Pollution
Volume:9 Issue: 2, Spring 2023

The development of suitability species models look for the availability to growth in a study area. These models can be used for different targets. In this research, a suitability model of Eucalyptus has been developed to soils contaminated by trace elements management. Guadiamar Green Corridor has been selected due to the huge data available regarding trace elements, forestry species and so on. Logistic regression (LR) and Random Forest (RF), as popular machine learning model, were applied in a geodatabase from Guadiamar Green Corridor with more of 20 years of data. This database is composed by soil physical and chemical variables, climate (temperature min and max, annual precipitation), forestry species. The results show the poor performance of LR and RF applied directly over the unbalanced training set. However, when Up-sampling or SMOTE are applied, both procedures improve its sensitivity, however, RF show more improve that LR. The methodology applied can help to determine the potential distribution of Eucalyptus in similar Mediterranean areas and extended to different areas according to Soil, Climate and Trace Elements data. Finally, the models developed under this research work can be used to reduce human and environmental health by trace elements taking into account local conditions but also climate change scenarios.

Natural quartz mineral was examined as a new sorbent for Hg(II) removal from synthetic wastewater systems. Batch adsorption experiments of Hg(II)  onto quartz mineral were conducted under various conditions such as solution pH, sorbent dosage, contact time, initial Hg(II)  concentration. Adsorption experiments results of Hg(II) by quartz mineral showed good achievement after 180 min with 1.0 g/L sorbent mass at pH of 2.0, agitation speed of 200 rpm and a temperature of 25°C. Moreover, the Hg(II) concentration was directly related to increases the adsorption capacity, the maximum Hg(II) uptake by quartz  sample was 16.52 mg/g for 80 mg/L (C0 (Hg(II)].  Langmuir isotherm and pseudo-second-order kinetics (R2 > 0.99) were found to be the most appropriate models to describe the adsorption of Hg(II) by quartz mineral. The intra-particle diffusion model and the calculated Dubinin–Radushkevich adsorption energy (Eads = 0.78 kJmol-1), confirms a physisorption adsorption reaction occurring in three stages.

Boreal freshwater ecosystems are highly sensitive to pollution, but too little information is available on the use of both biotic and chemical indicators for estimation of the effect of wastewater on boreal rivers and streams. The purpose of this study was to assess the wastewater impact on the boreal river (Perm Krai, Russia).  Physicochemical parameters of major ions and trace elements were detected with a field portable unit, capillary electrophoresis, and ICP-MS. Fish data was collected by gillnets. To evaluate the level of pollution from the Tolych River upstream to downstream, we calculated heavy metal evaluation index (HEI), ecological risk index (ERI), and index of biotic integrity (IBI). The anthropogenic impact from upstream to downstream showed the range from a very high to medium level of pollution by ERI and from a high to medium level by HEI values, where most of the studied major ions and trace elements often exceeded aquatic life limits. We found significant thermal pollution of the observed river with the decreasing temperature gradient from pollution source down to the river mouth due to hydromorphological factors. Observed thermal pollution leads to the absence of thermally sensitive cold-water fish species and the abundance of ecologically flexible fish species. The water quality assessed by biotic IBI index showed low and very low quality of lower reach of the studied river, which contradicts the results of assessment by HEI and ERI indices.  The results show the importance of using aquatic organisms as bioindicators for assessing ecological water quality.

The study was conducted in Lake Rinconada, a glacial lake affected by artisanal and small-scale gold mining activities in the southern Andes in Peru. The objectives of the study were to investigate the spatial distribution of heavy metals (As, Cu, Hg, Pb and Zn) in water and sediments and to assess the degree of metal pollution and ecological risk using the geoaccumulation and potential ecological risk indexes. The concentrations of As and Hg in sediments from Lake Rinconada exceeded the Canadian sediment quality regulations, whereas the concentrations of As, Hg and Pb in water and sediments from the mining-affected tributary, Lunar de Oro River exceeded the Peruvian and Canadian guidelines for water and sediments quality respectively. According to the geoaccumulation and potential ecological risk indexes, Lake Rinconada is extremely polluted by As and Hg, and the pollution is mostly concentrated in the northern part of the lake, where the mining-affected Lunar de Oro River flows into the lake. Concentrations of Pb are also high in the northern part of the lake, suggesting that the nearby gold mining town is a source of pollution. The results of this study allows to report that Lake Rinconada is completely deteriorated.

