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A horizontally pointing lidar is planned for deployment with other instruments in Fukushima, Japan, to continuously monitor and characterize the optical properties of radioactive aerosols and dust in an uninhabited area. Prior to installation, the performance of the lidar is tested at Chiba University. Data from the continuous operation of the lidar from August 2021 to February 2022 are analyzed for extinction and volume linear depolarization ratio. These are compared with the weather sensor and particulate matter (PM2.5) measurements to quantify the relationships between atmospheric conditions and optical properties of near-ground aerosols. The results show that the lidar data's extinction coefficient and depolarization ratio can have a quantifiable relationship with relative humidity (RH), absolute humidity, rain rate, wind speed, wind direction and PM2.5 concentration. Analysis of the 7-month data shows that the optical properties of aerosol and dust depend on the combined effects of the weather parameters. An increase in RH or PM2.5 concentration does not imply an increase in radioactive aerosols. The average extinction coefficient and depolarization ratio of aerosols and dust, originating from the land and ocean, show different values and opposing trends, which can aid in determining the occurrence of ground-based radioactive dust and aerosols. The information obtained from analyzing the inter-relationship among lidar, weather parameters and PM2.5 concentration is essential in assessing the occurrence of radioactive aerosols and characterizing local aerosol–weather relationships in a radioactive area. This result provides essential information in describing radioactive aerosols in Fukushima.

We introduce the new Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 product of total column ozone (O3), total and tropospheric column nitrogen dioxide (NO2), total column water vapour, total column bromine oxide (BrO), total column formaldehyde (HCHO), and total column sulfur dioxide (SO2) (daily products https://doi.org/10.15770/EUM_SAF_AC_0048, AC SAF, 2023a; monthly products https://doi.org/10.15770/EUM_SAF_AC_0049, AC SAF, 2023b). The GOME-2 level-3 products aim to provide easily translatable and user-friendly data sets to the scientific community for scientific progress as well as to satisfy public interest. The purpose of this paper is to present the theoretical basis as well as the verification and validation of the GOME-2 daily and monthly level-3 products. The GOME-2 level-3 products are produced using the overlapping area-weighting method. Details of the gridding algorithm are presented. The spatial resolution of the GOME-2 level-3 products is selected based on the sensitivity study. The consistency of the resulting level-3 products among three GOME-2 sensors is investigated through time series of global averages, zonal averages, and bias. The accuracy of the products is validated by comparison to ground-based observations. The verification and validation results show that the GOME-2 level-3 products are consistent with the level-2 data. Small discrepancies are found among three GOME-2 sensors, which are mainly caused by the differences in the instrument characteristic and level-2 processor. The comparison of GOME-2 level-3 products to ground-based observations in general shows very good agreement, indicating that the products are consistent and fulfil the requirements to serve the scientific community and general public.

This study investigated the spatiotemporal variabilities in nitrogen dioxide (NO2), formaldehyde (HCHO), ozone (O3), and light-absorbing aerosols within the Greater Tokyo Area, Japan, which is the most populous metropolitan area in the world. The analysis is based on total tropospheric column, partial tropospheric column (within the boundary layer), and in situ observations retrieved from multiple platforms as well as additional information obtained from reanalysis and box model simulations. This study mainly covers the 2013–2020 period, focusing on 2020 when air quality was influenced by the coronavirus 2019 (COVID-19) pandemic. Although total and partial tropospheric NO2 columns were reduced by an average of about 10 % in 2020, reductions exceeding 40 % occurred in some areas during the pandemic state of emergency. Light-absorbing aerosol levels within the boundary layer were also reduced for most of 2020, while smaller fluctuations in HCHO and O3 were observed. The significantly enhanced degree of weekly cycling of NO2, HCHO, and light-absorbing aerosol found in urban areas during 2020 suggests that, in contrast to other countries, mobility in Japan also dropped on weekends. We conclude that, despite the lack of strict mobility restrictions in Japan, widespread adherence to recommendations designed to limit the COVID-19 spread resulted in unique air quality improvements.

Formaldehyde (HCHO) and nitrogen dioxide (NO2) concentrations and profiles were retrieved from ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations during January 2017–December 2018 at three sites in Asia: (1) Phimai (15.18∘ N, 102.5∘ E), Thailand; (2) Pantnagar (29∘ N, 78.90∘ E) in the Indo-Gangetic Plain (IGP), India; and (3) Chiba (35.62∘ N, 140.10∘ E), Japan. Retrievals were performed using the Japanese MAX-DOAS profile retrieval algorithm ver. 2 (JM2). The observations were used to evaluate the NO2 and HCHO partial columns and profiles (0–4 km) simulated using the global chemistry transport model (CTM) CHASER (Chemical Atmospheric General Circulation Model for Study of Atmospheric Environment and Radiative Forcing). The NO2 and HCHO concentrations at all three sites showed consistent seasonal variation throughout the investigated period. Biomass burning affected the HCHO and NO2 variations at Phimai during the dry season and at Pantnagar during spring (March–May) and post-monsoon (September–November). Results found for the HCHO-to-NO2 ratio (RFN), an indicator of high ozone sensitivity, indicate that the transition region (i.e., 1 < RFN < 2) changes regionally, echoing the recent finding for RFN effectiveness. Moreover, reasonable estimates of transition regions can be derived, accounting for the NO2–HCHO chemical feedback. The model was evaluated against global NO2 and HCHO columns data retrieved from Ozone Monitoring Instrument (OMI) observations before comparison with ground-based datasets. Despite underestimation, the model well simulated the satellite-observed global spatial distribution of NO2 and HCHO, with respective spatial correlations (r) of 0.73 and 0.74. CHASER demonstrated good performance, reproducing the MAX-DOAS-retrieved HCHO and NO2 abundances at Phimai, mainly above 500 m from the surface. Model results agree with the measured variations within the 1-sigma (1σ) standard deviation of the observations. Simulations at higher resolution improved the modeled NO2 estimates for Chiba, reducing the mean bias error (MBE) for the 0–2 km height by 35 %, but resolution-based improvements were limited to surface layers. Sensitivity studies show that at Phimai, pyrogenic emissions contribute up to 50 % and 35 % to HCHO and NO2 concentrations, respectively.

The Second-generation Global Imager (SGLI) onboard the Global Change Observation Mission – Climate (GCOM-C) satellite, launched on 23 December 2017, observes various geophysical parameters with the aim of better understanding the global climate system. As part of that aim, SGLI has great potential to unravel several uncertainties related to clouds by providing new cloud products along with several other atmospheric products related to cloud climatology, including aerosol products from polarization channels. However, very little is known about the quality of the SGLI cloud products. This study uses data about clouds and global irradiances observed from the Earth's surface using a sky radiometer and a pyranometer, respectively, to understand the quality of the two most fundamental cloud properties – cloud optical depth (COD) and cloud-particle effective radius (CER) – of both water and ice clouds. The SGLI-observed COD agrees well with values observed from the surface, although it agrees better for water clouds than for ice clouds, while the SGLI-observed CER exhibits poorer agreement than does the COD, with SGLI values being generally higher than the sky radiometer values. These comparisons between the SGLI and sky radiometer cloud properties are found to differ for different cloud types of both the water and ice cloud phases and different solar and satellite viewing angles by agreeing better for relatively uniform and flat cloud type and for relatively low solar zenith angle. Analyses of SGLI-observed reflectance functions and values calculated by assuming plane-parallel cloud layers suggest that SGLI-retrieved cloud properties can have biases in the solar and satellite viewing angles, similar to other satellite sensors including the Moderate Resolution Imaging Spectroradiometer (MODIS). Furthermore, it is found that the SGLI-observed cloud properties reproduce global irradiances quite satisfactorily for both water and ice clouds by resembling several important features of the COD comparison, such as better agreement for water clouds than for ice clouds and the tendency to underestimate (resp. overestimate) the COD in SGLI observations for optically thick (resp. thin) clouds.

