As a new product of rapid urbanization, the sprawl of urban construction land can objectively reflect urban land use efficiency, which is of great significance to China\'s new urban construction. This study aimed to summarize the expansion patterns and utilization efficiency of urban construction land in China from the perspectives of the status, speed and trends of expansion, and to uncover the key factors that lead to the differential distribution of the expansion of construction land. It can also provide land management experience for other countries with rapid expansion of construction land. The results show the following. (1) The expansion of China\'s construction land presents a \"point-line-plane\" pattern of evolution, forming changing stages of point-like aggregation, linear series and planar spread. (2) China\'s construction land shows the characteristics of disorderly spread, a low utilization rate and low output efficiency. The speed of expansion presents clear characteristics of being high in the east and low in the west, mostly concentrated in the Yangtze River Delta, Pearl River Delta and the Beijing-Tianjin-Hebei urban agglomeration. Shanghai, Beijing, Shenzhen and Guangzhou have the highest intensity of construction land use. In Shandong Peninsula and eastern coastal areas, the intensity of the construction land use is generally high. In Xinjiang and Xizang, the intensity of construction land use is relatively low. (3) The urban economic level, population size, industrial structure, foreign investment and land policies have significant effects on the spatial distribution of the expansion of construction land.

Driven by industrialization and urbanization, urban air pollution can increase respiratory, heart, and cerebrovascular diseases, and thus mortality rates; as such, it is necessary to improve air quality through the consideration of individual pollutants and emission sources. In Republic of Korea, national and local governments have installed urban and roadside air quality monitoring systems. However, stations are lacking outside metropolitan regions, and roadside stations are sparsely distributed, limiting comparisons of pollutant concentrations with vehicle traffic and floating population levels. Local governments have begun using mobile laboratories (MLs) to supplement the fixed measurement network and investigate road pollution source characteristics based on their spatiotemporal distribution; however, the collected data cannot be used effectively if they are not visualized. Here, we propose a method to collect and visualize global information system (GIS)-based air quality data overlayed with environmental variables to support air quality management measures. Spatiotemporal analyses of ML-derived data from Bucheon, Korea, confirmed that particulate and gaseous pollutant concentrations were high during typical commuting hours, at intersections, and at a specially managed road. During commuting hours, the maximum PM10 concentration reached 200.7 µg/m3 in the Nae-dong, Gyeongin-ro, and Ojeong-dong ready-mix concrete complex areas, and the maximum PM2.5 concentration was 161.7 µg/m3. The maximum NOx, NO2, and NO levels of 1.34 ppm, 0.18 ppm, and 1.18 ppm, respectively, were also detected during commuting hours. These findings support the need for targeted management of air pollution in this region, and highlight the benefit of comprehensively comparing road levels, driving speed, and traffic levels when identifying hotspots of air pollution. Such analyses will contribute to the development of air quality management measures customized to regional characteristics.

Land use regression (LUR) models are mainly used for the simulation and prediction of conventional atmospheric pollutants. Whether the LUR models can be expanded to study more toxic and hazardous pollutants (such as heavy metals) remains to be verified. Combined with the factors of road, land use type, population, pollution enterprise, meteorology, and terrain, the LUR models were used to simulate the spatial distribution characteristics of heavy metals in road dust and determine the main influencing factors. Samples of road surface dust were collected from 144 evenly distributed points in Tianjin, China, with 108 modelling points and 36 verification points. The R2 values of the LUR models of Cd, Cr, Cu, Ni, and Pb contents were 0.301, 0.412, 0.399, 0.496, and 0.377, and their error rates were 2.72%, 4.96%, 4.64%, 8.91%, and 4.94%, respectively. The error rates of the kriging interpolation models were 3.33%, 6.50%, 5.14%, 18.30%, and 22.87%, which were all greater than those of the LUR models. The estimation effect of the LUR models was more refined than that of the kriging interpolation models. The contents of most heavy metals (except Ni) in road dust of the central area in Tianjin were generally higher than those of the surrounding areas. The heavy metal contents in road dust of Tianjin were mainly affected by road variables and meteorological variables. The LUR models were suitable for small-scale spatial prediction of heavy metals in urban road dust within urban areas.

The COVID-19 pandemic has inevitably changed people\'s lifestyles and demands for urban green space and public open space. The National Landscape Garden Cities in China (NLGCC) policy is one of the key development models in China aimed at building sustainable cities and society. In this paper, the development of the study\'s selection criteria and the significance and benefits of the NLGCC policy are first summarised. 391 cities were chosen from the NLGCC list to analyse the spatial distribution and construction of driving factors. The results show that the NLGCC\'s selection criteria have shifted from a focus on quantity to overall habitat quality. During the COVID-19 pandemic, city resilience has been examined more closely. The NLGCC policies have boosted to address ecological and environmental crises and enhanced urban disaster preparedness. The spatial distribution analysis shows that the NLGCC is spatially unevenly distributed and has a clustering trend. A total of 54.96% of the NLGCC is concentrated in China\'s eastern and central regions. The natural environment and socioeconomics are two main categories of driving factors. This study provides significant value to the understanding of the spatial pattern of the NLGCC offers a reference for decision-making about the construction of urban environments worldwide.

Lime mines are a potential source of pollution, and the surrounding soil environment is generally at threat, especially in abandoned lime mines. This paper focuses on the study area in eastern Anhui, attempting to analyze whether Cd enrichment is related to abandoned mines. On the basis of geological investigation, this study systematically used XRD, XRF, GTS and universal Kriging interpolation to determine the distribution law of Cd in the study area, and evaluated the potential ecological risk of Cd. The results showed that the main mineral types of soil samples of red clastic rock soil parent material (RdcPm) and soil samples of carbonate soil parent material (CPm) were not completely the same. Correlation analysis showed that CaO, MgO and Cd were positively correlated with the CPm. Human activities led to the accumulation of Cd in the study area. High Cd was mainly concentrated in the northwest of the study area, which was correlated with abandoned mines and soil parent materials. The study area was dominated by slight potential risks, although some areas had medium potential risks and high potential risks. All potential high risks were in the CPm field. This study provides a scientific basis for the comprehensive utilization and development planning of soil in the study area.

