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Pelster, D. E., M. C. Rufino, T. Rosenstock, J. Mango, G. Saiz, E. Diaz-Pines, G. Baldi, and K. Butterbach-Bahl. "Smallholder African farms in western Kenya have limited greenhouse gas fluxes." Biogeosciences Discussions 12, no. 18 (September 16, 2015): 15301–36. http://dx.doi.org/10.5194/bgd-12-15301-2015.
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Abstract. Few field studies examine greenhouse gas (GHG) emissions from African agricultural systems resulting in high uncertainty for national inventories. We provide here the most comprehensive study in Africa to date, examining annual CO2, CH4 and N2O emissions from 59 plots, across different vegetation types, field types and land classes in western Kenya. The study area consists of a lowland area (approximately 1200 m a.s.l.) rising approximately 600 m to a highland plateau. Cumulative annual fluxes ranged from 2.8 to 15.0 Mg CO2-C ha−1, −6.0 to 2.4 kg CH4-C ha−1 and −0.1 to 1.8 kg N2O-N ha−1. Management intensity of the plots did not result in differences in annual fluxes for the GHGs measured (P = 0.46, 0.67 and 0.14 for CO2, N2O and CH4 respectively). The similar emissions were likely related to low fertilizer input rates (≤ 20 kg ha−1). Grazing plots had the highest CO2 fluxes (P = 0.005); treed plots were a larger CH4 sink than grazing plots (P = 0.05); while N2O emissions were similar across vegetation types (P = 0.59). This case study is likely representative for low fertilizer input, smallholder systems across sub-Saharan Africa, providing critical data for estimating regional or continental GHG inventories. Low crop yields, likely due to low inputs, resulted in high (up to 67 g N2O-N kg−1 aboveground N uptake) yield-scaled emissions. Improving crop production through intensification of agricultural production (i.e. water and nutrient management) may be an important tool to mitigate the impact of African agriculture on climate change.
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Won, Seunggun, Youngbin Yoon, Muhammad Mahboob Ali Hamid, Arif Reza, Soomin Shim, Seungsoo Kim, Changsix Ra, Eliza Novianty, and Kyu-Hyun Park. "Estimation of Greenhouse Gas Emission from Hanwoo (Korean Native Cattle) Manure Management Systems." Atmosphere 11, no. 8 (August 10, 2020): 845. http://dx.doi.org/10.3390/atmos11080845.
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The agricultural sector is considered one of the major sources of greenhouse gas (GHG) emissions globally. The livestock industry as a significant contributor, is accounting for about 18% of GHG emissions measured in carbon dioxide (CO2) equivalent from agricultural practices. Depending on farming practices and climatic conditions, GHGs such as methane (CH4) and nitrous oxide (N2O) emissions from livestock agriculture can vary significantly. Country-specific emission factors are, therefore, needed for a precise estimation of GHG emissions and to avoid uncertainties. This study was aimed at estimating the CH4 and N2O emission fluxes from Hanwoo (the most famous and popular Korean native cattle) manure management systems. CH4 and N2O emission fluxes from litter in the Hanwoo cattle barn and composting lot were monitored and calculated for 52 weeks using the dynamic chamber method. The calculated monthly average fluxes of CH4 and N2O from litter in the cattle barn ranged from 0.0 to 30.0 ± 13.7 and 0.896 ± 0.557 to 2.925 ± 2.853 μg/m2 s, respectively during the whole measurement period. While during the composting period, the monthly average of CH4 and N2O emission fluxes were varied from 1.449 ± 0.783 to 86.930 ± 19.092 and 0.511 ± 0.410 to 2.629 ± 1.105 μg/m2 s, respectively. The calculated emission fluxes of CH4 and N2O from manure management systems in this study were almost 5.4 and 2.1 times, respectively higher than the values reported for the Asian, South and North American countries in the 2006 Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas Inventories. Overall, this study initiates the process along with signifies the importance of developing country-specific GHG inventories for the effective reduction of GHG emissions from the livestock sector in Korea.
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Petrescu, Ana Maria Roxana, Glen P. Peters, Greet Janssens-Maenhout, Philippe Ciais, Francesco N. Tubiello, Giacomo Grassi, Gert-Jan Nabuurs, et al. "European anthropogenic AFOLU greenhouse gas emissions: a review and benchmark data." Earth System Science Data 12, no. 2 (May 1, 2020): 961–1001. http://dx.doi.org/10.5194/essd-12-961-2020.
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Abstract. Emission of greenhouse gases (GHGs) and removals from land, including both anthropogenic and natural fluxes, require reliable quantification, including estimates of uncertainties, to support credible mitigation action under the Paris Agreement. This study provides a state-of-the-art scientific overview of bottom-up anthropogenic emissions data from agriculture, forestry and other land use (AFOLU) in the European Union (EU281). The data integrate recent AFOLU emission inventories with ecosystem data and land carbon models and summarize GHG emissions and removals over the period 1990–2016. This compilation of bottom-up estimates of the AFOLU GHG emissions of European national greenhouse gas inventories (NGHGIs), with those of land carbon models and observation-based estimates of large-scale GHG fluxes, aims at improving the overall estimates of the GHG balance in Europe with respect to land GHG emissions and removals. Whenever available, we present uncertainties, its propagation and role in the comparison of different estimates. While NGHGI data for the EU28 provide consistent quantification of uncertainty following the established IPCC Guidelines, uncertainty in the estimates produced with other methods needs to account for both within model uncertainty and the spread from different model results. The largest inconsistencies between EU28 estimates are mainly due to different sources of data related to human activity, referred to here as activity data (AD) and methodologies (tiers) used for calculating emissions and removals from AFOLU sectors. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.3662371 (Petrescu et al., 2020).
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Pelster, David, Mariana Rufino, Todd Rosenstock, Joash Mango, Gustavo Saiz, Eugenio Diaz-Pines, German Baldi, and Klaus Butterbach-Bahl. "Smallholder farms in eastern African tropical highlands have low soil greenhouse gas fluxes." Biogeosciences 14, no. 1 (January 12, 2017): 187–202. http://dx.doi.org/10.5194/bg-14-187-2017.
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Abstract. Few field studies examine greenhouse gas (GHG) emissions from African agricultural systems, resulting in high uncertainty for national inventories. This lack of data is particularly noticeable in smallholder farms in sub-Saharan Africa, where low inputs are often correlated with low yields, often resulting in food insecurity as well. We provide the most comprehensive study in Africa to date, examining annual soil CO2, CH4 and N2O emissions from 59 smallholder plots across different vegetation types, field types and land classes in western Kenya. The study area consists of a lowland area (approximately 1200 m a.s.l.) rising approximately 600 m to a highland plateau. Cumulative annual fluxes ranged from 2.8 to 15.0 Mg CO2-C ha−1, −6.0 to 2.4 kg CH4-C ha−1 and −0.1 to 1.8 kg N2O-N ha−1. Management intensity of the plots did not result in differences in annual GHG fluxes measured (P = 0.46, 0.14 and 0.67 for CO2, CH4 and N2O respectively). The similar emissions were likely related to low fertilizer input rates (≤ 20 kg N ha−1). Grazing plots had the highest CO2 fluxes (P = 0.005), treed plots (plantations) were a larger CH4 sink than grazing plots (P = 0.05), while soil N2O emissions were similar across vegetation types (P = 0.59). This study is likely representative for low fertilizer input, smallholder systems across sub-Saharan Africa, providing critical data for estimating regional or continental GHG inventories. Low crop yields, likely due to low fertilization inputs, resulted in high (up to 67 g N2O-N kg−1 aboveground N uptake) yield-scaled emissions. Improvement of crop production through better water and nutrient management might therefore be an important tool in increasing food security in the region while reducing the climate footprint per unit of food produced.
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SIRIN, A. A., and G. G. SUVOROV. "GREENHOUSE GAS EMISSIONS FROM PEAT EXTRACTION SITES IN THE CENTER OF THE EUROPEAN PART OF RUSSIA." Meteorologiya i Gidrologiya, no. 3 (March 2022): 68–80. http://dx.doi.org/10.52002/0130-2906-2022-3-68-80.
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The carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes measured at a peat extraction site in the Moscow region in different seasons of 2005-2015 are considered. The average daily (taking into account intradaily dynamics) and average annual fluxes (emission factors) of CO2, CH4, and N2O from the interditch spacing (including microscale elevations and depressions) and drainage channels were estimated. The values of CO2 and N2O fluxes from the main interditch surface were equal to 3.3 t C-CO2/(ha year) and 1.1 kg N-N2O/(ha year), respectively; the value of the CH4 flux from the channel was 3200 kg CH4/(ha year). The resulting estimates are consistent with the default emission factors proposed for the “peatland under extraction” land category by the 2013 Supplement to the IPCC 2006 Guidelines for National Greenhouse Gas Inventories: Wetlands. The results can be used for preparing the national report of the Russian Federation on the emission and absorption of greenhouse gases not controlled by the Montreal Protocol
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Deng, Zhu, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, et al. "Comparing national greenhouse gas budgets reported in UNFCCC inventories against atmospheric inversions." Earth System Science Data 14, no. 4 (April 11, 2022): 1639–75. http://dx.doi.org/10.5194/essd-14-1639-2022.
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Abstract. In support of the global stocktake of the Paris Agreement on climate change, this study presents a comprehensive framework to process the results of an ensemble of atmospheric inversions in order to make their net ecosystem exchange (NEE) carbon dioxide (CO2) flux suitable for evaluating national greenhouse gas inventories (NGHGIs) submitted by countries to the United Nations Framework Convention on Climate Change (UNFCCC). From inversions we also deduced anthropogenic methane (CH4) emissions regrouped into fossil and agriculture and waste emissions, as well as anthropogenic nitrous oxide (N2O) emissions. To compare inversion results with national reports, we compiled a new global harmonized database of emissions and removals from periodical UNFCCC inventories by Annex I countries, and from sporadic and less detailed emissions reports by non-Annex I countries, given by national communications and biennial update reports. No gap filling was applied. The method to reconcile inversions with inventories is applied to selected large countries covering ∼90 % of the global land carbon uptake for CO2 and top emitters of CH4 and N2O. Our method uses results from an ensemble of global inversions produced by the Global Carbon Project for the three greenhouse gases, with ancillary data. We examine the role of CO2 fluxes caused by lateral transfer processes from rivers and from trade in crop and wood products and the role of carbon uptake in unmanaged lands, both not accounted for by NGHGIs. Here we show that, despite a large spread across the inversions, the median of available inversion models points to a larger terrestrial carbon sink than inventories over temperate countries or groups of countries of the Northern Hemisphere like Russia, Canada and the European Union. For CH4, we find good consistency between the inversions assimilating only data from the global in situ network and those using satellite CH4 retrievals and a tendency for inversions to diagnose higher CH4 emission estimates than reported by NGHGIs. In particular, oil- and gas-extracting countries in central Asia and the Persian Gulf region tend to systematically report lower emissions compared to those estimated by inversions. For N2O, inversions tend to produce higher anthropogenic emissions than inventories for tropical countries, even when attempting to consider only managed land emissions. In the inventories of many non-Annex I countries, this can be tentatively attributed to a lack of reporting indirect N2O emissions from atmospheric deposition and from leaching to rivers, to the existence of natural sources intertwined with managed lands, or to an underestimation of N2O emission factors for direct agricultural soil emissions. Inversions provide insights into seasonal and interannual greenhouse gas fluxes anomalies, e.g., during extreme events such as drought or abnormal fire episodes, whereas inventory methods are established to estimate trends and multi-annual changes. As a much denser sampling of atmospheric CO2 and CH4 concentrations by different satellites coordinated into a global constellation is expected in the coming years, the methodology proposed here to compare inversion results with inventory reports (e.g., NGHGIs) could be applied regularly for monitoring the effectiveness of mitigation policy and progress by countries to meet the objective of their pledges. The dataset constructed by this study is publicly available at https://doi.org/10.5281/zenodo.5089799 (Deng et al., 2021).
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Zhang, X., X. Lee, T. J. Griffis, J. M. Baker, and W. Xiao. "Estimating regional greenhouse gas fluxes: an uncertainty analysis of planetary boundary layer techniques and bottom-up inventories." Atmospheric Chemistry and Physics 14, no. 19 (October 10, 2014): 10705–19. http://dx.doi.org/10.5194/acp-14-10705-2014.
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Abstract. Quantification of regional greenhouse gas (GHG) fluxes is essential for establishing mitigation strategies and evaluating their effectiveness. Here, we used multiple top-down approaches and multiple trace gas observations at a tall tower to estimate regional-scale GHG fluxes and evaluate the GHG fluxes derived from bottom-up approaches. We first applied the eddy covariance, equilibrium, inverse modeling (CarbonTracker), and flux aggregation methods using 3 years of carbon dioxide (CO2) measurements on a 244 m tall tower in the upper Midwest, USA. We then applied the equilibrium method for estimating CH4 and N2O fluxes with 1-month high-frequency CH4 and N2O gradient measurements on the tall tower and 1-year concentration measurements on a nearby tall tower, and evaluated the uncertainties of this application. The results indicate that (1) the flux aggregation, eddy covariance, the equilibrium method, and the CarbonTracker product all gave similar seasonal patterns of the regional CO2 flux (105−106 km2, but that the equilibrium method underestimated the July CO2 flux by 52–69%. (2) The annual budget varied among these methods from −54 to −131 g C–CO2 m−2 yr−1, indicating a large uncertainty in the annual CO2 flux estimation. (3) The regional CH4 and N2O emissions according to a top-down method were at least 6 and 2 times higher than the emissions from a bottom-up inventory (Emission Database for Global Atmospheric Research), respectively. (4) The global warming potentials of the CH4 and N2O emissions were equal in magnitude to the cooling benefit of the regional CO2 uptake. The regional GHG budget, including both biological and anthropogenic origins, is estimated at 7 ± 160 g CO2 equivalent m−2 yr−1.
