On uncertainty in the computation of global emissions from biomass burning
Abstract Estimation of global atmospheric emissions from biomass burning has used a variety of procedures, most of which involve chain multiplication. The terms in the chain of inference are often poorly quantified, and in many cases there is reason to suspect bias and intercorrelation between terms...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Robinson, Jennifer M. [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
1989 |
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| Schlagwörter: |
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| Systematik: |
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| Anmerkung: |
© Kluwer Academic Publishers 1989 |
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| Übergeordnetes Werk: |
Enthalten in: Climatic change - Kluwer Academic Publishers, 1977, 14(1989), 3 vom: Juni, Seite 243-261 |
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| Übergeordnetes Werk: |
volume:14 ; year:1989 ; number:3 ; month:06 ; pages:243-261 |
| Links: |
|---|
| DOI / URN: |
10.1007/BF00134965 |
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| Katalog-ID: |
OLC2062579365 |
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| 520 | |a Abstract Estimation of global atmospheric emissions from biomass burning has used a variety of procedures, most of which involve chain multiplication. The terms in the chain of inference are often poorly quantified, and in many cases there is reason to suspect bias and intercorrelation between terms. The leading estimates appear to have been conservative; however, uncertainty explodes when imprecisely known (coefficient of variation >0.3) terms are multiplied. Thus little confidence can be had in the precision of current best estimates. The situation can be improved through a combination of spatial disaggregation and process-oriented modeling. | ||
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| 650 | 4 | |a Global Emission | |
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10.1007/BF00134965 doi (DE-627)OLC2062579365 (DE-He213)BF00134965-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn RA 1000 VZ rvk Robinson, Jennifer M. verfasserin aut On uncertainty in the computation of global emissions from biomass burning 1989 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 1989 Abstract Estimation of global atmospheric emissions from biomass burning has used a variety of procedures, most of which involve chain multiplication. The terms in the chain of inference are often poorly quantified, and in many cases there is reason to suspect bias and intercorrelation between terms. The leading estimates appear to have been conservative; however, uncertainty explodes when imprecisely known (coefficient of variation >0.3) terms are multiplied. Thus little confidence can be had in the precision of current best estimates. The situation can be improved through a combination of spatial disaggregation and process-oriented modeling. Biomass Burning Biomass Burning Chain Multiplication Global Emission Enthalten in Climatic change Kluwer Academic Publishers, 1977 14(1989), 3 vom: Juni, Seite 243-261 (DE-627)130479020 (DE-600)751086-X (DE-576)016068610 0165-0009 nnns volume:14 year:1989 number:3 month:06 pages:243-261 https://doi.org/10.1007/BF00134965 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-GEO SSG-OLC-IBL SSG-OPC-GGO GBV_ILN_11 GBV_ILN_22 GBV_ILN_40 GBV_ILN_47 GBV_ILN_70 GBV_ILN_130 GBV_ILN_154 GBV_ILN_601 GBV_ILN_2003 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2015 GBV_ILN_4012 GBV_ILN_4028 GBV_ILN_4103 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4305 GBV_ILN_4311 GBV_ILN_4325 RA 1000 AR 14 1989 3 06 243-261 |
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10.1007/BF00134965 doi (DE-627)OLC2062579365 (DE-He213)BF00134965-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn RA 1000 VZ rvk Robinson, Jennifer M. verfasserin aut On uncertainty in the computation of global emissions from biomass burning 1989 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 1989 Abstract Estimation of global atmospheric emissions from biomass burning has used a variety of procedures, most of which involve chain multiplication. The terms in the chain of inference are often poorly quantified, and in many cases there is reason to suspect bias and intercorrelation between