The pomegranate (Punica granatum) fruit peel exposed to mixture air pollutants were collected from two sites with different air quality around the industrial area of Gabes city, Tunisia. The first site presented the ‘Polluted site’, which is situated in the oasis close to the industrial area. While, the second site referred to the ‘Control site’ located at 37 km from the industrial area. Using HPLC ES-MS, 21 phenols were identified and quantified in methanol extract from pomegranate fruit peel. The results showed that various phytochemical substances, including phenols acids and flavonoids, were identified and quantified in the peel extract. The polyphenols content and the flavonoids contents in peel obtained from polluted site were higher than that collected from the control site. The concentrations of the identified polyphenols were ranged between 0.39 and 7803.68 mg/ kg DW. The stimulation of some free phenolic compounds such syringic acid, transfrulic acid, epicatechin, rutin and quercetin was enregistred only in peel collected from contaminated environment. The quali-qualitative changes between sites are probably related to the difference in the air quality. The increase of polyphenols could be implicated during adaptive mechanisms under air pollution. Phenolic composition changes in Punica granatum peel could be also suggested as useful approach air pollution monitoring.

In this study, water from three urban wetlands of Gurugram – Sultanpur (WS), Damdama (WD), and Basai (WB), was studied for various physicochemical parameters to assess their suitability for the healthy survival of fishes and the results were compared with the limits of these parameters for fish farming. The parameters studied were colour, temperature, pH, alkalinity, hardness, Ca2+- Mg2+ ratio, NO3-, Cl-, SO42-, PO43-, and heavy metals (Fe, Mn, Cr, Cu, Zn, Ni and Pb). The results of the study indicate the majority of studied parameters are beyond the desirable limits in WB; thus, water is most unsuitable for fishes in WB. WB is unsuitable for parameters: colour, alkalinity, hardness, Ca -Mg ratio, NO3-, Cl-, SO42-, PO43-, Cr, Cu, Fe, Mn, Ni and Zn. WS needs consideration for temperature, NO3-, Cu, Ni and Zn, whereas WD needs improvement in temperature, TDS, NO3-, Cr, Cu, Fe, Mn, Ni and Zn concentration for better fish growth. Most of the parameters are high in summer as compared to winter, which is due to the dilution after rainfall. Hence, we recommend timely action for effective measures to improve the water quality of wetlands and their regular monitoring for improved fish habitat.

This work aims to assess the Water Quality Index (WQI) of the groundwater-based public drinking water supply system of Kamrup District (Rural) of Assam, India. For assessing WQI, water samples have been collected, both raw water and treated water, from seventy-eight public drinking water supply projects over the district for comprehensive physicochemical analysis. The WQI was calculated based on the weightage derived from the literature survey and based on the doctors’ weightage. The derived WQI showed that the water quality falls from poor to very poor quality. However, the concentration of the water quality parameters except Iron, Fluoride, and Manganese are within the permissible limit in all the water supply projects. It shows that the WQI calculated based on the weightage derived, as stated above, is not displaying the actual water quality of the supplied water. As such, a modified method is proposed to calculate the WQI of the supplied water considering the permissible limit of the parameters in deriving the weightage for the parameters. The WQI values calculated using the modified method falls in the range of good water quality to poor water quality and shows the true water quality of the supplied water. The statistical analysis of the water quality parameters and WQI shows that the WQI has a very high correlation with Manganese with a coefficient of correlation value of 0.86, followed by 0.4 with Chloride and 0.34 with Fluoride.

Water resource management requires simple tools to enable managers to make decisions. This is the case for water quality indices that provide access to clear, synthetic and well-targeted information. In this study, we have chosen two indices based on two different approaches, the Microbiological Quality Index (MQI), which is determined from bacteriological analyses of water, and the Water Quality Index (WQI), which is based on physicochemical parameters. The Water Quality Index (WQI) shows a longitudinal upstream-downstream variation and ranges from is between five (5) (Null Faecal Contamination) at sampling point P1 and 3.4 (Moderate Fecal Contamination) at P2. The Water Quality Index (WQI) ranges from a low of 14.08 (excellent water quality) at the P1 level to a high of 93.05 at the P2 level (poor water quality) receiving wastewater discharges. The WQI results for P3 and P4, show that the water is of good quality (downstream of P2), which shows the degree of self-purification of the Oum Er Rabia River, regardless of the sampling period. Finally, the results of the MQI corroborate those obtained with the WQI for the water quality of the different sampling points.

The critical parameters namely initial pH, time and current density largely impact the process efficiency of electrocoagulation (EC). Few works have been done on observing the interaction of these critical parameters and the possible combined effect on the overall pollutant removal efficiency. Therefore, the knowledge of the combined effect of critical parameter interaction would enhance the optimization of EC parameters to attain maximum efficiency with limited resources. Using aluminium electrodes with interelectrode distance of 10 mm on synthetic wastewater, representing biotreated palm oil mill effluent (BPOME), with a set range of initial pH, current density, and time of 3-8, 40-160 mA/cm2 and 15 to 60 minutes, respectively, the effect of the three critical variables was investigated. The optimum Chemical Oxygen Demand (COD) removal of 71.5% was determined at pH 6, current density of 160 mA/cm2 (with current 1.75 A) at EC time of 15 minutes. The experiment was validated with real BPOME, resulting in the removal efficiency of 60.7 % COD, 99.91 % turbidity, 100 % total suspended solids (TSS) and 95.7 % colour. Removal of a large quantity of pollutants in a time span of 15 minutes with optimized parameters in EC is notable for a wastewater treatment alternative that requires no extensive use of chemicals. The interaction of parameters observed in this study indicated a synergistic contribution of initial pH and current density in removing maximum wastewater COD in 15 minutes of EC.

