Agriculture and Land-Use in GCAM 3.0

Transcription

1 Agriculture and Land-Use in GCAM 3.0 Marshall Wise, Kate Calvin, Page Kyle, Patrick Luckow May 24, 2011 GTSP College Park, MD 1 PNNL-SA-80172

2 Outline! Model Structure & Assumptions! What underlying assumptions changed when we updated the Agriculture & Land Use component of GCAM?! Results! How did the model update affect model results?! We ll focus on the original RCP4.5 and an updated version! Three categories of changes:! Data updates, unrelated to model structure, that affect results! Model structure updates that improve spatial specificity, but don t change results at the 14 region or world level! Model structure updates that change results! New Functionality! What can we do with the new model that we couldn t do before? 2

3 3 Model Structure

4 The GCAM Model Inputs Economy Supply/Demand Markets Emissions Climate Regional Resource Bases Regional Energy Conversion Technologies Energy Demand Technologies Energy Supply Coal, Gas, Oil Renewables Electricity Hydrogen Energy Demand Transportation Buildings Industry The Energy System Energy Markets Fossil fuel prices Electricity prices Hydrogen prices Energy System Emissions Climate Regional Labor Force Economy Regional GDP Policy Markets Taxes Commercial Subsidies Biomass Regulation Climate Concentrations Radiative Forcing Global Mean Temperature Rise Sea Level Rise 4 Regional Labor Productivity Technologies Regional Land Characteristics Agricultural Demand Crops Livestock Forest Products Agricultural Supply Crops Livestock Forest Products Bioenergy Land Use & Land Cover Agricultural Markets Crops prices Livestock prices Forest Product prices Bioenergy prices Agriculture & Land Use Agriculture & Land Related Emissions

5 Assumptions in the Old AgLU (2008-present)! The world was divided into 14 regions! Farmers allocate land across a variety of uses in order to maximize profit! There is a distribution of profits for each land type across each of the 14 regions! The actual share of land allocated to a particular use is the probability in which that land type has the highest profit! The variation in profit rates was due to variation in yields! As land expands, yield decreases! Variable cost was fixed within each region 5

6 Updating AgLU: Goals and Strategies! Goal:! Represent more geospatially and physically-defined characteristics in our economic modeling of land! Strategy:! Model economic decisions on smaller units of land where characteristics could be assumed to be uniform! E.g. Physical characteristics such as crop yield for a given technology, carbon densities of each use of land.! Approach:! Model economic land use in up to 18 AEZs in each of our GCAM regions! Data, calibration, land use modeling at the regional AEZ level! Markets remain at regional or global levels! Challenges:! A LOT more data, model decision variables 6

7 Old AgLU vs. New AgLU: Assumptions Old AgLU! The world was divided into 14 regions! Farmers allocate land across a variety of uses in order to maximize profit! There is a distribution of profits for each land type across each of the 14 regions! The actual share of land allocated to a particular use is the probability in which that land type has the highest profit! The variation in profit rates was due to variation in yields! As land expands, yield decreases! Variable cost was fixed within each regions New AgLU! The world is divided into 151 regions! Farmers allocate land across a variety of uses in order to maximize profit! There is a distribution of profits for each land type across each of the 151 regions! The actual share of land allocated to a particular use is the probability in which that land type has the highest profit! The variation in profit rates is due to variation in costs! As land expands, variable cost increases! Yield is fixed within each region 7

8 8 Agro-ecological zone approach

9 9 Results Comparison

10 Representative Concentration Pathways (RCPs)! The RCPs are meant to serve as input for climate and atmospheric chemistry modeling as part of the preparatory phase for the development of new scenarios for the IPCC's Fifth Assessment Report and beyond.! They are based on selected scenarios from four modeling teams/ models (NIES/AIM, IIASA/MESSAGE, PNNL/GCAM, and PBL/ IMAGE).! The RCPs are not new, fully integrated scenarios (i.e., they are not a complete package of socioeconomic, emissions, and climate projections). They are consistent sets of projections of only the components of radiative forcing that are meant to serve as input for climate modeling, pattern scaling, and atmospheric chemistry modeling. Taken from the RCP Database: 10

11 The RCP4.5! PNNL/JGCRI was charged with completing the RCP4.5.! The RCP4.5 stabilizes at 4.5 W/m 2 in 2100, without exceeding the target.! Limiting radiative forcing to 4.5 W/m 2 requires an explicit climate change policy. The RCP4.5 employs a carbon price that is applied to all regions and emissions sources (including land use).! The original RCP4.5 was completed in Spring 2009 and delivered to the climate modeling community shortly after.! For the iesm project, we are updating the RCP4.5 to use the new AgLU model.! This scenario is based on: Full Disclosure:! Clarke et al. (2007). CCSP Synthesis and Assessment Product 2.1, Part A: Scenarios of Greenhouse Gas Emissions and Atmospheric Concentrations. U.S. Government Printing The RCP4.5 Office. Washington, was constructed DC. using a version of GCAM from July 7, 2009.! Wise et al. (2009). Implications of Limiting CO2 Concentrations for Land Use and Energy. AgLU is Science not the 324: only change that has occurred in the nearly 2 years since the! completion Further documentation: of the RCP. However, we will focus on changes to AgLU only in this presentation.! Thomson et al. (2010). "Climate mitigation and the future of tropical landscapes." Proceedings of the National Academy of Sciences of the United States of America 107(46): ! Thomson et al. (forthcoming) RCP4.5: A Pathway for Stabilization of Radiative Forcing by Climatic Change. 11

