scholarly journals Multifactor effects on the N2O emissions and yield of potato fields based on the DNDC model

2021 ◽  
Author(s):  
Liwei Wang ◽  
Kai Zhang ◽  
Kangjun Guo ◽  
Limin Liu ◽  
Tao Zhang ◽  
...  
Keyword(s):  
N2o Emissions ◽  
Dndc Model

Simulation of NO and N2O emissions from a spruce forest during a freeze/thaw event using an N-flux submodel from the PnET-N-DNDC model integrated to CoupModel

2008 ◽  
Vol 216 (1) ◽  
pp. 18-30 ◽  
Author(s):  
Josefine Norman ◽  
Per-Erik Jansson ◽  
Neda Farahbakhshazad ◽  
Klaus Butterbach-Bahl ◽  
Changsheng Li ◽  
...  
Keyword(s):  
N2o Emissions ◽  
Spruce Forest ◽  
Dndc Model ◽  
Freeze Thaw ◽  
N Flux

scholarly journals Mitigation of CO2 and N2O Emission from Cabbage Fields in Korea by Optimizing Tillage Depth and N-Fertilizer Level: DNDC Model Simulation under RCP 8.5 Scenario

2019 ◽  
Vol 11 (21) ◽  
pp. 6158 ◽  
Author(s):  
Wonjae Hwang ◽  
Minseok Park ◽  
Kijong Cho ◽  
Jeong-Gyu Kim ◽  
Seunghun Hyun
Keyword(s):  
Model Simulation ◽  
Supply And Demand ◽  
N2o Emission ◽  
Economic Losses ◽  
Change Scenario ◽  
N2o Emissions ◽  
Low Carbon ◽  
Farming Practices ◽  
Dndc Model ◽  
Tillage Depth

In this study, we applied the Denitrification and Decomposition model to predict the greenhouse gas (GHGs; CO2 and N2O) emissions and cabbage yields from 8072 cabbage fields in Korea in the 2020s and 2090s. Model outputs were evaluated as a function of tillage depth (T1, T2, and T3 for 10, 20, and 30 cm) and fertilizer level (F1, F2, and F3 for 100, 200, and 400 kg N ha−1) under the Representative Concentration Pathways 8.5 climate change scenario. For both time periods, CO2 emissions increased with tillage depth, and N2O emissions were predominantly influenced by the level of applied N-fertilizers. Both cabbage yields and GHGs fluxes were highest when the T3F3 farming practice was applied. Under current conventional farming practices (T1F3), cabbage yield was projected at 64.5 t ha−1 in the 2020s, which was close in magnitude to the predicted cabbage demand. In the 2090s, the predicted cabbage supply by the same practice far exceeded the projected demand at 28.9 t ha−1. Cabbage supply and demand were balanced and GHGs emissions reduced by 19.6% in the 2090s when 94% of the total cabbage farms adopted low carbon-farming practices (e.g., reducing fertilizer level). Our results demonstrate the large potential for Korean cabbage farms to significantly contribute towards the mitigation of GHGs emissions through the adoption of low-carbon farming practices. However, in order to incentivize the shift towards sustainable farming, we advise that lower yield and potential economic losses in farmlands from adopting low-carbon practices should be appropriately compensated by institutional policy.

scholarly journals Estimates of N2O Emissions and Mitigation Potential from a Spring Maize Field Based on DNDC Model

2012 ◽  
Vol 11 (12) ◽  
pp. 2067-2078 ◽  
Author(s):  
Hu LI ◽  
Jian-jun QIU ◽  
Li-gang WANG ◽  
Ming-yi XU ◽  
Zhi-qiang LIU ◽  
...  
Keyword(s):  
N2o Emissions ◽  
Dndc Model ◽  
Mitigation Potential ◽  
Maize Field ◽  
Spring Maize

scholarly journals Effects of Different Vegetation Zones on CH4and N2O Emissions in Coastal Wetlands: A Model Case Study

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Yuhong Liu ◽  
Lixin Wang ◽  
Shumei Bao ◽  
Huamin Liu ◽  
Junbao Yu ◽  
...  
Keyword(s):  
Coastal Wetlands ◽  
Coastal Wetland ◽  
Global Climate ◽  
N2o Emissions ◽  
Organic Carbon Content ◽  
Dndc Model ◽  
Model Case ◽  
Wetland Ecosystems ◽  
Factors Affecting ◽  
Vegetation Zones

