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Full catalog/MERRA2_CNN_HAQAST_PM25
MERRA2_CNN_HAQAST_PM25·v1·dataset

Hourly fine-particle air pollution (PM2.5)

MERRA2_CNN_HAQAST bias corrected global hourly surface total PM2.5 mass concentration, V1 (MERRA2_CNN_HAQAST_PM25) at GES DISC
atmosphere NASA GES_DISC Level 4 active
In plain English

What it measures. Hourly estimates of fine-particle air pollution (PM2.5) at the surface across the globe, in micrograms per cubic meter, along with a flag rating each value's quality.

How it's made. Not a direct satellite image, but a machine-learning product: a neural network corrects the MERRA-2 atmospheric model's output to better match real PM2.5, covering the years 2000 to 2024.

How & where you'd use it. Supports air-quality and public-health studies, letting researchers look at when and where harmful fine particles were highest, even in places without ground monitors. The quality flags help pick the most reliable points.

What's measured

ATMOSPHERE › AIR QUALITYATMOSPHERE › AEROSOLS › PARTICULATE MATTERHUMAN DIMENSIONS › PUBLIC HEALTH › ENVIRONMENTAL HEALTH FACTORS › PARTICULATE MATTER (PM 2.5)

Coverage & cadence

  • Time span2000-01-01 → ongoing
  • Measured byData Analysis (NOT APPLICABLE)
  • Processing levelLevel 4
  • Spatial extent-180, -90, 180, 90
  • StatusACTIVE

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

This product provides MERRA-2 bias-corrected global hourly surface total PM2.5 mass concentration with the same horizontal spatial resolution as MERRA-2, covering a temporal range from 2000 to 2024. It is derived using a machine learning (ML) approach with a convolutional neural network (CNN) method and is specifically developed for the NASA Health and Air Quality Applied Sciences Team (HAQAST). The dataset consists of two parameters: MERRA2_CNN_Surface_PM25 and QFLAG. MERRA2_CNN_Surface_PM25, a 3-dimensional variable (time, latitude, longitude), represents the surface PM2.5 concentrations in µg/m³. QFLAG denotes the quality of data at each grid point, where 4 indicates the highest quality and 1 indicates the lowest quality. It is recommended to use QFLAG values of 3 and 4 for quantitative analysis.

Get the data

merra2_cnn_haqast_pm25_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="MERRA2_CNN_HAQAST_PM25",
    version="1",
    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.