---
license: cc-by-4.0
task_categories:
- time-series-forecasting
tags:
- tsfile
- timeseries
- time-series
- air-quality
- pm25
- environment
- europe
- eea
- format:tsfile
pretty_name: EEA PM2.5 Air Quality Dataset (Europe)
configs:
- config_name: default
  data_files:
  - split: train
    path: "eea_pm25_forecasting_series*.tsfile"
---

# EEA PM2.5 Air Quality Dataset - Europe (TsFile)

Apache TsFile version of
[`cosuleabianca/eea-pm25-forecasting`](https://huggingface.co/datasets/cosuleabianca/eea-pm25-forecasting).

## Overview

Hourly air-quality and meteorology measurements from European Environment
Agency (EEA) monitoring sites prepared for PM2.5 forecasting research:
1,945,152 hourly rows (one per country + site + UTC hour) with PM2.5, NO2 and
PM10 concentrations, ERA5-style meteorology (temperature, humidity, dew
point, precipitation, pressure, wind components) and engineered calendar,
lag (1-168 h) and rolling (3-24 h) features for the three pollutants. The
repo's station reference table `site_metadata.csv` (EEA sampling-point
metadata) and `config.yaml` have no time axis and are mirrored unmodified
into this repository.

- **Rows:** 1,945,152 hourly observations; ~hundreds of EEA sites across
  countries (sample: 2018-01-08 start).
- Column names containing `.`/`-` (e.g. `PM2.5`, `PM2.5_lag_1h`,
  `StationArea_rural-nearcity`) are stored with `_` instead
  (PM2_5, PM2_5_lag_1h, StationArea_rural_nearcity).

## Schema (TsFile structure)

- **Time** (INT64, milliseconds) — `dt_utc` (explicit UTC offsets) as epoch.
- **Country, SiteNumber** (TAG, STRING) — one device per monitoring site.
- **dt_local, Start** (FIELD, STRING) — source wall-clock labels kept as-is.
- All other columns FIELD: PM2_5 / NO2 / PM10 (+ their lag/rolling features),
  meteorology columns, calendar/cyclical features (hour, day_of_week, ...
  season, hour_sin ...), and the station-type/area boolean flags.

## Usage

Install the Apache TsFile Python SDK (`pip install tsfile`) and read a converted file:

```python
from pathlib import Path
from tsfile import TsFileReader

path = Path("eea_pm25_forecasting_series_1.tsfile")
with TsFileReader(str(path)) as reader:
    schemas = reader.get_all_table_schemas()
    print("tables:", list(schemas))
    table_name = next(iter(schemas))
    table = schemas[table_name]
    columns = [column.get_column_name() for column in table.get_columns()]
    print("columns:", columns)
    field_names = [
        column.get_column_name()
        for column in table.get_columns()
        if column.get_column_name() not in {"Time", "time"}
    ]
    if field_names:
        with reader.query_table(table_name, field_names[:3], batch_size=1024) as result:
            batch = result.read_arrow_batch()
            if batch is not None:
                print(batch.to_pandas().head())
```

## Source & license

- Original dataset: <https://huggingface.co/datasets/cosuleabianca/eea-pm25-forecasting>
- License: CC-BY-4.0