Government
22 columns
120 rows
8 formats

Urban Air Quality Anomaly Logs

This dataset logs real-time urban air quality anomalies detected by distributed sensors, including detailed event metadata, pollutant measurements, severity levels, and resolution actions. It enables smart city teams and government agencies to monitor pollution spikes, identify sensor faults, and ensure rapid response for environmental compliance and public safety. The dataset supports spatial analysis, operational dashboards, and regulatory reporting.

last updated 9 Dec 2025
by GoMask

The brief that made it

Real-time monitoring and response to urban pollution spikes

Sample rows

preview · 8 of 120 rows · all 22 columns

anomaly_idstring	sensor_typestring	expected_range_maxfloat	resolvedboolean	location_countrystring	sensor_idstring	anomaly_timestampdatetime	location_latitudefloat	location_longitudefloat	location_street_addressstring	location_citystring	location_statestring	location_postal_codestring	pollutant_typestring	pollutant_valuefloat	anomaly_typestring	severity_levelstring	action_takenstring	resolution_timestampdatetime	reported_bystring	anomaly_descriptionstring
AQ-000001	PM2.5	35	true	USA	SENSOR-1240A	2024-04-16T08:15:23Z	34.052235	-118.243683	1200 S Flower St	Los Angeles	CA	90015	PM2.5	192.1	pollution_spike	high	notification_sent	2024-04-16T09:12:08Z	AutomatedSystem-1	Significant PM2.5 spike detected near downtown during morning rush hour.
AQ-000002	NO2	50	false	USA	SENSOR-2332B	2024-04-16T08:35:47Z	40.712776	-74.005974	55 Water St	New York	NY	10004	NO2	122.6	pollution_spike	medium	notification_sent	blank	FieldTech-7	Elevated NO2 levels observed near Battery Park, likely due to construction activity.
AQ-000003	CO2	600	false	UK	SENSOR-3923D	2024-04-16T10:02:20Z	51.507351	-0.127758	221B Baker St	London	blank	NW1 6XE	CO2	980.5	pollution_spike	critical	investigation_started	blank	AutomatedSystem-2	CO2 levels exceeded critical threshold in central London location.
AQ-000004	SO2	20	true	USA	SENSOR-2110C	2024-04-15T19:45:03Z	41.878113	-87.629799	233 N Michigan Ave	Chicago	IL	60601	SO2	89.2	pollution_spike	high	notification_sent	2024-04-15T20:10:44Z	FieldTech-2	SO2 spike detected near Millennium Park after power plant venting.
AQ-000005	O3	70	false	France	SENSOR-8765E	2024-04-16T11:25:46Z	48.856613	2.352222	10 Rue de Rivoli	Paris	blank	75001	O3	98.7	pollution_spike	medium	notification_sent	blank	AutomatedSystem-3	Ozone spike detected near city center during high traffic period.
AQ-000006	NO2	40	true	Japan	SENSOR-5432F	2024-04-16T13:13:18Z	35.689487	139.691711	2-8-1 Nishi-Shinjuku	Tokyo	blank	160-0023	NO2	284.3	pollution_spike	critical	investigation_started	2024-04-16T15:00:00Z	FieldTech-9	Critical NO2 anomaly detected in Shinjuku district during peak hour.
AQ-000007	CO2	650	false	Russia	SENSOR-3248G	2024-04-15T17:22:41Z	55.755825	37.617298	Arbat St 12	Moscow	blank	101000	CO2	2100	pollution_spike	critical	investigation_started	blank	AutomatedSystem-4	Record-breaking CO2 anomaly detected in Moscow center.
AQ-000008	PM2.5	35	true	Spain	SENSOR-1111H	2024-04-16T12:48:09Z	41.385063	2.173404	Carrer de Balmes 21	Barcelona	blank	08007	PM2.5	45.2	pollution_spike	medium	none	2024-04-16T13:30:00Z	FieldTech-3	PM2.5 levels moderately exceeded standards near Plaça Catalunya.
