







































Ecology, Economy and Society–the INSEE Journal 5 (1): 109-137 January 2022 

RESEARCH PAPER 

Valuation of Marine and Coastal Ecosystem Services 
in India 

KS Kavi Kumar, RC Bhatta, Pranab Mukhopadhya, LR Anneboina,  

P Naren, Megha Nath+, A Sharan++, Santadas Ghosh+++, V da 
Costa++++, S Pednekar+++++ 

Abstract: Coastal and marine ecosystems provide a host of services that are of vital 
importance to human well-being. We estimate the values of several provisioning, 
regulating, and recreational services using a combination of valuation methods. We 

find that the total value of these services in India was approximately ₹1.9 trillion (or 
US$0.11 trillion in purchase price parity [PPP] terms) in 2012–13, which constitutes 
about 2.4% of India’s net national product that year. Recreational services account 
for the largest share (45%), followed by regulating services (35%) and provisioning 
services (20%). These estimates do not include all the services provided by coastal 
and marine ecosystems; therefore, our estimates should be treated as a conservative 
underestimate of their total economic value. To the best of our knowledge, this is 
the first such attempt at the national level in India.  

Keywords: Coastal and marine ecosystems; Ecosystem services; Economic 
valuation; India 

JEL codes: Q57; Q51; Q22; Q26 

 
 Madras School of Economics, Chennai, kavi@mse.ac.in 

 National Centre for Sustainable Coastal Management, Chennai, rcbhat@gmail.com 

 Goa University, India, pm@unigoa.ac.in; https://orcid.org/0000-0001-9999-4938 

 Madras School of Economics, lavi.anneboina@gmail.com 

 National Centre for Sustainable Coastal Management, Chennai, narenp14@gmail.com 

+ National Centre for Sustainable Coastal Management, Chennai, meghanath23@gmail.com 

++ National Centre for Sustainable Coastal Management, Chennai, sharan.abhijit@gmail.com 

+++ Visva-Bharati University, Santiniketan, santadas_ghosh@yahoo.co.in 

++++ Goa University, India,  vanessdacosta@gmail.com 

+++++ Goa University, sulochana@unigoa.ac.in 

Copyright © Kumar, Bhatta, Mukhopadhyay, Anneboina, Naren, Nath, Sharan, Ghosh, 
Costa and Pednekar 2022. Released under Creative Commons Attribution © 
NonCommercial 4.0 International licence (CC BY-NC 4.0) by the author.  

Published by Indian Society for Ecological Economics (INSEE), c/o Institute of Economic 
Growth, University Enclave, North Campus, Delhi 110007.  

ISSN: 2581-6152 (print); 2581-6101 (web).  

DOI: https://doi.org/10.37773/ees.v5i1.536  

 

mailto:kavi@mse.ac.in
mailto:rcbhat@gmail.com
mailto:pm@unigoa.ac.in
https://orcid.org/0000-0001-9999-4938
mailto:lavi.anneboina@gmail.com
mailto:narenp14@gmail.com
mailto:meghanath23@gmail.com
mailto:sharan.abhijit@gmail.com
mailto:santadas_ghosh@yahoo.co.in
mailto:vanessdacosta@gmail.com
mailto:sulochana@unigoa.ac.in
https://doi.org/10.37773/ees.v5i1.536


Ecology, Economy and Society–the INSEE Journal [110] 

 

1. INTRODUCTION 

There have been a series of international efforts to address a significant gap 
in the conventional economist’s toolkit—an understanding of the state of 
the environment and how it impacts the economy and human welfare 
(Ayres 2008; Dasgupta 2008). While ecological economics and 
environmental economics emerged half a century ago (Dasgupta and Heal 
1979; Georgescu-Roegen 1971; Hartwick 1977; Martínez Alier 1987; Røpke 
2004; Solow 1974), the importance of the environment for sustaining life 
has attracted attention only in the last few decades (Daly 1993; Kates et al. 
2001; WCED 1987). National governments too have committed to 
expanding this knowledge base by commissioning focused studies on 
climate change (Stern 2007) and biodiversity (Dasgupta 2021). 

Just as economists and policymakers study national accounts to understand 
the state of the economy, we require a similar accounting framework to 
understand the implications of policy interventions for sustainability. This 
creates the need for comprehensive national accounts that not only tabulate 
conventional economic variables but also flows and stocks of natural and 
human resources (Arrow et al. 2012). The common problems that arise with 
natural resource accounting are that (a) many natural resources and assets 
do not have market prices; and (b) when they exist, these are not efficient 
(shadow) prices (Krutilla and Fisher 1975; UN 2014). 

Despite these limitations and the ethical issues that surround the valuation 
of natural resources (Daly 1993), there has been a growing consensus that 
unless an effort is made to value them, public policy will fail to give the 
environment its due place in decision-making (Torres and Hanley 2017). 
There has been remarkable progress in the evolution of techniques in this 
field (Arrow et al. 1993; Bateman 1993; Freeman 2003; Haab and 
McConnell 2002), and this has helped researchers place a price on natural 
resources to fit them into a utilitarian framework (Dasgupta 2009; Mäler, 
Aniyar, and Jansson 2008). One of the early studies that drew global 
attention to nature’s contribution estimated that ecosystem services that 
enhance human welfare far outweigh any contribution from conventional 
human-made capital (Costanza et al. 1997). This triggered a worldwide 
effort to understand the impact of anthropogenic pressures on natural 
capital, which was given a more concrete form by the Millennium 
Ecosystem Assessment (MA 2005). This was followed by the Global 
Initiative on the Economics of Ecosystems and Biodiversity (TEEB), which 
managed to bring together a wide range of studies on valuation (TEEB 
2010).  



[111] KS Kavi Kumar et al. 

 

Several studies were also commissioned in India under the Green 
Accounting for Indian States Project (GAISP), which attempted to replicate 
the methods used in global studies in the Indian context (GIST n.d.). Of 
the six studies carried out under GAISP, three were on forests, and of the 
remaining, there was one each on agriculture and pastures, education, and 
freshwater. Marine and coastal ecosystems were not studied separately 
under the GIST project.  