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VanderZaag, A. C., R. J. Gordon, R. C. Jamieson, D. L. Burton, and G. W. Stratton. "Effects of winter storage conditions and subsequent agitation on gaseous emissions from liquid dairy manure." Canadian Journal of Soil Science 90, no. 1 (February 1, 2010): 229–39. http://dx.doi.org/10.4141/cjss09040.
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An understanding of emissions from liquid manure facilities during winter, spring thaw and agitation is needed to improve national emissions inventories in Canada. In this study, liquid dairy manure was stored in six pilot-scale tanks (1.8 m deep × 6.6 m2 surface area) covered by steady-state chambers that enabled greenhouse gas (GHG) and ammonia (NH3) flux measurement. After 158 d of undisturbed storage, three tanks were agitated for 5 d (8 h per day) consecutively. During storage, methane (CH4) flux was correlated with manure temperature at 30 cm depth (P < 0.05). Nitrous oxide (N2O) fluxes occurred only during spring thaw - at rates comparable with agricultural soil during spring thaw. On a carbon dioxide (CO2) equivalent basis, however, cumulative N2O fluxes were negligible compared with CH4 fluxes. Flux of NH3 was correlated positively with manure temperature near the surface and negatively with the presence of ice or a surface crust (P < 0.01). Agitation did not affect N2O and NH3 fluxes, whereas CO2 and CH4 fluxes increased significantly (P < 0.01) as dissolved gas and bubbles were released. Trapped CH4 released during agitation was estimated to be 6.3 g CH4 m-3 manure, and was depleted in 2 d. Considering the entire storage period, agitated tanks (158 d + 5 d agitation) had 6% higher GHG fluxes due to higher CH4 losses than undisturbed tanks (163 d). This CH4 release is small in context of annual fluxes, but may partially explain discrepancies between predicted and measured winter fluxes.Key words: Manure storage, agitation, greenhouse gas emission, ammonia emission, dissolved gas
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Zanger, Benjamin, Jia Chen, Man Sun, and Florian Dietrich. "Recovery of sparse urban greenhouse gas emissions." Geoscientific Model Development 15, no. 20 (October 17, 2022): 7533–56. http://dx.doi.org/10.5194/gmd-15-7533-2022.
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Abstract. To localize and quantify greenhouse gas emissions from cities, gas concentrations are typically measured at a small number of sites and then linked to emission fluxes using atmospheric transport models. Solving this inverse problem is challenging because the system of equations often has no unique solution and the solution can be sensitive to noise. A common top–down approach for solving this problem is Bayesian inversion with the assumption of a multivariate Gaussian distribution as the prior emission field. However, such an assumption has drawbacks when the assumed spatial emissions are incorrect or not Gaussian distributed. In our work, we investigate sparse reconstruction (SR), an alternative reconstruction method that can achieve reasonable estimations without using a prior emission field by making the assumption that the emission field is sparse. We show that this assumption is generally true for the cities we investigated and that the use of the discrete wavelet transform helps to make the urban emission field even more sparse. To evaluate the performance of SR, we created concentration data by applying an atmospheric forward transport model to CO2 emission inventories of several major European cities. We used SR to locate and quantify the emission sources by applying compressed sensing theory and compared the results to regularized least squares (LSs) methods. Our results show that SR requires fewer measurements than LS methods and that SR is better at localizing and quantifying unknown emitters.
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Fiehn, Alina, Julian Kostinek, Maximilian Eckl, Theresa Klausner, Michał Gałkowski, Jinxuan Chen, Christoph Gerbig, et al. "Estimating CH<sub>4</sub>, CO<sub>2</sub> and CO emissions from coal mining and industrial activities in the Upper Silesian Coal Basin using an aircraft-based mass balance approach." Atmospheric Chemistry and Physics 20, no. 21 (November 3, 2020): 12675–95. http://dx.doi.org/10.5194/acp-20-12675-2020.
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Abstract. A severe reduction of greenhouse gas emissions is necessary to reach the objectives of the Paris Agreement. The implementation and continuous evaluation of mitigation measures requires regular independent information on emissions of the two main anthropogenic greenhouse gases, carbon dioxide (CO2) and methane (CH4). Our aim is to employ an observation-based method to determine regional-scale greenhouse gas emission estimates with high accuracy. We use aircraft- and ground-based in situ observations of CH4, CO2, carbon monoxide (CO), and wind speed from two research flights over the Upper Silesian Coal Basin (USCB), Poland, in summer 2018. The flights were performed as a part of the Carbon Dioxide and Methane (CoMet) mission above this European CH4 emission hot-spot region. A kriging algorithm interpolates the observed concentrations between the downwind transects of the trace gas plume, and then the mass flux through this plane is calculated. Finally, statistic and systematic uncertainties are calculated from measurement uncertainties and through several sensitivity tests, respectively. For the two selected flights, the in-situ-derived annual CH4 emission estimates are 13.8±4.3 and 15.1±4.0 kg s−1, which are well within the range of emission inventories. The regional emission estimates of CO2, which were determined to be 1.21±0.75 and 1.12±0.38 t s−1, are in the lower range of emission inventories. CO mass balance emissions of 10.1±3.6 and 10.7±4.4 kg s−1 for the USCB are slightly higher than the emission inventory values. The CH4 emission estimate has a relative error of 26 %–31 %, the CO2 estimate of 37 %–62 %, and the CO estimate of 36 %–41 %. These errors mainly result from the uncertainty of atmospheric background mole fractions and the changing planetary boundary layer height during the morning flight. In the case of CO2, biospheric fluxes also add to the uncertainty and hamper the assessment of emission inventories. These emission estimates characterize the USCB and help to verify emission inventories and develop climate mitigation strategies.
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Kurz, W. A., S. Hayne, M. Fellows, J. D. MacDonald, J. M. Metsaranta, M. Hafer, and D. Blain. "Quantifying the impacts of human activities on reported greenhouse gas emissions and removals in Canada’s managed forest: conceptual framework and implementation." Canadian Journal of Forest Research 48, no. 10 (October 2018): 1227–40. http://dx.doi.org/10.1139/cjfr-2018-0176.
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The land sector is expected to contribute to strategies aimed at mitigating global temperature increases and this necessitates an improved understanding of human actions on land sector emissions and removals. Current Intergovernmental Panel on Climate Change guidelines for the land sector of national greenhouse gas inventories are based on the assumption that all emissions and removals in managed lands are caused by humans. In Canada, however, natural disturbances in managed forests can result in large and highly variable emissions and subsequent removals that mask the impacts of management activities. Here we describe methods to isolate and quantify the impacts of management on trends in estimated anthropogenic emissions and removals in Canada’s managed forest by partitioning fluxes from two land components: fluxes from lands dominated by natural disturbance effects and fluxes from the remaining managed forests. The sum of the flux estimates of the two land components is equal to net emissions and removals in managed forest lands. Separating highly variable natural disturbance fluxes from the remaining fluxes in managed forest lands increases the understanding of how human activities impact flux trends. Comparing these anthropogenic emissions and removals with those from natural disturbances quantifies their relative contributions to global atmospheric CO2 concentrations.
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Corrêa, Darlena Caroline da Cruz, Abmael da Silva Cardoso, Mariane Rodrigues Ferreira, Débora Siniscalchi, Ariana Desie Toniello, Gilmar Cotrin de Lima, Ricardo Andrade Reis, and Ana Claudia Ruggieri. "Are CH4, CO2, and N2O Emissions from Soil Affected by the Sources and Doses of N in Warm-Season Pasture?" Atmosphere 12, no. 6 (May 29, 2021): 697. http://dx.doi.org/10.3390/atmos12060697.
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The intensification of pasture production has increased the use of N fertilizers—a practice that can alter soil greenhouse gas (GHG) fluxes. The objective of the present study was to evaluate the fluxes of CH4, CO2, and N2O in the soil of Urochloa brizantha ‘Marandu’ pastures fertilized with different sources and doses of N. Two field experiments were conducted to evaluate GHG fluxes following N fertilization with urea, ammonium nitrate, and ammonium sulfate at doses of 0, 90, 180, and 270 kg N ha−1. GHG fluxes were quantified using the static chamber technique and gas chromatography. In both experiments, the sources and doses of N did not significantly affect cumulative GHG emissions, while N fertilization significantly affected cumulative N2O and CO2 emissions compared to the control treatment. The N2O emission factor following fertilization with urea, ammonium nitrate, and ammonium sulfate was lower than the United Nations’ Intergovernmental Panel on Climate Change standard (0.35%, 0.24%, and 0.21%, respectively, with fractionation fertilization and 1.00%, 0.83%, and 1.03%, respectively, with single fertilization). These findings are important for integrating national inventories and improving GHG estimation in tropical regions.
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Helfter, Carole, Anja H. Tremper, Christoforos H. Halios, Simone Kotthaus, Alex Bjorkegren, C. Sue B. Grimmond, Janet F. Barlow, and Eiko Nemitz. "Spatial and temporal variability of urban fluxes of methane, carbon monoxide and carbon dioxide above London, UK." Atmospheric Chemistry and Physics 16, no. 16 (August 24, 2016): 10543–57. http://dx.doi.org/10.5194/acp-16-10543-2016.
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Abstract. We report on more than 3 years of measurements of fluxes of methane (CH4), carbon monoxide (CO) and carbon dioxide (CO2) taken by eddy-covariance in central London, UK. Mean annual emissions of CO2 in the period 2012–2014 (39.1 ± 2.4 ktons km−2 yr−1) and CO (89 ± 16 tons km−2 yr−1) were consistent (within 1 and 5 % respectively) with values from the London Atmospheric Emissions Inventory, but measured CH4 emissions (72 ± 3 tons km−2 yr−1) were over two-fold larger than the inventory value. Seasonal variability was large for CO with a winter to summer reduction of 69 %, and monthly fluxes were strongly anti-correlated with mean air temperature. The winter increment in CO emissions was attributed mainly to vehicle cold starts and reduced fuel combustion efficiency. CO2 fluxes were 33 % higher in winter than in summer and anti-correlated with mean air temperature, albeit to a lesser extent than for CO. This was attributed to an increased demand for natural gas for heating during the winter. CH4 fluxes exhibited moderate seasonality (21 % larger in winter), and a spatially variable linear anti-correlation with air temperature. Differences in resident population within the flux footprint explained up to 90 % of the spatial variability of the annual CO2 fluxes and up to 99 % for CH4. Furthermore, we suggest that biogenic sources of CH4, such as wastewater, which is unaccounted for by the atmospheric emissions inventories, make a substantial contribution to the overall budget and that commuting dynamics in and out of central business districts could explain some of the spatial and temporal variability of CO2 and CH4 emissions. To our knowledge, this study is unique given the length of the data sets presented, especially for CO and CH4 fluxes. This study offers an independent assessment of "bottom-up" emissions inventories and demonstrates that the urban sources of CO and CO2 are well characterized in London. This is however not the case for CH4 emissions which are heavily underestimated by the inventory approach. Our results and others point to opportunities in the UK and abroad to identify and quantify the "missing" sources of urban methane, revise the methodologies of the emission inventories and devise emission reduction strategies for this potent greenhouse gas.
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Kinsela, Andrew S., O. Tom Denmead, Bennett C. T. Macdonald, Michael D. Melville, Jason K. Reynolds, and Ian White. "Field-based measurements of sulfur gas emissions from an agricultural coastal acid sulfate soil, eastern Australia." Soil Research 49, no. 6 (2011): 471. http://dx.doi.org/10.1071/sr11089.
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The emissions of biogenic hydrogen sulfide (H2S) and sulfur dioxide (SO2) play important roles in the global atmospheric sulfur (S) cycle. Field-based investigations using ultraviolet fluorescence spectroscopy show that drained acid sulfate soils (ASS) are a potentially unaccounted source of biogenic H2S and SO2. Significant diurnal variations were evident in SO2 fluxes, with average daytime measurements 9.3–16.5-fold greater than night-time emissions. Similar diurnal patterns in H2S fluxes were observed but proved statistically insignificant. The results from simultaneously collected micrometeorological measurements suggest that emissions of SO2 and H2S are most likely occurring via different processes. The SO2 fluxes are closely linked to surface soil temperature and moisture content, whereas H2S is constantly emitted from the land surface at the two study sites. Drained ASS are most likely mapped as agricultural lands rather than drained backswamps. Therefore, these areas are likely to be assigned H2S and SO2 flux values of zero in greenhouse gas species inventories. These findings suggest a need to expand these measurements to other drained ASS areas to refine regional (and possibly global) atmospheric S budgets. Further research is necessary to elucidate the sources of measured S compounds, and specifically whether they are limited to individual agricultural drainage patterns in ASS.
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Kesik, M., P. Ambus, R. Baritz, N. Brüggemann, K. Butterbach-Bahl, M. Damm, J. Duyzer, et al. "Inventories of N<sub>2</sub>O and NO emissions from European forest soils." Biogeosciences 2, no. 4 (December 5, 2005): 353–75. http://dx.doi.org/10.5194/bg-2-353-2005.
