Air pollution, which accompanies industrial progression and urbanization, has become an urgent issue to address in contemporary society. As a result, our understanding and continued study of the spatial-temporal characteristics of a major pollutant, defined as 2.5-micron or less particulate matter (PM2.5), as well as the development of related approaches to improve the environment, has become vital. This paper studies the characteristics of yearly, quarterly, monthly, daily, and hourly PM2.5 concentrations, and discusses the influencing factors based on the hourly data of nationally controlled and provincially controlled monitoring stations, from 2012 to 2016, in Weifang City. The main conclusion of this study is that the annual PM2.5 concentrations reached a peak in 2013. With efficient aid from the government, this value has decreased annually and has high spatial characteristics in the northwest and low spatial characteristics in the southeast. Second, the seasonal and monthly PM2.5 concentrations form a U-shaped trend, meaning that the concentration is high in the summer and low in the winter. These trends are highly relevant to the factors of plantation, humidity, temperature, and precipitation. Third, within a week, higher PM2.5 concentrations appear on Mondays and Saturdays, whereas the lowest concentration occurs on Wednesdays. It can be inferred that PM2.5 concentrations tend to be highly dependent on human activities and living habits. Lastly, there are hourly discrepancies within the peaks and troughs depending on the month, and the overall daytime PM2.5 concentrations and reductive rates are higher in the daytime than in the nighttime.
Environmentally friendly shared transit systems have become ubiquitous at present. As a result, analyzing the ranges and tracts of human activities and gatherings based on bike share data is scientifically useful. This paper investigates the spatial and temporal travel characteristics of citizens based on real-time-extracted electric bikes (e-bikes) Global Positioning System (GPS) data from May to July in 2018 in the central area of Tengzhou City, Shandong Province, China. The research is conducive for the exploration of citizens’ changes in mobility behaviors, for the analysis of relationships between mobility changes and environmental or other possible factors, and for advancing policy proposals. The main conclusions of the study are as follows. First, in general, citizens’ travelling is featured by rides that are less than 10 min, shorter than 5 km, and with a speed between 5 km/h and 20 km/h. Second, in terms of temporal characteristics, monthly e-bike usage and citizens’ mobility are positively correlated with temperature in May and negatively correlated with temperature in July; an overall negative correlation is also manifested between the e-bike usage (mobility) and air quality index; daily usage reaches a trough on Tuesday and a peak on Friday, indicating the extent of mobility on respective days; e-bike usage and human outdoor behaviors are significantly lowered in rainy weather than in sunny weather; hourly rides reach a peak at 18:00 (more human activities) and a trough at 2:00 (less activities), and average hourly riding speed maximizes at 5:00 and minimizes around 8:00 and 17:00. Third, for spatial characteristics, destinations (D points) during morning rush hour and regions where e-bikes are densely employed are concentrated mainly in mid-north and middle parts of the central area (major human gatherings), and the rides have a diffusing pattern; e-bike origin–destination (O–D) trajectories radiate mostly towards the mid-north and the east during evening rush hour. In addition, 9.4% of the total trips to work areas during morning rush hour represent spillover commuting, indicating that separations between jobs and residential are not severe in the central area of Tengzhou City and commuting is relatively convenient.
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