# EU Air Quality Scenario Records — EEA AQ Plans (`nexgensignal/eu-air-quality-scenario-records`) Actor

Keyless pay-per-record EEA air-quality scenarios — base vs projection emissions/concentration/exceedances. Projections labelled verbatim; no persons. EEA acknowledge. GOLD $0.05 ladder.

- **URL**: https://apify.com/nexgensignal/eu-air-quality-scenario-records.md
- **Developed by:** [NexGen Signal](https://apify.com/nexgensignal) (community)
- **Categories:** Automation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $33.50 / 1,000 scenario records

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## EU Air Quality Scenario Records — EEA AQ Plans

**Keyless. Pay per record. Every European air-quality projection — base versus projected emissions, concentration, and exceedances — as one clean table.**

This actor turns the **European Environment Agency (EEA) Air Quality e-Reporting** scenarios dataset into clean, per-scenario records — the modelled base-and-projection scenarios that member states report under EU air-quality plans to show how a polluted zone is expected to reach compliance. Each run reads the EEA's keyless DiscoData SQL service and delivers one row per scenario: its identifier and code, the country and reporting year, the plan it belongs to, the start and attainment years, and — paired exactly as the source reports them — the **base**-scenario and **projection**-scenario values for emissions, concentration, and exceedances, plus the air pollutant, protection target, and zone. Scenario grain, structured for engineering use, reusable with acknowledgement of the EEA, with no personal data of any kind, and projections labelled as projections — never upgraded to fact.

### What this is, in one paragraph

When a European zone exceeds an air-quality limit, the member state models what will happen: a **base** scenario (the situation without new action) and a **projection** scenario (the expected situation once measures take effect), for a target attainment year. The EEA collects those scenarios. This actor reads that dataset and flattens each scenario into a single analysis-ready record: the scenario id and code, the country and reporting year, the plan id, the start year and attainment year, the first exceedance date, and the paired base/projection values for emissions, concentration, and exceedances — each carried under its own label — along with the air pollutant, protection target, objective type, reporting metric, and zone. The projection values are **modelled forecasts**, labelled exactly as the source labels them and never presented as measured outcomes. Values are carried **verbatim**. You are billed only for records actually delivered.

### Who buys this and for what job

- **Clean-air, policy-modelling, and consultancy teams** comparing projected air-quality improvements against baselines across Europe.
- **Environmental-analytics and ESG products** tracking which zones are projected to reach attainment, and when.
- **Researchers and NGOs** studying the gap between base and projection scenarios by pollutant and country.
- **Data engineers** who want the AQ scenarios as clean rows without writing SQL against the EEA service.

### EEA licence — reuse with acknowledgement

One licence rider travels on every record. EEA data may be **reused, including commercially, provided the source is acknowledged**: "Source: European Environment Agency (EEA)." Where third-party content is marked, it keeps its own terms. The data is a set of reported modelled scenarios as published — a projection is a forecast, not an outcome.

### Scenario grain — no person data, projections labelled as projections

The unit of every record is a modelled scenario — a projection, never a person. The dataset carries no natural-person fields; scenario codes, plan ids, pollutants, zones, and numeric base/projection values are the entire payload, and a person-key guard runs on every record as a pure backstop. Crucially, the base and projection values are kept **separate and labelled** — `base_scenario_*` and `projection_scenario_*` — so a projection is never silently presented as a measured fact.

### Sample output

![Sample output — EU Air Quality Scenario Records — EEA AQ Plans](https://api.apify.com/v2/key-value-stores/IXCaMKjxSmUTLHhmq/records/eu-air-quality-scenario-records.png)

