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Satellite-based observations of free-tropospheric water vapour isotopologue ratios (HDO / H 2 O, expressed in form of the δ value δ D) with good global and temporal coverage have become available recently. We investigate the potential of these observations for constraining the uncertainties of the atmospheric analyses fields of specific humidity (q), temperature (T), and δ D and of variables that capture important properties of the atmospheric water cycle, namely the vertical velocity (ω), the latent heating rate (Q2), and the precipitation rate (Prcp). Our focus is on the impact of the δ D observations relative to the impact achieved by the observation of q and T , which are much more easily observed by satellites and are routinely in use for atmospheric analyses. For our investigations we use an Observing System Simulation Experiment; i.e. we simulate the satellite observations of q , T , and δ D with known uncertainties and coverage (e.g. observations are not available for cloudy conditions, i.e. at locations where the atmosphere is vertically unstable). Then we use the simulated observations within a Kalman-filter-based assimilation framework in order to evaluate their potential for improving the quality of atmospheric analyses. The study is made for low latitudes (30° S to 30° N) and for 40 d between mid-July and the end of August 2016. We find that q observations generally have the largest impacts on the analyses' quality and that T observations have stronger impacts overall than δ D observations. We show that there is no significant impact of δ D observations for stable atmospheric conditions; however, for very unstable conditions, the impact of δ D observations is significant and even slightly stronger than the respective impact of T observations. Very unstable conditions are rare but are related to extreme events (e.g. storms, flooding); i.e. the δ D observations significantly impact the analyses' quality of the events that have the largest societal consequences. The fact that no satellite observations are available at the location and time of the unstable conditions indicates a remote impact of δ D observations that are available elsewhere. Concerning real-world applications, we conclude that the situation of δ D satellite observations is very promising but that further improving the model's linkage between convective processes and the larger-scale δ D fields might be needed for optimizing the assimilation impact of real-world δ D observations. [ABSTRACT FROM AUTHOR]

​​​​​​​Volatile organic compounds (VOCs) play a key role in tropospheric chemistry, giving rise to secondary products such as highly oxygenated organic molecules (HOMs) and secondary organic aerosols (SOAs). HOMs, a group of low-volatility gas-phase products, are formed through the autoxidation process of peroxy radicals (RO 2) originating from the oxidation of VOCs. The measurement of HOMs is made by a NO 3- ToFCIMS instrument, which also detects other species like small highly oxygenated VOCs (e.g., dicarboxylic acids) and sulfuric acid (H 2 SO 4). The instrument response to HOMs is typically estimated using H 2 SO 4 , as HOMs are neither commercially available nor easily synthesized in the laboratory. The resulting calibration factor is then applied to quantify all species detected using this technique. In this study, we explore the sensitivity of the instrument to commercially available small organic compounds, primarily dicarboxylic acids, given the limitations associated with producing known amounts of HOMs for calibration. We compare these single-compound calibration factors to the one obtained for H 2 SO 4 under identical operational conditions. The study found that the sensitivity of the NO 3- ToFCIMS varies depending on the specific type of organic compound, illustrating how a single calibration factor derived from sulfuric acid is clearly inadequate for quantifying all detected species using this technique. The results highlighted substantial variability in the calibration factors for the tested organic compounds, with 4-nitrocatechol exhibiting the highest sensitivity and pyruvic acid the lowest. The obtained sulfuric acid calibration factor agreed well with the previous values from the literature. In summary, this research emphasized the need to develop reliable and precise calibration methods for progressively oxygenated reaction products measured with a NO 3- chemical-ionization mass spectrometer (CIMS), for example, HOMs. [ABSTRACT FROM AUTHOR]

The Measurements Of Pollution In The Troposphere (MOPITT) is an ideal instrument to understand the impact of (1) assimilating multispectral and joint retrievals versus single spectral products, (2) assimilating satellite profile products versus column products, and (3) assimilating multispectral and joint retrievals versus assimilating individual products separately. We use the Community Atmosphere Model with chemistry with the Data Assimilation Research Testbed (CAM-chem + DART) to assimilate different MOPITT carbon monoxide (CO) products to address these three questions. Both anthropogenic and fire CO emissions are optimized in the data assimilation experiments. The results are compared with independent CO observations from TROPOspheric Monitoring Instrument (TROPOMI), the Total Carbon Column Observing Network (TCCON), NOAA Carbon Cycle Greenhouse Gases (CCGG) sites, In-service Aircraft for a Global Observing System (IAGOS), and Western wildfire Experiment for Cloud chemistry, Aerosol absorption and Nitrogen (WE-CAN). We find that (1) assimilating the MOPITT joint (multispectral; near-IR and thermal IR) column product leads to better model–observation agreement at and near the surface than assimilating the MOPITT thermal-IR-only column retrieval. (2) Assimilating column products has a larger impact and improvement for background and large-scale CO compared to assimilating profile products due to vertical localization in profile assimilation. However, profile assimilation can outperform column assimilations in fire-impacted regions and near the surface. (3) Assimilating multispectral and joint products results in similar or slightly better agreement with observations compared to assimilating the single spectral products separately. [ABSTRACT FROM AUTHOR]

The Geostationary Carbon Cycle Observatory (GeoCarb) was selected as NASA's second Earth Venture Mission (EVM-2). The scientific objectives of GeoCarb were to advance our knowledge of the carbon cycle, in particular, land–atmosphere fluxes of the greenhouse gases carbon dioxide (CO 2) and methane (CH 4) and the effects of these fluxes on the Earth's radiation budget. GeoCarb would retrieve column-integrated dry-air mole fractions of CO 2 (XCO2), CH 4 (XCH4) and CO (XCO), important for understanding tropospheric chemistry), in addition to solar-induced fluorescence (SIF), from hyperspectral resolution measurements in the O 2 A-band at 0.76 µ m, the weak CO 2 band at 1.6 µ m, the strong CO 2 band at 2.06 µ m, and a CH 4 /CO band at 2.32 µ m. Unlike its predecessors (OCO-2/3, GOSAT-1/2, TROPOMI), GeoCarb would be in a geostationary orbit with a sub-satellite point centered over the Americas. This orbital configuration combined with its high-spatial-resolution imaging capabilities would provide an unprecedented view of these quantities on spatial and temporal scales accurate enough to resolve sources and sinks to improve land–atmosphere CO 2 and CH 4 flux calculations and reduce the uncertainty of these fluxes. This paper will present a description of the GeoCarb instrument and the L2 retrieval algorithms which will be followed by simulation experiments to determine an error budget for each target gas. Several sources of uncertainty will be explored, including that from the instrument calibration parameters for radiometric gain, the instrument line shape (ILS), the polarization, and the geolocation pointing, in addition to forward model parameters including meteorology and spectroscopy, although there are some other instrument-related sources of uncertainty that are left out for this study, including that from "smile", the keystone effect, stray light, detector persistence, and scene inhomogeneity. The results indicate that the errors (1 σ) are less than the instrument's multi-sounding precision requirements of 1.2 ppm, 10 ppb, and 12 ppb (10 %), for XCO2 , XCH4 , and XCO , respectively. In particular, when considering the sources of uncertainty separately and in combination (all sources included), we find overall RMSEs of 1.06 ppm for XCO2 , 8.2 ppb for XCH4 , and 2.5 ppb for XCO , respectively. Additionally, we find that, as expected, errors in XCO2 and XCH4 are dominated by forward model and other systematic errors, while errors in XCO are dominated by measurement noise. It is important to note that the GeoCarb mission was canceled by NASA; however, the instrument is still in development and will be delivered to NASA, in full, with the hope that it will eventually be adopted in a future mission proposal. [ABSTRACT FROM AUTHOR]

