368841 Early Results and New Insights into Tropospheric NO2 Variability from a Network of Pandora Spectrometers in a Coastal Urban Environment

Monday, 13 January 2020
Hall B1 (Boston Convention and Exhibition Center)
Taylor Jonathan Adams, Boston University, Boston, MA; and J. A. Geddes, G. G. Abad, A. H. Souri, C. Miller, C. R. Nowlan, Y. Jung, and K. Chance

Despite significant improvements in air quality in recent years, exposure to criteria air contaminants continues to threaten human and environmental health. Even low levels of many criteria air pollutants can contribute to negative health effects as a result of long-term exposures. Satellite remote sensing of aerosol and trace gases is rapidly improving in spatial and temporal resolution and has provided unprecedented information on surface-level air quality where ground monitoring information is scarce. Despite improvements in resolution, validation of satellite products remains a challenge. Spatial representation issues often contribute to substantial differences between satellite pixel observations and point measurements made at the ground. The validation and application of satellite observations is a particular challenge over coastal urban areas at land-water boundaries that result in complex small scale dynamics which are difficult to represent in models and with coarse observations.

To aid in local validation and application of satellite atmospheric chemistry data products within individual urban areas, we have established an intra-urban network of ground-based remote sensing and co-located in-situ air quality observations across the greater Boston area. This network consists of six Pandora Spectrometers, two cavity attenuated phase shift nitrogen dioxide monitors, and leverages the five currently active Massachusetts Department of Environmental Protection air quality monitoring sites. The Pandora Spectrometer system was developed for the monitoring of total atmospheric columns of trace gases such as ozone, nitrogen dioxide, and formaldehyde, with high temporal resolution over a small spatial footprint. The in-situ measurements, while similarly limited in their spatial coverage, offer well-characterized measurements and high quality information about specific sites. This network, therefore, has the potential to provide an important link between in-situ measurements and total column observations made from space at the intra-urban scale.

We also make use of high resolution WRF-CMAQ modeling from previous DISCOVER-AQ campaigns to explore issues related to Pandora spectrometer placement and spatial representation compared to space-based observations, and to quantify other potential sources of error in satellite validation exercises (e.g. viewing geometry considerations. We will use this WRF-CMAQ product in conjunction with synthetic TEMPO products to explore differences in representation and diurnal variation between in-situ, Pandora, and satellite derived nitrogen dioxide. These results allow us to reflect on the representation of our Boston area network, and identify optimal site location and conditions for intra-urban satellite validation efforts.

We will present early insights from this network, focusing first on nitrogen dioxide (NO2). We will first report the results of a large study where several Pandora instruments were collocated for initial validation to establish the precision with which intra-urban variability in total column NO2 can be detected with these ground-based instruments. We will then report early results from observations across several network locations. Comparisons with available satellite observations will be performed, focusing on differences between satellite and in-situ as well as total column NO2 measurement. We will expand upon this variability by exploring the anthropogenic and meteorological features that contribute to this variability in the tropospheric columns within the Boston urban area. We will investigate drivers of the relationship between total column and surface concentrations in this urban area. In particular, we will present key features of the coastal environment that drive air quality variability in this setting, and how well these can be feasibly captured by space-based remote sensing. We will investigate whether these features specific to coastal settings are better captured as satellites have improved in resolution. Overall, we hope to demonstrate the value of such an intra-urban network in the application of satellite-based remote sensing of surface air quality within complex coastal urban environments.

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