Greenhouse gas emissions from land use change due to oil palm expansion in Thailand for biodiesel production

Accepted Manuscript Greenhouse Gas Emissions from Land Use Change due to Oil Palm Expansion in Thailand for Biodiesel Production Napapat Permpool, Sébastien Bonnet, Shabbir H. Gheewala PII:

S0959-6526(15)00595-8

DOI:

10.1016/j.jclepro.2015.05.048

Reference:

JCLP 5557

To appear in:

Journal of Cleaner Production

Received Date: 29 October 2014 Revised Date:

25 February 2015

Accepted Date: 13 May 2015

Please cite this article as: Permpool N, Bonnet S, Gheewala SH, Greenhouse Gas Emissions from Land Use Change due to Oil Palm Expansion in Thailand for Biodiesel Production, Journal of Cleaner Production (2015), doi: 10.1016/j.jclepro.2015.05.048. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Word count: 6,441 words Greenhouse Gas Emissions from Land Use Change due to Oil Palm Expansion in Thailand for Biodiesel Production

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Napapat Permpool1,2, Sébastien Bonnet1,2,* and Shabbir H Gheewala1,2

The Joint Graduate School of Energy and Environment, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand 2

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Centre for Energy Technology and Environment, Ministry of Education, Thailand * corresponding author: [email protected]

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Abstract

Thailand depends heavily on importation of fossil oil to satisfy its energy demand. The transportation sector is an important contributor to energy demand; biofuels are therefore strongly promoted in Thailand, notably biodiesel from oil palm. According to the Renewable and Alternative Energy Development Plan (AEDP 2012–2021) a biodiesel target of 5.97 million litres per day is to be achieved by 2021. This research focuses on assessing the implication of

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this on oil palm plantation area requirement, regions most suitable for its expansion and related greenhouse gas (GHG) implications as well as feedstock security. The investigations revealed that about 91,200 ha of land would be required for oil palm expansion to achieve the biodiesel target while also meeting other requirements for palm oil including domestic consumption,

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export, stock and surplus. The Eastern and Southern regions were identified as the two most suitable for oil palm cultivation with respectively 29,772 ha and 61,427 ha of mainly grassland

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and abandoned land. Oil palm expansion in the East would lead to overall land use change related GHG savings amounting to 47,214 tonnes CO2-eq per year. Oil palm expansion in the South would also bring GHG savings, 2.5 times higher than for the East. Keywords: Oil palm; Thailand; land expansion; GHG emissions; Feedstock security; Policy targets

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1. Introduction Thailand relies heavily on importation of fossil fuels to satisfy its energy demand. The importation of fossil oil translates in heavy financial cost and its use contributes to environmental

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impacts notably issues of climate change and air pollution, as well as risks to human health (Pleanjai et al., 2009).

At present, more than 70% of total energy consumption in Thailand is contributed in almost equal share by the industry and transport sectors (DEDE, 2012a). As Thailand is an agricultural

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country rich in biomass resources, the Thai government has made many efforts over the past 15 years in promoting renewable energy. The Renewable and Alternative Energy Development Plan

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(AEDP 2012 - 2021) is promoted by Thai government as a strategy to use such kind of energy to ensure greater self-reliance, improved energy stability and be able to meet the demand at both domestic and international levels. In this plan, a challenging target of 25% renewable energy has been set as a contribution to total energy consumption for 2021 with around 4% by biofuels (DEDE, 2011). The 2021 target of ethanol production has been set at 9 million litres per day (MLPD) while that of biodiesel around 6 MLPD. But with the growing demand for biofuels,

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issues of land use change and competition with food have surfaced (Kochaphum et al., 2013). Several studies have focused on investigating the sustainability of ethanol production in Thailand including environmental impacts, externalities and land use requirements (Nguyen and Gheewala, 2008; Silalertruksa and Gheewala 2009; Silalertruksa et al., 2009; Nguyen et al.,

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2010; Papong and Malakul 2010; Silalertruksa and Gheewala 2010). Other studies have also focused on similar issues for biodiesel (Pleanjai and Gheewala, 2009; Pleanjai et al., 2009;

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Siangjaeo et al., 2011; Silalertruksa and Gheewala, 2012; Silalertruksa et al., 2012). However, this study focuses on detailed modeling of the annual expansion of oil palm plantation area over the past decades, including harvested area, oil yield, and oil palm production and consumption. The processing of such information is however important to model future requirement in oil palm plantation to meet specific policy targets and so implications in terms of land use expansion and associated greenhouse gas (GHG) emissions (Silalertruksa and Gheewala, 2010). Biodiesel, also known as fatty acid methyl ester (FAME), is produced from the transesterification process of vegetable oils or animal fats with the addition of methanol (Meher et al., 2006). In Thailand, biodiesel is mainly produced from palm oil since oil palm plantations are well suited to 2

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tropical conditions and are characterized by the highest oil yield among oil yielding plants (Pleanjai and Gheewala, 2009). In 2012, biodiesel production capacity was around 1.72 MLPD (DEDE, 2012b). To achieve the 2021 policy target, the production of palm oil needs to be increased. This requires expanding oil palm plantations on to other land and also enhancing

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productivity.

