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Mehta SK, Ananthavel A, Velu V, Prabhakaran T, Pandithurai G, Rao DN. Characteristics of elevated aerosol layer over the Indian east coast, Kattankulathur (12.82 oN, 80.04°E): A northeast monsoon region. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 886:163917. [PMID: 37164082 DOI: 10.1016/j.scitotenv.2023.163917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 04/29/2023] [Accepted: 04/29/2023] [Indexed: 05/12/2023]
Abstract
The elevated aerosol layer (EAL) plays a vital role in weather and climate by modifying the Earth's radiation budget. In the present study, the EAL occurrence and its characteristics in the pre-monsoon season using micropulse lidar (MPL) observations during 2016-2018 and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) during 2007-2018 over Kattankulathur is being reported. We have collected 147 days (101 cases) of MPL (CALIPSO) observations during clear sky conditions in the pre-monsoon 2016-2018 (2007-2018), out of which EAL is observed for 56 days (61 cases). The EAL width is generally found to be ~2.0 km and occurs between ~1.0 km and 5.0 km. Three different types of EALs are categorized based on their altitudinal occurrence using the zero-crossing method. The EALs with their base at ~1.0-1.5 km, ~1.5-2.0 km, and ~ 2.0-3.0 km are taken as types I, II, and III, which occur for 9, 20, and 27 days, respectively. The EAL significantly modifies the total columnar aerosol optical depth (AOD). It is found that AOD, in total, within ABL and EAL, are ~0.72 (0.61), 0.28 (0.25), and 0.45 (0.36) using MPL (CALIPSO), respectively. The aerosols within ABL contribute ~38 % (41 %) while EAL ~ 62 % (59 %) to the total AOD obtained using MPL (CALIPSO). We observed that the ABL and EAL are characterized by different aerosol subtypes, such as dust marine (31 %) and smoke (~ 27 %) aerosols. Other aerosol subtypes, such as dust and polluted dust, commonly occur within the ABL (54 %) and EAL (52 %).
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Affiliation(s)
- Sanjay Kumar Mehta
- Atmospheric Observations and Modelling Laboratory (AOML), Dept. of Physics, SRM Institute of Science and Technology, Kattankulathur 603203, India.
| | - Aravindavel Ananthavel
- Atmospheric Observations and Modelling Laboratory (AOML), Dept. of Physics, SRM Institute of Science and Technology, Kattankulathur 603203, India; Indian Institute of Tropical Meteorology, Pune, India
| | - Vinoj Velu
- Indian Institute of Technology, Bhuvneshwar, India
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2
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Arowosegbe OO, Röösli M, Künzli N, Saucy A, Adebayo-Ojo TC, Schwartz J, Kebalepile M, Jeebhay MF, Dalvie MA, de Hoogh K. Ensemble averaging using remote sensing data to model spatiotemporal PM 10 concentrations in sparsely monitored South Africa. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 310:119883. [PMID: 35932898 DOI: 10.1016/j.envpol.2022.119883] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 07/29/2022] [Accepted: 07/30/2022] [Indexed: 06/15/2023]
Abstract
There is a paucity of air quality data in sub-Saharan African countries to inform science driven air quality management and epidemiological studies. We investigated the use of available remote-sensing aerosol optical depth (AOD) data to develop spatially and temporally resolved models to predict daily particulate matter (PM10) concentrations across four provinces of South Africa (Gauteng, Mpumalanga, KwaZulu-Natal and Western Cape) for the year 2016 in a two-staged approach. In stage 1, a Random Forest (RF) model was used to impute Multiangle Implementation of Atmospheric Correction AOD data for days where it was missing. In stage 2, the machine learner algorithms RF, Gradient Boosting and Support Vector Regression were used to model the relationship between ground-monitored PM10 data, AOD and other spatial and temporal predictors. These were subsequently combined in an ensemble model to predict daily PM10 concentrations at 1 km × 1 km spatial resolution across the four provinces. An out-of-bag R2 of 0.96 was achieved for the first stage model. The stage 2 cross-validated (CV) ensemble model captured 0.84 variability in ground-monitored PM10 with a spatial CV R2 of 0.48 and temporal CV R2 of 0.80. The stage 2 model indicated an optimal performance of the daily predictions when aggregated to monthly and annual means. Our results suggest that a combination of remote sensing data, chemical transport model estimates and other spatiotemporal predictors has the potential to improve air quality exposure data in South Africa's major industrial provinces. In particular, the use of a combined ensemble approach was found to be useful for this area with limited availability of air pollution ground monitoring data.
