A tool to link agricultural activity data with the DNDC model to estimate GHG emission factors in Canada

Smith, Ward; Grant, Brian; Desjardins, R. L.; Worth, Devon E.; Li, C.; Boles, Stephen; Huffman, E.C.

doi:10.1016/j.agee.2009.12.008

Cited by 95 publications

(53 citation statements)

References 25 publications

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“…The latter has the advantage to detect immediate or near-immediate effects of management practices on C loss via emissions. The impact of tillage on the loss of SOC and associated emission factors under different management systems has been studied (Smith et al, 2010;La Scala et al, 2008; La Scala et al, 2009 a,b), and some researchers have used tillage emission factors as bias for estimating soil conversion from conventional to no-till. However, Smith et al (2010) noted that this conversion can be affected by the depth of tillage, and multiple factors should be developed to reduce estimation errors.…”

Section: Introductionmentioning

confidence: 99%

“…The impact of tillage on the loss of SOC and associated emission factors under different management systems has been studied (Smith et al, 2010;La Scala et al, 2008; La Scala et al, 2009 a,b), and some researchers have used tillage emission factors as bias for estimating soil conversion from conventional to no-till. However, Smith et al (2010) noted that this conversion can be affected by the depth of tillage, and multiple factors should be developed to reduce estimation errors.Agricultural activities contribute with approximately 20 % to the global greenhouse gas emissions (Lokupitiya and Paustian, 2006). No-till farming combined with the maintenance of crop residues on the soil surface has been identifi ed as an important strategy for sequestering carbon (C) from the atmosphere (Lal, 2007).…”

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confidence: 99%

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Soil and crop residue CO2-C emission under tillage systems in sugarcane-producing areas of southern Brazil

Teixeira

Corradi

Fukuda

et al. 2013

Sci. agric. (Piracicaba, Braz.)

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Appropriate management of agricultural crop residues could result in increases on soil organic carbon (SOC) and help to mitigate gas effect. To distinguish the contributions of SOC and sugarcane (Saccharum spp.) residues to the short-term CO 2 -C loss, we studied the infl uence of several tillage systems: heavy offset disk harrow (HO), chisel plow (CP), rotary tiller (RT), and sugarcane mill tiller (SM) in 2008, and CP, RT, SM, moldboard (MP), and subsoiler (SUB) in 2009, with and without sugarcane residues relative to no-till (NT) in the sugarcane producing region of Brazil. Soil CO 2 -C emissions were measured daily for two weeks after tillage using portable soil respiration systems. Daily CO 2 -C emissions declined after tillage regardless of tillage system. In 2008, total CO 2 -C from SOC and/or residue decomposition was greater for RT and lowest for CP. In 2009, emission was greatest for MP and CP with residues, and smallest for NT. SOC and residue contributed 47 % and 41 %, respectively, to total CO 2 -C emissions. Regarding the estimated emissions from sugarcane residue and SOC decomposition within the measurement period, CO 2 -C factor was similar to sugarcane residue and soil organic carbon decomposition, depending on the tillage system applied. Our approach may defi ne new emission factors that are associated to tillage operations on bare or sugarcane-residue-covered soils to estimate the total carbon loss.Keywords: soil respiration, carbon dioxide, emission after tillage, soil organic carbon IntroductionLosses of soil organic carbon (SOC) due to soil management in agricultural areas have been identifi ed as a factor that accelerates the greenhouse effect, especially by emitting CO 2 in the atmosphere (Eugster et al., 2010). Losses of SOC can be assessed either by directly measuring changes in SOC content or by monitoring soil CO 2 emissions. The latter has the advantage to detect immediate or near-immediate effects of management practices on C loss via emissions. The impact of tillage on the loss of SOC and associated emission factors under different management systems has been studied (Smith et al., 2010;La Scala et al., 2008; La Scala et al., 2009 a,b), and some researchers have used tillage emission factors as bias for estimating soil conversion from conventional to no-till. However, Smith et al. (2010) noted that this conversion can be affected by the depth of tillage, and multiple factors should be developed to reduce estimation errors.Agricultural activities contribute with approximately 20 % to the global greenhouse gas emissions (Lokupitiya and Paustian, 2006). No-till farming combined with the maintenance of crop residues on the soil surface has been identifi ed as an important strategy for sequestering carbon (C) from the atmosphere (Lal, 2007). Tillage induces the loss of C as CO 2 by breaking up soil aggregates and exposing the protected organic matter to microbes. Tillage also incorporates and mixes residues, improving aeration, which can lead to additional C losses by maximizin...

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Soil and crop residue CO2-C emission under tillage systems in sugarcane-producing areas of southern Brazil

Teixeira

Corradi

Fukuda

et al. 2013

Sci. agric. (Piracicaba, Braz.)

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“…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

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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.

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“…Research has been carried out to compare different modelling methods for field emissions (Frolking et al, 1998, Li et al, 2005, Hutchinson et al, 2007, David et al, 2009, Smith et al, 2010. Notably, studies by and Hutchinson et al(2007) compared IPCC and DNDC and found that both models gave similar estimations of annual national inventory of direct N 2 O emission although geographical patterns differed.…”

Section: Simulation Models and Lcamentioning

confidence: 99%

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

Guo¹

2012

Springer Theses

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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

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A tool to link agricultural activity data with the DNDC model to estimate GHG emission factors in Canada

Cited by 95 publications

References 25 publications

Soil and crop residue CO2-C emission under tillage systems in sugarcane-producing areas of southern Brazil

Soil and crop residue CO2-C emission under tillage systems in sugarcane-producing areas of southern Brazil

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

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