Fine particles (PM 2.5 ) and coarse particles (PM 2.5-10 ) are generally produced by different sources, so the PM 2.5 /PM 10 ratio reveals characteristics of particle pollution. The ratio can be used to characterize the underlying atmospheric processes and evaluate historical PM 2.5 pollution in absence of direct measurements. However, application of the ratio needs its varying pattern because PM concentrations change significantly at time and space. Hourly PM 2.5 and PM 10 observations at nine monitoring sites in urban area (Urban-sites) and one remote Background-site in Wuhan in 2013-2015 were collected to investigate both long-term, short-term temporal variation and spatial distribution, spatial disparity of the ratio at a city scale. The results show that annual average PM 2.5 /PM 10 ratio is 0.62 at Urban-sites and 0.68 at Background-site with apparent seasonal, monthly and daily variations. The ratio reaches the maximum in winter because of stable atmospheric conditions. There are apparent night-day differences of daily variation of the ratio, which increases at night in all seasons in consequence of temperature inversion and declines in the daytime with a moderate rise in the afternoon. We find obvious spatial gradients of the ratio that gradually increases from urban core to urban fringe and to suburban. This study provides further insights to the spatio-temporal variability of PM 2.5 /PM 10 ratio. The evidence indicates that the variability of PM 2.5 /PM 10 should be noticed in its applications.

Abstract:The spatial structures of cities have changed dramatically with rapid socio-economic development in ways that are not well understood. To support urban structural analysis and rational planning, we propose a framework to identify urban functional regions and quantitatively explore the intensity of the interactions between them, thus increasing the understanding of urban structures. A method for the identification of functional regions via spatial semantics is proposed, which involves two steps: (1) the study area is classified into three types of functional regions using taxi origin/destination (O/D) flows; and (2) the spatial semantics for the three types of functional regions are demonstrated based on point-of-interest (POI) categories. To validate the existence of urban functional regions, we explored the intensity of interactions quantitatively between them. A case study using POI data and taxi trajectory data from Beijing validates the proposed framework. The results show that the proposed framework can be used to identify urban functional regions and promotes an enhanced understanding of urban structures.

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