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Dive into the research topics where V. Huijnen is active.

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Featured researches published by V. Huijnen.


Atmospheric Chemistry and Physics | 2014

Biomass burning influence on high-latitude tropospheric ozone and reactive nitrogen in summer 2008: a multi-model analysis based on POLMIP simulations

S. R. Arnold; Louisa Kent Emmons; S. A. Monks; Kathy S. Law; David A. Ridley; Solène Turquety; Simone Tilmes; Jennie L. Thomas; Johannes Flemming; V. Huijnen; Jingqiu Mao; Bryan N. Duncan; Stephen D. Steenrod; Y. Yoshida; Joakim Langner; Y. Long

Abstract. We have evaluated tropospheric ozone enhancement in air dominated by biomass burning emissions at high latitudes (> 50° N) in July 2008, using 10 global chemical transport model simulations from the POLMIP multi-model comparison exercise. In model air masses dominated by fire emissions, ΔO3/ΔCO values ranged between 0.039 and 0.196 ppbv ppbv−1 (mean: 0.113 ppbv ppbv−1) in freshly fire-influenced air, and between 0.140 and 0.261 ppbv ppbv−1 (mean: 0.193 ppbv) in more aged fire-influenced air. These values are in broad agreement with the range of observational estimates from the literature. Model ΔPAN/ΔCO enhancement ratios show distinct groupings according to the meteorological data used to drive the models. ECMWF-forced models produce larger ΔPAN/ΔCO values (4.47 to 7.00 pptv ppbv−1) than GEOS5-forced models (1.87 to 3.28 pptv ppbv−1), which we show is likely linked to differences in efficiency of vertical transport during poleward export from mid-latitude source regions. Simulations of a large plume of biomass burning and anthropogenic emissions exported from towards the Arctic using a Lagrangian chemical transport model show that 4-day net ozone change in the plume is sensitive to differences in plume chemical composition and plume vertical position among the POLMIP models. In particular, Arctic ozone evolution in the plume is highly sensitive to initial concentrations of PAN, as well as oxygenated VOCs (acetone, acetaldehyde), due to their role in producing the peroxyacetyl radical PAN precursor. Vertical displacement is also important due to its effects on the stability of PAN, and subsequent effect on NOx abundance. In plumes where net ozone production is limited, we find that the lifetime of ozone in the plume is sensitive to hydrogen peroxide loading, due to the production of HOx from peroxide photolysis, and the key role of HO2 + O3 in controlling ozone loss. Overall, our results suggest that emissions from biomass burning lead to large-scale photochemical enhancement in high-latitude tropospheric ozone during summer.


Journal of Geophysical Research | 2016

An observationally constrained evaluation of the oxidative capacity in the tropical western Pacific troposphere

Julie M. Nicely; Daniel C. Anderson; T. Canty; R. J. Salawitch; Glenn M. Wolfe; Eric C. Apel; S. R. Arnold; Elliot Atlas; Nicola J. Blake; James F. Bresch; Teresa L. Campos; Russell R. Dickerson; Bryan N. Duncan; Louisa Kent Emmons; M. J. Evans; Rafael P. Fernandez; Johannes Flemming; Samuel R. Hall; T. F. Hanisco; Shawn B. Honomichl; Rebecca S. Hornbrook; V. Huijnen; Lisa Kaser; Douglas E. Kinnison; Jean-Francois Lamarque; Jingqiu Mao; S. A. Monks; D. D. Montzka; Laura L. Pan; Daniel D. Riemer

Hydroxyl radical (OH) is the main daytime oxidant in the troposphere and determines the atmospheric lifetimes of many compounds. We use aircraft measurements of O3, H2O, NO, and other species from the Convective Transport of Active Species in the Tropics (CONTRAST) field campaign, which occurred in the tropical western Pacific (TWP) during January–February 2014, to constrain a photochemical box model and estimate concentrations of OH throughout the troposphere. We find that tropospheric column OH (OHCOL) inferred from CONTRAST observations is 12 to 40% higher than found in chemical transport models (CTMs), including CAM-chem-SD run with 2014 meteorology as well as eight models that participated in POLMIP (2008 meteorology). Part of this discrepancy is due to a clear-sky sampling bias that affects CONTRAST observations; accounting for this bias and also for a small difference in chemical mechanism results in our empirically based value of OHCOL being 0 to 20% larger than found within global models. While these global models simulate observed O3 reasonably well, they underestimate NOx (NO + NO2) by a factor of 2, resulting in OHCOL ~30% lower than box model simulations constrained by observed NO. Underestimations by CTMs of observed CH3CHO throughout the troposphere and of HCHO in the upper troposphere further contribute to differences between our constrained estimates of OH and those calculated by CTMs. Finally, our calculations do not support the prior suggestion of the existence of a tropospheric OH minimum in the TWP, because during January–February 2014 observed levels of O3 and NO were considerably larger than previously reported values in the TWP.


