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.

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 NO_x 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 NO_x 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 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.

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.

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.

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.