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Abstract. Forest soils are a significant source for the primary and secondary greenhouse gases N2O and NO. However, current estimates are still uncertain due to the still limited number of field measurements and the herein observed pronounced variability of N trace gas fluxes in space and time, which are due to the variation of environmental factors such as soil and vegetation properties or meteorological conditions. To overcome these problems we further developed a process-oriented model, the PnET-N-DNDC model, which simulates the N trace gas exchange on the basis of the processes involved in production, consumption and emission of N trace gases. This model was validated against field observations of N trace gas fluxes from 19 sites obtained within the EU project NOFRETETE, and shown to perform well for N2O (r2=0.68, slope=0.76) and NO (r2=0.78, slope=0.73). For the calculation of a European-wide emission inventory we linked the model to a detailed, regionally and temporally resolved database, comprising climatic properties (daily resolution), and soil parameters, and information on forest areas and types for the years 1990, 1995 and 2000. Our calculations show that N trace gas fluxes from forest soils may vary substantial from year to year and that distinct regional patterns can be observed. Our central estimate of NO emissions from forest soils in the EU amounts to 98.4, 84.9 and 99.2 kt N yr−1, using meteorology from 1990, 1995 and year 2000, respectively. This is <1.0% of pyrogenic NOx emissions. For N2O emissions the central estimates were 86.8, 77.6 and 81.6 kt N yr−1, respectively, which is approx. 14.5% of the source strength coming from agricultural soils. An extensive sensitivity analysis was conducted which showed a range in emissions from 44.4 to 254.0 kt N yr−1 for NO and 50.7 to 96.9 kt N yr−1 for N2O, for year 2000 meteorology. The results show that process-oriented models coupled to a GIS are useful tools for the calculation of regional, national, or global inventories of biogenic N trace gas emissions from soils. This work represents the most comprehensive effort to date to simulate NO and N2O emissions from European forest soils.
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Kesik, M., P. Ambus, R. Baritz, N. Brüggemann, K. Butterbach-Bahl, M. Damm, J. Duyzer, et al. "Inventories of N<sub>2</sub>O and NO emissions from European forest soils." Biogeosciences Discussions 2, no. 4 (July 15, 2005): 779–827. http://dx.doi.org/10.5194/bgd-2-779-2005.
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Abstract. Forest soils are a significant source for the primary and secondary greenhouse gases N2O and NO. However, current estimates are still uncertain due to the still limited number of field measurements and the herein observed pronounced variability of N trace gas fluxes in space and time, which are due to the variation of environmental factors such as soil and vegetation properties or meteorological conditions. To overcome these problems we further developed a process-oriented model, the PnET-N-DNDC model, which simulates the N trace gas exchange on the basis of the processes involved in production, consumption and emission of N trace gases. This model was validated against field observations of N trace gas fluxes from 19 sites obtained within the EU project NOFRETETE, and shown to perform well for N2O (r=0.68, slope=0.76) and NO (r2=0.78, slope=0.73). For the calculation of a European-wide emission inventory we linked the model to a detailed, regionally and temporally resolved database, comprising climatic properties (daily resolution), and soil parameters, and information on forest areas and types for the years 1990, 1995 and 2000. Our calculations show that N trace gas fluxes from forest soils may vary substantial from year to year and that distinct regional patterns can be observed. Our central estimate of NO emissions from forest soils in the EU amounts to 98.4, 84.9 and 99.2 kt N yr-1, using meteorology from 1990, 1995 and year 2000, respectively. This is <1.0% of pyrogenic NOx emissions. For N2O emissions the central estimates were 86.8, 77.6 and 81.6 kt N yr-1, respectively, which is approx. 14.5% of the source strength coming from agricultural soils. An extensive sensitivity analysis was conducted which showed a range in NO emissions from 44.4 to 254.0 kt N yr-1 for NO and 50.7 to 96.9 kt N yr-1 for N2O, for year 2000 meteorology. The results show that process-oriented models coupled to a GIS are useful tools for the calculation of regional, national, or global inventories of biogenic N-trace gas emissions from soils. This work represents the most comprehensive effort to date to simulate NO and N2O emissions from European forest soils.
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Webb, Jackie R., Peter R. Leavitt, Gavin L. Simpson, Helen M. Baulch, Heather A. Haig, Kyle R. Hodder, and Kerri Finlay. "Regulation of carbon dioxide and methane in small agricultural reservoirs: optimizing potential for greenhouse gas uptake." Biogeosciences 16, no. 21 (November 8, 2019): 4211–27. http://dx.doi.org/10.5194/bg-16-4211-2019.
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Abstract. Small farm reservoirs are abundant in many agricultural regions across the globe and have the potential to be large contributing sources of carbon dioxide (CO2) and methane (CH4) to agricultural landscapes. Compared to natural ponds, these artificial waterbodies remain overlooked in both agricultural greenhouse gas (GHG) inventories and inland water global carbon (C) budgets. Improved understanding of the environmental controls of C emissions from farm reservoirs is required to address and manage their potential importance in agricultural GHG budgets. Here, we conducted a regional-scale survey (∼ 235 000 km2) to measure CO2 and CH4 surface concentrations and diffusive fluxes across 101 small farm reservoirs in Canada's largest agricultural area. A combination of abiotic, biotic, hydromorphologic, and landscape variables were modelled using generalized additive models (GAMs) to identify regulatory mechanisms. We found that CO2 concentration was estimated by a combination of internal metabolism and groundwater-derived alkalinity (66.5 % deviance explained), while multiple lines of evidence support a positive association between eutrophication and CH4 production (74.1 % deviance explained). Fluxes ranged from −21 to 466 and 0.14 to 92 mmol m−2 d−1 for CO2 and CH4, respectively, with CH4 contributing an average of 74 % of CO2-equivalent (CO2-e) emissions based on a 100-year radiative forcing. Approximately 8 % of farm reservoirs were found to be net CO2-e sinks. From our models, we show that the GHG impact of farm reservoirs can be greatly minimized with overall improvements in water quality and consideration to position and hydrology within the landscape.
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Jones, Taylor S., Jonathan E. Franklin, Jia Chen, Florian Dietrich, Kristian D. Hajny, Johannes C. Paetzold, Adrian Wenzel, et al. "Assessing urban methane emissions using column-observing portable Fourier transform infrared (FTIR) spectrometers and a novel Bayesian inversion framework." Atmospheric Chemistry and Physics 21, no. 17 (September 6, 2021): 13131–47. http://dx.doi.org/10.5194/acp-21-13131-2021.
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Abstract. Cities represent a large and concentrated portion of global greenhouse gas emissions, including methane. Quantifying methane emissions from urban areas is difficult, and inventories made using bottom-up accounting methods often differ greatly from top-down estimates generated from atmospheric observations. Emissions from leaks in natural gas infrastructure are difficult to predict and are therefore poorly constrained in bottom-up inventories. Natural gas infrastructure leaks and emissions from end uses can be spread throughout the city, and this diffuse source can represent a significant fraction of a city's total emissions. We investigated diffuse methane emissions of the city of Indianapolis, USA, during a field campaign in May 2016. A network of five portable solar-tracking Fourier transform infrared (FTIR) spectrometers was deployed throughout the city. These instruments measure the mole fraction of methane in a total column of air, giving them sensitivity to larger areas of the city than in situ sensors at the surface. We present an innovative inversion method to link these total column concentrations to surface fluxes. This method combines a Lagrangian transport model with a Bayesian inversion framework to estimate surface emissions and their uncertainties, together with determining the concentrations of methane in the air flowing into the city. Variations exceeding 10 ppb were observed in the inflowing air on a typical day, which is somewhat larger than the enhancements due to urban emissions (<5 ppb downwind of the city). We found diffuse methane emissions of 73(±22) mol s−1, which is about 50 % of the urban total and 68 % higher than estimated from bottom-up methods, although it is somewhat smaller than estimates from studies using tower and aircraft observations. The measurement and model techniques developed here address many of the challenges present when quantifying urban greenhouse gas emissions and will help in the design of future measurement schemes in other cities.
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Riddick, Stuart N., Denise L. Mauzerall, Michael Celia, Neil R. P. Harris, Grant Allen, Joseph Pitt, John Staunton-Sykes, et al. "Methane emissions from oil and gas platforms in the North Sea." Atmospheric Chemistry and Physics 19, no. 15 (August 2, 2019): 9787–96. http://dx.doi.org/10.5194/acp-19-9787-2019.
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Abstract. Since 1850 the concentration of atmospheric methane (CH4), a potent greenhouse gas, has more than doubled. Recent studies suggest that emission inventories may be missing sources and underestimating emissions. To investigate whether offshore oil and gas platforms leak CH4 during normal operation, we measured CH4 mole fractions around eight oil and gas production platforms in the North Sea which were neither flaring gas nor offloading oil. We use the measurements from summer 2017, along with meteorological data, in a Gaussian plume model to estimate CH4 emissions from each platform. We find CH4 mole fractions of between 11 and 370 ppb above background concentrations downwind of the platforms measured, corresponding to a median CH4 emission of 6.8 g CH4 s−1 for each platform, with a range of 2.9 to 22.3 g CH4 s−1. When matched to production records, during our measurements individual platforms lost between 0.04 % and 1.4 % of gas produced with a median loss of 0.23 %. When the measured platforms are considered collectively (i.e. the sum of platforms' emission fluxes weighted by the sum of the platforms' production), we estimate the CH4 loss to be 0.19 % of gas production. These estimates are substantially higher than the emissions most recently reported to the National Atmospheric Emission Inventory (NAEI) for total CH4 loss from United Kingdom platforms in the North Sea. The NAEI reports CH4 losses from the offshore oil and gas platforms we measured to be 0.13 % of gas production, with most of their emissions coming from gas flaring and offshore oil loading, neither of which was taking place at the time of our measurements. All oil and gas platforms we observed were found to leak CH4 during normal operation, and much of this leakage has not been included in UK emission inventories. Further research is required to accurately determine total CH4 leakage from all offshore oil and gas operations and to properly include the leakage in national and international emission inventories.
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Luyssaert, S., G. Abril, R. Andres, D. Bastviken, V. Bellassen, P. Bergamaschi, P. Bousquet, et al. "The European land and inland water CO<sub>2</sub>, CO, CH<sub>4</sub> and N<sub>2</sub>O balance between 2001 and 2005." Biogeosciences 9, no. 8 (August 24, 2012): 3357–80. http://dx.doi.org/10.5194/bg-9-3357-2012.
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Abstract. Globally, terrestrial ecosystems have absorbed about 30% of anthropogenic greenhouse gas emissions over the period 2000–2007 and inter-hemispheric gradients indicate that a significant fraction of terrestrial carbon sequestration must be north of the Equator. We present a compilation of the CO2, CO, CH4 and N2O balances of Europe following a dual constraint approach in which (1) a land-based balance derived mainly from ecosystem carbon inventories and (2) a land-based balance derived from flux measurements are compared to (3) the atmospheric data-based balance derived from inversions constrained by measurements of atmospheric GHG (greenhouse gas) concentrations. Good agreement between the GHG balances based on fluxes (1294 ± 545 Tg C in CO2-eq yr−1), inventories (1299 ± 200 Tg C in CO2-eq yr−1) and inversions (1210 ± 405 Tg C in CO2-eq yr−1) increases our confidence that the processes underlying the European GHG budget are well understood and reasonably sampled. However, the uncertainty remains large and largely lacks formal estimates. Given that European net land to atmosphere exchanges are determined by a few dominant fluxes, the uncertainty of these key components needs to be formally estimated before efforts could be made to reduce the overall uncertainty. The net land-to-atmosphere flux is a net source for CO2, CO, CH4 and N2O, because the anthropogenic emissions by far exceed the biogenic sink strength. The dual-constraint approach confirmed that the European biogenic sink removes as much as 205 ± 72 Tg C yr−1 from fossil fuel burning from the atmosphere. However, This C is being sequestered in both terrestrial and inland aquatic ecosystems. If the C-cost for ecosystem management is taken into account, the net uptake of ecosystems is estimated to decrease by 45% but still indicates substantial C-sequestration. However, when the balance is extended from CO2 towards the main GHGs, C-uptake by terrestrial and aquatic ecosystems is offset by emissions of non-CO2 GHGs. As such, the European ecosystems are unlikely to contribute to mitigating the effects of climate change.
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Leiber-Sauheitl, K., R. Fuß, C. Voigt, and A. Freibauer. "High greenhouse gas fluxes from grassland on histic gleysol along soil carbon and drainage gradients." Biogeosciences Discussions 10, no. 7 (July 9, 2013): 11283–317. http://dx.doi.org/10.5194/bgd-10-11283-2013.
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Abstract. Drained organic soils are anthropogenic emission hotspots of greenhouse gases (GHGs). Most studies have focused on deep peat soils and on peats with high organic carbon content. In contrast, Histic gleysols are characterized by shallow peat layers, which are left over from peat cutting activities, or by peat mixed with mineral soil. It is unknown whether they emit less GHGs than deep Histosols when drained. We present the annual carbon and GHG balance of grasslands for six sites on nutrient-poor histic gleysols with a shallow (30 cm) histic horizon or mixed with mineral soil in Northern Germany (soil organic carbon concentration (Corg) from 9 to 52%). The net GHG balance, corrected for carbon export by harvest, was around 4 t CO2-C-eq. ha−1 yr−1 on soils with peat layer and little drainage (mean annual water table <20 cm below surface). The net GHG balance reached 7–9 t CO2-C-eq. ha−1 yr−1 on soils with peat layer and deeper drainage (mean annual water table >20 cm below surface) and on soils with sand mixed into the histic horizon, independent of water table level. GHG emissions from drained histic gleysols (i) were as high as those from deep histosols, (ii) linearly related to water table, (iii) but not affected by Corg content of the histic horizon. Ecosystem respiration (Reco) was linearly correlated with water table level even if it was below the histic horizon. The Reco : GPP ratio was 1.5 at all sites, so that we ruled out a major influence of the inter-site variability in vegetation composition on annual net ecosystem exchange (NEE). The IPCC definition of organic soils includes shallow histic topsoil, unlike most national and international definitions of histosols. Our study confirms that this broader definition is appropriate considering anthropogenic GHG emissions from drained organic soils. Countries currently apply soil maps in national GHG inventories which are likely not to include histic gleysols. The land area with GHG emission hotspots due to drainage is likely to be much higher than anticipated. Deeply drained histic gleysols are GHG hotspots which have so far been neglected or underestimated. Peat mixing with sand does not mitigate GHG emissions. Our study implies that rewetting organic soils, including histic gleysols, has a much higher relevance for GHG mitigation strategies than currently recognized.
