Surface ozone (Surface O3)is a secondary pollutant and there are only limited studies on ozone in South India. Studies have revealed a strong correlation between higher ozone levels and warmer days. Surface O3 along with its precursors like NO2, CO and CH4 are being measured at Kanyakumari (8.0780° N, 77.5410° E), TamilNadu, India and in this paper we present the summer time variation of ozone from 2010to 2014 . Surface O3 showed a clear diurnal variation, but an irregularity was observed during the night time for all the measuring days of Summer 2014.There was a formation of a well pronounced secondary peak in Surface O3 during 0230 hrs accompanied by relatively strong wind patterns. Since the normal diurnal variation cannot explain this phenomenon,this uncertain behavior is probably attributed tolow NOX titrations and the downward mixing of ozone in the ground layer.The daily mean of Surface O3showed an increasing trend in the study area during the summer monthsand a negative correlation was observed with its precursors. The correlation of Surface O3 with temperature and wind speed for the entire summer season was found as r= +0.68, p= 4.314E-05 and r= +0.63, p

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.

Bioretention or rain garden is a preferable low impact development (LID) approach due to its characteristics which reflect natural water cycle processes. However, this system is still little understood and quite complicated in terms of design and implementation due to many technical considerations. Hence, this paper gives a review of the challenges and developments for the use of bioretention facilities to enhance its capabilities in attenuating peak flow and treating stormwater runoff particularly in urban areas. This paper reviews the main aspects of bioretention which are stormwater hydrologic, hydraulic and treatment performance. Some of the limitations during the implementation of this natural approach are highlighted in design configuration and the public perception towards this new approach. It is concluded that the bioretention approach is one of the sustainable solutions for stormwater management that can be applied either for individual systems or regional systems.

This research compares the performance of floating systems planted with Vetiveria zizanioides as a hydroponic approach for removing nutrients from two contaminated waters. For this purpose, two pilots with overall net volume of 60 litres were constructed and inoculated by secondary treated domestic wastewater (STDW) and irrigation water obtained from Minab reservoir (IWMR) in batch mode. Regarding the experimental results, the total nitrogen removal efficiency reaches more than 40 and 75%, in two and four days’ detention time, respectively, while these figures are 75 and 85% for phosphorus. The comparative statistical analyses verify that the results reveal significant differences in nitrogen removal, its uptake and the shoots’ dry weight. Conversely, phosphorus removal, its uptake and the roots’ growth are not significantly different. The regression analysis shows that the nitrogen uptake is well correlated with the shoots’ expansion rate as a matter of substrate type. The decay coefficient rates of nitrogen and phosphorus are calculated as 0.43 and 0.52 day-1, respectively. It is then concluded that this system should be used for wastewater treatment rather than for surface water purification. However, it can be recommended as an environmental friendly approach for both, because of the high efficiency in nutrients’ removal and the aeration capability.

In this paper, we present an application of evolved neural networks using a real coded genetic algorithm for simulations of monthly groundwater levels in a coastal aquifer located in the Shabestar Plain, Iran. After initializing the model with groundwater elevations observed at a given time, the developed hybrid genetic algorithm-back propagation (GA-BP) should be able to reproduce groundwater level variations using the external input variables, including rainfall, average discharge, temperature, evaporation and annual time series. To achieve this purpose, the hybrid GA-BP algorithm is first calibrated on a training dataset to perform monthly predictions of future groundwater levels using past observed groundwater levels and additional inputs. Simulations are then produced on another data set by iteratively feeding back the predicted groundwater levels, along with real external data. This modelling algorithm has been compared with the individual back propagation model (ANN-BP), which demonstrates the capability of the hybrid GA-BP model. The later provides better results in estimation of groundwater levels compared to the individual one. The study suggests that such a network can be used as a viable alternative to physical-based models in order to simulate the responses of the aquifer under plausible future scenarios, or to reconstruct long periods of missing observations provided past data for the influencing variables is available.

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.

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.

Agricultural waste fibers have been found to be suitable as reinforcement in cement-based composites, but studies on oil palm fiber as reinforcement in gypsum-cement wall panels are scarce. A mixture of two equal weights of gypsum and cement, with water-binder ratios of 0.45 and 0.55 were prepared. In each mix a varying percentage of fiber contents of 2%, 3% and 4% by weight of the binders were added. The properties of the wall panels were determined from cast specimen sizes of 100x 100 x 40 mm for density, moisture content and water absorption; 160 x 40 x 40mm for compressive strength, and 650 x 100 x 25 mm for bending strength. The specimens were cured in water and tested at ages of 3, 7, 14, 21, and 28 days. The results of density of the wall panels were within the range of 1634–1742 kg/m3, while the moisture content range of 3.30–8.45%, and the water absorption varies from 5 to 12%. The compressive strengths were found within the range of 1.92–5.20N/mm2 and, generally, decreases with the increasing percentage of fiber contents, but increased with curing age. The bending strength falls within the range of 2.04–4.13 N/mm2that increases with curing age and slightly increased with fiber content. It is concluded that oil palm fiber reinforced gypsum-cement wall panels are suitable as wall element.

Rajasthan is one of the main mineral potential state of India. During the last 30 years it has witnessed enormous expansion of mining industries, but mining of most of the minor minerals coupled with changing climate has posed serious problems to the environmental fabric in the state, apart from base metal beneficiation plants. Groundwater is also being polluted day-by-day by effluents generated from mineral wastes and beneficiation processes in the vicinity of mining sites such as Khetri. Pollutant concentrations were measured in groundwater at the vicinity of Khetri copper mining project, Rajasthan to investigate the influence of copper mining on environment. Pollutant concentrations in groundwater were investigated. Copper metal concentration in water samples were found above the maximum desirable limit in two sources: G4 and G5, due to washing away of mineral with water. Mining industry has deteriorated quality of groundwater resources in the state of Rajasthan, and these industries are becoming centers of pollution sources which need timely actions at government level so that natural resources such as groundwater can be protected.

This comprehensive work explores the research performed inoptimization of the collection bin and in recycle bin location-allocation issues in solidwaste management. Although the collection phase of solid waste management accountsfor a significant proportion of the municipal budget, it has attracted only limitedattention of the researchers. Optimization of the collection bin and recycle bin location-allocation problems in solid waste management can be advantageous with respect to binaccess to every individual person of municipality, reduction in the numbers of opendumping yards, considerable profit if the recycled products are properly processed, andas an effort toward sustainable and green world. Hence, the topic of interest should bepursued, especially in developing countries, to enable development of a cost-efficient and sustainable solid waste management system.