Mutual inhibition effects of elevated CO2 and climate change on global forest GPP.

The impact of CO2 fertilization on enhancing global forest gross primary productivity (GPP) is acknowledged, but its interaction with climate factors-air temperature (Tem), precipitation (Pre), vapor pressure deficit (VPD), and radiation (Rad)-remains unclear. In this study, global forest GPP trends from 1982 to 2018 were examined using BEPS, NIRv, FLUXCOM, and revised EC-LUE datasets, with interannual trends of 5.618 (p < 0.01), 5.831 (p < 0.01), 0.227, and 6.566 g C m-2 yr-1 (p < 0.01), respectively. Elevated CO2 was identified as the primary driver of GPP trends, with the dominant area ranging from 51.11% to 90.37% across different GPP datasets. In the NIRv and revised EC-LUE datasets, the positive impact of CO2 on GPP showed a decrease of 0.222 g C m-2 yr-1, while the negative impact of Rad increased by 0.007 g C m-2 yr-1. An inhibitory relationship was found between the actual effects of elevated CO2 and climate change on GPP in most forest types. At lower latitudes, Tem primarily constrained CO2 fertilization, while at higher latitudes, VPD emerged as the key limiting factor. This was mainly attributed to the potential trade-off or competition between elevated CO2 and climate change in influencing GPP, with strategic resource allocation varying across different forest ecosystems. This study highlights the significant inhibitory effects of elevated CO2 and climate change on global forest GPP, providing insights into the dynamic responses of forest ecosystems to changing environments.

Global eight drought types: Spatio-temporal characteristics and vegetation response.

The traditional classification of drought events into seasonal and flash types oversimplified the complexity and variability of global drought phenomena, limiting a deeper understanding of drought characteristics and their impacts on vegetation. To address this issue, soil moisture percentile methods and the Soil Moisture Anomaly Percentage Index (SMAPI) were employed to create time series for flash drought (FD) and seasonal drought (SD) events globally from 1981 to 2020. A novel categorization framework was proposed to subdivide the two basic drought categories into eight distinct drought types using a set relationship identification method. The results showed fluctuating trends in the frequencies of Independent FD and Inclusion FD, which declined rapidly after 2011 at rates of 0.05 and 0.04 times/year, respectively. Independent FD frequency was highest in humid areas and decreased with increasing aridity. The spatial distributions of Inclusion FD and SD were similar, with both frequencies highest in extremely arid areas and decreasing with increasing humidity. The frequency of Independent SD, which peaked in semi-arid areas, increased significantly after 2011 at a rate of 0.01 times/year. The occurrence of FD evolving into SD or emerging at the end of SD was rare, with a global average of 0.46 events/decade and little spatial variation. Between 1981 and 2020, FD showed a U-shaped trend in drought duration, while SD showed no clear pattern. The duration of FD showed little difference across arid and humid zones, but the duration of SD decreased significantly with increasing humidity. Vegetation responses to drought varied, with arid regions showing longer response time compared to humid regions. A positive correlation between temperature and solar-induced chlorophyll fluorescence (SIF) during droughts was observed, while precipitation generally showed a negative correlation with SIF. Radiation had a minimal effect on SIF during droughts. The study offered a comprehensive categorization of drought events, enhancing our understanding of their spatiotemporal characteristics and vegetation responses on a global scale.

Identifying critical regions for nitrogen and phosphorus loss management in a large-scale complex basin: The Jialing River.