*Real rows from a live run of this actor (first 5 rows, selected columns).*

One full record from the same run, exactly as delivered:

```json
{
  "record_id": "01270629-dba7-e511-9f2a-000d3a213c5b",
  "scenario_id": "01270629-dba7-e511-9f2a-000d3a213c5b",
  "scenario_code": "PL0202/15/As;",
  "country": "Poland",
  "country_code": "PL",
  "reporting_year": 2013,
  "aq_plan_id": "606348e7-daa7-e511-9f2a-000d3a213c5b",
  "start_year": 2023,
  "attainment_year": 2013,
  "first_exceedance_date": "2013",
  "publication": null,
  "base_scenario_emissions": 3.25e-05,
  "projection_scenario_emissions": 2.147e-05,
  "base_scenario_concentration": 0.0115,
  "projection_scenario_concentration": 0.0069,
  "base_scenario_exceedances": null,
  "projection_scenario_exceedances": null,
  "ns_wss_correction": null,
  "air_pollutant": null,
  "protection_target": null,
  "objective_type": null,
  "reporting_metric": null,
  "zone_id": null,
  "attainment_id": null,
  "source_data_url": "https://cdr.eionet.europa.eu/pl/eu/aqd/j/envvokhyg/1_01270629-dba7-e511-9f2a-000d3a213c5b.xml",
  "source": "EEA Air Quality e-Reporting — scenarios",
  "source_url": "https://discodata.eea.europa.eu/",
  "licence": "European Environment Agency (EEA) Air Quality e-Reporting — air-quality SCENARIOS dataset. Reuse is permitted, including for commercial purposes, provided the source is acknowledged: 'Source: European Environment Agency (EEA)'. Third-party content, where marked, keeps its own terms.",
  "attribution": "Source: European Environment Agency (EEA), Air Quality e-Reporting — scenarios dataset.",
  "disclaimer": "Air-quality PROJECTION-SCENARIO records at scenario grain, as reported by member states under the Air Quality Directive and published by the EEA. Each record pairs a BASE-scenario value with a PROJECTION-scenario value for emissions, concentration, and exceedances. The projection values are modelled projections — labelled here exactly as the source labels them (base vs projection) and NEVER presented as measured fact. Scenario/zone/pollutant grain — no natural-person data. Values carried VERBATIM; a projection is a forecast, not an outcome.",
  "observed_at": "2026-09-25T17:31:28Z"
}
```

### Pricing

| Event | Free plan | Bronze | Silver | Gold / Platinum / Diamond |
|-------|-----------|--------|--------|---------------------------|
| `scenario_record` | $0.05 | $0.045 | $0.04 | $0.0335 |

Delivered before charged. Blocked runs and empty results cost nothing.

### Input

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `countryCode` | string | — | Optional 2-letter country code (e.g. DE, FR, IT). |
| `year` | integer | — | Optional reporting year to filter. |
| `pollutant` | string | — | Optional air pollutant (e.g. NO2, PM10, PM2.5, O3). |
| `maxRecords` | integer | 500 | Ceiling on records delivered and billed. |

### Output

One JSON object per scenario. Real example (values as published):

```json
{
  "record_id": "EVS.AT_05_NO2_2014",
  "scenario_id": "EVS.AT_05_NO2_2014",
  "scenario_code": "AT_05_2010_2020",
  "country": "Austria",
  "country_code": "AT",
  "reporting_year": 2014,
  "aq_plan_id": "PLA.AT_05_2014",
  "start_year": 2010,
  "attainment_year": 2020,
  "base_scenario_emissions": 5730.0,
  "projection_scenario_emissions": 4580.0,
  "base_scenario_concentration": 43.0,
  "projection_scenario_concentration": 40.0,
  "air_pollutant": "NO2",
  "protection_target": "Health",
  "objective_type": "Limit Value (LV)",
  "reporting_metric": "Annual mean / average",
  "zone_id": "ZON-AT_05",
  "source": "EEA Air Quality e-Reporting — scenarios",
  "licence": "European Environment Agency (EEA) ... provided the source is acknowledged ...",
  "disclaimer": "Air-quality PROJECTION-SCENARIO records ... labelled ... as the source labels them ... never ... measured fact ...",
  "observed_at": "2026-08-22T00:00:00Z"
}
```

An unbilled `RUN_RECEIPT` records the robots check, the filters, rows seen and delivered, and whether charged equals delivered.

### Field reference

Each record is one scenario. Identity: `record_id` / `scenario_id`, `scenario_code`, and `aq_plan_id`. Scope and time: `country`, `country_code`, `reporting_year`, `start_year`, `attainment_year`, and `first_exceedance_date`. Base vs projection (each labelled): `base_scenario_emissions` / `projection_scenario_emissions`, `base_scenario_concentration` / `projection_scenario_concentration`, and `base_scenario_exceedances` / `projection_scenario_exceedances`, plus `ns_wss_correction` and `publication`. Target: `air_pollutant`, `protection_target`, `objective_type`, and `reporting_metric`. Links: `zone_id`, `attainment_id`, and `source_data_url`. Provenance: `source`, `source_url`, `licence`, `attribution`, `disclaimer`, and `observed_at`.

