Abby Sebol

The Pandora Global Network (PGN) is a system of ground-based spectrometers reporting continuous daytime column HCHO and NO ₂ . While the Direct Sun (DS) NO ₂ product has been well studied, the Multi Axis Differential Optical Absorption Spectroscopy (MAX DOAS) and DS HCHO products are largely unvalidated. Using the Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas (AEROMMA) airborne campaign in the summer of 2023, we evaluate the performance of select Pandora monitors relative to in situ airborne observations. A case study over a Pandora in the California desert shows MAX DOAS HCHO captures the total tropospheric column (within 4 % of the integrated in situ column) but does not match the vertical shape of the HCHO profile where the Pandora is biased high near the surface and low near the top of the boundary layer. The MAX DOAS NO ₂ is 80 % lower for the entire profile however, the spatial heterogeneity of NO ₂ makes the comparison particularly sensitive to the viewing angle of the Pandora. Ten Pandoras located in the New York City (NYC) domain capture the day to day variability of HCHO as well as spatial gradients from New Jersey to NYC to Long Island. The mean NYC Pandora HCHO correlates well with mean Tropospheric Emissions Monitoring of Pollution (TEMPO) HCHO columns of a similar domain on clear sky days. On those days, MAX DOAS columns exhibit a lower slope (slope = 0.78, y -intercept = 1.08×10 ¹⁵ molec cm ⁻² ; R ² =0.62) while DS columns show a higher offset (slope = 0.90, y -intercept = 2.83×10 ¹⁵ molec cm ⁻² ; R ² =0.63) compared to TEMPO. These results demonstrate the value of Pandora HCHO products while highlighting the need for improved uncertainty quantification.

Asia accounts for approximately half of global anthropogenic emissions of major pollutants, yet emission inventories remain uncertain and ground-based monitoring is sparse across much of the region. To address these challenges, this study applies a multi-species satellite data assimilation framework to estimate emissions and concentrations of key chemical species during the NASA's ASIA-AQ campaign. The assimilation improves agreement with airborne observations for O₃, NO_x, CO, and CH₂O, with the largest gains for CO (correlation increasing from 0.63–0.64 to 0.77) and CH₂O (biases reduced by 41–70 %). Domain-wide, the optimized emissions show increases of 15 % for NO_x and 9 % for CO, and a 52 % reduction in isoprene. Comparisons with multiple emission inventories reveal large discrepancies, with normalized standard deviation ranging from 11 % for NO_x in mainland China to 68 % for CO in Taiwan. Over Thailand, the assimilation increases fire emissions from 3.6 Tg (GFASv1.2) to 8.3 Tg, while FINNv2.7 produces estimates roughly twice as high, highlighting persistent divergence among fire emission estimates. Source-receptor analysis reveals strong meteorological control on transboundary pollutant: long-range transport contributes up to 62 % of surface O₃ in Manila during strong monsoon conditions, whereas Seoul exhibits local NO_x-saturated chemistry. During a strong transport episode, Indian emissions account for 72–78 % of the free tropospheric O₃ response over Taipei and Chiang Mai, and 24 % over Seoul, highlighting an overlooked transport pathway affecting Asian air quality. These results highlight the value of satellite data assimilation and the need for improved inventories and coordinated action on local and transboundary pollution.

Wintertime photochemical air pollution in East Asia remains poorly constrained despite its impact on regional air quality. Sources and formation pathways of acyl peroxynitrates (PANs) and ozone (O₃), key photochemical products, are not well understood, hindering effective mitigation strategies. We investigate PANs and O₃ over South Korea using observations from the ASIA-AQ campaign (February–March 2024). PANs reached 5.5 ppbv, strongly correlating with formaldehyde and particulate matter, indicating active winter photochemistry. Median PANs were higher in the mid-southern peninsula (MS; 990 pptv) and Yellow Sea (1200 pptv) than the Seoul Metropolitan Area (840 pptv). Elevated homologue-to-acetyl peroxynitrate ratios over the MS, with enhanced acryloyl peroxynitrate, acrolein, and ethylene oxide, provided tracers for petrochemical emissions and their impacts. Acetaldehyde contributed 53 %–80 % of PAN production. Ethanol was a major precursor of acetaldehyde (∼ 50 %). Strong correlations (r² > 0.8) of ethanol and halocarbons indicate industrial and solvent sources under-represented in inventories. Formaldehyde and C₂₊ aldehydes contributed ∼ 30 % to ozone production. Low ozone production efficiency (< 10) and radical termination dominated by nitric acid and PANs (> 80 %) indicate VOC-limited conditions. The fractional PANs contribution to NO_x loss increased with decreasing OH reactivity ratio of NO₂ to aldehydes, suggesting spatial increases in ozone production following NO_x reductions. These findings demonstrate that a comprehensive understanding of VOC oxidation, particularly oxygenates from industrial sources, is essential for representing winter photochemistry. PANs measurements provide critical constraints on oxidation processes and their implications for emission control.

