From the global efforts on certification of bioenergy towards an integrated approach based on sustainable land use planning (original) (raw)
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Progress and barriers in understanding and preventing indirect land‐use change
Biofuels, Bioproducts and Biorefining, 2020
Climate change mitigation pathways have highlighted both the critical role of landuse emissions, and the potential use of biofuels as a low-emission energy carrier. This has led to concerns about the emission mitigation potential of biofuels, particularly related to indirect land-use change (ILUC). This arises when the production of biofuels displaces the production of land-based products elsewhere, either directly or via changes in crop prices, leading to indirect greenhouse gas (GHG) emissions. We review a large body of literature that has emerged on ILUC assessment and quantification, highlighting the methodologies employed, the resultant emission factors, modeled dynamics driving ILUC, and the uncertainty therein. Our review reveals that improvements in ILUC assessment methods have failed to reduce uncertainty and increase confidence in ILUC factors, instead making marginal improvements to economic models. Thus, while assessments have highlighted measures that could reduce ILUC, it is impossible to control or determine the actual ILUC resulting from biofuel production. This makes ILUC a poor guiding principle for land-use and climate policy, and does not help with the determination of the GHG performance of biofuels. Instead climate and landuse policy should focus on more integrated protection of terrestrial resources, covering all land-use
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"Indirect land use change for biofuels: Testing predictions and improving analytical methodologies" by S. Kim and B. Dale [1], presents a principal inference not supported by its results, that rests on a fundamental conceptual error, and that has no place in the current discussion of biofuels’ climate effects. The paper takes correlation between two variables in a system with many interacting factors to indicate (or contraindicate) causation, and draws a completely incorrect inference from observed sample statistics and their significance levels.► The recent Kim and Dale paper “Indirect land use change…” is wrong. ► The authors’ data (weakly) support a conclusion opposite to their inference. ► The paper misapprehends the relationship of biofuel expansion to land use change. ► It misuses statistical inference calculations and uses basic hypothesis testing incorrectly. ► It profoundly confuses correlation and causation in a multivariate environment.
Biofuels and land-use changes: searching for the top model
Interface Focus, 2011
The use of agricultural-based biofuels has expanded. Discussions on how to assess green house gas (GHG) emissions from biofuel policies, specifically on (non-observed) land-use change (LUC) effects involve two main topics: (i) the limitations on the existing methodologies, and (ii) how to isolate the effects of biofuels. This paper discusses the main methodologies currently used by policy-makers to take decisions on how to quantify LUCs owing to biofuel production expansion. It is our opinion that the concerns regarding GHG emissions associated with LUCs should focus on the agricultural sector as a whole rather than concentrating on biofuel production. Actually, there are several limitations of economic models and deterministic methodologies for simulating and explaining LUCs resulting from the expansion of the agricultural sector. However, it is equally true that there are avenues of possibilities to improve models and make them more accurate and precise in order to be used for pol...
Indirect Land Use Change: A Second-best Solution to a First-class Problem
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Concern about the possible affects of biofuels on deforestation have led to assigning biofuel producers with the responsibility for greenhouse gas (GHG) emissions of the indirect land use changes (ILUC) associated with their activities when assessing their compliance with biofuel policies. We show that the computation of the ILUC is shrouded with uncertainty; they vary frequently, and are strongly affected by policy choices. It seems that its overall impact on GHGs is relatively minor. Once the ILUCs are introduced other indirect effects of biofuel may need to be considered which will increase the cost of biofuel regulations. Concentrating on direct regulation of biofuel and on efforts to reduce deforestation, wherever it occurs, may be more effective than debating and refining the ILUC.
Biofuels and Indirect Land Use Change
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A key component of the U.S. and EU responses to climate change concerns was the introduction of a target for the inclusion of biofuels in the road transport sector to reduce greenhouse gas (GHG) emissions. As biofuel consumption rose, so too did concern that the use of agricultural land to produce its feedstocks could lead to a reduction in available land for food production, potentially leading to increased food price volatility and the conversion of natural land, such as forests, grasslands or peatlands (Ecofys, 2013)1.
