scholarly journals Isoprene photooxidation: new insights into the production of acids and organic nitrates

2009 ◽  
Vol 9 (4) ◽  
pp. 1479-1501 ◽  
Author(s):  
F. Paulot ◽  
J. D. Crounse ◽  
H. G. Kjaergaard ◽  
J. H. Kroll ◽  
J. H. Seinfeld ◽  
...  
Keyword(s):  
Carbon Flux ◽  
Chemical Transport ◽  
Chemical Mechanism ◽  
Organic Nitrates ◽  
Transport Models ◽  
Total Oxidation ◽  
Time Resolved ◽  
Chemical Transport Models ◽  
Isoprene Nitrates ◽  
Chamber Studies

Abstract. We describe a nearly explicit chemical mechanism for isoprene photooxidation guided by chamber studies that include time-resolved observation of an extensive suite of volatile compounds. We provide new constraints on the chemistry of the poorly-understood isoprene δ-hydroxy channels, which account for more than one third of the total isoprene carbon flux and a larger fraction of the nitrate yields. We show that the cis branch dominates the chemistry of the δ-hydroxy channel with less than 5% of the carbon following the trans branch. The modelled yield of isoprene nitrates is 12&plusmn3% with a large difference between the δ and β branches. The oxidation of these nitrates releases about 50% of the NOx. Methacrolein nitrates (modelled yield ~15±3% from methacrolein) and methylvinylketone nitrates (modelled yield ~11±3% yield from methylvinylketone) are also observed. Propanone nitrate, produced with a yield of 1% from isoprene, appears to be the longest-lived nitrate formed in the total oxidation of isoprene. We find a large molar yield of formic acid and suggest a novel mechanism leading to its formation from the organic nitrates. Finally, the most important features of this mechanism are summarized in a condensed scheme appropriate for use in global chemical transport models.

scholarly journals Isoprene photooxidation mechanism: resonance channels and implications for the production of nitrates and acids

2008 ◽  
Vol 8 (4) ◽  
pp. 14643-14716 ◽  
Author(s):  
F. Paulot ◽  
J. D. Crounse ◽  
H. G. Kjaergaard ◽  
J. H. Kroll ◽  
J. H. Seinfeld ◽  
...  
Keyword(s):  
Carbon Flux ◽  
Chemical Mechanism ◽  
Organic Nitrates ◽  
Transport Models ◽  
Total Oxidation ◽  
Time Resolved ◽  
Chemical Transport Models ◽  
Isoprene Nitrates ◽  
Photooxidation Mechanism ◽  
Chamber Studies

Abstract. We describe a nearly explicit chemical mechanism for isoprene photooxidation guided by chamber studies that include time-resolved observation of an extensive suite of volatile compounds. We provide new constraints on the chemistry of the poorly-understood isoprene resonance channels, which account for more than one third of the total isoprene carbon flux and a larger fraction of the nitrate yields. We show that the cis branch dominates the chemistry of the isoprene resonance channel with less than 5% of the carbon following the trans branch. We find that the yield of isoprene nitrates is approximately 11%. The oxidation of these nitrates releases nearly 50% of the NOx. Methacrolein nitrates (15% yield) and methylvinylketone nitrates (10% yield) are also observed. Propanone nitrate is produced with a yield of 1% and appears to be the longest-lived nitrate formed in the total oxidation of isoprene. We find a large molar yield of formic acid and suggest a novel mechanism leading to its formation from the organic nitrates. Finally, the most important features of this mechanism are summarized in a condensed scheme appropriate for inclusion in global chemical transport models.

scholarly journals Nitrogen oxide chemistry in an urban plume: investigation of the chemistry of peroxy and multifunctional organic nitrates with a Lagrangian model

2009 ◽  
Vol 9 (6) ◽  
pp. 27099-27165 ◽  
Author(s):  
I. M. Pérez ◽  
B. W. LaFranchi ◽  
R. C. Cohen
Keyword(s):  
Branching Ratio ◽  
Chemical Mechanism ◽  
Lagrangian Model ◽  
Organic Nitrates ◽  
Nox Emissions ◽  
Urban Centers ◽  
Alkyl Nitrate ◽  
Isoprene Nitrates ◽  
Urban Plume ◽  
Chamber Studies

