ESTIMATING CONSUMPTION-BASED CO2 EMISSIONS USING THE OECD ICIO 2015

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1 October 2015 ESTIMATING CONSUMPTION-BASED CO2 EMISSIONS USING THE OECD ICIO 2015 Kirsten S. Wiebe and Norihiko Yamano* OECD Directorate for Science, Technology and Innovation This document is a work-in-progress, comments and suggestions would be much appreciated. Any suggestions or queries can be sent to stan.contact@oecd.org, mentioning "Embodied CO2" in the title of your message. This description of the methodology should not be reported as representing the official views of the OECD or of its member countries. The opinions expressed and arguments employed are those of the authors. This document and any map included herein are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. * We would like to express our gratitude to the following colleagues who have contributed to the development of OECD consumption-based measures of CO2 emissions over the years; notably contributions to previous versions of the data sets (2011 and 2013) and to the estimation of sectoral allocation of emissions: Nadim Ahmad, Asako Okamura, Colin Webb, Karen Turner, Antonios Katris and Shiguang Zhu. 1

2 October Overview The OECD s inter-country input-output (ICIO) tables can be used to estimate economic, social and environmental effects along global value chains. The most prominent application of these tables is the WTO-OECD joint initiative on Trade in Value Added. The same theoretical approach can be used to estimate consumption-based emissions. Consumption-based CO 2 emissions, in contrast to territorial or production-based emissions, allocate emissions to those countries where the goods and services are eventually consumed. To link the consumption of goods and service to those industries and countries where emissions occur, the ICIO system needs to be extended to include CO 2 intensities for all countries and industries, i.e. CO 2 emissions per unit of production. Consumption-based CO 2 emission estimates have been published by the OECD since 2003 Ahmad and Wyckoff (2003) Nakano et al. (2009) OECD Green growth and sustainable development (OECD, 2011; GGKP; 2013) Consumption-based CO 2 emissions estimates based on 2011 (OECD, 2011) and 2013 editions of OECD ICIO tables: The development of the difference between production-based and consumption-based carbon emissions is highlighted in Figure 1. While the OECD countries in total have been and still are embodied carbon net-importers (the solid blue line representing consumption-based emissions is above the dashed blue line representing production-based emissions), the non-oecd countries are net-exporters. Note, that the shaded blue (OECD net imports) and green (non-oecd net exports) areas have the exact same size, i.e. OECD net-imports are non-oecd net-exports of embodied carbon. Net-imports of OECD countries have doubled between 1995 and 2005, peaked between 2005 and 2007 and then decreased due to the economic crises. Figure 1: CO2 emissions from fuel combustion (OECD and non-oecd countries) Net-imports of embodied CO2 into OECD countries Gt CO Net-exports of embodied CO2 of non-oecd countries Source: Own estimates based on the methodology described in this document Consumption-based (OECD) Production-based (OECD) Production-based (non-oecd) Consumption-based (non-oecd)

3 AUS USA CAN LUX SAU BEL CHE FIN NOR AUT OECD ISR KOR JPN EST DEU CZE IRL NLD GBR GRC SVN DNK NZL ITA SWE FRA RUS POL SVK ISL ESP ZAF HUN PRT CHN TUR CHL ARG MEX BRA IDN IND tonnes CO2 per capita October Calculating emissions embodied in international trade and final consumption 2.1 Methodology CO 2 emissions associated with final demand in country s emitted in industry i in country r, cc i rs, are calculated by multiplying the intensities of the production-based emissions (matrix EF, of size NK NK, N being the number of countries and K the number of industries) with the global Leontief inverse (I-A) -1 (of size NK NK) and global final demand matrix (Y, of size NK N) from the OECD ICIO: cc 11 cc 12 cc 1N [ cc 21 cc 22 cc 2N ] cc N1 cc N2 cc NN EF I A 11 A 12 A 1N = [ 0 EF 2 0 ] [ A 21 I A 22 A 2N ] 0 0 EF N A N1 A N2 I A NN 1 y 11 y 12 y 1N y 21 y 22 y 2N [ y N1 y N2 y NN ] with vectors cc rs representing the emissions produced in country r by industry associated with final demand of country s, EF r being a diagonalised vector of industry-specific emission intensities for country r, A rs being the coefficient matrix of country r s intermediate inputs into country s s production and y rs the demand of country s for final goods and services produced by country r, by industry. Consumption-based emissions of country s are then calculated as the column sum of column s in matrix CC plus direct emissions from final demand FNLC s = fnlc s [re] + fnlc s [pp], with fnlc s [re] being residential emissions (e.g. from burning gas) and fnlc s [pp] being emissions from private road transport. Similarly, production-based emission can be calculated as row sums of matrix CC (of size NK N) plus direct emissions from final demand FNLC s, and discrepancies, see below.. In this case, as cc rs, are vectors of the number of rows being equal to the number of industries, we get production-based emission by country and industry. Direct emission from final demand FNLC s are allocated to industries Coke, refined petroleum products and nuclear fuel (in case of emissions from private road transport) and to Electricity, gas and water supply (in case of residential emissions). It is also possible to calculate consumption-based emissions by final demand industry, see Section 2.2. Figure 2 shows per capita production- and consumption-based emissions for all OECD and G20 countries. Figure 2: Per capita CO2 emissions from fuel combustion Consumption-based 2011 Production-based* 2011 Consumption-based 1995 Production-based* * Production-based estimates after reallocation of emissions from non-resident expenditures on fuel Source: Own estimates based on the methodology described in this document and UN (2015) 3

