Interrelationship Between Brownfield development as a ...

www.theinternationaljournal.org> RJSSM : Volume: 09, Number: 10, February 2020 Page 25

Interrelationship Between Brownfield development as a mitigating factor

for climate change and critical infrastructure within a metropolis: a case of

Kolkata Metropolitan Area

Mouli Majumdar1 and Joy Sen

2

1 Research Scholar, RCG School of Infrastructure design and Management,

Indian Institute of Technology Kharagpur, West Bengal , India 2Head and professor, Department of Architecture and Regional Planning, Indian institute of Technology

Kharagpur, West Bengal , India. 2Professor, RCG School of Infrastructure design and Management,

Indian Institute of Technology Kharagpur, West Bengal , India

Corresponding Author: Mouli Majumdar

Abstract: The growth of an inclusive and sustainable metropolis is motivated by a close interaction between the

(i) investment and maintenance of it’s critical infrastructure, (ii) maximisation of the available resources and

(iii) incorporation of the technological advances. This growth trajectory is often affected adversely by extreme

climate changes like rise in sea level, heat waves, scarcity of food and frequent floods or storms. One of the

major reasons for this being the negative impact of climate changes on the critical infrastructure of the city

which in turn guides its spatial form. A more compact urban form therefore has positive climate effects of low

carbon emissions, more efficient use of energy, reduced environmental costs for infrastructure, more urban

green spaces. Along with climatic benefits it reduces construction and operational cost of infrastructure,

optimises travel time and encourages interactions creating an environment for innovation.

A metropolitan area expanding at the expense of green areas faces the consequence of drastic climate changes

like frequent flooding, extreme rainfall, floods etc which further aggravates the problem by depleting its

infrastructure. Renewal of Brownfield developments encourages a compact urban form reducing the pressure on

metropolitan expansion. Brownfield development discourages urban sprawl improves environmental conditions

and has other positive economic and ecological effects.

Kolkata Metropolitan Area in this context provides an interesting study opportunity at two levels (i) Kolkata is

one of the most vulnerable flood prone coastal cities considering the hydro-geological factors that influence

climate changes like cyclones, sea-level rise, and storm surges. (ii) The trend of the metropolitan structure

interrelated with its socio-economic condition of Kolkata that is shaped by its physical –environmental setting.

The methodology has a bipartite approach of (a) exploring the factors influencing scope of Brownfield

development at a metropolis level and (b) influence of the critical infrastructure amongst the factors influencing

the Brownfield development on the same scale.

KEYWORDS: Densification, Brownfield development, climate changes, critical infrastructure, fuzzy logic

overlay.

I. Introduction

In this century of rapid urbanisation trend, 90% of the expected world’s population growth will be

absorbed by the developing world. Most of this urbanisation is expected to be in Asian and African countries

(United Nations, 2014; Kotak Institutional, n.d.). This form of urban growth in developing world is not limited

to the incremental extension of existing city or the newly planned cities but also urban fragments and corridors

growing onto dispersed opportunities or activity nodes. Along with the opportunities from agglomeration of

economies, cities today also face multifaceted challenges. These challenges now include climate change

induced vulnerability that results in risks from natural hazards and displacement of population. The conventional

challenges of accelerating demand in several sectors like infrastructure, housing, and transportation further adds

to the pressure.

It can be observed that this wave of rapid urbanisation is simultaneous with the rising impact of climate change

worldwide because as the cities grow so does its dependency on energy consumption and green house gas

emissions. In general there are two approaches observed at city level in response to climate change. One is

adaptation that tries to minimise negative effects of the green house gas and exploit the possible beneficial effect

(Hamin & Gurran, 2009). The other approach is mitigation that reduces green house gas emissions from the

sources and adopts processes or methods to reduce it from the environment.


The repercussions of this climate change is often expressed in terms of extreme storms and floods, heat waves,

rise in sea level etc that disrupts the critical infrastructure of the city and affecting it’s urban transition (IPCC,

2014). Some of the impacts of the variability in climate on urban areas are:

• Urban heat islands that are results of dense built environment and anthropogenic emissions. Drastic

variations in temperature may result into secondary effects of high demand of energy to cool, health related

problems from warm spells and rise in air pollution

• Rise in sea level which affects the coastal cities and low lying areas adversely. Erosion and flooding of

coastal urban areas from the rising sea level coupled with extreme storms threaten the entire coastal

ecosystem along with the population and the built forms. Presence of extensive petro chemical or energy

industries, port facilities makes the coastal city more vulnerable.

