Validation of DNDC for 22 long-term N2O field emission measurements

Beheydt, Daan; Boeckx, Pascal; Sleutel, Steven; Li, Changsheng; Cleemput, Oswald Van

doi:10.1016/j.atmosenv.2007.04.003

Cited by 120 publications

(80 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The DNDC model has been adopted as a central model in the NitroEurope project (2005)(2006)(2007)(2008). The model has also been applied in many studies on greenhouse gas emissions from arable soils (Beheydt et al, 2007;Cai et al, 2003;Ludwig et al, 2011;Smith et al, 2008;Zhang et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

Field Validation of DNDC and SWAP Models for Temperature and Water Content of Loamy and Sandy Loam Spodosols

Balashov¹,

Buchkina²,

Rizhiya³

et al. 2014

International Agrophysics

View full text Add to dashboard Cite

A b s t r a c t. The objectives of the research were to: fulfil the preliminary assessment of the sensitivity of the soil, water, atmosphere, and plant and denitrification and decomposition models to variations of climate variables based on the existing soil database; validate the soil, water, atmosphere, and plant and denitrification and decomposition modelled outcomes against measured records for soil temperature and water content. The statistical analyses were conducted by the sensitivity analysis, Nash-Sutcliffe efficiency coefficients and root mean square error using measured and modelled variables during three growing seasons. Results of sensitivity analysis demonstrated that: soil temperatures predicted by the soil, water, atmosphere, and plant model showed a more reliable sensitivity to the variations of input air temperatures; soil water content predicted by the denitrification and decomposition model had a better reliability in the sensitivity to daily precipitation changes. The root mean square errors and Nash-Sutcliffe efficiency coefficients demonstrated that: the soil, water, atmosphere, and plant model had a better efficiency in predicting seasonal dynamics of soil temperatures than the denitrification and decomposition model; and among two studied models, the denitrification and decomposition model showed a better capability in predicting the seasonal dynamics of soil water content.K e y w o r d s: agroecosystem modelling, model validation, soil water content, soil temperature, Spodosols

show abstract

Section: Introductionmentioning

confidence: 99%

Field Validation of DNDC and SWAP Models for Temperature and Water Content of Loamy and Sandy Loam Spodosols

Balashov¹,

Buchkina²,

Rizhiya³

et al. 2014

International Agrophysics

View full text Add to dashboard Cite

show abstract

“…In the past 20 yr, the DNDC model has been proven to be effective in many places around the world, such as North America, Europe, Asia and Oceania (Li et al, 1996;Plant, 1999;Stange et al, 2000;Li, 2000;Zhang et al, 2002;Xu et al, 2003;Cai et al, 2003;Frolking et al, 2004;Grant et al, 2004;Smith et al, 2004;Butterbach-Bahl et al, 2004;Pathak et al, 2005;Jagadeesh Babu et al, 2005;Beheydt et al, 2007;Smith et al, 2010). Application of this model in China began in the late 1990s.…”

Section: Introductionmentioning

confidence: 99%

Modeling impacts of farming management practices on greenhouse gas emissions in the oasis region of China

et al. 2011

View full text Add to dashboard Cite

Abstract. Agricultural ecosystems are major sources of greenhouse gas (GHG) emissions, specifically nitrous oxide (N 2 O) and carbon dioxide (CO 2 ). An important method of investigating GHG emissions in agricultural ecosystems is model simulation. Field measurements quantifying N 2 O and CO 2 fluxes were taken in a summer maize ecosystem in Zhangye City, Gansu Province, in northwestern China in 2010. Observed N 2 O and CO 2 fluxes were used for validating flux predictions by a DeNitrification-DeComposition (DNDC) model. Then sensitivity tests on the validated DNDC model were carried out on three variables: climatic factors, soil properties and agricultural management. Results indicated that: (1) the factors that N 2 O emissions were sensitive to included nitrogen fertilizer application rate, manure amendment and residue return rate; (2) CO 2 emission increased with increasing manure amendment, residue return rate and initial soil organic carbon (SOC); and (3) net global warming potential (GWP) increased with increasing N fertilizer application rate and decreased with manure amendment, residue return rate and precipitation increase. Simulation of the long-term impact on SOC, N 2 O and net GWP emissions over 100 yr of management led to the conclusion that increasing residue return rate is a more efficient method of mitigating GHG emission than increasing fertilizer N application rate in the study area.

