Aerosols in Atmospheric Chemistry

2022 ◽  
Author(s):  
Scot T. Martin ◽  
Yue Zhang ◽  
Pengfei Liu ◽  
Qi Chen ◽  
Yongjie Li ◽  
...  
2003 ◽  
Vol 68 (12) ◽  
pp. 2297-2308 ◽  
Author(s):  
Max Mühlhäuser ◽  
Melanie Schnell ◽  
Sigrid D. Peyerimhoff

Multireference configuration interaction calculations are carried out for ground and excited states of trichloromethanol to investigate two important photofragmentation processes relevant to atmospheric chemistry. For CCl3OH five low-lying excited states in the energy range between 6.1 and 7.1 eV are found to be highly repulsive for C-Cl elongation leading to Cl2COH (X2A') and Cl (X2P). Photodissociation along C-O cleavage resulting in Cl3C (X2A') and OH (X2Π) has to overcome a barrier of about 0.8 eV (13A'', 11A'') and 1.2 eV (13A') because the low-lying excited states 11A'', 13A' and 13A'' become repulsive only after elongating the C-O bond by about 0.3 Å.


Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 680
Author(s):  
Chris D. Boone ◽  
Johnathan Steffen ◽  
Jeff Crouse ◽  
Peter F. Bernath

Line-of-sight wind profiles are derived from Doppler shifts in infrared solar occultation measurements from the Atmospheric Chemistry Experiment Fourier transform spectrometers (ACE-FTS), the primary instrument on SCISAT, a satellite-based mission for monitoring the Earth’s atmosphere. Comparisons suggest a possible eastward bias from 20 m/s to 30 m/s in ACE-FTS results above 80 km relative to some datasets but no persistent bias relative to other datasets. For instruments operating in a limb geometry, looking through a wide range of altitudes, smearing of the Doppler effect along the line of sight can impact the measured signal, particularly for saturated absorption lines. Implications of Doppler effect smearing are investigated for forward model calculations and volume mixing ratio retrievals. Effects are generally small enough to be safely ignored, except for molecules having a large overhang in their volume mixing ratio profile, such as carbon monoxide.


2021 ◽  
Vol 125 (15) ◽  
pp. 3159-3168
Author(s):  
Jérémy Bourgalais ◽  
Nathalie Carrasco ◽  
Ludovic Vettier ◽  
Antoine Comby ◽  
Dominique Descamps ◽  
...  

2013 ◽  
Vol 6 (1) ◽  
pp. 453-494 ◽  
Author(s):  
D. S. Moreira ◽  
S. R. Freitas ◽  
J. P. Bonatti ◽  
L. M. Mercado ◽  
N. M. É. Rosário ◽  
...  

Abstract. This article presents the development of a new numerical system denominated JULES-CCATT-BRAMS, which resulted from the coupling of the JULES surface model to the CCATT-BRAMS atmospheric chemistry model. The performance of this system in relation to several meteorological variables (wind speed at 10 m, air temperature at 2 m, dew point temperature at 2 m, pressure reduced to mean sea level and 6 h accumulated precipitation) and the CO2 concentration above an extensive area of South America is also presented, focusing on the Amazon basin. The evaluations were conducted for two periods, the wet (March) and dry (September) seasons of 2010. The statistics used to perform the evaluation included bias (BIAS) and root mean squared error (RMSE). The errors were calculated in relation to observations at conventional stations in airports and automatic stations. In addition, CO2 concentrations in the first model level were compared with meteorological tower measurements and vertical CO2 profiles were compared with aircraft data. The results of this study show that the JULES model coupled to CCATT-BRAMS provided a significant gain in performance in the evaluated atmospheric fields relative to those simulated by the LEAF (version 3) surface model originally utilized by CCATT-BRAMS. Simulations of CO2 concentrations in Amazonia and a comparison with observations are also discussed and show that the system presents a gain in performance relative to previous studies. Finally, we discuss a wide range of numerical studies integrating coupled atmospheric, land surface and chemistry processes that could be produced with the system described here. Therefore, this work presents to the scientific community a free tool, with good performance in relation to the observed data and re-analyses, able to produce atmospheric simulations/forecasts at different resolutions, for any period of time and in any region of the globe.