terms. The leading estimates appear to have been conservative; however, uncertainty explodes when imprecisely known (coefficient of variation >0.3) terms are multiplied. Thus little confidence can be had in the precision of current best estimates. The situation can be improved through a combination of spatial disaggregation and process-oriented modeling. Biomass Burning Biomass Burning Chain Multiplication Global Emission Enthalten in Climatic change Kluwer Academic Publishers, 1977 14(1989), 3 vom: Juni, Seite 243-261 (DE-627)130479020 (DE-600)751086-X (DE-576)016068610 0165-0009 nnns volume:14 year:1989 number:3 month:06 pages:243-261 https://doi.org/10.1007/BF00134965 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-GEO SSG-OLC-IBL SSG-OPC-GGO GBV_ILN_11 GBV_ILN_22 GBV_ILN_40 GBV_ILN_47 GBV_ILN_70 GBV_ILN_130 GBV_ILN_154 GBV_ILN_601 GBV_ILN_2003 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2015 GBV_ILN_4012 GBV_ILN_4028 GBV_ILN_4103 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4305 GBV_ILN_4311 GBV_ILN_4325 RA 1000 AR 14 1989 3 06 243-261 |
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10.1007/BF00134965 doi (DE-627)OLC2062579365 (DE-He213)BF00134965-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn RA 1000 VZ rvk Robinson, Jennifer M. verfasserin aut On uncertainty in the computation of global emissions from biomass burning 1989 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 1989 Abstract Estimation of global atmospheric emissions from biomass burning has used a variety of procedures, most of which involve chain multiplication. The terms in the chain of inference are often poorly quantified, and in many cases there is reason to suspect bias and intercorrelation between terms. The leading estimates appear to have been conservative; however, uncertainty explodes when imprecisely known (coefficient of variation >0.3) terms are multiplied. Thus little confidence can be had in the precision of current best estimates. The situation can be improved through a combination of spatial disaggregation and process-oriented modeling. Biomass Burning Biomass Burning Chain Multiplication Global Emission Enthalten in Climatic change Kluwer Academic Publishers, 1977 14(1989), 3 vom: Juni, Seite 243-261 (DE-627)130479020 (DE-600)751086-X (DE-576)016068610 0165-0009 nnns volume:14 year:1989 number:3 month:06 pages:243-261 https://doi.org/10.1007/BF00134965 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-GEO SSG-OLC-IBL SSG-OPC-GGO GBV_ILN_11 GBV_ILN_22 GBV_ILN_40 GBV_ILN_47 GBV_ILN_70 GBV_ILN_130 GBV_ILN_154 GBV_ILN_601 GBV_ILN_2003 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2015 GBV_ILN_4012 GBV_ILN_4028 GBV_ILN_4103 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4305 GBV_ILN_4311 GBV_ILN_4325 RA 1000 AR 14 1989 3 06 243-261 |
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10.1007/BF00134965 doi (DE-627)OLC2062579365 (DE-He213)BF00134965-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn RA 1000 VZ rvk Robinson, Jennifer M. verfasserin aut On uncertainty in the computation of global emissions from biomass burning 1989 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 1989 Abstract Estimation of global atmospheric emissions from biomass burning has used a variety of procedures, most of which involve chain multiplication. The terms in the chain of inference are often poorly quantified, and in many cases there is reason to suspect bias and intercorrelation between terms. The leading estimates appear to have been conservative; however, uncertainty explodes when imprecisely known (coefficient of variation >0.3) terms are multiplied. Thus little confidence can be had in the precision of current best estimates. The situation can be improved through a combination of spatial disaggregation and process-oriented modeling. Biomass Burning Biomass Burning Chain Multiplication Global Emission Enthalten in Climatic change Kluwer Academic Publishers, 1977 14(1989), 3 vom: Juni, Seite 243-261 (DE-627)130479020 (DE-600)751086-X (DE-576)016068610 0165-0009 nnns volume:14 year:1989 number:3 month:06 pages:243-261 https://doi.org/10.1007/BF00134965 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-GEO SSG-OLC-IBL SSG-OPC-GGO GBV_ILN_11 GBV_ILN_22 GBV_ILN_40 GBV_ILN_47 GBV_ILN_70 GBV_ILN_130 GBV_ILN_154 GBV_ILN_601 GBV_ILN_2003 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2015 GBV_ILN_4012 GBV_ILN_4028 GBV_ILN_4103 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4305 GBV_ILN_4311 GBV_ILN_4325 RA 1000 AR 14 1989 3 06 243-261 |