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Janardanan, Rajesh, Shamil Maksyutov, Aki Tsuruta, Fenjuan Wang, Yogesh K. Tiwari, Vinu Valsala, Akihiko Ito, et al. "Country-Scale Analysis of Methane Emissions with a High-Resolution Inverse Model Using GOSAT and Surface Observations." Remote Sensing 12, no. 3 (January 24, 2020): 375. http://dx.doi.org/10.3390/rs12030375.
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We employed a global high-resolution inverse model to optimize the CH4 emission using Greenhouse gas Observing Satellite (GOSAT) and surface observation data for a period from 2011–2017 for the two main source categories of anthropogenic and natural emissions. We used the Emission Database for Global Atmospheric Research (EDGAR v4.3.2) for anthropogenic methane emission and scaled them by country to match the national inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC). Wetland and soil sink prior fluxes were simulated using the Vegetation Integrative Simulator of Trace gases (VISIT) model. Biomass burning prior fluxes were provided by the Global Fire Assimilation System (GFAS). We estimated a global total anthropogenic and natural methane emissions of 340.9 Tg CH4 yr−1 and 232.5 Tg CH4 yr−1, respectively. Country-scale analysis of the estimated anthropogenic emissions showed that all the top-emitting countries showed differences with their respective inventories to be within the uncertainty range of the inventories, confirming that the posterior anthropogenic emissions did not deviate from nationally reported values. Large countries, such as China, Russia, and the United States, had the mean estimated emission of 45.7 ± 8.6, 31.9 ± 7.8, and 29.8 ± 7.8 Tg CH4 yr−1, respectively. For natural wetland emissions, we estimated large emissions for Brazil (39.8 ± 12.4 Tg CH4 yr−1), the United States (25.9 ± 8.3 Tg CH4 yr−1), Russia (13.2 ± 9.3 Tg CH4 yr−1), India (12.3 ± 6.4 Tg CH4 yr−1), and Canada (12.2 ± 5.1 Tg CH4 yr−1). In both emission categories, the major emitting countries all had the model corrections to emissions within the uncertainty range of inventories. The advantages of the approach used in this study were: (1) use of high-resolution transport, useful for simulations near emission hotspots, (2) prior anthropogenic emissions adjusted to the UNFCCC reports, (3) combining surface and satellite observations, which improves the estimation of both natural and anthropogenic methane emissions over spatial scale of countries.
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Thürig, Esther, and Stéphanie Schmid. "Jährliche CO2-Flüsse im Wald: Berechnungsmethode für das Treibhausgasinventar | Annual CO2 fluxes in forests: calculation method for the Greenhouse Gas Inventory." Schweizerische Zeitschrift fur Forstwesen 159, no. 2 (February 1, 2008): 31–38. http://dx.doi.org/10.3188/szf.2008.0031.
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Forests can be carbon sinks as well as carbon sources. In the Kyoto Protocol, forests play a special role. According to Art. 3.4 of the Kyoto Protocol, Switzerland has decided to account for forest management. Since 1990, each participating country must submit the Greenhouse Gas Inventory (GHGI) to the climate convention. These inventories build the basis for the annual estimation of carbon sink and sources under the Kyoto Protocol. This article describes the calculation method of the forest carbon budget in the Swiss GHGI, which is obtained by utilizing the database of the Swiss National Forest Inventory (NFI 1 and 2). Annual CO2-budgets are derived from using the annual wood production, annual climate values, and a climate-sensitive growth model. The large spatial and temporal resolutions of the emission data and factors optimally represent the spatial heterogeneity in Switzerland. The main gaps are in estimating carbon fluxes in dead wood and soil. Moreover, the effect of the annual climate variation on average growth should be investigated in more detail. Once the NFI3 data are available, CO2-budgets will need to be recalculated going as far back as 1995.
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Leppelt, T., R. Dechow, S. Gebbert, A. Freibauer, A. Lohila, J. Augustin, M. Drösler, et al. "Nitrous oxide emission budgets and land-use-driven hotspots for organic soils in Europe." Biogeosciences 11, no. 23 (December 1, 2014): 6595–612. http://dx.doi.org/10.5194/bg-11-6595-2014.
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Abstract. Organic soils are a main source of direct emissions of nitrous oxide (N2O), an important greenhouse gas (GHG). Observed N2O emissions from organic soils are highly variable in space and time, which causes high uncertainties in national emission inventories. Those uncertainties could be reduced when relating the upscaling process to a priori-identified key drivers by using available N2O observations from plot scale in empirical approaches. We used the empirical fuzzy modelling approach MODE to identify main drivers for N2O and utilize them to predict the spatial emission pattern of European organic soils. We conducted a meta-study with a total amount of 659 annual N2O measurements, which was used to derive separate models for different land use types. We applied our models to available, spatially explicit input driver maps to upscale N2O emissions at European level and compared the inventory with recently published IPCC emission factors. The final statistical models explained up to 60% of the N2O variance. Our study results showed that cropland and grasslands emitted the highest N2O fluxes 0.98 ± 1.08 and 0.58 ± 1.03 g N2O-N m−2 a−1, respectively. High fluxes from cropland sites were mainly controlled by low soil pH value and deep-drained groundwater tables. Grassland hotspot emissions were strongly related to high amount of N-fertilizer inputs and warmer winter temperatures. In contrast, N2O fluxes from natural peatlands were predominantly low (0.07 ± 0.27 g N2O-N m−2 a−1) and we found no relationship with the tested drivers. The total inventory for direct N2O emissions from organic soils in Europe amount up to 149.5 Gg N2O-N a−1, which also included fluxes from forest and peat extraction sites and exceeds the inventory calculated by IPCC emission factors of 87.4 Gg N2O-N a−1. N2O emissions from organic soils represent up to 13% of total European N2O emissions reported in the European Union (EU) greenhouse gas inventory of 2011 from only 7% of the EU area. Thereby the model demonstrated that the major part (85%) of the inventory is induced by anthropogenic management, which shows the significant reduction potential by rewetting and extensification of agriculturally used peat soils.
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Leppelt, T., R. Dechow, S. Gebbert, A. Freibauer, A. Lohila, J. Augustin, M. Drösler, et al. "Nitrous oxide emission hotspots from organic soils in Europe." Biogeosciences Discussions 11, no. 6 (June 16, 2014): 9135–82. http://dx.doi.org/10.5194/bgd-11-9135-2014.
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Abstract. Organic soils are a main source of direct nitrous oxide (N2O) emissions, an important greenhouse gas (GHG). Observed N2O emissions from organic soils are highly variable in space and time which causes high uncertainties in national emission inventories. Those uncertainties could be reduced when relating the upscaling process to a priori identified key drivers by using available N2O observations from plot scale in empirical approaches. We used the empirical fuzzy modelling approach MODE to identify main drivers for N2O and utilize them to predict the spatial emission pattern of European organic soils. We conducted a meta study with a total amount of 659 annual N2O measurements which was used to derive separate models for different land use types. We applied our models to available, spatial explicit input driver maps to upscale N2O emissions on European level and compared the inventory with recently published IPCC emission factors. The final statistical models explained up to 60% of the N2O variance. Our study results showed that cropland and grasslands emitted the highest N2O fluxes 0.98 ± 1.08 and 0.58 ± 1.03 g N2O-N m−2 a−1, respectively. High fluxes from cropland sites were mainly controlled by low soil pH-value and deep drained groundwater tables. Grassland hotspot emissions were strongly related to high amount of N-fertilizer inputs and warmer winter temperatures. In contrast N2O fluxes from natural peatlands were predominantly low (0.07±0.27 g N2O-N m−2 a−1) and we found no relationship with the tested drivers. The total inventory for direct N2O emissions from organic soils in Europe amount up to 149.5 Gg N2O-N a−1, which included also fluxes from forest and peat extraction sites and exceeds the inventory calculated by IPCC emission factors of 87.4 Gg N2O-N a−1. N2O emissions from organic soils represent up to 13% of total European N2O emissions reported in the European Union (EU) greenhouse gas inventory of 2011 from only 7% of the EU area. Thereby the model demonstrated that with up to 85% the major part of the inventory is induced by anthropogenic management, which shows the significant reduction potential by rewetting and extensivation of agricultural used peat soils.
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Turner, Peter A., Timothy J. Griffis, Xuhui Lee, John M. Baker, Rodney T. Venterea, and Jeffrey D. Wood. "Indirect nitrous oxide emissions from streams within the US Corn Belt scale with stream order." Proceedings of the National Academy of Sciences 112, no. 32 (July 27, 2015): 9839–43. http://dx.doi.org/10.1073/pnas.1503598112.
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N2O is an important greenhouse gas and the primary stratospheric ozone depleting substance. Its deleterious effects on the environment have prompted appeals to regulate emissions from agriculture, which represents the primary anthropogenic source in the global N2O budget. Successful implementation of mitigation strategies requires robust bottom-up inventories that are based on emission factors (EFs), simulation models, or a combination of the two. Top-down emission estimates, based on tall-tower and aircraft observations, indicate that bottom-up inventories severely underestimate regional and continental scale N2O emissions, implying that EFs may be biased low. Here, we measured N2O emissions from streams within the US Corn Belt using a chamber-based approach and analyzed the data as a function of Strahler stream order (S). N2O fluxes from headwater streams often exceeded 29 nmol N2O-N m−2⋅s−1 and decreased exponentially as a function of S. This relation was used to scale up riverine emissions and to assess the differences between bottom-up and top-down emission inventories at the local to regional scale. We found that the Intergovernmental Panel on Climate Change (IPCC) indirect EF for rivers (EF5r) is underestimated up to ninefold in southern Minnesota, which translates to a total tier 1 agricultural underestimation of N2O emissions by 40%. We show that accounting for zero-order streams as potential N2O hotspots can more than double the agricultural budget. Applying the same analysis to the US Corn Belt demonstrates that the IPCC EF5r underestimation explains the large differences observed between top-down and bottom-up emission estimates.
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Rozendaal, Danaë M. A., Daniela Requena Suarez, Veronique De Sy, Valerio Avitabile, Sarah Carter, C. Y. Adou Yao, Esteban Alvarez-Davila, et al. "Aboveground forest biomass varies across continents, ecological zones and successional stages: refined IPCC default values for tropical and subtropical forests." Environmental Research Letters 17, no. 1 (January 1, 2022): 014047. http://dx.doi.org/10.1088/1748-9326/ac45b3.
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Abstract For monitoring and reporting forest carbon stocks and fluxes, many countries in the tropics and subtropics rely on default values of forest aboveground biomass (AGB) from the Intergovernmental Panel on Climate Change (IPCC) guidelines for National Greenhouse Gas (GHG) Inventories. Default IPCC forest AGB values originated from 2006, and are relatively crude estimates of average values per continent and ecological zone. The 2006 default values were based on limited plot data available at the time, methods for their derivation were not fully clear, and no distinction between successional stages was made. As part of the 2019 Refinement to the 2006 IPCC Guidelines for GHG Inventories, we updated the default AGB values for tropical and subtropical forests based on AGB data from >25 000 plots in natural forests and a global AGB map where no plot data were available. We calculated refined AGB default values per continent, ecological zone, and successional stage, and provided a measure of uncertainty. AGB in tropical and subtropical forests varies by an order of magnitude across continents, ecological zones, and successional stage. Our refined default values generally reflect the climatic gradients in the tropics, with more AGB in wetter areas. AGB is generally higher in old-growth than in secondary forests, and higher in older secondary (regrowth >20 years old and degraded/logged forests) than in young secondary forests (⩽20 years old). While refined default values for tropical old-growth forest are largely similar to the previous 2006 default values, the new default values are 4.0–7.7-fold lower for young secondary forests. Thus, the refined values will strongly alter estimated carbon stocks and fluxes, and emphasize the critical importance of old-growth forest conservation. We provide a reproducible approach to facilitate future refinements and encourage targeted efforts to establish permanent plots in areas with data gaps.
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Tian, Hanqin, Jia Yang, Chaoqun Lu, Rongting Xu, Josep G. Canadell, Robert B. Jackson, Almut Arneth, et al. "The Global N2O Model Intercomparison Project." Bulletin of the American Meteorological Society 99, no. 6 (June 2018): 1231–51. http://dx.doi.org/10.1175/bams-d-17-0212.1.
