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Psychiatric drugs released by humans in wastewater have received more attention because of their potential risks for aquatic organisms. In this study, the occurrence of the two most common groups of psychiatric drugs (sedatives-hypnotics-anxiolytics and antidepressants) were evaluated in the Tehran South Municipal Wastewater Treatment Plant. All the target sedatives-hypnotics-anxiolytics (alprazolam, phenobarbital, and thioridazine) and antidepressants (fluoxetine, citalopram, sertraline, and venlafaxine) were observed in influent and secondary clarification (SC) effluent. Thioridazine (164.25 ± 218.74 ng/L) and citalopram (672.53 ± 938.56 ng/L) had the highest mean concentrations in the influent, while alprazolam (5.09 ± 2.33 ng/L) and citalopram (776.97 ± 1088.01 ng/L) had the highest concentrations in the SC effluent. The higher concentrations of the psychiatric drugs, except thioridazine, were detected in the SC effluent compared to the concentrations in the influent. The increased drugs concentrations, with negative removal efficiencies, were more distinctive in the cold season samples. Psychiatric drugs processed in the chlorination unit followed a completely different pattern compared to the drugs in the biological treatment unit. All the drugs' concentrations, except thioridazine, decreased in the chlorination unit, ranging between 27 ± 14% for alprazolam and 75 ± 10% for citalopram. However, the mean concentrations of the detected drugs were as follows: sertraline (11.96 ± 11.62 ng/L) and venlafaxine (184.94 ± 219.74 ng/L) which could cause environmental and ecological concerns.

This work reports a characterization of PAHs-PM10, including associated health effects in the largest composting facility in Tehran, Iran. Measured PAHs-PM10 stemmed primarily from petrogenic sources with mean concentrations between 231.19 to 401.25 ng m−3. The distribution pattern of PAHs (in terms of ring number) exhibited the following order when combining all sites: 3 > 4 > 5 > 6 > 2 rings. The average cumulative excess lifetime cancer risk values estimated for PAHs-PM10 surpassed the U.S. EPA limit (1 × 10−6): refining site (3.31 × 10−4) > processing site (1.75 × 10−4) > aeration site (9.81 × 10−5).

While chlorination is critical for water disinfection, a knowledge gap includes the nature of free residual chlorine (FRC) decay, which was investigated using four physical methods (SSA, SSR with a...

Solid waste components can be recycled in waste paper and cardboard sorting plants (WPCSP) through a multistep process. This work collected 15 samples every six days from each of the 9 points selected to study the processes taking place in a WPCSP (135 particulate matter samples total). Examining the concentration and size fraction of particulate matter (i.e., PM

PURPOSE: A successful hospital solid waste (HSW) management needs an accurate estimation of waste generation rates. The conventional regression methods upon increasing the number of input variables hardly can predict the HSW generation rate and require more complex modeling. In return, application of machine learning methods seems to be able to increase the power of predicting the produced wastes. METHODS: To predict the HSW, Multiple Linear Regression(MLR) and several Neuron- and Kernel-based machine learning methods were employed to analyze data from hospitals of Karaj metropolis. The number of wards, active and occupied beds, staffs and inpatients, and ownership type and activity years of hospital were defined as the model inputs. In addition, proposed models performance was evaluated based on coefficient of determination (R(2)) and Mean-Square Error (MSE). RESULTS: The performance of Neuron- and Kernel-based machine learning methods indicated that both models were satisfactory in predicting HSW. However, the better results of 0.82–0.86 for average R(2) value and 0.003–0.008 for average MSE value, indicated relative superiority of Kernel-based models compared to Neuron based (average R(2) = 0.68–0.74, average MSE = 0.009–0.023) and MLR models. Number of staffs and hospital ownership type were the most influential model variables in predicting the HSW generation rate. CONCLUSIONS: The machine learning methods could interpret the relationship between waste generation rate and model inputs, appropriately. Thus, they may play an effective role in developing cost-effective methods for suitable HSW management. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s40201-018-00324-z) contains supplementary material, which is available to authorized users.

Emissions of volatile organic compounds (VOCs) were studied during paper and cardboard recycling from a paper and cardboard solid waste recycling factory (PCSWRF). Data are summarized in this article for the following quantities for a PCSWRF during the winter in Tehran, Iran: VOC concentrations (μg m−3), the percentage of detected VOCs, exposure indices (Ei) of individual and total VOCs (TVOCs), inhalation lifetime cancer risk (LTCR) of VOCs, the hazard quotient (HQ) of VOCs, sensitivity analysis (SA) for VOC exposure in different age groups (birth to

