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Authors :. Julio Lumbreras Rafael Borge. Spain’s Emission Projection Project: Agriculture. Ministry of Environment Technical University of Madrid. Friday, 28 th February 2003. Introduction. Targets of the work. - To obtain emission projections for the period 2001-2020
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Authors: Julio Lumbreras Rafael Borge Spain’s Emission Projection Project: Agriculture Ministry of Environment Technical University of Madrid
Friday, 28th February 2003 Introduction Targets of the work - To obtain emission projections for the period 2001-2020 - Pollutants considered: - Geneva Convention - Kyoto Protocol • To determine possible future scenarios • To estimate the efficiency of the adopted measures in each scenario • To evaluate the fulfilment of the Directives and the Protocols • Cost-Benefit analysis
Friday, 28th February 2003 Projection Methodology - According to the EEA and EPAmethodological framework • The projections are evaluated on country yearly base (assessment for each SNAP activity) • Considerations: • Technological • Socioeconomic • Statistical • Legislative Hypothesis: - Activity rate - Emission factors - Emission trends = SCENARIO
Friday, 28th February 2003 Types of scenarios • In accordance with the CAFE criteria, the scenarios are divided into three general groups or types: Baseline:taking into account the past emission trend exclusively Business As Usual (BAU):the more likely situation of air emissions considering approved legislationand adopted plans, measures and policies. Target: the environmental objectives are reached through additional measures (e.g. good practices, technical improvements, furtherpolicies, etc.). NOX, SO2, NMVOC, NH3 emissions NEC 2010 1990 2000 Year Kyoto CO2-eq. emissions 2010 1990 2000 Year
Reached? Method for calculation Results Kyoto Protocol NEC Evaluated emissions Basis information Hypothesis Emission data (Inventory) Socioeconomic data Sectoral studies Legislation Technological aspects - Rate activity trend (A) - Emission factor trend (FE) - Emission trend (E) - Control Factor (FC) and Growth Factor (G) Friday, 28th February 2003 Specific methodology for the activity projection: YES NO CONCLUSIONS SCENARIOS Baseline BAU Definition of a Target scenario
Suitability criteria VA = activity rate VA 2 VA 1 Proj 1 Projection evaluation SNAP 1 Proj 2 SNAP 2 Proj ... SNAP ... ΣProj Linked activities Hypothesis harmonization Relations and implications Macro scenario Friday, 28th February 2003 Integration criteria • ‘Macroscenarios’ to achieve a coherent cohesion • Software: EmiPro 1.0
Doubts Projection Raw information Inventory assessment Friday, 28th February 2003 SNAP 10- AGRICULTURE Same methodology for the emission evaluation as the one used for the Spanish National Inventory Scheme of the presentation: - Base information - Main problems during the projection
Friday, 28th February 2003 SNAP 10.01- Cultures with fertilisers except animal manure Base information: - Climate and land characteristics - Amount and type of fertiliser applied - Cultivated surface area - Crop species - Production data (harvested product) • Problems: • - Projecting the surface area cultivated and its efficiency • - Evaluating the future trend of some types of fertilisers and the possible alternatives • - Projecting the amount of the culture waste • - Is it worth to use such a elaborated methodology for • N2O emission assessment?
Friday, 28th February 2003 SNAP 10.04- Enteric fermentation Base information: - Number of heads of the animal population for the different species and categories considered (Agriculture Ministry) - Secondary emission factors (they include the specific methodology for each species and category (Tier 2 approach, IPCC) Problems: - Future changes in assessing the gross energy required
Friday, 28th February 2003 SNAP 10.05- Manure management regarding organic compounds Base information: - Number of heads of each species - Average annual temperature - Average daily amount of volatile excrement solids - Potential methane emission factor - Distribution of the manure management systems (MMS) Problems: - Evaluating the future trend of MMS distribution - Knowing the evolution of the pasture percentage for each type of animal
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