Showing papers in "Atmospheric Measurement Techniques in 2019"

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

Abstract: The Aerosol Robotic Network (AERONET) has provided highly accurate, ground-truth measurements of the aerosol optical depth (AOD) using Cimel Electronique Sun–sky radiometers for more than 25 years In Version 2 (V2) of the AERONET database, the near-real-time AOD was semiautomatically quality controlled utilizing mainly cloud-screening methodology, while additional AOD data contaminated by clouds or affected by instrument anomalies were removed manually before attaining quality-assured status (Level 20) The large growth in the number of AERONET sites over the past 25 years resulted in significant burden to the manual quality control of millions of measurements in a consistent manner The AERONET Version 3 (V3) algorithm provides fully automatic cloud screening and instrument anomaly quality controls All of these new algorithm updates apply to near-real-time data as well as post-field-deployment processed data, and AERONET reprocessed the database in 2018 A full algorithm redevelopment provided the opportunity to improve data inputs and corrections such as unique filter-specific temperature characterizations for all visible and near-infrared wavelengths, updated gaseous and water vapor absorption coefficients, and ancillary data sets The Level 20 AOD quality-assured data set is now available within a month after post-field calibration, reducing the lag time from up to several months Near-real-time estimated uncertainty is determined using data qualified as V3 Level 20 AOD and considering the difference between the AOD computed with the pre-field calibration and AOD computed with pre-field and post-field calibration This assessment provides a near-real-time uncertainty estimate for which average differences of AOD suggest a +002 bias and one sigma uncertainty of 002, spectrally, but the bias and uncertainty can be significantly larger for specific instrument deployments Long-term monthly averages analyzed for the entire V3 and V2 databases produced average differences (V3–V2) of + 0002 with a ± 002 SD (standard deviation), yet monthly averages calculated using time-matched observations in both databases were analyzed to compute an average difference of −0002 with a ±0004 SD The high statistical agreement in multiyear monthly averaged AOD validates the advanced automatic data quality control algorithms and suggests that migrating research to the V3 database will corroborate most V2 research conclusions and likely lead to more accurate results in some cases

The OCO-3 mission: measurement objectives and expected performance based on 1 year of simulated data

Abstract: . The Orbiting Carbon Observatory-3 (OCO-3) is NASA's next instrument dedicated to extending the record of the dry-air mole fraction of column carbon dioxide ( XCO2 ) and solar-induced fluorescence (SIF) measurements from space. The current schedule calls for a launch from the Kennedy Space Center no earlier than April 2019 via a Space-X Falcon 9 and Dragon capsule. The instrument will be installed as an external payload on the Japanese Experimental Module Exposed Facility (JEM-EF) of the International Space Station (ISS) with a nominal mission lifetime of 3 years. The precessing orbit of the ISS will allow for viewing of the Earth at all latitudes less than approximately 52 ∘ , with a ground repeat cycle that is much more complicated than the polar-orbiting satellites that so far have carried all of the instruments capable of measuring carbon dioxide from space. The grating spectrometer at the core of OCO-3 is a direct copy of the OCO-2 spectrometer, which was launched into a polar orbit in July 2014. As such, OCO-3 is expected to have similar instrument sensitivity and performance characteristics to OCO-2, which provides measurements of XCO2 with precision better than 1 ppm at 3 Hz, with each viewing frame containing eight footprints approximately 1.6 km by 2.2 km in size. However, the physical configuration of the instrument aboard the ISS, as well as the use of a new pointing mirror assembly (PMA), will alter some of the characteristics of the OCO-3 data compared to OCO-2. Specifically, there will be significant differences from day to day in the sampling locations and time of day. In addition, the flexible PMA system allows for a much more dynamic observation-mode schedule. This paper outlines the science objectives of the OCO-3 mission and, using a simulation of 1 year of global observations, characterizes the spatial sampling, time-of-day coverage, and anticipated data quality of the simulated L1b. After application of cloud and aerosol prescreening, the L1b radiances are run through the operational L2 full physics retrieval algorithm, as well as post-retrieval filtering and bias correction, to examine the expected coverage and quality of the retrieved XCO2 and to show how the measurement objectives are met. In addition, results of the SIF from the IMAP–DOAS algorithm are analyzed. This paper focuses only on the nominal nadir–land and glint–water observation modes, although on-orbit measurements will also be made in transition and target modes, similar to OCO-2, as well as the new snapshot area mapping (SAM) mode.

How bias correction goes wrong: measurement of X CO 2 affected by erroneous surface pressure estimates

Abstract: . All measurements of X CO 2 from space have systematic errors. To reduce a large fraction of these errors, a bias correction is applied to X CO 2 retrieved from GOSAT and OCO-2 spectra using the ACOS retrieval algorithm. The bias correction uses, among other parameters, the surface pressure difference between the retrieval and the meteorological reanalysis. Relative errors in the surface pressure estimates, however, propagate nearly 1:1 into relative errors in bias-corrected X CO 2 . For OCO-2, small errors in the knowledge of the pointing of the observatory (up to ∼130 arcsec ) introduce a bias in X CO 2 in regions with rough topography. Erroneous surface pressure estimates are also caused by a coding error in ACOS version 8, sampling meteorological analyses at wrong times (up to 3 h after the overpass time). Here, we derive new geolocations for OCO-2's eight footprints and show how using improved knowledge of surface pressure estimates in the bias correction reduces errors in OCO-2's v9 X CO 2 data.

Evaluating the performance of five different chemical ionization techniques for detecting gaseous oxygenated organic species

Abstract: . The impact of aerosols on climate and air quality remains poorly understood due to multiple factors. One of the current limitations is the incomplete understanding of the contribution of oxygenated products, generated from the gas-phase oxidation of volatile organic compounds (VOCs), to aerosol formation. Indeed, atmospheric gaseous chemical processes yield thousands of (highly) oxygenated species, spanning a wide range of chemical formulas, functional groups and, consequently, volatilities. While recent mass spectrometric developments have allowed extensive on-line detection of a myriad of oxygenated organic species, playing a central role in atmospheric chemistry, the detailed quantification and characterization of this diverse group of compounds remains extremely challenging. To address this challenge, we evaluated the capability of current state-of-the-art mass spectrometers equipped with different chemical ionization sources to detect the oxidation products formed from α -Pinene ozonolysis under various conditions. Five different mass spectrometers were deployed simultaneously for a chamber study. Two chemical ionization atmospheric pressure interface time-of-flight mass spectrometers (CI-APi-TOF) with nitrate and amine reagent ion chemistries and an iodide chemical ionization time-of-flight mass spectrometer (TOF-CIMS) were used. Additionally, a proton transfer reaction time-of-flight mass spectrometer (PTR-TOF 8000) and a new “vocus” PTR-TOF were also deployed. In the current study, we compared around 1000 different compounds between each of the five instruments, with the aim of determining which oxygenated VOCs (OVOCs) the different methods were sensitive to and identifying regions where two or more instruments were able to detect species with similar molecular formulae. We utilized a large variability in conditions (including different VOCs, ozone, NOx and OH scavenger concentrations) in our newly constructed atmospheric simulation chamber for a comprehensive correlation analysis between all instruments. This analysis, combined with estimated concentrations for identified molecules in each instrument, yielded both expected and surprising results. As anticipated based on earlier studies, the PTR instruments were the only ones able to measure the precursor VOC, the iodide TOF-CIMS efficiently detected many semi-volatile organic compounds (SVOCs) with three to five oxygen atoms, and the nitrate CI-APi-TOF was mainly sensitive to highly oxygenated organic (O > 5) molecules (HOMs). In addition, the vocus showed good agreement with the iodide TOF-CIMS for the SVOC, including a range of organonitrates. The amine CI-APi-TOF agreed well with the nitrate CI-APi-TOF for HOM dimers. However, the loadings in our experiments caused the amine reagent ion to be considerably depleted, causing nonlinear responses for monomers. This study explores and highlights both benefits and limitations of currently available chemical ionization mass spectrometry instrumentation for characterizing the wide variety of OVOCs in the atmosphere. While specifically shown for the case of α -Pinene ozonolysis, we expect our general findings to also be valid for a wide range of other VOC–oxidant systems. As discussed in this study, no single instrument configuration can be deemed better or worse than the others, as the optimal instrument for a particular study ultimately depends on the specific target of the study.