Perfluorinated chemicals (PFCs) are widely used in industrial and commercial applications, leading to their release into the environment. The rapid industrialization and growing population in India make it a suitable case study to investigate PFOS contamination in environmental matrices. The purpose of this study is to investigate PFOS concentrations in river water and groundwater from several locations along the Bharathapuzha river basin and estimate PFOS intakes through drinking water. The highest PFOS level detected in the surface water is 1.3 ng/L and groundwater is 1.0 ng/L, which is significantly lower than the level of PFOS detected in major rivers of many developed countries. It is possible to attribute the low PFOS concentration to factors such as high annual precipitation, reduced industrial and municipal wastewater discharge, and relatively low emissions per capita in a region where agriculture is a major part of the economy. In addition, the daily intake of PFOS through drinking water in all age groups was below the safety threshold for cancer risk.

During the COVID-19 pandemic large numbers of single-use, surgical style face masks were lost or discarded in public spaces, primarily in on public streets and car parking settings. Many of these masks were blown onto the road surfaces where they were subjected to degradation through the tire impact of passing vehicle traffic. As series of field observations as well as experimental simulations show that the three-ply polypropylene mask fabric is subjected to shear forces when compressed between the tire and the road surface. The mechanical action breaks the bonds between the fibers (both spunbonded and meltblown) leading to a continual shedding of microfibers. Wind disperses these into the environment along road sides, while surface water action moves them into stormwater drains and from there into the waterways. As the decay is rapid, municipal agencies only have a short window of time to remove stray face masks from the urban environment if micro-fiber pollution is to be reduced.

Discharge of synthetic dyes from industries without treatment leads to major environmental problems. Present research highlighted the Mn-doped ZnO along with UV-induced photo degradation of Congo red (CR) dye through batch study. The synthesized Mn-doped ZnO (MDZO) was characterized by Transmission electron microscope (TEM) and Fourier transform infrared spectroscopy (FTIR). The results revealed that MDZO along with UV exposure degraded the CR dye up to 99.3% at concentration 4 mg/L, pH (7), adsorbent dose (0.6 g/L) and contact time (30 min). The degradation data nicely fitted with pseudo-secondary kinetics and the thermodynamic study suggest the said reaction is exothermic in nature. A statistical method, central composite design (CCD) was used to screen out the optimized condition of dye degradation. The interactions of main factors and optimal conditions were also evaluated by 3D surface plots. The statistical output clearly demonstrates that the dye degradation data is nicely fitted with very high goodness of fit and F value (86.19). Present research clearly suggested that Mn-doped ZnO along with UV could be an effective treatment towards degradation of Congo red dye.

We analyzed 125 samples collected from Joypurhat district, Bangladesh, in this study. Average inorganic arsenic (IAs) content obtained from collected polished rice, tomato, potato, radish, and arum leaves 0.31 - 0.91, 0.24 - 0.61, 0.49 - 0.88, 0.40 - 0.93, and 0.30 - 0.69 mg/kg, respectively. This report summarized that almost every agronomic sample contains arsenic; the As contents remain within the permissible limit set by FAO/WHO’s guideline (1.00 mg/kg) except for the rice sample. The As concentration for the rice sample was significantly higher (0.31 - 0.91) than the prescribed limit (0.20 mg/kg). But, the As level for water (mean range, 0.10 - 0.72 mg/l), sediment (0.13 - 0.53 mg/kg), and soil samples (24.1 - 43.1 mg/kg) also significantly surpassed the permissible level. The present study is alarming for water samples, where the highest IAs concentration (0.72 mg/l) is 72 times [14 times] higher than WHO/FAO’s [Bangladesh’s] allowable limit (0.01mg/l) [0.05 mg/l]. All agronomic fields contain higher IAs (25.50 - 43.10 mg/kg) than the world standard limit (10 mg/kg). Statistical Igeo confirmed the moderate pollution of the entire agronomic field of Joypurhat except for the river’s sediment. Again, EF values ensured the anthropogenic pollution by the moderately severe enrichment of As for the 65% agronomic field and significant enrichment of As for the 35% agronomic field. Hazard estimation results revealed the privileged possibility of non-carcinogenic [carcinogenic] health hazards to regular polished rice [water] consumers. So, present study suggests that authorities should take necessary steps to prevent contamination/upcoming health risks.