4 October 2015 Figure 3: Emissions associated with discrepancies as a percentage of total global emissions Source: Own estimates based on the methodology described in this document The ICIO system also reports discrepancies as unspecified trade partners. For the calculations, these are represented as an additional column in the final demand matrix, thus resulting in an additional column of matrix CC. The data therefore includes consumption-based emissions of discrepancies to ensure that global CO 2 production equals global CO 2 consumption. Emissions allocated to discrepancies are maximal 0.24% of global emissions, see Figure Emissions embodied in final demand by industry Section 2.1 showed the basic approach to calculating consumption-based emissions at the country level. In addition to the country-level data, it is also interesting to analyse emissions embodied in the consumption of country s by final demand industry. To this end, the global final demand matrix needs to be manipulated a little bit: instead of having column vectors y rs, we need to create a global final demand matrix consisting of matrix blocks that are made off diagonalised vectors y rs, rs y y rs rs 0 y = [ 2 0 ] and the global final demand matrix Y = y 21 y 22 y 2N. rs 0 0 y K [ y N1 y N2 y NN ] y 11 y 12 y 1N This, in matrix blocks diagonalised, global final demand matrix Y is of size NK NK. Thus, the resulting matrix CC = EF (I A) 1 Y is of size NK NK as well. The column sums of this matrix now give consumption-based emissions by country and by final demand industry. cc ij rs is CO 2 emitted in industry i in country r, when producing final goods/services of industry j consumed in country s. Note, to have total consumption-based emissions it is again necessary to add emissions from private road transport and residential emissions to consumption-based emissions of industries Coke, refined petroleum products and nuclear fuel and Electricity, gas and water supply, respectively. 3 Estimation of CO2 emissions factor using fuel combustion emissions and IO/SUT data sources The CO 2 emission factors used in the OECD ICIO system to estimate consumption-based emissions are calculated from the IEA's CO 2 emissions from fuel combustion 1. The aim is to have for each country r and year t a vector of CO 2 emissions per unit of industry output, the emission factor EF tr [i] for industry i. In addition, direct emissions from final demand (fnlc) have to be considered. These are residential emissions, fnlc tr [re], and direct emissions from private road transport (household consumption of petroleum products), fnlc tr [pp]. 1 The IEA's data seem to be the most appropriate source of data to be used for estimating consumption-based emissions using the OECD s ICIO, as the data is available for all countries in the ICIO at an industry level corresponding to the industry classification of the ICIO. The IEA data is in ISIC Rev. 4 classification. But as the industries are highly aggregated, the data is still compatible with the ICIOs ISIC revision 3 classification. See, ISIC Rev 3 to ISIC Rev 4 concordance. 4