Abstract. Air quality in the outflow from urban centers affects millions of people, as well as, natural and managed ecosystems downwind. In locations where there are large sources of biogenic VOCs downwind of urban centers, the outflow is characterized by a high VOC reactivity due to biogenic emissions and low NOx. However most field and chamber studies have focused on limiting cases of high NOx or of near zero NOx. Recent measurements of a wide suite of VOCs, O3 and meteorological parameters at several locations within the Sacramento urban plume have provided a detailed benchmark for testing our understanding of chemistry in a plume transitioning from high NOx to low NOx and high VOC reactivity. As an additional simplification, the strong mountain valley circulation in the region makes this urban plume a physical realization of a nearly idealized Lagrangian plume. Here, we describe a model of this plume. We use a Lagrangian model representing chemistry based on the Master Chemical Mechanism (MCM) v3.1 along with mixing and deposition. We discuss the effects of entrainment of background air, the branching ratio for the production of isoprene nitrates and the effects of soil NOx emissions on the composition of the evolving plume. The model predicts that after 2–3 h of chemical processing only 45% of the peroxynitrates (ΣPNs) are PAN and that most (69%) RONO2 are secondary alkyl nitrate products of the reaction of OH with RONO2. We find the model is more consistent with the observations if: a) the yield of ΣPNs from large and multi-functional aldehydes is close to zero; and b) the reaction between OH and RONO2 produces multifunctional nitrates as opposed to either HNO3 or NO2 as is typical in most currently adopted reaction mechanisms. Model results also show that adding NOx emissions throughout the transect increases the available NOx in the downwind regions, but modeled ozone concentrations were little affected by the increased NOx.

Improving the simulation of Intermediate Volatility Compounds (IVOCs) in chemical transport models

2021 ◽  
Author(s):  
Stella-Eftychia Manavi ◽  
Spyros Pandis
Keyword(s):  
Gas Phase ◽  
Polyaromatic Hydrocarbons ◽  
Chemical Transport ◽  
Road Transport ◽  
Basis Set ◽  
Chemical Mechanism ◽  
Semivolatile Organic Compounds ◽  
Transport Models ◽  
Additional Species ◽  
Chemical Transport Models

<p>Secondary organic aerosol (SOA) can be formed in the atmosphere through oxidation of volatile (VOCs), intermediate volatility (IVOCs) and semivolatile organic compounds (SVOCs), and condensation of their less volatile products to the particulate phase. While there has been a lot of progress with the simulation of the VOC chemistry, the simulation of the IVOCs remains challenging. In this study, we develop a new approach for the treatment of these compounds in chemical transport models, treating them as lumped species, similar to the VOCs. The new species are implemented in the SAPRC gas-phase chemical mechanism. We introduce four new lumped species representing larger alkanes, two species for polyaromatic hydrocarbons (PAHs) and one new lumped species representing aromatics, all in the IVOC volatility range. Their gas-phase chemistry is assumed to be analogous to that of the large alkanes and aromatics currently in the SAPRC mechanism but with appropriate parameters. The SOA yields for these additional species were estimated for low and high-NOx conditions following the Volatility Basis Set framework and using the available results of smog chamber studies. As most emission inventories do not include IVOCs, we estimated their emissions starting from road transport using existing non-methane hydrocarbons emissions and emission factors of individual IVOCs from laboratory studies. The total IVOC emissions from diesel vehicles for Europe were significantly higher than those coming from gasoline vehicles. The emissions and extended mechanism were implemented in PMCAMx and were used to simulate the EUCAARI intensive period. Cyclic alkanes, which have both high SOA yields and high emissions, were a major SOA precursor group. The contribution of the various IVOCs to SOA formation, and their overall role is discussed. Significant remaining uncertainties are summarized.</p>

Air quality forecasting system based on chemical transport models

2019 ◽  
Vol 4 ◽  
pp. 203-218
Author(s):  
I.N. Kusnetsova ◽  
◽  
I.U. Shalygina ◽  
M.I. Nahaev ◽  
U.V. Tkacheva ◽  
...  
Keyword(s):  
Air Quality ◽  
Chemical Transport ◽  
Transport Models ◽  
Chemical Transport Models ◽  
Forecasting System ◽  
Air Quality Forecasting

