# Food Carbon Footprint & Environmental Impact (Agribalyse) (`vigilant_jasmine/french-food-carbon-agribalyse`) Actor Look up the carbon footprint and 16 environmental impacts of 2455 food products from ADEME Agribalyse official LCA data. Search by name or food group. Free. - **URL**: https://apify.com/vigilant\_jasmine/french-food-carbon-agribalyse.md - **Developed by:** [DEV DEV](https://apify.com/vigilant_jasmine) (community) - **Categories:** Business, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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. Actors are written with capital "A". ## 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. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Food Carbon Footprint & Environmental Impact (Agribalyse) Look up the **carbon footprint and full environmental impact of food products** using **ADEME Agribalyse** — the French government's official life-cycle assessment (LCA) database ("empreinte carbone alimentaire", "impact environnemental", "bilan carbone aliment"). 2 455 food products, each scored across the **16 EU Environmental Footprint impact categories**, from farm to plate. This is the reference dataset behind most French food eco-scoring (Eco-score / Planet-score style labelling). **This actor is free.** You only pay your own Apify platform usage. ### Input | Field | Type | Description | |---|---|---| | `queries` | array | Food names in French: `pomme`, `boeuf`, `lait`… Empty = browse the whole database. | | `foodGroup` | string | Restrict to one group, e.g. `viandes, oeufs, poissons`. | | `sortBy` | string | Relevance, or carbon footprint / EF score ascending or descending. | | `maxResultsPerQuery` | integer | Cap per search term. Default `50`. | ### Output One item per food product, each with a `status` field (`found` / `not_found` / `error`). All impacts are expressed **per kg of product**. ```json { "status": "found", "productNameFr": "Abondance", "productNameEn": "Abondance cheese, from cow's milk", "foodGroup": "lait et produits laitiers", "foodSubGroup": "fromages", "codeAgb": "12112", "codeCiqual": "12112", "efSingleScoreMPt": 0.53606708, "dataQualityRating": 5, "preparation": "Pas de préparation", "packagingMaterial": "PACK AGB", "airFreighted": false, "unit": "per kg of product", "climateChangeKgCo2e": 4.9830797, "waterDepletionM3Deprived": 0.66368498, "landUsePt": 178.4429, "energyResourceDepletionMj": 32.429708, "acidificationMolHe": 0.074981339 } ```` Also included: ozone depletion, ionising radiation, photochemical ozone, fine particles, human toxicity (cancer / non-cancer), eutrophication (freshwater / marine / terrestrial), freshwater ecotoxicity and mineral resource depletion. ### Use cases - **Food eco-scoring** — power an Eco-score-style label or a carbon rating in a food app. - **Recipe & menu carbon accounting** — sum the footprint of ingredients for restaurants or caterers. - **CSR & Scope 3 reporting** — quantify the food-related emissions of a canteen or product range. - **Research & comparison** — rank foods by impact (the classic beef-vs-lentils comparison, with official numbers). ### Limitations & fair use - Source: [ADEME Agribalyse](https://data.ademe.fr/datasets/agribalyse-synthese) under the **Licence Ouverte / Etalab 2.0** (open licence, free to reuse with attribution). - Search is **French-language** and matches the product name field. - `dataQualityRating` (DQR) is Agribalyse's own data-quality index — **lower is better** (1 = excellent, 5 = weak). Check it before publishing figures. - Values are averages for a representative product, not a specific brand or supplier. - The actor retries with backoff and paces requests to stay polite to the source. ### More actors by this developer Reliable data tools built on official French & EU open data APIs — company data, compliance checks, geo and environment: **[apify.com/vigilant\_jasmine](https://apify.com/vigilant_jasmine)** # Actor input Schema ## `queries` (type: `array`): Food names to look up, in French (e.g. "pomme", "boeuf", "lait"). Leave empty to browse the whole database. ## `foodGroup` (type: `string`): Restrict to one food group, e.g. "fruits, légumes, légumineuses et oléagineux", "viandes, oeufs, poissons", "lait et produits laitiers". ## `sortBy` (type: `string`): Sort results by environmental impact. ## `maxResultsPerQuery` (type: `integer`): Maximum number of food products returned per search term. ## Actor input object example ```json { "queries": [ "pomme" ], "foodGroup": "", "sortBy": "", "maxResultsPerQuery": 50 } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "queries": [ "pomme" ] }; // Run the Actor and wait for it to finish const run = await client.actor("vigilant_jasmine/french-food-carbon-agribalyse").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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "queries": ["pomme"] } # Run the Actor and wait for it to finish run = client.actor("vigilant_jasmine/french-food-carbon-agribalyse").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "queries": [ "pomme" ] }' | apify call vigilant_jasmine/french-food-carbon-agribalyse --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=vigilant_jasmine/french-food-carbon-agribalyse", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Food Carbon Footprint & Environmental Impact (Agribalyse)", "description": "Look up the carbon footprint and 16 environmental impacts of 2455 food products from ADEME Agribalyse official LCA data. Search by name or food group. Free.", "version": "0.0", "x-build-id": "0Vlfu1v51Olj11EFo" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/vigilant_jasmine~french-food-carbon-agribalyse/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-vigilant_jasmine-french-food-carbon-agribalyse", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/vigilant_jasmine~french-food-carbon-agribalyse/runs": { "post": { "operationId": "runs-sync-vigilant_jasmine-french-food-carbon-agribalyse", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/vigilant_jasmine~french-food-carbon-agribalyse/run-sync": { "post": { "operationId": "run-sync-vigilant_jasmine-french-food-carbon-agribalyse", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "queries": { "title": "Food search terms", "type": "array", "description": "Food names to look up, in French (e.g. \"pomme\", \"boeuf\", \"lait\"). Leave empty to browse the whole database.", "items": { "type": "string" } }, "foodGroup": { "title": "Food group filter", "type": "string", "description": "Restrict to one food group, e.g. \"fruits, légumes, légumineuses et oléagineux\", \"viandes, oeufs, poissons\", \"lait et produits laitiers\".", "default": "" }, "sortBy": { "title": "Sort order", "enum": [ "", "-Changement_climatique", "Changement_climatique", "-Score_unique_EF", "Score_unique_EF" ], "type": "string", "description": "Sort results by environmental impact.", "default": "" }, "maxResultsPerQuery": { "title": "Max results per query", "minimum": 1, "type": "integer", "description": "Maximum number of food products returned per search term.", "default": 50 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```