Deriving the Carbon Footprint

We combine energy IO analysis with household demand structure to estimate the carbon footprint for Indian households. Therewith, we can trace the carbon content of each final consumption item back to its intermediates and account for the direct as well as indirect emissions from consumption. We focus on carbon emissions from fossil fuels¹⁸ since CO2

emissions represent the largest share of GHG emissions covert under the Kyoto Protocol.¹⁹ The method which has been applied is based on Leontief (1970) and we follow the approach of Lenzen (1998b) and Lenzen et al. (2004).

First we estimate the CO2 intensities (in local currency units) of each sector of the Indian economy. We apply a single region IO model based on the Global Trade Analysis Project (GTAP). By using a single region IO model we account for direct and indirect emissions from goods produced and consumed in India as well as for emissions from imported goods.²⁰

Figure 2.1 describes the process IO energy analysis. We use IO tables for the year 2004 from the Indian Central Statistical Organization (CSO) which provide us with an [jx1]

vector of domestic output x by 130 sectors j, a [jx1] vector of final demand y by 130

17 Our per capita carbon footprint is lower since we only analyse CO2 emissions from the combustion of fossil fuels and we give each household member the same weight not matter of their age.

18 The CO₂ emissions are derived from following energy sources: coal, crude oil, natural gas, petroleum products, gas, electricity and gas. The share of renewable and nuclear energy in India’s electricity was considerably low in 2005.

19 Figure B.1 and Figure B.2 in the Appendix to this chapter give insight on how much of the major GHGs we are accounting for. In terms of quantities we account for more than 95% of the Indian GHG emissions. In terms of CO2 equivalents we account for only 60% of the GHG emissions. Other GHGs such as methane CH4

and nitrous oxide N2O are released in far lower quantities but their global warming potential is 25 and 298 times higher than the one of CO₂ emissions.

20 The share of imported goods and services in the Indian GDP equals about 22% in 2005.

Methodology 38

sectors j (which includes imports).²¹ And a [jxj] matrix of the technical coefficients A, which reflect the input requirements of the jth sector of intermediates from other sectors measured in monetary units.²² We apply the simple technology assumption and assume that imported goods are produced with the same technology as local goods. We also assume that technology has not changed drastically between 2004 and 2009 since we use the same IO table to estimate the emission intensities of sectors for 2009.²³ Depending on the fuel type the CO2 emissions per unit of fuel use are represented in the emission coefficient vector c [mx1]. The [mxj] energy use matrix E^ind represents the quantitative fuel demand of the 58 sectors per monetary unit of intermediate output from other sectors.

The energy use matrix E^fd represents the household’s quantitative fuel use per monetary unit of final demand from 58 sectors.²⁴ Total emissions from consumption CO2 would consist of direct CO2fd from final demand and indirect CO2ind emissions from energy use by each sector.

Figure 2.1: IO Energy Analysis with Expenditure Data

Source: After (Kok et al. 2006)

In Table 2.1 the process of the data matching stages is outlined. In the first step we matched the 130 sectors of our IO tables with the energy use data, which is aggregated to 58 sectors in order to get the energy intensity matrix E. In a second step we match the 58 sector emission intensities with the corresponding expenditure categories from the

21 The 130 sectors include administration and defence.

22 All the values are in local currency units at 2004 producer prices.

23 This assumption is confirmed by the emission intensities per sector from the World Input Output database, which neither changed drastically in India between 2004 and 2009 (Erumban et al. 2012).

24 The data by the GTAB energy volume data is disaggregated into 58 sectors, which were matched with the 130 sectors from the Indian IO tables.

household survey data. The data on household expenditure is rather disaggregated and we match all the 340 expenditure categories with the corresponding emission intensities.²⁵ Even though the IO tables contain information on monetary fossil fuel and electricity demand we still need to refer to the quantitative energy intensity data from GTAP to gain a more precise estimate on emissions per sector.

In our model we consider a single region approach, which assumes that environmental and energy technology is the same as abroad. Therefore, we analyze the sum of direct and indirect emissions from industrial sectors. Direct emissions from final demand fd can be characterized as follows:

𝐶𝑂_!^!" =𝑐^!𝐸^!"𝑦 (2.1)

where c’ represents the inverse emissions coefficient vector, E^fd is the energy use matrix and y is the final demand vector (Suh 2010).

Indirect emissions CO2ind, which are divided into emissions from domestic production for domestic final demand, emissions from imported intermediates and emissions from imported final demand.²⁶ The emissions by sector can be estimated by multiplying the demand of each sector represented as vector y with the transposed emissions coefficients vector c and the industrial energy use matrix E^ind as well as the with the domestic Leontief inverse (I-A)^-1:

25 For an overview on the emission intensities of each economic sector and our matched IO sector please refer to Table B.1 in the Appendix to this chapter.

26 Exports are excluded.

Methodology 40

𝐶𝑂_!^!"# =

𝑐^!𝐸^!"# 𝐼−𝐴 ^!!𝑦_!!"# + 𝐼−𝐴_!"! ^!!− 𝐼−𝐴 ^!! 𝑦_!!"#+ 𝐼−𝐴_!"! ^!!𝑦_!"#!!"#

(2.2) where Atot=A+Aimp, ytot=y+yimp and y≠exp is domestic final demand, I represents an identity matrix and A is the technical coefficients matrix, which mirrors the contribution of the intermediates to one final output unit (Suh 2010).

Direct and indirect emissions from consumption can be estimated by:

𝐶𝑂_! = 𝐶𝑂_!^!"+𝐶𝑂_!^!"# (2.3)

𝐶𝑂_! = 𝑐^! 𝐸^!"+𝐸^!"# 𝐼−𝐴 ^!!𝑦_!!"# + 𝐼−𝐴_!"! ^!!− 𝐼−𝐴 ^!! 𝑦_!!"# + 𝐼−

𝐴_!"! ^!!𝑦_!"#!!"# (2.4)

In order to estimate the carbon footprint of each household i we deduct the value added tax VAT from the household expenditure Exp and multiply each consumption category j with the respective carbon intensity CO2j of the respective sector. ²⁷ Summing up over all the expenditure categories, which yields the household carbon footprint CO2hh in kg of CO2:

𝐶𝑂_!^!!_! = ^!_!!!"# 𝐶𝑂_!! 𝐸𝑥𝑝_!" −𝑉𝐴𝑇   (2.5)

where i represents the household and j the different expenditure category.