Pollution
Year:2017 | Volume:3 | Issue:2|Papers Count:15

The present study aims to analyze the existing indoor environmental conditions of Firozabad City along with its impact on people’ s health by going through the correlative index of indoor environment’ s determinant and different diseases, faced by the people. In order to measure spatial disparities, the statistical technique, i. e. the standard score additive model (Z-score), has been applied to develop a composite score for each set of indicators in order to arrive at the general environmental and health condition of the study area as a whole. The analysis reveals that high intensity of indoor pollution and disease are reported in peripheral and old parts of the city. Preventive measures, likely to have deleterious health effects and improve such harmful environmental conditions, should be adopted. Enhanced use of clean fuel and national uniform housing codes or guidelines that address factors, affecting indoor air quality, makes up the current need

Environmental pollution consists of different types of pollutants in air, soil, and water. Due to the fact that plants can respond to environmental pollution, they can be used as bio-indicators for environmental monitoring. Air pollution in areas with oil and gas refineries nearby is an important problem. This study aims to survey the effects of gas refinery air pollutants on Conocarpus erectus so that it can be used for air-pollution monitoring. For this purpose, physiological indicators such as proline, protein, and malondealdehyde content as well as Air Pollution Tolerance Index (APTI value) have been used to evaluate these effects. Based on the obtained results, Conocarpus erectus in polluted area showed increased pH, protein, proline, malondealdehyde, and ascorbic acid contents while carotenoid quantity, total leaf chlorophyll content, and relative water content were decreased in comparison to the control plants. Therefore, it proves that air pollution affects the plant.

One of the main aims of water resource planners and managers is to estimate and predict the parameters of groundwater quality so that they can make managerial decisions. In this regard, there have many models developed, proposing better management in order to maintain water quality. Most of these models require input parameters that are either hardly available or time-consuming and expensive to measure. Among them, the Artificial Neural Network (ANN) Models, inspired from human brain, are a better choice. The present study has simulated the groundwater quality parameters of Ramhormoz Plain, including Sodium Adsorption Ratio (SAR), Electrical Conductivity (EC), and Total Dissolved Solids (TDS), via ANN and ANN+ Particle Swarm Optimization (PSO) Models and at the end has compared their results with the measured data. The input data for TDS quality parameter is consisted of EC, SAR, pH, SO4, Ca, Mg, and Na, while for SAR, it includes TDS, pH, Na, and Hco3, and as for EC, it involves So4, Ca, Mg, SAR, and pH; all of them, gathered from 2009 to 2015. Results indicate that the highest prediction accuracy for SAR, EC, and TDS is related to the ANN + PSO model with the tangent sigmoid activation function so that both MAE and RMSE statistics have the minimum and R2 the maximum value for the model. Also the highest prediction accuracy is respectively related to EC, TDS, and SAR parameters. Considering the high efficiency of artificial neural network model, by training the PSO algorithm, it can be used in order to make managerial decisions and ensure monitoring and cost reduction results.

The present research analyzes air quality in Ahvaz, a city in the south of Iran, paying special attention to sulfur dioxide (SO2). In order to prepare the average data in the city, measurements have been carried out between 2009 and 2010 in two different locations. Relations between sulfur dioxide and some meteorological parameters have been calculated statistically, using the daily average data. The wind data (velocity, direction), relative humidity, temperature, sunshine periods, evaporation and rainfall have been considered as independent variables. The RMSE Test showed that among different prediction models, the stepwise one is the best option. The average concentrations have been calculated for every 24 hours, during each month and each season. Results show that the highest concentration of sulfur dioxide occurs generally in the morning while the lowest concentration is found before the sunshine. In case of the monthly concentrations of sulfur dioxide, the highest value belongs to January, while the lowest one occurs in October. And as for the seasonal concentrations, it has been shown that the highest amounts belong to winter. Results show that quantities of SO2 in different seasons as well as the entire year can be estimated by climate parameters. Results also indicate that the relations between the SO2 and meteorological parameters are stronger than the entire year during the seasons.

Groundwater makes up an important part of global freshwater resources, though it is often threatened by overuse of natural resources along with abundant production of wastes in modern society. This study aims to investigate the removal of three heavy metals including nickel, cadmium, and lead from groundwater via electrocoagulation, a suitable method for treatment of water-soluble compounds, dealing with the impact of this process on three major groundwater parameters, namely TDS (Total Dissolved Solid), TH, and EC at a laboratory scale. The experiments have been performed using four aluminum electrodes. In this research, the efficiency of contaminants removal and the parameters of interest have been investigated under several conditions such as the distance among the electrodes, potential difference among the electrodes, and different initial concentrations of heavy metals with a detention time of 20 min. Afterwards both results and observations have been analyzed, using diagrams and data tables. Results indicate that this method has had no significant effect on TDS and EC; however, in case of TH, the removal has increased by up to 29. 17%. As for the heavy metals, all three contaminants have achieved an increase of the potential difference to 15 V, a decrease in the distance among the electrodes to 2. 2 cm, as well as a removal of over 90%. Furthermore, result analysis shows that this process has had a better removal efficiency, concerning lead.