Laboratory wastewater is categorized as hazardous waste that should not be released into the environment since it poses a serious threat to environmental safety. In the present study, the use of Sulphate-Reducing Bacteria (SRB) colonies in an anaerobic reactor to treat heavy metals-containing laboratory wastewater was examined. SRB was initially cultivated with the treatment of fermented compost and Postgate's medium before being attached to the laboratory-size anaerobic reactor to treat laboratory waste containing heavy metal. Within the 15 days of initial incubation under the room temperature of 28 °C, we discovered that SRB optimally grew on the medium with the composition of 5% Postgate B solution, 30% fermented compost liquid, and 5% active suspension liquid, with a total population of cell colonies was 1.2 x 105 CFU/ml. After SRB colonies from the most optimum medium were affixed to the reactor, the reactor attained 89% of lead (Pb) removal, 69.78% of iron (Fe) removal, and 48.93% of copper (Cu) removal for 15 days treatment periods. On the 21st days of treatment time, the removal efficiency increased significantly to 91.57%, 78.09%, and 83.56% of Pb, Fe, and Cu removed, respectively.

Air fresheners are the synthetic products, used to improve the quality of indoor air by removing unpleasant or disturbing odours, in addition they disinfect the air by removing allergens and in turn add pleasant odours. However, these fresheners since they contain varied chemicals, which on magnification in a closed environment may cause respiratory illness. Therefore, constant usage of these air fresheners would deteriorate the ambient quality of indoor air. Even air fresheners which claim to be “green”, since these lack regulatory norms, they too emit hazardous or chemically harmful compounds. Hence there is a dire need to use alternative products that substantiate the quality of indoor air.  The present study aimed at exploring the efficacy of medicinal plant extracts of Azadirachta indica, Menta piperita and Aloe barbadensis in controlling air borne fungi in indoor environments by creating a simulation of an indoor environment and checking the efficiency of these natural air fresheners. About 60-70% reduction in the vegetative structures (colony diameter) and 30% reduction in reproductive structures were observed after exposure for 11 days to environment containing Azadirachta indica and Menta piperita extracts. Thus this study has novelty in formulating herbal based air fresheners based on the proven antifungal activities of these medicinal plant extracts, thereby replacing the usage of commercial air fresheners in the near future in controlling indoor air borne fungi. Since these natural formulations undoubtedly disinfect the indoor air, has commercial prospects and are eco-friendly, cost-effective with no health implications.

The presence of volatile organic compounds in the indoor environment and their unwanted effects on human health are inevitable. That's why different methods have been proposed to remove them from air. The present study examines using photocatalytic reaction system along with TiO2 particles coated on stainless steel webnet to study direct conversion of toluene using a new design. The study was carried out using UV radiation in a dynamic concentrator system. SEM and XRD analyses were performed to characterize prepared catalysts. Here, the aim was to employ photocatalytic oxidation (PCO) to optimize removal efficiency and elimination capacity using response surface methodology (RSM). To this end, initial concentration and flow rate were selected as independent variables. High removal efficiency and elimination capacity were realized using optimal settings. The findings indicated that PCO process with a new design other than RSM was an option to treat air pollution containing volatile organic compounds.

The simulation of photocatalytic reactor is conducted using computational fluid dynamics. Turbulence is described by using the RNG k-ε turbulence model. The DO radiation model is used to simulate the irradiance distribution in the photocatalytic reactor. The effects of operating parameters on the performance of photocatalytic reactor are considered. Results show that the degradation rate of oxalic acid decreases with the increase of inlet flow. The degradation efficiency decreases from 50% to 40% when the flow rate changes from 2.5 m3 h−1 to 10 m3 h−1. The degradation rate of oxalic acid can be improved by increasing the irradiance of the lamp. The degradation efficiency of oxalic acid in the photocatalytic reactor first reaches a maximum degradation efficiency with the increase of titanium dioxide concentration, and then decreases with the increase of titanium dioxide concentration. An optimal concentration of catalysts exists. The maximum degradation efficiency is 27% for the catalyst concentration of 20 µgL−1.

