Heat or power: How to increase the use of energy wood at the lowest cost?

Caurla, Sylvain; Bertrand, Vincent; Delacote, Philippe; Cadre, Elodie Le

doi:10.1016/j.eneco.2018.08.011

Cited by 11 publications

(7 citation statements)

References 26 publications

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“…When the energy source to be substituted is estimated to have higher GHG emission intensity than for instance, an average energy mix including renewable energy sources, the DF is higher (Smyth et al 2014;Ji et al 2016). Consequently, DF can be negative or positive, depending on substituted fuel type (Caurla et al 2018). Naturally, emissions of wood based energy is also an influential factor.…”

Section: Displacement Factors For Energy Substitutionmentioning

confidence: 99%

Wood substitution potential in greenhouse gas emission reduction–review on current state and application of displacement factors

et al. 2021

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Background Replacing non-renewable materials and energy with wood offers a potential strategy to mitigate climate change if the net emissions of ecosystem and technosystem are reduced in a considered time period. Displacement factors (DFs) describe an emission reduction for a wood-based product or fuel which is used in place of a non-wood alternative. The aims of this review were to map and assess DFs from scientific literature and to provide findings on how to harmonise practices behind them and to support coherent application. Results Most of the reviewed DFs were positive, implying decreasing fossil GHG emissions in the technosystem. The vast majority of the reviewed DFs describe avoided fossil emissions either both in processing and use of wood or only in the latter when wood processing emissions were considered separately. Some of the reviewed DFs included emissions avoided in post-use of harvested wood products (HWPs). Changes in forest and product carbon stocks were not included in DFs except in a few single cases. However, in most of the reviewed studies they were considered separately in a consistent way along with DFs. DFs for wood energy, construction and material substitution were widely available, whereas DFs for packaging products, chemicals and textiles were scarce. More than half of DFs were calculated by the authors of the reviewed articles while the rest of them were adopted from other articles. Conclusions Most of the reviewed DFs describe the avoided fossil GHG emissions. These DFs may provide insights on the wood-based products with a potential to replace emissions intensive alternatives but they do not reveal the actual climate change mitigation effects of wood use. The way DFs should be applied and interpreted depends on what has been included in them. If the aim of DFs is to describe the overall climate effects of wood use, DFs should include all the relevant GHG flows, including changes in forest and HWP carbon stock and post-use of HWPs, however, based on this literature review this is not a common practice. DFs including only fossil emissions should be applied together with a coherent assessment of changes in forest and HWP carbon stocks, as was the case in most of the reviewed studies. To increase robustness and transparency and to decrease misuse, we recommend that system boundaries and other assumptions behind DFs should be clearly documented.

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Section: Displacement Factors For Energy Substitutionmentioning

confidence: 99%

Wood substitution potential in greenhouse gas emission reduction–review on current state and application of displacement factors

et al. 2021

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“…These include general circulation models to account for climate change [43,151], landscape succession [102] or habitat quality models [46,131] to account for environmental impacts, or forest growth simulators and soil models to calculate carbon fluxes [89,152]. Another common linkage established is with energy models [153] or IAM [114], which is an alternative to the specialisation of FSM described earlier. Our sample also included the use of model couplings to study regulation services, for example, with spread models for pathogens [72] or hydrology models [132].…”

Section: Modelling Trends and Implicationsmentioning

confidence: 99%

Evolving Integrated Models From Narrower Economic Tools: the Example of Forest Sector Models

Rivière

Caurla

Delacote

2020

Environ Model Assess

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Integrated simulation models are commonly used to provide insight on the complex functioning of social-ecological systems, often drawing on earlier tools with a narrower focus. Forest sector models (FSM) encompass a set of simulation models originally developed to forecast economic developments in timber markets but now commonly used to analyse climate and environmental policy. In this paper, we document and investigate this evolution through the prism of the inclusion of several non-timber objectives into FSM. We perform a systematic, quantitative survey of the literature followed by a more in-depth narrative review. Results show that a majority of papers in FSM research today focuses on non-timber objectives related to climate change mitigation, namely carbon sequestration and bioenergy production. Habitat conservation, deforestation and the mitigation of disturbances are secondary foci, while aspects such as forest recreation and many regulation services are absent. Non-timber objectives closest to the original targets of FSM, as well as those for which economic values are easier to estimate, have been more deeply integrated to the models, entering the objective function as decision variables. Others objectives are usually modelled as constraints and only considered through their negative economic impacts on the forest sector. Current limits to a deeper inclusion of non-timber objectives include the models' ability to represent local environmental conditions as well as the formulation of the optimisation problem as a maximisation of economic welfare. Recent research has turned towards the use of model couplings and the development of models at the local scale to overcome these limitations. Challenges for future research comprise extensions to other non-timber objectives, especially cultural services, as well as model calibration at lower spatial scales.

