INASUD project findings on integrated assessment of climate policies

This communication summarizes the main findings of INASUD, an European-wide research project on integrated assessment of climate policies. The project aimed at improving the framing of climate policy analysis through the parallel use of various existing integrated assessment models. It provides a comprehensive examination of the link between uncertainty regarding damages and inertia in economic systems. Results show that the Kyoto targets and timing are consistent with the precautionary principle but offers little insurance for longer-term climate protection. Flexibility mechanisms offer potentials for cooperation with developing countries, and are necessary to tap the environmental and economic benefits of joint carbon and sulfur emissions abatement.     

Artificial neural network based carbon monoxide persistence models for episodic urban air quality management

This paper describes the development of artificial neural network (ANN) based carbon monoxide (CO) persistence (ANNCOP) models to forecast 8-h average CO concentration using 1-h maximum predicted CO data for the critical (winter) period (November–March). The models have been developed for three 8-h groupings of 10 p.m. to 6 a.m., 6 a.m. to 2 p.m. and 2–10 p.m., at two air quality control regions (AQCRs) in Delhi city, representing an urban intersection and an arterial road consisting heterogeneous traffic flows. The result indicates that time grouping of 2–10 pm is dominantly affected by inversion conditions and peak traffic flow. The ANNCOP model corresponding to this grouping predicts the 8-h average CO concentrations within the accuracy range of 68–71%. The CO persistence values derived from ANNCOP model are comparable with the persistence values as suggested by the Environmental Protection Agency (EPA), USA. This work demonstrates that ANN based model is capable of describing winter period CO persistence phenomena.     

Using Multi-Scale Sampling and Spatial Cross-Correlation to Investigate Patterns of Plant Species Richness

Land managers need better techniques to assess exoticplant invasions. We used the cross-correlationstatistic, I _YZ, to test for the presence ofspatial cross-correlation between pair-wisecombinations of soil characteristics, topographicvariables, plant species richness, and cover ofvascular plants in a 754 ha study site in RockyMountain National Park, Colorado, U.S.A. Using 25 largeplots (1000 m²) in five vegetation types, 8 of 12variables showed significant spatial cross-correlationwith at least one other variable, while 6 of 12variables showed significant spatial auto-correlation. Elevation and slope showed significant spatialcross-correlation with all variables except percentcover of native and exotic species. Percent cover ofnative species had significant spatialcross-correlations with soil variables, but not withexotic species. This was probably because of thepatchy distributions of vegetation types in the studyarea. At a finer resolution, using data from ten1 m² subplots within each of the 1000 m² plots, allvariables showed significant spatial auto- andcross-correlation. Large-plot sampling was moreaffected by topographic factors than speciesdistribution patterns, while with finer resolutionsampling, the opposite was true. However, thestatistically and biologically significant spatialcorrelation of native and exotic species could only bedetected with finer resolution sampling. We foundexotic plant species invading areas with high nativeplant richness and cover, and in fertile soils high innitrogen, silt, and clay. Spatial auto- andcross-correlation statistics, along with theintegration of remotely sensed data and geographicinformation systems, are powerful new tools forevaluating the patterns and distribution of native andexotic plant species in relation to landscape structure.     

The Role of Abatement Costs in GHG Permit Allocations: A Global Stabilization Scenario Analysis

Our objective is to propose permit allocation schemes that lead to a fair distribution of the net abatement cost among regions in a global greenhouse gas (GHG) stabilization scenario. We use a detailed technology-based energy model, World-MARKAL, to determine efficient abatement decisions, and to calculate the regional gross abatement costs (before permit allocation and trading). The net abatement costs are then calculated and used for different permit allocation schemes.     

