Analysis and Study on Spatial Gravity Center of PM_(2.5) and Population Scale

With the rapid development of urbanization construction in China,population and industries are rapidly gathering in cities,bringing about economic development and also causing a large number of environmental problems,among which PM_(2.5) is the most concerned.In this paper,a spatial gravity center model was used to systematically analyze the spatiotemporal distribution characteristics of PM_(2.5) and population scale in China from 1999 to 2016.Conclusions were as below:(1)there were significant regional differences in PM_(2.5) pollution from 1999 to 2016,characterized by a spatial distribution of"high in the north and low in the south,and high in the inland and low in the coastal areas".(2)Nationwide,there was a significant spatial mismatch between the gravity center of PM_(2.5) pollution and the gravity center of population scale,with the two centers showing a trend of reverse dislocation development.

Spatial Mismatch or Not?Evidence from Public Janitors in Xi’an,China

Research on the spatial mismatch experienced by low-income minority residents is US-centric.However,spatial mismatch is not necessarily an appropriate term when considering the situation of low-wage workers in cities of northwestern China where there is higher proximity between jobs and housing and lower levels of residential segregation.This paper empirically examines the jobs-housing spatial relationship for one of the most typical low-wage groups,namely,public janitors,in Xi’an,China.Also,the causes of the jobs-housing spatial relationship are discussed in detail.Individual-level data based on in-depth interviews and questionnaires,as well as the GIS network analysis method,are used to provide baseline analyses of the jobs-housing spatial relationship.Results indicate that there is no jobs-housing spatial mismatch for public janitors in Xi’an.This can be implied from the short commuting distance and time.A basic cause is that most public janitors rent low-cost accommodation in villages-in-the-city,and in old residential quarters,near to their places of work.Other causes lie in off-peak commuting and high sensitivity to commuting distance due to the greater extent of nonmotorized commuting modes.The conclusions,based on a large number of social surveys,are an illuminating analysis of the spatial mismatch issue among low-wage workers in Chinese cities.

Spatiotemporal mismatch of land use functions and land use efficiencies and their influencing factors:A case study in the Middle Reaches of the Yangtze River,China

Identification of the spatial mismatch between land use functions(LUFs)and land use efficiencies(LUEs)is essential to regional land use policies.However,previous studies about LUF-LUE mismatch and its driving factors have been insufficient.In this study,we explored the spatiotemporal mismatch of LUFs and LUEs and their influencing factors from 2000 to 2018 in the Middle Reaches of the Yangtze River(MRYR).Specifically,we used Spearman correlation analysis to reveal the trade-off relationship between LUFs and LUEs and determine the direction of the influencing factors on the LUF-LUE mismatch,adopted spatial mismatch analysis to measure the imbalance between LUFs and LUEs,and used the geographical detector model to analyze the factors influencing this spatial mismatch.The results showed that production function(PDF),living function(LVF),ecological function(ELF),agricultural production efficiency(APE),urban construction efficiency(UCE),and ecological services efficiency(ESE)all displayed significant spatial heterogeneity.The high trade-off areas were widely distributed and long-lasting in agricultural space and urban space,while gradually decreasing in ecological space.Wuhan and Changsha showed high spatial mismatch coefficients in urban space,but low spatial mismatch coefficients in agricultural space.Hunan generally presented high spatial mismatch coefficients in ecological space.Furthermore,the interaction of the proportion of cultivated area and transportation accessibility exacerbated the mismatch in agricultural space.The interaction effects of capital investment and technology innovation with other factors have the most intense impact on the mismatch in urban space.The internal factor for cultivated area interacts with other external factors to drastically affect ecological spatial mismatch.