Fengjiao Song

Understanding vegetation phenology is critical for assessing the impacts of climate change, particularly in regions vulnerable to environmental fluctuations. This study investigates the temporal trends and spatial variability of the start of photosynthetic activity (SOP) in natural vegetation across Central Asia over the past four decades (1982–2022) using satellite-derived Normalized Difference Vegetation Index (NDVI) data. The research emphasizes the critical role of vegetation phenology in understanding responses to climate change. To extract spring phenological data, various smoothing techniques were applied, including filter-based methods, asymmetrical Gaussian fitting, and three nonlinear and piecewise linear methods, ensuring accurate representation from continuous time series data. NDVI time series were smoothed using a phenological extraction package. The results indicate an average advance in SOP of 1.26 days per decade, with forest ecosystems exhibiting the greatest shift at 3.05 days per decade. A spring temperature threshold near 0 °C was identified as a reliable predictor for dormancy break. Ensemble Empirical Mode Decomposition (EEMD) was utilized to differentiate between cumulative and instantaneous trends, revealing dynamic phenological responses. A notable shift around 2005 was observed, with approximately 76.28% of pixels showing a change in SOP trend, while 23.60% displayed a stable, monotonic trend. Vegetation at elevations between 1500 and 3000 m experienced a significant SOP advance of 2.27 days per decade, whereas vegetation above 3000 m showed no significant change over the study period. Spatially, SOP trends exhibited a latitudinal gradient, with delays observed in the southern regions and advancements north of 45° N. These findings underscore the importance of developing region-specific phenological models to inform environmental management and climate adaptation strategies, particularly in arid and semi-arid ecosystems.

To achieve the goals of carbon peak and carbon neutrality, Xinjiang, as an autonomous region in China with large energy reserves, should adjust its energy development and vigorously develop new energy sources, such as photovoltaic (PV) power. This study utilized data spatiotemporal variation in solar radiation from 1984 to 2016 to verify that Xinjiang is suitable for the development of PV power generation. Then, the averages of the solar radiation, sunshine duration, and other data in the period after 2000 were used to assess the suitability of Xinjiang, based on spatial principal component analysis (SPCA). Finally, the theoretical power generation potential, fossil fuel reduction, and CO₂ emissions reduction were estimated. The results are as follows: (1) In terms of temporal variation, the solar radiation in Xinjiang decreased (1984–2002), increased (2002–2009), and decreased again (2009–2016), but the fluctuations were not statistically significant. In terms of spatial distribution, the Kunlun Mountains in southern Xinjiang had the highest solar radiation during the span of the study period. Hami and Turpan, in eastern Xinjiang, had sufficiently high and stable solar radiation. (2) The area in Xinjiang classed as highly suitable for solar PV power generation is about 87,837 km², which is mainly concentrated in eastern Xinjiang. (3) In the situation where the construction of PV power plants in Xinjiang is fully developed, the theoretical potential of annual solar PV power generation in Xinjiang is approximately 8.57 × 10⁶ GWh. This is equivalent to 2.59 × 10⁹ tce of coal. Furthermore, 6.58 × 10⁹ t of CO₂ emissions can be reduced. PV power generation potential is approximately 27 times the energy consumption of Xinjiang in 2020. Through the suitability assessment and calculations, we found that Xinjiang has significant potential for PV systems.