The values of the emission elasticity and the emission-intensity elasticity for Northern Ireland are reported in Table 2. Both elasticities are dependent on changes in the total emission multiplier effect mj (1st column of Table 2). Of all the economic sectors listed in the NIIO, electricity generation from coal and oil has the highest multiplier effect. For each £m output, it creates 21 kt of emissions throughout the economy. Among the agricultural sectors, the highest emission multiplier effects are related to production in cereals, potatoes, and livestock sectors ranging between 13 and 6.17 kte/£m. The forestry sector is the only sector with a negative emission multiplier effects (-48 kte/£m), thanks to its strong carbon sequestration effects. As discussed earlier, this indicator however only captured effects of change in one sector.
Taking this into an overall economy context, and measuring this multiplier effect in terms of emission elasticity,, the order of the sectors’ importance changes. In Northern Ireland, those showing the highest value, and therefore the most importance in terms of abatement efforts, are ranked (1) electricity generation from gas, (2) beef and sheep processing, (3) electricity from coal and oil, (4) dairy, and (5) beef. In this case, not only emission multiplier effects but also the relative size of sectors in the economy matter.
The results of the sensitivity analysis, indicating the emission-intensity (in kt CO2 equivalent per £million output) required to achieve a 1 percent decrease in economy-wide emissions for each sector, appear in the third column of Table 2. For example, the dairy sector would need to reduce emission-intensity from 5.86 to 5.45 kte/£m to reduce economy-wide emissions by 1 percent. In contrast, the cereals sector would need to move from 12.98 to 4.10 kte/£m to achieve the same effect, and several sectors, such as the pig sector, would need to reach negative emissions (sequestration). The emission-intensity elasticity index, measuring the percent change in emission-intensity to achieve the 1 percent decrease in total emissions,, is listed in the final column of Table 2. Taking the examples above, the dairy sector needs a 7%, cereals 68%, and the pig sector a 148% improvement in emission-intensity to achieve 1% of abatement in the economy. The smaller this value, the lower the magnitude of technical change required for the sector to achieve the reduction in total emissions. By its emission-intensity elasticity , forestry (-0.21), all other sector (0.03), electricity generation by gas (0.05) and by coal and oil (0.06) in order are among the most promising sectors for emission technical efficiency improvement in Northern Ireland. In agricultural sectors, more attention needs to be paid to dairy, beef and cereal sectors.
Moran and Gonzalez (2007) find in their application to Spain the most relevant sectors in terms of emission intensity (of CO2 emissions only) to include: the production and distribution of electricity (ranked 1st); agriculture, cattle raising, and hunting (ranked 7th); and food, drink, and tobacco manufacturing (ranked 9th). Despite the differences in sector aggregation and GHGs included in the emission intensity coefficients, we observe a similar pattern for Northern Ireland.
Total emission impact is a common term in both and , and in many cases the elasticities show a general divergent relationship, i.e. a high value of is often associated with a low value of , and vice versa. This is because the relative size of a sector in the economy is likely to increase its impact on economy wide emissions.
Combining the sensitivity and I-O multiplier results provides a measure of technical cost of structural change holding emissions to a baseline. The resulting matrix of technology elasticity of output measures is presented in Table 3. The diagonal represents each sector’s own elasticity of output, or, the percent reduction in emission-intensity required to compensate for a one percent increase in production of its commodity or service (i=j).
Electricity sectors based on fossil fuels have an elasticity of close to unity, meaning if emission-intensity can be reduced in the sector at the same rate its production increases, the expansion should be close to emission-neutral. Conversely, relatively small contractions in the sector, say displacement by low-emission electricity generation, can maintain the emission baseline even in the face of a structural shift towards increased electricity being used in the economy.
