Debora Griffin

Nitrogen dioxide (NO2), a criteria pollutant used for the Air Quality Health Index (AQHI) reporting, can have important environmental and human respiratory health effects when present in the near-surface atmosphere. For this study, urban surface volume mixing ratios (VMRs) are derived from Pandora total column measurements. Pandora remote sensing instruments can be used to evaluate surface air quality and complement in situ instruments to support long-term monitoring of ambient air quality. At four sites in the Greater Toronto Area and Detroit-Windsor Area, Pandora direct sun measurements are converted to surface VMRs following a method utilizing a high-resolution air quality forecasting model. The resulting VMRs agree with coincident in situ measurements to within 2 ppbv from 2020 through 2024. This method is shown to be most effective when the Planetary Boundary Layer (PBL) is above 750 m as estimated by ERA5 reanalysis, while dependence on PBL height below 750 m is evaluated. The surface VMR derived from Pandora direct sun measurements when the PBL is below 750 m has a median difference of -1.7 ppbv (parts per billion by volume) (10th percentile: -8.2 ppbv, 90th percentile: 3.2 ppbv) with respect to coincident in situ measurements. When a logarithmic correction is applied as a function of PBL height for these shallow PBL conditions, the median difference is reduced to 0.5 ppbv (-4.8 ppbv, 4.1 ppbv).

Total column ozone (TCO) has been observed since the 1920s, with a systematic monitoring network established during the International Geophysical Year (1957–1958). We compile and assess TCO records from six major ground-based instrument types: Dobson and Brewer spectrophotometers, Filter ozonometers, zenith-sky DOAS (UVVIS), Fourier-transform infrared (FTIR) spectroscopy, and Pandora spectrometers. Data are drawn from the World Ozone and Ultraviolet Radiation Data Centre, Network for the Detection of Atmospheric Composition Change, Pandonia Global Network, and European Brewer Network. Using harmonized statistical criteria and daily comparisons with multiple satellite products and four reanalysis datasets, we evaluate site-level performance in 5-year intervals from 1940 to 2024. Metrics include mean bias, variability of daily and monthly differences, seasonal amplitude, and the range of annual means, with percentile-based thresholds used to classify data quality. Ground-based annual means generally agree with satellite and reanalysis benchmarks within ± 2 %, with typical variability near 2 %. Larger discrepancies occur in the pre-satellite era, where reanalyses show biases of up to −5 % relative to Dobson observations. Network-wide distributions of daily mean differences to those from reanalysis and satellite data indicate comparable internal consistency for Brewer, Dobson, FTIR, and Pandora (standard deviations generally around 2 %), while Filter and UVVIS exhibit slightly broader spreads (< 3 %), especially at high latitudes. Network capacity has evolved substantially since the 2000s, with a decline in Dobson sites and expansion of Brewer and Pandora observations. By providing station-level flags and thresholds, this assessment helps network operators prioritize calibration and reprocessing efforts and helps users identify robust records, thereby improving confidence in long-term ozone trend detection and satellite validation.

Wildland fires are increasingly important drivers of ecosystem change, air quality degradation, and climate feedbacks, yet their emissions and plume rise are commonly prescribed in Earth system models. Here we introduce interactive fire aerosol emissions and a thermodynamical plume-height parameterization into CanESM5.1c. We evaluate simulated area burned, black carbon (BC) emissions, plume heights, and atmospheric BC distributions against multiple observation-based datasets for 2000--2023, and assess future changes under low- and moderate-warming scenarios. CanESM5.1c simulates global area burned between GFED4 and GFED5 estimates, while BC fire emissions are slightly high. Simulated mean plume heights are about 0.8 km lower than satellite-derived estimates but capture their broad spatial variability. Relative to fixed climatological injection heights, interactive plume height increases atmospheric BC above 850 hPa by 5--10% and decreases near-surface BC by 5--20%. Under moderate warming, end-of-century area burned and BC fire emissions increase by 23% and 53% in the Arctic and 33% and 37% in northern mid-latitudes, respectively, while globally dominant tropical area burned and emissions decrease by 24% and 22%. The frequency of fire plumes exceeding 8 km in height increase in several regions, including Australia/New Zealand, and the northern boreal forests. These changes are consistent with regional shifts in fuel availability, soil moisture, lightning, and atmospheric stability. Extreme fires contribute disproportionately to regional BC emissions and become more frequent in many extra-tropical regions. Under low warming, many fire characteristics remain closer to present-day conditions, emphasizing the benefits of climate change mitigation.

