Expanding System Boundaries in Attributional LCA to Assess GHG Emissions and Climate Impacts of Advanced Biofuels and Bioenergy Pathways

Transcription

1 Expanding System Boundaries in Attributional LCA to Assess GHG Emissions and Climate Impacts of Advanced Biofuels and Bioenergy Pathways Jacopo Giuntoli, Alessandro Agostini, Robert Edwards and Luisa Marelli 28 October 2015

2 (indicative target) 0.5% of transport fuels from advanced biofuels in EU by 2020 Energy and Climate Challenges The RED 2020 targets: decrease energy consumption by 20% increase the share of renewables to 20% (10% renewable energy in transport) Energy and climate package post % GHG reduction in 2030 Calls for a range of alternative fuels for 2030, with special focus on 2G and 3G biofuels Wide coordination for large scale deployment of alternative fuels Stable policy framework to attract investments NEW Energy Union Sustainable Low-carbon economy Alternative fuels and clean vehicles Road transport and Renewable Energy package Achieve the 40% GHG reduction target

3 Biofuels and bioenergy from wastes and residues, potentials: Abundant, relatively cheap and widespread No competition with food or land Wastes have no or low iluc Valorization of waste streams Mobilization of wastes and residues is essential but all the impacts of increased removal should be carefully assessed Policy decisions need to be backed up by a clear and comprehensive analysis of all associated environmental effects. 9 November

4 Attributional LCA is the tool often used for microlevel decision support or accounting. e.g. the RED methodology for accounting supplychain GHG emissions accounting is a simplified A- LCA. could be one of the appropriate methodologies for policy implementation and monitoring Consequential LCA is instead the appropriate methodology for policy analysis and meso/macro level decision support (i.e. large-scale analysis of consequences of a policy choice implementation) 9 November 2015 Complex modelling frameworks 4

5 An "Advanced" approach to attributional-lca? Consequential thinking and advanced tools can be applied also to A-LCA studies: For example, expanding the reference system to include the production o energy by a fossil source plus one or more development scenarios for the biomass without bioenergy (multiple "counterfactuals"). And using ecosystem models to calculate carbon pools development in agricultural or forest systems In addition to proper system design, this analysis can still provide relevant information on feedstocks, systems, configurations and management practices that carry potential environmental risks, highlighting particular red flags that will need to be looked at carefully The purpose of our approach is to assess potential environmental risks (or benefits) deriving from deploying bioenergy systems as compared to other systems (including fossil-based ones).

6 The pathways we are analyzing: Power generation Forest residues 80 MW el power plant Straw 15 MW el power plant Slurry-Biogas 300 KW el internal combust. engine Two-stage analysis: 1)supply-chain GHG emissions; Heat Forest residues Advanced log Stove District Heating Plant Domestic Pellet Stove 2)expanded system to include forest and soil systems; Biofuels Forest residues FT-Diesel (based on a plant of 1 Mt dry matter/year in input. Circulating Fluid Bed pressurized at 25 bar) Straw Ethanol (based on WtW v4 process with efficiencies from a modelled 60 Ktons/year ethanol plant)

7 Stage 1) Supply-chain GHG emissions Bioenergy system POWER GENERATION Logging operations [not included] Forest Agricultural system Cereal cultivation [not included] Dairy farm [not included] Forest Logging Residues (FR) on forest floor Straw chopped on soil Slurry collected Bioenergy systems (FRel) (STel) (Biogas OD/CD) Reference system Background systems (inputs) Residues collection Wood Chipping Truck Transport (Fresh Wood chips) [50 km] Wood chips boiler Pellet mill Heat Truck Transport (Pellets) [50 km] Baling Transport (Bales) [50 km] Heat + El. to digester Transport (Slurry) [5 km] Anaerobic Digester [η=0.42] Digestate to field (as organic fertilizer) Digestate Storage tank (Open / Closed) EU-27 generation mix (2011) [PE Professional (2015)] Electricity to grid Supply chains system boundaries Expanded system boundaries 80 MW el. Power Plant [η=34%] 15 MW el. Power Plant [η=29%] 300 kw el. Biogas engine [η=36%] Electricity to grid Emissions Electricity to grid Emissions Electricity to grid Emissions Emissions 7

8 GHG emissions [gco 2eq. MJ -1 el. ] Example of results Slurry AD (Open) Slurry AD (Close) Straw 15MW el FR pellets 80MW el EU-27 mix Bioenergy system POWER GENERATION CO 2 CH 4 N 2 O CH 4 (credits) N 2 O (credits) GHG savings Net emissions EU DEFAULT Slurry AD (Open) EU DEFAULT Slurry AD (Close) EU DEFAULT Straw 70% threshold EU DEFAULT FR pellets (a) GHG savings [%] GHG emissions (% of total) Slurry AD(Open) Slurry AD (Close) Straw 15MW el FR pellets 80MW el (b) Collection- Baling- Field application Transport Pellet mill-ad plant End-use Credits 8

