This study aims to examine the ability of free floating aquatic plants to remove phosphorus and to predict the reduction of phosphorus from rice mill wastewater using soft computing techniques. A mesocosm study was conducted at the mill premises under normal conditions, and reliable results were obtained. Four aquatic plants, namely water hyacinth, water lettuce, salvinia, and duckweed were used for this study. The growth of all the plants was inhibited in rice mill wastewater due to low pH, high chemical oxygen demand, high conductivity, and high phosphorus concentration. Subsequently, a 1:1 ratio of mill water to tap water was used. A control was maintained to assess the aquatic plant technology. In this study, the aquatic plants reduced the total phosphorus content up to 80 % within 15 days. A comparison between three modeling techniques e.g. Artificial neural network (ANN), Random forest (RF) and M5P has been done considering the reduction rate of total phosphorus as predicted variable. In this paper, the data set has been divided in two parts, 70 % is used to train the model and residual 30 % is used for testing of the model. Artificial neural network shows promising results as compared to random forest and M5P tree modelling. The root mean square error (RMSE) for all the three models is observed as 0.0162, 0.0204 and 0.0492 for ANN, RF and M5P tree, respectively.

The present paper tries to assess different scenarios for solid waste management in Khorramabad industrial park. It uses a new hybrid method of fuzzy Rapid Impact Assessment Matrix, and proposes the Fuzzy theory, the ranking method of which is innovated so that the accuracy and flexibility of the RIAM method could be improved. Four scenarios are studied, namely open dumping, sanitary landfill, gasification, and incineration. They are then evaluated in terms of their physical/chemical, biological/ecological, social/cultural, and economic/operational effects. Afterwards, two scenarios have been selected with the aim of energy production. The evaluation of these aspects for each scenario is in accordance to the expert's judgments and field study, with the results showing that sanitary landfill has had the least undesirable effects. Hence, this approach is selected as the best scenario for waste management in the studied area. According to the obtained results, it is suggested to consider sanitary landfills as the main part of the waste management hierarchy program of the studied area. Also, it is highly recommended to use the Fuzzy RIAM technique in similar studies and to compare the results with the new ones in order to examine the accuracy of the new improved method.

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).

The present study deals with sequential extraction of fine particulate matter (PM2.5) bound trace metals in an industrial area of Firozabad, India. During the study period, daily PM2.5 concentration ranged between 73.49 μg/m3 and 113.26 μg/m3 with poor air quality index of 196.37. In the present study, Ca recorded the highest while Co had the lowest concentration among all analysed metals. Mn, Ni, Pb, Co, and Cu had high bioavailability (34.80%-65.80%) than other elements. Cd, Pb, and Cu were found to be highly enriched (EF> 289-6516) by varied anthropogenic activities. Hazard Quotient (HQ) for Ni, Mn, and Cr and Excess Lifetime Cancer Risk (ELCR) of Cr(VI) and Ni exceeded the respective safer limit (HQ>1 and ELCR≥ 10-6), thus implying serious risk to the receptors. All the metals had the highest concentration in less mobile and residual fraction except for Ni and Co, which inferred greater risk due to their high toxicity. Overall, the results present exposure and risk assessment of metal associated particles; that provides in-depth knowledge of the risk factors through inhalation exposure pathway of particles associated with industrial environment.

Plastic debris is one of the major environmental concerns for the coastal area of Brunei Darussalam. It reduces the aesthetic appeals of the beaches in the country. The current study investigates marine debris on six different beaches of Brunei Darussalam along the South China Sea. Plastic was found the most abundant among whole debris by number (90.02%) and by weight (39.12%). It was classified by size (micro (<5 mm), meso (5-20 mm), macro (21-100), and mega (>100 mm)), colour (transparent, coloured, white and black). Fourier Transform Infrared Spectroscopy (FT-IR) was used to investigate the types of plastics and additives present in it. Statistical analysis using Minitab 17 and Kruskal-Wallis test was performed for comparison of data at different study sites. All major types of plastics were found in different forms with varying quantities from which toxic chemicals may leach out during degradation. The highest abundance by the number of plastic debris was found on Muara beach with a mean value 74.428 n/m2 ± 34.33 n/m2, while the lowest abundance was found on Lumut beach 53 n/m2 ± 20.9 n/m2. The study shows beaches used for recreational facilities are likely to have more debris as compared to other beaches.

This study aimed to evaluate the concentration of heavy metals in liquid effluents and to quantify the mercury content in dental amalgam waste generated by dental clinics. Three neighbouring cities in Northeast Algeria were considered in this study (Constantine, Skikda, and Annaba). Heavy metals, such as Hg, Cu, Zn, Fe, Ni, Mn, Cr, Cd, and Pb, were analysed in wastewater and then compared with acceptable standard values. Special attention was given to mercurybecause of its dangerous effects. The results collected indicated the presence of heavy metal contamination in dental wastewater. Heavy metal concentrations were significantly high for all heavy metals and exceeded the allowed concentrations. However, Pb and Cr were shown to have acceptable concentrations. This study highlights the possible contamination of the environment by mercury and heavy metals generated by dental clinics. This study also demonstrates an order of magnitude of the concentration of these heavy metal in a large agglomeration with a population of 2.5 million people.

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 life cycle of diesel fuel in non-passenger vehicles was assessed for all registered vehicles in Qatar as of November 2017. The Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model was used as a source of normalized data to evaluate diesel fuel emissions for all non-passenger vehicle categories. This work aims at estimating the emissions from all non-passenger diesel vehicles in Qatar and evaluating the impact of the fuel life cycle assessment. The emissions of CO2, NOx, CO, SO2, VOC, black carbon (BC), organic carbon, fine particulates PM2.5, and coarse particulates PM10 were evaluated. SO2 emissions were found to be dominant during the well to pump (WTP) stage of the life cycle assessment (LCA) process, while the pump to wheel (PTW) stage was found to be dominated by CO, VOC, PM10, PM2.5, and BC emissions. NOx and organic carbon emissions were virtually the same during both stages. Total greenhouse gas emissions amounted to 5367 kt of CO2 equivalent (CO2-eq) in 2017 as compared with that in 2014 (5277 kt), the only reported value in Qatar for transportation emissions. In addition, several mitigation strategies are proposed to ensure sustainability in the transport sector and to minimize the negative impact of diesel fuel emissions in the country.