Total column ozone (TCO) has been observed since the 1920s, with global monitoring established during the International Geophysical Year (1957–1958). We compile and assess TCO records from six major ground-based instrument types: Dobson and Brewer spectrophotometers, Filter ozonometers, zenith-sky DOAS (UVVIS), Fourier-transform infrared (FTIR) spectroscopy, and Pandora spectrometers. Data are drawn from the World Ozone and Ultraviolet Radiation Data Centre, Network for the Detection of Atmospheric Composition Change, Pandonia Global Network, and European Brewer Network. Using harmonized statistical criteria and daily comparisons with multiple satellite products and four reanalysis datasets, we evaluate site-level performance in five-year intervals from 1940 to 2024. Metrics include mean bias, variability of daily and monthly differences, seasonal amplitude, and the range of annual means, with percentile-based thresholds used to classify data quality. Ground-based annual means generally agree with satellite and reanalysis benchmarks within ±2 %, with typical variability near 2 %. Larger discrepancies occur in the pre-satellite era, where reanalyses show biases of up to −5 % relative to Dobson observations. Network-wide distributions of daily mean differences indicate comparable internal consistency for Brewer and Pandora (standard deviations generally <2 %), while Filter, FTIR and UVVIS exhibit slightly broader spreads (<3 %), especially at high latitudes. Network capacity has evolved substantially since the 2000s, with a decline in Dobson sites and expansion of Brewer and Pandora observations. By providing station-level flags and thresholds, this assessment helps users identify robust records, prioritize calibration and reprocessing, which ultimately strengthens their confidence in long-term ozone trend detection and satellite validation.

Total column ozone (TCO) has been observed since the 1920s, with global monitoring established during the International Geophysical Year (1957–1958). We compile and assess TCO records from six major ground-based instrument types: Dobson and Brewer spectrophotometers, Filter ozonometers, zenith-sky DOAS (UVVIS), Fourier-transform infrared (FTIR) spectroscopy, and Pandora spectrometers. Data are drawn from the World Ozone and Ultraviolet Radiation Data Centre, Network for the Detection of Atmospheric Composition Change, Pandonia Global Network, and European Brewer Network. Using harmonized statistical criteria and daily comparisons with multiple satellite products and four reanalysis datasets, we evaluate site-level performance in five-year intervals from 1940 to 2024. Metrics include mean bias, variability of daily and monthly differences, seasonal amplitude, and the range of annual means, with percentile-based thresholds used to classify data quality. Ground-based annual means generally agree with satellite and reanalysis benchmarks within ±2 %, with typical variability near 2 %. Larger discrepancies occur in the pre-satellite era, where reanalyses show biases of up to −5 % relative to Dobson observations. Network-wide distributions of daily mean differences indicate comparable internal consistency for Brewer and Pandora (standard deviations generally <2 %), while Filter, FTIR and UVVIS exhibit slightly broader spreads (<3 %), especially at high latitudes. Network capacity has evolved substantially since the 2000s, with a decline in Dobson sites and expansion of Brewer and Pandora observations. By providing station-level flags and thresholds, this assessment helps users identify robust records, prioritize calibration and reprocessing, which ultimately strengthens their confidence in long-term ozone trend detection and satellite validation.

Total column ozone (TCO) has been observed since the 1920s, with global monitoring established during the International Geophysical Year (1957–1958). We compile and assess TCO records from six major ground-based instrument types: Dobson and Brewer spectrophotometers, Filter ozonometers, zenith-sky DOAS (UVVIS), Fourier-transform infrared (FTIR) spectroscopy, and Pandora spectrometers. Data are drawn from the World Ozone and Ultraviolet Radiation Data Centre, Network for the Detection of Atmospheric Composition Change, Pandonia Global Network, and European Brewer Network. Using harmonized statistical criteria and daily comparisons with multiple satellite products and four reanalysis datasets, we evaluate site-level performance in five-year intervals from 1940 to 2024. Metrics include mean bias, variability of daily and monthly differences, seasonal amplitude, and the range of annual means, with percentile-based thresholds used to classify data quality. Ground-based annual means generally agree with satellite and reanalysis benchmarks within ±2 %, with typical variability near 2 %. Larger discrepancies occur in the pre-satellite era, where reanalyses show biases of up to −5 % relative to Dobson observations. Network-wide distributions of daily mean differences indicate comparable internal consistency for Brewer and Pandora (standard deviations generally <2 %), while Filter, FTIR and UVVIS exhibit slightly broader spreads (<3 %), especially at high latitudes. Network capacity has evolved substantially since the 2000s, with a decline in Dobson sites and expansion of Brewer and Pandora observations. By providing station-level flags and thresholds, this assessment helps users identify robust records, prioritize calibration and reprocessing, which ultimately strengthens their confidence in long-term ozone trend detection and satellite validation.

