scholarly journals Understanding and improving model representation of aerosol optical properties for a Chinese haze event measured during KORUS-AQ

2020 ◽  
Vol 20 (11) ◽  
pp. 6455-6478 ◽  
Author(s):  
Pablo E. Saide ◽  
Meng Gao ◽  
Zifeng Lu ◽  
Daniel L. Goldberg ◽  
David G. Streets ◽  
...  
Keyword(s):  
Optical Properties ◽  
Air Quality ◽  
Data Assimilation ◽  
South Korea ◽  
Mass Extinction ◽  
Model Representation ◽  
Climate Projections ◽  
Extinction Efficiency ◽  
Aerosol Mass ◽  
Mass Extinction Efficiency

Abstract. KORUS-AQ was an international cooperative air quality field study in South Korea that measured local and remote sources of air pollution affecting the Korean Peninsula during May–June 2016. Some of the largest aerosol mass concentrations were measured during a Chinese haze transport event (24 May). Air quality forecasts using the WRF-Chem model with aerosol optical depth (AOD) data assimilation captured AOD during this pollution episode but overpredicted surface particulate matter concentrations in South Korea, especially PM2.5, often by a factor of 2 or larger. Analysis revealed multiple sources of model deficiency related to the calculation of optical properties from aerosol mass that explain these discrepancies. Using in situ observations of aerosol size and composition as inputs to the optical properties calculations showed that using a low-resolution size bin representation (four bins) underestimates the efficiency with which aerosols scatter and absorb light (mass extinction efficiency). Besides using finer-resolution size bins (8–16 bins), it was also necessary to increase the refractive indices and hygroscopicity of select aerosol species within the range of values reported in the literature to achieve better consistency with measured values of the mass extinction efficiency (6.7 m2 g−1 observed average) and light-scattering enhancement factor (f(RH)) due to aerosol hygroscopic growth (2.2 observed average). Furthermore, an evaluation of the optical properties obtained using modeled aerosol properties revealed the inability of sectional and modal aerosol representations in WRF-Chem to properly reproduce the observed size distribution, with the models displaying a much wider accumulation mode. Other model deficiencies included an underestimate of organic aerosol density (1.0 g cm−3 in the model vs. observed average of 1.5 g cm−3) and an overprediction of the fractional contribution of submicron inorganic aerosols other than sulfate, ammonium, nitrate, chloride, and sodium corresponding to mostly dust (17 %–28 % modeled vs. 12 % estimated from observations). These results illustrate the complexity of achieving an accurate model representation of optical properties and provide potential solutions that are relevant to multiple disciplines and applications such as air quality forecasts, health impact assessments, climate projections, solar power forecasts, and aerosol data assimilation.

scholarly journals Understanding and improving model representation of aerosol optical properties for a Chinese haze event measured during KORUS-AQ

2019 ◽  
Author(s):  
Pablo E. Saide ◽  
Meng Gao ◽  
Zifeng Lu ◽  
Dan Goldberg ◽  
David G. Streets ◽  
...  
Keyword(s):  
Optical Properties ◽  
Air Quality ◽  
Data Assimilation ◽  
Health Effect ◽  
Model Representation ◽  
Climate Projections ◽  
Hygroscopic Growth ◽  
Multiple Sources ◽  
Inorganic Aerosols ◽  
Aerosol Mass

Abstract. KORUS-AQ was an international cooperative air quality field study in South Korea that measured local and remote sources of air pollution affecting the Korean peninsula during May–June 2016. Some of the largest aerosol mass concentrations were measured during a Chinese haze transport event (May 24th). Air quality forecasts using the WRF-Chem model with aerosol optical depth (AOD) data assimilation captured AOD during this pollution episode but over-predicted surface particulate matter concentrations, especially PM2.5 often by a factor of 2 or larger. Analysis revealed multiple sources of model deficiency related to the calculation of optical properties from aerosol mass that explain these discrepancies. Using in-situ observations of aerosol size and composition as inputs to the optical properties calculations showed that using a low resolution size bin representation under-estimates the efficiency at which aerosols scatter and absorb light (mass extinction efficiency). Besides using finer-resolution size bins, it was also necessary to increase the refractive indices and hygroscopicity of select aerosol species within the range of values reported in the literature to achieve consistency with measured values of mass/volume extinction efficiencies and light scattering enhancement factor (f(RH)) due to aerosol hygroscopic growth. Furthermore, evaluation of optical properties obtained using modeled aerosol properties revealed the inability of sectional and modal aerosol representations in WRF-Chem to properly reproduce the observed size distribution, with the models displaying a much wider accumulation mode. Other model deficiencies included an under-estimate of organic aerosol density and an over-prediction of the fractional contribution of inorganic aerosols other than sulfate, ammonium, nitrate, chloride and sodium (mostly dust). These results illustrate the complexity of achieving an accurate model representation of optical properties and provide potential solutions that are relevant to multiple disciplines and applications such as air quality forecasts, health-effect assessments, climate projections, solar-power forecasts, and aerosol data assimilation.

