The present study monitors BTEX concentration in outdoor and indoor air of eight different microenvironments during summer 2017 and winter 2018 at Asaloyeh city, Iran's energy capital. It samples BTEX compounds by charcoal tubes, analyzing the samples by means of a gas chromatograph with a flame ionization detector. According to the obtained results, outdoor concentrations of BTEX have been higher than the indoor ones, for both seasons, with the highest outdoor and indoor BTEX being 21.70 and 18.59 μg/m3, respectively. Toluene has been the most abundant substance, among the investigated BTEX in all sampling points. Based on the MIR scale, m, p-xylene is the most dominant contributor to ozone formation potential among BTEX species. Indoor to outdoor (I/O) ratios of BTEX compounds range from 0.53 to 0.88 and 0.41 to 0.77 in winter and summer, respectively. The cumulative hazard index (HI) is within an acceptable range. The LTCR value of benzene concentration, obtained, exceeds the value of 1.0E-06, recommended by USEPA. Sensitivity analysis shows that benzene concentration, exposure duration, and inhalation rate have a greater impact on health risk assessment.

Finding an environment-friendly and affordable method to remove contaminated soils from Polycyclic Aromatic Hydrocarbons (PAHs) has now become an attractive field for researchers, with super-critical fluid extraction being an innovative process in the field of contaminated soil treatment. Extraction with super-critical fluid is a simple and rapid extraction process that uses super-critical fluids as solvents. The present study has investigated the extraction of contaminated soil with Polycyclic Aromatic Hydrocarbons (PAHs) by means of batch supercritical water reactor, employing variables like pressure (100–300 bar), temperature (60–140 ◦C), residence time (0.5–3 hours), and base, acidic, and neutral pH values. In order optimize the process parameters, Response Surface Methodology (RSM) has been used. Results show that removal efficiency of PAHs is between 82%-100%, where the highest PAHs removal efficiency (100%) has been observed in Test No. 22, with a pressure of 300 bars, temperature of 500°C, acidic pH equal to 5, and duration of 3 hours. In addition, the lowest removal efficiency of these compounds (82%) has been obtained in Test No. 26, with a pressure of 300 bars, temperature of 350°C, base pH of 9, and duration of half an hour. According to the results from this study, it has become clear that residence time is the most important and most effective parameter for removing PAHs from contaminated soil. Afterwards, temperature and pH are most influential with pressure showing the least effect. Using supercritical water method in appropriate conditions can eliminate more than 99% of aromatic contamination.

The present research investigates the ability of graphene oxide nanosheets for treatment of dairy wastewater, using In Situ Sludge Magnetic Impregnation” (ISSMI) to separate sludge after adsorption process. To increase the interaction between magnetic nanoparticles and graphene oxide, the former has been functionalized, using 3-Aminopropyl triethoxysilane, with the synthesized graphene oxide and magnetic nanoparticles being characterized by FT-IR, SEM, and NCHS analysis. The experiments have been conducted on the effluent of Pegah factory. The batch adsorption experiments have been carried out to investigate the effect of adsorbent dose, contact time, and pH on the removal of total nitrogen, total phosphorus, COD, and turbidity. At adsorbent dose of 320 mg L-1, the removal efficiencies of 90, 80, 84, and 94% have been observed for TN, TP, COD, and turbidity, respectively. The adsorbent data has been modeled by Langmuir and Freundlich isotherms, giving results that are compatible with Freundlich isotherm. TN, TP, and COD are mostly particulate materials in dairy wastewaters; therefore, when nanosheets aggregate, particulate materials are trapped between GO nanosheets; as a result, pollutants are distributed heterogeneously on the adsorbent's surface. Consequently, adsorption does not occur as monolayer on the surface of GO; for this reason, adsorption follows Freundlich model. Maximum absorption capacity of the adsorbent turns out to be 730 mg g-1 for total nitrogen, 600 mg g-1 for total phosphorus, 26000 mg g-1 for COD, and 5500 mg g-1 for turbidity. Adsorption kinetic has been studied with the first and second order equation, giving results that are compatible with second order equation.

The present study is the first attempt to examine temporal and spatial characteristics of aerosol properties and classify their modes over Iran. The data used in this study include the records of Aerosol Optical Depth (AOD) and Angstrom Exponent (AE) from MODerate Resolution Imaging Spectroradiometer (MODIS) and Aerosol Index (AI) from the Ozone Monitoring Instrument (OMI), obtained from 2005 to 2015. The high concentration of AOD and AI values (representing high-high cluster) have been observed in the southwest and east regions, while their low concentrations (representing low-low cluster) have been found in the high mountainous areas. Based on AE values, Iran has been divided into three distinct regions, including fine, mixture, and coarse aerosol modes in each season. Results show that the maximum/minimum area under fine aerosols mode has occurred in the autumn, covering an area of 84.15% and in the spring, covering an area of 40.5%. In the case of coarse mode, the maximum/minimum area has been found in the spring, covered area=53.5% / in the Autumn covered area=12. 5%. The different aerosol modes regions strongly coincide with the topographical structure. To analyze the relation between aerosol properties and topography, Aerosol Properties Index (API) has been developed by combining OMI and MODIS datasets. API is a simple indicator, capable of showing the degree of aerosol coarseness in each pixel. There is a negative correlation between API and topography over the studied region, meaning that aerosol concentrations are high in the lowlands, but low in the highlands. However, this relation differs in various geographic regions, as Geographically Weighted Regression (GWR) model shows a higher determination coefficient in all seasons, in comparison to Ordinary Least Squares (OLS).

