660 m.y.     

The lateritic iron ores,itabiritic quartzites and epidiorites of the Kemmangundi area,Bababudan hills,Mysore state,India

Epidiorites forming the basement and occurring also as bands in ferruginous quartzites in Kemmangundi in the Bababudan Hills of Mysore State are described in regard to their structure, mineralogy, petrography, and the petrochemistry of the epidiorites and their role in the formation of the two types of iron ores in the area. The ferruginous quartzites, itabiritic iron ores, and epidiorites strike NW-SE and were simultaneously structurally deformed. They may be considered as eugeosynclinal formations. The data collected do not suggest any genetic relation between the itabiritic ores and the epidiorites. The lateritic iron ores on the other hand, were formed by the alteration of the ferruginous quartzites (itabiritic ores).

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Zusammenfassung Itabiritische Quarzite und Epidiorite aus Kemmangundi in den Bababudan-Hügeln des Staates Mysore wurden hinsichtlich ihrer Struktur, ihres Mineralbestandes und ihrer chemischen Zusammensetzung untersucht. Insbesondere wird der Zusammenhang mit den beiden Typen von Eisenlagerstätten in der Gegend beleuchtet: Die itabiritischen Quarzite haben sich nicht aus den Epidioriten gebildet; dagegen sind die lateritischen Eisenerze als Verwitterungsprodukte der Eisenquarzite zu betrachten.