AQ-000009	NO2	45	false	Germany	SENSOR-2232J	2024-04-16T07:55:13Z	52.520008	13.404954	Friedrichstrasse 45	Berlin	blank	10117	NO2	90.4	pollution_spike	high	notification_sent	blank	AutomatedSystem-5	High NO2 detected near train station, likely due to diesel engines.
AQ-000010	O3	65	true	Japan	SENSOR-8321K	2024-04-16T14:32:26Z	34.693737	135.502167	Umeda 1-1-1	Osaka	blank	530-0001	O3	85.9	pollution_spike	high	notification_sent	2024-04-16T15:05:00Z	AutomatedSystem-6	Ozone anomaly in Umeda district, above standard for urban areas.
AQ-000011	SO2	20	true	Russia	SENSOR-9087L	2024-04-16T09:50:00Z	59.93428	30.335099	Nevsky Ave 32	Saint Petersburg	blank	191025	SO2	34.7	pollution_spike	medium	notification_sent	2024-04-16T10:30:00Z	FieldTech-5	SO2 anomaly detected near Winter Palace. Levels moderately high.
AQ-000012	Other	5	false	USA	SENSOR-4863M	2024-04-15T22:12:37Z	37.774929	-122.419418	200 Market St	San Francisco	CA	94105	Other	9.4	pollution_spike	low	none	blank	AutomatedSystem-7	Unusual pollutant detected in Embarcadero area, value above baseline.
AQ-000013	SO2	20	true	USA	SENSOR-2110C	2024-04-16T17:05:55Z	41.878113	-87.629799	233 N Michigan Ave	Chicago	IL	60601	SO2	26.5	pollution_spike	medium	notification_sent	2024-04-16T17:45:00Z	FieldTech-2	SO2 levels slightly above the expected range in Chicago Loop.
AQ-000014	PM2.5	35	false	USA	SENSOR-1240A	2024-04-16T15:23:39Z	34.052235	-118.243683	1200 S Flower St	Los Angeles	CA	90015	PM2.5	310.9	pollution_spike	critical	investigation_started	blank	AutomatedSystem-1	Extreme PM2.5 event detected near convention center.
AQ-000015	NO2	40	true	Japan	SENSOR-5432F	2024-04-16T16:44:20Z	35.689487	139.691711	2-8-1 Nishi-Shinjuku	Tokyo	blank	160-0023	NO2	47.1	pollution_spike	high	notification_sent	2024-04-16T17:15:00Z	FieldTech-9	NO2 readings above typical rush hour levels in Shinjuku.
AQ-000016	CO2	650	true	Russia	SENSOR-3248G	2024-04-16T18:11:33Z	55.755825	37.617298	Arbat St 12	Moscow	blank	101000	CO2	865.2	pollution_spike	critical	investigation_started	2024-04-16T18:49:00Z	AutomatedSystem-4	CO2 spike recurred in Moscow, exceeding safe urban levels.
AQ-000017	O3	65	false	Japan	SENSOR-8321K	2024-04-16T20:21:09Z	34.693737	135.502167	Umeda 1-1-1	Osaka	blank	530-0001	O3	68	pollution_spike	high	notification_sent	blank	AutomatedSystem-6	Ozone anomaly in Umeda continues into evening hours.
AQ-000018	SO2	20	true	Russia	SENSOR-9087L	2024-04-16T21:07:42Z	59.93428	30.335099	Nevsky Ave 32	Saint Petersburg	blank	191025	SO2	21.5	pollution_spike	medium	none	2024-04-16T21:45:00Z	FieldTech-5	SO2 anomaly persists near museum quarter, slightly above threshold.
AQ-000019	Other	5	false	USA	SENSOR-4863M	2024-04-16T23:09:18Z	37.774929	-122.419418	200 Market St	San Francisco	CA	94105	Other	7.8	pollution_spike	low	none	blank	AutomatedSystem-7	Mild anomaly for unclassified pollutant in SOMA district.
AQ-000020	CO2	650	false	Russia	SENSOR-3248G	2024-04-17T01:01:11Z	55.755825	37.617298	Arbat St 12	Moscow	blank	101000	CO2	1450.3	pollution_spike	critical	investigation_started	blank	AutomatedSystem-4	Severe CO2 anomaly overnight, possible industrial source.

What the 120 rows show

from the 120-row sample

CO2 (sensor type) stands out: mean expected_range_max is 528.6, against 44.4 for the rest.