• Water scarcity in urban areas which has multiple adverse effects, like drought and shortage for human

consumption, agriculture and industry. Consumption of contaminated water in view of scarcity may lead to

health related problems. Urban areas dependent on hydropower generated source of electricity would also

suffer.

• Hydrological hazards including inland flooding, storm surges, heavy rainfall leads to destruction of built

form, livelihood, critical infrastructures and contamination of water followed by water borne disease etc.

• Adverse health impacts from various causes like extreme temperature, increasing air pollution, scarcity of

potable water and food.

• The economy of urban area is also affected by climate change induced events. The direct damage of critical

infrastructure , properties and assets, business opportunities leading to economic loss for rebuilding them

and indirectly by damaging the inputs for economic growth like resources, raw materials etc

II. Methodology

The area selected for the study consists of the urban region of Kolkata Metropolitan Area (KMA). KMA is

amongst the top five megacities in India along with Mumbai, Delhi, Chennai and Bangalore and it is the largest

urban agglomeration in eastern India. The study area specifically consists of three Municipal Corporations

(including Kolkata Municipal Corporation), thirty eight Municipalities (Kolkata Metropolitan Development

Authority, 2011). According to 2001 Census KMA has a population of 14.77 million and highest average

residential density of 8000 per square kilometres (Kolkata Metropolitan Development Authority, 2011).

Amongst the top 10 port cities that are vulnerable to flooding due to influence of climate change, Kolkata and

Mumbai are two Indian cities identified in a study by World Bank (Guerrero & Stein, N. Roberto Zagha John

Henry, 2011).Kolkata Metropolitan Area in this context is selected as a study area due to the two aspects:

(i) Considering the hydro-geological factors that influence climate changes like cyclones, sea-level rise, and

storm surges, Kolkata is observed to be one of the most vulnerable flood prone coastal cities.

(ii) Socio-economic condition of Kolkata that is shaped by its physical–environmental setting forms an

interesting trend of metropolitan structure.

The methodological approach is segmented under following heads

1 The influence of urban density on climate change and whether Brownfield Redevelopment can be a

mitigation measure is explored through a literature study as follows:

• Urban density and climate change

• Impact of climate change on critical infrastructure disruption

• Brownfield development as a mitigation measure for climate change

2 The factors influencing scope of Brownfield development at a metropolis level and

3 Influence of the infrastructure amongst the factors influencing the Brownfield development on the same

scale.


Figure 1: Levels of Green House Gas emissions in Kolkata, one of the major contributors of urban heat

island (compiled from data Emissions Dataset for Global Atmospheric Research (EDGAR) (2009)

The study area encompasses the urban area of KMA and includes following municipalities and municipal

corporations. The municipalities and municipal corporations are the urban areas that spread over six districts of

North 24 Parganas, South 24 Parganas, Kolkata, Howrah, Hugli and Nadia. The results for the municipalities are

agglomerated under subheads of the districts to which they belong for the ease of interpretation.

North 24

Parganas

Index

no:

South 24

Parganas

Index

no:

Baranagar 31 Baruipur 34

Barasat 26 Budge Budge 36

Barrackpore 14 Maheshtala 35

Bhatpara 8 Pujali 37

Dum Dum 30 Rajpur-Sonarpur 33

Garulia 10 Howrah

Halisahar 5 howrah B

Kamarhati 22 uluberia 38

Kanchrapara 4 bally 32

Khardah 18 Hugli

Madhyangram 25 Baidyabati 12

Naihati 7 Bhadreshwar 9

New Barrackpore 24 Bansberia 1

North Dumdum 23 Champdani 11

Panihati 20 Hugli-Chinsurah 6

Rajarhat-gopalpur 27 Konnagar 19

South Dum Dum 29 Rishra 36

Titagargh 16 Serampur 34

Bidhanagar 28 Uttarpara-Kotrang 21

Nadia Chandannagore C

Gayeshpur 3 KMC A

Kalyani 2

Figure 2 : Study Area (includes 38 municipalities and 3 municipal corporation of Kolkata Metropolitan Area)

III. LITERATURE REVIEW

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4.50E+06

5.00E+06

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Green House Gas emission in Kolkata

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Urban density and climate change

The urban areas with high population density produce a large amount of greenhouse gases and anthropogenic

heat. They are also high consumers of energy and influences the micro climate of the region.(IPCC, 2014) In

most of the scenarios the urban growth is accommodated either growing outward through horizontal expansion

and urban sprawl or growing upward in form of increasing the vertical density. Both the form of spatial growth

requires support of critical infrastructure which is vulnerable to this climate change induced damages.

