Model calculations of the impact of NOx from air traffic, lightning, and surface emissions, compared with measurements

Meijer, E.; Velthoven, P. F. J. van; Thompson, Anne M.; Pfister, L.; Schläger, Hans; Schulte, Peter; Kelder, H.

doi:10.1029/1999jd901052

Cited by 45 publications

(43 citation statements)

References 28 publications

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“…The literature however provides support that TM3 produces realistic NO x distributions. For instance, we note that various studies (Emmonds et al, 1997;Wauben et al, 1997;Meijer et al, 2000) have indicated that TM3 is capable of reproducing aircraft-and surface-observed NO x concentrations for a range of different meteorological and chemical situations. Also, recent studies by Brunner et al (2003Brunner et al ( , 2005 showed that TM3 is well capable of reproducing observed NO x and NO x -related species.…”

Section: Tm3 Errorsmentioning

confidence: 99%

“…The model simulations are performed with a spatial resolution of 144×72 grid cells (2.5 • ×2.5 • ) and 31 σ hybrid-pressure levels from the surface up to 10 hPa. Recently the performance of TM3 was evaluated by comparing model simulations with aircraft observations from various aircraft campaigns (Meijer et al, 2000;Brunner et al, 2003Brunner et al, , 2005.…”

Section: Tm3 Model and Lightning Parameterizationsmentioning

confidence: 99%

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Estimates of lightning NOx production from GOME satellite observations

et al. 2005

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Abstract. Tropospheric NO 2 column retrievals from the Global Ozone Monitoring Experiment (GOME) satellite spectrometer are used to quantify the source strength and 3-D distribution of lightning produced nitrogen oxides (NO x =NO+NO 2 ). A sharp increase of NO 2 is observed at convective cloud tops with increasing cloud top height, consistent with a power-law behaviour with power 5±2. Convective production of clouds with the same cloud height are found to produce NO 2 with a ratio 1.6/1 for continents compared to oceans. This relation between cloud properties and NO 2 is used to construct a 10:30 local time global lightning NO 2 production map for 1997. An extensive statistical comparison is conducted to investigate the capability of the TM3 chemistry transport model to reproduce observed patterns of lightning NO 2 in time and space. This comparison uses the averaging kernel to relate modelled profiles of NO 2 to observed NO 2 columns. It exploits a masking scheme to minimise the interference of other NO x sources on the observed total columns. Simulations are performed with two lightning parameterizations, one relating convective preciptation (CP scheme) to lightning flash distributions, and the other relating the fifth power of the cloud top height (H5 scheme) to lightning distributions. The satellite-retrieved NO 2 fields show significant correlations with the simulated lightning contribution to the NO 2 concentrations for both parameterizations. Over tropical continents modelled lightning NO 2 shows remarkable quantitative agreement with observations. Over the oceans however, the two model lightning parameterizations overestimate the retrieved NO 2 attributed to lightning. Possible explanations for these overestimations are discussed. The ratio between satellite-retrieved NO 2 and modelled lightning NO 2 is used to rescale the original modelled lightning NO x production. Eight estimates of the lightning NO x production in 1997 are obtained from spatial and temporal correCorrespondence to: K. F. Boersma (boersma@knmi.nl) lation methods, from cloud-free and cloud-covered observations, and from two different lightning parameterizations. Accounting for a wide variety of random and possible systematic errors, we estimate the global NO x production from lightning to be in the range 1.1-6.4 Tg N in 1997.

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Section: Tm3 Errorsmentioning

confidence: 99%

Section: Tm3 Model and Lightning Parameterizationsmentioning

confidence: 99%

Estimates of lightning NOx production from GOME satellite observations

et al. 2005

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“…Horowitz and Jacob, 1999;Lelieveld and Dentener, 2000;Meijer et al, 2000;Grewe, 2004;Gromov et al, 2010;Butler et al, 2011;Emmons et al, 2012;Grewe et al, 2012Grewe et al, , 2017.…”

Section: Tagged Species Techniquesmentioning

confidence: 99%

Source apportionment and sensitivity analysis: two methodologies with two different purposes

et al. 2017

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Abstract. This work reviews the existing methodologies for source apportionment and sensitivity analysis to identify key differences and stress their implicit limitations. The emphasis is laid on the differences between source "impacts" (sensitivity analysis) and "contributions" (source apportionment) obtained by using four different methodologies: brute-force top-down, brute-force bottom-up, tagged species and decoupled direct method (DDM). A simple theoretical example to compare these approaches is used highlighting differences and potential implications for policy. When the relationships between concentration and emissions are linear, impacts and contributions are equivalent concepts. In this case, source apportionment and sensitivity analysis may be used indifferently for both air quality planning purposes and quantifying source contributions.However, this study demonstrates that when the relationship between emissions and concentrations is nonlinear, sensitivity approaches are not suitable to retrieve source contributions and source apportionment methods are not appropriate to evaluate the impact of abatement strategies. A quantification of the potential nonlinearities should therefore be the first step prior to source apportionment or planning applications, to prevent any limitations in their use. When nonlinearity is mild, these limitations may, however, be acceptable in the context of the other uncertainties inherent to complex models.Moreover, when using sensitivity analysis for planning, it is important to note that, under nonlinear circumstances, the calculated impacts will only provide information for the exact conditions (e.g. emission reduction share) that are simulated.

