Working Paper in Economics and Development Studies

Department of EconomicsPadjadjaran University

Center for Economics and Development Studies,Department of Economics, Padjadjaran UniversityJalan Cimandiri no. 6, Bandung, Indonesia. Phone/Fax: +62-22-4204510http://www.ceds.fe.unpad.ac.id

For more titles on this series, visit:http://econpapers.repec.org/paper/unpwpaper/

The Effect of Forest Fires and Oil Palm Plantations on Green House Gases (GHG) Emissions in Indonesia

Farida Yulistianingrum

Master of Applied Economics, Universitas Padjadjaran

December, 2019

No. 201909

The Effect of Forest Fires and Oil Palm Plantations on Green House Gases

(GHG) Emissions in Indonesia

By FARIDA YULISTIANINGRUM *

Indonesia had recorded a large amount of carbon emissions from forests and peatland fires in last decade. This study therefore, investigates the effect of forest fires and oil palm plantations on GHG (Green-House Gases) emissions in Indonesia using the econometrics approach. The statistical result indicatesthat fire incidences (hotspots) do have a positive significant effect on GHG emissions in Indonesia. This implies that people still use fire as medium for land clearing in the forest. The coefficients of oil palm plantation measurement on GHG emission are positive, implying that land clearing process in forest and peatland areas and converting them into oil palm plantations have increased GHG emissions. To establish a system for sustainable forest management, it will be crucial that the government maintain the enforcement of legal sanctions to every aspect who burning the forests deliberately.

1. INTRODUCTION

The greenhouse gases (GHG) emission worldwide has grown rapidly over the last century. The total global GHG emissions in 2000 was 24.1 giga-tons of CO2 equivalent (GtCO2e) (Ritchie & Roser, 2019) and continue rising up to 50.9 GtCO2e in 2017 (Olivier & Peters, 2018). Moreover, the increasing concentration of GHG emissions in the atmosphere is responsible for the increasing global temperature. Global temperatures have increased by approximately 0.3°C over a decade and are expected to rise further up to 1- 3.5°C by 2100 (Stern, 2006 as cited in Perman et al., 2005). The increasing temperature will significantlybring impact not only for the ecosystem but also the economy. It will increase the frequencyof natural disasters such as drought and sea level rise flooding, and degrade the ecosystems in forest and marine areas (Perman et al., 2005).

Indonesia had recorded to have emitted a large amount of carbon emission from forest and peatland fires in the last decade. These numbers increased in year 2015, roughly about 1,750 million tCO2e to global emissions only from forest fires (World Bank, 2016). GHG emissions in Indonesia are primarily caused by several factors such as land use, land-use change and forestry, representing about 48 percent of the total GHG emissions, followed by energy sectors at approximately 35 percent (WRI, 2017). Moreover, Perman, et al. (2005) explained that agricultural activities, decomposition, and disposal waste can also increase GHG

emissions. Therefore, Indonesia becomes the world`s third largest emitter of GHG and largest contributor of forest-based emissions (WRI, 2017).

Forest and peatland fires are annual disaster which causes several impacts on the health and economic conditions in Indonesia. In the 1997-1998 massive fire events, 527 people died and recently in 2015, the fire and haze event has brought over half a million people suffered health effects and at least nineteen died (Tacconi, 2016). Furthermore, approximately 2.6 million ha of land was burned which equals to 4.5 times the size of the Bali islands and Indonesia lost about 16.1 billion USD in 2015 (approximately 1.9% of the total GDP)(World Bank, 2016).

Oil palm plantations bring two side effects for Indonesia. On the one hand, it brings good economic contribution through significant value added on export. For instance, the value added from gross palm oil exports in 2014 was about USD 8 billion and the entire palm oil production contributes USD 12 billion (World Bank, 2016). However, the expansion of oil palm plantation was reported to lead many environmental disadvantages such as deforestation, reducing biodiversity and changes traditional communities (Gunarso et al, 2013).

Many studies have been conducted to investigate the close link between environment degradation, for example through increased CO2 emissions, and economic growth. There is an evidence about the positive relationship between economic growth to CO2 emission in Indonesia, Malaysia, and Thailand (Islam et al., 2017), Pakistan (Hassan et al., 2015), Brazil, and India (Alam et al., 2016), in China (Xiongling, 2016). In the case of Indonesia, the causal link between economic growth and CO2 emission has been reported by several studies. Shahbaz et al. (2013) found a two-way relationship of GDP and CO2 emission while Alam et al. (2016) described a one-way relationship. Although many studies have been conducted on the relationship between carbon emission and economic development, very few have explored the effect of forest fires on GHG emission especially in forest and peatland areas moreover using econometric analysis approach. Studies on oil palm plantations and forest fires in exploring the relationship with GHG emission was calculated through field estimation and mapping analysis techniques. The result shows the contribution or the amount CO2 emitted from oil palm plantations and forest fires. For further analysis and information, this study willdiscuss the effect of forest fire and oil palm plantations on GHG emissions in Indonesia using econometrics analysis and will focus on GHG emissions in forest and peatland areas.

In Chapter 2, we will discuss more about GHG emission condition in Indonesia and the factors which affect the GHG emissions focused on forest and peatland area. The Chapter 3 will describe the data and methodology used in this study. The Chapter 4 will present the results and discussion with respect to relevant literatures. Finally, the last Chapter will conclude this research and suggest policy implications related to the result discussion.

