Complex Impacts of Wars on Global Sustainable Development in a Metacoupled World

Wars and armed conflicts have had profound impacts on local and global sustainable development in an interconnected world. However, evidence on the impacts of wars is fragmented and little attention has been paid to the impacts on the 17 UN’s Sustainable Development Goals (SDGs), a unifying framework for achieving global sustainable development. This perspective synthesizes the scattered information to provide a holistic analysis and highlight the applications of remote sensing in assessing the impacts of wars on global sustainable development in a metacoupling world. Wars have complex impacts on all 17 SDGs, which cascade beyond conflict zones and spillover to adjacent and distant countries worldwide. Satellite remote sensing can play a significant role in monitoring environmental and socioeconomic impacts such as crop production, deforestation, pollution, urban damage, and migration. Remote sensing can provide timely, spatiotemporal, large-scale data for sustainable development impact assessment of conflict zones with restricted access. As 2023 is the middle point of the time period (2015-2030) for the 2030 Agenda for Sustainable Development, it is urgent to conduct more quantitative assessments for wars around the world such as the Russia-Ukraine war. Enhancing remote sensing applications in war-related impact assessment with advanced models and frameworks is very helpful and significant. It is also critical to rethink about global governance by incorporating the ripple effects of wars for policy adjustments to achieve SDGs by 2030

Spatiotemporal evolution and drivers of carbon inequalities in urban agglomeration:An MLD-IDA inequality indicator decomposition

Increasing countries are articulating ambitious goals of carbon neutrality. However, large inequalities in regional emissions within a country may hinder progress toward a carbon–neutral future, as the unequal distribution of reduction responsibilities among regions could impair just transition and exacerbate uneven development, which necessitates an in-depth understanding of the mechanism of multi-scale carbon inequalities within country, region, and city. Yet, the evolution of carbon inequalities within urban agglomerations and the differences between adjacent or distant urban agglomerations have not been well understood, especially in countries undergoing rapid urbanization. Using the data of 89 cities in China’s Yangtze River Economic Belt (YREB) during 2006–2021, this paper quantifies carbon emissions inequality (CEI) at different scales in a systematic regional-urban agglomeration-city hierarchical structure. Then, under the integrated mean logarithmic deviation-logarithmic mean Divisia index (MLD-LMDI) decomposition framework, multi-scale CEIs are perfectly decomposed into six interrelated drivers, i.e., industrial emission structure, energy emission intensity, industrial energy mix, energy intensity, industrial structure, and economic development. The results show that economic development, energy intensity, and industrial energy mix disparities are the main determinants accounting for CEIs at different scales. The decreasing CEI in YREB is mainly due to the changes in industrial structure and economic development, while the energy intensity effect partially hinders the mitigation of CEI. In the upper reaches of the YREB, the energy intensity effect accounts for over 94% growth of CEI during 2006–2021, while the decline in CEIs in middle and lower reaches is primarily caused by the effects of industrial energy mix and industrial structure, respectively. Further spatial decomposition analysis reveals more refined city-level heterogeneous effects and emphasizes the prioritized emission reduction direction for each city. This paper offers implications for reducing carbon inequality and insights into coordinated carbon emissions mitigation at the regional level for a carbon–neutral future

Multiple telecouplings and their complex interrelationships

Increasingly, the world is becoming socioeconomically and environmentally connected, but many studies have focused on human-environment interactions within a particular area. Although some studies have considered the impacts of external factors, there is little research on multiple reciprocal socioeconomic and environmental interactions between a focal area and other areas. Here we address this important kowledge gap by applying the new integrated framework of telecouplings (socioeconomic and environmental interactions between two or more areas over distances). Results show that even a protected area - i.e., the Wolong Nature Reserve for giant pandas in southwest China - has multiple telecoupling processes with the rest of the world; these include panda loans, tourism, information dissemination, conservation subsidies, and trade of aricultural and industrial products. The telecoupling processes exhibit nonlinear patterns, they change over time, and they have varying socioeconomic and environmental effects across the world. We also find complex relationships among different telecouplings - e.g., amplification, offsetting, spatial overlaps - which cannot be detected by traditional separate studies. Such an integrated study leads to a more comprehensive understanding of distant human-enviroment interactions and has significant implications for global sustainability and human well-being

Productivity-Based Land Suitability and Management Sensitivity Analysis: The Eucalyptus E. urophylla × E. grandis Case

Eucalyptus plantations are productive and short rotation forests prevalent in tropical areas that experience fast expansion and face controversies in ecological issues. In this study, we perform a systematic analysis of factors influencing eucalyptus growth through plot records from the National Forest Inventories and satellite images. We find primary restricting factors for eucalyptus growth via machine learning algorithms with random forests and accumulated local effects plots, as conventional forest growth models are inadequate to calculate the causal effect with the large number of environmental and socioeconomic factors. As a result, despite common belief that temperature affects eucalyptus growth the most, we find that precipitation is the most evident restricting factor for eucalyptus growth. We then identify and rank key factors that affect timber growth, such as tree density, rotation period, and wood ownership. Finally, we suggest optimal management and planting strategies for local farmers and policymakers to facilitate eucalyptus growth