The influence of density of urban areas and their critical infrastructure in adapting with climate change

variations forms the premises of this study. It is observed that the large contiguous urban areas that are well

serviced by infrastructure and belong to the economically prosperous section tend to produce larger amount of

green house gases per capita compared to its densely populated counterparts that have low level of services

(Marcotullio, Albrecht, & Sarzynski, 2011)

The capacity of an urban area to adapt with the climate change induced risk depends on various dimensions as

observed in several studies. The factors influencing the adaptive capacity of a city belongs to two broad

categories, the bio-physical that includes the physical form of the city and its critical infrastructure, the second is

the socio-economic status of the population(Carter et al., 2015). Another study shows that the adaptive capacity

of the city or a community depends on its economic wealth, technology, information and skills, infrastructure,

institutions, and equity (Pouliotte, Smit, & Westerhoff, 2001). Analysis exploring the risks of a city from climate

change claims it to be the function of social, economic and political processes. It can be elaborated into factors

like economic stability, demographic structure, institutional stability, strength of public infrastructure and global

connectivity(Walsh et al., 2011) . The quality of housing and infrastructure, level of preparedness among city’s

population and key emergency services are also to be factors influence risk of a city to climate change

(Satterthwaite, Huq, Pelling, Reid, & Lankao, 2007). In a report by World Bank, the ‘ adaptation deficit’

against climate change variability is function of substantial poverty, inadequate infrastructure, environmental

degradation(The Global Commission on the Economy and Climate, 2014). So we can observe that there is

repetitive mention of the urban form and the critical infrastructure of the city playing a major role in deciding the

adaptive capacity of a city against climate change.

Impact of climate change on critical infrastructure disruption

The growth of the urban areas coincides with it its demand for critical infrastructure both in terms of scale of

requirement and dependency on other infrastructure. The density of these urban areas is higher, so it has a

concentrated demand for infrastructure and its disruption would affect more people. Sudden disruptive climatic

hazard and gradual climate change that depletes the critical infrastructure both can affect the functioning of the

society in term of its safety, security health, economic and social well being. Exposure to the climate change

stressor and how the critical infrastructure is vulnerable to it decides the probability of it’s degradation

(Wilbanks, T., & Fernandez, 2013).

Two of the major factors which makes disruption or failure of critical infrastructure severe is (i) they are often

interconnected so the failure of one may have a cascading effect , or even an escalating effect on others (Rinaldi,

Peerenboom, & Kelly, 2001). (ii) Disruption of a critical infrastructure can also lead to a trans-boundary crisis

that has impact beyond geographical, functional and time boundaries (Boin, 2009). In table number 1 the risks

faced by urban infrastructure sectors and the probable adaptation and mitigation measures are discussed.

Urban infrastructure

and service sector

Risk Mitigation or Adaptation measures

Energy Heat waves or cold waves can increase

power demand. Hydropower dependent areas

will be affected due to variations in

precipitation.

• Management to minimise the peak

demand.

• Updating network and plants to be more

resilient to extreme climate change events

like flood, rising heat waves, storms etc.

• Using more renewable sources as input

fuel

Water and Waste water Both quality and quantity of consumable

water will be affected due to occurrence of

drought and flood. Urban areas have

increased share of impervious surfaces and

with irregular precipitation drainage system

will be over burdened

Water conservation strategies like using low

flow toilet fixture, leak detection and

repairing, reuse of water for other purposes

like irrigation and gardening, rainwater

harvesting etc.

Transportation The impact on the transportation network

depends on its location (underground,

elevated, railways with overhead electrical

wires). Extreme weather conditions can

• Encouraging use of public transportation.

• Adaptation of energy efficient vehicles

and modes.


deform the transportation system.

Transportation services can also be affected

as a secondary effect from damage in power

and telecommunication.