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Affiliation(s)
| | - Martin Röösli
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland
| | - Nino Künzli
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland
| | - Apolline Saucy
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland
| | - Temitope C Adebayo-Ojo
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Moses Kebalepile
- Department for Education Innovation, University of Pretoria, Pretoria, South Africa
| | - Mohamed Fareed Jeebhay
- Centre for Environmental and Occupational Health Research, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa
| | - Mohamed Aqiel Dalvie
- Centre for Environmental and Occupational Health Research, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa
| | - Kees de Hoogh
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland.
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Adeyemi A, Molnar P, Boman J, Wichmann J. Particulate Matter (PM 2.5) Characterization, Air Quality Level and Origin of Air Masses in an Urban Background in Pretoria. ARCHIVES OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY 2022; 83:77-94. [PMID: 35680664 DOI: 10.1007/s00244-022-00937-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Accepted: 05/15/2022] [Indexed: 06/15/2023]
Abstract
Several sources have been identified as contributing to the concentration of ambient fine particulate matter, which has been associated to a variety of health issues. The chemical characteristics and sources of trace elements in PM2.5, as well as the air quality index, were investigated in this study. Twenty four-hour fine aerosol particles were collected in an urban area in Pretoria, South Africa, from April 2017 to April 2018. Eighteen trace elements were determined using an XEPOS 5 energy-dispersive X-ray fluorescence (EDXRF) spectrometer, while black and organic carbon were estimated using an optical transmissometer from the samples collected. The HYPLIT model (version 4.9) was used to estimate air mass trajectories. Health risk was calculated by comparing it to the World Health Organization's air quality index (AQI). The overall mean PM2.5 concentration of the collected sample equals 21 µg/m3. Majority of PM2.5 exceedances were reported during mid-autumn and winter seasons, as compared to daily WHO guidelines and South African standards. S had the highest concentrations, greater than 1 µg/m3. Ni, Se, Br and Sb showed they were extremely enriched, (EF > 10) and suggestive of anthropogenic or non crustal origin The 24-h PM, soot, BC and OC were significantly different by the geographical origin of air masses (p < 0.05). The AQI showed that 70% of the samples showed levels above the AQI range of good and healthy air. The findings include details on the concentration, composition, and potential sources of fine PM2.5, which is essential for policy formulation and mitigation strategies in South Africa's fight against air pollution.
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Affiliation(s)
- Adewale Adeyemi
- School of Health Systems and Public Health, University of Pretoria, 31 Bophelo Road 00 01, Pretoria, South Africa.
- Department of Environmental Modeling and Biometrics, Forestry Research Institute of Nigeria, Ibadan, Nigeria.
| | - Peter Molnar
- Occupational and Environmental Medicine, Sahlgrenska University Hospital & University of Gothenburg, Medicinaregatan 16A, 40530, Gothenburg, Sweden
| | - Johan Boman
- Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden
| | - Janine Wichmann
- School of Health Systems and Public Health, University of Pretoria, 31 Bophelo Road 00 01, Pretoria, South Africa
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4
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New Global View of Above-Cloud Absorbing Aerosol Distribution Based on CALIPSO Measurements. REMOTE SENSING 2019. [DOI: 10.3390/rs11202396] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Above-low-level-cloud aerosols (ACAs) have gradually gained more interest in recent years; however, the combined aerosol–cloud radiation effects are not well understood. The uncertainty about the radiative effects of aerosols above cloud mainly stems from the lack of comprehensive and accurate retrieval of aerosols and clouds for ACA scenes. In this study, an improved ACA identification and retrieval methodology was developed to provide a new global view of the ACA distribution by combining three-channel CALIOP (The Cloud–Aerosol Lidar with Orthogonal Polarization) observations. The new method can reliably identify and retrieve both thin and dense ACA layers, providing consistent results between the day- and night-time retrieval of ACAs. Then, new four-year (2007 to 2010) global ACA datasets were built, and new seasonal mean views of global ACA occurrence, optical depth, and geometrical thickness were presented and analyzed. Further discussion on the relative position of ACAs to low clouds showed that the mean distance between the ACA layer and the low cloud deck over the tropical Atlantic region is less than 0.2 km. This indicates that the ACAs over this region are more likely to be mixed with low-level clouds, thereby possibly influencing the cloud microphysics over this region, contrary to findings reported from previous studies. The results not only help us better understand global aerosol transportation and aerosol–cloud interactions but also provide useful information for model evaluation and improvements.