5 October Allocating CO 2 emissions by flow and fuel type to ICIO industries The industry dimension of IEA CO2 emissions data from fuel combustion does not fully comply with industry activity in Input-Output/ Supply-Use tables and, thus, with the industry classification of the ICIO system. For example, emissions from Machinery (MACHINE) includes fabricated metal products, machinery and equipment other than transport equipment (ISIC Rev 3 C28 to C33). Table 1 displays the correspondence between IEA CO 2 flow and ICIO industry. In the case of one IEA CO 2 flow corresponding to multiple ICIO industries, the emissions are allocated using total industry output as weights. For most flows, total emissions, that is the sum over all fuel types is used. For some flows, the allocation is significantly improved taking into account the data of CO 2 flow by fuel type. These flows are emissions from AUTOPROD = Unallocated autoproducers OTHEN = Other energy industry own use, DOMESAIR = Domestic aviation, RAIL = rail traffic, including industrial railways, PIPELINE = support and operation of pipelines transporting gases, liquids, slurries and other commodities, DOMESNAV = Domestic navigation, TRNONSPE = emissions from transport not elsewhere specified, NETRANS = non-energy use in transport Emissions from these flows are allocated according to the concordance between fuel types and ICIO industries as displayed in Table 2. Emissions from international marine and international aviation bunkers are not included in the calculations at this stage. One exception is the emission flow road transport, as this includes emissions associated with fuel combustion by transport activities of all industries and direct emissions from private road transport. Allocating these emissions to industries and households in done in several steps: 1. Total fuel (petroleum products ) used in one country as an intermediate input is calculated as the sum over all intermediate petroleum product imports and domestically produced petroleum products from industry in the IOT (orange parts of the intermediate input flow matrix in Figure 5). This is also done for final consumption expenditure (the red parts of the final demand matrix in Figure 5). 2. For each country, one vector of fuel use (inputs of industry ) in monetary terms is created, with length N+2 (number of industries plus domestic final consumption expenditure plus nonresident expenditure on ). Vector fueldemand $ $ $ $ $ $, see Figure After allocating all emission except emissions from road transport to industries, a vector of length N+3 containing shares of each industry in total emissions is calculated, with the share of road emissions in total emissions being the N+3 entry. Note that this vector only contains emissions from secondary fuel sources, i.e. only those fuels that are assumed to be sold by industry. Vector percco2scdry % % % % % % %, see Figure Multiplying total fuel demand, that is the sum of all entries of vector fueldemand, with the shares in vector percco2scdry results in a vector of monetary values of fuel inputs fueldemexroad (assuming that the price for CO2 associated with the fuel use is the same across industries). fueldemexroad[i] = fueldemand[i] * percco2scdry[i] for all i N+2 This vector has size N+2. The share of emissions associated with road transport is omitted from this vector, but used in the next step. 5. The vector fueldemexroad is then subtracted from vector fueldemand, leaving the monetary values of demand for inputs from industry that can be associated with demand for road transport fuel (i.e. the share of emissions indicated in blue in Figure 6). This vector, percfueldemroad, is then used to calculate industry shares to allocate road emissions across industries. 5

6 AUS AUT BEL CAN CHL CZE DNK EST FIN FRA DEU GRC HUN ISL IRL ISR ITA JPN KOR LUX MEX NLD NZL NOR POL PRT SVK SVN ESP SWE CHE TUR GBR USA ARG BGR BRA BRN CHN COL CRI CYP HKG HRV IDN IND KHM LTU LVA MLT MYS PHL ROU RUS SAU SGP THA TUN TWN VNM ZAF ROW Global October The effect of reallocating emissions using non-resident expenditures The emissions associated with fuel purchases by non-residents are reallocated to the country residents of the non-residents. This is based on the non-resident expenditure columns of the final demand matrix of the ICIO, which are estimated using tourism satellite account data. This reallocation of nonresident expenditures is displayed in the differences between the published IEA sectoral approach CO 2 emissions and the OECD CO 2 production perspective data, see Figure 4. On the global level, the OECD data is equal to the IEA data (if not, there would be an inconsistency in the data). The country averages across years are between -0.5% and 0.7%. the highest deviations are for relatively small countries, where road emission by residents abroad or by non-residents on the countries territory are a relatively high share of the country s total emissions. Examples for countries, in which the deviation is higher than 1% for at least one year, are Estonia, Iceland, Switzerland, Cyprus 2, Hong Kong, Croatia, Malta, and Singapore. Detailed figures for each country and industry are available upon request stan.contact@oecd.org. Figure 4: Deviation of OECD CO2 production perspective data from IEA sectoral approach CO2 data 3 2% average 1% 0% -1% -2% Source: Own estimates based on the methodology described in this document 3.3 Emission intensity by industry The emission intensities by industry, the emission factors EF tc [i] at time t for country c and industry i, are calculated from total emissions by industry (excluding emissions by private road and residential emissions) divided by industry output from the OECD ICIO: EF tc [i]=co2 tc [i] / PROD tc [i]. Detailed figures for each country and industry are available upon request stan.contact@oecd.org. 2 Footnotes on Cyprus Note by Turkey The information in this document with reference to «Cyprus» relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Turkey recognises the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of the United Nations, Turkey shall preserve its position concerning the Cyprus issue. Note by all the European Union Member States of the OECD and the European Union The Republic of Cyprus is recognised by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus. 3 Footnote on Israeli Statistical Data The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law. 6