Public Health Poor air quality, extreme temperatures and

vector borne health risks increase due to

climate change and it’s effects are amplified

due to high population density of urban

areas. Increased flooding and droughts are

followed by water borne health risks.

Adaptation strategies to be integrated with

other services and sectors e.g.: planting

trees, green roofs, and pervious surfaces to

reduce the effects of urban heat island.

Health surveillance , improved water supply

and energy service will also have positive

impact on public health

Urban Landuse Planning High pressure to develop lands that are

vulnerable to climate change extreme events.

Area along the coast, river basin, slide prone

areas along mountains should have restrictive

development.

Adjustment in existing building codes and

introduction of new regulations. Measures

to reduce urban sprawl by increasing the

density of building, encouraging public

transport, restricting landuse laws

Table 1: The risks faced by Urban infrastructure and service sectors due to climate change and the possible

adaptation measures (source :Wilbanks, T., & Fernandez 2013)

To sum up the points for climate change implications in context of critical infrastructures in urban areas:

• Due to high demand from growing population and rise in average standard of living, there will be a rise in

demand of critical infrastructure would be built on areas that are exposed extreme weathers and climate

change. So attempts to decrease the footprint of the critical infrastructure and making it less physical

structure intensive is important.

• The revitalization of the aging infrastructure which is stressed due to rising demand has to accommodate the

technological change and the financial investment that is needed.

Therefore with limited resources of land and finance building a compact urban form rather than a Greenfield

development is more suitable

Brownfield development as a mitigation measure for climate change

Most of the core areas of Indian cities have comparatively low floor space index or floor area ratio (1.2 -2.0)

compared to other Asian cities (5.0-15.0). This constitutes the pool of underutilized lands along with parcels of

lands in form of dysfunctional factories, large government or institutional areas etc (Idfc Foundation, 2016). So

planned densification supported by public spaces and transport infrastructure will help to promote reduction in

Greenhouse gas emissions.

For the rapidly growing Indian cities facing various challenges building critical infrastructure to support the

growth is the only way forward. But it should also be noted that reducing the carbon footprint of the

infrastructure is crucial which can be achieved by a compact city form.

It is evident that for an overall sustainable urban area many other factors are to be considered simultaneously but

densification certainly have some advantages: (i) Cities with high density consume less energy per capita when

compared to suburban areas that are low in density. Less density requires people to travel more and further

making them more dependent on vehicle.(ii) Dense areas also produce less waste and cooling or heating of

smaller spaces require lesser energy.(iii )The coordination of supply chain and infrastructure service is better for

densely populated city.(Rogers Richard & Power Anne, 2017). A city that has a compact physical form, well

connected with public transits and functions with less damage to the environment is more equipped to mitigate

the effects of climate change.

Densification should be integrated with an overall spatial planning strategy without which it may have a

contrasting effect on the adaptive capacity of the city against climate change (Cizler, 2014). To achieve it , the

underutilized land resources and buildings are to be recycled, density of development increased and sprawling

over suburbs should be discouraged(Rogers Richard & Power Anne, 2000). On one end it aims to reduce the

transformation of the green spaces, agricultural land, forest areas and peripheral lands to urban built forms,

reducing sprawl which works as an adaptation measure against climate change. On the other if not planned

properly and integrated with resilient infrastructure it might encourage over congestion leading to air pollution

and traffic, gentrification and deterioration of civil services.

Redevelopment of Brownfield can be practiced as a measure to integrate climate change mitigation concerns

with the spatial planning and policies (Fernandes, de Sousa, Brito, Neves, & Vicente, 2018). Renewal of

Brownfield encourages intense use of existing urbanised areas and an overall compact form. Benefits of renewal

of Brownfield development can be realised at multiple fronts that includes economic, environmental and

community development (Chicago Metropolitan Agency & May, 2009).


Before we look into the benefits of a Brownfield redevelopment, it is important to point out that there is lack of

an agreed definition for the term ‘Brownfield ’,. Different countries, organisations and people offer a wide range

of interpretations and probable perspective, so it is important to reach an agreeable definition. The term evolved

from being associated with damaged and probably contaminated land due to previous industrial activities which

cannot be reused without proper treatment .It is mainly referred to land that is previously developed land

irrespective of its condition, opposite of what Greenfield land signifies (Alker et al. 2000, Adams, De Sousa, and

Tiesdell 2009)

It may be noted that the definitions of Brownfield vary according to the approach by different countries.

