Oiconomy Pricing

Land Use


Common characterization factors in land use assessment are indicators on species richness (De Baan et al. 2012; Lindeijer 2000; Teixeira et al. 2015; Vogtländer et al. 2000; Weidema 2001) and impacts on ecosystem services (Milà i Canals et al. 2012; De Baan et al. 2012; Thoma et al. 2015). literature shows a fierce debate if the most sustainable way towards sustainable land use is via “land sparing” or via “land sharing” (Fischer et al., 2014). Advocates of land sparing argue that high yields by intensive agriculture saves land for high quality biodiversity elsewhere and believe in technology, business as usual in developed countries and closing the yield gap in development countries. Advocates of land sharing and organic agriculture prefer more biodiversity on all land (e.g. Balmford et al. 2005; Phalan et al. 2011; Fischer et al. 2014; Tscharntke et al. 2012). More recently a third option is discussed, that of “sustainable intensification (SI)” (Godfray, 2015; Petersen & Snapp, 2015; Pretty, 1997; Rockström et al., 2017; Tilman et al., 2011), which should develop towards intensive, land sparing agriculture while reducing the environmental impact. A meta analysis by Tuomisto shows that organic farming in Europe has generally lower environmental impacts per unit of area than conventional farming, but due to lower yields and the requirement to build the fertility of land, not always per product unit of product. (Balmford et al., 2018), a large group of scholars in the field, argue that land use assessment should cover a wide range of aspects, like biodiversity, yield, pollution and soil carbon content, which therefore is also the goal of the O.S.

Because the O.S. measures sustainability of products, it covers both “land use” and “land degradation”. (Pollution, including CO2 emissions, is covered in the relevant section).
Land use is characterized by the yield and land degradation by biodiversity.
Land use, the aspect considered in this section, makes the organization responsible for providing (products, biodiversity, or both).
50% of habitable land is used for agricultural purposes and 37% is forestry, 30% of which is used as production forestry. Only 1% is urban and build-up area. Therefore, considering land use aspects, the O.S. calculations of background ESCU’s is based on agricultural purposes.

Category related Sustainable Development Goals

Goal 2: End hunger, achieve food security and improved nutrition and promote sustainable agriculture.
Goal 7: Ensure access to affordable, reliable, sustainable and modern energy.
Goal 11: Make cities inclusive, safe, resilient and sustainable.
Goal 12: Ensure sustainable consumption and production patterns.



See above: general introduction Land Use

Impact category and indicator

The impact category is loss of valuable ecosystems by inefficient land use and the indicator the distance between the yield and the average crop yield in FAOSTAT (FAO, 2019).
The characterization factor is the distance to an average crop yield, obtained from FAOSTAT (www.fao.org/faostat/en/#data/QC).
In case of a yield gap, e.g. for organic agriculture, extra land is required to compensate for the loss of yield. Therefore, ESCU’s need to be allocated for restoration and maintenance of an extra piece of land which should be unproductive and of little biodiversity value. Because this will usually be arid, a continuous flow of considerable amounts of water is required for sustainable arable land.


The land sparing target is zero cause of further loss of valuable ecosystems or “land degradation neutrality” as set at the RIO conference on sustainable development (United Nations, 2012).
The O.S. seeks a balance between land sparing and land sharing by striving towards sustainable intensive agriculture. According to (Balmford et al., 2018), For Land assessment, all involved aspects should be accounted for. Therefore, the O.S. allocates ESCU’s for both below-average yields (category land use), emission of harmful chemicals (category pollution) and for biodiversity below 80% of locally natural biodiversity (category land degradation/biodiversity).

Background calculations

ESCU’s =Q x (1-CY/AY) x EWC, where
AY = Average Yield
CY = actual Crop Yield (or product yield)
EWC = extra water costs for growing crops in arid conditions
Q = quantity of occupied hectares

The background extra water costs are calculated as follows:
Corn is a globally common staple crop, growing under reasonably arid conditions. The world average corn yield (FAOSTAT) in 2014 is 5,615 tons/ha.
To compensate the yield gap, we propose the costs of “growing corn on a new piece of arid land, irrigated with desalinated seawater”. The involved extra costs consist of the costs of seawater desalination + the costs of water transport to the arid location + the yearly interest for the purchase of arid land + the costs of ESCU’s for emissions for the energy required for desalination and transport. We assume other agricultural activities equal to standard, without extra costs. Because desalinated water is very expensive, water saving irrigation techniques like subsurface drip technology will surely be economic, and are therefore assumed to be used and reduce water use by 40% (Budiharta et al., 2014; Lamm & Trooien, 2003), but not to need more energy and maintenance than conventional irrigation.
As interest rates we take 5% for high income countries and 13 % for low income countries.
For the average transport distance from sea to suitable arid areas we assume 1000 km horizontal at € 0,055/ m3.100 km. and 400 meters vertical at € 0,046/m3.100m distance (Zhou & Tol, 2005).

The globally average water footprint for corn (Mekonnen & Hoekstra, 2010) is 1222 m3/ton, in arid regions with only 50% green water availability resulting in a need of 611 m3/ton of extra water.
Costs of seawater desalination: € 0,66/m3, including ESCU’s for 4 KwH/m3 related emissions, excluding transport (Lenntech, 2017). For the purchase of arable land we assume € 100/ha., the highest of the price range of arid land in South Africa of € 10 – € 100/ha.
Table 1 shows the calculation of ESCU’s for land use, resulting in the very high ESCU sum of € 6022/ha.y. However this only applies to the proportion of land wasted by inefficient land use, by multiplication by a land use efficiency factor (EF): EF = (FAY-AY)/FAY, where AY is the actually achieved 5-year average yield and FAY the FAOSTAT listed average yield for the country (or region if reliable data are available). For example, for an efficiency loss of 20%, 0,2 x 6022 = 1204 ESCU’s/ ha.y need to be allocated for, or in the case of corn 80% of 5.615 kg of corn = € 0,27/kg.

