Carbon opportunity cost (COC) and indirect land use changes (iLUC) are two different approaches to calculate GHG emissions related to the use of land, e.g. by crops for food and biofuels. I.e. they are used for the same purposes, yet they are fundamentally different and lead to different calculated results. In this blog, I have tried to briefly describe the two approaches, to make a one-by-one comparison for the most important features, and finally to provide my remarks and recommendations.
At 2-0 LCA we have more than 15 years of experience in calculating land use change emissions using different approaches, hereunder iLUC, dLUC, sLUC, and COC. In this blog, I take a deep dive into the comparison of COC and iLUC, as the release of the GHG Protocol Land Sector and Removals Standard requires that the issue of "land use and leakage" shall be addressed, where COC shall be used if there is a high risk of "land carbon leakage". This has led to many questions on what the difference is between COC and iLUC.
Carbon opportunity cost (COC) refers to the CO2 sequestration that would have occurred if the occupied land had been left with native ecosystems instead of the current land cover. COC for 1 ha*year of a specific land use is calculated as the difference in carbon stock (difference between 1 and 2 below) annualised over an amortisation period of e.g. 100 years and converted to CO2 by multiplying with 44/12. The carbon stock of the two situations is described below:
Indirect land use changes (iLUC) account for upstream life cycle consequences of the use of land (also sometimes referred to as land leakage). Different models exist, e.g. see De Rosa et al. (2016), while here I only go into details with the model described in Schmidt et al. (2015).
iLUC refers to the impacts (not necessarily only GHG emissions) that are caused by the occupation of land, e.g. 1 ha*year. When occupying 1 ha*year of land in a certain location, this means that other crops cannot be cultivated on that plot of land, and consequently, these displaced crops will have to be produced in another way and/or somewhere else. This can either be on new land obtained from land conversion somewhere else, or by intensification of existing cropland, e.g. by additional fertiliser application. In addition to the above indirect effects, the actual studied activity that occupies land may store a different amount of carbon than the displaced crop, e.g. when cultivating apple trees on cropland, then the apple trees store more carbon that the crops they displace. This is referred to as direct land use changes. The identification of the indirect land conversion and intensification is made via a market for arable land, that has inputs of land conversion and intensification by country – identified via recent trends of the two based on FAOSTAT timeseries for all crops in all countries.
The total impact includes the sum of:
Direct land use changes
Indirect land use change (market for land affected)
Note that the area of indirectly affected land is calculated based on a weighting using potential net primary production (NPP0).
For the indirect effects, the proportion between land use change and intensification is calculated based on time-series of harvested crops, yields, and area of cropland based on FAOSTAT for all crops and all countries.
The emissions in (1) and (2) above are "gross" emissions, where it has not yet been considered that the conversion for the first year of cultivation of a crop is handed over to the next crops after a year, so that these crops can be cultivated without land conversions. As the occupied land for the crop under study is released for other crops after the occupation in one year, the land can be "recycled" to grow other crops. This means that the effect from occupying 1 ha in 1 year is that the emissions from (1) and (2) above are only preponed by one year, i.e. a bit simplified, if there was no demand for the crop under study, the land conversion effects would have happened one year later (because there currently is a general trend that cropland expands). The effect from changing (preponing) the timing of CO2 emissions can be calculated using the standard GWP100 formula as presented in the supplementary materials of the IPCC Assessment reports, see Schmidt et al. (2015).
In the table below, key features of the two approaches are compared.