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“…Given that the GoC is developing a Clean Fuel Standard for liquid, gaseous and solid fuels, potential competition between biofuels and traditional forest products is a consideration as previous models have demonstrated negative impacts on the composite panel industry [86,87]. Other models have included or considered additional factors to determine the best policy, such as trade balance and budgetary costs [17] and changes in the make-up of electricity capacity [18]. Although it is important to note that the best policies depend on the ultimate goal of the policy, e.g., short or long-term contribution to climate change mitigation from the land sector vs. increased wood use for bioenergy [17,18] The analysis presented here evaluates the effects of the GoC's carbon pricing policy and CF Standard credits on the Canadian composite panel industry.…”

Section: Model Considerations and Future Researchmentioning

confidence: 99%

“…Other models have included or considered additional factors to determine the best policy, such as trade balance and budgetary costs [17] and changes in the make-up of electricity capacity [18]. Although it is important to note that the best policies depend on the ultimate goal of the policy, e.g., short or long-term contribution to climate change mitigation from the land sector vs. increased wood use for bioenergy [17,18] The analysis presented here evaluates the effects of the GoC's carbon pricing policy and CF Standard credits on the Canadian composite panel industry. Although the analysis examines the indirect impacts of the climate policies on the panel industry ceteris paribus, this approach allows for a concise analysis of the possible implications of an increase in consumer demand for bioenergy.…”

Section: Model Considerations and Future Researchmentioning

confidence: 99%

“…Another study looked at the impact of bioenergy subsidies for coal to biomass conversions and carbon pricing on the uptake of bioenergy in the European Union [16]. Modeling done with the French Forest Sector Model has demonstrated that the impact on forest resource prices and availability depend on the type of policy implemented and whether policies are supporting biomass for heat or for energy [17,18] For example, the impacts on the forest sector and beyond depend on where in the supply chain the policies are targeted, e.g., upstream as a producer subsidy, downstream as a consumer subsidy or as fixed demand in the form of public procurement [17]. In Canada, researchers have examined the impact of increased bioenergy production on carbon emissions [19][20][21], changes in fiber flows and supply [13,22], production [12].…”

Section: Introductionmentioning

confidence: 99%

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Assessment of the Impact of Climate Change Policies on the Market for Forest Industrial Residues

2020

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As part of the Pan-Canadian Framework (PCF) on Clean Growth and Climate Change, the Government of Canada (GoC) introduced carbon pricing and is in the process of developing a Clean Fuel (CF) Standard. Both policies are key elements of the PCF and aim to reduce greenhouse gas (GHG) emissions through the use of lower carbon fuels, including bioenergy. Carbon pricing and the CF Standard are expected to increase the demand for biomass feedstocks, possibly threatening feedstock availability for existing forest industrial residues users, including composite panel manufacturers. To assess the potential impact of carbon pricing and the CF Standard on Canadian composite panel producers, a Monte Carlo-based model was developed to estimate possible increases in feedstock price-points that composite panel manufacturers may face as a result of increases in bioenergy consumption. Results suggest that the composite panel industry may be negatively impacted in the long-term (2030) by the relative price increase of fossil fuels covered by carbon pricing and additional revenues for biofuel suppliers from CF Standard credits, assuming no other adjustments to the market. Although these results are preliminary in that the analysis excludes external market factors that could influence the outcome, there is evidence that such policies have the potential to generate supply risks for the Canadian composite panel industry without careful consideration of the associated externalities.

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Heat or power: How to increase the use of energy wood at the lowest cost?

Cited by 11 publications

References 26 publications

Wood substitution potential in greenhouse gas emission reduction–review on current state and application of displacement factors

Wood substitution potential in greenhouse gas emission reduction–review on current state and application of displacement factors

Evolving Integrated Models From Narrower Economic Tools: the Example of Forest Sector Models

Assessment of the Impact of Climate Change Policies on the Market for Forest Industrial Residues

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