Over the period 2001-2010, based on statistics from the Office of Agricultural Economics (OAE) the average annual increase in oil palm plantation area was about 9%. In 2012, there were about

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660,000 ha of land occupied by oil palm plantation out of which 600,000 ha were harvested (OAE, 2012). Although oil palm production has been steadily increasing over the years, there are variations in the yield of fresh fruit bunch (FFB) from which crude palm oil (CPO) is extracted

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to produce refined oil products and biodiesel. These are due to various environmental factors including climate variability, flooding events, diseases, etc. But on average, OAE (2012) reports the yield of FFB for oil palm plantation in Thailand to be 18 tonnes per ha (OAE, 2012). The expansion of oil palm plantation can induce land use change (LUC) issues and competition with other cash crops. LUC has raised considerable concerns over the last decade as it frequently

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goes along with environmental impacts including, deforestation, animal extinction and peatland destruction (FAO, 2013). LUC can also be associated with GHG emissions that may challenge the global warming performance of biofuels depending on the vegetation replaced (Siangjaeo et al., 2011). For instance, the conversion of tropical grassland to oil palm has been reported to

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contribute removing 135 tonnes CO2-eq per ha while forest conversion to oil palm plantation contributes emissions of around 650 tonnes CO2-eq per ha (Germer et al., 2008). Such issues

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need therefore to be carefully considered when energy feedstocks such oil palm plantations are to be expanded, avoiding to replace high carbon stock vegetation such as forests. In addition to land use type, soil quality needs also to be carefully considered so that it is adequate for oil palm production and productivity is attractive enough for farmers to consider growing such a feedstock.

This study aims therefore at assessing the area requirement for oil palm expansion in suitable regions of Thailand based on the biodiesel target and the land use change related GHG emissions of such expansion.

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2. Methodology 2.1 Background information about oil palm plantation and assumptions of this study To assess the area of oil palm plantation required by 2021 to satisfy the overall demand in CPO including that for biodiesel production, two main factors need to be investigated, the area of oil

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palm plantation harvested in each year and the potential yield of fresh fruit bunch (FFB) per area. The area of oil palm plantation harvested is based on the assumption that the area of new planting in each year will be harvested in the third year after being planted (DOA, 2011). The yield of FFB varies with the age of an oil palm tree. However, its productive lifetime is

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considered to be 25 years as it corresponds to the period during which yields of FFB are still within competitive range and it is not too hard to harvest (Akesamatramate et al., 2005; ACFS,

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2008).

Yearly information about area of oil palm plantation since 1982 up to 2012 and yield of FFB per age of tree were obtained from OAE (2012). This information was combined to calculate past production of FFB up to 2012. In 2012, oil palm plantations covered an area of 0.7 million ha out of which 0.62 million ha were harvested and 11.33 million tonnes of FFB were produced. This

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information was used in order to forecast future production up to 2021.

2.2 Parameters to estimate the amount of CPO required for biodiesel production The two major aspects to consider when planning for oil palm plantation are the supply and

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demand side for all sectors consuming CPO. In terms of supply, in addition to plantation area and yield of FFB, oil extraction rate (OER) needs to be considered (about 17%) (OAE, 2012).

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Although the AEDP policy target for biodiesel production is used as the basis to assess the requirement in CPO by 2021, all sectors contributing to CPO demand are considered. Aside from biodiesel (B100), these include: domestic consumption, Bio-Hydrogenated Diesel (BHD) production, safety stocks and export. The assumptions and data used to estimate the future demand of those sectors for CPO are detailed below.

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2.2.1 Domestic consumption This sector provides refined oil products derived from CPO for food and cosmetic industries. In Thailand, domestic oil palm consumption has been increasing over the years at a stable rate and is directly proportional to the population growth rate. According to data from DIT (2010), this

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rate is in the range 3 to 5 %. It is therefore assumed in this study that the future increase in domestic oil consumption will follow a 3% annual increase as per population growth rate (DLT, 2012; NSO, 2012).

