Identifying chemical aerosol signatures using optical suborbital observations: how much can optical properties tell us about aerosol composition?

Improvements in air quality and Earth's climate predictions require improvements of the aerosol speciation in chemical transport models, using observational constraints. Aerosol speciation (e.g., organic aerosols, black carbon, sulfate, nitrate, ammonium, dust or sea salt) is typically determined using in situ instrumentation. Continuous, routine aerosol composition measurements from ground-based networks are not uniformly widespread over the globe. Satellites, on the other hand, can provide a maximum coverage of the horizontal and vertical atmosphere but observe aerosol optical properties (and not aerosol speciation) based on remote sensing instrumentation. Combinations of satellite-derived aerosol optical properties can inform on air mass aerosol types (AMTs). However, these AMTs are subjectively defined, might often be misclassified and are hard to relate to the critical parameters that need to be refined in models. &nbsp; In this paper, we derive AMTs that are more directly related to sources and hence to speciation. They are defined, characterized and derived using simultaneous in situ gas-phase, chemical and optical instruments on the same aircraft during the Study of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS, an airborne field campaign carried out over the US during the summer of 2013). We find distinct optical signatures for AMTs such as biomass burning (from agricultural or wildfires), biogenic and polluted dust. We find that all four AMTs, studied when prescribed using mostly airborne in situ gas measurements, can be successfully extracted from a few combinations of airborne in situ aerosol optical properties (e.g., extinction &Aring;ngstr&ouml;m exponent, absorption &Aring;ngstr&ouml;m exponent and real refractive index). However, we find that the optically based classifications for biomass burning from agricultural fires and polluted dust include a large percentage of misclassifications that limit the usefulness of results related to those classes. &nbsp; The technique and results presented in this study are suitable to develop a representative, robust and diverse source-based AMT database. This database could then be used for widespread retrievals of AMTs using existing and future remote sensing suborbital instruments/networks. Ultimately, it has the potential to provide a much broader observational aerosol dataset to evaluate chemical transport and air quality models than is currently available by direct in situ measurements. This study illustrates how essential it is to explore existing airborne datasets to bridge chemical and optical signatures of different AMTs, before the implementation of future spaceborne missions (e.g., the next generation of Earth Observing System (EOS) satellites addressing Aerosols, Cloud, Convection and Precipitation (ACCP) designated observables).</p

Sizing response of the Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) and Laser Aerosol Spectrometer (LAS) to changes in submicron aerosol composition and refractive index