The present paper has determined the radioactivity concentrations, which are due to natural occurrence of radionuclides along with heavy metal concentration in water, sediment, and fish from 2 reservoirs in Ghana. Heavy metal concentrations in all samples were generally within the WHO safe limits with the average activity concentrations of 238U, 232Th, and 40K in water being respectively 0. 42± 0. 20, 0. 33± 0. 31, and 1. 59± 1. 07 Bq/L in case of Lake Bosomtwe and 0. 26± 0. 14, 0. 67± 0. 34 and 1. 47± 0. 62 Bq/L for Bui Dam in Ghana. The average annual effective dose due to ingestion of radionuclides in water ranged from 20. 5 to 156 for Lake Bosomtwe and 26. 5 to 162 μ Sv/year for Bui dam and the absorbed dose rate and annual effective dose, measured for Lake Bosomtwe, was 15. 45± 2. 00 nGy/year and 18. 95± 2. 95  S/year respectively while in case of Bui dam it accounted to 10. 44± 4. 11 nGy/year and 12. 88± 5. 01  S/year respectively, found to be within the UNSCEAR recommended limits of 59 nGy/year and 100  S/year respectively. The observed metal concentrations, within safety limits, imply that metal-associated diseases cannot be expected among patrons of these reservoirs. Therefore, radionuclides and heavy metals levels in the reservoirs are not expected to cause any significant health problem for humans.

The present study has been conducted to determine the surface water quality of urban area in Savar, Dhaka, Bangladesh by determining some water quality parameters (Transparency, Temperature, pH, EC, Eh, DO, TSS, TDS, TS, BOD5, COD, TOC, Cl-, Br-, SO4-2, NO3-, NO2-, PO4-3, TP, HCO3-and Total alkalinity) as well as the status of phytoplankton’ s community in the water from two lakes (Tiger Lake and AERE Lake) and one canal (Karnapara Canal). The water quality of the AERE Lake is better than the Tiger Lake and the Karnapara Canal. Organic Pollution Index (OPI) demonstrates that water bodies are severely polluted by organic matters in the study area. R mode Cluster Analysis (CA) reveals that the water bodies are polluted and the common sources of pollutants are anthropogenic (industrial, agricultural, municipal sewerage). The Principle Component Analysis/Factor Analysis (PCA/FA) identifies two dominant factors, responsible for data structure, explaining 100% of total variance in the data set. The PCA agrees with CA, suggesting that multiple anthropogenic sources are responsible for the surface water quality deterioration in this area. The present study reflects the actual scenario of surface water quality of Savar urban area, thus will be helpful for the policy planers and makers to take proper management and abatement strategies for the sustainable management of water resources in urban areas of Bangladesh.

Djendjen River is one of the largest rivers in the region of Jijel (Algeria). Human activities such as urban discharges, industrial, agricultural, and livestock have significant effects on the quality of water. The present study attempts to evaluate the quality of water along the banks of the Djendjen River at different sampling sites, using physico-chemical and bacteriological methods. The collected samples are analyzed per standard method parameters and measured in situ. The mean values of the physico-chemical parameters of the river water samples are consistently lower than the levels, certified by the Algerian standard (exept for pH and PO43-). The total and fecal coliform surpasses the Algerian standard limits (0 cfu/ 100 ml) at all sites, signifying that without treatment the water is unsuitable for human consumption. Results reveal that water quality of the Djendjen River is generally affected by the anthropogenic activities, taking place along its banks. The moderate organic pollution (OPI= 2-2. 6) and high faecal contamination (MQI=3-3. 25) of water in the study area has adverse impacts on the environment and public health, which requires a combined treatment (biological and physicochemical).

Predicting the quality of water and air is a particular challenge for forecasting systems that support them. In order to represent the small-scale phenomena, a high-resolution model needs accurate capture of air and sea circulations, significant for forecasting environmental pollution. Data assimilation is one of the state of the art methods to be used for this purpose. Due to the importance of thermal structure in monitoring the variations of environmental phenomena, the present study has used Sea Surface Temperature (SST) in data assimilation method to optimize this parameter. SST is one of the most important factors to conduct researches on the ocean, the atmosphere, and their interaction, not to mention monitoring and forecasting air and ocean phenomena as well as commercial and fishing communities and weather forecasts. This study has aimed to present a satellite-derived SST based on pathfinder advanced very high resolution radiometer (AVHRR) data assimilating in FVCOM (finite volume community ocean model) on the Persian Gulf to examine the effect of data assimilation by using the Cressman scheme. The performance of this method has been compared to the optimal interpolation SST (OISST) data, via both visual comparisons and statistical parameters. Applying assimilation method improves correlation coefficient of the model from 0. 92 to 0. 99. Results demonstrate that the modeled SST has been completely reconstructed by the data assimilated experiment via the Cressman scheme for this region. The spatial and temporal pattern of SST reveals a significant improvement in the entire domain during the investigated period in the gulf.

