Study of the spatio-temporal variation of environmental sustainability at national and provincial levels in China

Multi-objective ecological restoration priority in China: Cost-benefit optimization in different ecological performance regimes based on planetary boundaries

In the context of the "United Nations Decade on Ecosystem Restoration", optimizing spatiotemporal arrangements for ecological restoration is an important approach to enhancing overall socioecological benefits for sustainable development. However, against the background of ecological degradation caused by the human use of most natural resources at levels that have approached or exceeded the safe and sustainable boundaries of ecosystems, it is key to explain how to optimize ecological restoration by classified management and optimal total benefits. In response to these issues, we combined spatial heterogeneity and temporal dynamics at the national scale in China to construct five ecological performance regimes defined by indicators that use planetary boundaries and ecological pressures which served as the basis for prioritizing ecological restoration areas and implementing zoning control. By integrating habitat conservation, biodiversity, water supply, and restoration cost constraints, seven ecological restoration scenarios were simulated to optimize the spatial layout of ecological restoration projects (ERPs). The results indicated that the provinces with unsustainable freshwater use, climate change, and land use accounted for more than 25%, 66.7%, and 25%, respectively, of the total area. Only 30% of the provinces experienced a decrease in environmental pressure. Based on the ecological performance regimes, ERP sites spanning the past 20 years were identified, and more than 50% of the priority areas were clustered in regime areas with increased ecological stress. As the restoration area targets doubled (40%) from the baseline (20%), a multi-objective scenario presents a trade-off between expanded ERPs in areas with highly beneficial effects and minimal restoration costs. In conclusion, a reasonable classification and management regime is the basis for targeted restoration. Coordinating multiple objectives and costs in ecological restoration is the key to maximizing socio-ecological benefits. Our study offered new perspectives on systematic and sustainable planning for ecological restoration.

Unraveling interactions and priorities under sustainable development goals in less-developed mountainous areas: case study on the National Innovation Demonstration Zone for the 2030 Agenda for Sustainable Development, China

Understanding the intricate relationships between progress and the United Nations' 17 Sustainable Development Goals (SDGs) is vital for informed and adaptable sustainable development policy formulation. This study focused on the Lincang National Innovation Demonstration Zone for the 2030 Agenda for Sustainable Development (LC-NIDZASD) in China. By evaluating sustainability scores at the county level from 2011 to 2020, the trade-offs and synergies among SDGs were explored. Priority SDGs for development were identified, and targeted recommendations were established based on these findings. The key findings are as follows: (1) The SDG index scores of Lincang and its counties showed an increase from 2011 to 2020, with scores riding from 42.1 to 52.2. SDG6 (Clean Water and Sanitation) and SDG12 (Responsible Production and Consumption) had the highest scores, while SDG1 (No Poverty) and SDG4 (Quality Education) increased significantly. However, the COVID-19 pandemic led to a decrease in the scores of SDG1, SDG8 (Decent Jobs and Economic Growth), and SDG17 (Partnerships for the Goals) in 2020 decreased compared to 2019. Decreased scores in SDG13 (Climate Action) and SDG15 (Life on Land) may be attributable to climate change. (2) The relationship between "Objectives" and ''Governance" appears to be synergistic, while ''Essential Needs" mainly shows a trade-off relationship with ''Objectives" and ''Governance." (3) To promote achievements in the construction of LC-NIDZASD, priority should be given to SDG3 (Health and Well-Being), SDG8, SDG9 (Industry, Innovation, and Infrastructure), and SDG12; SDG4 should not be ignored. (4) Overall, Lincang has made significant progress in sustainable development. However, to further consolidate these achievements, adjustments should be made for SDG7 (Energy Consumption and Production Structure). Efforts should be made to strengthen climate governance measures and improve warning and forecasting capabilities to promote the synergistic development of SDG7 (Affordable and Clean Energy) and SDG13 with other SDGs. This study's dynamic monitoring of changes in the SDGs in Lincang provides valuable insights into the synergies and trade-offs among these goals. Appropriate prioritization across various SDGs can allow for timely adjustments in sustainable management policies, ultimately contributing to the successful operation of the LC-NIDZASD.