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2.2.2 Biodiesel consumption

Biodiesel consumption in the transport sector is encouraged by the central government to reduce

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dependency on imported fossil fuel diesel, reduce energy cost, and improve environmental performance. The actual consumption of diesel referred to as high-speed diesel (HSD) and B100 for the years 2011 and 2012 are reported in Table 1. As mentioned earlier, the B100 production target of 2021 is set at 5.97 million litres per day. Thus, to assess the requirement in CPO to satisfy the target, two factors need to be assessed, the HSD consumption and the fraction of B100 to be blended with HSD to produce the required blend of biodiesel for transport. With regard to

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HSD, as recommended by DEDE (personal communication), a 3% annual increase in the population growth rate was used instead to forecast the future demand in HSD (DLT, 2012; NSO, 2012). In terms of blending, the level is based on the forecasted consumption of HSD over the next decade and the AEDP policy target set for B100. Based on information from DEDE

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(2012c), the blending level of biodiesel should reach 7% (B7) in 2015 and 9% in 2019 (B9).

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Table 1 Actual blending of biodiesel during 2011-2012

When assessing the amount of CPO required for producing a certain amount of B100, two major aspects need to be taken into consideration (1) the regulation from DEDE regarding blending level of biodiesel and (2) the proportion of stearin used for B100 production. According to DOEB (2012c), the biodiesel blending level is in the range 90 to 100% of the mandated blending level. Stearin, a co-product of palm oil refinery (for domestic consumption) is also used for biodiesel production. The production of stearin is around 0.29 kg per kg of CPO in the refining process (Papong and Malakul, 2010). In 2012, about 141,337 tonnes of stearin was used for 5

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biodiesel production, this fraction increased by 5% in 2013 (EPPO, 2012). Prediction of the amount of stearin used for biodiesel production during 2013-2021 is based on the assumption that 20% of the total amount of stearin produced each year is used for biodiesel over the period 2013-2016 increasing to 22% over the period 2017-2021 (DEDE, 2012c; Papong and Malakul,

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2010). Also, a CPO to biodiesel conversion factor of 0.87 (v/v) and a stearin to biodiesel conversion factor of 0.86 (w/v) were used in the calculations of biodiesel production based on

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information from DEDE (2012c), DIT (2012) and EPPO (2012).

2.2.3 Bio-hydrogenated diesel

Bio-hydrogenated diesel or BHD is a new biofuel. It requires CPO as raw product to be

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produced via the hydrotreating process. According to the 10-year AEDP (2012-2021) BHD should be available since 2017 with a targeted CPO requirement for its production of 300,000 tonnes per year (DEDE, 2011). This amount was also taken into consideration as part the overall assessment in CPO requirement and so oil palm plantation area.

2.2.4 Safety surplus

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The stock surplus corresponds to the amount of CPO that is stocked for consumption in the following year. Based on personal communication with OAE, it is around 1.5 times that of the monthly overage CPO consumed over a year to satisfy overall demand in Thailand (domestic consumption and biodiesel). In 2012, for instance, the average monthly consumption of CPO was

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(DIT, 2012).

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about 129,887 tonnes, which translates into 200,000 tonnes of surplus for the following year

2.2.5 Export

The amount of CPO exported is based on the remaining amount of CPO after demand in the country from all users has been satisfied. It is also an important aspect to consider for CPO requirement as it brings additional income to the country. The amount of CPO extracted from FFB each year surpasses the demand for national consumption. For future years, the assumption for this sector is that over the period 2013-2016, 200,000 tonnes per year of CPO would be exported, reducing to 100,000 tonnes per year over the period 2017-2021, as expansion of new

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oil palm plantations would be stopped in 2019 when the CPO amount is enough to satisfy the AEDP biodiesel target of 2021 (DEDE, 2011).

2.3 Selection of areas for oil palm expansion and land use change related GHG emissions

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2.3.1 Criteria of land suitability for oil palm expansion

A basic assumption of this study is that land previously occupied by forests and other perennial plantations, and productive food crops cannot be considered for oil palm expansion in order to avoid land use competition issues. The selection of areas for expansion of oil palm is based on

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the identification of land whose physical and soil characteristics are suitable for oil palm. Land suitability classification for oil palm is based on information from the land development

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department (LDD, 2009 and FAO, 2010). The criteria considered include various factors such as, temperature, rainfall, soil drainage, nutrient availability etc.

Based on this information, land falling under the categories ranging from “very suitable” to “marginally suitable”, are considered for oil palm expansion. According to this information, most of the areas located in the South and East of Thailand are suitable for oil palm expansion.

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According to LDD, the Northern and Northeastern regions are not recommended as rainfall is limited and there is reliance on irrigation to grow crops. Looking further into the types of land suitable for oil palm cultivation, oil palm expansion was restricted to land areas occupied only by abandoned land (including abandoned paddy fields and other crop lands), grassland and some

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marsh and swamps. This is as mentioned above to avoid land competition issues and minimize

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GHG emissions that may result from land use change.