The coastal wetland ecosystems are important in the global carbon and nitrogen cycle and global climate change. For higher fragility of coastal wetlands induced by human activities, the roles of coastal wetland ecosystems in CH4and N2O emissions are becoming more important. This study used a DNDC model to simulate current and future CH4and N2O emissions of coastal wetlands in four sites along the latitude in China. The simulation results showed that different vegetation zones, including bare beach,Spartinabeach, andPhragmitesbeach, produced different emissions of CH4and N2O in the same latitude region. Correlation analysis indicated that vegetation types, water level, temperature, and soil organic carbon content are the main factors affecting emissions of CH4and N2O in coastal wetlands.

scholarly journals Application of DNDC Model for Mapping Greenhouse Gas Emission from Paddy Rice Cultivation in Nam Dinh Province

2019 ◽  
Vol 35 (2) ◽  
Author(s):  
Nguyen Le Trang ◽  
Bui Thi Thu Trang ◽  
Mai Van Trinh ◽  
Nguyen Tien Sy ◽  
Nguyen Manh Khai
Keyword(s):  
Greenhouse Gas ◽  
Agricultural Sector ◽  
Greenhouse Gas Emission ◽  
Agricultural Soils ◽  
Paddy Rice ◽  
Rice Cultivation ◽  
N2o Emissions ◽  
Viet Nam ◽  
Alkaline Soils ◽  
Dndc Model

Abstract: This study used the Denitrification-Decomposition (DNDC) model to calculate greenhouse gas emissions from a paddy rice cultivation in ​​Nam Dinh province. The results show that the total CH4 emission from paddy rice field in Nam Dinh province ranges from 404 to 1146kg/ha/year. Total N2O emissions range from 0.8 to 4.2 kg/ha/year; The total amount of CO2e varies between 10,000 and 30,000 kg CO2e / ha / year. CH4 emissions on typical salinealluvial soils, light mechanics are the highest and lowest on alkaline soils. Alluvium, alkaline soils have the highest N2O emissions and the lowest is the typical saline soils. The study has also mapped CH4, N2O and CO2e emissions for Nam Dinh province. Keywords: DNDC, Green house gas, agricultural sector, Nam Dinh,  GIS. References: [1] Bộ Tài nguyên và Môi trường, Báo cáo kỹ thuật kiểm kê quốc gia KNK của Việt Nam năm 2014, NXB Tài Nguyên Môi trường và Bản đồ Việt Nam, 2018.[2] D.L. Giltrap, C.Li, S. Saggar, DNDC: A process-based model of greenhouse gas fluxes from agricultural soils, Agriculture, Ecosystems & Environment,Volume 136 (2010), 292–300. https://doi:10.1016/j.agee.2009.06.014.[3] Viện Thổ nhưỡng Nông hóa, Báo cáo kết quả đề tài: “Nghiên cứu, đánh giá tài nguyên đất sản xuất nông nghiệp phục vụ chuyển đổi cơ cấu cây trồng chính có hiệu quả tại tỉnh Nam Định”, 2017.[4] Trung tâm Khí tượng thủy văn quốc gia – Bộ TN&MT, Số liệu thống kê khí tượng thủy văn các trạm khí tượng Văn Lý, Nam Định, Ninh Bình, Thái Bình năm 2014, 2015.[5] Niên giám thống kê tỉnh Nam Định, 2015.[6] T. Weaver, P. Ramachandran, L. Adriano, Policies for High Quality, Safe, and Sustainable Food Supply in the Greater Mekong Subregion. ADB: Manila. (2019) Chapter 7, 178-204.[7] Mai Văn Trịnh, Sổ tay hướng dẫn đo phát thải khí nhà kính trong canh tác lúa. NXB Nông nghiệp, 2016.    

scholarly journals Effects of soil spatial resolution on quantifying CH4and N2O emissions from rice fields in the Tai Lake region of China by DNDC model

2011 ◽  
Vol 25 (2) ◽  
pp. n/a-n/a ◽  
Author(s):  
D. S. Yu ◽  
H. Yang ◽  
X. Z. Shi ◽  
E. D. Warner ◽  
L. M. Zhang ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Rice Fields ◽  
N2o Emissions ◽  
Dndc Model ◽  
Lake Region ◽  
Tai Lake

Evaluation of two process-based models to estimate soil N2O emissions in Eastern Canada

2008 ◽  
Vol 88 (2) ◽  
pp. 251-260 ◽  
Author(s):  
W N Smith ◽  
B B Grant ◽  
R L Desjardins ◽  
P. Rochette ◽  
C F Drury ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Water Content ◽  
Climatic Conditions ◽  
Fertilizer Treatment ◽  
N2o Emissions ◽  
Pig Slurry ◽  
Dndc Model ◽  
Eastern Canada ◽  
Maize Crop ◽  
Process Based Models

