SUNIL KUMAR SRIVASTAVA
@juet.ac.in
Assistant Professor , Department of Chemistry
Jaypee University of Engineering & Technology
Working in the area of Climate Change through GIS Remote Sensing and looking for an efficient source of Energy.
EDUCATION
Ph.D. (Jawaharlal Nehru University JNU)
RESEARCH INTERESTS
Water Resource, Energy and Environment
FUTURE PROJECTS
Carbon Footprint and Energy
Applications Invited
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Sunil Kumar Srivastava
Springer Science and Business Media LLC
Deependra Kumar Ban, Tyler Bodily, Abhijith G. Karkisaval, Yongliang Dong, Shreyam Natani, Anirudh Ramanathan, Armando Ramil, Sunil Srivastava, Prab Bandaru, Gennadi Glinsky,et al.
Proceedings of the National Academy of Sciences
We have developed a DNA aptamer-conjugated graphene field-effect transistor (GFET) biosensor platform to detect receptor-binding domain (RBD), nucleocapsid (N), and spike (S) proteins, as well as viral particles of original Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) coronavirus and its variants in saliva samples. The GFET biosensor is a label-free, rapid (≤20 min), ultrasensitive handheld wireless readout device. The limit of detection (LoD) and the limit of quantitation (LoQ) of the sensor are 1.28 and 3.89 plaque-forming units (PFU)/mL for S protein and 1.45 and 4.39 PFU/mL for N protein, respectively. Cognate spike proteins of major variants of concern (N501Y, D614G, Y453F, Omicron-B1.1.529) showed sensor response ≥40 mV from the control (aptamer alone) for fM to nM concentration range. The sensor response was significantly lower for viral particles and cognate proteins of Middle East Respiratory Syndrome (MERS) compared to SARS-CoV-2, indicating the specificity of the diagnostic platform for SARS-CoV-2 vs. MERS viral proteins. During the early phase of the pandemic, the GFET sensor response agreed with RT-PCR data for oral human samples, as determined by the negative percent agreement (NPA) and positive percent agreement (PPA). During the recent Delta/Omicron wave, the GFET sensor also reliably distinguished positive and negative clinical saliva samples. Although the sensitivity is lower during the later pandemic phase, the GFET-defined positivity rate is in statistically close alignment with the epidemiological population-scale data. Thus, the aptamer-based GFET biosensor has a high level of precision in clinically and epidemiologically significant SARS-CoV-2 variant detection. This universal pathogen-sensing platform is amenable for a broad range of public health applications and real-time environmental monitoring.
Sunil Kumar Srivastava
Springer Science and Business Media LLC
Vijay Kumar Garlapati, Surendra Kumar Parashar, Sergey Klykov, Pandu Ranga Vundavilli, Surajbhan Sevda, Sunil Kumar Srivastava, and Mohammad J. Taherzadeh
Elsevier BV
Waste to the product approach was proposed for tuning environ-threat soybean husk towards lipolytic enzyme by integrating the invasive weed optimization with biomass and product dynamics study. The invasive weed optimization constitutes based on the non-linear regression model results in a 47 % enhancement in lipolytic enzyme using the optimization parameters of 7% Sigma Final, 9% exponent; Smax of 5 with a population size of 35 and Max. generations of 99. The biomass dynamic study showcases the dynamic parameters of 0.0239 µmax, 8.17 XLimst and 0.852 RFin values. The product dynamic studies reveal the kinetic parameters of kst, kdiv, PFin, which seem to be equal to -0.0338, 0.0896 and 68.1, respectively. Overall, the present study put forth the zero-waste (soybean husk) to the product (lipolytic enzyme) approach by introducing the novel "Invasive Weed Optimization" coupled with "Biomass and product dynamics" to the bioprocessing field.
