the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 02 Dec 2024
Retrieval of NO2 profiles from three years of Pandora MAX-DOAS measurements in Toronto, Canada
Abstract. The purpose of this work is to derive new NO2 vertical profiling data products from Pandora spectrometers and investigate the factors contributing to the bias of this dataset relative to established ground-based and spaceborne datasets. Possible applications of the NO2 vertical profile dataset include air quality monitoring and satellite validation studies. We explore the application of the optimal estimation method to Pandora multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements to retrieve vertical profile information for nitrogen dioxide (NO2). We use the Heidelberg Profile (HeiPro) retrieval algorithm to derive, for the first time, NO2 profiles and partial columns (0–4 km) from Pandora MAX-DOAS measurements from 2018–2020 at Downsview, a suburban neighbourhood in the north end of Toronto, Canada that is subject to local traffic emissions and urban influences. Validation of the new dataset was done via comparison with official Pandora direct-Sun measurements, in situ observations, satellite data, and an air quality forecasting model. We find that, for tropospheric partial column comparisons, the HeiPro dataset has a positive mean relative bias to Pandora direct-Sun (61 % ± 9.7 %) and TROPOMI (41 % ± 47 %) observations, as well as the GEM-MACH model output (61 % ± 7.5 %), with similar seasonal and diurnal cycles in the bias with Pandora direct-Sun and GEM-MACH. Contributing factors to the large bias of HeiPro to Pandora direct-Sun were investigated, and NO2 heterogeneity, combined with differences between direct-Sun and multi-axis viewing geometries, was found to contribute a maximum of 52 % of the total relative bias during morning measurement times. For surface NO2 comparisons, we find that HeiPro measurements capture the magnitude and diurnal variability of surface NO2 reasonably well (mean relative bias to in situ surface NO2: −8.9 % ± 7.6 %) but are low-biased compared to GEM-MACH (mean relative bias: −36 % ± 2.4 %). Compared to HeiPro, the GEM-MACH model profiles are high-biased in the lower boundary layer and low-biased in the free troposphere.
- Preprint
(3695 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (until 14 Jan 2025)
-
RC1: 'Comment on amt-2024-180', Anonymous Referee #1, 28 Dec 2024
reply
The authors present a novel study using Pandora MAX-DOAS measurements and the HeiPro retrieval algorithm to produce a three-year dataset of NO2 profiles and partial columns in Toronto, Canada. While the paper provides valuable insights into the spatial and temporal distribution of NO2. However, several areas require clarification, reorganization, and deeper analysis to strengthen the validity and comprehensibility of the study. My detailed comments are below.
General Comments
Stratospheric-Tropospheric Separation (STS) Method
- The authors use a complicated approach involving a box model and OMI observations to separate stratospheric and tropospheric columns for Pandora direct-sun (DS) measurements. The STS method is questionable due to multiple layers of assumptions and models, creating uncertainties.
- Why not employ stratospheric-tropospheric column ratios from established models, such as CAMS, TM5, or GEM-MACH, to simplify and enhance the accuracy?
- A direct comparison of Pandora-DS total columns with TROPOMI total columns would provide additional insights into discrepancies between ground-based and satellite observations.
MAX-DOAS Retrieval and Atmospheric Profiles
- The description of the MAX-DOAS profile retrieval lacks essential details:
- Are the ERA5 atmospheric profiles daily averages or spatio-temporally interpolated to the measurement times?
- What assumptions are made about NO2 above the retrieval height? Are these values based on standard atmospheric profiles or other sources?
Data Consistency and Filtering
- The differences in coinciding data points in Figure 3(a) (direct sun) and Figure 3(c) (model comparisons) require clarification:
- If Pandora DS and MAX-DOAS data originate from the same source, why is there a discrepancy in the data points?
- Did the authors apply data filtering, such as cloud filtering, before using Pandora data for MAX-DOAS retrievals?
- Similarly, in Figure 4, the differences between MAX-DOAS (HeiPro) results in panels (a) vs. (c) and (b) vs. (d) need to be explained.
Organization and Logical Flow
- Figure 1 is currently located in the introduction but would fit better in Section 2, "Instrument Description," to align with the discussion of the Pandora instrument and measurement conditions.
- Section 2 should follow a logical sequence: instrument description, retrieval algorithm, and then the models/data used for comparison and validation. This reorganization would enhance the clarity of the methods section.
Wavelength Range and Spectral Retrieval
- The wavelength ranges for direct-sun and MAX-DOAS spectral fits are unclear:
- Did the authors use the same wavelength range for both retrievals? If not, provide justification for the differences.
- Details of the spectral retrieval process should be included.
- Line 217-218 mentions NO2 retrieval in both UV and VIS bands—did the authors compare results from these bands? Specify which band was used for comparisons with direct sun, satellite, and model data.
Quality Filtering and Averaging Kernels
- Section 2.2.2 discusses filtering criteria (e.g., DOFS < 1), but the rationale behind these criteria is not well explained:
- Provide theoretical or empirical justification for the chosen threshold.
- What is the typical DOFS value in the retrieval? Including an averaging kernel plot would help visualize the retrieval sensitivity.
- Demonstrating the impact of data filtering on the results would also improve transparency.
Comparison of Data Sources
- In the results section, the biases between HeiPro, Pandora-DS, TROPOMI, and GEM-MACH are analyzed, but the spatial, temporal, and observational characteristics of these datasets are not sufficiently discussed:
- Summarize the resolutions, error characteristics, and limitations of each dataset in a table for clarity.
- Quantify the contributions of individual factors (e.g., PBL height, SAA, and seasonality) to observed biases rather than relying solely on trend descriptions.
Seasonal and Diurnal Trends
- Provide more detailed explanations for observed trends:
- How do lower PBL heights in the early morning contribute to NO2 accumulation?
- Why are concentrations higher in winter?
- Correlate these trends with emission sources and meteorological conditions at the observation site.
Extrapolation and Vertical Profiles
- Discuss the limitations of linear extrapolation methods used in vertical NO2 profile retrievals. Explore non-linear methods for more accurate surface concentration estimates.
- Analyze the changes in GEM-MACH profiles before and after smoothing across different height ranges, identifying layers with the most significant changes.
Minor Comments
Technical Issues
- Line 225: The term "DOF" is inconsistently introduced. Ensure its full form and abbreviation are aligned throughout the text.
- Standardize terminology for "Pandora direct-Sun" and "Pandora-DS" to avoid confusion.
Figures and Tables
- Figures 3 and 4: Clarify the differences in datasets and ensure consistent labeling.
- Add a table summarizing key attributes of the datasets (e.g., resolution, uncertainties).
Section 3.1.1
- The calculation of the 0–15 meter column concentration relies on surface NO2 measurements. Discuss the reliability of this assumption and its impact on comparisons. Quantify the average 0–15 meter column in absolute and relative terms.
Citation: https://doi.org/10.5194/amt-2024-180-RC1
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 122 | 22 | 4 | 148 | 2 | 2 |
- HTML: 122
- PDF: 22
- XML: 4
- Total: 148
- BibTeX: 2
- EndNote: 2
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1