Wind erosion is one of the most calamity weather phenomenon in loess hilly-gully area of Hebei Province,it often occurs in winter or spring.Recently,sand-dust phenomenon happened frequently in hilly-gully area,which produced enormous effect on the production and development of the people in Beijing,Hebei and Tianjin area.According to the relational information,eighty percent sandstorm of Bejing comes from Zhangjiakou hilly-gully area.In order to improve the environment,through the analysis of test observation data,which were based on five different underlying surfaces in hilly-gully area,we studied the influenced factors,then put forward the control technology measures of soil wind erosion of farmlands in loess hilly-gully area of Hebei Province.
The 2030 agenda of the United Nations provides a framework of 17 Sustainable Development Goals (SDGs) and 232 indicators for its members to fulfill. The overall achievement critically depends on how nations understand the interactions between these SDGs and set priorities for development pathways. This study provides a comprehensive network analysis of global SDG complementarities, measured by the co-occurrences of comparative advantages in the same region. We construct the ‘SDG space’ at goal and indicator levels with the most recently available data and then validate its robustness by comparing it to the commonly used correlation network and confirm its predictive power using historical data. Network analysis reveals a strongly connected socioeconomic-related core and an environmental-related periphery, with ‘bridge’ indicators connecting different clusters. The goal-level space identifies the ‘bridge’ goals as SDG 17 (Partnerships for the Goals), SDG 8 (Decent Work and Economic Growth), SDG 15 (Life on Hand) in the environmental-related cluster, while identifying SDG 7 (Affordable and Clean Energy), SDG 6 (Clean water and Sanitation), and SDG 16 (Justice and Strong Institutions) in the socioeconomic cluster. The indicator-level space provides details to explain how they act as ‘bridges’ in the network. In particular, 16-9: Free Press Index is the ‘bridge’ indicator with the highest betweenness centrality value and acts as the bottleneck indicator in China for its overall sustainable development. Improving it can enhance connected indicators’ performance, leading to positive cascading effects on different aspects of sustainability.
Abstract Extensive efforts have been dedicated to deciphering the interactions associated with Sustainable Development Goals (SDGs). However, these developments are hampered by a lack of efficient strategies to avoid beneficial synergies being offset by harmful trade-offs. To fill these gaps, we used causal diagnosis and network analysis methods to construct 1302 directed networks of SDGs for 31 provinces in China from 2000 to 2020. We observed a dramatic offsetting effect of SDG synergies and trade-offs in China from 2000 to 2020, with approximately 27% of trade-off indicator pairs turning into synergies and about 25% of the synergy indicator pairs turning into trade-offs. However, our findings suggested that prioritising the progress of high-frequency indicators in virtuous cycles could multiply the positive systemic effects of the SDGs. Moreover, controlling the transition from passive to active in the trade-off network of SDGs remains a challenge in advancing the SDGs holistically.
Blue carbon is the carbon storage in vegetated coastal ecosystems such as mangroves, salt marshes, and seagrass. It is gaining global attention as its role in climate change mitigation and local welfare growth. However, a global assessment on the long-term spatiotemporal sustainable development status of blue carbon has not been conducted, and the relations among blue carbon ecosystems, driving forces for climate change mitigation, and socioeconomic interventions for development capacity on a global scale are still unclear. Here, we constructed a blue carbon development index (BCDI), comprising three subsystems: driving force, resource endowment, and development capacity, to assess the sustainable development level of 136 coastal countries' blue carbon over 24 consecutive years and explore the relationship among subsystems. We further propose a cooperation model to explore the feasibility of global blue carbon cooperation and quantify benefit allocation to specific countries. The results showed an upward trend in BCDI scores with variations in regional performance over the past two decades, and we found a positive correlation between development capacity and blue carbon resource endowment. Based on the scenario simulations of global cooperation, we found that coastal countries could improve the global average BCDI score, add 2.96 Mt of annual carbon sequestration, and generate $136.34 million in 2030 under Global Deep Cooperation scenario compared with the Business-As-Usual scenario.
Coastal urbanization is a key driver of mangrove loss, yet its global impacts on mangroves have yet to be thoroughly understood. Here we present a fine-scale assessment of the hidden impacts of urbanization on mangroves mediated by climate, and the joint effects of urbanization and climate at the global scale. Surprisingly, both urbanization and climate had positive impacts on mangrove growth and carbon stock in some regions, which is different from the general belief of the adverse impacts from previous research. In total, 27.3% of global mangroves received positive impacts from urbanization regarding their extent and carbon stock, among which 59.5% are indirectly mediated by climate. Moreover, mangroves in subtropical/temperate climate zones experienced more indirect positive impacts from urbanization, which enhances local climate conditions for growth by altering temperature, rainfall and sea levels. These findings suggest the feasibility of facilitating mangrove conservation through effective urban planning to achieve coastal sustainability. Mangroves may indirectly benefit from coastal urbanization in some areas due to more favorable local climatic conditions for growth, according to modeling of urbanization, climate, and mangrove growth causal relationships.
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