Pollution
Volume:7 Issue: 2, Spring 2021

The present study deals with groundwater pollution in multilayer aquifer. The model is based on decomposition of finite layers in semi-infinite groundwater reservoir. A constant pollutant source is injected at the input boundary of the uppermost layer (UML) of the landfill. At the intermediate inlet boundary, some average value for the longitudinal exchange of the input source concentration in each sub-layer is considered from the previous layer. Initially, the aquifer is not solute free in each sub layer that means some constant background contaminant concentration exists. In each sub layer, concentration gradient is assumed to be zero at the extreme boundary. The linear sorption and first orders decay terms are considered to model the groundwater pollution in multilayer aquifer. The Laplace transform technique is adopted to solve one-dimensional (1D) advection-dispersion equation (ADE). This approach is helpful to understand the solute migration in finite sub layers. The results are elucidated for the different time periods to examine the peak of pollutant concentration level in geological formations.

With growing global warming issues, the association between technological innovation and environmental pollution has created significant debate in recent years. This paper examines the long-run and causal impact of technological innovation, economic growth, and renewable energy on consumption-based carbon emissions in Japan. The study utilized quarterly data spanning between 1990 and 2015. The study utilized recent econometrics techniques such as Maki co-integration, ARDL bunds test, FMOLS, DOLS, and frequency domain causality techniques. To the author's understanding, no prior studies have been conducted in Japan using consumption-based carbon emissions as a proxy of environmental degradation. Thus, this empirical analysis contributes to the literature. The findings from the ARDL bounds and Maki co-integration tests revealed evidence of co-integration among the series. The results of FMOLS and DOLS reveal that both renewable energy and technological innovation improve the environmental quality, while economic growth harms the quality of the environment. The results of the frequency-domain causality technique reveal that technological innovation, renewable energy, and economic growth can significantly predict consumption-based carbon emissions in Japan. Based on these outcomes, we suggested that Japan's government should be careful when formulating policies that trigger growth, which will have a detrimental impact on the environmental quality. Our empirical outcome also revealed that any policy that encourages renewable energy should be encouraged since it enhances environmental quality.

Energy recovery is a sustainable method of municipal solid waste (MSW) management. The co-incineration of refuse derived fuel (RDF) has shown several economic and environmental advantages. The objective of this research is to assess the impact of RDF recovery on leachate quality using leachate tests and calculation of greenhouse gases (GHG) reduction in the kilns of a cement plant. The qualitative results of the eluate show that there is an impact on leachate quality depending on the type of waste. The values of the chemical oxygen demand (COD), biological oxygen demand (BOD5), electrical conductivity and pH of the leachate from the raw waste after 120 hours of leaching are 29.33 gO2/kg DM, 14.00 g O2/kg DM, 4.27 ms/cm and 7.57. On the other hand, the values of the same quality parameters of the eluate generated by the waste without RDF are 19.33 g O2/kg DM, 20.67 g O2/kg DM, 2.77 ms/cm and 7.13; respectively. The calculation of GHG reduction shows that the substitution of 83,000 tonnes per year of petroleum coke by 15% of RDF (25,493 tonnes per year) can reduces 28,970 tCO2 eq.

The Indoor Air Quality (IAQ) of a hospital is very important to properly protect both patients and the staff against hospital infections. The present study aims at evaluating the efficiency of photocatalytic filters as well as the impact of important factors such as the type of UV wavelength (UVC, UVA) with different intensities and loading rates of TiO2 in HEPA Filters on reducing airborne microorganisms. For so doing, it has prepared photocatalytic filters by dipping them into 2% and 4% titanium dioxide suspensions as low and high loading, respectively. The experiments have been carried out on four species’ microorganisms, namely Epidermidis, Subtilis, Niger, and Penicillium. Fungi and bacteria suspensions have been prepared with concentrations of 106, 107 CFU/m3, respectively. In terms of microorganism removal, the efficiency of HEPA filters in both types of TiO2 loading and UVC and UVA radiations with two intensities at three times intervals (60, 90, and 120 min) have been investigated. Results show that lower penetration microorganism belong to PCO (TiO2 + UV), compared to photolysis (UV alone) at all intervals of UV radiation. TiO2 loading has no significant effect on percentage removal in all microorganisms. The percentage penetration of microorganisms under UVC radiation is lower than UVA radiation. Also, increasing the radiation intensity in both types of UV shows that it has higher effectiveness for removing bacteria and fungi. Therefore, the use of photocatalytic HEPA filters with UVC radiation can play an influential role in reduction of the microorganisms in different places such as hospitals, cleanrooms, etc.

