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The recent surge in dam construction has sparked debates regarding their contribution to carbon neutrality and food security, focusing on trade-offs between production benefits and ecological drawbacks. However, how dams affect carbon emissions and land cover changes, including their spatial differentiations, remains unclear. We quantified spatiotemporal variations in carbon emissions and storage of 137 large dams in China from 1992 to 2020, resulting from land cover change in potentially affected areas. We observed a lesser increase in carbon emissions and a more pronounced increase in carbon storage driven by forest conservation and regeneration within dam-affected areas compared to unaffected areas. Additionally, we noticed an increased grain yield in nearby areas potentially due to increased water availability. Our findings highlight the importance of considering land cover change when assessing carbon neutrality or grain yield at regional and national scales. This study provides useful insights into optimizing dam locations to mitigate future carbon emissions effectively.
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Accelerating efforts for the Sustainable Development Goals requires understanding their synergies and trade-offs at the national and sub-national levels, which will help identify the key hurdles and opportunities to prioritize them in an indivisible manner for a country. Here, we present the importance of the 17 goals through synergy and trade-off networks. Our results reveal that 19 provinces show the highest trade-offs in SDG13 (Combating Climate Change) or SDG5 (Gender Equality) consistent with the national level, with other 12 provinces varying. 24 provinces show the highest synergies in SDG1 (No Poverty) or SDG6 (Clean Water and Sanitation) consistent with the national level, with the remaining 7 provinces varying. These common but differentiated SDG priorities reflect that to ensure a coordinated national response, China should pay more attention to the provincial situation, so that provincial governments can formulate more targeted policies in line with their own priorities towards accelerating sustainable development.
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Políticas , Desenvolvimento Sustentável , China , Pobreza , Mudança ClimáticaRESUMO
Domestic attempts to advance the Sustainable Development Goals (SDGs) in a country can have synergistic and/or trade-off effects on the advancement of SDGs in other countries. Transboundary SDG interactions can be delivered through various transmission channels (e.g., trade, river flow, ocean currents, and air flow). This study quantified the transboundary interactions through these channels between 768 pairs of SDG indicators. The results showed that although high income countries only comprised 14.18% of the global population, they contributed considerably to total SDG interactions worldwide (60.60%). Transboundary synergistic effects via international trade were 14.94% more pronounced with trade partners outside their immediate geographic vicinity than with neighbouring ones. Conversely, nature-caused flows (including river flow, ocean currents, and air flow) resulted in 39.29% stronger transboundary synergistic effects among neighboring countries compared to non-neighboring ones. To facilitate the achievement of SDGs worldwide, it is essential to enhance collaboration among countries and leverage transboundary synergies.
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The coastal zone is typically highly developed and its ocean environment is vastly exposed to the onshore activities. Land-based pollution, as the "metabolite" of terrestrial human activities, significantly impacts the ocean environment. Although numerous studies have investigated these effects, few have quantified the interactions among land-human activity-ocean across both spatial and temporal scales. In this study, we have developed a land-human activity-ocean systemic framework integrating the coupling coordination degree model and tipping point to quantify the spatiotemporal dynamic interaction mechanism among the land-based pollution, human activities, and ocean environment in China from 2001 to 2020. Our findings revealed that the overall coupling coordination degree of the China's coastal zone increased by 36.9 % over last two decades. Furthermore, the effect of human activities on China's coastal environment remained within acceptable thresholds, as no universal tipping points for coastal pollution or ocean environment has been found over the 20-year period. Notably, the lag time for algal blooms, the key indicator of ocean environment health, was found to be 0-3 years in response to the land economic development and 0-4 years in response to land-based pollution. Based on the differences in spatiotemporal interactions among land-human activity-ocean system, we employed cluster analysis to categorize China's coastal provinces into four types and to develop appropriate management measures. Quantifying the interaction mechanism within the land-human activity-ocean system could aid decision-makers in creating sustainable coastal development strategies. This enables efficient use of land and ocean resources, supports coastal conservation and restoration efforts, and fosters effective management recommendations to enhance coastal sustainability and resilience.