Nitrogen dioxide (NO 2) air pollution provides valuable information for quantifying NO x (NO x = NO + NO 2) emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO 2 emission strengths derived from 4-year (May 2018–June 2022) TROPOspheric Monitoring Instrument (TROPOMI) observations by combining a wind-assigned anomaly approach and a machine learning (ML) method, the so-called gradient descent algorithm. This combined approach is firstly applied to the Saudi Arabian capital city of Riyadh, as a test site, and yields a total emission rate of 1.09×1026 molec. s -1. The ML-trained anomalies fit very well with the wind-assigned anomalies, with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO 2 emissions are apparent at several sites: over a cement plant and power plants as well as over areas along highways. Using the same approach, an emission rate of 1.99×1025 molec. s -1 is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable with the Copernicus Atmosphere Monitoring Service (CAMS) inventory. Weekly variations in NO 2 emission are highly related to anthropogenic activities, such as the transport sector. The NO 2 emissions were reduced by 16 % at weekends in Riyadh, and high reductions were found near the city center and in areas along the highway. An average weekend reduction estimate of 28 % was found in Madrid. The regions with dominant sources are located in the east of Madrid, where residential areas and the Madrid-Barajas airport are located. Additionally, due to the COVID-19 lockdowns, the NO 2 emissions decreased by 21 % in March–June 2020 in Riyadh compared with the same period in 2019. A much higher reduction (62 %) is estimated for Madrid, where a very strict lockdown policy was implemented. The high emission strengths during lockdown only persist in the residential areas, and they cover smaller areas on weekdays compared with weekends. The spatial patterns of NO 2 emission strengths during lockdown are similar to those observed at weekends in both cities. Although our analysis is limited to two cities as test examples, the method has proven to provide reliable and consistent results. It is expected to be suitable for other trace gases and other target regions. However, it might become challenging in some areas with complicated emission sources and topography, and specific NO 2 decay times in different regions and seasons should be taken into account. These impacting factors should be considered in the future model to further reduce the uncertainty budget. [ABSTRACT FROM AUTHOR]

Four upper tropospheric humidity (UTH) datasets derived from satellite sounders are evaluated to assess their consistency as part of the activities for the Global Energy and Water Exchanges (GEWEX) water vapor assessment project. The datasets include UTH computed from brightness temperature measurements of the 183.31±1 GHz channel of the Special Sensor Microwave – Humidity (SSM/T-2), Advanced Microwave Sounding Unit-B (AMSU-B), and Microwave Humidity Sounder (MHS) and from channel 12 of the High-resolution Infrared Radiation Sounder (HIRS). The four datasets are generally consistent in the interannual temporal and spatial variability of the tropics. Large positive anomalies peaked over the central equatorial Pacific region during El Niño events in the same phase with the increase of sea surface temperature (SST). Conversely, large negative anomalies were obtained during El Niño events when the tropical-domain average is taken. The weakened ascending branch of the Pacific Walker circulation in the western Pacific and the enhanced descending branches of the local Hadley circulation along the Pacific subtropics largely contributed to widespread drying areas and thus negative anomalies in the upper troposphere during El Niño events as shown in all four datasets. During a major El Niño event, UTH had higher correlations with the coincident precipitation (0.60 to 0.75) and with 200 hPa velocity potential (-0.42 to -0.64) than with SST (0.37 to 0.49). Due to differences in retrieval definitions and gridding procedures, there can be a difference of 3 %–5 % UTH between datasets on average, and larger magnitudes of anomaly values are usually observed in spatial maps of microwave UTH data. Nevertheless, the tropical-domain averaged anomalies of the datasets are close to each other with their differences being mostly less than 0.5 %, and more importantly the phases of the time series are generally consistent for variability studies. [ABSTRACT FROM AUTHOR]

Nitrous acid (HONO) plays an important role in tropospheric oxidation chemistry as it is a precursor to the hydroxyl radical (OH). Measurements of HONO have been difficult historically due to instrument interferences and difficulties in sampling and calibration. The traditional calibration method involves generation of HONO by reacting hydrogen chloride vapor with sodium nitrite followed by quantification by various methods (e.g., conversion of HONO to nitric oxide (NO) followed by chemiluminescence detection). Alternatively, HONO can be generated photolytically in the gas phase by reacting NO with OH radicals generated by H 2 O photolysis. In this work, we describe and compare two photolytic HONO calibration methods that were used to calibrate an iodide adduct chemical ionization mass spectrometer (CIMS). Both methods are based on the water vapor photolysis method commonly used for OH and HO 2 (known collectively as HO x) calibrations. The first method is an adaptation of the common chemical actinometry HO x calibration method, in which HONO is calculated based on quantified values for [O 3 ], [H 2 O], and [O 2 ] and the absorption cross sections for H 2 O and O 2 at 184.9 nm. In the second, novel method HONO is prepared in mostly N 2 ([O 2]=0.040 %) and is simply quantified by measuring the NO 2 formed by the reaction of NO with HO 2 generated by H 2 O photolysis. Both calibration methods were used to prepare a wide range of HONO mixing ratios between ∼400 and 8000 pptv. The uncertainty of the chemical actinometric calibration is 27 % (2σ) and independent of HONO concentration. The uncertainty of the NO 2 proxy calibration is concentration-dependent, limited by the uncertainty of the NO 2 measurements. The NO 2 proxy calibration uncertainties (2σ) presented here range from 4.5 % to 24.4 % (at [HONO] =8000 pptv and [HONO] =630 pptv, respectively) with a 10 % uncertainty associated with a mixing ratio of ∼1600 pptv, typical of values observed in urban areas at night. We also describe the potential application of the NO 2 proxy method to calibrating HO x instruments (e.g., LIF, CIMS) at uncertainties below 15 % (2σ). [ABSTRACT FROM AUTHOR]

