Selection of particle characteristics to distinguish amongst potential sources of particulate matter in poultry and pigs.
The knowledge on the contribution of individual sources to particulate matter (PM) in different size fractions is essential to improve PM reduction from livestock houses. We investigated which input data (particle chemical, morphological or combined characteristics) were best to distinguish amongst specific potential sources of PM. We used a cross-validation procedure with classification rules based on decision trees and analyzed misclassification errors. The PM from two livestock species (poultry and pigs), and in two different fractions (fine and coarse) was studied. A total of 618 particles were analyzed from poultry houses for fine, and 805 for coarse PM. A total of 317 particles were analyzed from pig houses for fine, and 337 for coarse PM. Results showed the selection of the best input data varies depending on the sources, which depend on livestock species.
| Main Authors: | , , , |
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| Format: | Article in monograph or in proceedings biblioteca |
| Language: | English |
| Subjects: | Atmospheric pollution, Dust, Image analysis, Livestock housing, SEM-EDX, |
| Online Access: | https://research.wur.nl/en/publications/selection-of-particle-characteristics-to-distinguish-amongst-pote |
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