In those regions, based on the land use types and areas required for oil palm expansion, the associated GHG emissions were assessed as an indicator of environmental performance. The steps and assumptions considered are detailed below.

2.3.2 Land use change related GHG emissions associated to oil palm expansion The assessment of GHG emissions associated with oil palm expansion on the main land use types identified in the previous section was performed following the IPCC 2006 guidelines for 7

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the AFOLU sector (Agriculture, Forestry and Other Land Use) (IPCC, 2006). The basic equation used for this assessment is as shown below:

Where: ∆CLU = Carbon stock changes for a land use, t CO2-eq year-1

(1)

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∆ = ∆  + ∆ + ∆  + 

∆Cbiomass = Annual change in carbon stocks in biomass (the sum of above-ground and

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below-ground biomass) considering the total area, t CO2-eq year-1

∆CDOM = Annual change in carbon stocks in dead wood or litter, t CO2-eq year-1

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∆Csoil = Annual change in carbon stocks in soil, t CO2-eq year-1

Lfire = Annual GHG emissions from land clearing, i.e. removal of vegetation by fire (open burning) in t CO2-eq year-1

Based on the above, four parameters need to be assessed for land use change related GHG emission calculations. These are: annual change in carbon stocks in biomass, annual change in

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carbon stocks in dead wood or litter, annual change in carbon stocks in soils and GHG emissions from fire for land clearing. Data to perform this assessment was retrieved from the literature and when not available using relevant default values as reported in the IPCC 2006 guidelines. Details

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of each parameter are shown in Table 2.

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Table 2 Parameters considered for carbon stock change calculations

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3. Results and discussion 3.1 Oil palm area expansion requirement Based on the assumptions detailed in Sections 2.1 and 2.2, the future oil palm plantation area requirement to achieve the biodiesel target of 2021 was modeled taking into account CPO import

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and export, CPO stock and domestic consumption. The details of these assessments both for CPO supply and demand are reported in Tables 3 and 4. It must be noted here that oil palm trees produce FFB at year 3 and their yield keeps increasing until year 7. The yield then stabilises for 10-11 years before gradually decreasing until year 25 after which the oil palm is usually

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replanted. This has been taken into account to estimate the average yield of FFB in each year and consequently determine the amount of FFB produced (and so CPO) up to 2012. However,

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starting since 2013 and up to 2021, the yield of FFB in each year was calculated based on the estimated area of oil palm to be harvested and amount of FFB produced. Both these parameters were assessed based on the amount of CPO determined to be produced each year to satisfy the demand in accordance with the steps and assumptions detailed under section 2.2.

The Tables 3 and 4 reveal that there is no shortfall in CPO supply in any of the years up to 2021;

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this is an important consideration for feedstock security. A shortfall of CPO in an intermediate year would not have been revealed if only the final target value of biodiesel in the year 2021 had been considered. Another important point these tables highlight is that the expansion of oil palm is not influenced by biodiesel only, but all sectors requiring CPO, notably the domestic sector

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whose demand keeps gradually increasing over the years following the population growth rate

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(see sections 2.2.1 and 2.2.2).

Table 3 Total CPO production supply based on the model of this study

Table 4 Total CPO demand based on the model of this study

To meet the requirement in CPO to satisfy the biodiesel target of 5.97 MLPD by 2021, an estimated annual CPO production of around 1.6 million tonnes is required. In that year, the estimated FFB yield (20.5 tonnes per ha) and recommended OER (18.5%) values that were used to assess the overall requirement in oil palm plantation area are in accordance with those 9

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suggested in the 10-year AEDP (2012-2021). The additional area of oil palm required to achieve the 2021 biodiesel target while also satisfying all other requirements in CPO, amounts to about 91,200 ha and it is imperative that the expansion of oil palm plantation starts since 2013 to be

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able to achieve the 2021 biodiesel target.

Focusing on the results reported in Table 4, it is observed that biodiesel consumption contributes the major share of CPO consumption (almost half of the total CPO produced in 2021 is used for biodiesel production). As the total production of CPO in that year is estimated to amount to 3.4

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million tonnes, domestic consumption appears to be the next major consumer with 36% followed by BHD with 9%. The remaining 6% of the total CPO production is contributed by CPO stock,

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surplus and export combined together. With regard to the assumptions made for biodiesel production up to 2021, since B7 (7% biodiesel blend) should be made available on the market by 2015 (DEDE, 2011), it was identified that B9 should be made available for consumption by 2019 so that1.6 million tonnes of CPO can be produced by 2021 to reach the B10 biodiesel policy target of 5.97 MLPD as set in the 10-year AEDP (2012-2021).

