AirQualityBench: A Realistic Evaluation Benchmark for Global Air Quality Forecasting
Paper • 2605.05854 • Published
Datasets:
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: ValueError
Message: Dataset 'params' has length 6 but expected 8760
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 80, in _generate_tables
num_rows = _check_dataset_lengths(h5, self.info.features)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/hdf5/hdf5.py", line 359, in _check_dataset_lengths
raise ValueError(f"Dataset '{path}' has length {dset.shape[0]} but expected {num_rows}")
ValueError: Dataset 'params' has length 6 but expected 8760Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
AirQualityBench
A global-scale air quality forecasting benchmark featuring 3,720 monitoring stations across the world with authentic missing patterns and physical-scale evaluation.
Dataset Summary
AirQualityBench provides a realistic testbed for air quality prediction by preserving raw observational characteristics that prior benchmarks have removed through imputation. The dataset spans 5 years (2021–2025) of hourly measurements across 6 primary pollutants (PM2.5, PM10, NO₂, O₃, SO₂, CO).
Key Features
- Global scale: 3,720 active stations spanning 7 continents, sourced from OpenAQ
- Authentic missingness: No imputation — evaluation uses boolean masks to score only valid observations
- Physical-scale metrics: All statistics computed in original concentration units (μg/m³ for gases, mg/m³ for CO)
- Multi-pollutant: 6 pollutants evaluated jointly
Data Structure
Each yearly HDF5 file (aq_compact_{year}.h5) contains:
| Dataset | Shape | Description |
|---|---|---|
values |
(T, 3720, 6) |
Hourly concentrations (float32) |
masks |
(T, 3720, 6) |
Valid observation flags (bool) |
station_ids |
(3720,) |
Station identifiers |
params |
(6,) |
Pollutant names |
Additional files:
adj_mx_10.pkl— KNN adjacency matrix (k=10, Haversine distance)scaler.csv— Per-pollutant mean/std for normalizationglobal_quality_stats.csv— Per-station, per-pollutant coverage ratesselected_nodes_metadata.csv— Station coordinates and metadataall_stations_coords.csv— Raw station coordinates from OpenAQ
Data Splits
| Split | Years | Approx. Hours |
|---|---|---|
| Train | 2021–2023 | ~26,280 |
| Validation | 2024 | ~8,784 |
| Test | 2025 | ~8,760 |
Usage
This dataset uses the HDF5 format with multiple internal arrays of different shapes, which is incompatible with the datasets library's HDF5 loader. Use h5py to read the files directly:
import h5py
with h5py.File("aq_compact_2021.h5", "r") as f:
values = f["values"][:] # (T, 3720, 6) float32
masks = f["masks"][:] # (T, 3720, 6) bool
params = f["params"][:] # (6,) pollutant names
station_ids = f["station_ids"][:] # (3720,) station IDs
Benchmark Code
Training and evaluation code: github.com/Star-Learning/AirQualityBench
Citation
@article{xu2026airqualitybench,
title={AirQualityBench: A Realistic Evaluation Benchmark for Global Air Quality Forecasting},
author={Xu, Xing and Wang, Xu and Zhang, Yudong and Zhao, Huilin and Zhou, Zhengyang and Wang, Yang},
journal={arXiv preprint arXiv:2605.05854},
year={2026}
}
- Downloads last month
- -