Merge pull request magpiemodel#604 from flohump/f_peatland6

New realization in peatland module

CHANGELOG.md

@@ -17,6 +17,8 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
 ### added
 - **18_residues** Included cluster-level residue realization, for cluster-level production of residues (but balancing of recycling and burning budgets remains at region-level, for computational lightness)
 - **14_yields/config** Added option for considering impacts of land degradation on yields. If `s14_degradation` is switched to 1, MAgPIE will include cluster-specific information on the state of nature's contributions to people relevant for yields `./modules/14_yields/input/f14_yld_ncp_report.cs3`.
+- **58_peatland** added realization "v2" with updated peatland map and GHG emission factors
+- **32_forestry** new interface `vm_land_forestry`
 
 ### removed
 -

config/default.cfg

@@ -1524,8 +1524,14 @@ cfg$gms$s57_maxmac_ch4_awms  <- -1   # def = -1
 
 # ***---------------------    58_peatland   ------------------------------------
 # * (off):  Peatland area and associated GHG emissions are assumed zero
-# * (on):   Peatland area is initialized with present-day degraded and intact peatland.
-# *       GHG emissions are calculated using IPCC Tier 1 emission factors (2013 Wetland supplement).
+# * (on):   Peatland area is initialized with degraded and intact peatland for the year 2015, 
+# *         and projected into the future based on changes in managed land.
+# *         GHG emissions are calculated using IPCC Tier 1 emission factors (2013 Wetland supplement).
+# * (v2):   Peatland area is initialized with degraded and intact peatland area for the year 2020,  
+# *         and projected into the future based on changes in managed land.
+# *         For boreal and tropical climates, GHG emissions are calculated using emission 
+# *         factors from the IPCC 2013 Wetland supplement. For temperate climates, more recent 
+# *         estimates from Tiemeyer et al 2020 are used.
 cfg$gms$peatland  <- "on"                     # def = on
 
 # * peatland rewetting
@@ -1553,9 +1559,9 @@ cfg$gms$s58_cost_degrad_recur  <- 0   # def = 0
 # * High costs make sure that the balance variables are only used as a last resort.
 cfg$gms$s58_cost_balance  <- 1e+06   # def = 1e+06
 
-# * Switch for fixing peatland area to 2015 levels from 1995 onwards until the given year
-# * Note: The initial peatland area is only available for the year 2015.
-# *     Fixing the peatland area in previous time steps to 2015 levels provides a better
+# * Switch for fixing peatland area between 1995 and the year given by s58_fix_peatland
+# * Note: Depending on the realisation, the initial peatland area is only available for the year 2015 (`on`) or 2020 (`v2`).
+# *     Fixing  peatland area in previous time steps provides a better
 # *     proxy for GHG emissions from peatlands than assuming no peatland area.
 cfg$gms$s58_fix_peatland  <- 2015   # def = 2015
 

