Interrelations between surface, boundary layer, and columnar aerosol properties derived in summer and early autumn over a continental urban site in Warsaw, Poland
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[1] K. Carlson,et al. Turbulent Flows , 2020, Finite Analytic Method in Flows and Heat Transfer.
[2] Dongxiang Wang,et al. Variability of the Boundary Layer Over an Urban Continental Site Based on 10 Years of Active Remote Sensing Observations in Warsaw , 2020, Remote. Sens..
[3] Doina Nicolae,et al. The unprecedented 2017–2018 stratospheric smoke event: decay phase and aerosol properties observed with the EARLINET , 2019, Atmospheric Chemistry and Physics.
[4] M. J. Costa,et al. EARLINET evaluation of the CATS Level 2 aerosol backscatter coefficient product , 2019, Atmospheric Chemistry and Physics.
[5] M. Sicard,et al. Characterization of aerosol hygroscopicity using Raman lidar measurements at the EARLINET station of Payerne , 2019, Atmospheric Chemistry and Physics.
[6] M. J. Costa,et al. The unprecedented 2017–2018 stratospheric smoke event: Decay phase and aerosol properties observed with EARLINET , 2019 .
[7] Shuwen Zhang,et al. A Review of Techniques for Diagnosing the Atmospheric Boundary Layer Height (ABLH) Using Aerosol Lidar Data , 2019, Remote. Sens..
[8] M. Sicard,et al. Towards continuous monitoring of aerosol hygroscopicity by Raman lidar measurements at the EARLINET station of Payerne , 2019 .
[9] Pappalardo,et al. EARLINET evaluation of the CATS L2 aerosol backscatter coefficient product , 2019 .
[10] M. Haeffelin,et al. Long-range-transported Canadian smoke plumes in the lower stratosphere over northern France , 2019, Atmospheric Chemistry and Physics.
[11] Jasper R. Lewis,et al. Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements , 2019, Atmospheric Measurement Techniques.
[12] Kefei Zhang,et al. Estimating PM1 concentrations from MODIS over Yangtze River Delta of China during 2014–2017 , 2018, Atmospheric Environment.
[13] Doina Nicolae,et al. An automatic observation-based aerosol typing method for EARLINET , 2018, Atmospheric Chemistry and Physics.
[14] D. Balis,et al. Are EARLINET and AERONET climatologies consistent? The case of Thessaloniki, Greece , 2018, Atmospheric Chemistry and Physics.
[15] R. Engelmann,et al. Depolarization and lidar ratios at 355, 532, and 1064 nm and microphysical properties of aged tropospheric and stratospheric Canadian wildfire smoke , 2018, Atmospheric Chemistry and Physics.
[16] R. Engelmann,et al. Extreme levels of Canadian wildfire smoke in the stratosphere over central Europe on 21–22 August 2017 , 2018, Atmospheric Chemistry and Physics.
[17] C. Pietras,et al. Description and applications of a mobile system performing on-road aerosol remote sensing and in situ measurements , 2018, Atmospheric Measurement Techniques.
[18] C. Ritter,et al. Radiative impact of an extreme Arctic biomass-burning event , 2018, Atmospheric Chemistry and Physics.
[19] Francisco José Olmo Reyes,et al. Angular scattering of the Sahara dust aerosol , 2018, Atmospheric Chemistry and Physics.
[20] Doina Nicolae,et al. A neural network aerosol-typing algorithm based on lidar data , 2018, Atmospheric Chemistry and Physics.
[21] M. Werner,et al. The role of precursor emissions on ground level ozone concentration during summer season in Poland , 2018, Journal of Atmospheric Chemistry.
[22] Yu Gu,et al. Impact of varying lidar measurement and data processing techniques in evaluating cirrus cloud and aerosol direct radiative effects , 2018 .
[23] Dietrich Althausen,et al. Modification of Local Urban Aerosol Properties by Long-Range Transport of Biomass Burning Aerosol , 2018, Remote. Sens..
[24] J. Pelon,et al. Sources, Load, Vertical Distribution, and Fate of Wintertime Aerosols North of Svalbard From Combined V4 CALIOP Data, Ground‐Based IAOOS Lidar Observations and Trajectory Analysis , 2018 .
[25] Volker Freudenthaler,et al. EARLINET lidar quality assurance tools , 2018 .
[26] Yanjun Ma,et al. Temporal and spatial analyses of particulate matter (PM10 and PM2.5) and its relationship with meteorological parameters over an urban city in northeast China , 2017 .