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“…The models involved in TRADEOFF have contributed to numerous previous studies on the impact of aircraft emissions (Penner et al, 1999;Brasseur et al, 1998;Grewe et al, 2001;Meijer et al, 2000;Rogers et al, 2000;Pitari and Mancini, 2001) and participated in previous evaluation studies (Bregman et al, 2001;Law et al, 2000;Rogers et al, 2000;Penner et al, 1999;Brasseur et al, 1998;Houghton et al, 2001). Recently, Law et al (2000) compared monthly mean ozone fields of five CTMs with data from the MOZAIC program, in which ozone is measured continuously from passenger aircraft (Marenco et al, 1998).…”

Section: Introductionmentioning

confidence: 99%

An evaluation of the performance of chemistry transport models by comparison with research aircraft observations. Part 1: Concepts and overall model performance

Brunner¹,

Staehelin²,

Rogers³

et al. 2003

Atmos. Chem. Phys.

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Abstract.A rigorous evaluation of five global ChemistryTransport and two Chemistry-Climate Models operated by several different groups in Europe, was performed. Comparisons were made of the models with trace gas observations from a number of research aircraft measurement campaigns during the four-year period 1995-1998. Whenever possible the models were run over the same four-year period and at each simulation time step the instantaneous tracer fields were interpolated to all coinciding observation points. This approach allows for a very close comparison with observations and fully accounts for the specific meteorological conditions during the measurement flights. This is important considering the often limited availability and representativity of such trace gas measurements. A new extensive database including all major research and commercial aircraft measurements between 1995 and 1998, as well as ozone soundings, was established specifically to support this type of direct comparison. Quantitative methods were applied to judge model performance including the calculation of average concentration biases and the visualization of correlations and RMS errors in the form of so-called Taylor diagrams. We present the general concepts applied, the structure and content of the database, and an overall analysis of model skills over four distinct regions. These regions were selected to represent various atmospheric conditions and to cover large geographical domains such that sufficient observations are available Correspondence to: D. Brunner (dominik.brunner@iac.umnw.ethz.ch) for comparison. The comparison of model results with the observations revealed specific problems for each individual model. This study suggests the further improvements needed and serves as a benchmark for re-evaluations of such improvements. In general all models show deficiencies with respect to both mean concentrations and vertical gradients of important trace gases. These include ozone, CO and NO x at the tropopause. Too strong two-way mixing across the tropopause is suggested to be the main reason for differences between simulated and observed CO and ozone values. The generally poor correlations between simulated and measured NO x values suggest that in particular the NO x input by lightning and the convective transport from the polluted boundary layer are still not well described by current parameterizations, which may lead to significant differences in the spatial and seasonal distribution of NO x in the models. Simulated OH concentrations, on the other hand, were found to be in surprisingly good agreement with measured values.

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Model calculations of the impact of NO_x from air traffic, lightning, and surface emissions, compared with measurements

Cited by 45 publications

References 28 publications

Estimates of lightning NO<sub>x</sub> production from GOME satellite observations

Estimates of lightning NO<sub>x</sub> production from GOME satellite observations

Source apportionment and sensitivity analysis: two methodologies with two different purposes

An evaluation of the performance of chemistry transport models by comparison with research aircraft observations. Part 1: Concepts and overall model performance

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Model calculations of the impact of NOx from air traffic, lightning, and surface emissions, compared with measurements

Cited by 45 publications

References 28 publications

Estimates of lightning NO&lt;sub&gt;x&lt;/sub&gt; production from GOME satellite observations

Estimates of lightning NO&lt;sub&gt;x&lt;/sub&gt; production from GOME satellite observations

Source apportionment and sensitivity analysis: two methodologies with two different purposes

An evaluation of the performance of chemistry transport models by comparison with research aircraft observations. Part 1: Concepts and overall model performance

Contact Info

Product

Resources

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Model calculations of the impact of NO_x from air traffic, lightning, and surface emissions, compared with measurements

Estimates of lightning NO<sub>x</sub> production from GOME satellite observations

Estimates of lightning NO<sub>x</sub> production from GOME satellite observations