In recent years, intensified industrialization and rapid urbanization have accelerated the accumulation of trace metals in topsoils of the Golden Triangle of Southern Fujian Province in China. Trace metals can cause adverse impacts on ecosystems and human health. In order to assess the ecological and human health risks of trace metals in the Golden Triangle region and to determine the distribution and degree of pollution of trace metals, 456 soil samples were collected from 28 districts. The concentrations of six metals (As, Cr, Cu, Ni, Pb, and Zn) were analyzed to assess ecological risk using the geoaccumulation index (I_geo) and the potential ecological risk index (RI). The United States Environmental Protection Agency (USEPA) model was applied to calculate health risk. The average soil concentrations of the six elements are ranked as follows: As < Ni < Cu < Cr < Pb < Zn. Inverse distance weighting (IDW) interpolation maps showed that Cr, Cu, Ni, and Zn are enriched in the soils of developed areas, while As and Pb are enriched in the soils of undeveloped areas. The I_geo showed that the levels of metals in most soil samples are below polluting levels. Similarly, RI values indicated that trace metals pose low potential ecological risk in the region’s soils. The Hazard Quotient (HQ) ranked the mean total noncarcinogenic risk of the six metals, for both children and adults, as follows: As > Pb > Cr > Ni > Cu >Zn. The mean carcinogenic risk (CR) of the metals in the region’s soils are ranked as follows: Cr > As > Ni. The Hazard Index (HI) values indicated that 3.7% of soils contained unsafe levels of toxic metals for children and total carcinogenic risk (TCR) values indicated that 23.3% of soils contained unsafe levels, indicating that children are facing both noncarcinogenic and carcinogenic risks from trace metals. Principal component analysis (PCA) and matrix cluster analysis were used to identify pollution sources and classified trace metals and soil samples into two and five groups, respectively. The five groups represented the effects of different land use types, including agricultural area, residential and public area, industrial area, forest, and industrial area and roadside, based on the contents of trace metals in soils. Industrial, agricultural and traffic activities attribute to the enrichment of Cr, Cu, Ni, Pb, and Zn in the region’s soils. Moreover, the accumulation of As and Pb are also attributed to atmospheric deposition. These results can contribute to a better understanding of pollution, ecological risks, and human health risks from trace metals on large regional scales like the Golden Triangle of Southern Fujian Province.

The Chinese government has implemented a number of environmental policies to promote the continuous improvement of air quality while considering economic development. Scientific assessment of the impact of environmental policies on the relationship between air pollution and economic growth can provide a scientific basis for promoting the coordinated development of these two factors. This paper uses the Tapio decoupling theory to analyze the relationship between regional economic growth and air pollution in key regions of air pollution control in China—namely, the Beijing–Tianjin–Hebei region and surrounding areas (BTHS), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD)—based on data of GDP and the concentrations of SO₂, PM₁₀, and NO₂ for 31 provinces in China from 2000 to 2019. The results show that the SO₂, PM₁₀, and NO₂ pollution in the key regions show strong and weak decoupling. The findings additionally indicate that government policies have played a significant role in improving the decoupling between air pollution and economic development. The decoupling between economic growth and SO₂ and PM₁₀ pollution in the BTHS, YRD, and PRD is better than that in other regions, while the decoupling between economic growth and NO₂ pollution has not improved significantly in these regions. To improve the relationship between economic growth and air pollution, we suggest that the governments of China and other developing countries should further optimize and adjust the structure of industry, energy, and transportation; apply more stringent targets and measures in areas of serious air pollution; and strengthen mobile vehicle pollution control.

The analysis of the spatial and temporal characteristics of urban built-up area is conducive to the rational formulation of urban land use strategy, scientific planning and rational distribution of modern urban development. Based on the remote sensing data in four separate years (1999, 2004, 2010 and 2014), this research identified and inspected the urban built-up area boundary based on the temperature retrieval method. Combined with the second land investigation data and Google map data in Jingzhou, this paper used the qualitative and quantitative analysis methods to analyze the spatial-temporal characteristics of Jingzhou urban built-up area expansion over the past 15 years. The analysis shows that the entire spatial form of the urban built-up area has been evolving towards a compact and orderly state. On this basis, the urban area-population elasticity coefficient and algometric growth model were used to determine the reasonability of the urban sprawl. The results show that the expansion of built-up area in Jingzhou is not keeping up with the speed of population growth.

Estimation of impervious surface area is important to the study of urban environments and social development, but surface characteristics, as well as the temporal, spectral, and spatial resolutions of remote sensing images, influence the estimation accuracy. To investigate the effects of regional environmental characteristics on the estimation of impervious surface area, we divided China into seven sub-regions based on climate, soil type, feature complexity, and vegetation phenology: arid and semi-arid areas, Huang-Huai-Hai winter wheat production areas, typical temperate regions, the Pearl River Delta, the middle and lower reaches of the Yangtze River, typical tropical and subtropical regions, and the Qinghai Tibet Plateau. Impervious surface area was estimated from Landsat 8 images of five typical cities, including Yinchuan, Shijiazhuang, Shenyang, Ningbo, and Kunming. Using the linear spectral unmixing method, impervious and permeable surface areas were determined at the pixel-scale based on end-member proportions. We calculated the producer’s accuracy, user’s accuracy, and overall accuracy to assess the estimation accuracy, and compared the accuracies among images acquired from different seasons and locations. In tropical and subtropical regions, vegetation canopies can confound the identification of impervious surfaces and, thus, images acquired in winter, early spring, and autumn are most suitable; estimations in the Pearl River Delta, the middle and lower reaches of the Yangtze River are influenced by soil, vegetation phenology, vegetation canopy, and water, and images acquired in spring, summer, and autumn provide the best results; in typical temperate areas, images acquired from spring to autumn are most effective for estimations; in winter wheat-growing areas, images acquired throughout the year are suitable; and in arid and semi-arid areas, summer and early autumn, during which vegetation is abundant, are the optimal seasons for estimations. Knowledge of optimal time frames, multi-source data, and intelligent algorithms should be integrated to reduce spectral confusion and improve the estimation of impervious surface area from Landsat 8 OLI imagery.