2. LITERATURE REVIEW

2.1 Forest fires and GHG Emissions

Forest fires have become a serious issue for Indonesia since the 1990s. They have become an annual incidence and more frequent each year (Langner &Siegert, 2009; Putra et al., 2008 in Yulianti, Hayasaka, & Usup, 2012). Globally, forest fires are the source of carbon

emissions from the forest area. Page et al. (2002) described the contribution of forest fires to be approximately 0.81-2.57 GtCO2 from peat and vegetation and it was estimated about 13-40% of the global annual carbon emissions from the burning of fossil in 1997.Another report shows that the contribution of gas distribution for fire emissions in 2015 occurred in Sumatera Kalimantan and Papua region was about 83% in the form of CO2, 16% CO and 1% CH4 (Huijnen, V. et al, 2016). In contrast, a study in China stated that there was no significance increases of fire incidences and carbon emissions due to the spatial and temporal variation of fire regimes (Zhang et al., 2016).

The cause of forest fires has been a controversial issue among researchers. Some claim that it was to be natural cause and others claim to be human-based ignitions. Fanin et al. (2017) explained that tropical rain forests cannot naturally generate fires because of high rainfall rates and humidity. Moreover, it has been studied that in Southeast Asia, the cause of fires ismostly human related activities. In Kalimantan and Sumatera, most of fires are caused by human activities and occur along canals, roads, and at the seacoast (Yulianti, Hayasaka &Usup, 2012). They also found that the most dense fire incidence related to exploitative human activities such as deforestation, slash and burn for clearing land and plantations. During biggest fires in 1997-1998, CIFOR (2001) found that fires were being used in land clearingprocess, land tenure conflicts, resource extraction which further became the causes of fireincidence.

GHG emissions from fires are linked with global climate change through greenhouse effect (Liu, Goodrick & Heilman, 2014).Climate change increases drought and heat stress and indirectly influences forests and forest carbon emissions through wildfires by increasing fires frequency, density, and leading to warmer conditions (Loehman, Reinhardt & Riley, 2014). Therefore, climate change has impact on increasing wildfires in the forest area.

The changes in temperature could also impacts on ecosystems. Perman et al. (2011) mentioned that high temperatures degrade forests and lower the productivity of forests and marine ecosystems. Then, high temperature could evaporate the water content of peatland and swamp forests and make them resilient to wildfires. Peatland drainage and conversion to plantation agriculture has been associated with severe, uncontrolled� peat� fires� that� present�significant�climate,�public�health�and�economic�risks�(Carmenta�et�al.,�2017).�Therefore,� the�government should consider the relationship between GHG emissions and fires to create a policy suitable for these issues.

For economic purposes, people tend to convert forests into plantations or agriculture areas using fire as the cheapest and most effective way (Edwards et al., 2018). People open and utilize the forest to create economic opportunity and grow the local economy. Therefore, growing economy appeals residents and local firms to open more lands and burn more forests.However, Edwards et al. (2018) also explained that people usually do not build fire management systems which are costly and unaffordable which leads to more environment degradation and emissions in the future. Based on these explanations, we can conclude that economic development has relation of which either preserves or worsens the environment,and the government should maximize the protection of forest to repress activity related to fires.

2.2 Oil Palm Plantation and GHG emission

Oil palm plantation has impacts Indonesia in two manners. First, it contributes to the improvement of the economy through increasing export and GDP. It has driven rapid

economic growth in several tropical developing countries such as Malaysia and Indonesia and contributed to the alleviation of rural poverty (Sayer et al., 2012).

Second, oil palm plantation is also identified as the driver of deforestation and land-use change. Indonesia has lost its natural forest cover by up to 839,000 ha as of 2012 since at least 2000 (Margono et al., 2014) and mainly due to deforestation-caused expansion (Austin et al., 2017). Land use for palm oil production increased from 0.1 million ha in 1975 to 5.5 million ha in 2005(Wicke et al., 2011). In Jambi during the year 2001 to 2015, approximately 20.7% of forest was changed into forest plantation and approximately about 27.1% into oil palm plantation (Prasetyo et al., 2016). However, some studies have argued that oil palm plantation has less impact on deforestation. Austin et al. (2017) also estimated that oil palm driven deforestation decreased betweenyear2010 to 2015and contributed approximately to only 14% of national deforestation. A substantial proportion of oil palm plantation mostly occurred in logged forests, shrub and rubber agroforestry and conversion from natural forest, for instance, in West Kalimantan only covered 21% (Tarigan et al., 2015).

Oil palm plantation has been reported by several studies to have contribution in increasing GHG emissions. The amount of emissions from agricultural sector including the oil palm sector were approximately 4.6 to 5.0 GtCO2e per year in 1990-2000 and increased up to 5.3 GtCO2e in 2011 (Tubiello et al., 2014).GHG emissions from oil palm plantation are being released from land clearing activities from natural forest and peatland areas (Fargionne et al., 2008; Gunarso et al., 2013) as well as from the palm oil production process (Zulkifli et al., 2010). Moreover, carbon loss caused by converting natural forest into oil palm plantations could be replaced after producing palm oil for about 75-93 years and it will takelonger time approximately 600 years from peatland areas(Danielsen et al., 2009; Sayer et al., 2012).

The mechanism of GHG emissions from oil palm plantations occur through certain biological processes, such as microbial decomposition of organic carbon stored in plant biomass and soils (Fargionne et al., 2008).Trees produce fuel by absorbing CO2 and transforming it into biomass. When burned as charcoal or bio-fuel, the same amount of CO2is returned to the atmosphere, thereby forming a closed cycle (Chomitz et al., 2007). Biologically, the carbon intake and loss from oil palm plantation would be neutral if there were no additional activities which threaten the environment such as land clearing with fires.

Land clearing processes for oil palm plantation extensively involves burning systems especially by smallholders in Southeast Asia. Not only natural forests but peatland areas are also drained and changed into oil palm plantations mostly in the region of Sumatera and Kalimantan (Gunarso et al, 2013). The burning of peatland for oil palm plantation releases stored carbon as GHG emissions and forms smog (WRI, 2015 as cited in Paterson & Lima, 2018; Fargionne et al., 2008). Moreover, Zulkifli et al. (2010) proved that there is a significant environment impact of oil palm plantation on climate change especially in the use of N-based fertilizers and field machinery (include tractors and transport vehicle) in the production process. Combining fire and significant amount of fertilizer could worsen the environment quality and emit more harmful carbon emission from oil palm plantations.