Machine learning based bias correction for numerical chemical transport models

2021 ◽  
Vol 248 ◽  
pp. 118022
Author(s):  
Min Xu ◽  
Jianbing Jin ◽  
Guoqiang Wang ◽  
Arjo Segers ◽  
Tuo Deng ◽  
...  
Keyword(s):  
Machine Learning ◽  
Bias Correction ◽  
Chemical Transport ◽  
Transport Models ◽  
Chemical Transport Models

scholarly journals Skill-Testing Chemical Transport Models across Contrasting Atmospheric Mixing States Using Radon-222

2018 ◽  
Author(s):  
Scott D. Chambers ◽  
Elise-Andree Guérette ◽  
Khalia Monk ◽  
Alan D. Griffiths ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Air Quality ◽  
Diurnal Cycle ◽  
Transport Model ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Transport Models ◽  
Potential Health ◽  
Meteorological Model ◽  
Model Skill ◽  
Chemical Transport Models

We propose a new technique to prepare statistically-robust benchmarking data for evaluating chemical transport model meteorology and air quality parameters within the urban boundary layer. The approach employs atmospheric class-typing, using nocturnal radon measurements to assign atmospheric mixing classes, and can be applied temporally (across the diurnal cycle), or spatially (to create angular distributions of pollutants as a top-down constraint on emissions inventories). In this study only a short (<1-month) campaign is used, but grouping of the relative mixing classes based on nocturnal mean radon concentrations can be adjusted according to dataset length (i.e., number of days per category), or desired range of within-class variability. Calculating hourly distributions of observed and simulated values across diurnal composites of each class-type helps to: (i) bridge the gap between scales of simulation and observation, (ii) represent the variability associated with spatial and temporal heterogeneity of sources and meteorology without being confused by it, and (iii) provide an objective way to group results over whole diurnal cycles that separates ‘natural complicating factors’ (synoptic non-stationarity, rainfall, mesoscale motions, extreme stability, etc.) from problems related to parameterizations, or between-model differences. We demonstrate the utility of this technique using output from a suite of seven contemporary regional forecast and chemical transport models. Meteorological model skill varied across the diurnal cycle for all models, with an additional dependence on the atmospheric mixing class that varied between models. From an air quality perspective, model skill regarding the duration and magnitude of morning and evening “rush hour” pollution events varied strongly as a function of mixing class. Model skill was typically the lowest when public exposure would have been the highest, which has important implications for assessing potential health risks in new and rapidly evolving urban regions, and also for prioritizing the areas of model improvement for future applications.

scholarly journals The STRatospheric Estimation Algorithm from Mainz (STREAM): estimating stratospheric NO<sub>2</sub> from nadir-viewing satellites by weighted convolution

2016 ◽  
Vol 9 (7) ◽  
pp. 2753-2779 ◽  
Author(s):  
Steffen Beirle ◽  
Christoph Hörmann ◽  
Patrick Jöckel ◽  
Song Liu ◽  
Marloes Penning de Vries ◽  
...  
Keyword(s):  
Input Data ◽  
Polar Vortex ◽  
Chemical Transport ◽  
Estimation Algorithm ◽  
Satellite Observations ◽  
Satellite Measurements ◽  
Transport Models ◽  
Verification Algorithm ◽  
Chemical Transport Models ◽  
Total Column

Abstract. The STRatospheric Estimation Algorithm from Mainz (STREAM) determines stratospheric columns of NO2 which are needed for the retrieval of tropospheric columns from satellite observations. It is based on the total column measurements over clean, remote regions as well as over clouded scenes where the tropospheric column is effectively shielded. The contribution of individual satellite measurements to the stratospheric estimate is controlled by various weighting factors. STREAM is a flexible and robust algorithm and does not require input from chemical transport models. It was developed as a verification algorithm for the upcoming satellite instrument TROPOMI, as a complement to the operational stratospheric correction based on data assimilation. STREAM was successfully applied to the UV/vis satellite instruments GOME 1/2, SCIAMACHY, and OMI. It overcomes some of the artifacts of previous algorithms, as it is capable of reproducing gradients of stratospheric NO2, e.g., related to the polar vortex, and reduces interpolation errors over continents. Based on synthetic input data, the uncertainty of STREAM was quantified as about 0.1–0.2 × 1015 molecules cm−2, in accordance with the typical deviations between stratospheric estimates from different algorithms compared in this study.

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