Naukovij Vìsnik Nacìonalʹnoï Akademìï Statistiki, Oblìku ta Auditu (Nov 2021)
An Analysis of the International Law on Waste Statistics
Abstract
The article contains an analytical review of the regulatory framework in the waste statistics. By summing up documentary evidences (conventions on protection of the population health and environment, objectives and indicators of Sustainable Development Goals, related with waste), it is demonstrated that waste statistics plays important role in identifying waste-specific problems, priority setting in waste management, formulating and implementing policy goals in waste management. It is shown that the waste statistics is collected by various international entities, and reports on waste generated in the process of economic activities are made up using two main classifications: International Standard Industrial Classification of All Economic Activities (ISIC), and Statistical Classification of Economic Activities in the European Community (NACE). The EU practices in the waste statistics are highlighted. The EU approach to waste treatment is based on “waste hierarchy”. In practice, a major part of EU countries collects the data on waste types by the List of Waste. After that, the conformity between the types of waste and EWC-Stat is set using the translation table given in Annex III to the Waste Statistics Regulation. Only several countries collect data by the reliance on EWC-Stat. Problems faced by the waste statistics are discussed (inadequate comparability of waste statistics due to different methods and definitions used in the data production; incomplete coverage of waste-specific issues by the official waste statistics), sources of these problems are determined. The analysis demonstrates that the waste statistics is a rather new field in EU, which evidence is the ongoing change in the EU regulatory framework. The countries producing waste data with reference to it or implementing it should do it by taking account for the most recent change. The need for harmonization of national methodologies in the waste statistics is highlighted.