3. RESEARCH METHODS

3.1 Data

This study employ panel data from 32 different provinces in Indonesia obtained within the years 2001 and 2012. The DKI Jakarta province was excluded from the data set because of

zero forest and oil palm areas. The data were collected from various reports by the Central Bureau of Statistics (BPS), Ministry of National Development Planning/Bappenas, Ministry of Environment and Forestry (MoEF) and World Bank. The description of each variables used in this study are provided in Table 1.

3.1.1 Dependent Variable

This study employs GHG emission as the dependent variable. The GHG emissions variable represents the annual net GHG emissions from human-induced land use and land-use change in forests and peatland from year 2001 to 2012 obtained from the Indonesian National Carbon Accounting System (INCAS) report of 2015. In this document, the total GHG emission has been estimated from the sum of all GHG emissions and removals from Indonesian forests and peatland based on changes in carbon stocks from each carbon pool such as live above-ground biomass, live below-ground biomass, litter, dead wood, mineral soils, and peatland oxidation. The changes in carbon stocks are estimated from the total of changes from 5 carbon pool, as can be shown from the equation below:

ΔCLui =�ΔCAB + ΔCBB +�ΔCDW +�ΔCLI +�ΔCSO

where��ΔC�Lui��=��the�total�carbon�stock;�AB��=��the�emission�from�above��ground��biomass;��BB = the emission from below ground biomass; DW = the emission from deadwood; LI = the emission from litter and SO = the emission from soils. Moreover, emission from peatland decomposition is calculated differently based on IPCC Guidelines of 2006. It is multiplied with the emissions of peatland area and emission factor which is represented in equation below.

ΔC�LU organic=∑(A•EF)

where ΔC�LU��organic��=��total�CO2 emissions from peatland decomposition; A = peatland area (ha); and EF = emission factors.

TABLE 1. DATA DESCRIPTION

Variables Description Source

Dependent Variable GHGemission, is the annual net GHG emissions from human-induced land use and land-use change on

forests and peatland (ton CO2 eq)

Ministry of Environment and Forestry

Independent Variables Hotspots is the hotspots frequency of forest fire detections

GDPagri is the share of GDP from agriculture sector per total GDP (%)

Oil palm area is the oil palm planting area (ha)Regional is the dummy variable for Java and non-Java

BAPPENASIndodapoer, World Bank

BPS

3.1.2 Independent Variable

The variable Hotspots is the hotspots frequency of forest fire detections. This data was acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) Active Fire Detections distributed by NASA FIRMS (https://firms.modaps.eosdis.nasa.gov) and was overlaid with the Indonesian forest area map. According to Langner and Siegert (2009), hotspots are active fire events which are recorded by a satellite system (for instance NOAA

AVHRR, ERS, ENVISAT and TERRA/AQUA). The MODIS hotspots data is considered the most complete and accurate method for detecting active fires.

The variable oil palm area is described as the active planting area for oil palm plantation at the provincial level. This data set was gathered from the Indonesia Statistic of Oil Palm Report arranged by BPS from year 1998 until 2017. In this report, the data source used is primarily generated from the results of processing surveys conducted by the sub-directorate of plantation plant statistics, BPS and secondary data obtained from other publications such as Oil World publications, and the directorate general of plantation, the Ministry of Agriculture. This data set includes palm oil area under smallholders, government estates, and private estates. Data on size of the area and the production of large state and private plantations was obtained from the�results�of�„Survei�Perusahaan�Perkebunan‟�which�is�carried�out�by�complete�enumeration throughout all plantations` administration in Indonesia. BPS officers collect data through direct interviews within the period of survey (quarterly or yearly). Meanwhile, extensive data series of the area and production from smallholders were obtained from the Ministry of Agriculture. In this report, a plantation company refers to the business entity engaged in the cultivation of plantation crops on the land for economic or commercial purposes and which has legal licenses from the authorized agency. This company includes government estates, private estates. However, smallholders are categorized as non-legal entity plantations operated by households.

The variable GDP agriculture used in this study represents the percentage of GDP agriculture to total GDP. The GDP agriculture and total GDP is obtained from World Bank databank in million rupiah (constant, baseline year 2000).

The regional variable is categorized as a dummy variable. It is used to indicate the influence of regional to the dependent variable. This dummy variable (regional) is divided into two values, 0 for `non-Java` and 1 for `Java`. The interpretation of this dummy variable is a value of 0 which would have no role in influencing the dependent variable, while when the dummy takes on a value 1, its coefficient acts to alter the intercept.

3.2 Methodology

This study employed econometrics analysis using panel data regression model. Simple linear regression approach was used to investigate the effect of forest fires and oil palm plantations on GHG emission in Indonesia. In this paper, the equation is modified from the equation in Islam et al. (2017). They used CO2 emissions as dependent variable while energy consumption, GDP, population, poverty and forest area as independent variable. Then, the equation becomes the following:

lnGHGemissionit =�αi�+�β1Hotspotsit +�β2GDPagriit +�β3lnOilpalmareait + β4Regionalit + µit

where the dependent variable, lnGHGemission, is the log of annual net GHG emissions from human-induced land use and land-use change on forests and peatland. This study useshotspots, GDP agriculture, and oil palm area as the independent variables. Moreover, this study employ regional variable as dummy variables. The variable GDPagri is the share of GDP from the agriculture sector from total GDP in province level. Oilpalmarea is the oil palm planting area and Regional is the dummy variable for Java and non-Java. Oil palm area is in logarithmic terms.

