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Article

PREDICTION AND ANALYSIS OF POLLUTION AND CONGESTION LEVEL FOR PRESENT AND FUTURE SCENARIO ON AN URBAN ROAD NETWORK- INDIA

DOI: 10.7708/ijtte.2018.8(2).06


8 / 2 / 213-227 Pages

Author(s)

Awkash Kumar - Centre for Environmental Science and Engineering, Indian institute of Technology Bombay, Mumbai- 400 076, India -

Saloni Vijay - Department of Environmental Science and Engineering, Indian School of Mines, Dhanbad - 826004, India -

Rakesh Kumar - National Environmental Engineering Research Institute, Council of Scientific and Industrial Research, Nagpur – 440 020, India -

Rashmi S Patil - Centre for Environmental Science and Engineering, Indian institute of Technology Bombay, Mumbai- 400 076, India -

Anil Kumar Dikshit - Centre for Environmental Science and Engineering, Indian institute of Technology Bombay, Mumbai- 400 076, India -

Sunder Lal Dhingra - Transportation Systems Engineering, Department of Civil Engineering, Indian institute of Technology Bombay, Mumbai- 400 076, India -


Abstract

Due to increasing population and rising income level, most of the metropolitan cities in the world are facing problems of congestion and pollution. It is high time proper steps were taken to prevent the unbearable congestion and pollution that might occur in the near future. Before taking the mitigation measures, it is important to find out or estimate the level of congestion and pollution. Hence, the study has been conducted to assess the present and future pollution and congestion level for a highly congested Worli Road Network, Mumbai. Level of service analysis has been done for all the roads in the network to find out the congestion level. The impact of the traffic was quantified in terms of Volume/Capacity (V/C) ratio, for the coming 20 years in 10-year intervals. The years in which any road was reaching its theoretical capacity was also identified. USEPA AERMOD has been used with proper evaluation of the model results to model the concentration of air pollutants for present and future scenario. Through the predicted results of congestion and air pollution in future, some mitigation measures are suggested.


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References:

Abdul-Wahab, S.; Sappurd, A.; Al-Damkhi, A. 2011. Application of California Puff (CALPUFF) model: a case study for Oman, Clean Technologies and Environmental Policy 13(1): 177–189.

 

Abhijith, K.V.; Gokhale, S. 2015. Passive control potentials of trees and on-street parked cars in reduction of air pollution exposure in urban street canyons, Environmental Pollution 204: 99–108.

 

ARAI. 2007. Emission Factor development for Indian Vehicles, Air quality monitoring project-Indian Clean Air Programme (ICAP), ARAI, Pune, India. 89 p.

 

Briggs, D.J.; de Hoogh, C.; Gulliver, J.; Wills, J.; Elliott, P.; Kingham, S.; Smallbone, K. 2000. A regression based method for mapping traffic related air pollution: application and testing in four contrasting urban environments, Science of the Total Environment 253(1-3): 151–167.

 

Census data. 2011. Census of India Organisation, Ministry of Home Affairs, Government of India. Available from internet: http://www.censusindia.gov.in/2011-Common/CensusData2011.html.

 

Cimorelli, A. J.; Perry, S. G.; Venkatra, A.; Weil, J. C.; Paine, R. J.; Wilson Robert B., Lee R. F., Peters W. D., Brode R. W., Paumie J. O. 2004. AERMOD: Description of Model Formulation EPA-454/R-03-004, U.S. Environmental Protection Agency, USA. 91 p.

 

Choudhary, A.; Gokhale, S. 2016. Urban real-world driving traffic emissions during interruption and congestion, Transportation Research Part D: Transport and Environment 43: 59–70.

 

CPCB. 2009. National Ambient Air Quality Standards. Central Pollution Control Board, New Delhi, India. 4 p.

 

CTS. 2008. Comprehensive Transportation Study for Mumbai Metropolitan Region. World Bank Project, India. 40 p.

 

EPA. 1995. User's Guide for The Industrial Source Complex (ISC3) Dispersion Models. Volume I, EPA-454/B-95-003a. USEPA, USA.

 

Gokhale, S. 2011. Traffic flow pattern and meteorology at two distinct urban junctions with impacts on air quality, Atmospheric Environment 45(10): 1830–1840.

 

Gokhale, S. 2012. Impacts of traffic-flows on vehicular-exhaust emissions at traffic junctions, Transportation Research Part D: Transport and Environment 17(1): 21–27.

