Fine-scale population spatialization data of China in 2018 based on real location-based big data.

Accurate location-based big data has a high resolution and a direct interaction with human activities, allowing for fine-scale population spatial data to be realized. We take the average of Tencent user location big data as a measure of ambient population. The county-level statistical population data in 2018 was used as the assigned input data.

Control Models and Spatiotemporal Characteristics of Air Pollution in the Rapidly Developing Urban Agglomerations.

This paper systematically summarizes the hierarchical cross-regional multi-directional linkage in terms of air pollution control models implemented in the Beijing-Tianjin-Hebei urban agglomeration, including the hierarchical linkage structure of national-urban agglomeration-city, the cross-regional linkage governance of multiple provinces and municipalities, the multi-directional linkage mechanism mainly involving industry access, energy structure, green transportation, cross-regional assistance, monitoring and warning, consultation, and accountability. The concentration data of six air pollutants were used to analyze spatiotemporal characteristics. The concentrations of SO, NO, PM, PM, CO decreased, and the concentration of O increased from 2014 to 2017; the air pollution control has achieved good effect.

The pattern and mechanism of air pollution in developed coastal areas of China: From the perspective of urban agglomeration.

The green development of coastal urban agglomerations, which are strategic core areas of national economic growth in China, has become a major focus of both academics and government agencies. In this paper, China's coastal urban agglomeration is taken as the research area, aiming at the serious air pollution problem of coastal urban agglomeration, geographic information system (ArcGIS10.2) spatial analysis and the spatial Dubin model were applied to National Aeronautics and Space Administration atmospheric remote sensing image inversion fine particulate matter (PM2.

Spatial-temporal pattern evolution and driving factors of China's energy efficiency under low-carbon economy.

Improving energy efficiency and building a low-carbon economy are the important ways to resolve the current contradiction between economic growth and the environment in China. In this paper, we use the super-efficiency Slack-Based Measure model (super-efficiency SBM model) to measure the energy efficiency of 30 provinces in China, and then conduct Empirical Orthogonal Function (EOF) to analyze its spatial-temporal evolution. Moreover, we use the Geographically and Temporally Weighted Regression (GTWR) to analyze the spatial-temporal heterogeneity of its driving factors.

Synergy effects and it's influencing factors of China's high technological innovation and regional economy.

The Chinese government adheres to the innovation driven strategy and emphasizes that technological innovation is the strategic support for improving social productivity and comprehensive national strength. This paper discusses the mechanism of technological innovation and regional economic co-evolution, and constructs an index system to assess them based on the principles of synergy and systematics. The authors use a dynamic coupling model to study the law of the cooperative evolution of composite systems and geo-detector methods to reveal the main factors controlling the degree of coordination among them.

Spatio-temporal evolution of ozone pollution and its influencing factors in the Beijing-Tianjin-Hebei Urban Agglomeration.

Ozone has become a major atmospheric pollutant in China as the pattern of urban energy usage has changed and the number of motor vehicles has grown rapidly. The Beijing-Tianjin-Hebei Urban Agglomeration, also known as the Jing-Jin-Ji Urban Agglomeration (hereafter, JJJUA), with a precarious balance between protecting the ecological environment and sustaining economic development, is challenged by high levels of ozone pollution. Based on ozone observation data from 13 cities in the JJJUA from 2014 to 2017, the spatio-temporal trends in the evolution of ozone pollution and its associated influencing factors were analyzed using Moran's I Index, hot-spot analysis, and Geodetector using ArcGIS and SPSS software.

Spatiotemporal differentiation and the factors influencing urbanization and ecological environment synergistic effects within the Beijing-Tianjin-Hebei urban agglomeration.

Numerous environmental problems have been seen due to the "high energy consumption, high pollution, high emissions" economic model in the Beijing-Tianjin-Hebei urban agglomeration (BTHUA). The coupling coordination degree model is applied to provide a coordination of urbanization and ecological environment composite system (CUECS) value while a geographic detector is applied to explore the dominant factors controlling it. This study reached the following conclusions.

[Control Models and Effect Evaluation of Air Pollution in Jing-Jin-Ji Urban Agglomeration].

Controlling air pollution in the Jing-jin-ji urban agglomeration (JJJUA), the most seriously polluted area in China, is related to the integrated development strategy for the region. Based on the national and regional implementation of air pollution control measures in recent years, the hierarchical cross-regional multi-directional linkage (HCML) air pollution prevention and control model was applied in this study. The effect of air pollution control was evaluated by monitoring the pollutants, SO, NO, PM, PM, O, and CO, at 112 monitoring sites in 13 cities in 2014-2015.