Development of a general calibration model and long-term performance evaluation of low-cost sensors for air pollutant gas monitoring

Abstract: . Assessing the intracity spatial distribution and temporal variability in air quality can be facilitated by a dense network of monitoring stations. However, the cost of implementing such a network can be prohibitive if traditional high-quality, expensive monitoring systems are used. To this end, the Real-time Affordable Multi-Pollutant (RAMP) monitor has been developed, which can measure up to five gases including the criteria pollutant gases carbon monoxide (CO), nitrogen dioxide ( NO2 ), and ozone ( O3 ), along with temperature and relative humidity. This study compares various algorithms to calibrate the RAMP measurements including linear and quadratic regression, clustering, neural networks, Gaussian processes, and hybrid random forest–linear regression models. Using data collected by almost 70 RAMP monitors over periods ranging up to 18 months, we recommend the use of limited quadratic regression calibration models for CO, neural network models for NO, and hybrid models for NO2 and O3 for any low-cost monitor using electrochemical sensors similar to those of the RAMP. Furthermore, generalized calibration models may be used instead of individual models with only a small reduction in overall performance. Generalized models also transfer better when the RAMP is deployed to other locations. For long-term deployments, it is recommended that model performance be re-evaluated and new models developed periodically, due to the noticeable change in performance over periods of a year or more. This makes generalized calibration models even more useful since only a subset of deployed monitors are needed to build these new models. These results will help guide future efforts in the calibration and use of low-cost sensor systems worldwide.

An extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF) for online measurement of atmospheric aerosol particles

Abstract: . Real-time, online measurements of atmospheric organic aerosol (OA) composition are an essential tool for determining the emissions sources and physicochemical processes governing aerosol effects on climate and health. However, the reliance of current techniques on thermal desorption, hard ionization, and/or separated collection/analysis stages introduces significant uncertainties into OA composition measurements, hindering progress towards these goals. To address this gap, we present a novel, field-deployable extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF), which provides online, near-molecular (i.e., molecular formula) OA measurements at atmospherically relevant concentrations without analyte fragmentation or decomposition. Aerosol particles are continuously sampled into the EESI-TOF, where they intersect a spray of charged droplets generated by a conventional electrospray probe. Soluble components are extracted and then ionized as the droplets are evaporated. The EESI-TOF achieves a linear response to mass, with detection limits on the order of 1 to 10 ng m −3 in 5 s for typical atmospherically relevant compounds. In contrast to conventional electrospray systems, the EESI-TOF response is not significantly affected by a changing OA matrix for the systems investigated. A slight decrease in sensitivity in response to increasing absolute humidity is observed for some ions. Although the relative sensitivities to a variety of commercially available organic standards vary by more than a factor of 30, the bulk sensitivity to secondary organic aerosol generated from individual precursor gases varies by only a factor of 15. Further, the ratio of compound-by-compound sensitivities between the EESI-TOF and an iodide adduct FIGAERO-I-CIMS varies by only ±50 %, suggesting that EESI-TOF mass spectra indeed reflect the actual distribution of detectable compounds in the particle phase. Successful deployments of the EESI-TOF for laboratory environmental chamber measurements, ground-based ambient sampling, and proof-of-concept measurements aboard a research aircraft highlight the versatility and potential of the EESI-TOF system.

Discriminating between clouds and aerosols in the CALIOP version 4.1 data products

Abstract: . The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Operations (CALIPSO) mission released version 4.1 (V4) of their lidar level 2 cloud and aerosol data products in November 2016. These new products were derived from the CALIPSO V4 lidar level 1 data, in which the calibration of the measured backscatter data at both 532 and 1064 nm was significantly improved. This paper describes updates to the V4 level 2 cloud–aerosol discrimination (CAD) algorithm that more accurately differentiate between clouds and aerosols throughout the Earth's atmosphere. The level 2 data products are improved with new CAD probability density functions (PDFs) that were developed to accommodate extensive calibration changes in the level 1 data. To enable more reliable identification of aerosol layers lofted into the upper troposphere and lower stratosphere, the CAD training dataset used in the earlier data releases was expanded to include stratospheric layers and representative examples of volcanic aerosol layers. The generic “stratospheric layer” classification reported in previous versions has been eliminated in V4, and cloud–aerosol classification is now performed on all layers detected everywhere from the surface to 30 km. Cloud–aerosol classification has been further extended to layers detected at single-shot resolution, which were previously classified by default as clouds. In this paper, we describe the underlying rationale used in constructing the V4 PDFs and assess the performance of the V4 CAD algorithm in the troposphere and stratosphere. Previous misclassifications of lofted dust and smoke in the troposphere have been largely improved, and volcanic aerosol layers and aerosol layers in the stratosphere are now being properly classified. CAD performance for single-shot layer detections is also evaluated. Most of the single-shot layers classified as aerosol occur within the dust belt, as may be expected. Due to changes in the 532 nm calibration coefficients, the V4 feature finder detects ∼9.0 % more features at night and ∼2.5 % more during the day. These features are typically weakly scattering and classified about equally as clouds and aerosols. For those tropospheric layers detected in both V3 and V4, the CAD classifications of more than 95 % of all cloud and daytime aerosol layers remain unchanged, as do the classifications of ∼89 % of nighttime aerosol layers. Overall, the nighttime net cloud and aerosol fractions remain unchanged from V3 to V4, but the daytime net aerosol fraction is increased by about 2 % and the daytime net cloud fraction is decreased by about 2 %.

