Sustainable Development Goals Research Articles

'Show me the money': An analysis of US global health funding from 1995 to 2019.

Historically, the US has been the largest contributor to development assistance for health (DAH), although its allocation has shifted in response to outside forces. This included, for example, the establishment of the Millennium Development Goals (MDGs) in 2000, which emphasised child mortality, maternal health, HIV/AIDS, and malaria. This led to funds being earmarked for disease-specific interventions rather than health system strengthening (HSS). In 2007, the World Health Organization (WHO) published six health system building blocks, representing essential components of strong health systems. In 2015, the MDGs were replaced by the Sustainable Development Goals (SDGs), which emphasised capacity-building as opposed to specific health problems. The Lancet Commission on Global Surgery, meanwhile, highlighted surgical capacity building as essential to achieving Universal Health Coverage (UHC). Given the renewed emphasis on a comprehensive approach rather than disease-specific interventions, one might anticipate the US aligning with this rhetoric in its allocation of DAH. However, we hypothesise that this is not the case. We queried the Organization for Economic Co-operation and Development (OECD) database for allocation of US DAH to low- and middle-income countries between 1995 and 2019, thereby excluding data after 2019 to avoid the influence of the coronavirus disease 2019 pandemic. OECD entries were assigned to health systems strengthening (HSS) or disease-specific interventions categories. The WHO building blocks were used as a framework for health systems strengthening. From 1995 to 1999, US DAH allocated to HSS decreased from 42% to 34%. The allocation decreased further from 34% in 2000 to 4% in 2007; correspondingly, DAH allocated to disease-specific interventions increased from 67% to 96%. Between 2008 and 2019, the distribution of US DAH remained relatively stable, with funds allocated to HSS versus disease-specific interventions ranging from 3-12% and 88-98% respectively. While total US DAH contributions in the 1990s and early 2000s were significantly lower compared to the decade that followed, the distribution of these funds was more evenly divided between HSS and disease-specific interventions. Despite attempts by the WHO and United Nations to redirect attention to HSS as the path to achieving UHC, the US continues to largely support disease-specific interventions and overlook the importance of HSS, including surgical capacity building.

A Multi-Scale Evaluation Model of Sustainable Development Goal 11.7 for Problem-Solving at Different Levels

Sustainable Development Goal 11.7 (SDG 11.7) aims to promote the improvement of urban public spaces. However, the localization process of SDG 11.7 mainly relies on a bottom-up problem-solving approach, which fails to fully encompass the connotation of SDG 11.7. Additionally, existing evaluations primarily focus on a single scale, neglecting the impact of scale issues. These limitations can lead to imbalanced development or misallocation of responsibilities when guiding governments at different levels in promoting the sustainable development of public spaces. Therefore, this article introduces a multi-scale assessment model of SDG 11.7. It employs a top-down problem-solving approach to construct a sustainable development indicator framework, setting appropriate sustainable development indicators for various levels of government based on the connotation of SDG 11.7, and generates city-scale results by integrating three scales: apartment complexes, street blocks, and counties. Testing this model in Xi’an, China, revealed that it adequately captures four key aspects of SDG 11.7—safety, inclusiveness, accessibility, and greenness—through 11 indicators. The evaluation outcomes at the apartment complex, street block, and county levels effectively guide future development directions for various levels of government. Ultimately, the synthesis of these scales reveals the spatial pattern of SDG 11.7 at the city scale and identifies focal areas for development. Overall, this exploratory model demonstrates high accuracy and robustness, providing a comprehensive understanding of the essence of SDG 11.7. It also alleviates challenges posed by scale issues, offering decision support for monitoring SDG 11.7 across different levels of government in Chinese cities and promoting the process of sustainable development.

Groundwater potential zone mapping using AHP and geospatial techniques in the upper Narmada basin, central India

Water scarcity occurs in the agriculturally dominated Upper catchment area of Narmada River, Central India because of the overexploitation of underground water for residential, industrial, and other uses. Delineating the Ground Water Potential Zone (GWPZ) is critical to meeting the area’s water demand. Finding the Upper catchment Narmada River groundwater potential zone is the primary goal of this study. The study uses geographical methodologies based on the Analytical Hierarchical Process (AHP). To create a GWPZ map, ArcGIS 10.4 software compiles eight thematic layers, including elevation, slope, drainage density, geology, rainfall, soil texture, modified normalized difference water index, topographic wetness index, and land use/cover. There are five classifications for land use land cover map: Very low, low, moderate, high, and Very high. Each theme map in this study was given a weight based on its unique attributes and contribution to the GWP capacity. The AHP method, which takes into account each layer’s relative relevance regarding the others, was used to establish the weights. Four groups were created from the resulting groundwater potential map: excellent, good, moderate, and poor. According to the study, 26.05% of the basin was categorized as excellent, 34.59% as good, 23.97% as moderate, and 15.4% as poor groundwater potential.The results of this study further indicate that a sizable section of the Narmada River Basin has well to moderate groundwater potential, pointing to encouraging prospects for the area’s sustainable groundwater use. The study offers crucial insights for planners and policymakers to conscientiously harness groundwater resources, fostering sustainable development across diverse land uses in the fragile zone of the upper catchment of the Narmada, and it serves as a model for simulation in other sensitive river basins. The implications of the study are geared towards enhancing groundwater prospects, revitalizing fragile riverine ecosystems, and achieving the target outlined in Goal 6 of the Sustainable Development Goals (SDGs) of 2030.