literature.bib

@@ -881,6 +881,35 @@ @article{humpenoder_peatland_2020
   pages = {104093},
 }
 
+
+@article{leifeld_2018,
+    title = {The underappreciated potential of peatlands in global climate change mitigation strategies},
+    volume = {9},
+    copyright = {2018 The Author(s)},
+    issn = {2041-1723},
+    url = {https://www.nature.com/articles/s41467-018-03406-6},
+    doi = {10.1038/s41467-018-03406-6},
+    abstract = {Human activity, such as draining and mining of peatlands, is transforming these long-term carbon sinks into sources. Here, the authors assess current and future greenhouse gas (GHG) emissions from degrading peatlands and estimate the magnitude of potential GHG savings that could be achieved by restoring them.},
+    language = {en},
+    number = {1},
+    urldate = {2018-05-11},
+    journal = {Nature Communications},
+    author = {Leifeld, J. and Menichetti, L.},
+    month = mar,
+    year = {2018},
+    pages = {1071},
+}
+
+
+@book{IPCC_wetland_2013,
+    address = {Switzerland},
+    title = {2013 {Supplement} to the 2006 {IPCC} {Guidelines} for {National} {Greenhouse} {Gas} {Inventories}: {Wetlands}},
+    url = {http://www.ipcc-nggip.iges.or.jp/public/wetlands/},
+    publisher = {IPCC},
+    editor = {Hiraishi, T and Krug, T and Tanabe, K and Srivastava, N and Baasansuren, J and Fukuda, M and Troxler, T.G.},
+    year = {2014},
+}
+
 @article{valin_fooddemand_2013,
   title = {The future of food demand: understanding differences in global economic models},
   issn = {1574-0862},
@@ -1472,3 +1501,85 @@ @article{olson_biome_2001
   year = {2001},
   pages = {933--938},
 }
+
+
+@article{tiemeyer_peatland_2020,
+    title = {A new methodology for organic soils in national greenhouse gas inventories: {Data} synthesis, derivation and application},
+    volume = {109},
+    issn = {1470160X},
+    shorttitle = {A new methodology for organic soils in national greenhouse gas inventories},
+    url = {https://linkinghub.elsevier.com/retrieve/pii/S1470160X19308325},
+    doi = {10.1016/j.ecolind.2019.105838},
+    abstract = {Drained organic soils are large sources of anthropogenic greenhouse gases (GHG) in many European and Asian countries. Therefore, these soils urgently need to be considered and adequately accounted for when attempting to decrease emissions from the Agriculture and Land Use, Land Use Change and Forestry (LULUCF) sectors. Here, we describe the methodology, data and results of the German approach for measurement, reporting and verification (MRV) of anthropogenic GHG emissions from drained organic soils and outline ways forward towards tracking drainage and rewetting. The methodology was developed for and is currently applied in the German GHG inventory under the United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol.},
+    language = {en},
+    urldate = {2023-06-19},
+    journal = {Ecological Indicators},
+    author = {Tiemeyer, Bärbel and Freibauer, Annette and Borraz, Elisa Albiac and Augustin, Jürgen and Bechtold, Michel and Beetz, Sascha and Beyer, Colja and Ebli, Martin and Eickenscheidt, Tim and Fiedler, Sabine and Förster, Christoph and Gensior, Andreas and Giebels, Michael and Glatzel, Stephan and Heinichen, Jan and Hoffmann, Mathias and Höper, Heinrich and Jurasinski, Gerald and Laggner, Andreas and Leiber-Sauheitl, Katharina and Peichl-Brak, Mandy and Drösler, Matthias},
+    month = feb,
+    year = {2020},
+    pages = {105838},
+}
+
+
+@article{humpenoeder_overcoming_2022,
+    title = {Overcoming global inequality is critical for land-based mitigation in line with the {Paris} {Agreement}},
+    volume = {13},
+    copyright = {2022 The Author(s)},
+    issn = {2041-1723},
+    url = {https://www.nature.com/articles/s41467-022-35114-7},
+    doi = {10.1038/s41467-022-35114-7},
+    abstract = {Transformation pathways for the land sector in line with the Paris Agreement depend on the assumption of globally implemented greenhouse gas (GHG) emission pricing, and in some cases also on inclusive socio-economic development and sustainable land-use practices. In such pathways, the majority of GHG emission reductions in the land system is expected to come from low- and middle-income countries, which currently account for a large share of emissions from agriculture, forestry and other land use (AFOLU). However, in low- and middle-income countries the economic, financial and institutional barriers for such transformative changes are high. Here, we show that if sustainable development in the land sector remained highly unequal and limited to high-income countries only, global AFOLU emissions would remain substantial throughout the 21st century. Our model-based projections highlight that overcoming global inequality is critical for land-based mitigation in line with the Paris Agreement. While also a scenario purely based on either global GHG emission pricing or on inclusive socio-economic development would achieve the stringent emissions reductions required, only the latter ensures major co-benefits for other Sustainable Development Goals, especially in low- and middle-income regions.},
+    language = {en},
+    number = {1},
+    urldate = {2022-12-02},
+    journal = {Nature Communications},
+    author = {Humpenöder, Florian and Popp, Alexander and Schleussner, Carl-Friedrich and Orlov, Anton and Windisch, Michael Gregory and Menke, Inga and Pongratz, Julia and Havermann, Felix and Thiery, Wim and Luo, Fei and v. Jeetze, Patrick and Dietrich, Jan Philipp and Lotze-Campen, Hermann and Weindl, Isabelle and Lejeune, Quentin},
+    month = dec,
+    year = {2022},
+    note = {Number: 1
+Publisher: Nature Publishing Group},
+    keywords = {Sustainability, Climate-change policy, Climate-change mitigation, Socioeconomic scenarios},
+    pages = {7453},