Building the COllaborative Carbon Column Observing Network (COCCON): long-term stability and ensemble performance of the EM27/SUN Fourier transform spectrometer

Abstract: . In a 3.5-year long study, the long-term performance of a mobile, solar absorption Bruker EM27/SUN spectrometer, used for greenhouse gas observations, is checked with respect to a co-located reference Bruker IFS 125HR spectrometer, which is part of the Total Carbon Column Observing Network (TCCON). We find that the EM27/SUN is stable on timescales of several years; the drift per year between the EM27/SUN and the official TCCON product is 0.02 ppmv for X CO2 and 0.9 ppbv for X CH4 , which is within the 1 σ precision of the comparison, 0.6 ppmv for X CO2 and 4.3 ppbv for X CH4 . The bias between the two data sets is 3.9 ppmv for X CO2 and 13.0 ppbv for X CH4 . In order to avoid sensitivity-dependent artifacts, the EM27/SUN is also compared to a truncated IFS 125HR data set derived from full-resolution TCCON interferograms. The drift is 0.02 ppmv for X CO2 and 0.2 ppbv for X CH4 per year, with 1 σ precisions of 0.4 ppmv for X CO2 and 1.4 ppbv for X CH4 , respectively. The bias between the two data sets is 0.6 ppmv for X CO2 and 0.5 ppbv for X CH4 . With the presented long-term stability, the EM27/SUN qualifies as an useful supplement to the existing TCCON network in remote areas. To achieve consistent performance, such an extension requires careful testing of any spectrometers involved by application of common quality assurance measures. One major aim of the COllaborative Carbon Column Observing Network (COCCON) infrastructure is to provide these services to all EM27/SUN operators. In the framework of COCCON development, the performance of an ensemble of 30 EM27/SUN spectrometers was tested and found to be very uniform, enhanced by the centralized inspection performed at the Karlsruhe Institute of Technology prior to deployment. Taking into account measured instrumental line shape parameters for each spectrometer, the resulting average bias across the ensemble with respect to the reference EM27/SUN used in the long-term study in X CO2 is 0.20 ppmv, while it is 0.8 ppbv for X CH4 . The average standard deviation of the ensemble is 0.13 ppmv for X CO2 and 0.6 ppbv for X CH4 . In addition to the robust metric based on absolute differences, we calculate the standard deviation among the empirical calibration factors. The resulting 2 σ uncertainty is 0.6 ppmv for X CO2 and 2.2 ppbv for X CH4 . As indicated by the executed long-term study on one device presented here, the remaining empirical calibration factor deduced for each individual instrument can be assumed constant over time. Therefore the application of these empirical factors is expected to further improve the EM27/SUN network conformity beyond the scatter among the empirical calibration factors reported above.

Automatic pollen recognition with the Rapid-E particle counter: the first-level procedure, experience and next steps

Abstract: . Pollen-induced allergies are among the most prevalent non-contagious diseases, with about a quarter of the European population being sensitive to various atmospheric bioaerosols. In most European countries, pollen information is based on a weekly-cycle Hirst-type pollen trap method. This method is labour-intensive and requires narrow specialized abilities and substantial time, so that the pollen data are always delayed and subject to sampling- and counting-related uncertainties. Emerging new approaches to automatic pollen monitoring can, in principle, allow for real-time availability of the data with no human involvement. The goal of the current paper is to evaluate the capabilities of the new Plair Rapid-E pollen monitor and to construct a first-level pollen recognition algorithm. The evaluation was performed for three devices located in Lithuania, Serbia and Switzerland, with independent calibration data and classification algorithms. The Rapid-E output data include multi-angle scattering images and the fluorescence spectra recorded at several times for each particle reaching the device. Both modalities of the Rapid-E output were treated with artificial neural networks (ANNs) and the results were combined to obtain the pollen type. For the first classification experiment, the monitor was challenged with a large variety of pollen types and the quality of many-to-many classification was evaluated. It was shown that in this case, both scattering- and fluorescence-based recognition algorithms fall short of acceptable quality. The combinations of these algorithms performed better, exceeding 80 % accuracy for 5 out of 11 species. Fluorescence spectra showed similarities among different species, ending up with three well-resolved groups: (Alnus, Corylus, Betula and Quercus), (Salix and Populus) and (Festuca, Artemisia and Juniperus). Within these groups, pollen is practically indistinguishable for the first-level recognition procedure. Construction of multistep algorithms with sequential discrimination of pollen inside each group seems to be one of the possible ways forward. In order to connect the classification experiment to existing technology, a short comparison with the Hirst measurements is presented and the issue of false positive pollen detections by Rapid-E is discussed.

TROPOMI/S5P total ozone column data: global ground-based validation and consistency with other satellite missions

Abstract: . In October 2017, the Sentinel-5 Precursor (S5P) mission was launched, carrying the TROPOspheric Monitoring Instrument (TROPOMI), which provides a daily global coverage at a spatial resolution as high as 7 km × 3.5 km and is expected to extend the European atmospheric composition record initiated with GOME/ERS-2 in 1995, enhancing our scientific knowledge of atmospheric processes with its unprecedented spatial resolution. Due to the ongoing need to understand and monitor the recovery of the ozone layer, as well as the evolution of tropospheric pollution, total ozone remains one of the leading species of interest during this mission. In this work, the TROPOMI near real time (NRTI) and offline (OFFL) total ozone column (TOC) products are presented and compared to daily ground-based quality-assured Brewer and Dobson TOC measurements deposited in the World Ozone and Ultraviolet Radiation Data Centre (WOUDC). Additional comparisons to individual Brewer measurements from the Canadian Brewer Network and the European Brewer Network (Eubrewnet) are performed. Furthermore, twilight zenith-sky measurements obtained with ZSL-DOAS (Zenith Scattered Light Differential Optical Absorption Spectroscopy) instruments, which form part of the SAOZ network (Systeme d'Analyse par Observation Zenitale), are used for the validation. The quality of the TROPOMI TOC data is evaluated in terms of the influence of location, solar zenith angle, viewing angle, season, effective temperature, surface albedo and clouds. For this purpose, globally distributed ground-based measurements have been utilized as the background truth. The overall statistical analysis of the global comparison shows that the mean bias and the mean standard deviation of the percentage difference between TROPOMI and ground-based TOC is within 0 –1.5 % and 2.5 %–4.5 %, respectively. The mean bias that results from the comparisons is well within the S5P product requirements, while the mean standard deviation is very close to those limits, especially considering that the statistics shown here originate both from the satellite and the ground-based measurements. Additionally, the TROPOMI OFFL and NRTI products are evaluated against already known spaceborne sensors, namely, the Ozone Mapping Profiler Suite, on board the Suomi National Polar-orbiting Partnership (OMPS/Suomi-NPP), NASA v2 TOCs, and the Global Ozone Monitoring Experiment 2 (GOME-2), on board the Metop-A (GOME-2/Metop-A) and Metop-B (GOME-2/Metop-B) satellites. This analysis shows a very good agreement for both TROPOMI products with well-established instruments, with the absolute differences in mean bias and mean standard deviation being below +0.7 % and 1 %, respectively. These results assure the scientific community of the good quality of the TROPOMI TOC products during its first year of operation and enhance the already prevalent expectation that TROPOMI/S5P will play a very significant role in the continuity of ozone monitoring from space.