Tellus B | 2015

On the use of MOZAIC-IAGOS data to assess the ability of the MACC reanalysis to reproduce the distribution of ozone and CO in the UTLS over Europe

Audrey Gaudel; Hannah Clark; V. Thouret; L. Jones; A. Inness; Johannes Flemming; Olaf Stein; V. Huijnen; Henk Eskes; Philippe Nedelec; Damien Boulanger

MOZAIC-IAGOS data are used to assess the ability of the MACC reanalysis (REAN) to reproduce distributions of ozone (O3) and carbon monoxide (CO), along with vertical and inter-annual variability in the upper troposphere/lower stratosphere region (UTLS) over Europe for the period 2003–2010. A control run (CNTRL, without assimilation) is compared with the MACC reanalysis (REAN, with assimilation) to assess the impact of assimilation. On average over the period, REAN underestimates ozone by 60 ppbv in the lower stratosphere (LS), whilst CO is overestimated by 20 ppbv. In the upper troposphere (UT), ozone is overestimated by 50 ppbv, while CO is partly over or underestimated by up to 20 ppbv. As expected, assimilation generally improves model results but there are some exceptions. Assimilation leads to increased CO mixing ratios in the UT which reduce the biases of the model in this region but the difference in CO mixing ratios between LS and UT has not changed and remains underestimated after assimilation. Therefore, this leads to a significant positive bias of CO in the LS after assimilation. Assimilation improves estimates of the amplitude of the seasonal cycle for both species. Additionally, the observations clearly show a general negative trend of CO in the UT which is rather well reproduced by REAN. However, REAN misses the observed inter-annual variability in summer. The O3–CO correlation in the Ex-UTLS is rather well reproduced by the CNTRL and REAN, although REAN tends to miss the lowest CO mixing ratios for the four seasons and tends to oversample the extra-tropical transition layer (ExTL region) in spring. This evaluation stresses the importance of the model gradients for a good description of the mixing in the Ex-UTLS region, which is inherently difficult to observe from satellite instruments.


Journal of Geophysical Research | 2017

Quantifying the causes of differences in tropospheric OH within global models

Julie M. Nicely; R. J. Salawitch; T. Canty; Daniel C. Anderson; S. R. Arnold; M. P. Chipperfield; Louisa Kent Emmons; Johannes Flemming; V. Huijnen; Douglas E. Kinnison; Jean-Francois Lamarque; Jingqiu Mao; S. A. Monks; Stephen D. Steenrod; Simone Tilmes; Solène Turquety

The hydroxyl radical (OH) is the primary daytime oxidant in the troposphere and provides the main loss mechanism for many pollutants and greenhouse gases, including methane (CH4). Global mean tropospheric OH differs by as much as 80% among various global models, for reasons that are not well understood. We use neural networks (NNs), trained using archived output from eight chemical transport models (CTMs) that participated in the POLARCAT Model Intercomparison Project (POLMIP), to quantify the factors responsible for differences in tropospheric OH and resulting CH4 lifetime (τCH4) between these models. Annual average τCH4, for loss by OH only, ranges from 8.0–11.6 years for the eight POLMIP CTMs. The factors driving these differences were quantified by inputting 3-D chemical fields from one CTM into the trained NN of another CTM. Across all CTMs, the largest mean differences in τCH4 (ΔτCH4) result from variations in chemical mechanisms (ΔτCH4 = 0.46 years), the photolysis frequency (J) of O3→O(1D) (0.31 years), local O3 (0.30 years), and CO (0.23 years). The ΔτCH4 due to CTM differences in NOx (NO + NO2) is relatively low (0.17 years), though large regional variation in OH between the CTMs is attributed to NOx. Differences in isoprene and J(NO2) have negligible overall effect on globally averaged tropospheric OH, though the extent of OH variations due to each factor depends on the model being examined. This study demonstrates that NNs can serve as a useful tool for quantifying why tropospheric OH varies between global models, provided essential chemical fields are archived.