In this study, efficiency of humic acids (HAs) derived from various sources to reduce CrVI in aqueous solutions was compared. HAs were extracted from leonardite, peat moss, peat, cocopeat, coal, common char, biochar, vermicompost and sewage sludge. Some chemical and spectral characteristics of the extracted HAs were measured. Then, the reducing efficiency of HAs was measured and its relationship with the determined properties was investigated. To measure the reducing efficiency of HAs, a concentration of 0.1 mM CrVI (as potassium dichromate) in a sodium nitrate solution (0.03M) with a pH of 2 and in the presence of 100 mg of HA per liter was used. The experiment was conducted in three ways (symbolized by E1, E2 and E3). They differ from each other with respect to the method of phosphate buffer addition to release CrVI ions adsorbed by HA. This buffer was added to an aliquot of final extract, to the whole volume of final suspension and to initial solution containing CrVI in experiments E1, E2 and E3, respectively. According to the results, the CrVI reducing efficiency depends not only on the nature of HA but on the method of experiment. The minimum reducing efficiency was observed for common char using experiment E2 and the maximum value was for biochar and cocopeat in all three experiments. The results showed that the two factors of ΔlogK and maximum reducing efficiency in the format of a multiple regression had a significant relationship with CrVI reducing efficiency of HAs.

The present study attempts to investigate some blood parameters of Otolithes ruber during different seasons in terms of both temperature and pollution. For so doing it uses 10 specimens, for each station and season, collected from 5 polluted stations, including Petrochemical, Ghanam, Zangi, Douragh, Patil, and Sajafi as the control group, away from pollution in Musa Creek. The fish are anesthetized with 1ml of clove extract per liter. Their blood samples are taken immediately from the caudal vein, using a heparinized syringe. Afterwards, the serum is separated in a centrifuge with a speed of 6000 rpm for 2 minutes. The desired factors are measured by the Mindray BS200 auto-analyzer and the total protein level, by Bradford's usual laboratory methods. Results show that AST, ALT, ALP, Glucose, and Triglycerides have increased in more polluted stations (P≤0.05). In sheer contrast, total protein and Albumin have decreased as pollution grows (P≥0.05). According to this study, environmental water pollution of the fish has a large impact on the concentration of measured blood parameters, whereas the influence of seasonal changes on most of them is low.

The production rate of industrial and agricultural waste is increasing due to population growth. Soil is the most important receiver of industrial and agricultural waste. Contaminants such as heavy metals in various waste after reception by the soil, immediately become part of the cycle that has different impacts on the environment. Geopolymer, as a chemical stabilizer has the potential to stabilize heavy metals in the soil. In this research, several geopolymers for the stabilization of heavy metals in soil were synthesized. Silicon dioxide (SiO2) and aluminosilicate (Al2SiO4) must be used to produce the geopolymers. Rice husk ash was used as the SiO2 source. Also, Iranian zeolite and sepiolite, and red clay soil were utilized as the source of Al2SiO4. The synthesized geopolymers were investigated for the adsorption of nickel and cadmium. Also, batch and column studies of using geopolymers for the chemical stabilization of heavy metals in soil were conducted. The results revealed a high adsorption capacity of the geopolymers. The zeolite, sepiolite, and red clay geopolymer-soil samples adsorbed 100% of the heavy metals (i.e., Ni and Cd) at a concentration of 100 ppm. The zeolite geopolymer adsorbent adsorbed 57% and 96% of Ni and Cd at a concentration of 1000 ppm, respectively. In general, it was concluded that the use of geopolymer compounds in soils with high heavy metal adsorption capacity could be an efficient approach to prevent groundwater resource pollution.

Transformation of food and beverage industrial sludge into vermicompost into value-added product simultaneously can control gaseous emission. Addition of biochar in the vermicomposting as a bulking agent increases fertilizer value. This research aimed to investigate the effect of biochar amendment on vermicomposting of the food and beverage industry sludge (FBIS) and cow dung (CD) in a different ratio using earthworm Eisenia fetida. We had further investigated the survival rate of E. fetida and the cocoon productions after 35 days of the vermicomposting. Besides, we have also evaluated the seed germination bioassay using Malabar spinach (Basella alba) to determine the toxicity and maturity of produced compost. The survival and cocoon production of E. fetida were higher in vermicompost amended with 10% biochar. Vermicomposting with biochar resulted in a slight pH shift. Reduction in organic carbon (OC) percentage not so significant in biochar added FBIS and CD. An increase in phosphorus and potassium content and a decrease in nitrogen percentage observed; vermicomposting with biochar resulted in higher seed germination, root elongation, and germination index than vermicomposting without biochar.