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Li Z, Guo J, Ding A, Liao H, Liu J, Sun Y, Wang T, Xue H, Zhang H, Zhu B. Aerosol and boundary-layer interactions and impact on air quality. Natl Sci Rev 2017. [DOI: 10.1093/nsr/nwx117] [Citation(s) in RCA: 387] [Impact Index Per Article: 55.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Air quality is concerned with pollutants in both the gas phase and solid or liquid phases. The latter are referred to as aerosols, which are multifaceted agents affecting air quality, weather and climate through many mechanisms. Unlike gas pollutants, aerosols interact strongly with meteorological variables with the strongest interactions taking place in the planetary boundary layer (PBL). The PBL hosting the bulk of aerosols in the lower atmosphere is affected by aerosol radiative effects. Both aerosol scattering and absorption reduce the amount of solar radiation reaching the ground and thus reduce the sensible heat fluxes that drive the diurnal evolution of the PBL. Moreover, aerosols can increase atmospheric stability by inducing a temperature inversion as a result of both scattering and absorption of solar radiation, which suppresses dispersion of pollutants and leads to further increases in aerosol concentration in the lower PBL. Such positive feedback is especially strong during severe pollution events. Knowledge of the PBL is thus crucial for understanding the interactions between air pollution and meteorology. A key question is how the diurnal evolution of the PBL interacts with aerosols, especially in vertical directions, and affects air quality. We review the major advances in aerosol measurements, PBL processes and their interactions with each other through complex feedback mechanisms, and highlight the priorities for future studies.
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Affiliation(s)
- Zhanqing Li
- State Key Laboratory of Earth Surface Processes and Resource Ecology, GCESS, Beijing Normal University, Beijing 1000875, China
- Department of Atmospheric and Oceanic Sciences, University of Maryland, MD 21029, USA
| | - Jianping Guo
- State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Aijun Ding
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
| | - Hong Liao
- School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Jianjun Liu
- Department of Atmospheric and Oceanic Sciences, University of Maryland, MD 21029, USA
| | - Yele Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Tijian Wang
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
| | - Huiwen Xue
- Department of Atmospheric and Oceanic Sciences, Peking University, Beijing 100871, China
| | - Hongsheng Zhang
- Department of Atmospheric and Oceanic Sciences, Peking University, Beijing 100871, China
| | - Bin Zhu
- School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, China
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Hersey SP, Garland RM, Crosbie E, Shingler T, Sorooshian A, Piketh S, Burger R. An overview of regional and local characteristics of aerosols in South Africa using satellite, ground, and modeling data. ATMOSPHERIC CHEMISTRY AND PHYSICS 2015; 15:4259-4278. [PMID: 26312061 PMCID: PMC4547400 DOI: 10.5194/acp-15-4259-2015] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
We present a comprehensive overview of particulate air quality across the five major metropolitan areas of South Africa (Cape Town, Bloemfontein, Johannesburg and Tshwane (Gauteng Province), the Industrial Highveld Air Quality Priority Area (HVAPA), and Durban), based on a decadal (1 January 2000 to 31 December 2009) aerosol climatology from multiple satellite platforms and detailed analysis of ground-based data from 19 sites throughout Gauteng Province. Satellite analysis was based on aerosol optical depth (AOD) from MODIS Aqua and Terra (550 nm) and MISR (555 nm) platforms, Ångström Exponent (α) from MODIS Aqua (550/865 nm) and Terra (470/660 nm), ultraviolet aerosol index (UVAI) from TOMS, and results from the Goddard Ozone Chemistry Aerosol Radiation and Transport (GOCART) model. At continentally influenced sites, AOD, α, and UVAI reach maxima (0.12-0.20, 1.0-1.8, and 1.0-1.2, respectively) during austral spring (September-October), coinciding with a period of enhanced dust generation and the maximum integrated intensity of close-proximity and subtropical fires identified by MODIS Fire Information for Resource Management System (FIRMS). Minima in AOD, α, and UVAI occur during winter. Results from ground monitoring indicate that low-income township sites experience by far the worst particulate air quality in South Africa, with seasonally averaged PM10 concentrations as much as 136 % higher in townships that in industrial areas. We report poor agreement between satellite and ground aerosol measurements, with maximum surface aerosol concentrations coinciding with minima in AOD, α, and UVAI. This result suggests that remotely sensed data are not an appropriate surrogate for ground air quality in metropolitan South Africa.