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3.2 Regions for oil palm expansion and land use change related GHG emissions 3.2.1 Regions and types of land suitable for expansion of oil palm plantation For the expansion of oil palm in Thailand, based on the land suitability criteria outlined in Section 2.3 and land use data from LDD (2012) for the year 2012, it was found that a total of

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105,111 ha of land could potentially be used for oil palm expansion in the Southern and Eastern

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regions of Thailand. This surpasses the actual requirement for oil palm expansion of 91,200 ha.

Based on this information the main land use types identified to be suitable and available for oil palm expansion in the Eastern region include mainly grassland, abandoned paddy field and abandoned cropland. In the South, these include abandoned paddy field, grassland, and marsh and swamps. The land use types and corresponding areas needed to match the area requirement for oil palm expansion are detailed in Table 5. Table 5 Land types and areas for oil palm expansion in the Eastern and Southern regions of Thailand

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To match the land area requirement for oil palm expansion (91,200 ha out of the available 115,111 ha) the extra area of land was cut out from the marsh and swamps category in the South as this is less environmentally preferable. Based on this assumption, it is observed that in this

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region most of the land area that could be used for oil palm expansion is represented by abandoned paddy field with 60% followed by grassland with 36%, while marsh and swamps contribute the remaining 5%. In total 61,427 ha of land could be used in the South for oil palm

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expansion (the original potential was 75,338 ha).

In the Eastern region, grassland is the land use offering the highest coverage for oil palm expansion with 56%, followed by abandoned paddy field with 31% and then abandoned cropland

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with 13%. In total these land types selected for oil palm expansion cover an area of 29,772 ha.

3.2.2 GHG implications associated to oil palm expansion

The land use change associated to oil palm expansion and resulting GHG emissions can be a useful indicator of environmental performance for land zoning and planning.

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In Eastern, Table 5 reveals that the largest area of land that could be converted to oil palm is grassland followed by abandoned paddy field and abandoned cropland. The GHG implications of such land conversions to oil palm plantation were assessed following the steps and assumptions

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reported in Table 2. The results in Table 6 indicate that oil palm expansion in the East would contribute GHG savings amounting to 47,214 tonnes CO2-eq per year. The greatest savings are from the conversion of grassland to oil palm with about 31,278 tonnes CO2-eq per year. This

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represents about 66% of the overall GHG savings associated to oil palm expansion in this region; abandoned paddy conversion to oil palm contributes another 24% and abandoned crop and conversion the remaining 10%. It is also noticed that the GHG savings are mostly influenced by the area of land being replaced by oil palm rather than the type of land being converted.

Table 6 Estimation of carbon stock change for oil palm expansion in the East In the South, the largest area of land that could be converted to oil palm is abandoned paddy field, followed by grassland, and marsh and swamp (see Table 5). The GHG implications of such 11

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land conversion are reported in Table 7. The results show that oil palm expansion in the South also brings GHG savings which for this region are 2.5 times that of the East, at about 115,882 tonnes CO2-eq per year. As the land area that could be converted to oil palm in this region is about half that of the Easter region, this result confirms that most of the GHG savings are

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attributable to the land area itself. The greatest carbon savings are from the conversion of abandoned paddy field with about 62,183 tonnes CO2-eq per year. However the conversion of marsh and swamps contributes net GHG emissions amounting to 5,137 tonnes CO2-eq per year.

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Table 7 Estimation of carbon stock change for oil palm expansion in the South

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These results also reveal that the conversion of abandoned paddy field and grassland to oil palm contributes each about half of the overall carbon saving. Marsh and swamps because of their comparatively much smaller area coverage (as compared to grassland and abandoned paddy field) have a minor impact on reducing the overall GHG saving associated to oil palm expansion in that region.

The above investigations have shown that the East and South offer enough land area with

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suitable soil quality to grow oil palm plantation. Since the land types selected are essentially grassland or abandoned cropland (including abandoned paddy field), conflicts of direct land use competition issues with food or other energy crops are avoided. The expansion of oil palm on such land enables also to bring GHG benefits through the storage of carbon in oil palm biomass

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which by far outweighs the carbon losses associated to the initial land use types being replaced. Since the South and East of Thailand where initially retained on the basis that they offer

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favorable weather conditions, i.e. sufficient water supply via rainfall, and good soil suitability for oil palm cultivation, the results of this environmental assessment confirm the good potential of these two regions for oil palm expansion. Looking back at the AEDP target for biodiesel in 2021, since half of the CPO produced in that year would be required to satisfy this target (see Table 4), the results reported in Tables 6 and 7, indicate that the expansion of oil palm in the South and East would contribute GHG savings of about 80,000 tonnes CO2-eq per year. Such an expansion would therefore contribute to further benefit the overall life cycle GHG performance of biodiesel (Pleanjai et al., 2009). 12