We evaluate the sensitivity of the size calibrations of two commercially available, high-resolution optical particle sizers to changes in aerosol composition and complex refractive index (RI). The Droplet Measurement Technologies Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) and the TSI, Inc. Laser Aerosol Spectrometer (LAS) are two commonly used instruments for measuring the portion of the aerosol size distribution with diameters larger than nominally 60&ndash;90&thinsp;nm. Both instruments illuminate particles with a laser and relate the single-particle light scattering intensity and count rate measured over a wide range of angles to the size-dependent particle concentration. While the optical block geometry and flow system are similar for each instrument, a significant difference between the two models is the laser wavelength (1054&thinsp;nm for the UHSAS and 633&thinsp;nm for the LAS) and intensity (about 100 times higher for the UHSAS), which may affect the way each instrument sizes non-spherical or absorbing aerosols. Here, we challenge the UHSAS and LAS with laboratory-generated, mobility-size-classified aerosols of known chemical composition to quantify changes in the optical size response relative to that of ammonium sulfate (RI of 1.52+0i at 532&thinsp;nm) and NIST-traceable polystyrene latex spheres (PSLs with RI of 1.59+0i at 589&thinsp;nm). Aerosol inorganic salt species are chosen to cover the real refractive index range of 1.32 to 1.78, while chosen light-absorbing carbonaceous aerosols include fullerene soot, nigrosine dye, humic acid, and fulvic acid standards. The instrument response is generally in good agreement with the electrical mobility diameter. However, large undersizing deviations are observed for the low-refractive-index fluoride salts and the strongly absorbing nigrosine dye and fullerene soot particles. Polydisperse size distributions for both fresh and aged wildfire smoke aerosols from the recent Fire Influence on Regional to Global Environments Experiment and Air Quality (FIREX-AQ) and the Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) airborne campaigns show good agreement between both optical sizers and contemporaneous electrical mobility sizing and particle time-of-flight mass spectrometric measurements. We assess the instrument uncertainties by interpolating the laboratory response curves using previously reported RIs and size distributions for multiple aerosol type classifications. These results suggest that, while the optical sizers may underperform for strongly absorbing laboratory compounds and fresh tailpipe emissions measurements, sampling aerosols within the atmospherically relevant range of refractive indices are likely to be sized to better than &plusmn;10&thinsp;%&ndash;20&thinsp;% uncertainty over the submicron aerosol size range when using instruments calibrated with ammonium sulfate. Richard H. Moore1, Elizabeth B. Wiggins1,2, Adam T. Ahern3,4, Stephen Zimmerman1, Lauren Montgomery1, Pedro Campuzano Jost4,5, Claire E. Robinson1,6, Luke D. Ziemba1, Edward L. Winstead1,6, Bruce E. Anderson1, Charles A. Brock3, Matthew D. Brown1,6, Gao Chen1, Ewan C. Crosbie1,6, Hongyu Guo4,5, Jose L. Jimenez4,5, Carolyn E. Jordan1,7, Ming Lyu8, Benjamin A. Nault4,5,a, Nicholas E. Rothfuss9, Kevin J. Sanchez1,2, Melinda Schueneman4,5, Taylor J. Shingler1, Michael A. Shook1, Kenneth L. Thornhill1,6, Nicholas L. Wagner3,4, and Jian Wang9 1NASA Langley Research Center, Hampton, VA, USA 2NASA Postdoctoral Program, Universities Space Research Association, Columbia, MD, USA 3NOAA Chemical Sciences Laboratory, Boulder, CO, USA 4Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, CO, USA 5Department of Chemistry, University of Colorado, Boulder, CO, USA 6Science Systems and Applications, Inc., Hampton, VA, USA 7National Institute of Aerospace, Hampton, VA, USA 8Department of Chemistry, University of Alberta, Edmonton, AB, Canada​​​​​​​ 9Center for Aerosol Science and Engineering, Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA anow at: Center for Aerosol and Cloud Chemistry, Aerodyne Research, Inc., Billerica, MA, USA &nbsp;</p

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

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&ndash;June&nbsp;2016. Some of the largest aerosol mass concentrations were measured during a Chinese haze transport event (24&nbsp;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&ndash;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&thinsp;m2&thinsp;g&minus;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&thinsp;g&thinsp;cm&minus;3 in the model vs. observed average of 1.5&thinsp;g&thinsp;cm&minus;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&thinsp;%&ndash;28&thinsp;% modeled vs. 12&thinsp;% 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. Full List of Authors: Pablo E. Saide1,2, Meng Gao3, Zifeng Lu4, Daniel L. Goldberg4, David G. Streets4, Jung-Hun Woo5, Andreas Beyersdorf6, Chelsea A. Corr7, Kenneth L. Thornhill8,18, Bruce Anderson8, Johnathan W. Hair8, Amin R. Nehrir8, Glenn S. Diskin8, Jose L. Jimenez9, Benjamin A. Nault9, Pedro Campuzano-Jost9, Jack Dibb10, Eric Heim10, Kara D. Lamb11, Joshua P. Schwarz11, Anne E. Perring12, Jhoon Kim13, Myungje Choi13,14, Brent Holben15, Gabriele Pfister16, Alma Hodzic16, Gregory R. Carmichael17, Louisa Emmons16, and James H. Crawford8 1Department of Atmospheric and Oceanic Sciences, University of California &ndash; Los Angeles, Los Angeles, CA, USA 2Institute of the Environment and Sustainability, University of California &ndash; Los Angeles, Los Angeles, CA, USA 3Department of Geography, Hong Kong Baptist University, Hong Kong SAR, China 4Energy Systems Division, Argonne National Laboratory, Lemont, IL 60439, USA 5Department of Technology Fusion Engineering, Konkuk University, Seoul, South Korea 6Department of Chemistry &amp; Biochemistry, California State University San Bernardino, San Bernardino, CA, USA 7USDA UV-B Monitoring and Research Program, Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO, USA 8NASA Langley Research Center, Hampton, VA, USA 9Department of Chemistry, and Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA 10Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA 11Chemical Sciences Laboratory, Earth System Research Laboratories, Boulder, CO, USA 12Department of Chemistry, Colgate University, Hamilton, NY, USA 13Department of Atmospheric Sciences, Yonsei University, Seoul, 03722, Korea 14Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA 15NASA Goddard Space Flight Center, Greenbelt, Maryland, USA 16Atmospheric Chemistry Observations and Modeling Lab, National Center for Atmospheric Research, Boulder, CO, USA 17Center for Global &amp; Regional Environmental Research, University of Iowa, Iowa City, Iowa, USA 18Science Systems and Applications Inc., Hampton, VA USA </ul

