Particulate matter represents a serious hazard to human health, and air quality models contribute to the understanding of its dispersion. This study describes particulate matter with a <= 10 mu m diameter (PM10) dynamics in an urban-industrial area, through the comparison of three datasets: modeled (TAPM-The Air Pollution Model), measured concentration (environmental control stations-ECS), and leaf deposition values. Results showed a good agreement between ECS and TAPM data. A steel plant area was used as a PM10 emissions reference source, in relation to the four sampling areas, and a distance/wind-based factor was introduced (Steel Factor, SF). Through SF, the three datasets were compared. The SF was able to describe the PM10 dispersion values for ECS and leaf deposition (r(2) = 0.61-0.94 for ECS; r(2) = 0.45-0.70 for leaf); no relationship was found for TAPM results. Differences between measured and modeled data can be due to discrepancies in one district and explained by a lack of PM10 inventory for the steel plant emissions. The study suggests the use of TAPM as a suitable tool for PM10 modeling at the urban scale. Moreover, tree leaves are a low-cost tool to evaluate the urban environmental quality, by providing information on whether and when data from leaf deposition can be used as a proxy for air pollution concentration. Further studies to include the re-suspension of particles as a PM10 source within emission inventories are suggested.
Particulate Matter in an Urban-Industrial Environment: Comparing Data of Dispersion Modeling with Tree Leaves Deposition
Sgrigna Gregorio;
2022
Abstract
Particulate matter represents a serious hazard to human health, and air quality models contribute to the understanding of its dispersion. This study describes particulate matter with a <= 10 mu m diameter (PM10) dynamics in an urban-industrial area, through the comparison of three datasets: modeled (TAPM-The Air Pollution Model), measured concentration (environmental control stations-ECS), and leaf deposition values. Results showed a good agreement between ECS and TAPM data. A steel plant area was used as a PM10 emissions reference source, in relation to the four sampling areas, and a distance/wind-based factor was introduced (Steel Factor, SF). Through SF, the three datasets were compared. The SF was able to describe the PM10 dispersion values for ECS and leaf deposition (r(2) = 0.61-0.94 for ECS; r(2) = 0.45-0.70 for leaf); no relationship was found for TAPM results. Differences between measured and modeled data can be due to discrepancies in one district and explained by a lack of PM10 inventory for the steel plant emissions. The study suggests the use of TAPM as a suitable tool for PM10 modeling at the urban scale. Moreover, tree leaves are a low-cost tool to evaluate the urban environmental quality, by providing information on whether and when data from leaf deposition can be used as a proxy for air pollution concentration. Further studies to include the re-suspension of particles as a PM10 source within emission inventories are suggested.File | Dimensione | Formato | |
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