There is variation in the results amongst the agri-food sectors in the economy in terms of their own-technology-elasticity of output. The poultry-eggs and pig sectors, for example, require an emission-intensity reduction rate of close to twice the production increase to keep economy-wide emissions static. The remaining agricultural sectors (1-6 in Table 3) are closer to one percent, meaning total emissions can be checked by reducing emission intensity at about the same rate as economic output increases.
The food processing sectors (sectors 11 – 20 in Table 3) exhibit a wide range of own-elasticity measures, with the lowest 3.6% (amounting to a reduction from 0.053 kte/£m to 0.051 kte/£m for fruit and vegetable processing for a percent increase in output) up to 171 % (a change from 0.026 kte/£m to -0.018 kte/£m in the case of meat processing) to cover their own expansion. The large magnitude of change is needed in several processing sectors because they have low emission intensity to begin with, therefore it would take a more extreme efficiency gain to cover indirect emissions from backwards linkages to higher emitting agricultural sectors. This result indicates that it will not always be practical to implement emission savings in the growing sector itself, but may be more feasible to adjust emission-intensity elsewhere in the economy.
These alternative options can also be explored by examining the off-diagonal elements of the isoemisssion matrix. Reading down the column of Table 3 lists each alternative adjustment to emission intensity possible to compensate for a production increase in the sector heading the column. This allows for easy comparison of the own elasticity figure with that of the other sectors of the economy to produce the same emission-effect. For example, a percent increase in final demand from the dairy sector could be countered by either a 1.06% improvement in emission-intensity in the dairy sector itself, or a 67.11% reduction for emission-intensity in milk processing. Conversely a percent increase in output from milk processing would require a 45% improvement in emission-intensity in the processing sector itself, or a less extreme efficiency gain of 0.71% in the dairy sector.
While the columns of the matrix provide equivalent alternative scenarios of structural change for each economic sector, the rows of the matrix are more useful for entertaining scenarios of uniform growth across the economy. If all sectors in the matrix increased output by one percent simultaneously, summing along a row will show the percent improvement required for that sector to bear the entire burden of the economy-wide emissions increase. For example, under a uniform 1% growth in all sectors, the emission baseline for the economy can be maintained given a 6.3% reduction in emission intensity for electricity generated from coal and oil. The same result can be achieved through a 7.1% improvement in emission efficiency for the dairy sector. As expected, sectors with relatively low output and emission-intensity would require unrealistic efficiency improvements to counter the additional emissions.
The forestry sector has a negative emission coefficient therefore all the cross-elasticities associated with forestry are negative and the own-technology-elasticity of output positive. Reading down the first column of the matrix, the negative value indicates that additional emissions from expanding the cereals sector can be offset by making the emission coefficient for forestry even more negative (increasing the rate of sequestration per forestry output). The forestry column itself shows the percentage emission intensity could worsen in each sector, given a percent increase in forestry output, except for the own-elasticity, in which the rate of sequestration could decrease, as long as output from forestry increases at about the same rate. The own-technology-elasticity of output for forestry is close to unity as it has negligible links with other emission intensive sectors. As the cross-elasticity of forestry in each column is relatively small (usually less than one percent), forestry is often a good candidate for offsetting emission increases caused by structural shifts and increased output. It is also a potential option for countering emissions from general economic growth. The sum of the forestry row in Table 3 indicates a 20% improvement in sequestration per unit output, or roughly 20% increase in forestry output, would allow the sector to single-handedly counter emission increases from a uniform 1% output increase across all sectors in the matrix (i.e. a 1% increase in the economy including forestry in Northern Ireland).
An important result is that the additional emissions from increases in output from any sector can be compensated by relatively small changes in emission-intensity for electricity generated from fossil fuels. This pattern is less strong for increases in final demand from the dairy, beef, milk processing and meat processing sectors with values closer to 1% for emission-intensity reductions in electricity from coal/oil, and natural gas. Therefore, although reducing emission-intensity from electricity generation may do much towards compensating for growth in much of the economy, cattle sectors and those with strong linkages to cattle sectors are likely to require additional measures if structural shift expands production.