4. RESULT AND DISCUSSION

This study employs GHG emissions from forest and peatland area as the dependent variable. GHG emissions comprise three primary greenhouse gases such as carbon dioxide (CO2), methane (CH4) and nitrogen dioxide (NO2) which have a warming effect on the global temperature. According to Indonesia`s First Biennial Update Report submitted to the UNFCCC in 2016, the total GHG emissions in 2012 were estimated at 1,454 MtCO2e. The Ministry of Environment and Forestry performed an estimation of GHG emissions in forest and peatland areas from the year 2001 to 2012 and published a report called INCAS in 2015. This study used those GHG emissions data to analyze its relation to hotspots, oil palm plantation, and GDP. GHG emissions data in the report were collected from various source pools such as above-ground biomass, below-ground biomass, debris wood, peatland oxidation and emissions from fires. However, we have eliminated emissions data from fire in order to reduce multicollinearity on the data. Furthermore, we conducted simple linear regression to estimate the effect of GHG emissions on hotspots, oil palm plantation, and GDP. The results of linear regression are provided in Table 2.

TABLE 2. REGRESSION RESULT

Variable Coefficient Std. ErrLn_oilpalmarea 0.07023196*** 0.0135911

Hotspots 0.00033465*** 0.0000559GDPagri 1.220854* 0.726115regional -1.17282*** 0.3133509

cons 15.354317*** 0.2911418

Note: R2 = 0.35 (N = 371, * p<0.1, *** p<0.01)

*** Significant at the 1 percent level.

** Significant at the 5 percent level.

* Significant at the 10 percent level.

Source: Author`s calculation

4.1 GHG Emissions and Oil Palm Plantation

Table 2 shows that oil palm plantations and GHG emissions have a positive relationship with the significant level at one percent (1%). This implies that increasing the area of oil palm plantation by1% will increase the percentage of GHG emissions by 0.07 percent. This result is in line with other studies which claim that oil palm plantation contributes to GHG emissions (Fargionne et al., 2008; Gunarso et al., 2013; Zulkifli et al., 2010).The mechanism of GHG emissions released from oil palm plantations could be a result from the process of land clearing until harvesting the palm oil. Zulkifli et al. (2010) described how the palm oil companies use N-based fertilizers in weeding process and heavy machine such as tractors which emit CO2 and CO emission while transporting the palm oil seed. While Fargionne et al (2013) explained that fire usage to clear the targeted area for oil palm plantation will contribute on increasing GHG emissions in oil palm plantations. However, this study only capture the increasing amount of emissions between 2001 until 2012, therefore, further research is required on the recent condition of emissions from the expansion of oil palm plantation.

Figure 1 The trend of oil palm area in Indonesia (1998-2017)

Source: composed by author based on BPS data

Economic reasons are the predominant factors of expansion oil palm plantation. People tend to look for economic opportunities to improve their welfare by selling their land or changing their commodities into oil palm plantations. Sayer et al. (2012) explained that oil palm plantations contribute to the economic growth in Southeast Asia especially in reducing poverty in the rural area. The demand for palm oil products keep increasing which provides good incentives to open the factories and clear more land.

Although oil palm plantations frequently appears to improve income, large-scale estates have frequently been associated with negative social impacts on rural communities and indigenous people. Research in the local Malayas in Sibu complex site reported to have human rights abuse during land acquisition for plantation development by companies and revealed several claims of land encroachment inside the tribes` territories (Veloo, van Ranst& Selliah, 2015).Another study found that there are uneven benefits of distribution among stakeholders such as employees, farmers, and landowners (Obidzinski et al, 2012). Therefore, land conflicts might arise because of unbalanced economic advantages in traditional communities.

In Indonesia, there exists a kind of permit for companies to plant and manage limited areas of forest called forest concession. This scheme describes limited right offered for government or private company to engage in limited activities such as cutting trees, reforestation, processing and marketing of forest products for local industry or export, based on the Forestry Ministers decree with specific condition and a maximum time period of 20 years which might be extended(BPS, 2012). This scheme was reported to be the reason behind land conflict at the provincial level. Due to financial problems, companies in which have legal permit cannot manage and leave the land without proper protection. People used this opportunity to claim and utilize the abandoned land for oil palm plantation. However, there is little evidence on how many area of concession have been converted to oil palm plantation. Therefore, the government should investigate companies which cannot continue managing the forest area and terminate the contract to protect the forest from being claimed by people.

Oil palm plantations are often associated with deforestation and other environmental issues. According to Obidzinski et al (2012), oil palm plantations cause deforestation and other

0

2000

4000

6000

8000

10000

12000

14000

Indonesia Sumatera Kalimantan Sulawesi

170000

370000

570000

770000

970000

1170000

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

SUMATERA KALIMANTAN

negative impacts such as soil erosion, and air and water pollution. Moreover, oil palm expansion especially in Sumatera and Kalimantan has expanded on the peatland area because of the increasing demand for palm oil (Gunarso et al, 2013). It is known that Sumatera and Kalimantan have huge forest and peatland areas which are fundamental resources for expanding oil palm plantations. Increasing the size of oil palm plantation leads to declining forest cover. As evident from Figure 2, the forest cover in Sumatera and Kalimantan islands increased significantly from 2003 to 2012.

FIGURE 2. FOREST COVER LOSS IN SUMATERA AND KALIMANTAN (2003-2012)

Source: composed by author based on Bappenas (2019) data

4.2 GHG emissions and Forest Fires

Table 2 indicates that forest fire events (hotspots) have positive effects on GHG emissions in forest and peatland areas with significant level of one percent (1%). This implies that increasing the number of hotspots could rise up GHG emissions in forest and peatland areas.According to Page et al. (2002), the contribution of forest fires is about 0.81-2.57 GtCO2 from peat and vegetation and it was estimated to be approximately 13-40% of the global annual carbon emissions from the burning of fossil fuels in 1997. Another report suggests that the contribution of gas distribution from fire emissions in 2015 in Sumatera, Kalimantan, and Papua regions was approximately 83% in the form of CO2, 16% CO, and 1% CH4 (Huijnen et al, 2016). However, the coefficient of hotspots is rather small compared to other variables used in this study. This result is in line with a study conducted by van der Werf in 2010. He investigated that most carbon emissions from the year 2001 to 2009were from fires in grasslands and savannas (44%) while fires from forest and tropical peat was approximately 18%. This implies that forest fires do have a minor contribution in GHG emissions in the forest and peatland areas.

