Geographical Detector Model for Influencing Factors of Industrial Sector Carbon Dioxide Emissions in Inner Mongolia, China

Abstract:The Beijing-Tianjin-Hebei Region Integration Plan is one of the most important national strategies in China promoting regional economic development. The environmental problems in this region, however, especially air pollution and contaminated groundwater, have enormous influence on the people's health while also causing economic loss. Therefore, this study aims to analyze the pattern of its environmental and economic development. Panel data in the period 2004-2014 are used to establish an advanced model of the Environmental Kuznets Curve. The results indicate that the economic growth and environmental pollution of Beijing-Tianjin-Hebei region do not completely meet the Environment Kuznets Curve assumptions. The discharge volume of industrial wastewater and economic growth reflect a wave-type relation. The sulfur dioxide discharge volume and economic growth reflect a U-shaped relation; the generated volume of industrial solid wastes and economic growth reflect a reversed N-shaped relation, which is in accordance with the Environmental Kuznets Curve characteristics at the second inflection point. The variables added value of the secondary industry, population size and raw coal consumption volume have a significant positive influence on the discharge of various environmental pollutants in Beijing-Tianjin-Hebei region. The analysis provides policy recommendations for the government to develop regional economic and environmental protection policies.

Section: Discussionmentioning

confidence: 93%

Economic Transformation in the Beijing-Tianjin-Hebei Region: Is It Undergoing the Environmental Kuznets Curve?

Xiong

Jong

et al. 2017

“…The symbol "∩" denotes the interaction between A and B. We used ArcGIS software to overlay layers A and B and to obtain a new layer C. We can determine the influence of an interaction by comparing the P values of A, B, and C [48,49].…”

Section: Geographical Detector Modelmentioning

confidence: 99%

Identifying the Impacts of Social, Economic, and Environmental Factors on Population Aging in the Yangtze River Delta Using the Geographical Detector Technique

Zhao

Zhang

et al. 2018

Under the background of social transformation and space reconstruction, population aging in China is becoming more and more diverse and complex. "Aging before getting rich", a notion in population and economic development, has been a serious threat to sustainable development in China. On the basis of town-and street block-scale data from the Fifth and Sixth National Census in the Yangtze River Delta, we studied spatial distribution characteristics of population aging using global Moran's I and hotspot analysis, and applied the geographical detector technique to explain the spatial heterogeneity of population aging. Several conclusions were drawn. (1) The promotion and replacement of aging coexist. Cluster of aging degree exhibits an increasing trend. Population aging is more severe in suburban areas than urban areas.(2) Migration is the main factor affecting the spatial heterogeneity of population aging. Per capital GDP and road network density are the second most influential factors. By contrast, the relief degree of land surface and the air quality index minimally influence population aging. The mechanisms of aging in various regions are affected by varying development levels. (3) The interaction among social, economic, and environmental factors enhances their effects and, thus, interacting factors have a greater influence on population aging than any single factor. The findings of this study have significant implications for local inhabitants and policy makers to address the population aging challenge in achieving sustainability of society, economy, and environment. will become the highest-aged country in the world [3]. Under the background of social transformation and space reconstruction, the aging of China is becoming more and more complex. "Aging before getting rich" and "demographic dividend disappeared", the notion in population and economic development, has been a serious threat to social sustainable development. On the other hand, an aging acceleration significantly affects the urban structure, urban formation, and land use of a city, all of which bring about new challenges for urban planning, especially with regard to the allocation of adequate facilities for an increasing number of elderly people [4]. Under such a circumstance, the aging issue has become a common and fundamental subject for local inhabitants, scholars, and governments all over the world. In the Yangtze River Delta in 2010, as an important economically developed area, the proportion of individuals who were over 60 years was 10.45%, which was significantly higher than the national average. Meanwhile, the Yangtze River Delta is a core area for rapid urbanization. In 2010, the region's gross domestic product (GDP) increased to 7.07 trillion RMB, accounting for 16.42% of the national total. It is not only an economically developed region but also an area where interaction occurs between nature and humans, which has resulted in various environmental and ecological problems and brought great challenges to regional sustainable development. R...

“…GeoDetector is a spatial statistical method for detecting and analyzing spatial variation [40] and has been gradually applied to study regional economies, regional planning, land use, ecological environments, and so forth. [41][42][43][44]. Three detectors (factor, risk, and interaction detectors) were used in this study, excluding the ecological detector.…”

Section: Modeling Using Geodetectormentioning

confidence: 99%

Quantitative Analysis of the Determinants Influencing Urban Expansion: A Case Study in Beijing, China

Zheng

Zhang

2018

A quantitative analysis of spatial influencing factors on urban sprawl can offer better support for urban planning and management. There are many concerns regarding the influence of each factor. However, a quantitative analysis to detect the interactions between factors is limited because of the complexity of the urban systems, especially the role of planning. Additionally, spatial heterogeneity is often overlooked. This study aims to improve and strengthen the knowledge in this field through a spatial statistical method known as GeoDetector. A new spatial quantification of urban expansion was presented in this study and the spatio-temporal characteristics and mechanism of urban growth in Beijing from 2010 to 2015 were also analyzed. The results show that urban expansion presents spatial heterogeneity with different grid cells, and the optimal scale was 4500 m. At this scale, urban expansion in Beijing linearly expands along the traffic trunk. In addition, urban expansion in Beijing is jointly influenced by socioeconomic, geographical, and policy factors. Population density has had the greatest influence on urban expansion from 2010 to 2015, and policy factors rank first. The impact of economic factors on urban growth is gradually weakening. It is important for urban geographical research to further plans and guide urban development.