Validation, comparison, and integration of GOCI, AHI, MODIS, MISR, and VIIRS aerosol optical depth over East Asia during the 2016 KORUS-AQ campaign

Abstract: . Recently launched multichannel geostationary Earth orbit (GEO) satellite sensors, such as the Geostationary Ocean Color Imager (GOCI) and the Advanced Himawari Imager (AHI), provide aerosol products over East Asia with high accuracy, which enables the monitoring of rapid diurnal variations and the transboundary transport of aerosols. Most aerosol studies to date have used low Earth orbit (LEO) satellite sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging Spectroradiometer (MISR), with a maximum of one or two overpass daylight times per day from midlatitudes to low latitudes. Thus, the demand for new GEO observations with high temporal resolution and improved accuracy has been significant. In this study the latest versions of aerosol optical depth (AOD) products from three LEO sensors – MODIS (Dark Target, Deep Blue, and MAIAC), MISR, and the Visible/Infrared Imager Radiometer Suite (VIIRS), along with two GEO sensors (GOCI and AHI), are validated, compared, and integrated for a period during the Korea–United States Air Quality Study (KORUS-AQ) field campaign from 1 May to 12 June 2016 over East Asia. The AOD products analyzed here generally have high accuracy with high R (0.84–0.93) and low RMSE (0.12–0.17), but their error characteristics differ according to the use of several different surface-reflectance estimation methods. High-accuracy near-real-time GOCI and AHI measurements facilitate the detection of rapid AOD changes, such as smoke aerosol transport from Russia to Japan on 18–21 May 2016, heavy pollution transport from China to the Korean Peninsula on 25 May 2016, and local emission transport from the Seoul Metropolitan Area to the Yellow Sea in South Korea on 5 June 2016. These high-temporal-resolution GEO measurements result in more representative daily AOD values and make a greater contribution to a combined daily AOD product assembled by median value selection with a 0.5 ∘ × 0.5 ∘ grid resolution. The combined AOD is spatially continuous and has a greater number of pixels with high accuracy (fraction within expected error range of 0.61) than individual products. This study characterizes aerosol measurements from LEO and GEO satellites currently in operation over East Asia, and the results presented here can be used to evaluate satellite measurement bias and air quality models.

Characterising low-cost sensors in highly portable platforms to quantify personal exposure in diverse environments.

Abstract: . The inaccurate quantification of personal exposure to air pollution introduces error and bias in health estimations, severely limiting causal inference in epidemiological research worldwide. Rapid advancements in affordable, miniaturised air pollution sensor technologies offer the potential to address this limitation by capturing the high variability of personal exposure during daily life in large-scale studies with unprecedented spatial and temporal resolution. However, concerns remain regarding the suitability of novel sensing technologies for scientific and policy purposes. In this paper we characterise the performance of a portable personal air quality monitor (PAM) that integrates multiple miniaturised sensors for nitrogen oxides ( NOx ), carbon monoxide (CO), ozone ( O3 ) and particulate matter (PM) measurements along with temperature, relative humidity, acceleration, noise and GPS sensors. Overall, the air pollution sensors showed high reproducibility (mean R ‾ 2 = 0.93 , min–max: 0.80–1.00) and excellent agreement with standard instrumentation (mean R ‾ 2 = 0.82 , min–max: 0.54–0.99) in outdoor, indoor and commuting microenvironments across seasons and different geographical settings. An important outcome of this study is that the error of the PAM is significantly smaller than the error introduced when estimating personal exposure based on sparsely distributed outdoor fixed monitoring stations. Hence, novel sensing technologies such as the ones demonstrated here can revolutionise health studies by providing highly resolved reliable exposure metrics at a large scale to investigate the underlying mechanisms of the effects of air pollution on health.

Improved aerosol correction for OMI tropospheric NO2 retrieval over East Asia : Constraint from CALIOP aerosol vertical profile

Abstract: . Satellite retrieval of vertical column densities (VCDs) of tropospheric nitrogen dioxide ( NO2 ) is critical for NOx pollution and impact evaluation. For regions with high aerosol loadings, the retrieval accuracy is greatly affected by whether aerosol optical effects are treated implicitly (as additional “effective” clouds) or explicitly, among other factors. Our previous POMINO algorithm explicitly accounts for aerosol effects to improve the retrieval, especially in polluted situations over China, by using aerosol information from GEOS-Chem simulations with further monthly constraints by MODIS/Aqua aerosol optical depth (AOD) data. Here we present a major algorithm update, POMINO v1.1, by constructing a monthly climatological dataset of aerosol extinction profiles, based on level 2 CALIOP/CALIPSO data over 2007–2015, to better constrain the modeled aerosol vertical profiles. We find that GEOS-Chem captures the month-to-month variation in CALIOP aerosol layer height (ALH) but with a systematic underestimate by about 300–600 m (season and location dependent), due to a too strong negative vertical gradient of extinction above 1 km. Correcting the model aerosol extinction profiles results in small changes in retrieved cloud fraction, increases in cloud-top pressure (within 2 %–6 % in most cases), and increases in tropospheric NO2 VCD by 4 %–16 % over China on a monthly basis in 2012. The improved NO2 VCDs (in POMINO v1.1) are more consistent with independent ground-based MAX-DOAS observations ( R2=0.80 , NMB = −3.4 %, for 162 pixels in 49 days) than POMINO ( R2=0.80 , NMB = −9.6 %), DOMINO v2 ( R2=0.68 , NMB = −2.1 %), and QA4ECV ( R2=0.75 , NMB = −22.0 %) are. Especially on haze days, R2 reaches 0.76 for POMINO v1.1, much higher than that for POMINO (0.68), DOMINO v2 (0.38), and QA4ECV (0.34). Furthermore, the increase in cloud pressure likely reveals a more realistic vertical relationship between cloud and aerosol layers, with aerosols situated above the clouds in certain months instead of always below the clouds. The POMINO v1.1 algorithm is a core step towards our next public release of the data product (POMINO v2), and it will also be applied to the recently launched S5P-TROPOMI sensor.

A scientific algorithm to simultaneously retrieve carbon monoxide and methane from TROPOMI onboard Sentinel-5 Precursor

Abstract: . Carbon monoxide ( CO ) is an important atmospheric constituent affecting air quality, and methane ( CH4 ) is the second most important greenhouse gas contributing to human-induced climate change. Detailed and continuous observations of these gases are necessary to better assess their impact on climate and atmospheric pollution. While surface and airborne measurements are able to accurately determine atmospheric abundances on local scales, global coverage can only be achieved using satellite instruments. The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite, which was successfully launched in October 2017, is a spaceborne nadir-viewing imaging spectrometer measuring solar radiation reflected by the Earth in a push-broom configuration. It has a wide swath on the terrestrial surface and covers wavelength bands between the ultraviolet (UV) and the shortwave infrared (SWIR), combining a high spatial resolution with daily global coverage. These characteristics enable the determination of both gases with an unprecedented level of detail on a global scale, introducing new areas of application. Abundances of the atmospheric column-averaged dry air mole fractions XCO and XCH4 are simultaneously retrieved from TROPOMI's radiance measurements in the 2.3 µm spectral range of the SWIR part of the solar spectrum using the scientific retrieval algorithm Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS). This algorithm is intended to be used with the operational algorithms for mutual verification and to provide new geophysical insights. We introduce the algorithm in detail, including expected error characteristics based on synthetic data, a machine-learning-based quality filter, and a shallow learning calibration procedure applied in the post-processing of the XCH4 data. The quality of the results based on real TROPOMI data is assessed by validation with ground-based Fourier transform spectrometer (FTS) measurements providing realistic error estimates of the satellite data: the XCO data set is characterised by a random error of 5.1 ppb ( 5.8 %) and a systematic error of 1.9 ppb ( 2.1 %); the XCH4 data set exhibits a random error of 14.0 ppb ( 0.8 %) and a systematic error of 4.3 ppb ( 0.2 %). The natural XCO and XCH4 variations are well-captured by the satellite retrievals, which is demonstrated by a high correlation with the validation data ( R=0.97 for XCO and R=0.91 for XCH4 based on daily averages). We also present selected results from the mission start until the end of 2018, including a first comparison to the operational products and examples of the detection of emission sources in a single satellite overpass, such as CO emissions from the steel industry and CH4 emissions from the energy sector, which potentially allows for the advance of emission monitoring and air quality assessments to an entirely new level.