The fire incidences continue to occur each year and the trend has been represented inFigure.3. Many researchers have investigated the cause of fires in Indonesia. In Southeast Asia, for instance Malaysia and Indonesia, fires in tropical forests mostly result from human activities and are naturally caused by lightning strikes (Hansen et al., 2013). Further research done by Page et al. (2002) suggests that the extensive fire damage in tropical peatlands of Indonesia has accelerated due to forest clearance and drainage which began in 1997. The more activities inside or near the forest areas, for example illegal logging, hunting, clearing or tourism development, would increase the possibility of people to ignite fires.

FIGURE 3. THE NUMBER OF FOREST FIRES (HOTSPOTS) IN INDONESIA (2001-2018)

Source: composed by author based on Bappenas (2019) data

Human activities in the forest and peatland areas are known as the trigger of deforestation and forest cover loss. Forest cover loss is also related to land-use change issue and is considered as the indicator of deforestation. Hansen et al.(2013) defined forest cover loss asdecreasing the certain number of trees because of human activities such as harvesting, deforestation (the conversion of natural forest for other land uses), illegal logging, land clearing procedures using fires and natural causes such as disease or disaster. Gunarso et al. (2013) argue that the combination of unsustainable logging processes followed by the impact of fire is the biggest cause of forest cover loss in Indonesia which leads to the progressive conversion large areas of forest landscape into agroforestry and plantation.

People in villages near the forests mostly use fires as media for clearing the forest or changing the land use for plantations and other usages. Although the government of Indonesia has prohibited and limited the use of fires for land clearing in Law no18/2004, Law no 32/2009 and Ministry of Environment regulation no 10/2010, people continue to use this method considering it is as cheap, effective and efficient. Not only farmers, it was also revealed that fires were also utilized by oil palm and forest plantation companies (Prasetyo etal., 2016). However, Cattau et al. (2016) claim that only a small proportion of escaped fires

0

2000

4000

6000

8000

10000

12000

14000

16000

Kalimantan Tengah Riau Sumatera Selatan

from oil palm plantation and settlements lead to fires in Kalimantan and mostly fires in non-forest area. Therefore, the government should accelerate the monitoring and enforcement system in the forest areas which has high record of fires to combat this issue. This kind of programs could protect the sustainability of forest and prevent it from disasters in the future.

Forest areas used for logwood commodities have higher tendency of fire intact. By assessing the logging activity through Landsat images during the period of 1997 and 2000, Page et al. (2002) found that logging activities had made the remaining forest areas more susceptible to fire and could results in more carbon emissions through decomposition in the peatland. The remaining grass and bushes of harvested forests could easily ignite by accidental fires from cigarettes or electrical machinery. Therefore, the government should make a policy which require company whether smallholders or private companies to engage in sustainable logging or harvesting procedures. By implementing this kind of actions, GHG emissions from plantations sites whether in forest or non-forest area could be reduced. A study conducted by Griscom et al. (2019) claimed that reduced-impact logging such as clean harvesting and long-line cable winching could reduce emissions by 33% which is on average approximately 64.9 MgCO2per ha harvested. Therefore, a clean and monitored process of harvesting and logging could prevent forest fires and support economic growth while preserving the environment.

In Graph 2, we can see the peak of fire incidents in five provinces (Riau, South Sumatera, Central Kalimantan, West Kalimantan, and Papua) which occurred in 2002, 2006, 2009 and 2015. Some researchers explained the reason for the sudden increasing number of hotspots was mostly by El-Nino, a climate pattern linked to the warming waters in the central and eastern areas of the equatorial Pacific Ocean (Tacconi, 2003; Harrison et al., 2009). El-Ninotriggers the extension of dry season in Indonesia which increases the likelihood of wildfires(Cahyono, Fearns, & McAtee, 2013). This implies that fires not only affect the GHG emissions which also affects climate but also climate change in turn influences the number of forest fires.

Hotspots shown in Graph 2 depict a sudden decrease in 2003, 2007, 2010, and 2016 in those five provinces. The government introduced certain policies related to forest fire in these periods such as Forest Moratorium policy in 2011, andPeatland Restoration Agency in 2015. Moratorium�Policy�is�described�in�the�regulation�called�Presidential�Instruction�“Inpres”�No.�10/2011 which aims to suspend the granting of new concession licenses for logging and conversion of forests and peatlands for two years from the date of enactment, with the suspension allowing better planning of forest governance through necessary coordination processes, data collection and, potentially, new regulations (Murdiyarso et al., 2011). A study conducted by WRI (2017) explained the impact on Moratorium Policy to the CO2 emissions and estimated that this policy could avoid emissions by about 0.2 GtCO2e in 2030 including prohibition of clearing and conversion of primary forest and peatland areas. However, we can see on Graph 1, oil palm plantation keep increasing and expanding after the implementation of this regulation. This can be due to the lack of a proper monitoring system and corruption at the provincial level, makes situations complicated and worse.

Furthermore, in 2015, President Joko Widodo established PRA as the organization which coordinates the management of forest fires prevention and restoration of peatland. The government also mobilized local polices, armies and other local staffs from BNPB in order to investigate the source of fires and help local people restore the environment. This strategy succeed in controlling fires as we can see on the Graph 1 that number of fires drastically decreased in 2016. However, hotspots surprisingly are going up again in 2018. This might

bedue to inefficient monitoring systems and resources for controlling and preventing the fires which affect on spreading the fires again in the forest and peatland area.

