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.     

Geochemistry of ochreous precipitates from coal mine drainage in India

The deposition of ochreous is common by a consequence of acid mine drainage (AMD). The ochreous precipitated from the AMD sites around Tertiary coalfield of Assam, India were collected and characterized by X-ray diffractometry (XRD), Fe to S molar ratio, ammonium oxalate acid (pH 3.0) extraction, fourier-transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FESEM), scanning electron microscope (SEM) and transmission electron microscope (TEM). The ochreous mainly consists of goethite, schwertmannite, ferrihydrite and jarosite. Mineralogy of ochreous was controlled by the pH whereas formation of ferrihydrite was favored at high organic carbon content. Role of bacteria for the formation of secondary minerals was observed. Mobility of metals was controlled by the ochreous, and they were also retained during the process of phase transformation of poorly ordered iron-oxyhydroxysulfates into the stable forms.     

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.

     

Environmental aspects in Dalli-Rajhara iron ore mine area,M.P. using digital image processing techniques

Landsat MSS (1982) and IRS LISS-II (1989) data have been used to study the land use/land cover changes in Dalli-Rajhara iron ore mine area. Supervised classification has been performed on the temporal data to generate land use/land cover maps. Land use/land cover categories generated from IRS LISS-II data of 36 m resolution has been resampled to 80 m and areal statistics have been computed for 2, 4, 8 and 10 km wide strips around Dalli-Rajhara iron ore mine. The environmental impact due to on-going mining activities in the area has been analysed. The results of this study indicate that due to increase in mine-related and agricultural activities, forests have been degraded and also forest areas have been reduced considerably.     

Quantitative precipitation forecasting over Narmada Catchment

Quantitative precipitation forecasting (QPF) has been attempted over the Narmada Catchment following a statistical approach. The catchment has been divided into five sub-regions for the development of QPF models with a maximum lead-time of 24 hours. For this purpose the data of daily rainfall from 56 raingauge stations, twice daily observations on different surface meteorological parameters from 28 meteorological observatories and upper air data from 11 aerological stations for the nine monsoon seasons of 1972–1980 have been utilized. The horizontal divergence, relative vorticity, vertical velocity and moisture divergence are computed using the kinematic method at different pressure levels and used as independent variables along with the rainfall and surface meteorological parameters. Multiple linear regression equations have been developed using the stepwise procedure separately with actual and square root and log-transformed rainfall using 8-year data (1972–1979). When these equations were verified with an independent data for the monsoon season of 1980, it was found that the transformed rainfall equations fared much better compared to the actual rainfall equations. The performance of the forecasts of QPF model compared to the climatological and persistence forecasts has been assessed by computing the verification scores using the forecasts for the monsoon season of 1980.