Quantifying the relationship between carbon dioxide gas emission in relation to the compactness dimension of urban form

Document Type : Original Article

Authors

1 Department of Environmental Science, Natural Resources Faculty, Tarbiat Modares University, Noor, Mazandaran, Iran

2 Depatment of Urban and Regional Planning, Art and Artichucter Faculty, Tarbiat Modares University, Tehran, Iran

Abstract

Introduction:
Global warming is an absolute fact and an inevitable threat to life in the environment. Considering that urban areas are an important factor in the increase in CO2 gas emissions, the community needs to take action to reduce greenhouse gas emissions. Since the increase in the population is responsible for increasing the demand for housing and the rapid development of activity centres in the suburbs and the rapid growth of urban areas in Iran, we see the importance of fuel in sustainable development and the important and potential role of sustainable forms of urban development; the necessity of quantifying the relationship between the compactness of the urban form and CO2 emissions due to fossil fuel consumption is thus released.
 Materials and methods:
The present study is designed in two phases. In the first phase, the changes of 15 urban forms in Guilan and Mazandaran Provinces are investigated according to the compactness dimension using landscape metrics (AI, PLADJ, PROXIM, COHESSION). OLI and TM Landsat satellite imagery from the years 2001 and 2015 was used to provide the urban maps. Also, a supervised classification based on the maximum likelihood algorithm was used for image classification. Post classification comparison was used for detection of change. In the second phase, after calculation of CO2 emissions the panel data analysis was used to calculate the relationship between time series variables of CO2 emissions and cross-section variables of landscape metrics.  
Results and discussion:
The results of the landscape metrics show that, for all the urban forms studied during the period 1380-1394 (Persian calendar), the compactness in the class level in all urban areas of Guilan Province except for Bandar Anzali has shown a decreasing trend compared with Mazandaran Province, but an increasing trend of compactness was observed only in Ramsar, Behshahr and Amol in Mazandaran Province. Therefore, it can be said that the urban areas of Mazandaran Province are more compact than those of Guilan Province. According to the results, these four compactness variables (AI, PLADJ, PROXIM, COHESION) showed a negative correlation with CO2 emissions due to concentrations of gasoline and diesel oil at the urban class level. Among the metrics used, COHESIOM showed the highest correlations (8.79 and -10.17)) with carbon dioxide due to gasoline and diesel oil consumption, respectively. According to the results of the panel data analysis, the increase in the COHESION value of about one percent has caused CO2 emissions from gasoline to decrease by about nine percent, while a one percent increase in the COHESION value caused a 10% reduction in CO2 emissions from diesel oil. For example, if we consider that the amount of CO2 emissions from gasoline is 133.63 tons CO2 per hectare in Amol for 1394 and also, according to the results of the COHESION metrics which indicate that if the urban compactness increases by one percent CO2 emissions will be reduced by 8.8 percent, a reduction of 11.73 tons per hectare will occur. 
Conclusion:
In sum, consideration of the urban form in the future planning of the northern cities development is recommended for creation of low carbon cities in Iran.

