Global Oil Supply Research Articles

Complex network approach for the structural optimization of global crude oil trade system

Abstract It is essential to reveal the optimal structure of global crude oil supply and demand, which has become one of the most important factors affecting every country’s energy strategy and economic development. However, the existing crude oil supply and demand structure does not function well. This paper proposes a distributed bipartite network to model crude oil trade. The optimal network structure, which has the minimal total trade cost is obtained by Simulated Annealing Algorithm. The presented optimization model encompasses the framework of complex network theory and crude oil trading issues, providing a good solution for the crude oil trade system. Comparing with the pre-optimized trading network, the proposed model can effectively reduce trade cost. The Robustness Indicator is proposed to reveal that the major oil-exporting countries choose their partners more wisely and the trade relations are steadier. In the optimal distributed network, both the major oil-exporting countries and major oil-importing countries play important roles in distributing crude oil among the trading countries. Overall, the proposed model offers fresh insights for structural reconstruction of crude oil supply and demand network centered on the efficient usage of crude oil and keeping the international oil trade running smoothly.

Simulations of US-Iran War and Its Impact on Global Oil Price Behavior

We perform simulations to assess the impact of a war between the US and Iran on global oil price behavior. To do so, we evaluate different levels of war intensity and oil price behavior from a multidimensional perspective. In this context, we simulate various scenarios using a simulator which is based on a complex algorithm and multidimensional coordinate spaces. This new simulator is the “War Oil Crisis Simulator (WOC-Simulator). The WOC-Simulator provides policymakers and researchers with a new, simple analytical tool to study the impact of war on oil prices. We apply the simulator to different war scenarios between the US and Iran between 1980 and 2025. The two countries have been geopolitical adversaries since 1979, when an Islamic revolution toppled a pro-Western monarchy. The US remains the world’s only global superpower and Iran is a major oil exporter with significant regional geopolitical influence. Persistent conflict between the two countries in the Middle East, a vital oil-producing region, may disrupt smooth flow of global oil supplies and thus destabilize global oil prices.

Energy, Environment, and Social Development: The Role of R&D in Energy Sustainability - Global Oil and Gas Supply Security and Future Energy Mix

President's column A key component of sustainability is human lifestyle—meeting not just the basics, but for all people to have the opportunity to grow, develop, and prosper. Unquestionably, access to energy is a key component of achieving this goal. Having an adequate, reliable, affordable, environmentally-cleaner and uninterrupted supply of energy is crucial. Despite the calls to immediately cease using fossil fuels, hydrocarbon resources are essential to support the global economy. We cannot achieve a sustainable world in the long term without access to oil and gas. Currently, more than 50% of world energy demand is met by oil and gas. The difficult and yet-to-be-answered questions in the energy industry are the timing of oil and gas depletion and the energy mix afterward. Will oil remain as the primary source of energy at the end of this century, especially in the transportation sector which currently consumes from 75 to 80% of the oil produced? Will gas remain as a primary source of energy for power generation and petrochemicals by the end of this century? Even with renewable energy growing by 400% or more, when will there be enough of these sources to replace oil and gas? Will they be practical for transportation? No one disagrees that oil and gas are depletable energy sources, and that we must find other sources of energy to replace them if mankind’s lifestyle on Earth is to be maintained or improved for hundreds, or I may say, thousands of years to come. However, knowing precisely when this will happen is quite challenging. The oil and gas industry long ago embraced the challenge of finding and producing enough resources to meet growing world demand. Replacing what is produced each year isn’t enough; as demand grows, production capacity must grow, which means discovering more resources. We’ve met that challenge. How? By making enormous investments in research and development (R&D). There is absolutely no doubt that the last few decades’ R&D efforts have reduced uncertainties on the exploration side and have increased recovery efficiency. Thanks to newly developed technologies, fields that were not economically feasible before are now being developed. We’ve learned how to economically and safely produce tight and unconventional resources, and those in hostile environments. All of this has resulted in significant reserves addition and recovery increases.

A systemic approach for disruption risk assessment in oil and gas supply chains

Twenty-first century systems are characterised by rapid changes and constantly evolving dynamics. Therefore, supply chains have become more globalised and complex than ever before. Global supply chains are often accompanied by serious threats and significant additional risks to industries that rely heavily on them. The oil and gas industry encounter significant supply chain risks throughout all stages. The objective of this paper is to provide a holistic complex system governance (CSG) perspective to investigate disruption risks in oil and gas supply chains. As a case study, the piracy problem in Africa is used to demonstrate the efficacy and extensibility of the CSG perspective to a wider array of potential supply chain disruptions. Unlike ready-made solutions or 'off-the-shelf' strategies that may actually undermine the establishment of a resilient global oil and gas supply chain, this paper examines associated risks as a complex system, or a system of systems problem.

