A study on the waste metal remediation using floriculture at East Calcutta Wetlands, a Ramsar site in India

Use of specific plant species in remediation of heavy metal-contaminated soil and water was a promising eco-friendly technology. The present study indicated the possibilities of phytoremediation of metal-contaminated (namely Ca, Cr, Mn, Fe, Cu, Zn, and Pb) soil by using plant species important for floriculture of East Calcutta Wetlands, a Ramsar site at the eastern fringe of Calcutta city. Plant species like sunflower (Helianthus annuus), marigold (Tagetes patula), and cock's comb (Celocia cristata) grew on soil contaminated by industrial sludge and irrigated regularly with wastewater accumulated different metals in different plant parts in varied concentrations. Pot culture study in the laboratory setup was also done to ascertain the efficiency of these plants for ameliorating contaminated soil. It was found that general accumulation patterns of metals concerned in different plant parts were root > leaf > stem > flower. This work indicated the importance of cultivation of economically important, non-edible, ornamental plant species as an alternative cost-effective practice to remediate heavily contaminated farmlands of East Calcutta Wetlands.     

Cleaning the river Damodar (India): impact of COVID-19 lockdown on water quality and future rejuvenation strategies

Globally, it is established that the partial lockdown system assists to improve the health of the total environment due to inadequate anthropogenic actions in different economic sectors. The ample research on fitness of environment has been proved that the strict imposition of lockdown was the blessings of environment. The river Damodar has historical significance and lifeline for huge population of Jharkhand and West Bengal state of India but in the recent years the water quality has been deteriorated due to untreated industrial effluents and urban sewage. The main objective of this study is to examine the water quality of river Damodar during and prelockdown phase for domestic use and restoration of river ecosystem. A total of eleven (11) effluent discharge sites were selected in prelockdown and during lockdown phase. A new approach of water quality assessment, i.e., water pollution index (WPI) has been applied in this study. WPI is weightage free, unbiased method to analysis of water quality. The result shows that the physical, chemical and heavy elements were found beyond the standard limit in prelockdown period. The cation and anion were arranged in an order of Na²⁺ ?>?K⁺ ?>?Ca²⁺ ?>?Mg²⁺ and Cl^??>?So₄^??>?No₃^??>?F^? in both the sessions. WPI of prelockdown showed that about 100% water samples are of highly polluted. WPI of lockdown period showed that around 90.90% samples improved to ‘good quality’ and 9.10% of samples are of ‘moderately polluted.’ Hypothesis testing by ‘t’ test proved that there was a significant difference (ρ?=?0.05%) in values of each parameter between two periods. Null hypothesis was rejected and indicated the improvement of river water quality statistically. Spatial mapping using Arc GIS 10.4 interpolation (IDW) helps to understand spatial intensity of pollution load in two periods. This research study should be helpful for further management and spatial diagnosis of water resource of river Damodar.

     

Removal of Pb(II) ions from aqueous solution and industrial effluent using natural biosorbents

Purpose

The purpose of the research is to investigate the applicability of the low-cost natural biosorbents for the removal of Pb(II) ions from aqueous solution and effluent from battery industry.

Methods

Six different biosorbents namely rice straw, rice bran, rice husk, coconut shell, neem leaves, and hyacinth roots have been used for the removal of Pb(II) ions from aqueous solution in batch process. All the biosorbents were collected from local area near Kolkata, West Bengal, India. The removal efficiency was determined in batch experiments for each biosorbent.

Results

The biosorbents were characterized by SEM, FTIR, surface area, and point of zero charge. The sorption kinetic data was best described by pseudo-second-order model for all the biosorbents except rice husk which followed intraparticle diffusion model. Pb(II) ions adsorption process for rice straw, rice bran, and hyacinth roots were governed predominately by film diffusion, but in the case of rice husk, it was intraparticle diffusion. Film diffusion and intraparticle diffusion were equally responsible for the biosorption process onto coconut shell and neem leaves. The values of mass transfer coefficient indicated that the velocity of the adsorbate transport from the bulk to the solid phase was quite fast for all cases. Maximum monolayer sorption capacities onto the six natural sorbents studied were estimated from the Langmuir sorption model and compared with other natural sorbents used by other researchers. The Elovich model, the calculated values of effective diffusivity, and the sorption energy calculated by using the Dubinin?CRadushkevich isotherm were indicated that the sorption process was chemical in nature. The thermodynamic studies indicated that the adsorption processes were endothermic. FTIR studies were carried out to understand the type of functional groups responsible for Pb(II) ions binding process. Regeneration of biosorbents were carried out by desorption studies using HNO₃. Battery industry effluents were used for the application study to investigate applicability of the biosorbents.

Conclusion

The biosorbents can be utilized as low-cost sorbents for the removal of Pb(II) ions from wastewater.     

Control of industrial air pollution through sustainable development

The environmental issue has become a major subject in the last few decades affecting science and technology throughout the world due to the serious environmental impacts caused by industrial air pollution. Consequently, pulse jet filtration has become the preferred choice all around the world. Researchers are continuously striving for new concepts of more energy-efficient and compact particulate collector which can meet future emission limits and operating requirements. The system can also satisfy stringent emission norms and if required, it can be embedded with new technique for simultaneous control of particulate and gaseous pollutants. In the recent past, stress is also being given to having control over the source to reduce or eliminate waste, and finally, on waste management. Prevention is frequently more cost-effective than control. The paper discusses all these methodology toward sustainability in the perspective of effective control of industrial air pollution.     