scholarly journals Mass Extinction Efficiency Approximation for Polydispersed Aerosol Using Harmonic Mean-Type Approximation

2020 ◽  
Vol 10 (23) ◽  
pp. 8637
Author(s):  
Junshik Um ◽  
Seonghyeon Jang ◽  
Young Jun Yoon ◽  
Seoung Soo Lee ◽  
Ji Yi Lee ◽  
...  
Keyword(s):  
Optical Properties ◽  
Chemical Composition ◽  
Extinction Coefficient ◽  
Mass Extinction ◽  
Aerosol Particles ◽  
Size Distributions ◽  
Extinction Efficiency ◽  
Type Approximation ◽  
Aerosol Mass ◽  
Mass Extinction Efficiency

Among many parameters characterizing atmospheric aerosols, aerosol mass extinction efficiency (MEE) is important for understanding the optical properties of aerosols. MEE is expressed as a function of the refractive indices (i.e., composition) and size distributions of aerosol particles. Aerosol MEE is often considered as a size-independent constant that depends only on the chemical composition of aerosol particles. The famous Malm’s reconstruction equation and subsequent revised methods express the extinction coefficient as a function of aerosol mass concentration and MEE. However, the used constant MEE does not take into account the effect of the size distribution of polydispersed chemical composition. Thus, a simplified expression of size-dependent MEE is required for accurate and conventional calculations of the aerosol extinction coefficient and also other optical properties. In this study, a simple parameterization of MEE of polydispersed aerosol particles was developed. The geometric volume–mean diameters of up to 10 µm with lognormal size distributions and varying geometric standard deviations were used to represent the sizes of various aerosol particles (i.e., ammonium sulfate and nitrate, elemental carbon, and sea salt). Integrating representations of separate small mode and large mode particles using a harmonic mean-type approximation generated the flexible and convenient parameterizations of MEE that can be readily used to process in situ observations and adopted in large-scale numerical models. The calculated MEE and the simple forcing efficiency using the method developed in this study showed high correlations with those calculated using the Mie theory without losing accuracy.

scholarly journals Improving air quality forecasting with the assimilation of GOCI aerosol optical depth (AOD) retrievals during the KORUS-AQ period

2020 ◽  
Vol 20 (10) ◽  
pp. 6015-6036
Author(s):  
Soyoung Ha ◽  
Zhiquan Liu ◽  
Wei Sun ◽  
Yonghee Lee ◽  
Limseok Chang
Keyword(s):  
Air Quality ◽  
Data Assimilation ◽  
South Korea ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Three Dimensional ◽  
Upstream Region ◽  
Temporal And Spatial Distribution ◽  
The Impact ◽  
Air Quality Forecasting

Abstract. The Korean Geostationary Ocean Color Imager (GOCI) satellite has monitored the East Asian region in high temporal (e.g., hourly) and spatial resolution (e.g., 6 km) every day for the last decade, providing unprecedented information on air pollutants over the upstream region of the Korean Peninsula. In this study, the GOCI aerosol optical depth (AOD), retrieved at the 550 nm wavelength, is assimilated to enhance the quality of the aerosol analysis, thereby making systematic improvements to air quality forecasting over South Korea. For successful data assimilation, GOCI retrievals are carefully investigated and processed based on data characteristics such as temporal and spatial distribution. The preprocessed data are then assimilated in the three-dimensional variational data assimilation (3D-Var) technique for the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). For the Korea–United States Air Quality (KORUS-AQ) period (May 2016), the impact of GOCI AOD on the accuracy of surface PM2.5 prediction is examined by comparing with effects of other observations including Moderate Resolution Imaging Spectroradiometer (MODIS) sensors and surface PM2.5 observations. Consistent with previous studies, the assimilation of surface PM2.5 measurements alone still underestimates surface PM2.5 concentrations in the following forecasts, and the forecast improvements last only for about 6 h. When GOCI AOD retrievals are assimilated with surface PM2.5 observations, however, the negative bias is diminished and forecast skills are improved up to 24 h, with the most significant contributions to the prediction of heavy pollution events over South Korea.

