Climate change is a complicated issue with many factors playing role in its formation and distribution. Considering this complication, a comprehensive and holistic approach is needed for a better understanding and management of those factors. The causal frameworks are among systemic and integrated methods for addressing the causes of environmental problems and the relationships that exist between the environmental systems in order to propose proper solutions. The DPSIR model is a functional analysis framework that depicts the cause-effect relationships that exist in creating environmental problems. Tehran is one of the major megacities in the Middle East that faces environmental consequences of overpopulation and unplanned urban sprawl, and being located in an arid region, makes it vulnerable to rise of temperature and reduction of precipitation. In this research, by using the DPSIR framework, different aspects of climate condition of Tehran are analyzed and later with the help of this conceptual framework, strategies for controlling climate change are presented.

Today, ecotourism is a major tourist activity around the world. It is based on environment potential through which suitable utilization and conservation of sites under management practices including considering accurate planning, potential, and peoples’ preferences are realized. The present study was conducted to determine people’s recreational preferences using questionnaires to evaluate the ecotourism potentials (recreational activities that choice in questioner by visitors) for site selection and land use planning, and to analyze the functional relationships among zones in the MianKaleh wildlife sanctuary, south of the Caspian Sea in Mazandaran and Golestan Provinces of Iran. Recreational preferences of people were found to be bird watching, swimming, camping, sightseeing, horse riding, and boating. Multi Criteria Evaluation was used to assess the ecotourism potential. For land use planning, the Multi Objective Land Allocation function included environmental suitability maps, zone weighting, and a set of desirable areas for each zone. Post processing functions (filters, zone size, and distance to other zones) and functional relationship diagrams were applied to amend the zoning maps. The functional relationship diagram concept was applied to the amended maps for optimizing access and identifying the relationships among zones. Overall, the results revealed that MCE and MOLA methods are capable of evaluating and zoning the wildlife sanctuary. Furthermore, post-processing and functional relationship diagrams were effective in selecting recreational sites. The results of this research revealed the recreational potential of MianKaleh wildlife sanctuary. Land planning for ecotourism can now be implemented using the results of this study that will upgrade the conservation status in the area.

Bioremoval and bioreduction activities of hydrocarbon (diesel) isolation from environmental samples were studied by the activity of biosurfactant production, and calculating emulsification index, gravimetric, and FTIR analysis along with the estimation of bacterial biomass. Sample from soil near petrol, diesel pumps and water sample from Thesjaswini River near Padannakad, Kasaragod, Kerala, India, were used to screen the potential diesel oil utilizing bacteria. Among the bacterial isolates (Staphylococcus, Bacillus and Corynebacterium strains), Staphylococcus sp was the potent degraders of diesel oil. Staphylococcus strain was observed to be maximum diesel oil utilizing ability (73% emulsification index) and change in the functional groups of the compound (FTIR analysis). The strain showed optimal growth at 37oC with pH 7, agitation of 150 rpm and time period (5days). The results revealed the possibility to use these strain for the reduction of complex hydrocarbon in ecosystems where they accumulate and cause pollution problems. The highest rate of hydrocarbon degradation occurred when the bacterial strain is a biosurfactants producer. The selective strain produces biosurfactants which increase the interfacial area for contact to give improved uptake of hydrophobic substrates. Bacterial strains capable of degrading complex hydrocarbons, present in the environment, have a potential to be used as an effective tool for removing ecotoxic compounds. Furthermore, results indicated that the bacterial strain Staphylococcus sp could be potentially used in biodegradation of diesel oil in waste water and had a promising application in bioremediation of hydrocarbon contaminated environments.

The concentration of selected trace metals (Fe, Cd, Cu, Pb, and Zn) in 30surface sediments were measured using Atomic Absorption Spectrometer to investigatethe spatial and seasonal variations of trace metals along Kanyakumari coast, India. Toassess the environmental risk of trace metals, enrichment factor, geo-accumulation index,pollution load index, and ecological risk index have been calculated. According to thepollution load index and geo-accumulation index (Igeo) values, Kanyakumari coastalsediments were unpolluted by Fe, Cu, Pb, and Zn, whereas moderately polluted by Cdwith low to moderate ecological risk. The existence of the high hydrodynamic conditionduring the southwest monsoon is more favorable to the transport of sediments andenhance the accumulation of metals, whereas during the northeast monsoon theaccumulation of metals is less. The baseline data for spatial distribution and seasonalvariation of trace metals and their controlling factors found in this study will be useful forpollution monitoring program along the Kanyakumari coast.

Air pollution is a challenging issue in some of the large cities in developing countries. Air quality monitoring and interpretation of data are two important factors for air quality management in urban areas. Several methods exist to analyze air quality. Among them, we applied the dynamic neural network (TDNN) and Radial Basis Function (RBF) methods to predict the concentrations of ground-level ozone in Karaj City in Iran. Input data included humidity, hour temperature, wind speed, wind direction, PM2.5, PM10 and benzene, which were monitored in 2014. The coefficient of determination between the observed and predicted data was 0.955 and 0.999 for the TDNN and RBF, respectively. The Index of Agreement (IA) between the observed and predicted data was 0.921 for TDNN and 0.9998 for RBF. Both methods determined reliable results. However, the RBF neural network performance had better results than the TDNN neural network. The sensitivity analysis related to the TDNN neural network indicated that the PM2.5 had the greatest and benzene had the minimum effect on prediction of ground-level ozone concentration in comparison with other parameters in the study area.