Indirect land use change: review of existing models and strategies for mitigation
Biofuels, 2012
This study reviews the current status, uncertainties and shortcomings of existing models of land use change (LUC) and associated greenhouse gas emissions as a result of biofuel production. The study also identifies options for improving the models and conducting further analysis. Moreover, because the extent of indirect LUC related to biofuels largely depends on other land uses -particularly agriculture -, this study explores strategies for mitigating overall LUC and its effects. Despite recent improvements and refinements of the models, this review finds large uncertainties, primarily related to the underlying data and assumptions of the market equilibrium models. There is thus still considerable scope for further scientific improvements of the modeling efforts. In addition, analyzing how overall LUC and its effects can be minimized is an important topic for further research and can deliver more concrete input for developing proper policy strategies. Future studies should investigate the impact of sustainability criteria and the effects of strategies for mitigating LUC, such as increasing agricultural efficiency, optimizing bioenergy production chains, using currently unused residues and by-products, and producing feedstocks on degraded and marginal land.
Chapter 11 - Agriculture, forestry and other land use (AFOLU)
Cambridge University Press eBooks, 2014
Agriculture, Forestry, and Other Land Use (AFOLU) is unique among the sectors considered in this volume, since the mitigation potential is derived from both an enhancement of removals of greenhouse gases (GHG), as well as reduction of emissions through management of land and livestock (robust evidence; high agreement). The land provides food that feeds the Earth's human population of ca. 7 billion, fibre for a variety of purposes, livelihoods for billions of people worldwide, and is a critical resource for sustainable development in many regions. Agriculture is frequently central to the livelihoods of many social groups, especially in developing countries where it often accounts for a significant share of production. In addition to food and fibre, the land provides a multitude of ecosystem services; climate change mitigation is just one of many that are vital to human well-being (robust evidence; high agreement). Mitigation options in the AFOLU sector, therefore, need to be assessed, as far as possible, for their potential impact on all other services provided by land. [Section 11.1] The AFOLU sector is responsible for just under a quarter (~10-12 GtCO 2 eq / yr) of anthropogenic GHG emissions mainly from deforestation and agricultural emissions from livestock, soil and nutrient management (robust evidence; high agreement) [11.2]. Anthropogenic forest degradation and biomass burning (forest fires and agricultural burning) also represent relevant contributions. Annual GHG emissions from agricultural production in 2000-2010 were estimated at 5.0-5.8 GtCO 2 eq / yr while annual GHG flux from land use and land-use change activities accounted for approximately 4.3-5.5 GtCO 2 eq / yr. Leveraging the mitigation potential in the sector is extremely important in meeting emission reduction targets (robust evidence; high agreement) [11.9]. Since publication of the IPCC Fourth Assessment Report (AR4), emissions from the AFOLU sector have remained similar but the share of anthropogenic emissions has decreased to 24 % (in 2010), largely due to increases in emissions in the energy sector (robust evidence, high agreement). In spite of a large range across global Forestry and Other Land Use (FOLU) flux estimates, most approaches indicate a decline in FOLU carbon dioxide (CO 2) emissions over the most recent years, largely due to decreasing deforestation rates and increased afforestation (limited evidence, medium agreement). As in AR4, most projections suggest declining annual net CO 2 emissions in the long run. In part, this is driven by technological change, as well as projected declining rates of agriculture area expansion, which, in turn, is related to the expected slowing in population growth. However, unlike AR4, none of the more recent scenarios projects growth in the near-term [11.9]. Opportunities for mitigation include supply-side and demandside options� On the supply side, emissions from land-use change (LUC), land management and livestock management can be reduced, terrestrial carbon stocks can be increased by sequestration in soils and biomass, and emissions from energy production can be saved through Agriculture, Forestry and Other Land Use (AFOLU) Chapter 11 agreement) [11.7]. Implementation challenges, including institutional barriers and inertia related to governance issues, make the costs and net emission reduction potential of near-term mitigation