Process-based models play an important role in the estimation of soil N2O emissions from regions with contrasting soil and climatic conditions. A study was performed to evaluate the ability of two process-based models, DAYCENT and DNDC, to estimate N2O emissions, soil nitrate- and ammonium-N levels, as well as soil temperature and water content. The measurement sites included a maize crop fertilized with pig slurry (Quebec) and a wheat-maize-soybean rotation as part of a tillage-fertilizer experiment (Ontario). At the Quebec site, both models accurately simulated soil temperature with an average relative error (ARE) ranging from 0 to 2%. The models underpredicted soil temperature at the Ontario site with ARE from −5 to −7% for DNDC and from −5 to −13% for DAYCENT. Both models underestimated soil water content particularly during the growing season. The DNDC model accurately predicted average seasonal N2O emissions across treatments at both sites whereas the DAYCENT model underpredicted N2O emissions by 32 to 58% for all treatments excluding the fertilizer treatment at the Quebec site. Both models had difficulty in simulating the timing of individual emission events. The hydrology and nitrogen transformation routines need to be improved in both models before further enhancements are made to the trace gas routines. Key words: Nitrous oxide, process-based model, DNDC, greenhouse gas emissions, soil

scholarly journals Multifactor Effects on the N2O Emissions and Yield of Potato Fields Based on the DNDC Model

2021 ◽  
Author(s):  
Liwei Wang ◽  
Kai Zhang ◽  
Kangjun Guo ◽  
Limin Liu ◽  
Tao Zhang ◽  
...  
Keyword(s):  
Growth Period ◽  
Normal Growth ◽  
Soil Bulk Density ◽  
Efficiency Index ◽  
Annual Precipitation ◽  
N2o Emissions ◽  
Dndc Model ◽  
Nitrogen Levels ◽  
Average Temperature ◽  
Model Efficiency

Abstract Maintaining or increasing grain yields while also reducing the emissions of field agricultural greenhouse gases is an important objective. To explore the multifactor effects of nitrogen fertilizer on nitrous oxide (N2O) emissions and the yield of potato fields and to verify the applicability of the DeNitrification-DeComposition (DNDC) model when used to project the N2O emission load and yield, this research chooses a potato field in Shenyang northeast China from 2017~2019 as the experiment site. The experiment includes four nitrogen levels observed the emission of N2O by static chamber/gas chromatograph techniques. The results of this study are as follows: (1) DNDC has a good performance regarding the projection of N2O emissions and yields. The model efficiency index EFs were 0.45~0.88 for N2O emissions and 0.91, 0.85 and 0.85 for yields from 2017~2019. (2) The annual precipitation, soil organic carbon and soil bulk density had the most significant influence on the accumulated N2O emissions during the growth period of potato. The annual precipitation, annual average temperature and CO2 mass concentration had the most significant influences on yield. (3) Under the premise of a normal water supply, sowing potatoes within 5 days after the 5-day sliding average temperature in this area exceeds 10 °C can ensure the temperature required for the normal growth of potatoes and achieve the purpose of maintaining and increasing yield. (4) The application of 94.5 kg·hm-2 nitrogen and 15 mm irrigation represented the best results for reducing N2O emissions while also maintaining the yield in potato fields.

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

2011 ◽  
Vol 8 (8) ◽  
pp. 2377-2390 ◽  
Author(s):  
Y. Wang ◽  
G. J. Sun ◽  
F. Zhang ◽  
J. Qi ◽  
C. Y. Zhao
Keyword(s):  
Greenhouse Gas ◽  
Ghg Emissions ◽  
Fertilizer Application ◽  
Application Rate ◽  
Return Rate ◽  
N2o Emissions ◽  
Co2 Fluxes ◽  
Dndc Model ◽  
Agricultural Ecosystems ◽  
Fertilizer Application Rate

Abstract. Agricultural ecosystems are major sources of greenhouse gas (GHG) emissions, specifically nitrous oxide (N2O) and carbon dioxide (CO2). An important method of investigating GHG emissions in agricultural ecosystems is model simulation. Field measurements quantifying N2O and CO2 fluxes were taken in a summer maize ecosystem in Zhangye City, Gansu Province, in northwestern China in 2010. Observed N2O and CO2 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 N2O emissions were sensitive to included nitrogen fertilizer application rate, manure amendment and residue return rate; (2) CO2 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, N2O 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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