scholarly journals Dust Constraints from joint Observational-Modelling-experiMental analysis (DustCOMM): comparison with measurements and model simulations

2020 ◽  
Vol 20 (2) ◽  
pp. 829-863 ◽  
Author(s):  
Adeyemi A. Adebiyi ◽  
Jasper F. Kok ◽  
Yang Wang ◽  
Akinori Ito ◽  
David A. Ridley ◽  
...  
Keyword(s):  
Mass Extinction ◽  
Global Model ◽  
Earth System ◽  
Atmospheric Dust ◽  
Global Models ◽  
Model Simulations ◽  
Extinction Efficiency ◽  
Dust Size Distribution ◽  
The Earth ◽  
Mass Extinction Efficiency

Abstract. Mineral dust is the most abundant aerosol species by mass in the atmosphere, and it impacts global climate, biogeochemistry, and human health. Understanding these varied impacts on the Earth system requires accurate knowledge of dust abundance, size, and optical properties, and how they vary in space and time. However, current global models show substantial biases against measurements of these dust properties. For instance, recent studies suggest that atmospheric dust is substantially coarser and more aspherical than accounted for in models, leading to persistent biases in modelled impacts of dust on the Earth system. Here, we facilitate more accurate constraints on dust impacts by developing a new dataset: Dust Constraints from joint Observational-Modelling-experiMental analysis (DustCOMM). This dataset combines an ensemble of global model simulations with observational and experimental constraints on dust size distribution and shape to obtain more accurate constraints on three-dimensional (3-D) atmospheric dust properties than is possible from global model simulations alone. Specifically, we present annual and seasonal climatologies of the 3-D dust size distribution, 3-D dust mass extinction efficiency at 550 nm, and two-dimensional (2-D) atmospheric dust loading. Comparisons with independent measurements taken over several locations, heights, and seasons show that DustCOMM estimates consistently outperform conventional global model simulations. In particular, DustCOMM achieves a substantial reduction in the bias relative to measured dust size distributions in the 0.5–20 µm diameter range. Furthermore, DustCOMM reproduces measurements of dust mass extinction efficiency to almost within the experimental uncertainties, whereas global models generally overestimate the mass extinction efficiency. DustCOMM thus provides more accurate constraints on 3-D dust properties, and as such can be used to improve global models or serve as an alternative to global model simulations in constraining dust impacts on the Earth system.

Interactive Aerosol Feedbacks on Photolysis Rates in the GEM-MACH Air Quality Model for an Athabasca Oil-Sands Modelling Study

2020 ◽  
Author(s):  
Mahtab Majdzadeh ◽  
Craig Stroud ◽  
Ayodeji Akingunola ◽  
Paul Makar ◽  
Christopher Sioris ◽  
...  
Keyword(s):  
Optical Properties ◽  
Air Quality ◽  
Radiative Transfer ◽  
Forest Fire ◽  
Lookup Table ◽  
Aerosol Optical Properties ◽  
Extinction Efficiency ◽  
Scattering Cross ◽  
Photolysis Rates ◽  
On Line

<p>The radiative transfer module of an on-line chemical transport models requires input data from aerosol extinction efficiency, single scatter albedo and asymmetry factor, in order to predict the radiative state of the atmosphere. These aerosol optical properties (aerosol optical depth, AOD), may be integrated vertically for comparison to satellite observations. These optical effects may also influence the shorter wavelengths associated with atmospheric gas photolysis, influencing atmospheric reactivity. These processes may be harmonized in an on-line reaction transport model, such as Environment and Climate Change Canada’s GEM-MACH (GEM: Global Environmental Multi-scale – MACH: Modelling Air quality and Chemistry). Previous photolysis routine in the radiative transfer module, MESSY-JVAL (Modular Earth Sub-Model System), in GEM-MACH, made use of a climatology of aerosol optical properties, and the previous on-line version made use of a homogeneous mixture Mie code for meteorological radiative transfer calculations.</p><p>We calculated a new lookup table for the extinction efficiency, absorption and scattering cross sections of each aerosol type. The new version of MESSY-JVAL uses GEM-MACH predicted aerosol size distributions, chemical composition and relative humidity in each vertical column at each time step as input, reads aerosol absorption and scattering cross section data from the new lookup table and calculates aerosol optical properties, that are then used to modify both photolysis and meteorological radiative transfer calculations.</p><p>In order to evaluate these modifications to the model, we performed a series of simulations with GEM-MACH with wildfire emissions inputs from the Canadian Forest Fire Emissions Prediction System (CFFEPS) and compared the model AOD output with satellite and AERONET (Aerosol Robotic Network) measurement data. Comparison of the hourly AERONET and monthly-averaged satellite AOD demonstrates major improvements in the revised model AOD predictions. The impact of the updated photolysis rates and meteorological radiative transfer calculations on predictions of oxidant mixing ratios and rates of pollutant oxidation (nitrogen dioxide conversion to nitric acid) will be assessed both within and below the forest fire plume.</p>

