T/XZBX 0173-2025 Industrial Park Air Characteristic Pollutant Source Attribution Technology Guide for the Perimeter Environment
T/XZBX 0173-2025 Industrial Park Air Characteristic Pollutant Source Attribution Technology Guide for the Perimeter Environment
Basic Information
Scope
Industrial parks are important carriers of regional industrial agglomeration and energy consumption. They feature diverse emission sources, complex process chains, coexistence of unorganized and intermittent emissions, and frequent overlapping and coupling with transportation sources, residential sources, catering sources, and dust sources, resulting in the surrounding environmental air pollution of industrial parks exhibiting characteristics of "complex components, intense spatial-temporal variations, significant boundary effects, and pollution processes easily driven by meteorological factors". Conducting scientific source attribution of environmental air pollutants around industrial parks is a key foundation for conducting fine-grained supervision, identifying key emission units, optimizing governance pathways, evaluating governance effectiveness, and responding to sudden odor or exceeded standard events. Traditional air pollution source attribution has focused on conventional pollutants (such as particulate matter, sulfur dioxide, nitrogen oxides, etc.) and regional-scale transport contributions. However, there are certain limitations in rapidly identifying, quantitatively analyzing the contribution of, and locating the source units of "characteristic pollutants" (such as typical volatile organic compounds, characteristic odor substances, characteristic metal elements, characteristic halogenated hydrocarbons, and sulfur- and nitrogen-containing organic compounds) around industrial parks. At the same time, source attribution work around industrial parks often faces practical problems such as incomplete emission information, inconsistent source lists, insufficient monitoring data dimensions, missing source spectra, limited model applicability, and difficulty in separating multi-source mixtures, which easily leads to unstable conclusions, insufficient interpretability, or difficulties in supporting law enforcement and governance decisions. This document addresses