We present the first global glyoxal (CHOCHO) tropospheric column product derived from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor satellite. Atmospheric glyoxal results from the oxidation of other non-methane volatile organic compounds (NMVOCs) and from direct emissions caused by combustion processes. Therefore, this product is a useful indicator of VOC emissions. It is generated with an improved version of the BIRA-IASB scientific retrieval algorithm relying on the differential optical absorption spectroscopy (DOAS) approach. Among the algorithmic updates, the DOAS fit now includes corrections to mitigate the impact of spectral misfits caused by scene brightness inhomogeneity and strong NO2 absorption. The product comes along with a full error characterization, which allows for providing random and systematic error estimates for every observation. Systematic errors are typically in the range of 1 ×1014–3 ×1014 molec. cm−2 (∼30 %–70 % in emission regimes) and originate mostly from a priori data uncertainties and spectral interferences with other absorbing species. The latter may be at the origin, at least partly, of an enhanced glyoxal signal over equatorial oceans, and further investigation is needed to mitigate them. Random errors are large (>6×1014 molec. cm−2) but can be reduced by averaging observations in space and/or time. Benefiting from a high signal-to-noise ratio and a large number of small-size observations, TROPOMI provides glyoxal tropospheric column fields with an unprecedented level of detail. Using the same retrieval algorithmic baseline, glyoxal column data sets are also generated from the Ozone Monitoring Instrument (OMI) on Aura and from the Global Ozone Monitoring Experiment-2 (GOME-2) on board Metop-A and Metop-B. Those four data sets are intercompared over large-scale regions worldwide and show a high level of consistency. The satellite glyoxal columns are also compared to glyoxal columns retrieved from ground-based Multi-AXis DOAS (MAX-DOAS) instruments at nine stations in Asia and Europe. In general, the satellite and MAX-DOAS instruments provide consistent glyoxal columns both in terms of absolute values and variability. Correlation coefficients between TROPOMI and MAX-DOAS glyoxal columns range between 0.61 and 0.87. The correlation is only poorer at one mid-latitude station, where satellite data appear to be biased low during wintertime. The mean absolute glyoxal columns from satellite and MAX-DOAS generally agree well for low/moderate columns with differences of less than 1×1014 molec. cm−2. A larger bias is identified at two sites where the MAX-DOAS columns are very large. Despite this systematic bias, the consistency of the satellite and MAX-DOAS glyoxal seasonal variability is high.

The TROPOspheric Monitoring Instrument (TROPOMI), launched in October 2017 on board the Sentinel-5 Precursor (S5P) satellite, monitors the composition of the Earth's atmosphere at an unprecedented horizontal resolution as fine as 3.5 × 5.5 km2. This paper assesses the performances of the TROPOMI formaldehyde (HCHO) operational product compared to its predecessor, the OMI (Ozone Monitoring Instrument) HCHO QA4ECV product, at different spatial and temporal scales. The parallel development of the two algorithms favoured the consistency of the products, which facilitates the production of long-term combined time series. The main difference between the two satellite products is related to the use of different cloud algorithms, leading to a positive bias of OMI compared to TROPOMI of up to 30 % in tropical regions. We show that after switching off the explicit correction for cloud effects, the two datasets come into an excellent agreement. For medium to large HCHO vertical columns (larger than 5 × 1015 molec. cm−2) the median bias between OMI and TROPOMI HCHO columns is not larger than 10 % (< 0.4 × 1015 molec. cm−2). For lower columns, OMI observations present a remaining positive bias of about 20 % (< 0.8 × 1015 molec. cm−2) compared to TROPOMI in midlatitude regions. Here, we also use a global network of 18 MAX-DOAS (multi-axis differential optical absorption spectroscopy) instruments to validate both satellite sensors for a large range of HCHO columns. This work complements the study by Vigouroux et al. (2020), where a global FTIR (Fourier transform infrared) network is used to validate the TROPOMI HCHO operational product. Consistent with the FTIR validation study, we find that for elevated HCHO columns, TROPOMI data are systematically low (−25 % for HCHO columns larger than 8 × 1015 molec. cm−2), while no significant bias is found for medium-range column values. We further show that OMI and TROPOMI data present equivalent biases for large HCHO levels. However, TROPOMI significantly improves the precision of the HCHO observations at short temporal scales and for low HCHO columns. We show that compared to OMI, the precision of the TROPOMI HCHO columns is improved by 25 % for individual pixels and by up to a factor of 3 when considering daily averages in 20 km radius circles. The validation precision obtained with daily TROPOMI observations is comparable to the one obtained with monthly OMI observations. To illustrate the improved performances of TROPOMI in capturing weak HCHO signals, we present clear detection of HCHO column enhancements related to shipping emissions in the Indian Ocean. This is achieved by averaging data over a much shorter period (3 months) than required with previous sensors (5 years) and opens new perspectives to study shipping emissions of VOCs (volatile organic compounds) and related atmospheric chemical interactions.

This study provides comparisons of aerosol representation methods incorporated into a regional-scale nonhydrostatic meteorology–chemistry model (NHM-Chem). Three options for aerosol representations are currently available: the five-category non-equilibrium (Aitken, soot-free accumulation, soot-containing accumulation, dust, and sea salt), three-category non-equilibrium (Aitken, accumulation, and coarse), and bulk equilibrium (submicron, dust, and sea salt) methods. The three-category method is widely used in three-dimensional air quality models. The five-category method, the standard method of NHM-Chem, is an extensional development of the three-category method and provides improved predictions of variables relating to aerosol–cloud–radiation interaction processes by implementing separate treatments of light absorber and ice nuclei particles, namely, soot and dust, from the accumulation- and coarse-mode categories (implementation of aerosol feedback processes to NHM-Chem is still ongoing, though). The bulk equilibrium method was developed for operational air quality forecasting with simple aerosol dynamics representations. The total CPU times of the five-category and three-category methods were 91 % and 44 % greater than that of the bulk method, respectively. The bulk equilibrium method was shown to be eligible for operational forecast purposes, namely, the surface mass concentrations of air pollutants such as O3, mineral dust, and PM2.5. The simulated surface concentrations and depositions of bulk chemical species of the three-category method were not significantly different from those of the five-category method. However, the internal mixture assumption of soot/soot-free and dust/sea salt particles in the three-category method resulted in significant differences in the size distribution and hygroscopicity of the particles. The unrealistic dust/sea salt complete mixture of the three-category method induced significant errors in the prediction of the mineral dust-containing cloud condensation nuclei (CCN), which alters heterogeneous ice nucleation in cold rain processes. The overestimation of soot hygroscopicity by the three-category method induced errors in the BC-containing CCN, BC deposition, and light-absorbing aerosol optical thickness (AAOT). Nevertheless, the difference in AAOT was less pronounced with the three-category method because the overestimation of the absorption enhancement was compensated by the overestimation of hygroscopic growth and the consequent loss due to in-cloud scavenging. In terms of total properties, such as aerosol optical thickness (AOT) and CCN, the results of the three-category method were acceptable.

This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOspheric Monitoring Instrument (TROPOMI) on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5P) satellite. Tropospheric, stratospheric, and total NO2 column data from S5P are compared to correlative measurements collected from, respectively, 19 Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS), 26 Network for the Detection of Atmospheric Composition Change (NDACC) Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 Pandonia Global Network (PGN)/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g. by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5P data show, on average, (i) a negative bias for the tropospheric column data, of typically −23 % to −37 % in clean to slightly polluted conditions but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative median difference for the stratospheric column data, of about −0.2 Pmolec cm−2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec cm−2 and negative values above. The dispersion between S5P and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec cm−2) but exceed those for the tropospheric column data (0.7 Pmolec cm−2). While a part of the biases and dispersion may be due to representativeness differences such as different area averaging and measurement times, it is known that errors in the S5P tropospheric columns exist due to shortcomings in the (horizontally coarse) a priori profile representation in the TM5-MP chemical transport model used in the S5P retrieval and, to a lesser extent, to the treatment of cloud effects and aerosols. Although considerable differences (up to 2 Pmolec cm−2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and offline (OFFL) versions of the S5P NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.

Multi-axis differential optical absorption spectroscopy (MAX-DOAS) and direct sun NO2 vertical column network data are used to investigate the accuracy of tropospheric NO2 column measurements of the GOME-2 instrument on the MetOp-A satellite platform and the OMI instrument on Aura. The study is based on 23 MAX-DOAS and 16 direct sun instruments at stations distributed worldwide. A method to quantify and correct for horizontal dilution effects in heterogeneous NO2 field conditions is proposed. After systematic application of this correction to urban sites, satellite measurements are found to present smaller biases compared to ground-based reference data in almost all cases. We investigate the seasonal dependence of the validation results as well as the impact of using different approaches to select satellite ground pixels in coincidence with ground-based data. In optimal comparison conditions (satellite pixels containing the station) the median bias between satellite tropospheric NO2 column measurements and the ensemble of MAX-DOAS and direct sun measurements is found to be significant and equal to −34 % for GOME-2A and −24 % for OMI. These biases are further reduced to −24 % and −18 % respectively, after application of the dilution correction. Comparisons with the QA4ECV satellite product for both GOME-2A and OMI are also performed, showing less scatter but also a slightly larger median tropospheric NO2 column bias with respect to the ensemble of MAX-DOAS and direct sun measurements.

