logging in or signing up EAGER UNECE 2007 Kestrel Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINTLite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 24 Category: Entertainment License: All Rights Reserved Like it (0) Dislike it (0) Added: October 15, 2007 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript EAGEREuropean Agricultural Gaseous Emissions Inventory Researchers NetworkUpdate 2007: EAGER European Agricultural Gaseous Emissions Inventory Researchers Network Update 2007 Participants Denmark: Nick Hutchings Germany: Ulrich Daemmgen & Dieter Haenel, FAL; Helmut Doehler, KTBL; Netherlands: Gert-Jan Monteny, IMAG; F.K. van Evert, PRI; H.H. Luesink, LEI Sweden: Lena Rodhe, JTI Switzerland: Harald Menzi and Beat Reidy, SHL UK: Jim Webb, AEA Energy & Environment; Tom Misselbrook, IGER Affiliated: Zig Klimont, IIASASlide2: Why EAGER ? Check comparability and reliability of existing inventory methods quality control; improvement of methods Develop inventories suitable for reporting under the convention Present inventories are not sufficient for time series: insufficient information on farming practice (expert assumptions); not all influencing factors considered Better harmonisation of inventory approaches Common general approach Comparable emission factors Comparable presentation of resultsSlide3: Past activities Analysis of the situation and the existing problems associated with inventory making Detailed introduction of the methods developed/used by members Compilation and comparison of N excretions Compilation and comparison of emission factors Congruency testing of models for slurry systems (calculations with common model scenarios; cattle and pigs) Paper accepted for publication in Atmospheric Environment Slide4: Current activities Extension of congruency testing exercise to solid manure systems (calculations with common model scenarios; beef cattle and broilers) Work still under progress Situation appeared to be even more complex than that for slurry systems N transformation processes (mineralization, immobilization) Relevance of other N losses N2O)Congruency testing: Beef FF scenario (fixed emission factors, fixed N excretions): Congruency testing: Beef FF scenario (fixed emission factors, fixed N excretions) Bad agreement of total emissions and emissions from individual emission stages What are the reasons?Congruency testing: Beef FF scenario (fixed emission factors, fixed N excretions): Congruency testing: Beef FF scenario (fixed emission factors, fixed N excretions) Agreement is much better if immobilization of TAN in bedding material and other N losses are accounted for Models differ highly to the extend these processes are taken into account Significance of N immobilization and other N lossesSlide7: Conclusions for solid manure scenarios Individual models differ highly with respect to the degree immobilisation of TAN and other N losses (N2O) are accounted for If these two processes are included in the comparisons, the different models generally compare very well Variation of NH3 emissions is much higher than for slurry systems Need for a better understanding of the size of other N losses and the role of N transformation processes Conclusions after 4 years of EAGER: Conclusions after 4 years of EAGER Thorough and critical analysis of models and intensive exchange between participants Weaknesses of all models recognized and improved all partners and models profited from the exercise Starting harmonization between calculation procedures Evidence of good comparability between N-flow models Indication that models are following the same general procedure and are based on comparable data and assumptions Relatively good agreement for slurry scenarios, variation is much higher for solid manure scenarios You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.
EAGER UNECE 2007 Kestrel Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINTLite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 24 Category: Entertainment License: All Rights Reserved Like it (0) Dislike it (0) Added: October 15, 2007 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... Premium member Presentation Transcript EAGEREuropean Agricultural Gaseous Emissions Inventory Researchers NetworkUpdate 2007: EAGER European Agricultural Gaseous Emissions Inventory Researchers Network Update 2007 Participants Denmark: Nick Hutchings Germany: Ulrich Daemmgen & Dieter Haenel, FAL; Helmut Doehler, KTBL; Netherlands: Gert-Jan Monteny, IMAG; F.K. van Evert, PRI; H.H. Luesink, LEI Sweden: Lena Rodhe, JTI Switzerland: Harald Menzi and Beat Reidy, SHL UK: Jim Webb, AEA Energy & Environment; Tom Misselbrook, IGER Affiliated: Zig Klimont, IIASASlide2: Why EAGER ? Check comparability and reliability of existing inventory methods quality control; improvement of methods Develop inventories suitable for reporting under the convention Present inventories are not sufficient for time series: insufficient information on farming practice (expert assumptions); not all influencing factors considered Better harmonisation of inventory approaches Common general approach Comparable emission factors Comparable presentation of resultsSlide3: Past activities Analysis of the situation and the existing problems associated with inventory making Detailed introduction of the methods developed/used by members Compilation and comparison of N excretions Compilation and comparison of emission factors Congruency testing of models for slurry systems (calculations with common model scenarios; cattle and pigs) Paper accepted for publication in Atmospheric Environment Slide4: Current activities Extension of congruency testing exercise to solid manure systems (calculations with common model scenarios; beef cattle and broilers) Work still under progress Situation appeared to be even more complex than that for slurry systems N transformation processes (mineralization, immobilization) Relevance of other N losses N2O)Congruency testing: Beef FF scenario (fixed emission factors, fixed N excretions): Congruency testing: Beef FF scenario (fixed emission factors, fixed N excretions) Bad agreement of total emissions and emissions from individual emission stages What are the reasons?Congruency testing: Beef FF scenario (fixed emission factors, fixed N excretions): Congruency testing: Beef FF scenario (fixed emission factors, fixed N excretions) Agreement is much better if immobilization of TAN in bedding material and other N losses are accounted for Models differ highly to the extend these processes are taken into account Significance of N immobilization and other N lossesSlide7: Conclusions for solid manure scenarios Individual models differ highly with respect to the degree immobilisation of TAN and other N losses (N2O) are accounted for If these two processes are included in the comparisons, the different models generally compare very well Variation of NH3 emissions is much higher than for slurry systems Need for a better understanding of the size of other N losses and the role of N transformation processes Conclusions after 4 years of EAGER: Conclusions after 4 years of EAGER Thorough and critical analysis of models and intensive exchange between participants Weaknesses of all models recognized and improved all partners and models profited from the exercise Starting harmonization between calculation procedures Evidence of good comparability between N-flow models Indication that models are following the same general procedure and are based on comparable data and assumptions Relatively good agreement for slurry scenarios, variation is much higher for solid manure scenarios