9 Points of concern in LCA of bioenergy (from residual biomass) 1. Supply-chain attributional LCA of bioenergy often overlooks, or excludes from system boundaries, the development of some important carbon pools, mainly related to land use or management change driven by bioenergy demand; 2. Many of these additional developments are time-dependent, bringing into play transient emission profiles which are dealt poorly by the "standard" GWP(100) metric; 3. Other climate forcers than WMGHG may have a significant mitigating impact on the overall climate impact of bioenergy. So we also wanted to look whether other climate forcers, such as ozone precursors and aerosols, may be significant or not for the case of the residual biomass considered. Biogeophyisical forcers may be relevant for certain feedstocks/systems but 9 rarely for residual biomass.

10 Stage 2) Expanding system boundaries Bioenergy system POWER GENERATION Logging operations [not included] Forest Agricultural system Cereal cultivation [not included] Dairy farm [not included] Forest Logging Residues (FR) on forest floor Straw chopped on soil Slurry collected Bioenergy systems (FRel) (STel) (Biogas OD/CD) Reference system Background systems (inputs) Residues collection Wood Chipping Truck Transport (Fresh Wood chips) [50 km] Wood chips boiler Pellet mill Heat Truck Transport (Pellets) [50 km] Baling Transport (Bales) [50 km] Heat + El. to digester Transport (Slurry) [5 km] Anaerobic Digester [η=0.42] Digestate to field (as organic fertilizer) Digestate Storage tank (Open / Closed) EU-27 generation mix (2011) [PE Professional (2015)] Electricity to grid Supply chains system boundaries Expanded system boundaries 80 MW el. Power Plant [η=34%] 15 MW el. Power Plant [η=29%] 300 kw el. Biogas engine [η=36%] Emissions Emissions Electricity to grid Emissions Electricity to grid Emissions Electricity to grid Impacts at mid-point Climate Change, Acidification, PM, Photochemical Ozone 10

11 Results: Surface temperature Response 1. Power generation Note: Results obtained applying AGTP model formulations from IPCC AR5, Including WMGHG (CO 2, CH 4, N 2 O) and NTCF (NOx, CO, NMVOC, SO 2, BC, OC). Excluding infrastructure impacts. Surface Temperature Response (instantaneous) [K] [x ] (Case 1) Forest residues - Branches Cattle Slurry biogas - Close Digestate EU-27 Mix Straw - EU Cattle Slurry biogas - Open Digestate EU-27 Mix FR el. ST el. Biogas OD Biogas CD Years Surface Temperature Response (instantaneous) [K] [x ] Forest residues - Branch Cattle Slurr Open Dige Cattle Slu Close Y

12 Results: Surface temperature Response 1. Power generation: WMGHG vs. NTCF (straw electricity)

13 Results: Surface temperature Response 2. Heat generation (only pellet stove) Surface Temperature Response (instantaneous) [K] 6.0 [x ] Coal Fuel Oil NG Bioenergy (Branches) Bioenergy (2.7%) Bioenergy (20%) Range decay (2% - 40%) 2% yr -1 (a) 2.7% yr % yr -1 20% yr -1 40% yr Years Surface Temperature Response (instantaneous) [K] 2.0 [x ] (b) 40% yr % 20% yr -1

14 Results: Surface temperature Response 2. Heat generation (WMGHG vs NTCF vs Albedo) (a) NG - Net Bio - Net NG - WMGHG Bio - WMGHG NG - NTCF Bio - NTCF Albedo change Net CO 2 biomass November 2015 Surface Temperature Response (cumulative) [K yr] 75 [x ] NG - Net Bio - Net NG - WMGHG Bio - WMGHG NG - NTCF Bio - NTCF Albedo change Net CO 2 biomass (b) Years

15 Stress test - Variability: Logging residues Note: Results obtained applying AGTP formulations from IPCC AR5, Including WMGHG (CO 2, CH 4, N 2 O) and NTCF (NOx, CO, NMVOC, SO 2, BC, OC). Excluding infrastructure impacts. Decay rates (k) apply in an exponential decay of forest residues on the forest floor: M(t) = M(0) * Exp(-k * t) Bioenergy system POWER GENERATION 12.0 [x ] Surface Temperature Response (instantaneous) [K] EU-28 Mix Bioenergy (Branches %) Bioenergy (5.2%) Bioenergy (20%) Range decay (2% - 40%) 2% yr % yr -1 20% yr -1 (Case 1) 11.5% yr -1 40% yr Years 4.5 [x ] (Case 2) (2.7% in the case of FR-pellets to pellet stove vs. NG boiler) Surface Temperature Response (instantaneous) [K] 20% yr -1 40% yr Ye