Satellite measurements in nadir and limb viewing geometry provide a complementary view of the atmosphere. An effective combination of the limb and nadir measurements can give new information about atmospheric composition. In this work, we present tropospheric ozone column datasets that have been created using a combination of total ozone columns from OMI (Ozone Monitoring Instrument) and TROPOMI (TROPOspheric Monitoring Instrument) with stratospheric ozone column datasets from several available limb-viewing instruments: MLS (Microwave Limb Sounder), OSIRIS (Optical Spectrograph and InfraRed Imaging System), MIPAS (Michelson Interferometer for Passive Atmospheric Sounding), SCIAMACHY (SCanning Imaging Spectrometer for Atmospheric CHartographY), OMPS-LP (Ozone Mapping and Profiles Suite – Limb Profiler), and GOMOS (Global Ozone Monitoring by Occultation of Stars). We have developed further the methodological aspects of the assessment of tropospheric ozone using the residual method supported by simulations with the chemistry transport model SILAM (System for Integrated modeLling of Atmospheric coMposition). It has been shown that the accurate assessment of ozone in the upper troposphere and the lower stratosphere (UTLS) is of high importance for detecting the ground-level ozone patterns. The stratospheric ozone column is derived from a combination of ozone profiles from several satellite instruments in limb-viewing geometry. We developed a method for the data homogenization, which includes the removal of biases and a posteriori estimation of random uncertainties, thus making the data from different instruments compatible with each other. The high-horizontal- and vertical-resolution dataset of ozone profiles is created via interpolation of the limb profiles from each day to a 1∘×1∘ horizonal grid. A new kriging-type interpolation method, which takes into account data uncertainties and the information about natural ozone variations from the SILAM-adjusted ozone field, has been developed. To mitigate the limited accuracy and coverage of the limb profile data in the UTLS, a smooth transition to the model data is applied below the tropopause. This allows for the estimation of the stratospheric ozone column with full coverage of the UTLS. The derived ozone profiles are in very good agreement with collocated ozonesonde measurements. The residual method was successfully applied to OMI and TROPOMI clear-sky total ozone data in combination with the stratospheric ozone column from the developed high-resolution limb profile dataset. The resulting tropospheric ozone column is in very good agreement with other satellite data. The global distributions of tropospheric ozone exhibit enhancements associated with the regions of high tropospheric ozone production. The main datasets created are (i) a monthly 1∘×1∘ global tropospheric ozone column dataset (from ground to 3 km below the tropopause) using OMI and limb instruments, (ii) a monthly 1∘×1∘ global tropospheric ozone column dataset using TROPOMI and limb instruments, and (iii) a daily 1∘×1∘ interpolated stratospheric ozone column from limb instruments. Other datasets, which are created as an intermediate step of creating the tropospheric ozone column data, are (i) a daily 1∘×1∘ clear-sky and total ozone column from OMI and TROPOMI, (ii) a daily 1∘×1∘ homogenized and interpolated dataset of ozone profiles from limb instruments, and (iii) a daily 1∘×1∘ dataset of ozone profiles from SILAM simulations with adjustment to satellite data. These datasets can be used in various studies related to variability and trends in ozone distributions in both the troposphere and the stratosphere. The datasets are processed from the beginning of OMI and TROPOMI measurements until December 2020 and are planned to be regularly extended in the future. [ABSTRACT FROM AUTHOR]

After the successful launch of Aeolus, which is the first spaceborne wind lidar developed by the European Space Agency (ESA), on 22 August 2018, we deployed several ground-based coherent Doppler wind lidars (CDLs) to verify the wind observations from Aeolus. By the simultaneous wind measurements with CDLs at 17 stations over China, the Rayleigh-clear and Mie-cloudy horizontal-line-of-sight (HLOS) wind velocities from Aeolus in the atmospheric boundary layer and the lower troposphere are compared with those from CDLs. To ensure the quality of the measurement data from CDLs and Aeolus, strict quality controls are applied in this study. Overall, 52 simultaneous Mie-cloudy comparison pairs and 387 Rayleigh-clear comparison pairs from this campaign are acquired. All of the Aeolus-produced Level 2B (L2B) Mie-cloudy HLOS wind and Rayleigh-clear HLOS wind and CDL-produced HLOS wind are compared individually. For the inter-comparison result of Mie-cloudy HLOS wind and CDL-produced HLOS wind, the correlation coefficient, the standard deviation, the scaled mean absolute deviation (MAD) and the bias are 0.83, 3.15 m s -1 , 2.64 m s -1 and - 0.25 m s -1 , respectively, while the y=ax slope, the y=ax+b slope and the y=ax+b intercept are 0.93, 0.92 and - 0.33 m s -1. For the Rayleigh-clear HLOS wind, the correlation coefficient, the standard deviation, the scaled MAD and the bias are 0.62, 7.07 m s -1 , 5.77 m s -1 and - 1.15 m s -1 , respectively, while the y=ax slope, the y=ax+b slope and the y=ax+b intercept are 1.00, 0.96 and - 1.2 m s -1. It is found that the standard deviation, the scaled MAD and the bias on ascending tracks are lower than those on descending tracks. Moreover, to evaluate the accuracy of Aeolus HLOS wind measurements under different product baselines, the Aeolus L2B Mie-cloudy HLOS wind data and L2B Rayleigh-clear HLOS wind data under Baselines 07 and 08, Baselines 09 and 10, and Baseline 11 are compared against the CDL-retrieved HLOS wind data separately. From the comparison results, marked misfits between the wind data from Aeolus Baselines 07 and 08 and wind data from CDLs in the atmospheric boundary layer and the lower troposphere are found. With the continuous calibration and validation and product processor updates, the performances of Aeolus wind measurements under Baselines 09 and 10 and Baseline 11 are improved significantly. Considering the influence of turbulence and convection in the atmospheric boundary layers and the lower troposphere, higher values for the vertical velocity are common in this region. Hence, as a special note, the vertical velocity could impact the HLOS wind velocity retrieval from Aeolus. [ABSTRACT FROM AUTHOR]