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Conservação dos Recursos Naturais , Ecossistema , Humanos , Poluição Ambiental , China , Oceanos e MaresRESUMO
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 SDG pairs' comparative advantages in the same region by adopting the 'product space' concept from economics. 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), and 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.
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Saúde Global , Desenvolvimento Sustentável , Desenvolvimento Econômico , China , ÁguaRESUMO
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.
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Unraveling the complexity of the 17 interacting sustainable development goals (SDGs) is crucial for their achievement. Empirically revealing the dimensions of the SDGs helps generalize the dominant features of SDGs and better understand their drivers. Here, using a database of 166 countries' progress toward achieving each individual SDG, we found that about 70% of the variability of national SDG performance can be captured by three dimensions: socioeconomic development at the expense of resource and climate, the environment, and development at the expense of equality. Moreover, these dimensions are mainly affected by the economy; as gross domestic product (GDP) per capita increases, the first dimension increases monotonically, the environment dimension decreases and then increases, and the inequality dimension increases and then decreases. Our findings indicate a dim prospect of eventually achieving all SDGs because of the conflicts between economic growth and resource and climate goals under the current development paradigm, highlighting the importance of sustainable transformation.
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At the mid-point to 2030, progress towards achieving the Sustainable Development Goals (SDGs) varies significantly across countries. While the classification of countries can lay the foundation for improving policy efficiency and promoting joint action, bottom-up, SDG data-driven country classifications have largely remained unexplored. Here, we classified 166 countries based on their performances in the 17 SDGs and further used the classification to analyze SDG interactions and compare development aid distributions. The countries were classified into five groups, ranging from "lowest development with good environment" to "high development needing climate action". None of them scored highly in all SDGs, and due to trade-offs related to environment and climate SDGs, none of them can achieve all SDGs eventually. To maximize the potential for achieving the SDGs, all countries need to undergo a sustainable transformation, and prioritizing certain SDGs, such as SDG 9 (industry, innovation and infrastructure), can help countries with lower sustainable development levels achieve more with less. Furthermore, global development aid should be better aligned with country needs, particularly in areas of education, energy, environment, and water supply and sanitation. By better characterizing different countries, this study reveals the bleak prospects of achieving all SDGs and provides valuable insights into more targeted actions for national sustainable development and global collaboration.
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Achieving sustainability and coping with climate change are the greatest challenges to human survival and harmonious human-nature relationship. However, there is a lack of research on quantifying the resilience of sustainability to climate change over space and time. Here, a quantification method was developed to evaluate resilient performance of sustainability (includes economic, social, and environmental sub-resilient performance and resilient performance index) to climate change, and performed the first demonstration in China's 280 cities. It was found that resilient performance index of China's sustainability to climate change improved from 2005 to 2017, especially in Southwest China, but 6.8 % of cities showed a decreasing trend. With the improvement of the resilient performance index, the synergy degree among economic, social, and environmental sub-resilient performance scores increased. Economic development and sustainability improvement related to a higher but more disparity of the resilient performance index. This study encourages researchers and policymakers worldwide to focus on resilience of sustainability to climate change to help achieve sustained development and prosperity under climate change.
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The Intelligent Earth (iEarth) framework, composed of four major themes: iEarth data, science, analytics, and decision, is proposed to define and build an interdisciplinary and synergistic framework for research, practice, and education that simultaneously safeguards the sustainable development of our living planet.
