Bo Yuan

CPVG (Utility-scale photovoltaic generation) is expanding rapidly worldwide, yet its cumulative ecological effects remain insufficiently quantified. This review synthesizes current evidence to clarify how CPVG influences ecosystems through linked mechanisms of energy redistribution, biogeochemical cycling disturbance, and ecological responses. CPVG alters surface radiation balance, modifies microclimate, and disrupts carbon–nitrogen–water fluxes, thereby driving vegetation shifts, soil degradation, and biodiversity decline. These impacts accumulate across temporal scales—from short-term construction disturbances to long-term operational feedbacks—and propagate spatially from local to regional and watershed levels. Ecological outcomes differ substantially among deserts, grasslands, and agroecosystems due to contrasting resilience and limiting factors. Based on these mechanisms, we propose a multi-scale cumulative impact assessment framework integrating indicator development, multi-source monitoring, coupled modelling, and ecological risk tiering. A full-chain mitigation pathway is further outlined, emphasizing optimized siting, disturbance reduction, adaptive management, and targeted restoration. This study provides a systematic foundation for evaluating and regulating CPVG’s cumulative ecological impacts, supporting more sustainable solar deployment.

Water quality safety in the water source constitutes a crucial guarantee for public health and the ecological environment. This study undertakes a comprehensive assessment of the water quality conditions within the Jing River Basin of the Loess Plateau, emphasizing the spatial and temporal characteristics, as well as the determinants influencing surface water quality in the Shaanxi section. We utilized data from seven monitoring stations collected between 2016 and 2022, employing an enhanced comprehensive Water Quality Index (WQI) method, redundancy analysis (RDA), and Spearman’s correlation analysis. The results show that the average annual WQI value of the water quality of the Shaanxi section of the Jing River increased from 68.01 in 2016 to 76.18 in 2022, and the river’s water quality has gradually improved, with a significant improvement beginning in 2018, and a series of water quality management policies implemented by Shaanxi Province is the primary reason for the improvement. The river’s water quality has deteriorated slightly in recent years, necessitating stricter supervision of the coal mining industry in the upper section. The river has an average WQI value of 73.70 and is rated as ‘good’. The main pollution indicators influencing the river’s water quality are COD_Mn, COD, BOD₅, NH₃-N, and TP. From the upstream to the downstream, the water quality of the river shows a pattern of increasing and then decreasing, among which S4 (Linjing Bridge in Taiping Town) and S5 (Jinghe Bridge) have the best water quality. The downstream part (S6, S7) of the Jing River near the Weihe River has poor water quality, which is mostly caused by nonpoint source contamination from livestock and poultry rearing, agricultural activities, and sewage discharge. Redundancy analysis revealed that the spatial scale of the 2500 m buffer zone best explained water quality changes, and the amount of bare land and arable land in land use categories was the key influencing factor of river water quality.

Dissimilatory nitrate reduction to ammonium (DNRA) is an important nitrate reduction pathway in freshwater sediments. Many studies have focused on the DNRA process in various natural habitats. However, the joint operation of cascade reservoirs will affect the physical and chemical properties of sediments, which may change the DNRA process and bacterial community pattern in the surface sediments of cascade reservoirs. Our study was the first to investigate the spatiotemporal distribution patterns of potential DNRA rate, nrfA gene abundances, and DNRA bacterial community diversity in surface sediments of the Lancang River cascade reservoirs. The results of slurry incubation experiments combined with the ¹⁵N isotope tracer experiment ascertained that the potential rates of DNRA were 0.01–0.15 nmol-N cm⁻³ h⁻¹, and qPCR results indicated that the abundance range of nrfA was 1.08 × 10⁵–2.51 × 10⁶ copies g⁻¹ dry weight. High throughput sequencing of the nrfA gene revealed that the relative abundance of Anaeromyxobacter (4.52% on average), Polyangium (4.09%), Archangium (1.86%), Geobacter (1.34%), and Lacunisphaera (1.32%) were high. Pearson and RDA correlation analysis exhibited that nrfA gene abundance was positively correlated with altitude, pH, OC, and sand concentration. Anaeromyxobacter was positively correlated with reservoir age and DNRA potential rate. The deterministic environmental selection process plays a crucial role in the formation of the DNRA bacterial community. Network analysis displayed that the dominant DNRA genus was the key population of the DNRA microbial community in the sediments of Lancang River cascade reservoirs. This study reveals that the variation of DNRA bacterial activity and community structure is largely driven by the construction of cascade reservoirs, and provides a new idea for further understanding the characteristics of the DNRA community in the cascade reservoir ecosystem.

Photovoltaic (PV) farms have location-dependent effects on soil, climate, and vegetation. To assess the soil quality status of large-scale PV farms in desert areas, this study was carried out at th...