55%resolved = true
55median expected_range_max
4severity levels
4action takens
6pollutant types
85.8median pollutant_value

Mean expected_range_max by sensor_type120 rows

expected_range_max120 rows, in bands of 100

Median 55, from 5 to 650.

location_country120 rows · top 10 of 33 values

USA30
Japan15
Russia12
Germany8
France7
Spain5
UK3
United Kingdom3
Italy3
India3

22 columns by typefrom the column list below

string 14
float 5
datetime 2
boolean 1

Columns

22 columns in four groups

blueprint · 22 columns
column	type	description	example
Text 14 columns
`anomaly_id`	string	Unique identifier for each air quality anomaly eventunique	AQ-000001
`sensor_id`	string	Unique identifier for the air quality sensor reporting the anomaly	SENSOR-1240A
`sensor_type`	string	Type of air quality sensor (e.g., PM2.5, NO2, CO2)6 values	PM2.5
`location_street_address`	string	Street address of the sensor locationoptional	1200 S Flower St
`location_city`	string	City where the sensor is located	Los Angeles
`location_state`	string	State or province of the sensor locationoptional	CA
`location_postal_code`	string	Postal code of the sensor locationoptional	90015
`location_country`	string	Country where the sensor is located	USA
`pollutant_type`	string	Type of pollutant detected as anomalous (e.g., PM2.5, NO2, CO2)6 values	PM2.5
`anomaly_type`	string	Type of anomaly detected (e.g., pollution_spike, sensor_fault)pollution_spike · sensor_fault · data_gap · other	pollution_spike
`severity_level`	string	Severity of the anomaly (e.g., low, medium, high, critical)low · medium · high · critical	high
`anomaly_description`	string	Detailed description of the anomaly eventoptional	Significant PM2.5 spike d…
`action_taken`	string	Immediate action taken in response to the anomaly (e.g., notification_sent, sensor_reset, investigation_started)5 values · optional	notification_sent
`reported_by`	string	Name or identifier of the system or user reporting the anomalyoptional	AutomatedSystem-1
Numbers 5 columns
`location_latitude`	float	Latitude coordinate of the sensor location-90 to 90	34.052235
`location_longitude`	float	Longitude coordinate of the sensor location-180 to 180	-118.243683
`pollutant_value`	float	Measured value of the pollutant at the time of anomaly0 or more	192.1
`expected_range_min`	float	Minimum expected value for the pollutant under normal conditions0 or more · optional	0
`expected_range_max`	float	Maximum expected value for the pollutant under normal conditions0 or more · optional	35
Dates and times 2 columns
`anomaly_timestamp`	datetime	Date and time when the anomaly was detected	2024-04-16T08:15:23Z
`resolution_timestamp`	datetime	Date and time when the anomaly was resolved (if applicable)optional	2024-04-16T09:12:08Z
True or false 1 column
`resolved`	boolean	Indicates whether the anomaly has been resolved	true

Use it for

A government dashboard
The resolved rate, expected_range_max by sensor_type and a breakdown of location_country. Excel, Power BI or Tableau.
Why do the 21 CO2 rows have a mean expected_range_max of 528.6?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Anomalies120
AQ-00000135PM2.5
AQ-00000250NO2
AQ-00000420SO2
A software demo
Believable anomalies with sensor_id, sensor_type and anomaly_timestamp to fill a screen in front of a buyer.

This dataset120 rows22 columns

Yours1,000 rows22 columnslocation_latitude: UK only

blueprint · urban-air-quality-anomaly-logs

Behind this dataset

Same schema. As many rows as you need.

These 120 rows came out of a blueprint — 22 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with

Log entries must include timestamp, sensor ID, location coordinates, and detected anomaly type.
Anomaly types include: high PM2.5, low O2, sensor malfunction, and unexpected chemical presence.
Each sensor can report only one anomaly per 10-minute interval.
Severity rating (Low/Medium/High/Critical) is assigned based on deviation from regulatory thresholds.
Response action field is required if severity is Critical.

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: urban-air-quality-anomaly-logs

What should your data show?

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Sample rows

What the 120 rows show

Columns

Use it for

A government dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Government

What should your data show?