| Feature | COC | iLUC |
| Counterfactual: this is essential as this represents the situation without land occupation | Natural vegetation on the actual occupied piece of land after 100 years of no disturbance. | The effect from land use is dLUC + iLUC + intensification. The counterfactual for these three elements are:
|
| Geographical scope | Applicable for any land cover at location at any detailed level of granularity. | Applicable for any land cover at location at any detailed level of granularity. |
| Function and functional unit of land | Most often COC are calculated directly per unit of final products, i.e. there is not a well-defined function and a comparable unit of the supply of land. | The functional unit refers to the potential productivity of land and is measured as 1 ha*year global average land. The use of land in a specific location is linked to the functional unit via relative difference in NPP0 of the affected land plot and the global average NPP0 of the affected market for land, i.e. most often arable land. This means that land use in the wet tropics (with high NPP0) induce more iLUC than in the colder temperate ecozones. |
| Driver of impact | Size of land occupation (ha*year) and potential sequestration through vegetation on the affected plot of land. | Size of land occupation (ha*year), affected market for land, and NPP0 of affected land relative the global average. |
| Market for land | No market for land, and no indirect effects are considered. | A global market for each of the following three market segments is considered: arable land, forest land, and grassland. The markets refer to the marginal use of the land. |
| Temporal aspects | Emissions from 1 year of occupation are estimated from expected carbon stocks over a decided timeframe, e.g. 30-100 years, from the time of occupation and decided years onwards (also assuming that a similar occupation activity as the studied one continues during this time). The decision on this amortization period is arbitrary and has large influence on results. | Emissions from 1 year of occupation are estimated from predicted caused land conversion, where the net effect is induced land conversion at start of occupation and avoided land conversion at end of occupation. |
| GHG metrics | CO2 emissions are calculated based on carbon stock changes and by using 100 years amortization. | GHG emissions include both CO2 (from land conversion) and N2O (from intensification). As described under "Temporal aspects", CO2 emissions from land conversion are induced at beginning of occupation and avoided at end of conversion. The GWP100 of this preponement of CO2 is calculated using time dependent GWP100. |
| Impact | Only CO2 emissions. No good overviews have been identified. Through, based on the supplementary information in Searchinger et al. (2018), the emissions from 1 ha*year occupation have been estimated as typically ranging from ~3-20 t CO2e depending on location and type of land/counterfactual. | The iLUC model is a general life cycle inventory model, which can be linked to any impact category. However, most relevant ones are global warming, nature occupation/biodiversity, and respiratory inorganics (caused by NH3 emissions). The GWP100 from 1 ha*year occupation of global average arable land is ~1.8 t CO2e, data per country is available here: https://2-0-lca.com/wp-content/uploads/iLUC-GHG-summary-per-country-and-land-market_OPEN_20230630-2.xlsx |
The counterfactual of COC is highly hypothetical and makes predictions about what will happen on the land up to 100 years into the future. It can be observed in statistics that >>99% of all global cropland is replanted with new crops every year, indicating that the assumed counterfactual of renaturalisation in COC is not realistic. On the other hand, iLUC models more correctly assume that local use of land will divert cultivation of other crops to somewhere else, and also addressing the fact that intensification is affected. In fact, more than 75% of the global annual increase in crop production is achieved through intensification, which is a key driver of increase in fertiliser demand. So, this must not be ignored.
COC only considers land use effects on the studied plot of land. This means that no land leakage is assumed. Therefore, COC can be said to be a kind of "direct land use change model". This is in conflict with the concept of life cycle assessment, which requires that all affected up- and downstream effects must be included. On the other hand, iLUC models explicitly consider that fact that changing the occupation of a specific land plot will displace another land use, i.e. other crops must be cultivated elsewhere. When identifying this effect, iLUC models assume that there is a market for land (or alternatively that land can be indirectly affected via markets for crops). Therefore, iLUC models do not introduce a cut-off at direct effects for land use changes, as is the case for COC.
Based on the comparison of carbon opportunity cost (COC) and indirect land use change (iLUC) models, I would recommend using iLUC models, as they overcome several serious limitations of COC. iLUC models:
Blaustein-Rejto D, Soltis N, Blomqvist L (2023). Carbon opportunity cost increases carbon footprint advantage of grain-finished beef. PLoS ONE 18(12): e0295035. https://doi.org/10.1371/journal.pone.0295035
De Rosa M, Knudsen M T, Hermansen J E (2016). A comparison of Land Use Change models: challenges and future developments. Journal of Cleaner Production, Volume 113, 1 February 2016, Pages 183-193. https://doi.org/10.1016/j.jclepro.2015.11.097
Schmidt J, Weidema B P, Brandão M (2015). A framework for modelling indirect land use changes in life cycle assessment. Journal of Cleaner Production 99:230-238. https://doi.org/10.1016/j.jclepro.2015.03.013
Searchinger TD, Wirsenius S, Beringer T, Dumas P (2018). Assessing the efficiency of changes in land use for mitigating climate change. Nature; 564(7735): 249–53. https://doi.org/10.1038/s41586-018-0757-z