This is in line with Erbaugh&Nurrochmat (2019) who highlighted a significant increase in the amount of Indonesian forest-related policies from 1999 to 2016 and focused primarily on encouraging forest protection and redefining the structure and funding for forest-related organizations to combat fires.

4.3 GHG emissions and GDP Agriculture

The GDP share from agriculture has positive and significant effects on GHG emissions in forest and peatland areas in significant level of 10%. This implies that increasing the share of GDP agriculture to total GDP will increase the amount of GHG emissions by about 2.91 ton CO2eq. Several studies have reported that Indonesia displays strong relationship between GDP and CO2 emissions (Shahbaz et al., 2013; Alamet al., 2016). According to BPS, GDP agriculture comprises of GDP from food crops, estate crops, livestock and its products, forestry and fisheries. The estate crop commodities are the mainstay of national income and�Indonesia‟s�foreign�exchange�which�can�be�seen�from�the�export�value of the estate crop commodities in 2015, total export of the estate crops was 23.933 billion USD (Directorate General of Estate Crops, 2016).The contribution of estate crops sub sector to the national economy tends to increase from year to year. However, it is hard to define which commodities have impact on increasing GHG emissions in forest and peatland area. Based on the previous discussion, increasing production and areal of oil palm plantations which one of the most essential estate crop commodities would increase GDP agriculture. Consequently, it would lead to increase in the GHG emissions.

Based on the results shown in Table 2, the regional dummy variables indicate that the Java islands have a significantly negative effect of GHG emissions in forest and peatland area. This implies that the contribution of GHG emissions other islands such as Kalimantan, Sumatera, Papua, Maluku and Nusa Tenggara are higher compared to the Java islands. This is because the total area of oil palm plantation in Java islands is relatively smaller and only available in two province, East Java and Banten (see Appendix).

5. CONCLUSION AND POLICY IMPLICATION

This study aimed to determine the effect of forest fires and oil palm plantations on GHG emissions in Indonesia. The statistical result indicates that fire incidents (hotspots) have a positive significant effect on GHG emissions in Indonesia. This study also finds significant effect of oil palm plantation on GHG emission. Converting and land clearing processes for oil palm plantations increase GHG emissions. People tend to use fires and toxic fertilizers in the production and planting steps not only for palm oil but also other agricultural commodities which contributes more to GHG emissions.

Whether oil palm plantations have significant contribution to the GDP, the government should estimate the cost and benefit of expansion oil palm plantation especially in the forest and peatland areas. Regarding fire usage during land clearing process, the government should continuously monitor and coordinate with the local community or village representatives to prevent fire disasters. To sustain the forest, it is crucial that the government maintain the enforcement of legal forces to every aspect who burning the forests deliberately.

This study focused on GHG emissions from the year 2001 until 2012. This range of data could not capture and discuss the current situation of forest fires and GHG emissions in forest and peatland areas. Further studies are required exploring current data of GHG emissions not only from the forestry sector but also include from other sectors such as energy and agriculture sector. Besides oil palm plantation, other type of land-use changes such as mining, building, and wood-based plantations should be included for further analysis.

REFERENCES

Alam, M.M., Murad, M.W., Noman, A.H.M., & Ozturk, I. 2016. Relationships among carbon emissions, economic growth, energy consumption and population growth: Testing environmental Kuznets curve hypothesis for Brazil, China, India and Indonesia. Ecological Indicators, 70, 477-479.

Austin, K.G., Mosnier, A., Pirker, J., McCallum, I., Fritz, S., & Kasibhatla, P.S. 2017. Shifting patterns of oil palm driven deforestation in Indonesia and implications for zero-deforestation commitments. Land Use Policy, 69, 41-48.

Bappenas. 2019. [Source of forest fire and forest cover loss]. Unpublished raw data.BPS. 1998-2018. Indonesian oil palm statistics (In Indonesia). Jakarta: BPS. Retrieved from https://www.bps.go.idBrown S, Sathaye J, &Cannell MGR.1996. Management of forest for mitigation of green-housegas emissions: In climate

change 1995 Impacts, Adaptation and mitigation of climate change. UK: Cambridge University Press, p. 773–797Busch, J., Gallon, K.F., Engelmann, J., Wright, M., Austin, K. G., Stolle, F., Turubanova, S., Potapov, P. V., Margono, B.,

Hansen M. C., & Baccini, A. 2015. Reduction in emissions from deforestation�from�Indonesia‟s�moratorium�on�new�oil�palm, timber, and logging concessions. PNAS, 112(5), 1328-1333

Cahyono, B.E., Fearns, P., & McAtee, B. 2013. Application of MODIS data to a decadal study of fire hotspots and climate relationships over Riau province Indonesia. Asian Journal of Applied Sciences, 1 (1), 31-37

Carlson, K.M., Curran, L.M., Ratnasari, D., Pittman A.M., Soares-Filho, B.S., Asner, G.P., Trigg, S.N., Gaveau, D.A.,Lawrence, D & Rodrigues, H.O. 2012. Committed carbon emission, deforestation, and community land conversion from oil palm plantation expansion in West Kalimantan, Indonesia. PNAS, 109(19), 7559-7564

Carmenta, R., Zabala, A., Daeli, W., & Phelps, J. 2017. Perceptions across scales of governance and the Indonesia peatland fires. Global Environmental Change, 46, 50-59

Chomitz, K.M., Buys, P., De Luca, G., Thomas, T.S., & Wertz-Kanounnikoff, S. 2007. At Loggerheads? Agricultural expansion, poverty reduction, and environmentin the tropical forests. World Bank, Retrieved from http://documents.worldbank.org/curated/en/223221468320336327/pdf/367890Loggerheads0Report.pdf

