scholarly journals Interpretation of geostationary satellite aerosol optical depth (AOD) over East Asia in relation to fine particulate matter (PM<sub>2.5</sub>): insights from the KORUS-AQ aircraft campaign and seasonality

2021 ◽  
Author(s):  
Shixian Zhai ◽  
Daniel J. Jacob ◽  
Jared F. Brewer ◽  
Ke Li ◽  
Jonathan M. Moch ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
South Korea ◽  
East Asia ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Fine Particulate Matter ◽  
Geostationary Satellite ◽  
Fine Particulate ◽  
Residential Coal

Abstract. Geostationary satellite sensors over East Asia (GOCI and AHI) are now providing continuous mapping of aerosol optical depth (AOD) at 550 nm to improve monitoring of fine particulate matter (PM2.5) air quality. Here we evaluate our understanding of the physical relationships between AOD and PM2.5 over East Asia by using the GEOS-Chem atmospheric chemistry model to simulate observations from multiple sources: 1) the joint NASA-NIER Korea – United States Air Quality aircraft campaign over South Korea (KORUS-AQ; May–June 2016); 2) AODs from the AERONET ground-based network; 3) AOD from a new GOCI/AHI fused product; and 4) surface PM2.5 networks in South Korea and China. The KORUS-AQ data show that 550 nm AOD is mainly contributed by sulfate-nitrate-ammonium (SNA) and organic aerosols in the planetary boundary layer (PBL), despite large dust concentrations in the free troposphere, reflecting the optically effective size and the high hygroscopicity of the PBL aerosols. Although GEOS-Chem is successful in reproducing the KORUS-AQ vertical profiles of aerosol mass, its ability to link AOD to PM2.5 is limited by under-accounting of coarse PM and by a large overestimate of nighttime PM2.5 nitrate. A broader analysis of the GOCI/AHI AOD data over East Asia in different seasons shows agreement with AERONET AODs and a spatial distribution consistent with surface PM2.5 network data. The AOD observations over North China show a summer maximum and winter minimum, opposite in phase to surface PM2.5. This is due to low PBL depths compounded by high residential coal emissions in winter, and high relative humidity (RH) in summer. Seasonality of AOD and PM2.5 over South Korea is much weaker, reflecting weaker variation of PBL depth and lack of residential coal emissions. Physical interpretation of the satellite AOD data in terms of surface PM2.5 is sensitive to accurate information on aerosol size distributions, PBL depths, RH, the role of coarse particles, and diurnal variation of PM2.5.

scholarly journals Relating geostationary satellite measurements of aerosol optical depth (AOD) over East Asia to fine particulate matter (PM<sub>2.5</sub>): insights from the KORUS-AQ aircraft campaign and GEOS-Chem model simulations

2021 ◽  
Vol 21 (22) ◽  
pp. 16775-16791
Author(s):  
Shixian Zhai ◽  
Daniel J. Jacob ◽  
Jared F. Brewer ◽  
Ke Li ◽  
Jonathan M. Moch ◽  
...  
Keyword(s):  
Particulate Matter ◽  
South Korea ◽  
East Asia ◽  
Aerosol Optical Depth ◽  
Fine Particulate Matter ◽  
Organic Aerosols ◽  
Size Distributions ◽  
Satellite Measurements ◽  
Fine Particulate ◽  
Residential Coal

