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Rapid development of urbanization and intense human activities had a profound influence on the ecosystem service functions. As an integrated monetary index for the evaluation of final ecosystem services, the gross ecosystem product (GEP) is widely used in the quantification of ecosystem service value (ESV). This study initially assessed and analyzed the spatial distribution of the GEP at the county-level scale using multisource data spanning 2000, 2005, 2010, 2015, and 2020. Then, the spatial transfer characteristics of the GEP were measured. Finally, the study employed spatial panel econometric models and the geographically weighted regression (GWR) model to investigate the spatial effect of urbanization and ecological construction on the GEP. The results indicated that: (1) In 2020, the GEP in the Yangtze River Delta Region was RMB 15.24 trillion, and the GEP per unit area was RMB 42.58 million per square kilometer. It exhibited a cumulative decrease of RMB 298.72 billion from 2000 to 2020. (2) The spatial transfer efficiency of the GEP in urban agglomerations showed a clear decline trend. During the period of 2000–2020, over 96% of county-level units exhibited a decline with RMB 90,076,103.17/km2, indicating a consistent downward trend from the central regions towards the periphery. (3) Based on the decomposition effects of the spatial Durbin mode, urbanization and the ecological construction indicator showed spatial spillover effects on the GEP, but their impact mechanisms varied substantially. Among them, the urbanization rate (UR), population density (PD), and the proportion of impervious land (ILP) had the largest negative effect on the GEP, and a 1% rise in ILP locally resulted in a 0.044% decline in the local GEP and a 0.078% rise in the GEP of neighboring units. And the area of ecological land had a positive effect on the GEP of both local and neighboring areas. Those conclusions can offer evidence in favor of encouraging ecologically responsible building practices and sustainable growth in urban agglomerations.

The optimization of the ecological network structure in Nanping can provide a scientific reference for guaranteeing ecological safety in Southeast China. This study estimated ecosystem services in Nanping with the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model based on land-use data from 2020 to 2025 simulated with the CLUE-S model under the natural development scenario and ecological protection scenario and then explored their trade-offs and synergies. The ecological network structure was, thereafter, optimized in terms of the eco-matrix, eco-corridors and nodes based on simulated land use and ecosystem services. The results suggested that the average habitat quality and total soil retention increased, while the average degradation index and total water yield decreased under the ecological protection scenario, indicating that the ecological environment quality tended to be improved. In addition, soil retention had significant synergies with habitat quality and water yield, and habitat quality had significant trade-offs with ecological degradation and water yield on the regional scale under two scenarios, while ecological degradation also showed significant trade-offs with soil retention and water yield. In addition, the results suggested that 11 additional ecological sources could be added, and the number of eco-corridors increased from 15 to 136; a total of 1019 ecological break points were restored, and 1481 stepping stone patches were deployed, which jointly made network circuitry, edge/node ratio and network connectivity reach 0.45, 1.86 and 0.64, respectively, indicating that optimization could effectively improve the structure and connectivity of the ecological network. These findings can provide a theoretical basis for improving the ecological network structure and ecological service functions in Nanping and other regions.

Northwest China is significantly affected by sandstorm disasters. To mitigate the negative impacts of sandstorm events, it is critical to understand the spatio-temporal variations in typical sand and dust storms and their influencing factors. In this work, using ground-based measurements of particulate matter and remote sensing data such as MODIS, OMI, and CALIPSO data, the sources of aerosol pollution and aerosol optical properties of a typical sandstorm event that occurred in Northwest China in 2018 was studied. In addition, the HYSPLIT model was used to explore the air mass trajectories in order to analyze the sand and dust migration process during the sandstorm event. Furthermore, the wind erosion sensitivity of Northwest China was analyzed via single factor analysis and multi-factor superposition of wind field intensity, soil drought index, vegetation coverage, and relief amplitude. Finally, the region of the study area having a high comprehensive wind erosion sensitivity was identified. The results showed that the PM10 concentrations exceeded 400 µg/m3 and the PM2.5/PM10 ratio did not exceeded 0.6 during the sandstorm event, indicating that natural particulate matter was dominant in the ambient air. At the epicenter of pollution, the aerosol optical depth (AOD) at 550 nm was 0.75–1. By combining AOD data with wind speed and direction data from field observation stations, it was found that the sandstorm event in 2018 mainly occurred between 1 April and 3 April, and affected all of Northwest China on 2 April and 3 April. The absorbed aerosol index (AAI) ranged between 2.5 and 4, indicating that the Taklimakan Desert was the main source of sandstorm events in Northwest China. The CALIPSO total attenuated backscatter coefficient at 532 nm indicated that the main component of tropospheric aerosol in this region was distributed in the range of 0–12.5 km. The simulated airflow track showed that it had the same dust source regions as AAI index studies. Moreover, investigation of wind erosion sensitivity in the study areas indicated that the Taklimakan Desert and other desert regions were the main ecologically sensitive areas. These conclusions can provide references and suggestions for the mitigation of damage caused by sandstorm events, in addition to the enhancement of ecological governance.