Sunil Kumar Srivastava
Springer International Publishing
Sunil Kumar Srivastava
Springer Science and Business Media LLC
The crisis of fossil fuel and their negative impact on the environment has caused concern among the scientific communities leading them to look around for renewable sources of energy. This review has emphasized the efficient utilization of organic municipal solid waste as well as agriculture waste in an anaerobic digester for the production of biogas as a sustainable renewable energy. Recent advances in biogas production along with previous research work have been discussed to offer a comprehensive synopsis of the accumulated knowledge. This review also elucidates about the design of an anaerobic digester, the prospect of anaerobic digestion and opportunity in new advances in technology. Biogas is one of the most accepted sustainable renewable energy. The characterization, elimination of contaminants, pretreatment, anaerobic digestion in optimum condition and utilization of energy crops enhanced the efficiency of an anaerobic digester. Pretreatment of segregated organic solid waste increased its putrescibility and further biogas production. The optimized parameters in this review were pH, temperature, loading rate, C/N ratio and solid/liquid ratio of the feedstock. The flow rate of the feedstock was optimized according to the available volume of the digester, residence time and the characteristics of the feedstock. The design of an anaerobic digester should be preferably cylindrical in shape, with a diameter ranging from 6 to 40 m, the depth ranging from 7.5 to 15 m and the conical floor having a slope around 15%. A comprehensive reform in technical, economic, and social policies is essential to accomplish a sustainable energy system considering biogas as a future renewable energy. The flowsheet of the biogas and methanol production has been given in Fig. 1 . Fig. 1 Flowsheet of the biogas and methanol production
Mohd. Farooq Azam, P. Wagnon, C. Vincent, AL. Ramanathan, N. Kumar, S. Srivastava, J.G. Pottakkal, and P. Chevallier
Elsevier BV
Abstract Glacier-wide mass balances and runoffs are reconstructed over 1969–2016 for Chhota Shigri Glacier catchment (India) applying a glacio-hydrological model. The model is forced using in-situ daily air-temperature and precipitation records from the meteorological stations at Bhuntar Observatory (1092 m a.s.l.), glacier base camp (3850 m a.s.l.) and glacier side moraine (4863 m a.s.l.). The modelled mean annual mass balance is −0.30 ± 0.36 m w.e.a−1 (meter water equivalent per year), while the mean catchment-wide runoff is 1.56 ± 0.23 m w.e.a−1 over 1969–2016. Three periods are distinguished in the reconstructed mass balance and runoff series. Periods I (1969–1985) and III (2001–2016) show glacier mass wastage at rates of −0.36 and −0.50 m w.e.a−1, respectively, corresponding to catchment-wide runoffs of 1.51 and 1.65 m w.e.a−1, respectively. Conversely, period II (1986–2000) exhibits steady-state conditions with average mass balances of −0.01 m w.e.a−1, and corresponding runoff of 1.52 m w.e.a−1. The reduced ice melt (0.20 m w.e.a−1) over period II, in agreement with steady-state conditions, is compensated by the increased snow melt (1.03 m w.e.a−1), providing almost similar catchment-wide runoffs for period I and II. The increased runoff after 2000 is mainly governed by increased ice melt (0.32 m w.e.a−1) over period III. Snow accumulation in winter and summer seasons together control the glacier-wide mass balances as well as catchment-wide runoffs. Snow melt contributes the maximum to the total mean annual runoff with 63% share while glacier melt and rain contribute 17% and 20% respectively over the whole period.
