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.

The Chaohu Lake Basin (CLB) is the main flow area of the Yangtze River–Huaihe River Water Transfer Project in Central China. It is important to quantitatively evaluate the water resources in the CLB and predict their response to future climate change. This study simulated and calibrated the water yield in the CLB from 2000 to 2019 based on InVEST. We also analyzed the influence factor on the water yield and predicted the water yield in future years with CMIP6 data. The results demonstrate that: (1) The InVEST water production module had good applicability in this study region. There was a strong linear relationship between the simulated water yield and the observed surface runoff (y = 1.2363x − 8.6038, R² = 0.868, p < 0.01); (2) The explanatory percentage of interaction between precipitation and land use/land cover for water yield in 2001, 2008, and 2016 reached 71%, 77%, and 85%, respectively, which were the two dominant factors affecting water yield in the CLB; and (3) The average annual water yield in the CLB increased under the SSP2-4.5, SSP3-7.0, and SSP5-8.5 future scenarios with increasing precipitation, increased with 71%, 139.8%, and 159.5% in 2100 compared with 2040, respectively. The overall trend of water production decreased with increases in carbon emission intensity.

The verification efficiency and precision of copper ore grade has a great influence on copper ore mining. At present, the common method for the exploration of reserves often uses chemical analysis and identification, which have high costs, long cycles, and pollution risks but cannot realize the in situ determination of the copper grade. The existing scalar spectrometric techniques generally have limited accuracy. As a vector spectrum, polarization state information is sensitive to mineral particle distribution and composition, which is conducive to high-precision detection. Taking the visible-near infrared parallel polarization reflectance spectrum data and grade data of a copper mine in Xiaoyuan village, Huaining County, Anhui Province, China, as an example, the characteristics of the parallel polarization spectra of the copper mine were analyzed. The spectra were pretreated by first-order derivative transform and wavelet denoising, and the dimensions of wavelet denoising spectra, parallel polarization spectra, and first-order derivative spectra were also reduced by principal component analysis (PCA). Three, four, and eight principal components of the three types of spectra were selected as variables. Four machine learning models, the radial basis function (RBF), support vector machine (SVM), generalized regression neural network (GRNN), and partial least squares regression (PLSR), were selected to establish the PCA parallel polarization reflectance spectrum and copper grade prediction model. The accuracy of the model was evaluated by the determination coefficient (R²) and root mean square error (RMSE). The results show that, for parallel polarization spectra, first-order derivative spectra, and wavelet denoising spectra, the PCA-SVM model has better results, with R² values of 0.911, 0.942, and 0.953 and RMSE values of 0.022, 0.019, and 0.017, respectively. This method can effectively reduce the redundancy of polarized hyperspectral data, has better model prediction ability, and provides a useful exploration for the grade analysis of hydrothermal copper deposits at meso-low temperatures.

This study examined the influence of the Yangtze River-Huaihe River Water Transfer Project (YHWTP) on the transportation accessibility of bulk cargo in 16 cities of Anhui Province based on modern transportation infrastructure. We also discussed the change in the strength of economic linkages affected by the YHWTP for 16 cities within Anhui Province and the Yangtze River Delta using the gravity model. The results demonstrate that: (1) The YHWTP will significantly improve the transportation accessibility of bulk commodities among the 16 cities in Anhui Province, especially the cities along the project route. It will reduce the minimum average transport cost (MATC) and the weighted average transport cost (WATC). (2) The YHWTP has a different influence on the transportation accessibility of the 16 cities, making the location conditions more unequal. (3) The change of spatial distribution of transportation accessibility of the 16 cities caused by YHWTP will be mainly concentrated in the triangular region, formed by Huainan, Anqing, and Wuhu. (4) The YHWTP will improve the total strength of economic linkages (TSEL) of the 16 cities within Anhui Province and Yangtze River Delta (YRD) region, with an increase by 27.62% and 9.04%, respectively. (5) Overall, Hefei will benefit the most from the YHWTP.