16 Stress test - Sensitivity : straw Note: Results obtained applying AGTP formulations from IPCC AR5, Including WMGHG (CO 2, CH 4, N 2 O) and NTCF (NOx, CO, NMVOC, SO 2, BC, OC). Excluding infrastructure impacts. Scenario 1) No additional mineral fertilization to compensate nutrients removal by straw (N, P, K) + N2O credits for removal of straw-n; Scenario 2) Additional mineral fertilization and no loss of yield; Scenario 3) Additional mineral fertilization and loss of 8% of long-term yield accounted with an iluc factor (Ref: IFPRI for cereals) + additional emissions for cultivation of the additional wheat Bioenergy system POWER GENERATION Surface Temperature Response (instantaneous) [K] [x ] EU-27 Mix ST el. - EU (base case) ST el. - EU - Scenario 1 ST el. - EU - Scenario 2 ST el. - EU - Scenario 3 (Case 1) EU-27 Mix Scenario 3 Scenario 2 Straw - EU Scenario Years Surface Temperature Response (instantaneous) [K] [x ] EU-27 Mix ST el. - EU (base ca ST el. - EU - Scenar ST el. - EU - Scenar ST el. - EU - Scenar Straw - EU Scenario Year

17 Other environmental impacts are relevant - example for forest residues to heat (Giuntoli et al. 2015) NG Boiler NH 3 NO x SO 2 9.1E-5 (a) NG Boiler Collection Transport Pellet mill End-use NG supply (b) Pellets (PS) Chips (DH) 2.2E-4 1.9E-4 Pellets (PS) Chips (DH) Logs (AS) 1.4E-4 Logs (AS) x x x x x Acidification Potential [mol H + eq. MJ-1 ] heat Acidification Potential (% of total) NG Boiler Pellets (PS) Chips (DH) NH 3 NO x SO 2 PM E-6 4.8E-5 1.9E-5 (c) NG Boiler Pellets (PS) Chips (DH) (d) Logs (AS) 2.6E-4 Logs (AS) x x x x Particulate matter [kg PM 2.5 eq. MJ -1 ] heat Particulate matter (% of total) NG Boiler Pellets (PS) NO x SO 2 NMVOC CO 8.3E-5 2.3E-4 (e) NG Boiler Pellets (PS) (f) Chips (DH) 2.1E-4 Chips (DH) Logs (AS) 9.1E-4 Logs (AS) x x x x Photochemical ozone formation [kg NMVOC 2.5 eq. MJ -1 ] heat Photochemical ozone formation (% of total) 19

18 Example of electricity generation from biogas from manure, maize and sorghum

19 Non-standard environmental impacts We have looked only qualitatively into potential impacts (or benefits) of some biomass residues removal. (Baselines = left on soil except prunings) Total GHG emissions compared to fossil fuels SOC Nutrients Pool Soil health / fertility N 2 O, CH 4 Pests, Displace Biodiversity Water ment diseases, odours effects Straw Pruning residues Manure No alternative use Forest residues Short term: Long- No alternative use

20 Conclusions - results Supply GHG savings >75% for all the analyzed pathways; Application of AGTP helps to interpret transient emission profiles: by 2100 all bioenergy pathways considered achieve a mitigation of temperature increase compared to the chosen fossil reference, albeit of different magnitude depending on the feedstock and pathway considered; Caution is needed when exploiting logging residues with slow decay rates; Biogas systems using slurry can mitigate global warming in absolute terms by decreasing GHG emissions from common agricultural practices; WMGHG dominate for FR but NTCF mitigate fully the warming for straw for the first 20 years and continue to mitigate about 50% of the total long-term impact; Additional environmental impacts usually worse than fossil alternative 9 November 2015 (eutrophication, PM, biodiversity etc ) 22

21 CONCLUSIONS - methodology - Results that focus only on supply-chain GHG emissions and WMGHG are giving an incomplete information, e.g.: excluding land use and C-stocks will largely underestimate total STR Non considering NTCF overestimates warming impacts in some bioenergy systems. and biogeophysical forcers are also important in certain systems (e.g. albedo in boreal, snow-covered forests) - In addition to proper system design, Advanced A-LCA can still provide precious information about the potential impacts of bioenergy systems, avoiding the use of complex and time-consuming tools such as large integrated modelling suites. 09/11/

22 Giuntoli et al., 2015, JRC Database of input data and GHG emissions for solid and gaseous biomass for power and heat: n/solid-and-gaseousbioenergy-pathwayspbldna27215 Thank you for your Agostini et al., Environmentally Sustainable Biogas? The Key Role of Manure Co-Digestion with Energy Crops, Energies 8 (2015) attention! JEC Well-to-Wheels study: ut-jec/downloads Giuntoli et al., Domestic heating from forest logging residues: environmental risks and benefits, Journal of Cleaner Production 99 (2015) Alternative Fuels project: