The authors used the terrestrial ecosystem model (TEM, version 4.0) to estimate global responses of annual net primary production (NPP) and total carbon storage to changes in climate and atmospheric CO2, driven by the climate outputs from the 2-dimensional MIT L-O climate model and the 3-dimensional GISS and GFDL-q atmospheric general circulation models (GCMs). For contemporary climate with 315 ppmv CO2, TEM estimates that global NPP is 47.9 PgC/yr and global total carbon storage is 1658 PgC: 908 PgC of vegetation carbon and 750 PgC of reactive soil organic carbon. For climate change associated with a doubling of radiative forcing and an atmospheric level of 522 ppmv CO2, the responses of global NPP are +17.8% for the MIT L-O climate, +18.5% for the GFDL-q climate and +20.6% for the GISS climate. The responses of global total carbon storage are +6.9% for the MIT L-O climate, +8.3% for GFDL-q climate and +8.7% for the GISS climate. Among the three climate change predictions, the changes in latitudinal distributions of cumulative NPP and total carbon storage along 0.5^o latitudinal bands vary slightly, except in high latitudes. There are generally minor differences in cumulative NPP and total carbon storage for most of the 18 biomes, except for the responses of total carbon storage in boreal biomes for the 2-D MIT L-O climate change. The results demonstrate that the linkage between the TEM and the 2-D climate model is useful for impact assessment and uncertainty analysis within an integrated assessment framework at the scales of the globe, economic regions and biomes, given the compromise between computational efficiency in the 2-D climate model and more detailed spatial representation of climate fields in 3-D GCMs.

© 1997 John Wiley & Sons, Inc.
 

We have incorporated a reduced-form urban air chemistry model in MIT's 2D-LO coupled chemistry-climate model. The computationally efficient reduced-form urban model is derived from the California Institute of Technology-Carnegie Institute of Technology (at Carnegie Mellon University) Urban Airshed Model by employing the probabilistic collocation method. To study the impact of urban air pollution on global chemistry and climate we carried out three simulations each including or excluding the reduced-form urban model for the time period from 1977 to 2100. In all three runs we use identical emissions, however in the two runs involving the reduced-form urban model the emissions assigned to urban areas are allocated in different ways depending on the scenario we assume for the future development of polluted urban areas. These two simulations are compared to the reference, which does not utilize the reduced-form urban model. We find that the incorporation of the urban air chemistry processes leads to lower global tropospheric NOx, ozone, and OH concentrations, but to a higher methane mole fraction than in the reference. The tropospheric mole fraction of CO is altered either up or down depending on the projections of urban emissions. The global mean surface temperature is effected very little by the implementation of the reduced-form urban model because predicted increases in CH4 are offset in part by decreases in O3 leading to only small changes in overall radiative forcing.

Marginal abatement cost (MAC) curves, relationships between tons of emissions abated and the CO2 (or GHG) price, have been widely used as pedagogic devices to illustrate simple economic concepts such as the benefits of emissions trading. They have also been used to produce reduced form models to examine situations where solving the more complex model underlying the MAC is difficult. Some important issues arise in such applications: (1) are MAC relationships independent of what happens in other regions? (2) are MACs stable through time regardless of what policies have been implemented in the past?, and (3) can one approximate welfare costs from them? This paper explores the basic characteristics of MAC and marginal welfare cost (MWC) curves, deriving them using the MIT Emissions Prediction and Policy Analysis (EPPA) model. We find that, depending on the method used to construct them, MACs are affected by policies abroad. They are also dependent on policies in place in the past and depend on whether they are CO2-only or include all GHGs. Further, we find that MACs are, in general, not closely related to MWCs and therefore should not be used to derive estimates of welfare change. It would be a great convenience if a reduced-form response of a more complex model could be used to reliably conduct empirical analysis of climate change policy, but it appears that, at least as commonly constructed, MACs may be unreliable in replicating results of the parent model when used to simulate GHG policies. This is especially true if the policy simulations differ from the conditions under which the MACs were simulated. Care is needed to derive MACs under conditions closely related to the policy under consideration. In such a circumstance they may provide approximate estimates of CO2 or GHG prices for a given policy constraint. They remain a convenient way to visualize responses to a range of abatement levels.

Appendix A: Data Tables (MS Excel file: 340 kB)
Appendix B: A Comparison of U.S. Marginal Abatement Cost Curves from a McKinsey & Co. Study with Results from the MIT EPPA Model

The prospect that governments of one or a few large countries, or trading blocs, would engage in international greenhouse gas emissions trading has led several policy analysts to express concerns that trade would be influenced by market power. The experiment reported here mimics a case where twelve countries, one of which is a large buyer (the mirror-image of a large seller), trade carbon emissions on an emissions exchange (a double-auction market) and where traders have quite accurate information about the underlying net demand. The findings deviate from those of the standard version of market power effects in that trade volumes and prices converge on competitive levels.