Improving air quality forecasting with the assimilation of GOCI AOD retrievals

2020 ◽  
Author(s):  
Soyoung Ha ◽  
Zhiquan Liu
Keyword(s):  
Air Quality ◽  
Data Assimilation ◽  
South Korea ◽  
Positive Impact ◽  
Fine Particulate Matter ◽  
Three Dimensional ◽  
Basis Set ◽  
Upstream Region ◽  
The Impact ◽  
Air Quality Forecasting

<p>The Korean Geostationary Ocean Color Imager (GOCI) satellite has monitored the East Asian region in high temporal and spatial resolution every day for the last decade, providing unprecedented information on air pollutants over the upstream region of the Korean peninsula. In this study, the GOCI Aerosol optical depth (AOD), retrieved at 550 nm wavelength, is assimilated to ameliorate the analysis quality, thereby making systematic improvements on air quality forecasting in South Korea. For successful data assimilation, GOCI retrievals are carefully investigated and processed based on data characteristics. The preprocessed data are then assimilated in the three-dimensional variational data assimilation (3DVAR) technique for the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Over the Korea-United States Air Quality (KORUS-AQ) period (May 2016), the impact of GOCI AOD on the accuracy of air quality forecasting is examined by comparing with other observations including Moderate Resolution Imaging Spectroradiometer (MODIS) sensors and fine particulate matter (PM2.5) observations at the surface. Consistent with previous studies, the assimilation of surface PM2.5 concentrations alone systematically underestimates surface PM2.5 and its positive impact lasts mainly for about 6 h. When GOCI AOD retrievals are assimilated with surface PM2.5 observations, however, the negative bias is diminished and forecasts are improved up to 24 h, with the most significant contributions to the prediction of heavy pollution events over South Korea. The talk will be finished with an introduction of our ongoing efforts on developing the assimilation capability for more sophisticated aerosol schemes such as Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) and the Modal Aerosol Dynamics Model for Europe (MADE)-Volatility basis set (VBS).</p>

Mass extinction efficiency and extinction hygroscopicity of ambient PM2.5 in urban China

2017 ◽  
Vol 156 ◽  
pp. 239-246 ◽  
Author(s):  
Zhen Cheng ◽  
Xin Ma ◽  
Yujie He ◽  
Jingkun Jiang ◽  
Xiaoliang Wang ◽  
...  
Keyword(s):  
Mass Extinction ◽  
Urban China ◽  
Extinction Efficiency ◽  
Mass Extinction Efficiency

scholarly journals Mixing of dust and NH<sub>3</sub> observed globally over anthropogenic dust sources

2012 ◽  
Vol 12 (5) ◽  
pp. 12503-12530
Author(s):  
P. Ginoux ◽  
L. Clarisse ◽  
C. Clerbaux ◽  
P.-F. Coheur ◽  
O. Dubovik ◽  
...  
Keyword(s):  
Mass Extinction ◽  
Indian Subcontinent ◽  
Monsoon Season ◽  
Coastal Region ◽  
Mineralogical Composition ◽  
Extinction Efficiency ◽  
Deep Blue ◽  
Cloud Properties ◽  
Fine Mode ◽  
Mass Extinction Efficiency

Abstract. The global distribution of dust column burden derived from MODIS Deep Blue aerosol products is compared to NH3 column burden retrieved from IASI infrared spectra. We found similarities in their spatial distributions, in particular their hot spots are often collocated over croplands and to a lesser extent pastures. Globally, we found 22% of dust burden collocated with NH3. This confirms the importance of anthropogenic dust from agriculture. Regionally, the Indian subcontinent has the highest amount of dust mixed with NH3 (26%), mostly over cropland and during the pre-monsoon season. North Africa represents 50% of total dust burden but accounts for only 4% of mixed dust, which is found over croplands and pastures in Sahel and the coastal region of the Mediterranean. In order to evaluate the radiative effect of this mixing on dust optical properties, we derive the mass extinction efficiency for various mixtures of dust and NH3, using AERONET sunphotometers data. We found that for dusty days the coarse mode mass extinction efficiency decreases from 0.62 to 0.48 m2 g−1 as NH3 burden increases from 0 to 40 mg m−2. The fine mode extinction efficiency, ranging from 4 to 16 m2 g−1, does not appear to depend on NH3 concentration or relative humidity but rather on mineralogical composition and mixing with other aerosols. Our results imply that a significant amount of dust is already mixed with ammonium salt before its long range transport. This in turn will affect dust lifetime, and its interactions with radiation and cloud properties.

