Search Results
level 2 data products from the lidar are the locations of atmospheric regions containing particulate matter (clouds and aerosols), the identification of these particles according to type, and profiles and layer integrals of particulate backscatter and extinction in these regions. This paper focuses on the fully automated retrieval of profiles of particulate backscatter and extinction. Note that the level 2 algorithms covered here are applied to measurements made by a single instrument (CALIOP
level 2 data products from the lidar are the locations of atmospheric regions containing particulate matter (clouds and aerosols), the identification of these particles according to type, and profiles and layer integrals of particulate backscatter and extinction in these regions. This paper focuses on the fully automated retrieval of profiles of particulate backscatter and extinction. Note that the level 2 algorithms covered here are applied to measurements made by a single instrument (CALIOP
Development of a Sampling Probe for Representative Sampling of PM at Freestream Velocities in the Range from 0 to 300 km h−1), a honeycomb section, a contraction section, a downstream section (i.e., a test chamber section), and a sirocco fan. The cross-sectional areas of the upstream and test sections were 600 mm × 600 mm and 120 mm × 120 mm, respectively. Particle-free airflow was induced into the wind tunnel by installing a high-efficiency particulate air (HEPA) filter with a cross-sectional area of 600 mm × 600 mm at the inlet of the upstream section. The Arizona Test Dust A4 was aerosolized by using a solid aerosol
), a honeycomb section, a contraction section, a downstream section (i.e., a test chamber section), and a sirocco fan. The cross-sectional areas of the upstream and test sections were 600 mm × 600 mm and 120 mm × 120 mm, respectively. Particle-free airflow was induced into the wind tunnel by installing a high-efficiency particulate air (HEPA) filter with a cross-sectional area of 600 mm × 600 mm at the inlet of the upstream section. The Arizona Test Dust A4 was aerosolized by using a solid aerosol
Tracking Smoke from a Prescribed Fire and Its Impacts on Local Air Quality Using Temporally Resolved GOES-16 ABI Aerosol Optical Depth (AOD)1. Introduction Wildfires and prescribed fires release large amounts of smoke aerosols into the atmosphere ( Wiedinmyer et al. 2006 ; Akagi et al. 2011 ; Koplitz et al. 2018 ), which can degrade fine particulate matter (PM 2.5 ) air quality and cause adverse health effects ( Sapkota et al. 2005 ; Rappold et al. 2011 ; Johnston et al. 2012 ). In particular, prescribed fires, which are controlled burns to support land management, have been shown to be substantial sources of PM 2.5 emissions
1. Introduction Wildfires and prescribed fires release large amounts of smoke aerosols into the atmosphere ( Wiedinmyer et al. 2006 ; Akagi et al. 2011 ; Koplitz et al. 2018 ), which can degrade fine particulate matter (PM 2.5 ) air quality and cause adverse health effects ( Sapkota et al. 2005 ; Rappold et al. 2011 ; Johnston et al. 2012 ). In particular, prescribed fires, which are controlled burns to support land management, have been shown to be substantial sources of PM 2.5 emissions
values greater than 0.500 (boldface type) were set as the selection threshold. The VF1 contributes about 31.44% of the air pollutant data variation in the case of the prelockdown period. It has high loadings from three variables: PM 2.5 (0.844), PM 10 (0.891), and NH 3 (0.746). This factor can be interpreted as a measure of primary and secondary pollutants. As a secondary particulate precursor, NH 3 also contributes to the formation of particulate aerosols in the atmosphere. The VF1 highlights
values greater than 0.500 (boldface type) were set as the selection threshold. The VF1 contributes about 31.44% of the air pollutant data variation in the case of the prelockdown period. It has high loadings from three variables: PM 2.5 (0.844), PM 10 (0.891), and NH 3 (0.746). This factor can be interpreted as a measure of primary and secondary pollutants. As a secondary particulate precursor, NH 3 also contributes to the formation of particulate aerosols in the atmosphere. The VF1 highlights
Babila , J. E. , A. G. Carlton , C. J. Hennigan , and V. P. Ghate , 2020 : On aerosol liquid water and sulfate associations: The potential for fine particulate matter biases . Atmosphere , 11 , 194 , https://doi.org/10.3390/atmos11020194 . Carlton , A. G. , and Coauthors , 2018 : Synthesis of the Southeast Atmosphere Studies: Investigating fundamental atmospheric chemistry questions . Bull. Amer. Meteor. Soc. , 99 , 547 – 567 , https://doi.org/10.1175/BAMS-D-16
Babila , J. E. , A. G. Carlton , C. J. Hennigan , and V. P. Ghate , 2020 : On aerosol liquid water and sulfate associations: The potential for fine particulate matter biases . Atmosphere , 11 , 194 , https://doi.org/10.3390/atmos11020194 . Carlton , A. G. , and Coauthors , 2018 : Synthesis of the Southeast Atmosphere Studies: Investigating fundamental atmospheric chemistry questions . Bull. Amer. Meteor. Soc. , 99 , 547 – 567 , https://doi.org/10.1175/BAMS-D-16
