Abstract
Fire disasters pose a severe threat to the functionality of the cities and their sustainable development. Lack of analytical approach in research literature hinders the development of a fire-resilient city. A novel analytical framework is proposed in this paper to reduce the overall fire susceptibility of a city through a cost-effective redevelopment of the existing urban built forms (UBF). The proposed framework involves a regression model to capture the linear relationship between the fire susceptibility of an area and the built-up variables at a granular scale. Additionally, extended pinch analysis is incorporated in the framework to minimize the financial expenses incurred during the redevelopment, for the reduction in fire susceptibility of a city. The applicability of the proposed framework is demonstrated through a case study involving the southern region of Mumbai, India. The results suggest medium-rise buildings should be the main constituent for the UBF in Mumbai to reduce its fire susceptibility cost-effectively. Based on the illustrated case study, specific policies are recommended. The proposed novel methodology endorses a holistic decision-making process, applicable in developing fire-resilient cities in developing countries.
Graphic abstract
Similar content being viewed by others
Abbreviations
- a j :
-
Linear regression coefficient of fire susceptibility for jth built form
- C :
-
Total redevelopment cost
- c j :
-
Cost coefficient for constructing jth built form
- C c :
-
Total cost of construction
- d j :
-
Cost coefficient for demolishing an existing jth built form
- D c :
-
Total cost of demolition
- J :
-
Set of UBF variables
- S p :
-
Fire susceptibility
- \(S_{p}^{\min }\) :
-
Minimum value of the fire susceptibility
- \(x_{j}^{{{\text{ex}}}}\) :
-
Existing footprint of jth built form
- x j :
-
Print of jth built form
- \(x_{j}^{\max }\) :
-
Maximum value of the footprint of jth built form
- \(x_{j}^{\min }\) :
-
Minimum value of the footprint of jth built form
- x m :
-
Construction footprint for a building type m
- x n :
-
Demolition footprint for a building type n
- ∆cnm :
-
Change in the cost caused by the demolition of xn and construction of xm
- ∆s/∆c :
-
Susceptibility-to-cost ratio
- ∆snm :
-
Change in the fire susceptibility caused by the demolition of xn and construction of xm
References
Bandyopadhyay S (2015) Mathematical foundation of pinch analysis. Chem Eng Trans 45:1753–1758
Bandyopadhyay S (2020) Pinch analysis for economic appraisal of sustainable projects. Process Integr Optim Sustain. https://doi.org/10.1007/s41660-020-00106-x
Basu R, Jana A, Bardhan R, Bandyopadhyay S (2017) Pinch Analysis as a quantitative decision framework for determining gaps in health care delivery systems. Process Integr Optim Sustain 1(3):213–223
Bureau of Indian Standards (2016) National Building Code of India 2016, vol 2. www.academia.edu/37343763/india-national-building-code-nbc-2016-vol-2.pdf?auto=download
Burton E, Jenks M, Williams K (2013) Achieving sustainable urban form. Routledge, Abingdon
Chang DL, Sabatini-Marques J, Da Costa EM, Selig PM, Yigitcanlar T (2018) Knowledge-based, smart and sustainable cities: a provocation for a conceptual framework. J Open Innov Technol Market Complex 4(1):5
Choei NY, Kim H, Kim S (2020) Improving infrastructure installation planning processes using procedural modeling. Land 9(2):48
Corcoran J, Higgs G, Rohde D, Chhetri P (2011) Investigating the association between weather conditions, calendar events and socio-economic patterns with trends in fire incidence: an Australian case study. J Geogr Syst 13(2):193–226. https://doi.org/10.1007/s10109-009-0102-z
