Abstract

In recent years, the surface water quality has been observed deteriorating due to industrial activities and pollution in the Punjab state. Evaluation of surface water quality is an important issue to assure from its safe and stable use. However, describing quality conditions is generally difficult considering spatial variability of pollutants and a wide range of indicators like biological, physical and chemical substances which can be measured. This paper includes the study of surface water quality parameters in the northern Punjab region. Samples from different sources across northern Punjab were analysed for pH, TDS, TSS, turbidity, DO, chloride content, iron content and hardness of surface water. The pH, TDS, TSS, turbidity, DO, chloride content, iron content and hardness were found in the range of 6.7-8.7, 1358.00-1430.60 mg/l, 135.10-141.21 mg/l, 0.001-0.62 NTU, 0.96-7.80 mg/l, 0.80-15.56 mg/l, 0.01-0.02 mg/l and 1.2-13.9 mg/l respectively. The obtained results were compared with the acceptance limits as given by Indian standard code IS: 10500-2012. The high values of water quality parameters obtained as a result of this study indicates the level of pollution of the different sources of surface water of northern Punjab. At the end the obtained results were critically examined and suggestions were made for better management of surface water resources. An efficient transportation system is vital to economic development and a sustainable environment in a country. India's road transportation contributes to approximately 5.4% of the GDP carrying 65% of freight traffic and 85% of passenger traffic. India's fuel imports are growing at an average of 18% annually for which India spends 3.5% of GDP, thereby posing a major threat to the economy of the country in the future. Also, the use of such a high quantity of fuel causes vehicular pollution, which is responsible for fuel emission in urban areas. This study concentrates on carrying out an interdisciplinary work involving the sectors of transportation, energy, and environment considering the parameters like vehicle model split, fuel consumption and vehicular emissions. This is done by building, System Dynamics (SD) forecasting simulation models using STELLA software to mathematically forecast these parameters in the upcoming years until 2030. Hence, a scenario of augmenting the growth rate of public transportation and simultaneously restricting the growth rate of personalised transportation showed a substantial decrease in fuel consumption and fuel emissions, which eventually resulted in a reduction of fuel cost as well as an increase in the GDP in the transportation system for Chennai city

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