Urban horticulture is of growing importance in developing and developed countries around the world; however, contamination of urban horticultural products can exceed the precautionary values, posing significant human health risks due to dietary exposure to high levels of the pollutants. In this study, samples of rhizosphere soil and corresponding vegetables have been collected from an urban garden in Ilorin, Nigeria, to assess the contamination level of trace metals as well as the health risk, associated with dietary intake of contaminated vegetables, in adult sub-population. The range of Cu, Pb, and Cd in garden topsoil was 14. 0-52. 50, 33. 00-121. 40, and 1. 00-4. 50 mg/kg, respectively. The metals sources were both anthropogenic and lithogenous, though the long-term accumulation of trace metals in the soil led to significant soil-plant transfer as evident in the levels of metals in some of the vegetables. The estimated daily intakes (EDI) of Cu and Pb through vegetable consumption were far below the recommended tolerable daily intakes (TDI) and the hazard quotient (HQ) values were within the safe zone for the adult population. In contrast, the EDI of Cd for the vegetables was several folds greater than the TDI, thus greatly contributing to a high hazard index (HI>1. 0), observed in all vegetables. Therefore, risk assessment of trace metal ingestion through consumption of the vegetables in the adult sub-population depicts serious health hazards with Cd, mainly contributing to vegetable contamination in the studied area.

Water and sediment samples were collected from six different stations, located along the Nil River between February and June 2015. Concentrations of cadmium, lead, zinc, and copper were determined. The extent of the sediment pollution was assessed, using the multiple pollution indices, namely contamination factor (CF), pollution load index (PLI), and the geoaccumulation index (Igeo). The results showed that the level of metals in water samples exceeded background concentrations for Cd and Pb, and the average values for those elements were higher than those of Zn and Cu, ranked as the following: Pb (0. 58)> Zn (0. 38)> Cd (0. 32)> Cu (0. 061). For sedimentary samples, the results showed that Zn and Pb concentrations were greater than the concentrations of Cu and Cd, exceeding the background values (except for Cu). The concentration of the tested heavy metals decreased to the following order: Zn (96. 2)> Pb (61. 5)> Cu (38. 83)> Cd (2. 34). The Igeo values revealed that Cd (2. 87) and Pb (1. 61) had accumulated significantly in the Nil River. Contamination factor (CF) confirmed that the sedimentary samples were moderate to very high in terms of Cd, Pb, and Zn contamination. The Pollution Load Index (PLI) values were above one (>1), indicating an advanced decline of the sediment quality. Also, the results showed that the stations, located at the middle portion of the river (S3, S4, and S5) have higher levels of metals than the other stations (S1, S2, and S6). The assessment of heavy metals' levels in water and sedimentary samples indicated that river water and the sediments in the study area were strongly impacted by agricultural activities and domestic waste water.

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.

With a mean precipitation rate, much lower than that of the world, Iran is among the countries that face severe water challenges. The present study has dealt with the evaluation of hydrochemistry of Faryab spring water in Hormozgan Province, Iran. Four different composite water samples have been analyzed to detect major anions, cations, total dissolved solids, electrical conductivity, pH, and sodium absorption ratio. The dominant water type was detected as sodium-chloride, with remarkable high concentration of sodium and chloride ions that makes it unfit for drinking purposes. Regarding irrigation use, high values of electrical conductivity (29989 to 31983 μ S/cm) and sodium absorption ratio (SAR) (58. 1 to 61) indicate a very high risk level for salinity and sodium alkali hazards, respectively. Abundance of secondary minerals such as halite and gypsum is considered to be the main reason for remarkably-high TDS values. Intensity of salt domes within the area would also facilitate solution/dissolution process of Na+ and Cl-into water column.

Dust particles have dangerous impacts on human health, the environment, and the economy. Recently dust storms, originating from Arabian countries, have increased remarkably, affecting western and central parts of Iran. HYSPLIT model and the mean monthly maps of AAI (Absorbing Aerosol Index), surface skin temperature, and top soil layer moisture from OMI (Ozone Measurement Instrument) have been used to study the origins and trajectories of suspended particles of dust storms from wind erosion during the warm period in 2010. According to HYSPLIT Model, during their move from their source areas to the downwind ones, dust particles could arrive at city of Ahvaz in different directions: (a) NW-SE (the dust particles are transported from north western region of Iraq and eastern Syria), (b) W-E (the dust particles are transported from central parts of Iraq to the south western and western parts of Iran). Also, inspecting dust emission potential with the aerosol index data from Ozone Measurement Instrument (OMI) shows a persistent intense dust activity in north western parts of Iraq and eastern Syria, hitting South-West of Iran, especially the city of Ahvaz. As a result, the main origins of dust particles in the city of Ahvaz include north west Iraq as well as east Syria.