CIFOR. 2011. The underlying causes and impacts of fires in Southeast Asia. Jakarta: Center for International Forest Research

Cochrane M.A., &Ryan K.C. 2009. Fire and fire ecology: Concepts and principles. In: Tropical Fire Ecology. Springer Praxis Books. Berlin: Springer

Danielsen, F., Beukema, H., Burgess, N.D., Parish, F., Bruhl, C.A., Donald, P.F., Murdiyarso, D., Phalan, B., Reijnders, L., Struebig, M., & Fitzherbert, E.B. 2009. Biofuel plantations on forested lands: double jeopardy for biodiversity and climate. Conservation Biology, 23, 348–358

Edwards, R.B., Falcon, W.P., Higgins, M.M., & Naylor, R.L. 2018.�Causes�of�Indonesia‟s�forest�fires.�(Stanford�University�Center on Food Security and the Environment. Working Paper). Retrieved from: https://static1.squarespace.com/static/57d5edcf197aea51693538dc/t/5bb2264953450ab8c895e2dc/1538401871026/eard_1809-merged.pdf

Erbaugh, J.T., & Nurrochmat, D.R. 2019. Paradigm shift and business as ususal through policy layering: Forest-related policy change in Indonesia (1999-2016). Land Use Policy, 86, 136-146

Fanin, T., &Van der Werf, G.R. 2017. Precipitation-fire linkages in Indonesia (1997-2015). Biogeosciences, 14, 3995-4008Fargione, J., Hill, J., Tilman, D., Polasky, S., & Hawthorne, P. 2008. Land clearing and the biofuel carbon debt. Science,

319, 1235–1238.Gunarso, P., Hartoyo, M.E, Agus, F & Kileen, T.J. 2013. Oil palm and land use change in Indonesia, Malaysia, and Papua

New Guinea. RSPO. (Reports from The Technical Panel of 2nd GHG working group of Roundtable on Susitainable Palm oil). Retrieved from: https://www.tropenbos.org/file.php/1343/4_oil_palm_and_land_use_change_gunarso_et_al.pdf

Griscom, B.W., Ellis, P.W., Burivalova, Z., Halperin, J., Marthinus, D., Runting, R.K., Ruslandi, Shoch, D., & Putz, F.E. 2019. Reduce-impact logging in Borneo to minimize carbon emissions and impacts on sensitive habitats while maintaining timber yields. Forest Ecology Management, 438, 176-185

Hansen, M.C., Potapov, P.V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., Thau, D., Stehman, S. V., Goetz, S. J., Loveland, T.R., Kommareddy, A., Egorov, A., Chini, L., Justice, C.O., & Townshend, J.R.G. 2013. High-Resolution global maps of 21st-Century forest cover change. Science, 342, 850–53

Harrison, M.E., Page, S.E., & Limin, S.H. 2009. The global impact of Indonesian forest fires. IOB, 25 (3), 156-163Hassan, S.A, Zaman, K., & Gul, S. 2015. The relationship between growth-inequality-poverty triangle and environmental

degradation: Unveiling the reality. Arab Economics and Business Journal, 10, 57-71Huijnen V., Wooster, M.J., Kaiser, J.W., Gaveau, D.L.A., Flemming, J., Parrington, M., Inness, A., Murdiyaso, D., Main,

B., & VanWeele, M. 2016. Fire carbon emissions over maritime Southeast Asia in 2015 largest since 1997. Scientific Reports, 6, 26886.

Islam, R., Ghani, A.B.A., and Mahyudin, E. 2017. Carbon dioxide emission, energy consumption, economic growth, population, poverty and forest area: Evidence from panel data analysis. International Journal of Energy Economics and Policy, 7(4), 99-106.

Langner, S., & Siegert, F. 2009. Spatio-temporal fire occurrence in Borneo over period of 10 years. Global Change Biology, 15, 48-62.

Langner, S., Miettinen, J., & Siegert, F. 2007. Land cover change 2002-2005 in Borneo and the role of fire derived from MODIS imagery. Global Change Biology, 13, 2329-2340.

Loehman, R.A., Reinhardt, E., & Riley, K.L. (2014). Wildland fire emissions, carbon and climate: Seeing the forest and the trees – A cross-scale assessment of wildfire and carbon dynamics in fire-.prone, forested ecosystems. Forest Ecology and Management, 317, 9-19

Liu, Y., Goodrick, S., & Heilman, W. 2014. Wildland fire emissions, carbon, and climate: Wildfire-climate interactions. Forest Ecology and Management, 317, 80-96.

Directorate General of Estate Crops. 2016. Tree crop estate statistics of Indonesia 2015-2017. Jakarta: Ministry of Agriculture. Retrieved from: http://ditjenbun.pertanian.go.id/tinymcpuk/gambar/file/statistik/2017/Kelapa-Sawit-2015-2017.pdf

Ministry of Environment and Forestry/MoEF. 2015. National forest reference emission level for deforestation and forest degradation: in the context of decision 1/CP.16 para 70 UNFCCC (Encourages developing country parties to contribute to mitigation actions in the forest sectors). Jakarta: Ministry of Environment and Forestry

Murdiyarso, D., Dewi, S., Lawrence, D., & Seymour, F. 2011.�Indonesia‟s� forest�moratorium:�A�stepping�stone� to�better�forest governance? Bogor: Center for International Forestry Research

Obidzinski, K., Andriani, R., Komarudin, H., & Andrianto, A.. 2012. Environmental and social impacts of oil palm plantations and their implications for biofuel production in Indonesia. Ecology and Society,17(1), 25.