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4. Conclusion The assessment of the oil palm plantation area required to meet the AEDP targets of 2021 for biodiesel (5.97 MLD) revealed that about 91,200 ha of additional land would be needed to meet

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this target. This would also enable to meet whole domestic demand in CPO, stock and surplus requirements as well as export thus ensuring feedstock security over the next 8 years. With regards to the expansion of oil palm plantations in Thailand, based on land availability and suitability criteria, the East and South were identified the most promising regions. In the Eastern region, it was found that 29,772 ha of land would be required for oil palm expansion leading to

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annual GHG savings amounting to 47,214 tonnes CO2-eq. In the Southern region, 61,427 ha of land would be required for oil palm expansion leading to annual GHG savings amounting to

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115,882 tonnes CO2-eq.

The results of this study should be useful for policy makers, providing information on the area and regions of Thailand that should be considered for oil palm expansion and meet the 10-year AEDP (2012-2021) biodiesel target set of 2021. They also highlight that such expansion would contribute to enhance the life cycle GHG benefits associated to biodiesel and the importance of

Acknowledgements

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land planning and zoning for oil palm expansion.

The authors would like to acknowledge the Joint Graduate School of Energy and Environment at

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research study.

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King Mongkut’s University of Technology Thonburi for providing scholarship to perform this

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LDD, 2012. The suitable Land for Oil Palm Plantation in Thailand. Land Development Department, Ministry of Agriculture and Cooperatives, Thailand. Meher, L.C., Vidya Sagar, D., Naik, S.N., 2006. Technical Aspects of Biodiesel Production by

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Transesterification - A Review. Renew. Sust. Energ. Rev. 10, 248–268. Nguyen, T.L.T, Gheewala, S.H., 2008. Fossil Energy, Environmental and Cost Performance of Ethanol in Thailand. J. Clean. Prod. 16(16), 1814-1821. Nguyen, T.L.T, Gheewala, S.H., Sagisaka, M., 2010. Greenhouse gas savings potential of sugar

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cane bio-energy systems. J. Clean. Prod. 18(5), 412-418. NSO, 2012. Population Statistics in Thailand. National Statistical Office, Ministry of

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Information and Communication Technology, Thailand. OAE, 2012. Agricultural Statistics of Thailand. Office of Agricultural Economics, Ministry of Agriculture and Cooperatives, Thailand. www.oae.go.th. Papong, S., Malakul, P., 2010. Life-cycle Energy and Environmental Analysis of Bioethanol Production from Cassava in Thailand. Bioresource Technol. 101, 112-118. Pleanjai, S., Gheewala, S.H., 2009. Full Chain Energy Analysis of Biodiesel Production from Palm Oil in Thailand. Appl. Energ. 86, 209-214. Pleanjai, S., Gheewala, S.H., Garivait, S., 2009. Greenhouse gas emissions from production and use of used cooking oil methyl ester as transport fuel in Thailand. J. Clean. Prod. 17(9), 15

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873-876. Siangjaeo, S., Gheewala, S.H., Unnanon, K., Chidthaisong, A., 2011. Implications of Land Use Change on the Life Cycle Greenhouse Gas Emissions from Palm Biodiesel Production in Thailand. Energ. Sustain. Dev. 15, 1-7.

ethanol Production in Thailand. Energy, 34, 1933-1946.

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Silalertruksa, T., Gheewala, S. H., 2009. Environmental Sustainability Assessment of Bio-

Silalertruksa, T., Gheewala, S. H., Sagisaga, M., 2009. Impacts of Thai Bio-ethanol Policy Target on Land Use and Greenhouse Gas Emissions. Appl. Energ. 86, 170–177.

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Silalertruksa, T., Gheewala, S. H., 2010. Security of Feedstocks Supply for Future Bio-ethanol Production in Thailand. Energ. Policy 38, 7476–7486.

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Silalertruksa, T., Gheewala, S.H. (2012) Environmental Sustainability Assessment of Palm Biodiesel Production in Thailand. Energy 43, 306–314.

Silalertruksa, T., Bonnet,S., Gheewala, S. H., 2012. Life Cycle Costing and Externalities of Palm

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oil Biodiesel in Thailand. J. Clean. Prod. 28, 225-232.

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Table 1 Actual blending of biodiesel during 2011-2012

2011 2012 a

b

HSD consumption

c

B100 production

Actual Blending

(MLPD)

(MLPD)

(%)

51.4

1.72

3.35

54.7 b

2.42 c

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a

Year

4.43

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Source: ( DOEB, 2012a, DOEB, 2012b and EPPO 2012). Notice: MLPD stands for million litres per day

17

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Table 2 Parameters considered for carbon stock change calculations Carbon stock change calculations   

(1) ∆CG was set as zero for all land use types considered in this study.