India has, for some time, been contemplating the adoption of a system of 
natural resource accounting to complement its annual national accounts of 
domestic product. Since 1997, the Indian government has been publishing 
an annual report titled the Compendium of Environmental Statistics. The Central 
Statistics Office of the Government of India also set up a technical working 
group called Natural Resource Accounting in the late 1990s, which 
commissioned a set of eight studies (land, forests, air, water, and subsoil 
resources) across eight selected Indian states (GASAB 2020). 

India took its most significant step toward evaluating ecosystem services in 
2011, with the formation of an expert committee headed by Partha 
Dasgupta (GoI 2013). The framework that this committee proposed went 
beyond that of the System of Environmental Economic Accounting 
(SEEA) developed under the United Nation’s System of National Accounts 
(UN 2014). The report also provided a way to integrate changes in natural 
capital with conventional national income accounts. It went on to record 
that “Empirical studies of the value of ecosystem services in India are sorely 
needed” (GoI 2013, 50). In fact, the TEEB database on ecosystem 
valuation records 1310 studies globally, of which only 32 pertain to India 
and only nine deal with coastal and marine ecosystems (CMEs) 
(Mukhopadhyay and Shyamsundar 2012; Ploeg and de Groot 2010). A 
recent review of 146 studies conducted between 1980 to 2018 on ecosystem 
services in India found that only 19 belonged to the CME category (Verma 
2018).  

There have been some international efforts at valuing CME services. In a 
comprehensive review, Schaafsma and Turner (2015) cover journal articles 
and book chapters published between 2000 and 2014. They found that 
most of these are case studies in Europe, the USA, and Southeast Asia, 
including 233 primary studies and nine meta-analyses. In recent years, there 
have been increased efforts at scaling up these valuation studies to the 
national, regional, and continental scale, especially in other parts of the 
world. We mention a few of these here. Recently, Trégarot et al. (2020) 
assessed the value of the mangroves, seagrass beds, coral reefs, and kelp 
forests of the whole African continent, across nine large marine ecosystems. 
They estimated the annual value of ecosystem services to be US$814 



Ecology, Economy and Society–the INSEE Journal [112] 

 

billion/year (at 2018 USD values) for four ecosystems—(a) coral reefs 
(US$588 billion/year); (b) seagrass (US$135 billion/year); (c) mangroves 
(US$91 billion/year); and (d) kelp (US$0.4 billion/year). In Asia, a regional-
level study found that CME services contributed about US$72 billion a 
year, amounting to about 6% of the gross domestic product (GDP) of the 
countries involved—Bangladesh, India, Indonesia, Malaysia, Maldives, 
Myanmar, Sri Lanka, and Thailand (BOBLME 2014). The study included 10 
categories of ecosystem services under the classification of (a) provisioning 
services—capture fisheries, aquaculture, wood-based energy, and timber 
and medicines; (b) regulating services—coastal protection and hazard 
mitigation, regulation of water flow and quality, mitigation of climate 
variability and change, maintenance of nursery populations and habitats; 
and (c) cultural services—recreational and cultural services, mainly tourism. 
This study relied almost entirely on benefit transfer values. 

In recognition of this knowledge gap, an Indo-German partnership between 
the Ministry of Environment, Forest and Climate Change (MoEFCC) and 
Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH 
(popularly known as GIZ) was formed to launch a national-level effort 
called The Economics of Ecosystems and Biodiversity – India Initiative 
(TII). The effort started with a scoping study that established the current 
landscape of ecosystem studies in India (Parikh et al. 2012). The programme 
funded 12 studies on three ecosystems—forests, wetlands, and CMEs—
which were completed by 2016. Even though these studies led to new 
knowledge, they were primarily case studies and have not led to national-
level aggregated estimates of the value of ecosystem goods and services.  

The absence of macro-level studies on ecosystem services in India, 
therefore, remains a knowledge gap. The current study aims to fill this gap 
by estimating the value of ecosystem services provided by CMEs. India, 
with its 7,517 km-long coastline, and over two million square kilometres of 
exclusive economic zone, which is rich in living and non-living resources, 
has a unique maritime position. The CMEs of India are not only relevant 
from an economic and environmental perspective, but also from a social 
perspective, with over four million fisherfolk and other coastal communities 
deriving their livelihoods from CMEs.  

The ecosystem classification we have followed derives from the Millennium 
Assessment (MA 2005) and TEEB (TEEB 2010). The study focuses on 
three types of ecosystem services: provisioning, regulating, and recreational 
services. It does not focus on supporting services due to data limitations. 
The results suggest that the total value of CME services in India is 



[113] KS Kavi Kumar et al. 

 

approximately ₹1.9 trillion (or, US$0.11 trillion, in PPP terms 1 ), which 
constitutes about 2.4% of India’s net national product in 2013.  

This study, to the best of our knowledge, is the first attempt to estimate the 
value of coastal and marine ecosystem services at the national level in India. 
Methodologically, it improves upon earlier attempts at large-scale valuation 
by combining different methods as well as local values rather than relying 
solely on global estimates and the benefit transfer method. It thus 
contributes to the relatively thin literature on the valuation of coastal and 
marine ecosystems at the national level. 

The rest of the paper is organized as follows. Section 2 describes the 
material and methods used for estimating ecosystem services. Section 3 
presents the results and analysis. Section 4 concludes the paper and 
provides a brief discussion of the findings.  

2. MATERIAL AND METHODS 

CMEs provide a wide range of goods and services, including marine 
fisheries, seaweeds, coastal minerals, coastal salt, seawater for drinking (after 
desalination) and industrial cooling, coastal shipping, coastal protection, 
carbon sequestration, and coastal recreation. The total value of ecosystems 
is generally divided into two categories: use- and non-use-value. The use 
values of ecosystems are the benefits that individuals derive from the direct 
or indirect use of ecosystem services. Non-use-values, on the other hand, 
reflect the satisfaction that individuals derive from knowing that ecosystem 
services are maintained and that others will have access to them. In the 
current valuation exercise, only the use values of coastal ecosystem services 
are estimated, including the benefits obtained from the direct or indirect use 
of ecosystem services. Among the direct use values estimated in this study, 
the values of fish, seaweeds, minerals, salt, and seawater used for 
desalination and industrial cooling fall under the extractive or consumptive 
use category, while the values of coastal shipping and coastal tourism fall 
under the non-extractive or non-consumptive use category. Either way, 
both categories of direct use values are reflected in market transactions (at 
least partially in some cases). Indirect use values are usually associated with 
regulating services such as coastal protection and carbon sequestration, 
both of which have also been estimated in this study. These may be seen as 
public services that are generally not reflected in market transactions. 

