Abstract
With the increased interest in the ‘carbon footprint’ of global economic activities, civil society, governments and the private sector are calling into question the wisdom of transporting food products across continents instead of consuming locally produced food. While the proposition that local consumption will reduce one’s carbon footprint may seem obvious at first glance, this conclusion is not at all clear when one considers that the economic emissions intensity of food production varies widely across regions. In this paper we concentrate on the tradeoff between production and transport emissions reductions by testing the following hypothesis: Substitution of domestic for imported food will reduce the direct and indirect Greenhouse Gas (GHG) emissions associated with consumption. We focus on ruminant livestock since it has the highest emissions intensity across food sectors, but we also consider other food products as well, and alternately perturb the mix of domestic and imported food products by a marginal (equal) amount. We then compare the emissions associated with each of these consumption changes in order to compute a marginal emissions intensity of local food consumption, by country and product. The variations in regional ruminant emissions intensities have profound implications for the food miles debate. While shifting consumption patterns in wealthy countries from imported to domestic livestock products reduces GHG emissions associated with international trade and transport activity, we find that these transport emissions reductions are swamped by changes in global emissions due to differences in GHG emissions intensities of production. Therefore, diverting consumption to local goods only reduces global emissions when undertaken in regions with relatively low emissions intensities. For non-ruminant products, the story is more nuanced. Transport costs are more important in the case of dairy products and vegetable oils. Overall, domestic emissions intensities are the dominant part of the food miles story in about 90 % of the country/commodity cases examined here.
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Notes
The equilibrium climate sensitivity is a measure of the climate system response to sustained radiative forcing. It is not a projection but is defined as the global average surface warming following a doubling of carbon dioxide concentrations (IPCC 2007).
Note that the “best-estimate” climate sensitivity \((3\,^{\circ }\mathrm{C})\) represents the value with the highest probability (IPCC 2007).
See Peters et al. (2011).
In order to ensure tax neutrality, we adjust the overall level of consumption taxation so as to keep constant the share of total tax receipts in net national income.
A legitimate concern associated with this experimental design is that it might favor high quality goods, with relatively lower tonnage, and hence potentially lower transportation costs. However, this is a fundamental feature of the global economic geography and hence cannot be ignored.
The factors that affect the output of ruminant products are discussed in detail in Appendix 8.
We redo the same 50 US$ million food miles experiment only in regions where the change in consumption patterns of ruminant products does not make its imports negative in the GTAP data base.
We redo the same 50 US$ million food miles experiment only in regions where the change in consumption patterns of dairy and non-ruminant products, vegetable oils and fats, and processed rice, does not make their imports negative in the GTAP data base.
Abbreviations
- CDE:
-
Constant difference of elasticities
- CES:
-
Constant elasticity of substitution
- CGE:
-
Computable general equilibrium
- GHG:
-
Greenhouse gas
- GTAP:
-
Global Trade Analysis Project
- GWP:
-
Global warming potential
- LCA:
-
Life cycle analysis
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Appendices
Appendix A
1.1 The Linkage of Emissions and Economic Drivers
The following equations are used to link emissions to economic drivers in the model (all variables are expressed as percentage changes in the corresponding levels variables):
where, the change in output related emissions in region \(r\, qemo_{jr}\) is linked to \(qf_{ijr}\), which is the change in the demand for commodity \(i\) for use by \(j\) in \(r\).
where, the change in firm’s factor-related emissions in region \(r\, ghgff_{gijr}\) is linked to \(qfe_{ijr}\), which is the change in the demand for endowment \(i\) for use in ind. \(j\) in region \(r\).
where, the change in emissions from firms’ usage of domestic product \(ghgfd_{gijr}\) is linked to \(qfd_{ijr}\), which is the change in the domestic good \(i\) demanded by industry \(j\) in region \(r\).
where, the change in emissions from firms’ usage of imports \(ghgfm_{gijr}\) is linked to \(qfm_{ijr}\), which is the change in the demand for \(i\) by industry \(j\) in region \(r\).
where, the change in emissions from private consumption of domestic product \(ghgpd_{gir}\) is linked to \(qpd_{ir}\), which is the change in private household demand for domestic \(i\) in region \(r\).
where, the change in emissions from private consumption of imports \(ghgpm_{gir}\) is linked to \(qpm_{ir}\), which is the change in private household demand for imports of \(i\) in region \(r\).