Countries with low population densities consider Brownfield land as contaminated land, particularly land

affected by previous industrial activities. For countries having high population density, like developing

countries, definitions of Brownfield includes a wider range. Initially it only included previously developed but

now it also includes vacant land and currently used land that has potential for further development(Tang & Paul

Nathanail, 2012) .

To sum it up the definition for Brownfield is as follows:

“Brownfield site is any land or premises which has previously been used or developed and is not currently fully

in use. It may be partially occupied or utilised or may also be vacant, derelict or contaminated. Therefore a

Brownfield site is not available for immediate use without intervention.”(Alker et al., 2000)

In the context of this study the following advantages of encouraging Brownfield development can be noted in

terms of adaptation towards climate change:

• It has existing infrastructure so building new networks of infrastructure which is energy intensive both in

construction and maintenance is less.

• It utilises the existing land resources fully and discourages urban sprawl

• A compact urban form is encouraged, which reduces the commuting distance and usage of vehicles

minimising energy consumption and greenhouse gas emissions.

• Brownfield development reduces the pressure on Greenfield development. For every hectare of

Brownfield redevelopment , it is estimated that up to 4.5 hectares of Greenfield development in an

outlying area can be saved (Heid, 2004).

The major causes of climate changes like emission of greenhouse gases, consumption of energy, depletion of

natural ecosystem can be minimised by adopting Brownfield redevelopment as a solution. Some of the measures

taken in Brownfield redevelopment and its probable impact on climate change are as follows:

Impacts of Brownfield development Anticipated influence on climate change

Land recycling Compact urban development, preservation of natural environment

Reuse of buildings Compact urban development, preservation of natural environment

Creation of green areas Preservation of the natural ecosystem

Application of renewable energy sources Reduction of emissions, reduction of energy consumption and conservation

of resources

Inclusion in public transport network Reduction of emissions through reduction in car use

Mixed-use development Reduction of emissions through reduction in car use

Table 2: Impacts of Brownfield redevelopment and its anticipated impacts on climate change (Cizler, 2014)

.

IV. FINDINGS

The starting point is to define the aim which as mentioned earlier is to find the factors influencing the scope of

Brownfield development at a metropolis level with a focus on influence on infrastructure

The basic approach for the analysis was as follows:

• Factor Identification: Identifying variables to assess the scope of Brownfield development at metropolitan

level and grouping them into categories or factors through literature studies.

• Reclassifying data within a layer using Fuzzy Membership tool: Mapping the required data and reclassify

them on a GIS interface for the year of 1991, 2001 and 2011. The process of reclassification is also known as

fuzzification using a ‘Fuzzy Membership’ function.

• Combining the layers using Fuzzy Overlay Tool: Overlay the reclassified data using ‘Fuzzy Logic Overlay’

function to find the performance of the area under each category and overall scope of Brownfield development

for the region

Factors influencing scope of Brownfield development at a metropolis level

There are two major approaches found in the literature as the process of identifying Brownfield Sites: (a) a pre

assessment in prioritization of Brownfield sites comparing it with indicators that are derived from defined

characteristics of Brownfield, (b) a post assessment that prioritize Brownfield sites based on its probable impact


on being redeveloped. The range of indicators varies widely depending on the aim of assessment, giving more

importance to health and environmental based indicators or based purely on economic returns. Nevertheless the

most recurring set of 35 indicators can be grouped into following categories of demographic characteristics,

urban structure, probable contamination level, availability of utilities and infrastructure and last but not the least

the probable economic returns from redevelopment of the Brownfield site.

The table number 3 summarizes the final 15 indicators that occur most frequently in the existing literature

eliminating duplicates, redundant or unavailable ones and they are grouped under broad heads of:

socioeconomic, environmental, social infrastructure, and urban environment/infrastructure.

• Socio-economic factors play a major role in prioritizing the sites for Brownfield redevelopment as the idea is

to maximise the economic and social benefits through it. Higher population density and unemployment rate

therefore means a large population might benefit though the Brownfield redevelopment (Chrysochoou et al.,

2012).

• Brownfield are often synonymous with contaminated or probably contaminated lands that may be an

environmental burden. The second factor therefore considers the maximum environmental benefit that can be

achieved through Brownfield redevelopment. The areas with higher permeability and probable contaminated

sites are preferred.