As default value at lacking yield data, 50% of the average yield is assumed (the lowest % mentioned in literature for the relative yield of organic crops).

Balancing for double counting
With the same amount of water as required for a commercial crop, without any crop bare land in most cases a rich biodiversity would emerge. Although not the same as locally natural, this means that simple aggregation of ESCU’s for land use and biodiversity would be a case of double counting. In addition, considering the following:

  • Nature with 100% biodiversity and no commercial use (zero yield) obtains zero ESCU’s.
  • Built land with 100% yield and zero biodiversity obtains full biodiversity ESCU’s.

Therefore, the full biodiversity ESCU’s is also the maximum allocation for the aggregation of both.

Because the O.S. wants to lead towards an equilibrium of bott aspects, the ESCU’s for land use and biodiversity are divided over both aspects as follows:

For land use: ESCU’s/ha = (Min(FBE; UE) x (UE/ (UE + BE).
For biodiversity: ESCU’s/ha = BE x (BE/ (OE + BE).
FBE represents full biodiversity ESCU’s
UE represents the ESCU’s for land use.
BE represents the ESCU’s for biodiversity.

To obtain the ESCU’s per unit of product, both values are divided by the yield/hectare.

Table 1. The calculations for growing 5,615 tons of corn on 1 hectare of arid land (50% green water), 1000 km from sea and at 400 m altitude, with seawater desalinated water and using a Subsurface Drip Irrigation system (SDI) (40% water use reduction):

Action Calculation Result (€/ha.y)
Water desalination, including ESCU’s for emissions 0,6 (40% reduction for SDI) x 5,615 x 611 x 1,00 (ESCU’s for 1 m3 water) 2058


Water transport 0,6 x 5,615 x 611 x (1000/100) x 0,0552
+ 0,6 x 5,615 x 611 x (400/100) x 0,046
ESCU’s for pumping emissions. (0,6 x 5,615 x 611) x 0,00455 (kwh/m3.m) x 400 (vertical)  x 0,1546  (ESCU’s/kwh) +
(0,6 x 5,615 x 611) x 0,00546 (kwh/m3.m) x 1000 (horizontal)  x 0,1546 (ESCU’s/kwh)


Financing Land + subsurface drip irrigation system (SDI) 100 x 0,13 (interest arid land) + 604 x 0,13 (interest SDI) + 604/15 (depreciation SDI) 132
Total 6022

(Idemat 2018 lists for transport of liquids (weight/volume ratio = 1) € 0,01/m3.km, assuming return freight available, and neglecting the vertical transport, results in 0,6 x 5,615 x 611 x € 0,01 x 1000 = € 20585 for the ESCU’s for road transport of the water, showing the unsustainability of this solution.
SDI is “Subsurface Drip Irrigation”

Foreground calculations

Organizations are challenged to determine their foreground costs of mitigation of inefficient land use without loss (or rather under simultaneous increase) of biodiversity.

Note that the background preventative measure against loss of more valuable ecosystems is based on compensation elsewhere, which means that the options to demonstrate lower specific foreground preventative costs are to either find another way to increase his own land use efficiency, self-convert and use a piece of arid land, or finance distant farmers to do so in a verified and demonstrable way. Because in practice at many locations cheaper conversion will be possible, e.g. because brackish water is available and can be desalinated at much lower costs and shorter distance than 1000 km. at lower altitude than 400 meters. there are ample possibilities for lower costs.

If for instance ESCU’s for transport (pumping) KwH’s are calculated based on exclusive use of PV, like we, following Vogtlander also did for the desalination, the Land use ESCU’s/ha.y. become € 4748, and the break-even point at 559/4748 = 11,8%.

The best way however is to produce sparing both land and biodiversity on the self-exploited land. The O.S. allocate ESCU’s first per hectares and thereafter divides the score by the yield. Therefore, the higher the yield, the lower the ESCU’s per unit of product. The ESCU calculations are equal to those for background cases but based on demonstrable foreground data.

All above explanations apply for non-food forestry products, with the following additional details:

Additional details

For forestry products, a carbon sequestration bonus compensation is added in two cases:

  • Forestry for which a positive long-term balance of carbon sequestration and harvesting can be demonstrated.
  • For non-food forest products for which a lifetime > 50 years can be demonstrated.


Section in development – (Insufficient data investigated): Need of statistics for reference yields per hectare without foreign nutrients. 



Agriculture and forestry make is by far the largest contribution to land use. 50 % of habitual land on earth is used for agriculture, 37% for forestry, 11% is shrubland and only 1% is urban and built-up land. This means that most other land use than agriculture and forestry is insignificant. For exceptions, e.g. for mining, roads, rail, airports, harbors or defense purposes, the O.S. only requires calculation for non agricultural or forestry products with a yield > € 100.000 /ha or land use > 100 ha.

Impact category and Indicator
Loss of valuable ecosystems


Restoration and maintenance of valuable ecosystems either on the own premises or elsewhere

Background calculations

Determination of the ESCU’s per hectare following the above described method and dividing by the amount of units.

Foreground calculations

Not applicable.