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.

Air Pollution Tolerance Index (APTI) is an important tool to screen out plants, based on their tolerance or sensitivity level to different air pollutants. The present study has been conducted to evaluate APTI of four different plant species around polluted and unpolluted industrial site in Sfax, Tunisia. In order to determine the susceptibility level of the selected plant species, it has used four physiological and biochemical parameters like leaf relative water content, ascorbic acid content, chlorophyll content, and leaf pH to compute the APTI values. The results of the study reveal that among the four studied plant species, Olea europaea (APTI = 20.09) and Phoenix dactylifera (APTI = 17.10) are the most tolerant species, whereas Ficus carica (APTI = 8.87) and Morus alba (APTI = 7.49) are the most sensitive ones. The present study suggests that the most tolerant species, i.e., olive and date palm, can be planted in polluted sites for both air pollution abatement and aesthetic improvement. While, the sensitive species, namely common figand white Mulberry, help indicating air pollution and should be utilized as bio-indicators.

Emphasis on sustainable development and the need to protect the environment as well as the adverse effects of environmental pollution on the quality of life have made environmental protection one of the main concerns of economic policymakers. For this purpose, approaches to improve the quality of the environment and the factors affecting it have triggered extensive theoretical and empirical studies over the past few decades. These issues have caught the attention of economic analysts. Accordingly, the main objective of this study is to investigate pollution determinants in developing countries from 1996 to 2016, using  Bayesian Model Averaging Method. Given the fact that the weighted mean square coefficient of GDP is positive, the Environmental Kuznets Curve (EKC) Hypothesis can be confirmed with a high degree of certainty. The probability of  this variable's effect is 0.98%, being partially a component of each of the 10 optimal models which highlights the great importance of this variable to explain the environmental performance. Energy consumption variables for each unit of GDP and value added of industry sector are placed in the second and third ranks with effectiveness  probability of 0.89 and 0.85, respectively. They also have a negative impact on environmental performance. Thus, energy consumption per unit of GDP is considered one of the elements of 8 out of 10 optimal models, while the value added of the industrial sector is an element of 7 out of 10 models. This highlights the relative importance of these variables in explaining environmental performance.

The study has been carried out to assess surface water quality of Old Brahmaputra River from September 2015 to March 2016. DO, BOD5, COD, pH, EC, Chloride, Alkalinity, and Hardness concentrations in water samples have been found to range within 0.66-2.9 mg/L, 21-138 mg/L, 45-250 mg/L, 7.1-7.8, 185-1080 uS/cm, 10-98 mg/L, 85-197 mg/L, and 84-148 mg/L, respectively. Multivariate statistical analyses such as Principal Component Analysis (PCA) and Correlation Matrix (CM) reveal significant anthropogenic intrusion of pollutants in water, while Cluster Analysis (CA) gives decent results that render three different groups of resemblance between the two sampling sites, reflecting the different water quality indicators of the river system. Very strong positive linear relations have been found between Alkalinity vs. Chloride (0.998), COD vs. BOD (0.994), Chloride vs. EC (0.981), Alkalinity vs. EC (0.976), and Hardness vs. EC (0.952) at the significance level of 0.01, which direct their common origin from industrial effluents, municipal wastes, and agricultural activities. River Pollution Index (RPI) indicates that the water of the Old Brahmaputra River varies from low to high pollution.

Surface waters become more and more polluted, depending on human activities around them. The current study has been conducted to evaluate the impact of Syrian civil war on water quality of the Turkish part of Orontes River. For so doing, it has obtained monitoring data between 2006 and 2014 from state of Hydraulic Works of Turkey, analyzing them via Water Quality Index (WQI) and Principal Component Analysis (PCA). WQI reveals that water quality in Orontes River has dropped sharply after 2011 and slightly improved by 2013. This time interval overlaps with Syrian civil war when conflicts between regime forces and dissidents occurred densely. Therefore, it can be concluded that Syrian civil war has impacted the water quality of Turkish water’s with potential causes of water quality degradation identified as polluters from conflicts and immigration activities. In addition, this research has conducted PCA to investigate indicator parameters, representing the water quality variation as a result of war. Results showed that NO2- and NO3- concentration in the surface water can be used as main indicators of Syrian civil war's impact on water quality. Finally, it may said that anthropogenic activities happening in the Turkish part of the watershed also contribute to the pollution level of river, especially domestic and industrial discharges.

Wind erosion is considered a major global environmental problem. Dust storms from the migration of sand dunes can seriously damage civil, industrial, and agricultural areas and a method to stabilize these sand dunes is mulching. The present study investigates the feasibility of using organic wastes of Press mud and Dunder with clay for the production of environmentally-friendly mulches. Sandy soil from the Dejgah Region, Fars Province, has been used as bed treatment. The treatments have been prepared, using different ratios of the above mentioned materials and 250 ml of water has been added to the each mulch combination to be sprinkled on a plot of sand, 50 × 30 × 1 cm in size. The research has measured Mechanical parameters such as Compressive Resistance (CR), Abrasion Resistance (AR), and Impact Resistance (IR), created by mulches, along with Wind Erodibility (WE) of the treatments and has analyzed the resultant measured data by means of SPSS software. An increase in the fraction of organic wastes has significantly increased CR, IR, and AR values, thus reducing WE. Higher amounts of organic matter and clay increase the CR and the application of 100g Dunder plus 100g Clay has been considered the best composition of organic mulch for stabilization of sand dunes.

Industrialization releases significant amounts of various air pollutants such as F, Cd, Pb, particulate matter, etc., which can in turn have a deleterious effect on a variety of biochemical and physiological processes as well as the structural organization within the cells. Responses from plants species to air pollutants is varied with certain species being very sensitive to such pollutants, ending up with well visible and measurable symptoms. Morphological damage is generally visible through lesions on the aerial parts, while biochemical and physiological changes which are invisible can be measured and quantified. This study has been designed to investigate the biochemical and physiological biomarkers of apricot (Prunus armeniaca L.) exposed to air pollution. It has been observed that, in comparison to unpolluted sites, lipid peroxidation level has increased in the leaves of apricot trees, grown in polluted areas, whereas photosynthetic capacity (Net photosynthesis, stomatal conductance, transpiration rate, total chlorophyll, and carotenoids) along with osmotic regulator (proline and soluble sugars) levels have declined. In P. armeniaca leaves, these symptoms can be used as indicators of air pollution stress for its early diagnosis, making them a reliable marker for a particular physiological disorder.