[27] T. K. Mandal,et al. Relationships of surface ozone with its precursors, particulate matter and meteorology over Delhi , 2017, Journal of Atmospheric Chemistry.
[28] Albert Ansmann,et al. Dry versus wet marine particle optical properties: RH dependence of depolarization ratio, backscatter, and extinction from multiwavelength lidar measurements during SALTRACE , 2017 .
[29] Iwona S. Stachlewska,et al. Effect of Heat Wave Conditions on Aerosol Optical Properties Derived from Satellite and Ground-Based Remote Sensing over Poland , 2017, Remote. Sens..
[30] Iwona S. Stachlewska,et al. Temporal variations in optical and microphysical properties of mineral dust and biomass burning aerosol derived from daytime Raman lidar observations over Warsaw, Poland , 2017 .
[31] Sang Woo Kim,et al. Classifying aerosol type using in situ surface spectral aerosol optical properties , 2017 .
[32] Krzysztof M. Markowicz,et al. The relation between columnar and surface aerosol optical properties in a background environment , 2017 .
[33] D. Althausen,et al. Raman lidar water vapor profiling over Warsaw, Poland , 2017 .
[34] S. Patade,et al. Aerosol–Cloud Interaction in Deep Convective Clouds over the Indian Peninsula Using Spectral (Bin) Microphysics , 2017 .
[35] M. Wiegner,et al. Mixing layer height as an indicator for urban air quality , 2017 .
[36] D. Melas,et al. Investigating the quality of modeled aerosol profiles based on combined lidar and sunphotometer data , 2017 .
[37] Albert Ansmann,et al. Three-dimensional evolution of Saharan dust transport towards Europe based on a 9-year EARLINET-optimized CALIPSO dataset , 2017 .
[38] Hongliang Zhang,et al. Characterization of criteria air pollutants in Beijing during 2014–2015 , 2017, Environmental research.
[39] Aleksander Pietruczuk,et al. Analysis of aerosol transport over southern Poland in August 2015 based on a synergy of remote sensing and backward trajectory techniques , 2017 .
[40] Yuan Wang,et al. Aerosol vertical distribution and optical properties over China from long-term satellite and ground-based remote sensing , 2017 .
[41] I. Stachlewska,et al. Modelling and Observation of Mineral Dust Optical Properties over Central Europe , 2016, Acta Geophysica.
[42] L. Alados-Arboledas,et al. Microphysical characterization of long-range transported biomass burning particles from North America at three EARLINET stations , 2016 .
[43] Iwona S. Stachlewska,et al. Study of aerosol optical properties during long-range transport of biomass burning from Canada to Central Europe in July 2013 , 2016 .
[44] Yuan Wang,et al. Review of Aerosol–Cloud Interactions: Mechanisms, Significance, and Challenges , 2016 .
[45] Victoria E. Cachorro,et al. Long-term comparative study of columnar and surface mass concentration aerosol properties in a background environment , 2016 .
[46] S. Trippetta,et al. Fine aerosol particles (PM1): natural and anthropogenic contributions and health risk assessment , 2016, Air Quality, Atmosphere & Health.
[47] B. Albrecht,et al. Aerosols, clouds, and precipitation in the North Atlantic trades observedduring the Barbados aerosol cloud experiment – Part 1: Distributions andvariability , 2016 .
[48] M. Chin,et al. Evaluation of the aerosol vertical distribution in global aerosol models through comparison against CALIOP measurements: AeroCom phase II results , 2016, Journal of geophysical research. Atmospheres : JGR.
[49] M. Lawrence,et al. BAERLIN2014 – the influence of land surface types on and the horizontal heterogeneity of air pollutant levels in Berlin , 2016 .
[50] R. Engelmann,et al. Study Case of Air-Mass Modification over Poland and Romania Observed by the Means of Multiwavelength Raman Depolarization Lidars , 2016 .
[51] C. Bretherton,et al. Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system , 2016, Proceedings of the National Academy of Sciences.
[52] Fei Chen,et al. Impact of physics parameterizations on high‐resolution weather prediction over two Chinese megacities , 2016 .
[53] Albert Ansmann,et al. The automated multiwavelength Raman polarization and water-vapor lidar PollyXT: The neXT generation , 2016 .
[54] R. Engelmann,et al. An overview of the first decade of Polly NET : an emerging network of automated Raman-polarization lidars for continuous aerosol profiling , 2016 .