7 October Limitations and next steps Two more general problems with this approach to consumption-based emissions are: First, that emissions data are not collected according to the same methodologies as economic activity data, i.e. the emissions data does not entirely comply with the principals of national accounts data. And, second, that the use of industry averages introduces errors in both directions, over- and underestimating emissions. In addition, the underlying ICIO is in nominal terms, thus improvements in the emission intensity are partly due to changing prices. This can be overcome by using tables in monetary terms in constant prices or physical flow tables. More specific current limitations are I. The allocation of road emissions across industries, which is done with intermediate and final fuel products consumptions of of the Coke, refined petroleum products and nuclear industry (ISIC Rev.3 ) product by fuel consuming industries and households, which is too aggregated. II. The non-re-allocation of emissions associated with intermediate non-resident purchases of road transportation fuel. III. The discarding of emissions from international bunker fuels (aviation and marine). IV. The exclusion of carbon emissions not included in the IEA data, i.e. from IPCC source/sink categories other than 1A (non-fuel combustion CO 2 ), due to difficulties of matching to industry classification. V. The exclusion of greenhouse gases other than CO 2, due to data availability and difficulties of matching to industry classification. Related next steps are I. Using more detailed data to allocate emissions from road transport, if available. This is for example the case for Japan. II. This issue will not be solved in the near future due to data limitations. It may be possible to improve the estimates, when SEEA emission data is available in ISIC Rev.4 classification and the ICIO has been transferred to ISIC Rev.4 classification as well. III. Using additional data on international transport from other institutions e.g. experts from the OECD International Transport Forum (ITF), IMO, and UN ICAO. IV. Filling the gaps of emissions data from non-annex I countries. V. Filling the gaps of emissions data from non-annex I countries. Finally, the next release of the OECD ICIO will include a more detailed industry list to improve current and enable additional environmental footprint calculations, e.g. material flows. 5 References Ahmad, N. and A. Wyckoff (2003) "Carbon Dioxide Emissions Embodied in International Trade of Goods", OECD Science, Technology and Industry Working Papers, No. 2003/15, OECD Publishing, Paris. DOI: GGKP (2013) Moving towards a Common Approach on Green Growth Indicators. A Green Growth Knowledge Platform Scoping Paper. April Global Green Growth Institute (GGGI), Organisation for Economic Co-operation and Development (OECD), United Nations Environment Programme (UNEP), and World Bank. Nakano S, A.Okamura, N. Sakurai, M.Suzuki, Y.Tojo and N. Yamano (2009) The Measurement of CO2 Embodiments in International Trade Evidence from the Harmonised Input-Output and Bilateral Trade Database, OECD Science, Technology and Industry Working Papers, No. 2009/03, OECD Publishing, Paris. link OECD (2011) Towards Green Growth: Monitoring Progress: OECD Indicators, OECD Green Growth Studies, OECD Publishing, Paris. UN (2015) World Population Prospects: The 2015 Revision. File POP/1-1: Total population (both sexes combined) by major area, region and country, annually for (thousands). UN DESA Population Division, July