• The next two factors that include urban environment/infrastructure and social are essential for prioritizing

Brownfield areas. It is assumed that a Brownfield is already served by some basic level of physical and

social infrastructure. The urban primary core and areas served by sewer network, water supply, educational

and healthcare facilities are prioritized.

Variables Measurement Category

Population density Population per sq mile Socio-economic

Unemployment rate

Percentage of unemployed people amongst the

labour force Socio-economic

Soil type

Permeable-sand, Semi- permeable- silt,

impermeable- clay Environmental

Proximity to water source or aquifers Aquifer depth Environmental

Presence of flood prone area Availability Environmental

Presence of wetlands Availability Environmental

Threat due to former landuse/

contamination and existence of

environmental burden in official databases Number of probable contaminated sites Environmental

Parks, Open spaces & Recreation Percentage of area Environmental

Access to schools number of existing schools Social

Access to healthcare Number of (Hospitals+ dispensaries+ health

centres+ family planning centres + nursing

homes+ other institutions Social

Access to recreational-cultural-banking

facilities Number of existing facilities Social

Location in urban setting

Classification according to sequence of

development and density

Urban environment/

infrastructure

Transport accessibility

Share of area within walking distance of arterial

road

Urban environment/

infrastructure

Intersection Density Intersection/ sq mile of arterial roads within

urban footprint

Urban environment/

infrastructure

Utility Service Area Access to water supply and waste water

Urban environment/

infrastructure

Table 3: List of variables selected

Reclassifying data within a layer using Fuzzy Membership tool The next step was to get an idea how the Kolkata Metropolitan Area performs when assessed through the factors

of socio-economic, environmental, infrastructure, social. The data was obtained for the year 1991, 2001 and

2011 through various sources and mapped on a GIS interface.

It is followed by an overlay analysis that allowed combining the data to give a single output. The values that

were mapped consisted of various data levels of measure like nominal, ordinal interval and ratio. The nominal or

ordinal scale data (eg: location in urban setting is defined as primary urban core, secondary urban core, suburban

fringe and dispersed development zones) cannot be defined into specific categories but one is preferred over the

other and can guide in decision-making process (MesgariI, Pirmoradi, & Fallahi, 2008). So here fuzzy overlay

function is used which works on fuzzy membership logic in determining the level of confidence that the area is a

preferred for Brownfield redevelopment. The data is therefore reclassified and fuzzy membership function is

used. The values returned ranges from 0 to 1 where 0 indicating low possibility of membership and 1 indicating


higher possibility of membership. The variables are first overlaid to assess the performance of the study area in

the four categories identified. Finally the four factors were integrated using fuzzy overlay function to get a

conclusive result.

Combining the layers using Fuzzy Overlay Tool

In the final overlay the layers are combined using the Fuzzy logic and it explores the possibility of an area to

belong in different categories which are unlike Boolean or Index logic where the boundaries are well defined

(Raines, Sawatzky, & Bonham-Carter, 2010). The first level of overlay is done by combining variables to get

results under the four major categories. The results are grouped against the four categories of socio-economic,

environmental, infrastructure, social versus the six districts namely North 24 Parganas, South 24 Parganas,

Kolkata, Howrah, Hugli and Nadia.

Table number 4 shows the results through soft scoring with low, medium and high scores denoted by +, ++, +++

signs. The four layers are finally combined to get the scenarios for the scope of Brownfield redevelopment for

the years 1991, 2001 and 2011. For the final combination the type of Fuzzy overlay used was ‘AND’ to identify

locations that meet all the categories of suitability. The purpose was that all the categories namely

socioeconomic, environmental, and social and infrastructure find equal importance in the area identifications.

V. CONCLUSION For better interpretation the results from the fuzzy overlay was tabulated into categories along with districts to

which the municipalities belong. Following observation can be made from the table number 4:

• North 24 Parganas has high scores under environmental category and medium scores for socioeconomic, social

and infrastructure.

• South 24 Parganas: Follows a similar trend like North 24 Parganas with medium scores in all factors except

environment where it scores high.

• Kolkata : It is a high scorer in all the categories except in socioeconomic. In the 2011 it scores low in the

socioeconomic category which may be low unemployment rate.

• Howrah scores medium in all the categories except the environmental. It may be attributed to location of a

number of sites that are probably contaminated.