 
1 The purchasing power parity exchange rates are sourced from the OECD (n.d.) database. 



Ecology, Economy and Society–the INSEE Journal [114] 

 

Following the Millennium Ecosystem Assessment (MA 2005), the above 
mentioned coastal goods and services are further classified under three 
broad heads: (a) provisioning services, which includes the values of marine 
fisheries, seaweeds, coastal minerals, coastal salt, seawater used for 
desalination and industrial cooling, and coastal shipping; (b) regulating 
services, which includes the value of coastal protection provided by 
mangroves and the value of carbon sequestered by mangroves and 
seagrasses; and (c) recreational services, which includes the value derived 
from coastal tourism.  

The total economic value of ecosystem services is the sum of the consumer 
surplus (CS) and the producer surplus (or net rent), excluding the cost of 
production. In the case of essential ecosystem services that are not easily 
substitutable, there are no costs of production, and, thus, the product of the 
price and quantity estimates represents the producer surplus value. Further, 
if the ecosystem service approaches infinity as the quantity available 
approaches zero (or some minimal value), the CS is negligible. In such 
cases, the product of the price and quantity values could serve as a 
conservative underestimate of the sum of the consumer and the producer 
surplus, i.e., the ecosystem service value (Costanza et al. 1997). It must, 
however, be noted that such a conceptualization may provide an 
underestimate of the total economic value of the ecosystem service, as CS 
values are typically non-negligible. Simultaneously, since the input costs 
were not subtracted, the product of the price and quantity values could be 
upwardly biased. 

The present study uses three methods to estimate the value of coastal 
ecosystem services: (a) the direct market valuation approach; (b) the travel 
cost method; and (c) benefit transfers. We use three types of methods due 
to the complexity involved in evaluating different types of ecosystem 
services. While method (a) is suitable for provisioning services, method (b) 
is suitable for recreational services. For the remaining types of services, in 
the absence of reliable data, method (c) was adopted. In fact, the benefits 
transfer method is the most popular among these methods, as evidenced by 
its use in recent large-scale studies (BOBLME 2014; Milon and Alvarez 
2019; Trégarot et al. 2020). 

Where markets for ecosystem services exist, individuals’ preferences for 
ecosystem services are directly reflected in data from actual markets. Thus, 
in such cases, market data such as price, quantity, and cost information has 
been used to value coastal ecosystem services. This is commonly referred to 
as the direct market valuation approach, and it may be further divided into 
the market price-based approach and the cost-based approach, depending 
on whether price or cost information is used. The values of provisioning 



[115] KS Kavi Kumar et al. 

 

services such as fish, seaweeds, minerals, salt, and seawater used for 
desalination and industrial cooling have been obtained by multiplying the 
price of the service by the quantity produced in a given year. Cost-based 
approaches are based on estimates of the costs that would be incurred if the 
ecosystem’s benefits need to be recreated through artificial means (TEEB 
2010). One of the techniques used to estimate the value of ecosystems in 
this approach is the avoided cost method, which relates to the costs that 
would have been incurred in the absence of marine ecosystem services. The 
value of coastal and marine ecosystems in transporting goods via shipping 
has been estimated using the avoided cost method; specifically, we look at 
the costs avoided by transporting via sea instead of by road or rail.  

We use the travel cost method, which is a revealed preference approach, to 
estimate the value of coastal tourism. The rationale behind this method is 
that the opportunity costs of time, and the direct expenses that people incur 
when visiting a particular tourist site, represent the lower bound of the 
value of the recreational experience. Based on the number of trips that 
people make to a particular site and the travel costs incurred by them (i.e., 
based on the demand function for visiting the site), individuals’ willingness 
to pay to visit the site and associated CS can be estimated. Moreover, the 
demand function can be used to infer the value of a change in the quality or 
size of a particular tourist site due to changes in the ecosystem.  

In this study, the demand for recreational services is estimated using the 
zonal travel cost method. The travel cost (the total of actual travel expenses, 
accommodation and food expenses, and the opportunity costs of time) for 
domestic and foreign tourists was also estimated. This cost was deducted 
from the area under the demand curve to arrive at an estimate of the CS for 
all tourists who visited various coastal destinations in India in 2012–13.  

The third approach used is benefit transfer, which is the method of 
transferring values estimated in one study, location, and/or context to 
another. The advantage of using this method is that it circumvents the need 
to undertake several new ecological and economic studies, which are likely 
to prove expensive and time-consuming. The value of coastal protection 
(provided by mangroves) has been estimated using the benefits transfer 
method. The unit value of coastal protection estimated by Das and Vincent 
(2009) for Kendrapada district in Odisha has been scaled-up to the all-India 
level after adjusting for differences across coastal states and union 
territories (UT) in terms of a) the physical characteristics of cyclonic 
activity, b) the probability of occurrence of severe storms, c) mangrove 
quality, and d) income. 



Ecology, Economy and Society–the INSEE Journal [116] 

 

A brief description of the approaches adopted to evaluate various coastal 
ecosystem services is presented below. Table 1 summarizes the data sources 
and methodology followed to estimate the value of various coastal 
ecosystem services. Unless otherwise mentioned, data corresponding to the 
year 2012–13 has been used for the analysis. 

2.1 Marine Fisheries 

The fish catch statistics used in this study are taken from official sources 
(CMFRI 2014). The marine fishery resources are classified under three 
broad categories—demersal, pelagic, and shellfish. Pelagic species, which 
include common varieties such as oil sardines, mackerels, and tunas, 
dominate fish landings in India, amounting to 56% of landings in 2013. 
Demersal fish, including snappers, catfishes, pomfrets, and croakers, 
contributed to over 26% of landings. Shellfish, including crustacea, which 
comprise sought-after resources like prawns and lobsters and molluscs 
(clams, oysters, and squids), together contributed 18%. 

Using the direct market pricing method, each fish species’ value is estimated 
by multiplying its annual landing quantity across India by its standardized 
annual average price for 2012–13. The total of all values is estimated for 
three broad marine fish categories. 

