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A Comparison of PM10 Exposure Characteristics of Swine Farmers by Body Parts using Direct-reading Instrument

직독식 기기를 이용한 양돈작업자의 신체부위별 PM10 노출 특성 비교 연구

  • Received : 2019.04.26
  • Accepted : 2019.06.24
  • Published : 2019.06.30

Abstract

Objectives: The purpose of this study was to evaluate the personal exposure to $PM_{10}$ by body parts for the development of dust monitoring wearable device for swine farmers. Methods: Tasks were classified by using motion pictures taken by action cameras attached to swine farmers. Concentrations of $PM_{10}$ were measured by attaching direct-reading instruments at the head, neck and waist of worker. Differences of $PM_{10}$ exposure between body parts were analyzed with linear regression. Results: We identified three tasks(vaccination, moving pigs, and manure treatment). $PM_{10}$ concentration during vaccination was the highest among the tasks, and the body part showing the highest concentration of $PM_{10}$ was the waist regardless of task. In all tasks, the closer distance between the body parts, the higher were the R-squared values(vaccination 0.4221, moving pigs 0.6990, and manure treatment 0.2164). Conclusions: We presumed that $PM_{10}$ concentrations were affected by the parts of the body in which they were measured. In order to develop swine farmer's wearable device for monitoring dust concentration in air, the determination of the positions of monitoring sensor to ensure accurate measurement is essential. Considering the results of this study, wearable sensor should be positioned at the waist.

Keywords

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Figure 1. Measurement of PM10 using direct-reading instrument

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Figure 2. Variation of PM10 concentration on time based among the tasks

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Figure 3. Comparison of R2 between body parts(Head-Neck, Neck-Waist, Head-Waist) by tasks

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Figure 4. Vaccination in pig room

Table 1. Range and resolution of direct reading instrument for Sidepak

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Table 2. Classification of task used an action camera in pig house and measured time

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Table 3. Concentration of PM10 in body parts of each task

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