Aerosol size distributions during the Atmospheric Tomography Mission (ATom): methods, uncertainties, and data products

Abstract: . From 2016 to 2018 a DC-8 aircraft operated by the US National Aeronautics and Space Administration (NASA) made four series of flights, profiling the atmosphere from 180 m to ∼12 km above sea level (km a.s.l.) from the Arctic to the Antarctic over both the Pacific and Atlantic oceans. This program, the Atmospheric Tomography Mission (ATom), sought to sample the troposphere in a representative manner, making measurements of atmospheric composition in each season. This paper describes the aerosol microphysical measurements and derived quantities obtained during this mission. Dry size distributions from 2.7 nm to 4.8 µ m in diameter were measured in situ at 1 Hz using a battery of instruments: 10 condensation particle counters with different nucleation diameters, two ultra-high-sensitivity aerosol size spectrometers (UHSASs), one of which measured particles surviving heating to 300 ∘ C, and a laser aerosol spectrometer (LAS). The dry aerosol measurements were complemented by size distribution measurements from 0.5 to 930 µ m diameter at near-ambient conditions using a cloud, aerosol, and precipitation spectrometer (CAPS) mounted under the wing of the DC-8. Dry aerosol number, surface area, and volume, and optical scattering and asymmetry parameters at several wavelengths from the near-UV to the near-IR ranges were calculated from the measured dry size distributions (2.7 nm to 4.8 µ m). Dry aerosol mass was estimated by combining the size distribution data with particle density estimated from independent measurements of aerosol composition with a high-resolution aerosol mass spectrometer and a single-particle soot photometer. We describe the instrumentation and fully document the aircraft inlet and flow distribution system, the derivation of uncertainties, and the calculation of data products from combined size distributions. Comparisons between the instruments and direct measurements of some aerosol properties confirm that in-flight performance was consistent with calibrations and within stated uncertainties for the two deployments analyzed. The unique ATom dataset contains accurate, precise, high-resolution in situ measurements of dry aerosol size distributions, and integral parameters, and estimates and measurements of optical properties, for particles µ m in diameter that can be used to evaluate aerosol abundance and processes in global models.

Measurements of delays of gas-phase compounds in a wide variety of tubing materials due to gas–wall interactions

Abstract: . Losses of gas-phase compounds or delays on their transfer through tubing are important for atmospheric measurements and also provide a method to characterize and quantify gas–surface interactions. Here we expand recent results by comparing different types of Teflon and other polymer tubing, as well as glass, uncoated and coated stainless steel and aluminum, and other tubing materials by measuring the response to step increases and decreases in organic compound concentrations. All polymeric tubings showed absorptive partitioning behavior with no dependence on humidity or concentration, with PFA Teflon tubing performing best in our tests. Glass and uncoated and coated metal tubing showed very different phenomenology due to adsorptive partitioning to a finite number of surface sites. Strong dependencies on compound concentration, mixture composition, functional groups, humidity, and memory effects were observed for glass and uncoated and coated metals, which (except for Silonite-coated stainless steel) also always caused longer delays than Teflon for the compounds and concentrations tested. Delays for glass and uncoated and coated metal tubing were exacerbated at low relative humidity but reduced for RH >20 %. We find that conductive PFA and Silonite tubing perform best among the materials tested for gas-plus-particle sampling lines, combining reduced gas-phase delays with good particle transmission.

Radiance-based retrieval bias mitigation for the MOPITT instrument: the version 8 product

Abstract: . The MOPITT (Measurements of Pollution in the Troposphere) satellite instrument has been making nearly continuous observations of atmospheric carbon monoxide (CO) since 2000. Satellite observations of CO are routinely used to analyze emissions from fossil fuels and biomass burning, as well as the atmospheric transport of those emissions. Recent enhancements to the MOPITT retrieval algorithm have resulted in the release of the version 8 (V8) product. V8 products benefit from updated spectroscopic data for water vapor and nitrogen used to develop the operational radiative transfer model and exploit a new method for minimizing retrieval biases through parameterized radiance bias correction. In situ datasets used for algorithm development and validation include the NOAA (National Oceanic and Atmospheric Administration) and HIPPO (HIAPER Pole-to-Pole Observations) datasets used for earlier MOPITT validation work in addition to measurements from the ACRIDICON-CHUVA (Aerosol, Cloud, Precipitation, and Radiation Interactions and Dynamics of Convective Cloud Systems – Cloud processes of the main precipitation systems in Brazil: A contribution to cloud resolving modeling and to the GPM (Global Precipitation Measurement)), KORUS-AQ (The Korea-United States Air Quality Study), and ATom (The Atmospheric Tomography Mission) programs. Validation results illustrate clear improvements with respect to long-term bias drift and geographically variable retrieval bias. For example, whereas bias drift for the V7 thermal-infrared (TIR)-only product exceeded 0.5 % yr −1 for levels in the upper troposphere (e.g., at 300 hPa), bias drift for the V8 TIR-only product is found to be less than 0.1 % yr −1 at all levels. Also, whereas upper-tropospheric (300 hPa) retrieval bias in the V7 TIR-only product exceeded 10 % in the tropics, corresponding V8 biases are less than 5 % (in terms of absolute value) at all latitudes and do not exhibit a clear latitudinal dependence.

Sulfur dioxide layer height retrieval from Sentinel-5 Precursor/TROPOMI using FP_ILM

Abstract: . The accurate determination of the location, height, and loading of sulfur dioxide ( SO2 ) plumes emitted by volcanic eruptions is essential for aviation safety. The SO2 layer height is also one of the most critical parameters with respect to determining the impact on the climate. Retrievals of SO2 plume height have been carried out using satellite UV backscatter measurements, but, until now, such algorithms are very time-consuming. We have developed an extremely fast yet accurate SO2 layer height retrieval using the Full-Physics Inverse Learning Machine (FP_ILM) algorithm. This is the first time the algorithm has been applied to measurements from the TROPOMI instrument onboard the Sentinel-5 Precursor platform. In this paper, we demonstrate the ability of the FP_ILM algorithm to retrieve SO2 plume layer heights in near-real-time applications with an accuracy of better than 2 km for SO2 total columns larger than 20 DU. We present SO2 layer height results for the volcanic eruptions of Sinabung in February 2018, Sierra Negra in June 2018, and Raikoke in June 2019, observed by TROPOMI.