Atmospheric nitrogen oxides (NO + NO 2 = NO x) have been measured at the Cape Verde Atmospheric Observatory (CVAO) in the tropical Atlantic (16 ∘ 51 ′ N, 24 ∘ 52 ′ W) since October 2006. These measurements represent a unique time series of NO x in the background remote troposphere. Nitrogen dioxide (NO 2) is measured via photolytic conversion to nitric oxide (NO) by ultraviolet light-emitting diode arrays followed by chemiluminescence detection. Since the measurements began, a blue light converter (BLC) has been used for NO 2 photolysis, with a maximum spectral output of 395 nm from 2006 to 2015 and of 385 nm from 2015 onwards. The original BLC used was constructed with a Teflon-like material and appeared to cause an overestimation of NO 2 when illuminated. To avoid such interferences, a new additional photolytic converter (PLC) with a quartz photolysis cell (maximum spectral output also 385 nm) was implemented in March 2017. Once corrections are made for the NO 2 artefact from the original BLC, the two NO 2 converters are shown to give comparable NO 2 mixing ratios (BLC = 0.99 × PLC + 0.7 ppt, linear least-squares regression), giving confidence in the quantitative measurement of NO x at very low levels. Data analysis methods for the NO x measurements made at CVAO have been developed and applied to the entire time series to produce an internally consistent and high-quality long-term data set. NO has a clear diurnal pattern with a maximum mixing ratio of 2–10 ppt during the day depending on the season and ∼ 0 ppt during the night. NO 2 shows a fairly flat diurnal signal, although a small increase in daytime NO x is evident in some months. Monthly average mixing ratios of NO 2 vary between 5 and 30 ppt depending on the season. Clear seasonal trends in NO and NO 2 levels can be observed with a maximum in autumn and winter and a minimum in spring and summer. [ABSTRACT FROM AUTHOR]

Nitrogen oxides (NOx≡NO+NO2) in the NOx -limited upper troposphere (UT) are long-lived and so have a large influence on the oxidizing capacity of the troposphere and formation of the greenhouse gas ozone. Models misrepresent NOx in the UT, and observations to address deficiencies in models are sparse. Here we obtain a year of near-global seasonal mean mixing ratios of NO2 in the UT (450–180 hPa) at 1∘×1∘ by applying cloud-slicing to partial columns of NO2 from TROPOMI. This follows refinement of the cloud-slicing algorithm with synthetic partial columns from the GEOS-Chem chemical transport model. TROPOMI, prior to cloud-slicing, is corrected for a 13 % underestimate in stratospheric NO2 variance and a 50 % overestimate in free-tropospheric NO2 determined by comparison to Pandora total columns at high-altitude free-tropospheric sites at Mauna Loa, Izaña, and Altzomoni and MAX-DOAS and Pandora tropospheric columns at Izaña. Two cloud-sliced seasonal mean UT NO2 products for June 2019 to May 2020 are retrieved from corrected TROPOMI total columns using distinct TROPOMI cloud products that assume clouds are reflective boundaries (FRESCO-S) or water droplet layers (ROCINN-CAL). TROPOMI UT NO2 typically ranges from 20–30 pptv over remote oceans to >80 pptv over locations with intense seasonal lightning. Spatial coverage is mostly in the tropics and subtropics with FRESCO-S and extends to the midlatitudes and polar regions with ROCINN-CAL, due to its greater abundance of optically thick clouds and wider cloud-top altitude range. TROPOMI UT NO2 seasonal means are spatially consistent (R=0.6 –0.8) with an existing coarser spatial resolution (5 ∘ latitude × 8 ∘ longitude) UT NO2 product from the Ozone Monitoring Instrument (OMI). UT NO2 from TROPOMI is 12–26 pptv more than that from OMI due to increase in NO2 with altitude from the OMI pressure ceiling (280 hPa) to that for TROPOMI (180 hPa), but possibly also due to altitude differences in TROPOMI and OMI cloud products and NO2 retrieval algorithms. The TROPOMI UT NO2 product offers potential to evaluate and improve representation of UT NOx in models and supplement aircraft observations that are sporadic and susceptible to large biases in the UT. [ABSTRACT FROM AUTHOR]

A gas detection system has been developed, characterized, and deployed for pressurized gas-phase sample analyses and near-real-time online measurements. It consists of a cryogenic pre-concentrator (CryoTrap), a gas chromatograph (GC), and a new high-resolution atomic emission detector (AED III HR). Here the CryoTrap–GC–AED instrumental setup is presented, and the performance for iodine (1635 ± 135 counts I atom -1 pptv -1), sulfur (409 ± 57 counts S atom -1 pptv -1), carbon (636 ± 69 counts C atom -1 pptv -1), bromine (9.1 ± 1.8 counts Br atom -1 pptv -1), and nitrogen (28 ± 2 counts N atom -1 pptv -1) emission lines is reported and discussed. The limits of detection (LODs) are in the low parts per trillion by volume range (0.5–9.7 pptv), and the signal is linear to at least 4 orders of magnitude, which makes it a suitable method for diverse volatile organic compound (VOC) measurements in the atmosphere, even in remote unpolluted regions. The new system was utilized in a field study in a boreal forest at Hyytiälä, Finland, in late summer 2016, which made monoterpene measurements possible among other VOCs. Furthermore, pressurized global whole-air samples, collected on board the Lufthansa Airbus A340-600 IAGOS–CARIBIC aircraft in the upper troposphere and lower stratosphere region, were measured with the new setup, providing data for many VOCs, including the long-lived organosulfur compound carbonyl sulfide. [ABSTRACT FROM AUTHOR]