• Hugli also shows similar trend as Howrah with high scores in environmental category and a more or less

medium scores in all other.

• Nadia score high on infrastructure and environmental categories. It has a medium score in socioeconomic and

social categories.

Districts Year Socio-Economic Environmental Social Urban Environment/ Infrastructure

North 24

Parganas

1991 ++ +++ ++ +++

2001 ++ +++ ++ ++

2011 ++ ++ + +++

South 24

Parganas

1991 ++ +++ ++ +

2001 + +++ ++ ++

2011 ++ +++ + ++

Kolkata 1991 +++ +++ +++ +++

2001 +++ +++ +++ ++

2011 + +++ +++ +++

Howrah 1991 ++ +++ ++ ++

2001 +++ +++ ++ ++

2011 + +++ ++ ++

Hugli

1991 ++

+++ ++ ++

2001 ++ +++ ++ ++

2011 ++ +++ ++ +++

Nadia 1991 ++

+++ ++ +++

2001 +++ +++ ++ ++

2011 + +++ ++ +++

Table 4 : Summary of the scores from overlay function


Figure 3: The Urban environment/ infrastructure score (for the 1991. 2001 and 2911) If we focus on the urban environment and infrastructure category we observe that South 24 Parganas have

improved and North 24 Parganas have declined slightly for the year 2001 but improved later . Kolkata and Nadia

have more or less has been well serviced with some basic level of infrastructure. Howrah has a stagnant medium

level of infrastructure and has not been able to improve much. Hugli has improved its infrastructure over the

decade of 2001 to 2011. We observe that the Kolkata municipal corporation and its adjoin areas dominates the

region in terms of infrastructure sector showing a primacy behaviour. So scope of Brownfield development

would be more if only infrastructure sector was considered but a combined effect of all the factors show

different results.

Figure 4 : The final Brownfield Redevelopment score (for the 1991. 2001 and 2911)

After overlaying all the four categories we observe that for the year 1991 Howrah and Kolkata had maximum

conditions fulfilled for a Brownfield Redevelopment. In the year 2001,

Kolkata definitely dominated the region with its high levels of infrastructure, population density and social

factors. It also had the highest number of contaminated sites hence it has maximum scope for a Brownfield

Redevelopment. By the 2011 the whole region presented more or less equal scope for the Brownfield

redevelopment.

scale 1:400000

1991 2001 2011

scale 1:400000

1991 2001 2011


References [1] Adams, D., De Sousa, C., & Tiesdell, S. (2009). Brownfield Development: A Comparison of North American and British Approaches.

Urban Studies, 47(1), 75–104. https://doi.org/10.1177/0042098009346868

[2] Alker, S., Joy, V., Roberts, P., & Smith, N. (2000). The Definition of Brownfield. Journal of Environmental Planning and

Management, 43(1), 49–69. https://doi.org/10.1080/09640560010766

[3] Boin, A. (2009). The new world of crises and crisis management: Implications for policymaking and research. Review of Policy

Research, 26(4), 367–377. https://doi.org/10.1111/j.1541-1338.2009.00389.x

[4] Carter, J. G., Cavan, G., Connelly, A., Guy, S., Handley, J., & Kazmierczak, A. (2015). Climate change and the city: Building

capacity for urban adaptation. Progress in Planning, 95(July), 1–66. https://doi.org/10.1016/j.progress.2013.08.001

[5] Chicago Metropolitan Agency, & May, P. (2009). Brownfields Redevelopment Strategy, (May 2008).

[6] Chrysochoou, M., Brown, K., Dahal, G., Granda-Carvajal, C., Segerson, K., Garrick, N., & Bagtzoglou, A. (2012). A GIS and

indexing scheme to screen brownfields for area-wide redevelopment planning. Landscape and Urban Planning, 105(3), 187–198.

https://doi.org/10.1016/j.landurbplan.2011.12.010

[7] Cizler, J. (2014). Brownfield redevelopment as a measure for climate changes mitigation. Journal of the Geographical Institute Jovan

Cvijic, SASAZbornik Radova Geografskog Instituta Jovan Cvijic, SANU, 63(4), 57–73. https://doi.org/10.2298/ijgi1304057c

[8] Fernandes, A., de Sousa, J. F., Brito, S. S., Neves, B., & Vicente, T. (2018). Preparing Waterfront Brownfields Redevelopment for

Climate Change: the Water City Project, Almada (Portugal). Journal of Coastal Research, 85, 1531–1535.

https://doi.org/10.2112/si85-307.1

[9] Guerrero, I. M., & Stein, N. Roberto Zagha John Henry, S. M. (2011). India - Vulnerability of Kolkata metropolitan area to increased

precipitation in a changing climate. https://doi.org/Report No. 53282-IN

[10] Hamin, E. M., & Gurran, N. (2009). Urban form and climate change: Balancing adaptation and mitigation in the U.S. and Australia.