[55] S. Ghan,et al. Challenges in constraining anthropogenic aerosol effects on cloud radiative forcing using present-day spatiotemporal variability , 2016, Proceedings of the National Academy of Sciences.
[56] Allison McComiskey,et al. New approaches to quantifying aerosol influence on the cloud radiative effect , 2016, Proceedings of the National Academy of Sciences.
[57] A. Amodeo,et al. Effective resolution concepts for lidar observations , 2015 .
[58] M. Kahnert,et al. Observations of the spectral dependence of linear particle depolarization ratio of aerosols using NASA Langley airborne High Spectral Resolution Lidar , 2015 .
[59] R. Draxler,et al. NOAA’s HYSPLIT Atmospheric Transport and Dispersion Modeling System , 2015 .
[60] L. Mona,et al. CALIPSO climatological products: evaluation and suggestions from EARLINET , 2015 .
[61] V. Freudenthaler,et al. EARLINET instrument intercomparison campaigns: overview on strategy and results , 2015 .
[62] Albert Ansmann,et al. Optical properties of long-range transported Saharan dust over Barbados as measured by dual-wavelength depolarization Raman lidar measurements , 2015 .
[63] M. Chin,et al. What controls the vertical distribution of aerosol? Relationships between process sensitivity in HadGEM3–UKCA and inter-model variation from AeroCom Phase II , 2015 .
[64] J. Lelieveld,et al. The contribution of outdoor air pollution sources to premature mortality on a global scale , 2015, Nature.
[65] Simone Lolli,et al. Principal Component Analysis Approach to Evaluate Instrument Performances in Developing a Cost-Effective Reliable Instrument Network for Atmospheric Measurements , 2015 .
[66] Riko Oki,et al. The EarthCARE Satellite: The Next Step Forward in Global Measurements of Clouds, Aerosols, Precipitation, and Radiation , 2015 .
[67] L. Mona,et al. A methodology for investigating dust model performance using synergistic EARLINET/AERONET dust concentration retrievals , 2015 .
[68] T. Trickl,et al. Stratospheric ozone in boreal fire plumes – the 2013 smoke season over central Europe , 2015 .
[69] I. Riipinen,et al. Particulate matter, air quality and climate: Lessons learned and future needs , 2015 .
[70] Katarzyna Juda-Rezler,et al. Explaining the high PM10 concentrations observed in Polish urban areas , 2015, Air Quality, Atmosphere & Health.
[71] Qi Ying,et al. Relationships between meteorological parameters and criteria air pollutants in three megacities in China. , 2015, Environmental research.
[72] Jos Lelieveld,et al. Long-term (2001-2012) concentrations of fine particulate matter (PM2.5) and the impact on human health in Beijing, China , 2015 .
[73] K. Dawson,et al. Spaceborne observations of the lidar ratio of marine aerosols , 2015 .
[74] Josef Gasteiger,et al. Benefit of depolarization ratio at λ = 1064 nm for the retrieval of the aerosol microphysics from lidar measurements , 2014 .
[75] Lucas Alados-Arboledas,et al. Hygroscopic growth of atmospheric aerosol particles based on active remote sensing and radiosounding measurements: selected cases in southeastern Spain , 2014 .
[76] V. Freudenthaler,et al. EARLINET: towards an advanced sustainable European aerosol lidar network , 2014 .
[77] Mian Chin,et al. A multi-model evaluation of aerosols over South Asia: common problems and possible causes , 2014 .
[78] D. Nicolae,et al. Optical properties of long-range transported volcanic ash over Romania and Poland during Eyjafjallajökull eruption in 2010 , 2014, Acta Geophysica.
[79] Doina Nicolae,et al. Assessment of aerosol's mass concentrations from measured linear particle depolarization ratio (vertically resolved) and simulations , 2013 .
[80] R. Bar-Or,et al. Relative humidity and its effect on aerosol optical depth in the vicinity of convective clouds , 2013 .
[81] M. Perrone,et al. Vertically resolved aerosol properties by multi-wavelength lidar measurements , 2013 .
[82] A. Comerón,et al. Wavelet Correlation Transform Method and Gradient Method to Determine Aerosol Layering from Lidar Returns: Some Comments , 2013 .
[83] A. Pietruczuk,et al. Impact of urban pollution emitted in Warsaw on aerosol properties , 2013 .
[84] B. Weinzierl,et al. Aerosol classification by airborne high spectral resolution lidar observations , 2012 .
[85] A. Szkop,et al. Ceilometer observations of the boundary layer over Warsaw, Poland , 2012, Acta Geophysica.
