This module describes technical mitigation of GHG emissions. It allows to reduce GHG emissions by undertaking mitigation measures in exchange for additional mitigation costs. The technical mitigation measures include, for example, better spreader maintenance, feed additives or investments in animal waste management facilities. Please note that technical mitigation is possible only in the “on” module realization below. For simplicity, we considered only the effects of mitigation measure costs and emissions. Their direct consequences on biophysical values like yields or water requirements is ignored at the moment.
Mitigation costs are estimated using marginal abatement cost curves (MACCs). The curves are applied on the original emissions before technical mitigation (btm), and reduce them by a certain percentage in exchange for additional costs. The MACCs used in this module are based on the data from Lucas et al. (2007).
| Description | Unit | A | B | |
|---|---|---|---|---|
| im_pollutant_prices (t_all, i, pollutants) |
Certificate prices for N2O-N CH4 CO2-C used in the model | \(USD_{05MER}/Mg\) | x | |
| vm_btm_reg (i, emis_source, pollutants) |
Regional emissions before technical mitigation | \(Tg/yr\) | x |
| Description | Unit | |
|---|---|---|
| im_maccs_mitigation (t, i, emis_source, pollutants) |
Technical mitigation of GHG emissions | \(percent\) |
| vm_maccs_costs (i) |
Costs of technical mitigation of GHG emissions | \(10^6 USD_{95MER}/yr\) |
Technical mitigation is not considered in this realization.
Accordingly, this implementation sets the cost of technical mitigation of GHG emissions (vm_maccs_costs) to zero. Please see and compare this with the equation in the next realization.
vm_maccs_costs.fx(i) = 0;
im_maccs_mitigation(t,i,emis_source,pollutants) = 0;Limitations It is unrealistic to assume no technical mitigation attempts.
Unlike the previous realization, this implementation allows for the possibility that non-CO2 emissions can be reduced by technical mitigation at additional costs. The following MACC data sets are available in this module: Lucas et al. (2007) (PBL_2007) and Harmsen et al. (2019) (PBL_2019).
Therefore, the equation below is used to estimate the mitigation costs. It is simply calculated as a product of GHG emissions before technical mitigation (vm_btm_reg), and the costs per unit of technical mitigation (p57_maccs_costs_integral). The mitigation costs will go into the objective function of the model.
\[\begin{multline*} vm\_maccs\_costs(i2) \geq \sum_{ct,emis\_source}\left( p57\_maccs\_costs\_integral(ct,i2,emis\_source,"n2o\_n\_direct") \cdot vm\_btm\_reg(i2,emis\_source,"n2o\_n\_direct") + p57\_maccs\_costs\_integral(ct,i2,emis\_source,"ch4") \cdot vm\_btm\_reg(i2,emis\_source,"ch4") \right) \end{multline*}\]
Limitations The data set PBL_2007 is outdated and only kept for backward compatibility
| Description | Unit | A | B | |
|---|---|---|---|---|
| f57_maccs_ch4 (t_all, i, maccs_ch4, maccs_steps) |
CH4 MACC from Image model | \(percent\) | x | |
| f57_maccs_n2o (t_all, i, maccs_n2o, maccs_steps) |
N2O MACC from Image model | \(percent\) | x | |
| i57_mac_step_ch4 (t, i) |
Helper to map CH4 prices and maccs_steps | \(1\) | x | |
| i57_mac_step_n2o (t, i) |
Helper to map N2O prices and maccs_steps | \(1\) | x | |
| p57_maccs_costs_integral (t, i, emis_source, pollutants) |
Costs of technical mitigation | \(USD_{95MER}/Tg N CH4 C\) | x | |
| q57_total_costs (i) |
Calculation of total costs of technical mitigation | \(10^6 USD_{95MER}/yr\) | x | |
| s57_step_length | Step length in MACC data | \(yr\) | x |
| description | |
|---|---|
| awms | animal waste management systems |
| ct(t) | Current time period |
| emis_source | Emission sources |
| emis_source_awms_ch4(emis_source) | subset awms emissions |
| emis_source_awms_manure_n2o(emis_source) | subset awms_manure_n2o |
| emis_source_ent_ferm_ch4(emis_source) | subset ent_ferm emissions |
| emis_source_inorg_fert_n2o(emis_source) | subset inorg_fert_n2o emissions |
| emis_source_rice_ch4(emis_source) | subset rice emissions |
| i | all economic regions |
| i2(i) | World regions (dynamic set) |
| maccs_ch4 | ch4 mitigation categories with MACCS |
| maccs_n2o | n2o mitigation categories with MACCS |
| maccs_steps | maccs tax level steps |
| pollutants(pollutants_all) | subset of pollutants_all that can be taxed |
| t_all(t_ext) | 5-year time periods |
| t(t_all) | Simulated time periods |
| type | GAMS variable attribute used for the output |
Benjamin Leon Bodirsky, Florian Humpenoeder
Harmsen, J. H. M., Detlef P. van Vuuren, Dali R. Nayak, Andries F. Hof, Lena Höglund-Isaksson, Paul L. Lucas, Jens B. Nielsen, Pete Smith, and Elke Stehfest. 2019. “Long-Term Marginal Abatement Cost Curves of Non-CO2 Greenhouse Gases.” Environmental Science & Policy 99 (September): 136–49. https://doi.org/10.1016/j.envsci.2019.05.013.
Lucas, Paul L., Detlef P. van Vuuren, Jos G. J. Olivier, and Michel G. J. den Elzen. 2007. “Long-Term Reduction Potential of Non-Co2 Greenhouse Gases.” Environmental Science & Policy 10 (2): 85–103. https://doi.org/https://doi.org/10.1016/j.envsci.2006.10.007.