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AbstractNitrous oxide (N2O) is an important greenhouse gas and also an ozone-depleting substance that has both natural and anthropogenic sources. Large estimation uncertainty remains on the magnitude and spatiotemporal patterns of N2O fluxes and the key drivers of N2O production in the terrestrial biosphere. Some terrestrial biosphere models have been evolved to account for nitrogen processes and to show the capability to simulate N2O emissions from land ecosystems at the global scale, but large discrepancies exist among their estimates primarily because of inconsistent input datasets, simulation protocol, and model structure and parameterization schemes. Based on the consistent model input data and simulation protocol, the global N2O Model Intercomparison Project (NMIP) was initialized with 10 state-of-the-art terrestrial biosphere models that include nitrogen (N) cycling. Specific objectives of NMIP are to 1) unravel the major N cycling processes controlling N2O fluxes in each model and identify the uncertainty sources from model structure, input data, and parameters; 2) quantify the magnitude and spatial and temporal patterns of global and regional N2O fluxes from the preindustrial period (1860) to present and attribute the relative contributions of multiple environmental factors to N2O dynamics; and 3) provide a benchmarking estimate of N2O fluxes through synthesizing the multimodel simulation results and existing estimates from ground-based observations, inventories, and statistical and empirical extrapolations. This study provides detailed descriptions for the NMIP protocol, input data, model structure, and key parameters, along with preliminary simulation results. The global and regional N2O estimation derived from the NMIP is a key component of the global N2O budget synthesis activity jointly led by the Global Carbon Project and the International Nitrogen Initiative.
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Wang, Fenjuan, Shamil Maksyutov, Aki Tsuruta, Rajesh Janardanan, Akihiko Ito, Motoki Sasakawa, Toshinobu Machida, et al. "Methane Emission Estimates by the Global High-Resolution Inverse Model Using National Inventories." Remote Sensing 11, no. 21 (October 24, 2019): 2489. http://dx.doi.org/10.3390/rs11212489.
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We present a global 0.1° × 0.1° high-resolution inverse model, NIES-TM-FLEXPART-VAR (NTFVAR), and a methane emission evaluation using the Greenhouse Gas Observing Satellite (GOSAT) satellite and ground-based observations from 2010–2012. Prior fluxes contained two variants of anthropogenic emissions, Emissions Database for Global Atmospheric Research (EDGAR) v4.3.2 and adjusted EDGAR v4.3.2 which were scaled to match the country totals by national reports to the United Nations Framework Convention on Climate Change (UNFCCC), augmented by biomass burning emissions from Global Fire Assimilation System (GFASv1.2) and wetlands Vegetation Integrative Simulator for Trace Gases (VISIT). The ratio of the UNFCCC-adjusted global anthropogenic emissions to EDGAR is 98%. This varies by region: 200% in Russia, 84% in China, and 62% in India. By changing prior emissions from EDGAR to UNFCCC-adjusted values, the optimized total emissions increased from 36.2 to 46 Tg CH4 yr−1 for Russia, 12.8 to 14.3 Tg CH4 yr−1 for temperate South America, and 43.2 to 44.9 Tg CH4 yr−1 for contiguous USA, and the values decrease from 54 to 51.3 Tg CH4 yr−1 for China, 26.2 to 25.5 Tg CH4 yr−1 for Europe, and by 12.4 Tg CH4 yr−1 for India. The use of the national report to scale EDGAR emissions allows more detailed statistical data and country-specific emission factors to be gathered in place compared to those available for EDGAR inventory. This serves policy needs by evaluating the national or regional emission totals reported to the UNFCCC.
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Levin, Ingeborg, Ute Karstens, Samuel Hammer, Julian DellaColetta, Fabian Maier, and Maksym Gachkivskyi. "Limitations of the radon tracer method (RTM) to estimate regional greenhouse gas (GHG) emissions – a case study for methane in Heidelberg." Atmospheric Chemistry and Physics 21, no. 23 (December 7, 2021): 17907–26. http://dx.doi.org/10.5194/acp-21-17907-2021.
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Abstract. Correlations of nighttime atmospheric methane (CH4) and 222radon (222Rn) observations in Heidelberg, Germany, were evaluated with the radon tracer method (RTM) to estimate the trend of annual nocturnal CH4 emissions from 1996–2020 in the footprint of the station. After an initial 30 % decrease in emissions from 1996 to 2004, there was no further systematic trend but small inter-annual variations were observed thereafter. This is in accordance with the trend of total emissions until 2010 reported by the EDGARv6.0 inventory for the surroundings of Heidelberg and provides a fully independent top-down verification of the bottom-up inventory changes. We show that the reliability of total nocturnal CH4 emission estimates with the RTM critically depends on the accuracy and representativeness of the 222Rn exhalation rates estimated from soils in the footprint of the site. Simply using 222Rn fluxes as estimated by Karstens et al. (2015) could lead to biases in the estimated greenhouse gas (GHG) fluxes as large as a factor of 2. RTM-based GHG flux estimates also depend on the parameters chosen for the nighttime correlations of CH4 and 222Rn, such as the nighttime period for regressions and the R2 cut-off value for the goodness of the fit. Quantitative comparison of total RTM-based top-down flux estimates with bottom-up emission inventories requires representative high-resolution footprint modelling, particularly in polluted areas where CH4 emissions show large heterogeneity. Even then, RTM-based estimates are likely biased low if point sources play a significant role in the station footprint as their emissions may not be fully captured by the RTM method, for example, if stack emissions are injected above the top of the nocturnal inversion layer or if point-source emissions from the surface are not well mixed into the footprint of the measurement site. Long-term representative 222Rn flux observations in the footprint of a station are indispensable in order to apply the RTM method for reliable quantitative flux estimations of GHG emissions from atmospheric observations.
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Custódio, Danilo, Carlos Borrego, and Hélder Relvas. "Worldwide Evaluation of CAMS-EGG4 CO2 Data Re-Analysis at the Surface Level." Toxics 10, no. 6 (June 17, 2022): 331. http://dx.doi.org/10.3390/toxics10060331.
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This study systematically examines the global uncertainties and biases in the carbon dioxide (CO2) mixing ratio provided by the Copernicus Atmosphere Monitoring Service (CAMS). The global greenhouse gas re-analysis (EGG4) data product from the European Centre for Medium-Range Weather Forecasts (ECMWF) was evaluated against ground-based in situ measurements from more than 160 of stations across the world. The evaluation shows that CO2 re-analysis can capture the general features in the tracer distributions, including the CO2 seasonal cycle and its strength at different latitudes, as well as the global CO2 trend. The emissions and natural fluxes of CO2 at the surface are evaluated on a wide range of scales, from diurnal to interannual. The results highlight re-analysis compliance, reproducing biogenic fluxes as well the observed CO2 patterns in remote environments. CAMS consistently reproduces observations at marine and remote regions with low CO2 fluxes and smooth variability. However, the model’s weaknesses were observed in continental areas, regions with complex sources, transport circulations and large CO2 fluxes. A strong variation in the accuracy and bias are displayed among those stations with different flux profiles, with the largest uncertainties in the continental regions with high CO2 anthropogenic fluxes. Displaying biased estimation and root-mean-square error (RMSE) ranging from values below one ppmv up to 70 ppmv, the results reveal a poor response from re-analysis to high CO2 mixing ratio, showing larger uncertainty of the product in the boundaries where the CAMS system misses solving sharp flux variability. The mismatch at regions with high fluxes of anthropogenic emission indicate large uncertainties in inventories and constrained physical parameterizations in the CO2 at boundary conditions. The current study provides a broad uncertainty assessment for the CAMS CO2 product worldwide, suggesting deficiencies and methods that can be used in the future to overcome failures and uncertainties in regional CO2 mixing ratio and flux estimates.
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Grainger, Alan, and Junwoo Kim. "Reducing Global Environmental Uncertainties in Reports of Tropical Forest Carbon Fluxes to REDD+ and the Paris Agreement Global Stocktake." Remote Sensing 12, no. 15 (July 23, 2020): 2369. http://dx.doi.org/10.3390/rs12152369.
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The magnitude of net carbon dioxide emissions resulting from global forest carbon change, and hence the contribution of forests to global climate change, is highly uncertain, owing to the lack of direct measurement by Earth observation and ground data collection. This paper uses a new method to evaluate this uncertainty with greater precision than before. Sources of uncertainty are divided into conceptualization and measurement categories and distributed between the spatial, vertical and temporal dimensions of Earth observation. The method is applied to Forest Reference Emission Level (FREL) reports and National Greenhouse Gas Inventories (NGGIs) submitted to the UN Framework Convention on Climate Change (UNFCCC) by 12 countries containing half of tropical forest area. The two sets of estimates are typical of those to be submitted to the Reducing Emissions from Deforestation and Degradation (REDD+) mechanism of the UNFCCC and the 2023 Global Stocktake of its Paris Agreement, respectively. Assembling the Uncertainty Fingerprint of each estimate shows that Uncertainty Scores are between 10 and 14 for the NGGIs and 5 and 10 for the FREL reports, and so both exceed the threshold of 2 when it is advisable to evaluate uncertainty by standard statistical methods. Conceptualization uncertainties account for 60% of all uncertainties in the NGGIs and 47% in the FREL reports, e.g., there is incomplete coverage of forest carbon fluxes, and limited disaggregation of fluxes between different ecosystem types and forest carbon pools. Of the measurement uncertainties, all FREL reports base forest area estimates on at least medium resolution satellite data, compared with only 3 NGGIs; after REDD+ Readiness schemes, mean area mapping frequency has fallen to 2.3 years in Latin America and 3.0 years in Asia, but only 8.3 years in Africa; and carbon density estimates are based on national forest inventory data in all FREL reports but only 4 NGGIs. The effectiveness of the Global Stocktake and REDD+ monitoring will therefore be constrained by considerable uncertainties, and to reduce these requires a new phase of REDD+ Readiness to ensure more frequent national forest inventories and forest carbon mapping.
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Pongratz, Julia, Clemens Schwingshackl, Selma Bultan, Wolfgang Obermeier, Felix Havermann, and Suqi Guo. "Land Use Effects on Climate: Current State, Recent Progress, and Emerging Topics." Current Climate Change Reports 7, no. 4 (December 2021): 99–120. http://dx.doi.org/10.1007/s40641-021-00178-y.
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Abstract Purpose of Review As demand for food and fiber, but also for negative emissions, brings most of the Earth’s land surface under management, we aim to consolidate the scientific progress of recent years on the climatic effects of global land use change, including land management, and related land cover changes (LULCC). Recent Findings We review the methodological advances in both modeling and observations to capture biogeochemical and biogeophysical LULCC effects and summarize the knowledge on underlying mechanisms and on the strength of their effects. Recent studies have raised or resolved several important questions related to LULCC: How can we derive CO2 fluxes related to LULCC from satellites? Why are uncertainties in LULCC-related GHG fluxes so large? How can we explain that estimates of afforestation/reforestation potentials diverge by an order of magnitude? Can we reconcile the seemingly contradicting results of models and observations concerning the cooling effect of high-latitude deforestation? Summary Major progress has been achieved in understanding the complementarity of modeling, observations, and inventories for estimating the impacts of various LULCC practices on carbon, energy, and water fluxes. Emerging fields are the operationalization of the recently achieved integration of approaches, such as a full greenhouse gas balance of LULCC, mapping of emissions from global models to country-reported emissions data, or model evaluation against local biogeophysical observations. Fundamental challenges remain, however, e.g., in separating anthropogenic from natural land use dynamics and accurately quantifying the first. Recent progress has laid the foundation for future research to integrate the local to global scales at which the various effects act, to create co-benefits between global mitigation, including land-based carbon dioxide removal, and changes in local climate for effective adaptation strategies.
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Jauhiainen, Jyrki, Jukka Alm, Brynhildur Bjarnadottir, Ingeborg Callesen, Jesper R. Christiansen, Nicholas Clarke, Lise Dalsgaard, et al. "Reviews and syntheses: Greenhouse gas exchange data from drained organic forest soils – a review of current approaches and recommendations for future research." Biogeosciences 16, no. 23 (December 10, 2019): 4687–703. http://dx.doi.org/10.5194/bg-16-4687-2019.
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Abstract. Drained organic forest soils in boreal and temperate climate zones are believed to be significant sources of the greenhouse gases (GHGs) carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), but the annual fluxes are still highly uncertain. Drained organic soils exemplify systems where many studies are still carried out with relatively small resources, several methodologies and manually operated systems, which further involve different options for the detailed design of the measurement and data analysis protocols for deriving the annual flux. It would be beneficial to set certain guidelines for how to measure and report the data, so that data from individual studies could also be used in synthesis work based on data collation and modelling. Such synthesis work is necessary for deciphering general patterns and trends related to, e.g., site types, climate, and management, and the development of corresponding emission factors, i.e. estimates of the net annual soil GHG emission and removal, which can be used in GHG inventories. Development of specific emission factors also sets prerequisites for the background or environmental data to be reported in individual studies. We argue that wide applicability greatly increases the value of individual studies. An overall objective of this paper is to support future monitoring campaigns in obtaining high-value data. We analysed peer-reviewed publications presenting CO2, CH4 and N2O flux data for drained organic forest soils in boreal and temperate climate zones, focusing on data that have been used, or have the potential to be used, for estimating net annual soil GHG emissions and removals. We evaluated the methods used in data collection and identified major gaps in background or environmental data. Based on these, we formulated recommendations for future research.
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Tallec, T., K. Klumpp, A. Hensen, Y. Rochette, and J. F. Soussana. "Methane emission measurements in a cattle grazed pasture: a comparison of four methods." Biogeosciences Discussions 9, no. 10 (October 17, 2012): 14407–36. http://dx.doi.org/10.5194/bgd-9-14407-2012.
