Atmospheric Measurement Techniques

Abstract. The twin Moderate resolution Imaging Spectroradiometer (MODIS) sensors have been flying on Terra since 2000 and Aqua since 2002, creating an extensive data set of global Earth observations. Here, we introduce the Collection 6 (C6) algorithm to retrieve aerosol optical depth (AOD) and aerosol size parameters from MODIS-observed spectral reflectance. While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. The C6 aerosol data set will be created from three separate retrieval algorithms that operate over different surface types. These are the two "Dark Target" (DT) algorithms for retrieving (1) over ocean (dark in visible and longer wavelengths) and (2) over vegetated/dark-soiled land (dark in the visible), plus the "Deep Blue" (DB) algorithm developed originally for retrieving (3) over desert/arid land (bright in the visible). Here, we focus on DT-ocean and DT-land (#1 and #2). We have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to ≤ 84°) to increase poleward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season/location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence on the surface reflectance, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time, we quantified how "upstream" changes to instrument calibration, land/sea masking and cloud masking will also impact the statistics of global AOD, and affect Terra and Aqua differently. For Aqua, all changes will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. We compared preliminary data to surface-based sun photometer data, and show that C6 should improve upon C5. C6 will include a merged DT/DB product over semi-arid land surfaces for reduced-gap coverage and better visualization, and new information about clouds in the aerosol field. Responding to the needs of the air quality community, in addition to the standard 10 km product, C6 will include a global (DT-land and DT-ocean) aerosol product at 3 km resolution.

Abstract. Aerosol black carbon is a unique primary tracer for combustion emissions. It affects the optical properties of the atmosphere and is recognized as the second most important anthropogenic forcing agent for climate change. It is the primary tracer for adverse health effects caused by air pollution. For the accurate determination of mass equivalent black carbon concentrations in the air and for source apportionment of the concentrations, optical measurements by filter-based absorption photometers must take into account the "filter loading effect". We present a new real-time loading effect compensation algorithm based on a two parallel spot measurement of optical absorption. This algorithm has been incorporated into the new Aethalometer model AE33. Intercomparison studies show excellent reproducibility of the AE33 measurements and very good agreement with post-processed data obtained using earlier Aethalometer models and other filter-based absorption photometers. The real-time loading effect compensation algorithm provides the high-quality data necessary for real-time source apportionment and for determination of the temporal variation of the compensation parameter k.

Abstract. Mobility particle size spectrometers often referred to as DMPS (Differential Mobility Particle Sizers) or SMPS (Scanning Mobility Particle Sizers) have found a wide range of applications in atmospheric aerosol research. However, comparability of measurements conducted world-wide is hampered by lack of generally accepted technical standards and guidelines with respect to the instrumental set-up, measurement mode, data evaluation as well as quality control. Technical standards were developed for a minimum requirement of mobility size spectrometry to perform long-term atmospheric aerosol measurements. Technical recommendations include continuous monitoring of flow rates, temperature, pressure, and relative humidity for the sheath and sample air in the differential mobility analyzer. We compared commercial and custom-made inversion routines to calculate the particle number size distributions from the measured electrical mobility distribution. All inversion routines are comparable within few per cent uncertainty for a given set of raw data. Furthermore, this work summarizes the results from several instrument intercomparison workshops conducted within the European infrastructure project EUSAAR (European Supersites for Atmospheric Aerosol Research) and ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) to determine present uncertainties especially of custom-built mobility particle size spectrometers. Under controlled laboratory conditions, the particle number size distributions from 20 to 200 nm determined by mobility particle size spectrometers of different design are within an uncertainty range of around ±10% after correcting internal particle losses, while below and above this size range the discrepancies increased. For particles larger than 200 nm, the uncertainty range increased to 30%, which could not be explained. The network reference mobility spectrometers with identical design agreed within ±4% in the peak particle number concentration when all settings were done carefully. The consistency of these reference instruments to the total particle number concentration was demonstrated to be less than 5%. Additionally, a new data structure for particle number size distributions was introduced to store and disseminate the data at EMEP (European Monitoring and Evaluation Program). This structure contains three levels: raw data, processed data, and final particle size distributions. Importantly, we recommend reporting raw measurements including all relevant instrument parameters as well as a complete documentation on all data transformation and correction steps. These technical and data structure standards aim to enhance the quality of long-term size distribution measurements, their comparability between different networks and sites, and their transparency and traceability back to raw data.

