The present study aims to have a comparative study of the results, from biological monitoring as well as conventional method, based on physico-chemical variables. Water quality index (WQI) and planktonic diatom metrics have been used to determine water quality and ecological conditions of the Dong Nai River (DNR) and Canonical Correspondence Analysis (CCA) to find out the main environmental variables that regulate the phytoplankton community. A total of 51 planktonic diatom species, belonging to 23 genera, have been identified during the study period. Fragillaria was the most dominant diatom in the upper course site, while the Aulacoseira was the most dominant species in the middle and lower ones. One-way ANOVA showed that the mean of turbidity, ammonium, nitrate, and phosphate were significantly different (P<0.05) among upper, middle, and lower course sites in both dry and wet seasons. The WQI showed that water quality in the Dong Nai River was classified in medium level at all sites, while water quality varied from good, moderate, to low level, based on the Biological Diatom Index (BDI) values. CCA indicated that nutrients (PO43-, NO3-, NH4+) and turbidity were the most important factors, regulating the variation in structure of the planktonic community. In this study, the BDI has been applied for the first time to bio-monitor water quality in Vietnam. The sensitivity of the BDI to environmental stressors, supported the use of this index to bio-monitor surface water in tropical regions.

The present study investigates the accumulation of vanadium, iron, and nickel in different depths of soil in collection sites of oil sludge, in Masjed Soleyman Oil and Gas Exploitation Company, located in Choob Sorkh Region. To conduct the research, four sampling points have been selected at the mentioned site, with one sampling point chosen outside the site, as the clean area. Soil sampling has been carried out at depths of 50 and 100 cm, using an auger. All samples are measured to evaluate heavy metals, according to the standard method of Inductive Coupled Plasma (ICP) spectroscopy. The parameters of pH, EC, density, and organic compounds have also been measured. Results have shown that EC, TOM, and density of the soil in the collection site of oil sludge were relatively higher than the reference site. In addition, statistical analysis has shown that electrical conductivity and organic compounds were influenced by the discharge of oil sludge. The mean concentrations of Ni, V, and Fe in both depths (50 cm and 100 cm) of the four studied plots were 68.8 mg/kg, 46.3 mg/kg, and 53565 mg/kg, respectively, indicating that Ni concentration is more than the acceptable limits in the soil. Although, the amounts of V (36.3 mg/kg), Ni (62 mg/kg), and Fe (19416 mg/kg) in the reference site were lower than the studied oil sludge accumulation site. Thus the study area is a place for the accumulation of oil sludge, since the high concentration of heavy metals can be attributed to human interference.

Seasonal variation in water quality of Anchar Lake was evaluated using multivariate statistical techniques- principal component analysis (PCA) and cluster analysis (CA). Water quality data collected during 4 seasons was analyzed for 13 parameters. ANOVA showed significant variation in pH (F3 = 10.86, P < 0.05), temperature (F3 = 65, P <0.05), Electrical conductivity (F3 = 32.72, P <0.05), Calcium (F3 = 36.84, P <0.05), Magnesium (F3 = 16.52, P <0.05), nitrate-nitrogenSeasonal variation in water quality of Anchar Lake has been evaluated, using two multivariate statistical techniques, namely Principal Component Analysis (PCA) and Cluster Analysis (CA). Water quality data, collected during four seasons, have been analyzed for 13 parameters and ANOVA has shown that pH (F3= 10.86, P < 0.05), temperature (F3 = 65, P < 0.05), electrical conductivity (F3= 32.72, P < 0.05), Calcium (F3= 36.84, P < 0.05), Magnesium (F3= 16.52, P < 0.05), nitrate-nitrogen (F3= 48.06, P < 0.05), ammonical nitrogen (F3 =198.75, P < 0.05), and dissolved oxygen (F3= 4.96, P < 0.05) varied by season, whereas the substantial variations of sodium (F2= 7.18, P <0.05), phosphate-phosphorous (F2= 25.31, P < 0.05), biological oxygen demand (F2= 11.02, P < 0.05), and chemical oxygen demand (F2=37.73, P < 0.05) were based on different sites. CA has grouped the three sampling sites throughout the four seasons into three clusters of similar water quality as relatively Less-Polluted (LP), Medium-Polluted (MP), and Highly-Polluted (HP). In addition, PCA has been applied on the extract to recognize the factors, responsible for water quality variations in four seasons of the year, resulting in four principal components for winter, summer, and autumn, five ones for spring, accounting for 79.58%, 89.07%, 83.34%, and 93.13% of total variance respectively. Thus the factors, responsible for water quality variation, are mainly related to domestic wastewaters, seasonal variation, agricultural runoff, and catchment geology. These results will help decision-makers better understand the influence of various factors on water quality and manage pollution/eutrophication adaptively in Anchar Lake.