Habitat International, 33(3), 238–245. https://doi.org/10.1016/j.habitatint.2008.10.005

[11] Heid, J. (2004). Greenfield Development Without Sprawl�: The Role of Planned Communities.

[12] Idfc Foundation. (2016). India Infrastructure Report 2012. India Infrastructure Report 2012. https://doi.org/10.4324/9781315538914

[13] IPCC. (2014). Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Retrieved from

http://www.tandfonline.com/doi/abs/10.4155/cmt.13.80.

[14] Kolkata Metropolitan Development Authority. (2011). Introducing KMA. Retrieved from http://kmdaonline.org/home/download

[15] Marcotullio, P., Albrecht, J., & Sarzynski, A. (2011). The geography of greenhouse gas emissions from within urban areas of India: a

preliminary assessment. Journal of Resources, Energy and Development, 8(1), 11–35. https://doi.org/10.3233/RED-120079

[16] MesgariI, M. S., Pirmoradi, A., & Fallahi, G. R. (2008). Implementation of Overlay Function Based on Fuzzy Logic in Spatial

Decision Support System. World Applied Sciences, 3(1), 60–65.

[17] Pouliotte, J., Smit, B., & Westerhoff, L. (2009). Adaptation and development: Livelihoods and climate change in Subarnabad,

Bangladesh. Climate and Development, 1(1), 31–46. https://doi.org/10.3763/cdev.2009.0001

[18] Raines, G. L., Sawatzky, D. L., & Bonham-Carter, G. F. (2010). New fuzzy logic tools in ArcGIS 10. ArcUser, Spring, 8–13.

Retrieved from www.esri.com

[19] Rinaldi, S. M., Peerenboom, J. P., & Kelly, T. K. (2001). Identifying, understanding, and analyzing critical infrastructure

interdependencies. IEEE Control Systems Magazine, 21(6), 11–25. https://doi.org/10.1109/37.969131

[20] Rogers Richard, & Power Anne. (2000). The compact sustainable city - Designing Buildings Wiki. Retrieved July 12, 2017, from

https://www.designingbuildings.co.uk/wiki/The_compact_sustainable_city#Brownfield_vs_greenfield

[21] Rogers Richard, & Power Anne. (2017). The compact sustainable city - Designing Buildings Wiki. Retrieved July 12, 2017, from

https://www.designingbuildings.co.uk/wiki/The_compact_sustainable_city#Brownfield_vs_greenfield

[22] Satterthwaite, D., Huq, S., Pelling, M., Reid, H., & Lankao, P. R. (2007). Human Settlements Discussion Paper Series Adapting to

Climate Change in Urban Areas The possibilities and constraints in low-and middle-income nations. Retrieved from

http://www.rockfound.org/initiatives/climate/climate_change.shtml

[23] Tang, Y. T., & Paul Nathanail, C. (2012). Sticks and Stones: The impact of the definitions of brownfield in policies on socio-

economic sustainability. Sustainability, 4(5), 840–862. https://doi.org/10.3390/su4050840

[24] The Global Commission on the Economy and Climate. (2014). Cities. Better Growth, Better Climate: The New Climate Economy

Report, 2–33.

[25] Walsh, C. L., Dawson, R. J., Hall, J. W., Barr, S. L., Batty, M., Bristow, A. L., … Zanni, A. M. (2011). Assessment of climate change

mitigation and adaptation in cities. Proceedings of the Institution of Civil Engineers - Urban Design and Planning, 164(2), 75–84.

https://doi.org/10.1680/udap.2011.164.2.75

[26] Wilbanks, T., & Fernandez, S. (2013). Climate Change and Infrastructure, Urban Systems, and Vulnerabilities: Technical Report for

the U.S. Department of Energy in Support of the National Climate Assessment.

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