The agricultural sector uses fertilizers such as urea to add more nutrients to the soil needed for plant growth. Although it is cost-effective in crop production, indiscriminate use of nitrate-based fertilizer may result in behavioural, morphological, and physiological alterations on non-target organisms. This study determined the angiogenesis activity in the chorioallantoic membrane of urea-exposed duck embryos. It also investigated the weight, morphometries, and liver histopathology to gather more information on urea fertilizer's toxicity. It was observed that urea promoted angiogenesis in the CAM of duck embryos, especially at higher concentrations (P<0.05). Embryos treated with urea resulted in an alteration of the head-beak length (P<0.05). However, weight, crown-rump length, forelimb length, and hind limb length were not affected. The developing liver of urea-treated embryos showed distortion of the central vein shape and had larger sinusoidal spaces. The presence of Kupffer cells and lipid droplets were observed in the treated section. Congestion of blood cells, haemorrhage, and necrosis of hepatocytes were also observed in the tissue suggesting the extent of damage caused by the fertilizer. The findings of this study showed multiple developmental effects of urea on duck embryos. Further investigations are needed to shed more light on the toxicity of urea fertilizer on vertebrates.

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 research evaluates the carcinogenic and non-carcinogenic risks from cadmium, lead, and zinc in Bandar Abbas groundwater sources. The samples from 25 wells were analyzed for cadmium, lead and zinc. Total lifetime cancer risk and non-cancer risk assessment from exposure to these pollutants in drinking water (ingestion, inhalation and skin routes) were conducted for people living in these villages. In these regions most of the drinking water supplied, are from these wells which shows the importance of analyzing the quality of them in order to prevent diseases and cancer risks. The highest risk from cadmium seems to be in village Dehno Paein and also this amount for lead occurs in Tifakan Tal-e Gerdu. The highest hazard index (HI) based on human health risk assessment (HHRA) model for cadmium, lead, and zinc through oral, inhalation and dermal pathways were computed as 0.005, 1.63 and 0.043 which are in Dehno Paein, Tifakan Tal-e Gerdu and Faryab. Results show that lead can lead to more cancer cases in these villages that cadmium. The total expected cancer cases from exposure to cadmium in different routes are lower than lead.

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

Microbial fuel cell (MFC) is a well-known technology that can convert contaminated substrate in the wastewater to electrical power. To gain more power output, the multi-electrode MFC was developed owing to it has a high surface area for anaerobic microbe adhesion. Here we show the multi-anode was made from the bamboo charcoal was combined with laccase-based cathode in the ceramic separator MFC for the rubber wastewater treatment and enhancing the power generation. The untreated rubber wastewater with initial COD and contaminated sulfate concentration of 3,500 mg/L and 1,100 mg/L was used as a anolyte. The 843.33±5.77 mA/m3 of CD, the 711.23±9.76 mW/m3 of PD were generated. Moreover, this system reached 83.07±3.01% of sulfate removal when it was operated at 30 °C for 12 hr. This study recommended that multi-anode with laccase based MFC can more successfully produce energy from untreated rubber wastewater. it will be greater in terms of electricity generation and sulfate removal.

The pomegranate (Punica granatum) fruit peel exposed to mixture air pollutants were collected from two sites with different air quality around the industrial area of Gabes city, Tunisia. The first site presented the ‘Polluted site’, which is situated in the oasis close to the industrial area. While, the second site referred to the ‘Control site’ located at 37 km from the industrial area. Using HPLC ES-MS, 21 phenols were identified and quantified in methanol extract from pomegranate fruit peel. The results showed that various phytochemical substances, including phenols acids and flavonoids, were identified and quantified in the peel extract. The polyphenols content and the flavonoids contents in peel obtained from polluted site were higher than that collected from the control site. The concentrations of the identified polyphenols were ranged between 0.39 and 7803.68 mg/ kg DW. The stimulation of some free phenolic compounds such syringic acid, transfrulic acid, epicatechin, rutin and quercetin was enregistred only in peel collected from contaminated environment. The quali-qualitative changes between sites are probably related to the difference in the air quality. The increase of polyphenols could be implicated during adaptive mechanisms under air pollution. Phenolic composition changes in Punica granatum peel could be also suggested as useful approach air pollution monitoring.

