Quantifying methane and nitrous oxide emissions from the UK and Ireland using a national-scale monitoring network

Abstract. The UK is one of several countries around the world that has enacted legislation to reduce its greenhouse gas emissions. In this study, we present top-down emissions of methane (CH4) and nitrous oxide (N2O) for the UK and Ireland over the period August~2012 to August~2014. These emissions were inferred using measurements from a network of four sites around the two countries. We used a hierarchical Bayesian inverse framework to infer fluxes as well as a set of covariance parameters that describe uncertainties in the system. We inferred average UK total emissions of 2.09 (1.65–2.67) Tg yr−1 CH4 and 0.101 (0.068–0.150) Tg yr−1 N2O and found our derived UK estimates to be generally lower than the a priori emissions, which consisted primarily of anthropogenic sources and with a smaller contribution from natural sources. We used sectoral distributions from the UK National Atmospheric Emissions Inventory (NAEI) to determine whether these discrepancies can be attributed to specific source sectors. Because of the distinct distributions of the two dominant CH4 emissions sectors in the UK, agriculture and waste, we found that the inventory may be overestimated in agricultural CH4 emissions. We found that annual mean N2O emissions were consistent with both the prior and the anthropogenic inventory but we derived a significant seasonal cycle in emissions. This seasonality is likely due to seasonality in fertilizer application and in environmental drivers such as temperature and rainfall, which are not reflected in the annual resolution inventory. Through the hierarchical Bayesian inverse framework, we quantified uncertainty covariance parameters and emphasized their importance for high-resolution emissions estimation. We inferred average model errors of approximately 20 and 0.4 ppb and correlation timescales of 1.0 (0.72–1.43) and 2.6 (1.9–3.9) days for CH4 and N2O, respectively. These errors are a combination of transport model errors as well as errors due to unresolved emissions processes in the inventory. We found the largest CH4 errors at the Tacolneston station in eastern England, which may be due to sporadic emissions from landfills and offshore gas in the North Sea.

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Quantifying methane and nitrous oxide emissions from the UK using a dense monitoring network

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-15-857-2015 ◽

2015 ◽

Vol 15 (1) ◽

pp. 857-886 ◽

Cited By ~ 1

Author(s):

A. L. Ganesan ◽

A. J. Manning ◽

A. Grant ◽

D. Young ◽

D. E. Oram ◽

...

Keyword(s):

Nitrous Oxide ◽

Transport Model ◽

Monitoring Network ◽

Nitrous Oxide Emissions ◽

Environmental Drivers ◽

Hierarchical Bayesian ◽

Model Errors ◽

Top Down ◽

Ch4 Emissions ◽

The Uk

Abstract. The UK is one of several countries around the world that has enacted legislation to reduce its greenhouse gas emissions. Monitoring of emissions has been done through a detailed sectoral level bottom-up inventory (UK National Atmospheric Emissions Inventory, NAEI) from which national totals are submitted yearly to the United Framework Convention on Climate Change. In parallel, the UK government has funded four atmospheric monitoring stations to infer emissions through top-down methods that assimilate atmospheric observations. In this study, we present top-down emissions of methane (CH4) and nitrous oxide (N2O) for the UK and Ireland over the period August 2012 to August 2014. We used a hierarchical Bayesian inverse framework to infer fluxes as well as a set of covariance parameters that describe uncertainties in the system. We inferred average UK emissions of 2.08 (1.72–2.47) Tg yr−1 CH4 and 0.105 (0.087–0.127) Tg yr−1 N2O and found our derived estimates to be generally lower than the inventory. We used sectoral distributions from the NAEI to determine whether these discrepancies can be attributed to specific source sectors. Because of the distinct distributions of the two dominant CH4 emissions sectors in the UK, agriculture and waste, we found that the inventory may be overestimated in agricultural CH4 emissions. We also found that N2O fertilizer emissions from the NAEI may be overestimated and we derived a significant seasonal cycle in emissions. This seasonality is likely due to seasonality in fertilizer application and in environmental drivers such as temperature and rainfall, which are not reflected in the annual resolution inventory. Through the hierarchical Bayesian inverse framework, we quantified uncertainty covariance parameters and emphasized their importance for high-resolution emissions estimation. We inferred average model errors of approximately 20 and 0.4 ppb and correlation timescales of 1.0 (0.72–1.43) and 2.6 (1.9–3.9) days for CH4 and N2O, respectively. These errors are a combination of transport model errors as well as errors due to unresolved emissions processes in the inventory. We found the largest CH4 errors at the Tacolneston station in eastern England, which is possibly to do with sporadic emissions from landfills and offshore gas in the North Sea.

