Water samples have been collected from a part of Surma River along different points and analyzed for various water quality parameters during dry and monsoon periods. Effects of industrial wastes, municipal sewage, and agricultural runoff on river water quality have been investigated. The study was conducted within the Chattak to Sunamganj portion of Surma River, which is significant due to the presence of two major industries-a paper mill and a cement factory. The other significant feature is the conveyors that travel from India to Chattak. This study involves determination of physical, biological and chemical parameters of surface water at different points. The river was found to be highly turbid in the monsoon season. But BOD and fecal coliform concentration was found higher in the dry season. The water was found slightly acidic. The mean values of parameters were Conductivity 84-805µs; DO: dry-5.52 mg/L, monsoon-5.72 mg/L; BOD: dry-1 mg/L, monsoon-0.878 mg/L; Total Solid: dry-149.4 mg/L, monsoon-145.7 mg/L. A model study was also conducted and values of different model parameters were estimated.

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This paper formulates a multidimensional choice model system that is capable of handling multiple nominal variables, multiple count dependent variables, and multiple continuous dependent variables.The system takes the form of a treatment-outcome selection system with multiple treatments and multiple outcome variables. The Maximum Approximate Composite Marginal Likelihood (MACML) approach is proposed in estimation, and a simulation experiment is undertaken to evaluate the ability of the MACML method to recover the model parameters in such integrated systems. These experiments show that our estimation approach recovers the underlying parameters very well and is efficient from an econometric perspective. The parametric model system proposed in the paper is applied to an analysis of household-level decisions on residential location, motorized vehicle ownership, the number of daily motorized tours, the number of daily non-motorized tours, and the average distance for the motorized tours. The empirical analysis uses the NHTS 2009 data from the San Francisco Bay area. Model estimation results show that the choice dimensions considered in this paper are inter-related, both through direct observed structural relationships and through correlations across unobserved factors (error terms) affecting multiple choice dimensions.The significant presence of self-selection effects (endogeneity) suggests that modeling the various choice processes in an independent sequence of models is not reflective of the true relationships that exist across these choice dimensions, as also reinforced through the computation of treatment effects in the paper.

Transport sector is a major consumer of energy. Concern of energy scarcity and price fluctuations enhanced significance of transport sector in national planning. This paper analyses energy demand for transport services in Bangladesh for different policy scenarios. Aggregate transport demand model is integrated into Long-range Energy Alternatives Planning model to forecast consequences of transport policy on energy demand and economy. Demand for imported energy for transport sector is observed to increase from 1.7 million ton of oil equivalent (Mtoe) in 2005 to 11.8 Mtoe in 2030 for business-as-usual scenario. In increased fuel price scenario, cost of importing fuel for transport sector is projected to increase from 1.37 to more than 14.9 % of Gross Domestic Product during the same period. Country's energy demand may be reduced by 2 and 4 Mtoe in 2030 by improvement of waterway and railway, respectively. Moreover, by using compressed natural gas in motor vehicles cost of importing fuel may be reduced by US $5 billion annually in 2030 and a further reduction of transport sector energy demand by 9 % can be achieved through eliminating subsidy on fuel.