Today, indoor air pollution is a major concern. So far, many quantitative and qualitative studies have been conducted on particulate matter pollution in closed environments, but not much research has been done to measure air pollution in subway station. In this study, we have investigated the concentrations of PM10, PM2.5 and TSP particles in 12 underground stations on the oldest and main Tehran metro line, in two seasons, autumn and spring. For sampling suspended particles, we have used a portable direct reading device for monitoring suspended-particles (HAZDUST EPMA5000). We also used Pair T- test to compare the particle concentrations in different modes of the ventilation system (on, off, and inlet air) and Three-way variance analyze. According to the results, the mean concentrations of PM2.5-PM10 - TSP values in line-1 on the station platforms are significantly higher in spring than in autumn, off state of the ventilation system than on state of the ventilation system (P <0.001). Also, the concentration of particles measured in the air of subway stations is higher in the off state of ventilation systems, compared to Inlet air to stations (P<0.001). There is a correlation between concentration of particles measured in different sampling season, condition of the ventilation mode (on, off, inlet air) (P<0.001). Improving the efficiency of ventilation systems (equipped with a suitable filter) and fan in stations is suggested as one of the factors to reduce the concentration of particles, especially in spring.

In this study, the removal of nitrogen from effluent of ammonia plant by Chlorella vulgaris and Spirulina platensis was investigated. For this purpose, microalgae were cultivated in three diluting percentage of the wastewater (1, 3, and 5%) at 29±1 ◦C and light intensity at surface of culture were adjusted to 150 µmol photon / (m2. s). The results showed that Spirulina platensis is more capable than Chlorella vulgaris to grow in high levels of total nitrogen concentration. Also, maximum biomass production rate happened in 1% diluted samples for Chlorella vulgaris and 3% for Spirulina platensis. Furthermore, Chlorella vulgaris reduce total nitrogen concentration up to 55%. This value for Spirulina platensis was about 96%. However, for both species the removal of nitrogen in 1% diluted wastewater was maximum. According to the results of diluted wastewater of ammonia plant, it is a suitable culture medium for microalgae and it can be used to remove the nitrogen before entering the wastewater in nature.

Air pollution is considered a global concern due to its impacts on human life and the urban environment. Therefore, precise modeling techniques are necessary to predict air quality in congested areas such as megacities. Recently, machine learning algorithms such as Neural Networks show significant possibilities in air quality studies. This paper proposes a model to estimate air quality in a congested urban area in Baghdad city using Artificial Neural Network (ANN) algorithm and Geospatial Information System (GIS) techniques. Carbon Monoxide (CO) gas is selected as the main air pollutant. The model parameters involve; CO samples, traffic flow, weather data, and land use information collected in the field. The proposed model is implemented in Matlab environment and the results are processed after entering ArcGIS software. Using its spatial analysis tools, the outputs are presented as a map. The final findings indicate the highest value of CO emissions that reached 34 ppm during the daytime. The most polluted areas are located near congested roads and industrial locations in comparison with residential areas. The proposed model is validated by using actual values that are collected from the field, where the model's accuracy is 79%. The proposed model showed feasibility and applicability in a congested urban area due to the integration between the machine learning algorithm and GIS modeling. Therefore, the proposed model in this research can be used as a supportive model for decision making of city managers.

Mineralogy studies can help understand the interactions of geographical, environmental, and geological factors. Considering frequent occurrence of urinary tract stones in the south and west of Iran, the present paper examines trace elements, like heavy metals, in 53 urine stone samples collected from patients in Lorestan Province. It investigates the mineralogy of the stones, using X-ray diffraction. The samples are then classified into five mineral groups (calcium oxalate, urate, cysteine, calcium oxalate-urate, and calcium oxalate/phosphate). Results from this analysis are confirmed by SEM images, showing the crystalline form of the mineral phases. The microscopic studies show that only the mineral group of calcium oxalate (whewellite) could be detected in thin sections, prepared from urinary tract stone samples. The main and trace elements in each group are determined through ICP-MS method with the results showing that calcium is the most abundant substance in urinary tract stones, compared to other elements. This is caused by the role of calcium in most basic functions of cell metabolism. The correlation between magnesium and strontium is 0.64, originated from the placement of high amounts of strontium in calcium oxalate minerals. The positive correlation between sodium and calcium also indicates that sodium is replaced by calcium due to the similarity of the ionic radius in the crystal structure. Results from this study can help us find the causes behind the frequent occurrence of urinary tract stones in Lorestan Province.

The Air Pollution Tolerance index (APTI) of six plants located within Ikpoba Okha gas flaring site in Oredo Local Government Area of Edo State, Nigeria during wet and dry seasons were assessed. Plant samples for this research work were randomly collected from the vicinity of the flaring site. Six (6) sample of each plant was used for laboratory analysis. The plant parameters assessed include relative water content (RWC), the ascorbic acid content (AAC), total leaf chlorophyll (TLC) and pH extract of the leaves and were used to compute the Air pollution tolerance indices (APTI). Based on the analyzed result, the RWC in Drypetes leonensis, Ficus exasperata Vahl, Chromolaena odorata (Linn) and Gmelina arborea Roxb. ex Smith   species in dry season were higher than those in wet season. Icacina tricantha showed a relatively high level of acidity when compared to others. A. boonei De Wild has the highest ascorbic acid content in the leaves in both seasons. The highest level of chlorophyll contents was recorded in the dry season with Drypetes leonensis having the highest, followed by Icacina trichantha. There was no statistically significant difference in pH and total chlorophyll contents between samples collected in wet and dry season; however, there were significant difference observed in ascorbic acid and RWC in both seasons. APTI in wet and dry season showed a statistically significant difference. This study recommends planting of tolerant species that can acts as bio-indicators especially in gas flaring stations in Nigeria.