Relating geostationary satellite measurements of aerosol optical depth (AOD) over East Asia to fine particulate matter (PM2.5): insights from the KORUS-AQ aircraft campaign and GEOS-Chem model simulations

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&ndash;PM2.5 relationship. Here we use the GEOS-Chem chemical transport model to analyze the critical variables determining the AOD&ndash;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&ndash;June 2016) with concurrent ground-based PM2.5 composition, PM10, and AERONET AOD measurements. The KORUS-AQ data show that 550&thinsp;nm AOD is mainly contributed by sulfate&ndash;nitrate&ndash;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&thinsp;&micro;m with geometric standard deviation of 1.4) and 20&thinsp;% 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&ndash;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. &nbsp; Full List of Authors Shixian Zhai1, Daniel J. Jacob1, Jared F. Brewer1, Ke Li1, Jonathan M. Moch1, Jhoon Kim2,3, Seoyoung Lee2, Hyunkwang Lim2, Hyun Chul Lee3, Su Keun Kuk3, Rokjin J. Park4, Jaein I. Jeong4, Xuan Wang5, Pengfei Liu6, Gan Luo7, Fangqun Yu7, Jun Meng8, Randall V. Martin9, Katherine R. Travis10, Johnathan W. Hair10, Bruce E. Anderson10, Jack E. Dibb11, Jose L. Jimenez12, Pedro Campuzano-Jost12, Benjamin A. Nault12,a, Jung-Hun Woo13, Younha Kim14, Qiang Zhang15, and Hong Liao16 1Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA 2Department of Atmospheric Sciences, Yonsei University, Seoul, Republic of Korea 3Samsung Particulate Matter Research Institute, Samsung Advanced Institute of Technology, 130 Samsung-ro, Yeongtong-gu, Suwon-si, Gyeonggi-do, Republic of Korea 4School of Earth and Environmental Sciences, Seoul National University, Seoul, Republic of Korea 5School of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China 6School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA 7Atmospheric Sciences Research Center, University at Albany, Albany, New York, USA 8Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, California, USA 9Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA 10NASA Langley Research Center, Hampton, VA, USA 11Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA 12Department of Chemistry, Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA 13Department of Civil and Environmental Engineering, Konkuk University, Seoul, Republic of Korea 14International Institute for Applied Systems Analysis (IIASA), 2361 Laxenburg, Austria 15Department of Earth System Science, Tsinghua University, Beijing, China 16Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, China anow at: Center for Aerosol and Cloud Chemistry, Aerodyne Research, Inc., Billerica, MA, USA &nbsp; &nbsp;</p

Simulating wildfire emissions and plume rise using geostationary satellite fire radiative power measurements: a case study of the 2019 Williams Flats fire

