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A factor analysis of landscape metrics of particles deposited on leaf surface

Lin, Lin, Chen, Guojian, Yan, Jingli, Tang, Rongli, Yuan, Xiu, Yin, Zhe, Zhang, Rui
Environmental science and pollution research international 2018 v.25 no.28 pp. 28391-28402
Ailanthus, air quality, factor analysis, green infrastructure, landscapes, leaf characteristics, leaves, monitoring, particulates, principal component analysis, China
Particulate matter in the airborne environment is one of the top environmental concerns, as well as reasons of deaths and diverse diseases. Urban green infrastructure can improve the air quality by mitigating particulate matters from airborne environment and provide high spatial monitoring of particles by means of leaf particles as indicators. Three common species in Beijing (ailanthus, ash, and willow) were chosen to represent three different leaf characteristics. Then, we analyzed the correlation relationship of the particle metrics at landscape, class, and patch levels and implemented the principal components analysis and factor analysis. Firstly, at landscape level, metrics are mostly correlated with each other and the correlation relationship of metrics of ailanthus and willow were stronger than that of ash, which has coarse-texture leaves without hair. At class level, most of the metrics were correlated and the correlation relationship of metrics of ailanthus, whose leaves have microgrooves without hair, was weaker than that of ash and willow. At patch level, judging from proximity, the distance between particles from the same range was smaller for particles with complicated shape. Secondly, particles from four ranges were analyzed separately. The shape complexity of particles decreased and increased as the area increased respectively for PM1 (diameter ≤ 1 μm) and large particles (diameter ≥ 10 μm). Two principle components were identified for landscape and class levels respectively. These results will be useful for the in-depth understanding of the particles deposited on the leaf surface.