Regional common prosperity level and its spatial relationship with carbon emission intensity in China

The characteristics of common prosperity include harmonious relationships between humans and the environment, as well as sustainable economic and social growth. The process of achieving common prosperity will necessarily have an impact on carbon emissions. In this article, panel statistics collected from 30 Chinese provinces and cities between the years 2006 and 2020 are utilized to assess the level of common prosperity and the intensity of carbon emissions in China. Then the SDM model is applied to explore the effects of the common prosperity level on the intensity of carbon emissions. The findings reveal that: (i) The common prosperity level in China has shown an increasing tendency. Between 2006 and 2020, the mean level of common prosperity increased from 0.254 to 0.486. From the regional perspective, eastern China has seen greater levels of common prosperity than central China, while central China has experienced greater levels of common prosperity than western China; regional disparities in the degree of common prosperity are substantial among Chinese provinces from 2006 to 2020; the common prosperity level is relatively high in economically developed provinces and relatively low in economically backward provinces. (ii) China's carbon emission intensity shows a continuous downward tendency. The annual average intensity of China's carbon emissions decreased from 4.458 in 2006 to 2.234 in 2020. From the regional perspective, the three main regions' carbon emission intensity likewise exhibits a decline in tendency between 2006 and 2020; still, western China continues to have the greatest carbon emission intensity, following central China, while eastern China has the smallest; however, certain provinces, notably Inner Mongolia and Shanxi, continue to have high carbon emission intensity. (iii) China's common prosperity level and carbon emission intensity both exhibit positive spatial autocorrelation at a 1% significant level under the adjacency matrix. The spatial agglomeration effect is significant, and adjacent provinces can affect each other. (iv) The SDM (Spatial Durbin Model) model test with fixed effects finds that the increase in the level of common prosperity suppresses the intensity of carbon emissions in the local area and neighboring regions. (v) The mediating effects model indicates that the process of common prosperity suppresses carbon emission intensity through high-quality economic development, narrowing the income disparity, and the development of a sharing economy.

Assessing the Beautiful China Initiative from an environmental perspective: indicators, goals, and provincial performance

The Beautiful China Initiative (BCI) is part of China's national strategy for implementing the long-term goals of building an ecological civilization and promoting sustainable development. However, currently, there is no goal-oriented, comparable, and standardized indicator framework for monitoring the performance of the BCI. Here, we established the BCI from an environmental perspective (BCIE) index comprising 40 indicators and targets in eight fields and used a systematic approach to measure the distance and progress towards the goal of building a "Beautiful China" by 2035 at the national and subnational levels. Our analyses indicate that the BCIE index score (range: [0, 1]) was 0.757 at the national level and 0.628-0.869 at the provincial level in 2020. Between 2015 and 2020, the BCIE index scores of all provinces improved; however, large spatio-temporal variations were evident. Provinces with better BCIE performances exhibited relatively balanced scores across different sectors and cities. Our study revealed that the BCIE index scores at the city level surpassed provincial administrative boundaries, resulting in a wider range of aggregation. By focusing on the strategic arrangement of BCI, this study provides an effective index system and evaluation method for dynamic monitoring and phased evaluations at all levels of government in China.

Decomposition of drivers and identification of decoupling states for the evolution of carbon emissions from energy consumption in China

As the largest energy consumer, China's control of carbon emissions from energy consumption plays a pivotal role in world climate governance. However, few studies have been conducted to explore the emission reduction pathways that promote a high level of synergy between China's economic growth and the " carbon peaking and carbon neutrality " goal from the perspective of energy consumption. Based on the measurement of energy consumption carbon emissions, this paper reveals the spatial and temporal distribution and evolution trends of carbon emissions in China at the national-provincial level. The multi-dimensional socio-economic factors such as R&D and urbanization are taken into account, and the LMDI model is used to decompose the driving effects of energy consumption carbon emissions at the national-provincial levels. Further, this paper combines the Tapio decoupling index with the LMDI model to decompose the decoupling states of China year by year and at the provincial level in four periods to explore the reasons for the change of carbon decoupling states. The results show that: (1) China's energy consumption carbon emissions grew at a high rate before 2013, and slowed down after that. There are significant differences in the scale and growth rate of carbon emissions among provinces, which can be classified into four types accordingly. (2) The R&D scale effect, urbanization effect, and population scale effect are the factors driving the growth of China's carbon emissions; while the energy structure effect, energy consumption industry structure effect, energy intensity effect, and R&D efficiency effect inhibit the growth of China's carbon emissions. (3) Weak decoupling is the most dominant decoupling state in China from 2003 to 2020, and the decoupling state varies significantly among provinces. According to the conclusions, this paper proposes targeted policy recommendations based on China's energy endowment.