Coronavirus (COVID-19) pandemic ushered in a new era that led to the adjustments of diverse ecosystems. The pandemic restructured the global socio-economic events which prompted several adaptation measures as a response mechanism to cushion the negative impact of the disease pandemic. Critical health safety actions were imperative to curtail the spread of the disease such as wearing personal protective equipment (PPEs), masks, goggles, and using sanitizers for disinfection purposes. The daily demands for the products by individuals and medical personnel heightened their production and consumption, leading to a corresponding increase of COVID-19 wastes in the environment following indiscriminate waste disposal and poor waste management. The persistent occurrence of COVID-19 wastes aggravated microplastics (MPs) contamination in the aquatic ecosystem following the breakdown of PPEs-based plastics via oxidation, fragmentation, and photo-degradation actions. These MPs are transported in the aquatic environment via surface runoff and wind action, apart from discrete sources. MPs' presence in the aquatic systems is not without repercussions. Ingestion of MPs by aquatic organisms can cause several diseases (e.g., poor growth, oxidative distress, neurotoxicity, developmental toxicity, reproductive toxicity, immunotoxicity, and organ toxicity). Humans are at high risk of MPs uptake. Apart from aerial and soil contamination sources, consumption of aquatic food products is a critical pathway of MPs into the human body. MP toxicities in humans include liver disorder, respiratory failure, infertility, hormonal imbalance, diarrhea, developmental disorder, and mortality. Measures to alleviate the effect of COVID-19 waste litters include effective waste management plans and the adoption of technologies to extract cum degrade MPs from the aquatic and terrestrial environment.

The pollution generated by metallic trace elements discharged by mines into the environment can become a very worrying source of contamination for soil, water and plants. The characterization of the chemical properties of metals in mine tailings and soils is of crucial importance to assess the risk of their potential mobility and therefore their bioavailability. In this paper, the bioavailability of metallic trace elements  in agricultural soils in the vicinity of the Draa Lasfar mine in the northwest of Marrakech city (Morocco) was studied by determining the contents of Cd, Cu, Pb and Zn in soils and in two plants: wheat (main food for the human population) and couch grass (main food for livestock). The results showed that these metals move from agricultural land to plants. They also showed that couch grass seems to strongly absorb and accumulate metallic trace elements present in the soil; it removes considerable amounts of metallic trace elements from the soil with its deeply penetrating root system.

The present study aims to provide baseline information on the temporal characteristics of PM2.5 and PM10 concentration time series variations, mainly on the cross-correlation between PM2.5 and PM10, using the improved mathematical and nonlinear methods. Firstly, the fractal theory such as fractal dimension is used to detect the pollution level in PM2.5 and PM10 time series. Secondly, the Multifractal Detrending Moving-Average Analysis (MFDMA) is used to analyze the multifractal characteristics of PM2.5 and PM10 concentrations. Thirdly, Multifractal Detrending Moving-Average cross-correlation Analysis (MFXDMA) is used to study the cross-correlation between PM2.5 and PM10 concentrations measured from January 1 to December 31, 2020, along the Boulevard de la Marina, one of the major roads in Cotonou. The results have indicated that: (1) PM10 and PM2.5 concentration time series are characterized by a fractal dimension, which can permit to detect the pollution levels and to analyze the differences in emissions sources; (2) there is a significant multifractal structure in the PM2.5 and PM10 concentration data and their fluctuations are long-range correlated, however, the multifractal properties and self-memory characteristics change with the months; (3) generally, the multifractal degree and the complexity of PM10 are much stronger than those of PM2.5. However, they present a similar multifractality degree in some months of the year; (4) except, in February, the cross-correlation between PM2.5 and PM10 time series in the months of the year presents multifractal characteristics with positive persistence; (5) the cross-correlation multifractal features show monthly variation. This paper provides the inter-relationship between air PM2.5 and PM10 time series which may help taking steps in controlling the air quality and management of the Cotonou port area environment.

In this study, the concentrations of heavy metals were studied using atomic absorption spectroscopy of samples from the sediments of the Tigris River within the boundaries of the city of Mosul, northern Iraq, and the environmental parameters of heavy metals were calculated. The results showed that the average concentrations of Co, Cu, Cd, Pb, Zn, and Ni in (ppm) were (8.78, 30.42, 0.179, 12.04, 75.53, and 144.75), respectively, where these results were higher than the international accepted average. It indicates that the main factor in the high concentrations of heavy metals in the environment of the Tigris River in the city of Mosul is the pollution caused by human activities. The results of the environmental treatments for the studied heavy metals showed that the values of the enrichment factor (EF) were moderately contaminated with Cu, Cd, Ni, and Zn and not contaminated with Co and Pb. The value of the contamination factor (CF) for the sediments of the Tigris River in the studied areas showed that the sediments of those areas are moderately polluted with Co, Ni, and Zn metals. The degree of contamination (Cdeg) for the sediments of the study area in general ranges from low - medium pollution, the pollution load index (PLI) average of (1.03) showed that the sediments of the study area were contaminated with heavy metals. Therefore, we conclude that the environment of the Tigris River is polluted with heavy metals, but it is not at the level that causes concern at present.

