Forest Carbon Sequestration, Pathogens and the Costs of the EU’s 2050 Climate Targets
Abstract
:1. Introduction
2. Structure of the Dynamic Optimization Model
- The cost of delaying harvest and the opportunity cost of land. Relatively low net benefits from harvest and the opportunity cost of land, give high value of carbon sequestration.
- Costs and depreciation of investments in reductions of fossil fuels. High cost and depreciation give high value.
- Discount rates, which implies lower future costs of all emission mitigation options and thereby delays costly actions. High discount rate generates low abatement cost and value of carbon sequestration.
- Impact of pathogens, where high impacts generate relatively low effective areas, i.e., , which reduces the carbon sink contribution and thereby its value.
- Forest growth, where an increase raises the value of carbon sequestration as higher growth promotes carbon sequestration.
3. Description of Data
3.1. Forest Carbon Sink and Emissions from Fossil Fuels
3.2. Costs of Carbon Sink and Emission Reduction
3.3. Emission Targets, Constraints and Discount Rate
4. Results: Calculated Value of Carbon Sink and Costs of Pathogens
4.1. Value of Carbon Sink from Forest
4.2. The Cost of Pathogens
5. Discussion
6. Conclusions
Author Contributions
Funding
Conflicts of Interest
Appendix A. Derivation of First-Order Conditions for Cost Minimization
Appendix B
Country | Forest Area 1000 ha a | % of Total Forest Area Affected by Pathogen c | Forest Carbon Sink Mill Ton CO2e d | CO2 Emissions from Fossil Fuels j | Agricultural Area, 1000 ha b | Carbon Sequestration from Afforestation, kton/ha j |
---|---|---|---|---|---|---|
AT, Austria | 3869 | 2.3 d | 5.14 | 61 | 3358 | 1.57 |
BE, Belgium | 683 | 0.3 e | 3.65 | 138 | 1828 | 6.34 |
BG, Bulgaria | 3823 | 3.0 | 10.40 | 49 | 5328 | 2.96 |
CY, Cyprus | 173 | 3.6 | 0.18 | 8 | 302 | 1.04 |
CZ, Check | 2667 | 2.3 | 8.76 | 109 | 4283 | 3.20 |
DE, Germany | 11,419 | 2.4 | 34.95 | 717 | 19,421 | 3.02 |
DK, Denmark | 544 | 0.6 | 5.90 | 45 | 2939 | 10.69 |
EE, Estonia | 2232 | 0.2 | 6.34 | 18 | 1333 | 2.52 |
ES, Spain | 18,418 | 8.4 f | 33.78 | 291 | 20,090 | 1.65 |
FI, Finland | 22,218 | 0.1 | 35.70 | 57 | 3477 | 2.10 |
FR, France | 16,989 | 2.4 g | 47.31 | 333 | 30529 | 2.99 |
GR, Greece | 4054 | 0.02 | 2.52 | 91 | 4577 | 0.54 |
HU, Hungary | 2069 | 8.2 | 2.97 | 46 | 5916 | 1.26 |
IE, Ireland | 754 | 0.3 e | 4.30 | 37 | 4384 | 6.42 |
IT, Italy | 9297 | 8.4 | 30.05 | 392 | 14,100 | 2.90 |
LT, Lithuania | 2180 | 2.3 | 11.07 | 12 | 3552 | 5.39 |
LU, Luxembourg | 87 | 0.3 | 0.47 | 11 | 135 | 5.31 |
LV, Latvia | 3356 | 2.3 h | 16.14 | 8 | 2411 | 5.20 |
NL, the Netherlands | 376 | 0.3 | 2.42 | 201 | 2288 | 6.27 |
PL, Poland | 9435 | 1.8 | 30.93 | 303 | 17,513 | 3.45 |
PT, Portugal | 3182 | 15.2 | 8.18 | 51 | 3136 | 3.75 |
RO, Romania | 6861 | 19.0 | 23.28 | 80 | 14,177 | 3.22 |
SE, Sweden | 28,073 | 1.2 | 47.01 | 50 | 4319 | 1.49 |
SI, Slovenia | 1248 | 0.6 g | 11.96 | 15 | 635 | 11.42 |