2.2 Seaweeds 

Seaweed is commercially-processed to manufacture processing agents such 
as agar, alginate, and carrageenan in the pharmaceutical, food, fertilizer 
industries (Kaliaperumal, Kalimuthuand, and Ramalingam 2004; McHugh 
2003). In India, agar is used as a gel in food products such as processing 
jelly, dairy products, biopolymers, and many others. It has specific 
properties that make it suitable for use in solidifying agents in 
pharmaceuticals and disinfectants, nutraceuticals, veterinary medicines, 
tablet coating, and food supplements. There are three main types of 
carrageenan derived from red algae—lambda, kappa, and iota—each having 
its own gel characteristics. The culturing of Kappaphycus alvarezii was 
introduced due to its commercial viability in the Indian market. It is used as 
a clarifying agent while brewing beer and is used extensively in the dairy 
industry to stabilize ice-creams, flavoured milk, and evaporated milk 
products. The first attempt at culturing seaweed at a commercial scale was 
undertaken by PepsiCo Holdings India Ltd. in 2000, and this was further 
taken up by the Council of Scientific and Industrial Research–Central Salt 
and Marine Chemicals Research Institute (CSIR–CSMCRI) in Bhavnagar, 
Gujarat. Using production and price (at seashore) data sourced from the 
Seaweed Association and CSIR–CSMCRI, we estimated the total value 



[117] KS Kavi Kumar et al. 

 

generated by seaweed for provisioning services. The price and quantity data 
have been collected at the primary stage of the production cycle to avoid 
double counting. 

2.3 Coastal Minerals 

Indian beaches and coastal dunes contain several heavy minerals including 
ilmenite, rutile, garnet, zircon, sillimanite, and monazite. Information on 
production quantities and the average prices of these minerals are sourced 
from the Indian Mineral Year Book (IBM 2014). The quantity of reserves of 
ilmenite (including leucoxene) and rutile present in Indian coasts as of 
2011–12 was estimated to be 334.24 million and 28.91 million tonnes, 
respectively. Both minerals are found in coastal states such as Andhra 
Pradesh, Kerala, Odisha, and Tamil Nadu. The annual production of these 
minerals is less than 1% of the reserves. A total of 56.81 million tonnes of 
garnet is available on Indian coasts as of 2011–12, with Tamil Nadu and 
Andhra Pradesh—the states with the largest reserves of garnet—producing 
close to 4% and 0.3% of their total reserves, respectively, in 2011–12. The 
production of other minerals (sillimanite, zircon, and monazite) is largely 
concentrated in the states of Andhra Pradesh, Odisha, Tamil Nadu, Kerala, 
and Maharashtra. The valuation of coastal minerals in India is based on the 
amount produced in 2011–12 and their respective declared average prices 
for the same year. 

2.4 Coastal Salt 

Gujarat, Tamil Nadu, and Rajasthan are the major salt-producing states in 
India, meeting over 90% of the country’s requirements. The salt produced 
in coastal states and their respective prices were taken from the Annual 
Report of the Salt Department, Ministry of Commerce and Industry (2013–14) 
(GoI 2014). The production values were estimated by taking the difference 
between the salt stocks as of 31 March 2013 and 31 March 2014. For this 
study, only the average price of non-iodized salt in the respective states was 
taken to calculate the price of all salt entering the market in these states. 
The price of iodized salt was not considered, as the cost of iodization added 
to that of non-iodized salt would lead to an overestimation of salt prices. 

2.5 Seawater Desalination 

Given increasing water stress, several Indian states have started looking for 
alternative sources to address water scarcity. Seawater (and brackish water) 
desalination is increasingly being seen as an important means to address 
water scarcity in India. Tamil Nadu and Gujarat, two states that have widely 

https://www.zotero.org/google-docs/?V325Ip


Ecology, Economy and Society–the INSEE Journal [118] 

 

adopted desalination technologies, account for over 96% of the total 
installed seawater desalination capacity in the country. 

The value of seawater desalination is assessed as the installed production 
capacity multiplied by the price of water. The monetary value of the water 
(its scarcity cost) is taken as equal to the cost of the new source of supply, 
i.e., desalination. The desalination cost from the Minjur plant in Tamil 
Nadu is used to value this service. The price range used to estimate the 

value of the desalination service is ₹48.66–60 per m3 (in 2005 prices), 
which, when converted to 2012–13 prices using a GDP deflator, is 

estimated as ₹80.9–99.7 per m3. 

2.6 Seawater Used for Industrial Cooling 

Given that power plants consume the most water among all industries, and 
that coal-based thermal power plants and nuclear power plants have 
relatively lower efficiencies and thus higher water requirements for cooling, 
the analysis has been restricted to valuing the benefits of seawater used for 
cooling in coal-based thermal and nuclear power plants located along the 
coasts in India. 

The direct market valuation approach is used to value this service by 
multiplying the volume of seawater used by power plants with the price of 
raw water or freshwater. The value represents the water costs that power 
companies would have incurred if they did not have access to seawater and 
had to use freshwater instead. To that effect, this approach can also be seen 
as the avoided cost method, since the benefit power companies derive is the 
cost they avoid by using seawater instead of freshwater. 

Further, since the water requirements of power plants vary depending on 
the type of cooling system they use (i.e., once-through, closed-cycle, or dry), 
the valuation exercise considers the type of power plant, the cooling system 
it uses, and its operating capacity. The data on the capacity of power plants 
(CEA 2013), their water requirements, and the price of raw water (CEA 
2012) is obtained from the reports of the Central Electricity Authority.  



[119] KS Kavi Kumar et al. 