ЭКСПОРТ НЕФТИ ИЗ РОССИИ НА МИРОВЫЕ ЭНЕРГЕТИЧЕСКИЕ РЫНКИ

The article analyzes the stable trends in the development of export supplies of oil from Russia. The laws governing the functioning of the oil industry in Russia and the transformation of the global oil supply system are investigated. The structure of directions and methods of supplying oil from Russia to the countries of Europe and Asia-Pacific regions is analyzed.

Permian Pulse: Using Satellite Imagery Analytics To Track the World’s Busiest Oil Play

A trip on Highway 285 between Fort Stockton, Texas, and Carlsbad, New Mexico, is both fascinating and horrifying for the average commuter in the US desert Southwest. The 140-mile stretch of two-lane road can take hours to traverse on a given day as trucks hauling crude oil, sand, water, chemicals, and petroleum equipment overload the battered, sun-fried pavement. The mostly flat, dusty landscape is populated by drilling rigs, workover rigs, and gas flares as far as the eye can see. Even on the highway’s best day, most traffic laws are ignored as oilfield workers in pickup trucks race from site to site. The industrial chaos along the corridor serves as a snapshot of the now multiyear industry boom in the Delaware Basin and greater, 75,000-sq-mile Permian Basin. Keeping track of it all has become a massive challenge for operators, service firms, and midstream companies that make the basin move. They work in an environment that is changing daily, and they can’t afford to be caught by surprise when hydraulically fracturing a well, building infrastructure, delivering equipment to a remote area, or prospecting for new business. An emerging solution: an intelligent, continually updated view from above—or satellite imagery analytics. Companies such as Sourcewater, Planet, and West-wood Global Energy Group are stepping up to monitor the world’s busiest oil play by leveraging relatively inexpensive satellite technology and machine learning. Application of satellite imagery in the oil and gas industry is nothing new. It has been used by companies to monitor remote facilities. Market observers have used the technology to assess global oil supplies by tracking tanker traffic and storage levels. The World Bank has used it to estimate emissions from the flaring of natural gas and oil output by the Islamic State. The real breakthrough is in merging this capability with artificial intelligence and advanced analytics to aid planning for development, production, and logistics while providing competitor intelligence and market research. Development is still in the early stages as companies refine their models to produce the most reliable information possible, and products are just now being rolled out to clients. Finding Water in the Desert An early entrant in the satellite imagery analytics space, Sourcewater’s primary objective is to serve as an online data analytics platform and marketplace for oilfield water sourcing, recycling, and disposal. Founded in 2014 as part of MIT’s Energy Ventures program, Sourcewater “is really about providing oilfield water market intelligence” to its clients, which often are operators planning their completions and production work and logistics or midstream water companies determining where to add new capacity, explained Josh Adler, Sourcewater chief executive officer. Relatively new to the industry himself, Adler’s career path includes founding one of the Internet’s first match-making sites and serving as chief speechwriter to former US Treasury Secretary Paul O’Neill.

Evaluating the Impact Of Sustainability and Pipeline Quality on Global Crude Oil Supply Chain - Part 3

Evaluating the Impact Of Sustainability and Pipeline Quality on Global Crude Oil Supply Chain - Part 3

Evaluating the Impact Of Sustainability and Pipeline Quality on Global Crude Oil Supply Chain - Part 1

United states is one of the largest crude oil producer in the world but the consumption rate is higher than production hence united states imports oil from varies part of world depend on different criteria. The objective of this dissertation is to evaluate the impact of pipeline quality and facility sustainability on crude oil supply chain cost for Russia and Colombia that gave idea about when and where we have to invest to satisfy United states oil requirement.

