Issue 2

In this study, Mieczkowski's Tourism Climate Index (TCI) was used for Iran to investigate the climate change impacts on outdoor human comfort. The long-term data covering a network of 153 stations were used to compute TCI under baseline conditions (1981–2015) and a climate change scenario (HadCM3-A1B) for 2016-2045. In this study LARS-WG was used for downscaling of large spatial resolution GCM outputs to a finer spatial resolution. User-friendly and multi-platform software which is called ITCIC (Iran Tourism Climate Index Calculator) was designed to calculate TCI. The spatial distribution of TCI for baseline and climate change conditions was investigated and the covered area by each TCI class was calculated by using ArcGIS 10. The annual distributions of TCI were investigated based on Scott and McBoyle (2001) Models. Also, a suite of multiple linear and non-linear regression models was used to determine the relationship between TCI, latitudes, longitudes and elevations of regions. Root mean square error (RMSE), mean error (ME), mean absolute relative error (MARE) and coefficient of determination (R2) were used to evaluate the modeling accuracy. The best time and regions for outdoor activities in the base and future periods were determined. Comparison of the covered area by each TCI class in the base and future periods showed that the climate change occurrence was led to improving climate comfort. The results of error evaluation criteria showed that non-linear regression was appropriate for all month except January and October.

Municipal solid waste generation in Malaysia has increase significantly. Organic materials continue to be the major portion of solid waste generated in Kampar, Malaysia. As a result of increasing rate of waste generation and population growth, land area will become more demanding causing the increment of the cost in solid waste management. As a result, solid waste management will become more expensive in the future. Waste separation and organic composting can provide good solution in reducing waste disposal. Nevertheless, public awareness is an important key to improve solid waste management issue. During this study, questionnaire was designed to test out public general knowledge regarding waste management, and their willingness to do composting. 270 questionnaires were distributed to the public. Data analysis of the questionnaire shows that only a few of the respondents (24 numbers) have good awareness. Likert scale was applied to prioritize the factors that discourage waste separation and organic composting practices in Kampar District. This paper concluded that public education and awareness toward solid waste minimization using composting is crucial.

This study focuses on the impact of the disposal of Tirunelveli city municipal waste in the quality of groundwater in Ramayanpatti village where the waste is disposed; the study also assesses the quality of the groundwater suitability in irrigation in the disposed region. Tirunelveli city generates municipal waste of nearly 15 MLD of domestic wastewater and 100 tons of solid waste in a day. The domestic wastewater is treated by waste stabilization pond. The solid waste is dumped in the open yard. These two disposal sites are located in the Ramayanpatti area and their boundaries are at a distance of 500m from each other. Ground water resources are extracted in use for agriculture in the area of Ramayanpatti. Around thirty, locations have been identified in the Ramayanpatti area for sampling, based on the contour and flow direction. The dominant chemical cation species in the majority of the groundwater samples are in the order of Na>Ca>Mg>K and anion species are in the order of HCO3>Cl>SO4>NO3. Gibbs plot shows that the region is dominated by evaporation and dilution phenomenon. Rhode’s plot shows that there is no reduction in the rate of infiltration of soil in the Ramayanpatti region. Dendrogram shows that the leachates infiltration is predominant in the winter season. The study shows that the groundwater quality, nearer and to the southeastern side of the disposal sites are most affected and contaminated by solid waste leachates. The inference with various irrigation plots show that the quality of groundwater in the southeastern region is doubtful for use in irrigation and the groundwater needs to be assessed in order to use in irrigation for agriculture.

Multivariate statistical analysis including cluster analysis, factor analysis and correlation coefficient was applied to the groundwater samples to understand the groundwater condition in Wadi Bani Malik area. Water samples collected from the study area were analysed for physical parameters, major cations and major anions. The groundwater quality is not good in this area and the physicochemical parameters go beyond the acceptable limits of the Kingdom of Saudi Arabia and WHO drinking water standards. The water type in the study area was primarily NaCl. Correlation coefficients were determined among different parameters and then regression analysis was performed to realize the linear relationship between the best correlated parameters. Results of factor analysis specify that factor 1 is dominant and is responsible for 45.5% of the total variance and is dominated by Cl-, Na+, Mg++ and K+. Ground water samples can be divided into four clusters.