We use the Weather Research and Forecasting with Chemistry (WRF-Chem) model with new implementations of GOES-16 wildfire emissions and plume rise based on fire radiative power (FRP) to interpret aerosol observations during the 2019 NASA-NOAA FIREX-AQ field campaign and perform model evaluations. We compare simulated aerosol concentrations and optical properties against observations of black carbon aerosol from the NOAA Single Particle Soot Photometer (NOAA-SP2), organic aerosol from the CU High-Resolution Aerosol Mass Spectrometer (HR-AMS), and aerosol backscatter coefficients from the high-spectral-resolution lidar (HSRL) system. This study focuses on the Williams Flats fire in Washington, which was repeatedly sampled during four science flights by the NASA DC-8 (3&ndash;8 August 2019). The emissions and plume-rise methodologies are implemented following NOAA's operational High-Resolution Rapid Refresh coupled with Smoke (HRRR-Smoke) forecasting model. In addition, new GOES-16 FRP-based diurnal cycle functions are developed and incorporated into WRF-Chem. The FIREX-AQ observations represented a diverse set of sampled environments ranging from fresh/aged smoke from the Williams Flats fire to remnants of plumes transported over long distances. The Williams Flats fire resulted in significant aerosol enhancements during 3&ndash;8 August 2019, which were substantially underestimated by the standard version of WRF-Chem. The simulated black carbon (BC) and organic carbon (OC) concentrations increased between a factor of 92&ndash;125 (BC) and a factor of 28&ndash;78 (OC) with the new implementation compared to the standard WRF-Chem version. These increases resulted in better agreement with the FIREX-AQ airborne observations for BC and OC concentrations (particularly for fresh smoke sampling phases) and aerosol backscatter coefficients. The model still showed a low bias in simulating the aerosol loadings observed in aged plumes from Williams Flats. WRF-Chem with the FRP-based plume rise simulated similar plume heights to the standard plume-rise model in WRF-Chem. The simulated plume heights (for both versions) compared well with estimated plume heights using the HSRL measurements. Therefore, the better agreement with observations was mainly driven by the higher emissions in the FRP-based version. The model evaluations also highlighted the importance of accurately accounting for the wildfire diurnal cycle and including adequate representation of the underlying chemical mechanisms, both of which could significantly impact model forecasting performance. &nbsp;</p

Photochemical evolution of the 2013 California Rim Fire: synergistic impacts of reactive hydrocarbons and enhanced oxidants

Large wildfires influence regional atmospheric composition, but chemical complexity challenges model predictions of downwind impacts. Here, we elucidate key connections within gas-phase photochemistry and assess novel chemical processes via a case study of the 2013 California Rim Fire plume. Airborne in situ observations, acquired during the NASA Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) mission, illustrate the evolution of volatile organic compounds (VOCs), oxidants, and reactive nitrogen over 12&thinsp;h of atmospheric aging. Measurements show rapid formation of ozone and peroxyacyl nitrates (PNs), sustained peroxide production, and prolonged enhancements in oxygenated VOCs and nitrogen oxides (NOx). Observations and Lagrangian trajectories constrain a 0-D puff model that approximates plume photochemical history and provides a framework for evaluating process interactions. Simulations examine the effects of (1)&nbsp;previously unmeasured reactive VOCs identified in recent laboratory studies and (2)&nbsp;emissions and secondary production of nitrous acid (HONO). Inclusion of estimated unmeasured VOCs leads to a 250&thinsp;% increase in OH reactivity and a 70&thinsp;% increase in radical production via oxygenated VOC photolysis. HONO amplifies radical cycling and serves as a downwind NOx source, although impacts depend on how HONO is introduced. The addition of initial HONO (representing primary emissions) or particulate nitrate photolysis amplifies ozone production, while heterogeneous conversion of NO2 suppresses ozone formation. Analysis of radical initiation rates suggests that oxygenated VOC photolysis is a major radical source, exceeding HONO photolysis when averaged over the first 2&thinsp;h of aging. Ozone production chemistry transitions from VOC&nbsp;sensitive to NOx sensitive within the first hour of plume aging, with both peroxide and organic nitrate formation contributing significantly to radical termination. To simulate smoke plume chemistry accurately, models should simultaneously account for the full reactive VOC pool and all relevant oxidant sources. &nbsp;</p

Integration of airborne and ground observations of nitryl chloride in the Seoul metropolitan area and the implications on regional oxidation capacity during KORUS-AQ 2016

