scholarly journals Global land-atmosphere exchange of methane and nitrous oxide: magnitude and spatiotemporal patterns

2013 ◽  
Vol 10 (12) ◽  
pp. 19811-19865 ◽  
Author(s):  
H. Tian ◽  
G. Chen ◽  
C. Lu ◽  
X. Xu ◽  
W. Ren ◽  
...  

Abstract. Methane (CH4) and nitrous oxide (N2O) are two most important greenhouse gases after carbon dioxide, but their regional and global budgets are far from certain, which is largely owing to uncertainties in scaling up field measurements as well as the poor model representation of processes and factors governing CH4 and N2O exchange between the terrestrial biosphere and atmosphere. In this study, we applied a process-based, coupled biogeochemical model (DLEM – the Dynamic Land Ecosystem Model) to estimate the magnitudes, spatial and temporal patterns of CH4 and N2O fluxes as driven by multiple environmental changes including climate variability, rising atmospheric CO2, increasing nitrogen deposition, tropospheric ozone pollution, land use change and nitrogen fertilizer use. The estimated CH4 and N2O emissions from global land ecosystems were 169.43 ± 32.92 Tg C yr−1 and 12.52 ± 1.52 Tg N yr−1, respectively. Our simulations have indicated a significant (P < 0.01) increasing trend for CH4 (0.75 ± 0.08 Tg C yr−1) and N2O (0.14 ± 0.02 Tg N yr−1) during 1981–2010. CH4 and N2O emissions increased significantly in most climatic zones and continents, especially in tropical region and Asia. The most rapid increase in CH4 emission was found in wetlands (including rice fields and natural wetlands) owing to increased rice field area and climate change; N2O emission increased substantially for all the biome types and the largest increase occurred in upland crops owing to increasing air temperature and nitrogen fertilizer use. Given large increase in CH4 and N2O emission at global scale, we suggest that these two gases together with CO2 have to be simultaneously considered when evaluating if a policy is effective or efficient to reduce global warming in the future.

2010 ◽  
Vol 7 (6) ◽  
pp. 2039-2050 ◽  
Author(s):  
F. Zhang ◽  
J. Qi ◽  
F. M. Li ◽  
C. S. Li ◽  
C. B. Li

Abstract. As one of the largest land cover types, grassland can potentially play an important role in the ecosystem services of natural resources in China. Nitrous oxide (N2O) is a major greenhouse gas emitted from grasslands. Current N2O inventory at a regional or national level in China relies on the emission factor method, which is based on limited measurements. To improve the accuracy of the inventory by capturing the spatial variability of N2O emissions under the diverse climate, soil and management conditions across China, we adopted an approach by utilizing a process-based biogeochemical model, DeNitrification-DeComposition (DNDC), to quantify N2O emissions from Chinese grasslands. In the present study, DNDC was tested against datasets of N2O fluxes measured at eight grassland sites in China with encouraging results. The validated DNDC was then linked to a GIS database holding spatially differentiated information of climate, soil, vegetation and management at county-level for all the grasslands in the country. Daily weather data for 2000–2007 from 670 meteorological stations across the entire domain were employed to serve the simulations. The modelled results on a national scale showed a clear geographic pattern of N2O emissions. A high-emission strip showed up stretching from northeast to central China, which is consistent with the eastern boundary between the temperate grassland region and the major agricultural regions of China. The grasslands in the western mountain regions, however, emitted much less N2O. The regionally averaged rates of N2O emissions were 0.26, 0.14 and 0.38 kg nitrogen (N) ha−1 y−1 for the temperate, montane and tropical/subtropical grasslands, respectively. The annual mean N2O emission from the total 337 million ha of grasslands in China was 76.5 ± 12.8 Gg N for the simulated years.


2017 ◽  
Vol 8 (4) ◽  
pp. 223-228
Author(s):  
Duc Minh Ngo ◽  
Van Trinh Mai ◽  
Dang Hoa Tran ◽  
Trong Nghia Hoang ◽  
Manh Khai Nguyen ◽  
...  