2016 ◽  
Vol 49 (1) ◽  
pp. 10-20 ◽  
Author(s):  
Mads P. Sulbaek Andersen ◽  
Sissel Bjørn Svendsen ◽  
Freja From Østerstrøm ◽  
Ole John Nielsen

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Manon Rocco ◽  
Erin Dunne ◽  
Maija Peltola ◽  
Neill Barr ◽  
Jonathan Williams ◽  
...  

AbstractBenzene, toluene, ethylbenzene and xylenes can contribute to hydroxyl reactivity and secondary aerosol formation in the atmosphere. These aromatic hydrocarbons are typically classified as anthropogenic air pollutants, but there is growing evidence of biogenic sources, such as emissions from plants and phytoplankton. Here we use a series of shipborne measurements of the remote marine atmosphere, seawater mesocosm incubation experiments and phytoplankton laboratory cultures to investigate potential marine biogenic sources of these compounds in the oceanic atmosphere. Laboratory culture experiments confirmed marine phytoplankton are a source of benzene, toluene, ethylbenzene, xylenes and in mesocosm experiments their sea-air fluxes varied between seawater samples containing differing phytoplankton communities. These fluxes were of a similar magnitude or greater than the fluxes of dimethyl sulfide, which is considered to be the key reactive organic species in the marine atmosphere. Benzene, toluene, ethylbenzene, xylenes fluxes were observed to increase under elevated headspace ozone concentration in the mesocosm incubation experiments, indicating that phytoplankton produce these compounds in response to oxidative stress. Our findings suggest that biogenic sources of these gases may be sufficiently strong to influence atmospheric chemistry in some remote ocean regions.


2018 ◽  
Author(s):  
Ying Wei ◽  
Xueshun Chen ◽  
Huansheng Chen ◽  
Jie Li ◽  
Zifa Wang ◽  
...  

Abstract. In this study, a full description and comprehensive evaluation of a global-regional nested model, the Aerosol and Atmospheric Chemistry Model of the Institute of Atmospheric Physics (IAP-AACM), is presented for the first time. Not only the global budgets and distribution, but also a comparison of nested simulation over China against multi-datasets are investigated, benefiting from the access of air quality monitoring data in China since 2013 and the Model Inter-Comparison Study for Asia project. The model results and analysis can greatly help reduce uncertainties and understand model diversity in assessing global and regional aerosol effects, especially over East Asia and areas affected by East Asia. The 1-year simulation for 2014 shows that the IAP-AACM is within the range of other models, and well reproduces both spatial distribution and seasonal variation of trace gases and aerosols over major continents and oceans (mostly within the factor of two). The model nicely captures spatial variation for carbon monoxide except an underestimation over the ocean that also shown in other models, which suggests the need for more accurate emission rate of ocean source. For aerosols, the simulation of fine-mode particulate matter (PM2.5) matches observation well and it has a better simulating ability on primary aerosols than secondary aerosols. This calls for more investigation on aerosol chemistry. Furthermore, IAP-AACM shows the superiority of global model, compared with regional model, on performing regional transportation for the nested simulation over East Asia. For the city evaluation over China, the model reproduces variation of sulfur dioxide (SO2), nitrogen dioxide (NO2) and PM2.5 accurately in most cities, with correlation coefficients above 0.5. Compared to the global simulation, the nested simulation exhibits an improved ability to capture the high temporal and spatial variability over China. In particular, the correlation coefficients for PM2.5, SO2 and NO2 are raised by ~ 0.25, ~ 0.15 and ~ 0.2 respectively in the nested grid. The summary provides constructive information for the application of chemical transport models. In future, we recommend the model's ability to capture high spatial variation of PM2.5 is yet to be improved.


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