Tropospheric Emissions: Monitoring of Pollution (TEMPO) provides valuable hourly measurements of airborne pollutants over North America. Data quality over snowy surfaces may degrade due to difficulty in accurately characterizing surface reflectivity and cloud properties, as snow and cloud are both highly reflective and therefore challenging to distinguish optically. Cloud properties for satellite‐based trace gas retrievals are commonly extracted from measurements of oxygen, through either direct absorption (A band, B band) or collisional absorption (oxygen dimer). Here we investigate a combination of the two methods, with potential for extracting additional cloud information over challenging scenes due to the different responses of the two methods to various atmospheric conditions. A combined retrieval is successfully applied to simplified simulated data, extracting cloud information under conditions which would cause either retrieval to fail on its own. A second technique is demonstrated on the simulated data which attempts to flag partially cloudy scenes in the absence of external surface reflectivity information. The individual retrievals are applied to TEMPO data and compared in order to investigate their compatibility for potential use in combined retrievals. Variability in effective cloud fraction is found to be on the order of 0.1, and a bias in optical centroid pressure (representing the altitude of the cloud) is observed between methods, up to 50 hPa for fully overcast scenes and higher for partially cloud scenes. Further investigation is required to determine if these discrepancies are due to retrieval error, instrument calibration, or physical differences between spectral bands.

Tropospheric and stratospheric ozone variability plays a critical role in controlling the polar radiation budget. Although the factors influencing stratospheric ozone variation are quite well researched, tropospheric and near-surface ozone are subject to both dynamical and photochemical constraints that are still poorly understood. Measurements from a Thermo Scientific TEI-49i in-situ ozone analyzer at the Polar Environment Atmospheric Research Laboratory (PEARL) at Eureka, Nunavut, Canada (80.05°N, 86.42°W) show that surface ozone in the Arctic is characterized by two major annual depletion events: (1) a primary depletion which occurs during the springtime following polar sunrise, and has been attributed to enhancements of BrO (bromine explosion events), as well as (2) a secondary depletion which occurs in the late summer and early fall period. The PEARL MAX-DOAS (Multi-Axis Differential Optical Absorption Spectroscopy) ultraviolet (UV)-visible Ground-Based Spectrometer (PEARL-GBS) results show tropospheric BrO enhancements correlated with periods of reduced ozone concentrations. Additionally, we also use several UV-visible Pandora spectrometers affiliated with the Pandonia Global Network (PGN) to evaluate the feasibility of retrieving BrO and IO, which are not currently among the standard PGN products. We present here preliminary results of polar Pandora BrO and IO retrievals and investigate the potential link between summertime IO and late summer ozone depletions detected at Eureka. For this investigation, we use the MAX-DOAS measurements made by three Pandora instruments: Pandora #144 which was located at the PEARL Ridge Lab from 2019-2023, Pandora #280 located at the Eureka 0-Altitude PEARL Auxiliary Laboratory (0PAL) since 2024, and Pandora #152 located at the Norwegian Polar Institute Sverdrup in Ny-Ålesund, Svalbard (78.92°N, 11.93°E) since 2019. We retrieve BrO and IO from the Pandora spectra and find good agreement between Pandora and PEARL-GBS BrO dSCDs (Differential Slant Column Densities). Although measured enhancements of BrO from the Eureka instruments coincide with periods of springtime reduced surface ozone, this is not as evident for the IO results in the context of the summer ozone depletions. We demonstrate the capability of using the Pandora instruments to retrieve these halogen species with MAX-DOAS measurements. These Pandora retrieval methods for BrO and IO will allow for further study of the role of these trace gases in the polar tropospheric ozone cycle.

In this presentation TEMPO NO2 observations are evaluated with a focus on snow-covered surfaces. Its ability to capture sharp spatial and temporal gradients in NO2 vertical column densities (VCDs) and surface concentrations are assessed, which are key parameters for assessing air quality and public health impacts. Data from the 2024 Study of Winter Air Pollution in Toronto (SWAPIT), including in situ and mobile MAX-DOAS measurements, are used to assess TEMPO’s precision and accuracy. Additional evaluations are performed at Pandora sites across North America to examine wintertime performance. Comparisons show strong correlations between TEMPO and surface observations, with significant improvements in bias after applying corrections to air mass factors, cloud fraction, and surface albedo (from -32% to -9% over snow).