Distribution of PM2.5 and PM10-2.5 in PM10 Fraction in Ambient Air Due to Vehicular Pollution in Kolkata Megacity

This research paper aims at establishing baseline PM₁₀ and PM_2.5 concentration levels, which could be effectively used to develop and upgrade the standards in air pollution in developing countries. The relative contribution of fine fractions (PM_2.5) and coarser fractions (PM_10-2.5) to PM₁₀ fractions were investigates in a megacity which is overcrowded and congested due to lack of road network and deteriorated air quality because of vehicular pollution. The present study was carried out during the winter of 2002. The average 24h PM₁₀ concentration was 304 μg/m³, which is 3 times more than the Indian National Ambient Air Quality Standards (NAAQS) and higher PM₁₀ concentration was due to fine fraction (PM_2.5) released by vehicular exhaust. The 24h average PM_2.5 concentration was found 179 μg/m³, which is exceeded USEPA and EU standards of 65 and 50 μg/m³ respectively for the winter. India does not have any PM_2.5 standards. The 24 h average PM_10-2.5 concentrations were found 126 μg/m³. The PM_2.5 constituted more than 59% of PM₁₀ and whereas PM₁₀-PM_2.5 fractions constituted 41% of PM₁₀. The correlation between PM₁₀ and PM_2.5 was found higher as PM_2.5 comprised major proportion of PM₁₀ fractions contributed by vehicular emissions.     

GIS-based statistical model for the prediction of flood hazard susceptibility

At present, flood is the most significant environmental problem in the entire world. In this work, flood susceptibility (FS) analysis has been done in the Dwarkeswar River basin of Bengal basin, India. Fourteen flood causative factors extracted from different datasets like DEM, satellite images, geology, soil and rainfall data have been considered to predict FS. Three heuristic models and one statistical model fuzzy Logic (FL), frequency ratio (FR), multi-criteria decision analysis (MCDA) and logistic regression (LR) have been used. The validating datasets are used to validate these models. The result shows that 68.71%, 68.7%, 60.56% and 48.51% area of the basin is under the moderate to very high FS by the MCDA, FR, FL and LR, respectively. The ROC curve with AUC analysis has shown that the accuracy level of the LR model (AUC?=?0.916) is very much successful to predict the flood. The rest of the models like FL, MCDA and FR (AUC?=?0.893, 0.857 and 0.835, respectively) have lesser accuracy than the LR model. The elevation was the most dominating factor with coefficient value of 19.078 in preparation of the FS according to the LR model. The outcome of this study can be implemented by local and state authority to minimize the flood hazard.

     

Is shrimp farming a successful adaptation to salinity intrusion? A geospatial associative analysis of poverty in the populous Ganges–Brahmaputra–Meghna Delta of Bangladesh

The Ganges–Brahmaputra–Meghna delta of Bangladesh is one of the most populous deltas in the world, supporting as many as 140 million people. The delta is threatened by diverse environmental stressors including salinity intrusion, with adverse consequences for livelihood and health. Shrimp farming is recognised as one of the few economic adaptations to the impacts of the rapidly salinizing delta. Although salinity intrusion and shrimp farming are geographically co-located in the delta, there has been no systematic study to examine their geospatial associations with poverty. In this study, we use multiple data sources including Census, Landsat Satellite Imagery and soil salinity survey data to examine the extent of geospatial clustering of poverty within the delta and their associative relationships with salinity intensity and shrimp farming. The analysis was conducted at the union level, which is the lowest local government administrative unit in Bangladesh. The findings show a strong clustering of poverty in the delta, and whilst different intensities of salinization are significantly associated with increasing poverty, neither saline nor freshwater shrimp farming has a significant association with poverty. These findings suggest that whilst shrimp farming may produce economic growth, in its present form it has not been an effective adaptation for the poor and marginalised areas of the delta. The study demonstrates that there are a series of drivers of poverty in the delta, including salinization, water logging, wetland/mudflats, employment, education and access to roads, amongst others that are discernible spatially, indicating that poverty alleviation programmes in the delta require strengthening with area-specific targeted interventions.     

Biodiversity variability and metal accumulation strategies in plants spontaneously inhibiting fly ash lagoon,India

Environmental Science and Pollution Research - Out of 29 plant species taken into consideration for biodiversity investigations, the present study screened out Cyperus rotundus L., Calotropis...     

Visible light photocatalysts from low-grade iron ore: the environmentally benign production of magnetite/carbon (Fe3O4/C) nanocomposites

Environmental Science and Pollution Research - Magnetite (Fe3O4) nanoparticles coated with dextrose and gluconic acid possessing both super-paramagnetism and excellent optical properties have been...     

A comparative study of biopolymers and alum in the separation and recovery of pulp fibres from paper mill effluent by flocculation

Recovery of cellulose fibres from paper mill effluent has been studied using common polysacchatides or biopolymers such as Guar gum, Xanthan gum and Locust bean gum as flocculent. Guar gum is commonly used in sizing paper and routinely used in paper making. The results have been compared with the performance of alum, which is a common coagulant and a key ingredient of the paper industry. Guar gum recovered about 3.86 mg/L of fibre and was most effective among the biopolyrners. Settling velocity distribution curves demonstrated that Guar gum was able to settle the fibres faster than the other biopolymers; however, alum displayed the highest particle removal rate than all the biopolymers at any of the settling velocities. Alum, Guar gum, Xanthan gum and Locust bean gum removed 97.46%, 94.68%, 92.39% and 92.46% turbidity of raw effluent at a settling velocity of 0.5 cm/min, respectively. The conditions for obtaining the lowest sludge volume index such as pH, dose and mixing speed were optimised for guar gum which was the most effective among the biopolymers. Response surface methodology was used to design all experiments, and an optimum operational setting was proposed. The test results indicate similar performance of alum and Guar gum in terms of fioc settling velocities and sludge volume index. Since Guar gum is a plant derived natural substance, it is environmentally benign and offers a green treatment option to the paper mills for pulp recycling.