Harmonizing Chemical Identity Data for Environmental Monitoring A Python Solution for Multilingual Consistency at Brussels Environment Environmental Data Management Tags: Python, chemical data, data validation, multilingual data, environmental monitoring, EQS

Environmental monitoring relies on accurate and consistent chemical identity data. In regulatory contexts such as Environmental Quality Standards (EQS), even small inconsistencies in chemical names or identifiers can lead to misinterpretation, duplicated records, or flawed analyses. During my work with Brussels Environment (Belgium), I developed a Python-based chemical data identification program to address this challenge in a multilingual regulatory environment. The Challenge Brussels Environment operates in three official languages: English, French, and Dutch. Chemical substances may appear under different names, synonyms, or translations across datasets, making data alignment and validation complex. The Solution I designed a Python program that: • Extracts chemical identity data from multiple sources • Validates chemical names and identifiers across languages • Harmonizes identity parameters into a unified structure • Flags inconsistencies and ambiguities automatically The program ensures that every chemical substance used in environmental assessments is unambiguously identified, regardless of language or data source. Impact This solution: • Improved data quality and reliability • Reduced duplication and manual correction • Enhanced collaboration between multilingual teams • Provided a clean foundation for downstream EQS calculations Accurate identification is the first critical step in any environmental data pipeline — and this project ensured that step was scientifically robust.