Climate Change 2001: Mitigation

8.2.4.3 Why Do Studies for the Same Country Differ?

It is enlightening to consider why estimates of ancillary benefits (or costs) for two different studies of the same country differ.

In the case of Chile, Dessus and O’Connor (1999) estimate benefits of about US$250/tC, as compared to US$62/tC in Cifuentes et al. (2000). Half of the Dessus and O’Connor (1999) benefits are attributable to effects on intelligence quotient (IQ) associated with reduced lead exposure, an endpoint not considered by Cifuentes et al. (2000) and by most studies. The large lead–IQ effect seems to be at variance with US and European studies that consider this and more conventional endpoints. Also, the VSL used by Dessus and O’Connor (1999) is more than twice as large as that used by Cifuentes et al. (2000; US$2.1 million versus US$0.78 million by the year 2020). These choices were driven by alternative benefit transfer approaches: Dessus and O’Connor (1999) used 1992 purchasing power parity to transfer a mid estimate of US VSL, while Cifuentes et al. (2000) used 1995 per capita income differences and the exchange rate to transfer a lower bound US VSL. This comparison illustrates that the choice of benefit transfer approach in estimating ancillary benefits dominates by far the modelling choices (Dessus and O’Connor (1999) used a T-D model while Cifuentes et al. (2000) used a B-U approach).

For the USA, Burtraw et al. (1999) found that for a US$25 carbon tax, the ancillary benefits per tonne are US$2.30, while Abt Associates and Pechan-Avanti Group (1999) found that for a slightly larger tax (US$30), the ancillary benefits per tonne are US$8. For a US$50/tC tax, Burtraw et al. (1999) found ancillary benefits of only US$1.50/tC, while for an even larger tax (US$67), Abt Associates and Pechan-Avanti Group (1999) estimated the ancillary benefits to be US$68/tC. These differences are explained by:

The effect of a unit change in particulate nitrates (derived from NO_x emissions) on the mortality rate which in Burtraw et al. (1999) are about one-third of those used by Abt Associates and Pechan-Avanti Group (1999).
The value of statistical life used to value mortality risk reductions (about 35% lower in Burtraw et al. (1999) who adjust the VSL for the effects of pollution on older people rather than on those of average age).
Sectors included (Burtraw et al., 1999) are restricted to the electricity sector by 2010, and NO_x emissions per unit carbon are projected to be lower for this sector than in the general US economy.
Effect of carbon tax on SO₂ emissions (Abt Associates and Pechan-Avanti Group, 1999) finds that the US$67 carbon tax is large enough to bring SO₂ emissions significantly under an SO₂ cap 60% lower than the current cap. It also cuts NO_x emissions enough to bring significant numbers of non-attainment areas under the national ambient standards. Burtraw et al. (1999) does not find such a large effect.
Baseline emissions (Burtraw et al., 1999) do not account for new, tighter ozone and PM standards, but Abt Associates and Pechan-Avanti Group (1999) do (while assuming only partial attainment of the standards). This baseline assumption leaves lower emissions of conventional pollutants to be controlled in the Abt Associates and Pechan-Avanti Group (1999) study than in the Burtraw et al. (1999) study.

8.2.4.4 Conclusions

The diffusion of methods and key studies to estimate health effects and their monetization has contributed to a reasonable degree of standardization in the literature. However, some of the differences in estimates result from different assumptions and/or methodologies used to estimate them:

Selection of concentration–response functions, such as use of time series rather than the cohort mortality studies.
Consideration of more and/or different endpoints, such as considering the lead effects on IQ.
Use of different assumptions to perform benefit transfers across countries and across time. For example, considering per capita income as opposed to purchasing power parity to perform the unit value transfer; choice of the income elasticity value.
Defining the baseline differently: most of the literature on ancillary benefits systematically treats only government regulations with respect to environmental policies. In contrast, other regulatory policy baseline issues, such as those relating to energy, transportation, and health, are generally ignored, as have baseline issues that are associated to technology, demography, and the natural resource base.

Therefore, although the standard methodology is generally accepted and applied, a number of assumptions or judgements can lead to estimates of ancillary benefits in terms of US$/tC for a given country that differ by more than an order of magnitude. The least standardized, least transparent and most uncertain component for modelling ancillary benefits is the link from emissions to atmospheric concentrations, particularly in light of the importance of secondary particulates to public health.

Also, the above review reveals implicitly the lack of studies estimating non-health effects from GHG mitigation policies (damages from traffic crashes, the effects of air pollution on materials, and air pollution effects on crops losses, which have been shown to be quite high in some regions). Depending upon the GHG mitigation policies selected, some of this damage could well be reduced, but the nature of this relationship remains a speculative matter. More information can be found in sectoral studies reviewed in Chapter 9, but no comprehensive evaluation can be derived from them.

For all these reasons, it remains very challenging to arrive at quantitative estimates of the ancillary benefits of GHG mitigation policies. Despite the difficulties, it can be said that the ancillary benefits related to public health accrue over the short term, and under some circumstances can be a significant fraction of private (direct) mitigation costs. With respect to this category of impacts alone mortality tends to dominate. The exact magnitude, scale, and scope of these ancillary benefits varies with local geographical and baseline conditions; if the baseline scenario assumes a rapid decrease in non-GHG pollutant emissions, benefits may be low, especially in low density areas. Net ancillary costs (i.e., where the ancillary benefits are less than ancillary costs) may occur under certain conditions, but the models reviewed here are generally not designed to capture these effects. While most of the studies assessed above address ancillary benefits of explicit climate mitigation measures, it should be noted that in many cases, these ancillary benefits can be expected to be as least as important as climate mitigation for decision making. Hence, the terms co-benefits is also used in this report. Therefore, there is a strong need for more research in the area of integrated policies addressing climate mitigation alongside other environmental, social or economic objectives.

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