 

2.7 Coastal Shipping 

The benefits of coastal shipping are assessed as the costs avoided by 
transporting goods via sea instead of transporting them by road and rail. 
The analysis takes into consideration (a) all the maritime zones through 
which goods have been transported in 2012–13 (the year of analysis); (b) 
the different commodities transported (e.g., petroleum oil and lubricants, 
cement, among others); and (c) the economic as well as environmental costs 
associated with transportation. The benefits of coastal shipping as a means 
of transportation are estimated as: 

          (1) 

where, 

VSi are the benefits of coastal shipping, S, in terms of costs saved 
with respect to i, the alternate mode of transportation; 

i is the mode of transport other than shipping. Only the two major 
modes of freight transportation, namely, road and rail transport, are 
considered as alternatives in this exercise; 

z represents a pair of maritime zones across which goods are 
transported. There are 12 maritime zones and 48 pairs of maritime 
zones across which goods were transported in 2012–13; 

j is the type of commodity transported across maritime zones (e.g., 
petroleum oil and lubricants, cement). Transportation costs tend to 
vary by the type of commodity transported both within and across 
the different modes of transportation. Moreover, different 
commodities are transported via specific routes, depending on the 
demand and supply of the same; 

k is the category of the cost estimated. Economic and 
environmental costs alone are considered; 

D is the distance in kilometres between a representative port in one 
maritime zone and another port. Note that transportation routes, 
and, thus, distances, vary for the different modes of transportation 
for the same z; 

C is the cost in rupees per tonne-km by commodity. Costs vary not 
only by the type of commodity being transported but also by the 
distance travelled in some cases (road transport) as well as other 
specifics of the route (type of terrain (ghat/plain), type of road 
(national highway/other), type of track (single line/double line)) 



Ecology, Economy and Society–the INSEE Journal [120] 

 

and the mode of transportation (whether diesel or electric traction; 
more on this in the subsequent section); and 

T is the tonnes of goods transported by coastal shipping between 
the different maritime zones. 

Various economic and environmental cost parameters have been sourced 
from a Planning Commission study on Total Transport System (TTS-
RITES) (2013). The data on the commodity-wise quantity of goods 
transported across the maritime zones of India is taken from the 
Directorate General of Commercial Intelligence and Statistics (DGCIS 
2013).  

Sea distances between representative ports were calculated with the help of 
the SeaRates port distance calculator, road distances were calculated using 
Google Maps, and rail distances between the main railway stations closest 
to the representative ports in each maritime zone were obtained from the 
Indian Railways website. 

2.8 Coastal Protection by Mangroves 

We used the benefit transfer method to estimate the value of the storm-
protection service of mangroves. In particular, the value of the storm-
protection service rendered per hectare of mangrove per year from a study 
for Kendrapada district (Das and Vincent 2009) was first scaled-up to the 
coastal state/UT level and then to the all-India level. The coastal protection 
value of mangroves is estimated as follows: 

                           (2) 

                                (3) 

                                              (4) 

where V* is the one-time value of the storm-protection service as estimated 
by Das (2009) in INR/ha, pi is the probability of occurrence of a severe 
cyclonic storm over a 30-year period, i is the state/UT in question, CD is 
the mean canopy density in percentage, j is the category of mangroves (very 
dense, moderately dense, and open), CDmd is the mean canopy density of 
the moderately dense mangrove cover category (i.e., 55%), SFi is the state-
wise scaling factor, and Aij is the mangrove area (in ha) of the state i under 
mangrove cover category j.  

Summing the values across states and mangrove cover categories (the Vijs) 
gives the all-India value (VAI in INR/yr). The scaling factor (SF) is used to 



[121] KS Kavi Kumar et al. 

 

scale the Kendrapada storm-protection value to the state/UT level based 
on three variables: maximum wind speed (or probable maximum wind 
speed), probable maximum surge height, and per capita net state domestic 
product. Differences in the two former variables capture differences in the 
physical characteristics of cyclonic activity across states; meanwhile, 
differences in the latter capture differences in income (a proxy for the stock 
of goods and built infrastructure) across states.  

The data on the state-wise physical characteristics of cyclonic activity comes 
from the Vulnerability Atlas (BMTPC 2006). The historical data on the 
number of severe cyclonic storms that occurred over the past 30 years 
(from 1983–2013) in each coastal state is sourced from the Cyclone eAtlas 
(IMD, Version 2.0 web-based application). Data on the per capita net state 
domestic product (at constant 2004–05 prices) are from the Central 
Statistics Office. Data on mangrove area disaggregated by states/UTs and 
the three categories of mangrove cover were obtained from the India State of 
Forest Report (FSI 2017).  

2.9 Carbon Sequestration 

The direct market pricing approach is used to value the carbon 
sequestration service of mangroves and seagrass meadows in India. 
Estimates of the value of carbon sequestration by CMEs is based on the 
sequestration potential of the respective ecosystems, the extent of coverage 
of the coastal ecosystem, and the market rate or the social cost of carbon. 
The following function is used to determine the economic value of the blue 
carbon sequestered: 

             (5) 
   

where the value of carbon sequestered (VS) by a particular ecosystem (i) is 
measured by the product of its rate of carbon sequestration (SQ), measured 
in tonnes CO2-e/ha/year, the area (A) measured in ha, and the social cost 
of carbon (C) measured in INR/tonne CO2. 

The state-wise annual rates of carbon sequestration are estimated from total 
biomass stocks in mangrove forests in different coastal states, the data for 
which is taken from Sahu et al. (2015). The mean annual increase in 
mangrove biomass was estimated from the total biomass stock using Von 
Mantel’s formula, which states that the sustained annual yield is equal to 
twice the growing stock volume of the forest divided by the rotation age of 
the forest. For the rotation age of mangrove forests, we use the weighted 
average rotation period for littoral and swamp forests (averaging very dense, 



Ecology, Economy and Society–the INSEE Journal [122] 

 

moderately dense, and open littoral and swamp forests), which is 68.67 
years (Verma et al. 2014). The mean annual biomass increment is converted 
to an annual rate of carbon sequestration, assuming 50% of biomass as 
carbon and 1 tC as equivalent to 3.67 tCO2 following the IPCC (2003). The 
rates of carbon sequestration for seagrass meadows are sourced from 
Murray et al. (2010). It combines estimates from a variety of species and 
considers other characteristics such as sediment characteristics and the 
depth range of the seagrass habitat. The social cost of carbon is obtained 
from Nordhaus (2011). 

2.10 Coastal Recreation 

There were two methods available to estimate the recreational value of 
coastal and marine tourism. One possibility was to estimate the recreational 
value using the benefits transfer approach based on average values from the 
received literature (Costanza et al. 2014, 1997). The second possibility was 
to estimate the CS using the travel cost method (TCM), which is considered 
a robust technique (Freeman 2003; Mendelsohn and Olmstead 2009). This 
study relied on state-level studies conducted to estimate the tourism 
demand based on surveys of tourists. Using a normalization procedure, the 
zonal travel cost method (ZTCM) was used to estimate tourism demand for 
coastal zones (destination states) from various regions of the world as well 
as every state in India (origin zones) (Mukhopadhyay et al. 2020). The 
ZTCM estimates the visitation rate (V) to a destination (zone “i”) as 
follows:  

i

i
i

P

N
V =                (6) 

where, “Ni” is the estimated number of visitors from zone “i”, and Pi is the 
total population of the origin zone. 