∆Cbiomass = Annual change in carbon stocks in biomass (above-ground + below-ground biomass) (t CO2-eq year-1)

(4) Time period: 25 years.

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T: time period between time of the second stock estimate and the first stock estimate (years)

In (2) and (3) carbon stocks converted from t C year-1 to t CO2-eq year-1 using a factor 3.67

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A  {(DOMin  DOMout '  CF} T

A = area of managed land (ha)

Abandoned cropland: 1,697 t CO2-eq year-1; Grassland: 18,498 t CO2-eq year-1. year-1; Marsh and swamps: 3,139 t CO2-eq year-1.

∆CL = annual decrease in carbon stocks due to biomass loss (t CO2-eq year-1)

∆CDOM = annual change in carbon stocks in dead wood or litter (t CO2-eq year-1)

(2) ∆CL in the East: Abandoned paddy field: 4,133 t CO2-eq year-1; (3) ∆CL in the South: Abandoned paddy field: 16,460 t CO2-eq year-1; Grassland: 24,195 t CO2-eq

∆CG = annual increase in carbon stocks due to biomass growth (t CO2-eq year-1)

2. ΔCDOM =

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1. ∆  =

Values used in this study

Based on information from Silalertruksa and Gheewala (2012), and Siangjaeo et al. (2011), DOMout and DOMin were considered equal to zero for all types of land use considered in this study.

DOMout = dead wood/litter stock at time t1 for managed land (t d.m. ha-1)

Therefore ∆CDOM could be omitted from the carbon stock change calculations.

DOMin = dead wood/litter stock at time t2 for managed land (t d.m. ha-1)

Note: The area of each land use type considered in this study is identified in section 3.2.1.

T = time period between time of the second stock estimate and the first stock estimate (years) CF: carbon fraction of dry matter

(1) ∆CMineral in the East: Abandoned paddy field: -16,072 t CO2-eq year-1;

∆CSoil = annual change in carbon stocks in soil (t CO2-eq year-1)

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3. ∆-  = ∆. − ∆0.1 + ∆2. 0.1

Abandoned cropland: -6,601 t CO2-eq year-1; Grassland: -50,280 t CO2-eq year-1.

∆CMineral = annual change in organic carbon stocks in mineral soil (t CO2-eq year-1)

(2) ∆CMineral in the South: Abandoned paddy field: -81,569 t CO2-eq year-1;

∆LOrganic = annual loss of carbon from drained organic soil (t CO2-eq year-1)

Grassland: -83,581 t CO2-eq year-1; Marsh and swamps: 1,998 t CO2-eq year-1.

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4.  = A MB  Cf  Gef  10-3

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∆CInorganic = annual change in inorganic carbon stocks from soil (t CO2-eq year-1)

Lfire = Amount of CO2 and non-CO2 emissions from open biomass burning (t CO2-eq year-1) A = Area of biomass burnt (ha year-1)

MB = Mass of biomass (dry matter) available for combustion (t d.m. ha-1) Cf = Combustion factor

Gef = Emission factor (kg of air pollutant (CO2-eq) (t d.m.)-1 of burned biomass

(3) LOrganic was not considered in this study as it is rare in Thailand (Silalertruksa and Gheewala, 2012). (4) ∆CInorganic was not considered in this study as not significant. Note: In (1) and (2) carbon stocks converted from t C year-1 to t CO2-eq year-1 using a factor 3.67 (1) MB: Abandoned paddy field: 2.1 t ha-1; Grassland: 5.2 t ha-1; abandoned cropland: 2.1 t ha-1. (2) Cf: Abandoned paddy field, grassland and abandoned cropland: 77%. (3) GHG (non-CO2) emission factors (Gef): abandoned paddy field: 88.36 kg CO2-eq (t d.m.)-1 of burned biomass; grassland: 120 kg CO2-eq (t d.m.)-1 of burned biomass; abandoned cropland: 88.36 kg CO2-eq (t d.m.)-1 of burned biomass. Note: There is no open burning to clear the land considered for marsh and swamps. Also CO2 emissions from open burning of grassland and abandoned land (including crop and paddies) were considered as zero as per recommendations from the IPCC 2006 guidelines.

Source: IPCC (2006) and Akesamatramate et al. (2005) in Annual change in carbon stocks in soils.

