Mitigation of atmospheric pollution has been a topic of concern over the past decades. In this study, tree rings have been used to reconstruct past climates as well as to assess the effects of recent climatic and environmental changes on tree growth. Vehicular emission is one of the major sources of pollutants in the atmosphere and this study focused on the Haatso-Atomic road which over the years has been a spot for heavy vehicular traffic. Swietenia mahagoni (Mahogany) tree was logged and the rings counted and age determined to be 61 years spanning from 1957 to 2018. X-ray fluorescence (XRF) was used to investigate the presence of the following heavy metals. Heavy metals (Cu, Mn, Zn, Pb, Cd and Ni) which ranged from (3.15—9.84mg/kg), (2.58 – 5.49 mg/kg), (8.18 – 15.78mg/kg), (0.12—0.60 mg/kg), (0.01—0.09 mg/kg) and (0.10 – 0.99 mg/kg) respectively, from vehicular emissions were determined for annual rings spanning from 1957 to 2018 and surprisingly an increasing trend was observed with some the heavy metals exceeding WHO guidelines. Tree growth rates were calculated through ring width measurements and related to annual precipitation data spanning over the sampling period. It was observed that wet seasons correlate with high growth rates of trees while low precipitations seasons related to low or no growth rate of trees.

The changes in diatom assemblages along an urban-to-rural gradient were characterized to assess the ecological status of the Sai Gon River, Vietnam. Diatoms and physico-chemical variables were measured at 10 stations during dry and rainy season. One-way ANOVA showed that diatom metrics and physicochemical variables were significantly different (p < 0.05) between the upper course sites and both the middle- and the lower sites. However, no significant differences were observed between the middle course sites and the lower course sites. Achnanthidium minutissimum and A. exigua were potential indicators of low nutrient in the upper course sites; Melosira granulata and Navicula viridula were preferred moderately eutrophic water in the middle course sites; while Navicula cryptocephala and Nitzschia palea were tolerant to very heavy pollution and dominant in the lower course sites. Canonical correlation analysis (CCA) results showed that concentration of TSS, TN, TP, BOD5 and COD were the most important factors in structuring benthic diatom communities in the Sai Gon River. The results of this study indicated that diatom community was sensitive to changes in urban condition and could be used as an indicator of urbanization.

In this work, the backward Bayesian multiple linear regression (BBMLR) as a new approach is presented to predict the adsorption efficiency (AE) of Cd(II) ions by ostrich bone char (OBC) in the fixed bed adsorption with four operational variables consisting of pH (2-9), inlet Cd(II) concentration (Co= 25-100 mg/L), bed depth (h= 3-9 cm) and feed flow rate (Q= 0.5-30 mL/min). The performance of the BBMLR was evaluated using the coefficient of determination (R2), normalized root means square error (NRMSE) and mean residual error (MRE). The AE of Cd(II) ions by OBC increased from 42.3% to 99.9% when pH was increased from 2 to 9 with h of 6 cm and Q of 1.5 mL min-1. It was found that the AE dramatically increased from 70.5% to 99.9% with decreasing Q from 30 to 0.5 mL min-1 at pH of 7 and h of 6 cm. At pH= 7 and Q= 1.5 mL min-1, the AE increased from 71.9% to 100% when h increased from 3 to 9 cm. The BBMLR model presented excellent performance (NRMSE=6.69%) for predicting Cd(II) removal in a continuous adsorption system, although it gave a slight underestimation (approximately 3.52%). The BBMLR is more sensitive to the pH, followed by h and Q, while the Co has no significant effect on it. This research displays that OBC has great potential as an eco-friendly low-cost adsorbent in removing Cd(II) ions from the contaminated waters.

This study was conducted to identify and classify the lichens; determine the diversity index and richness of lichens. A total of 36 species belonging to six genera under three families was identified. Lichen species were mostly found at moderate high altitudinal range with an elevation of 1,131 meters above sea level and open areas where they received adequate sunlight with high moisture and humidity contents. Diversity, composition and altitudinal distribution of lichens was evaluated in Mt. Kitanglad Range, Kaatauan, Lantapan, Bukidnon, Philippines a wet forest type forest. The maximum species richness was reported on Usnea rubicunda Stirt. The abiotic factors were shown to be essential in adapting the relative abundance of lichens for it is capable to survive in the range of light levels, it appears that drier and lighter conditions competitively favored. Additionally, lichen diversity is dependent on the climatic and environmental conditions which makes them as an excellent biological indicators of ecosystem changes in the forests of Mindanao Island, Philippines.

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.