Nitrous oxide (N2O) emisison from paddy soil via the soil nitrification and denitrification processes makes an important contribution to atmospheric greenhouse gas concentrations. The soil N2O emission processes are controlled not only by biological, physical and chemical factors but also by farming practices. In recent years, modeling approach has become popular to predict and estimate greenhouse gas fluxes from field studies. In this study, the DeNitrification–DeComposition (DNDC) model were calibrated and tested by incorporating experimental data with the local climate, soil properties and farming management, for its simulation applicability for the irrigated rice system in Duy Xuyen district, a delta lowland area of Vu Gia-Thu Bon River Basin regions. The revised DNDC was then used to quantitatively estimate N2O emissions from rice fields under a range of three management farming practices (water management, crop residue incorporation and nitrogen fertilizer application rate). Results from the simulations indicated that (1) N2O emissions were significantly affected by water management practices; (2) increases in temperature, total fertilizer N input substantially increased N2O emissions. Finally, five 50-year scenarios were simulated with DNDC to predict their long-term impacts on crop yield and N2O emissions. The modelled results suggested that implementation of manure amendment or crop residue incorporation instead of increased nitrogen fertilizer application rates would more efficiently mitigate N2O emissions from the tested rice-based system. Phát thải nitơ ôxít (N2O) từ canh tác lúa nước (thông qua quá trình nitrat hóa và phản nitrat hóa) đóng góp đáng kể vào tổng lượng khí nhà kính có nguồn gốc từ sản xuất nông nghiệp. Quá trình phát thải N2O là không chỉ phụ thuộc vào các yếu tố sinh-lý-hóa học mà còn phụ thuộc các phương pháp canh tác. Trong những năm gần đây, việc ứng dụng mô hình hóa nhằm tính toán và ước lượng sự phát thải khí nhà kính ngày càng trở lên phổ biến. Trong nghiên cứu này, số liệu quan trắc từ thí nghiệm đồng ruộng và dữ liệu về đất đai, khí hậu, biện pháp canh tác được sử dụng để kiểm nghiệm và phân tích độ nhạy của mô hình DNDC (mô hình sinh địa hóa). Sau đó, mô hình được sử dụng để tính toán lượng N2O phát thải trong canh tác lúa nước dưới các phương thức canh tác khác nhau (về chế độ tưới, mức độ vùi phụ phẩm, bón phân hữu cơ, phân đạm) tại huyện Duy Xuyên, thuộc vùng đồng bằng thấp của lưu vực sông Vu Gia-Thu Bồn. Kết quả kiểm định chỉ ra rằng (1) sự phát thải N2O bị ảnh hưởng đáng kể do sự thay đổi chế độ tưới; (2) nhiệt độ tăng và lượng phân bón N tăng sẽ làm tăng phát thải N2O. Kết quả mô phỏng về tác động lâu dài (trong 50 năm) của các yếu tố đến năng suất cây trồng và phát thải N2O cho thấy: Việc sử dụng phân hữu cơ và phụ phẩm nông nghiệp thay thế cho việc bón phân đạm sẽ giúp giảm phát thải N2O đáng kể.


2010 ◽  
Vol 7 (2) ◽  
pp. 1675-1706 ◽  
Author(s):  
F. Zhang ◽  
J. Qi ◽  
F. M. Li ◽  
C. S. Li ◽  
C. B. Li