### How a run works

A run first re-reads the source host's robots posture from your runtime — the EEA DiscoData host — and stops at the door if that ever changes. It queries the scenarios table through the DiscoData SQL service, applies your optional country, year, and pollutant filters, and flattens each scenario to one record — carrying the base and projection values **verbatim and separately labelled**, never merging them or presenting a projection as fact, and never anything person-shaped — delivered **before** it is charged, so a blocked or empty run costs you nothing. The actor stops at your `maxRecords` ceiling and records `charge_equals_delivered` in the receipt.

### Coverage and scope

The scenarios dataset holds on the order of **7,000 reported scenarios** across the reporting countries. Because each record carries the `country_code`, `air_pollutant`, `attainment_year`, and the base/projection pairs, segmenting by country, pollutant, or target year — and computing the projected improvement — is straightforward. Pull one country, one pollutant, or the whole set to seed a scenarios table.

### Working with the scenarios

The scenarios are built to be compared against their baselines, and the paired labelling makes that safe. Because every record carries `base_scenario_concentration` alongside `projection_scenario_concentration` (and the same for emissions and exceedances), the projected improvement is a single subtraction — while the labelling keeps the projection clearly a forecast, never a measurement. The `attainment_year` and `start_year` frame each scenario in time, so an analyst can line up scenarios by target year across countries, and the `air_pollutant` with `protection_target` and `objective_type` locate each scenario against the specific limit it addresses. The `zone_id` and `aq_plan_id` join scenarios to zones and plans, and to the companion air-quality **measures** dataset, so the projected effect of a plan can be read next to the measures that produce it.

### Cost guidance

One `scenario_record` per delivered scenario: cost = scenarios delivered × your plan's per-record price. Scope with `countryCode`, `year`, or `pollutant`. The whole set is ~7,000 scenarios; 1,000 scenarios is **$50** (Free) / **$33.50** (Gold).

### Honest limitations

- **Projections, not outcomes.** Projection values are modelled forecasts, labelled as such and never presented as measured fact.
- **As published.** Base and projection values are carried verbatim; this actor reformats, it does not re-model.
- **Acknowledge the EEA.** The acknowledgement travels on every record.
- **No person data** of any kind.

### Differentiation

It is the projection companion to the fleet's air-quality **measure** records (the actions) and distinct from any monitoring or emissions cell (measured readings, not modelled scenarios). Its specific job is the **EEA air-quality scenarios dataset** — base versus projection, scenario by scenario.

### The NexGen Signal family

Part of the NexGen Signal family of pay-per-record data products:

- [EU Air Quality Measure Records — EEA AQ Plans](https://apify.com/nexgensignal/eu-air-quality-measure-records)
- [EU GHG Inventory Records — EEA](https://apify.com/nexgensignal/eu-ghg-inventory-records)
- [EU Industrial Emissions Records — EEA IED Facilities](https://apify.com/nexgensignal/eu-industrial-emissions-records)
- [EU Nitrate Monitoring Records — EEA WISE Nitrates](https://apify.com/nexgensignal/eu-nitrate-monitoring-records)
- [EU Bathing Water Quality Records — EEA BWD](https://apify.com/nexgensignal/eu-bathing-water-quality-records)

*Source: European Environment Agency (EEA), Air Quality e-Reporting — scenarios dataset (discodata.eea.europa.eu). EEA data may be reused, including commercially, provided the source is acknowledged: "Source: European Environment Agency (EEA)"; marked third-party content keeps its own terms. Scenario grain; base and projection values labelled separately and carried verbatim, projections never presented as measured fact; no person data of any kind.*

# Actor input Schema

## `countryCode` (type: `string`):

Optional 2-letter country code (e.g. DE, FR, IT).

## `year` (type: `integer`):

Optional reporting year to filter.

## `pollutant` (type: `string`):

Optional air pollutant to filter (e.g. NO2, PM10, PM2.5, O3).

## `maxRecords` (type: `integer`):

Maximum records delivered and billed.

## Actor input object example

```json
{
  "maxRecords": 10
}
```

# Actor output Schema

## `results` (type: `string`):

Delivered records.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "maxRecords": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("nexgensignal/eu-air-quality-scenario-records").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "maxRecords": 10 }

# Run the Actor and wait for it to finish
run = client.actor("nexgensignal/eu-air-quality-scenario-records").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "maxRecords": 10
}' |
apify call nexgensignal/eu-air-quality-scenario-records --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,nexgensignal/eu-air-quality-scenario-records"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/9QvBR5PbAnv0EdTkU/builds/0ScMIKlNPf5r9ooG4/openapi.json