The main purpose of this research is to determine the generation quantity of each generator in a power system. In this way, not only will the electricity demanded by the system be supplied, but the cost of fuel along with the level of pollution can be minimized. Obviously, calculation of the optimal layout of power plants with the aim of minimizing fuel costs and pollutants level contributes to sustainable socio-economic development. For this purpose, modeling a multi-objective decision making framework by means of the weighting method makes it possible to attain the mentioned goals. After modeling the goals and constraints of the power system, the problem associated with economic-environmental load dispatch with the Institute of Electrical and Electronics Engineers 30-Bus data is optimized by means of the Lagrange approach. Moreover, the sensitivity analysis in connection with the weight of short-term costs is conducted to determine the final point of the system usage. Results show that if the importance coefficient of the fuel cost reduction is 1 (W=1), the economic and environmental load dispatch will pose some problems for the economic load dispatch. In contrast, if the importance coefficient of the reducing fuel cost is zero (W=0), the economic and environmental load dispatch will become problematic for environmental load dispatch. Incidentally, the trade off curve of the fuel cost and the pollutant amount involves the functional information for the system operator. The current research is mainly innovative in its use of a method to reduce fuel consumption and environmental impacts on emission at optimization process. This can, in turn, lead to generation of sustainable energy.

Arsenic (As) contamination in the groundwater of Bangladesh is one of the major public health concerns. It has become a challenge to remove As from groundwater and a great deal of efforts employed in this regards with limited success. Cerium oxide is one of the important medias of arsenic removal techniques. Nine units of cerium-based arsenic technology were tested with seven different well waters in five hydro-geological areas in Bangladesh. Interestingly, the same technology showed variable results in terms of As removal performance from well water. Therefore, this study aimed to investigate the reasons behind the variant performance of the As removal technology. The studied wells were contaminated with a range of 283 to 873 μg/L of arsenic, 0.35 to 10.4 mg/L of iron, 0.29 to 6.83 mg/L of phosphate, 32.5 to 49.5 mg/L of silicate, 0.08 to 0.25 mg/L of sulfate and pH range was 7.11 to 7.65. The cerium-based As removal technology consistently produced As safe water from three wells containing more than 80% As (III) of total arsenic (As) and >3 mg/L of iron and reduced As concentration to below 50 μg/L consistently but failed at other four wells containing less than 75% As (III) of tAs and

Defined as any substance in the air that may harm humans, animals, vegetation, and materials, air pollution poses a great danger to human health. It has turned into a worldwide problem as well as a huge environmental risk. Recent years have witnessed the increase of air pollution in many cities around the world. Similarly, it has become a big problem in Iran. Although ground-level monitoring can provide accurate PM2.5 measurements, it has limited spatial coverage and resolution. As a result, Satellite Remote Sensing (RS) has emerged as an approach to estimate ground-level ambient air pollution, making it possible to monitor atmospheric particulate matters continuously and have a spatial coverage of them. Recent studies show a high correlation between ground level PM2.5, estimated by RS on the one hand, and measurements, collected at regulatory monitoring sites on the other. As such, the present study addresses the relation between air pollution and satellite images. For so doing, it derives RS estimates, using satellite measurements from Landsat satellite images. Monitoring data is the daily concentration of PM2.5 contaminants, obtained from air pollution stations. The relation between the concentration of pollutants and the values of various bands of Landsat satellite images is examined through 19 regression models. Among them, the Ensembles Bagged Trees has the lowest Root-Mean-Square Error (RMSE), equal to 21.88. Results show that this model can be used to estimate PM2.5 contaminants, based on Landsat satellite images.

Arsenic is a highly toxic element for human beings, which is generally found in groundwater. Dissolved Arsenic in water can be seen as As+3 and As+5 states. The adsorption process is one of the available methods to remove Arsenic from aqueous solutions. Thus, this papers aims at removing Arsenic (III) from aqueous solutions through adsorption on iron oxide granules. The relation among four independent variables, namely the initial concentration of Arsenic (III), pH, adsorbent dose, and contact time have been investigated through Response Surface Methodology. Design-Expert software and Central Composite Design method have been used to design and analyze the experiments and results. Also, SEM and FTIR analysis have been conducted to characterize the absorbent morphology. The optimum initial concentration of Arsenic (III), pH, contact time, and adsorbent dosage are 30ppm, 5, 49.99min, and 8g/l, respectively. Under these optimum conditions, the Arsenic (III) removal efficiency is 67%. The predicted 2FI model shows the highest Arsenic removal coefficient (R2=0.887).

Immobilizing of zero-valent iron in mono- and bi-metallic systems on the bentonite clay surface as new nanocatalyst were synthesized and used to degrade model acidic dyes from aqueous media. The Fourier-transform infrared spectroscopy, scanning electron microscopy-energy dispersive X-ray spectroscopy, transmission electron microscopy, X-ray diffraction, and Brunauer-Emmett-Teller analysis were used to characterize the synthesized nanocomposites, which demonstrated successful loading of nanoscale Fe-Cu bi-metallic onto bentonite support. Different variables controlling the congo red, methyl orange and methyl red dyes degradation using zero-valent iron based bimetallic nanoparticle on the bentonite clay surface as new nanocatalyst were concurrently optimized through an experimental design. Basic evaluations proved the nanocatalyst quantity, medium pH, initial dye concentration, and contact time as the most important variables influencing the degradation phenomenon and hence a response surface methodology based on the central composite design was conducted to determine the relations between the variables and the degradation efficiencies. The statistical factors (e.g. R2 and F-value) of the derived models were considered. Using response surface plots obtained through the models, the effects of the variables on the degradation efficiencies for each dye were assessed. Also, the Nelder-Mead non-linear optimizations were performed and the optimal degradation efficiencies at a 95% confidence level were determined which were found to comply with the respective experimental response values.