1.2 Decomposition of the Change in the Ruminant Products Output
To analyze the change in the output of ruminant products we refer to the linearized market clearing condition for merchandise commodities in GTAP:
where:
-
\(qo_{ir}\) is percent change in industry output of commodity i in region r;
-
\(qds_{ir}\) is percent change in domestic sales of commodity i in r;
-
\(qxs_{irs}\) is percent change in exports of commodity i from r to region s;
-
\(SHRDM_{ir}\) is the share of domestic sales of i in r;
-
\(SHRXMD_{irs}\) is the share of export sales of i to s in r.
Under scenario EURUMINANTS the decomposition of output in the EU reveals that the dominating portion of the change in ruminant products comes from domestic sales (\(-\)0.06 %). Next, we decompose the domestic sales using its market clearing condition:
where:
-
\(qfd_{ijr}\) is percent change in domestic product i demanded by industry j in region r;
-
\(qpd_{ir}\) is percent change in private household demand for domestic product i in region r;
-
\(qgd_{ir}\) is percent change in government demand for domestic product i in r;
-
\(SHRDFM_{ijr}\) is share of domestic product i used by sector j in r at market prices;
-
\(SHRDPM_{ir}\) is share of domestic product i used by private household in r;
-
\(SHRDGM_{ir}\) is share of imports of product i used by government in r.
The results show that most of the change in domestic sales of ruminant products in the EU is due to increase in private consumption (0.08 %). To further analyze the factors that cause the increase in the output of ruminant products we decompose its domestic demand using the Eq. (9):
where:
-
\(qft_{ijs}\) is percent change in demand for commodity i for use by j in region s;
-
\(ESUBD_{i}\) is region-generic elasticity of subst. domestic/imported for all agents;
-
\(pfd_{ijs}\) is percent change in price index for domestic purchases of commodity i by j in s;
-
\(pft_{ijs}\) is percent change in firms’ price for commodity i for use by j in s.
The outcome shows that the demand component of ruminant products dominates the substitution effect. Hence, we validate that the change in ruminant products is due to increased domestically sourced ruminant product consumption in the EU.
Appendix B
1.1 Trade Elasticities of Substitution
The following trade elasticities of substitution are used in the model simulations (Table 7).
Appendix C
1.1 “Food miles” Experiments for Other Food Products in Different Regions of the Global Model
For the robustness of our analysis of the food miles issue we perform additional “food miles” experiments focusing on changes in consumption patterns of dairy and non-ruminant products, vegetable oils and fats, and processed rice, where available,Footnote 10 and then summarize the results in Tables 8, 9, 10 and 11. In particular, we impose taxes on private consumption (while maintaining tax neutrality) of both locally produced and imported dairy and non-ruminant products, vegetable oils and fats, and processed rice, to increase domestic purchases in the region by 50 US$ million, and reduce their import sourced consumption by the same amount.
As can be noted from Tables 8, 9, 10 and 11, substitution of local for imported food products may reduce global GHG emissions due to lower use of international transport and not because of changes in production patterns of these food products. This is especially true for dairy products in the European Union and non-ruminant products in Canada.
Appendix D
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Avetisyan, M., Hertel, T. & Sampson, G. Is Local Food More Environmentally Friendly? The GHG Emissions Impacts of Consuming Imported versus Domestically Produced Food. Environ Resource Econ 58, 415–462 (2014). https://doi.org/10.1007/s10640-013-9706-3
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DOI: https://doi.org/10.1007/s10640-013-9706-3