Evidence of the health impact of air pollution in Morocco is scarce. We aimed to test our hypothesis that exposure to air pollutants has a significant impact on the health of Moroccans. For this systematic review, we searched PubMed, ScienceDirect, LILACS, and ProQuest databases, Google Scholar, and forward and backward citations for studies published between the database inception and August 16, 2022. All studies and reports that measure air quality in Morocco and its health impact were included, without language restrictions. This study is registered on PROSPERO under number CRD42020163948. Studies were selected based on inclusion and exclusion criteria rather than their methods. The data was extracted, coded, and prepared for future examination. After that, descriptive and thematic analyses were carried out. Of 1230 records identified, 31 were eligible, all of which had annual air pollutant concentrations in excess of WHO Air Quality Guidelines. The health impact was demonstrated in five studies. The most studied pathologies were asthma, respiratory and cardiac infections in children under 12 years and adults. In addition to heavy metals, the most investigated pollutants were PM10, O3, SO2, and NOx. The significant association between exposure to air pollutants and health in the Moroccan population has been demonstrated, even if it is not causal. Future research should quantify the health impact of pollution in other Moroccan cities.

Benin’s waterways are affected by several forms of pollution that are linked in particular to anthropic activities. This study aims to detect the presence of antibiotic residues, the frequency of antibiotic resistant bacteria and the levels of heavy metals in Benin’s waterways. 160 surface water samples from streams in Benin were collected. They were filtered by the membrane filtration method, then incubated on different media. The isolated bacterial species were identified by API 20E gallery and specific biochemical tests. After detection of the resistance profile of the latter, the antibiotic residues were quantified in the samples by the ELISA technique on plate and the physicochemical analyses were performed by Multi 3630 IDS SET KS2 multimeter. Finally, heavy metal levels were detected by the MERCK test kit method specific to each metal. The bacterial species mostly identified were Klebsiella pneumoniae (56.59%), Klebsiella spp. (18.68%), Enterobacter spp. (12.63%). The most abundant resistance of bacterial strains was to amoxicillin + clavulanic acid (92%), followed by metronidazole (86%). Metronidazole was the antibiotic with the highest residue concentration in the samples (6.578 to 6.829 µg/L), followed by ciprofloxacin (2.142 to 9.299 µg/L). Benin streams contain heavy metals such as mercury (0.454±0.129 µg/L), lead (0.040±0.50 mg/L), zinc (6.120±16.017 mg/L), nickel (0.155±0.233 mg/L) and cadmium (0.154±0.132 mg/L). The analysis of the physico-chemical parameters showed that, apart from electrical conductivity, all parameters comply with Beninese and World Health Organization standards. Actions must be taken to clean up these rivers to preserve the integrity of aquatic ecosystems in Benin.

Gas storage is an important branch of technology that has many economic and environmental aspects. This technique could save gas to the need time and contribute to solving the CO2 and global warming problems. In this work, the structure and physicochemical properties of the prepared palladium complex were characterized in the solid and solution states using spectroscopic techniques. These examination methods include ultraviolet-visible (UV-Vis), Fourier transform infrared (FTIR), metal and elemental analyses, and measurements of magnetic susceptibility and conductivity at room temperature. Also, findings on the surface morphology and surface area were provided via Field emission scanning electron microscopy (FESEM) and Brunauer–Emmett–Teller (BET) techniques, respectively. High-pressure adsorption measurements were investigated by storing carbon dioxide, and the results proved that such materials own remarkable gas adsorption properties that make them a good option for gas separation and storage. Gases uptake at 323 K for the complexes leads to the highest CO2 uptake. The prepared material could pave the road for further exploitation of similar materials.