The present paper has examined the degrading ability of phenol-oxidizing bacterium, Ralstonia eutropha, for biological removal of methylene blue (MB) from aqueous solutions under aerobic conditions. Results show that MB has been extensively eliminated as a co-metabolism in the presence of supplementary carbon (glucose) and nitrogen (yeast extract and peptone) sources and the experimental observations indicate that MB is initially adsorbed on the cell’s surface, in accordance to Langmuir Theory, then to be degraded by the cell. The type of nitrogen source, initial pH, aeration rate, and the presence of CaCl2 are all influential factors in the process of MB removal. The biodegradation kinetics modeling has determined that while playing an uncompetitive role, MB inhibits its biodegradation at high concentrations. According to the best fit Han-Levenspiel Model, the maximum MB specific biodegradation rate (rmax), half-saturation concentration of MB (KS), maximum allowable MB concentration (Sm), and the shape factors (n and m) have been 7.37 mg gcell-1 h-1, 32.13 mg/L, 158.8 mg/L, 0.27, and 0.76, respectively.

The present investigation characterizes tannery effluents by determining water quality parameters and some selected trace metallic constituents in order to measure the magnitude of environmental pollution. Effluents and sediments have also been used to isolate chromium-resistant bacteria, collected from Hazaribagh area, Dhaka, claimed to be increasing Cr (VI)-enriched environments, and utilized to reduce Cr (VI). The pH, TDS, DO, and EC values of all investigated samples have been within the range of 4.35 to 9.74, 290 to 9,200 mg/L, 1.5 to 4.90 mg/L, and 587 to 19,000 µs/cm, respectively. The concentrations of trace metallic constituents have been determined by means of Atomic Absorption Spectrophotometer (AAS), giving the following ranges: Cr: 14.282 to 6,769.554 mg/L; Cd: 1.546 to 2.214 mg/L; Pb: 18.808 to 32.026 mg/L; Cu: 1.522 to 2.578 mg/L; Zn: 0.682 to 8.688 mg/L; Fe: 1.37 to 108.556 mg/L; and Mn: 3.494 to 17.17 mg/L. The order of trace metallic constituents in the effluent samples was Cr > Fe > Pb > Mn > Zn > Cd > Cu. The water quality parameters and metallic constituents’ concentration were higher than that of standard permissible limits in all the examined samples. The average number of Cr (VI)-resistant bacteria in the sediment samples with glucose (0.5%, w/v) supplementation was 2.35× 103 CFU/gm at 24h. One of the representative isolate was able to tolerate up to 400 mg/L of K2Cr2O7 as Cr (VI). The bacteria, isolated in the present study, can be used as eco-friendly biological agents for the remediation and/or detoxification of chromium (Cr) pollution from the chromium contaminated environments.

The present study has been conducted to assess the surface water quality of Halda River from September 2015 to March 2016. DO, BOD5, COD, pH, EC, Chloride, Alkalinity, and Hardness concentrations in water samples have been found to range within 0.93-5.15 mg/L, 30-545 mg/L, 43-983 mg/L, 6.3-7.3, 110-524 uS/cm, 12-56 mg/L, 35-67 mg/L, and 38-121 mg/L, respectively. Multivariate statistical analyses, such as Principal Component Analysis (PCA) as well as Correlation Matrix (CM) have revealed significant anthropogenic pollutant intrusions in water. Cluster Analysis (CA) has indicated decent results of rendering three different groups of resemblance between the two sampling sites, reflecting the different water quality indicators of the river system. A very strong positive linear relation has been found between COD and BOD (1.000), hardness and EC (0.993), pH and DO (0.979), hardness and COD (0.929), hardness and BOD (0.924), EC and COD (0.922), and EC and BOD (0.916) at a significance level of 0.01, proving their common origin entirely from industrial effluents, municipal wastes, and agricultural activities. River Pollution Index (RPI) has indicated that the water from rivers at Kalurghat and Modhunaghat varied from low to high pollution, which is due to the former area's being mostly industrial zone with some domestic sewage, while the latter underwent less industrial activities. On the contrary, lots of agricultural activities have been found in Modhunaghat. Use of river water can pose serious problems to human health and aquatic ecosystem via biological food chain. The present research suggests special preference for proper management of the river with eco-friendly automation along with development of the country's sustainable economic.

