Recycle, Bury, or Burn Wood Waste Biomass?: LCA Answer Depends on Carbon Accounting, Emissions Controls, Displaced Fuels, and Impact Costs

Morris, Jeffrey

doi:10.1111/jiec.12469

Cited by 40 publications

(26 citation statements)

References 53 publications

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“…A more accurate estimation of the regional to global distribution of forest aboveground biomass is required to provide the baseline of forest carbon stocks, and to quantify the anthropogenic emissions caused by deforestation and forest degradation [2,3]. In addition, the quantification of forest biomass has large economic implications for the supply of goods such as wood, timber, food, fiber and energy [4,5]. Forest biomass has also important ecological implications in ecosystem sustainability, including soil and water management [6].…”

Section: Introductionmentioning

confidence: 99%

Modeling of Aboveground Biomass with Landsat 8 OLI and Machine Learning in Temperate Forests

López-Serrano

Domínguez

Corral-Rivas

et al. 2019

Forests

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An accurate estimation of forests’ aboveground biomass (AGB) is required because of its relevance to the carbon cycle, and because of its economic and ecological importance. The selection of appropriate variables from satellite information and physical variables is important for precise AGB prediction mapping. Because of the complex relationships for AGB prediction, non-parametric machine-learning techniques represent potentially useful techniques for AGB estimation, but their use and comparison in forest remote-sensing applications is still relatively limited. The objective of the present study was to evaluate the performance of automatic learning techniques, support vector regression (SVR) and random forest (RF), to predict the observed AGB (from 318 permanent sampling plots) from the Landsat 8 Landsat 8 Operational Land Imager (OLI) sensor, spectral indexes, texture indexes and physical variables the Sierra Madre Occidental in Mexico. The result showed that the best SVR model explained 80% of the total variance (root mean square error (RMSE) = 8.20 Mg ha−1). The variables that best predicted AGB, in order of importance, were the bands that belong to the region of red and near and middle infrared, and the average temperature. The results show that the SVR technique has a good potential for the estimation of the AGB and that the selection of the model hyperparameters has important implications for optimizing the goodness of fit.

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Section: Introductionmentioning

confidence: 99%

Modeling of Aboveground Biomass with Landsat 8 OLI and Machine Learning in Temperate Forests

López-Serrano

Domínguez

Corral-Rivas

et al. 2019

Forests

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“…Harnessing the full energetic and environmental potential of this resource, therefore, requires a holistic assessment of alternative competing pathways to their utilization taking into account the spatial distribution of each specific type of waste and the local conditions under which the wastes will be processed. The majority of previous life-cycle assessment (LCA) studies have focused on either a smaller number of waste types 14,[27][28][29][30][31][32][33][34][35] , certain types of bioenergy product 15,19,20,[36][37][38] or certain conversion technologies 29,31,37,[39][40][41][42][43][44][45] . Comparing the effectiveness and environmental impacts of all feasible conversion pathways for all types of waste from a systems perspective is necessary for policies that address the best use of wastes and biomass residues.…”

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confidence: 99%

Life-cycle energy and climate benefits of energy recovery from wastes and biomass residues in the United States

2019

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A t the beginning of the new millennium, energy insecurity, global climate change and stagnant rural economies led to policies supporting domestic biofuels as a renewable alternative fuel in more than 60 countries worldwide 1. As a consequence, global production of ethanol and biodiesel combined almost quadrupled (from about 35 billion litres to 135 billion litres) in the short span from 2005 to 2016 (ref. 2). However, these policies had two major flaws. First, appropriation of edible crops for biofuel (mainly corn and sugarcane for ethanol, and soybean, canola and palm for biodiesel) was an important factor responsible for food price inflation alongside other factors such as rising income that drove rapid growth in food demand (especially meat demand), rising energy prices, adverse weather shocks, currency fluctuations and trade policies 1,3-6 , the consequences of which were particularly severe for poorer households in developing countries 7. Second, these crops required intensive use of land, water, nitrogen and other farm chemicals, which meant low, and in the worst case uncertain, net environmental benefits 8-12. Being widely available and replenishable, wastes and biomass residues from agricultural, dairy, forestry and household activities seem to contain the basic attributes of a sustainable energy resource, in stark contrast to bioenergy from food crops 13-15. The US Department of Energy 2016 Billion-Ton Study estimates an annual availability of 233 million tonnes (Mt) of dry waste 16. To put this in perspective, the approximately 60 billion litres of corn ethanol produced in the United States in 2017 required about 150 Mt of corn (assuming a yield of 402 l ethanol per Mt). Furthermore, wastes and biomass residues can be used to derive a number of alternative energy products, including electricity along with heat, biomethane (or renewable natural gas), ethanol, renewable diesel or bio jet fuel, each through various conversion pathways, which currently are at different stages of technical and economic maturity 14,15,17-21. Beyond energy production and mitigation of climate change, efficient use of wastes and residues is integral to the achievement of sustainable development 22 , and to redesigning our economies to minimize

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“…In such cases, the C + D figures for energy recovery might look less favourable. In one set of scenarios investigated, recycling of end-of-life wood into new products has been found always to be better than burning or burying, with burying better (from a climate perspective) than burning to displace gas boiler fuel [36].…”

Section: Beyond the System-including Stage D In The Analysismentioning

confidence: 99%

More Timber in Construction: Unanswered Questions and Future Challenges

Hart

Pomponi

2020

Sustainability

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The built environment is one of the greatest contributors to carbon emissions, climate change, and to the unsustainable pressure on the natural environment and its ecosystems. The use of more timber in construction is one possible response, and an authoritative contribution to this growing movement comes from the UK’s Committee on Climate Change, which identifies a “substantial increase in the use of wood in the construction of buildings” as a top priority. However, a global encouragement of such a strategy raises some difficult questions. Given the urgency of effective solutions for low-carbon built environments, and the likely continued growth in demand for timber in construction, this article reviews its sustainability and identifies future challenges and unanswered questions. Existing evidence points indeed towards timber as the lower carbon option when modelled through life cycle assessment without having to draw on arguments around carbon storage. Issues however remain on the timing of carbon emissions, land allocation, and the environmental loads and benefits associated with the end-of-life options: analysis of environmental product declarations for engineered timber suggests that landfill might either be the best or the worst option from a climate change perspective, depending on assumptions.

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Recycle, Bury, or Burn Wood Waste Biomass?: LCA Answer Depends on Carbon Accounting, Emissions Controls, Displaced Fuels, and Impact Costs

Cited by 40 publications

References 53 publications

Modeling of Aboveground Biomass with Landsat 8 OLI and Machine Learning in Temperate Forests

Modeling of Aboveground Biomass with Landsat 8 OLI and Machine Learning in Temperate Forests

Life-cycle energy and climate benefits of energy recovery from wastes and biomass residues in the United States

More Timber in Construction: Unanswered Questions and Future Challenges

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