Sunil Kumar Srivastava
Elsevier BV
Abstract This study was performed to understand the impact of groundwater quality on the crop yields and its suitability for the irrigation. The hydrogeochemical assessment indicates chemical weathering is prevalent in the aquifer system. Low sodium-hazard observed in almost all samples. High salinity-hazard observed in the shallow aquifer indicates leaching of contaminants from the surface. Salinity-hazard statistics indicates ∼27.60% groundwater suitable for irrigation, ∼47.65% groundwater considerable for irrigation of selected crops whose salinity tolerance limit is high, ∼13.44% groundwater (fresh-brackish) cause problem in the soil and ∼11.31% groundwater unsuitable for the irrigation. Salinity tolerance limit indicates yield (%) of the few crops remain unaffected. These crops are Hordeum vulgare (Barley), Gossy pium (Cotton), Beta vulgaris (Sugar-beet), Cynodon dactylon (Bermuda-grass), Thinopyrum ponticum (tall Wheat-grass), Thinopyrum intermedium (Wheat-grass) etc. The yield potential (%) partially affected in the few crops like Arachis hypogaea (Groundnut) (∼95.30%), Oryza sativa (Rice) (∼93.29%), Carthamus tintorius (Safflower) (∼97.32%), Sorghum bicolor (Sorghum) (∼95.97%), Glycine max (Soybean) (∼97.32%), Triticum aestivum (Wheat) (∼99.33%), Brassica oleracea var. italica (Broccoli) (∼92.62%), Cucumis sativus (Cucumber) (∼90.60%), Solanum lycopersicum (Tomato) (∼90.60%), Phalaris aquatic (Harding-grass) (∼97.96%), Lolium perenne (Perennial ray-grass) (∼97.99%), Sorghum drummondii (Sudan-grass) (∼92.62%), Festuca arundinacea (tall-Fescue) (∼95.30%), Lotus corniculatus (Trefoil-small) (∼97.32%), Phoenix dactylifera (Date-palm) (∼95.97%), Ficus carica (Fig) (∼95.97%), Olea europaea (Olive) (∼95.97%), Punica granatum (Pomegranate) (∼91.28%) etc. Few crops sensitive to salinity-hazard indicate low-yield potential listed as Phaseolus vulgaris (Bean) (∼36.91%), Daucus carota (Carrot) (∼36.91%), Fragaria ananassa (Strawberry) (∼36.91%). This groundwater is suitable for the irrigation of crops like Barley, Cotton, Sugar-beet, Wheat, Wheat-grass, Bermuda-grass, etc. But this groundwater can be used for irrigation after salinity management for the crops like Groundnut, Rice, Soybean, Broccoli, Cucumber, Tomato, Harding-grass, tall Fescue, Trefoil-small, Date-palm, Fig, Olive, and Pomegranate. The similar range of the crop yields observed in both Soil Water Salinity (SWS) Model and Ayers and Westcot Model, if the salinity of the irrigation water is low (≤1.5 mS/cm). While low reduction in crop yields observed according to SWS Model in comparisons to Ayers and Westcot Model if the salinity of the irrigation water is high (>1.5 mS/cm). The major reduction in crop yields observed in Ayers and Westcot Model, while the moderate decline in crop yields observed in SWS Model at higher salinity. Crop yield in the study area can be improved by implementing proper irrigation water management.
Sunil Kumar Srivastava and A L Ramanathan
Springer Science and Business Media LLC
This systematic study was carried out with objective to delineate the various sources responsible for $$\\hbox {NO}_{3}^{-}$$NO3- contamination and $$\\hbox {F}^{-}$$F- enrichment by utilizing statistical and graphical methods. Since Central Ground Water Board, India, indicated susceptibility of $$\\hbox {NO}_{3}^{-}$$NO3- contamination and $$\\hbox {F}^{-}$$F- enrichment, in most of the groundwater, $$\\hbox {NO}_{3}^{-}$$NO3- and $$\\hbox {F}^{-}$$F- concentration primarily observed $${>}45$$>45 and $${>}1.5~\\hbox {mg/L}$$>1.5mg/L, respectively, i.e., higher than the permissible limit for drinking water. Water Quality Index (WQI) indicates $${\\sim }22.81\\%$$∼22.81% groundwater are good-water, $${\\sim }71.14\\%$$∼71.14% groundwater poor-water, $${\\sim }5.37\\%$$∼5.37% very poor-water and 0.67% unsuitable for drinking purpose. Piper diagram indicates $${\\sim }59.73\\%$$∼59.73% groundwater hydrogeochemical facies are Ca–Mg–$$\\hbox {HCO}_{3 }$$HCO3 water-types, $${\\sim }28.19\\%$$∼28.19% Ca–Mg–$$\\hbox {SO}_{4}$$SO4–Cl water-types, $${\\sim }8.72\\%$$∼8.72% Na–K–$$\\hbox {SO}_{4}$$SO4–Cl water-types and 3.36% Na–K–$$\\hbox {HCO}_{3 }$$HCO3 water-types. This classification indicates dissolution and mixing are mainly controlling groundwater chemistry. Salinity diagram indicate $${\\sim }44.30\\%$$∼44.30% groundwater under in low sodium and medium salinity hazard, $${\\sim }49.66\\%$$∼49.66% groundwater fall under low sodium and high salinity hazard, $${\\sim }3.36\\%$$∼3.36% groundwater fall under very-high salinity hazard. Sodium adsorption ratio indicates $${\\sim }97\\%$$∼97% groundwater are in excellent condition for irrigation. The spatial distribution of $$\\hbox {NO}_{3}^{-}$$NO3- indicates significant contribution of fertilizer from agriculture lands. Fluoride enrichment occurs in groundwater through the dissolution of fluoride-rich minerals. By reducing the consumption of fertilizer and stress over groundwater, the water quality can be improved.