Methods for Dispersal of Precipitated Calcium Carbonate for Stratospheric Aerosol Injectionnecessary scale. Among the various forms of SRM, stratospheric aerosol injection (SAI) is considered the mechanism to most reliably cool the climate, and as such has been the focus of much SRM research to date ( National Academies of Sciences, Engineering, and Medicine 2021 ). The focus on SAI stems in part because of the observational evidence for the climatic cooling effect created by sulfur-based particles that has followed past major volcanic eruptions ( Robock 2000 ). For SAI, both sulfate based
necessary scale. Among the various forms of SRM, stratospheric aerosol injection (SAI) is considered the mechanism to most reliably cool the climate, and as such has been the focus of much SRM research to date ( National Academies of Sciences, Engineering, and Medicine 2021 ). The focus on SAI stems in part because of the observational evidence for the climatic cooling effect created by sulfur-based particles that has followed past major volcanic eruptions ( Robock 2000 ). For SAI, both sulfate based
constant aerosol concentration through the lowest 1250 m are shown by dashed lines. LEEDR-modeled absorption and scattering effects for the same vertical path and boundary layer aerosol concentration but applying an observed Dayton, Ohio, summer atmosphere at 1400 eastern daylight time 25 Jul 13 are shown with solid lines ( Fiorino et al. 2015 ). Coupling the boundary layer effects on atmospheric particulates (aerosols and hydrometeors) is accomplished internally within LEEDR. Molecular absorption
constant aerosol concentration through the lowest 1250 m are shown by dashed lines. LEEDR-modeled absorption and scattering effects for the same vertical path and boundary layer aerosol concentration but applying an observed Dayton, Ohio, summer atmosphere at 1400 eastern daylight time 25 Jul 13 are shown with solid lines ( Fiorino et al. 2015 ). Coupling the boundary layer effects on atmospheric particulates (aerosols and hydrometeors) is accomplished internally within LEEDR. Molecular absorption
Meteorological Administration (KMA) employs the Asian Dust Aerosol Model 2 (ADAM2) ( In and Park 2003 ; Park et al. 2010 ; Park and In 2003 ) to forecast Asian dust events. The model has been used in various Asian dust studies: simulation of dry deposition of Asian dusts in EA ( Park et al. 2011 ; Lee et al. 2005 ), the effects of particulate matter (PM) assimilation on Asian dust forecasting ( Lee et al. 2013a ), and intercomparison of Asian dust simulations using ADAM2 and Lagrangian models ( Kim and
Meteorological Administration (KMA) employs the Asian Dust Aerosol Model 2 (ADAM2) ( In and Park 2003 ; Park et al. 2010 ; Park and In 2003 ) to forecast Asian dust events. The model has been used in various Asian dust studies: simulation of dry deposition of Asian dusts in EA ( Park et al. 2011 ; Lee et al. 2005 ), the effects of particulate matter (PM) assimilation on Asian dust forecasting ( Lee et al. 2013a ), and intercomparison of Asian dust simulations using ADAM2 and Lagrangian models ( Kim and
.5 concentration using satellite aerosol optical depth . Atmosphere , 7 , 129 , https://doi.org/10.3390/atmos7100129 . 10.3390/atmos7100129 Chudnovsky , A. A. , H. J. Lee , A. Kostinski , T. Kotlov , and P. Koutrakis , 2012 : Prediction of daily fine particulate matter concentrations using aerosol optical depth retrievals from the Geostationary Operational Environmental Satellite (GOES) . J. Air Waste Manage. Assoc. , 62 , 1022 – 1031 , https://doi.org/10
.5 concentration using satellite aerosol optical depth . Atmosphere , 7 , 129 , https://doi.org/10.3390/atmos7100129 . 10.3390/atmos7100129 Chudnovsky , A. A. , H. J. Lee , A. Kostinski , T. Kotlov , and P. Koutrakis , 2012 : Prediction of daily fine particulate matter concentrations using aerosol optical depth retrievals from the Geostationary Operational Environmental Satellite (GOES) . J. Air Waste Manage. Assoc. , 62 , 1022 – 1031 , https://doi.org/10
aerosols . J. Geophys. Res. , 104 , 31 333 – 31 349 , https://doi.org/10.1029/1999JD900923 . 10.1029/1999JD900923 Fast , J. D. , W. I. Gustafson Jr ., R. C. Easter , R. A. Zaveri , J. C. Barnard , E. G. Chapman , G. A. Grell , and S. E. Peckham , 2006 : Evolution of ozone, particulates, and aerosol direct radiative forcing in the vicinity of Houston using a fully coupled meteorology-chemistry-aerosol model . J. Geophys. Res. , 111 , D21305 , https://doi.org/10
aerosols . J. Geophys. Res. , 104 , 31 333 – 31 349 , https://doi.org/10.1029/1999JD900923 . 10.1029/1999JD900923 Fast , J. D. , W. I. Gustafson Jr ., R. C. Easter , R. A. Zaveri , J. C. Barnard , E. G. Chapman , G. A. Grell , and S. E. Peckham , 2006 : Evolution of ozone, particulates, and aerosol direct radiative forcing in the vicinity of Houston using a fully coupled meteorology-chemistry-aerosol model . J. Geophys. Res. , 111 , D21305 , https://doi.org/10