Industrial Symbiosis and Circular Economy Practices Towards Sustainability in Forest-Based Clusters: Case Studies in Southern Brazil

This study aimed to investigate how Industrial Symbiosis (IS) built around thermoelectric power plants (TPPs) located in forest-based clusters in the southern plateau region of the state of Santa Catarina, Brazil, can stimulate the adoption of circular economy (CE) practices. Data were collected to identify the presence of forest-based clusters and the purchase and sale of logs, processed wood, and forest residues from companies within the clusters, and to investigate CE practices using the ReSOLVE framework adopted in two TPPs, which used residues and black liquor as fuel. The results indicate that the nature of the forest-based activities enhances the formation of clusters, especially when TPPs use forest residues for energy production with IS intensified in this process. Brazil has 140 TTPs that use forest biomass with the capacity to generate 5.5 million wK. Three clusters were identified in the study region with purchase and sale, respectively, of logs (78.6 and 100%), processed wood (75 and 66.7%), and wood residues (45.5 and 83.3%) within the region. The case studies indicated the strong occurrence of CE practices in the cases analyzed that contribute to four of the Sustainable Development Goals (SDG) proposed by the United Nations (7, 8, 9, and 12).

How Financial Development Heterogeneity, Macroeconomic Volatility, Domestic Investment, and Digital Economy Are Driving Sustainable Economic Growth in Africa

The roles of finance are well stipulated in the various indicators of the sustainable development goals (SDGS). However, the extant literature still finds conflicting outcomes of the finance-led growth. Hence, this study redirects empirical evidence by unbundling the effects of financial development on sustainable economic growth into aggregated and disaggregated, focusing on seven robust indicators (financial development index, financial institution index, depth, and access, and financial market index, depth, and access) in selected African countries from 1995 to 2021. Similarly, the intervening roles of government expenditure, digital economy, domestic investment, human capital, macroeconomic volatility, and trade openness are evaluated based on advanced estimators. Findings show that the seven indices of financial development drive sustainable economic growth in Africa both in the long and short runs. Similarly, government expenditure, digital economy, and human capital promote sustainable economic growth both in the short- and long-term periods. The driving effects of domestic investment are only noticeable in the long run. Conversely, trade openness and macroeconomic instability are noted to be growth-deterring. Policy insights that support sustainable economic growth in Africa emanate from the outcomes.

Exploring the Role of Public and Private Partnerships in Educational Development of Nepal

The education system of Nepal has undergone significant transformation in the last few decades. The transition is observed from a primarily government-driven model to one that increasingly incorporates public-private partnerships (PPPs). This paper aims to explore the role of these partnerships in enhancing educational quality, access, and equity in Nepal. By examining case studies, policy frameworks, and outcomes of various initiatives, it is assessed the efficacy of PPPs in addressing the systemic challenges faced by the Nepali education sector. The research also provides critical insights into how these partnerships can be leveraged to achieve Sustainable Development Goal (SDG) 4: Quality Education. Additionally, this paper also explores the role of PPPs in enhancing Nepal's educational development by improving infrastructure, access to education, teacher training, and overall quality of education. Through a review of existing literature and case studies, this study assesses the effectiveness, challenges, and potential of PPPs in transforming educational landscape of Nepal. Int. J. Soc. Sc. Manage. Vol. 11, Issue-4: 136-140.

A comparative analysis of the evaluation system for comprehensive reform of agricultural water prices in China