Biocarriers are a key factor in moving bed biofilm reactors (MBBR) for domestic wastewater treatment and studies targeting biocarriers can be explored in more depth. In this study, two different types of biocarriers, namely anaerobic microbial carriers (AMC) and porous biogels (PBG), were used to treat real domestic wastewater and acted on a lab-scale tertiary MBBR system. The effects of the start-up process, water quality degradation, secondary start-up, and organic loading rate (OLR) on MBBR performance at room temperature (19–24 °C) and the same filling ratio (40%) were investigated, as well as the calculation of sludge yield. The results showed that the AMC–PBG/MBBR biological treatment process could complete the start-up process quickly in a short time and the OLR was finally determined to be 1.5 kgCOD/(m³·d). In this case, the system was able to operate stably and complete the secondary start-up relatively quickly, with 80% and 95% removal of COD and NH₄⁺-N, respectively. The biofilm was characterized by scanning electron microscopy (SEM) and high-throughput sequencing which revealed the changes of microorganisms in the biofilm during operation, among which the dominant phyla were Euryarchaeota and Proteobacteria. Finally, the apparent production of process sludge was monitored and calculated to be 0.043 kgMLSS/kgCOD which is a significant reduction in sludge compared to the conventional activated sludge method. These conclusions provide valuable information for the full-scale treatment of domestic wastewater.

The accurate estimation of phenological metrics from satellite data, especially the start of season (SOS), is of great significance to enhance our understanding of trends in vegetation phenology under climate change at regional or global scales. However, for regions with winter snow cover, such as the alpine grasslands on the Tibetan Plateau, the presence of snow inevitably contaminates satellite signals and introduces bias into the detection of the SOS. Despite recent progress in eliminating the effect of snow cover on SOS detection, the mechanism of how snow cover affects the satellite-derived vegetation index (VI) and the detected SOS remains unclear. This study investigated the effect of snow cover on both VI and SOS detection by combining simulation experiments and real satellite data. Five different VIs were used and compared in this study, including four structure-based (i.e., NDVI, EVI2, NDPI, NDGI) VIs and one physiological-based (i.e., NIRv) VI. Both simulation experiments and satellite data analysis revealed that the presence of snow can significantly reduce the VI values and increase the local gradient of the growth curve, allowing the SOS to be detected. The bias in the detected SOS caused by snow cover depends on the end of the snow season (ESS), snow duration parameters, and the snow-free SOS. An earlier ESS results in an earlier estimate of the SOS, a later ESS results in a later estimate of the SOS, and an ESS close to the snow-free SOS results in small bias in the detected SOS. The sensitivity of the five VIs to snow cover in SOS detection is NDPI/NDGI < NIRv < EVI2 < NDVI, which has been verified in both simulation experiments and satellite data analysis. These findings will significantly advance our research on the feedback mechanisms between vegetation, snow, and climate change for alpine ecosystems.

The effect of dams on the longitudinal variability, characteristics, and release mechanism of different nitrogen fractions is unknown along with canyon cascade reservoirs. In this study, we analyzed the longitudinal distribution of the iron-exchangeable, carbonate, iron–manganese oxide, and organic matter-sulfide fractions in sediments of seven cascade reservoirs along the Lancang River Basin in Southwest China. The contribution ratios of all nitrogen fractions to the release of nitrogen from reservoirs sediment were also determined. From upstream to downstream, the total nitrogen content and all different nitrogen fractions in the sediment showed obvious spatial heterogeneity. Ion-exchangeable fraction, iron–manganese oxides fraction, carbonate fraction, and organic matter–sulfide fraction nitrogen accounted for 2.7–17.7%, 0.5–4.4%, 1.2–3.5%, and 31.1–71.6% of the total nitrogen, respectively. Correlation and redundancy analyses showed that various nitrogen fractions had a significant correlation with total nitrogen, total organic carbon, water velocity, clay, and sand. Organic matter–sulfide fraction nitrogen and the total transferable nitrogen were positively correlated with iron–manganese oxide minerals and iron–manganese–aluminum oxide minerals. Approximately 27.90–82.66% of ion-exchangeable fraction nitrogen, 9.80–35.70% of carbonate fraction nitrogen, 17.30–36.88% of iron–manganese oxides fraction nitrogen, and 4.82–17.10% of organic matter–sulfide fraction nitrogen were released. The results show that the different nitrogen fractions in the sediments of seven cascade reservoirs are in dynamic equilibrium with the overlying water, and the weak ecological risk is caused by nitrogen release from the sediments.

The photovoltaic power station in Qinghai has been built for 8 years; however, its impact on the regional soil ecological environment has not been studied in depth. To reveal the structure and distribution pattern of archaeal communities in desert soil under the influence of a large photovoltaic power station, a comparative study was carried out between the soil affected by photovoltaic panels and the bare land samples outside the photovoltaic station in Gonghe, Qinghai Province. The abundance, community structure, diversity, and distribution characteristics of archaea were analyzed by quantitative PCR and Illumina-MiSeq high-throughput sequencing, and the main environmental factors affecting the variation in soil archaeal community were identified by RDA. The contribution rate of environmental factors and human factors to microbial community diversity was quantitatively evaluated by VPA. The results showed that there was no significant difference in soil nutrients and other physicochemical factors between the photovoltaic power station and bare land. Thaumarchaeota was the dominant archaeal phylum in the area, accounting for more than 99% of archaeal phylum, while at the level of genus, Nitrososphaera was the dominant archaeal genera. There was no significant difference in archaeal community structure between and under different types of PV panels. The analysis has shown that the construction of a photovoltaic station has little effect on the community structure of soil archaea in a desert area, and it was speculated that the selection of niche played a leading role in the distribution pattern of soil archaeal community. This study provides the basis for a scientific understanding of the characteristics and distribution patterns of soil archaeal communities affected by the construction of a photovoltaic power station.