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Modelling Methane and Nitrous Oxide Emissions from Rice Paddy Wetlands in India Using Artificial Neural Networks (ANNs)

Water ◽

10.3390/w11102169 ◽

2019 ◽

Vol 11 (10) ◽

pp. 2169 ◽

Cited By ~ 4

Author(s):

Tabassum Abbasi ◽

Tasneem Abbasi ◽

Chirchom Luithui ◽

Shahid Abbas Abbasi

Keyword(s):

Nitrous Oxide ◽

Paddy Fields ◽

Anthropogenic Sources ◽

Nitrous Oxide Emissions ◽

Soil Conditions ◽

N2o Emissions ◽

Ch4 Emissions ◽

Artificial Neural ◽

Ch4 And N2o

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.

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Efficient ruminant production from grassland

Proceedings of the British Society of Animal Science ◽

10.1017/s1752756200030878 ◽

2009 ◽

Vol 2009 ◽

pp. 248-248

Author(s):

N D Scollan ◽

J Moorby

Keyword(s):

Nitrous Oxide ◽

Production Efficiency ◽

Anthropogenic Sources ◽

Nitrous Oxide Emissions ◽

Increase Production Efficiency ◽

Plant Nitrogen ◽

Rumen Microbes ◽

Ruminant Meat ◽

Choice Of Species ◽

The Uk

Ruminant production in the UK is largely dependent on grasslands: approximately 52% of UK land is (improved) grassland and rough grazing. Herbage production from improved grassland can be over five times higher than that of indigenous swards (Davies et al., 1984) and these pastures account for the majority of ruminant (meat and milk) production from grassland the UK. They are also amenable to manipulation through the choice of species, variety and mixture of forages sown. Efficiency of production can be influenced at the levels of both the plant and the animal and by the nutrition and genetics of both. This paper examines strategies to increase production efficiency based upon optimising rumen fermentation linked to plant breeding approaches. In this way efficiency can be improved without recourse to diet manipulation with supplements, which is generally impractical at grazing. Although the rumen microbial population allows the ruminant animal to extract energy from otherwise unusable sources (i.e. fibres), the rumen is also the source of greatest inefficiencies in the use of nitrogen and energy. Degraded plant nitrogen that is not captured by the rumen microbes tends to be absorbed as ammonia, much of which is excreted as urea and contributes to ammonia and nitrous oxide emissions. Similarly, methane release from the rumen represents a waste of energy that could otherwise be used for production. Globally, these two processes result in ruminant livestock accounting for approximately a third of the methane emissions (Beauchemin et al., 2008) and half of the nitrous oxide emissions (de Klein and Eckard, 2008) from anthropogenic sources.

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Nitrous oxide emissions from European agriculture – an analysis of variability and drivers of emissions from field experiments

Biogeosciences ◽

10.5194/bg-10-2671-2013 ◽

2013 ◽

Vol 10 (4) ◽

pp. 2671-2682 ◽

Cited By ~ 75

Author(s):

R. M. Rees ◽

J. Augustin ◽

G. Alberti ◽

B. C. Ball ◽

P. Boeckx ◽

...

