Scholarlink

<p>Precise characterization of microplastic morphology and size distribution is essential for understanding particle mobility through porous media, since particle size and morphology strongly influence filtration, retention, and transport behavior. Image analysis has been investigated as a cost-effective and efficient way to quantify and measure polydisperse environmental microplastics, but it has yet to be proven effective for use in hydrological studies. In this study, three common image-analysis workflows were evaluated to quantify concentrations and size distributions of Nile Red-stained microplastics in laboratory transport studies. Filter images were captured using (1) a digital single-lens reflex camera; or (2) a stereomicroscope, both as random frames or as stitched full-filter images. Automated particle counts were compared to manual counts from various dilutions, based on panoramic full-filter images. Then, a controlled sand column experiment was conducted as proof-of-concept to evaluate method performance under advective transport conditions. All imaging approaches exhibited concentration-dependent sensitivity, with high particle densities causing quantification and sizing errors due to particle overlap (coincidence) and fluorescence halo effects. Stitched full-filter stereomicroscopic images were deemed too time-consuming for use in high-throughput hydrological studies, but DSLR photography and random frame-stereomicroscopy identified comparable breakthrough timing and mobility trends. Differences in particle recovery and relative concentration magnitudes were driven by method-specific detection limits and image processing biases. Both methods confirmed size-dependent mobility, with particles &lt; 50&#xa0;μm exhibiting increased transport potential. These findings confirm the potential for use of image processing in hydrological studies, but they demonstrate that imaging method selection directly constrains interpretation of microplastic transport metrics, supporting a size-targeted, method-aware approach for porous media transport studies.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Opportunities and limitations of image analysis-based microplastic quantification and characterization in a hydrological context

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月8日

查看全文
  • Ofir Meidan,
  • Iris Zohar,
  • Shai Arnon,
  • Emily Lena Tran

摘要

Precise characterization of microplastic morphology and size distribution is essential for understanding particle mobility through porous media, since particle size and morphology strongly influence filtration, retention, and transport behavior. Image analysis has been investigated as a cost-effective and efficient way to quantify and measure polydisperse environmental microplastics, but it has yet to be proven effective for use in hydrological studies. In this study, three common image-analysis workflows were evaluated to quantify concentrations and size distributions of Nile Red-stained microplastics in laboratory transport studies. Filter images were captured using (1) a digital single-lens reflex camera; or (2) a stereomicroscope, both as random frames or as stitched full-filter images. Automated particle counts were compared to manual counts from various dilutions, based on panoramic full-filter images. Then, a controlled sand column experiment was conducted as proof-of-concept to evaluate method performance under advective transport conditions. All imaging approaches exhibited concentration-dependent sensitivity, with high particle densities causing quantification and sizing errors due to particle overlap (coincidence) and fluorescence halo effects. Stitched full-filter stereomicroscopic images were deemed too time-consuming for use in high-throughput hydrological studies, but DSLR photography and random frame-stereomicroscopy identified comparable breakthrough timing and mobility trends. Differences in particle recovery and relative concentration magnitudes were driven by method-specific detection limits and image processing biases. Both methods confirmed size-dependent mobility, with particles < 50 μm exhibiting increased transport potential. These findings confirm the potential for use of image processing in hydrological studies, but they demonstrate that imaging method selection directly constrains interpretation of microplastic transport metrics, supporting a size-targeted, method-aware approach for porous media transport studies.