Ecological sustainability and high-quality development of the Yellow River Delta in China based on the improved ecological footprint model

Aiming at the traditional ecological footprint model, the improved ecological footprint of the carbon footprint effectively makes up for the singularity of the ecological footprint's consideration of carbon emissions, and plays an important role in promoting high-quality development and ecological sustainability. This paper selects 2015, 2018 and 2020 as important time points for the study, corrects the ecological footprint parameter factors based on net primary productivity (NPP), measures the ecological footprint after the improvement of the carbon footprint, studies the spatial and temporal variation in the ecological footprint at the 100-m grid scale with the support of IPCC greenhouse gas inventory analysis, and analyzes the current ecological conservation status of the Yellow River Delta. Additionally, in the context of a low carbon economy, the decoupling index of carbon emissions and GDP is extended to the evaluation and analysis of high-quality development. The study showed that (1) the ecological footprint of the Yellow River Delta has increased year by year, from 0.721 hm²·person^- 1 to 0.758 hm²·person^- 1, an average annual increase of 2.9%; the ecological carrying capacity has decreased from 0.40 hm²·person^- 1 to 0.31 hm²·person^- 1, an overall decrease of 28.59%. (2) The overall ecological deficit of the Yellow River Delta grid is lightly overloaded, with most of the ecological surplus occurring in the northern and eastern parts of the study area and a few moderate and heavy overloads in the center of the core area where there is a lot of built-up land and the area is small and easy to gather. (3) Based on the low-carbon economy analysis, 2015, 2017 and 2020 reach absolute decoupling and are in the ideal scenario. However, in the rest of the years, carbon emissions and economic development are still in a large contradiction, and decoupling has fluctuated and varied greatly in the last six years. The effective combination of ecological footprint and low carbon economy analysis provides an important theoretical basis for improving ecological conservation and achieving high-quality development.

Drivers of green growth in the Kingdom of Saudi Arabia: can financial development promote environmentally sustainable economic growth?

The Kingdom of Saudi Arabia has recently declared its vision of turning carbon neutral by 2060. This declaration has motivated policymakers in this Arab nation to design policies that can green economic activities in Saudi Arabia so that environmentally sustainable growth can be ensured. Against this backdrop, this study models the independent and joint effects of financial development, globalization, and energy efficiency rates on green growth of the Saudi Arabian economy. In this regard, green growth in the Kingdom of Saudi Arabia is proxied by the difference between the nation's annual per capita growth rates of gross domestic product and carbon dioxide emission. Utilizing data from 1972 to 2018 and controlling for structural break-induced problems found in the data, the findings from the regression and causality analyses confirm the green growth-inhibiting impacts of financial development and trade globalization. In contrast, greater financial globalization is evidenced to drive green growth in the Kingdom of Saudi Arabia. Furthermore, more efficient uses of energy resources are found to not only directly boost green growth but also partially neutralize the long-run green growth-dampening impacts associated with the development of the financial sector. In addition, financial development and trade globalization are observed to jointly inhibit green growth attainment both in the short and long run. In line with these important findings, it is recommended that the government of Saudi Arabia conceptualizes new green growth policies so that the nation's annual per capita economic growth rate outpaces its annual per capita growth rate of carbon dioxide emissions.

Assessing progress towards achieving the transport dimension of the SDGs in China

Transport is an important service industry in the national economy. Sustainable transport is central to sustainable development. Currently, investigating the sustainable development process and trade-offs in China's transport sector is urgent. In this study, 11 transport indicators were selected and constructed for the sustainable development goals (SDGs) under the UN indicator framework. The scores of each indicator were calculated, and spatiotemporal patterns and interactions were analyzed. The results revealed that China's transport infrastructure performed well in large transportation volumes and guaranteed traffic safety and strict land use control, with scores above 75. However, China's transport sector currently faces a challenge in using clean energy, and a more balanced development of bus ownership among the provinces is expected. The interaction analysis revealed three pairs of indicators with synergy (ρ > 0.5), but both the significant negative and positive relationships among the selected indicators accounted for approximately half, indicating the development of sustainable transport in China would move in zigzags. Road accessibility was an indicator interacting with most sustainable transport indicators. We suggest that more SDG indicators with indirect impacts should be included in future sustainable transport research.

Indicators, Goals, and Assessment of the Water Sustainability in China: A Provincial and City-Level Study

The United Nations and scholars called for more attention and efforts for cleaner water and water sustainability. This study established a water sustainability evaluating method framework, including indicators, goals, and methods and performs provincial and city-level assessments as case studies. The framework involves six fields, surface water quality, marine environmental quality, water-soil-agriculture, water infrastructure, water conservation, aquatic ecology, water-efficient use, and pollutant emission reduction. The methods innovatively integrate multi fields and concerns of water sustainability while providing a goal-oriented evaluation and implementing the United Nations' call for the refinement and clarification of SDGs. China's overall water sustainability was evaluated as 0.821 in 2021, and have performed well in surface water quality, sea quality, water conservation, and aquatic ecology fields while performing poorly in the water-soil-agriculture field. The overall strategy, policy, and action for water sustainability could be developed based on the evaluation. The water sustainability evaluation presented the regional and field/indicator differentiations. It is necessary to implement regionally classified policies and differentiated management for sustainable water development. The correlation analysis with socioeconomic factors implies the complicated and intimate interaction between socioeconomic development and water sustainability while revealing that development stages and the inherent conditions of natural ecology and water sources bring about the differentiations. A comprehensive evaluation of water sustainability may be three-dimensional, involving water quality and ecology, development related to water, and water resources and utilization.