The intensive measurement campaign CoMet 1.0 (Carbon Dioxide and Methane Mission) took place during May and June 2018, with a focus on greenhouse gases over Europe. CoMet 1.0 aimed at characterising the distribution of CH4 and CO2 over significant regional sources with the use of a fleet of research aircraft as well as validating remote sensing measurements from state-of-the-art instrumentation installed on board against a set of independent in situ observations. Here we present the results of over 55 h of accurate and precise in situ measurements of CO2 , CH4 and CO mole fractions made during CoMet 1.0 flights with a cavity ring-down spectrometer aboard the German research aircraft HALO (High Altitude and LOng Range Research Aircraft), together with results from analyses of 96 discrete air samples collected aboard the same platform. A careful in-flight calibration strategy together with post-flight quality assessment made it possible to determine both the single-measurement precision as well as biases against respective World Meteorological Organization (WMO) scales. We compare the result of greenhouse gas observations against two of the available global modelling systems, namely Jena CarboScope and CAMS (Copernicus Atmosphere Monitoring Service). We find overall good agreement between the global models and the observed mole fractions in the free tropospheric range, characterised by very low bias values for the CAMS CH4 and the CarboScope CO2 products, with a mean free tropospheric offset of 0 (14) nmolmol-1 and 0.8 (1.3) µmolmol-1 respectively, with the numbers in parentheses giving the standard uncertainty in the final digits for the numerical value. Higher bias is observed for CAMS CO2 (equal to 3.7 (1.5) µmolmol-1), and for CO the model–observation mismatch is variable with height (with offset equal to -1.0 (8.8) nmolmol-1). We also present laboratory analyses of air samples collected throughout the flights, which include information on the isotopic composition of CH4 , and we demonstrate the potential of simultaneously measuring δ13C-CH4 and δ2H-CH4 from air to determine the sources of enhanced methane signals using even a limited number of discrete samples. Using flasks collected during two flights over the Upper Silesian Coal Basin (USCB, southern Poland), one of the strongest methane-emitting regions in the European Union, we were able to use the Miller–Tans approach to derive the isotopic signature of the measured source, with values of δ2H equal to -224.7 (6.6) ‰ and δ13C to -50.9 (1.1) ‰, giving significantly lower δ2H values compared to previous studies in the area. [ABSTRACT FROM AUTHOR]

We present two-dimensional scanning Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations of nitrogen dioxide (NO2) and formaldehyde (HCHO) in Munich. Vertical columns and vertical distribution profiles of aerosol extinction coefficient, NO2 and HCHO are retrieved from the 2D MAX-DOAS observations. The measured surface aerosol extinction coefficients and NO2 mixing ratios derived from the retrieved profiles are compared to in situ monitoring data, and the surface NO2 mixing ratios show a good agreement with in situ monitoring data with a Pearson correlation coefficient (R) of 0.91. The aerosol optical depths (AODs) show good agreement as well (R=0.80) when compared to sun photometer measurements. Tropospheric vertical column densities (VCDs) of NO2 and HCHO derived from the MAX-DOAS measurements are also used to validate Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) satellite observations. Monthly averaged data show a good correlation; however, satellite observations are on average 30 % lower than the MAX-DOAS measurements. Furthermore, the MAX-DOAS observations are used to investigate the spatiotemporal characteristic of NO2 and HCHO in Munich. Analysis of the relations between aerosol, NO2 and HCHO shows higher aerosol-to-HCHO ratios in winter, which reflects a longer atmospheric lifetime of secondary aerosol and HCHO during winter. The analysis also suggests that secondary aerosol formation is the major source of these aerosols in Munich. [ABSTRACT FROM AUTHOR]

An improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mass factor (AMF) calculations performed with more realistic model parameters is presented. The viewing angle dependency of surface albedo is taken into account by improving the GOME-2 Lambertian-equivalent reflectivity (LER) climatology with a directionally dependent LER (DLER) dataset over land and an ocean surface albedo parameterisation over water. A priori NO2 profiles with higher spatial and temporal resolutions are obtained from the IFS (CB05BASCOE) chemistry transport model based on recent emission inventories. A more realistic cloud treatment is provided by a clouds-as-layers (CAL) approach, which treats the clouds as uniform layers of water droplets, instead of the current clouds-as-reflecting-boundaries (CRB) model, which assumes that the clouds are Lambertian reflectors. On average, improvements in the AMF calculation affect the tropospheric NO2 columns by ±15 % in winter and ±5 % in summer over largely polluted regions. In addition, the impact of aerosols on our tropospheric NO2 retrieval is investigated by comparing the concurrent retrievals based on ground-based aerosol measurements (explicit aerosol correction) and the aerosol-induced cloud parameters (implicit aerosol correction). Compared with the implicit aerosol correction utilising the CRB cloud parameters, the use of the CAL approach reduces the AMF errors by more than 10 %. Finally, to evaluate the improved GOME-2 tropospheric NO2 columns, a validation is performed using ground-based multi-axis differential optical absorption spectroscopy (MAXDOAS) measurements at different BIRA-IASB stations. At the suburban Xianghe station, the improved tropospheric NO2 dataset shows better agreement with coincident ground-based measurements with a correlation coefficient of 0.94. [ABSTRACT FROM AUTHOR]

While water vapor is the most important tropospheric greenhouse gas, it is also highly variable in both space and time, and water vapor concentrations range over 3 orders of magnitude in the troposphere. These properties challenge all observing systems to accurately measure and resolve the vertical structure and variability of tropospheric humidity. In this study we characterize the humidity measurements of various observing techniques, including four separate Global Positioning System (GPS) radio occultation (RO) humidity retrievals (University Corporation for Atmospheric Research (UCAR) direct, UCAR one-dimensional variational retrieval (1D-Var), Wegener Center for Climate and Global Change (WEGC) 1D-Var, Jet Propulsion Laboratory (JPL) direct), radiosonde, and Atmospheric Infrared Sounder (AIRS) data. Furthermore, we evaluate how well the ERA-Interim reanalysis and NCEP Global Forecast System (GFS) model perform in analyzing water vapor at different levels. To investigate detailed vertical structure, we analyzed time-height cross sections over four radiosonde stations in the tropical and subtropical western Pacific for the year 2007. We found that the accuracy of RO humidity is comparable to or better than both radiosonde and AIRS humidity over 800 to 400 hPa, as well as below 800 hPa if super-refraction is absent. The various RO retrievals of specific humidity agree within 20% in the 1000-400 hPa layer, and differences are most pronounced above 600 hPa. [ABSTRACT FROM AUTHOR]