Nitryl chloride (ClNO2) is a radical reservoir species that releases chlorine radicals upon photolysis. An integrated analysis of the impact of ClNO2 on regional photochemistry in the Seoul metropolitan area (SMA) during the Korea&ndash;United States Air Quality Study (KORUS-AQ) 2016 field campaign is presented. Comprehensive multiplatform observations were conducted aboard the NASA DC-8 and at two ground sites (Olympic Park, OP; Taehwa Research Forest, TRF), representing an urbanized area and a forested suburban region, respectively. Positive correlations between daytime Cl2 and ClNO2 were observed at both sites, the slope of which was dependent on O3 levels. The possible mechanisms are explored through box model simulations constrained with observations. The overall diurnal variations in ClNO2 at both sites appeared similar but the nighttime variations were systematically different. For about half of the observation days at the OP site the level of ClNO2 increased at sunset but rapidly decreased at around midnight. On the other hand, high levels were observed throughout the night at the TRF site. Significant levels of ClNO2 were observed at both sites for 4&ndash;5&thinsp;h after sunrise. Airborne observations, box model calculations, and back-trajectory analysis consistently show that these high levels of ClNO2 in the morning are likely from vertical or horizontal transport of air masses from the west. Box model results show that chlorine-radical-initiated chemistry can impact the regional photochemistry by elevating net chemical production rates of ozone by &sim;25&thinsp;% in the morning.</p

Urban influence on the concentration and composition of submicron particulate matter in central Amazonia

An understanding of how anthropogenic emissions affect the concentrations and composition of airborne particulate matter (PM) is fundamental to quantifying the influence of human activities on climate and air quality. The central Amazon Basin, especially around the city of Manaus, Brazil, has experienced rapid changes in the past decades due to ongoing urbanization. Herein, changes in the concentration and composition of submicron PM due to pollution downwind of the Manaus metropolitan region are reported as part of the GoAmazon2014/5 experiment. A high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and a suite of other gas- and particle-phase instruments were deployed at the T3 research site, 70&thinsp;km downwind of Manaus, during the wet season. At this site, organic components represented 79&plusmn;7&thinsp;% of the non-refractory PM1 mass concentration on average, which was in the same range as several upwind sites. However, the organic PM1 was considerably more oxidized at T3 compared to upwind measurements. Positive-matrix factorization (PMF) was applied to the time series of organic mass spectra collected at the T3 site, yielding three factors representing secondary processes (73&plusmn;15&thinsp;% of total organic mass concentration) and three factors representing primary anthropogenic emissions (27&plusmn;15&thinsp;%). Fuzzy c-means clustering (FCM) was applied to the afternoon time series of concentrations of NOy, ozone, total particle number, black carbon, and sulfate. Four clusters were identified and characterized by distinct air mass origins and particle compositions. Two clusters, Bkgd-1 and Bkgd-2, were associated with background conditions. Bkgd-1 appeared to represent near-field atmospheric PM production and oxidation of a day or less. Bkgd-2 appeared to represent material transported and oxidized for two or more days, often with out-of-basin contributions. Two other clusters, Pol-1 and Pol-2, represented the Manaus influence, one apparently associated with the northern region of Manaus and the other with the southern region of the city. A composite of the PMF and FCM analyses provided insights into the anthropogenic effects on PM concentration and composition. The increase in mass concentration of submicron PM ranged from 25&thinsp;% to 200&thinsp;% under polluted compared with background conditions, including contributions from both primary and secondary PM. Furthermore, a comparison of PMF factor loadings for different clusters suggested a shift in the pathways of PM production under polluted conditions. Nitrogen oxides may have played a critical role in these shifts. Increased concentrations of nitrogen oxides can shift pathways of PM production from HO2-dominant to NO-dominant as well as increase the concentrations of oxidants in the atmosphere. Consequently, the oxidation of biogenic and anthropogenic precursor gases as well as the oxidative processing of preexisting atmospheric PM can be accelerated. This combined set of results demonstrates the susceptibility of atmospheric chemistry, air quality, and associated climate forcing to anthropogenic perturbations over tropical forests.</p