Sunil Kumar Srivastava and AL Ramanathan
Springer Science and Business Media LLC
This investigation was carried out with the objective to understand the impacts of landfill leachate on groundwater quality. This study also explained the movement of trace metals in groundwater by using Visual MODFLOW/MT3D. It also delineates the various factors controlling the suitability of groundwater for domestic, agriculture and drinking purpose. The statistical assessment shows ~ 60.09% groundwater are in good condition, ~ 35.38% in poor condition and 4.53% in very poor condition. The spatial distributions of water quality index (LWQI) around landfills indicate landfills are in depleted condition. Hydrogeochemical classification indicates ~ 90.91% groundwater shows Ca–Na water-type cation facies and Cl− water-type anion facies. While 9.09% groundwater shows Ca–Na water-type cation facies and Cl−–SO42−–HCO3− anion hydrogeochemical facies. The mineral equilibrium diagram of groundwater has revealed that it is in equilibrium with silicate minerals and favors kaolinite formation. The saturation index indicates chrysotile (Mg3Si2O5(OH)4) (2.84), dolomite (CaMg(CO3)2) (0.45), ferric hydroxide (Fe(OH)3) (1.97–3.58), goethite (FeOOH) (7.86–9.47), hematite (Fe2O3) (17.73–20.95), hydroxyapatite (Ca5(PO4)3OH) (2.38–4.62), jarosite-K (KFe3(SO4)2(OH)6) (0.22–1.92), cerussite (PbCO3) (0.39), vivianite (Fe3(PO4)2·8H2O) (0.39) and willemite (Zn2SiO4) (0.35) are reactive mineral in groundwater aquifer of study area. The seasonal and temporal variation indicates anthropogenic influence. The calibration and validation of model show > 90% models correct with 95% confidence. The contaminant transport simulated in groundwater aquifer with the high accuracy (estimated standard error 0.049 m) for the large area (~ 300 km2). The trends of contour lines of trace metals concentration indicate; it will contaminate study area within few years of its release through the landfill.
Surendra Kumar Parashar, Sunil Kumar Srivastava, N. N. Dutta, and Vijay Kumar Garlapati
Wiley
Cross‐linked enzyme crystal (CLEC) and sol‐gel entrapped pseudomonas sp. lipase were investigated for the esterification of lauric acid with ethanol by considering the effects of reaction conditions on reaction rate. The activation energy for the reaction was estimated to be 1097.58 J/mol and 181.75 J/mol for sol‐gel and CLEC entrapped lipase respectively. CLEC lipase exhibited a marginal internal diffusion effect on reaction rate over sol‐gel lipases and found to be interesting. The overall reaction mechanism was found to conform to the Ping Pong Bi Bi mechanism. The higher efficiency of sol‐gel lipases over CLEC lipases in esterification reaction is mainly due to the combined effects of crowding, confinement and diffusional limitations.
