Environmental Management
A. Jaiswal; C. Samuel
Abstract
BACKGROUND AND OBJECTIVES: The study provides an assessment of fuel wastage, particulate matter particles pollution, and noise pollution at three toll booths near district Varanasi, India. The objective of the study is to analyze the effects of vehicle idling conditions on road tolls in terms of pollution ...
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BACKGROUND AND OBJECTIVES: The study provides an assessment of fuel wastage, particulate matter particles pollution, and noise pollution at three toll booths near district Varanasi, India. The objective of the study is to analyze the effects of vehicle idling conditions on road tolls in terms of pollution and fuel wastage.METHODS: The study used mathematical formulation on queuing observations for assessment of fuel wastage due to vehicle idling at toll booths. Handheld device HT-9600 Air Particle counter was used for getting the readings of PM2.5 and PM10. SL10 noise meter of Extech Instruments was used for measuring the noise levels at the selected three toll booths of Dafi Toll Booth, Lalanagar Toll Booth, and Mohania Toll Booth.FINDING: The study assessed a greater extent of fuel wastage at all the three toll booths with maximum fuel wastage at Dafi Toll booth due to vehicle idling. In terms of air pollution, severe levels of particulate matter particles were observed over all the three toll booths. The noise levels over the three toll booths were also observed significantly high.CONCLUSION: The study suggested that serious measures are required to control and regulate toll booths to avoid vehicle idling, which will lead to savings of fuel and air and noise pollution.
A. Jaiswal; C. Samuel; V.M. Kadabgaon
Abstract
The study provides a statistical trend analysis of different air pollutants using Mann-Kendall and Sen’s slope estimator approach on past pollutants statistics from air quality index station of Varanasi, India. Further, using autoregressive integrated moving average model, future values of air ...
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The study provides a statistical trend analysis of different air pollutants using Mann-Kendall and Sen’s slope estimator approach on past pollutants statistics from air quality index station of Varanasi, India. Further, using autoregressive integrated moving average model, future values of air pollutant levels are predicted. Carbon monoxide, nitrogen dioxide, sulphur dioxide, particulate matter particles as PM2.5 and PM10 are the pollutants on which the study focuses. Mann-Kendall and Sen’s slope estimator tests are used on summer (February-May), monsoon (June-September) and winter (October-January) seasonal data from year 2013 to 2016 and trend results and power of the slopes are estimated. For predictive analysis, different autoregressive integrated moving average models are compared with goodness of fit statistics, and the observed results stated autoregressive integrated moving average (1,1,1) as the best-suited for forecast modeling of different pollutants in Varanasi. Autoregressive integrated moving average model (1,1,1) is also used on the annual concentration levels to predict forthcoming year's annual pollutants value. Study reveals that PM 10 shows a rising trend with predicted approximate annual concentration of 273 µg/m3 and PM2.5, carbon monoxide, nitrogen dioxide and sulphur dioxide show a reducing trend with approximate annual concentration of 139 µg/m3, 1.37 mg/ m3, 38 µg/m3 and 17 µg/m3, respectively, by the year 2030. The study predicted carbon monoxide, nitrogen dioxide andsulphur dioxide concentrations are lower and PM10 and PM2.5 concentrations are much higher to the standard permissible limits in future years also, and specific measures are required to control emissions of these pollutants in Varanasi.