Keyword(s):

Nitrous Oxide ◽

Field Experiments ◽

Nitrogen Addition ◽

Greenhouse Gas Mitigation ◽

Nitrous Oxide Emissions ◽

N2o Emissions ◽

Management Interventions ◽

Management Controls ◽

The Uk ◽

Selection Of

Abstract. Nitrous oxide emissions from a network of agricultural experiments in Europe were used to explore the relative importance of site and management controls of emissions. At each site, a selection of management interventions were compared within replicated experimental designs in plot-based experiments. Arable experiments were conducted at Beano in Italy, El Encin in Spain, Foulum in Denmark, Logården in Sweden, Maulde in Belgium, Paulinenaue in Germany, and Tulloch in the UK. Grassland experiments were conducted at Crichton, Nafferton and Peaknaze in the UK, Gödöllö in Hungary, Rzecin in Poland, Zarnekow in Germany and Theix in France. Nitrous oxide emissions were measured at each site over a period of at least two years using static chambers. Emissions varied widely between sites and as a result of manipulation treatments. Average site emissions (throughout the study period) varied between 0.04 and 21.21 kg N2O-N ha−1 yr−1, with the largest fluxes and variability associated with the grassland sites. Total nitrogen addition was found to be the single most important determinant of emissions, accounting for 15% of the variance (using linear regression) in the data from the arable sites (p < 0.0001), and 77% in the grassland sites. The annual emissions from arable sites were significantly greater than those that would be predicted by IPCC default emission factors. Variability of N2O emissions within sites that occurred as a result of manipulation treatments was greater than that resulting from site-to-site and year-to-year variation, highlighting the importance of management interventions in contributing to greenhouse gas mitigation.

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Assessing Seasonal Methane and Nitrous Oxide Emissions from Furrow-Irrigated Rice with Cover Crops

Agriculture ◽

10.3390/agriculture11030261 ◽

2021 ◽

Vol 11 (3) ◽

pp. 261

Author(s):

Sandhya Karki ◽

M. Arlene A. Adviento-Borbe ◽

Joseph H. Massey ◽

Michele L. Reba

Keyword(s):

Nitrous Oxide ◽

Cover Crops ◽

Management Practices ◽

Irrigation Management ◽

Nitrous Oxide Emissions ◽

N2o Emissions ◽

Irrigated Rice ◽

Cereal Rye ◽

Ch4 Emissions ◽

Ch4 And N2o

Improved irrigation management is identified as a potential mitigation option for methane (CH4) emissions from rice (Oryza sativa). Furrow-irrigated rice (FR), an alternative method to grow rice, is increasingly adopted in the Mid-South U.S. However, FR may provide a potential risk to yield performance and higher emissions of nitrous oxide (N2O). This study quantified the grain yields, CH4 and N2O emissions from three different water management practices in rice: multiple-inlet rice irrigation (MIRI), FR, and FR with cereal rye (Secale cereale) and barley (Hordeum vulgare) as preceding winter cover crops (FRCC). CH4 and N2O fluxes were measured from May to September 2019 using a static chamber technique. Grain yield from FR (11.8 Mg ha−1) and MIRI (12.0 Mg ha−1) was similar, and significantly higher than FRCC (8.5 Mg ha−1). FR and FRCC drastically reduced CH4 emissions compared to MIRI. Total seasonal CH4 emissions decreased in the order of 44 > 11 > 3 kg CH4-C ha−1 from MIRI, FR, and FRCC, respectively. Cumulative seasonal N2O emissions were low from MIRI (0.1 kg N2O-N ha−1) but significantly higher from FR (4.4 kg N2O-N ha−1) and FRCC (3.0 kg N2O-N ha−1). However, there was no net difference in global warming potential among FR, FRCC and MIRI. These results suggest that the increased N2O flux from furrow-irrigated rice may not greatly detract from the potential benefits that furrow-irrigation offers rice producers.

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Management matters: Testing a mitigation strategy for nitrous oxide emissions on intensively managed grassland

10.5194/bg-2018-192 ◽

2018 ◽

Cited By ~ 2

Author(s):

Kathrin Fuchs ◽

Lukas Hörtnagl ◽

Nina Buchmann ◽

Werner Eugster ◽

Valerie Snow ◽

...