Nickel nitrate is a heavy metal known as an environmental contaminant due to its toxicity, long environmental half-lives, and capacity for bioaccumulation.  This study aims to determine chromosomal aberration, nuclear alteration, and cell death in Allium cepa var. aggregatum L. root caused by different nickel concentrations.  Roots of Allium cepa var. aggregatum were induced by soaking bulbs in water, then transferred to a solution containing nickel (Ni) at a concentration of 20 ppm, 30 ppm, and 40 ppm for 72 hours.  Root tip mitotic chromosome preparations were done by the squash method.  The chromosome was stained with aceto-orcein and chromosomal damages were observed under a microscope.  The results showed that the mitotic index decreased from 5.025% at control to 3.144%, 2.467%, and 2.181% at immersion with 20 ppm, 30 ppm 40 ppm nickel nitrate, respectively.  Anaphase and telophase indexes in roots with Ni treatments were lower than in control, suggesting that nickel inhibits cell division.  Nickel nitrate induced chromosomal damages and nuclear abnormalities, such as sticky chromosome, fragmented chromosome, chromosome bridge and chromosome laggard, micronuclei, binucleate and nuclear budding.  The percentage of chromosomal damage increases with a higher concentration of Ni.  In situ cell visualization showed that the higher the nickel concentration, the more coloured the root tips indicating high levels of cell death.

The high amount of Electrical Conductivity (EC) in the groundwater is one of the major negative Geo-environmental problems which has a considerable effect on the quality of drinking water. To address this challenging problem we proposed an intelligent Machine Learning (ML) based approach to predict EC in urban areas. We applied the deep learning technique as one of the most applicable ML techniques with high capabilities for intelligent predictions. Five different deep neural networks (Net 1 to Net 5) were developed in this study and their reliability to predict EC with an emphasis on different settings of inputs, features, functions, and the number of hidden layers was evaluated. The achieved results showed that deep neural networks can predict EC parameters using minimum and economic input parameters. Results showed parameters Cl and SO4 with a high range of correlation and pH with a low range of Pearson correlation properties are influential parameters to be used as the input of neural networks. Activation function Relu, optimization function Adam with a learning rate of 0.0005 and loss function Mean Squared Error with the minimum of two hidden dense layers from Keras laboratory of Tensor Flow developed an efficient and fast network to predict the EC parameter in urban areas. Maximum epochs for developed networks were defined up to 2000 iterations while epochs are reducible up to 200 to drive minimum loss function outcome. The maximum training and testing R2 for developed networks was 0.99 in both the training and testing parts.

BTEX is one of the common compounds in the breathing air of gas station workers, which can cause high carcinogenic and health risks. The present study was conducted to assess the carcinogenic and health risks of occupational exposure to BTEX compounds in gasoline fuel distribution stations in Karaj. This descriptive and cross-sectional study was conducted to assess the carcinogenic and health risks caused by exposure to BTEX compounds in 2021 during the summer and winter in six fuel distribution stations in Karaj. Occupational exposure to BTEX was measured according to the NIOSH 1501 method. Cancer and non-cancer risk assessment were performed according to the United States Environmental Protection Agency (USEPA) method. Data were analyzed in SPSS software version 26. The average occupational exposure to benzene, toluene, ethyl benzene, and xylene during a work shift among all participants in summer and winter were 83.33 - 89.33, 202 - 210.66, 126.55 - 136.83, and 168.81 - 174.83 µg.m-3, respectively. The highest concentration of BTEX compounds was observed in Gas station in the center of the city. The mean carcinogenic risk value of benzene and ethylbenzene were 139×10-2 and 27×10-2, respectively. The highest carcinogenic risk value due to exposure to benzene and ethyl benzene was observed in Gas station in the center of the city. The mean non-carcinogenic and health risks of occupational exposure to benzene, toluene, ethyl benzene, and xylene were 173.79, 14.19, 3.61, and 12.87, respectively.  The findings demonstrated the values of carcinogenic and non-carcinogenic risk in the majority of participants were within the definitive and unacceptable risk levels. Therefore, corrective measures are necessary to protect the employees from the non-cancer and cancer risks.