Abstract. As one of the largest land cover types, grassland can potentially play an important role in the ecosystem services of natural resources in China. Nitrous oxide (N2O) is a major greenhouse gas emitted from grasslands. Current N2O inventory at regional or national level in China relies on the emission factor method, and is based on limited measurements. To improve inventory accuracy and capture the spatial variability of the N2O emissions under the diverse climate, soil and management conditions across China, we adopted an approach that uses a process-based biogeochemical model, DeNitrification-DeComposition (DNDC) in this study, to map the N2O emissions from China's grasslands. The DNDC was linked to a GIS database of spatially distributed information of climate, soil, vegetation and management at county-level for all grasslands in China. Daily weather data from 2000–2007 based on the national network of 670 meteorological stations were utilized in the model simulations. The results were validated against observations from several grasslands in China and from other countries. The modelled results showed a clear geographic pattern of N2O emissions from China's grasslands. A high-emission strip was found that stretched from northeast to central China, along the eastern boundary of the temperate grassland region adjacent to the major agricultural regions. The grasslands in the western mountain regions, however, emitted much less N2O. The regional average of N2O emission rates was 0.23, 0.11 and 0.39 kg N ha−1y−1 for the temperate, montane and tropical/subtropical grasslands, respectively. The national N2O emission was 76.5 Gg N from the 337 million ha of grasslands in China. The modelled results were in good agreement with observations (R2=0.64 for 11 datasets), suggesting that the process-based model can be used to capture the spatial dynamics of N2O emissions as an effective alternative to statistical method currently used in China.


2021 ◽  
Vol 13 (9) ◽  
pp. 4928
Author(s):  
Alicia Vanessa Jeffary ◽  
Osumanu Haruna Ahmed ◽  
Roland Kueh Jui Heng ◽  
Liza Nuriati Lim Kim Choo ◽  
Latifah Omar ◽  
...  

Farming systems on peat soils are novel, considering the complexities of these organic soil. Since peat soils effectively capture greenhouse gases in their natural state, cultivating peat soils with annual or perennial crops such as pineapples necessitates the monitoring of nitrous oxide (N2O) emissions, especially from cultivated peat lands, due to a lack of data on N2O emissions. An on-farm experiment was carried out to determine the movement of N2O in pineapple production on peat soil. Additionally, the experiment was carried out to determine if the peat soil temperature and the N2O emissions were related. The chamber method was used to capture the N2O fluxes daily (for dry and wet seasons) after which gas chromatography was used to determine N2O followed by expressing the emission of this gas in t ha−1 yr−1. The movement of N2O horizontally (832 t N2O ha−1 yr−1) during the dry period was higher than in the wet period (599 t N2O ha−1 yr−1) because of C and N substrate in the peat soil, in addition to the fertilizer used in fertilizing the pineapple plants. The vertical movement of N2O (44 t N2O ha−1 yr−1) was higher in the dry season relative to N2O emission (38 t N2O ha−1 yr−1) during the wet season because of nitrification and denitrification of N fertilizer. The peat soil temperature did not affect the direction (horizontal and vertical) of the N2O emission, suggesting that these factors are not related. Therefore, it can be concluded that N2O movement in peat soils under pineapple cultivation on peat lands occurs horizontally and vertically, regardless of season, and there is a need to ensure minimum tilling of the cultivated peat soils to prevent them from being an N2O source instead of an N2O sink.


2021 ◽  
Vol 18 (13) ◽  
pp. 4211-4225
Author(s):  
Wei Zhang ◽  
Zhisheng Yao ◽  
Siqi Li ◽  
Xunhua Zheng ◽  
Han Zhang ◽  
...  

