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Assessing sustainable forest biomass potential and bioenergy implications for the northern Lake States region,USA
Affiliation:1. Department of Forest Resources, University of Minnesota, St. Paul, 55108 MN, USA;2. Rubenstein School of Environment and Natural Resources, University of Vermont, Burlington, 05095 VT, USA;3. College of Natural Resources, University of Idaho, Moscow, 83844 ID, USA;1. INRA, UMR 211 Agronomie, F-78850, Thiverval-Grignon, France;2. AgroParisTech, UMR 211 Agronomie, F-78850, Thiverval-Grignon, France;1. Forest Genetics and Physiology Research Group, School of Forest Engineering, Technical University of Madrid (UPM), Ciudad Universitaria s/n, 28040 Madrid, Spain;2. INIA-CIFOR, Forest Research Centre, Crta. de la Coruña km 7,5, 28040 Madrid, Spain;3. SFM-RI, Sustainable Forest Management Research Institute UVa INIA, Madrid, Spain;4. CESEFOR, Forestry Services and Promotion Centre of Castilla y León, Polígono Industrial “Las Casas”, Calle C, Parcela 4, 42005 Soria, Spain;1. Department of Agricultural Engineering, KNUST, Kumasi, Ghana;2. Department of Chemical and Biochemical Engineering, Technical University of Denmark, DTU, DK-2800 Kongens Lyngby, Denmark;3. Department of Chemical Engineering, Kumasi Polytechnic, Kumasi, Ghana;4. Department of Chemical Engineering, KNUST, Kumasi, Ghana
Abstract:Forestlands in the United States have tremendous potential for providing feedstocks necessary to meet emerging renewable energy standards. The Lake States region is one area recognized for its high potential of supplying forest-derived biomass; however, the long-term availability of roundwood harvests and associated residues from this region has not been fully explored. Better distribution and temporal availability estimates are needed to formulate emerging state policies regarding renewable energy development. We used a novel predictive methodology to quantify sustainable biomass availability and likely harvest levels over a 100-year period in the Lake States region. USDA Forest Inventory and Analysis estimates of timberland were combined with published growth and yield models, and historic harvest data using the Forest Age Class Change Simulator (FACCS) to generate availability estimates. Monte-Carlo simulation was used to develop probability distributions of biomass harvests and to incorporate the uncertainty of future harvest levels. Our results indicate that 11.27–15.71 Mt y−1 dry roundwood could be sustainably harvested from the Lake States. Assuming 65% collection rate, 1.87–2.62 Mt y−1 residue could be removed, which if substituted for coal would generate 2.12–2.99 GW h of electricity on equivalent energy basis while reducing GHG (CO2e) emission by 1.91–2.69 Mt annually. In addition to promoting energy security and reducing GHG emissions, forest residues for energy may create additional revenues and employment opportunities in a region historically dependent on forest-based industries.
Keywords:Bioenergy  Forest residue  GHG reduction  Lake states  Sustainable harvest  Biomass estimation  BRDA"}  {"#name":"keyword"  "$":{"id":"kwrd0045"}  "$$":[{"#name":"text"  "_":"Biomass Research and Development Act  ESDT"}  {"#name":"keyword"  "$":{"id":"kwrd0055"}  "$$":[{"#name":"text"  "_":"Exponential Smoothing with Damped Trend  ERFMax"}  {"#name":"keyword"  "$":{"id":"kwrd0065"}  "$$":[{"#name":"text"  "_":"Extended Rotation Forest Maximum Age  FACCS"}  {"#name":"keyword"  "$":{"id":"kwrd0075"}  "$$":[{"#name":"text"  "_":"Forest Age Class Change Simulator  FIA"}  {"#name":"keyword"  "$":{"id":"kwrd0085"}  "$$":[{"#name":"text"  "_":"Forest Service Forest Inventory and Analysis  GEIS"}  {"#name":"keyword"  "$":{"id":"kwrd0095"}  "$$":[{"#name":"text"  "_":"Generic Environmental Impact Statement  GHG"}  {"#name":"keyword"  "$":{"id":"kwrd0105"}  "$$":[{"#name":"text"  "_":"Greenhouse Gases  GMHT"}  {"#name":"keyword"  "$":{"id":"kwrd0115"}  "$$":[{"#name":"text"  "_":"Growth to Maximum Harvest Trend  HFRA"}  {"#name":"keyword"  "$":{"id":"kwrd0125"}  "$$":[{"#name":"text"  "_":"Healthy Forest Restoration Act  LTSY"}  {"#name":"keyword"  "$":{"id":"kwrd0135"}  "$$":[{"#name":"text"  "_":"Theoretical Long Term Sustained Yield  MSE"}  {"#name":"keyword"  "$":{"id":"kwrd0145"}  "$$":[{"#name":"text"  "_":"Mean Squared Error  MN-IHT"}  {"#name":"keyword"  "$":{"id":"kwrd0155"}  "$$":[{"#name":"text"  "_":"Minnesota Increasing Harvest Trend  MN-DHT"}  {"#name":"keyword"  "$":{"id":"kwrd0165"}  "$$":[{"#name":"text"  "_":"Minnesota Declining Harvest Trend  MN-HHT"}  {"#name":"keyword"  "$":{"id":"kwrd0175"}  "$$":[{"#name":"text"  "_":"Minnesota historical harvest trend (1980–2010)
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