ORI GIN AL PA PER
Assessment of carbon leakage in multiple carbon-sinkprojects: a case study in Jambi Province, Indonesia
Rizaldi Boer Upik R. Wasrin Perdinan Hendri Bambang D. Dasanto Willy Makundi Julius Hero M. Ridwan Nur Masripatin
Received: 23 June 2006 / Accepted: 12 August 2006 / Published online: 20 March 2007 Springer Science+Business Media B.V. 2007
Abstract Rehabilitation of degraded forest land through implementation of carbon-sinkprojects can increase terrestrial carbon (C) stock. However, carbon emissions outside the
project boundary, which is commonly referred to as leakage, may reduce or negate the
sequestration benefits. This study assessed leakage from carbon-sink projects that could
potentially be implemented in the study area comprised of 11 sub-districts in the Batanghari
District, Jambi Province, Sumatra, Indonesia. The study estimates the probability of a given
land use/cover being converted into other uses/cover, by applying a logit model. The pre-
dictor variables were: proximity to the center of the land use area, distance to transportation
channel (road or river), area of agricultural land, unemployment (number of job seekers), job
opportunities, population density and income. Leakage was estimated by analyzing with and
without carbon-sink projects scenarios. Most of the predictors were estimated as being sig-
nificant in their contribution to land use cover change. The results of the analysis show that
R. Boer (&) Perdinan Hendri B. D. DasantoClimatology Laboratory, Department of Geophysics and Meteorology, Faculty of Mathematicsand Natural Sciences, Bogor Agricultural University, Kampus IPB Darmaga, Bogor 16680Indonesiae-mail: email@example.com
U. R. WasrinLand Management Grand College, Bogor Agricultural University, Kampus IPB Darmaga,Bogor 16680, Indonesia
J. Hero U. R. WasrinEcology Laboratory, Faculty of Forestry, Bogor Agricultural University, Kampus IPBDarmaga, Bogor 16680, Indonesia
W. MakundiLawrence Berkeley National Laboratory, Berkeley, CA, USA
M. RidwanLestari Hutan Indonesia, Jakarta, Indonesia
N. MasripatinDepartment of Forestry, Jakarta, Republic of Indonesia
Mitig Adapt Strat Glob Change (2007) 12:11691188DOI 10.1007/s11027-006-9058-1
leakage in the study area can be large enough to more than offset the projects carbon
sequestration benefits during the period 20022012. However, leakage results are very
sensitive to changes of carbon density of the land uses in the study area. By reducing
C-density of lowland and hill forest by about 10% for the baseline scenario, the leakage
becomes positive. Further data collection and refinement is therefore required. Nevertheless,
this study has demonstrated that regional analysis is a useful approach to assess leakage.
Keywords Carbon leakage Carbon-sink projects Logistic modeling Mitigation
In the past few decades, forest cover in Indonesia has declined significantly due to
increasing rate of deforestation in the larger islands (Kalimantan, Sumatra, Sulawesi and
Irian Jaya), extensive forest destruction by wild fires and a declining rate of reforestation
and afforestation. The forest estate is generally classified into several main types (ITTO
2002): (i) conservation forestfor scientific reserve and nature reserve, wild life sanc-
tuaries, national parks, grand forest parks and nature recreation parks, (ii) protection
forestusually on very steep slopes and vulnerable to soil erosion and water degrada-
tion, and not made available for logging, (iii) production and conversion forestfor
logging and also for conversion to other land uses, (iv) critical forestformer forest land
severely damaged by excessive harvesting of wood and/or non-wood forest products,
poor management, repeated fires, grazing, and disturbances or land uses that damage
soils and vegetation to a degree that inhibits or severely delays the re-establishment of
forest after abandonment, (v) degraded forestprimary forest that has been adversely
affected by the unsustainable harvesting of wood and/or non-wood forest products and
has lost the structure, function, species composition and/or productivity normally asso-
ciated with the natural forest type expected at that site, (vi) unproductive landslands
with reduced capability to produce goods and services that are economically and socially
viable such as fallow land, bare land, bush and thickets, and (vii) plantation forestsa
forest stand that has been established by planting or seeding. To illustrate the rate of
decline of forest cover, in 1997, the area classified as critical land and degraded forest
was estimated to be about 30 million hectares (Mha) (Boer 2001). By 2000, the area of
critical and unproductive lands in the state forestland had increased to 54.6 Mha (MOF
2001), an increase of 82% over 3 years.
