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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.

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.

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.

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.

With the rising pressure due to energy consumption and costs of environmental protection and recovery, industrial transfer from the eastern to central and western areas has surged in China. However, extremely fragile ecological conditions and severe water shortage are significant hurdles for industry development in Western China. Whether the vulnerable environment can bear the pollution caused by the transferred industry from Eastern China becomes a significant issue. This study firstly estimates energy and environmental costs in different areas of China, and assesses the necessity to upgrade the industrial structure of Qinghai Province. Then the emissions of waste water, waste gas, and smoke caused by transferred industries are calculated by Input-Output Model. On the basis of the effect analysis of waste emission on environment, pollution risks of Qinghai province are assessed. The results illustrate that the costs of environmental protection and recovery in China have a gradient distribution, of which the energy efficiency is lower while environmental costs are higher in Western China. Industrial structure adjustment has different impacts on the pollution of different sectors. Although the development of machinery and equipment, hotels and catering services, and real estate, leasing, and business services has increased the emission of pollutants, it is offset by the decreasing emissions caused by other industries such as construction and metal products. Therefore, although economic development will increase environmental pollution, industrial adjustments can effectively decrease waste water and waste gas emissions to reduce the pollution risk. It should be noted that there are still tremendous challenges for industrial transfer in Qinghai Province to coordinate the environment and industry development.

Food safety and its related influencing factors in China are the hot research topics currently, and cultivated land conversion is one of the significant factors influencing food safety in China. Taking the North China Plain as the study area, this paper examines the changes of cultivated land area using satellite images, estimates land productivity from 1985 to 2005 using the model of Estimation System for Land Productivity (ESLP), and analyzes the impact of cultivated land conversion on the land production. Compared with the grain yield data from statistical yearbooks, the results indicate that ESLP model is an effective tool for estimating land productivity. Land productivity in the North China Plain showed a slight decreasing trend from 1985 to 2005, spatially, increased from the north to the south gradu- ally, and the net changes varied in different areas. Cultivated land area recorded a marginal decrease of 8.0 × 10 5 ha, mainly converted to other land uses. Cultivated land conversion had more significant negative impacts on land produc- tion than land productivity did. Land production decreased by about 6.48 × 10 6 t caused by cultivated land conversion between 1985 and 2005, accounting for 91.9% of the total land production reduction. Although the land productivity increased in Anhui and Jiangsu provinces, it can not offset the overall adverse effects caused by cultivated land con- version. Therefore, there are significant meanings to control the cultivated land conversion and improve the land pro- ductivity for ensuring the land production in the North China Plain.

With the economic development and population growth, humans have changed ecosystems more rapidly and extensively to meet the rapidly growing demand for food, fresh water, timber, fiber and fuel. This has led to a substantial and largely irreversible loss of the biodiversity on earth. The ecosystem risk is created as a new concept to understand the environmental problems. Therefore, it is important to develop quantitative methods for regional ecosystem risk analysis. Yellow River Delta is the widest, most intact and youngest delta both in China and in the world; its ecosystem environment is much more vulnerable due to its special location and industrial structure. Therefore, it is very important to manage them wisely and strategically. Therefore, Yellow River Delta is selected as the case area to reveal the impacts of economic development on ecosystem risk in this study. This study selected the ecological quality index to show the potential ecosystem risk and estimated the impacts of economic development on ecosystem risk using the panel data model on the pixel level based on the GIS, RS technique. It's found that the economic development will have impacts on the ecological environment to a certain degree, however, these impacts can exchange to a greater degree with the development. Then more funds and advanced technologies can be used to promote the intensive development of land use, which may decrease the impacts of economic development on the environment. Therefore, we need to ensure the coordinated development of the economy and ecological environment. The research results provide meaningful decision-making information for the urbanization process and environmental protection in the Yellow River Delta.

Based on field survey and statistical analysis, the immediate impacts of the Wenchuan Earthquake happened on May 12, 2008, are evaluated from two aspects, i.e., the influence on the prices and yields of grain and pork products in the local region and that on China. Wenchuan Earthquake, undoubtedly, has some negative effects on the local agricultural yields in Sichuan Province. It has caused immediate impacts on the grain and livestock breeding industry in the earthquake worst-hit counties. For example, due to the earthquake, the grain yields in Sichuan Province will decreased more than 0.4% and the pork productions decrease 5% at least. Thus, prices of grain and pork products are likely to rise in local mountainous areas over a short term. Our studying results that the disaster rate, the hazard rate and the complete loss rate of grain productions are 18%, 10% and 6% respectively in the earthquake worst-hit counties, while the disaster rate in the eastern plain areas even reach to 30%-49%. Even so, the results of model analysis for sample survey indicates that Wenchuan Earthquake has caused only marginal impacts on agricultural production, does not heavily hurt the stability of the prices and yields of grain and pork products at the national level. In other words,Wenchuan Earthquake had not affected the overall situation of national agricultural production. It is estimated that the reduction rate of national grain yield is as low as 0.006%, and the price changes of grain and pork products are no more than 0.5% and 2.2% respectively.

The purpose of this study is to examine the conversions of forests in Northeast China during 1988-2005 by using a 1-km area percentage data model (1-km APDM) with remote sensing data and to find the spatiotemporal characteristics of land conversions between forests and other land uses/covers and internal conversions between forest cover types. Data were derived from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) images of bands 3, 5, and 4 acquired in 1988, 1995, 2000, and 2005. Research results show that in the period between 1988 and 2005, the forest area in Northeast China underwent dramatic changes, and 4.11 million ha of forest area was aggregately lost because of the conversions of forests to other land uses/covers; at the same time, the forest area also gained 2.00 million ha because of the conversions from other land uses/covers to forests. The results also demonstrate the forest degradation resulting from the conversions between different forest cover types. This research demonstrates the feasibility and importance of using the 1-km APDM at a finer resolution to trace the spatiotemporal patterns of the forest conversions.