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.

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.

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.

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.

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.

Human developmental activities always result to waste generation; that invariably pollute the environment, if not properly managed. The aim of this study is to determine soil quality around Odo Iya-Alaro at Ojota, Lagos. A total of 12 soil samples were collected from 0 -15 cm and 15- 30 cm at three different spots of 100 and 500 m (control) away from the bank of the river. Samples were analysed for pH, EC, NO3, TOC; Zn, Na, K, Ca, Mg, Cu, Fe, Cd, Cr, Ni, and Pb using standard analytical methods. The results were subjected to both differential and inferential statistics using statistical package (SPSS 22.0 version). Subsequently, the data were compared with Earth crust values. The soil pollution was evaluated using pollution, ecological risk, and geo-accumulation index. Cr (50.43), Ni (29.47), and Cu (104.10) mg/kg at 100 m were higher than their controls; (12.09), (8.14), and (86.06) mg/kg respectively, but lower than their respective Earth crusts; (100), (80) except (50) mg/kg. The soil was moderately polluted with pH (1.15), Na (3.00), K (2.11), Mg (1.87), Ca (1.26) and Cu (1.21); considerably polluted with EC (3.82), TOC (3.39), and Ni (3.62); and very highly polluted with Fe (8.26). Fe (711.73) had a very high ecological risk.  The Geo – accumulation index was moderately - strongly polluted with Zn (2.61), and very strongly polluted with pH (5.37), EC (14.90), NO3 (9.66), Na (15.41), K (11.31), Mg (9.51), Ca (17.08), Fe (15.32), Cu (12.54), Cr (8.67), and Ni (7.32). The soil was polluted. and urgently needs reclamation for Garden Park (relaxation).

Increasing the level of environmental knowledge of consumers and their level of concern towards the environment and green brands are among the important factors that have been considered in the discussion of consumer behavior in recent years. Marketing managers also try to attract customers' attention to their green products and brands in order to succeed in selling and marketing their products. Therefore, the present study was conducted with the aim of investigating the effect of green packaging on attracting and retaining environmentally friendly customers with the mediating role of green brand image. In terms of the purpose of the research, the type of applied research, the method of collecting descriptive data is of the correlation type. The statistical population of this research is the students of University of Mohaghegh Ardabili, 373 of them were selected as a sample by referring to Morgan's table and using the available sampling method. The required data were collected using a questionnaire and analyzed based on the structural equation modeling method and using SPSS and Smart PLS software. The results of the research showed that green packaging has a positive and significant effect on attracting and retaining environmentally friendly customers as well as the image of the green brand. On the other hand, the image of the green brand has a positive and significant effect on attracting and retaining environmentally friendly customers. Finally, green brand image acts as a mediating factor in the relationship between green packaging and attracting and retaining environmentally friendly customers.

Polychlorinated biphenyls (PCBs) are known amongst the most dangerous toxicants entering the coastal marine waters from various polluting sources. Even the smallest PCBs doses are capable to change physiological and biochemical processes exerting toxic, mutagenic and carcinogenic effects. So, the aim of this study was to analyze the impact of PCBs at 1, 100, 1000 µg/L on oxidative stress parameters (level of oxidized proteins (neutral aldehydes and ketones, basic aldehydes and ketones) and lipid peroxidation), antioxidant enzyme activities (superoxide dismutase (SOD), catalase (CAT)) and cholinesterase (ChE) activity in the hepatopancreas of mussel Mytilus galloprovincialis during 5 days’ of the toxicological experiment. Level of all forms of the oxidized proteins was found significantly increased at 100 µg/L and 1000 µg/L (+50-78% and +150-282%, respectively) compared to the control (p<0.05). Level of lipid peroxidation was considerably higher at 1, 100, 1000 µg/L (+59%, +134%, +269%, respectively) compared to the control (p<0.05). SOD activity significantly raised at 1, 100, 1000 µg/L (+63%, +200%, +118%, respectively) compared to the control (p<0.05), while CAT activity reduced at 1000 µg/L compared to the control, 1 µg/L and 100 µg/L (-29%, -66%, -40%, respectively) (p<0.05). ChE activity was found lower at 1, 100, 1000 µg/L (-60%, -93%, -30%, respectively) compared to the control (p<0.05). Possible mechanisms of M. galloprovincialis biochemical response to PCBs are discussed. Studied biochemical parameters can be suitable biomarkers for evaluating the toxicity of PCBs and M. galloprovincialis can be used as a bioindicator in the monitoring of marine ecosystems contaminated with these pollutants.

Random and unscientific disposal of municipal waste is an important factor affecting the geotechnical characteristics and concentrations of heavy metals in the soil. Unconfined compressive strength, Atterberg limit, and maximum dry density tests were included. These tests were designed to determine the effects of open waste dumps on geotechnical properties and the concentration of heavy metals in the underlying open dump soil. Soil samples collected from the landfill at Al-Sayyahia Village, Babylon Governorate, showed changes in the rates of geotechnical properties evaluation, as the value of the confined compressive strength decreased by high rates from 54 to 22 kN/m2. As well, when comparing the maximum values of dry density of samples from the control site, neighboring the landfill, the average value decreased from 1.91 to 1.74 gm/cm3. Chemical tests revealed that the pH and organic matter percentages in the open dump soil samples were significantly higher than in the control site. These percentages ranged from 9.67% and 2.542% to 7.4% and 0.215%, respectively. In addition, the average value of electrical conductivity was 5.6 mS/cm in the open dump soil, whereas in the control site was 3.6 mS/cm. Iron, lead, Copper, Nickel, Chrome, Zinc, Cadmium, and Arsenic have average concentrations of 4.64%, 14.02, 44.86, 236.36, 278.36, 95.26, 2.034, and 13.84 ppm, respectively. They are higher at open landfill sites than in control site samples.

Anthropogenic activities have polluted soil and aquatic ecosystems by introducing harmful heavy metals (HMs) such as cadmium, copper, mercury, lead, manganese, nickel, zinc, and others. These HMs lead to serious health conditions in humans like cancer, skin lesions, birth defects, liver and kidney damage, and mental retardation leading to other disabilities. Conventional methods of HM remediation of contaminated soil and water include physical, chemical, biological, and integrated methods. The use of physical and chemical methods, in isolation, has been reduced in practice, owing to their negative impacts, however, work on suitable integrated approaches, and the use of organisms for HM remediation has been in steady progress since past few decades. These approaches have proved to be eco-friendly, cost-effective, and show reduced negative impacts on the environment and biota. However, there is consistent increase in anthropogenic contribution to this problem, so, to keep pace with it, more recently work is in advancement on exploiting the biological system to increase the efficiency of bioremediation, using the latest technologies such as genetic engineering and nanotechnology. This paper provides an overview of the current methods deployed to address this problem, developments made in this field in past few decades, and evokes a research thrust that might lead to novel remediation approaches in the future.