Dust mass, cloud condensation nuclei, and ice-nucleating particle profiling with polarization lidar: updated POLIPHON conversion factors from global AERONET analysis

Abstract: . The POLIPHON (Polarization Lidar Photometer Networking) method permits the retrieval of particle number, surface area, and volume concentration for dust and non-dust aerosol components. The obtained microphysical properties are used to estimate height profiles of particle mass, cloud condensation nucleus (CCN) and ice-nucleating particle (INP) concentrations. The conversion of aerosol-type-dependent particle extinction coefficients, derived from polarization lidar observations, into the aerosol microphysical properties (number, surface area, volume) forms the central part of the POLIPHON computations. The conversion parameters are determined from Aerosol Robotic Network (AERONET) aerosol climatologies of optical and microphysical properties. In this article, we focus on the dust-related POLIPHON retrieval products and present an extended set of dust conversion factors considering all relevant deserts around the globe. We apply the new conversion factor set to a dust measurement with polarization lidar in Dushanbe, Tajikistan, in central Asia. Strong aerosol layering was observed with mineral dust advected from Kazakhstan (0–2 km height), Iran (2–5 km), the Arabian peninsula (5–7 km), and the Sahara (8–10 km). POLIPHON results obtained with different sets of conversion parameters were contrasted in this central Asian case study and permitted an estimation of the conversion uncertainties.

Detectability of CO 2 emission plumes of cities and power plants with the Copernicus Anthropogenic CO 2 Monitoring (CO2M) mission

Abstract: . High-resolution atmospheric transport simulations were used to investigate the potential for detecting carbon dioxide ( CO2 ) plumes of the city of Berlin and neighboring power stations with the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) mission, which is a proposed constellation of CO2 satellites with imaging capabilities. The potential for detecting plumes was studied for satellite images of CO2 alone or in combination with images of nitrogen dioxide ( NO2 ) and carbon monoxide (CO) to investigate the added value of measurements of other gases coemitted with CO2 that have better signal-to-noise ratios. The additional NO2 and CO images were either generated for instruments on the same CO2M satellites (2 km × 2 km resolution) or for the Sentinel-5 instrument (7.5 km × 7.5 km) assumed to fly 2 h earlier than CO2M. Realistic CO2 , CO and NO X ( = NO + NO 2 ) fields were simulated at 1 km × 1 km horizontal resolution with the Consortium for Small-scale Modeling model extended with a module for the simulation of greenhouse gases (COSMO-GHG) for the year 2015, and they were used as input for an orbit simulator to generate synthetic observations of columns of CO2 , CO and NO2 for constellations of up to six satellites. A simple plume detection algorithm was applied to detect coherent structures in the images of CO2 , NO2 or CO against instrument noise and variability in background levels. Although six satellites with an assumed swath of 250 km were sufficient to overpass Berlin on a daily basis, only about 50 out of 365 plumes per year could be observed in conditions suitable for emission estimation due to frequent cloud cover. With the CO2 instrument only 6 and 16 of these 50 plumes could be detected assuming a high-noise ( σVEG50=1.0 ppm) and low-noise ( σVEG50=0.5 ppm) scenario, respectively, because the CO2 signals were often too weak. A CO instrument with specifications similar to the Sentinel-5 mission performed worse than the CO2 instrument, while the number of detectable plumes could be significantly increased to about 35 plumes with an NO2 instrument. CO2 and NO2 plumes were found to overlap to a large extent, although NOX had a limited lifetime (assumed to be 4 h) and although CO2 and NOX were emitted with different NOX:CO2 emission ratios by different source types with different temporal and vertical emission profiles. Using NO2 observations from the Sentinel-5 platform instead resulted in a significant spatial mismatch between NO2 and CO2 plumes due to the 2 h time difference between Sentinel-5 and CO2M. The plumes of the coal-fired power plant Janschwalde were easier to detect with the CO2 instrument (about 40–45 plumes per year), but, again, an NO2 instrument could detect significantly more plumes (about 70). Auxiliary measurements of NO2 were thus found to greatly enhance the capability of detecting the location of CO2 plumes, which will be invaluable for the quantification of CO2 emissions from large point sources.

Potential of next-generation imaging spectrometers to detect and quantify methane point sources from space

Abstract: . We examine the potential for global detection of methane plumes from individual point sources with the new generation of spaceborne imaging spectrometers (EnMAP, PRISMA, EMIT, SBG, CHIME) scheduled for launch in 2019–2025. These instruments are designed to map the Earth's surface at high spatial resolution ( 30 m×30 m ) and have a spectral resolution of 7–10 nm in the 2200–2400 nm band that should also allow useful detection of atmospheric methane. We simulate scenes viewed by EnMAP (10 nm spectral resolution, 180 signal-to-noise ratio) using the EnMAP end-to-end simulation tool with superimposed methane plumes generated by large-eddy simulations. We retrieve atmospheric methane and surface reflectivity for these scenes using the IMAP-DOAS optimal estimation algorithm. We find an EnMAP precision of 3 %–7 % for atmospheric methane depending on surface type. This allows effective single-pass detection of methane point sources as small as 100 kg h −1 depending on surface brightness, surface homogeneity, and wind speed. Successful retrievals over very heterogeneous surfaces such as an urban mosaic require finer spectral resolution. We tested the EnMAP capability with actual plume observations over oil/gas fields in California from the Airborne Visible/Infrared Imaging Spectrometer – Next Generation (AVIRIS-NG) sensor ( 3 m×3 m pixel resolution, 5 nm spectral resolution, SNR 200–400), by spectrally and spatially downsampling the AVIRIS-NG data to match EnMAP instrument specifications. Results confirm that EnMAP can successfully detect point sources of ∼100 kg h −1 over bright surfaces. Source rates inferred with a generic integrated mass enhancement (IME) algorithm were lower for EnMAP than for AVIRIS-NG. Better agreement may be achieved with a more customized IME algorithm. Our results suggest that imaging spectrometers in space could play an important role in the future for quantifying methane emissions from point sources worldwide.

Evaluating the impact of spatial resolution on tropospheric NO 2 column comparisons within urban areas using high-resolution airborne data

Abstract: . NASA deployed the GeoTASO airborne UV–visible spectrometer in May–June 2017 to produce high-resolution (approximately 250 m×250 m ) gapless NO2 datasets over the western shore of Lake Michigan and over the Los Angeles Basin. The results collected show that the airborne tropospheric vertical column retrievals compare well with ground-based Pandora spectrometer column NO2 observations ( r2=0.91 and slope of 1.03). Apparent disagreements between the two measurements can be sensitive to the coincidence criteria and are often associated with large local variability, including rapid temporal changes and spatial heterogeneity that may be observed differently by the sunward-viewing Pandora observations. The gapless mapping strategy executed during the 2017 GeoTASO flights provides data suitable for averaging to coarser areal resolutions to simulate satellite retrievals. As simulated satellite pixel area increases to values typical of TEMPO (Tropospheric Emissions: Monitoring Pollution), TROPOMI (TROPOspheric Monitoring Instrument), and OMI (Ozone Monitoring Instrument), the agreement with Pandora measurements degraded, particularly for the most polluted columns as localized large pollution enhancements observed by Pandora and GeoTASO are spatially averaged with nearby less-polluted locations within the larger area representative of the satellite spatial resolutions (aircraft-to-Pandora slope: TEMPO scale =0.88 ; TROPOMI scale =0.77 ; OMI scale =0.57 ). In these two regions, Pandora and TEMPO or TROPOMI have the potential to compare well at least up to pollution scales of 30×1015 molecules cm −2 . Two publicly available OMI tropospheric NO2 retrievals are found to be biased low with respect to these Pandora observations. However, the agreement improves when higher-resolution a priori inputs are used for the tropospheric air mass factor calculation (NASA V3 standard product slope =0.18 and Berkeley High Resolution product slope =0.30 ). Overall, this work explores best practices for satellite validation strategies with Pandora direct-sun observations by showing the sensitivity to product spatial resolution and demonstrating how the high-spatial-resolution NO2 data retrieved from airborne spectrometers, such as GeoTASO, can be used with high-temporal-resolution ground-based column observations to evaluate the influence of spatial heterogeneity on validation results.

