A four year long research programme divided into four phases has been designed for the first time to assess the combined Noise-Air quality and combined exposure to Noise-Air pollution at the curbside open-air microenvironment of Kolkata city, India. The results and the findings of the different phases of study had already been published. The objective of the review work is to fuse the findings of the different phases of studies; to identify the factor(s) influences the degree of correlation between concentration of the air pollutant(s) and traffic noise level at the microenvironment of the city. Incidence of moderate to very strong positive Pearson’s correlation coefficients between concentration of the air pollutant(s) and traffic noise level indicated chances of correlated exposure to these environmental stressors at the microenvironment of the city. Average combined Noise-Air quality and combined exposure to Noise-Air pollution of the microenvironment of the city was very poor (0.17) to fair (0.50) and poor (-0.06) to excellent (3.33) respectively. The best combined Noise-Air quality and the best level of combined exposure to Noise-Air pollution at the microenvironment of the city was prominently evidenced in after-noon, in summer and under variable road geometry. However, the worst combined Noise-Air quality and the worst level of combined exposure to Noise-Air pollution at the microenvironment of the city was prominently evidenced in evening, in winter and under constant road geometry. A principal component analysis revealed that intensity of wind determines the degree of correlation between the environmental stressors at the microenvironment.

Climate change is a complicated issue with many factors playing role in its formation and distribution. Considering this complication, a comprehensive and holistic approach is needed for a better understanding and management of those factors. The causal frameworks are among systemic and integrated methods for addressing the causes of environmental problems and the relationships that exist between the environmental systems in order to propose proper solutions. The DPSIR model is a functional analysis framework that depicts the cause-effect relationships that exist in creating environmental problems. Tehran is one of the major megacities in the Middle East that faces environmental consequences of overpopulation and unplanned urban sprawl, and being located in an arid region, makes it vulnerable to rise of temperature and reduction of precipitation. In this research, by using the DPSIR framework, different aspects of climate condition of Tehran are analyzed and later with the help of this conceptual framework, strategies for controlling climate change are presented.

Today, ecotourism is a major tourist activity around the world. It is based on environment potential through which suitable utilization and conservation of sites under management practices including considering accurate planning, potential, and peoples’ preferences are realized. The present study was conducted to determine people’s recreational preferences using questionnaires to evaluate the ecotourism potentials (recreational activities that choice in questioner by visitors) for site selection and land use planning, and to analyze the functional relationships among zones in the MianKaleh wildlife sanctuary, south of the Caspian Sea in Mazandaran and Golestan Provinces of Iran. Recreational preferences of people were found to be bird watching, swimming, camping, sightseeing, horse riding, and boating. Multi Criteria Evaluation was used to assess the ecotourism potential. For land use planning, the Multi Objective Land Allocation function included environmental suitability maps, zone weighting, and a set of desirable areas for each zone. Post processing functions (filters, zone size, and distance to other zones) and functional relationship diagrams were applied to amend the zoning maps. The functional relationship diagram concept was applied to the amended maps for optimizing access and identifying the relationships among zones. Overall, the results revealed that MCE and MOLA methods are capable of evaluating and zoning the wildlife sanctuary. Furthermore, post-processing and functional relationship diagrams were effective in selecting recreational sites. The results of this research revealed the recreational potential of MianKaleh wildlife sanctuary. Land planning for ecotourism can now be implemented using the results of this study that will upgrade the conservation status in the area.