Abstract. Geostationary satellite measurements of aerosol optical depth (AOD) over East Asia from the Geostationary Ocean Color Imager (GOCI) and Advanced Himawari Imager (AHI) instruments can augment surface monitoring of fine particulate matter (PM2.5) air quality, but this requires better understanding of the AOD–PM2.5 relationship. Here we use the GEOS-Chem chemical transport model to analyze the critical variables determining the AOD–PM2.5 relationship over East Asia by simulation of observations from satellite, aircraft, and ground-based datasets. This includes the detailed vertical aerosol profiling over South Korea from the KORUS-AQ aircraft campaign (May–June 2016) with concurrent ground-based PM2.5 composition, PM10, and AERONET AOD measurements. The KORUS-AQ data show that 550 nm AOD is mainly contributed by sulfate–nitrate–ammonium (SNA) and organic aerosols in the planetary boundary layer (PBL), despite large dust concentrations in the free troposphere, reflecting the optically effective size and high hygroscopicity of the PBL aerosols. We updated SNA and organic aerosol size distributions in GEOS-Chem to represent aerosol optical properties over East Asia by using in situ measurements of particle size distributions from KORUS-AQ. We find that SNA and organic aerosols over East Asia have larger size (number median radius of 0.11 µm with geometric standard deviation of 1.4) and 20 % larger mass extinction efficiency as compared to aerosols over North America (default setting in GEOS-Chem). Although GEOS-Chem is successful in reproducing the KORUS-AQ vertical profiles of aerosol mass, its ability to link AOD to PM2.5 is limited by under-accounting of coarse PM and by a large overestimate of nighttime PM2.5 nitrate. The GOCI–AHI AOD data over East Asia in different seasons show agreement with AERONET AODs and a spatial distribution consistent with surface PM2.5 network data. The AOD observations over North China show a summer maximum and winter minimum, opposite in phase to surface PM2.5. This is due to low PBL depths compounded by high residential coal emissions in winter and high relative humidity (RH) in summer. Seasonality of AOD and PM2.5 over South Korea is much weaker, reflecting weaker variation in PBL depth and lack of residential coal emissions.

scholarly journals A low-cost monitor for measurement of fine particulate matter and aerosol optical depth – Part 2: Citizen-science pilot campaign in northern Colorado

2019 ◽  
Vol 12 (12) ◽  
pp. 6385-6399 ◽  
Author(s):  
Bonne Ford ◽  
Jeffrey R. Pierce ◽  
Eric Wendt ◽  
Marilee Long ◽  
Shantanu Jathar ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Aerosol Optical Depth ◽  
Citizen Science ◽  
Optical Depth ◽  
Spatial Scales ◽  
Fine Particulate Matter ◽  
Optical Measurements ◽  
Fine Particulate ◽  
Northern Colorado

Abstract. A pilot field campaign was conducted in the fall and winter of 2017 in northern Colorado to test the deployment of the Aerosol Mass and Optical Depth (AMOD) instrument as part of the Citizen-Enabled Aerosol Measurements for Satellites (CEAMS) network. Citizen scientists were recruited to set up the device to take filter and optical measurements of aerosols in their backyards. The goal of the network is to provide more surface particulate matter and aerosol optical depth (AOD) measurements to increase the spatial and temporal resolution of ratios of fine particulate matter (PM2.5) to AOD and to improve satellite-based estimates of air quality. Participants collected 65 filters and 160 multi-wavelength AOD measurements, from which 109 successful PM2.5 : AOD ratios were calculated. We show that PM2.5, AOD, and their ratio (PM2.5 : AOD) often vary substantially over relatively short spatial scales; this spatial variation is not typically resolved by satellite- and model-based PM2.5 exposure estimates. The success of the pilot campaign suggests that citizen-science networks are a viable means for providing new insight into surface air quality. We also discuss lessons learned and AMOD design modifications, which will be used in future wider deployments of the CEAMS network.

scholarly journals Continuous mapping of fine particulate matter (PM<sub>2.5</sub>) air quality in East Asia at daily 6×6 km<sup>2</sup> resolution by application of a random forest algorithm to 2011–2019 GOCI geostationary satellite data

2021 ◽  
Author(s):  
Drew C. Pendergrass ◽  
Daniel J. Jacob ◽  
Shixian Zhai ◽  
Jhoon Kim ◽  
Ja-Ho Koo ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Random Forest ◽  
South Korea ◽  
East Asia ◽  
Fine Particulate Matter ◽  
Eastern China ◽  
Ambient Air ◽  
Population Exposure ◽  
Fine Particulate

