Source: Lin Jintai Lab, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University

Product Link: http://www.phy.pku.edu.cn/~acm/acmProduct.php#POMINO

Introduction

Tropospheric NO2 columns retrieved from satellite instruments are useful to infer NOx pollution, NOx emissions and atmospheric chemistry. Current satellite products are subject to limitations in assumptions of aerosol optical effects, surface reflectance anisotropy, vertical profiles of NO2, and cloud optical properties.

Here we develop an improved Peking University Ozone Monitoring Instrument NO2 product (POMINO) for China. As of 2018/09/20, there are two versions available: POMINO v1 and POMINO v2.

Algorithm

POMINO v1 (Lin et al., 2014; Lin et al., 2015):

This is the original "POMINO" algorithm.

POMINO v1 explicitly accounts for aerosol optical effects, angular dependence of surface reflectance, and dynamically varying atmospheric profiles of air pressure, air temperature and NO2 at a high horizontal resolution (25-50 km). The daily AOD data are simulated by nested GEOS-Chem and further constrained by MODIS (C5.1) data on a monthly basis. The daily BRDF data are from MCD43C2 (C5.1).

Prior to the NO2 retrieval, we retrieve cloud top pressure and cloud fraction using consistent assumptions about the states of the atmosphere and surface.

For our NO2 and cloud retrievals, we adopt from KNMI (viawww.temis.nl) the SCDs of tropospheric NO2 (DOMINO v2) and O2-O2 dimer (OMCLDO2 v1.1.1.3), the TOA reflectance, and some other ancillary information.

We develop the AMFv6 code for air mass factor calculation, based on the radiative transfer model LIDORT v3.6. The AMFv6 code improves upon the code developed by Paul Palmer, Randall Martin et al., with various aforementioned capability added/extended to accommodate the calculation here. With AMFv6, radiative transfer is calculated explicitly for each satellite pixel with no need to use a look-up table. The calculation of AMFv6 is parallelized and is sufficiently fast so that one day of retrieval with global coverage would only take about three hours using 16 CPU cores.

POMINO v2 (Liu et al., 2018):

On top of POMINO v1, POMINO v2 further constrains the vertical profile of aerosol extinction by monthly climatology from CALIOP, uses the SCD data from QA4ECV, and updates to MODIS (C6) merged AOD and MCD43C2 (C6) daily BRDF.

Validation

The POMINO v1 product is consistent with MAX-DOAS NO2 data in China, with a R^2 of 0.96 as compared to the value at 0.72 for DOMINO v2. The improved consistency is related to explicit pixel-by-pixel radiative transfer calculation (instead of using a look-up table), consistent treatments of all parameters in retrieving clouds and NO2, explicit consideration of aerosol optical effects (rather than adjusting 'effective' clouds to implicitly account for aerosols), and consideration of surface reflectance anisotropy.

The POMINO v1 product is able to capture the high pollution situations (e.g., high aerosol and NO2 concentrations), in addition to the modest and low population situations.

The POMINO v2 product further reduces the bias against MAX-DOAS data, while maintaining the high correlation.

AMFv6 Code

Our AMFv6 code is available for public use. Currently, AMFv6 also allows users to (some of them may need further customization):

1. Turn on/off explicit treatment of aerosol optical effects, or revise aerosol info using measurements

2. Choose from a variety of surface reflectance data (currently OMI, MODIS black-sky, MODIS blue-sky, MODIS BRDF)

3. Turn on/off dynamic atmosphere (e.g., time-varying air temperature, pressure profile, etc.)

4. Retrieve clouds online, or read cloud data from a third party

5. Read surface pressure measurement instead of using the one from model met field

6. Output AMFv6 results in either ascii, binary or netcdf format

7. Produce/use a look-up table (if desired in some cases)

POMINO v1 product

This is the original "POMINO" product.

As of 2018/09/20, data are available from 2004 through 2016. For newer data, see our POMINO v2 product below.

Figures

POMINO animation of monthly mean NO2 VCD maps (0.25 x 0.25 degree): 2004/10-2016/12

Level-3 data

POMINO Monthly or Daily Level-3 Data Download

Both daily and monthly Level-3 NO2 tropospheric VCD products are on a 0.25 x 0.25 degree grid, spatially aggregated from the Level-2 data.

Included in the Level-3 data are tropospheric NO2 AMF, tropospheric NO2 VCD, AOD at 550 nm, SSA at 550 nm, and other ancillary parameters.

The file "readme_POMINO_level3.txt" in the link above provides an introduction, including example reading programs in IDL and Fortran.

Level-2 data

POMINO Level-2 Data Download

Included are pixel-specific NO2 tropospheric VCD product and ancillary data.

Each tar.gz file contains a month worth of data files. Each data file contains Level-2 data for tropospheric NO2 AMF, tropospheric NO2 VCD, AOD at 550 nm, SSA at 550 nm, and other ancillary parameters.

The file "readme_POMINO_level2.txt" in the link above provides an introduction, including example reading programs in IDL and Fortran.

POMINO v2 product

This product is added on 2018/09/20.

As of 2018/09/20, data are available from 2004 through 2017.

Figures

POMINO v2 animation of monthly mean NO2 VCD maps (0.25 x 0.25 degree): 2004/10-2017/12

Level-3 data

POMINO v2 Monthly or Daily Level-3 Data Download

Both daily and monthly Level-3 NO2 tropospheric VCD products are on a 0.25 x 0.25 degree grid, spatially aggregated from the Level-2 data.

Included in the Level-3 data are tropospheric NO2 AMF, tropospheric NO2 VCD, AOD at 550 nm, SSA at 550 nm, and other ancillary parameters.

See user guide for brief documentation of the variables included (NO2 VCD, AMF, AOD, SSA, etc.), as well as how to read the Level-3 data.

Level-2 data

POMINO v2 Level-2 Data Download

See user guide for brief documentation of the variables included (NO2 VCD, AMF, AOD, SSA, etc.).

Examples to read the Level-2 data in IDL and Fortran are provided in the link above.

References

Lin, J.-T. *, R. V. Martin, K. F. Boersma, M. Sneep, P. Stammes, R. Spurr, P. Wang, M. Van Roozendael, K. Clémer, and H. Irie: Retrieving tropospheric nitrogen dioxide from the Ozone Monitoring Instrument: Effects of aerosols, surface reflectance anisotropy, and vertical profile of nitrogen dioxide, Atmos. Chem. Phys., 14, 1441-1461, doi:10.5194/acp-14-1441-2014, 2014 (PDF)

Lin, J.-T.*,Liu, M.-Y., Xin, J.-Y., Boersma, K. F., Spurr, R., Martin, R., and Zhang, Q.: Influence of aerosols and surface reflectance on satellite NO2 retrieval: seasonal and spatial characteristics and implications for NOx emission constraints, Atmospheric Chemistry and Physics, 15, 11217-11241, doi:10.5194/acp-15-11217-2015, 2015 (PDF) (Supplement)

Liu, M.-Y.,Lin, J.-T. *, Boersma, K. F. *, Pinardi, G., Wang, Y., Chimot, J., Wagner, T., Xie, P., Eskes, H., Van Roozendael, M., Hendrick, F., Wang, P., and Yan, Y.-Y.: Improved aerosol correction for OMI tropospheric NO2 retrieval over East Asia: constraint from CALIOP aerosol vertical profile, Atmospheric Measurement Techniques Discussions, doi:10.5194/amt-2018-34, 2018 (PDF) (under review for final publication at AMT)