Abstract. The hydro-biogeochemical model Catchment Nutrient Management Model – DeNitrification-DeComposition (CNMM-DNDC) was established to simultaneously quantify ecosystem productivity and losses of nitrogen and carbon at the site or catchment scale. As a process-oriented model, this model is expected to be universally applied to different climate zones, soils, land uses and field management practices. This study is one of many efforts to fulfill such an expectation, which was performed to improve the CNMM-DNDC by incorporating a physically based soil thermal module to simulate the soil thermal regime in the presence of freeze–thaw cycles. The modified model was validated with simultaneous field observations in three typical alpine ecosystems (wetlands, meadows and forests) within a catchment located in seasonally frozen regions of the eastern Tibetan Plateau, including observations of soil profile temperature, topsoil moisture, and fluxes of methane (CH4) and nitrous oxide (N2O). The validation showed that the modified CNMM-DNDC was able to simulate the observed seasonal dynamics and magnitudes of the variables in the three typical alpine ecosystems, with index-of-agreement values of 0.91–1.00, 0.49–0.83, 0.57–0.88 and 0.26–0.47, respectively. Consistent with the emissions determined from the field observations, the simulated aggregate emissions of CH4 and N2O were highest for the wetland among three alpine ecosystems, which were dominated by the CH4 emissions. This study indicates the possibility for utilizing the process-oriented model CNMM-DNDC to predict hydro-biogeochemical processes, as well as related gas emissions, in seasonally frozen regions. As the original CNMM-DNDC was previously validated in some unfrozen regions, the modified CNMM-DNDC could be potentially applied to estimate the emissions of CH4 and N2O from various ecosystems under different climate zones at the site or catchment scale.


Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2169 ◽  
Author(s):  
Tabassum Abbasi ◽  
Tasneem Abbasi ◽  
Chirchom Luithui ◽  
Shahid Abbas Abbasi

Paddy fields, which are shallow man-made wetlands, are estimated to be responsible for ~11% of the total methane emissions attributed to anthropogenic sources. The role of water use in driving these emissions, and the apportioning of the emissions to individual countries engaged in paddy cultivation, are aspects that have been mired in controversy and disagreement. This is largely due to the fact that methane (CH4) emissions not only change with the cultivar type but also regions, climate, soil type, soil conditions, manner of irrigation, type and quantity of fertilizer added—to name a few. The factors which can influence these aspects also encompass a wide range, and have origins in causes which can be physical, chemical, biological, and combinations of these. Exceedingly complex feedback mechanisms, exerting different magnitudes and types of influences on CH4 emissions under different conditions, are operative. Similar is the case of nitrous oxide (N2O); indeed, the present level of understanding of the factors which influence the quantum of its emission is still more patchy. This makes it difficult to even understand precisely the role of the myriad factors, less so model them. The challenge is made even more daunting by the fact that accurate and precise data on most of these aspects is lacking. This makes it nearly impossible to develop analytical models linking causes with effects vis a vis CH4 and N2O emissions from paddy fields. For situations like this the bioinspired artificial intelligence technique of artificial neural network (ANN), which can model a phenomenon on the basis of past data and without the explicit understanding of the mechanism phenomena, may prove useful. However, no such model for CH4 or N2O has been developed so far. Hence the present work was undertaken. It describes ANN-based models developed by us to predict CH4 and N2O emissions using soil characteristics, fertilizer inputs, and rice cultivar yield as inputs. Upon testing the predictive ability of the models with sets of data not used in model development, it was seen that there was excellent agreement between model forecasts and experimental findings, leading to correlations coefficients of 0.991 and 0.96, and root mean square error (RMSE) of 11.17 and 261.3, respectively, for CH4 and N2O emissions. Thus, the models can be used to estimate CH4 and N2O emissions from all those continuously flooded paddy wetlands for which data on total organic carbon, soil electrical conductivity, applied nitrogen, phosphorous and potassium, NPK, and grain yield is available.


Soil Research ◽  
2016 ◽  
Vol 54 (5) ◽  
pp. 598 ◽  
Author(s):  
Peter Grace ◽  
Iurii Shcherbak ◽  
Ben Macdonald ◽  
Clemens Scheer ◽  
David Rowlings

As a significant user of nitrogen (N) fertilisers, the Australian cotton industry is a major source of soil-derived nitrous oxide (N2O) emissions. A country-specific (Tier 2) fertiliser-induced emission factor (EF) can be used in national greenhouse gas inventories or in the development of N2O emissions offset methodologies provided the EFs are evidence based. A meta-analysis was performed using eight individual N2O emission studies from Australian cotton studies to estimate EFs. Annual N2O emissions from cotton grown on Vertosols ranged from 0.59kgNha–1 in a 0N control to 1.94kgNha–1 in a treatment receiving 270kgNha–1. Seasonal N2O estimates ranged from 0.51kgNha–1 in a 0N control to 10.64kgNha–1 in response to the addition of 320kgNha–1. A two-component (linear+exponential) statistical model, namely EF (%)=0.29+0.007(e0.037N – 1)/N, capped at 300kgNha–1 describes the N2O emissions from lower N rates better than an exponential model and aligns with an EF of 0.55% using a traditional linear regression model.