An ever-increasing drift of energy consumption, unequal geographical distribution of natural wealth and the quest for low carbon fuel for a cleaner environment are sparking the production and use of biodiesels in many countries around the globe. In this work, jatropha and karanja biodiesels were produced from the respective crude vegetable oils through transesterification, and the different physical properties of the produced biodiesels have been presented and found to be acceptable according to the ASTM biodiesel specification standard. This paper presents the experimental results of the research carried out to evaluate the BTH, BSFC exhaust emission characteristics of jatropha and karanja blends in a single-cylinder diesel engine at different engine load. Comparative measures of brake thermal efficiency, smoke opacity, HC, CO, and NOx have been presented and discussed. Engine performance, in terms of higher brake thermal efficiency and lower emissions (HC, CO, NOx) with jatropha-based biodiesel (JB50) operation, were observed compared to karanja-based biodiesel (KB50).

This paper examines the relationship between domestic water sources, demand and associated problems in the context of a rapidly increasing household population in Nassarawa Eggon town, Nasarawa State, Nigeria. The data for this research were generated using a questionnaire survey of systematically selected households, and analysed using descriptive statistics in the form of frequencies and percentages, and are presented as tables and graphs. The study revealed that the major sources of water in the area are hand-dug wells and streams, with no pipe-borne water. This has greatly affected the inhabitants of the locality, resulting in cases of water-related diseases. Consequently, due to the recent inter-communal and ethnic crisis in some parts of the local government area and the state, which led to massive immigration of people into Nassarawa Eggon, pressure on the available sources of domestic water has intensified, resulting in insufficiency in meeting domestic water demand. Against this backdrop, the paper seeks to examine in detail the various sources of domestic water and the problems associated with accessing it.

The main objective of this study was to reveal the impact of nine climate indices on temperature changes and climate oscillations in Golestan Province along the southern coast of the Caspian Sea. Climate indices data from across the Atlantic-Eurasian sector were collected from the NCEP/NCAR, the Climate Prediction Centre (CPC) and the Climatic Research Unit (CRU) over a period of 40 years (1971-2010). The climate indices are then compared and correlated with temperature observations from 47 weather stations collected from meteorological and energy organizations. The correlations are based on the 12-month moving average. The study results show a significant increasing temperature trend in most months over different regions of Golestan. For maximum temperature, a significant increasing trend was seen in 55.64, 41.8 and 40% of the land area in the province during August, June and July, respectively. In general, summer had the most significant maximum-temperature trends, with an average of 37.8% of the land area. On the other hand, increasing minimum-temperature trends were seen in 58% of the land area of the province compared to the other seasons. It was concluded that there is high correlation between climate indices and temperature components. The correlation coefficients obtained for various indices including North Atlantic Oscillation (NAO), North Sea Caspian Pattern (NCP), Arctic Oscillation Index (AO), East Atlantic (EA), East Atlantic/West Russia (EATL/WRUS), Atlantic Multi-decadal Oscillation (AMO), North Tropical Atlantic (NTA), Polar/Eurasia (PE), and Scandinavia teleconnection index (SCAND) suggest an inverse relationship between these indices and temperature components. Therefore, the higher the values of these indices, the lower the temperature values, and vice versa.

Bedload transport is an essential component of river dynamics and estimation of its rate is important to many aspects of river management. In this study, measured bedload by Helley- Smith sampler was used to estimate the bedload transport of Kurau River in Malaysia. An artificial neural network, genetic programming and a combination of genetic programming and a neural network were used to estimate the bedload carried in Kurau River, based on bedload transport measurement data and hydraulic variables. A statistical analysis was carried out to validate methods by computing RMSE, MARE and inequality ratio (U). In general, the ability of the artificial neural network combined with genetic programming with R2 equal to 0.95, RMSE equal to 0.1 as a precipitation predictive tool for predicting the bedload transport rate was observed as being acceptable.

Regarding the importance of the prevention of hazards and adverse environmental impacts in industrial and populated areas such as southern parts of Tehran city, the response of impulsive period ground-supported tanks were assessed. Having considered the study area's soil properties, the response of ground-supported tanks was modelled. Regarding the soil properties of southern parts of Tehran, the soil structure interaction method explained in FEMA 368 revealed that the interactional impulsive period (~T) was greater than non-interactional one (T). In addition, results showed that Poisson's ratio and stiffness ratio (K/Kx) were more effective regarding the response of the interactional period of ground-supported tank systems. According to the achieved results, the liquid mass density effect on impulsive period was as low as the thickness of the ground-supported walls effect. Results showed that wall materials significantly affected the variation within the impulsive period. Generally, concrete materials were shown to be more periodic than steel materials. Overall, in southern parts of Tehran, when the soil fluid structure interaction method was used, the period increased from 1 to up to 3.6 times greater than the normal impulsive period.