Olivier, J.G.J., and Peters, J.A.H.W. 2018. Trends in global CO2 and total greenhouse gas emissions: 2018 report. PBL Netherlands Environmental Assessment Agency. Retrieved from: https://www.pbl.nl/sites/default/files/cms/publicaties/pbl-2018-trends-in-global-co2-and-total-greenhouse-gas-emissons-2018-report_3125.pdf

Page, S.E., Siegert, F., Rieley, J.O., Boehm, H.D.V., Jaya, A., & Limin, S. 2002. The amount of carbon released from peat and forest fires in Indonesia during 1997. Nature, 420, 61-65.

Paterson, R.R.M.,& Lima N. 2018. Climate change affecting oil palm agronomy, and oil palm cultivation increasing climate change, requires amelioration. Ecology and Evolution, 8 (1), 452–461.

Perman, R., Ma, Y., Common, M., Maddison, D., & McGilvray, J. 2011. Natural Resource and Environmental Economics. 4th ed. UK: Pearson Education

Prasetyo, L.B., Dharmawan, A.H., Nasdian, F.T., & Ramdhoni, S. 2016. Historical forest fire occurence analysis in Jambi province during period of 2000 – 2015: Its distribution and land cover trajectories. Procedia Environmental Sciences, 33, 450-459.

Ritchie, H and Roser, M. 2019. CO2 and other Greenhouse Gas Emissions. Published online at OurWorldInData.org. Retrieved from:https://ourworldindata.org/co2-and-other-greenhouse-gas-emissions

Sayer, J., Ghazoul, J., Nelson, P., & Boedhihartono, A.K. 2012. Oil palm expansion transforms tropical landscapes and livelihoods. Global Food Security, 1, 114-119.

Shahbaz, M., Hye, Q.M.A., Tiwari, A.K., & Leitao, N.C. (2013). Economic growth, energy consumption, financial development, international trade and CO2 emissions in Indonesia. Renewable and Sustainable Energy Reviews, 25, 109-121.

Smith P., Bustamante, M., Ahammad, H., Clark, H., Dong, H., Elsiddig, E.A., Haberl, H., Harper, R., House, J., Jafari, M., Masera, O.,Mbow, C., Ravindranath,N.H., Rice,C.W., Abad,C.R., Romanovskaya, A., Sperling, F., & Tubiello, F.(2014). Agriculture, forestry and other land use (AFOLU). In: Climate Change 2014: Mitigation of Climate Change. Contribution ofWorking Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press

Tacconi, L. 2003. Fires in Indonesia: Causes, costs and policy implications. CIFOR. Bogor. Retrievedfrom:https://www.researchgate.net/publication/230676882_Fires_in_Indonesia_Causes_Costs_and_Policies

Tacconi, L. 2016. Preventing fires and haze in Southeast Asia. Nature Climate Change, 6, 640-643.Tarigan,S.D., Sunarti, &Widyalyza, S. 2015. Expansion of oil palm plantations and forest cover changes in Bungo and

Merangin Districts, Jambi Province, Indonesia. Procedia Environmental Sciences, 24, 199–205.Toochi EC. 2018. Carbon sequestration: how much can forestry sequester CO2? Forestry Research and Engineer

International Journal, 2(3), 148�150.Tubiello, F.N., Salvatire, M., Golec, R.D.C., Ferrara, A., Rossi, S., Biancalani, R., Federici, S., Jacobs, H., & Flammini, A.

2014. Agriculture, forestry, and other land use emissions by sources and removals by sinks 1990-2011 analysis. ESS

Working Paper. No.2. FAOStat.Van der Werf, G.R., Randerson, J.T., Giglio, L., Collatz, G.J., Mu, M., Kasibhatla, P.S., Morton, D.C., DeFries, R.S., Jin,

Y., & Van Leeuwen, T.T. 2010. Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009), Atmospheric Chemistry and Physics, 10, 11707-11735.

Veloo, R., van Ranst, E., & Selliah, P. 2015. Peat characteristics and its impact on Oil Palm yield. NJAS-Wagenigen Journal of Life Sciences, 72-73, 33-40

Welch,B., Gauci, V., & Sayer, E.J. 2019. Tree stem bases are sources of CH4 and N2O in a tropical forest on upland soil during the dry to wet season transition. Global Change Biology, 25 (1), 361-372.

Wicke, B., Sikkema R., Dornburg, V., & Faaij, A. 2011. Exploring land use changes and the role of palm oil production in Indonesia and Malaysia. Land Use Policy, 193-206.

World Bank. 2016. The cost of fire: An economic analysis of Indonesia`s 2015 fire crisis. Jakarta. World Bank Retrieved from: http://pubdocs.worldbank.org/en/643781465442350600/Indonesia-forest-fire-notes.pdf

WRI. 2017. How can Indonesia Achieve Its Climate Change Mitigation Goal? An Analysis of Potential Emissions Reductions from Energy and Land-Use Policies. Retrieved from: https://wri-indonesia.org/sites/default/WRI%20Layout%20Paper%20OCN%20v7.pdf

Xiongling, T.U. 2016. The relationship between carbon dioxide emission intensity and economic growth in China* cointegration, linier and non-linear Granger causality. Journal of Resources and Ecology, 7(2), 122-129.

Yulianti, N., Haysaka, H., and Usup, A. 2012. Recent forest and peat fire trends in Indonesia: The latest decade by MODIS hotspots data. Global Environmental Research, 16, 105-116.

Zulkifli, H., Halimah, M., Chan, K.W., Choo, Y.M., &MohdBasri, W. 2010. Life cycle assessment for oil palm fresh fruit bunch production from continued land use for oil palm planted on mineral soil. Journal of Oil Palm Research, 22, 887-894.

Zhang, Y., Qin, D., Yuan, W., & Jia, B. 2016. Historical�trends�of�forest�firesand�carbon�emissions�in�China�from1988�to�2012. Journal Geophysical Research of Biogeosciences, 121, 2506 – 2517.