Response surface methodology (RSM) and artificial neural network (ANN) were applied to investigate the chemical coagulation/precipitation process in the treatment of water contaminated with humic acid and processed kaolin. Accordingly, the removal efficiencies of total organic carbon (TOC), turbidity, and colour were considered to assess the effectiveness of the process. The proposed models were evaluated based on determination coefficient (R2) and Mean-Square Error (MSE). Although both models could satisfactorily interpret the correlation of targets with model inputs, i.e. pH and coagulant dosage, the ANN exhibited a slightly better fit to the process data than the RSM, based on comparison between determination coefficients (R2) and Mean-Square Error (MSE). R2, MSE, and error values of 0.990–0.999, 0.112–3.569 and 0.000–1.660% for ANN were respectively demonstrated. To investigate the predictive performance of both models, some additional experiments were subsequently carried out at obtained optimum conditions by genetic algorithm technique. TOC, colour, and turbidity removal efficiencies of 58.8, 93.0, and 100% were demonstrated at identified optimum conditions (i.e. pH 6.7 and 3 mM of ferric chloride). The results revealed a low deviation from their predicted values with maximum errors of 1.90 for RSM and 1.66 for ANN. Also, our results suggest that setting the RSM before ANN could considerably improve its prediction weaknesses.

Composting process of sewage sludge requires a preprocessing step in order to prepare the appropriate mixture of dewatered sludge (Xs) with amendment (Xa), bulking agent (Xb), and/or recycled materials (Xr). This research aimed to develop a novel mathematical model for finding an optimal mixture ratio of dewatered sludge with the aforementioned influencing elements on co-composting process. Seven feasible scenarios were presented and the best one was selected in viewpoint of technical and economic perspectives. The optimum mixture was prepared and its quality was evaluated in the terms of physical, chemical, and microbial characteristics. The optimum mixture was loaded in an aerated static pile composting reactor in order to evaluate the quality of the final compost product. If the test results were not in compliance with the USEPA standards, the model was iteratively modified to fulfill the desired objective. The model was validated using the experimental results. The mixture of Xs:Xa:Xb:Xr with a weight ratio 7.4:1.0:1.4:2.3 allowed optimal moisture content (59.8 ± 0.5%), organic matter (80.0 ± 2.6%), dry matter (40.2 ± 0.6%), C/N ratio (28.0 ± 1.6), and free air space (> 30%) across the composting pile. The final product of compost met the heavy metal and microbial requirements for land application. It can be concluded this mathematical model is a promising method for selecting the optimal amount and type of materials for preparing the initial mixture of co-composting process.

This study reports a characterization of outdoor gaseous and particulate pollutants and their associated health effects in four different urban hotspots in Tehran, Iran during winter and summer. Buses, taxis, and cars are prominent sources of toxic pollutants in Tehran. There is a significant level of exposure to emissions from diesel buses in bus terminals, especially with boarding, disembarking, and waiting. Mean concentrations (μg/m3) in summer and winter, respectively, ranged from 10 to 20.67 and 17–21 for PM1, 52.50–79.19 and 58.33–85.33 for PM2.5, 64.50–102 and 78.83–125.83 for PM7, 130.17–204.67 and 157–231.67 for PM10, 261–409.50 and 305.83–458.83 for TSP, and 372.50–418.33 vs. 351.27–373.47 for CO2 (ppm). Particulate concentrations were higher in winter, especially the first three days of the week, assisted in part by the shallower mixing layer height as compared to summer. Mean hazard quotient (HQ) values for both PM2.5 and PM10 in both seasons for bus terminals in three scenarios ranged between 0.81 and 4.96, which exceeded reference levels (1

The aim of this study is to focus exclusively on the issues of minimisation, separation, treatment and disposal of hospital solid wastes (HSW). The existing scenario for these issues has been asses...

This research aimed to develop an index known as swimming pool water quality index (SPWQI) for quantifying the water pollution potential. The index is a quantitative tool to show the data on the water quality of swimming pools consistently. It makes summarizing the complex data on water quality possible and paves the way for its communication to the general public and decision makers. In this study, the SPWQI has been formulated according to the literature review and Delphi method. According to literature review and the total judgment of the panelist (23 experts specialized in environmental health engineering), 13 physicochemical and biological parameters along with their weights were selected for inclusion in the SPWQI. The results indicated the possibility of calculating a single numerical value (i.e., SPWQI), which indicates the combined effect of significant selected parameters on water quality. In addition, biological composition (47%) had a strong preference weighting than physical and chemical parameters in evaluating the index. Next, it was attempted to implement a novel and user-friendly mathematical model for evaluating the SPWQI. Then, the model accuracy and performance was confirmed by a case study. Overall, it could be said that the assessment of SPWQI sheds light on the concurrent power of several pollutants and can help the authorities to decide upon water quality management and treatment approaches.

This study aimed to determine the methane production's potential from municipal solid wastes based on two setups; firstly, based on waste composition and secondly based on using the landfill gas em...

