sensorair-qualityenvironmentpollutioncitiesclimatepublic-healthsensor-dataglobaldailyAQI

Urban Air Quality Monitoring

2020–2025

Free

Open dataset

Sample structure: 100 / 100

12 download links issued

Seller: waseemahmad

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Source, license and coverage

Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.

License: Not documented — confirm reuse terms with the seller
Source / creator: Not documented
Collection method: uploaded
Coverage / snapshot: 2020–2025
Data last updated: Not documented
Update schedule: Not documented

Coverage is stated by the supplier; it has not been verified against every record in the full file.

Sample structure score: 100 / 100

This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.

Assessed 10 sample records (CSV) on 2026-10-09. All records in the provided sample were checked.

Check	Points	Evidence
Populated cells	50 / 50	190 of 190 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated.
Consistent value types	30 / 30	190 of 190 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth.
Consistent record shape	20 / 20	10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys.

Field-level findings and improvements

Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.

Field	Missing cells	Most common type	Other populated types
date	0 / 10	string	0 / 10
city	0 / 10	string	0 / 10
country	0 / 10	string	0 / 10
continent	0 / 10	string	0 / 10
station_id	0 / 10	string	0 / 10
latitude	0 / 10	number	0 / 10
longitude	0 / 10	number	0 / 10
pm25_ugm3	0 / 10	number	0 / 10
pm10_ugm3	0 / 10	number	0 / 10
no2_ppb	0 / 10	number	0 / 10
so2_ppb	0 / 10	number	0 / 10
o3_ppb	0 / 10	number	0 / 10
co_mgm3	0 / 10	number	0 / 10
aqi	0 / 10	number	0 / 10
aqi_category	0 / 10	string	0 / 10
temperature_celsius	0 / 10	number	0 / 10
relative_humidity_pct	0 / 10	number	0 / 10
wind_speed_kmh	0 / 10	number	0 / 10
city_population_millions	0 / 10	number	0 / 10

How the score is calculated, its limitations, and how to correct an assessment →

About this data

Daily air quality measurements for 60 major cities across 6 continents, including PM2.5, PM10, NO2, SO2, O3, CO concentrations, computed AQI values, weather conditions, and city metadata. Data reflects seasonal patterns and multi-year trends.

Retrieve with your agent or Python

Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.

Download the Python example

python3 retrieve-dataset.py 7ca3e269-fb6d-4f3e-8fea-c4d0a5add01e --output dataset.bin

Full supplier documentation

Original supplier listing: Urban Air Quality Monitoring — 60 Cities, 6 Continents (2020–2025) Consolidated daily air quality monitoring data for 60 major cities across 6 continents, spanning 2020-2025. Includes PM2.5, PM10, NO2, SO2, O3, and CO concentrations alongside computed AQI values, weather conditions (temperature, humidity, wind speed), and city metadata. Data is normalized across stations and reflects realistic seasonal patterns, weekend effects, and multi-year improvement trends. Ideal for environmental analysis, public health research, smart city planning, and ML model training for air quality prediction.

Schema

Name	Type	Description
date	string
city	string
country	string
continent	string
station_id	string
latitude	string
longitude	string
pm25_ugm3	string
pm10_ugm3	string
no2_ppb	string
so2_ppb	string
o3_ppb	string
co_mgm3	string
aqi	string
aqi_category	string
temperature_celsius	string
relative_humidity_pct	string
wind_speed_kmh	string
city_population_millions	string

Sample Data

Preview a sample of the data before downloading.

Public sample only. Sign in to retrieve the full dataset, including free datasets.

For AI Agents

Via MCP Server

# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
  "mcpServers": {
    "databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
  }
}

# 2. Your agent can then call:
search_datasets({ query: "Urban Air Quality Monitoring" })
// Found: 7ca3e269-fb6d-4f3e-8fea-c4d0a5add01e
get_download_url({ dataset_id: "7ca3e269-fb6d-4f3e-8fea-c4d0a5add01e" })  // free — sign in with MCP OAuth first

Via REST API

# Free dataset — sign in or use your account API key:
curl https://api.databazaar.io/datasets/7ca3e269-fb6d-4f3e-8fea-c4d0a5add01e/download-url -H "Authorization: Bearer $DATABAZAAR_API_KEY"