A new method to quantify mineral dust and other aerosol species from aircraft platforms using single-particle mass spectrometry

Abstract: . Single-particle mass spectrometry (SPMS) instruments characterize the composition of individual aerosol particles in real time. Their fundamental ability to differentiate the externally mixed particle types that constitute the atmospheric aerosol population enables a unique perspective into sources and transformation. However, quantitative measurements by SPMS systems are inherently problematic. We introduce a new technique that combines collocated measurements of aerosol composition by SPMS and size-resolved absolute particle concentrations on aircraft platforms. Quantitative number, surface area, volume, and mass concentrations are derived for climate-relevant particle types such as mineral dust, sea salt, and biomass burning smoke. Additionally, relative ion signals are calibrated to derive mass concentrations of internally mixed sulfate and organic material that are distributed across multiple particle types. The NOAA Particle Analysis by Laser Mass Spectrometry (PALMS) instrument measures size-resolved aerosol chemical composition from aircraft. We describe the identification and quantification of nine major atmospheric particle classes, including sulfate–organic–nitrate mixtures, biomass burning, elemental carbon, sea salt, mineral dust, meteoric material, alkali salts, heavy fuel oil combustion, and a remainder class. Classes can be sub-divided as necessary based on chemical heterogeneity, accumulated secondary material during aging, or other atmospheric processing. Concentrations are derived for sizes that encompass the accumulation and coarse size modes. A statistical error analysis indicates that particle class concentrations can be determined within a few minutes for abundances above ∼10 ng m −3 . Rare particle types require longer sampling times. We explore the instrumentation requirements and the limitations of the method for airborne measurements. Reducing the size resolution of the particle data increases time resolution with only a modest increase in uncertainty. The principal limiting factor to fast time response concentration measurements is statistically relevant sampling across the size range of interest, in particular, sizes D µ m for accumulation-mode studies and D > 2 µ m for coarse-mode analysis. Performance is compared to other airborne and ground-based composition measurements, and examples of atmospheric mineral dust concentrations are given. The wealth of information afforded by composition-resolved size distributions for all major aerosol types represents a new and powerful tool to characterize atmospheric aerosol properties in a quantitative fashion.

Validity and limitations of simple reaction kinetics to calculate concentrations of organic compounds from ion counts in PTR-MS

Abstract: . In September 2017, we conducted a proton-transfer-reaction mass-spectrometry (PTR-MS) intercomparison campaign at the CESAR observatory, a rural site in the central Netherlands near the village of Cabauw. Nine research groups deployed a total of 11 instruments covering a wide range of instrument types and performance. We applied a new calibration method based on fast injection of a gas standard through a sample loop. This approach allows calibrations on timescales of seconds, and within a few minutes an automated sequence can be run allowing one to retrieve diagnostic parameters that indicate the performance status. We developed a method to retrieve the mass-dependent transmission from the fast calibrations, which is an essential characteristic of PTR-MS instruments, limiting the potential to calculate concentrations based on counting statistics and simple reaction kinetics in the reactor/drift tube. Our measurements show that PTR-MS instruments follow the simple reaction kinetics if operated in the standard range for pressures and temperature of the reaction chamber (i.e. 1–4 mbar, 30–120 ∘ , respectively), as well as a reduced field strength E∕N in the range of 100–160 Td. If artefacts can be ruled out, it becomes possible to quantify the signals of uncalibrated organics with accuracies better than ±30 %. The simple reaction kinetics approach produces less accurate results at E∕N levels below 100 Td, because significant fractions of primary ions form water hydronium clusters. Deprotonation through reactive collisions of protonated organics with water molecules needs to be considered when the collision energy is a substantial fraction of the exoergicity of the proton transfer reaction and/or if protonated organics undergo many collisions with water molecules.

All-sky assimilation of infrared radiances sensitive to mid- and upper-tropospheric moisture and cloud

Abstract: . All-sky assimilation of infrared (IR) radiances has not yet become operational at any weather forecasting centre, but it promises to bring new observations in sensitive areas and avoid the need for cloud detection. A new all-sky IR configuration gives results comparable to (and in some areas better than) clear-sky assimilation of the same data, meaning that operational implementation is now feasible. The impact of seven upper-tropospheric water vapour (WV) sounding channels from the Infrared Atmospheric Sounding Interferometer (IASI) is evaluated in both all-sky and clear-sky approaches. All-sky radiative transfer simulations (and the forecast model's cloud fields) are now sufficiently accurate that systematic errors are comparable to those of clear-sky assimilation outside of a few difficult areas such as deep convection. All-sky assimilation brings 65 % more data than clear-sky assimilation globally, with the biggest increases in midlatitude storm tracks and tropical convective areas. However, all-sky gives slightly less weight to any one observation than in the clear-sky approach. In the midlatitudes, all-sky and clear-sky assimilation have similarly beneficial impact on mid- and upper-tropospheric dynamical forecast fields. Here the addition of data in cloudy areas is offset by the slightly lower weight given to the observations. But in the tropics, all-sky assimilation is significantly more beneficial than clear-sky assimilation, with improved dynamical short-range forecasts throughout the troposphere and stratosphere.

Aerosol-type classification based on AERONET version 3 inversion products

Abstract: . This study proposes an aerosol-type classification based on the particle linear depolarization ratio (PLDR) and single-scattering albedo (SSA) provided in the AErosol RObotic NETwork (AERONET) version 3 level 2.0 inversion product. We compare our aerosol-type classification with an earlier method that uses fine-mode fraction (FMF) and SSA. Our new method allows for a refined classification of mineral dust that occurs as a mixture with other absorbing aerosols: pure dust (PD), dust-dominated mixed plume (DDM), and pollutant-dominated mixed plume (PDM). We test the aerosol classification at AERONET sites in East Asia that are frequently affected by mixtures of Asian dust and biomass-burning smoke or anthropogenic pollution. We find that East Asia is strongly affected by pollution particles with high occurrence frequencies of 50 % to 67 %. The distribution and types of pollution particles vary with location and season. The frequency of PD and dusty aerosol mixture (DDM+PDM) is slightly lower (34 % to 49 %) than pollution-dominated mixtures. Pure dust particles have been detected in only 1 % of observations. This suggests that East Asian dust plumes generally exist in a mixture with pollution aerosols rather than in pure form. In this study, we have also considered data from selected AERONET sites that are representative of anthropogenic pollution, biomass-burning smoke, and mineral dust. We find that average aerosol properties obtained for aerosol types in our PLDR–SSA-based classification agree reasonably well with those obtained at AERONET sites representative for different aerosol types.

