sectoral economic costs and benefits of ghg mitigation - IPCC

Terry Barker, Lenny Bernstein, Ken Gregory, Steve Lennon and Julio Torres Martinez
Discussion on Bioenergy
José Roberto Moreira, of the Biomass Users Network, Brazil discussed the externalities related to
biomass energy – focusing on ethanol production and use and the public health impacts due to
the use of gasoline, diesel and coal. He highlighted the following positive externalities for
ethanol:
• increased employment,
• improved balance of trade,
• increased state tax receipts,
• enhanced energy security, and
• reduced imports of oil,
and the following negative externalities for the use of fossil fuels:
• increase local and regional air pollution, and
• increased public health expenditures in developing countries.
In assessing the social costs of ethanol, it is clear that there are gains and losses, according to
different author's evaluations. For fossil fuel use public health damages are significant. He
concluded that there are so many different approaches used in the literature that accurate
quantification and comparison are virtually impossible. However, it is clear that social costs can
be even higher than private costs. This means that social costs must be considered and that
information forwarded to policymakers as a tool for evaluating countries' policies. As such it is
essential to establish a methodology for quantifying externalities which can be consistently
applied across countries and sectors.
General Discussion
During the general discussion the following points were made relating to Criqui’s presentation:
• Oliver Headley indicated that PV investment costs are coming down rapidly so investment
costs included in the model must be reflected as decreasing. Criqui responded that whilst PV
costs are clearly decreasing, this decrease is taken as exogenous for "rural photovoltaics"
technology under the two scenarios included in the presentation.
• Lenny Bernstein commented that the model is based on the premise that public energy R&D
is seen as a proxy for a pool of knowledge. This is not always the case; for example in
sectors such as coal, oil and gas private investment is the primary source of information,
hence this data may not be in a common pool. Criqui responded that the key variable
required is the sum of public and private sector R&D. This variable is indeed used in the
model, however, data on business R&D are scarce and work is still needed in order to
improve them and increase the reliability of results.
• Ken Gregory mentioned that the model simulates R&D decision behaviour. This can be
critically influenced by discount rate, and as such, the rate used in the utility sector should be
considered. Criqui's response was that the R&D investment decision is not always taken by
the electricity sector, especially when it comes to supply side technology development. In
this case the R&D investment decision is usually taken by equipment manufacturers. The
technology end use decision is usually taken by the utilities, for which a typical discount rate
of 9% was applied in the model.
• Jonathan Pershing commented that the figures used are heavily weighted in terms of USA
R&D investment due to the high level of USA public and private sector investment in energy
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