The average travel cost is calculated per visitor. It includes all actual 
expenses like entry-fee (if any) and the opportunity cost of time. The trip-
generating function (TGF) is the relation between the visitation rate (Vi), 
the average travel cost from zone “i” (Ti), and other zonal characteristics: 

Vi = f (Ti, Zi)               (7)  

The demand function for each zone is assessed by applying the relevant 
value of “Zi” in the estimated TGF. The sum of such demand for all 
originating states to a destination state would provide an estimate of the 
aggregate demand curve for that coastal state. The CS is estimated as the 
area under the demand curve net of the visitor’s actual travel cost.  



[123] KS Kavi Kumar et al. 

 

Every destination state’s demand curve will have a choke price. At this 
price, the visitation from that zone reduces to zero. If “Ta” is the average 
(actual) price paid by visitors and “Tc” is the choke price for a zone, then 
the zonal CS would be: 

=
c

a

T

T

dtVCS             (8) 

The sum of all such zonal CS was considered as the recreational value of 
the destination state site (equation 8). 

Table 1: Valuation of Coastal Ecosystem Services – Data Source and Methodology 

Sl. 
No. 

Coastal and 
Marine 
Ecosystem 
Services 

Data Sources Methodology 

1 Marine 
fisheries 

CMFRI (2014) Direct market 
pricing 

2 Seaweeds Seaweed Association and CSIR–
CSMCRI; seaweed collectors; seaweed 
industries (Reddy, Rao, 
Meenakshisundaram, et al. 2014; Rao 
and Mantri 2006; personal 
communication) 

Direct market 
pricing 

3 Coastal 
minerals 

IBM (2014) Direct market 
pricing 

4 Coastal salt Ministry of Commerce and Industry, 
GoI (2014) 

Direct market 
pricing 

5 Seawater 
desalination 

Bulk water purchase agreement 
(BWPA), 2005, between Chennai 
Metropolitan Water Supply and Water 
Sewerage Board (CMWSSB) and 
Chennai Water Desalination (CWDL) 
(for the cost of desalination at Minjur 
plant) (CMWSSB n.d.; Water 
Technology n.d.); Global Water 
Intelligence reports; Chennai 
Metropolitan Water Supply and 
Sewerage Board  

Direct market 
pricing 



Ecology, Economy and Society–the INSEE Journal [124] 

 

Sl. 
No. 

Coastal and 
Marine 
Ecosystem 
Services 

Data Sources Methodology 

6 Seawater – 
industrial 
cooling 

CEA (2013; 2012); Batra (2012) Direct market 
pricing / 
avoided cost 

7 Coastal 
shipping 

 DGCIS (2013) Avoided cost 

8 Coastal 
protection 
(mangroves) 

Das and Vincent (2009); Das (2009, 2); 
BMTPC (2006); FSI (2017) 

Benefit transfer 

9 Carbon 
sequestration 
(mangroves) 

IPCC (2003); Nordhaus (2011); Sahu et 
al. (2015); Verma et al. (2014) 

Direct market 
pricing 

10 Carbon 
sequestration 
(seagrasses) 

11 Coastal 
recreation 

 Mukhopadhyay et al. (2020) Zonal travel 
cost 

 Source: Authors’ compilation. 

3. RESULTS AND ANALYSIS  

The values of different coastal ecosystem services are reported here for 
2012–13 prices. This section discusses the estimated values of coastal 
ecosystem services. 

3.1 Marine Fisheries 

The total estimated value of marine fish is approximately ₹295 billion as of 
2012–13. It may be noted that because cured fish as well as subsistence fish 
have not been accounted for in the valuation, the estimated value is 
significantly lower than that reported by the Central Statistics Office for 
2012–13. On the other hand, since the value of inputs has not been 
deducted, the estimates reported here also overestimate marine fish value in 
India. Among the broad fish types, results suggest that shellfish contribute 
40% to the total value of marine fish, even though shellfish landings 



[125] KS Kavi Kumar et al. 

 

account for only 18% of total landings. Pelagic and demersal fish contribute 
31% and 29%, respectively, to the total marine fish value in India.  

3.2 Seaweeds 

The estimated value of seaweeds is approximately ₹92 million in 2012–13 
prices. In terms of seaweed used in the manufacture of major processing 
agents, agarophyte, alginophyte, and carrageenophyte contribute about 
31%, 25% and 43%, respectively, of the total value of seaweed. 

3.3 Coastal Minerals 

Coastal minerals worth about ₹12.44 billion were produced per year in 
India. Ilmenite contributed close to 60% of the total value of coastal 
minerals, followed by zircon (about 18%), garnet (9%), and rutile (8%). 
Owing to the non-production of monazite in 2010–11 and 2011–12 by 
Indian Rare Earths Limited, the estimated value of coastal minerals does 
not include this mineral. Thus, the true annual value of coastal minerals in 
India is likely to be higher than that reported in this study. 

3.4 Coastal Salt 

The value of coastal salt in India is about ₹12.4 billion per year, with close 
to 80% of this value coming from the western state of Gujarat, followed by 
the southern state of Tamil Nadu (about 15%). As the recreational and 
cultural services offered by coastal salts are not included, the values 
reported here provide an underestimate of the true value of coastal salt. 

3.5 Seawater Desalination 

The value of saltwater desalination is estimated to be in the range of ₹18–

22 billion per year (in 2012–13 prices), with a mean value of roughly ₹20 
billion per year. Since Tamil Nadu and Gujarat have the highest production 
capacity in the country, together, they account for more than 96% of the 
value of saltwater desalination in India. Since the desalination capacity in 
India is likely to increase significantly in the future, the value of saltwater 

desalination could increase fourfold to about ₹80 billion per year. 