Some essential water conservation areas in China have continuously suffered from various serious problems such as water pollution and water quality deterioration in recent decades and thus called for real-time water pollution monitoring system underwater resources management. On the basis of the remote sensing data and ground monitoring data, this study firstly constructed a more accurate retrieval model for total phosphorus (TP) concentration by comparing 12 machine learning algorithms, including support vector machine (SVM), artificial neural network (ANN), Bayesian ridge regression (BRR), lasso regression (Lasso), elastic net (EN), linear regression (LR), decision tree regressor (DTR), K neighbor regressor (KNR), random forest regressor (RFR), extra trees regressor (ETR), AdaBoost regressor (ABR) and gradient boosting regressor (GBR). Then, this study applied the constructed retrieval model to explore the spatial-temporal evolution of the Miyun Reservoir and finally assessed the water quality. The results showed that the model of TP concentration built by the ETR algorithm had the best accuracy, with the coefficient R2 reaching over 85% and the mean absolute error lower than 0.000433. The TP concentration in Miyun Reservoir was between 0.0380 and 0.1298 mg/L, and there was relatively significant spatial and temporal heterogeneity. It changed remarkably during the periods of the flood season, winter tillage, planting, and regreening, and it was lower in summer than in other seasons. Moreover, the TP in the southwest part of the reservoir was generally lower than in the northeast, as there was less human activities interference. According to the Environmental Quality Standard for the surface water environment, the water quality of Miyun Reservoir was overall safe, except only for an over-standard case occurrence in the spring and September. These conclusions can provide a significant scientific reference for water quality monitoring and management in Miyun Reservoir.

Net Primary Productivity (NPP) is one of the significant indicators to measure environmental changes; thus, the relevant study of NPP in Northeast China, Asia, is essential to climate changes and ecological sustainable development. Based on the Global Production Efficiency (GLO-PEM) model, this study firstly estimated the NPP in Northeast China, from 2001 to 2019, and then analyzed its spatio-temporal evolution, future changing trend and phenology regularity. Over the years, the NPP of different forests type in Northeast China showed a gradual increasing trend. Compared with other different time stages, the high-value NPP (700–1300 gC·m−2·a−1) in Changbai Mountain, from 2017 to 2019, is more widely distributed. For instance, the NPP has an increasing rate of 6.92% compared to the stage of 2011–2015. Additionally, there was a significant advance at the start of the vegetation growth season (SOS), and a lag at the end of the vegetation growth season (EOS), from 2001 to 2019. Thus, the whole growth period of forests in Northeast China became prolonged with the change of phenology. Moreover, analysis on the sustainability of NPP in the future indicates that the reverse direction feature of NPP change will be slightly stronger than the co-directional feature, meaning that about 30.68% of the study area will switch from improvement to degradation. To conclude, these above studies could provide an important reference for the sustainable development of forests in Northeast China.

The increasing scale of urbanization and human activities has resulted in the fragmentation of natural habitats, leading to the reduction of ecological landscape connectivity and biodiversity. Taking Nanping as the study area, the core areas with good connectivity were extracted as ecological sources using a morphological spatial pattern analysis (MSPA) and landscape connectivity index. Then the ecosystem service functions of the ecological sources were evaluated based on the InVEST model. Finally, we extracted the potential ecological corridor based on the land type, elevation and ecosystem service functions. The results showed that the ecological source with higher landscape connectivity is distributed in the north and there are clear landscape connectivity faults in the northern and southern regions. Moreover, the areas with high habitat quality, soil retention and water production are mainly distributed in the northern ecological source areas. The 15 potential ecological corridors extracted were distributed unevenly. Among them, the important ecological corridors formed a triangle network, while the general ecological corridors were concentrated in the northwest. Therefore, it is suggested that the important core patches in the north be protected, and the effective connection between the north and south be improved. These results can provide a scientific basis for ecological construction and hierarchical management of the ecological networks.

