Stochastic Diffusion Model for Estimating Trace Gas Emissions with Static Chambers

Abstract. A new chemical mechanism for the oxidation of biogenic volatile organic compounds (BVOCs) is presented and implemented in the Model of Atmospheric composition at Global and Regional scales using Inversion Techniques for Trace gas Emissions (MAGRITTE v1.0). With a total of 99 organic species and over 240 gas-phase reactions, 67 photodissociations and 7 heterogeneous reactions, the mechanism treats the chemical degradation of isoprene – its main focus – as well as acetaldehyde, acetone, methylbutenol and the family of monoterpenes. Regarding isoprene, the mechanism incorporates a state-of-the-art representation of its oxidation scheme accounting for all major advances put forward in recent theoretical and laboratory studies. The model and its chemical mechanism are evaluated against the suite of chemical measurements from the SEAC4RS (Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) airborne campaign, demonstrating a good overall agreement for major isoprene oxidation products, although the aerosol hydrolysis of tertiary and non-tertiary nitrates remain poorly constrained. The comparisons for methylnitrate indicate a very low nitrate yield (

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Parameter-induced uncertainty quantification of soil N<sub>2</sub>O, NO and CO<sub>2</sub> emission from Höglwald spruce forest (Germany) using the LandscapeDNDC model

Biogeosciences ◽

10.5194/bg-9-3983-2012 ◽

2012 ◽

Vol 9 (10) ◽

pp. 3983-3998 ◽

Cited By ~ 11

Author(s):

K.-H. Rahn ◽

C. Werner ◽

R. Kiese ◽

E. Haas ◽

K. Butterbach-Bahl

Keyword(s):

Greenhouse Gas ◽

Trace Gas ◽

Parameter Distribution ◽

Model Parameters ◽

Gas Emissions ◽

Soil C ◽

Trace Gas Emissions ◽

Soil Atmosphere ◽

Soil C And N ◽

C And N

Abstract. Assessing the uncertainties of simulation results of ecological models is becoming increasingly important, specifically if these models are used to estimate greenhouse gas emissions on site to regional/national levels. Four general sources of uncertainty effect the outcome of process-based models: (i) uncertainty of information used to initialise and drive the model, (ii) uncertainty of model parameters describing specific ecosystem processes, (iii) uncertainty of the model structure, and (iv) accurateness of measurements (e.g., soil-atmosphere greenhouse gas exchange) which are used for model testing and development. The aim of our study was to assess the simulation uncertainty of the process-based biogeochemical model LandscapeDNDC. For this we set up a Bayesian framework using a Markov Chain Monte Carlo (MCMC) method, to estimate the joint model parameter distribution. Data for model testing, parameter estimation and uncertainty assessment were taken from observations of soil fluxes of nitrous oxide (N2O), nitric oxide (NO) and carbon dioxide (CO2) as observed over a 10 yr period at the spruce site of the Höglwald Forest, Germany. By running four independent Markov Chains in parallel with identical properties (except for the parameter start values), an objective criteria for chain convergence developed by Gelman et al. (2003) could be used. Our approach shows that by means of the joint parameter distribution, we were able not only to limit the parameter space and specify the probability of parameter values, but also to assess the complex dependencies among model parameters used for simulating soil C and N trace gas emissions. This helped to improve the understanding of the behaviour of the complex LandscapeDNDC model while simulating soil C and N turnover processes and associated C and N soil-atmosphere exchange. In a final step the parameter distribution of the most sensitive parameters determining soil-atmosphere C and N exchange were used to obtain the parameter-induced uncertainty of simulated N2O, NO and CO2 emissions. These were compared to observational data of an calibration set (6 yr) and an independent validation set of 4 yr. The comparison showed that most of the annual observed trace gas emissions were in the range of simulated values and were predicted with a high certainty (Root-mean-squared error (RMSE) NO: 2.4 to 18.95 g N ha−1 d−1, N2O: 0.14 to 21.12 g N ha−1 d−1, CO2: 5.4 to 11.9 kg C ha−1 d−1). However, LandscapeDNDC simulations were sometimes still limited to accurately predict observed seasonal variations in fluxes.

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Design and application of a mobile ground-based observatory for continuous measurements of atmospheric trace gas and criteria pollutant species

Atmospheric Measurement Techniques ◽

10.5194/amt-8-3481-2015 ◽

2015 ◽

Vol 8 (8) ◽

pp. 3481-3492 ◽

Cited By ~ 5

Author(s):

S. E. Bush ◽

F. M. Hopkins ◽

J. T. Randerson ◽

C.-T. Lai ◽

J. R. Ehleringer

Keyword(s):

Spatial Scales ◽

Point Sources ◽

Trace Gas ◽

Mobile Laboratory ◽

Gas Emissions ◽

Trace Gas Emissions ◽

Criteria Pollutants ◽

Position Data ◽

Health Related ◽

Atmospheric Trace Gas

Abstract. Ground-based measurements of atmospheric trace gas species and criteria pollutants are essential for understanding emissions dynamics across space and time. Gas composition in the lower 50 m of the atmosphere has the greatest direct impacts on human health as well as ecosystem processes; hence data at this level are necessary for addressing carbon-cycle- and public-health-related questions. However, such surface data are generally associated with stationary measurement towers, where spatial representation is limited due to the high cost of establishing and maintaining an extensive network of measurement stations. We describe here a compact mobile laboratory equipped to provide high-precision, high-frequency, continuous, on-road synchronous measurements of CO2, CO, CH4, H2O, NOx, O3, aerosol, meteorological, and geospatial position data. The mobile laboratory has been deployed across the western USA. In addition to describing the vehicle and its capacity, we present data that illustrate the use of the laboratory as a powerful tool for investigating the spatial structure of urban trace gas emissions and criteria pollutants at spatial scales ranging from single streets to whole ecosystem and regional scales. We assess the magnitude of known point sources of CH4 and also identify fugitive urban CH4 emissions. We illustrate how such a mobile laboratory can be used to better understand emissions dynamics and quantify emissions ratios associated with trace gas emissions from wildfire incidents. Lastly, we discuss additional mobile laboratory applications in health and urban metabolism.

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Soil Trace Gas Emissions and Climate Change

Global Environmental Change ◽

10.1007/978-94-007-5784-4_4 ◽

2014 ◽

pp. 325-334 ◽

Cited By ~ 5

Author(s):

Klaus Butterbach-Bahl ◽

Eugenio Diaz-Pines ◽

Michael Dannenmann

Keyword(s):

Climate Change ◽

Trace Gas ◽

Gas Emissions ◽

Trace Gas Emissions

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Ocean acidification and marine trace gas emissions

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.0907163107 ◽

2009 ◽

Vol 107 (2) ◽

pp. 760-765 ◽

Cited By ~ 70

Author(s):

F. E. Hopkins ◽

S. M. Turner ◽

P. D. Nightingale ◽

M. Steinke ◽

D. Bakker ◽

...

Keyword(s):

Ocean Acidification ◽

Trace Gas ◽

Gas Emissions ◽

Trace Gas Emissions

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