3.6 Seawater Used for Industrial Cooling 

For coal-based coastal thermal power plants that use seawater for cooling, 

the annual value of services ranges between ₹2.52–4.66 billion. Plants using 
the once-through cooling system account for almost 60% of this value, with 



Ecology, Economy and Society–the INSEE Journal [126] 

 

the remaining value accruing to the plants using closed-cycle cooling 
systems. The value of seawater used by coastal nuclear power plants is 

estimated to be about ₹0.06–0.10 billion, making the total average annual 

value of the cooling service contributed by the seawater, ₹3.67 billion. 

3.7 Coastal Shipping 

Coastal shipping leads to significant savings on transportation costs for 
goods compared to transporting via road and rail. Table 2 below presents 
the estimated range of values for the benefits of coastal shipping a) under 
the baseline scenario (i.e., considering economic and environmental costs 
only), b) with the inclusion of accident costs in addition to baseline costs, 
and c) with the removal of bottlenecks in coastal shipping, which would 
lead to an increase in the share of coastal shipping in the overall cargo 
movement. It is important to note that the first two categories of benefits 
are currently realizable (estimated for 2012–13). In contrast, the third 
category of benefits is hypothetical. An increase in the share of coastal 
shipping would occur only if the bottlenecks in the coastal shipping sector 
are dealt with effectively by the government. 

Table 2: Annual Value of Coastal Shipping (in INR billion) 

Category of Benefits 
 

Cost Savings over 
Road Transport 

Cost Savings over 
Rail Transport 

Baseline value (economic + 
environmental costs) 

61.85 15.86 

Inclusion of social (accident) 
costs 

63.80 15.88 

Increase in the share of coastal 
shipping 

127.59 31.76 

Source: Authors’ estimates 

3.8 Coastal Protection by Mangroves 

The annual storm-protection values for mangroves in India are estimated to 

range between ₹560–754 billion, with an average value of approximately 

₹650 billion per year. The storm-protection value of the Andaman and 
Nicobar Islands alone contributes almost 30% to the total, annual all-India 
storm-protection value, providing a strong basis for the conservation of 
mangroves on the islands. 

It is important to note that the values estimated in this study only include 
the storm-protection service of mangroves in terms of lives saved, livestock 
saved, and damages to buildings averted. Presumably, other types of 



[127] KS Kavi Kumar et al. 

 

damages are prevented by mangroves during storms, such as damages to 
agricultural land and public infrastructure. Similarly, mangroves could also 
serve as a nursery for young fish and hence contribute towards productivity 
enhancement in the fishery sector (Anneboina and Kavi Kumar 2017). 
Thus, the estimated benefits of mangroves reported in this study would be 
a lower bound of the true value. 

3.9 Carbon Sequestration 

The carbon sequestration service of seagrasses is valued between ₹12–40 

million per year (with a mean value of ₹30 million per year). In contrast, 
mangroves in India are estimated to provide carbon sequestration valued at 

between ₹0.76 and ₹1.65 billion (with a mean value of ₹1.21 billion per 
year), depending on the range of carbon sequestration rates and the average 
social cost of carbon considered.  

Verma et al. (2014) estimated the annual per hectare carbon sequestration 

values of littoral and swamp forests in India to be ₹8,736 for very dense 

forests, ₹3,729 for moderately dense forests, and ₹1,207 for open forests. 
Applying these values to mangrove areas with these canopy density 
classifications gives the total carbon sequestration value for mangrove 

forests in India as ₹1.94 billion per annum. This value is in the ballpark of 
the carbon sequestration value estimated for mangroves in the present 

study (i.e., mean of ₹1.21 billion), though it is slightly higher, which is 
expected since the values by Verma et al. (2014) were estimated for all 
littoral and swamp forests in India, whereas the value estimated in this study 
is for mangrove forests alone. 

3.10  Coastal Recreation 

The estimated CS by coastal recreation for visitors is estimated at ₹857.2 

billion. CS for domestic visitors is estimated at ₹295 billion, and that for 

visitors from the rest of the world is estimated at ₹562 billion. The extent 
of CS generated for visitors from the rest of the world is almost 1.8 times 
(in aggregate) more than the CS generated for domestic visitors 
(Mukhopadhyay et al. 2020). 

3.11  Consolidated Values 

As described above, the benefits derived from a wide range of CME 
services are estimated for India in this study. The CME services considered 
include provisioning services such as marine fisheries, seaweeds, coastal 
minerals, coastal salt, seawater desalination, seawater used for industrial 



Ecology, Economy and Society–the INSEE Journal [128] 

 

cooling, and coastal shipping; regulating services such as coastal protection 
and carbon sequestration; and recreational services such as coastal tourism. 
The estimates of CME services across these broad categories in India for 
2012–13 are presented in Table 3. 

Table 3: Annual Values of Coastal and Marine Ecosystem Services in India (2012–
13 Prices; in INR Billion) 

S. 
No. 

Service Valued Method of 
Estimation 

Value 
Range 

Average 
Value 

% of 
Total 
Value Min. Max. 

I. PROVISIONING SERVICES 

1. Marine fisheries Direct market 
pricing 

- - 294.48 20 

2. Seaweeds Direct market 
pricing 

- - 0.09 

3. Coastal minerals Direct market 
pricing 

- - 12.47 

4. Coastal salt Direct market 
pricing 

- - 12.40 

5. Seawater 
desalination 

Direct market 
pricing 

18.01 22.21 20.11 

6. Seawater – 
industrial 
cooling 

Direct market 
pricing 

2.58 4.76 3.67 

7. Coastal shipping Avoided cost 15.88 63.80 39.84 

 Total provisioning - - 383.06 

 
II. REGULATING SERVICES 

8. Coastal protection 
(mangroves) 

Benefit transfer 560.38 754.04 653.98 35 

9. Carbon sequestration 
(mangroves) 

Direct market 
pricing 

0.76 1.65 1.21 

10. Carbon sequestration 
(seagrasses) 

Direct market 
pricing 

0.01 0.04 0.03 

II. Total regulating 561.16 755.73 655.21 

III. RECREATIONAL SERVICES 

11. Coastal recreation Zonal travel 
cost  

  -  857.15 45 

III. Total recreational 857.15 

IV. GRAND TOTAL (I+II+III) 1,895.42 100 

Note: In cases where the parameters have been borrowed from other studies (e.g., 
coastal protection and carbon sequestration), all necessary adjustments have been 
made to standardize the values for use in the present study. 



