The Yangtze River Delta plays an important strategic role in China’s economic development pattern, and its carbon emission intensity, which reflects the development of a low-carbon economy, has attracted much attention. From the perspective of the city-level, this study uses the coefficient of variation, spatial autocorrelation and the Multi-scale Geographically Weighted Regression (MGWR) model to study the spatio-temporal characteristics of carbon emission intensity in the Yangtze River Delta from 1997 to 2017 and the spatial heterogeneity of its influencing factors. The results indicated that: (1) the carbon emission intensity in the Yangtze River Delta increased first and then decreased during the sample period, and the number of low-carbon emission intensity zones decreased first and then increased. (2) Through the coefficient of variation analysis, it is known that the ratio of nugget value to base value is much less than 25%, indicating that the correlation between the cities in the Yangtze River Delta is becoming more and more obvious, the spatial difference is becoming smaller, and the integration level is growing higher and higher. (3) The carbon emission intensity of the Yangtze River Delta has a strong positive spatial correlation, and the carbon emission intensity of the Yangtze River Delta decreases from the north to the south. (4) The effect of population size on carbon emission intensity is bidirectional, but the inhibition effect is greater than the promotion effect, and the average regression coefficient is −0.0796; the average regression coefficient of economic development level is 0.3674, and the average regression coefficient of industrial structure is 0.1702, both of which have a positive impact on carbon emission intensity. The degree of urbanization has a bidirectional effect, and the regression coefficient ranges from −0.920 to 0.091, and the negative effect is quite strong. Additionally, each factor has spatial heterogeneity.

As the second most abundant greenhouse gas after carbon dioxide (CO₂), methane not only plays an important role in global and regional photochemical reactions, but also has an important impact on energy balance and climate change. To explore the long-term trends and spatiotemporal variation of methane concentration over China, we verified the accuracy of the column-averaged, dry air-mixing ratio of CH₄ (abbreviated as XCH₄ hereafter) merged by SCIAMACHY and GOSAT products, utilizing the data of six surface observation stations in China and the surrounding areas. The root mean square error (RMSE) was mostly less than 2.5%, and the correlation coefficients (r) were 0.77, 0.84, 0.66, 0.42, 0.62 and 0.75. Furthermore, we analyzed the temporal and spatial variation patterns of the XCH₄ concentration over China from 2003 to 2020. The results showed that the XCH₄ concentration had an increasing trend over China from 2003 to 2020; the average growth rate was 6.64 ppb·a⁻¹, and the value range of the increase rate was from 4.66 ppb·a⁻¹ to 8.46 ppb·a⁻¹. The lowest XCH₄ concentration was located over Tibet (1764.03 ppb), and the high values were located in the Sichuan Basin, Central China (Hunan, Hubei, and Henan) and East China (Anhui and Jiangxi) (1825–1845 ppb). The XCH₄ concentration was higher in autumn and summer, low in winter and spring, and had obvious seasonal variations. Human factors such as population density, GDP and energy consumption have a significant impact on the XCH₄ concentration over China.

Vegetation filter strips (VFSs) have always been an important measure to control agricultural soil erosion, especially in mountainous and hilly areas with more sloping farmland. To investigate the mechanism of the sediment-trapping process by VFSs, a series of tests were conducted with four gradients of flow rate, 7.5–45 L min⁻¹ m⁻¹, and two different sediment concentrations of 40 and 120 g L⁻¹. The whole process of overland flow was monitored, and sediment and particle size samples from the inflow and outflow were collected and measured. The results showed that the changes in sediment concentration did not significantly affect the corresponding coefficients in the power function relationship between overland flow rate and velocity. Using the Reynolds number alone cannot effectively indicate the flow pattern of overland flow on vegetation hillslopes. The peak particle size and linear function were effective in describing the relationship between sediment particle composition and delivery rate during the sediment-trapping process by VFSs. During the sediment-trapping process, the sediment-trapping capacity of VFSs continued to decrease. The increase in sediment discharge was accompanied by a higher proportion of coarse particles. Under the same flow rate conditions, when the sediment concentration was higher, the coarse particles and their proportion also increased faster. Therefore, using only a certain particle size threshold to distinguish suspended and transported sediment may lead to inaccurate estimation of the sediment-trapping performance of VFSs. This study deepened the understanding of the mechanism of water–sediment processes on vegetation hillslopes and promoted the widespread and efficient application of VFSs management technology.