Bioremoval and bioreduction activities of hydrocarbon (diesel) isolation from environmental samples were studied by the activity of biosurfactant production, and calculating emulsification index, gravimetric, and FTIR analysis along with the estimation of bacterial biomass. Sample from soil near petrol, diesel pumps and water sample from Thesjaswini River near Padannakad, Kasaragod, Kerala, India, were used to screen the potential diesel oil utilizing bacteria. Among the bacterial isolates (Staphylococcus, Bacillus and Corynebacterium strains), Staphylococcus sp was the potent degraders of diesel oil. Staphylococcus strain was observed to be maximum diesel oil utilizing ability (73% emulsification index) and change in the functional groups of the compound (FTIR analysis). The strain showed optimal growth at 37oC with pH 7, agitation of 150 rpm and time period (5days). The results revealed the possibility to use these strain for the reduction of complex hydrocarbon in ecosystems where they accumulate and cause pollution problems. The highest rate of hydrocarbon degradation occurred when the bacterial strain is a biosurfactants producer. The selective strain produces biosurfactants which increase the interfacial area for contact to give improved uptake of hydrophobic substrates. Bacterial strains capable of degrading complex hydrocarbons, present in the environment, have a potential to be used as an effective tool for removing ecotoxic compounds. Furthermore, results indicated that the bacterial strain Staphylococcus sp could be potentially used in biodegradation of diesel oil in waste water and had a promising application in bioremediation of hydrocarbon contaminated environments.

The concentration of selected trace metals (Fe, Cd, Cu, Pb, and Zn) in 30surface sediments were measured using Atomic Absorption Spectrometer to investigatethe spatial and seasonal variations of trace metals along Kanyakumari coast, India. Toassess the environmental risk of trace metals, enrichment factor, geo-accumulation index,pollution load index, and ecological risk index have been calculated. According to thepollution load index and geo-accumulation index (Igeo) values, Kanyakumari coastalsediments were unpolluted by Fe, Cu, Pb, and Zn, whereas moderately polluted by Cdwith low to moderate ecological risk. The existence of the high hydrodynamic conditionduring the southwest monsoon is more favorable to the transport of sediments andenhance the accumulation of metals, whereas during the northeast monsoon theaccumulation of metals is less. The baseline data for spatial distribution and seasonalvariation of trace metals and their controlling factors found in this study will be useful forpollution monitoring program along the Kanyakumari coast.

Air pollution is a challenging issue in some of the large cities in developing countries. Air quality monitoring and interpretation of data are two important factors for air quality management in urban areas. Several methods exist to analyze air quality. Among them, we applied the dynamic neural network (TDNN) and Radial Basis Function (RBF) methods to predict the concentrations of ground-level ozone in Karaj City in Iran. Input data included humidity, hour temperature, wind speed, wind direction, PM2.5, PM10 and benzene, which were monitored in 2014. The coefficient of determination between the observed and predicted data was 0.955 and 0.999 for the TDNN and RBF, respectively. The Index of Agreement (IA) between the observed and predicted data was 0.921 for TDNN and 0.9998 for RBF. Both methods determined reliable results. However, the RBF neural network performance had better results than the TDNN neural network. The sensitivity analysis related to the TDNN neural network indicated that the PM2.5 had the greatest and benzene had the minimum effect on prediction of ground-level ozone concentration in comparison with other parameters in the study area.

Groundwater is a major source of water for domestic, industrial, and agricultural sectors in many countries. The main objective of this research was to provide an overview of present groundwater quality using parameters such as calcium, magnesium, sodium, chloride, sulfate, pH, and electrical conductivity (EC) in the Mehran plain, Ilam province using GIS and geostatistical techniques. A total of 23 deep and semi-profound wells were selected based on the classified randomized sampling method. The sampling locations were obtained by GPS. Plastic containers were used for the collection of water samples. These samples were transferred to the laboratory for analyzing water quality parameters. Statistical characteristics, qualitative data interpolation, and zoning were investigated using SPSS 20 ،GS+5.3 and ArcGIS10.1. Kolmogorov–Smirnov test were used to test data normality. In order to normalize parameters, logarithm, and 1/x were used for sulfate, EC, cation, and anion. Then the variogram analysis was performed to select the appropriate model. Results showed that co-kriging is the best method for cation and anion, whereas local polynomial interpolation is suitable for sulfate. The results of the interpolation of groundwater quality factors showed that there is approximately good adaption among groundwater factors and geomorphology and topology of the region. Because of inappropriate irrigation system, the highest concentration is in the northwest and western parts of the region, where there is the minimum height and maximum agricultural land. Growth of arable land and agricultural activities has caused increasing concentrations of studied elements, especially EC.