Evaluating the Impact Of Sustainability and Pipeline Quality on Global Crude Oil Supply Chain - Part 2

Evaluating the Impact Of Sustainability and Pipeline Quality on Global Crude Oil Supply Chain - Part 2

A firm-level analysis of the upstream-downstream dichotomy in the oil-stock nexus

In this paper, we query whether the stock prices of nonintegrated firms in the upstream and downstream sectors of the global oil supply chain respond symmetrically to changes in oil prices. This inquiry relates to the “homogenous expectation” assumption among investors and fund managers pertaining to the returns and variances of assets of specialized firms operating in upstream and downstream sectors of the supply chain. Motivated by the Arbitrage Pricing Theory, we formulate a Panel Autoregressive Distributed Lag (PARDL) model, which explains the possible macroeconomic factors in the oil-stock nexus as well as any inherent persistence and heterogeneity effects due to large cross-sections and time. In accordance with the Shin, Yu, and Greenwood-Nimmo (2014) approach, a Nonlinear Panel ARDL model is also formulated to test for possible asymmetric responses of the nonintegrated oil firms to positive and negative changes in the oil price. Our findings indicate that the stock prices of upstream and downstream firms move in contrasting directions in response to changes in the benchmark crude oil prices in the long-run. Specifically, we show that the stock prices of upstream sector firms increased in response to an increase in oil prices, while the reverse holds for the stock prices of downstream firms. In the short run, returns on the stock of firms in both sectors increase following an increase in oil prices; however, downstream firms' stock returns decreased in response to negative oil price shocks. The findings further show that both sectors respond differently to episodic changes in market conditions that emanated from the global financial crisis. However, upstream firms show a stronger response to changing market conditions than their downstream counterparts.

Oil supply shocks and the U.S. economy: An estimated DSGE model

We develop and use a medium-sized DSGE model of the U.S. economy to evaluate how U.S. real GDP responds to oil price movements that originate from global oil supply shocks. The core of the model is a standard macroeconomic DSGE framework that includes nominal and real frictions. The model includes oil as an input in multiple domestic sectors (consumption, intermediate goods, and transportation services). We include a domestic oil production sector for the United States to reflect the recent development in shale oil technology. The model also captures international trade in goods and oil. The model parameters are set through a combination of calibration and Bayesian estimation using quarterly data for 1991 through 2015. Baseline estimation of the model finds the elasticity of U.S. real GDP with respect to an oil price shock of − 0.015, which is among the less elastic estimates in the literature. Using the model to conduct counterfactual analysis, we find that decreasing steady state U.S. oil consumption substantially reduces the response of real GDP to oil prices. Increasing U.S. domestic oil production only modestly reduces the response of real GDP to oil prices.

Petroleum Distribution Characteristics of the Americas and the Exploration Prospect Analysis

AbstractThe world's present demand for oil and gas is still in a rapid growth period, and traditional oil and gas resources account for more than 60% of the global oil and gas supply. The Americas is the world's second largest production and consumption center of liquid fuel, and is also the world's largest natural gas producer. In 2016, the Americas had 85.3 billion tons of proven oil reserves and 18.7 trillion m3 of proven natural gas reserves, which account for 35.4% and 10.0% of world's total reserves, respectively. It produced 1267.1 Mt of oil and 1125.4 billion m3 of natural gas, which account for 28.9% and 31.7% of the world's total production, respectively. The crude oil and natural gas reserves are mainly distributed in the U.S., Canada and Venezuela. The U.S. is the earliest and most successful country in shale gas exploration and development, and its shale gas is concentrated in the southern, central and eastern U.S., including the Marcellcus shale, Barnett shale, EagleFord shale, Bakken shale, Fayettevis shale, Haynsvill shale, Woodford shale and Monterey/Santos shale. The potential oil and gas resources in the Americas are mainly concentrated in the anticline and stratigraphic traps in the Middle‐Upper Jurassic slope deposition of the North Slope Basin, the Paleozoic Madsion group dolomite and limestone in the Williston Basin, dominant stratigraphic traps and few structural traps in the Western Canada Sedimentary Basin, the Eocene structural‐stratigraphic hydrocarbon combination, structural‐unconformity traps and structural hydrocarbon combination, and the Upper Miocene stratigraphic‐structural hydrocarbon combination in the Maracaibo Basin of Venezuela, the stratigraphic‐structural traps and fault horst, tilting faulted blocks and anticlines related to subsalt structure and basement activity in the Campos Basin, the subsalt central low‐uplift belt and supra‐salt central low‐uplift belt in the Santos Basin of Brazil, and the structural‐stratigraphic traps in the Neuquen Basin of Argentina. In addition, the breakthrough of seismic subsalt imaging technology makes the subsalt deepwater sea area of eastern Barzil an important oil and gas potential area.