Nitrogen Dioxide (NO₂) is a key component of tropospheric chemistry and air quality, yet large uncertainties persist in regional NO_x emissions across rapidly developing megacities in Southeast Asia. Observations from the Geostationary Emissions Monitoring Spectrometer (GEMS) provide new constraints on anthropogenic NO₂ variability, while the 2024 NASA Airborne and Satellite Investigation of Asian Air Quality (ASIA-AQ) campaign, offers an extensive, independent dataset for model evaluation. Here, we examine air quality in Bangkok using coarse (20 km) and high-resolution (4 km) WRF-Chem simulations during ASIA-AQ. We develop a top-down framework that uses hourly GEMS NO₂ columns to derive constraints on the daytime cycle of NO_x emissions. Emissions are first estimated from GEMS using a Cross-Sectional Flux (CSF) inversion and then incorporated into WRF-Chem through a novel optimization that reshapes the magnitude and daytime structure of NO_x while accounting for lifetime and satellite vertical sensitivity. GEMS-constrained NO_x emissions for March 2024 are estimated to range from 2.7 to 4.3 kt month⁻¹ after accounting for known low biases in the GEMS retrievals. Re-running WRF-Chem with the updated emissions leads to substantial improvements in modeled NO₂ magnitude and temporal variability when evaluated against independent ground-based, Pandora, and airborne measurements. Remaining negative biases are consistent with a systematic low bias in the GEMS v3 NO₂ product, highlighting the importance of multi-platform evaluation using independent observations. Together, these results demonstrate the value of hourly geostationary observations combined with high-resolution modeling as a scalable pathway for improving urban NO_x emissions estimates and air quality simulations in Southeast Asia.

Asia accounts for approximately half of global anthropogenic emissions of major pollutants, yet emission inventories remain uncertain and ground-based monitoring is sparse across much of the region. To address these challenges, this study applies a multi-species satellite data assimilation framework to estimate emissions and concentrations of key chemical species during the NASA's ASIA-AQ campaign. The assimilation improves agreement with airborne observations for O₃, NO_x, CO, and CH₂O, with the largest gains for CO (correlation increasing from 0.63–0.64 to 0.77) and CH₂O (biases reduced by 41–70 %). Domain-wide, the optimized emissions show increases of 15 % for NO_x and 9 % for CO, and a 52 % reduction in isoprene. Comparisons with multiple emission inventories reveal large discrepancies, with normalized standard deviation ranging from 11 % for NO_x in mainland China to 68 % for CO in Taiwan. Over Thailand, the assimilation increases fire emissions from 3.6 Tg (GFASv1.2) to 8.3 Tg, while FINNv2.7 produces estimates roughly twice as high, highlighting persistent divergence among fire emission estimates. Source-receptor analysis reveals strong meteorological control on transboundary pollutant: long-range transport contributes up to 62 % of surface O₃ in Manila during strong monsoon conditions, whereas Seoul exhibits local NO_x-saturated chemistry. During a strong transport episode, Indian emissions account for 72–78 % of the free tropospheric O₃ response over Taipei and Chiang Mai, and 24 % over Seoul, highlighting an overlooked transport pathway affecting Asian air quality. These results highlight the value of satellite data assimilation and the need for improved inventories and coordinated action on local and transboundary pollution.

Controlling ozone (O3) in rapidly urbanizing megacities in Southeast and East Asia remains a challenge. O3 is a secondary pollutant formed through nonlinear photochemical reactions with its precursors: nitrogen oxides (NOx) and volatile organic compounds (VOCs). Observation-based quantification of precursor sensitivity remains scarce, limiting actionable O3 control. To address this, we leverage airborne observations from the NASA DC-8 during the ASIA-AQ campaign conducted in February and March 2024 across four Asian megacities: Metro Manila, the Seoul Metropolitan Area, the Tainan–Kaohsiung Metropolitan Area, and the Bangkok Metropolitan Region. These extensive measurements of various trace gases were used to constrain a zero-dimensional box model and estimate the net production rates of Ox (POx, Ox = O3 + NO2). Precursor sensitivity regimes were characterized for each megacity by generating isopleths of POx across varying levels of NOx and VOCs. The analysis revealed that Manila and Tainan–Kaohsiung exhibited predominantly NOx-sensitive conditions, favoring NOx reduction as an effective O3 mitigation strategy, while Bangkok showed a more mixed sensitivity, suggesting combined NOx and VOC reductions. In contrast, Seoul exhibited a primarily VOC-sensitive regime associated with its higher NOx conditions relative to the other cities, underscoring the importance of VOC-focused strategies. In addition, to quantitatively assess sensitivity transitions, we computed orthogonal distances from the isopleth transition boundaries for all four study areas. Diurnal analyses of these distances revealed a shift from more VOC-sensitive conditions in the morning toward more NOx-sensitive regimes in the afternoon. These findings provide critical insights for formulating effective, city-specific O3 control policies in urban environments.