12 Results Comparison Case 1: updating input assumptions unrelated to model structure impacts model results 12

13 Total Radiative Forcing!"# $% $"!# ("$# ("!# '"$# '"!# &"$# &"!# %"$# %"!#,-.#!"$# /01#!"!# &!!$# &!&!# &!'$# &!$!# &!)$# &!*!# &!+$# 13

14 Radiative Forcing From Kyoto Gases!"# $% $"!# ("$# ("!# '"$# '"!# &"$# &"!# %"$# %"!#,-.#!"$# /01#!"!# &!!$# &!&!# &!'$# &!$!# &!)$# &!*!# &!+$# 14

15 Radiative Forcing From Kyoto Gases Official RCP4.5 Updated 4.5 $"!# $"!# ("$# ("!# '"$#,-./010# 2&3# 45(# 43&# 0.9 W/m 2 ("$# ("!# '"$#,-./010# 2&3# 45(# 43&# 1.1 W/m 2 '"!# '"!#!"# $% &"$#!"# $% &"$# &"!# &"!# %"$# %"$# %"!# %"!#!"$#!"$#!"!# &!!$# &!&!# &!'$# &!$!# &!)$# &!*!# &!+$#!"!# &!!$# &!&!# &!'$# &!$!# &!)$# &!*!# &!+$# 15

16 Global Beef Consumption ("'# ("&# ("%#,-.# /01#!"#$%&'())*&+&,-& ("$# ("!#!"'#!"&#!"%#!"$#!"!# $!!)# $!$!# $!*)# $!)!# $!&)# $!'!# $!+)# 16

17 The Effect of Future Meat Consumption Assumptions on Stabilizing at 4.5 W/m 2 ("'# ("&# ("%# Global Beef Consumption!"#$%&'())*&+&,-& ("$# ("!#!"'#!"&#!"%#!"$#,-.# /01# /01#234#,-.#50678.#!"!# $!!)# $!$!# $!*)# $!)!# $!&)# $!'!# $!+)# 17

18 Radiative Forcing From Kyoto Gases Official RCP4.5 New Ag, Old Food Demand $"!# $"!# ("$#,-./010# 2&3# ("$#,-./010# 2&3# ("!# 45(# ("!# 45(# '"$# 43&# '"$# 43&# '"!# '"!#!"# $% &"$#!"# $% &"$# &"!# &"!# %"$# %"$# %"!# %"!#!"$#!"$#!"!# &!!$# &!&!# &!'$# &!$!# &!)$# &!*!# &!+$#!"!# &!!$# &!&!# &!'$# &!$!# &!)$# &!*!# &!+$# 18

19 Results Comparison Case 2: regional specificity adds spatial resolution, but does not change overall model results 19

20 Global Forest Cover )"!# ("!# '"!#!"##"$%&'(& &"!# %"!# $"!#,-.# /01#!"!# %!!(# %!%!# %!&(# %!(!# %!)(# %!*!# %!+(# 20

21 Canadian Forest Cover!"##"$%&'(& $"!#!",#!"+#!"*#!")#!"(#!"'#!"&#!"%# -./#!"$# 012#!"!# %!!(# %!%!# %!&(# %!(!# %!)(# %!+!# %!,(# 21

22 Canadian Forest Cover:

23 Results Comparison Case 3: regional specificity changes overall model results 23

24 The Effect of a CO 2 Price on Agricultural Production! Imposing a carbon price on the energy system increases demand for bioenergy, and thus, increases demand for biomass production on land! Imposing a carbon price on the terrestrial system increases incentives to hold carbon stocks, and thus, increases forest land cover! Both result in increased competition for land, driving up the price of land, and forcing economic specialization! As a result, regions focus on producing what they grow best and trading to get anything else they need! Comparative Advantage (see Ricardo, 1817) 24

25 Crop land in the United States $!!"#,!"# +!"# *!"# )!"# (!"# '!"# &!"# %!"# $!"# -./01# # 9:;/# <1./5=50:># 675>#!"#!""#$ %&'$ ()*$!"+#$ 25

26 Crop land in the United States in 2095 $!!"#,!"# +!"# *!"# )!"# (!"# '!"# &!"# %!"# -./01# # 9:;/# <1./5=50:># 675># $!"#!"#!"#$%!"#&%!"#'%!"#()%!"#((%!"#(*% 26