Keyword(s):

Nitrous Oxide ◽

N2o Emission ◽

Mitigation Strategy ◽

Nitrous Oxide Emissions ◽

Environmental Drivers ◽

Plant Residues ◽

N2o Emissions ◽

Biomass Yields ◽

N2o Fluxes ◽

Intensively Managed

Abstract. Replacing fertilizer nitrogen with biological nitrogen fixation (BNF) through legumes has been suggested as a strategy for nitrous oxide (N2O) mitigation from intensively managed grasslands. While current literature provides evidence for an N2O emission reduction effect due to reduced fertilizer input, little is known about the effect of increased legume proportions potentially offsetting these reductions, i.e. by increased N2O emissions from plant residues and root exudates. In order to assess the overall effect of this mitigation strategy on permanent grassland, we performed an in-situ experiment to quantify net N2O fluxes and biomass yields in two differently managed grass-clover mixtures. We measured N2O fluxes in an unfertilized parcel with high clover proportions vs. a fertilized control parcel with low clover proportions using the eddy–covariance (EC) technique over two years. Furthermore, we related the measured N2O fluxes to management and environmental drivers. To assess the effect of the mitigation strategy, we measured biomass yields and quantified biologically fixed nitrogen using the 15N natural abundance method. The mitigation management effectively reduced N2O emissions by 54 % and 39 % in 2015 and 2016, respectively. These reductions in N2O emissions can be attributed to the absence of fertilization on the clover parcel. Differences in clover proportions during periods with no recent management showed no measurable effect on N2O emissions, indicating that decomposition of plant residues and rhizodeposition did not compensate the effect of fertilizer reduction on N2O emissions. Annual biomass yields were similar under mitigation management, resulting in a reduction of N2O emission intensities from 0.42 g N2O-N kg−1 DM (control) to 0.28 g N2O-N kg−1 DM (clover parcel) over the two years observation period. We conclude that N2O emissions from fertilized grasslands can be effectively reduced without losses in yield by increasing the clover proportion and reducing fertilization.

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Biochar and urease inhibitor mitigate NH3 and N2O emissions and improve wheat yield in a urea fertilized alkaline soil

Scientific Reports ◽

10.1038/s41598-021-96771-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Khadim Dawar ◽

Shah Fahad ◽

M. M. R. Jahangir ◽

Iqbal Munir ◽

Syed Sartaj Alam ◽

...

Keyword(s):

Nitrous Oxide ◽

Grain Yield ◽

Block Design ◽

N Uptake ◽

Nitrous Oxide Emissions ◽

N2o Emissions ◽

Urease Inhibitor ◽

Alkaline Soil ◽

Total N ◽

N Assimilation

AbstractIn this study, we explored the role of biochar (BC) and/or urease inhibitor (UI) in mitigating ammonia (NH3) and nitrous oxide (N2O) discharge from urea fertilized wheat cultivated fields in Pakistan (34.01°N, 71.71°E). The experiment included five treatments [control, urea (150 kg N ha−1), BC (10 Mg ha−1), urea + BC and urea + BC + UI (1 L ton−1)], which were all repeated four times and were carried out in a randomized complete block design. Urea supplementation along with BC and BC + UI reduced soil NH3 emissions by 27% and 69%, respectively, compared to sole urea application. Nitrous oxide emissions from urea fertilized plots were also reduced by 24% and 53% applying BC and BC + UI, respectively, compared to urea alone. Application of BC with urea improved the grain yield, shoot biomass, and total N uptake of wheat by 13%, 24%, and 12%, respectively, compared to urea alone. Moreover, UI further promoted biomass and grain yield, and N assimilation in wheat by 38%, 22% and 27%, respectively, over sole urea application. In conclusion, application of BC and/or UI can mitigate NH3 and N2O emissions from urea fertilized soil, improve N use efficiency (NUE) and overall crop productivity.

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Nitrous Oxide Emissions in Pineapple Cultivation on a Tropical Peat Soil

Sustainability ◽

10.3390/su13094928 ◽

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 ◽

...

Keyword(s):

Nitrous Oxide ◽

Soil Temperature ◽

Peat Soil ◽

Farming Systems ◽

N2o Emission ◽

Nitrous Oxide Emissions ◽

Natural State ◽

N2o Emissions ◽

Wet Season ◽

Peat Soils

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.