The determination of critical management areas for nitrogen (N) and phosphorus (P) losses in large-scale basins is critical to reduce costs and improve efficiency. In this study, the spatial and temporal characteristics of the N and P losses in the Jialing River from 2000 to 2019 were calculated based on the Soil and Water Assessment Tool (SWAT) model. The trends were analyzed using the Theil-Sen median analysis and Mann-Kendall test. The Getis-Ord Gi* was used to determine significant coldspot and hotspot regions to identify critical regions and priorities for regional management. The ranges of the annual average unit load losses for N and P in the Jialing River were 1.21-54.53 kg ha-1 and 0.05-1.35 kg ha-1, respectively. The interannual variations in both N and P losses showed decreasing trends, with change rates of 0.327 and 0.003 kg ha-1·a-1 and change magnitudes of 50.96% and 41.05%, respectively. N and P losses were highest in the summer and lowest in the winter. The coldspot regions for N loss were clustered northwest of the upstream Jialing River and north of Fujiang River. The coldspot regions for P loss were clustered in the central, western, and northern areas of the upstream Jialing River. The above regions were found to be not critical for management. The hotspot regions for N loss were clustered in the south of the upstream Jialing River, the central-western and southern areas of the Fujiang River, and the central area of the Qujiang River. The hotspot regions for P loss were clustered in the south-central area of the upstream Jialing River, the southern and northern areas of the middle and downstream Jialing River, the western and southern areas of the Fujiang River, and the southern area of the Qujiang River. The above regions were found to be critical for management. There was a significant difference between the high load area for N and the hotspot regions, while the high load region for P was consistent with the hotspot regions. The coldspot and hotspot regions for N would change locally in spring and winter, and the coldspot and hotspot regions for P would change locally in summer and winter, respectively. Therefore, managers should make specific adjustments in critical regions for different pollutants according to seasonal characteristics when developing management programs.

Large-scale sediment and phosphorus transport in the Three Gorges Reservoir based on a new reservoir operation method.

Change of hydrodynamic conditions is a key factor inducing sedimentation, water eutrophication and algal blooms in the Three Gorges Reservoir (TGR). How to mitigate sedimentation and phosphorus (P) retention by improving hydrodynamic conditions in the Three Gorges Reservoir area (TGRA) is an urgent issue in the study of sediment and water environment. In this study, a Hydrodynamic-Sediment-Water quality model for the whole TGRA is proposed considering sediment and P inputs from numerous tributaries, and a new reservoir operation method namely the tide-type operation method (TTOM) is used to investigate the large-scale sediment and P transport in the TGR based on the model. Results indicate that the TTOM can reduce sedimentation and total phosphorus (TP) retention in the TGR. Compared with the actual operation method (AOM), sediment outflow and sediment export ratio (Eratio) of the TGR increased about 17.13% and 1%-3% in 2015-2017, and sedimentation decreased about 3% under the TTOM. TP retention flux and retention rate (RE) decreased about 13.77% and 2%-4%. The flow velocity (V) and sediment carrying capacity (S*) increased about 40% in the local reach. Larger daily water level fluctuation at dam site is more conducive to reducing sedimentation and TP retention in the TGR. Sediment inputs from the Yangtze River, Jialing River, Wu River and other tributaries account for 59.27%, 11.21%, 3.81% and 25.70% of the total sediment inflow during 2015-2017, and TP inputs were 65.96%, 10.01%, 17.40% and 6.63%. In the paper, an innovative method is proposed to reduce sedimentation and P retention in the TGR under the given hydrodynamic conditions and related quantitative contribution driven by the proposed method is analyzed. The work is favorable for expanding the understanding of the hydrodynamic and nutrition flux changes in the TGR, and provides a new perspective for water environment protection and reasonable operation of large reservoirs.

Synergistic effect of organic matter-floc size-bound water and multifactorial quantitative model of optimal reagent demand in sewage sludge conditioning process prior to dewatering.

The high amount of densely hydrated organic substance present in sewage sludge impedes its filterability, thus restricting sludge disposal. Although chemical conditioning can facilitate filtration, the diverse sludge properties complicate the quantitative control of conditioning process. Investigating how to accurately quantify the optimal reagent demand (ORD) based on the critical physicochemical properties of the target sludge is an effective way to address the current issue. This study focused on the sewage and stockpiled sludge with varying properties, and their ORD under different chemical conditioning. The results showed that organic content, floc size, and bound water synergistically influenced conditioning process. The quantitative models were established between their coupling indicators and ORD, with coupling indicators including the ratio of organic content to floc size, the ratio of flow viscosity to floc size, and the ratio of the product of organic content and bound water to floc size. The linear correlation of the coupling indicator with ORD was higher than that of the traditional single-factor indicator. Furthermore, the inherent filterability of the sludge was somewhat separate from the adjustability of its filtration. A "dual-system" impact model was proposed to characterized the conditioning and filtration processes. These results provide theoretical guidance for the quantitative regulation of conditioning and filtration processes of sludge with complex characteristics.