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

Permpool, Napapat; Gheewala, Shabbir H.

doi:10.1016/j.jclepro.2015.05.048

Cited by 49 publications

(21 citation statements)

References 14 publications

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“…For Thailand, 15% of extra land for plantation is required in order to achieve its B10 target [97]. This is also complicated where oil palm requires 24 years till maturation [77].…”

Section: Discussionmentioning

confidence: 99%

Operational Management Implemented in Biofuel Upstream Supply Chain and Downstream International Trading: Current Issues in Southeast Asia

2020

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Bioenergy is one of the alternatives to secure energy demand, despite increasing debate on the sustainability of using bioenergy as a renewable source. As the source is disseminated over a large area and affected by seasonality, the potential benefit is highly dependent on other cost and benefit trade-offs along the supply chain. This review paper aims to assess operational management research methods used in biofuel supply chain planning, including both upstream production and international downstream trading. There have been considerable operational management studies done on upstream processes in biofuel production based on different strategic and tactical decision making of a single or multiple feedstocks, considering economic and environmental factor. However, the environmental consideration is often limited to carbon emission where the other environmental impact such as land-use change, biodiversity loss, irrigation and fertilisation are often being overlooked. Biofuel supply chain and trading at international level remain as an apparent research potential where only limited numbers of global energy models explicitly simulate international bioenergy trade. The leading biofuel producing countries in Southeast Asia: Malaysia, Indonesia and Thailand, are selected as a case study to investigate further on how the supply chain management model could be applied considering the existing biofuel support policies. This study is expected to contribute to the selection of operational management research methods used for decision making under robust policy context, followed by several recommendations.

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“…For Thailand, 15% of extra land for plantation is required in order to achieve its B10 target [97]. This is also complicated where oil palm requires 24 years till maturation [77].…”

Section: Discussionmentioning

confidence: 99%

Operational Management Implemented in Biofuel Upstream Supply Chain and Downstream International Trading: Current Issues in Southeast Asia

2020

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“…This revised plan increased the target for renewable energy from 25% to 30% of the total consumption and adjusted the timeframe to 22 years (2015‐2036). According to the Thai AEDP (2012‐2021; the Thai Government has set the biodiesel consumption target at 7.2 million liters per day while the target of ethanol production has been planned about 6 million liters per day by 2021 . The plan focuses on both supply and demand of biodiesel.…”

Section: Overview Of Developments In the Emergence Of The Biodiesel Imentioning

confidence: 99%

“…According to the Thai AEDP (2012-2021; 21 the Thai Government has set the biodiesel consumption target at 7.2 million liters per day 22 while the target of ethanol production has been planned about 6 million liters per day by 2021. 23 The plan focuses on both supply and demand of biodiesel. On the supply side, the government has targeted an oil palm acreage of 5.5 million rai (880 000 ha) by 2021.…”

Section: Biodiesel Policies In Thailandmentioning

confidence: 99%

Implementing a palm oil‐based biodiesel policy: The case of Thailand

Nupueng

Oosterveer

Mol

2018

Energy Science & Engineering

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Renewable energy promotion is recognized as an important goal in international climate policies in order to reduce CO2‐emissions. Biodiesel can potentially be an important contributor in this respect, especially in Thailand with its large biomass production from oil palm cultivation. Palm oil is the main raw feedstock for biodiesel production. However, biodiesel production is also controversial in many respects, in particular considering its sustainability. This paper assesses the collaboration between different actors in the Thai biodiesel and oil palm networks in organizing biodiesel provision. Through qualitative interviews with key political, economic, and societal actors the structure and the dynamic of the biodiesel and oil palm industry, as well as the relevant policy dynamics, were investigated. We found that the implementation of biodiesel policy was dominated by the need to secure the production of palm oil‐based cooking oil leading to frequent adjustments. Sustainable improvement and environmental considerations hardly played a role in the interactions between the actors involved in the palm oil and biodiesel industries. Government agencies were dominant and steered the biodiesel and the oil palm industries both directly and indirectly via economic and societal actors. Nevertheless, the promotion of biodiesel continues to be the basis of the national renewable energy master plan with its clear target to balance and stabilize the economic, social and environmental issues. As the renewable energy master plan does not fit with the possible feedstock, the main challenges in achieving these sustainable targets are therefore how to maintain a stable and consistent policy, especially concerning balancing the palm oil used for biodiesel production on the one hand and palm oil‐based cooking oil on the other.

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“…However, the rapid expansion of oil palm plantations has also led to deforestation and a series of negative environmental impacts, such as forest estate losses, social costs, alternative revenue losses, reduced biodiversity, and diminished ecological connectivity [3]. In addition, oil palm plantations are a substantial and frequent cause of fires in Indonesia, many palm oil producers take advantage of the conditions to clear vegetation for oil palm plantations using the slash-and-burn method, they often spin out of control and spread into protected forested areas, and these fires emit increasing quantities of greenhouse gases that threaten the global climate and ecosystem [4][5][6]. Therefore, to scientifically manage and supervise this activity and to safeguard forests beneficial for the global climate and ecosystem services, it is necessary to precisely detect and monitor oil palm plantations.…”

Section: Introductionmentioning

confidence: 99%

A New Machine Learning Approach in Detecting the Oil Palm Plantations Using Remote Sensing Data

Qian

et al. 2021

Remote Sensing

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The rapid expansion of oil palm is a major driver of deforestation and other associated damage to the climate and ecosystem in tropical regions, especially Southeast Asia. It is therefore necessary to precisely detect and monitor oil palm plantations to safeguard the ecosystem services and biodiversity of tropical forests. Compared with optical data, which are vulnerable to cloud cover, the Sentinel-1 dual-polarization C-band synthetic aperture radar (SAR) acquires global observations under all weather conditions and times of day and shows good performance for oil palm detection in the humid tropics. However, because accurately distinguishing mature and young oil palm trees by using optical and SAR data is difficult and considering the strong dependence on the input parameter values when detecting oil palm plantations by employing existing classification algorithms, we propose an innovative method to improve the accuracy of classifying the oil palm type (mature or young) and detecting the oil palm planting area in Sumatra by fusing Landsat-8 and Sentinel-1 images. We extract multitemporal spectral characteristics, SAR backscattering values, vegetation indices, and texture features to establish different feature combinations. Then, we use the random forest algorithm based on improved grid search optimization (IGSO-RF) and select optimal feature subsets to establish a classification model and detect oil palm plantations. Based on the IGSO-RF classifier and optimal features, our method improved the oil palm detection accuracy and obtained the best model performance (OA = 96.08% and kappa = 0.9462). Moreover, the contributions of different features to oil palm detection are different; nevertheless, the optimal feature subset performed the best and demonstrated good potential for the detection of oil palm plantations.

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

Cited by 49 publications

References 14 publications

Operational Management Implemented in Biofuel Upstream Supply Chain and Downstream International Trading: Current Issues in Southeast Asia

Operational Management Implemented in Biofuel Upstream Supply Chain and Downstream International Trading: Current Issues in Southeast Asia

Implementing a palm oil‐based biodiesel policy: The case of Thailand

A New Machine Learning Approach in Detecting the Oil Palm Plantations Using Remote Sensing Data

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