The Pandora Global Network (PGN) is a system of ground-based spectrometers reporting continuous daytime column HCHO and NO₂. While the Direct Sun (DS) NO₂ product has been well studied, the Multi Axis Differential Optical Absorption Spectroscopy (MAX DOAS) products are largely unvalidated. Using the Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas (AEROMMA) airborne campaign in the summer of 2023, we evaluate the performance of select Pandora monitors relative to in situ airborne observations. A case study over a Pandora in the California desert shows MAX DOAS HCHO captures the total tropospheric column (within 4 % of the integrated in situ column) but does not match the vertical shape of the HCHO profile where the Pandora is biased high near the surface and low near the top of the boundary layer. The MAX DOAS NO₂ is 80 % lower for the entire profile and is particularly sensitive to the viewing angle of the Pandora due to the spatial heterogeneity of NO₂. Nine Pandoras located in the New York City (NYC) domain capture the day to day variability of HCHO as well as spatial gradients from New Jersey to NYC to Long Island. The mean NYC Pandora HCHO correlates well with mean Tropospheric Emissions Monitoring of Pollution (TEMPO) HCHO columns of a similar domain on clear sky days. On those days, MAX DOAS columns exhibit a lower slope (slope = 0.78, y-intercept=1.08 x 10¹⁵ molec/cm²; R² = 0.62) while DS columns show a higher offset (slope = 0.90, y-intercept=2.83 x 10¹⁵ molec/cm²; R² = 0.63). These results demonstrate the value of Pandora HCHO products while highlighting the need for improved uncertainty quantification.

The Pandora Global Network (PGN) is a system of ground-based spectrometers reporting continuous daytime column HCHO and NO₂. While the Direct Sun (DS) NO₂ product has been well studied, the Multi Axis Differential Optical Absorption Spectroscopy (MAX DOAS) products are largely unvalidated. Using the Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas (AEROMMA) airborne campaign in the summer of 2023, we evaluate the performance of select Pandora monitors relative to in situ airborne observations. A case study over a Pandora in the California desert shows MAX DOAS HCHO captures the total tropospheric column (within 4 % of the integrated in situ column) but does not match the vertical shape of the HCHO profile where the Pandora is biased high near the surface and low near the top of the boundary layer. The MAX DOAS NO₂ is 80 % lower for the entire profile and is particularly sensitive to the viewing angle of the Pandora due to the spatial heterogeneity of NO₂. Nine Pandoras located in the New York City (NYC) domain capture the day to day variability of HCHO as well as spatial gradients from New Jersey to NYC to Long Island. The mean NYC Pandora HCHO correlates well with mean Tropospheric Emissions Monitoring of Pollution (TEMPO) HCHO columns of a similar domain on clear sky days. On those days, MAX DOAS columns exhibit a lower slope (slope = 0.78, y-intercept=1.08 x 10¹⁵ molec/cm²; R² = 0.62) while DS columns show a higher offset (slope = 0.90, y-intercept=2.83 x 10¹⁵ molec/cm²; R² = 0.63). These results demonstrate the value of Pandora HCHO products while highlighting the need for improved uncertainty quantification.

Nitrogen Dioxide (NO₂) is a key component of tropospheric chemistry and air quality, yet large uncertainties persist in regional NO_x emissions across rapidly developing megacities in Southeast Asia. Observations from the Geostationary Emissions Monitoring Spectrometer (GEMS) provide new constraints on anthropogenic NO₂ variability, while the 2024 NASA Airborne and Satellite Investigation of Asian Air Quality (ASIA-AQ) campaign, offers an extensive, independent dataset for model evaluation. We examine air quality in Bangkok using coarse (20 km) and high-resolution (4 km) WRF-Chem simulations during ASIA-AQ. We develop a top-down framework that uses hourly GEMS NO₂ columns to derive constraints on the daytime cycle of NO_x emissions. Emissions are first estimated from GEMS using a Cross-Sectional Flux (CSF) inversion and then incorporated into WRF-Chem through a novel optimization that reshapes the magnitude and daytime structure of NO_x while accounting for lifetime and satellite vertical sensitivity. GEMS-constrained NO_x emissions for March 2024 are estimated at 2.7 kT month^–1 over Bangkok, approximately 75 % lower than EDGAR v5. Re-running WRF-Chem with the updated emissions leads to substantial improvements in modeled NO₂ magnitude and temporal variability when evaluated against independent ground-based, Pandora, and airborne measurements. Remaining negative biases are consistent with a systematic low bias in the GEMS v3 NO₂ product that cannot be diagnosed using satellite data alone, highlighting the importance of multi-platform evaluation. Together, these results demonstrate the value of hourly geostationary observations combined with high-resolution modeling as a scalable pathway for improving urban NO_x emissions estimates and air quality simulations in Southeast Asia.