[129] KS Kavi Kumar et al. 

 

Source: Authors’ estimates. 

The total value of the provisioning services estimated amounts to ₹383 
billion. The total value of the regulating services estimated is roughly 1.7 

times that of the provisioning service value at ₹655 billion, with a value 

range of ₹561–756 billion. The total coastal recreational value is more than 

double the value of the provisioning services (estimated at ₹857 billion) and 
is the highest of the three services examined in this study. The total value of 

CME services in India is approximately ₹1.9 trillion, of which provisioning 
services account for 20%, regulating services account for 35%, and coastal 
recreation accounts for 45%. The net national product (NNP) at factor cost 

(in current prices) in 2012–13 was ₹80.3 trillion (RBI 2020). Therefore, the 

estimated mean total CME service value for India (₹1.9 trillion or US$0.11 
trillion in PPP terms) is approximately 2.4% of the net national product 
(NNP).  

4. DISCUSSION AND CONCLUSION 

As discussed earlier, research on marine and coastal ecosystem services 
have mainly focused on provisioning services (like fisheries, seaweeds, and 
minerals, including sand and rare minerals), regulating services (like carbon 
sequestration and coastal protection), and recreation. There are several 
other services provided by CMEs, such as marine bio-pharmaceuticals and 
bio-prospecting, shoreline stabilization (erosion control), and cultural and 
spiritual values. These are domains that the present study could not value 
and constitute an area for future research. Knowledge gaps are not always 
caused by a lack of data or information—they are also caused by access 
restrictions and a lack of standardized data-collection protocols and 
coordination across different sectors.  

Questions have also been raised about the validity of aggregating ecosystem 
services as independent components to determine the value of a biome, 
especially since the science of interlinkages and feedbacks between 
ecosystems and the services they produce is incomplete (Barbier 2012).  

On the other hand, despite the increased importance of ecosystem services, 
coastal and marine resource policy and planning decisions are often not 
informed by ecosystem service valuations. A review of four major 
geographic regions across the globe (the European Union, the United 
States, Australia, and the Caribbean) indicates that CME service values are 
most often used for informational purposes and rarely used to evaluate 
trade-offs in policy decisions (Milon and Alvarez 2019). 



Ecology, Economy and Society–the INSEE Journal [130] 

 

Studies cite a variety of reasons for this situation. The most common 
concerns are a lack of understanding of ecosystem services among both 
policymakers and the public and the limited availability of valuation 
information for non-provisioning services in specific settings. This 
decision-making context for CME services policy and planning is a classic 
“wicked problem” with complexities, interdependence, and conflicting 
social interests. This emphasizes the need for valuation research on CME 
services in a wealth accounting framework. An economic valuation will 
build a case for investment in neglected sectors that have huge potential 
(Torres and Hanley 2017).  

It must be reiterated that the estimates reported in this study include only 
three broad types of services—provisioning, regulating, and recreational 
services—and exclude estimates for supporting services. Thus, the 
aggregate estimate reported here must be seen as a floor value of ecosystem 
services from CMEs in India.  

The only national estimate available for comparing the values reported in 
the present study is the one by World Bank (2013). They found the total 
value of ecosystem services from all biomes (including coastal ecosystems) 

to be ₹1.4 trillion in 2009. To put this in a comparative perspective, the 
value of ecosystem services was about 3% of India’s GDP in that year. The 
classification used for biomes (services) was forests, grasslands, wetlands 
(including coastal wetlands), mangroves, coral reefs, lakes, and rivers. In this 
classification, CMEs include mangroves, coral reefs, and coastal wetlands. 
However, ecosystem services from wetlands have not been separated by 
location (coastal or non-coastal). So, the contribution of the coastal zone 
cannot be separated clearly. The World Bank study found that wetlands 
accounted for the highest percentage contribution (48%), followed by coral 
reefs (22%) and mangroves (2%).  

The estimates reported in the present study suggest a much larger 
contribution of ecosystem services in India as compared to earlier studies. 
This assumes importance from the point of policy-making, where decisions 
about preserving natural capital need to be made. Another World Bank 
study estimated the extent of environmental degradation in India to be 

about ₹3.75 trillion as of 2009, which was 5.7% of the GDP (Mani et al. 
2012). This study focused largely on damages due to air pollution, land 
degradation, and water and sanitation but did not examine coastal and 
marine issues. UNISDR/UNDP highlighted threats to coastal ecosystems, 
especially in the context of climate change and sea-level rise (2012). These 
findings emphasize the need for economic policies and environmental laws 



[131] KS Kavi Kumar et al. 

 

to be cognizant of the importance of ecosystems in sustaining human 
welfare. 

To better inform the management of ecosystems and the sustainable 
development of ocean economies, data needs to be integrated across 
environmental, economic, and social knowledge domains. The development 
of more holistic statistics and indicators to measure the contribution of 
CME services to society and the economy, as has been attempted in this 
study, is in line with the Government of India’s stated policy towards the 
“Blue Economy” (GoI 2020). Such an attempt is also in sync with the 
central idea of The Dasgupta Review — that “economies are embedded within 
the Nature, not external to it” (Dasgupta 2021). For a comprehensive 
assessment of the contribution of coastal and marine ecosystem services, 
one must address the potential trade-offs and/or complementarities among 
various services to avoid overestimation and double counting and also to 
carry out assessments across multiple years. Future research could address 
some of the limitations of the present study and contribute towards the 
development of ocean accounts that are compatible with national 
accounting.  

ACKNOWLEDGEMENTS 
This work was undertaken as part of the project, ‘Linking Coastal Zone 
Management to Ecosystem Services in India’, funded by National Centre 
for Sustainable Coastal Management (NCSCM), Chennai. The authors 
would like to thank Prof. Kanchan Chopra and two anonymous referees for 
comments on earlier versions of the paper. The authors acknowledge the 
useful comments provided by the project review committee consisting of 
Prof. R. Ramesh, Prof. B. R. Subramanian, Prof. D. Chandramohan, Prof. 
R. Maria Saleth, Dr. Ahana Lakshmi, Dr. D. Asir Ramesh and Dr. Purvaja 
Ramachandran 



Ecology, Economy and Society–the INSEE Journal [132] 

 

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