Ravi Ranjan, Sunil Kumar Srivastava, and A. L. Ramanathan
Springer Science and Business Media LLC
A total of 30 water samples and 8 sediment samples were collected and chemically analysed for major ions (Na+, K+, Mg2+, Ca2+, HCO3−, SO42−, Cl−, NO3−, silica, PO43−, F−), trace elements (Fe, Mn, Ni, Cd, Zn, Pb, Cu), minerals and nutrients to determine the factors that control the chemistry of water in the Kawar-Tal and Kusheshwar-Asthan wetlands in the Bihar State of India. These analyses indicate that Ca2+ and HCO3− ions are the most dominant ions in both of the wetlands. It also indicates rock weathering is a major source of ions in these wetlands, particularly the dissolution of carbonate minerals. The hydrogeochemistry of water in Kusheshwar-Asthan is favouring kaolinite formation and in Kawar-Tal favouring kaolinite–gibbsite formation. Quartz (~36%), clay minerals (~21%) and chlorite (~10%) are the dominant minerals in both the wetlands. Orthoclase (~12.49%), calcite (~7.51%) and illite (4.89%) minerals are only available in Kawar-Tal surface sediment, while albite (6.29%) and biotite (~13.6%) minerals are only available in Kusheshwar-Asthan. Total carbon (~3%), inorganic carbon (0.9%), organic carbon (~2.1%), total sulphur (~0.0008%), nitrogen (~0.55%) and phosphate (~0.96%) are available in Kawar-Tal surface sediments, while total carbon (~2.38%), inorganic carbon (0.55%), organic carbon (~1.84%), total sulphur (~0.001%), nitrogen (~0.62%) and phosphate (~0.64%) are available in Kusheshwar-Asthan surface sediments. The study indicates wetlands are rich in nutrient for biological activities and are sufficient to support the biodiversity, but few locations are influenced by anthropogenic activities which cause the increase of sulphur, chloride, iron and lead.
Sunil Kumar Srivastava and A. L. Ramanathan
Springer Science and Business Media LLC
A geochemical assessment of groundwater quality and possible contamination in the vicinity of the Bhalswa landfill site was carried out by using a hydrochemical approach with graphical and multivariate statistical methods with the objective of identifying the occurrence of various geochemical processes and understanding the impact of landfill leachates on groundwater quality. Results indicate that nitrate, fluoride and heavy-metal pollution are in an alarming state with respect to the use of groundwater for drinking purposes. Various graphical plots and statistical analyses have been applied to the chemical data based on the ionic constituents, water types, and hydrochemical facies to infer the impact of the landfill on groundwater quality. The statistical analysis and spatial and temporal variations indicate the leaching of contaminants from the landfill to the groundwater aquifer system. The concentrations of heavy metals in the landfill leachates are as follows: Fe (22 mg/l), Mn (~20 mg/l), Cu (~10 mg/l), Pb (~2 mg/l), Ni (0.25 mg/l), Zn (~10 mg/l), Cd (~0.2 mg/l), Cl− (~4,000 mg/l), SO42− (~3,320 mg/l), PO43− (~4 mg/l), NO3− (30 mg/l) and fluoride (~50 mg/l); all were much higher than the standards. The study reveals that the landfill is in a depleted phase and is affecting groundwater quality in its vicinity and the surrounding area due to leaching of contaminants.
M. Bala Krishna Prasad, A. L. Ramanathan, Sunil Kr. Shrivastav, Anshumali, and Rajinder Saxena
Springer Science and Business Media LLC
The Fractionation of Fe, Zn, Cu, Pb, Mn and Cd in the sediments of the Achankovil River, Western Ghats, India using a sequential extraction method was carried out to understand the metal availability in the basin for biotic and abiotic activities. Spatial distribution of heavy metals has been studied. Sediment grain size has significant control over the heavy metal distribution. The fluctuations in their concentration partly depend upon the lithology of the river basin and partly the anthropogenic activities. The sediments are dominated by sand and are moderately to strongly positively skewed and are very leptokurtotic in nature. The quartzite and feldspars are abundant minerals along with significant amount of mica with low clay content. The core sediments show increasing trend of heavy metal concentration with depth due to the recent addition of anthropogenic sources and post-diagenic activities. Significant amount of Cd (18%) was found in carbonate fraction, which may pose environmental problems due to its toxic nature. Small concentrations of metals, except Cd and Cu, are in exchangeable fraction, which indicate low bio-availability. Enrichment Factor (EF) for individual metals shows the contribution from terrregious and in part from anthropogenic sources. Selective Sequential Extraction (SSE) study shows the variation in specific metal distribution pattern, their distribution in different phases and their bio-availability. Maximum amount of the metals were bound to the non-residual fractions (mainly Fe-oxides). Overall, bio-availability of these micronutrients from sediments seems to be very less. Non-residual phase is the most important phase for majority of heavy metals studied. Among the non-residual fraction, maximum amount of the heavy metals bound to Fe-oxides. The study high lights the need for in-depth study of heavy metals distribution and fractionation in the smaller river basins to get precise information on the behavior and transport of heavy metals in the fluvial environment and their contribution to the world ocean.