Benzene is considered a toxic and hazardous pollutant in Tehran metropolis. The storage tanks of petroleum products and refueling in gas stations are among the main sources of benzene emissions. Using the software AERMOD and reviewing the benzene dispersion maps at different distances from 412 storage tanks at 148 gas stations, it was found the permissible distance of the emission source is dependent on various variables such as the number of loading times and the storage capacity. When, storage capacity in the range of 60,000 L to 96,000 L and the number of loading is in the range of 675 to 1328 times a year, the concentration of benzene at a distance of 30 m of the emission source reaches the annual standard of 5 μg/ m3. While, storage capacity in the range of 80,000 L to 128,000 L and the number of loading is in the range of 1329 to 1834 times a year, the concentration of benzene at a distance of 40 m of the emission source reaches the annual standard of 5 μg/ m3. Also, based on the analysis of data and the linear regression equation, the permissible distance of the emission source can be predicted.

Effect of salinity and oxidation-reduction potential (ORP) in the mobility of metals bound to suspended sediments at estuarine zone is investigated. Saline and freshwater samples as well as suspended sediments from estuarine zone of the Chalus River and the Caspian Sea, have been collected. Two series of four aquaria sets (natural and ORP-augmented conditions) containing turbid water with salinities of 0.25, 0.75, 1.5 and 2.5 psu were arranged. An increasing pattern of exchangeable-phase of all studied metals contents (at higher salinities) was observed under natural and ORP-modified conditions. Furthermore, the exchangeable-phase metal contents under ORP-modified conditions are higher (or equal) when compared with natural conditions. The overall trend of metals mobility potential might be evaluated as: Cd > Pb > Mn > Cu > Zn > Co > Ni. Findings of this research confirm the direct effect of both salinity and ORP parameters in mobility of metals bound to suspended particles in estuarine zones.

Using ethanol in gasoline is considered one of the most significant goals in the 2030 agenda, which has been set a 15-year plan in order to achieve it since 2015. Appropriately, this project was planned for predicting the value of the most important engine parameters such as the equivalence air-fuel ratio (φ), fuel consumption (ṁf), and brake thermal efficiency nb. th, and brake-specific fuel consumption (BSFC) by regression models. According to the protocol of this project, first, the determined percentages of ethanol were added (0, 20, 40, 60, and 80%) to gasoline at different engine speeds (850, 1000, 2000, 3000, and 4000 rpm and the New European Driving Cycle test). After testing, calculating, mathematical programming, and fitting the regression models for the two SI-engine (TU5 and EF7) with different properties of engine design,12 regression equations have been determined for each of the ‘ (positive linear model), (ṁf) (negative linear model), nb.th (negative second-order polynomial model), and BSFC (positive second-order polynomial model), respectively. Clearly, these 48 regression equations with different line slopes will be able to predict the exact value of the ‘, (ṁf), nb.th, and BSFC for each concentration of ethanol at different engine speeds in order to help automotive industries for trend predicting them in other similar engines.

In this work, single layered Ti3C2(OH)2 MXene nanosheets have been successfully prepared through a facile approach by etching Ti3AlC2 with alkaline solution treatment (KOH with minimum amounts of water). The structure and morphology of the produced nanosheets were evaluated through X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM) analysis and the chemical composition was determined using an energy dispersion X-ray (EDX) spectrometer. Methylene Blue (MB) as a target pollutant adsorption and photocatalytic degradation tests were subsequently performed to assess the functionalities of hydroxyl-terminated MXene. MB removal using Ti3C2(OH)2 MXene in the dark in 20 minutes achieved an absorption-desorption balance of 51.2%, and then MB was degraded within 80 minutes under UV light irradiation with great efficiency. Our results presented that the powder of as produced exhibited good photocatalytic activity for three cycles photodegradation. The first-order rate constant (k) was calculated to be 0.0372 1/min. About 97% degradation of Methylene Blue dye in the solution was confirmed within 80 min of exposure to ultraviolet light.

