High-resolution multi-objective optimization of feedstock landscape design for hybrid first and second generation biorefineries

Nguyen, Trung Quang; Granger, Julien; Pandya, Deval; Paustian, Keith

doi:10.1016/j.apenergy.2019.01.117

Cited by 21 publications

(3 citation statements)

References 65 publications

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“…In total, eight research articles were found, indicating that this field has been underexploited, which confirms the statement made by Almeida et al (2016). In these works that focus on the optimal spatial distribution of land uses, Geographic Information System (GIS) is used to calculate spatially explicit LCA (Almeida et al, 2016;Kreidenweis et al, 2016;Galán-Martín et al, 2017;Nguyen et al, 2019), assess land suitability (Yuan et al, 2018), record water sources allocation (Marzban et al, 2022;Ren et al, 2022) and propose optimal facility locations (Almeida et al, 2016). However, these works mainly focus on the spatial allocation of single-use (e.g., bioethanol production), which should be extended to optimize land uses for multiple purposes as the land use competition intensifies (Miret et al, 2016;Yao et al, 2017).…”

Section: Introductionsupporting

confidence: 68%

Coupling optimization with territorial LCA to support agricultural land-use planning

Ding

Steubing

Achten

2023

Journal of Environmental Management

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Section: Introductionsupporting

confidence: 68%

Coupling optimization with territorial LCA to support agricultural land-use planning

Ding

Steubing

Achten

2023

Journal of Environmental Management

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“…• a first and widespread effort in merging ES into LCA is performed in the literature starting from the evaluation scope of LCA, which typically focuses on identifying and characterizing detrimental impacts generated by human processes (driven by, e.g., land use) on the provision of ES (e.g., [71][72][73]); • this somehow anticipates a second effort of the LCA community to account for ES in LCA based on unconventional methodological grounds, such as integrated modeling frameworks developed to capture the complexity of ecological dynamics, usually implemented outside the LCA field (e.g., [74][75][76]).…”

Section: Progress On Esa-lcamentioning

confidence: 99%

Environmental Footprint Neutrality Using Methods and Tools for Natural Capital Accounting in Life Cycle Assessment

Rugani,

Osset,

Blanc

et al. 2023

Land

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Natural Capital Accounting (NCA) is becoming a reference tool for an increasing number of organizations transitioning towards environmental impact neutrality. However, one NCA technique applicable to all types of actors (individual, community, company, etc.) is missing because of the lack of consensus on how to quantify both their environmental impacts and dependencies on ecosystems. A coupled systematic and non-systematic review of the grey and scientific literature is performed here to (i) make an extensive review of state-of-the-art NCA methods, identifying their current utilization and limitations, and (ii) discern prospects about the challenges of integrating an Ecosystem Service Accounting in Life Cycle Assessment (ESA-LCA). While NCA methods can extensively evaluate the supply of ES, they tend to disregard the quantification of environmental impacts that imply a demand for ES. The ESA-LCA approach is identified as a robust solution to balance supply and demand of ecosystem services in NCA, allowing private and public actors to quantify their distance from impact neutrality targets. A novel definition of NC(A) in LCA is also formulated to support these future efforts, promoting a Mitigation Hierarchy-based strategy to avoid, minimize, restore, and offset impacts, and outlining a roadmap for practitioners to apply ESA-LCA across multiple economic sectors.

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“…Previous studies used the DayCent crop model to optimize landscape design around a single, pre-existing biorefinery and showed that careful crop establishment and management can increase the amount of soil carbon sequestration, complementing industrial carbon capture and storage (CCS) 10,11 . Additionally, researchers presented multi-objective optimization models that considered several land-management practices to analyse their pareto trade-offs when designing the landscape around a biorefinery 12 .…”

mentioning

confidence: 99%

Large-scale spatially explicit analysis of carbon capture at cellulosic biorefineries

O’Neill,

Geissler,

Maravelias

2024

Nat Energy

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The large-scale production of cellulosic biofuels would involve spatially distributed systems including biomass fields, logistics networks and biorefineries. Better understanding of the interactions between landscape-related decisions and the design of biorefineries with carbon capture and storage (CCS) in a supply chain context is needed to enable efficient systems. Here we analyse the cost and greenhouse gas mitigation potential for cellulosic biofuel supply chains in the US Midwest using realistic spatially explicit land availability and crop productivity data and consider fuel conversion technologies with detailed CCS design for their associated CO2 streams. Optimization methods identify trade-offs and design strategies leading to systems with attractive environmental and economic performance. Strategic and operational decisions depend on underlying spatial features and are sensitive to biofuel demand and CCS incentives. US CCS incentives neglect to motivate greenhouse gas mitigation from all supply chain emission sources, which leverage spatial interactions between CCS, electricity prices and the biomass landscape.

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High-resolution multi-objective optimization of feedstock landscape design for hybrid first and second generation biorefineries

Cited by 21 publications

References 65 publications

Coupling optimization with territorial LCA to support agricultural land-use planning

Coupling optimization with territorial LCA to support agricultural land-use planning

Environmental Footprint Neutrality Using Methods and Tools for Natural Capital Accounting in Life Cycle Assessment

Large-scale spatially explicit analysis of carbon capture at cellulosic biorefineries

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