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.

The Yellow River Delta in China is the most active one for sea–land changes over all deltas worldwide, and its coastline evolution is critical to urban planning and environmental sustainability in coastal areas. Existing studies rarely used yearly temporal resolution, and lack more detailed and quantitative analysis of coastline evolution characteristics. This paper used visual interpretation to extract the coastline of the Yellow River Delta in year interval Landsat images for 45 years from 1976 to 2020, and analyzed the spatiotemporal characteristics of the coastline evolution through statistical methods such as calculating change values and change rate. The main results are as follows: (1) overall, the coastline of the Yellow River Delta presented a spatial pattern involving northern landward retreat and southern seaward expansion. Since 1990, the Yellow River Delta has entered a period of decline. In addition, the length of the artificial coastline increased by about 55 km; (2) in the Qingshuigou region, the land area and the coastline length increased first and then stabilized. The southeastern part of the Qingshuigou was in a state of erosion, while the northeastern part was expanding toward the sea along the north direction; (3) in the Diaokou region, the land area has been decreasing, but the reduction rate has gradually slowed down. The main conclusions are as follows: (1) through the research on the evolution model and mechanism of the coastline of the Yellow River Delta, it was found that human factors and natural factors were the two major driving factors that affect the evolution of the coastline; (2) a river branch appeared in the northern part of the Qingshuigou region in 2014 and became a major branch in 2020, which would affect the development of the coastal region of Chengdao. This study is important for better understanding the evolution pattern of the Yellow River Delta coastline and will help to provide guidance for coastline management and resource exploitation.

China has achieved good results in SO₂ pollution control, but SO₂ pollution still exists in some areas. Analyzing the spatio-temporal distribution of SO₂ is critical for regional SO₂ pollution prevention and control. Compared with existing air pollution studies that paid more attention to PM₂.₅, NO₂ and O₃, and focused on the macro scale, this study took the small-scale Weifang city as the research area, analyzed the temporal and spatial changes in SO₂, discussed the migration trajectory of SO₂ pollution and explored the impact of wind on SO₂ pollution. The results show that the average annual concentration of SO₂ in Weifang has exhibited a downward trend in the past 13 years, showing the basic characteristics of “highest in winter, lowest in summer and slightly higher in spring and autumn”, “highest on Sunday, lowest on Thursday and gradually decreasing from Monday to Thursday” and “highest at 9 a.m., lowest at 4 p.m. and gradually increasing from midnight to 9 a.m.”. SO₂ concentration showed obvious spatial heterogeneity: higher in the north and lower in the south. In addition, Shouguang, Changyi and Gaomi were seriously polluted. The SO₂ pollution shifted from south to northeast. The clean wind direction (southeast wind and northeast wind) of Weifang city accounted for about 41%, and the pollution wind direction (northwest wind and west wind) accounted for about 7%. Drawing from the multi-scale analysis, vegetation, precipitation, temperature, transport situation and human activity were the most relevant factors. Limited to data collection, more quantitative research is needed to gain insight into the influence mechanism in the future.

The author would like to make the following corrections about the published paper