Abstract. We use 2011–2019 aerosol optical depth (AOD) observations from the Geostationary Ocean Color Imager (GOCI) instrument over East Asia to infer 24-h daily surface fine particulate matter (PM2.5) concentrations at continuous 6x6 km2 resolution over eastern China, South Korea, and Japan. This is done with a random forest (RF) algorithm applied to the gap-filled GOCI AODs and other data and trained with PM2.5 observations from the three national networks. The predicted 24-h PM2.5 concentrations for sites entirely withheld from training in a ten-fold crossvalidation procedure correlate highly with network observations (R2 = 0.89) with single-value precision of 26–32 % depending on country. Prediction of annual mean values has R2 = 0.96 and single-value precision of 12 %. The RF algorithm is only moderately successful for diagnosing local exceedances of the National Ambient Air Quality Standard (NAAQS) because these exceedances are typically within the single-value precisions of the RF, and also because of RF smoothing of extreme PM2.5 concentrations. The area-weighted and population-weighted trends of RF PM2.5 concentrations for eastern China, South Korea, and Japan show steady 2015–2019 declines consistent with surface networks, but the surface networks in eastern China and South Korea underestimate population exposure. Further examination of RF PM2.5 fields for South Korea identifies hotspots where surface network sites were initially lacking and shows 2015–2019 PM2.5 decreases across the country except for flat concentrations in the Seoul metropolitan area. Inspection of monthly PM2.5 time series in Beijing, Seoul, and Tokyo shows that the RF algorithm successfully captures observed seasonal variations of PM2.5 even though AOD and PM2.5 often have opposite seasonalities. Application of the RF algorithm to urban pollution episodes in Seoul and Beijing demonstrates high skill in reproducing the observed day-to-day variations in air quality as well as spatial patterns on the 6 km scale. Comparison to a CMAQ simulation for the Korean peninsula demonstrates the value of the continuous RF PM2.5 fields for testing air quality models, including over North Korea where they offer a unique resource.

scholarly journals Fine particulate matter predictions using high resolution Aerosol Optical Depth (AOD) retrievals

2014 ◽  
Vol 89 ◽  
pp. 189-198 ◽  
Author(s):  
Alexandra A. Chudnovsky ◽  
Petros Koutrakis ◽  
Itai Kloog ◽  
Steven Melly ◽  
Francesco Nordio ◽  
...  
Keyword(s):  
Particulate Matter ◽  
High Resolution ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Fine Particulate Matter ◽  
Fine Particulate

Relationship between the concentration of fine particulate matter and aerosol optical depth in the Middle Urals

2021 ◽  
Author(s):  
Anna P. Luzhetskaya ◽  
Ekaterina S. Nagovitsyna ◽  
Elena V. Omelkova ◽  
Vasiliy A. Poddubny ◽  
Alexey A. Shchelkanov ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Fine Particulate Matter ◽  
Middle Urals ◽  
The Middle Urals ◽  
Fine Particulate

scholarly journals Impacts of historical climate and land cover changes on fine particulate matter (PM<sub>2.5</sub>) air quality in East Asia over 1980–2010

2016 ◽  
Author(s):  
Yu Fu ◽  
Amos P. K. Tai ◽  
Hong Liao
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Particulate Matter ◽  
Air Quality ◽  
Land Cover ◽  
East Asia ◽  
Fine Particulate Matter ◽  
Anthropogenic Emissions ◽  
Voc Emissions ◽  
Fine Particulate

Abstract. To examine the effects of changes in climate, land cover and land use (LCLU), and anthropogenic emissions on fine particulate matter (PM2.5) between the 5-year periods 1981–1985 and 2007–2011 in East Asia, we perform a series of simulations using a global chemical transport model (GEOS-Chem) driven by assimilated meteorological data and a suite of land cover and land use data. Our results indicate that climate change alone could lead to a decrease in wintertime PM2.5 concentration by 4.0–12.0 μg m−3 in northern China, but an increase in summertime PM2.5 by 6.0–8.0 μg m−3 in those regions. These changes are attributable to the changing chemistry and transport of all PM2.5 components driven by long-term trends in temperature, wind speed and mixing depth. The concentration of secondary organic aerosol (SOA) is simulated to increase by 0.2–0.8 μg m−3 in both summer and winter in most regions of East Asia due to climate change alone, mostly reflecting higher biogenic volatile organic compound (VOC) emissions under warming. The impacts of LCLU change alone on PM2.5 (−2.1 to +1.3 μg m−3) are smaller than that of climate change, but among the various components the sensitivity of SOA and thus organic carbon to LCLU change (−0.4 to +1.2 μg m−3) is quite significant especially in summer, which is driven mostly by changes in biogenic VOC emissions following cropland expansion and changing vegetation density. The combined impacts show that while the effect of climate change on PM2.5 air quality is more pronounced, LCLU change could offset part of the climate effect in some regions but exacerbate it in others. As a result of both climate and LCLU changes combined, PM2.5 levels are estimated to change by −12.0 to +12.0 μg m−3 across East Asia between the two periods. Changes in anthropogenic emissions remain the largest contributor to deteriorating PM2.5 air quality in East Asia during the study period, but climate and LCLU changes could lead to a substantial modification of PM2.5 levels.

