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Full catalog/MSAQSO2L4
MSAQSO2L4·v2·dataset

Sulfur dioxide air pollution worldwide, long record

Multi-Satellite Air Quality Sulfur Dioxide (SO2) Database Long-Term L4 Global V2 (MSAQSO2L4) at GES DISC
atmosphere NASA GES_DISC Level 4
In plain English

What it measures. A worldwide catalogue of sulfur dioxide pollution from large point sources — listing each site's location, type, country, and yearly emissions with uncertainty estimates.

How it's made. Built by combining sulfur-dioxide measurements from several satellites (OMI on Aura, OMPS on Suomi-NPP, and TROPOMI on Sentinel-5P) into a long-term, multi-decade record.

How & where you'd use it. Useful for tracking emissions from power plants, smelters, and volcanoes, and for monitoring how pollution sources change over the years.

What's measured

ATMOSPHERE › AEROSOLS › SULFATE PARTICLESATMOSPHERE › AIR QUALITY › SULFUR OXIDESATMOSPHERE › ATMOSPHERIC CHEMISTRY › SULFUR COMPOUNDS › SULFUR DIOXIDEHUMAN DIMENSIONS › NATURAL HAZARDS › VOLCANIC ERUPTIONS

Coverage & cadence

  • Time span2005-01-01 → 2024-12-31
  • Measured byAura (OMI) · Suomi-NPP (OMPS) · Sentinel-5P (TROPOMI) · NOAA-20 (OMPS)
  • Processing levelLevel 4
  • Spatial extent-180, -90, 180, 90
  • StatusCOMPLETE

What you can do with it

  • Map air pollutants — NO₂, aerosols, ozone
  • Track greenhouse gases and Earth's energy budget
  • Feed weather and air-quality analysis
Official description

These data are a part of Multi-Decadal Sulfur Dioxide (SO2) Climatology from Satellite Instruments (MEaSUREs-12-0022 project). Version 2 of the global catalogue of emissions from large SO2 point sources combines data from the Ozone Monitoring Instrument (OMI) on NASA's EOS Aura spacecraft, the Ozone Mapping and Profiler Suite (OMPS) on the NASA-NOAA Suomi National Polar-orbiting Partnership (SNPP), and the TROPOspheric Monitoring Instrument (TROPOMI) on the ESA/Copernicus Sentinel-5 Precursor (S-5P) spacecraft. The catalogue MSAQSO2L4 file contains the site coordinates, source type, country, source name, annual SO2 emissions, annual emission uncertainties, and the number of satellite pixels in the fitting area for three satellite instruments as well as for their weighted average. The emission estimates are based on operational version 2 OMI and OMPS Principal Component Analysis (PCA) retrieval algorithm SO2 slant column density (SCD) data (Li et al., 2020) as well as on new TROPOMI Covariance-Based Retrieval Algorithm (COBRA) SCD data (Theys et al., 2021). A single time-independent site-specific Air-Mass Factor (AMF) value for each site was calculated (McLinden et al., 2014) and applied consistently to each satellite SCD dataset to derive SO2 vertical column densities (VCDs=SCDs/AMFs). The emission estimate method is based on a fit of satellite VCDs to an empirical plume model developed to describe the SO2 spatial distribution near emission point sources. The plume model assumes that the SO2 concentrations emitted from a point source decline exponentially with distance and that they are affected by turbulent diffusion that can be described by a two-dimensional (2D) exponentially modified Gaussian function. The total SO2 mass is derived from the fit and the annual emission rate is calculated as the ratio between the total mass and the prescribed SO2 lifetime.

Get the data

msaqso2l4_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="MSAQSO2L4",
    version="2",
    bounding_box=(-122.5, 37.2, -121.8, 37.9),  # your area (W,S,E,N)
    temporal=("2024-01-01", "2024-12-31"),       # your dates
)
files = earthaccess.open(results)   # stream straight from GES_DISC
Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.