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Abstract. Methane (CH4) is considered to be the second main contributor to the global greenhouse gas effect, with major CH4 emissions originating from livestock. Accurate measurements from ruminating herds are required to improve emission coefficients used in national emission inventories, and to evaluate mitigation strategies. Previous measurements of enteric methane emissions from domestic animals have been carried out in artificial conditions such as laboratory chambers, or by fitting individual animals with capillary tubes and using SF6 as a tracer. Here we evaluated the reliability of eddy covariance technique (EC), already used for CO2 fluxes, for continuous CH4 measurements over a grazed field plot. Analyzer accuracy and reliability of eddy covariance technique were tested against field scale measurements with the SF6 tracer technique, Gaussian plume model and emission factors (i.e. IPCC). Results indicate a better agreement between EC and SF6 method when grazing heifers were parked close to the EC setup. However, a systematic underestimation of EC data appeared and even more when the distance between the source (ruminating heifers) and EC setup (mast) was increased. A two-dimensional footprint density function allowed to correct for the dilution effect on measured CH4 and led to a good agreement with results based on the SF6 technique (on average 231 and 252 g CH4 ha−1 over the grazing experiment, respectively). Estimations of the CH4 budgets for the whole grazing season were in line with estimates (i.e. emission factor coefficients) based on feed intake and animal live weight as well as SF6 technique. IPCC method Tier 2, however, led to an overestimation of CH4 fluxes on our site.
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Lemarpe, Shaankua E., Collins M. Musafiri, Joseph M. Macharia, Milka N. Kiboi, Onesmus K. Ng’etich, Chris A. Shisanya, Jeremiah Okeyo, Elizabeth A. Okwuosa, and Felix K. Ngetich. "Nitrous Oxide Emissions from Smallholders’ Cropping Systems in Sub-Saharan Africa." Advances in Agriculture 2021 (November 1, 2021): 1–13. http://dx.doi.org/10.1155/2021/4800527.
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Increased concentration of atmospheric nitrous oxide (N2O), a potent greenhouse gas (GHG), is of great concern due to its impact on ozone layer depletion leading to climate change. Ozone layer depletion allows penetration of ultraviolet radiations, which are hazardous to human health. Climate change culminates in reduced food productivity. Limited empirical studies have been conducted in Sub-Saharan Africa (SSA) to quantify and understand the dynamics of soil N2O fluxes from smallholder cropping systems. The available literature on soil N2O fluxes in SSA is limited; hence, there is a pressing need to consolidate it to ease mitigation targeting and policy formulation initiatives. We reviewed the state of N2O emissions from selected cropping systems, drivers that significantly influence N2O emissions, and probable soil N2O emissions mitigation options from 30 studies in SSA cropping systems have been elucidated here. The review outcome indicates that coffee, tea, maize, and vegetables emit N2O ranging from 1 to 1.9, 0.4 to 3.9, 0.1 to 4.26, and 48 to 113.4 kg N2O-N ha-1 yr−1, respectively. The yield-scaled and N2O emissions factors ranged between 0.08 and 67 g N2O-N kg−1 and 0.01 and 4.1%, respectively, across cropping systems. Soil characteristics, farm management practices, and climatic and environmental conditions were significant drivers influencing N2O emissions across SSA cropping systems. We found that site-specific soil N2O emissions mitigation measures are required due to high variations in N2O drivers across SSA. We conclude that appropriate fertilizer and organic input management combined with improved soil management practices are potential approaches in N2O emissions mitigation in SSA. We recommend that (i) while formulating soil N2O emissions mitigation approaches, in SSA, policymakers should consider site-specific targeting approaches, and (ii) more empirical studies need to be conducted in diverse agroecological zones of SSA to qualify various mitigation options on N2O emissions, yield-scaled N2O emissions, and N2O emission factors which are essential in improving national and regional GHG inventories.
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Lehtonen, Aleksi, Tapio Linkosalo, Mikko Peltoniemi, Risto Sievänen, Raisa Mäkipää, Pekka Tamminen, Maija Salemaa, et al. "Forest soil carbon stock estimates in a nationwide inventory: evaluating performance of the ROMULv and Yasso07 models in Finland." Geoscientific Model Development 9, no. 11 (November 22, 2016): 4169–83. http://dx.doi.org/10.5194/gmd-9-4169-2016.
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Abstract. Dynamic soil models are needed for estimating impact of weather and climate change on soil carbon stocks and fluxes. Here, we evaluate performance of Yasso07 and ROMULv models against forest soil carbon stock measurements. More specifically, we ask if litter quantity, litter quality and weather data are sufficient drivers for soil carbon stock estimation. We also test whether inclusion of soil water holding capacity improves reliability of modelled soil carbon stock estimates. Litter input of trees was estimated from stem volume maps provided by the National Forest Inventory, while understorey vegetation was estimated using new biomass models. The litter production rates of trees were based on earlier research, while for understorey biomass they were estimated from measured data. We applied Yasso07 and ROMULv models across Finland and ran those models into steady state; thereafter, measured soil carbon stocks were compared with model estimates. We found that the role of understorey litter input was underestimated when the Yasso07 model was parameterised, especially in northern Finland. We also found that the inclusion of soil water holding capacity in the ROMULv model improved predictions, especially in southern Finland. Our simulations and measurements show that models using only litter quality, litter quantity and weather data underestimate soil carbon stock in southern Finland, and this underestimation is due to omission of the impact of droughts to the decomposition of organic layers. Our results also imply that the ecosystem modelling community and greenhouse gas inventories should improve understorey litter estimation in the northern latitudes.
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Basu, Sourish, Scott J. Lehman, John B. Miller, Arlyn E. Andrews, Colm Sweeney, Kevin R. Gurney, Xiaomei Xu, John Southon, and Pieter P. Tans. "Estimating US fossil fuel CO2emissions from measurements of14C in atmospheric CO2." Proceedings of the National Academy of Sciences 117, no. 24 (June 1, 2020): 13300–13307. http://dx.doi.org/10.1073/pnas.1919032117.
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We report national scale estimates of CO2emissions from fossil-fuel combustion and cement production in the United States based directly on atmospheric observations, using a dual-tracer inverse modeling framework and CO2andΔ14CO2measurements obtained primarily from the North American portion of the National Oceanic and Atmospheric Administration’s Global Greenhouse Gas Reference Network. The derived US national total for 2010 is 1,653 ± 30 TgC yr−1with an uncertainty (1σ) that takes into account random errors associated with atmospheric transport, atmospheric measurements, and specified prior CO2and14C fluxes. The atmosphere-derived estimate is significantly larger (>3σ) than US national emissions for 2010 from three global inventories widely used for CO2accounting, even after adjustments for emissions that might be sensed by the atmospheric network, but which are not included in inventory totals. It is also larger (>2σ) than a similarly adjusted total from the US Environmental Protection Agency (EPA), but overlaps EPA’s reported upper 95% confidence limit. In contrast, the atmosphere-derived estimate is within1σof the adjusted 2010 annual total and nine of 12 adjusted monthly totals aggregated from the latest version of the high-resolution, US-specific “Vulcan” emission data product. Derived emissions appear to be robust to a range of assumed prior emissions and other parameters of the inversion framework. While we cannot rule out a possible bias from assumed prior Net Ecosystem Exchange over North America, we show that this can be overcome with additionalΔ14CO2measurements. These results indicate the strong potential for quantification of US emissions and their multiyear trends from atmospheric observations.
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Dietrich, Florian, Jia Chen, Benno Voggenreiter, Patrick Aigner, Nico Nachtigall, and Björn Reger. "MUCCnet: Munich Urban Carbon Column network." Atmospheric Measurement Techniques 14, no. 2 (February 11, 2021): 1111–26. http://dx.doi.org/10.5194/amt-14-1111-2021.
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Abstract. In order to mitigate climate change, it is crucial to understand urban greenhouse gas (GHG) emissions precisely, as more than two-thirds of the anthropogenic GHG emissions worldwide originate from cities. Nowadays, urban emission estimates are mainly based on bottom-up calculation approaches with high uncertainties. A reliable and long-term top-down measurement approach could reduce the uncertainty of these emission inventories significantly. We present the Munich Urban Carbon Column network (MUCCnet), the world's first urban sensor network, which has been permanently measuring GHGs, based on the principle of differential column measurements (DCMs), since summer 2019. These column measurements and column concentration differences are relatively insensitive to vertical redistribution of tracer masses and surface fluxes upwind of the city, making them a favorable input for an inversion framework and, therefore, a well-suited candidate for the quantification of GHG emissions. However, setting up such a stationary sensor network requires an automated measurement principle. We developed our own fully automated enclosure systems for measuring column-averaged CO2, CH4 and CO concentrations with a solar-tracking Fourier transform spectrometer (EM27/SUN) in a fully automated and long-term manner. This also includes software that starts and stops the measurements autonomously and can be used independently from the enclosure system. Furthermore, we demonstrate the novel applications of such a sensor network by presenting the measurement results of our five sensor systems that are deployed in and around Munich. These results include the seasonal cycle of CO2 since 2015, as well as concentration gradients between sites upwind and downwind of the city. Thanks to the automation, we were also able to continue taking measurements during the COVID-19 lockdown in spring 2020. By correlating the CO2 column concentration gradients to the traffic amount, we demonstrate that our network is capable of detecting variations in urban emissions. The measurements from our unique sensor network will be combined with an inverse modeling framework that we are currently developing in order to monitor urban GHG emissions over years, identify unknown emission sources and assess how effective the current mitigation strategies are. In summary, our achievements in automating column measurements of GHGs will allow researchers all over the world to establish this approach for long-term greenhouse gas monitoring in urban areas.
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Groot Zwaaftink, Christine D., Stephan Henne, Rona L. Thompson, Edward J. Dlugokencky, Toshinobu Machida, Jean-Daniel Paris, Motoki Sasakawa, Arjo Segers, Colm Sweeney, and Andreas Stohl. "Three-dimensional methane distribution simulated with FLEXPART 8-CTM-1.1 constrained with observation data." Geoscientific Model Development 11, no. 11 (November 8, 2018): 4469–87. http://dx.doi.org/10.5194/gmd-11-4469-2018.
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Abstract. A Lagrangian particle dispersion model, the FLEXible PARTicle dispersion chemical transport model (FLEXPART CTM), is used to simulate global three-dimensional fields of trace gas abundance. These fields are constrained with surface observation data through nudging, a data assimilation method, which relaxes model fields to observed values. Such fields are of interest to a variety of applications, such as inverse modelling, satellite retrievals, radiative forcing models and estimating global growth rates of greenhouse gases. Here, we apply this method to methane using 6 million model particles filling the global model domain. For each particle, methane mass tendencies due to emissions (based on several inventories) and loss by reaction with OH, Cl and O(1D), as well as observation data nudging were calculated. Model particles were transported by mean, turbulent and convective transport driven by 1∘×1∘ ERA-Interim meteorology. Nudging is applied at 79 surface stations, which are mostly included in the World Data Centre for Greenhouse Gases (WDCGG) database or the Japan–Russia Siberian Tall Tower Inland Observation Network (JR-STATION) in Siberia. For simulations of 1 year (2013), we perform a sensitivity analysis to show how nudging settings affect modelled concentration fields. These are evaluated with a set of independent surface observations and with vertical profiles in North America from the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL), and in Siberia from the Airborne Extensive Regional Observations in SIBeria (YAK-AEROSIB) and the National Institute for Environmental Studies (NIES). FLEXPART CTM results are also compared to simulations from the global Eulerian chemistry Transport Model version 5 (TM5) based on optimized fluxes. Results show that nudging strongly improves modelled methane near the surface, not only at the nudging locations but also at independent stations. Mean bias at all surface locations could be reduced from over 20 to less than 5 ppb through nudging. Near the surface, FLEXPART CTM, including nudging, appears better able to capture methane molar mixing ratios than TM5 with optimized fluxes, based on a larger bias of over 13 ppb in TM5 simulations. The vertical profiles indicate that nudging affects model methane at high altitudes, yet leads to little improvement in the model results there. Averaged from 19 aircraft profile locations in North America and Siberia, root mean square error (RMSE) changes only from 16.3 to 15.7 ppb through nudging, while the mean absolute bias increases from 5.3 to 8.2 ppb. The performance for vertical profiles is thereby similar to TM5 simulations based on TM5 optimized fluxes where we found a bias of 5 ppb and RMSE of 15.9 ppb. With this rather simple model setup, we thus provide three-dimensional methane fields suitable for use as boundary conditions in regional inverse modelling as a priori information for satellite retrievals and for more accurate estimation of mean mixing ratios and growth rates. The method is also applicable to other long-lived trace gases.
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Grassi, Giacomo, Giulia Conchedda, Sandro Federici, Raul Abad Viñas, Anu Korosuo, Joana Melo, Simone Rossi, et al. "Carbon fluxes from land 2000–2020: bringing clarity to countries' reporting." Earth System Science Data 14, no. 10 (October 20, 2022): 4643–66. http://dx.doi.org/10.5194/essd-14-4643-2022.
