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 OConnor (1999) estimate benefits of about US$250/tC, as compared to US$62/tC in Cifuentes et al. (2000). Half of the Dessus and OConnor (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 leadIQ 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 OConnor (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 OConnor (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 OConnor (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$68/tC.
These differences are explained by:
The diffusion of methods and key studies to estimate health effects and their
monetization has contributed to a reasonable degree of standardization in the
literature. However, some of the differences in estimates result from different
assumptions and/or methodologies used to estimate them:
Therefore, although the standard methodology is generally accepted and applied, a number of assumptions or judgements can lead to estimates of ancillary benefits in terms of US$/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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