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Affiliation(s)
- S. P. Hersey
- Department of Environmental Sciences and Management, North-West University, Potchefstroom, South Africa
- Now at Franklin W. Olin College of Engineering, Needham, MA, USA
| | - R. M. Garland
- Now at Franklin W. Olin College of Engineering, Needham, MA, USA
- Council for Scientific and Industrial Research (CSIR), Pretoria, South Africa
| | - E. Crosbie
- Department of Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
| | - T. Shingler
- Department of Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
| | - A. Sorooshian
- Department of Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
| | - S. Piketh
- Department of Environmental Sciences and Management, North-West University, Potchefstroom, South Africa
| | - R. Burger
- Department of Environmental Sciences and Management, North-West University, Potchefstroom, South Africa
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7
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Kanitz T, Ansmann A, Engelmann R, Althausen D. North-south cross sections of the vertical aerosol distribution over the Atlantic Ocean from multiwavelength Raman/polarization lidar during Polarstern cruises. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2013; 118:2643-2655. [PMID: 25821662 PMCID: PMC4370761 DOI: 10.1002/jgrd.50273] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/11/2012] [Revised: 02/01/2013] [Accepted: 02/12/2013] [Indexed: 06/04/2023]
Abstract
Shipborne aerosol lidar observations were performed aboard the research vessel Polarstern in 2009 and 2010 during three north-south cruises from about 50°N to 50°S. The aerosol data set provides an excellent opportunity to characterize and contrast the vertical aerosol distribution over the Atlantic Ocean in the polluted northern and relatively clean southern hemisphere. Three case studies, an observed pure Saharan dust plume, a Patagonian dust plume east of South America, and a case of a mixed dust/smoke plume west of Central Africa are exemplarily shown and discussed by means of their optical properties. The meridional transatlantic cruises were used to determine the latitudinal cross section of the aerosol optical thickness (AOT). Profiles of particle backscatter and extinction coefficients are presented as mean profiles for latitudinal belts to contrast northern- and southern-hemispheric aerosol loads and optical effects. Results of lidar observations at Punta Arenas (53°S), Chile, and Stellenbosch (34°S), South Africa, are shown and confirm the lower frequency of occurrence of free-tropospheric aerosol in the southern hemisphere than in the northern hemisphere. The maximum latitudinal mean AOT of 0.27 was found in the northern tropics (0- 15°N) in the Saharan outflow region. Marine AOT is typically 0.05 ± 0.03. Particle optical properties are presented separately for the marine boundary layer and the free troposphere. Concerning the contrast between the anthropogenically influenced midlatitudinal aerosol conditions in the 30- 60°N belt and the respective belt in the southern hemisphere over the remote Atlantic, it is found that the AOT and extinction coefficients for the vertical column from 0-5km (total aerosol column) and 1-5km height (lofted aerosol above the marine boundary layer) are a factor of 1.6 and 2 higher at northern midlatitudes than at respective southern midlatitudes, and a factor of 2.5 higher than at the clean marine southern-hemispheric site of Punta Arenas. The strong contrast is confined to the lowermost 3km of the atmosphere.
