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As part of the Pandonia Global Network (PGN), Pandora spectrometers are widely deployed around the world. These ground-based, remote-sensing instruments are federated such that they employ a common algorithm and data protocol for reporting on trace gas column densities and lower atmospheric profiles using two modes based on direct-sun and sky-scan observations. To aid users in the analysis of Pandora observations, the PGN standard quality assurance procedure assigns flags to the data indicating high, medium, and low quality. This work assesses the suitability of these data quality flags for filtering data in the scientific analysis of nitrogen dioxide (NO2) and formaldehyde (HCHO), two critical precursors controlling tropospheric ozone production. Pandora data flagged as high quality assures scientifically valid data and is often more abundant for direct-sun NO2 columns. For direct-sun HCHO and sky-scan observations of both molecules, large amounts of data flagged as low quality also appear to be valid. Upon closer inspection of the data, independent uncertainty is shown to be a better indicator of data quality than the standard quality flags. After applying an independent uncertainty filter, Pandora data flagged as medium or low quality in both modes can be demonstrated to be scientifically useful. Demonstrating the utility of this filtering method is enabled by correlating contemporaneous but independent direct-sun and sky-scan observations. When evaluated across 15 Pandora sites in North America, this new filtering method increased the availability of scientifically useful data by as much as 90 % above that tagged as high quality. A method is also developed for combining the direct-sun and sky-scan observations into a single dataset by accounting for biases between the two observing modes and differences in measurement integration times. This combined data provides a more continuous record useful for interpreting Pandora observations against other independent variables such as hourly observations of surface ozone. When Pandora HCHO columns are correlated with surface ozone measurements, data filtered by independent uncertainty exhibits similarly strong and more robust relationships than high-quality data alone. These results suggest that Pandora data users should carefully assess data across all quality flags and consider their potential for useful application to scientific analysis. The present study provides a method for maximizing use of Pandora data with expectation of more robust satellite validation and comparisons with ground-based observations in support of air quality studies. [ABSTRACT FROM AUTHOR]

Data from ozonesondes launched at ARIES Nainital (29.40o N, 79.50o E, and 1793 m elevation) are used to evaluate the Atmospheric Infrared Sounder (AIRS) version 6 ozone profiles and total column ozone during the period 2011-2017 over the central Himalaya. The AIRS ozone products are analyzed in terms of retrieval sensitivity, retrieval biases/errors, and ability to retrieve the natural variability of columnar ozone, which has not been done so far from the Himalayan region having complex topography. For a direct comparison, averaging kernels information is used to account for the sensitivity difference between the AIRS and ozonesonde data. We show that AIRS can provide quality data of ozone in the lower and middle troposphere and stratosphere with nominal underestimation (<20%). However, in the upper troposphere and lower stratosphere (UTLS), we observe a considerable overestimation of the magnitude as high as 102%. The weighted statistical error analysis of AIRS ozone shows higher positive bias, root mean squared error, and standard deviation in the upper troposphere of about 65%, 65%, and 25%, respectively. Similar to AIRS, Infrared Atmospheric Sounding Interferometer (IASI) and Cross-track Infrared Sounder (CrIS) are also able to produce ozone peaks and gradients successfully. However, the statistical errors are again higher in the UTLS region that are likely related to larger variability of ozone, lower ozone partial pressure and inadequate retrieval information on the surface parameters. The monthly variations of columnar ozone (total, UTLS, and tropospheric) are captured well by AIRS, except the total columnar ozone, which shows a strong bimodal variation, unlike unimodal variation seen in ozonesonde and Ozone Monitoring Instrument (OMI). Increases in ozone of 5 - 20% (in 2 - 6 km altitude) after the biomass burning and during events of downward transport (in 2 - 16 km altitude) are captured well by AIRS. Ozone radiative forcing (RF) derived from total column ozone matches well between ozonesonde (4.86 mW/m²) and OMI (4.04 mW/m²), while significant RF underestimation is seen in AIRS (2.96 mW/m²). The fragile and complex landscapes of the Himalayas are more sensitive to global climate change, and establishing such biases and error analysis of space-borne sensors will help study the long-term trends and estimate accurate radiative budgets. [ABSTRACT FROM AUTHOR]

Escalating emissions of several air pollutants over South Asia could play a detrimental role in the regional and global atmosphere. Therefore, it is necessary to investigate these emissions within the boundary layer and at higher heights utilizing satellite data that are more inclusionary, where limited in situ observations are available. Here, we utilize the Infrared Atmospheric Sounding Interferometer (IASI), Ozone Monitoring Instruments (OMI), TROPOspheric Monitoring Instrument (TROPOMI), and Global Ozone Monitoring Experiment (GOME-2) hyperspectral satellite data to assess the changes in emission sources during Indian lockdown with a primary focus on the tropospheric profiles of ozone and carbon monoxide (CO). A significant reduction (> 20%) in the tropospheric ozone was seen over northern and northeast regions compared to 2018, while a dramatic increase (> 20%) compared to 2019 was seen. The subtropical dynamics mainly contributed to the increased ozone over the northern region. An analysis of the ozone production regime showed mostly NO2 limited regime over the major part of India and VOC limited regime over thermal power plants regions. Unlike in the boundary layer, where CO showed reduction (15–20%), CO profiles showed a consistent increase (as high as 31%) in the free troposphere over the majority of cities and thermal power plants. The CO total column also showed an increase (~ 20%) over central and western India and a slight decrease (5%) over northern India. Similar to CO, an increase (~ 15%) of NO2 column over the western region was observed particularly compared to 2019. However, unlike ozone and CO, reduction of tropospheric NO2 columns was seen over the major part of India, with the highest reduction over northern regions (20–52%). Furthermore, homogeneous yearly differences (> 30%) between OMI and TROPOMI NO2 observations were also seen distinctly over the remote areas. Contrary to surface-based studies, the present study shows an increase in CO, ozone (decrease), and NO2 at several locations and in the free troposphere during the lockdown. [ABSTRACT FROM AUTHOR]

Since January 2017 continuous multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations have been performed for the first time at Pantnagar (29.03°N, 79.47°E), a semi-urban site located in the Indo-Gangetic Plain region in India. Here we report the formaldehyde (HCHO), glyoxal (CHOCHO), and nitrogen dioxide (NO2) concentrations for the lowest layer (0-1 km) of the retrieved vertical profiles. The ratio of CHOCHO to HCHO concentrations (RGF), an important tracer indicative of changes in volatile organic compound emissions was estimated. During spring and autumn enhanced concentrations of HCHO and CHOCHO were observed under the influence of biomass burning. The mean RGF for the whole observation period (January- November) in Pantnagar was estimated to be 0.029 ± 0.006. Comparing with similar MAX-DOAS observations in central Thailand and reported literature values, we found that the RGF tends to be < ~0.04 under the influence of biomass burning and/or anthropogenic emissions. [ABSTRACT FROM AUTHOR]