The 40_transport module simulates the intraregional transportation of agricultural products between producer site and the next city centre (market). It covers the transport of inputs such as fertilizers to the production site as well as the transport of products to the market. Calculations are based on cellular and global parameters and returns the corresponding cellular transport costs which are then used by the 11_costs module.
| Description | Unit | A | B | |
|---|---|---|---|---|
| vm_prod (j, k) |
Production in each cell | \(10^6 tDM/yr\) | x |
| Description | Unit | |
|---|---|---|
| vm_cost_transp (j, k) |
Transportation costs | \(10^6 USD_{05MER}/yr\) |
In this realization transportation costs are calculated based on the assumption that transport costs are proportional to the mass which has to be transported and the time which is required for the transport.
\[\begin{multline*} vm\_cost\_transp(j2,k) = vm\_prod(j2,k) \cdot f40\_distance(j2) \cdot f40\_transport\_costs(k) \end{multline*}\]
Transportation costs for each cell are calculated as the product of the production in each cell, the transport distance to a urban centre and the transport costs.
As cellular distance information f40_distance(j2), the
European Commission Joint Research Centre (EC JRC)’s 30 arc-second
resolution map on travel time for any location on the earth surface to
the nearest large city is used (figure below - Nelson (2008)). The data set is based on
multiple indicators (biophysical, administrative and transport mode)
which determine the friction surface that in turn determines the time
needed to transport goods across grid cells. The cumulated time needed
to reach an urban center of minimal 50000 inhabitants stands as static
proxy for accessibility of a grid cell.
Relative transport costs f40_transport_costs(k) are
calibrated using total agricultural transport costs taken from the GTAP
7 database (see Narayanan and Walmsley (2008)
for a general description of the GTAP model structure). GTAP
agricultural transport costs represent transport costs from one sector
to another sector (e.g. from a farm to the mill). Based on GTAP we
calculate sector to sector transport costs for agricultural inputs and
outputs. In MAgPIE we want to represent market to market transport
costs. Since markets are the links between sectors, we assume that the
sum of 50% of the agricultural input transport costs and 50% of the
output transport costs represent the agricultural transport costs for a
commodity.
Relative transport costs f40_transport_costs(k) are
calculated by dividing total agricultural transport costs from GTAP 7 by
the product of an initial (1995 as default) cellular MAgPIE production
pattern and cellular travel time. By doing so we ensure that relative
transport costs, multiplied with the initial MAgPIE production
allocation and given travel times match the absolute transport costs as
reported by GTAP 7.
Total agricultural transport costs from GTAP 7 are based on total agricultural production in 2004. For consistency, we scale the GTAP data with the ratio of FAO production data for 2004 and 1995. Subsequently, MAgPIE is run several times in yield calibration mode until regional MAgPIE production is consistent with FAO production for the initial time step. Based on this first calibration run, total MAgPIE transportation costs are summed up and compared with GTAP data (see Figure 3). In case of low agreement, the calculation of relative transportation costs is repeated based on the calibrated MAgPIE production pattern and a second round of MAgPIE yield calibration is started. This process is repeated until MAgPIE total transport costs are in good agreement with GTAP total transport costs.
Limitations The information in distances between production sites and markets is static over time, meaning that infrastructure is assumed to be static over time.
In this realization the transport of goods is assumed to be free of charge. Correspondingly transportation costs are fixed to 0.
Limitations No simulation of transportation (transportation free of charge).
| Description | Unit | A | B | |
|---|---|---|---|---|
| f40_distance (j) |
Transport distance to urban center | \(min\) | x | |
| f40_transport_costs (kall) |
Relative transport costs | \(USD_{05MER}/tDM/min\) | x | |
| q40_cost_transport (j, k) |
Cellular transport costs for k | \(10^6 USD_{05MER}/yr\) | x | |
| s40_pasture_transport_costs | Transport costs for pasture | \(USD_{05MER}/tDM/min\) | x |
| description | |
|---|---|
| j | number of LPJ cells |
| j2(j) | Spatial Clusters (dynamic set) |
| k(kall) | Primary products |
| kall | All products in the sectoral version |
| t(t_all) | Simulated time periods |
| type | GAMS variable attribute used for the output |
Jan Philipp Dietrich, Florian Humpenöder, Benjamin Bodirsky, Isabelle Weindl, Michael Krause.