Coupling upland watershed and downstream waterbody hydrodynamic and water quality models (SWAT and CE-QUAL-W2) for better water resources management in complex river basins

Effective water resources management programs have always incorporated detailed analyses of hydrological and water quality processes in the upland watershed and downstream waterbody. We have integrated two powerful hydrological and water quality models (SWAT and CE-QUAL-W2) to simulate the combined processes of water quantity and quality both in the upland watershed and downstream waterbody. Whereas the SWAT model outputs water quality variables in its entirety, the CE-QUAL-W2 model requires inputs in various pools of organic matter contents. An intermediate program was developed to extract outputs from SWAT at required subbasin and reach outlets and converts them into acceptable CE-QUAL-W2 inputs. The CE-QUAL-W2 model was later calibrated for various hydrodynamic and water quality simulations in the Cedar Creek Reservoir, TX, USA. The results indicate that the two models are compatible and can be used to assess and manage water resources in complex watersheds comprised of upland watershed and downstream waterbodies.     

Multi-stand Forest Management under a Climatic Risk: Do Time and Risk Preferences Matter?

We propose a stochastic dynamic programming framework to model the management of a multi-stand forest under climate risk (strong wind occurrence). The preferences of the forest-owner are specified by a non-expected utility in order to separately analyze intertemporal substitution and risk aversion effects. A numerical method is developed to characterize the optimal forest management policies and the optimal consumption-saving strategy. The stochastic dynamic programming framework is applied to a non-industrial private forest-owner located in North-East of France. We show that the optimal decisions both depend upon risk and time preferences. The authors would like to thank participants at the international conference on Economics of Sustainable Forest Management in Toronto, at the PARIS 1 seminar on Environmental and Natural Resource Economics, at the 2004 Applied Microeconomics Conference in Lille and at the 13th annual conference of the European Association of Environmental and Resource Economists at Budapest.     

Hydrologic–Economic Model for Managing Irrigation Intensity in Irrigation Areas under Watertable and Soil Salinity Targets

This paper gives mathematical details and sample applications of SWAGMAN Farm (SWAGMAN, Salt Water and Groundwater Management), a farm-scale hydrologic economic model that integrates agronomic, climatic, irrigation, hydrogeological and economic aspects of irrigated agriculture. The model is capable of determining optimum mix of land use to keep watertable and soil salinity within acceptable limits while maximising the economic returns. Alternatively, the model can simulate water and salt balance and economics of a given cropping preference. Web-based and Geographic Information Systems versions of the model are available for integration with the environmental reporting systems of the irrigation areas.     

Optimal Selection of Priority Development Areas Considering Tradeoffs Between Hydrology and Development Configuration

Mixed-integer linear programs are proposed for siting development and conservation areas in watersheds, addressing economic objectives (development perimeter and proximity) and ecological objectives. Links between watershed hydrology and ecology need not be well defined. Parameters for the linear programs are obtained from linearization of the SWAT hydrologic model.     

Modeling Acidification Recovery on Threatened Ecosystems: Application to the Evaluation of the Gothenburg Protocol in France

To evaluate the acid deposition reduction negotiated for 2010 within the UNECE LRTAP Gothenburg Protocol, sulphur and nitrogen deposition time-series (1880–2100) were compared to critical loads of acidity on five French ecosystems: Massif Central basalt (site 1) and granite (2); Paris Bassin tertiary sands (3); Vosges mountains sandstone (4) and Landes eolian sands (5). The SAFE model was used to estimate the response of soil solution pH and ratio to the deposition scenario. Among the five sites, critical loads were exceeded in the past at sites 3, 4 and 5. Sites 3 and 4 were still expected to exceed in 2010, the Protocol year. Further reduction of atmospheric deposition, mainly nitrogen, would be needed to achieve recovery on these ecosystems. At sites 3, 4 and 5, the delay between the critical load exceedance and the violation of the critical chemical criterion was estimated to be 10 to 30 years in the top soil and 50 to 90 years in the deeper soil. At site 5, a recovery was expected in the top soil in 2010 with a time lag of 10 years. Unexpectedly, soil pH continued to decrease after 1980 in the deeper soil at sites 2 and 5. This time lag indicated that acidification moved down the soil profile as a consequence of slow base cation depletion by ion exchange. This delayed response of the soil solution was the result of the combination of weathering rates and vegetation uptake but also of the relative ratio between base cation deposition and acid compounds.