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.

Evaluation of surface water quality is a complex process undertakingmultiple parameters. Converting great amount of parameters into a simpler expressionand enabling easy interpretation of data are the main purposes of water quality indices.The main aim of this study is to plan effective water resources management system forKarun River by combination of CCMEWQI and Geographic Information System (GIS).The investigation was carried out to set a management plan through exploratory andspatial analysis of physicochemical water parameters of collected samples from 10stations over one year period. Since all indices were obtained from index, river zoningwas conducted by GIS. Moreover, trace metals concentrations (As, Cr, Cd, Fe, Zn, Mn,and Al) ranged in safer limit. The highest values of F1 belonged to aquatic life and thelowest ones belonged to irrigation. Aquatic life and drinking uses received the maximumvalues of F2. The lowest values were devoted to livestock and then recreation uses. It wasinferred from index that the quality of the Karun River is principally impacted by highturbidity, TDS, NO3, SO4, and PO4 due to high suspended sediment loads. The maincause is incremental agricultural, industrial, and residential effluents. Amongst stations,station one only received the priority for drinking water supply and recreation.

We investigated the issue of noise pollution in the Bidboland gas refineryby noise measurement and surveys. The Bidboland gas refinery has several process units.The sound pressure levels were measured at several places, such as units of 200, 300,400, 500, boiler, powerhouse area, cooling towers pumps, and maintenance area, and thecorresponding noise maps were produced by using sound plan software. We identified thesources of noise pollution. We first measured the mean A-weighted sound pressure levelin each study unit and analyzed the obtained data in Microsoft Excel. The noisiest unitswere identified and some suggestions were offered to reduce the sound exposure level. Itwas specifically noted through the surveys that the noise levels detected in all testedindustries was much above 80 dBA limit specified by regulations. In lieu, variousmeasures to control the noise pollution were contemplated and discussed.

The knowledge of local and regional factors that affect effective solidwaste collection plays an important role in choosing appropriate technology. Wastecollection has grown to become a major challenge demanding daily response from wastemanagers and it becomes inevitable to provide stakeholders with necessary information toaid key decision-making. This paper provides a comprehensive and detailed review oflocal-based factors that affect waste collection in Nigeria. Literature study and on-siteobservation were used for getting theoretical and useful information on the collection ofwaste in the study area. The study considered various standard collection technologiesand their supporting factors in order to assess the effectiveness of existing methods. Thecurrent collection techniques existing in different parts of the country together withunique local factors for these various areas are reported. The findings in many casesreveal that the method of waste collection adopted and equipment used are faced withmany challenges. This paper revealed that there is no investment presently made on theexisting development plan to initiate a modern waste collection system. The studyrecommends a new approach that could be used by institutions and government agenciesfor efficient municipal solid waste collection to achieve sustainable and effectivesanitation which will consequently facilitate the development of an aesthetically balancedand friendly environment.

Kerosene is the colorless liquid and slightly heavier than gasoline thatspecific odor removes after evaporation. Soil and underground water source arecontaminated with different pollutants such as petroleum hydrocarbons. These pollutantshave various negative environmental effects on soil and surrounding environment. Theaim of this research is to understand the effect of kerosene pollution on two differentsoils. The two different collected soils include Industrial and Forest soil. Six microcosmswere designed. Indeed, each soil has three microcosms: unpolluted microcosm, pollutedmicrocosm, and polluted microcosm with nutrient (Nitrogen and Phosphor). Some factorswere assayed in each microcosm during 120 day of experiment. These factors includetotal heterotrophic bacteria, total kerosene degrading bacteria, dehydrogenase enzyme,and kerosene biodegradation. The results of this study show that the highest quantity ofheterotrophic bacteria is related to forest soil (6×109). The quantities of kerosenedegrading bacteria significantly were lower than heterotrophic bacteria in all soilmicrocosms. The quantity of kerosene degrading bacteria have decrement pattern until60th day of experiment, but, after this day, these bacteria have increment pattern. The bestdehydrogenase activity between different microcosms is related to polluted microcosmwith kerosene except for farmland soil. The highest biodegradation of kerosene in allstudied soil belongs to industrial microcosm (95%). Statistical analysis of the resultsshows that there is a significant correlation between MPN quantity of heterotrophicbacteria and other assayed factrs. Also, forest soil has significant difference with othersoils. It may be possible to propose appropriate strategies for bioremediation of differentstudied soil types using the results obtained in this research.

The estimation of pollution fields, especially in densely populated areas, is an important application in the field of environmental science due to the significant effects of air pollution on public health. In this paper, we investigate the spatial distribution of three air pollutants in Tehran’s atmosphere: carbon monoxide (CO), nitrogen dioxide (NO2), and atmospheric particulate matters less than 10 μm in diameter (PM10μm). To do this, we use four geostatistical interpolation methods: Ordinary Kriging, Universal Kriging, Simple Kriging, and Ordinary Cokriging with Gaussian semivariogram, to estimate the spatial distribution surface for three mentioned air pollutants in Tehran’s atmosphere. The data were collected from 21 air quality monitoring stations located in different districts of Tehran during 2012 and 2013 for 00UTC. Finally, we evaluate the Kriging estimated surfaces using three statistical validation indexes: mean absolute error (MAE), root mean square error (RMSE) that can be divided into systematic and unsystematic errors (RMSES, RMSEU), and D-Willmot. Estimated standard errors surface or uncertainty band of each estimated pollutant surface was also developed. The results indicated that using two auxiliary variables that have significant correlation with CO, the ordinary Cokriginga scheme for CO consistently outperforms all interpolation methods for estimating this pollutant and simple Kriging is the best model for estimation of NO2 and PM10. According to optimal model, the highest concentrations of PM10 are observed in the marginal areas of Tehran while the highest concentrations of NO2 and CO are observed in the central and northern district of Tehran.

In the present study, air quality analyses for ozone (O3) were conducted in Shiraz, a city in the south of Iran. The measurements were taken from 2011 through 2012 in two different locations to prepare average data in the city. The average concentrations were calculated for every 24 hours, each month and each season. Results showed that the highest concentration of ozone occurs generally in the afternoon while the least concentration was found in the morning and at midnight. Monthly concentrations of ozone showed the highest value in August and June while the least value was in December. The seasonal concentrations showed the least amounts in autumn while the highest amounts were in spring. Relations between the air pollutant and some meteorological parameters were calculated statistically using the daily average data. The wind data (velocity, direction), relative humidity, temperature, sunshine periods, evaporation, dew point, and rainfall were considered as independent variables. The relationships between concentration of pollutant and meteorological parameters were expressed by multiple linear regression equations for both annual and seasonal conditions using SPSS software. Root mean square error (RMSE) test showed that among different prediction models, stepwise model is the best option.