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Abstract. Despite an increasing attention on the role of land in meeting countries' climate pledges under the Paris Agreement, the range of estimates of carbon fluxes from land use, land-use change, and forestry (LULUCF) in available databases is very large. A good understanding of the LULUCF data reported by countries under the United Nations Framework Convention on Climate Change (UNFCCC) – and of the differences with other datasets based on country-reported data – is crucial to increase confidence in land-based climate change mitigation efforts. Here we present a new data compilation of LULUCF fluxes of carbon dioxide (CO2) on managed land, aiming at providing a consolidated view on the subject. Our database builds on a detailed analysis of data from national greenhouse gas inventories (NGHGIs) communicated via a range of country reports to the UNFCCC, which report anthropogenic emissions and removals based on the IPCC (Intergovernmental Panel on Climate Change) methodology. Specifically, for Annex I countries, data are sourced from annual GHG inventories. For non-Annex I countries, we compiled the most recent and complete information from different sources, including national communications, biennial update reports, submissions to the REDD+ (reducing emissions from deforestation and forest degradation) framework, and nationally determined contributions. The data are disaggregated into fluxes from forest land, deforestation, organic soils, and other sources (including non-forest land uses). The CO2 flux database is complemented by information on managed and unmanaged forest area as available in NGHGIs. To ensure completeness of time series, we filled the gaps without altering the levels and trends of the country reported data. Expert judgement was applied in a few cases when data inconsistencies existed. Results indicate a mean net global sink of −1.6 Gt CO2 yr−1 over the period 2000–2020, largely determined by a sink on forest land (−6.4 Gt CO2 yr−1), followed by source from deforestation (+4.4 Gt CO2 yr−1), with smaller fluxes from organic soils (+0.9 Gt CO2 yr−1) and other land uses (−0.6 Gt CO2 yr−1). Furthermore, we compare our NGHGI database with two other sets of country-based data: those included in the UNFCCC GHG data interface, and those based on forest resources data reported by countries to the Food and Agriculture Organization of the United Nations (FAO) and used as inputs into estimates of GHG emissions in FAOSTAT. The first dataset, once gap filled as in our study, results in a net global LULUCF sink of −5.4 Gt CO2 yr−1. The difference with the NGHGI database is in this case mostly explained by more updated and comprehensive data in our compilation for non-Annex I countries. The FAOSTAT GHG dataset instead estimates a net global LULUCF source of +1.1 Gt CO2 yr−1. In this case, most of the difference to our results is due to a much greater forest sink for non-Annex I countries in the NGHGI database than in FAOSTAT. The difference between these datasets can be mostly explained by a more complete coverage in the NGHGI database, including for non-biomass carbon pools and non-forest land uses, and by different underlying data on forest land. The latter reflects the different scopes of the country reporting to FAO, which focuses on area and biomass, and to UNFCCC, which explicitly focuses on carbon fluxes. Bearing in mind the respective strengths and weaknesses, both our NGHGI database and FAO offer a fundamental, yet incomplete, source of information on carbon-related variables for the scientific and policy communities, including under the Global stocktake. Overall, while the quality and quantity of the LULUCF data submitted by countries to the UNFCCC significantly improved in recent years, important gaps still remain. Most developing countries still do not explicitly separate managed vs. unmanaged forest land, a few report implausibly high forest sinks, and several report incomplete estimates. With these limits in mind, the NGHGI database presented here represents the most up-to-date and complete compilation of LULUCF data based on country submissions to UNFCCC. Data from this study are openly available via the Zenodo portal (Grassi et al., 2022), at https://doi.org/10.5281/zenodo.7190601.
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Chandra, Naveen, Shyam Lal, S. Venkataramani, Prabir K. Patra, and Varun Sheel. "Temporal variations of atmospheric CO<sub>2</sub> and CO at Ahmedabad in western India." Atmospheric Chemistry and Physics 16, no. 10 (May 20, 2016): 6153–73. http://dx.doi.org/10.5194/acp-16-6153-2016.
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Abstract. About 70 % of the anthropogenic carbon dioxide (CO2) is emitted from the megacities and urban areas of the world. In order to draw effective emission mitigation policies for combating future climate change as well as independently validating the emission inventories for constraining their large range of uncertainties, especially over major metropolitan areas of developing countries, there is an urgent need for greenhouse gas measurements over representative urban regions. India is a fast developing country, where fossil fuel emissions have increased dramatically in the last three decades and are predicted to continue to grow further by at least 6 % per year through to 2025. The CO2 measurements over urban regions in India are lacking. To overcome this limitation, simultaneous measurements of CO2 and carbon monoxide (CO) have been made at Ahmedabad, a major urban site in western India, using a state-of-the-art laser-based cavity ring down spectroscopy technique from November 2013 to May 2015. These measurements enable us to understand the diurnal and seasonal variations in atmospheric CO2 with respect to its sources (both anthropogenic and biospheric) and biospheric sinks. The observed annual average concentrations of CO2 and CO are 413.0 ± 13.7 and 0.50 ± 0.37 ppm respectively. Both CO2 and CO show strong seasonality with lower concentrations (400.3 ± 6.8 and 0.19 ± 0.13 ppm) during the south-west monsoon and higher concentrations (419.6 ± 22.8 and 0.72 ± 0.68 ppm) during the autumn (SON) season. Strong diurnal variations are also observed for both the species. The common factors for the diurnal cycles of CO2 and CO are vertical mixing and rush hour traffic, while the influence of biospheric fluxes is also seen in the CO2 diurnal cycle. Using CO and CO2 covariation, we differentiate the anthropogenic and biospheric components of CO2 and found significant contributions of biospheric respiration and anthropogenic emissions in the late night (00:00–05:00 h, IST) and evening rush hours (18:00–22:00 h) respectively. We compute total yearly emissions of CO to be 69.2 ± 0.07 Gg for the study region using the observed CO : CO2 correlation slope and bottom-up CO2 emission inventory. This calculated emission of CO is 52 % larger than the estimated emission of CO by the emissions database for global atmospheric research (EDGAR) inventory. The observations of CO2 have been compared with an atmospheric chemistry-transport model (ACTM), which incorporates various components of CO2 fluxes. ACTM is able to capture the basic variabilities, but both diurnal and seasonal amplitudes are largely underestimated compared to the observations. We attribute this underestimation by the model to uncertainties in terrestrial biosphere fluxes and coarse model resolution. The fossil fuel signal from the model shows fairly good correlation with observed CO2 variations, which supports the overall dominance of fossil fuel emissions over the biospheric fluxes in this urban region.
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Pillai, Dhanyalekshmi, Michael Buchwitz, Christoph Gerbig, Thomas Koch, Maximilian Reuter, Heinrich Bovensmann, Julia Marshall, and John P. Burrows. "Tracking city CO<sub>2</sub> emissions from space using a high-resolution inverse modelling approach: a case study for Berlin, Germany." Atmospheric Chemistry and Physics 16, no. 15 (August 2, 2016): 9591–610. http://dx.doi.org/10.5194/acp-16-9591-2016.
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Abstract. Currently, 52 % of the world's population resides in urban areas and as a consequence, approximately 70 % of fossil fuel emissions of CO2 arise from cities. This fact, in combination with large uncertainties associated with quantifying urban emissions due to lack of appropriate measurements, makes it crucial to obtain new measurements useful to identify and quantify urban emissions. This is required, for example, for the assessment of emission mitigation strategies and their effectiveness. Here, we investigate the potential of a satellite mission like Carbon Monitoring Satellite (CarbonSat) which was proposed to the European Space Agency (ESA) to retrieve the city emissions globally, taking into account a realistic description of the expected retrieval errors, the spatiotemporal distribution of CO2 fluxes, and atmospheric transport. To achieve this, we use (i) a high-resolution modelling framework consisting of the Weather Research Forecasting model with a greenhouse gas module (WRF-GHG), which is used to simulate the atmospheric observations of column-averaged CO2 dry air mole fractions (XCO2), and (ii) a Bayesian inversion method to derive anthropogenic CO2 emissions and their errors from the CarbonSat XCO2 observations. We focus our analysis on Berlin, Germany using CarbonSat's cloud-free overpasses for 1 reference year. The dense (wide swath) CarbonSat simulated observations with high spatial resolution (approximately 2 km × 2 km) permits one to map the city CO2 emission plume with a peak enhancement of typically 0.8–1.35 ppm relative to the background. By performing a Bayesian inversion, it is shown that the random error (RE) of the retrieved Berlin CO2 emission for a single overpass is typically less than 8–10 Mt CO2 yr−1 (about 15–20 % of the total city emission). The range of systematic errors (SEs) of the retrieved fluxes due to various sources of error (measurement, modelling, and inventories) is also quantified. Depending on the assumptions made, the SE is less than about 6–10 Mt CO2 yr−1 for most cases. We find that in particular systematic modelling-related errors can be quite high during the summer months due to substantial XCO2 variations caused by biogenic CO2 fluxes at and around the target region. When making the extreme worst-case assumption that biospheric XCO2 variations cannot be modelled at all (which is overly pessimistic), the SE of the retrieved emission is found to be larger than 10 Mt CO2 yr−1 for about half of the sufficiently cloud-free overpasses, and for some of the overpasses we found that SE may even be on the order of magnitude of the anthropogenic emission. This indicates that biogenic XCO2 variations cannot be neglected but must be considered during forward and/or inverse modelling. Overall, we conclude that a satellite mission such as CarbonSat has high potential to obtain city-scale CO2 emissions as needed to enhance our current understanding of anthropogenic carbon fluxes, and that CarbonSat-like satellites should be an important component of a future global carbon emission monitoring system.
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Voglmeier, Karl, Johan Six, Markus Jocher, and Christof Ammann. "Grazing-related nitrous oxide emissions: from patch scale to field scale." Biogeosciences 16, no. 8 (April 25, 2019): 1685–703. http://dx.doi.org/10.5194/bg-16-1685-2019.
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Abstract. Grazed pastures are strong sources of the greenhouse gas nitrous oxide (N2O). The quantification of N2O emissions is challenging due to the strong spatial and temporal variabilities of the emission sources and so N2O emission estimates are very uncertain. This study presents N2O emission measurements from two grazing systems in western Switzerland over the grazing season of 2016. The 12 dairy cows of each herd were kept in an intensive rotational grazing management. The diet for the two herds of cows consisted of different protein-to-energy ratios (system G: grass only diet; system M: grass with additional maize silage) resulting in different nitrogen (N) excretion rates. The N in the excretion was estimated by calculating the animal nitrogen budget taking into account the measurements of feed intake, milk yield, and body weight of the cow herds. Directly after the rotational grazing phases, background and urine patches were identified based on soil electric conductivity measurements while fresh dung patches were identified visually. The magnitude and temporal pattern of these different emission sources were measured with a fast-box (FB) chamber and the field-scale fluxes were quantified using two eddy covariance (EC) systems. The FB measurements were finally upscaled to the field level and compared to the EC measurements for quality control by using EC footprint estimates of a backward Lagrangian stochastic dispersion model. The comparison between the two grazing systems was performed during emission periods that were not influenced by fertilizer applications. This allowed the calculation of the excreta-related N2O emissions per cow and grazing hour and resulted in considerably higher emissions for system G compared to system M. Relating the found emissions to the excreta N resulted in excreta-related emission factors (EFs) of 0.74±0.26 % for system M and 0.83±0.29 % for system G. These EF values were thus significantly smaller compared to the default EF of 2 % provided by the IPCC guidelines for cattle excreta deposited on pasture. The measurements showed that urine patch emission dominated the field-scale fluxes (57 %), followed by significant background emissions (38 %), and only a small contribution of dung patch emission (5 %). The resulting source-specific EFs exhibited a clear difference between urine (1.12±0.43 %) and dung (0.16±0.06 %), supporting a disaggregation of the grazing-related EFs by excreta type in emission inventories. The study also highlights the advantage of a N-optimized diet, which resulted in reduced N2O emissions from animal excreta.
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Teh, Yit Arn, Wayne A. Murphy, Juan-Carlos Berrio, Arnoud Boom, and Susan E. Page. "Seasonal variability in methane and nitrous oxide fluxes from tropical peatlands in the western Amazon basin." Biogeosciences 14, no. 15 (August 7, 2017): 3669–83. http://dx.doi.org/10.5194/bg-14-3669-2017.
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Abstract. The Amazon plays a critical role in global atmospheric budgets of methane (CH4) and nitrous oxide (N2O). However, while we have a relatively good understanding of the continental-scale flux of these greenhouse gases (GHGs), one of the key gaps in knowledge is the specific contribution of peatland ecosystems to the regional budgets of these GHGs. Here we report CH4 and N2O fluxes from lowland tropical peatlands in the Pastaza–Marañón foreland basin (PMFB) in Peru, one of the largest peatland complexes in the Amazon basin. The goal of this research was to quantify the range and magnitude of CH4 and N2O fluxes from this region, assess seasonal trends in trace gas exchange, and determine the role of different environmental variables in driving GHG flux. Trace gas fluxes were determined from the most numerically dominant peatland vegetation types in the region: forested vegetation, forested (short pole) vegetation, Mauritia flexuosa-dominated palm swamp, and mixed palm swamp. Data were collected in both wet and dry seasons over the course of four field campaigns from 2012 to 2014. Diffusive CH4 emissions averaged 36.05 ± 3.09 mg CH4–C m−2 day−1 across the entire dataset, with diffusive CH4 flux varying significantly among vegetation types and between seasons. Net ebullition of CH4 averaged 973.3 ± 161.4 mg CH4–C m−2 day−1 and did not vary significantly among vegetation types or between seasons. Diffusive CH4 flux was greatest for mixed palm swamp (52.0 ± 16.0 mg CH4–C m−2 day−1), followed by M. flexuosa palm swamp (36.7 ± 3.9 mg CH4–C m−2 day−1), forested (short pole) vegetation (31.6 ± 6.6 mg CH4–C m−2 day−1), and forested vegetation (29.8 ± 10.0 mg CH4–C m−2 day−1). Diffusive CH4 flux also showed marked seasonality, with divergent seasonal patterns among ecosystems. Forested vegetation and mixed palm swamp showed significantly higher dry season (47.2 ± 5.4 mg CH4–C m−2 day−1 and 85.5 ± 26.4 mg CH4–C m−2 day−1, respectively) compared to wet season emissions (6.8 ± 1.0 mg CH4–C m−2 day−1 and 5.2 ± 2.7 mg CH4–C m−2 day−1, respectively). In contrast, forested (short pole) vegetation and M. flexuosa palm swamp showed the opposite trend, with dry season flux of 9.6 ± 2.6 and 25.5 ± 2.9 mg CH4–C m−2 day−1, respectively, versus wet season flux of 103.4 ± 13.6 and 53.4 ± 9.8 mg CH4–C m−2 day−1, respectively. These divergent seasonal trends may be linked to very high water tables (> 1 m) in forested vegetation and mixed palm swamp during the wet season, which may have constrained CH4 transport across the soil–atmosphere interface. Diffusive N2O flux was very low (0.70 ± 0.34 µg N2O–N m−2 day−1) and did not vary significantly among ecosystems or between seasons. We conclude that peatlands in the PMFB are large and regionally significant sources of atmospheric CH4 that need to be better accounted for in regional emissions inventories. In contrast, N2O flux was negligible, suggesting that this region does not make a significant contribution to regional atmospheric budgets of N2O. The divergent seasonal pattern in CH4 flux among vegetation types challenges our underlying assumptions of the controls on CH4 flux in tropical peatlands and emphasizes the need for more process-based measurements during periods of high water table.