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Affiliation(s)
- T Kanitz
- Leibniz Institute for Tropospheric Research Leipzig, Germany
| | - A Ansmann
- Leibniz Institute for Tropospheric Research Leipzig, Germany
| | - R Engelmann
- Leibniz Institute for Tropospheric Research Leipzig, Germany
| | - D Althausen
- Leibniz Institute for Tropospheric Research Leipzig, Germany
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8
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Tesfaye M, Sivakumar V, Botai J, Mengistu Tsidu G. Aerosol climatology over South Africa based on 10 years of Multiangle Imaging Spectroradiometer (MISR) data. ACTA ACUST UNITED AC 2011. [DOI: 10.1029/2011jd016023] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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9
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Duflot V, Royer P, Chazette P, Baray JL, Courcoux Y, Delmas R. Marine and biomass burning aerosols in the southern Indian Ocean: Retrieval of aerosol optical properties from shipborne lidar and Sun photometer measurements. ACTA ACUST UNITED AC 2011. [DOI: 10.1029/2011jd015839] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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10
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Wang SH, Lin NH, Chou MD, Tsay SC, Welton EJ, Hsu NC, Giles DM, Liu GR, Holben BN. Profiling transboundary aerosols over Taiwan and assessing their radiative effects. ACTA ACUST UNITED AC 2010. [DOI: 10.1029/2009jd013798] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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11
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Tummon F, Solmon F, Liousse C, Tadross M. Simulation of the direct and semidirect aerosol effects on the southern Africa regional climate during the biomass burning season. ACTA ACUST UNITED AC 2010. [DOI: 10.1029/2009jd013738] [Citation(s) in RCA: 60] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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12
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He Q, Li C, Mao J, Lau AKH, Chu DA. Analysis of aerosol vertical distribution and variability in Hong Kong. ACTA ACUST UNITED AC 2008. [DOI: 10.1029/2008jd009778] [Citation(s) in RCA: 70] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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13
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Cattrall C. Variability of aerosol and spectral lidar and backscatter and extinction ratios of key aerosol types derived from selected Aerosol Robotic Network locations. ACTA ACUST UNITED AC 2005. [DOI: 10.1029/2004jd005124] [Citation(s) in RCA: 224] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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14
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Chung CE, Zhang GJ. Impact of absorbing aerosol on precipitation: Dynamic aspects in association with convective available potential energy and convective parameterization closure and dependence on aerosol heating profile. ACTA ACUST UNITED AC 2004. [DOI: 10.1029/2004jd004726] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Chul Eddy Chung
- Center for Atmospheric Sciences; Scripps Institution of Oceanography; La Jolla California USA
| | - Guang J. Zhang
- Center for Atmospheric Sciences; Scripps Institution of Oceanography; La Jolla California USA
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15
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Mahesh A, Eager R, Campbell JR, Spinhirne JD. Observations of blowing snow at the South Pole. ACTA ACUST UNITED AC 2003. [DOI: 10.1029/2002jd003327] [Citation(s) in RCA: 52] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Ashwin Mahesh
- Goddard Earth Sciences and Technology CenterUniversity of Maryland at Baltimore Greenbelt Maryland USA
- NASA Goddard Space Flight Center Greenbelt Maryland USA
| | - Rebecca Eager
- Department of Geography and MeteorologyValparaiso University Valparaiso Indiana USA
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16
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Swap RJ, Annegarn HJ, Suttles JT, King MD, Platnick S, Privette JL, Scholes RJ. Africa burning: A thematic analysis of the Southern African Regional Science Initiative (SAFARI 2000). ACTA ACUST UNITED AC 2003. [DOI: 10.1029/2003jd003747] [Citation(s) in RCA: 167] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Robert J. Swap
- Department of Environmental Sciences; University of Virginia; Charlottesville Virginia USA
