Understanding plasticiser leaching from polystyrene microplastics

SCIENCE OF THE TOTAL ENVIRONMENT(2023)

引用 19|浏览13
暂无评分
摘要
Plastic pollution in our oceans is of growing concern particularly due to the presence of toxic additives, such as plasticisers. Therefore, this work aims to develop a comprehensive understanding of the leaching properties of plasticisers from microplastics. This work investigates the leaching of phthalate acid ester (dioctyl terephthalate (DEHT) and diethylhexyl phthalate (DEHP)) and diphenol (bisphenol A (BPA) and bisphenol S (BPS)) plasticisers from polystyrene (PS) microplastics (mean diameter = 136 mu m to 1.4 mm) under controlled aqueous conditions (tem-perature, agitation, pH and salinity). The leaching behaviours of plasticised polymers were quantified using gel perme-ation chromatography, high performance liquid chromatography and thermal gravimetric analysis, and the particle's plasticisation characterised using differential scanning calorimetry. Leaching rates of phthalate acid ester and diphenol plasticisers were modelled using a diffusion and boundary layer model, whereby these behaviours varied depending on their plasticisation efficiency of PS, the size of the microplastic particle and the surrounding abiotic conditions. Leaching behaviours of DEHT and DEHP were strongly influenced by the microplastic-surface water boundary layer properties, thus wave action (i.e., water agitation) increased the leaching rate of these plasticiser up to 66 % over 21-days, whereas BPA and BPS plasticisers displayed temperature-and size-dependent leaching and were limited by molecular diffusion throughout the bulk polymer (i.e., the microplastic). This information will improve predictions of plasticiser concentration (both that remain in the plastic and released into the surrounding water) at specific time points during the lifetime of a plastic, ultimately ensuring greater accuracy in the assessment of toxicity responses and environmental water quality.
更多
查看译文
关键词
Microplastics,Plasticiser leaching,Diffusion model,Boundary layer
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要