This paper is an overview of the progress in sky radiometer technology and the development of the network called SKYNET. It is found that the technology has produced useful on-site calibration methods, retrieval algorithms, and data analyses from sky radiometer observations of aerosol, cloud, water vapor, and ozone. A formula was proposed for estimating the accuracy of the sky radiometer calibration constant F0 using the improved Langley (IL) method, which was found to be a good approximation to observed monthly mean uncertainty in F0, around 0.5 % to 2.4 % at the Tokyo and Rome sites and smaller values of around 0.3 % to 0.5 % at the mountain sites at Mt. Saraswati and Davos. A new cross IL (XIL) method was also developed to correct an underestimation by the IL method in cases with large aerosol retrieval errors. The root-mean-square difference (RMSD) in aerosol optical thickness (AOT) comparisons with other networks took values of less than 0.02 for λ≥500 nm and a larger value of about 0.03 for shorter wavelengths in city areas and smaller values of less than 0.01 in mountain comparisons. Accuracies of single-scattering albedo (SSA) and size distribution retrievals are affected by the propagation of errors in measurement, calibrations for direct solar and diffuse sky radiation, ground albedo, cloud screening, and the version of the analysis software called the Skyrad pack. SSA values from SKYNET were up to 0.07 larger than those from AERONET, and the major error sources were identified as an underestimation of solid viewing angle (SVA) and cloud contamination. Correction of these known error factors reduced the SSA difference to less than 0.03. Retrievals of other atmospheric constituents by the sky radiometer were also reviewed. Retrieval accuracies were found to be about 0.2 cm for precipitable water vapor amount and 13 DU (Dobson Unit) for column ozone amount. Retrieved cloud optical properties still showed large deviations from validation data, suggesting a need to study the causes of the differences. It is important that these recent studies on improvements presented in the present paper are introduced into the existing operational systems and future systems of the International SKYNET Data Center.

In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, the Netherlands (51.97∘ N, 4.93∘ E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were (1) to characterise and better understand the differences between a large number of multi-axis differential optical absorption spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen collision complex (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region, and NO2 in an additional (smaller) wavelength range in the visible region. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in a unique set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the selected reference (which is obtained from the median of either all data sets or a subset), and the rms error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

The Prede sky radiometer measures direct solar irradiance and the angular distribution of diffuse radiances at the ultraviolet, visible, and near-infrared wavelengths. These data are utilized for the remote sensing of aerosols, water vapor, ozone, and clouds, but the calibration constant, which is the sensor output current of the extraterrestrial solar irradiance at the mean distance between Earth and the Sun, is needed. The aerosol channels, which are the weak gas absorption wavelengths of 340, 380, 400, 500, 675, 870, and 1020 nm, can be calibrated by an on-site self-calibration method, the Improved Langley method. This on-site self-calibration method is useful for the continuous long-term observation of aerosol properties. However, the continuous long-term observation of precipitable water vapor (PWV) by the sky radiometer remains challenging because calibrating the water vapor absorption channel of 940 nm generally relies on the standard Langley (SL) method at limited observation sites (e.g., the Mauna Loa Observatory) and the transfer of the calibration constant by a side-by-side comparison with the reference sky radiometer calibrated by the SL method. In this study, we developed the SKYMAP algorithm, a new on-site method of self-calibrating the water vapor channel of the sky radiometer using diffuse radiances normalized by direct solar irradiance (normalized radiances). Because the sky radiometer measures direct solar irradiance and diffuse radiance using the same sensor, the normalization cancels the calibration constant included in the measurements. The SKYMAP algorithm consists of three steps. First, aerosol optical and microphysical properties are retrieved using direct solar irradiances and normalized radiances at aerosol channels. The aerosol optical properties at the water vapor channel are interpolated from those at aerosol channels. Second, PWV is retrieved using the angular distribution of the normalized radiances at the water vapor channel. Third, the calibration constant at the water vapor channel is estimated from the transmittance of PWV and aerosol optical properties. Intensive sensitivity tests of the SKYMAP algorithm using simulated data of the sky radiometer showed that the calibration constant is retrieved reasonably well for PWV cm, which indicates that the SKYMAP algorithm can calibrate the water vapor channel on-site in dry conditions. Next, the SKYMAP algorithm was applied to actual measurements under the clear-sky and low-PWV ( cm) conditions at two sites, Tsukuba and Chiba, Japan, and the annual mean calibration constants at the two sites were determined. The SKYMAP-derived calibration constants were 10.1 % and 3.2 % lower, respectively, than those determined by a side-by-side comparison with the reference sky radiometer. After determining the calibration constant, we obtained PWV from the direct solar irradiances in both the dry and wet seasons. The retrieved PWV values corresponded well to those derived from a global-navigation-satellite-system–global-positioning-system receiver, a microwave radiometer, and an AERONET (Aerosol Robotic Network) sun–sky radiometer at both sites. The correlation coefficients were greater than 0.96. We calculated the bias errors and the root mean square errors by comparing PWV between the DSRAD (direct solar irradiance) algorithm and other instruments. The magnitude of the bias error and the root mean square error were and  cm for PWV cm, respectively. However, our method tended to underestimate PWV in the wet conditions, and the magnitude of the bias error and the root mean square error became large, and  cm for PWV>3 cm, respectively. This problem was mainly due to the overestimation of the aerosol optical thickness before the retrieval of PWV. These results show that the SKYMAP algorithm enables us to observe PWV over the long term, based on its unique on-site self-calibration method.

An optimal estimation algorithm to retrieve the cloud optical depth (COD) and cloud particle effective radius (CER) from spectral zenith radiances observed by narrow field-of-view (FOV) ground-based sky radiometers was developed. To further address the filter degradation problem while analyzing long-term observation data, an on-site calibration procedure is proposed, which has good accuracy compared with the standard calibration transfer method. An error evaluation study conducted by assuming errors in observed transmittances and ancillary data for water vapor concentration and surface albedo suggests that the errors in input data affect retrieved CER more than COD. Except for some narrow domains that fall within a COD of

Time-resolved charge transport measurement for one-dimensional edge states is a powerful means for investigating nonequilibrium charge dynamics and underlying interaction effects therein. Here, we report a versatile on-chip time-resolved transport measurement scheme that does not require a quantum point contact and is therefore applicable to narrow-gap systems. We apply the technique to noninverted InAs/In_{x}Ga_{1−x}Sb composite quantum wells, where its ambipolar character enables us to demonstrate the scheme in both the electron and hole regimes separately using a single device. Time-resolved measurements in the quantum Hall regimes clearly exhibit the chirality of each carrier, with pulsed charge waveforms observed only for one magnetic field direction opposite for electrons and holes. Waveform analysis in the time domain reveals reduced group velocity and broadening of edge magnetoplasmon pulses in both the electron and hole regimes, suggesting the influence of charge puddles in the bulk. Our time-resolved measurement scheme, applicable to various systems, will pave the way for investigations of dynamical properties of exotic topological edge states.

The first intensive multicomponent ground-based remote-sensing observations by sky radiometer and multi-axis differential optical absorption spectroscopy (MAX-DOAS) were performed simultaneously at the SKYNET Phimai site located in central Thailand (15.18∘ N, 102.56∘ E) from January to April 2016. The period corresponds to the dry season associated with intense biomass burning (BB) activity around the site. The near-surface concentration of formaldehyde (HCHO) retrieved from MAX-DOAS was found to be a useful tracer for absorption aerosols from BB plumes, when BB was the dominant source of HCHO and absorption aerosols over other sources. As the HCHO concentration tripled from 3 to 9 ppbv, the ratio of gaseous glyoxal to HCHO concentrations in daytime decreased from ∼0.04 to ∼0.03, responding presumably to the increased contribution of volatile organic compound emissions from BB. In addition, clear increases in aerosol absorption optical depths (AAODs) retrieved from sky radiometer observations were seen with the HCHO enhancement. At a HCHO of 9 ppbv, AAOD at a wavelength of 340 nm reached as high as ∼0.15±0.03. The wavelength dependence of AAODs at 340–870 nm was quantified by the absorption Ångström exponent (AAE), providing evidence for the presence of brown carbon aerosols at an AAE of 1.5±0.2. Thus, our multicomponent observations around central Thailand are expected to provide unique constraints for understanding physical–chemical–optical properties of BB plumes.