8 RoW RoW Country C Country C Country B Country B Country A Country A CONS NONRES CONS NONRES CONS NONRES CONS NONRES October 2015 Figure 5: Creating the vector fueldemand Global intermediate input flow matrix Global final demand matrix Country A Country B Country C RoW Cou A Cou B Cou C RoW sum Demand for products of industry in country B domestically produced goods of used as intermediates by N industries goods of produced abroad used as intermediates by N industries domestically produced final goods of industry final goods of industry produced abroad non-resident demand for final goods of industry sum of sum of sum of total demand for goods of industry as intermediate inputs total demand for final goods of industry total demand for final goods of industry by non-residents $ $ $ $ $ $ fueldemand size: N+2 N = number of industries Agriculture, hunting, forestry and fishing Coke, refined petroleum products and nuclear fuel Figure 6: Vector percco2scdry % % % % % % % percco2scdry size: N+3 N = number of industries Secondary emissions by N industries except emissions associated with road transport Secondary emissions by households except emissions associated with road transport Secondary emissions by non-residents except emissions associated with road transport Emissions associated with road transport as a share of total secondary emissions (i.e. emissions associated with fuels sold by ) 8

9 MAINELEC MAINCHP MAINHEAT EPOWERPLT AUTOPROD OTHEN IRONSTL CHEMICAL NONFERR NONMET TRANSEQ MACHINE MINING FOODPRO PAPERPRO WOODPRO CONSTRUC TEXTILES INONSPEC NEINTREN ROAD DOMESAIR RAIL PIPELINE DOMESNAV TRNONSPE NETRANS RESIDENT COMMPUB AGRICULT FISHING ONONSPEC NEOTHER AVBUNK MARBUNK October 2015 Table 1: Concordance between CO2 flows and ICIO industry classification (in ISIC Rev. 3) IO Classification Agriculture, hunting, forestry and fishing Mining and quarrying C10T Food products, beverages and tobacco C15T Textiles, textile products, leather and footwear C17T Wood and products of wood and cork C Pulp, paper, paper products, printing and publishing C21T Coke, refined petroleum products and nuclear fuel Chemicals C Rubber & plastics products C Other non-metallic mineral products C Basic metals C Fabricated metal products, except machinery & equipment C Machinery & equipment, nec C Computer, electronic and optical equipment C30,32, Electrical machinery & apparatus, nec C Motor vehicles, trailers & semi-trailers C Other transport equipment C Manufacturing nec; recycling (include Furniture) C36T Electricity, gas and water supply C40T Construction C Wholesale & retail trade; repairs C50T Hotels & restaurants C Transport and storage C60T Post & telecommunications C Financial intermediation C65T Real estate activities C Renting of machinery & equipment C Computer & related activities C Other Business Activities C73T Public admin. & defence; compulsory social security C Education C Health & social work C Other community, social & personal services C90T Private households with employed persons C Household final consumption PrivHH ICIO industry classification in ISIC Rev. 3 9

10 C10T14 C24 C27 C36T37 C40T41 C90T93 Mining and quarrying Coke, refined petroleum products and nuclear fuel Chemicals Basic metals Manufacturing nec; recycling (include Furniture) Electricity, gas and water supply Other community, social & personal services October 2015 Table 2: Concordance CO2 fuel types and ICIO industries 0 Hard coal (if no detail) HARDCOAL Brown coal (if no detail) BROWN Anthracite ANTCOAL Coking coal COKCOAL Other bituminous coal BITCOAL Sub-bituminous coal SUBCOAL Lignite LIGNITE Patent fuel PATFUEL Coke oven coke COKEOVGS Gas coke GASCOKE Coal tar COALTAR BKB BKB Gas works gas GASWKSGS Coke oven gas OVENCOKE Blast furnace gas BLFURGS Other recovered gases OTHKERO Peat PEAT Peat products PEATPROD Oil shale OILSHALE Natural gas NATGAS Crude/NGL/feedstocks (if no detail) CRNGFEED Crude oil CRUDEOIL Natural gas liquids NGL Refinery feedstocks REFFEEDS Additives/blending components ADDITIVE Orimulsion ORIMUL Other hydrocarbons NONCRUDE Refinery gas REFINGAS Ethane ETHANE Liquefied petroleum gases (LPG) LPG Motor gasoline excl. bio NONBIOGASO Aviation gasoline AVGAS Gasoline type jet fuel JETGAS Kerosene type jet fuel excl. bio NONBIOJETK Other kerosene OGASES Gas/diesel oil excl. bio NONBIODIES Fuel oil RESFUEL Naphtha NAPHTHA White spirit & SBP WHITESP Lubricants LUBRIC Bitumen BITUMEN Paraffin waxes PARWAX Petroleum coke PETCOKE Non-specified oil products ONONSPEC Industrial waste INDWASTE Municipal waste (non-renew) MUNWASTEN Total TOTAL