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Pineapple Residue Ash Reduces Carbon Dioxide and Nitrous Oxide Emissions in Pineapple Cultivation on Tropical Peat Soils at Saratok, Malaysia

Sustainability ◽

10.3390/su13031014 ◽

2021 ◽

Vol 13 (3) ◽

pp. 1014

Author(s):

Liza Nuriati Lim Kim Choo ◽

Osumanu Haruna Ahmed ◽

Nik Muhamad Nik Majid ◽

Zakry Fitri Abd Aziz

Keyword(s):

Carbon Dioxide ◽

Nitrous Oxide ◽

Peat Soil ◽

Nitrous Oxide Emissions ◽

N2o Emissions ◽

Peat Soils ◽

Closed Chamber ◽

Npk Fertilizers ◽

Npk Fertilizer ◽

Carbon Dioxide Co2

Burning pineapple residues on peat soils before pineapple replanting raises concerns on hazards of peat fires. A study was conducted to determine whether ash produced from pineapple residues could be used to minimize carbon dioxide (CO2) and nitrous oxide (N2O) emissions in cultivated tropical peatlands. The effects of pineapple residue ash fertilization on CO2 and N2O emissions from a peat soil grown with pineapple were determined using closed chamber method with the following treatments: (i) 25, 50, 70, and 100% of the suggested rate of pineapple residue ash + NPK fertilizer, (ii) NPK fertilizer, and (iii) peat soil only. Soils treated with pineapple residue ash (25%) decreased CO2 and N2O emissions relative to soils without ash due to adsorption of organic compounds, ammonium, and nitrate ions onto the charged surface of ash through hydrogen bonding. The ability of the ash to maintain higher soil pH during pineapple growth primarily contributed to low CO2 and N2O emissions. Co-application of pineapple residue ash and compound NPK fertilizer also improves soil ammonium and nitrate availability, and fruit quality of pineapples. Compound NPK fertilizers can be amended with pineapple residue ash to minimize CO2 and N2O emissions without reducing peat soil and pineapple productivity.

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Spatial and temporal variability of nitrous oxide emissions in a mixed farming landscape of Denmark

Biogeosciences ◽

10.5194/bg-9-2989-2012 ◽

2012 ◽

Vol 9 (8) ◽

pp. 2989-3002 ◽

Cited By ~ 18

Author(s):

K. Schelde ◽

P. Cellier ◽

T. Bertolini ◽

T. Dalgaard ◽

T. Weidinger ◽

...

Keyword(s):

Land Use ◽

Nitrous Oxide ◽

Agricultural Land ◽

Nitrous Oxide Emissions ◽

Soil Conditions ◽

Spatial And Temporal Variability ◽

N2o Emissions ◽

N2o Production ◽

Mixed Farming ◽

N2o Fluxes

Abstract. Nitrous oxide (N2O) emissions from agricultural land are variable at the landscape scale due to variability in land use, management, soil type, and topography. A field experiment was carried out in a typical mixed farming landscape in Denmark, to investigate the main drivers of variations in N2O emissions, measured using static chambers. Measurements were made over a period of 20 months, and sampling was intensified during two weeks in spring 2009 when chambers were installed at ten locations or fields to cover different crops and topography and slurry was applied to three of the fields. N2O emissions during spring 2009 were relatively low, with maximum values below 20 ng N m−2 s−1. This applied to all land use types including winter grain crops, grasslands, meadows, and wetlands. Slurry application to wheat fields resulted in short-lived two-fold increases in emissions. The moderate N2O fluxes and their moderate response to slurry application were attributed to dry soil conditions due to the absence of rain during the four previous weeks. Cumulative annual emissions from two arable fields that were both fertilized with mineral fertilizer and manure were large (17 kg N2O-N ha−1 yr−1 and 5.5 kg N2O-N ha−1 yr−1) during the previous year when soil water conditions were favourable for N2O production during the first month following fertilizer application. Our findings confirm the importance of weather conditions as well as nitrogen management on N2O fluxes.

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