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Sustainable development goals (SDGs) in the United Nations 2030 Agenda call for action by all nations to promote economic prosperity while protecting the planet. Projection of future land-use change under SDG scenarios is a new attempt to scientifically achieve the SDGs. Herein, we proposed four scenario assumptions based on the SDGs, including the sustainable economy (ECO), sustainable grain (GRA), sustainable environment (ENV), and reference (REF) scenarios. We forecasted land-use change along the Silk Road (resolution: 300 m) and compared the impacts of urban expansion and forest conversion on terrestrial carbon pools. There were significant differences in future land use change and carbon stocks, under the four SDG scenarios, by 2030. In the ENV scenario, the trend of decreasing forest land was mitigated, and forest carbon stocks in China increased by approximately 0.60% compared to 2020. In the GRA scenario, the decreasing rate of cultivated land area has slowed down. Cultivated land area in South and Southeast Asia only shows an increasing trend in the GRA scenario, while it shows a decreasing trend in other SDG scenarios. The ECO scenario showed highest carbon losses associated with increased urban expansion. The study enhances our understanding of how SDGs can contribute to mitigate future environmental degradation via accurate simulations that can be applied on a global scale.
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Payments for ecosystem services (PES) are becoming a global ecological protection strategy used to promote sustainable social and economic development. However, the current PES research and applications are often local and one-sided. The lack of a unified framework for PES results in a high policy cost and low ecological and social benefits. A large number of local PES experiences need to be comprehensively analyzed to construct a unified PES framework, which can provide support for the implementation and optimization of nature conservation policy in different regions of the world. Here, we combined natural language processing methods to analyze 1919 global studies on PES. We obtained the topics and spatiotemporal distributions of PES, as well as the compensation modes of hotspot ecosystem services in 114 countries worldwide. PES have been studied in 80% of the world (excluding Antarctica), but the research topics and distributions are very uneven. We found a disconnection between PES socioeconomic strategies and knowledge of natural ecosystem dynamics. Therefore, the knowledge and experience of PES must be exchanged globally, and PES need to be further integrated with the sustainable development goal (SDG) framework. We propose a PES framework that couples socioeconomic and ecosystem dynamics and be oriented toward sustainable development to make comprehensive management decisions. On this basis, a consistent PES solution may be provided for future theoretical research and implementation strategies of conservation.
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Ecossistema , Desenvolvimento Sustentável , Conservação dos Recursos Naturais/métodos , Fatores Socioeconômicos , Regiões Antárticas , ChinaRESUMO
The global outbreak of the coronavirus disease 2019 (COVID-19) has strongly affected human lives. The restrictions taken to slow down the spread of the virus impact socio-economic activities and the environment. A comprehensive review of these COVID-19 impacts on the ocean-human system is lacking. The current study fills this gap by synthesizing the environmental and socio-economic effects of the COVID-19 pandemic on the global ocean by conducting a systemic scoping review of 92 published articles. From a geospatial perspective, the studies covered a total of 37 countries, mainly from Asia, Europe, and North America, with a particular focus on the Indian Ocean and the Mediterranean Sea. From an environmental perspective, both positive and negative effects on global oceans were summarized. Notably, improved coastal water quality and reduced underwater noise were reported. On the other hand, the increasing COVID-19-related medical waste such as personal protective equipment leads to severe pollution, which threatens the marine ecosystem and wildlife. From a socioeconomic perspective, the impacts of the pandemic were negative throughout with marine tourism and the fishery industry being severely disrupted. Coastal communities suffered from loss of income, unemployment, inequalities and health problems. The COVID-19 pandemic offers an opportunity for transformation of management and economic practices in order to save our ocean and boost progress towards Sustainable Development Goal 14 (SDG 14). Future research should include other sectors such as marine biodiversity, marine renewable energy, climate change, and blue economy development of Small Island Developing States. Effective policies and strategies across land and ocean around the world need to be developed and implemented to enhance resilience of the human-ocean system and to achieve post-pandemic global sustainable ocean development.