Global observations of tropospheric nitrogen dioxide (NO2) columns have been shown to be feasible from space, but consistent multi-sensor records do not yet exist, nor are they covered by planned activities at the international level. Harmonised, multi-decadal records of NO2 columns and their associated uncertainties can provide crucial information on how the emissions and concentrations of nitrogen oxides evolve over time. Here we describe the development of a new, community best-practice NO2 retrieval algorithm based on a synthesis of existing approaches. Detailed comparisons of these approaches led us to implement an enhanced spectral fitting method for NO2, a 1°  ×  1° TM5-MP data assimilation scheme to estimate the stratospheric background and improve air mass factor calculations. Guided by the needs expressed by data users, producers, and WMO GCOS guidelines, we incorporated detailed per-pixel uncertainty information in the data product, along with easily traceable information on the relevant quality aspects of the retrieval. We applied the improved QA4ECV NO2 algorithm to the most current level-1 data sets to produce a complete 22-year data record that includes GOME (1995–2003), SCIAMACHY (2002–2012), GOME-2(A) (2007 onwards) and OMI (2004 onwards). The QA4ECV NO2 spectral fitting recommendations and TM5-MP stratospheric column and air mass factor approach are currently also applied to S5P-TROPOMI. The uncertainties in the QA4ECV tropospheric NO2 columns amount to typically 40 % over polluted scenes. The first validation results of the QA4ECV OMI NO2 columns and their uncertainties over Tai'an, China, in June 2006 suggest a small bias (−2 %) and better precision than suggested by uncertainty propagation. We conclude that our improved QA4ECV NO2 long-term data record is providing valuable information to quantitatively constrain emissions, deposition, and trends in nitrogen oxides on a global scale.

Quantifying aerosol absorption at ultraviolet (UV) wavelengths is important for monitoring air pollution and aerosol amounts using current (e.g., Aura/OMI) and future (e.g., TROPOMI, TEMPO, GEMS, and Sentinel-4) satellite measurements. Measurements of column average atmospheric aerosol single scattering albedo (SSA) are performed on the ground by the NASA AERONET in the visible (VIS) and near-infrared (NIR) wavelengths and in the UV-VIS-NIR by the SKYNET networks. Previous comparison studies have focused on VIS and NIR wavelengths due to the lack of co-incident measurements of aerosol and gaseous absorption properties in the UV. This study compares the SKYNET-retrieved SSA in the UV with the SSA derived from a combination of AERONET, MFRSR, and Pandora (AMP) retrievals in Seoul, South Korea, in spring and summer 2016. The results show that the spectrally invariant surface albedo assumed in the SKYNET SSA retrievals leads to underestimated SSA compared to AMP values at near UV wavelengths. Re-processed SKYNET inversions using spectrally varying surface albedo, consistent with the AERONET retrieval improve agreement with AMP SSA. The combined AMP inversions allow for separating aerosol and gaseous (NO2 and O3) absorption and provide aerosol retrievals from the shortest UVB (305 nm) through VIS to NIR wavelengths (870 nm).

Observations from the new Japanese geostationary satellite Himawari-8 permit quasi-real-time estimation of global shortwave radiation at an unprecedented temporal resolution. However, accurate comparisons with ground-truthing observations are essential to assess their uncertainty. In this study, we evaluated the Himawari-8 global radiation product AMATERASS using observations recorded at four SKYNET stations in Japan and, for certain analyses, from the surface network of the Japanese Meteorological Agency in 2016. We found that the spatiotemporal variability of the satellite estimates was smaller than that of the ground observations; variability decreased with increases in the time step and spatial domain. Cloud variability was the main source of uncertainty in the satellite radiation estimates, followed by direct effects caused by aerosols and bright albedo. Under all-sky conditions, good agreement was found between satellite and ground-based data, with a mean bias in the range of 20–30 W m−2 (i.e., AMATERASS overestimated ground observations) and a root mean square error (RMSE) of approximately 70–80 W m−2. However, results depended on the time step used in the validation exercise, on the spatial domain, and on the different climatological regions. In particular, the validation performed at 2.5 min showed largest deviations and RMSE values ranging from about 110 W m−2 for the mainland to a maximum of 150 W m−2 in the subtropical region. We also detected a limited overestimation in the number of clear-sky episodes, particularly at the pixel level. Overall, satellite-based estimates were higher under overcast conditions, whereas frequent episodes of cloud-induced enhanced surface radiation (i.e., measured radiation was greater than expected clear-sky radiation) tended to reduce this difference. Finally, the total mean bias was approximately 10–15 W m−2 under clear-sky conditions, mainly because of overall instantaneous direct aerosol forcing efficiency in the range of 120–150 W m−2 per unit of aerosol optical depth (AOD). A seasonal anticorrelation between AOD and global radiation differences was evident at all stations and was also observed within the diurnal cycle.

We performed a feasibility study of constraining the vertical profile of the tropospheric ozone by using a synergetic retrieval method on multiple spectra, i.e., ultraviolet (UV), thermal infrared (TIR), and microwave (MW) ranges, measured from space. This work provides, for the first time, a quantitative evaluation of the retrieval sensitivity of the tropospheric ozone by adding the MW measurement to the UV and TIR measurements. Two observation points in East Asia (one in an urban area and one in an ocean area) and two observation times (one during summer and one during winter) were assumed. Geometry of line of sight was nadir down-looking for the UV and TIR measurements, and limb sounding for the MW measurement. The retrieval sensitivities of the ozone profiles in the upper troposphere (UT), middle troposphere (MT), and lowermost troposphere (LMT) were estimated using the degree of freedom for signal (DFS), the pressure of maximum sensitivity, reduction rate of error from the a priori error, and the averaging kernel matrix, derived based on the optimal estimation method. The measurement noise levels were assumed to be the same as those for currently available instruments. The weighting functions for the UV, TIR, and MW ranges were calculated using the SCIATRAN radiative transfer model, the Line-By-Line Radiative Transfer Model (LBLRTM), and the Advanced Model for Atmospheric Terahertz Radiation Analysis and Simulation (AMATERASU), respectively. The DFS value was increased by approximately 96, 23, and 30 % by adding the MW measurements to the combination of UV and TIR measurements in the UT, MT, and LMT regions, respectively. The MW measurement increased the DFS value of the LMT ozone; nevertheless, the MW measurement alone has no sensitivity to the LMT ozone. The pressure of maximum sensitivity value for the LMT ozone was also increased by adding the MW measurement. These findings indicate that better information on LMT ozone can be obtained by adding constraints on the UT and MT ozone from the MW measurement. The results of this study are applicable to the upcoming air-quality monitoring missions, APOLLO, GMAP-Asia, and uvSCOPE.

A first direct intercomparison of aerosol vertical profiles from Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations, performed during the Cabauw Intercomparison Campaign of Nitrogen Dioxide measuring Instruments (CINDI) in summer 2009, is presented. Five out of 14 participants of the CINDI campaign reported aerosol extinction profiles and aerosol optical thickness (AOT) as deduced from observations of differential slant column densities of the oxygen collision complex (O4) at different elevation angles. Aerosol extinction vertical profiles and AOT are compared to backscatter profiles from a ceilometer instrument and to sun photometer measurements, respectively. Furthermore, the near-surface aerosol extinction coefficient is compared to in situ measurements of a humidity-controlled nephelometer and dry aerosol absorption measurements. The participants of this intercomparison exercise use different approaches for the retrieval of aerosol information, including the retrieval of the full vertical profile using optimal estimation and a parametrised approach with a prescribed profile shape. Despite these large conceptual differences, and also differences in the wavelength of the observed O4 absorption band, good agreement in terms of the vertical structure of aerosols within the boundary layer is achieved between the aerosol extinction profiles retrieved by the different groups and the backscatter profiles observed by the ceilometer instrument. AOTs from MAX-DOAS and sun photometer show a good correlation (R>0.8), but all participants systematically underestimate the AOT. Substantial differences between the near-surface aerosol extinction from MAX-DOAS and from the humidified nephelometer remain largely unresolved.

Coincident aerosol observations of multi-axis differential optical absorption spectroscopy (MAX-DOAS), cavity ring-down spectroscopy (CRDS), lidar, and sky radiometer were conducted in Tsukuba, Japan, on 5–18 October 2010. MAX-DOAS aerosol retrieval (for aerosol extinction coefficient and aerosol optical depth at 476 nm) was evaluated from the viewpoint of the need for a correction factor for oxygen collision complexes (O4 or O2–O2) absorption. The present study strongly supports this need, as systematic residuals at relatively high elevation angles (20 and 30°) were evident in MAX-DOAS profile retrievals conducted without the correction. However, adopting a single number for the correction factor (fO4 = 1.25) for all of the elevation angles led to systematic overestimation of near-surface aerosol extinction coefficients, as reported in the literature. To achieve agreement with all three observations, we limited the set of elevation angles to ≤10° and adopted an elevation-angle-dependent correction factor for practical profile retrievals with scattered light observations by a ground-based MAX-DOAS. With these modifications, we expect to minimize the possible effects of temperature-dependent O4 absorption cross section and uncertainty in DOAS fit on an aerosol profile retrieval, although more efforts are encouraged to quantitatively identify a physical explanation for the need of a correction factor.