- Atmosphere and Energy Research Group; University of the Witwatersrand; Johannesburg South Africa
| | - Harold J. Annegarn
- Atmosphere and Energy Research Group; University of the Witwatersrand; Johannesburg South Africa
| | | | - Michael D. King
- Earth Sciences Directorate; NASA Goddard Space Flight Center; Greenbelt Maryland USA
| | - Steven Platnick
- Laboratory for Atmospheres; NASA Goddard Space Flight Center; Maryland USA
| | - Jeffrey L. Privette
- Laboratory for Terrestrial Physics; NASA Goddard Space Flight Center; Greenbelt Maryland USA
| | - Robert J. Scholes
- Division of Water, Environment and Forestry Technology; CSIR; Pretoria South Africa
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17
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King MD, Platnick S, Moeller CC, Revercomb HE, Chu DA. Remote sensing of smoke, land, and clouds from the NASA ER-2 during SAFARI 2000. ACTA ACUST UNITED AC 2003. [DOI: 10.1029/2002jd003207] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Michael D. King
- Earth Sciences Directorate; NASA Goddard Space Flight Center; Greenbelt Maryland USA
| | - Steven Platnick
- Laboratory for Atmospheres; NASA Goddard Space Flight Center; Greenbelt Maryland USA
| | | | - Henry E. Revercomb
- Space Science and Engineering Center; University of Wisconsin; Madison Wisconsin USA
| | - D. Allen Chu
- Laboratory for Atmospheres; NASA Goddard Space Flight Center; Greenbelt Maryland USA
- Science Systems and Applications, Inc.; Seabrook Maryland USA
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18
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Schmid B, Redemann J, Russell PB, Hobbs PV, Hlavka DL, McGill MJ, Holben BN, Welton EJ, Campbell JR, Torres O, Kahn RA, Diner DJ, Helmlinger MC, Chu DA, Robles-Gonzalez C, de Leeuw G. Coordinated airborne, spaceborne, and ground-based measurements of massive thick aerosol layers during the dry season in southern Africa. ACTA ACUST UNITED AC 2003. [DOI: 10.1029/2002jd002297] [Citation(s) in RCA: 85] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- B. Schmid
- Bay Area Environmental Research Institute; Sonoma California USA
| | - J. Redemann
- Bay Area Environmental Research Institute; Sonoma California USA
| | - P. B. Russell
- NASA Ames Research Center; Moffett Field California USA
| | - P. V. Hobbs
- Department of Atmospheric Sciences; University of Washington; Seattle Washington USA
| | - D. L. Hlavka
- Science Systems and Applications, Inc.; NASA Goddard Space Flight Center; Greenbelt Maryland USA
| | - M. J. McGill
- NASA Goddard Space Flight Center; Greenbelt Maryland USA
| | - B. N. Holben
- NASA Goddard Space Flight Center; Greenbelt Maryland USA
| | - E. J. Welton
- Goddard Earth Sciences and Technology Center; NASA Goddard Space Flight Center; Greenbelt Maryland USA
| | - J. R. Campbell
- Science Systems and Applications, Inc.; NASA Goddard Space Flight Center; Greenbelt Maryland USA
| | - O. Torres
- Joint Center for Earth Systems; University of Maryland, Baltimore County; Greenbelt Maryland USA
| | - R. A. Kahn
- Jet Propulsion Laboratory; California Institute of Technology; Pasadena California USA
| | - D. J. Diner
- Jet Propulsion Laboratory; California Institute of Technology; Pasadena California USA
| | - M. C. Helmlinger
- Jet Propulsion Laboratory; California Institute of Technology; Pasadena California USA
| | - D. A. Chu
- Science Systems and Applications, Inc.; NASA Goddard Space Flight Center; Greenbelt Maryland USA
| | | | - G. de Leeuw
- TNO Physics and Electronics Laboratory; The Hague Netherlands
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19
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McGill MJ, Hlavka DL, Hart WD, Welton EJ, Campbell JR. Airborne lidar measurements of aerosol optical properties during SAFARI-2000. ACTA ACUST UNITED AC 2003. [DOI: 10.1029/2002jd002370] [Citation(s) in RCA: 58] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Matthew J. McGill
- Laboratory for Atmospheres, Code 912; NASA Goddard Space Flight Center; Greenbelt Maryland USA
| | - Dennis L. Hlavka
- Science Systems and Applications, Inc.; NASA Goddard Space Flight Center; Greenbelt Maryland USA
| | - William D. Hart
- Science Systems and Applications, Inc.; NASA Goddard Space Flight Center; Greenbelt Maryland USA
| | - Ellsworth J. Welton
- Goddard Earth Sciences and Technology Center; NASA Goddard Space Flight Center; Greenbelt Maryland USA
| | - James R. Campbell
- Science Systems and Applications, Inc.; NASA Goddard Space Flight Center; Greenbelt Maryland USA
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