 

Gulia, S.; Nagendra, S.S.; Khare, M.; Khanna I. 2015. Urban air quality management- a review, Atmospheric Pollution Research 6(2): 286–304.

 

IRC. 1990. Guidelines of Capacity of Urban Roads in Plain Areas, In Proceedings of the Indian Road Congress, New Delhi, 106 p.

 

Joseph, A.; Sawant, A.D.; Srivastava, A. 2003. PM10 and its impacts on health - a case study in Mumbai, International Journal of Environmental Health Research 13(2): 207-214.

 

Kumar, R.; Joseph, A.E. 2006. Air pollution concentrations of PM2.5, PM10 and NO2 at ambient and Kerbsite and their correlation in Metro City, Mumbai, Environmental Monitoring and Assessments 119(1-3): 191–199.

 

Kumar, A.; Dikshit, A.K.; Fatima, S.; Patil, R. S. 2015. Application of WRF model for vehicular pollution modelling using AERMOD, Atmospheric and Climate Sciences 5: 57–62.

 

Kumar, A.; Gupta, I.; Brandt, J.; Kumar, R.; Dikshit, A.K.; Patil, R.S. 2016. Air quality mapping using GIS and economic evaluation of health impact for Mumbai city, India, Journal of the Air and Waste Management Association 66(5): 470–481.

 

Kumar, A.; Patil, R.S.; Dikshit, A.K.; Islam, S.; Kumar, R. 2016. Evaluation of control strategies for industrial air pollution sources using American Meteorological Society/Environmental Protection Agency Regulatory Model with simulated meteorology by Weather Research and Forecasting Model, Journal of Cleaner Production 116: 110-117.

 

Ma. J.; Yi, H.; Tang, X.; Zhang, Y.; Xiang, Y.; Pu, L. 2013. Application of AERMOD on near future air quality simulation under the latest national emission control policy of China: a case study on an industrial city, Journal of Environmental Sciences 25(8): 1608–1617.

 

Mohan, M.; Bhati, S.; Sreenivas, A.; Marrapu, P. 2011. Performance evaluation of AERMOD and ADMS-Urban for total suspended particulate matter concentrations in Megacity Delhi, Aerosol and Air Quality Research 11(7): 883–894.

 

Mokhtar, M. M.; Hassim, M. H.; Taib, R. M. 2014. Health risk assessment of emissions from a coal-fired power plant using AERMOD modelling, Process Safety and Environmental Protection 92(5): 476–485.

 

Mohan, R. A.; Ramachandra, R.K. 2012. Measuring Urban Traffic Congestion – a Review, International Journal of Traffic and Transportation Engineering 2(4): 286–305.

 

MSRDC. 2006. Western Freeway Sea Link, Pedar Road viaduct Rapid Environmental Impact Assessment, Maharashtra State Road Development Corporation Limited (MSRDC), Mumbai, India.

 

MVD. 2013. Statistics, Motor Vehicle Department, Maharashtra, India. 96 p. Available from internet: http://mahatranscom.in/pdf/MVD%20Statistics%20-%202012-13.pdf.

 

Nagendra, S.M.S.; Khare, M. 2002. Line source emission modelling, Atmospheric Environment 36(13): 2083–2098.

 

NGT. 2015. Ambient Air Quality Modelling and Traffic Studies around Worli Sea Face Area. Mumbai, India.

 

Pawar, D.S.; Patil, G.R. 2015. Pedestrian temporal and spatial gap acceptance at mid-block street crossing in developing world, Journal of Safety Research 52: 39-46.

 

Patankar, A.M.; Trivedi, P.L. 2011. Monetary burden of health impacts of air pollution in Mumbai, India: implications for public health policy, Public Health 125(3): 157–64.

 

Seangkiatiyuth, K.; Surapipith, V.; Tantrakarnapa, K.; Lothongkum, A.W. 2011. Application of the AERMOD modeling system for environmental impact assessment of NO2 emissions from a cement complex, Journal of Environmental Sciences 23(6): 931–940.

 

Sharma, N.; Chaudhry, K.K.; Rao, C.C. 2004. Vehicular pollution prediction modelling: a review of highway dispersion models, Transport Reviews 24(4): 409–435.

 

Sivacoumar, R.; Thanasekaran, K. 1999. Line source model for vehicular pollution prediction near roadways and model evaluation through statistical analysis, Environmental Pollution 104(3): 389–395.