We assess the standard operational nitrogen dioxide (NO2) data product (OMNO2, version 2.1) retrieved from the Ozone Monitoring Instrument (OMI) onboard NASA's Aura satellite using a combination of aircraft and surface in~situ measurements as well as ground-based column measurements at several locations and a bottom-up NOx emission inventory over the continental US. Despite considerable sampling differences, NO2 vertical column densities from OMI are modestly correlated (r = 0.3–0.8) with in situ measurements of tropospheric NO2 from aircraft, ground-based observations of NO2 columns from MAX-DOAS and Pandora instruments, in situ surface NO2 measurements from photolytic converter instruments, and a bottom-up NOx emission inventory. Overall, OMI retrievals tend to be lower in urban regions and higher in remote areas, but generally agree with other measurements to within ± 20%. No consistent seasonal bias is evident. Contrasting results between different data sets reveal complexities behind NO2 validation. Since validation data sets are scarce and are limited in space and time, validation of the global product is still limited in scope by spatial and temporal coverage and retrieval conditions. Monthly mean vertical NO2 profile shapes from the Global Modeling Initiative (GMI) chemistry-transport model (CTM) used in the OMI retrievals are highly consistent with in situ aircraft measurements, but these measured profiles exhibit considerable day-to-day variation, affecting the retrieved daily NO2 columns by up to 40%. This assessment of OMI tropospheric NO2 columns, together with the comparison of OMI-retrieved and model-simulated NO2 columns, could offer diagnostic evaluation of the model.

We investigated the effect of surface reflectance anisotropy, bidirectional reflectance distribution function (BRDF), on satellite retrievals of tropospheric NO2. We assume the geometry of geostationary measurements over Tokyo, which is one of the worst air-polluted regions in East Asia. We calculated air mass factors (AMF) and box AMFs (BAMF) for tropospheric NO2 to evaluate the effect of BRDF by using the radiative transfer model SCIATRAN. To model the BRDF effect, we utilized the Moderate Resolution Imaging Spectroradiometer (MODIS) products (MOD43B1 and MOD43B2), which provide three coefficients to express the RossThick–LiSparse reciprocal model, a semi-empirical and kernel-based model of BRDF. Because BRDF depends on the land cover type, we also utilized the High Resolution Land-Use and Land-Cover Map of the Advanced Land Observing Satellite (ALOS)/Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2), which classifies the ground pixels over Tokyo into six main types: water, urban, paddy, crop, deciduous forest, and evergreen forest. We first develop an empirical model of the three BRDF coefficients for each land cover type over Tokyo and then apply the model to the calculation of land-cover-type-dependent AMFs and BAMFs. Results show that the variability of AMF among the land types is up to several tens of percent, and if we neglect the reflectance anisotropy, the difference with AMFs based on BRDF reaches 10% or more. The evaluation of the BAMFs calculated shows that not considering BRDF will cause large errors if the concentration of NO2 is high close to the surface, although the importance of BRDF for AMFs decreases for large aerosol optical depth (AOD).

We conducted long-term network observations using standardized Multi-Axis Differential optical absorption spectroscopy (MAX-DOAS) instruments in Russia and ASia (MADRAS) from 2007 onwards and made the first synthetic data analysis. At seven locations (Cape Hedo, Fukue and Yokosuka in Japan, Hefei in China, Gwangju in Korea, and Tomsk and Zvenigorod in Russia) with different levels of pollution, we obtained 80 927 retrievals of tropospheric NO2 vertical column density (TropoNO2VCD) and aerosol optical depth (AOD). In the technique, the optimal estimation of the TropoNO2VCD and its profile was performed using aerosol information derived from O4 absorbances simultaneously observed at 460–490 nm. This large data set was used to analyze NO2 climatology systematically, including temporal variations from the seasonal to the diurnal scale. The results were compared with Ozone Monitoring Instrument (OMI) satellite observations and global model simulations. Two NO2 retrievals of OMI satellite data (NASA ver. 2.1 and Dutch OMI NO2 (DOMINO) ver. 2.0) generally showed close correlations with those derived from MAX-DOAS observations, but had low biases of up to ~50%. The bias was distinct when NO2 was abundantly present near the surface and when the AOD was high, suggesting a possibility of incomplete accounting of NO2 near the surface under relatively high aerosol conditions for the satellite observations. Except for constant biases, the satellite observations showed nearly perfect seasonal agreement with MAX-DOAS observations, suggesting that the analysis of seasonal features of the satellite data were robust. Weekend reduction in the TropoNO2VCD found at Yokosuka and Gwangju was absent at Hefei, implying that the major sources had different weekly variation patterns. While the TropoNO2VCD generally decreased during the midday hours, it increased exceptionally at urban/suburban locations (Yokosuka, Gwangju, and Hefei) during winter. A global chemical transport model, MIROC-ESM-CHEM (Model for Interdisciplinary Research on Climate–Earth System Model–Chemistry), was validated for the first time with respect to background NO2 column densities during summer at Cape Hedo and Fukue in the clean marine atmosphere.

Satellite observations of the tropospheric NO2 vertical column density (VCD) are closely correlated to, and thus can be used to estimate, surface NOx emissions. In this study, the NO2 VCD simulated by a regional chemical transport model with emissions data from the updated Regional Emission inventory in ASia (REAS) version 2.1 were validated through comparison with multisatellite observations during the period 2000–2010. Rapid growth in NO2 VCD (~11% year−1) driven by the expansion of anthropogenic NOx emissions was identified above the central eastern China (CEC) region, except for the period during the economic downturn. In contrast, slightly decreasing trends (~2% year−1) were identified above Japan accompanied by a decline in anthropogenic emissions. To systematically compare the modeled NO2 VCD, we estimated sampling bias and the effect of applying the averaging kernel information, with particular focus on the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) data. Using the updated REAS, the modeled NO2 VCD reasonably reproduced annual trends observed by multisatellites, suggesting that the rate of increase of NOx emissions estimated by the updated REAS inventory would be robust. Province-scale revision of emissions above CEC is needed to further refine emission inventories. Based on the close linear relationship between modeled and observed NO2 VCD and anthropogenic NOx emissions, NOx emissions in 2009 and 2010, which were not covered by the updated REAS inventory, were estimated. NOx emissions from anthropogenic sources in China in 2009 and 2010 were determined to be 26.4 and 28.5 Tg year−1, respectively, indicating that NOx emissions increased more than twofold between 2000 and 2010. This increase reflected the strong growth of anthropogenic emissions in China following the rapid recovery from the economic downturn from late 2008 until mid-2009. Our method consists of simple estimations from satellite observations and provides results that are consistent with the most recent inventory of emissions data for China.

Retrievals of tropospheric nitrogen dioxide (NO2) from the Ozone Monitoring Instrument (OMI) are subject to errors in the treatments of aerosols, surface reflectance anisotropy, and vertical profile of NO2. Here we quantify the influences over China via an improved retrieval process. We explicitly account for aerosol optical effects (simulated by nested GEOS-Chem at 0.667° long. × 0.5° lat. and constrained by aerosol measurements), surface reflectance anisotropy, and high-resolution vertical profiles of NO2 (simulated by GEOS-Chem). Prior to the NO2 retrieval, we derive the cloud information using consistent ancillary assumptions. We compare our retrieval to the widely used DOMINO v2 product, using MAX-DOAS measurements at three urban/suburban sites in East China as reference and focusing the analysis on the 127 OMI pixels (in 30 days) closest to the MAX-DOAS sites. We find that our retrieval reduces the interference of aerosols on the retrieved cloud properties, thus enhancing the number of valid OMI pixels by about 25%. Compared to DOMINO v2, our retrieval better captures the day-to-day variability in MAX-DOAS NO2 data (R2 = 0.96 versus 0.72), due to pixel-specific radiative transfer calculations rather than the use of a look-up table, explicit inclusion of aerosols, and consideration of surface reflectance anisotropy. Our retrieved NO2 columns are 54% of the MAX-DOAS data on average, reflecting the inevitable spatial inconsistency between the two types of measurement, errors in MAX-DOAS data, and uncertainties in our OMI retrieval related to aerosols and vertical profile of NO2. Sensitivity tests show that excluding aerosol optical effects can either increase or decrease the retrieved NO2 for individual OMI pixels with an average increase by 14%. Excluding aerosols also complexly affects the retrievals of cloud fraction and particularly cloud pressure. Employing various surface albedo data sets slightly affects the retrieved NO2 on average (within 10%). The retrieved NO2 columns increase when the NO2 profiles are taken from MAX-DOAS retrievals (by 19% on average) or TM4 simulations (by 13%) instead of GEOS-Chem simulations. Our findings are also relevant to retrievals of other pollutants (e.g., sulfur dioxide, ormaldehyde, glyoxal) from UV–visible backscatter satellite instruments.