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Flechard, Chris R., Andreas Ibrom, Ute M. Skiba, Wim de Vries, Marcel van Oijen, David R. Cameron, Nancy B. Dise, et al. "Carbon–nitrogen interactions in European forests and semi-natural vegetation – Part 1: Fluxes and budgets of carbon, nitrogen and greenhouse gases from ecosystem monitoring and modelling." Biogeosciences 17, no. 6 (March 26, 2020): 1583–620. http://dx.doi.org/10.5194/bg-17-1583-2020.
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Abstract. The impact of atmospheric reactive nitrogen (Nr) deposition on carbon (C) sequestration in soils and biomass of unfertilized, natural, semi-natural and forest ecosystems has been much debated. Many previous results of this dC∕dN response were based on changes in carbon stocks from periodical soil and ecosystem inventories, associated with estimates of Nr deposition obtained from large-scale chemical transport models. This study and a companion paper (Flechard et al., 2020) strive to reduce uncertainties of N effects on C sequestration by linking multi-annual gross and net ecosystem productivity estimates from 40 eddy covariance flux towers across Europe to local measurement-based estimates of dry and wet Nr deposition from a dedicated collocated monitoring network. To identify possible ecological drivers and processes affecting the interplay between C and Nr inputs and losses, these data were also combined with in situ flux measurements of NO, N2O and CH4 fluxes; soil NO3- leaching sampling; and results of soil incubation experiments for N and greenhouse gas (GHG) emissions, as well as surveys of available data from online databases and from the literature, together with forest ecosystem (BASFOR) modelling. Multi-year averages of net ecosystem productivity (NEP) in forests ranged from −70 to 826 g C m−2 yr−1 at total wet + dry inorganic Nr deposition rates (Ndep) of 0.3 to 4.3 g N m−2 yr−1 and from −4 to 361 g C m−2 yr−1 at Ndep rates of 0.1 to 3.1 g N m−2 yr−1 in short semi-natural vegetation (moorlands, wetlands and unfertilized extensively managed grasslands). The GHG budgets of the forests were strongly dominated by CO2 exchange, while CH4 and N2O exchange comprised a larger proportion of the GHG balance in short semi-natural vegetation. Uncertainties in elemental budgets were much larger for nitrogen than carbon, especially at sites with elevated Ndep where Nr leaching losses were also very large, and compounded by the lack of reliable data on organic nitrogen and N2 losses by denitrification. Nitrogen losses in the form of NO, N2O and especially NO3- were on average 27 % (range 6 %–54 %) of Ndep at sites with Ndep < 1 g N m−2 yr−1 versus 65 % (range 35 %–85 %) for Ndep > 3 g N m−2 yr−1. Such large levels of Nr loss likely indicate that different stages of N saturation occurred at a number of sites. The joint analysis of the C and N budgets provided further hints that N saturation could be detected in altered patterns of forest growth. Net ecosystem productivity increased with Nr deposition up to 2–2.5 g N m−2 yr−1, with large scatter associated with a wide range in carbon sequestration efficiency (CSE, defined as the NEP ∕ GPP ratio). At elevated Ndep levels (> 2.5 g N m−2 yr−1), where inorganic Nr losses were also increasingly large, NEP levelled off and then decreased. The apparent increase in NEP at low to intermediate Ndep levels was partly the result of geographical cross-correlations between Ndep and climate, indicating that the actual mean dC∕dN response at individual sites was significantly lower than would be suggested by a simple, straightforward regression of NEP vs. Ndep.
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Williams, J. E., P. F. J. van Velthoven, and C. A. M. Brenninkmeijer. "Quantifying the uncertainty in simulating global tropospheric composition due to the variability in global emission estimates of Biogenic Volatile Organic Compounds." Atmospheric Chemistry and Physics Discussions 12, no. 11 (November 5, 2012): 28765–836. http://dx.doi.org/10.5194/acpd-12-28765-2012.
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Abstract. The emission of organic compounds from biogenic processes acts as an important source of trace gases in remote regions away from urban conurbations, and is likely to become more important in future decades due to the further mitigation of anthropogenic emissions that affect air quality and climate forcing. In this study we examine the contribution of biogenic volatile organic compounds (BVOCs) towards global tropospheric composition using the global 3-D chemistry transport model TM5 and the recently developed modified CB05 chemical mechanism. By comparing regional BVOC emission estimates we show that biogenic processes act as dominant sources for many regions and exhibit a large variability in the annually and seasonally integrated emission fluxes. By performing sensitivity studies we find that the contribution of BVOC species containing between 1 to 3 carbon atoms has an impact on the resident mixing ratios of tropospheric O3 and CO, accounting for ~3% and ~11% of the simulated global distribution, respectively. This is approximately a third of the cumulative effect introduced by isoprene and the monoterpenes. By examining an ensemble of 3-D global chemistry-transport simulations which adopt different global BVOC emission inventories we determine the associated uncertainty introduced towards simulating the composition of the troposphere for the year 2000. By comparing the model ensemble values against a~composite of atmospheric measurements we show that the effects on tropospheric O3 are limited to the lower troposphere (with an uncertainty between −2% to 10%), whereas that for tropospheric CO extends up to the upper troposphere (with an uncertainty of between 10 to 45%). Comparing the mixing ratios for low molecular weight alkenes in TM5 against surface measurements taken in Europe implies that the cumulative emission estimates are too low, regardless of the chosen BVOC inventory. This variability in the global distribution of CO due to BVOC emissions introduces an associated uncertainty in the tropospheric CO burden of ~11%, which impacts strongly on the oxidative capacity of the troposphere, introducing an uncertainty in the atmospheric lifetime of the greenhouse gas CH4 of ~3%. This study thus identifies the necessity of placing further constraints on non-CH4 global biogenic emission estimates in large-scale global atmospheric chemistry models.
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Williams, J. E., P. F. J. van Velthoven, and C. A. M. Brenninkmeijer. "Quantifying the uncertainty in simulating global tropospheric composition due to the variability in global emission estimates of Biogenic Volatile Organic Compounds." Atmospheric Chemistry and Physics 13, no. 5 (March 11, 2013): 2857–91. http://dx.doi.org/10.5194/acp-13-2857-2013.
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Abstract. The emission of organic compounds from biogenic processes acts as an important source of trace gases in remote regions away from urban conurbations, and is likely to become more important in future decades due to the further mitigation of anthropogenic emissions that affect air quality and climate forcing. In this study we examine the contribution of biogenic volatile organic compounds (BVOCs) towards global tropospheric composition using the global 3-D chemistry transport model TM5 and the recently developed modified CB05 chemical mechanism. By comparing regional BVOC emission estimates we show that biogenic processes act as dominant sources for many regions and exhibit a large variability in the annually and seasonally integrated emission fluxes. By performing sensitivity studies we find that the contribution of BVOC species containing between 1 to 3 carbon atoms has an impact on the resident mixing ratios of tropospheric O3 and CO, accounting for ~2.5% and ~10.8% of the simulated global distribution, respectively. This is approximately a third of the cumulative effect introduced by isoprene and the monoterpenes. By examining an ensemble of 3-D global chemistry transport simulations which adopt different global BVOC emission inventories we determine the associated uncertainty introduced towards simulating the composition of the troposphere for the year 2000. By comparing the model ensemble values against a composite of atmospheric measurements we show that the effects on tropospheric O3 are limited to the lower troposphere (with an uncertainty between −2% to 10%), whereas that for tropospheric CO extends up to the upper troposphere (with an uncertainty of between 10 to 45%). Comparing the mixing ratios for low molecular weight alkenes in TM5 against surface measurements taken in Europe implies that the cumulative emission estimates are too low, regardless of the chosen BVOC inventory. This variability in the global distribution of CO due to BVOC emissions introduces an associated uncertainty in the tropospheric CO burden of 11.4%, which impacts strongly on the oxidative capacity of the troposphere, introducing an uncertainty in the atmospheric lifetime of the greenhouse gas CH4 of ~3.3%. This study thus identifies the necessity of placing further constraints on non-CH4 global biogenic emission estimates in large-scale global atmospheric chemistry models.
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Officer, Sally Jane, Frances Phillips, Gavin Kearney, Roger Armstrong, John Graham, and Debra Partington. "Response of soil nitrous oxide flux to nitrogen fertiliser application and legume rotation in a semi-arid climate, identified by smoothing spline models." Soil Research 53, no. 3 (2015): 227. http://dx.doi.org/10.1071/sr12049.
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Although large areas of semi-arid land are extensively cropped, few studies have investigated the effect of nitrogen (N) fertiliser on nitrous oxide (N2O) emissions in these regions (Galbally et al. 2010). These emissions need to be measured in order to estimate N losses and calculate national greenhouse gas inventories. We examined the effect of different agronomic management practices applied to wheat (Triticum aestivum) grown on an alkaline Vertosol in south-eastern Australia on N2O emissions. In 2007, N2O emissions were measured over 12 months, during which N fertiliser (urea) was applied at sowing or N fertiliser plus supplementary irrigation (50 mm) was applied during the vegetative stage and compared with a treatment of no N fertiliser or irrigation. In a second experiment (2008), the effect of source of N on N2O emissions was examined. Wheat was grown on plots where either a pulse (field peas, Pisum sativum) or pasture legume (barrel medic, Medicago truncatula) crop had been sown in the previous season compared with a non-legume crop (canola, Brassica napus). To account for the N supplied by the legume phase, N fertiliser (50 kg N ha–1 as urea) was applied only to the wheat in the plots previously sown to canola. Fluxes of N2O were measured on a sub-daily basis (up to 16 measurements per chamber) by using automated chamber enclosures and a tuneable diode laser, and treatment differences were evaluated by a linear mixed model including cubic smoothing splines. Fluxes were low and highly variable, ranging from –3 to 28 ng N2O-N m–2 s–1. The application of N fertiliser at sowing increased N2O emissions for ~2 months after the fertiliser was applied. Applying irrigation (50 mm) during the vegetative growth stage produced a temporary (~1-week) but non-significant increase in N2O emissions compared with plots that received N fertiliser at sowing but were not irrigated. Including a legume in the rotation significantly increased soil inorganic N at sowing of the following wheat crop by 38 kg N ha–1 (field peas) or 57 kg ha–1 (barrel medic) compared with a canola crop. However, N2O emissions were greater in wheat plots where N fertiliser was applied than where wheat was sown into legume plots where no N fertiliser was applied. Over the 2 years of the field study, N2O emissions attributed to fertiliser ranged from 41 to 111 g N2O-N ha–1, and averaged of 75 g N2O-N ha–1 or 0.15% of the applied N fertiliser. Our findings confirm that the proportion of N fertiliser emitted as N2O from rainfed grain crops grown in Australian semi-arid regions is less than the international average of 1.0%.
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Petrescu, Ana Maria Roxana, Matthew J. McGrath, Robbie M. Andrew, Philippe Peylin, Glen P. Peters, Philippe Ciais, Gregoire Broquet, et al. "The consolidated European synthesis of CO<sub>2</sub> emissions and removals for the European Union and United Kingdom: 1990–2018." Earth System Science Data 13, no. 5 (May 28, 2021): 2363–406. http://dx.doi.org/10.5194/essd-13-2363-2021.
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Abstract. Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO2), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well-characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results and inverse modeling estimates over the period 1990–2018. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGIs, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the member states following the IPCC Guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arises from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGIs with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO2 fossil) and the use of different land use definitions for reporting emissions from land use, land use change and forestry (LULUCF) activities (CO2 land). At the EU27 + UK level, the NGHGI (2019) fossil CO2 emissions (including cement production) account for 2624 Tg CO2 in 2014 while all the other seven bottom-up sources are consistent with the NGHGIs and report a mean of 2588 (± 463 Tg CO2). The inversion reports 2700 Tg CO2 (± 480 Tg CO2), which is well in line with the national inventories. Over 2011–2015, the CO2 land sources and sinks from NGHGI estimates report −90 Tg C yr−1 ± 30 Tg C yr−1 while all other BU approaches report a mean sink of −98 Tg C yr−1 (± 362 Tg of C from dynamic global vegetation models only). For the TD model ensemble results, we observe a much larger spread for regional inversions (i.e., mean of 253 Tg C yr−1 ± 400 Tg C yr−1). This concludes that (a) current independent approaches are consistent with NGHGIs and (b) their uncertainty is too large to allow a verification because of model differences and probably also because of the definition of “CO2 flux” obtained from different approaches. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4626578 (Petrescu et al., 2020a).