Which determinant is the most informative in forecasting crude oil market volatility: Fundamental, speculation, or uncertainty?

This paper aims to identify the most informative determinant in forecasting crude oil market volatility. We use a new GARCH-class model based on mixed data sampling regression and the dynamic model averaging combination method to examine the predicting power of the determinants. We integrate both the global economic policy uncertainty (GEPU) indices and several national economic policy uncertainty (EPU) indices with traditional determinants, such as global oil demand, supply, and speculation. Our analysis suggests that the EPU indices comprehensively integrate the information contained in other determinants. Specifically, GEPU indices and the U.S.’s EPU index have superior predictive powers for West Texas Intermediate spot oil volatility. This finding highlights the importance of EPU indices, implying that they are key factors to consider when determining crude oil market volatility.

Comments: Volatility Trumps Stability

Editor's column Last month, OPEC received another warning that the battle for market share in the global oil market was not over. “It’s not beneficial for OPEC to deepen their cuts because prices will go up and shale oil producers and others will take OPEC’s market share,” Abdullah al-Attiyad, the former oil minister of Qatar, said in an interview with the Bloomberg news agency. “The problem is that there is someone waiting in the dark corner for OPEC—it’s shale oil producers and whenever prices rise, they raise production.” Al-Attiyad’s remarks came after the International Energy Agency reported that the oil market was not balancing as quickly this year as some had predicted. OPEC output rose to its highest level of the year in June and its compliance with production cuts slumped to 68%. Meanwhile, oil prices meander in the USD 45–50/bbl range and remain under pressure as US production remains strong. The oil market has historically been an interplay between supply and demand. But a new book by a consultant and former top energy adviser to US President George W. Bush argues that oil boom-and-bust cycles are here to stay and will likely be more volatile than those in the past. Periods such as from 2004 to 2008—when oil rose to USD 147/bbl and then dropped to USD 33/bbl—or what has happened between June 2014 and the present—prices falling from USD 107/bbl to USD 26/bbl and then back to around USD 50/bbl—could be the new norm. “Recent oil fluctuations mark the return of a new and unfettered market for crude oil and, as a consequence, boom-bust oil prices are making a return after 8 decades,” Robert McNally, who is also a fellow at the Columbia University Center on Global Energy Policy, writes in his new book Crude Volatility. Contradicting the current general consensus that US shale producers have replaced Saudi Arabia as the market’s swing producer—increasing supply as the market tightens and prices rise, and decreasing production as the market dictates—McNally argues that Saudi Arabia abandoned that stabilizing role in the mid-1980s, except for some occasional tinkering with global oil supplies in the 1990s, and shale producers are not cohesive enough to fill that role. The lack of a true swing producer explains the dramatic ups and downs of oil prices since 1998. McNally divides oil price history into 5 eras: the severe boom-bust cycles after oil’s discovery in Pennsylvania in the late 1800s; John D. Rockefeller’s Standard Oil monopoly that enriched him but stabilized prices; the return of volatility after the Standard Oil breakup and the discovery of huge quantities of oil in Texas, Venezuela, California, and Mexico beginning in the 1920s; price stabilization by the Texas Railroad Commission from the mid-1930s to 1972; and OPEC’s attempts to control the market. But OPEC has never had sufficient spare production capacity to truly control prices, McNally believes, and non-OPEC discoveries from Alaska to the Gulf of Mexico and elsewhere have undercut the cartel’s attempts. McNally believes that price swings in the range of USD 30/bbl to USD 100/bbl may be likely, playing havoc with governments that depend on oil revenues and companies trying to plan expensive projects. Oil cycle volatility is caused by basic economics—imbalance in supply and demand, which fuels price swings, which causes further sup-ply fluctuations. And because the industry is often surprised—whether it be the sharp growth in Asian demand in the early 2000s or the recent incredible growth in shale production in the US—it will be impossible to stabilize prices in the short term.

Establishment of a multi-cycle generalized Weng model and its application in forecasts of global oil supply

Low oil prices under the influence of economic structure transformation and slow economic growth have hit the existing markets of traditional big oil suppliers and upgraded the conflict of oil production capacity and interest between OPEC producers and other big oil supplier countries such as the USA and Russia. Forecasting global oil production is significant for all countries for energy strategy planning, although many past forecasts have later been proved to be very seriously incorrect. In this paper, the original generalized Weng model is expanded to a multi-cycle generalized Weng model to better reflect the multi-cycle phenomena caused by political, economic and technological factors. This is used to forecast global oil production based on parameter selection from a large sample, depletion rate of remaining resources, constraints on oil reserves and cycle number determination. This research suggests that the world will reach its peak oil production in 2022, at about 4340 × 106 tonnes. China needs to plan for oil import diversity, a domestic oil production structure based on the supply pattern of large oil suppliers worldwide and the oil demand for China’s own development.