Heavy metal accumulation in aquatic organisms has been an important issue due to environmental pollution resulting from anthropogenic activities. In this study, Cr, Mn, Fe, Cu, and Zn in the selected fish species (Mullus barbatus, Solea solea, and Siganus rivulatus) from three consecutive bays (İskenderun, Mersin, and Antalya from North-Eastern Mediterranean Sea) were considered to provide some information on heavy metal accumulation level and assessment of their health risk on both general and fishermen populations. There were some significant differences inter- and intra- species/ tissues/bays. The stability in heavy metal accumulation in fish tissues varied and the most stable tissue for Cr, Cu, Fe, Mn and Zn were determined as skin, muscle, liver, liver and, muscle, respectively. In general, the lowest heavy metal values were observed in the fish muscle. The Target Hazard Quotients (THQ) and Total Target Hazard Quotients (TTHQ) values based on muscle were not exceeded 1.00. Therefore, these results suggest that both general and fishermen populations are not subjected to the significant potential health risk from those bays.

Butachlor (BUT) is a chloroacetanilide herbicide widely applied to rice paddies to control annual grass and broad-leaf weeds. A BUT-degrading bacterial strain (PK) was isolated from paddy soils. Biochemical and 16S rRNA sequencing characteristics confirmed the strain as Pseudomonas aeruginosa (99% resemblance). The isolate dissipated BUT (100 μg/mL) in an M9 liquid medium with a rate of 0.5 ± 0.03 day-1 and DT50 and DT90 of 1.38 ± 0.10 days and 4.58 ± 0.32 days, respectively. Soil dissipation of BUT was investigated under flooded conditions. In sterile soils, the isolate increased the dissipation of BUT (200 μg/g) (DT50 = 12.38 ± 1.83 days, DT90 = 41.12 ± 6.09 days, k = 0.06 ± 0.01 day-1) compared to sterile non-inoculated samples (DT50 = 26.87 ± 2.82 days, DT90 = 89.25 ± 9.36 days, k = 0.03 ± 0.00 day-1). In non-inoculated non-sterile soil experiments, the dissipation of BUT was faster (DT50 = 15.17 ± 2.11 days, DT90 = 50.38 ± 7.02 days, k = 0.05 ± 0.00 day-1) compared to non-inoculated sterile ones, and inoculating the isolate accelerated the removal of BUT in non-sterile soils significantly (DT50 = 8.03 ± 1.20 days, DT90 = 26.68 ± 3.97 days, k = 0.09 ± 0.01 day-1). BUT inhibited soil respiration (SR) initially for 5 days, followed by an increase until day 20. The increase in SR was more pronounced in the co-presence of BUT and the isolate. The results of this research suggest P. aeruginosa PK as a suitable candidate for BUT bioremediation.

Fluoride is one of the parameters which is non-degradable and naturally occurring inorganic anion found in many natural streams, lakes, and groundwater. Serious problems are faced in several parts of India due to the high consumption of fluoride through drinking water. These may cause dental and skeletal fluorosis to humans. This study aims to examine the level of fluoride in both Bharalu river water and groundwater within Guwahati city, Assam, India, and also to analyze the impact of fluoride reach river water on the groundwater aquifer adjacent to the river. From the investigation, it has been observed that the concentration of fluoride varies from 0.02 to 3.73 mg/l in river water and 0.04 to 4.7 mg/l in the case of groundwater. The statistical analysis shows that there is a strong correlation between the fluoride concentration of river water and groundwater. This indicates that the groundwater might have contaminated by the polluted river water.

Air quality in greater Algiers, in Algeria was assessed analyzing aerosol particulate matter (PM10 and PM2.5) at a site influenced by heavy road traffic. Particulate matters were collected using a Gent sampler to characterize the atmospheric aerosol of Algiers. An Energy dispersive X ray spectrometer (EDXRF) was used to determine the heavy metal concentrations in the PM2.5 and PM10 size fractions. Principal Component analysis and Enrichment factor were used to identify the major sources of air pollutants for PM10 fraction in the studied area. Backward trajectories were calculated in order to identify potential distant sources that contribute to particulate pollution in our site. Significant concentrations of PM 2.5 and PM10 as well as associated heavy metals have been documented. The mean concentrations of heavy metals contained in PM10 and PM2.5 were, in descending order, Fe>Zn>Ni>Pb>Mn>Co>Cr; Pb>Mn>Co>Fe>Zn>Ni>Cr respectively. The contribution of road traffic to the levels of fine (PM2.5), and coarse (PM10) particles were studied.

The present study tries to investigate the effect of composting process on some properties and heavy metals status of two municipal sewage sludge (MSS) as affected by three different organic bulking agents (BAs) at three levels (10%, 25%, and 45% V/V). According to the results, the composting process could reduce the fecal coliform to class A, a reduction more obvious in treatments with BAs than produced composts without them. Changes in the chemical properties of the composts vary according to the type of MSS and Bas. Based on the compost quality standard, most of the produced samples are classified in compost-class II. Examination of the total form of three heavy metals (HMs: Zn, Ni, Fe) of both MSS shows that composting process without BAs increases the HMs total concentration, but using of BAs have not been clear trends. In the contrary, BAs application reduced the available form of Fe and Ni, but increased the Zn available form. Examination of chemical forms of each studied HMs also shows that the composting process reduces the Ni and Fe mobility factor, but increases that of Zn. Generally, while, prepared composts can classify into the compost-class II, based on their properties, the high concentration of total Zn above the standard limit makes it extremely restrictive to be used as class II compost. However, according to EPA regulations, the composts with this concentration of Zn can be used as a relatively safe organic material on agricultural land.