Persistent pollution of surface waters by hydrocarbon compounds is one of the foremost threats to limited global freshwater resources. This study analyzed the abundance, diversity and degradative capacities of hydrocarbon-utilizing bacteria in chronically polluted Kono River in the Nigerian Niger Delta in order to establish the bacterial drivers of ecological regeneration of the river after an oil spill. The study further aimed to develop a specialized bacterial consortium for application in bioremediation interventions. Bacillus, Pseudomonas and Enterobacter spp. were predominant out of the 82 isolates obtained. Klebsiella pneumoniae and two species of Enterobacter cloacae were identified as the most efficient hydrocarbon utilizers. The isolates were also confirmed as biosurfactant producers and possessed the alkB1 and nahAc genes for degradation of aliphatics and aromatics. E. cloacae-K11, K. pneumoniae-K05, E. cloacae-K12 and their consortium were able to degrade the total petroleum hydrocarbons and polycyclic aromatic hydrocarbons in batch systems by 59.37% – 96.06% and 68.40% – 92.46% respectively. K. pneumoniae-K05 showed the greatest petroleum degradation capacity of the three isolates but hydrocarbon degradation was most efficient with the bacterial consortium. The results obtained showed no significant differences at p≤0.05 between the degradation capacities of K. pneumoniae-K05 and the consortium for PAHs but a significant difference (p≤0.05) was seen with TPH degradation. A viable hydrocarbon degrading bacterial consortium was developed at the end of the study and it was concluded that the polluted river water displayed inherent potential for effective natural attenuation.

Researchers are interested in developing techniques to monitor, manage and predict the risks of gases and particles emitted from cement factories, which have a direct and negative impact on human health. Deep learning (DL) is a critical component of data mining, which further involves statistics and prediction. In this study, we developed a deep learning prediction model called the Deep Pollutant Prediction Model (DPPM). The data used for DPPM are separated into two types: observed data from a pollution monitoring station of the Institute of Mental Health in Ahmedabad City, India coded as (GJ001), to validate the model and simulated data generated using the Gaussian Plume Model for the hypothetical receptor (Laylan District, Kirkuk, Iraq) to predict the pollution that emitted from Kirkuk Cement Plant 5 km apart from the study area. The findings indicated that the DPPM has high efficiency in both Allahabad and Laylan stations, with more closed results for the data in the Laylan station, which is based on the Gaussian equation simulated data. Since the highest loss function value in the Laylan is 0.0221 of the CaO parameter, while it is 4.466 of the AQI parameter for the Allahabad Station, and the smallest loss function value in the Laylan is equal to 0.0041of both Fe2O3 and MgO parameters, it corresponds to 0.038 of Xylene for the Allahabad station. The results of the study proved that data continuity and non-volatility produce excellent outcomes for DPPM.

A comprehensive investigation was engaged to determine the spatial distribution of Uranium (U) and the consequential chemical and radiological health risk associated due to the consumption of groundwater containing U, in Panchkula district. A well-accepted technique of fluorescence of U estimation in an aqueous medium was employed having a detection limit of 0.50 µgL-1. The chemo-radiological health risk and water quality index was computed using a standard equation of concerned agencies to determine the suitability for human health. The concentration of U was observed to vary from 1.70 – 12.28 µgL-1 with the mean value of 5.89 µgL-1 The concentration of U was far below the standard prescribed limits as per World Health Organisation, Atomic Energy Regulatory Board, and United Nation Environmental Protection Agency. Except  nitrate and total alkalinity in few samples, all water quality paramters were within the recommended limit of BIS. The annual effective dose (AED), excess cancer risk (ECR), and lifetime average daily dose (LADD) indicated no potential health issue due to the consumption of groundwater of studied locations. The correlation was computed between U and various macro-anions and cations present in water samples. U was observed to have a significant weak positive correlation with total dissolved solids (TDS), electrical conductivity (EC), and salinity.

Four regions of the Farahzad River Valley with different topography were selected to fully survey it and study the effects of morphology on local climate. then one of the hot days of the month of June 2021 (June 6th) was selected because the wind speeds increase in spring. According to the comparison of the simulation results with the existing site plans, the temperature in area 3 was the highest, 39.60 degrees, and the wind speed was 3.57 m/s. On the other hand, the study and analysis of the maps showed that the temperature of the roads in regions 3 and 4 were higher than the other two regions with a temperature range of 37.69-38.40, so the presence of impervious asphalt surfaces on the roads is very effective in increasing the air temperature in these areas.  Comparisons also showed that tall buildings and vegetation create shaded areas and increase wind speed. Based on this, two scenarios were designed. In the first scenario, doubling the height of buildings increased wind speed in Region 3 by 3.42 m/s and decreased temperatures by 1.59 degrees. In the second scenario, when tall trees were planted at certain distances around the streets, the temperature in Region 3 decreased by 1.68 degrees and the wind speed increased by 1.68 m/s. The results show that the differences in the topography of urban valleys cause ventilation of the environment and that the effect of this feature in other environments is more effective through planting than through buildings.