Suchergebnisse

Theoretical Foundation of Urban Migration and Urban Governance -- An Overview of Global Urban Migration and Its Characteristics -- An Overview of Urban Migration in China and Its Characteristics -- Factors and Mechanisms Influencing Urban Migration and Inclusion in China -- Evolution of Macro Contexts of Urban Migration in Shanghai.

Industrial pollution control is a difficult problem in China's current economic transformation, and the Chinese government has implemented many measures to deal with it. However, little research has focused on the relationship between land policy and industrial pollution. Based on the theoretical discussion of the mechanism influencing the market-oriented reform of industrial land (mainly refer to the marketization of land conveyance price and the openness of land conveyance process) on urban industrial pollution, we constructed an analytical framework by linking land policy with industrial pollution. Then, we constructed an econometric model and chose the statistical data of 104 large- and medium-sized cities in mainland China from 2003 to 2016. The results indicate that with the marketization of the industrial land conveyance price, urban industrial pollution is presenting an inverted U-shaped change trend. For cities in different development stages of industrialization, there is no difference in the impact of industrial land conveyance price on urban industrial pollution. However, the openness of industrial land conveyance promotes and inhibits the urban industrial pollution in the stages of industrialization and post-industrialization, respectively. Finally, this paper puts forward some suggestions on how to control industrial pollution from the perspective of further improving the industrial land conveyance mechanism.

Abstract. In regions with distinct seasons, soil salinity usually
varies greatly by season. Thus, the seasonal dynamics of soil salinization
must be monitored to prevent and control soil salinity hazards and to reduce
ecological risk. This article took the Kenli District in the Yellow River
delta (YRD) of China as the experimental area. Based on Landsat data from
spring and autumn, improved vegetation indices (IVIs) were created and then
applied to inversion modeling of the soil salinity content (SSC) by
employing stepwise multiple linear regression, back propagation neural
network and support vector machine methods. Finally, the optimal SSC model
in each season was extracted, and the spatial distributions and seasonal
dynamics of SSC within a year were analyzed. The results indicated that the
SSC varied by season in the YRD, and the support vector machine method
offered the best SSC inversion models for the precision of the calibration
set (R2>0.72, RMSE < 6.34 g kg−1) and the validation
set (R2>0.71, RMSE < 6.00 g kg−1 and RPD > 1.66). The best SSC inversion model for spring could be applied to the SSC
inversion in winter (R2 of 0.66), and the best model for autumn could be applied to the SSC inversion in summer (R2 of 0.65). The SSC exhibited a gradual increasing trend from the southwest to northeast in the Kenli District. The SSC also underwent the following seasonal dynamics: soil salinity accumulated in spring, decreased in summer, increased in autumn and reached its peak at the end of winter. This work provides data support for the control of soil salinity hazards and utilization of saline–alkali soil in the YRD.

Private (out-of-pocket) healthcare expenditure (PHCE) is a complex phenomenon that is shaped by many different factors. In this paper, we analyzed the influencing factors of PHCE in China, with a specific focus on regional differences. We found that old-age dependency ratio, income, and education have significant impacts on PHCE in all regions, whereas public HCE, number of beds in medical institutions, and economic development levels have significant impacts only in some regions. The results indicate that the government should pay attention to regional inequality and implement targeted adjustments for improving the health service system. In particular, we recommend: (1) monitoring regional inequality in PHCE and other healthcare issues to unmask geographical differences in healthcare interventions; (2) adopting regional-specific policy measures—the government should divert some resources from eastern to western and central regions to increasing the support for public health undertakings and improve the quality of the local health services while providing matching medical resources by targeting the needs of the residents; (3) paying more attention to the healthcare demand of the elderly population; and (4) improving the education level of residents to improve public health and avoid high PHCE.

This study examined the changing trajectory and factors that influenced the health and medical expenditure of the Chinese elderly population over the past two decades. Based on the Chinese Longitudinal Healthy Longevity Survey (CLHLS) from 1998 to 2018, inferential and multiple linear regression models were constructed. The key finding is that China has experienced a decoupling of healthcare demand (HCD) and healthcare expenditure (HCE) since around 2014, when HCE began to decline despite the fact that HCD continued to rise. This is a promising sign, suggesting that the government's health insurance policy is working. Furthermore, participating in health insurance schemes can significantly reduce the elderly's HCD and HCE, demonstrating that health insurance can effectively affect the elderly's decision to seek medical treatment and improve their health condition. We also found that age, region, basic old-age insurance, and care by the government and institutions were significant factors that influenced the healthcare demand and expenditure of the elderly population.