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COVID-19 , Resíduos de Serviços de Saúde , COVID-19/epidemiologia , Ecossistema , Humanos , Oceano Índico , Pandemias , Fatores SocioeconômicosRESUMO
Achieving the 17 United Nations sustainable development goals (SDGs) in China largely depends on the transition of cities toward sustainable development. However, significant knowledge gaps exist in evaluating the SDG index at the city scale and in understanding how to simulate pathways to achieve the 17 SDGs for Chinese cities by 2030. This study aimed to quantify the SDG index of 285 Chinese cities and developed a forecasting model to simulate the performance of each SDG in each city until 2030 using varied scenarios. The results indicated that although the SDG index in Chinese cities increased by 33.97% during 2005-2016, Chinese cities, which continued their past paths, achieved an average of only five SDGs by 2030. To promote the joint achievement of all SDGs, we designed different paths for all SDGs of each of the 285 cities and simulated their SDG index until 2030. Under the scenarios, 216 Chinese cities (75.79%) could achieve 9-13 more SDGs in 2030 and the overall SDG index can improve from 74.57 in 2030 to 97.49 (target score 100) by adopting more intensive path adjustment. We lastly determined a cost-effective path for each SDG of each city to promote joint achievement of all SDGs by 2030. The proposed simulation model and cost-effective path serve as a foundation for other countries to simulate SDG progress and develop pathways for achieving SDGs in the future.
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Since the adoption of the open-door policy, the Chinese dietary pattern has changed greatly. Based on the dietary changes, this study analyzed the arable land and water footprints (WFs) for the food consumption of urban and rural residents in China. The results showed that the arable land demand and WFs for meat, vegetable oil, soybeans and liquor exceeded those for other foods, and the per capita arable land and WFs for food consumption of urban residents were higher than those of rural residents. The total arable land and WFs for the food consumption of residents increased by 16.9 million ha (from 91.1 to 108 million ha) and 214.5 billion m3 (from 457.9 to 672.4 billion m3), respectively, from 1983 to 2017. Specifically, the total arable land and WFs for the food consumption of urban residents increased by 45.9 million hm2 (from 22.6 to 68.5 million hm2) and 318.3 billion m3 (from 113.2 to 431.5 billion m3), respectively. Additionally, those of rural residents decreased by 29.7 million hm2 (from 69.2 to 39.5 million hm2) and 103.9 billion m3 (344.8 to 240.9 billion m3), respectively, mainly due to the migration of the rural population to cities and the reductions in per capita arable land and WFs due to increased crop yields. The arable land and blue WFs required for food consumption will reach 127.7 million hm2 and 221.1 billion m3, respectively, in 2030. However, these values will be reduced by approximately 23% and 20%, respectively, to 98.9 million hm2 and 177.8 billion m3 under a balanced dietary pattern. Measures such as improving the investment in agricultural research and development, advocating a balanced diet, and increasing the import of resource-intensive foods could alleviate the pressure on land and water resources.
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Conservação dos Recursos Naturais , População Rural , Agricultura , China , Conservação dos Recursos Naturais/métodos , Humanos , Água , Recursos HídricosRESUMO
Developing countries, such as China, have achieved unprecedented success in a single Sustainable Development Goal (SDG), which usually leads to trade-offs between the three pillars of sustainability, and even destroys sustainability. Quantifying the degrees of coupling among the pillars is essential to support policymakers' systematic actions to minimize trade-offs and maximize co-benefits between the pillars, and simultaneously achieve all SDGs. However, assessing the degrees of coupling among the pillars for the full SDGs is lacking. Here, we evaluate the progress of the pillars towards the SDGs and quantify the degrees of coupling among them at both national and sub-national levels in China from 2000 to 2015. The results indicate that the degrees of coupling among the pillars were almost constant while the degrees of coupling between the pillars and economic growth declined over time. The degrees of coupling between environmental impact and economic growth accounted for 52%-83% of the SDGs' progress. Reducing the degrees of coupling helps achieve simultaneously economic growth and environmental protection. The higher the degrees of coupling, the lower progress. This trend was universal among all provinces (sub-national level) regardless of their development levels. Our study highlights not only the necessity to track the degrees of coupling among the pillars, but also decoupling environmental impact from economic growth to achieve the SDGs.