SK, Slovakia | 1940 | 0.6 | 6.53 | 31 | 2260 | 2.89 |
UK, United Kingdom | 3144 | 0.3 e | 10.47 | 479 | 13,850 | 3.39 |
Total | 159,091 | 2.4 | 400.91 | 3634 | 186,141 |
Country | Conversion Factor in the Reference Case When θ = 0.5 and δ = 0.03 | Conversion Factor When θ = 0 and δ = 0.045 | ||
---|---|---|---|---|
Initial | In 2050 | Initial | In 2050 | |
AT, Austria | 0.989 | 0.968 | 0.977 | 0.893 |
BE, Belgium | 0.999 | 0.996 | 0.997 | 0.986 |
BG, Bulgaria | 0.985 | 0.958 | 0.970 | 0.860 |
CY, Cyprus | 0.982 | 0.949 | 0.964 | 0.832 |
CZ, Czech | 0.989 | 0.968 | 0.977 | 0.893 |
DE, Germany | 0.988 | 0.966 | 0.976 | 0.888 |
DK, Denmark | 0.997 | 0.992 | 0.994 | 0.972 |
EE, Estonia | 0.999 | 0.997 | 0.998 | 0.991 |
ES, Spain | 0.958 | 0.882 | 0.916 | 0.608 |
FI, Finland | 1.000 | 0.999 | 0.999 | 0.995 |
FR, France | 0.988 | 0.966 | 0.976 | 0.888 |
GR, Greece | 1.000 | 0.999 | 1.000 | 0.999 |
HU, Hungary | 0.959 | 0.885 | 0.918 | 0.617 |
IE, Ireland | 0.999 | 0.996 | 0.997 | 0.986 |
IT, Italy | 0.958 | 0.882 | 0.916 | 0.608 |
LT, Lithuania | 0.989 | 0.968 | 0.977 | 0.893 |
LU, Luxembourg | 0.999 | 0.996 | 0.997 | 0.986 |
LV, Latvia | 0.989 | 0.968 | 0.977 | 0.893 |
NL, the Netherlands | 0.999 | 0.996 | 0.997 | 0.986 |
PL, Poland | 0.991 | 0.975 | 0.982 | 0.916 |
PT, Portugal | 0.924 | 0.786 | 0.848 | 0.291 |
RO, Romania | 0.905 | 0.733 | 0.810 | 0.113 |
SE, Sweden | 0.994 | 0.983 | 0.988 | 0.944 |
SI, Slovenia | 0.997 | 0.992 | 0.994 | 0.972 |
SK, Slovakia | 0.997 | 0.992 | 0.994 | 0.972 |
UK, United Kingdom | 0.999 | 0.996 | 0.997 | 0.986 |
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No Sink | With Sink | ||
---|---|---|---|
All Options | Only Afforestation | ||
Total Cost | 2266 | 1850 | 1922 |
Value of Carbon Sink | 416 | 344 |
Equivalence Area | Dispersal Rate | Equivalence and Dispersal Rate | ||||
---|---|---|---|---|---|---|
θ = 0.75 | θ = 0 | δ = 0.015 | δ = 0.045 | θ = 0.75 | θ = 0 | |
δ = 0.015 | δ = 0.045 | |||||
Value of Carbon Sequestration | 464 | 315 | 446 | 373 | 483 | 224 |
Cost of Pathogen | 57 | 206 | 75 | 148 | 38 | 297 |
Discount Rate Is 0.01 | Depreciation Rate Is 0.067 | 33% Increase in Cost of Afforestation | 33% Increase in Intrinsic Growth Rate and Carrying Capacity | |
---|---|---|---|---|
Value of Carbon Sink | 564 | 150 | 387 | 822 |
Costs of Pathogens | 53 | 80 | 98 | 52 |
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Gren, I.-M.; Aklilu, A.Z.; Elofsson, K. Forest Carbon Sequestration, Pathogens and the Costs of the EU’s 2050 Climate Targets. Forests 2018, 9, 542. https://doi.org/10.3390/f9090542
Gren I-M, Aklilu AZ, Elofsson K. Forest Carbon Sequestration, Pathogens and the Costs of the EU’s 2050 Climate Targets. Forests. 2018; 9(9):542. https://doi.org/10.3390/f9090542
Chicago/Turabian StyleGren, Ing-Marie, Abenezer Zeleke Aklilu, and Katarina Elofsson. 2018. "Forest Carbon Sequestration, Pathogens and the Costs of the EU’s 2050 Climate Targets" Forests 9, no. 9: 542. https://doi.org/10.3390/f9090542