Urbanization generates increased amounts of solid wastes in cities and as a consequence leads to high air pollution levels. As a result of these trends, the subject of air quality management for sustainable concept of cities has received increasing attention. This work characterized volatile organic compound (VOC) emissions and health effects at different processing stages in a recycling facility for waste paper and cardboard. The highest total VOC levels were observed in the conveyor belt line one (5.23 ± 0.33 mg/m3), followed by a baling machine (1.38 ± 0.07 mg/m3), conveyor belt line two (1.34 ± 0.08 mg/m3), tipping floor line one (1.22 ± 0.07 mg/m3), and manual separation line one (1.20 ± 0.06 mg/m3). Hence, exposure to VOCs lead to high health risks in this PCSWRF, especially at the manual separation stage (HQ = 2.7–3 and lifetime cancer risks (LTCRs) = 1.11 × 10−4 - 1.03 × 10−4), and strategies such as adjustment of the factory to enclose the conveyors, designing proper ventilation and air conditioning systems, minimization of VOC-contaminated waste generation (pre-treatment), and using personal protective equipment should be considered to eliminate pollutants and to protect workers from the non-carcinogenic and carcinogenic effects.

This study characterized spatio-temporal variations in the concentration of benzene, toluene, ethylbenzene, and xylene (BTEX) compounds in the vicinity of gas and compressed natural gas (CNG) stations in Tehran, Iran. Health risk assessment (HRA) was computed using Monte Carlo simulations (MCS) for evaluating inhalation lifetime cancer risk (LTCR), the hazard quotient (HQ), and sensitivity analysis (SA) for BTEX exposure in different age groups (birth to 0.05). Factors promoting BTEX formation in the study region were fuel evaporation and gas/CNG station emissions. The LTCRs for the target compounds in the winter for different age groups and distances from the center of stations was limited to 2.11 × 10−4 to 1.82 × 10−3 and 2.30 × 10−4 to 2.01 × 10−3, respectively, which exceeded proposed values by U.S. EPA. Moreover, the HQs for BTEX for three age groups and distances were limited to between 2.89 × 10−5 and 9.33 × 10−2, which were lower than the acceptable limit (HQs

Presence of heavy metals, phenols, and cyanides is highly dangerous, and in the simultaneous presence, the effect is compounded. Chemical precipitation of such pollutants from industrial waste has gained momentum in recent years, as it promise to surpass the major drawbacks laid by the other physicochemical and biological methods and can be practically carried out in all conditions. The present work illustrates the possible removal mechanisms and interactions between organic and inorganic compounds during this process. Jar test experiments, using ferric chloride, were conducted to compare the removal efficiencies of phenol, chromium, and cyanide, either in separate or simultaneous presence. Moderate removal of Cr+6 was observed during conventional coagulation; though removal efficiencies were insignificant in the case of cyanide and phenol. The presence of cyanide ions in the solution showed an antagonistic influence on the removal of chromium. Enhanced coagulation outperformed conventional coagulation in terms of Cr+6 removal and 97% elimination was attained; however, phenol removal was slightly augmented. Although the results provided no evidence for possible removal mechanisms, electrostatic attraction was considered as the dominant removal mechanism in separate coagulation. Indeed, removal efficiencies of cyanide and chromium decreased in simultaneous presence, which can be attributed to the cyanide and Cr complexes. Higher removal efficiencies which achieved during enhanced coagulation might be due to the increase of specific surface area, aggregation rate, and settling efficiencies, as well as cyano-complexes destruction. The results of Mann–Whitney test revealed a significant difference (pvalue ⩽ 0.05) between separate and simultaneous removal performances of phenol and chromium.

Background and objectives: phenol, cyanide, and chromium (VI) are toxic pollutants. They can be discharged from different industries simultaneously such as iron and steel industry, coal mining, automobile manufacturing of parts. Presence of these pollutants in water and wastewater is a serious hazard and these substances lead to undesirable effects on both the environment and human. Thus, control of these contaminants is essential for human health and environment. The main objective of this study was to assess the efficiency of Fenton process for simultaneous removal of phenol, cyanide, and chromium (VI) from synthetic wastewater. Materials and methods: This study is an experimental study in lab scale that was carried out in a batch system. Variations of this study including pH, chemicals concentration (Fe2+ and H2O2 and molar ratio Fe2+/H2O2), and reaction time were investigated. Cyanide, phenol, and total chromium were determined respectively by colorimetric method (spectrophotometer), high-per...

This work aimed to remove hexavalent chromium and three treatment schemes were examined based on a laboratory scale design: (a) Fenton process, (b) precipitation process, and (c) Fenton process followed by precipitation process. Variations of this study including pH, Fenton and precipitation reagents (molar ratio of Fe2+/H2O2 and FeCl3), contact time, and initial concentration of chromium were investigated. The results showed that about 98% of Cr+6 is removed by the coagulation property of the Fenton process, and the ideal conditions for its removal included Cr+6 = 10 mg/L, pH = 4, molar ratio Fe2+/H2O2 = 2.4 with a time duration of 30 min. Maximal removal efficiency of Cr+6 in the precipitation process was equivalent to 97% in the following optimum conditions: Cr+6 = 5 mg/L, pH = 7, FeCl3 = 0.7 g/L and deposition time of 20 min. Combination of these two methods can remove greater concentrations of chromium (15 mg/L) to about 99.99%. Therefore, removal of Cr+6 by the combined Fenton and precipitation process was better than any of the methods alone (Kruskal-Wallis, P value ≤0.05). Consequently, the Fenton process followed by precipitation process can be considered as a suitable process for Cr+6 removal to achieve environmental standards.