[86] E. Katragkou,et al. Modelling the effects of climate change on air quality over Central and Eastern Europe: concept, evaluation and projections , 2012 .
[87] L. Sauvage,et al. Evaluation of Mixing-Height Retrievals from Automatic Profiling Lidars and Ceilometers in View of Future Integrated Networks in Europe , 2012, Boundary-Layer Meteorology.
[88] Katarzyna Juda-Rezler,et al. Determination and analysis of PM10 source apportionment during episodes of air pollution in Central Eastern European urban areas: The case of wintertime 2006 , 2011 .
[89] R. Ferrare,et al. Aerosol classification using airborne High Spectral Resolution Lidar measurements – methodology and examples , 2011 .
[90] Luminita Filip,et al. Study of the correlation between the near-ground PM10 mass concentration and the aerosol optical depth , 2011 .
[91] L. Mona,et al. Multi-wavelength Raman lidar observations of the Eyjafjallajökull volcanic cloud over Potenza, southern Italy , 2011 .
[92] L. Alados-Arboledas,et al. Optical and microphysical properties of fresh biomass burning aerosol retrieved by Raman lidar, and star‐and sun‐photometry , 2011 .
[93] Ricardo Barrios,et al. Seasonal variability of aerosol optical properties observed by means of a Raman lidar at an EARLINET site over Northeastern Spain , 2011 .
[94] V. Freudenthaler,et al. Characterization of Saharan dust, marine aerosols and mixtures of biomass-burning aerosols and dust by means of multi-wavelength depolarization and Raman lidar measurements during SAMUM 2 , 2011 .
[95] W. Thomas,et al. Aerosol profiling using the ceilometer network of the German Meteorological Service , 2010 .
[96] T. Nagai,et al. Backscattering linear depolarization ratio measurements of mineral, sea-salt, and ammonium sulfate particles simulated in a laboratory chamber. , 2010, Applied optics.
[97] Hendrik Wolff,et al. Policy Monitor , 2010, Review of Environmental Economics and Policy.
[98] Jie Guang,et al. Correlation between PM concentrations and aerosol optical depth in eastern China , 2009 .
[99] C. Zerefos,et al. Optical properties of different aerosol types: seven years of combined Raman-elastic backscatter lidar measurements in Thessaloniki, Greece , 2009 .
[100] M. Petters,et al. Cloud condensation nucleation activity of biomass burning aerosol , 2009 .
[101] C. Ritter,et al. Aerosol distribution around Svalbard during intense easterly winds , 2009 .
[102] V. Freudenthaler,et al. Depolarization ratio profiling at several wavelengths in pure Saharan dust during SAMUM 2006 , 2009 .
[103] A. Ansmann,et al. Vertical profiling of convective dust plumes in southern Morocco during SAMUM , 2009 .
[104] M. Wiegner,et al. Vertical aerosol profiles from Raman polarization lidar observations during the dry season AMMA field campaign , 2008 .
[105] A. Stohl,et al. Optical characteristics of biomass burning aerosols over Southeastern Europe determined from UV-Raman lidar measurements , 2008 .
[106] Chenbo Xie,et al. Characteristics of aerosol optical properties in pollution and Asian dust episodes over Beijing, China. , 2008, Applied optics.
[107] Y. H. Zhang,et al. Relative humidity dependence of aerosol optical properties and direct radiative forcing in the surface boundary layer at Xinken in Pearl River Delta of China : An observation based numerical study , 2008 .
[108] Alexis K.H. Lau,et al. Analysis of aerosol vertical distribution and variability in Hong Kong , 2008 .
[109] L. Mona,et al. Systematic lidar observations of Saharan dust over Europe in the frame of EARLINET (2000-2002) , 2008 .
[110] Robin J. Hogan,et al. A variational scheme for retrieving ice cloud properties from combined radar, lidar, and infrared radiometer , 2008 .
[111] Haidong Kan,et al. Air pollution and population health: a global challenge , 2008, Environmental health and preventive medicine.
[112] D. Winker,et al. Initial performance assessment of CALIOP , 2007 .
[113] A. Ansmann,et al. Aerosol-type-dependent lidar ratios observed with Raman lidar , 2007 .
[114] Yang Liu,et al. Using aerosol optical thickness to predict ground-level PM2.5 concentrations in the St. Louis area: A comparison between MISR and MODIS , 2007 .
[115] Stefan Emeis,et al. Influence of mixing layer height upon air pollution in urban and sub-urban areas , 2006 .