We conducted an intensive field campaign at the summit of Mt. Tai (36.26° N, 117.11° E, 1534 m above sea level), Shandong Province, located at the center of central East China, during the period 28 May to 30 June 2006, to study seasonal maxima of regional air pollution with respect to ozone (O3) and aerosols. The specific objectives, campaign design, and major findings are summarized. High concentrations of O3 and its precursors, and aerosols, were detected and studied in the context of annual variations. Most importantly, we identified that emissions from regional-scale open crop residue burning after the harvesting of winter wheat, together with photochemical aging, strongly increased the concentrations of O3, aerosols, and primary pollutants in this month of year. Studies of in situ photochemical activity, regional source attribution of O3, O3–aerosol interactions, validation of satellite observations of tropospheric NO2, behaviors of volatile organic compounds and organic/inorganic aerosol species, loss rates of black carbon (BC), and instrument inter-comparisons are also summarized. The observed BC levels must have a strong impact on the regional climate.

Gaseous and particulate semi-volatile carbonyl compounds were determined every three hours in the atmosphere of Mount Tai (elevation, 1534 m) in the North China Plain during 2–5, 23–24 and 25 June 2006 under clear sky conditions. Using a two-step filter cartridge in a series, particulate carbonyls were first collected on a quartz filter and then gaseous carbonyls were collected on a quartz filter impregnated with O-benzylhydroxylamine (BHA). After the two-step derivatization with BHA and N,O-Bis(trimethylsilyl)trifluoroacetamide (BSTFA), carbonyl derivatives were measured using a gas chromatography. The gaseous concentrations were obtained as follow: glycolaldehyde (range 0–826 ng m−3, average 303 ng m−3), hydroxyacetone (0–579 ng m−3, 126 ng m−3), glyoxal (46–1200 ng m−3, 487 ng m−3), methylglyoxal (88–2690 ng m−3, 967 ng m−3), n-nonanal (0–500 ng m−3, 89 ng m−3), and n-decanal (0–230 ng m−3, 39 ng m−3). These concentrations are among the highest ever reported in the urban and forest atmosphere. We found that gaseous α-dicarbonyls (glyoxal and methylglyoxal) are more than 20 times more abundant than particulate carbonyls and that glycolaldehyde is one order of magnitude more abundant than in aerosol phase. In contrast, hydroxyacetone and normal aldehydes (nonanal and decanal) are equally present in both phases. Time-resolved variations of carbonyls did not show any a clear diurnal pattern, except for hydroxyacetone. We found that glyoxal, methylglyoxal and glycolaldehyde positively correlated with levoglucosan (a tracer of biomass burning), suggesting that a contribution from field burning of agricultural wastes (wheat crops) is significant for the bifunctional carbonyls in the atmosphere of Mt. Tai. Upward transport of the pollutants to the mountaintop from the low lands in the North China Plain is a major process to control the distributions of carbonyls in the upper atmosphere over Mt. Tai.

We present intercomparison results for formaldehyde (HCHO) slant column measurements performed during the Cabauw Intercomparison campaign of Nitrogen Dioxide measuring Instruments (CINDI) that took place in Cabauw, the Netherlands, in summer 2009. During two months, nine atmospheric research groups simultaneously operated MAX-DOAS (MultiAXis Differential Optical Absorption Spectroscopy) instruments of various designs to record UV-visible spectra of scattered sunlight at different elevation angles that were analysed using common retrieval settings. The resulting HCHO data set was found to be highly consistent, the mean difference between instruments generally not exceeding 15% or 7.5 × 1015 molec cm−2, for all viewing elevation angles. Furthermore, a sensitivity analysis was performed to investigate the uncertainties in the HCHO slant column retrieval when varying key input parameters such as the molecular absorption cross sections, correction terms for the Ring effect or the width and position of the fitting interval. This study led to the identification of potentially important sources of errors associated with cross-correlation effects involving the Ring effect, O4, HCHO and BrO cross sections and the DOAS closure polynomial. As a result, a set of updated recommendations was formulated for HCHO slant column retrieval in the 336.5–359 nm wavelength range. To conclude, an error budget is proposed which distinguishes between systematic and random uncertainties. The total systematic error is estimated to be of the order of 20% and is dominated by uncertainties in absorption cross sections and related spectral cross-correlation effects. For a typical integration time of one minute, random uncertainties range between 5 and 30%, depending on the noise level of individual instruments.

For the intercomparison of tropospheric nitrogen dioxide (NO2) vertical column density (VCD) data from three different satellite sensors (SCIAMACHY, OMI, and GOME-2), we use a common standard to quantitatively evaluate the biases for the respective data sets. As the standard, a regression analysis using a single set of collocated ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations at several sites in Japan and China from 2006–2011 is adopted. Examinations of various spatial coincidence criteria indicates that the slope of the regression line can be influenced by the spatial distribution of NO2 over the area considered. While the slope varies systematically with the distance between the MAX-DOAS and satellite observation points around Tokyo in Japan, such a systematic dependence is not clearly seen and correlation coefficients are generally higher in comparisons at sites in China. On the basis of these results, we focus mainly on comparisons over China and estimate the biases in SCIAMACHY, OMI, and GOME-2 data (TM4NO2A and DOMINO version 2 products) against the MAX-DOAS observations to be −5 ± 14%, −10 ± 14%, and +1 ± 14%, respectively, which are all small and insignificant. We suggest that these small biases now allow for analyses combining these satellite data for air quality studies, which are more systematic and quantitative than previously possible.

Nitrogen dioxide (NO2) profile retrievals were performed by ship-borne Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) using a compact/low-power spectrometer on the Japanese research vessel Kaiyo during two ocean cruises around Japan and Japan–Bali (Indonesia)–Indian Ocean. DOAS analysis using a 425–450 nm fitting window revealed a clear land–ocean contrast in NO2 differential slant column densities (DSCDs) but poor fitting results and negative values, especially at low elevation angles at low latitudes (2 volume mixing ratio (VMR) data for the 0–1 km layer after applying our vertical profile retrieval method. In contrast, NO2 VMRs retrieved using fitting results from 460–490 nm are positive even at low latitudes, while they are reasonably similar to those obtained from 425–450 nm at mid-latitudes. Because NO2 DSCD for 425–450 nm shows a negative correlation with water vapor (H2O) DSCD, the poor fitting appears to be due primarily to interference by H2O. We analyzed a 338–370 nm fitting window, which is free from H2O, and found good agreement between NO2 VMRs retrieved from 460–490 nm and 338–370 nm, even at low latitudes, at NO2 VMRs higher than ~0.2 ppbv. The results indicate that the background value of NO2 VMR over the western Pacific and Indian Ocean during the cruises was less than ~0.2 ppbv, with occasional enhancement to levels of ~0.2–0.4 ppbv.

Anthropogenic SO2 emissions increased alongside economic development in China at a rate of 12.7% yr−1 from 2000 to 2005. However, under new Chinese government policy, SO2 emissions declined by 3.9% yr−1 between 2005 and 2009. Between 2000 and 2010, we found that the variability in the fine-mode (submicron) aerosol optical depth (AOD) over the oceans adjacent to East Asia increased by 3–8% yr−1 to a peak around 2005–2006 and subsequently decreased by 2–7% yr−1, based on observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) on board NASA's Terra satellite and simulations by a chemical transport model. This trend is consistent with ground-based observations of aerosol particles at a mountainous background observation site in central Japan. These fluctuations in SO2 emission intensity and fine-mode AOD are thought to reflect the widespread installation of fuel-gas desulfurization (FGD) devices in power plants in China, because aerosol sulfate is a major determinant of the fine-mode AOD in East Asia. Using a chemical transport model, we confirmed that the contribution of particulate sulfate to the fine-mode AOD is more than 70% of the annual mean and that the abovementioned fluctuation in fine-mode AOD is caused mainly by changes in SO2 emission rather than by other factors such as varying meteorological conditions in East Asia. A strong correlation was also found between satellite-retrieved SO2 vertical column density and bottom-up SO2 emissions, both of which were also consistent with observed fine-mode AOD trends. We propose a simplified approach for evaluating changes in SO2 emissions in China, combining the use of modeled sensitivity coefficients that describe the variation of fine-mode AOD with changes in SO2 emissions and satellite retrieval. Satellite measurements of fine-mode AOD above the Sea of Japan marked a 4.1% yr−1 decline between 2007 and 2010, which corresponded to the 9% yr−1 decline in SO2 emissions from China during the same period.