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Table 3 Total CPO production supply based on the model of this study New planted

Planted

Harvested

Total FFB

FFB

areaa

area

area

produced

yield

6

CPO

CPO

Total CPO

production

stock

supply

6

(×106 t)

OER

6

(ha)

(ha)

(×10 t)

(t/ha)

%

(×10 t)

2010

30,400

652,800

512,000

8.04

15.69

17

1.37

2011

16,000

667,200

588,800

8.68

14.75

17

2012

22,400

689,600

622,400

11.33

18.19

17

2013

19,200

689,600

652,800

12.13

18.58

17

2014

32,000

721,600

668,800

12.84

19.20

17.5

2015

40,000

761,600

691,200

13.44

19.44

17.5

2016

40,000

801,600

710,400

14.12

19.88

2017

40,000

841,600

742,400

14.96

20.15

2018

32,000

873,600

782,400

15.83

20.23

2019

16,000

905,600

822,400

16.64

20.24

2020

16,000

905,600

862,400

17.45

2021

16,000

905,600

894,400

18.35

0.14

1.50

1.48

0.07

1.54

1.89

0.34

2.23

2.06

0.35

2.42

2.25

0.37

2.62

2.35

0.54

2.89

2.54

0.48

3.02

18

2.69

0.48

3.17

18

2.85

0.36

3.21

18.5

3.07

0.32

3.39

20.25

18.5

3.23

0.16

3.39

20.50

18.5

3.39

0.05

3.44

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Note: a including replanting

(×10 t)

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(ha)

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Year

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Table 4 Total CPO demand based on the model of this study Year

Domestic

Biodiesel

Total STR

CPO for

CPO for

CPO

Total CPO

CPO

consumption

blending

for B100

B100

BHD

export

demand

Surplus

6

6

6

6

6

6

6

(%)

(×10 t)

(×10 t)

(×10 t)

(×10 t)

(×10 t)

(×10 t)

2012

0.81

B5

0.09

0.64

-

0.31

1.57

0.35

2013

0.90

B5

0.14

0.69

-

0.20

1.85

0.37

2014

0.93

B5

0.22

0.70

-

0.20

1.88

0.54

2015

0.96

B7

0.23

0.99

-

0.20

2.21

0.48

2016

0.99

B7

0.24

1.09

-

0.20

2.34

0.48

2017

1.02

B7

0.24

1.12

0.30

0.10

2.71

0.36

2018

1.05

B7

0.28

1.18

0.30

0.10

2.79

0.32

2019

1.08

B9

0.28

1.48

0.30

0.10

3.13

0.16

2020

1.11

B9

0.29

1.55

0.30

0.10

3.24

0.05

2021

1.15

B10

0.31

3.34

0.007

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0.30

0.10

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Note: STR=Stearin

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(×10 t)

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Table 5 Land types and areas for oil palm expansion in the Eastern and Southern regions of Thailand Area in the South (ha) 36,578

Grassland

16,816

21,995

Abandoned cropland

3,772

-

Abandoned paddy field

-

Marsh and swamps

29,772

2,854

61,427

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Total

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Area in the East (ha) 9,184

Types of Land

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Table 6 Estimation of carbon stock change for oil palm expansion in the East Region

∆Cbiomass

∆CMineral

∆Lfire

∆CLU

t CO2-eq year-1

t CO2-eq year-1

t CO2-eq year-1

t CO2-eq year-1

4,133

-16,072

680

-11,296

Grassland

18,498

-50,280

420

-31,278

Abandoned Cropland

1,697

-6,601

Total

24,328

-72,953

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Abandoned paddy field

-4,640

1,379

-47,214

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Table 7 Estimation of carbon stock change for oil palm expansion in the South ∆CMineral

∆Lfire

∆CLU

t CO2-eq year-1

t CO2-eq year-1

t CO2 eq-year-1

t CO2-eq year-1

Abandoned paddy field

16,460

-81,569

2,707

-62,183

Grassland

24,195

-83,581

550

-58,837

3,139

1,998

Total

43,794

-163,152

-

5,137

3,257

-115,882

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Marsh and swamps

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∆Cbiomass Region

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List of Symbols and Abbreviations

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DIT DOEB EPPO FAME FFB GHG HSD IPCC LDD LUC MLPD OAE OER v/v w/v

Meaning Alternative Energy Development Plan Agriculture, Forestry and Other Land Use 100% biodiesel 7% biodiesel with 93% diesel 9% biodiesel with 91% diesel Bio-hydrogenated diesel Crude palm oil Department of Alternative Energy Development and Efficiency Department of Internal Trade Department of Energy Business Energy Policy and Planning Office Fatty acid methyl ester Fresh fruit bunch Greenhouse gas High-speed diesel Intergovernmental Panel on Climate Change Land Development Department Land use change Million litres per day Office of Agricultural Economics Oil extraction rate Volume by volume Weight by volume

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Symbol AEDP AFOLU B100 B7 B9 BHD CPO DEDE