Keywords


  1. Abbasi, H., Hajipour, Kh. and Hossein pour, M., 2012. Explanation of effective urban form factors on households fuel consumption in transportation sector. Naghshe Jahan. 3, 7-18.
  2. Andong, R.F. and Sajor, E., 2017. Urban sprawl, public transport, and increasing CO2 emissions: The case of Metro Manila, Philippines. Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development. 19(1), 99-123.
  3. Baltagi, B.H., 2005. Econometric Analysis of Panel Data, (Third ed), John Wiley and Sons., New York, USA.
  4. Baur, A.H., Förster, M. and Kleinschmit, B., 2015. The spatial dimension of urban greenhouse gas emissions: Analyzing the influence of spatial structures and LULC patterns in European cities. Landscape Ecology. 30(7), 1195-1205.
  5. Bazzi, Kh. and Vahdati, M., 2014. Evaluation of urban density and city rate's fraction and its effects on increasing of households costs in Bojnourd city. Journal of Geography and Planning. 46, 1-18.
  6. Condon, P.M., Cavens, D. and Miller, N., 2009. Urban planning tools for climate change mitigation. Cambridge, MA: Lincoln Institute of Land Policy.
  7. Dunn, C.P., Sharpe, D.M., Guntenspergen, G.R., Stearns, F., and Yang, Z., 1991. Methods for analyzing temporal changes in landscape pattern. Ecological studies: analysis and synthesis (USA).
  8. ECOTEC, 1993. Reducing Transport Emissions Through Planning. HMSO, London.
  9. Fang, C., Wang, Sh. and Li, G., 2015. Urban Forms Changing and Carbon Dioxide Emissions in China, A Case Study of 30 Provincial Capital Cities. Applied Energy. 158, 519-531.
  10. Fragkias, M., Lobo, J., Strumsky, D., and Seto, K.C., 2013. Does size matter? Scaling of CO2 emissions and US urban areas. PLoS One. 8, e64727.
  11. Frohn, R.C., McGwire, K.C., Dale, V.H. and Estes, J.E., 1996. Using satellite remote sensing analysis to evaluate a socio-economic and ecological model of deforestation in Rondonia, Brazil. Remote Sensing. 17, 3233-3255.
  12. Gardner, R.H., O'Neill, R.V., and Turner, M.G. 1993. Ecological implications of landscape fragmentation. Humans as components of ecosystems: the ecology of subtle human effects and populated areas, 208-226.
  13. Hajipour, Kh. and Frozan, N., 2014. Study of the urban form effect on operational energy consumption; the case of Shiraz, Honarhae-Ziba Memari va Sharsazi. 19, 17-26.
  14. Hammerling, D.M., Michalak, A.M. and Kawa, S.R., 2012. Mapping of CO2 at high spatiotemporal resolution using satellite observations: Global distributions from OCO‐2. Journal of Geophysical Research: Atmospheres. 117, 1-10.
  15. Herzog, F., and Lausch, A., 2001. Supplementing land-use statistics with landscape metrics: some methodological considerations. Environmental Monitoring and Assessment. 72, 37-50.
  16. Hillman, M., 1996, In Favour of the Compact City, In the Compact City: A Sustainable Urban Form? Ed, Mike Jenks, Elizabeth Burton, and Katie Williams, E & FN Spon, London.
  17. IEA., 2012. World energy outlook 2012. Paris.
  18. Intergovernmental Panel on Climate Change (IPCC). 2007, the fourth assessment report of the intergovernmental panel on climate change. England: Cambridge University Press.
  19. Jensen, J.R., 2005. Introductory Digital Image Pro-cessing: A Remote Sensing Perspective, 3rd ed, Upper Saddle River: Prentice-Hall.
  20. Keitt, T., Urban, D. and Milne, B., 1997. Detecting critical scales in fragmented landscapes. Conservation ecology. 1, 1-13.
  21. Lee, S. and Lee, B., 2014. The influence of urban form on GHG emissions in the US household sector. Energy Policy, 68, 534-549.
  22. Lillesand, T.M., Kiefer, R.W. and Chipman, J.W., 2004. Remote Sensing and Image Interpretation, Fifth ed John Wiley and Sons, New York, USA.
  23. Liu, X. and Sweeney, J., 2012. Modelling the impact of urban form on household energy demand and related CO2 emissions in the Greater Dublin Region. Energy Policy. 46, 359-369.
  24. Lotfi, S., Mahdian Bahnamiri, M. and Mahdi, E., 2014. Analyzing the Physical Expansion of City and Its Impact on the Quality of Urban Environment (Case Study: Babolsar City). Journal of geography and regional development. 22, 106-128.
  25. Ma J., Liu Z. and Chai Y., 2015. The Impact of urban form on CO2 emission from work and non-work trips, the Case of Beijing, China. Habitat International. 47, 1-10.
  26. Makido Y., Dhakal S. and Yamagata Y., 2012. Relationship between Urban Form and CO2 Emissions، Evidence From Fifty Japanese Cities، Urban Climate، 2, 55-67.
  27. McGarigal, K., Cushman, S.A., Neel, M.C. and Ene, E., 2002. FRAGSTATS: spatial pattern analysis program for categorical maps.
  28. McGarigal K. and Marks B.J., 1995. FRAGSTATS: Spatial Pattern Analysis Program for Quantifying Landscape Structure, General Technical. Report. PNW-351. US Department of Agriculture Forest Service, P.141.
  29. Nerlove, M., 2002. An Essay on the History of Panel Data Econometrics. Department of Agricultural and Resource Economics.
  30. Newman, P. W. and Kenworthy, J.R., 1989. Gasoline consumption and cities: a comparison of US cities with a global survey. Journal of the American planning association. 55, 24-37.
  31. O'neill, R.V., Hunsaker, C.T., Timmins, S.P., Jackson, B.L., Jones, K.B., Riitters, K.H. and Wickham, J.D., 1996. Scale problems in reporting landscape pattern at the regional scale. Landscape ecology, 11. 169-180.
  32. Osorio, B.M., McCullen, N., Walker, I. and Coley, D., 2016. Understanding the relationship between energy consumption and urban form. Athens Journal of Sciences. 4, 115-141.
  33. PourAhmad, A., Mohamadpour. S., Manochehri Miandoab. A. and Khalili, A., 2012. Evaluation of dispersal and compactness of urban form using quantitative models, Journal of Iranian geography society. 32, 50-74.
  34. Rezaei, P. and Ostad Malekroudi, P., 2010. Geomorphological limitation for Roudbar physical development. Journal of natural geography. 7, 42-52.
  35. Richards, J.A. and Jia, X., 2006. Interpretation of hyperspectral image data. Remote Sensing Digital Image Analysis. An Introduction, 359-388.
  36. Seyfoddini, F., Ziari, K. and PourAhmad, A., 2012. Determination of dispersal and compactness of urban form in Amol by sustainable urban form approach. Human geography research quarterly. 44, 155-176.
  37. Statistical center of Iran, 2011. Results of people and house public census of Guilan province.
  38. Statistical center of Iran, 2011. Results of people and house public census of Mazandaran province.
  39. Statistical yearbook of Mazandaran province., 2012. Land, weather and population, Firest and second chapter, 65-132.
  40. Turner, M.G., O'Neill, R.V., Gardner, R.H. and Milne, B. T., 1989. Effects of changing spatial scale on the analysis of landscape pattern. Landscape ecology. 3, 153-162.
  41. Venkataramanan, M., 2011. Causes and effects of global warming. Indian Journal of Science and Technology. 4, 226-229.
  42. Wang, Z.H., Yin, F.C., Zhang, Y.X. and Zhang, X., 2012. An empirical research on the influencing factors of regional CO2 emissions: evidence from Beijing city, China. Applied Energy. 100, 277–84.
  43. Wang, S.J, Fang, C.L., Wang, Y., Huang, Y.B. and Ma, H.T., 2014. Quantifying the relationship between urban development intensity and carbon dioxide emissions using a panel data analysis. Ecological Indicators. 49, 121–31.
  44. Wang, S., Liu, X., Zhou, C., Hu, J. and Ou, J., 2017. Examining the impacts of socioeconomic factors, urban form, and transportation networks on CO2 emissions in China’s megacities. Applied Energy.185, 189-200.
  45. Williams, K., Burton, E. and Jenks, M., 2000. Achieving sustainable urban form: an introduction. Achieving sustainable urban form. 1, 1-5.