# A Cost-Effective Standardized Quantitative Detection Method for Soil Microplastics in Different Substrates

## TL;DR

This paper introduces a standardized, cost-effective method for detecting microplastics in soil, improving data consistency and global pollution monitoring.

## Contribution

A unified, reproducible detection protocol for soil microplastics is developed, optimizing recovery, cost, and applicability.

## Key findings

- The method achieves an average recovery rate of 96.4% across sandy, loam, and clay soils.
- The detection process costs USD 9.77 per sample and takes 68 hours to complete.
- High-density polymers like PVC and PET have limited recovery due to the use of NaCl.

## Abstract

Microplastics (MPs) are emerging pollutants with widespread global distribution, continuously accumulating in soils and posing risks of cross-media pollution. Current soil MP detection methods lack unified standards, suffering from high inter-laboratory variability and cost, which become key bottlenecks limiting data comparability and global microplastics pollution control. Here, we systematically reviewed soil MPs studies (2020–2024) and based on stepwise verification, we established a standardized, reproducible detection method: soil samples were dried at 80 °C for 12 h; density separation was performed in Erlenmeyer flasks with decantation, 10 s glass rod stirring, and 12 h settling, repeated five times; digestion was conducted using a 1:2 volume ratio of H2O2 to supernatant at 80 °C for 8 h; and MPs were quantified via stereo-microscopy combined with ImageJ. It should be noted that the use of NaCl limits the recovery of high-density polymers (e.g., PVC, PET), and the minimum detectable particle size is approximately 127 µm. The method was validated in sandy, loam, and clay soils, achieving an average recovery rate of 96.4%, with a processing time of 68 h and a cost of USD 9.77 per sample. In contrast to previous fragmented, non-standardized protocols, this workflow synergistically optimizes high recovery efficiency, cost-effectiveness, and broad applicability, offering a low-cost, efficient, and widely applicable approach for soil MPs monitoring, supporting data comparability across studies and contributing to global pollution assessment and the United Nations 2030 Sustainable Development Goals.