Development of aerosol optical properties for improving the MESSy photolysis module in the GEM-MACH v2.4 air quality model and application for calculating photolysis rates in a biomass burning plume

Majdzadeh, Mahtab; Stroud, Craig; Sioris, Christopher E.; Makar, Paul A.; Akingunola, Ayodeji; McLinden, Chris A.; Zhao, Xiaoyi; Moran, Michael D.; Abboud, Ihab; Chen, Jack

doi:10.5194/gmd-15-219-2022

Cited by 7 publications

(8 citation statements)

References 89 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Another aspect is the calculation of AOD and aerosol properties, which can vary from model to model. Recent studies (e.g., Majdzadeh et al, 2022) have discussed and proposed new approaches to calculate aerosol properties which could improve the accuracy of the reported AODs from the model.…”

Section: Discussionmentioning

confidence: 99%

Introducing the VIIRS-based Fire Emission Inventory version 0 (VFEIv0)

et al. 2022

View full text Add to dashboard Cite

Abstract. A new open biomass burning inventory is presented that relies on the fire radiative power data from the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi NPP satellite. This VIIRS-based Fire Emission Inventory (VFEI) provides emission data from early 2012 to 2019 for more than 40 species of gases and aerosols at spatial resolutions of around 500 m. We found that VFEI produces similar results when compared to other major inventories in many regions of the world. Additionally, we conducted regional simulations using VFEI with the Weather Research and Forecasting (WRF) model with chemistry (WRF-Chem) for Southern Africa (September 2016) and North America (July–August 2019). We compared aerosol optical depth (AOD) from the model against two observational datasets: the MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) product and AErosol RObotic NETwork (AERONET) stations. Results showed good agreement between both simulations and the datasets, with mean AOD biases of around +0.03 for Southern Africa and −0.01 for North America. Both simulations were not only able to reproduce the AOD magnitudes accurately, but also the inter-diurnal variations of smoke concentration. In addition, we made use of the airborne data from the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES; Southern Africa) and the Fire Influence on Regional to Global Environments Experiment and Air Quality (FIREX-AQ; North America) campaigns to evaluate the simulations. In Southern Africa, results showed correlations higher than 0.77 when comparing carbon monoxide and black carbon. In North America, correlations were lower and biases higher. However, this is because the model was not able to reproduce the timing, shape, and location of individual plumes over complex terrain (Rocky Mountains) during the FIREX-AQ campaign period.

show abstract

Section: Discussionmentioning

confidence: 99%

Introducing the VIIRS-based Fire Emission Inventory version 0 (VFEIv0)

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Aerosol-radiation interactions are calculated as described in Majdzadeh et al (2022). For the radiation calculations, sea spray and dust are always assumed to exist as pure particles, externally mixed from the other components.…”

Section: Model Description and Methodsmentioning

confidence: 99%

“…The emissions inventories used in study are the same as those described in Majdzadeh et al (2022) and very similar to the protocol for contributions to AQMEII4 (Galmarini et al, 2021). Anthropogenic emissions from Canada and the United States were sourced from the Canadian Air Pollutant Emissions Inventory and the US Environ-mental Protection Agency (EPA) 2011 Air Emissions Modelling Platform, respectively.…”

Section: Emissionsmentioning

confidence: 99%

“…Our approach was inspired by the results of Ching et al (2016): we independently account for both changes in hygroscopicity and BC mass fraction, as aerosol hygroscopic properties and optical properties do not necessarily co-vary. The existing air quality-weather interactions in GEM-MACH include aerosol-radiation interactions and changes in cloud droplet activation based on CCN concentrations (Gong et al, 2015;Majdzadeh et al, 2022). We perform a case study focused on biomass-burning over North America to evaluate GM-MixingState.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An improved representation of aerosol mixing state for air quality–weather interactions