Central Public Works Department (2019) Schedule of Rates 2018. https://cpwd.gov.in/Documents/cpwd_publication.aspx, Accessed Oct 2019
Demographia (2019) Demographia World Urban Areas (No. 15; Annual Edition: 201904). https://www.demographia.com/db-worldua.pdf
Forkuo EK, Quaye-Ballard JA (2013) GIS based fire emergency response system, vol 2, pp 9. https://dspace.knust.edu.gh/bitstream/123456789/7338/1/Forkuo%2C%2520E.K.pdf
Guay F (2019) Fire resilient cities: the impact of fire regulations, technological and community resilience. Int J Urb Civ Eng 13(7):386–391
Hohmann EC (1971) Optimum networks for heat exchange. Ph.D. thesis, University of South California, USA. https://digitallibrary.usc.edu/cdm/ref/collection/p15799coll17/id/211425
Hosseinali F, Alesheikh Ali A, Farshad N (2013) Agent-based modeling of urban landuse development, case study: Simulating future scenarios of Qazvin city. Cities 31:105–113. https://doi.org/10.1016/j.cities.2012.09.002
Jain S, Bandyopadhyay S (2019) Multi-objective optimisation for segregated targeting problems using pinch analysis. J Clean Prod 221:339–352
Jana A, Bardhan R, Sarkar S, Kumar V (2016) Framework to assess and locate affordable and accessible housing for developing nations: empirical evidences from Mumbai. Habitat Int 57:88–99
Jennings CR (2013) Social and economic characteristics as determinants of residential fire risk in urban neighborhoods: a review of the literature. Fire Saf J 62:13–19
Jia X, Gao Y, Wei B, Wang S, Tang G, Zhao Z (2019) Risk Assessment and regionalization of fire disaster based on analytic hierarchy process and modis data: a case study of inner mongolia China. Sustainability 11(22):6263
Jia X, Klemeš JJ, Alwi SRW, Varbanov PS (2020) Regional water resources assessment using water scarcity pinch analysis. Resour Conserv Recycl 157:104749
Klemeš JJ, Varbanov PS, Walmsley TG, Jia X (2018) New directions in the implementation of pinch methodology (PM). Renew Sustain Energy Rev 98:439–468
Kropf K (2014) Ambiguity in the definition of built form. Urban Morphology, International Seminar on Urban Form, pp 41–57
Kumar V, Jana A, Ramamritham K (2020a) A decision framework to access urban fire vulnerability in cities of developing nations: empirical evidence from Mumbai. Geocarto Int. https://doi.org/10.1080/10106049.2020.1723718
Kumar V, Jana A, Ramamritham K (2020) Simulating fire-safe cities using a machine learning-based algorithm for the complex urban forms of developing nations: a case of Mumbai India. Geocarto Int. https://doi.org/10.1080/10106049.2020.1756463
Kumar V, Ramamritham K, Jana A (2019) Resource allocation for handling emergencies considering dynamic variations and urban spaces: fire fighting in Mumbai. In: Proceedings of the tenth international conference on information and communication technologies and development, pp 1–11. https://doi.org/10.1145/3287098.3287099
Li F, Li Z, Chen H, Chen Z, Li M (2020) An agent-based learning-embedded model (ABM-learning) for urban land use planning: a case study of residential land growth simulation in Shenzhen China. Land Use Policy 95:104620
Malik J, Bardhan R (2020) Energy target pinch analysis for optimising thermal comfort in low-income dwellings. J Build ineering 28:101045
Martin I, Patow G (2019) Ruleset-rewriting for procedural modeling of buildings. Comput Gr 84:93–102
Municipal Corporation of Greater Mumbai (2005) Fire hazard response & mitigation plan (No. 1; p. 97). Mumbai Fire Brigade. https://www.mahafireservice.gov.in/Site/PDFs/NewsEvents/FireHazardResponseMitigationPlan/MillenniumCityMitigationPlan/mumbai_mitigation_plan.pdf