Abstract. The NASA Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL) on the NASA B200 aircraft has acquired extensive datasets of aerosol extinction (532 nm), aerosol optical depth (AOD) (532 nm), backscatter (532 and 1064 nm), and depolarization (532 and 1064 nm) profiles during 18 field missions that have been conducted over North America since 2006. The lidar measurements of aerosol intensive parameters (lidar ratio, depolarization, backscatter color ratio, and spectral depolarization ratio) are shown to vary with location and aerosol type. A methodology based on observations of known aerosol types is used to qualitatively classify the extensive set of HSRL aerosol measurements into eight separate types. Several examples are presented showing how the aerosol intensive parameters vary with aerosol type and how these aerosols are classified according to this new methodology. The HSRL-based classification reveals vertical variability of aerosol types during the NASA ARCTAS field experiment conducted over Alaska and northwest Canada during 2008. In two examples derived from flights conducted during ARCTAS, the HSRL classification of biomass burning smoke is shown to be consistent with aerosol types derived from coincident airborne in situ measurements of particle size and composition. The HSRL retrievals of AOD and inferences of aerosol types are used to apportion AOD to aerosol type; results of this analysis are shown for several experiments.

Abstract. In this paper we present recent achievements on developing and testing a tool to detect the composition of ambient ions in the mass/charge range up to 2000 Th. The instrument is an Atmospheric Pressure Interface Time-of-Flight Mass Spectrometer (APi-TOF, Tofwerk AG). Its mass accuracy is better than 0.002%, and the mass resolving power is 3000 Th/Th. In the data analysis, a new efficient Matlab based set of programs (tofTools) were developed, tested and used. The APi-TOF was tested both in laboratory conditions and applied to outdoor air sampling in Helsinki at the SMEAR III station. Transmission efficiency calibrations showed a throughput of 0.1–0.5% in the range 100–1300 Th for positive ions, and linearity over 3 orders of magnitude in concentration was determined. In the laboratory tests the APi-TOF detected sulphuric acid-ammonia clusters in high concentration from a nebulised sample illustrating the potential of the instrument in revealing the role of sulphuric acid clusters in atmospheric new particle formation. The APi-TOF features a high enough accuracy, resolution and sensitivity for the determination of the composition of atmospheric small ions although the total concentration of those ions is typically only 400–2000 cm−3. The atmospheric ions were identified based on their exact masses, utilizing Kendrick analysis and correlograms as well as narrowing down the potential candidates based on their proton affinities as well isotopic patterns. In Helsinki during day-time the main negative ambient small ions were inorganic acids and their clusters. The positive ions were more complex, the main compounds were (poly)alkyl pyridines and – amines. The APi-TOF provides a near universal interface for atmospheric pressure sampling, and this key feature will be utilized in future laboratory and field studies.

Abstract. The aerosol light absorption coefficient is an essential parameter involved in atmospheric radiation budget calculations. The Aethalometer (AE) has the great advantage of measuring the aerosol light absorption coefficient at several wavelengths, but the derived absorption coefficients are systematically too high when compared to reference methods. Up to now, four different correction algorithms of the AE absorption coefficients have been proposed by several authors. A new correction scheme based on these previously published methods has been developed, which accounts for the optical properties of the aerosol particles embedded in the filter. All the corrections have been tested on six datasets representing different aerosol types and loadings and include multi-wavelength AE and white-light AE. All the corrections have also been evaluated through comparison with a Multi-Angle Absorption Photometer (MAAP) for four datasets lasting between 6 months and five years. The modification of the wavelength dependence by the different corrections is analyzed in detail. The performances and the limits of all AE corrections are determined and recommendations are given.

Abstract. We report on the temperature dependence of ozone absorption cross-sections measured in our laboratory in the broad spectral range 213–1100 nm with a spectral resolution of 0.02–0.24 nm (full width at half maximum, FWHM) in the atmospherically relevant temperature range from 193 K to 293 K. The temperature dependence of ozone absorption cross-sections was established using measurements at eleven temperatures. This investigation is superior in terms of spectral range and number of considered temperatures compared to the previous studies. The methodology of the absolute broadband measurements, experimental procedures and spectra processing were described in our companion paper together with the associated uncertainty budget. In this paper, we report in detail on our data below room temperature and compare them with literature data using direct comparisons as well as the standard approach using a quadratic polynomial in temperature fitted to the cross-section data.

