Narración de la vivencia en el aula

(Mt CO

-e)

Australian emission's

abatement that

occurs overseas

(Mt CO

-e)

Income paid by Australians to purchase foreign emissions

permits

Foreign emissions permits purchased by Australians

a _{Assuming that Australia is a net purchaser of emissions permits overseas. If Australia is a net seller of} emissions permits, the flows are in the opposite direction to that indicated. Whether Australia is a net buyer or seller of emissions permits in VURM5 depends on the price of Australian permits relative to the Australian dollar price of foreign permits.

8.2.3 Conceptual model

Emissions can be modelled from the quantity of each fossil fuel used (for combustion emissions) and the level of each relevant activity (for non-combustion emissions) by applying the appropriate emissions coefficient.59 _{If Q denotes the physical quantity of a particular fossil fuel burnt (such as} tonnes or litres) or activity undertaken (such as cubic metres of gas extracted or the number of sheep) and the corresponding emissions coefficient is C (tonnes of CO2-e per tonne or litre of that fuel burnt or per unit of activity undertaken), CO2-e emissions are:

E = C × Q (E8.1)

A strength of this approach is that, in a stylised manner, it reflects the underlying chemistry giving rise to the emissions. This is a highly stylised version of the approach that all countries, including Australia, use in their reporting obligations under the Kyoto Protocol.

The percentage change form of equation (E8.1) is:

e = c + q (E8.2)

8.2.4 TABLO Implementation

The variable and coefficient names used in the TABLO implementation are also outlined in annex 8A.2 at the end of this chapter. These variable and coefficients generally span multiple dimensions, such as the fuels and activities giving rise to the emissions.

The main energy and greenhouse gas emission sets used in the TABLO implementation are set out in annex 8A.3 at the end of this chapter. As implemented in the model database:

 the set FUEL represents the fossil fuels that give rise to combustion emissions: coal; gas; petrol; and other refinery products; and

 the element “Activity” represents non-combustion emissions.

Together they cover all sources of greenhouse gas emissions in VURM5 (denoted by the set FUELX). The industries, activities and sectors that give rise to these emissions are represented by the set FUELUSER. In the model database, the set consists of all 64 industries and households (termed “residential”). It is assumed that no fuels are used in investment and that no emissions arise from investment. As a result, there are 65 emitters in the VURM5 model database.

These sets are used in the TABLO implementation to give the coefficients and variables a high degree of dimensionality. For example, the coefficients for the level of emissions and specific emission tax rates (QGAS and ETAXRATE, respectively) have the dimensions source of greenhouse gas emissions (the set FUELX) by emitting sectors (the set FUELUSER) by region (the set REGDST). This means that

59 _{The notation used in the conceptual models detailed in this and subsequent sections is set out in annex 4.2} at the end of this chapter. While not presented in the conceptual model, each variable discussed below can be thought of as representing a more detailed matrix (such as emissions by fuel type and industry). The additional dimensions that accompany each variable are included in the Tablo implementation.

each ‘coefficient’ corresponds to 2 600 different coefficients in the TABLO implementation (= 5 × 65 × 8).

All of the greenhouse-specific data for the emission module are contained on the physical file that corresponds to the file with the logical name GDATA(annex 8A.4 at the end of this chapter). The three main data items read are:

 the quantity of greenhouse gas emissions (the coefficient QGAS);

 the specific Australian tax rates on emissions (if any) (the coefficient ETAXRATE); and  the price to which the specific tax rates are indexed, which is a scalar used to convert

the tax rates into the price level prevailing in the current simulation year (the coefficient ENERINDEX).

The data items read in are discussed in the relevant sections to which they relate. Equations

The first six equations determine the percentage change in CO2-e emissions (the variable xgas):  equations E_xgasA, E_xgasB, E_xgasC and E_xgasD cover industry emissions; and  equations E_xgasE and E_xgasF cover household emissions.

Each equation determines elements of the variable xgas. xgas is also used to update the coefficient QGAS, which records the level of emissions expressed in kilo-tonnes (kt). The coefficient is read from header “QGAS” in the file GDATA.60

Percentage change in industry emissions (E_xgasA to E_actdriveC) Emissions by industry and region are determined by four equations:

 Equation E_xgasA determines combustion emissions arising from the burning of coal;  Equation E_xgasB determines combustion emissions arising from the burning of gas;  Equation E_xgasC determines combustion emissions arising from the burning of

petroleum products; and

 Equation E_xgasD determines non-combustion emissions. The basic form of each equation is the same.

 The left-hand side denotes the percentage change by industry and region in emissions from that source (emissions from the burning of coal in the case of equation E_xgasA).  The first term on the right-hand side denotes the percentage change in the

corresponding quantity term that gives rise to those emissions (the driver of those emissions). In the case of equation E_xgasA, for example, the relevant quantity term is the percentage change in primary energy sourced from coal (the variable xprimen). This is equivalent to the variable q in equation (E8.2).

 The second term on the right-hand side denotes the percentage in per unit emissions (emissions intensity) and is equivalent to the variable c in equation (E8.2). The emissions-intensity term for coal, for example is agas(“Coal”,i,q). The emissions- intensity term is generally exogenous and can be shocked to introduce technical change

60 _{In this chapter, GDATA refers to the file associated with the logical filename GDATA in the Tablo code. The} physical file that corresponding to GDATA for VURM5 is gdatnew6pc2.har.

that affects the intensity of industry emissions. Note that the marginal abatement curves discussed in section 8.6.1 feed through into emissions via this emission-intensity term.

The details on each of these four equations are set out in table 8.1.

Emissions sequestered through forestry are modelled as being proportional to changes in output of the VURM5 industry forestry, which, in turn, is based on the ABS input-output industry of the same name. This approach uses the change in the value of forestry output as a proxy for the change in the quantity of logs harvested and, assuming that forestry is in a steady state, that the quantity of logs harvested proxies CO2 sequestration.61

61 _{Alternatively, as the amount of CO}

2 sequestered from forestry in any given year is a function of tree growth occurring in plantations in that year, emissions sequestration could instead be modelled by treating forestry as an investment activity and by making emissions a function of the stock of investment in forestry. Pant (2010) implemented a version of this in the GTEM model after splitting the forestry industry into separate activities, including an investment component.