Anthropogenic noise is debatably one of the most common threats to national parks' resources. Park visitors and workers generally suffer from adverse effects of noise from on- and off-road vehicles. The parks, studied here, are located in strictly urban areas, surrounded by streets with intense vehicle traffic. This study assesses the soundscape of urban parks in two cities of Odisha State, on the basis of acoustic field measurements and interviews. Noise descriptors in and around three different parks in Bhubaneswar and Puri cities have been measured and analyzed. A field experiment has been conducted with 330 participants in three parks, representing urban natural environment. The questionnaire comprised identification of the interviewee, characteristics of the user's profile in terms of his/her use of the park, and aspects of individual’s perception of the soundscape and environmental quality of the park. Positive correlation has been established among the noise levels of these three parks. The present study reveals that the acoustic sound levels of all the investigated parks are more than 50 dB (A) [permissible limit, established by Central Pollution Control Board (CPCB) for green parks]. Considering the urban elements and acoustical characteristics, it can be concluded that all the parks are affected by several factors such as urban planning, land use, main traffic routes, type of public transportation, and its internal sounds.

Even though solid waste management has become a major public health and environmental concern in urban areas of Ethiopia, only 2% of the population receive solid waste management services. The primary objective of this study is to assess solid waste management practices of Bahir Dar City. The technique of multistage random sampling has been employed to draw 350 households for this study, with both quantitative and qualitative primary data put into good use. Finally, the quantitative data has been analyzed by means of descriptive statistics with the results indicating that 78% of the respondents feel that the current solid waste management service is far below the required level; whereas, 22% of the respondents show satisfaction with the existing waste management service. The municipality has planned to provide solid waste management service for the residents once a week, but the survey results demonstrate that only 29% of the sample households received solid waste management services weekly, indicating that the performance of solid waste management service is low. Among 350 households, a sum of 66.6% practice illegal solid waste disposal with the remaining 33.4% waiting until solid waste collectors come to the area to take the waste away. Therefore, participation of urban households, micro and small enterprises, and governmental and non-governmental organizations plays a great role to upgrade the existing low status of solid waste management services.

The association of the emergence of bacterial resistance to clinical environments is common; however, aquatic environments, especially the polluted ones, also play a key role in this regard. Aquatic environments can act as facilitator for the exchange of mobile elements, responsible for resisting antibiotics. They even may stimulate the emergence and selection of these elements through contaminants or the natural competition between bacterial phyla. Currently there is a large number of highly-reliable resistance genes, which is selected in aquatic environments, mostly due to several types of pollution, such as the mcr-1 gene that causes resistance to one of the antibiotics, available in the market, namely colistin. Thus, the present review aims to show a range of impacts capable of selecting bacterial resistance in the environment, thus clarifying this environment's role in dispersion of resistance.

Acid rain still poses a global problem today, exerting many adverse effects on man, animal, and materials. As its research question, the present study tries to find out whether or not acid rains exist in Akure, Nigeria. For so doing, it determines physico-chemical properties of rain water samples, namely pH, temp, Electrical Conductivity (EC), TDS, acidity, SO4-, NO2-, Cl-, and Free CO2. According to the results, the pH ranged between 6.0 and 7.8, never falling below 5.6 which is an indication of acid rain. Also, the minimum EC was 3µS/cm and the maximum, 201µS/cm. Moreover, TDS was between 1 and 100mg/L, while Free CO2 had a mean of 23.00 and Standard Deviation of 6.16. The dominant ion was SO4- (10-11%), followed by NO3-, and Cl-. Results from the first six months (July-December 2015) reveal slight correlations in the following: TDS with pH (0.532), EC and pH (0.501), Temp and Free CO2 (0.59), whereas strong correlations have been recorded in the following parameters: Acidity with pH (0.71) and Temperature (0.69), NO2- with pH (0.96) and acidity (0.96), SO4- with temp (0.68) and NO2- (0.83), and finally Cl-  with Free CO2 (0.61), NO2- (0.73), and Cl- (0.65). It can be concluded that in the environment under this study there have been no acid rain within the period.

The present study aims at designing a promising Microbial Fuel Cell (MFC) to utilize wastewater in order to generate electricity. Two types of salt bridge have been used in MFC (KCl and NaCl). The maximum electricity generation with 1M KCl and NaCl has been 823 and 713 mV, respectively. Varied salt concentrations (0.5M, 1M, 2M, and 3M) of salt bridge in MFC have been analyzed with different factors like temperature, type of electrode, configuration, and surface area of electrode being studied. The optimum temperature is found to be 32Co, with the optimum type of electrode being graphite rod, while the optimum configuration and surface area of electrode is graphite plate with surface area of 183.6 cm2. Artificial Neural Network (ANN) has been employed to predict voltage production of MFC and compare it with the experimental voltage. Multiple   correlation methodology has optimized the voltage production with the correlation coefficient (R2) being 0.999.

As the largest service industry in the world, tourism plays a special role in sustainable development. Geomorphic tourism is known to be a segment of this industry with lower environmental impact and underlying causes that explain lower demand; therefore, it is essential to study, identify, assess, plan, and manage natural tourist attractions. As such, the present study assesses the ability of geomorphological landforms of Haraz watershed, one of the major tourism areas of Iran. In this regard, the features of geomorphologic landforms, including Mount Damavand, the Damavand Icefall, Shahandasht Waterfall, Larijan Spa, and Deryouk Rock Waterfall in different parts of the Haraz watershed have been compared from the standpoint of geotourism features. To assess these landforms, geological maps, topographic and aerial photos, satellite imagery, Geographic Information Systems (GIS), and data field have been used as research tools. Evaluation results demonstrate that the average of scientific values in these landforms’ catchment (with 0.76 points) has been greater than the average of other values. These high ratings show the landforms’ potentials to be informative to those examining them for the purpose of education as well as tourist attraction. Through proper planning and understanding of its both merits and demerits, this type of tourism can play an important role in national development and diversify regional economies.