The global oil supply - prevailing situation and prognosis.

Keywords: peak oil, crude oil, petroleum, Energy Returned on Investment, EROI, Energy Returned on Energy Invested, EROEI, hydraulic fracturing, oil sands, tar sands, ultra deepwater drilling, unburned carbon, global oil production, unconventional oil, conventional oil. 1. Introduction It is fair to say that the 'peak oil' scenario does not appear to have played out as straightforwardly as was being anticipated around a decade ago (1). At that time, the prediction was that the global production of oil, having peaked (1) around 2005 (to precede the bumpy plateau that it has been on ever since (2)), would fall into an inexorable decline and be unable to keep pace with demand for it, leading to enormous hikes in the oil price, perhaps to $200 a barrel. The (Brent) oil price (Figure 1) did indeed rise to $ 147 on 11 July 2008, but this had fallen to around $32 a barrel by the end of December, in that same year. The prices subsequently rose (3) to above $100 a barrel in March 2011, and remained high for the next few years, before crashing from a record $115 for Brent crude in June 2014, to just under $60 (a fall of nearly one hall) by the end of the year. Having declined to a low of $30 a barrel in Januaiy 2016, Brent crude is today (4) (29 March 2017) trading at $51.Thus, there are complex and interlocking forces at play, to which the price of oil is highly sensitive, which have included such events as the Lehmann Brothers financial collapse, the death of King Abdullah in Saudi Arabia (with attendant uncertainties over the future of the Kingdom), and the relative oversupply of oil against demand for it, primarily due to hydraulic fracturing of shale in the U.S., along with Canadian oil sands production, which caused the price of oil to initially plummet and then to languish as it has for the past three years. However, whatever may be quibbled over the cost/price of oil in $, the true measure of production viability is Energy Returned on Energy Invested (1-5,6) (EROEI)--sometimes the equivalent term, Energy Returned on Investment (EROI) is used--since it takes energy to produce energy, and ultimately it is primary input energy that is the determining factor in the production rate of a resource (i.e. physics trumps economics). The 'peak oil' concept (1) was never about 'running out of oil' per se, rather maintaining the global oil supply given not only prevailing technical, but also economic limits. An increasing reliance on unconventional oil--i.e. 'tight oil' produced by hydraulic fracturing ('tracking') of shale, oil from oil sands, (ultra) deepwater drilling etc.--means falling EROEI (1,5,6), higher production costs, higher carbon emissions, and less available energy for society from the total primary energy that is available, if more of that energy is consumed by overall energy production. However, it was only the very high oil price (3) that prevailed prior to its crash in 2014, which rendered alternative sources, such as recovering oil from shale by hydraulic fracturing, and processing bitumen from Canadian oil sands, economically viable. In the present period of low oil prices, the high costs of producing oil from these sources are pushing companies to the verge of bankruptcy (7), and further investment in them is stalling. 2. The global oil supply in overview The majority of the total energy (8) used by humans on Earth is provided by crude oil (33%), followed closely by coal (30%), and natural gas (24%); hence we are reliant on the fossil fuels for 87% of our primary energy. In terms of low-carbon energy, nuclear power provides 4%, and hydro-power 7%, with renewable energy (mainly wind and solar) contributing just above 2% of the total. Prior to about 1930, oil could be produced at an EROEI of 100, but this has declined over time (it is now nearer to 17 as a global average (6)), and is falling further (9,10) as unconventional oil sources increasingly make up for the decline in conventional production. …

Modeling systemic risk of crude oil imports: Case of China’s global oil supply chain

Ways to accurately identify and measure systemic risk of oil imports continues to be the focus of intense research because of the increasing importance of energy security. This study reexamines the risk of oil imports from the perspective of global oil supply chain (OSC) and designs a standardized framework of four risk factors, that is, availability, accessibility, affordability and acceptability risk. The former three factors reveal the internal physical disruption risk of OSC and the last describes the external economic risk which OSC faces. Then, a two-dimensional matrix is proposed to derive systemic risk of oil imports from the internal to external risk. Taken China’s OSC for example, the empirical results demonstrate that the method proposed in this study has the advantages of wide applicability and good efficiency. The results show that, during the period 2003–2013, China’s oil-imports risk has experienced three different evolution stages, which are driven by different risk-dominate factors. On considering that China’s OSC has different risk characters in different stages, there is absolutely a need for China to make some improvements in the strategy and tactics of oil imports.