scholarly journals Dust Constraints from joint Observational-Modelling-experiMental analysis (DustCOMM): Comparison with measurements and model simulations

2019 ◽  
Author(s):  
Adeyemi A. Adebiyi ◽  
Jasper F. Kok ◽  
Yang Wang ◽  
Akinori Ito ◽  
David A. Ridley ◽  
...  
Keyword(s):  
Mass Extinction ◽  
Global Model ◽  
Earth System ◽  
Atmospheric Dust ◽  
Global Models ◽  
Model Simulations ◽  
Extinction Efficiency ◽  
Dust Size Distribution ◽  
The Earth ◽  
Mass Extinction Efficiency

Abstract. Mineral dust is the most abundant aerosol specie by mass in the atmosphere, and it impacts global climate, biogeochemistry, and human health. Understanding these varied impacts on the Earth system requires accurate knowledge of dust abundance, size, and optical properties, and how they vary in space and time. However, current global models show substantial biases against measurements of these dust properties. For instance, recent studies suggest that atmospheric dust is substantially coarser and more aspherical than accounted for in models, leading to persistent biases in modelled impacts of dust on the Earth system. Here, we facilitate more accurate constraints on dust impacts by developing a new dataset: Dust Constraints from joint Observational-Modelling-experiMental analysis (DustCOMM). This dataset leverages observational and experimental constraints on dust size distribution and shape to obtain more accurate constraints on three-dimensional (3-D) atmospheric dust properties than is possible from global model simulations alone. Specifically, we present annual and seasonal climatologies of the 3-D dust size distribution, 3-D dust mass extinction efficiency at 550 nm, and two-dimensional atmospheric dust loading. Comparisons with independent measurements taken over several locations, heights, and seasons show that DustCOMM estimates consistently outperform conventional global model simulations. In particular, DustCOMM achieves a substantial reduction in the bias relative to measured dust size distributions in the 0.5–20 µm diameter range. Furthermore, DustCOMM reproduces measurements of dust mass extinction efficiency to almost within the experimental uncertainties, whereas global models generally overestimate the mass extinction efficiency. DustCOMM thus provides more accurate constraints on 3-D dust properties, and as such can be used to improve global models or serve as an alternative to global model simulations in constraining dust impacts on the Earth system.

scholarly journals Improving air quality forecasting with the assimilation of GOCI AOD retrievals during the KORUS-AQ period

2019 ◽  
Author(s):  
Soyoung Ha ◽  
Zhiquan Liu ◽  
Wei Sun ◽  
Yonghee Lee ◽  
Limseok Chang
Keyword(s):  
Air Quality ◽  
Data Assimilation ◽  
South Korea ◽  
Positive Impact ◽  
Fine Particulate Matter ◽  
Three Dimensional ◽  
Upstream Region ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Impact ◽  
Air Quality Forecasting

Abstract. The Korean Geostationary Ocean Color Imager (GOCI) satellite has monitored the East Asian region in high temporal and spatial resolution every day, providing unprecedented information on air pollutants over the upstream region of the Korean peninsula for the last decade. In this study, the GOCI Aerosol optical depth (AOD), retrieved at 550 nm wavelength, is assimilated to ameliorate the analysis quality, thereby making systematic improvements on air quality forecasting in South Korea. For successful data assimilation, GOCI retrievals are carefully investigated and processed based on data characteristics. The preprocessed data are then assimilated in the three-dimensional variational data assimilation (3DVAR) technique for the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). During the Korea-United States Air Quality (KORUS-AQ) period (May 2016), the impact of GOCI AOD on the accuracy of air quality forecasting is examined by comparing with other observations including Moderate Resolution Imaging Spectroradiometer (MODIS) sensors and fine particulate matter (PM2.5) observations at the surface. Consistent with previous studies, the assimilation of surface PM2.5 concentrations alone systematically underestimates surface PM2.5 and its positive impact lasts mainly for about 6 h. When GOCI AOD retrievals are assimilated with surface PM2.5 observations, however, the negative bias is diminished and forecasts are improved up to 24 h, with the most significant contributions to the prediction of heavy pollution events over South Korea.

Sign in / Sign up

Export Citation Format

Share Document