The surface water chemistry of Thiruvananthapuram Museum Lake was carried out in the period of February 2013 to January 2014. Correlation study of the parameters and overall CCME WQI (Canadian Council of Ministers of the Environment Water quality Index) was also prepared in the study for the lake water. The parameters analysed are cations such as Ca2+, Na+, Mg2+ and K+ and the anions like PO4-, Si4- , NO3- and NO2-. Abiotic factors like water pH, Temperature, Conductivity, TDS, Total Alkalinity and Total Hardness were also analysed. The pH ranged between 6.5 to 7.4. The total hardness ranged between 50.8-99 mg/L which shows the water is moderately hard one. During the pre monsoon period, water temperature showed a positive correlation with total alkalinity (r= 0.915) pH (r= 0.841) and TDS (0.876). Dissolved Oxygen (DO) value showed a positive correlation with Biological Oxygen Demand (BOD) (r= 0.999). The overall CCME water quality index was 80.81 which indicate the water body is protected with only a minor degree of threats. The quality of the water is an essential element of the Thiruvananthapuram Zoo environment with respect to both healths of the ecosystem and zoo tourism enjoyment. Moreover, if maintained properly, this water body can be treated as a major drinking water source for the zoo animals.

The present study has been undertaken in a laboratory scale to characterize and investigate pollution potential of textile effluents from DEPZ area in Dhaka, Bangladesh. Collected effluent samples from five different industries were analyzed for physico-chemical parameters using field kits and Standard Methods, and for metals using Flame Atomic Absorption Spectrophotometer (FAAS). The average physico-chemical parameters such as temperature, color, pH, DO, EC, BOD, COD, TS, total alkalinity and total hardness were found 52.4 ºC, 2646 PCU, 9.788, 1.492 mg/L, 7473.2 μS/cm, 157 mg/L, 508.8 mg/L, 9140.8 mg/L, 761.2 mg/L and 189.6 mg/L, respectively. The average concentrations of metal found in the textile effluents were in the order of Na (4611.762 mg/L) > Ca (9.166 mg/L) > Mg (3.578 mg/L) > Zn (0.113 mg/L) > Ni (0.0074 mg/L) > Cu (0.0032 mg/L). All the measured physico-chemical parameter values are negatively deviated but metal concentrations (except Na) are positively deviated from standard limits of wastewater discharge set by Department of Environment and US Environmental Protection Agency. In view of those characteristics, the textile industry effluents should be considered to be treated by setting eco-friendly effluent treatment plant (ETP) before directly discharging into the water bodies.

The contamination of riverbed sediments by heavy metals has assumedserious problems due to their toxicity and accumulative behavior. The present studyinvestigated the concentrations of heavy metals from the bottom sediments of ShitalakhyaRiver to understand the level of contamination and their distribution. The averageconcentrations of heavy metals Al, K, Ca, Mg, Fe, As, Cu, Co, Cr, and Zn are 30432.41,10929.21, 391139.13, 23148.14, 38697.37, 14.02, 143.69, 13.37, 74.82, and 200.59mg/kg respectively in river sediments, and their abundance decreased in the followingorder: Ca (79.05%)>Fe (7.82%)>Al (6.15%)>Mg (4.68%)>K (2.21%)>Zn (0.04%)>Cu(0.03%)>Cr (0.015%)>As (0.0028%)>Co (0.0027%). In most cases, the meanconcentrations of the heavy metals exceed the permissible limit. Significantly higherconcentrations of Ca, Mg, Zn, and Cu were found in sediment samples. The heavy metalscontaminations in the sediments were also evaluated by applying index of geoaccumulation(Igeo), contamination factor (Cf), degree of contamination (Cd), and pollutionload index (PLI) etc. These indices indicated that most of the samples were moderate tostrongly pollute by heavy metals and the spatial distribution showed that the northern andsouthern parts of the study area are more contaminant than middle portion.