This work explores the synthesis and characterization of two novel nanocomposites that can be used in various applications, such as aqueous solution adsorption of pollutants. The first nanocomposite consists of tin (Sn)-doped titanium dioxide (TiO2) on activated carbon, while the other one consists of polypyrole (PPy), chitosan (CS), and Sn-doped TiO2. A contrast was made of their effective adsorbent materials for the removal of Cibacron Brilliant Yellow dye from aqueous solutions. Different analytical techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), atomic force microscopy (AFM), energy dispersive X-ray analysis (EDX), and Fourier transform - infrared (FT-IR) were used to analysis the nanocomposite samples. SEM images show that the average particle diameter of PPy-CS/Sn-doped TiO2 NC is 75 ± 3 nm, while Sn-doped TiO2/AC particles have an average diameter of 40 ± 2 nm. The greater PPy-CS/Sn-doped TiO2 nanocoposite particle diameter indicates that the polymers cover the Sn-doped TiO2 nanoparticles, which leads to higher in the diameter of the particles. The adsorption efficiency of Sn-doped TiO2/AC was higher than that of PPy-CS/Sn-doped TiO2 sample due to its smaller particle size which resulted in a higher surface area which provides more adsorption sites. However, both samples showed remarkable adsorption capacity, where the adsorption capacity of Sn-doped TiO2/AC and PPy-CS/Sn-doped TiO2 were 104 and 103 mg/g, respectively.

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 paper presents concentrations and sources of Aliphatic and Aromatic Hydrocarbons in the sediments from Babolsar coastal area and the inlet of Babolrood River in the southern side of the Caspian Sea. The concentration of hydrocarbons in 13 sediment samples from the study area were measured by gas chromatography (GC). Total Petroleum Hydrocarbon (TPH) concentrations in sediment samples in the coastal area ranged from 115 to 201 μg/g. In the inlet samples, TPH concentrations were close to each other and ranged from 294 to 367 μg/g. The TPH results showed moderate level of oil pollution in the study area. Total Polycyclic Aromatic Hydrocarbons (ΣPAHs) concentrations in sediment samples inside the inlet ranged from 498 to 702 ng/g, indicating moderate level of pollution. Concentrations of ΣPAHs in sediment samples in the coastal area ranged from 341 to 1703 ng/g, indicating moderate to less than significant level of pollution. Developed indices for pollutant origins showed that hydrocarbons in all sediment samples collected in the study area had petrogenic origin. The results also showed the Babolrood River as the main source of oil pollution in the sediments in the study area.

The main objective of this paper is to propose K-Nearest-Neighbor (KNN) algorithm for predicting NOx emissions from natural gas electrical generation turbines. The process of producing electricity is dynamic and rapidly changing due to many factors such as weather and electrical grid requirements. Gas turbine equipment are also a dynamic part of the electricity generation since the equipment characteristics and thermodynamics behavior change as turbines age and equipment degrade gradually. Regular maintenance of turbines are also another dynamic part of the electrical generation process, affecting performance of equipment as parts and components may be upgraded over time. This analysis discovered using KNN, trained on a relatively small dataset produces the most accurate prediction rates in comparison with larger historical datasets. This observation can be explained as KNN finds the historical K nearest neighbor to the current input parameters and approximates a rated average of similar observations as prediction. This paper incorporates ambient weather conditions, electrical output as well as turbine performance factors to build a machine learning model predicting NOx emissions. The model can be used to optimize the operational processes for harmful emissions reduction and increasing overall operational efficiency. Latent algorithms such as Principle Component Algorithms (PCA) have been used for monitoring the equipment performance behavior change which deeply influences process paraments and consequently determines NOx emissions. Typical statistical methods of performance evaluations such as multivariate analysis, clustering and residual analysis have been used throughout the paper. This paper incorporates ambient weather conditions, electrical output as well as turbine performance factors to build a machine learning model predicting NOx emissions. The model can be used to optimize the operational processes for harmful emissions reduction and increasing overall operational efficiency. Latent algorithms such as Principle Component Algorithms (PCA) have been used for monitoring the equipment performance behavior change which deeply influences process paraments and consequently determines NOx emissions. Typical statistical methods of performance evaluations such as multivariate analysis, clustering and residual analysis have been used throughout the paper.