A pyrolysis gas chromatography high resolution mass spectrometry (Py-GC-MS) method for analysis of phthalic acid...

The increasing volume of electronic waste (e-waste) is a significant global environmental and public health concern. Phthalic acid esters (PAEs) are used as plasticisers in insulation coatings of electric materials, and if not effectively separated in preliminary recycling processes and enter pyrometallurgical processes, can lead to unintentional PAE emissions. Understanding these emissions is crucial for assessing potential environmental and health risks, as well as for developing effective recycling and emission control strategies. Most current analytical methods have limitations for estimating airborne PAE emissions during e-waste pyrolysis as they either rely on offline sampling and preparation potentially introducing uncertainties and contamination from ubiquitous environmental PAEs or employ online techniques that have relatively high limits of detection (LOD). In this work, we developed, validated, and applied a new quantitative online single-shot pyrolysis gas chromatography mass spectrometry (Py-GC-MS) method for analysis of PAEs, including di(2-ethylhexyl)adipate (DEHA), di(2-ethylhexyl)phthalate (DEHP), and di-n-octyl phthalate (DOP) in e-waste matrices. The effect of pyrolysis settings, including temperature and sample residence time, on PAE chromatographic responses were assessed. The chromatographic responses of DEHA, DEHP, and DOP demonstrated good linearity (R² > 0.990) over 0.1 ng to 20 ng, with LODs ranging from 0.56 to 0.68 ng. The method showed acceptable accuracy and precision (% coefficient of variation, CV and relative error, RE < 20%). Matrix effects showed a strong impact on the analysis, requiring the use of an increased split sample ratio, and correction strategies to minimise bias. The validated method was successfully applied to three representative electronic matrices: a thermocouple cable, an electrolytic capacitor, and a film capacitor, where DEHP and DOP emissions ranged from 3 to 30 mg kg^-1. This study presents the development and application of a quantitative analytical method, for the first time, to estimate DEHA, DEHP, and DOP in representative e-waste matrices using a single-shot Py-GC-MS.