+}
+
+
+@article{mishra_forestry_2021,
+    title = {Estimating global land system impacts of timber plantations using {MAgPIE} 4.3.5},
+    volume = {14},
+    copyright = {All rights reserved},
+    issn = {1991-959X},
+    url = {https://gmd.copernicus.org/articles/14/6467/2021/},
+    doi = {10.5194/gmd-14-6467-2021},
+    abstract = {{\textless}p{\textgreater}{\textless}strong class="journal-contentHeaderColor"{\textgreater}Abstract.{\textless}/strong{\textgreater} Out of 1150 {\textless}span class="inline-formula"{\textgreater}Mha{\textless}/span{\textgreater} (million hectares) of forest designated primarily for production purposes in 2020, plantations accounted for 11 \% (131 {\textless}span class="inline-formula"{\textgreater}Mha{\textless}/span{\textgreater}) of this area and fulfilled more than 33 \% of the global industrial roundwood demand. However, adding additional timber plantations to meet increasing timber demand intensifies competition for scarce land resources between different land uses such as food, feed, livestock and timber production. Despite the significance of plantations with respect to roundwood production, their importance in meeting the long-term timber demand and the implications of plantation expansion for overall land-use dynamics have not been studied in detail, in particular regarding the competition for land between agriculture and forestry in existing land-use models.{\textless}/p{\textgreater} {\textless}p{\textgreater}This paper describes the extension of the modular, open-source land system Model of Agricultural Production and its Impact on the Environment (MAgPIE) using a detailed representation of forest land, timber production and timber demand dynamics. These extensions allow for a better understanding of the land-use dynamics (including competition for land) and the associated land-use change emissions of timber production.{\textless}/p{\textgreater} {\textless}p{\textgreater}We show that the spatial cropland patterns differ when timber production is accounted for, indicating that timber plantations compete with cropland for the same scarce land resources. When plantations are established on cropland, it causes cropland expansion and deforestation elsewhere. Using the exogenous extrapolation of historical roundwood production from plantations, future timber demand and plantation rotation lengths, we model the future spatial expansion of forest plantations. As a result of increasing timber demand, we show a 177 \% increase in plantation area by the end of the century ({\textless}span class="inline-formula"{\textgreater}+{\textless}/span{\textgreater}171 {\textless}span class="inline-formula"{\textgreater}Mha{\textless}/span{\textgreater} in 1995–2100). We also observe (in our model results) that the increasing demand for timber amplifies the scarcity of land, which is indicated by shifting agricultural land-use patterns and increasing yields from cropland compared with a case without forestry. Through the inclusion of new forest plantation and natural forest dynamics, our estimates of land-related {\textless}span class="inline-formula"{\textgreater}CO$_{\textrm{2}}${\textless}/span{\textgreater} emissions better match with observed data, in particular the gross land-use change emissions and carbon uptake (via regrowth), reflecting higher deforestation with the expansion of managed land and timber production as well as higher regrowth in natural forests and plantations.{\textless}/p{\textgreater}},
+    language = {English},
+    number = {10},
+    urldate = {2021-10-27},
+    journal = {Geoscientific Model Development},
+    author = {Mishra, Abhijeet and Humpenöder, Florian and Dietrich, Jan Philipp and Bodirsky, Benjamin Leon and Sohngen, Brent and P. O. Reyer, Christopher and Lotze-Campen, Hermann and Popp, Alexander},
+    month = oct,
+    year = {2021},
+    note = {Publisher: Copernicus GmbH},
+    pages = {6467--6494},
+}
+
+
+@article{mishra_timbercities_2022,
+    title = {Land use change and carbon emissions of a transformation to timber cities},
+    volume = {13},
+    copyright = {2022 The Author(s)},
+    issn = {2041-1723},
+    url = {https://www.nature.com/articles/s41467-022-32244-w},
+    doi = {10.1038/s41467-022-32244-w},
+    abstract = {Using engineered wood for construction has been discussed for climate change mitigation. It remains unclear where and in which way the additional demand for wooden construction material shall be fulfilled. Here we assess the global and regional impacts of increased demand for engineered wood on land use and associated CO2 emissions until 2100 using an open-source land system model. We show that if 90\% of the new urban population would be housed in newly built urban mid-rise buildings with wooden constructions, 106 Gt of additional CO2 could be saved by 2100. Forest plantations would need to expand by up to 149 Mha by 2100 and harvests from unprotected natural forests would increase. Our results indicate that expansion of timber plantations for wooden buildings is possible without major repercussions on agricultural production. Strong governance and careful planning are required to ensure a sustainable transition to timber cities even if frontier forests and biodiversity hotspots are protected.},
+    language = {en},
+    number = {1},
+    urldate = {2022-08-30},
+    journal = {Nature Communications},
+    author = {Mishra, Abhijeet and Humpenöder, Florian and Churkina, Galina and Reyer, Christopher P. O. and Beier, Felicitas and Bodirsky, Benjamin Leon and Schellnhuber, Hans Joachim and Lotze-Campen, Hermann and Popp, Alexander},
+    month = aug,
+    year = {2022},
+    note = {Number: 1
+Publisher: Nature Publishing Group},
+    keywords = {Forestry, Climate-change mitigation},
+    pages = {4889},
+}

