chemicalparks.eu — European Chemical Parks & Clusters Database

It is the site-selection map of European chemical manufacturing: 76 chemical parks and clusters across roughly 20 European countries, kept as a structured, filterable directory by the European Chemical Site Promotion Platform (ECSPP), whose stated mission is promoting new investment in Europe's integrated chemical clusters.

Every entry carries five published columns — park name, total area in hectares, free hectares available for new investment, city and country — and most entries continue into a full site profile. Germany anchors the list with 31 parks, followed by France (8), the Netherlands (6), Belgium and Poland (4 each) and Spain and the United Kingdom (3 each), with Austria, Switzerland, Portugal, Finland, Hungary, Slovakia, Sweden, Norway, Ireland, Italy, Serbia, Iceland and Estonia completing the spread. Scale runs from single-site clusters to verbund giants: ChemCoast Park Brunsbüttel lists 2,000 hectares and BASF SE Ludwigshafen 1,000 — that profile describing around 200 production plants joined by over 2,850 km of pipelines and 8.5 million metric tons of annual output.

Get a sample of this dataset filtered to the countries and regions you are screening before you commit.

Five rows straight from the main table, one row per park:

| PARK                        | AREA HA | FREE HA | CITY         | COUNTRY  |
| --------------------------- | ------- | ------- | ------------ | -------- |
| Agro-Chemie Park Piesteritz |     220 |      30 | Piesteritz   | Germany  |
| Baltic Chemical Park        |     700 |     300 | Kohtla-Järve | Estonia  |
| BASF SE, Ludwigshafen       |    1000 |      50 | Ludwigshafen | Germany  |
| ChemCoast Park Brunsbüttel  |    2000 |     250 | Brunsbüttel  | Germany  |
| Amoniaco - Estarreja, PT    |         |         | Estarreja    | Portugal |

Read the grammar, because it holds across all 76 rows: one park per row, location always resolved to a city and country pair, and hectare figures carried as numbers where the platform publishes them and left genuinely blank where it does not — the Estarreja row ships empty cells, not zeros, so averages and sums behave correctly only if you preserve that distinction. Roughly two-thirds of entries carry an area figure; the blanks cluster in smaller southern and eastern sites. Every value above arrives mapped and typed in a Datadory delivery, with the profile-level fields below folded alongside on request.

Five fields define the standard record, and each does distinct work: the park name doubles as the join key onto site profiles, the area and free-hectare pair separates total footprint from expandable capacity — the difference between the two is the number site selectors actually rank on — and the city/country pair resolves geography down to a mappable point. The field dictionary below types every column and illustrates it with a real value from the set, so joining onto your own facility, logistics or sales-territory tables needs no archaeology.

Four further field groups live on the site profiles rather than the main table: transport-infrastructure flags, the land-status attribute block, named operator contacts and the descriptive profile text. They arrive as additional fields, listed in the second table.

The main table is deliberately shallow; the depth sits on individual site profiles, and we fold those into deliveries as requested extensions:

1. Infrastructure flags — highway, railway, waterway and sea-harbour availability per site, the filters site selectors apply first and the fields logistics models join on.
2. Land-status attributes — the Total / Free / Greenfield / Brownfield / Utilities block, which tells you whether expansion means building on prepared brownfield or permitting a greenfield.
3. Operator contacts — named settlement and business-development contacts with phone and email per park.
4. Profile text — the platform's own description of each site's scale, integration and output.

Name them when you request the sample; scope locks at that point. Several parks publish no profile page yet, so extension coverage varies by country — confirm the fill rate for your target markets when scoping.

• Geography: Europe-wide — 76 parks across roughly 20 countries with Germany holding 31 of them — and the platform's country filter additionally lists Brazil, the UAE and China as options beyond the European table.
• Temporal: a current snapshot of active sites, maintained by ECSPP rather than issued in dated editions, with no historical archive behind it. Treat it as a who-exists-now register, not a time series.
• Granularity: one record per chemical park or cluster — hectare totals, free land, city, country on every row, with operator contact and infrastructure attributes at profile level. There is no plant, tenant-company or production dimension in the set; firm-level questions need a statistical or emissions complement from the rail below.

API, files, or your warehouse. Daily, weekly, or hourly.

The delivery point matters more than usual here. The platform publishes a designed browsing experience — dropdown filters, checkbox infrastructure selectors, a live counter, a table-versus-map toggle — while teams need flat rows that load beside their own facility, territory and logistics tables without reshaping. Closing that gap happens once on our side: every delivery carries the field dictionary above unchanged across all three channels, with the profile-level extensions attached where you asked for them. Load the full 76-park register once for territory planning, or pull scoped payloads when a screen needs fresh rows.

1. Market researchers mapping Europe's integrated chemical clusters by country and capacity — 31 German parks against 8 French ones is the shape of the continental footprint in one table.
2. Investors and quants screening expansion capacity: the free-hectare column ranks where new chemical production can physically land, park by park.
3. Competitive intel and product teams tracking cluster membership and site scale for customers, prospects and rivals' manufacturing footprints.
4. Sales and growth teams building territory plans around Verbund sites — each park concentrates dozens of resident producers behind one gate.
5. Data scientists geocoding the 76 rows to enrich site-level models with cluster membership, capacity and infrastructure features.
6. Supply-chain and logistics analysts routing feedstocks and products through parks by their highway, rail, waterway and harbour access.

Developers and data-product builders get a compact, stable register that turns into a lookup feature or map layer without a heavy pipeline — see developers builders use cases. Data scientists gain cluster-membership and capacity features for siting and logistics models — see data scientists use cases. Competitive intel and product teams read rival and customer footprints off one table instead of dozens of press releases — see competitive intel product teams use cases. Sales and growth teams prioritise territories by counting parks and free hectares per country — see sales growth teams use cases.

Completeness note — hectare figures populate roughly two-thirds of entries and a handful of names carry no detail page at all, so treat profile-level fields as variable-fill and confirm rates for your target countries. Blank cells are genuine absences, never zeros.

Scope note — this is the physical-site layer for diversified chemicals: parks, hectares, infrastructure, operators. Sector turnover, trade and production volumes live in the statistical complements below; the register tells you where capacity sits, they tell you what it produces.

Where to go next — the rail collects the European macro frame, the national account for the country holding 31 of the 76 parks, EU production context and the US counterpart, each one hop from a question this register opens.