Middel A, Lukasczyk J, Zakrzewski S, Arnold M, Maciejewski R (2019) Urban form and composition of street canyons: a human-centric big data and deep learning approach. Landsc Urban Plan 183:122–132. https://doi.org/10.1016/j.landurbplan.2018.12.001
Ministry of Home Affairs (2011) Fire hazard and risk analysis in the country for revamping the fire services in the Country. https://dgfscdhg.gov.in/sites/default/files/Delhi.pdf
Ministry of Urban Development (2014) General building requirements. Ministry of Housing and Urban Affairs. https://www.indiaenvironmentportal.org.in/files/file/MODEL%2520BUILDING%2520BYE%2520LAWS-2016.pdf
Ministry of Urban Development (2015) Urban and regional development plans formulation and implementation (URDPFI) Guidelines. https://mohua.gov.in/upload/uploadfiles/files/URDPFI%2520Guidelines%2520Vol%2520I.pdf
Nyong-Bassey BE, Giaouris D, Patsios C, Papadopoulou S, Papadopoulos AI, Walker S, Voutetakis S, Seferlis P, Gadoue S (2020) Reinforcement learning based adaptive power pinch analysis for energy management of stand-alone hybrid energy storage systems considering uncertainty. Energy 193:116622
Ongpeng JMC, Dungca JR, Aviso KB, Tan RR (2019) Minimizing the carbon footprint of urban reconstruction projects. J Clean Prod 240:118222
Pillai HK, Bandyopadhyay S (2007) A rigorous targeting algorithm for resource allocation networks. Chem Eng Sci 62:6212–6221
Singh M (2019) Forecasting of GHG emission and linear pinch analysis of municipal solid waste for the city of Faridabad, India. Energy Sources Part A Recovery, Utiliz Environ Effects 41(22):2704–2714
Subramanian D, Bandyopadhyay S, Jana A (2019) Optimization of financial expenditure to improve urban recreational open spaces using pinch analysis: a case of three indian cities. Process Integr Optim Sustain 3(2):273–284
Tan RR, Aziz MKA, Ng DK, Foo DC, Lam HL (2016) Pinch analysis-based approach to industrial safety risk and environmental management. Clean Technol Environ Policy 18(7):2107–2117
Tan RR, Bandyopadhyay S, Foo DC, Ng DK (2015) Prospects for novel pinch analysis application domains in the 21st century. Ital Assoc Chem Eng 45:1741–1746. https://doi.org/10.3303/CET1545291
Taridala S, Yudono A, Ramli MI, Akil A (2017) Expert system development for urban fire hazard assessment: study case—Kendari City, Indonesia. IOP Conf Ser Earth Environ Sci 79:012035. https://doi.org/10.1088/1755-1315/79/1/012035
Tishi TR, Islam I (2019) Urban fire occurrences in the Dhaka Metropolitan Area. GeoJournal 84(6):1417–1427
Town and Country Planning Organisation (2016) Model building bye laws-2016. Ministry of Urban Development. www.indiaenvironmentportal.org.in/files/file/MODEL%2520BUILDING%2520BYE%2520LAWS-2016.pdf
Walmsley MR, Walmsley TG, Atkins MJ, Kamp PJ, Neale JR, Chand A (2015) Carbon emissions pinch analysis for emissions reductions in the New Zealand transport sector through to 2050. Energy 92:569–576
Wang F, Gao Y, Dong W, Li Z, Jia X, Tan RR (2017) Segmented pinch analysis for environmental risk management. Resour Conserv Recycl 122:353–361
Zhang X, Yao J, Sila-Nowicka K, Jin Y (2020) Urban fire dynamics and its association with urban growth: evidence from Nanjing China. ISPRS Int J Geo-Inf 9(4):218
Zhang X, Yao J, Sila-Nowicka K (2018) Exploring spatiotemporal dynamics of urban fires: a case of Nanjing China. ISPRS Int J Geo-Inform 7(1):7. https://doi.org/10.3390/ijgi7010007
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Kumar, V., Bandyopadhyay, S., Ramamritham, K. et al. Pinch analysis to reduce fire susceptibility by redeveloping urban built forms. Clean Techn Environ Policy 22, 1531–1546 (2020). https://doi.org/10.1007/s10098-020-01895-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10098-020-01895-y