Forestland dynamics can affect the ecological security of a country and even the global environment, and therefore it is of great practical significance to understand the characteristics of temporal and spatial variations of forestland. Taking Jiangxi Province as the study area, this study first explored the driving mechanism of the natural environment and social economy on deforestation and afforestation using a simultaneous equation model. The results indicate that population size, topographic and geomorphologic factors, climate, and location play leading roles in influencing forestland density fluctuations. Specifically, the population size, economic development level, gross value of forestry production, climate conditions, and government policies are key influencing factors of afforestation. Deforestation is mainly influenced by agricultural population, non-agricultural economy, forestry production, forestry density, location, transportation, and climate. In addition, this study simulated the spatial distribution of land use and analyzed the spatial characteristics and variation trends of forestland area and quality under the Representative Concentration Pathways (RCPs) climate scenarios from 2010 to 2030 using the Conversion of Land Use and its Effects (CLUE) model. The results indicate that forestland declines under the Asia-Pacific integrated model (AIM) climate scenario. The environment tends to be heavily damaged under this kind of scenarios, and measures should be taken in order to protect the environment. Although the model for energy supply strategy alternatives and their general environmental impact (MESSAGE) scenario is to some extent better than the AIM scenario, destruction of the environment will still occur, and it is necessary to restrain deforestation and convert shrub land into forestland or garden land. These results can provide significant information for environmental protection, forest resource exploitation, and utilization in the areas experiencing deforestation and afforestation.

Guishui River Basin in northwestern Beijing has ecological significance and will be one of the venues of the upcoming Beijing Winter Olympic Games in 2022. However, accelerating climate change and human disturbance in recent decades has posed an increasing challenge to the sustainable use of water in the basin. This study simulated the runoff of the Guishui River Basin using the Soil and Water Assessment Tool (SWAT) model to reveal the spatio-temporal variations of runoff in the basin and the impacts of climate change and human activities on the runoff changes. The results showed that annual runoff from 2004 to 2018 was relatively small, with an uneven intra-annual runoff distribution. The seasonal trends in runoff showed a decreasing trend in spring and winter while an increasing trend in summer and autumn. There was a first increasing and then decreasing trend of average annual runoff depth from northwest to southeast in the study area. In addition, the contributions of climate change and human activities to changes in runoff of the Guishui River Basin were 60% and 40%, respectively, but with opposite effects. The results can contribute to the rational utilization of water resources in the Guishui River Basin.

It is of great practical significance to construct a water-based ecological network in arid and semi-arid areas. The spatial distribution of water resources is one of the most important factors in determining the ecological stability of such areas. In this study, groundwater level trends were analyzed with a model called Empirical Mode Decomposition (EMD). The temporal and spatial evolution of groundwater depth data from 1990 to 2016 were analyzed. The surface water bodies were analyzed using a point pattern analysis method. Based on this, a water-based ecological network was constructed with a minimum cumulative resistance surface model. The study indicated that the trend lines for the groundwater tables of 17 wells could be divided into five types in Denko County. The landscape types that changed from a desert landscape to an oasis landscape had a positive impact on groundwater. Precipitation trend was related to the spatial distribution of the groundwater depth, and the spatial pattern of the water nodes was characterized by a small-scale highly aggregated distribution and a large-scale uniform distribution in Denko County. These results suggest that for the stability of arid and semi-arid ecological environments, the appropriate human intervention (such as construction of an artificial oasis) is of great significance. Based on the analysis of groundwater and surface water bodies, a water-based ecological network in Denko County, which consisted of 391 ecological sources and 7360 ecological corridors, was constructed in 2016. The water-based ecological network constructed in this study was more sustainable and stable, and also suitable for arid and semi-arid areas, which is of great practical significance and application value.