In order to promote the development of the passive DOAS technique the Multi Axis DOAS - Comparison campaign for Aerosols and Trace gases (MAD-CAT) was held at the Max Planck Institute for Chemistry in Mainz, Germany, from June to October 2013. Here, we systematically compare the differential slant column densities (dSCDs) of nitrous acid (HONO) derived from measurements of seven different instruments.We also compare the tropospheric difference of SCDs (delta SCD) of HONO, namely the difference of the SCDs for the non-zenith observations and the zenith observation of the same elevation sequence. Different research groups analysed the spectra from their own instruments using their individual fit software. All the fit errors of HONO dSCDs from the instruments with cooled large-size detectors are mostly in the range of 0.1 to 0.3 x 1015 molecules cm-2 for an integration time of 1 min. The fit error for the mini MAX-DOAS is around 0.7 x 1015 molecules cm-2. Although the HONO delta SCDs are normally smaller than 6 x 1015 molecules cm-2, consistent time series of HONO delta SCDs are retrieved from the measurements of different instruments. Both fits with a sequential Fraunhofer reference spectrum (FRS) and a daily noon FRS lead to similar consistency. Apart from the mini-MAX-DOAS, the systematic absolute differences of HONO delta SCDs between the instruments are smaller than 0.63 x 1015 molecules cm-2. The correlation coefficients are higher than 0.7 and the slopes of linear regressions deviate from unity by less than 16% for the elevation angle of 1°. The correlations decrease with an increase in elevation angle. All the participants also analysed synthetic spectra using the same baseline DOAS settings to evaluate the systematic errors of HONO results from their respective fit programs. In general the errors are smaller than 0.3 x 1015 molecules cm-2, which is about half of the systematic difference between the real measurements. The differences of HONO delta SCDs retrieved in the selected three spectral ranges 335-361, 335-373 and 335-390 nm are considerable (up to 0.57 x 1015 molecules cm-2) for both real measurements and synthetic spectra. We performed sensitivity studies to quantify the dominant systematic error sources and to find a recommended DOAS setting in the three spectral ranges. The results show that water vapour absorption, temperature and wavelength dependence of O4 absorption, temperature dependence of Ring spectrum, and polynomial and intensity offset correction all together dominate the systematic errors. We recommend a fit range of 335-373 nm for HONO retrievals. In such fit range the overall systematic uncertainty is about 0.87 x 1015 molecules cm-2, much smaller than those in the other two ranges. The typical random uncertainty is estimated to be about 0.16 x 1015 molecules cm-2, which is only 25% of the total systematic uncertainty for most of the instruments in the MAD-CAT campaign. In summary for most of the MAX-DOAS instruments for elevation angle below 5°, half daytime measurements (usually in the morning) of HONO delta SCD can be over the detection limit of 0.2 x 1015 molecules cm-2 with an uncertainty of ~0.9 x 1015 molecules cm-2. [ABSTRACT FROM AUTHOR]

Hydroperoxy radicals (HO2/ play an important part in tropospheric photochemistry, yet photochemical models do not capture ambient HO2 mixing ratios consistently. This is likely due to a combination of uncharacterized chemical pathways and measurement limitations. The indirect nature of current HO2 measurements introduces challenges in accurately measuring HO2; therefore a direct technique would help constrain HOx chemistry in the atmosphere. In this work we evaluate the feasibility of using chemical ionization mass spectrometry (CIMS) and propose a direct HO2 detection scheme using bromide as a reagent ion. Ambient observations were made with a high-resolution timeof- flight chemical ionization mass spectrometer (HR-ToFCIMS) in Atlanta over the month of June 2015 to demonstrate the capability of this direct measurement technique. Observations displayed expected diurnal profiles, reaching daytime median values of ~5 ppt between 2 and 3 p.m. local time. The HO2 diurnal profile was found to be influenced by morning-time vehicular NOx emissions and shows a slow decrease into the evening, likely from non-photolytic production, among other factors. Measurement sensitivities of approximately 5.1±1.0 cps ppt-1 for a bromide ion (79Br-/ count rate of 106 cps were observed. The relatively low instrument background allowed for a 3σ lower detection limit of 0.7 ppt for a 1 min integration time. Mass spectra of ambient measurements showed the 79BrHO-2 peak was the major component of the signal at nominal mass-to-charge 112, suggesting high selectivity for HO2 at this mass-to-charge. More importantly, this demonstrates that these measurements can be achieved using instruments with only unit mass resolution capability. [ABSTRACT FROM AUTHOR]

Measurements from multiple laboratories have to be related to unifying and traceable reference material in order to be comparable. However, such fundamental reference materials are not available for isotope ratios in atmospheric methane, which led to misinterpretations of combined data sets in the past. We developed a method to produce a suite of synthetic CH4-in-air standard gases that can be used to unify methane isotope ratio measurements of laboratories in the atmospheric monitoring community. Therefore, we calibrated a suite of pure methane gases of different methanogenic origin against international referencing materials that define the VSMOW (Vienna Standard Mean Ocean Water) and VPDB (Vienna Pee Dee Belemnite) isotope scales. The isotope ratios of our pure methane gases range between -320 and C40 for δ²H-CH4 and between -70 and -40 for δ13C-CH4, enveloping the isotope ratios of tropospheric methane (about -85 and -47 for δ²H-CH4 and δ13C-CH4 respectively). Estimated uncertainties, including the full traceability chain, are < 1.5 and < 0.2 for δ²H and δ13C calibrations respectively. Aliquots of the calibrated pure methane gases have been diluted with methane-free air to atmospheric methane levels and filled into 5 L glass flasks. The synthetic CH4-in-air standards comprise atmospheric oxygen/nitrogen ratios as well as argon, krypton and nitrous oxide mole fractions to prevent gasspecific measurement artefacts. The resulting synthetic CH4- in-air standards are referred to as JRAS-M16 (Jena Reference Air Set - Methane 2016) and will be available to the atmospheric monitoring community. JRAS-M16 may be used as unifying isotope scale anchor for isotope ratio measurements in atmospheric methane, so that data sets can be merged into a consistent global data frame. [ABSTRACT FROM AUTHOR]

Initial objectives and design of the Benchmark campaign organized within the European COST Action ES1206 (2013–2017) are described in the paper. This campaign has aimed to support the development and validation of advanced Global Navigation Satellite System (GNSS) tropospheric products, in particular high-resolution and ultra-fast zenith total delays (ZTDs) and tropospheric gradients derived from a dense permanent network. A complex data set was collected for the 8-week period when several extreme heavy precipitation episodes occurred in central Europe which caused severe river floods in this area. An initial processing of data sets from GNSS products and numerical weather models (NWMs) provided independently estimated reference parameters – zenith tropospheric delays and tropospheric horizontal gradients. Their provision gave an overview about the product similarities and complementarities, and thus a potential for improvements of a synergy in their optimal exploitations in future. Reference GNSS and NWM results were intercompared and visually analysed using animated maps. ZTDs from two reference GNSS solutions compared to global ERA-Interim reanalysis resulted in accuracy at the 10 mm level in terms of the root mean square (rms) with a negligible overall bias, comparisons to Global Forecast System (GFS) forecasts showed accuracy at the 12 mm level with the overall bias of −5 mm and, finally, comparisons to mesoscale ALADIN-CZ forecast resulted in accuracy at the 8 mm level with a negligible total bias. The comparison of horizontal tropospheric gradients from GNSS and NWM data demonstrated a very good agreement among independent solutions with negligible biases and an accuracy of about 0.5 mm. Visual comparisons of maps of zenith wet delays and tropospheric horizontal gradients showed very promising results for future exploitations of advanced GNSS tropospheric products in meteorological applications, such as severe weather event monitoring and weather nowcasting. The GNSS products revealed a capability of providing more detailed structures in atmosphere than the state-of-the-art numerical weather models are able to capture. In an initial study on the contribution of hydrometeors (e.g. cloud water, ice or snow) to GNSS signal delays during severe weather, the effect reached up to 17 mm, and it was suggested that hydrometeors should be carefully accounted for within the functional model. The reference products will be further exploited in various specific studies using the Benchmark data set. It is thus going to play a key role in these highly interdisciplinary developments towards better mutual benefits from advanced GNSS and meteorological products. [ABSTRACT FROM AUTHOR]