From June to July 2009 more than thirty different in-situ and remote sensing instruments from all over the world participated in the Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI). The campaign took place at KNMI's Cabauw Experimental Site for Atmospheric Research (CESAR) in the Netherlands. Its main objectives were to determine the accuracy of state-of-the-art ground-based measurement techniques for the detection of atmospheric nitrogen dioxide (both in-situ and remote sensing), and to investigate their usability in satellite data validation. The expected outcomes are recommendations regarding the operation and calibration of such instruments, retrieval settings, and observation strategies for the use in ground-based networks for air quality monitoring and satellite data validation. Twenty-four optical spectrometers participated in the campaign, of which twenty-one had the capability to scan different elevation angles consecutively, the so-called Multi-axis DOAS systems, thereby collecting vertical profile information, in particular for nitrogen dioxide and aerosol. Various in-situ samplers and lidar instruments simultaneously characterized the variability of atmospheric trace gases and the physical properties of aerosol particles. A large data set of continuous measurements of these atmospheric constituents has been collected under various meteorological conditions and air pollution levels. Together with the permanent measurement capability at the CESAR site characterizing the meteorological state of the atmosphere, the CINDI campaign provided a comprehensive observational data set of atmospheric constituents in a highly polluted region of the world during summertime. First detailed comparisons performed with the CINDI data show that slant column measurements of NO2, O4 and HCHO with MAX-DOAS agree within 5 to 15%, vertical profiles of NO2 derived from several independent instruments agree within 25% of one another, and MAX-DOAS aerosol optical thickness agrees within 20–30% with AERONET data. For the in-situ NO2 instrument using a molybdenum converter, a bias was found as large as 5 ppbv during day time, when compared to the other in-situ instruments using photolytic converters.

Understanding the relationship between black carbon (BC) and carbon monoxide (CO) will help improve BC emission inventories and the evaluation of global/regional climate forcing effects. In the present work, the BC (PM1) mass concentration and CO mixing ratio were continuously measured at a high-altitude background station on the summit of Mt. Huang (30.16° N, 118.26° E, 1840 m a.s.l.). Annual mean BC mass concentration was 1004.5 ± 895.5 ng m−3 with maxima in spring and autumn, and annual mean CO mixing ratio was 424.1 ± 159.2 ppbv. A large increase of CO was observed in the cold season, implying the contribution from the large-scale domestic coal/biofuel combustion for heating. The BC-CO relationship was found to show different seasonal features but strong positive correlation (R>0.8). In Mt. Huang area, the ΔBC/ΔCO ratio showed unimodal diurnal variations and had a maximum during the day (09:00–17:00 LST) and minimum at night (21:00–04:00 LST) in all seasons, indicating the impact of planetary boundary layer and the intrusion of clean air masses from the high troposphere. Back trajectory cluster analysis showed that the ΔBC/ΔCO ratio of plumes from the Eastern China (Jiangsu, Zhejiang provinces and Shanghai) was 8.8 ± 0.9 ng m−3 ppbv−1. Transportation and industry were deemed as controlling factors of the BC-CO relationship in this region. The ΔBC/ΔCO ratios for air masses from Northern China (Anhui, Henan, Shanxi and Shandong provinces) and southern China (Jiangxi, Fujian and Hunan provinces) were quite similar with mean values of 6.5 ± 0.4 and 6.5 ± 0.2 ng m−3 ppbv−1 respectively. The case studies combined with satellite observations demonstrated that the ΔBC/ΔCO ratio for biomass burning (BB) plumes were 10.3 ± 0.3 and 11.6 ± 0.5ng m−3 ppbv−1, significantly higher than those during non-BB impacted periods. The loss of BC during transport was also investigated on the basis of the ΔBC/ΔCO-RH (relative humidity) relationship along air mass pathways. The results showed that BC particles from Eastern China area was much more easily removed from atmosphere than other inland regions due to the higher RH along transport pathway, implying the importance of chemical compositions and mixing states on BC residence time in the atmosphere.

We attempt for the first time to retrieve lower-tropospheric vertical profile information for 8 quantities from ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations. The components retrieved are the aerosol extinction coefficients at two wavelengths, 357 and 476 nm, and NO2, HCHO, CHOCHO, H2O, SO2, and O3 volume mixing ratios. A Japanese MAX-DOAS profile retrieval algorithm, version 1 (JM1), is applied to observations performed at Cabauw, the Netherlands (51.97° N, 4.93° E), in June–July 2009 during the Cabauw Intercomparison campaign of Nitrogen Dioxide measuring Instruments (CINDI). Of the retrieved profiles, we focus here on the lowest-layer data (mean values at altitudes 0–1 km), where the sensitivity is usually highest owing to the longest light path. In support of the capability of the multi-component retrievals, we find reasonable overall agreement with independent data sets, including a regional chemical transport model (CHIMERE) and in situ observations performed near the surface (2–3 m) and at the 200-m height level of the tall tower in Cabauw. Plumes of enhanced HCHO and SO2 were likely affected by biogenic and ship emissions, respectively, and an improvement in their emission strengths is suggested for better agreement between CHIMERE simulations and MAX-DOAS observations. Analysis of air mass factors indicates that the horizontal spatial representativeness of MAX-DOAS observations is about 3–15 km (depending mainly on aerosol extinction), comparable to or better than the spatial resolution of current UV-visible satellite observations and model calculations. These demonstrate that MAX-DOAS provides multi-component data useful for the evaluation of satellite observations and model calculations and can play an important role in bridging different data sets having different spatial resolutions.

In the field, aerosol in-situ measurements are often performed under dry conditions (relative humidity RHsp(λ) was measured dry and at various, predefined RH conditions between 20 and 95% with a humidified nephelometer. The scattering enhancement factor f(RH,λ) is the key parameter to describe the effect of RH on σsp(λ) and is defined as σsp(RH,λ) measured at a certain RH divided by the dry σsp(dry,λ). The measurement of f(RH,λ) together with the dry absorption measurement (assumed not to change with RH) allows the determination of the actual extinction coefficient σep(RH,λ) at ambient RH. In addition, a wide range of other aerosol properties were measured in parallel. The measurements were used to characterize the effects of RH on the aerosol optical properties. A closure study showed the consistency of the aerosol in-situ measurements. Due to the large variability of air mass origin (and thus aerosol composition) a simple parameterization of f(RH,λ) could not be established. If f(RH,λ) needs to be predicted, the chemical composition and size distribution need to be known. Measurements of four MAX-DOAS (multi-axis differential optical absorption spectroscopy) instruments were used to retrieve vertical profiles of σep(λ). The values of the lowest layer were compared to the in-situ values after conversion of the latter ones to ambient RH. The comparison showed a good correlation of R2 = 0.62–0.78, but the extinction coefficients from MAX-DOAS were a factor of 1.5–3.4 larger than the in-situ values. Best agreement is achieved for a few cases characterized by low aerosol optical depths and low planetary boundary layer heights. Differences were shown to be dependent on the applied MAX-DOAS retrieval algorithm. The comparison of the in-situ extinction data to a Raman LIDAR (light detection and ranging) showed a good correlation and higher values measured by the LIDAR (R2 = 0.82−0.85, slope of 1.69–1.76) if the Raman retrieved profile was used to extrapolate the directly measured extinction coefficient to the ground. The comparison improved if only nighttime measurements were used in the comparison (R2 = 0.96, slope of 1.12).

In June 2009, 22 spectrometers from 14 institutes measured tropospheric and stratospheric NO2 from the ground for more than 11 days during the Cabauw Intercomparison Campaign of Nitrogen Dioxide measuring Instruments (CINDI), at Cabauw, NL (51.97° N, 4.93° E). All visible instruments used a common wavelength range and set of cross sections for the spectral analysis. Most of the instruments were of the multi-axis design with analysis by differential spectroscopy software (MAX-DOAS), whose non-zenith slant columns were compared by examining slopes of their least-squares straight line fits to mean values of a selection of instruments, after taking 30-min averages. Zenith slant columns near twilight were compared by fits to interpolated values of a reference instrument, then normalised by the mean of the slopes of the best instruments. For visible MAX-DOAS instruments, the means of the fitted slopes for NO2 and O4 of all except one instrument were within 10% of unity at almost all non-zenith elevations, and most were within 5%. Values for UV MAX-DOAS instruments were almost as good, being 12% and 7%, respectively. For visible instruments at zenith near twilight, the means of the fitted slopes of all instruments were within 5% of unity. This level of agreement is as good as that of previous intercomparisons, despite the site not being ideal for zenith twilight measurements. It bodes well for the future of measurements of tropospheric NO2, as previous intercomparisons were only for zenith instruments focussing on stratospheric NO2, with their longer heritage.