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10.1007/BF00134965 doi (DE-627)OLC2062579365 (DE-He213)BF00134965-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn RA 1000 VZ rvk Robinson, Jennifer M. verfasserin aut On uncertainty in the computation of global emissions from biomass burning 1989 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 1989 Abstract Estimation of global atmospheric emissions from biomass burning has used a variety of procedures, most of which involve chain multiplication. The terms in the chain of inference are often poorly quantified, and in many cases there is reason to suspect bias and intercorrelation between terms. The leading estimates appear to have been conservative; however, uncertainty explodes when imprecisely known (coefficient of variation >0.3) terms are multiplied. Thus little confidence can be had in the precision of current best estimates. The situation can be improved through a combination of spatial disaggregation and process-oriented modeling. Biomass Burning Biomass Burning Chain Multiplication Global Emission Enthalten in Climatic change Kluwer Academic Publishers, 1977 14(1989), 3 vom: Juni, Seite 243-261 (DE-627)130479020 (DE-600)751086-X (DE-576)016068610 0165-0009 nnns volume:14 year:1989 number:3 month:06 pages:243-261 https://doi.org/10.1007/BF00134965 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-UMW SSG-OLC-GEO SSG-OLC-IBL SSG-OPC-GGO GBV_ILN_11 GBV_ILN_22 GBV_ILN_40 GBV_ILN_47 GBV_ILN_70 GBV_ILN_130 GBV_ILN_154 GBV_ILN_601 GBV_ILN_2003 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2015 GBV_ILN_4012 GBV_ILN_4028 GBV_ILN_4103 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4305 GBV_ILN_4311 GBV_ILN_4325 RA 1000 AR 14 1989 3 06 243-261 |
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on uncertainty in the computation of global emissions from biomass burning |
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On uncertainty in the computation of global emissions from biomass burning |
| abstract |
Abstract Estimation of global atmospheric emissions from biomass burning has used a variety of procedures, most of which involve chain multiplication. The terms in the chain of inference are often poorly quantified, and in many cases there is reason to suspect bias and intercorrelation between terms. The leading estimates appear to have been conservative; however, uncertainty explodes when imprecisely known (coefficient of variation >0.3) terms are multiplied. Thus little confidence can be had in the precision of current best estimates. The situation can be improved through a combination of spatial disaggregation and process-oriented modeling. © Kluwer Academic Publishers 1989 |
| abstractGer |
Abstract Estimation of global atmospheric emissions from biomass burning has used a variety of procedures, most of which involve chain multiplication. The terms in the chain of inference are often poorly quantified, and in many cases there is reason to suspect bias and intercorrelation between terms. The leading estimates appear to have been conservative; however, uncertainty explodes when imprecisely known (coefficient of variation >0.3) terms are multiplied. Thus little confidence can be had in the precision of current best estimates. The situation can be improved through a combination of spatial disaggregation and process-oriented modeling. © Kluwer Academic Publishers 1989 |
| abstract_unstemmed |
Abstract Estimation of global atmospheric emissions from biomass burning has used a variety of procedures, most of which involve chain multiplication. The terms in the chain of inference are often poorly quantified, and in many cases there is reason to suspect bias and intercorrelation between terms. The leading estimates appear to have been conservative; however, uncertainty explodes when imprecisely known (coefficient of variation >0.3) terms are multiplied. Thus little confidence can be had in the precision of current best estimates. The situation can be improved through a combination of spatial disaggregation and process-oriented modeling. © Kluwer Academic Publishers 1989 |
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On uncertainty in the computation of global emissions from biomass burning |
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