We introduce a retrieval algorithm to estimate lower tropospheric methane (CH4) concentrations from the surface to 1 km with uncertainty estimates using Hyperspectral Thermal Emission Spectrometer (HyTES) airborne radiance measurements. After resampling, retrievals have a spatial resolution of 6 × 6 m2. The total error from a single retrieval is approximately 20 %, with the uncertainties determined primarily by noise and spectral interferences from air temperature, surface emissivity, and atmospheric water vapor. We demonstrate retrievals for a HyTES flight line over storage tanks near Kern River Oil Field (KROF), Kern County, California, and find an extended plume structure in the set of observations with elevated methane concentrations (3.0 ± 0.6 to 6.0 ± 1.2 ppm), well above mean concentrations (1.8 ± 0.4 ppm) observed for this scene. With typically a 20 % estimated uncertainty, plume enhancements with more than 1 ppm are distinguishable from the background values with its uncertainty. HyTES retrievals are consistent with simultaneous airborne and ground-based in situ CH4 mole fraction measurements within the reported accuracy of approximately 0.2 ppm (or  ∼ 8 %), due to retrieval interferences related to air temperature, emissivity, and H2O. [ABSTRACT FROM AUTHOR]

We present an algorithm for retrieving tropospheric nitrogen dioxide (NO2) vertical column densities (VCDs) from ground-based zenith-sky (ZS) measurements of scattered sunlight. The method is based on a four-step approach consisting of (1) the differential optical absorption spectroscopy (DOAS) analysis of ZS radiance spectra using a fixed reference spectrum corresponding to low NO2 absorption, (2) the determination of the residual amount in the reference spectrum using a Langley-plot-type method, (3) the removal of the stratospheric content from the daytime total measured slant column based on stratospheric VCDs measured at sunrise and sunset, and simulation of the rapid NO2 diurnal variation, (4) the retrieval of tropospheric VCDs by dividing the resulting tropospheric slant columns by appropriate air mass factors (AMFs). These steps are fully characterized and recommendations are given for each of them. The retrieval algorithm is applied on a ZS data set acquired with a multi-axis (MAX-) DOAS instrument during the Cabauw (51.97° N, 4.93° E, sea level) Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI) held from 10 June to 21 July 2009 in the Netherlands. A median value of 7.9 × 1015 molec cm-2 is found for the retrieved tropospheric NO2 VCDs, with maxima up to 6.0 × 1016 molec cm-2. The error budget assessment indicates that the overall error σTVCD on the column values is less than 28 %. In the case of low tropospheric contribution, σTVCD is estimated to be around 39% and is dominated by uncertainties in the determination of the residual amount in the reference spectrum. For strong tropospheric pollution events, σTVCD drops to approximately 22% with the largest uncertainties on the determination of the stratospheric NO2 abundance and tropospheric AMFs. The tropospheric VCD amounts derived from ZS observations are compared to VCDs retrieved from off-axis and direct-sun measurements of the same MAX-DOAS instrument as well as to data from a co-located Système d'Analyse par Observations Zénithales (SAOZ) spectrometer. The retrieved tropospheric VCDs are in good agreement with the different data sets with correlation coefficients and slopes close to or larger than 0.9. The potential of the presented ZS retrieval algorithm is further demonstrated by its successful application on a 2-year data set, acquired at the NDACC (Network for the Detection of Atmospheric Composition Change) station Observatoire de Haute Provence (OHP; Southern France). [ABSTRACT FROM AUTHOR]

This paper presents a temperature sensitivity method (TESEM) to accurately calculate total vertical NO2 column, atmospheric slant NO2 profile-weighted temperature (T ), and to separate stratospheric and tropospheric columns from direct-sun (DS), ground-based measurements using the retrieved T . TESEM is based on differential optical absorption spectroscopy (DOAS) fitting of the linear temperature-dependent NO2 absorption cross section, σ(T ), regression model (Vandaele et al., 2003). Separation between stratospheric and tropospheric columns is based on the primarily bimodal vertical distribution of NO2 and an assumption that stratospheric effective temperature can be represented by temperature at 27 km±3 K, and tropospheric effective temperature is equal to surface temperature within 3–5 K. These assumptions were derived from the Global Modeling Initiative (GMI) chemistry-transport model (CTM) simulations over two northern midlatitude sites in 2011. TESEM was applied to the Washington State University Multi-Function DOAS instrument (MFDOAS) measurements at four midlatitude locations with low and moderate NO2 anthropogenic emissions: (1) the Jet Propulsion Laboratory's Table Mountain Facility (JPLTMF), CA, USA (34.38 N/117.68 W); (2) Pullman, WA, USA (46.73 N/117.17 W); (3) Greenbelt, MD, USA (38.99 N/76.84 W); and (4) Cabauw, the Netherlands (51.97 N/4.93 E) during July 2007, June–July 2009, July– August and October 2011, November 2012–May 2013, respectively. NO2 T and total, stratospheric, and tropospheric NO2 vertical columns were determined over each site. [ABSTRACT FROM AUTHOR]