uncertain. In mitigation scenarios with idealized comprehensive climate policies, agriculture, forestry, and bioenergy contribute substantially to the reduction of global CO 2 , CH 4 , and N 2 O emissions, and to the energy system, thereby reducing policy costs (medium evidence; high agreement) [11.9]. More realistic partial and delayed policies for global land mitigation have potentially significant spatial and temporal leakage, and economic implications, but could still be cost-effectively deployed (limited evidence; limited agreement) [11.9]. Economic mitigation potential of supply-side measures in the AFOLU sector is estimated to be 7�18 to 10�60 (full range: 0�49-10�60) GtCO 2 eq / yr in 2030 for mitigation efforts consistent with carbon prices up to 100 USD / tCO 2 eq, about a third of which can be achieved at < 20 USD / tCO 2 eq (medium evidence; medium agreement) [11.6]. These estimates are based on studies that cover both forestry and agriculture and that include agricultural soil carbon sequestration. Estimates from agricultural sector-only studies range from 0.3 to 4.6 GtCO 2 eq / yr at prices up to 100 USD / tCO 2 eq, and estimates from forestry sector-only studies from 0.2 to 13.8 GtCO 2 eq / yr at prices up to 100 USD / tCO 2 eq (medium evidence; medium agreement) [11.6]. The large range in the estimates arises due to widely different collections of options considered in each study, and because not all GHGs are considered in all of the studies. The composition of the agricultural mitigation portfolio varies with the carbon price, with the restoration of organic soils having the greatest potential at higher carbon prices (100 USD / tCO 2 eq) and cropland and grazing land management at lower (20 USD / tCO 2 eq). In forestry there is less difference between measures at different carbon prices, but there are significant differences between regions, with reduced deforestation dominating the forestry mitigation potential in Latin America and Caribbean (LAM) and Middle East and Africa (MAF), but very little potential in the member countries of the Organisation for Economic Cooperation and Development (OECD-1990) and Economies in Transition (EIT). Forest management, followed by afforestation, dominate in OECD-1990, EIT, and Asia (medium evidence, strong agreement) [11.6]. Among demand-side measures, which are under-researched compared to supply-side measures, changes in diet and reductions of losses in the food supply chain can have a significant, but uncertain, potential to reduce GHG emissions from food production (0.76-8.55 GtCO 2 eq / yr by 2050), with the range being determined by assumptions about how the freed land is used (limited evidence; medium agreement) [11.4]. More research into demand-side mitigation options is merited. There are significant regional differences in terms of mitigation potential, costs, and applicability, due to differing local biophysical, socioeconomic, and cultural circumstances, for instance between developed and developing regions, and among developing regions (medium evidence; high agreement) [11.6]. Agriculture, Forestry and Other Land Use (AFOLU) Chapter 11 11.2 New developments in emission trends and drivers Estimating and reporting the anthropogenic component of gross and net AFOLU GHG fluxes to the atmosphere, globally, regionally, and at country level, is difficult compared to other sectors. First, it is not always possible to separate anthropogenic and natural GHG fluxes from land. Second, the input data necessary to estimate GHG emissions globally and regionally, often based on country-level statistics or on remote-sensing information, are very uncertain. Third, methods for estimating GHG emissions use a range of approaches, from simple default methodologies such as those specified in the IPCC GHG Guidelines 2 (IPCC, 2006), to more complex estimates based on terrestrial carbon cycle modelling and / or remote sensing information. Global trends in total GHG emissions from AFOLU activities between 1971 and 2010 are shown in Figure 11.2; Figure 11.3 shows trends of major drivers of emissions. 2 Parties to the United Nations Framework Convention on Climate Change (UNFCCC) report net GHG emissions according to IPCC methodologies (IPCC, 2006). Reporting is based on a range of methods and approaches dependent on available data and national capacities, from default equations and emission factors applicable to global or regional cases and assuming instantaneous emissions of all carbon that will be eventually lost from the system following human action (Tier 1) to more complex approaches such as model-based spatial analyses (Tier 3). Figure 11�1 | Multiple ecosystem services, goods and benefits provided by land (after MEA, 2005; UNEP-WCMC, 2011). Mitigation actions aim to enhance climate regulation, but this is only one of the many functions fulfilled by land.