In this paper, human hair, as a waste material, was utilized in order to prepare keratin nanoparticles. The characterization of keratin nanoparticles was performed applying Transmission electron microscopy (TEM), Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR) and X-Ray diffraction (XRD). The average diameter of keratin nanoparticles was found to be 63.7 nm, using particle size analyzer. Subsequently, the keratin nanoparticles were employed for Cr (VI) ions adsorption. The batch experiment was carried out to find the optimum conditions; i.e. contact time, pH, adsorbent dose and initial concentration of Cr (VI) ions. The adsorption capacity was extremely pH-dependent, and the maximum adsorption of Cr (VI) happened in the acidic pH range. The results demonstrated that the maximum adsorption capacity, obtained in acidic pH, was 161.29 mg/g. The equilibrium data were well fitted by Freundlich isotherm. The kinetic studies were performed with the Lagergren’s first-order, Pseudo-second order, Elovich, and Intra-particle diffusion models. In this sense, in order to describe kinetic data, we came to this understanding that Pseudo-second order model was the best choice. The thermodynamic parameters of the adsorption process indicated that the Cr (VI) adsorption on keratin nanoparticles is endothermic and spontaneous.

This paper is the first to report on the role of a wastewater treatment plant (WWTP) in Sari, as a source of microplastics (MPs) in the Caspian Sea. Composite 270-liter/24-hour samples were taken the treated effluent of the WWTP in winter and spring, two seasons with different levels of human activity. The effluent contained 380±52.5 and 423±44.9 MPs/m3 in winter and spring, respectively, with the total numbers of MPs/m3 not differing between the two seasons. The dominant type of MPs in the effluent was microfibers with 237±68.7 and 328±33.4 per m3 in winter and spring, respectively. In both seasons, fiber sizes of

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.

In order to assess the environmental impact of soil polluted with trace metals, representative soils were collected surrounding the abandoned Pb–Zn mine mill (SM soils), and the new temporary ore storage site (SS soils), which are located in the vicinity of Medina (Aures), North-east of Algeria. Total digestion has been used to determine the total content of Zinc, Copper, Lead, Cadmium, and Arsenic, then it was analysed by inductively coupled plasma atomic emission spectrometry (ICP-AES). The sequential extraction Tessier scheme was also used to extract the chemical forms of Zn, Cu, and Pb, and their concentrations in each fraction were analyzed by atomic absorption spectrometry. Lead was the most abundant trace metals, its concentration in mg.kg-1 ranged between (67.20 – 46000), followed by Zinc (26 - 1853), Copper (32 – 495), Arsenic (8 – 116), and Cadmium (0.3 - 7.30). Sequential extraction shows that Zinc was mainly associated with reducible and residual fractions. Copper was bound predominantly with the minerals in the residual fraction, followed by the organic matter. Lead was bound mainly with carbonate fraction in SM soils, while Pb in the SM soils was mainly associated with the reducible fraction. The Pb, Zn, Cu mobility factor was significantly higher in SM soils than in SS soils. These results indicate that anthropic activities related to ore concentration and mining process lead to increased concentration of trace metals in surrounding soils, hence their mobility and bioavailability, this consists a potential risk to the environment and biota.

Bed Sediment is a dynamic and complex material that plays an important role in the aquatic ecosystems and provides habitat from a highly various community of organisms. To address the major issue, this study, which its substantive subject done for the first time in Iran, aimed to assess the current status of Darreh-rood river's health and quality using SOD rate and its associated factors including Texture, fine-PSD, TOC and TP of bed sediments along with some basic field parameters of river-water. All required samples were collected from 10 sampling points in due course. SOD data with regard to related factors were calculated and analyzed. The rates of SOD ranged from 0.69 to 1.57 g O2/m2/day. Moreover, this index was classified in varied quality domains. Afterwards, a predictive equation was determined among SOD rate and its associated parameters using MATLAB software. Finally, the Results showed that the river quality and health suitability in research area are in categories slightly clean and slightly degraded, in targeted zones during the study period. Also, the increase in TOC and TP concentrations together with a decrease in sediment particle size was led to an increase in SOD-rate accordingly. In conclusion, the consequences of this study under Survivability-based Adaptive Management (SAM) perspective can be used as a rapid diagnostic tool to support water policy decision-makers and other stakeholders to promote the best practices for protecting the health conditions of riverine systems, focusing on selecting the appropriate points for discharging the wastewaters into the receiving water-bodies.

To support the fulfillment of Sweden’s targets in term of climate change and economic growth, we need to do a distinct study to show the Environmental Kuznets Curve (EKC) pattern in different sector of the economy, as the GDP allocation, energy intensities, GHG emission, and technological development are different between sectors. This kind of study helps to figure out how the different sectors contribute to climate change and could appoint more particular and effective environment-energy policies. For this aim, we analyzed the existence of the EKC by implementing the ARDL Bound test approach in the whole and individual sectors of Sweden’s economy throughout 1990-2019. Our results indicated the contribution of a particular sector on total GHG emissions per capita. Results of the whole economy confirmed the EEKC hypothesis with a turning point in 1996, in which the AFF sector, unlike industry and service, had increased GHG emissions. Disaggregated sectoral analysis showed various results. The industry sector had efficient energy improvement. Policymakers should pay attention to AFF’s GHG emissions, as different sources of energy consumption had not impressive impact in both the short and long term. Also, effective fossil-related policies are necessary for the service sector due to the main contribution to transportation.

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.

Safe and clean water is essential for all living beings. Consumption of polluted water which is contaminated with iron may cause serious health implications. Therefore, removal of Fe3+ from wastewater is prerequisite for further uses. The present study intended to prepare activated charcoal (AC) from Borassus flabellifer male flower (BF) for the removal of Fe3+ ions from wastewater in a cost effective way. BFAC was produced based on carbonization method. Surface morphology and elemental composition were investigated by Scanning Electron Microscopy and Energy Dispersive X-Ray Spectroscopy. Additionally surface charge was determined by iodine number and zero point charge calculation. Batch adsorption studies were monitored using UV-visible spectroscopy. The obtain results showed a maximum adsorption at pH 8 with 0.3g adsorbent dosage at 50ppm initial Fe3+ ion concentration for 130 min contact time. The analysis of adsorption isotherm was in good agreement with both Langmuir and Freundlich adsorption isotherms. The Fe3+ removal method was found to be controlled by 1st order kinetics mechanism. However, the production cost was much cheaper and the removal performance was comparatively better than other commercial charcoals. Hence, BFAC could be used as a commercial charcoal in rural area of Bangladesh for purification of waste water.

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.