The Reaction of Oil Producers to the Uncorrelated Oil Market Shocks

This study investigates the relationship between oil production and oil market shocks taking into account endogeneity of the oil market factors, during 1986 to 2016. Using the structural VAR framework, we compute the main oil market structural shocks, namely flow supply shocks, global demand shocks that are uncorrelated to supply shocks, and the real crude oil price shocks that are uncorrelated to supply and demand shocks. Next, we apply a PMG method to regress OPEC and non-OPEC oil productions against the three uncorrelated shocks. We find that when the global oil supply and demand increase, producers increase their production, however an increase in the real crude oil prices only weekly trigger OPEC production. Finally, the asymmetric responses are found, as OPEC and non-OPEC producers asymmetrically respond to demand and supply shocks, respectively.

Value Chain Analysis of Palm Oil Biodiesel through a Hybrid (ISO-Eco) Life Cycle Assessment Approach

<p class="TTPParagraph1st">This study assesses the life-cycle impacts of palm oil biodiesel value chain in order to provide insights toward holistic sustainability awareness on the current development of bio-based energy policy. The assessment methodology was performed under a hybrid approach combining ISO-14040 Life Cycle Assessment (ISO-LCA) technique and Ecologically-based Life Cycle Assessment (Eco-LCA) methodology. The scope of this study covers all stages in palm oil biodiesel value chain or is often referred to as “cradle-to-grave” analysis. The functional unit to which all inputs and outputs were calculated is the production of 1 ton of biodiesel. For the analysis, life cycle inventory data were collected from professional databases and from scholarly articles addressing global palm oil supply chains. The inventory analysis yields a linked flow associating the land used, fresh fruit bunch (FFB), crude palm oil (CPO), per functional unit of 1 kg of palm oil biodiesel (POB). The linked flow obtained in the inventory analysis were then normalized and characterized following the characterization model formulated inISO-LCA guidelines. The aggregation of ecological inputs was classified based on the mass and energy associated to each unit process in the value chain, which are cultivation, extraction, conversion, and utilization. It is noted that compared to other unit processes, cultivation is the most crucial unit process within the whole palm oil biodiesel value chain. This study serves as a big picture about the current state of palm oil biodiesel value chain, which will be beneficial for further improving oversight of the policy making and service toward sustainable development.</p><p class="TTPKeywords"><strong><span> </span></strong></p>

Value Chain Analysis of Palm Oil Biodiesel through a Hybrid (ISO-Eco) Life Cycle Assessment Approach

<p class="TTPParagraph1st">This study assesses the life-cycle impacts of palm oil biodiesel value chain in order to provide insights toward holistic sustainability awareness on the current development of bio-based energy policy. The assessment methodology was performed under a hybrid approach combining ISO-14040 Life Cycle Assessment (ISO-LCA) technique and Ecologically-based Life Cycle Assessment (Eco-LCA) methodology. The scope of this study covers all stages in palm oil biodiesel value chain or is often referred to as “cradle-to-grave” analysis. The functional unit to which all inputs and outputs were calculated is the production of 1 ton of biodiesel. For the analysis, life cycle inventory data were collected from professional databases and from scholarly articles addressing global palm oil supply chains. The inventory analysis yields a linked flow associating the land used, fresh fruit bunch (FFB), crude palm oil (CPO), per functional unit of 1 kg of palm oil biodiesel (POB). The linked flow obtained in the inventory analysis were then normalized and characterized following the characterization model formulated inISO-LCA guidelines. The aggregation of ecological inputs was classified based on the mass and energy associated to each unit process in the value chain, which are cultivation, extraction, conversion, and utilization. It is noted that compared to other unit processes, cultivation is the most crucial unit process within the whole palm oil biodiesel value chain. This study serves as a big picture about the current state of palm oil biodiesel value chain, which will be beneficial for further improving oversight of the policy making and service toward sustainable development.</p><p class="TTPKeywords"><strong><span> </span></strong></p>