Soil Research ◽  
2003 ◽  
Vol 41 (2) ◽  
pp. 165 ◽  
Author(s):  
Ram C. Dalal ◽  
Weijin Wang ◽  
G. Philip Robertson ◽  
William J. Parton

Increases in the concentrations of greenhouse gases, carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and halocarbons in the atmosphere due to human activities are associated with global climate change. The concentration of N2O has increased by 16% since 1750. Although atmospheric concentration of N2O is much smaller (314 ppb in 1998) than of CO2 (365 ppm), its global warming potential (cumulative radiative forcing) is 296 times that of the latter in a 100-year time horizon. Currently, it contributes about 6% of the overall global warming effect but its contribution from the agricultural sector is about 16%. Of that, almost 80% of N2O is emitted from Australian agricultural lands, originating from N fertilisers (32%), soil disturbance (38%), and animal waste (30%). Nitrous oxide is primarily produced in soil by the activities of microorganisms during nitrification, and denitrification processes. The ratio of N2O to N2 production depends on oxygen supply or water-filled pore space, decomposable organic carbon, N substrate supply, temperature, and pH and salinity. N2O production from soil is sporadic both in time and space, and therefore, it is a challenge to scale up the measurements of N2O emission from a given location and time to regional and national levels.Estimates of N2O emissions from various agricultural systems vary widely. For example, in flooded rice in the Riverina Plains, N2O emissions ranged from 0.02% to 1.4% of fertiliser N applied, whereas in irrigated sugarcane crops, 15.4% of fertiliser was lost over a 4-day period. Nitrous oxide emissions from fertilised dairy pasture soils in Victoria range from 6 to 11 kg N2O-N/ha, whereas in arable cereal cropping, N2O emissions range from <0.01% to 9.9% of N fertiliser applications. Nitrous oxide emissions from soil nitrite and nitrates resulting from residual fertiliser and legumes are rarely studied but probably exceed those from fertilisers, due to frequent wetting and drying cycles over a longer period and larger area. In ley cropping systems, significant N2O losses could occur, from the accumulation of mainly nitrate-N, following mineralisation of organic N from legume-based pastures. Extensive grazed pastures and rangelands contribute annually about 0.2 kg N/ha as N2O (93 kg/ha per year CO2-equivalent). Tropical savannas probably contribute an order of magnitude more, including that from frequent fires. Unfertilised forestry systems may emit less but the fertilised plantations emit more N2O than the extensive grazed pastures. However, currently there are limited data to quantify N2O losses in systems under ley cropping, tropical savannas, and forestry in Australia. Overall, there is a need to examine the emission factors used in estimating national N2O emissions; for example, 1.25% of fertiliser or animal-excreted N appearing as N2O (IPCC 1996). The primary consideration for mitigating N2O emissions from agricultural lands is to match the supply of mineral N (from fertiliser applications, legume-fixed N, organic matter, or manures) to its spatial and temporal needs by crops/pastures/trees. Thus, when appropriate, mineral N supply should be regulated through slow-release (urease and/or nitrification inhibitors, physical coatings, or high C/N ratio materials) or split fertiliser application. Also, N use could be maximised by balancing other nutrient supplies to plants. Moreover, non-legume cover crops could be used to take up residual mineral N following N-fertilised main crops or mineral N accumulated following legume leys. For manure management, the most effective practice is the early application and immediate incorporation of manure into soil to reduce direct N2O emissions as well as secondary emissions from deposition of ammonia volatilised from manure and urine.Current models such as DNDC and DAYCENT can be used to simulate N2O production from soil after parameterisation with the local data, and appropriate modification and verification against the measured N2O emissions under different management practices.In summary, improved estimates of N2O emission from agricultural lands and mitigation options can be achieved by a directed national research program that is of considerable duration, covers sampling season and climate, and combines different techniques (chamber and micrometeorological) using high precision analytical instruments and simulation modelling, under a range of strategic activities in the agriculture sector.