The COVID-19 pandemic is a public health emergency, which continues to have a significant impact on the functioning of society and the public\'s daily life. From the perspective of psychological distance (PD), this study used descriptive, differential, and spatial autocorrelation analysis methods to explore the cognitive distance, emotional distance, expected distance and behavioral distance of the Chinese public in relation to the COVID-19 pandemic. An analysis of 4042 valid sample data found that: (1) The event emotional distance and subject emotional distance were both furthest from the event and subject psychological distance dimensions, and anger about the event was the strongest. (2) The government was the most appealing subject in the process of pandemic prevention and control, but at the same time, the public\'s sense of closeness to the government was also lower than that of the other three subjects, e.g., medical institutions. (3) Different pandemic regions showed significant differences in PD. Mean scores of PD in each risk region were as follows: High-risk regions > medium-risk regions > low-risk regions. (4) From a global perspective, no spatial autocorrelation was found in PD. However, from a local perspective, high-value regions (provinces with distant PD) are mainly concentrated in the southern regions (Guizhou, Guangxi, Hainan, Jiangxi), and low-value regions (provinces with close PD) are mainly concentrated in North China (Shanxi, Hebei, Beijing). Combined with the relevant conclusions, this paper put forward policy recommendations.

In recent years, a series of earthquakes have occurred in Sichuan province, southwest China. On April 20, 2013, 1013 landslides were triggered in the Lushan earthquake within the research area of 1215.87 km2. On August 8, 2017, 821 landslides were induced in the Jiuzhaigou earthquake within the study area of 541.61 km2. The slope, aspect, elevation, distance to the river, distance to fault, stratum lithology, curvature, and PGA as evaluation factors were chosen to research the distribution characteristics of coseismic landslides. The relationship between influence factors and distribution of coseismic landslides were analyzed using landslide area density (LAD), defined as the ratio between the coseismic landslides area and the total area under the specific classification of eight factors, and landslide number density (LND), interpreted as the number of landslides per square kilometer affected by an earthquake. Both the LAD and LND curves show the common correlations between distribution characteristics of coseismic landslides and the classification of eight factors. The high density of coseismic landslides was found at locations where the valley evolves from U-shaped to V-shaped, along slopes with an inclination between 20 and 50°. Due to the effect of river cutting erosion and human engineering activities, massive coseismic landslides appeared within the scope of 200 m from the river system. Eight hundred sixty small shallow coseismic landslides were found less than 3 km from the seismogenic fault in both earthquakes. Both concave and convex terrain has the same effect of promoting coseismic landslides. The strata of the Carboniferous and Cretaceous are more prone to coseismic landslides occurrence. In the event of another earthquake of similar magnitude in southwest China in the future, the research results can quickly predict the distribution of coseismic landslides and provide a scientific basis for emergency rescue.

River sediment is the ultimate sink for heavy metal pollution. Copper (Cu) and zinc (Zn) are consistently found at environmentally significant levels in sediments worldwide. We hypothesized that the bioavailability and potential ecological risk of Cu and Zn in river sediments may be affected by seasonal variations and spatial distribution. In this study, we tested our hypothesis using highly industrialized river sediments (Laojie River) as an example. The concentration of heavy metals, pollution indexes, and risk indexes were evaluated and multivariate statistical analyses were performed. We found that seasonal variations affect heavy metal contamination, pollution indexes, and potential ecological risk in sediments and this effect was more severe in the dry season. In addition, higher levels of metal contamination, pollution indexes, and potential ecological risk were observed midstream and downstream of the Laojie River. We found that Cu and Zn were the primary contaminants in Laojie River sediments and may originate from common anthropogenic sources. Analysis of the chemical fractions further revealed that Cu and Zn exhibited high mobility and potential bioavailability risk. In addition, a high percentage and amount of Cu and Zn were found in exchangeable fractions, suggesting they pose a great risk to aquatic organisms. Our results indicate that seasonal variations and spatial distribution affect the bioavailability and potential ecological risk of Cu and Zn in river sediments. These findings suggest that seasonal variations and spatial distribution are important parameters to consider for environmental monitoring and environmental management in aquatic environments.

Spatial distribution characteristics of heavy metal (Cd, Pb, Cr, Cu, Zn, and Hg) contents and their ecological risks in the farmland along the shoreline of the Caohai wetland were investigated. Incubation experiments were also conducted to characterize the emission of heavy metals across soil-water interface if the farmland was reclaimed to wetland. The results showed that spatial distribution characteristics of these heavy metal contents were significantly different. Concentrations of Cd, Zn, and Hg were higher than the corresponding geochemical background levels. Ecological risk assessment suggested that the farmland along the shoreline of Caohai wetland were characterized by non-pollution or slight pollution of Pb, Cr, and Cu, moderate pollution of Cd, slight to moderate pollution of Hg, and slight pollution of Zn. Emission rates of Cd, Zn, and Hg across soil/sediment-water interface first increased, then decreased and finally reached equilibrium after the farmland soil was submersed. The contribution-rates of Cd, Zn, and Hg transferring from sediment to overlying water were calculated to be 12.7%, 14.8%, and 10.4%, respectively. We conclude that environmental issues caused by heavy metals, especially by Cd, Zn, and Hg, in the farmland along the shoreline of the Caohai wetland should be paid great attention.