This study is based on analysis done for potential carbon sequestration projects in Jambi
province. Based on a 1986 vegetation map and 1992 satellite imagery (Landsat TM), the
mean annual rate of deforestation in the province was estimated at 106,700 ha/year. The
annual rate of forestation (re-greening, reforestation, and timber estate plantations) was
significantly lower, estimated at about 14,000 ha per year between 1988 and 2000, with the
difference representing the annual increase in critical land area. In 1989, the total area of
critical land inside and outside forest area was 194,000 ha, and by 1999, this area had
increased to 716,000 ha. Total critical land in Jambi at the end of 2000 was about
887,500 ha, distributed in four districts, i.e., 77,100 ha in Batanghari 96,400 ha in Kerinci,
321,400 ha in Bungo Tebo and 329,500 ha in Sarko. About 61% of the critical land is
grassland, while the remaining is shrubs or fallow or shifting cultivation.
1170 Mitig Adapt Strat Glob Change (2007) 12:11691188
Funding sources for restoring forests are very limited. The Forest Rehabilitation Fund
(Dana Reboisasi) is only enough for restoring 34 Mha of degraded lands and forests(Boer et al. 2001), while total degraded lands and forest of Indonesia in 2000 reached
49 Mha (MoE 2003). Thus in order to reforest the remaining degraded lands other sources
of funds must be sought, including other domestic sources, and bilateral and other inter-
national funding mechanisms. The clean development mechanism (CDM) of the United
Nations Framework Convention on Climate Change (UN FCCC) Kyoto Protocol provides
one likely source of investment for reforesting these areas.
In addition to carbon benefits from the rehabilitation of degraded lands such projects
may have other benefits, including biodiversity, quality of life, watershed and water
quality, and adaptive capacity to climate change. However, accounting for the carbon (C)
that is actually saved by the projects poses a number of challenges (Brown et al. 1997).
First, most carbon sequestration projects involve multiple point sources of emissions or
sequestration and they are spread over a wider geographic area. This leads to complexities
arising from the variations in data, biomass and soil properties as well as in land-use
classification. Second, projects that sequester carbon may carry some risk of unintended
release of the C (e.g. in forest fires) or the duration of C storage may only be temporary.
Third, the implementation of these projects in a given location may lead to C emission or
sequestration in another area outside the project locationcommonly referred to as
leakage. Various suggestions have been put forth on approaches to address leakage (IPCC2000) but so far there has not been clear acceptable methodology which can resolve all the
major associated technical problems.
The two key elements in accounting for greenhouse gas (GHG) benefits are the (i) setting
of a baseline against which a change in GHG emissions or removals are to be measured, and
(ii) determination of additionality (the additional amount of C stored or emissions reduced by
the project). In addition, the baseline needs to be adjusted against leakage, i.e., for the loss or
gain of net GHG benefits beyond the project boundary. This study develops an approach for
the determination of the baseline and measurement of leakage in multiple potential forestry
projects in Batanghari District, Jambi Province, Indonesia.
Leakage is defined as loss or gain of net GHG benefits outside a project boundary.
According to a COP9 decision, leakage refers only to the increase of all greenhouse gases
outside the project boundary, measurable and attributable to the project. CIFOR (2001)
stated that leakage in sinks projects might occur when one of the following phenomena
occurs outside the project boundary:
Unallocated forested lands are harvested Protected areas are converted into production forest areas Illegal logging increases in protected and production forests Land is converted to lower C stocking rates due to emissions reductions elsewhere.
Furthermore, establishment of community woodlots may result from protection of an
area which previously was the source of timber and woodfuel for a community.
In order to predict whether leakage will occur or not, Auckland et al. (2001) stated that
baseline drivers, baseline agents, causes and motivations, and indicators that exist in theproject sites should be understood. Baseline drivers are defined as activities predominantly
Mitig Adapt Strat Glob Change (2007) 12:11691188 1171
taking place in the absence of the project, and that the project will replace. Baseline agentsare actors who are engaged in those activities. Causes and motivations refer to factors thatdrive the baseline agents to do the activities and these can be represented by indicators. Byknowing the interrelationship between these factors, we can predict whether leakage would
occur or not. The following example illustrates the definitions mentioned above.