Atmospheric Chemistry and Physics | 2012

The MACC reanalysis: An 8 yr data set of atmospheric composition

A. Inness; Frank Baier; Angela Benedetti; Simon Chabrillat; Hannah Clark; Cathy Clerbaux; Pierre-François Coheur; Richard J. Engelen; Quentin Errera; Johannes Flemming; Michael George; Claire Granier; Juliette Hadji-Lazaro; V. Huijnen; Daniel Hurtmans; Louis M Jones; Johannes W. Kaiser; J. Kapsomenakis; K. Lefever; Joana Leitão; M. Razinger; Andreas Richter; Martin G. Schultz; A. J. Simmons; Michael Suttie; Olaf Stein; Jean Noël Thépaut; V. Thouret; M. Vrekoussis; C. Zerefos


Geoscientific Model Development | 2010

The global chemistry transport model TM5: description and evaluation of the tropospheric chemistry version 3.0,

V. Huijnen; J. E. Williams; M. van Weele; T. van Noije; M. Krol; F. Dentener; Arjo Segers; Sander Houweling; Wouter Peters; J. de Laat; F.K. Boersma; P. Bergamaschi; P. F. J. van Velthoven; P. Le Sager; Henk Eskes; F. Alkemade; Rinus Scheele; P. Nédélec; H.-W. Pätz


Atmospheric Chemistry and Physics | 2009

Comparison of OMI NO2 tropospheric columns with an ensemble of global and European regional air quality models

V. Huijnen; Henk Eskes; A. Poupkou; Hendrik Elbern; K. F. Boersma; Gilles Foret; Mikhail Sofiev; A. Valdebenito; Johannes Flemming; O. Stein; A. Gross; Lennart Robertson; Massimo D'Isidoro; I. Kioutsioukis; Elmar Friese; B. Amstrup; Robert Bergström; A. Strunk; Julius Vira; D. Zyryanov; Dimitrios Melas; V-H Peuch; C. Zerefos


Geoscientific Model Development | 2009

Coupling global chemistry transport models to ECMWF's integrated forecast system

Johannes Flemming; A. Inness; H. Flentje; V. Huijnen; P. Moinat; M. Schultz; Oliver Stein


Atmospheric Chemistry and Physics | 2014

The POLARCAT Model Intercomparison Project (POLMIP): Overview and evaluation with observations

Louisa Kent Emmons; S. R. Arnold; S. A. Monks; V. Huijnen; Simone Tilmes; Kathy S. Law; Jennie L. Thomas; Jean-Christophe Raut; Solène Turquety; Y. Long; Bryan N. Duncan; Stephen D. Steenrod; Johannes Flemming; Jingqiu Mao; Joakim Langner; Anne M. Thompson; David W. Tarasick; Eric C. Apel; D. R. Blake; R. C. Cohen; Jack E. Dibb; Glenn S. Diskin; Alan Fried; Samuel R. Hall; L. G. Huey; Andrew J. Weinheimer; Armin Wisthaler; Tomas Mikoviny; J. B. Nowak; J. Peischl


Atmospheric Chemistry and Physics | 2014

Multi-model study of chemical and physical controls on transport of anthropogenic and biomass burning pollution to the Arctic

S. A. Monks; S. R. Arnold; Louisa Kent Emmons; Kathy S. Law; Solène Turquety; Bryan N. Duncan; Johannes Flemming; V. Huijnen; Simone Tilmes; Joakim Langner; Jingqiu Mao; Y. Long; Jennie L. Thomas; Stephen D. Steenrod; Jean-Christophe Raut; C. Wilson; M. P. Chipperfield; Glenn S. Diskin; Andrew J. Weinheimer; Hans Schlager; Gérard Ancellet

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Johannes Flemming

European Centre for Medium-Range Weather Forecasts

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A. Inness

European Centre for Medium-Range Weather Forecasts

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Olaf Stein

Forschungszentrum Jülich

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Henk Eskes

Royal Meteorological Institute

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Louisa Kent Emmons

National Center for Atmospheric Research

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S. A. Monks

National Oceanic and Atmospheric Administration

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V. Thouret

University of Toulouse

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