Spatiotemporal evolution and drivers of carbon inequalities in urban agglomeration:An MLD-IDA inequality indicator decomposition

Increasing countries are articulating ambitious goals of carbon neutrality. However, large inequalities in regional emissions within a country may hinder progress toward a carbon–neutral future, as the unequal distribution of reduction responsibilities among regions could impair just transition and exacerbate uneven development, which necessitates an in-depth understanding of the mechanism of multi-scale carbon inequalities within country, region, and city. Yet, the evolution of carbon inequalities within urban agglomerations and the differences between adjacent or distant urban agglomerations have not been well understood, especially in countries undergoing rapid urbanization. Using the data of 89 cities in China's Yangtze River Economic Belt (YREB) during 2006–2021, this paper quantifies carbon emissions inequality (CEI) at different scales in a systematic regional-urban agglomeration-city hierarchical structure. Then, under the integrated mean logarithmic deviation-logarithmic mean Divisia index (MLD-LMDI) decomposition framework, multi-scale CEIs are perfectly decomposed into six interrelated drivers, i.e., industrial emission structure, energy emission intensity, industrial energy mix, energy intensity, industrial structure, and economic development. The results show that economic development, energy intensity, and industrial energy mix disparities are the main determinants accounting for CEIs at different scales. The decreasing CEI in YREB is mainly due to the changes in industrial structure and economic development, while the energy intensity effect partially hinders the mitigation of CEI. In the upper reaches of the YREB, the energy intensity effect accounts for over 94% growth of CEI during 2006–2021, while the decline in CEIs in middle and lower reaches is primarily caused by the effects of industrial energy mix and industrial structure, respectively. Further spatial decomposition analysis reveals more refined city-level heterogeneous effects and emphasizes the prioritized emission reduction direction for each city. This paper offers implications for reducing carbon inequality and insights into coordinated carbon emissions mitigation at the regional level for a carbon–neutral future.</p

Impacts of Green Innovation, Institutional Constraints and Their Interactions on High-Quality Economic Development across China

In 2015, China put forward five development concepts, propounded the concept of green development and green innovation, and adhered to the road of sustainable development. China also promoted the vision of high-quality economic development in 2017. It is very important to study the impacts of green innovation on high-quality development. However, scant research has been conducted on the impact of green innovation and institutional constraints on high-quality economic development simultaneously over both space and time in China. In this study, we analyze the impacts of green innovation on high-quality economic development across China from 2014 to 2018. The panel data model and the panel threshold model are developed, and the impact of green innovation and institutional constraints on high-quality economic development is empirically analyzed. Our results indicate that the comprehensive index and the level of high-quality economic development in all regions of China are increasing consistently. At the national level, addressing green innovation and institutional constraints have shown a significant positive impact on high-quality economic development. At the regional level, the interaction of green innovation and institutional constraints (i.e., mitigation of institutional constraints by green revolution) has a more positive impact on the economic quality of eastern China than that of central China. The interaction between green innovation and institutional constraints shows no positive impact on the high-quality economic development of the central and western regions because the green innovation, institutional constraints, and economic development in the central and western regions are weaker than those in the eastern regions. Therefore, it is suggested that different regions of China, especially the central and western ones, should strengthen green innovation, improve the market system, and increase government support

Bleak prospects and targeted actions for achieving the Sustainable Development Goals

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

Environmental impact assessment of water-saving irrigation systems across 60 irrigation construction projects in northern China

With increasing water shortages partly due to increasing demands, water has become a globally relevant issue especially in arid and semi-arid regions. Water-saving irrigation technologies provide new ways for improving the efficiency of water use for agricultural production. Although efficient irrigation management could lead to water savings and increased yields, the water consumption and greenhouse gas emissions during the construction of irrigation projects also puts pressure on environmental health. However, little research has considered the environmental impact of the construction process and materials. To fill this gap, the water footprint (WF) and carbon footprint (CF) of irrigation projects were calculated using life cycle assessment (LCA) methods. The results for sixty typical irrigation projects in northern China showed that the WF accounted for only 0.2–1.5% of the total agricultural WF and 2.3–8.8% of the water saved. When the WF to construct modern irrigation systems is not considered, the water-saving effects of these systems are generally overestimated by 13%. The CF for irrigation projects was 42.0% of all agricultural activities. Due to the difficulty to obtain detailed information for irrigation projects, this paper established the relationship between financial investment or area and CF for three kinds of irrigation projects. It provided a simple quantitative method for assessing its environmental impacts. By comparing environmental impacts and production benefits under different scenarios, using drip irrigation over the long-term could increase crop yield and reduce water footprint, but carbon footprint was increased at the same time. This study suggests that it is necessary to assess the environmental impacts of irrigation construction projects from a life cycle perspective rather focusing only on yield increases and reductions in irrigation amounts.</p

Three main dimensions reflected by national SDG performance

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