1997 ◽  
Vol 45 (3) ◽  
pp. 347-360 ◽  
Author(s):  
G.L. Velthof ◽  
O. Oenema

A large part of the nitrogen (N) input in dairy farming systems in the Netherlands is lost from the system via N leaching and volatilization of gaseous N compounds, including the greenhouse gas nitrous oxide (N2O). The aim of the present study was to quantify N2O emission from dairy farming systems in the Netherlands, using a whole-farm approach. A total of 14 N2O sources was identified and emission factors were derived for each of these using the literature. Figures are presented for the amounts of N2O produced/kg herbage N produced (ranging from 4 to 89 g N2O-N kg-1 herbage N), depending on soil type and grassland management. Using Monte Carlo simulations, variations in mean total N2O emissions from the different sources were calculated for 3 model dairy farming systems differing in nutrient management. These different farming systems were chosen to assess the effect of improved nutrient management on total N2O emission. The total direct annual N2O emissions ranged from 15.4 +or-9.4 kg N2O-N/ha for the average dairy farming system in the 1980s to 5.3 +or-2.6 kg N2O-N/ha for a prototype of an economically feasible farming system with acceptable nutrient emissions. Leaching-derived, grazing-derived and fertilizer-derived N2O emissions were the major N2O sources on dairy farming systems. The total direct N2O emissions accounted for 3.2 to 4.6% of the N surplus on the dairy farming systems, suggesting that only a small amount of N was lost as N2O. Total N2O emissions from dairy farming systems in the Netherlands were 13.7+or-5.1 Gg N/year, which is about 35% of the estimated total N2O emission in the Netherlands. It is concluded that improvement of nutrient management of dairy farming systems will significantly decrease the N2O emissions from these systems, and thus the total N2O emission in the Netherlands.


Agronomy ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1936
Author(s):  
John Kormla Nyameasem ◽  
Enis Ben Halima ◽  
Carsten Stefan Malisch ◽  
Bahar S. Razavi ◽  
Friedhelm Taube ◽  
...  

Soil–plant interactions affecting nitrous oxide (N2O) are not well-understood, and experimental data are scarce. Therefore, a greenhouse experiment was conducted in a 3 × 3 full factorial design, comprising three mineral N fertilizer rates (0, 150 and 300 kg N ha−1) applied to monoculture swards and a binary mixture of Plantago lanceolata and Lolium perenne. The parameters measured included daily N2O emissions, aboveground (AG) and belowground biomass (BG), N and C yields, as well as leucine aminopeptidase (LAP) activity in the soil as an indicator for soil microbial activity. Nitrous oxide emission and LAP were measured using the static chamber method and fluorimetric microplate assays, respectively. Cumulative N2O emissions were about two times higher for P. lanceolata than L. perenne monoculture swards or the mixture (p < 0.05). The binary mixtures also showed the highest N use efficiency and LAP activity, which significantly (p < 0.05) correlated with the C concentration in the belowground biomass. Plantago lanceolata was generally ineffective at reducing N2O emissions, probably due to the young age of the swards. Among the biological factors, N2O emission was significantly associated with biomass productivity, belowground C yield, belowground N use efficiency and soil microbial activity. Thus, the results suggested belowground resource allocation dynamics as a possible means by which swards impacted N2O emission from the soils. However, a high N deposition might reduce the N2O mitigation potential of grasslands.


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