Suppose that the type of activity proposed involves the establishment of timber estate
plantationHutan Tanaman Industri (HTI). The establishment of HTI in Indonesia nor-
mally takes place on state-owned land carried out by state enterprises or private forest
companies. At present only a few of the degraded production forests in Batanghari district
in Jambi have been converted into HTI. The idle degraded forest-lands are normally left as
unmanaged land (fallow) or used by local community for ranching, agricultural activities
or as a source of fuel wood. Fallow, ranching or agricultural activities are baseline drivers,while local communities that engage in these activities are the baseline agents. One of themain reasons for the local community to engage in these activities on this land is to get
additional income, and this factor is taken as cause and motivation. The next question is,what indicator can be used to measure the leakage?
To answer the above question, further information from related stakeholders in the
project site needs to be sought (see Fig. 1). The responses to the questions in Fig. 1 help to
determine whether leakage is likely to occur or not.
There are two main types of leakageprimary and secondary leakage (Moura-Costa
et al. 1997; SGS 1998). Primary leakage occurs when the GHG benefits of the project
cause an increase or decrease of GHG emissions elsewhere. For example, if the degraded
forest-land allocated for HTI is already used by the local community for agriculture, the
implementation of the HTI project may displace the agricultural activities to other areas or
may cause the community to engage in other income generating activities such as logging,
which would increase emissions elsewhere (negative leakage). Secondary leakage occurs
when a projects outputs create incentives to increase or to decrease GHG emissions
elsewhere. For example, the project increases economic activity in the project area that
creates additional income for the local community thus leading to a reduction in defor-
estation or illegal logging outside the project area (positive leakage). The project can also
lead to negative leakage if the increase in income leads to activities that increase GHG
emissions such as conversion of forest areas to rice cultivation. Thus, both primary and
secondary leakage can be positive or negative depending on the nature of their causes, and
the agents involved.
The above examples show that change in forest cover and C density outside the project
area can be an indicator of leakage. In order to know whether the deforestation rate is
altered by the project activities, we may need to track historical series of deforestation
surrounding such projects, before and after the initiation of the project. Other external
factors that may affect deforestation such as rate of population growth, agricultural prices,
demand for timber/fiber/fire wood, road density, change in forest law, and enforcement
policies also need to be assessed, as well as agents involved in baseline activities
throughout the project timeframe and the activities they engage in.
Considering that leakage may cover very wide areas away from the project area, the use
of satellite imagery for assessing the leakage can be very useful (e.g. Chomitz and Gray
1995; Hall et al. 1995). The potential extensive area of leakage impact is one reason put
forth advocating the use of regional baselines (IPCC 2000). In this study, we utilized
satellite imagery for assessing leakage and setting up a regional baseline for future sinks
1172 Mitig Adapt Strat Glob Change (2007) 12:11691188
Project site characteristics
Location of carbon-sink projects
The available maps could not be used to identify the critical lands, as such the analysis
assumed that the critical/degraded lands are generally to be found in the lowland logged-
over forest and secondary re-growth areas.
In this study, satellite images for the analysis were from Landsat TM 1986 and 1992, which
were obtained from Wasrin et al. (2000). The study area in Batanghari district has 12 sub-
districts, and it is assumed that carbon sequestration or avoidance projects will be
implemented in 11 sub-districts excluding the sub-district of Kodya Jambi.
What is the status of allocated degraded forest-land
Is the allocated land already planned for HTI by
government or companies?
Is the allocated land already degraded before
Is the allocated land used by local community for income
Does the project provide alternative livelihood
Do the baseline agents engage in the livelihood
It may not meet additionality rule
It may not meet Kyoto rule
Will the project increase wood supply or create new
No leakage expected
It may reduce deforestation
(positive leakage) It may increase deforestation
No leakage expected
Will the livelihood programs provide equal income with or more than the replaced ones?
Will the increase in income change the attitude...