A spatially explicit model to identify suitable sites to establish dedicated woody energy crops

Self Cite

Bioenergy crops are considered as potential biomass feedstocks to support the bioenergy industry in the southern US. Even though there are suitable areas to grow bioenergy crops, commercial scale production of bioenergy crops has not been established to meet the increasing energy demand. Establishing bioenergy crops in the region requires landowners’ participation and it is crucial to understand whether they intend to promote bioenergy crop production. This study evaluated landowners’ perception of bioenergy and their willingness to supply lands for bioenergy crops in northern Kentucky. A questionnaire survey of randomly selected landowners was administered in four selected counties. Results indicated that landowners’ land use decisions for bioenergy crop production were based on their current land management practices, socio-economic and environmental factors. Overall, there was a low willingness of landowners to participate in bioenergy crop production. Those who were interested indicated that a higher biomass price would be required to promote bioenergy crops on their land. This information could be useful to plan for policies that provide economic incentives to landowners for large-scale production of bioenergy crops in the study area and beyond. Further, results showed how landowners’ opinion on bioenergy affected their preferences for land use decisions. Younger landowners with positive attitude towards bioenergy were more willing to promote bioenergy crops. This information could be useful to develop outreach programs for landowners to encourage them to promote bioenergy crops in the study area.

Section: Introductionmentioning

confidence: 99%

Determinants of Landowners’ Willingness to Participate in Bioenergy Crop Production: A Case Study from Northern Kentucky

Nepal

Tran

Hodges

2020

Self Cite

“…We used a spatially-explicit model developed by Nepal et al [26] to identify the amount and spatial distribution of economically feasible sites to establish energy crops. First, the model calculates total production costs (establishment and management, harvesting, and transportation) and combines them with the delivered biomass price to determine break-even biomass amount for each potential site (grid cell).…”

Section: Model Descriptionmentioning

confidence: 99%

“…These soil data were obtained from spatial and tabular soil data from the Soil Survey Geographic Database (SSURGO) [39]. For a more detailed description of procedures used to estimate biomass yields, please refer to Nepal et al [26].…”

Section: Model Descriptionmentioning

confidence: 99%

“…The objective of this study was to quantify the effect of different market and policy scenarios on the amount of land where it is economically feasible to establish dedicated woody energy crops. Economically feasible lands were identified using a fully spatially-explicit model that identifies sites where potential biomass yields exceed the break-even biomass amounts [26]. The model considers biomass productivity estimated using biomass prices, site index, and total production costs, which are computed considering off-road transportation costs from parcels to existing roads and on-road transportation costs to closest conversion facilities.…”

Section: Introductionmentioning

confidence: 99%

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Quantifying the Effects of Biomass Market Conditions and Policy Incentives on Economically Feasible Sites to Establish Dedicated Energy Crops

Nepal

Contreras

Stainback

et al. 2015

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This study used a spatially-explicit model to identify the amount and spatial distribution of economically feasible sites for establishing dedicated energy crops under various market and policy scenarios. A sensitivity analysis was performed for a biomass market with different discount rates and biomass prices as well as policy scenarios including propriety tax exemption, carbon offset payments, and the inclusion of farmland for biomass production. The model was applied to a four-county study area in Kentucky representing conditions commonly found in the Ohio River Valley. Results showed that both biomass price and discount rate have a can strongly influence the amount of economically efficient sites. Rising the biomass price by 5 $·t −1 and lowering discount rate by 1% from the baseline scenario (40 $·t −1 and 5%) resulted in an over fourteen fold increment. Property tax exemption resulted in a fourfold increase, a carbon payment on only 1 $·t −1 caused a twelve fold increase and extending the landbase from marginal land to farmland only slightly increase the economically efficient sites. These results provide an objective evaluation of market and policy scenarios in terms of their potential to increase land availability for establishing dedicated energy crops and to promote the bioenergy industry.

“…Dawson and Schlyter [25] assessed suitable areas of varying degree of suitability (high and low suitable) based on the factors like access to roads and ecological conditions. More recently, Nepal et al [26] designed spatially explicit model to identify suitable sites for bioenergy crops in four counties of northern Kentucky. An area of 10,088 ha was found suitable and economically feasible for establishment of sweetgum for bioenergy purposes.…”

mentioning

confidence: 99%

Projecting Land Use Changes by Integrating Site Suitability Analysis with Historic Land Use Change Dynamics in the Context of Increasing Demand for Wood Pellets in the Southern United States

Shrestha

Dwivedi

2017

Rising export of wood pellets from southern United States would bring more land under loblolly pine (Pinus taeda L.) at the expense of other competitive land uses. We developed an approach to project potential changes in existing land uses by integrating site suitability analysis with historical land use dynamics in a watershed located within Oconee River Basin, Georgia, United States. We developed a GIS-based site suitability model to classify land into three categories (High, Medium, and Low) for loblolly pine. Then, we calculated historical rates of land use changes in the selected watershed. Finally, we integrated the output of suitability analysis with the projected rates of land use changes under the two scenarios of wood pellet demand (High and Low) to determine an increase in area under loblolly pine for 2016, 2021, and 2026 in a spatially explicit manner. Relative to 2011, the combined changes in the shrubland and evergreen forest land cover categories under High Demand scenario were 7.6, 14.6, and 21.1% and under Low Demand scenario were 3.8, 7.5, and 11.1% for the years 2016, 2021, and 2026, respectively. The developed approach could be applied in a relatively short time at modest spatial scales. The outputs of this study can also be used to determine the environmental implications of land use changes for ensuring the overall sustainability of wood-based bioenergy development in the United States and beyond.