et al. 2022

View full text Add to dashboard Cite

Abstract. We implement a detailed representation of aerosol mixing state in the Global Environmental Multiscale – Modelling Air quality and CHemistry (GEM-MACH) air quality and weather forecast model. Our mixing-state representation includes three categories: one for more hygroscopic aerosol, one for less hygroscopic aerosol with a high black carbon (BC) mass fraction, and one for less hygroscopic aerosol with a low BC mass fraction. The more detailed representation allows us to better resolve two different aspects of aerosol mixing state: differences in hygroscopicity due to aerosol composition and the amount of absorption enhancement of BC due to non-absorbing coatings. Notably, this three-category representation allows us to account for BC thickly coated with primary organic matter, which enhances the absorption of the BC but has a low hygroscopicity. We compare the results of the three-category representation (1L2B, (one hydrophilic, two hydrophobic)) with a simulation that uses two categories, split by hygroscopicity (HYGRO), and a simulation using the original size-resolved internally mixed assumption (SRIM). We perform a case study that is focused on North America during July 2016, when there were intense wildfires over northwestern North America. We find that the more detailed representation of the aerosol hygroscopicity in both 1L2B and HYGRO decreases wet deposition, which increases aerosol concentrations, particularly of less hygroscopic species. The concentration of PM2.5 increases by 23 % on average. We show that these increased aerosol concentrations increase cloud droplet number concentrations and cloud reflectivity in the model, decreasing surface temperatures. Using two categories based on hygroscopicity yields only a modest benefit in resolving the coating thickness on black carbon, however. The 1L2B representation resolves BC with thinner coatings than the HYGRO simulation, resulting in absorption aerosol optical depths that are 3 % less on average, with greater differences over strong anthropogenic source regions. We did not find strong subsequent effects of this decreased absorption on meteorology.

show abstract

“…Our approach was inspired by the results of Ching et al (2016): We independently account for both changes in hygroscopicity and BC mass fraction, as aerosol hygroscopic properties and optical properties do not necessarily co-vary. The existing air-quality-weather interactions in GEM-MACH include aerosol-radiation interactions and changes in cloud droplet activation based on CCN concentrations (Gong et al, 2015;Majdzadeh et al, 2022). We perform a case study focused on biomass-burning over North America to evaluate GM-MixingState.…”

mentioning

confidence: 99%

An Improved Representation of Aerosol Mixing State for Air-Quality-Weather Interactions

Stevens

Ryjkov

Majdzadeh

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract. We implement a detailed representation of aerosol mixing-state into the GEM-MACH air quality and weather forecast model. Our mixing-state representation includes three categories: one for more-hygroscopic aerosol, one for less-hygroscopic aerosol with a high black carbon (BC) mass fraction, and one for less-hygroscopic aerosol with a low BC mass fraction. This is the first model with a mixing-state representation of this type simulating a continent-scale domain. The more-detailed representation allows us to better resolve two different aspects of aerosol mixing state: differences in hygroscopicity due to aerosol composition, and the amount of absorption enhancement of BC due to non-absorbing coatings. Notably, this three-category representation allows us to account for BC thickly coated with primary organic mass, which enhances the absorption of the BC but has a low hygroscopicity. We compare the results of the three-category representation (1L2B) with a simulation that uses two categories, split by hygroscopicity (HYGRO), and a simulation using the original size-resolved internally mixed assumption (SRIM). We find that the more-detailed representation of the aerosol hygroscopicity in both 1L2B and HYGRO decreases wet deposition, which increases aerosol concentrations, particularly of less-hygroscopic species. The concentration of PM2.5 increases by 23 % on average. We show that these increased aerosol concentrations increase cloud droplet number concentrations and cloud reflectivity in the model, decreasing surface temperatures. Using two categories based on hygroscopicity yields only a modest benefit in resolving the coating thickness on black carbon, however. The 1L2B representation resolves BC with thinner coatings than the HYGRO simulation, resulting in absorption aerosol optical depths that are 3 % less on average. We did not find strong subsequent effects of this decreased absorption on meteorology.

show abstract

Development of aerosol optical properties for improving the MESSy photolysis module in the GEM-MACH v2.4 air quality model and application for calculating photolysis rates in a biomass burning plume

Cited by 7 publications

References 89 publications

Introducing the VIIRS-based Fire Emission Inventory version 0 (VFEIv0)

Introducing the VIIRS-based Fire Emission Inventory version 0 (VFEIv0)

An improved representation of aerosol mixing state for air quality–weather interactions

An Improved Representation of Aerosol Mixing State for Air-Quality-Weather Interactions

Contact Info

Product

Resources

About