Contributions of biomass-burning, urban, and biogenic emissions to the concentrations and light-absorbing properties of particulate matter in central Amazonia during the dry season

Urbanization and deforestation have important impacts on atmospheric particulate matter (PM) over Amazonia. This study presents observations and analysis of PM1 concentration, composition, and optical properties in central Amazonia during the dry season, focusing on the anthropogenic impacts. The primary study site was located 70 km downwind of Manaus, a city of over 2 million people in Brazil, as part of the GoAmazon 2014/5 experiment. A high-resolution time-of-flight aerosol mass spectrometer (AMS) provided data on PM1 composition, and aethalometer measurements were used to derive the absorption coefficient babs,BrC of brown carbon (BrC) at 370 nm. Non-refractory PM1 mass concentrations averaged 12.2 &micro; g m-3 at the primary study site, dominated by organics (83%), followed by sulfate (11 %). A decrease inbabs,BrC was observed as the mass concentration of nitrogen-containing organic compounds decreased and the organic PM1 O:C ratio increased,suggesting atmospheric bleaching of the BrC components. The organic PM1 was separated into six different classes by positive-matrix factorization(PMF), and the mass absorption efficiency Eabs associated with each factor was estimated through multivariate linear regression ofbabs,BrC on the factor loadings. The largest Eabs values were associated with urban (2.04&plusmn;0.14 m2 g-1) and biomass-burning(0.82&plusmn;0.04 to 1.50&plusmn;0.07 m2 g-1 ) sources. Together, these sources contributed at least 80 % ofbabs,BrC while accounting for 30 % to 40 % of the organic PM1 mass concentration. In addition, a comparison of organic PM1 composition between wet and dry seasons revealed that only part of the 9-fold increase in mass concentration between the seasons can be attributed to biomass burning. Biomass-burning factor loadings increased by 30-fold,elevating its relative contribution to organic PM1 from about 10 % in the wet season to 30 % in the dry season. However, most of the PM1 mass (&gt;60 %) in both seasons was accounted for by biogenic secondary organic sources, which in turn showed an 8-fold seasonal increase in factor loadings. A combination of decreased wet deposition and increased emissions and oxidant concentrations, as well as a positive feedback on larger mass concentrations are thought to play a role in the observed increases. Furthermore, fuzzy c -means clustering identified three clusters, namely "baseline", "event", and "urban" to represent different pollution influences during the dry season. The baseline cluster,representing the dry season background, was associated with a mean mass concentration of 9&plusmn;3 &micro; g m-3 . This concentration increased on average by 3 &micro; g m-3 for both the urban and the event clusters.The event cluster, representing an increased influence of biomass burning and long-range transport of African volcanic emissions, was characterized by remarkably high sulfate concentrations. The urban cluster, representing the influence of Manaus emissions on top of the baseline, was characterized by an organic PM1 composition that differed from the other two clusters.The differences discussed suggest a shift in oxidation pathways as well as an accelerated oxidation cycle due to urban emissions, in agreement with findings for the wet season.</p

Real-time measurement of sodium in single aerosol particles by flame emission: laboratory characterization

A flame emission aerosol sodium detector (ASD) has been developed to study the distribution of seasalt in individual marine aerosol droplets. The instrument detects sodium via D-line emission in a fuel-rich, laminar, hydrogen/oxygen/nitrogen flame. Laboratory studies with synthetic monodisperse aerosols were carried out in order to characterize the sensitivity, precision, and linearity of the technique. Experiments were also carried out with aerosols generated from mixed salt solutions and seawater in order to determine whether ionic or other matrix effects lead to interference. The ASD has a linear response function for NaCl aerosol particles from 100 nm to 2.0μm in diameter. The precision of sodium mass measurements is on the order of ±3% standard error on replicate measurements, with a quantitative response to the sodium content of a single aerosol particle that is independent of the chemical composition of the particle, i.e. anions, cations, seawater. No interferences were found with major ions in seawater and common atmospheric aerosols. These experiments demonstrate a detection limit equivalent to a 100 nm diameter dry 100% NaCl aerosol. Copyright © 2001 Elsevier Science Ltd