show abstract

“…Amongst process-oriented models, DNDC is one of the most well-established and has been widely validated (Wang et al, 1997, Butterbach-Bahl et al, 2001, Smith et al, 2002, Brown et al, 2002, Cai et al, 2003, Butterbach-Bahl et al, 2004, Grant et al, 2004, Babu et al, 2006, Beheydt et al, 2007, Abdalla et al, 2009 (Cai et al, 2003, Babu et al, 2006, Tonitto et al, 2007, Beheydt et al, 2007.…”

Section: Dndc Modelmentioning

confidence: 99%

“…LCA of wheat agro-eco-system 132 Butterbach-Bahl et al, 2001, Smith et al, 2002, Brown et al, 2002, Cai et al, 2003, Butterbach-Bahl et al, 2004, Grant et al, 2004, Babu et al, 2006, Beheydt et al, 2007, Abdalla et al, 2009). Furthermore, it has been applied to develop regional GHGs inventories in the USA (Li et al, 1996), New Zealand, UK (Brown et al, 2002), China (Qiu et al, 2009) and the EU (Levy et al, 2007).…”

Section: Lca Of Light-weight Eco-compositesmentioning

confidence: 99%

Life Cycle Assessment (LCA) of Light-Weight Eco-composites

Guo¹

2012

Springer Theses

View full text Add to dashboard Cite

LCA of Light-weight Eco-composites Statement of originality 2 Statement of originalityI hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person.Contributions made to the research of this thesis by others, with whom I have worked with are explicitly acknowledged. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others with data collection and modification of process-oriented model DNDC is acknowledged. Miao GuoSep 2010 LCA of Light-weight Eco-compositesAbstract 3 AbstractThe environmental profiles of novel wheat based foam materials were investigated in this thesis using Life Cycle Assessment (LCA) methods. The LCAs were developed using primary data collected from industrial sources combined with new laboratory experiments supplemented with secondary data from publicly available sources.Laboratory research was conducted to obtain important missing data on WBFs for the LCA modelling, including physico-chemical parameters, biodegradability and energy recovery under anaerobic digestion conditions.Contribution analysis suggested that the emissions evolved from the wheat agroecosystem and PVOH production, together with the energy and infrastructure involved in WBF production were the major contributors to the environmental burdens of the WBF life cycle in most impact categories. The atmospheric emissions resulting from WBF degradation at the end-of-life also emerged as another important contributor to environmental impact. Amongst the diverse ‗end-of-life' scenarios examined, AD and home composting were suggested to be the optimum choices for WBF waste treatment. This research discusses two N 2 O modelling approaches and presents a method to expand the system boundary by integrating the process-oriented model DNDC for field emissions into the LCA. Sensitivity analysis suggests that the environmental profiles of agricultural products are influenced substantially by the system boundary definition. LCA of Light-weight Eco-compositesAbstract 4 Furthermore, it suggests that the ‗general rule' in LCA practice by applying an empirical model or a default emission factor (EF) could deliver unreliable LCA findings.This study also evaluated the sensitivity of the LCA results to methodology and data variations and quantified the uncertainties in the LCA outcomes arising from uncertainty in the inventory and data variability. This has led to an increase in confidence in the LCA findings. At the same time it indicates the areas where improvements in data or methods are needed in order for robust conclusions to be drawn and unbiased information to be delivered e.g. the methodological rigidity of characterization models, the IPCC Tier 1 EF uncertainty range. LCA of Light-weight Eco-compositesAcknowledgements 5

show abstract

Validation of DNDC for 22 long-term N2O field emission measurements

Cited by 120 publications

References 52 publications

Field Validation of DNDC and SWAP Models for Temperature and Water Content of Loamy and Sandy Loam Spodosols

Field Validation of DNDC and SWAP Models for Temperature and Water Content of Loamy and Sandy Loam Spodosols

Modeling impacts of farming management practices on greenhouse gas emissions in the oasis region of China

Life Cycle Assessment (LCA) of Light-Weight Eco-composites

Contact Info

Product

Resources

About