The impact of open crop residual burning (OCRB) on O3, CO, black carbon (BC) and organic carbon (OC) concentrations over Central Eastern China (CEC; 30–40° N, 111–120° E), during the Mount Tai Experiment in 2006 (MTX2006) was evaluated using a regional chemical transport model, the Models–3 Community Multiscale Air Quality Modeling System (CMAQ). To investigate these pollutants during MTX2006 in June 2006, daily gridded OCRB emissions were developed based on a bottom-up methodology using land cover and hotspot information from satellites. This model system involving daily emissions captured monthly–averages of observed concentrations and day-to-day variations in the patterns of O3, CO, BC and OC at the summit of Mount Tai (36° N, 117° E, 1534 m a.s.l., Shandong Province of the People's Republic of China) with high correlation coefficients between the model and observations ranging from 0.55 to 0.69. These results were significantly improved from those using annual biomass burning emissions. For monthly-averaged O3, the simulated concentration of 80.8 ppbv was close to the observed concentration (81.3 ppbv). The MTX2006 period was roughly divided into two parts: 1) polluted days with heavy OCRB in the first half of June; and 2) cleaner days with negligible field burning in the latter half of June. Additionally, the first half of June was characterized by two high-pollution episodes during 5–7 and 12–13 June, separated by a relatively cleaner intermediate period during 8–10 June. In the first high-pollution episode, the model captured the high O3, CO, BC and OC concentrations at the summit of Mount Tai, which were associated with OCRB over southern CEC and subsequent northward transport. For this episode, the impacts of OCRB emissions on pollutant concentrations were 26% (O3), 62% (CO), 79% (BC) and 80% (OC) at the summit of Mount Tai. The daily OCRB emissions were an essential factor in the evaluation of these pollutants during MTX2006. These emissions have a large impact not only on primary pollutants but also on secondary pollutants, such as O3, in the first half of June over northeastern Asia. The model reproduced reasonably well the variation of these pollutants in MTX2006, but underestimated daily averages of both CO and BC by a factor of 2, when using emission data from almost solely anthropogenic fuel sources in the latter half of the observation period when field burning can be neglected.

We present vertical profiles of the aerosol extinction coefficient retrieved from ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements at Tsukuba, Japan (36.1° N, 140.1° E), from November 2006 to March 2007. Retrievals utilizing absorption by the oxygen collision complex O4 are first made at two wavelengths, 354 and 476 nm. A robust assessment of the MAX-DOAS aerosol data is then made using coincident lidar measurements throughout the period. Agreement between aerosol extinction coefficients measured by MAX-DOAS and the lidar tends to be better at the longer wavelength and at lower altitudes. At 476 nm, the best agreement, to within 30%, is found at altitudes of 0–1 km, confirming results from a literature assessment for a two-month measurement period. These findings are supported by comparisons between aerosol optical depths derived from MAX-DOAS and sky radiometer measurements and are further explained by differences in the altitude-dependent measurement sensitivity to the aerosol extinction coefficient between 354 and 476 nm. Thus, uncertainty in MAX-DOAS aerosol measurements is well quantified and characterized, providing a basis for quantitative studies using MAX-DOAS measurements.

A challenge for the quantitative analysis of tropospheric nitrogen dioxide (NO2) column data from satellite observations is posed partly by the lack of satellite-independent observations for validation. We performed such observations of the tropospheric NO2 column using the ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) technique in the North China Plain (NCP) from 29 May to 29 June, 2006. Comparisons between tropospheric NO2 columns measured by MAX-DOAS and the Ozone Monitoring Instrument (OMI) onboard the Aura satellite indicate that OMI data (the standard product, version 3) over NCP may have a positive bias of 1.6×1015 molecules cm−2 (20%), yet within the uncertainty of the OMI data. Combining these results with literature validation results for the US, Europe, and Pacific Ocean suggests that a bias of +20%/−30% is a reasonable estimate, accounting for different regions.

Ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements were performed at Tsukuba, Japan (36.1° N, 140.1° E), in November–December 2006. By analyzing the measured spectra of scattered sunlight with DOAS and optimal estimation methods, we first retrieve the aerosol optical depth (τ) and the vertical profile of the aerosol extinction coefficient (k) at 476 nm in the lower troposphere. These retrieved quantities are characterized through comparisons with coincident lidar and sky radiometer measurements. The retrieved k values for layers of 0–1 and 1–2 km agree with lidar data to within 30% and 60%, respectively, for most cases, including partly cloudy conditions. Results similar to k at 0–1 km are obtained for the retrieved τ values, demonstrating that MAX-DOAS provides a new, unique aerosol dataset in the lower troposphere.

Formaldehyde (HCHO), the most abundant carbonyl compound in the atmosphere, is generated as an intermediate product in the oxidation of nonmethane hydrocarbons. Proton transfer reaction mass spectrometry (PTR-MS) has the capability to detect HCHO from ion signals at m/z 31 with high time-resolution. However, the detection sensitivity is low compared to other detectable species, and is considerably affected by humidity, due to back reactions between protonated HCHO and water vapor prior to analysis. We performed a laboratory calibration of PTR-MS for HCHO and examined the detection sensitivity and humidity dependence at various field strengths. Subsequently, we deployed the PTR-MS instrument in a field campaign at Mount Tai in China in June 2006 to measure HCHO in various meteorological and photochemical conditions; we also conducted intercomparison measurements by Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS). Correction of interference in the m/z 31 signals by fragments from proton transfer reactions with methyl hydroperoxide, methanol, and ethanol greatly improves agreement between the two methods, giving the correlation [HCHO]MAX-DOAS=(0.99±0.16) [HCHO]PTR-MS+(0.02±0.38), where error limits represent 95% confidence levels.

The results of a comparison exercise of radiative transfer models (RTM) of various international research groups for Multiple AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) viewing geometry are presented. Besides the assessment of the agreement between the different models, a second focus of the comparison was the systematic investigation of the sensitivity of the MAX-DOAS technique under various viewing geometries and aerosol conditions. In contrast to previous comparison exercises, box-air-mass-factors (box-AMFs) for different atmospheric height layers were modelled, which describe the sensitivity of the measurements as a function of altitude. In addition, radiances were calculated allowing the identification of potential errors, which might be overlooked if only AMFs are compared. Accurate modelling of radiances is also a prerequisite for the correct interpretation of satellite observations, for which the received radiance can strongly vary across the large ground pixels, and might be also important for the retrieval of aerosol properties as a future application of MAX-DOAS. The comparison exercises included different wavelengths and atmospheric scenarios (with and without aerosols). The strong and systematic influence of aerosol scattering indicates that from MAX-DOAS observations also information on atmospheric aerosols can be retrieved. During the various iterations of the exercises, the results from all models showed a substantial convergence, and the final data sets agreed for most cases within about 5%. Larger deviations were found for cases with low atmospheric optical depth, for which the photon path lengths along the line of sight of the instrument can become very large. The differences occurred between models including full spherical geometry and those using only plane parallel approximation indicating that the correct treatment of the Earth's sphericity becomes indispensable. The modelled box-AMFs constitute an universal data base for the calculation of arbitrary (total) AMFs by simple convolution with a given trace gas concentration profile. Together with the modelled radiances and the specified settings for the various exercises, they can serve as test cases for future RTM developments.

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) onboard the ENVISAT satellite provides profiles of temperature and various trace-gases from limb-viewing mid-infrared emission measurements. The stratospheric nitric acid (HNO3) from September 2002 to March 2004 was retrieved from the MIPAS observations using the science-oriented data processor developed at the Institut für Meteorologie und Klimaforschung (IMK), which is complemented by the component of non-local thermodynamic equilibrium (non-LTE) treatment from the Instituto de Astrofísica de Andalucía (IAA). The IMK-IAA research product, different from the ESA operational product, is validated in this paper by comparison with a number of reference data sets. Individual HNO3 profiles of the IMK-IAA MIPAS show good agreement with those of the balloon-borne version of MIPAS (MIPAS-B) and the infrared spectrometer MkIV, with small differences of less than 0.5 ppbv throughout the entire altitude range up to about 38 km, and below 0.2 ppbv above 30 km. However, the degree of consistency is largely affected by their temporal and spatial coincidence, and differences of 1 to 2 ppbv may be observed between 22 and 26 km at high latitudes near the vortex boundary, due to large horizontal inhomogeneity of HNO3. Statistical comparisons of MIPAS IMK-IAA HNO3 VMRs with respect to those of satellite measurements of Odin/SMR, ILAS-II, ACE-FTS, as well as the MIPAS ESA product show good consistency. The mean differences are generally ±0.5 ppbv and standard deviations of the differences are of 0.5 to 1.5 ppbv. The maximum differences are 2.0 ppbv around 20 to 25 km. This gives confidence in the general reliability of MIPAS HNO3 VMR data and the other three satellite data sets.

No abstract available.