modules/32_forestry/dynamic_feb21/declarations.gms

@@ -59,6 +59,7 @@ parameters
  p32_bii_coeff(type32,bii_class_secd,potnatveg)     bii coeff (1)
  p32_c_density_ac_fast_forestry(t_all,j,ac)         Carbon densities in plantations based on Braakhekke et al (tC per ha)
  p32_disturbance_loss_ftype32(t,j,type32,ac)        Loss due to disturbances in all plantation type forests (mio. ha)
+ pcm_land_forestry(j,type32)                        Forestry land (mio. ha)
 ;
 
 positive variables
@@ -73,6 +74,7 @@ positive variables
  v32_cost_establishment(i)                          Cost of establishment calculated at the current time step (mio. USD)
  v32_hvarea_forestry(j,ac)                          Harvested area from timber plantations (mio. ha)
  vm_prod_forestry(j,kforestry)                      Production of woody biomass from commercial plantations (mio. tDM per yr)
+ vm_land_forestry(j,type32)                         Forestry land (mio. ha)
  ;
 
 variables
@@ -104,6 +106,7 @@ equations
  q32_bv_aff(j,potnatveg)                           Biodiversity value for aff forestry land (Mha)
  q32_bv_ndc(j,potnatveg)                           Biodiversity value for ndc forestry land (Mha)
  q32_bv_plant(j,potnatveg)                         Biodiversity value for plantations (Mha)
+ q32_land_forestry(j,type32)                       Forestry land (Mha)
 ;
 
 
@@ -120,6 +123,7 @@ parameters
  ov32_cost_establishment(t,i,type)          Cost of establishment calculated at the current time step (mio. USD)
  ov32_hvarea_forestry(t,j,ac,type)          Harvested area from timber plantations (mio. ha)
  ov_prod_forestry(t,j,kforestry,type)       Production of woody biomass from commercial plantations (mio. tDM per yr)
+ ov_land_forestry(t,j,type32,type)          Forestry land (mio. ha)
  ov_cdr_aff(t,j,ac,aff_effect,type)         Expected bgc (CDR) and local bph effects of afforestation depending on planning horizon (mio. tC)
  oq32_cost_total(t,i,type)                  Total forestry costs constraint (mio. USD)
  oq32_land(t,j,type)                        Land constraint (mio. ha)
@@ -145,5 +149,6 @@ parameters
  oq32_bv_aff(t,j,potnatveg,type)            Biodiversity value for aff forestry land (Mha)
  oq32_bv_ndc(t,j,potnatveg,type)            Biodiversity value for ndc forestry land (Mha)
  oq32_bv_plant(t,j,potnatveg,type)          Biodiversity value for plantations (Mha)
+ oq32_land_forestry(t,j,type32,type)        Forestry land (Mha)
 ;
 *##################### R SECTION END (OUTPUT DECLARATIONS) #####################

modules/32_forestry/dynamic_feb21/equations.gms

@@ -56,6 +56,9 @@ sum(ac_est, v32_land(j2,"aff",ac_est)) =l= sum(ac, v32_land(j2,"aff",ac)) - sum(
  q32_land(j2) ..
  vm_land(j2,"forestry") =e= sum((type32,ac), v32_land(j2,type32,ac));
 
+ q32_land_forestry(j2,type32) ..
+ vm_land_forestry(j2,type32) =e= sum(ac, v32_land(j2,type32,ac));
+
 *' The constraint `q32_aff_pol` accounts for the exogenous afforestation prescribed by NPI/NDC policies.
 
  q32_aff_pol(j2) ..