[116] Christos Zerefos,et al. Four‐year aerosol observations with a Raman lidar at Thessaloniki, Greece, in the framework of European Aerosol Research Lidar Network (EARLINET) , 2005 .
[117] C. Böckmann,et al. Microphysical aerosol parameters from multiwavelength lidar. , 2005, Journal of the Optical Society of America. A, Optics, image science, and vision.
[118] Alexandros Papayannis,et al. Vertical aerosol distribution over Europe: Statistical analysis of Raman lidar data from 10 European Aerosol Research Lidar Network (EARLINET) stations , 2004 .
[119] Albert Ansmann,et al. Multiyear aerosol observations with dual‐wavelength Raman lidar in the framework of EARLINET , 2004 .
[120] A. Ansmann,et al. Aerosol lidar intercomparison in the framework of the EARLINET project. 2. Aerosol backscatter algorithms. , 2004, Applied optics.
[121] P. Buseck,et al. Atmospheric tar balls: Particles from biomass and biofuel burning , 2003 .
[122] Jun Wang,et al. Intercomparison between satellite‐derived aerosol optical thickness and PM2.5 mass: Implications for air quality studies , 2003 .
[123] David S. Covert,et al. A Study of the Extinction-to-Backscatter Ratio of Marine Aerosol during the Shoreline Environment Aerosol Study* , 2003 .
[124] M. Wendisch,et al. Dependence of solar radiative forcing of forest fire aerosol on ageing and state of mixture , 2003 .
[125] O. Boucher,et al. A satellite view of aerosols in the climate system , 2002, Nature.
[126] U. Wandinger,et al. Inversion with regularization for the retrieval of tropospheric aerosol parameters from multiwavelength lidar sounding. , 2002, Applied optics.
[127] R. Halthore,et al. Comparison of aerosol optical depth inferred from surface measurements with that determined by Sun photometry for cloud-free conditions at a continental U.S. site , 2000 .
[128] A. Smirnov,et al. AERONET-a federated instrument network and data archive for aerosol Characterization , 1998 .
[129] I. Tang. Chemical and size effects of hygroscopic aerosols on light scattering coefficients , 1996 .
[130] J. Michalsky,et al. Automated multifilter rotating shadow-band radiometer: an instrument for optical depth and radiation measurements. , 1994, Applied optics.
[131] R. Stull. An Introduction to Boundary Layer Meteorology , 1988 .
[132] Anders Ångström,et al. On the Atmospheric Transmission of Sun Radiation and on Dust in the Air , 1929 .
[133] I. Stachlewska,et al. Lidar Based Separation of Polluted Dust Observed Over Warsaw (Case Study on 09 August 2013) , 2020 .
[134] D. Balis,et al. Are EARLINET and AERONET climatologies consistent ? The case of Thessaloniki , Greece , 2018 .
[135] H. Kalesse,et al. Vertical aerosol distribution in the Southern hemispheric Midlatitudes as observed with lidar at Punta Arenas, Chile (53.2◦S and 70.9◦W) during ALPACA , 2018 .
[136] Yi Li,et al. Estimating ground-level PM2.5 concentrations in Beijing, China using aerosol optical depth and parameters of the temperature inversion layer. , 2017, The Science of the total environment.
[137] C. Allery,et al. Application of POD-based dynamical systems to dispersion and deposition of particles in turbulent channel flow , 2014 .
[138] S. Schiavon,et al. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of IPCC the Intergovernmental Panel on Climate Change , 2014 .
[139] Shuyan Liu,et al. Urban Boundary Layer Height Characteristics and Relationship with Particulate Matter Mass Concentrations in Xi'an, Central China , 2013 .
[140] H. Mayer,et al. Variability of PM10 concentrations dependent on meteorological conditions , 2009 .
[141] Keith D. Hutchison,et al. Improving correlations between MODIS aerosol optical thickness and ground-based PM2.5 observations through 3D spatial analyses , 2008 .
[142] G. Leeuw,et al. Exploring the relation between aerosol optical depth and PM 2.5 at Cabauw, the Netherlands , 2008 .
[143] F. D. Leeuw,et al. Air pollution by ozone in Europe in 1998 and summer 1999 , 2000 .
[144] S. Pope. Turbulent Flows: FUNDAMENTALS , 2000 .
[145] E. Eloranta,et al. University of Wisconsin High Spectral Resolution Lidar , 1991 .
[146] M. Iqbal. An introduction to solar radiation , 1983 .