A current obstacle to the observation system simulation experiments (OSSEs) used to quantify the potential performance of future atmospheric composition remote sensing systems is a computationally efficient method to define the scene-dependent vertical sensitivity of measurements as expressed by the retrieval averaging kernels (AKs). We present a method for the efficient prediction of AKs for multispectral retrievals of carbon monoxide (CO) and ozone (O3) based on actual retrievals from MOPITT (Measurements Of Pollution In The Troposphere) on the Earth Observing System (EOS)-Terra satellite and TES (Tropospheric Emission Spectrometer) and OMI (Ozone Monitoring Instrument) on EOS-Aura, respectively. This employs a multiple regression approach for deriving scene-dependent AKs using predictors based on state parameters such as the thermal contrast between the surface and lower atmospheric layers, trace gas volume mixing ratios (VMRs), solar zenith angle, water vapor amount, etc. We first compute the singular value decomposition (SVD) for individual cloud-free AKs and retain the first three ranked singular vectors in order to fit the most significant orthogonal components of the AK in the subsequent multiple regression on a training set of retrieval cases. The resulting fit coefficients are applied to the predictors from a different test set of test retrievals cased to reconstruct predicted AKs, which can then be evaluated against the true retrieval AKs from the test set. By comparing the VMR profile adjustment resulting from the use of the predicted vs. true AKs, we quantify the CO and O3 VMR profile errors associated with the use of the predicted AKs compared to the true AKs that might be obtained from a computationally expensive full retrieval calculation as part of an OSSE. Similarly, we estimate the errors in CO and O3 VMRs from using a single regional average AK to represent all retrievals, which has been a common approximation in chemical OSSEs performed to date. For both CO and O3 in the lower troposphere, we find a significant reduction in error when using the predicted AKs as compared to a single average AK. This study examined data from the continental United States (CONUS) for 2006, but the approach could be applied to other regions and times. [ABSTRACT FROM AUTHOR]

Formaldehyde (CH2O) is an important tracer of tropospheric photochemistry, whose slant column abundance can be retrieved from satellite measurements of solar backscattered UV radiation, using differential absorption retrieval techniques. In this work a spectral fitting sensitivity analysis is conducted on CH2O slant columns retrieved from the Global Ozone Monitoring Experiment 2 (GOME-2) instrument. Despite quite different spectral fitting approaches, the retrieved CH2O slant columns have geographic distributions that generally match expected CH2O sources, though the slant column magnitudes and corresponding uncertainties are particularly sensitive to the retrieval set-up. The choice of spectral fitting window, polynomial order, I0 correction, and inclusion of minor absorbers tend to result in the largest modulations of retrieved slant column magnitude and fit quality. However, application of a reference sector correction using observations over the remote Pacific Ocean is shown to largely homogenise the resulting CH2O vertical columns obtained with different retrieval settings, thereby largely reducing any systematic error sources from spectral fitting. [ABSTRACT FROM AUTHOR]

Monitoring the global distribution and long-term variations of CO2 sources and sinks is required for characterizing the global carbon budget. Total column measurements are useful for estimating regional-scale fluxes; however, model transport remains a significant error source, particularly for quantifying local sources and sinks. To improve the capability of estimating regional fluxes, we estimate lower tropospheric CO2 concentrations from groundbased near-infrared (NIR) measurements with space-based thermal infrared (TIR) measurements. The NIR measurements are obtained from the Total Carbon Column Observing Network (TCCON) of solar measurements, which provide an estimate of the total CO2 column amount. Estimates of tropospheric CO2 that are co-located with TCCON are obtained by assimilating Tropospheric Emission Spectrometer (TES) free tropospheric CO2 estimates into the GEOS-Chem model.We find that quantifying lower tropospheric CO2 by subtracting free tropospheric CO2 estimates from total column estimates is a linear problem, because the calculated random uncertainties in total column and lower tropospheric estimates are consistent with actual uncertainties as compared to aircraft data. For the total column estimates, the random uncertainty is about 0.55 ppm with a bias of -5.66 ppm, consistent with previously published results. After accounting for the total column bias, the bias in the lower tropospheric CO2 estimates is 0.26 ppm with a precision (one standard deviation) of 1.02 ppm. This precision is sufficient for capturing the winter to summer variability of approximately 12 ppm in the lower troposphere; double the variability of the total column. This work shows that a combination of NIR and TIR measurements can profile CO2 with the precision and accuracy needed to quantify lower tropospheric CO2 variability. [ABSTRACT FROM AUTHOR]

The article discusses the two sets of bromine monoxide (BrO) maps that correspond to two field campaigns conducted in the course of the International Polar Year 2007-2008. It states that the maps are averaged tropospheric column densities retrieved from measurements within the denoted day. It notes that the location of the ground-based measurements are marked with a white circle in the center of the map.

The article discusses a study that develops an algorithm to retrieve tropospheric vertical column densities of bromine monoxide (BrO) from data of high-resolution spectroscopic satellite instruments. It shows that the presented approach does not depend on extensive chemistry models and climatological data. It suggests that the comparison to ground-based data from two field campaigns confirmed that near-surface processes are the source of activated bromine compounds.

The article focuses on a method for retrieving troposheric water vapour profiles from pressure broadened emission spectra at 22 gegahertz. The retrieval method was assessed by a ground based microwave radiometer installed in the south of Bern. Classical microwave instruments focusing on the troposphere observe several channels in the center and wings of the water vapour line.

The article focuses on a study regarding the effect of spatial under-sampling of a priori data on the retrieval of nitrogen dioxide columns for a typical coastal area in San Francisco, California. It mentions that the satellite retrievals of tropospheric columns of nitrogen dioxide and other traces gases of solar radiation relies on the use of accurate a priori information. The study suggests the need for high-resolution a priori data in quantitative analysis of the spatial patterns.

The article discusses a study which aims to account for surface reflectance anisotropy in satellite retrievals of tropospheric nitrogen dioxide (NO2). It notes that surface reflectance is a vital parameter in satellite trace gas retrievals in the ultraviolet (UV) or visible range specifically for the recovery of NO2. It mentions the special need in further studies on accounting surface anisotropic reflectance effect in tropospheric NO2 retrieval, particularly for satellites with wide belts.

The article discusses a study which aims to account for surface reflectance anisotropy in satellite retrievals of tropospheric nitrogen dioxide (NO2). It notes that surface reflectance is a vital parameter in satellite trace gas retrievals in the ultraviolet (UV) or visible range specifically for the recovery of NO2. It mentions the special need in further studies on accounting surface anisotropic reflectance effect in tropospheric NO2 retrieval, particularly for satellites with wide belts.

The article discusses the determination of nitrogen dioxide's tropospheric column densities through the combination of Sciamachy nadir or limb measurements. It explores the unusual feature of Sciamachy and its capacity to determine stratospheric column densities (CDs). It also examines the potential and restrictions of the instrument for the evaluation of nitrogen dioxide's CDs.

The article discusses the mobile Multi-Axis-Differential Optical Absorption Spectroscopy (MAX-DOAS) analysis of tropospheric trace gases. It states that the analysis is usually performed at fixed locations since it would allow the diurnal variation of tropospheric species at the area. It also notes that it could also be developed on mobile platforms including cars, ships and aircraft.