The present study is aimed at characterizing the landfill leachate as well as its impact on the surrounding groundwater in Kolkata, India. Landfill leachate has been seasonally characterized from 2012-2014, indicating the landfill site in methanogenic phase with high contamination of organics, nutrients, salts, and heavy metals. Sixty groundwater samples have been analyzed for twenty two physico-chemical parameters in pre-monsoon, monsoon, and post-monsoon season of 2014. Seasonal alterations of groundwater quality have been evaluated with a statistical tool, Kruskal-Wallis test, to assess the influence of leachate, showing significant changes in almost all its physico-chemical parameters with sampling time. Majority of groundwater samples were contaminated with Hg, Pb, Cd, Cr, Fe, and Mn, indicating very little effect of redox control on the occurrence and transport of heavy metals. Comparison of physico-chemical parameters with World Health Organization (WHO) and Bureau of Indian Standards (BIS) indicate that majority of groundwater samples have been inadequate to use as potable water. Therefore, this study would help in developing policies for landfill leachate treatment programs and controlling groundwater pollution at the concerned landfill site.

Certain species of Hermetia illucens, also known as the Black Soldier Fly(BSF), were found in a compost plant in Roorkee located in Northern India. Its larvae arevoracious eaters of organic waste, hence can play an ecologically-important role in solidwaste management. Morphological analysis of various stages of BSF life cycle by SEMshowed that its body along with its wings is densely covered with hair. The identifiedspecies of BSF were black in color and oviposited into the composted material. The larvaegrew up to 30 mm long in 12 days from an initial length of only 6mm, gaining almost 200%of its initial weight after voraciously feeding on organic waste. The mouth of the H. illucensshowed a well-developed mandibular-maxillary complex that had similar characteristics ofscavengers, making the insect a suitable candidate for organic waste consumption.

For the first time, the present study removes ions of mercury, in the form of Hg (I) and Hg (II) ions, from aqueous solutions by adsorbing them onto titanium dioxide nanoparticles. The effects of various parameters, such as solution's initial pH, temperature, sorbent dosage, initial mercury concentration, and contact time have been examined on the adsorption process. The experimental results have been compared with Langmuir, Freundlich, and Temkin adsorption isotherms. The maximum adsorption, obtained for Hg (I) and Hg (II) ions, have been 97.5% and 98.6%, respectively. Also, it has been shown that the Langmuir isotherm has better fitting with the equilibrium data than the Freundlich and Temkin isotherms. Thermodynamic parameters of the adsorption, such as and  have been calculated, the negative values of which show that the mercury ions adsorption is an exothermic process and that randomness is decreased, respectively. The study of adsorption kinetics shows that the adsorption of Hg (I) and (II) ions with TiO2 nanoparticles is pseudo-second order.

The present study analyzes air quality for Carbon monoxide (CO), in Esfahan with the measurements taken in three different locations to prepare average data in the city. The average concentrations have been measured every 24 hours, every month and every season with the results showing that the highest concentration of CO occurs generally in the morning and at the beginning of night, while the least concentration has been found in the afternoon and early morning. Monthly concentrations of CO show the highest values in August and the lowest values in February. The seasonal concentrations show the least amounts in spring, while the highest amounts belong to summer. Relations between the air pollutant and some meteorological parameters have been calculated statistically, using the daily average data. The data include Temperature (min, max), precipitation, Wind Direction (max), Wind Speed (max), and Evaporation, considered independent variables. The relations between the pollutant concentration and meteorological parameters have been expressed by multiple linear regression equations for both annual and seasonal conditions, using SPSS software. Analysis of variance shows that both regressions of ‘enter’ and ‘stepwise’ methods are highly significant, indicating a significant relation between the CO and different variables, especially for temperature and wind speed in annual condition. RMSE test shows that among different prediction models, stepwise model is the best option.