Assessing progress towards sustainable development goals for Chinese urban land use: A new cloud model approach

Rapid urbanization poses great challenges to China's urban land use sustainability (ULUS). Land is the essential space to achieve the Sustainable Development Goals (SDGs) of the United Nations, so SDGs provide a new guide to evaluate land use sustainability. However, there is still a lack of SDGs-oriented assessment of urban land use at national level. Moreover, there is still a need to address the problems about the randomness and fuzziness within evaluation, which tends to cause more uncertainties. Here we developed a SDGs-oriented evaluation framework based on the cloud model and derived the spatial and temporal patterns of urban land use sustainability for China at the prefecture-level from 2004 to 2019. Then, we used the McKinsey matrix to classify the types of urban land use sustainability, and examined their main drivers using the Geodetector method. The results showed that the development level of ULUS in China was high in the east and low in the west. High-value hotspots were mainly distributed in primary and secondary urban agglomerations in China. From 2004 to 2019, the development level of ULUS in China gradually increased, but the growth rate slowed down. In 2009 the value of central China exceeded that of the northeast. In contrast, the coordination level of ULUS had declined in more than 50% of Chinese cities during the study period. The high values were in southern China, northeast China, and Chengdu-Chongqing urban agglomeration, while the low values were in central and southern Liaoning and the urban agglomeration in the Central Plains. The development level was mainly controlled by anthropogenic activities and urban development, while natural conditions constrained the improvement of the coordination level. Combining the development and coordination, we found that cities with higher development level often had a wide range of coordination level, and suggestions were put forward for different regions to achieve sustainable land use. Our research provides scientific guidance for China's territory planning and sustainable urban development.

Social Sustainability in Construction Projects—A Systematic Review of Assessment Indicators and Taxonomy

Despite its importance and appeal, the social dimension of sustainability in construction projects is less explored and lacks a comprehensive and standardized framework. This diminishes the holistic view of sustainability. The existing customized frameworks make the selection of factors challenging across different contexts. Eventually, the practitioners have to pick and choose the factors. This reduces the reliability of social sustainability assessments and makes them a procedural challenge. To fill this gap, the current review synthesizes a framework of social sustainability for construction projects. For this purpose, a systematic review of the literature published until 2021 is performed. The indicators are extracted from the selected 22 papers and their content is analyzed to check for similarities. The final set of 76 factors is synthesized into an assessment framework through a thematic analysis based on a bottom-up approach. The framework is organized into 7 enablers or themes, 27 indicators, and 76 sub-indicators. The enablers of social sustainability are stakeholder, safety and health, human resource development, project, industry, community, and government. The framework provides a comprehensive and precise view of social sustainability which can be leveraged to ensure better planning and sustainable development of construction projects.

Spatial-Temporal Evolution of Health Impact and Economic Loss upon Exposure to PM2.5 in China

Exposure to PM_2.5 can seriously endanger public health. Policies for controlling PM_2.5 need to consider health hazards under different circumstances. Unlike most studies on the concentration, distribution, and influencing factors of PM_2.5, the present study focuses on the impact of PM_2.5 on human health. We analysed the spatial-temporal evolution of health impact and economic loss caused by PM_2.5 exposure using the log-linear exposure-response function and benefit transfer method. The results indicate that the number of people affected by PM_2.5 pollution fluctuated and began to decline after reaching a peak in 2014, benefiting from the Air Pollution Prevention and Control Action Plan. Regarding the total economic loss, the temporal pattern continued to rise until 2014 and then declined, with an annual mean of 86,886.94 million USD, accounting for 1.71% of China’s GDP. For the spatial pattern, the health impact and economic loss show a strong spatial correlation and remarkable polarisation phenomena, with high values in East China, North China, Central China, and South China, but low values in Southwest China, Northwest China, and Northeast China. The spatial-temporal characterisation of PM_2.5 health hazards is visualised and analysed accordingly, which can provide a reference for more comprehensive and effective policy decisions.