scholarly journals A low-cost monitor for simultaneous measurement of fine particulate matter and aerosol optical depth – Part 1: Specifications and testing

2019 ◽  
Vol 12 (10) ◽  
pp. 5431-5441 ◽  
Author(s):  
Eric A. Wendt ◽  
Casey W. Quinn ◽  
Daniel D. Miller-Lionberg ◽  
Jessica Tryner ◽  
Christian L'Orange ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Low Cost ◽  
Fine Particulate Matter ◽  
Ground Level ◽  
Aerosol Mass ◽  
Fine Particulate ◽  
The Cost ◽  
Equivalent Method

Abstract. Globally, fine particulate matter (PM2.5) air pollution is a leading contributor to death, disease, and environmental degradation. Satellite-based measurements of aerosol optical depth (AOD) are used to estimate PM2.5 concentrations across the world, but the relationship between satellite-estimated AOD and ground-level PM2.5 is uncertain. Sun photometers measure AOD from the Earth's surface and are often used to improve satellite data; however, reference-grade photometers and PM2.5 monitors are expensive and rarely co-located. This work presents the development and validation of the aerosol mass and optical depth (AMOD) sampler, an inexpensive and compact device that simultaneously measures PM2.5 mass and AOD. The AMOD utilizes a low-cost light-scattering sensor in combination with a gravimetric filter measurement to quantify ground-level PM2.5. Aerosol optical depth is measured using optically filtered photodiodes at four discrete wavelengths. Field validation studies revealed agreement within 10 % for AOD values measured between co-located AMOD and AErosol RObotics NETwork (AERONET) monitors and for PM2.5 mass measured between co-located AMOD and EPA Federal Equivalent Method (FEM) monitors. These results demonstrate that the AMOD can quantify AOD and PM2.5 accurately at a fraction of the cost of existing reference monitors.

scholarly journals Impacts of historical climate and land cover changes on fine particulate matter (PM<sub>2.5</sub>) air quality in East Asia between 1980 and 2010

2016 ◽  
Vol 16 (16) ◽  
pp. 10369-10383 ◽  
Author(s):  
Yu Fu ◽  
Amos P. K. Tai ◽  
Hong Liao
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Particulate Matter ◽  
Air Quality ◽  
Land Cover ◽  
East Asia ◽  
Fine Particulate Matter ◽  
Anthropogenic Emissions ◽  
Voc Emissions ◽  
Fine Particulate

Abstract. To examine the effects of changes in climate, land cover and land use (LCLU), and anthropogenic emissions on fine particulate matter (PM2.5) between the 5-year periods 1981–1985 and 2007–2011 in East Asia, we perform a series of simulations using a global chemical transport model (GEOS-Chem) driven by assimilated meteorological data and a suite of land cover and land use data. Our results indicate that climate change alone could lead to a decrease in wintertime PM2.5 concentration by 4.0–12.0 µg m−3 in northern China, but to an increase in summertime PM2.5 by 6.0–8.0 µg m−3 in those regions. These changes are attributable to the changing chemistry and transport of all PM2.5 components driven by long-term trends in temperature, wind speed and mixing depth. The concentration of secondary organic aerosol (SOA) is simulated to increase by 0.2–0.8 µg m−3 in both summer and winter in most regions of East Asia due to climate change alone, mostly reflecting higher biogenic volatile organic compound (VOC) emissions under warming. The impacts of LCLU change alone on PM2.5 (−2.1 to +1.3 µg m−3) are smaller than that of climate change, but among the various components the sensitivity of SOA and thus organic carbon to LCLU change (−0.4 to +1.2 µg m−3) is quite significant especially in summer, which is driven mostly by changes in biogenic VOC emissions following cropland expansion and changing vegetation density. The combined impacts show that while the effect of climate change on PM2.5 air quality is more pronounced, LCLU change could offset part of the climate effect in some regions but exacerbate it in others. As a result of both climate and LCLU changes combined, PM2.5 levels are estimated to change by −12.0 to +12.0 µg m−3 across East Asia between the two periods. Changes in anthropogenic emissions remain the largest contributor to deteriorating PM2.5 air quality in East Asia during the study period, but climate and LCLU changes could lead to a substantial modification of PM2.5 levels.

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