Intercomparison of nitrous acid (HONO) measurement techniques in a megacity (Beijing)

Abstract: . Nitrous acid (HONO) is a key determinant of the daytime radical budget in the daytime boundary layer, with quantitative measurement required to understand OH radical abundance. Accurate and precise measurements of HONO are therefore needed; however HONO is a challenging compound to measure in the field, in particular in a chemically complex and highly polluted environment. Here we report an intercomparison exercise between HONO measurements performed by two wet chemical techniques (the commercially available a long-path absorption photometer (LOPAP) and a custom-built instrument) and two broadband cavity-enhanced absorption spectrophotometer (BBCEAS) instruments at an urban location in Beijing. In addition, we report a comparison of HONO measurements performed by a time-of-flight chemical ionization mass spectrometer (ToF-CIMS) and a selected ion flow tube mass spectrometer (SIFT-MS) to the more established techniques (wet chemical and BBCEAS). The key finding from the current work was that all instruments agree on the temporal trends and variability in HONO ( r2 > 0.97), yet they displayed some divergence in absolute concentrations, with the wet chemical methods consistently higher overall than the BBCEAS systems by between 12 % and 39 %. We found no evidence for any systematic bias in any of the instruments, with the exception of measurements near instrument detection limits. The causes of the divergence in absolute HONO concentrations were unclear, and may in part have been due to spatial variability, i.e. differences in instrument location and/or inlet position, but this observation may have been more associative than casual.

Effects of gas–wall interactions on measurements of semivolatile compounds and small polar molecules

Abstract: . Recent work has quantified the delay times in measurements of volatile organic compounds (VOCs) caused by the partitioning between the gas phase and the surfaces of the inlet tubing and instrument itself. In this study we quantify wall partitioning effects on time responses and transmission of multifunctional, semivolatile, and intermediate-volatility organic compounds (S/IVOCs) with saturation concentrations ( C∗ ) between 10 0 and 10 4 µg m−3 . The instrument delays of several chemical ionization mass spectrometer (CIMS) instruments increase with decreasing C∗ , ranging from seconds to tens of minutes, except for the NO 3 - CIMS where it is always on the order of seconds. Six different tubing materials were tested. Teflon, including PFA, FEP, and conductive PFA, performs better than metals and Nafion in terms of both delay time and transmission efficiency. Analogous to instrument responses, tubing delays increase as C∗ decreases, from less than a minute to >100 min . The delays caused by Teflon tubing vs. C∗ can be modeled using the simple chromatography model of Pagonis et al. (2017). The model can be used to estimate the equivalent absorbing mass concentration ( Cw ) of each material, and to estimate delays under different flow rates and tubing dimensions. We also include time delay measurements from a series of small polar organic and inorganic analytes in PFA tubing measured by CIMS. Small polar molecules behave differently than larger organic ones, with their delays being predicted by their Henry's law constants instead of their C∗ , suggesting the dominance of partitioning to small amounts of water on sampling surfaces as a result of their polarity and acidity properties. PFA tubing has the best performance for gas-only sampling, while conductive PFA appears very promising for sampling S/IVOCs and particles simultaneously. The observed delays and low transmission both affect the quality of gas quantification, especially when no direct calibration is available. Improvements in sampling and instrument response are needed for fast atmospheric measurements of a wide range of S/IVOCs (e.g., by aircraft or for eddy covariance). These methods and results are also useful for more general characterization of surface–gas interactions.

CALIPSO lidar calibration at 1064 nm: version 4 algorithm

Abstract: . Radiometric calibration of space-based elastic backscatter lidars is accomplished by comparing the measured backscatter signals to theoretically expected signals computed for some well-characterized calibration target. For any given system and wavelength, the choice of calibration target is dictated by several considerations, including signal-to-noise ratio (SNR) and target availability. This paper describes the newly implemented procedures used to calibrate the 1064 nm measurements acquired by CALIOP (i.e., the Cloud-Aerosol Lidar with Orthogonal Polarization), the two-wavelength (532 and 1064 nm) elastic backscatter lidar currently flying on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission. CALIOP's 532 nm channel is accurately calibrated by normalizing the molecular backscatter from the uppermost aerosol-free altitudes of the CALIOP measurement region to molecular model data obtained from NASA's Global Modeling and Assimilation Office. However, because CALIOP's SNR for molecular backscatter measurements is prohibitively lower at 1064 nm than at 532 nm, the direct high-altitude molecular normalization method is not a viable option at 1064 nm. Instead, CALIOP's 1064 nm channel is calibrated relative to the 532 nm channel using the backscatter from a carefully selected subset of cirrus cloud measurements. In this paper we deliver a full account of the revised 1064 nm calibration algorithms implemented for the version 4.1 (V4) release of the CALIPSO lidar data products, with particular emphases on the physical basis for the selection of “calibration quality” cirrus clouds and on the new averaging scheme required to characterize intra-orbit calibration variability. The V4 procedures introduce latitudinally varying changes in the 1064 nm calibration coefficients of 25 % or more, relative to previous data releases, and are shown to substantially improve the accuracy of the V4 1064 nm attenuated backscatter coefficients. By evaluating calibration coefficients derived using both water clouds and ocean surfaces as alternate calibration targets, and through comparisons to independent, collocated measurements made by airborne high spectral resolution lidar, we conclude that the CALIOP V4 1064 nm calibration coefficients are accurate to within 3 %.

Intercomparison of MAX-DOAS vertical profile retrieval algorithms: studies using synthetic data

Abstract: . Multi-axis differential optical absorption spectroscopy (MAX-DOAS) is a widely used measurement technique for the detection of a variety of atmospheric trace gases. Using inverse modelling, the observation of trace gas column densities along different lines of sight enables the retrieval of aerosol and trace gas vertical profiles in the atmospheric boundary layer using appropriate retrieval algorithms. In this study, the ability of eight profile retrieval algorithms to reconstruct vertical profiles is assessed on the basis of synthetic measurements. Five of the algorithms are based on the optimal estimation method, two on parametrised approaches, and one using an analytical approach without involving any radiative transfer modelling. The synthetic measurements consist of the median of simulated slant column densities of O4 at 360 and 477 nm , as well as of HCHO at 343 nm and NO2 at 477 nm , from seven datasets simulated by five different radiative transfer models. Simulations are performed for a combination of 10 trace gas and 11 aerosol profiles, as well as 11 elevation angles, three solar zenith, and three relative azimuth angles. Overall, the results from the different algorithms show moderate to good performance for the retrieval of vertical profiles, surface concentrations, and total columns. Except for some outliers, the root-mean-square difference between the true and retrieved state ranges between (0.05–0.1) km −1 for aerosol extinction and (2.5–5.0) ×1010 molec cm −3 for HCHO and NO2 concentrations.