Abstract. Laboratory calibrations of the Cloud Droplet Probe (CDP) sample area and droplet sizing are performed using water droplets of known size, generated at a known rate. Although calibrations with PSL and glass beads were consistent with theoretical instrument response, liquid water droplet calibrations were not, and necessitated a 2 μm shift in the manufacturer's calibration. We show that much of this response shift may be attributable to a misalignment of the optics relative to the axis of the laser beam. Comparison with an independent measure of liquid water content (LWC) during in-flight operation suggests much greater biases in the droplet size and/or droplet concentration measured by the CDP than would be expected based on the laboratory calibrations. Since the bias in CDP-LWC is strongly concentration dependent, we hypothesize that this discrepancy is a result of coincidence, when two or more droplets pass through the CDP laser beam within a very short time. The coincidence error, most frequently resulting from the passage of one droplet outside and one inside the instrument sample area at the same time, is evaluated in terms of an "extended sample area" (SAE), the area in which individual droplets can affect the sizing detector without necessarily registering on the qualifier. SAE is calibrated with standardized water droplets, and used in a Monte-Carlo simulation to estimate the effect of coincidence on the measured droplet size distributions. The simulations show that extended coincidence errors are important for the CDP at droplet concentrations even as low as 200 cm−3, and these errors are necessary to explain the trend between calculated and measured LWC observed in liquid and mixed-phase clouds during the Aerosol, Radiation and Cloud Processes Affecting Arctic Climate (ARCPAC) study. We estimate from the simulations that 60% oversizing error and 50% undercounting error can occur at droplet concentrations exceeding 400 cm−3. Modification of the optical design of the CDP is currently being explored in an effort to reduce this coincidence bias.

Abstract. We describe a new algorithm for the retrieval of nitrogen dioxide (NO2) vertical columns from nadir-viewing satellite instruments. This algorithm (SP2) is the basis for the Version 2.1 OMI This algorithm (SP2) is the basis for the Version 2.1 Ozone Monitoring Instrument (OMI) NO2 Standard Product and features a novel method for separating the stratospheric and tropospheric columns. NO2 Standard Product and features a novel method for separating the stratospheric and tropospheric columns. The approach estimates the stratospheric NO2 directly from satellite data without using stratospheric chemical transport models or assuming any global zonal wave pattern. Tropospheric NO2 columns are retrieved using air mass factors derived from high-resolution radiative transfer calculations and a monthly climatology of NO2 profile shapes. We also present details of how uncertainties in the retrieved columns are estimated. The sensitivity of the retrieval to assumptions made in the stratosphere–troposphere separation is discussed and shown to be small, in an absolute sense, for most regions. We compare daily and monthly mean global OMI NO2 retrievals using the SP2 algorithm with those of the original Version 1 Standard Product (SP1) and the Dutch DOMINO product. The SP2 retrievals yield significantly smaller summertime tropospheric columns than SP1, particularly in polluted regions, and are more consistent with validation studies. SP2 retrievals are also relatively free of modeling artifacts and negative tropospheric NO2 values. In a reanalysis of an INTEX-B validation study, we show that SP2 largely eliminates an ~20% discrepancy that existed between OMI and independent in situ springtime NO2 SP1 measurements.

Abstract. Aerosol classification products from the NASA Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL-1) on the NASA B200 aircraft are compared with coincident V3.01 aerosol classification products from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on the CALIPSO satellite. For CALIOP, aerosol classification is a key input to the aerosol retrieval, and must be inferred using aerosol loading-dependent observations and location information. In contrast, HSRL-1 makes direct measurements of aerosol intensive properties, including the lidar ratio, that provide information on aerosol type. In this study, comparisons are made for 109 underflights of the CALIOP orbit track. We find that 62% of the CALIOP marine layers and 54% of the polluted continental layers agree with HSRL-1 classification results. In addition, 80% of the CALIOP desert dust layers are classified as either dust or dusty mix byHSRL-1. However, agreement is less for CALIOP smoke (13%) and polluted dust (35%) layers. Specific case studies are examined, giving insight into the performance of the CALIOP aerosol type algorithm. In particular, we find that the CALIOP polluted dust type is overused due to an attenuation-related depolarization bias. Furthermore, the polluted dust type frequently includes mixtures of dust plus marine aerosol. Finally, we find that CALIOP's identification of internal boundaries between different aerosol types in contact with each other frequently do not reflect the actual transitions between aerosol types accurately. Based on these findings, we give recommendations which may help to improve the CALIOP aerosol type algorithms.