Water is a fundamental natural resource that affects human and social development, and also plays an important role in modern agricultural production and food security. In China, agricultural water consumption accounts for the majority of the total water consumption. For a long time, China has not fully implemented water pricing and payment for agricultural water, and the lower agricultural water cost have led to the waste of water resource and the rapid conversion of agricultural water to other industries. In order to avoid agricultural water waste and achieve the goal of agricultural sustainable development, the Chinese government has launched a comprehensive reform of agricultural water prices nationwide since 2016. According to the plan, nowadays, the reform will faces overall evaluation and acceptance in 2024 and 2025. However, there is a lack of a relatively unified and flexible nationwide evaluation index system and acceptance measures. In this study, a comparative research of the evaluation system for comprehensive reform of agricultural water prices was developed. Based on existing evaluation and acceptance measures issued by four typical provincial regions, this study compared and analyzed the compliance and similarities and differences of these acceptance measures with national reform policies and requirements. From the aspects of evaluation procedure and index system, a systematic comparative analysis was conducted on the integrity and differences in the four regions. At the same time, suggestions were given for policy-making of national evaluation process and standard. The comparative analysis results showed that the evaluation indices in the four provincial regions have met all the key points of national reform policies and have a complete system, but there were significant differences in the structure of the evaluation index system in different provincial regions. It is recommended to establish a simple, relatively unified and practical national evaluation and acceptance system as soon as possible. In addition, evaluation criteria for individual specific indices should be determined by region based on the differences in economic capacity and agricultural water conservancy facilities conditions.

Practical Research on the Work of College Counselors in the Internet Era

With the rapid development of modern technology, the internet and computers have been widely integrated into production and daily life. To achieve sustainable development goals and move towards diversification in the education sector, it is necessary to introduce modern educational concepts and work models. Counselors are an indispensable element in the work of college students. Traditional work models are no longer able to meet the personalized development needs of students and even seriously hinder the progress of the work. Counselors should transform their traditional work thinking, rely on internet technology to expand their work space, break the constraints of time and space, and provide objective conditions for exploring the future prospects of their work. In order to improve the overall efficiency of daily management work, counselors need to follow the trend of the times, seize the opportunities of the times under the premise of adhering to the laws of student development, and give full play to the advantages of internet technology applications to meet the diverse challenges of their work.

Advanced hybrid neural network techniques for minimizing gas turbine emissions

Purpose Emissions have significant environmental impacts. Hence, minimizing emissions is essential. This study aims to use a hybrid neural network model to predict carbon monoxide (CO) and nitrogen oxide (NOx) emissions from gas turbines (GTs) to enhance emission prediction for GTs in predictive emissions monitoring systems (PEMS). Design/methodology/approach The hybrid model architecture combines convolutional neural networks (CNN) and bidirectional long-short-term memory (Bi-LSTM) networks called CNN-BiLSTM with modified extrinsic attention regression. Over five years, data from a GT power plant was uploaded to Google Colab, split into training and testing sets (80:20), and evaluated using test matrices. The model’s performance was benchmarked against state-of-the-art emissions prediction methodologies. Findings The model showed promising results for GT CO and NOx emissions. CO predictions had a slight underestimation bias of −0.01, with root mean-squared error (RMSE) of 0.064, mean absolute error (MAE) of 0.04 and R2 of 0.82. NOx predictions had an RMSE of 0.051, MAE of 0.036, R2 of 0.887 and a slight overestimation bias of +0.01. Research limitations/implications While the model demonstrates relative accuracy in CO emission predictions, there is potential for further improvement in future research. Practical implications Implementing the model in real-time PEMS and establishing a continuous feedback loop will ensure accuracy in real-world applications, enhance GT functioning and reduce emissions, fuel consumption and running costs. Social implications Accurate GT emissions predictions support stricter emission standards, promote sustainable development goals and ensure a healthier societal environment. Originality/value This paper presents a novel approach that integrates CNN and Bi-LSTM networks. It considers both spatial and temporal data to mitigate previous prediction shortcomings.

The Peer Effects of Residents’ Carbon Emission Behavior: An Empirical Analysis in China

The responsible low-carbon behavior of household residents is a crucial factor for the purpose of achieving carbon neutrality in the economy and society. Based on the peer effects theory, this study constructs a fixed-effects model to empirically analyze the existence, heterogeneity, and action mechanism of peer effects in household carbon emission behavior, which uses panel data from the China Household Finance Survey (CHFS). The results indicate that peer effects have a significantly positive impact on residents’ carbon emission behavior, and the results are verified by the robustness test in various ways. Further mechanism tests show that peer effects influence carbon emission behavior through methods including the learning imitation mechanism and competitive imitation mechanism. In addition, we find that peer effects have different impacts on residents’ carbon emission behavior in varying regions, income levels, education levels, and ages groups. This study aims to embed residents’ carbon emission behavior into the strong relationship between surrounding groups, raise consumers low-carbon awareness through publicity, guidance, and group interaction, form a low-carbon atmosphere for the whole society, and contribute to the realization of Sustainable Development Goals.

AI-Assisted Automated Identification of Human Activities Using Ficus religiosa Leaf-Based Triboelectric Nanogenerator.

Movement monitoring and effective identification of different actions are the keys that help in fitness services, health status, clinical studies, etc. In this technological era, Internet of Things (IoT) technologies, including smart wireless devices and sensors, are very effectively used for monitoring human activities, but the demand for sustainable and green power sources is a crucial issue with these devices. Triboelectric nanogenerators (TENG) are proven to be promising applications in these devices because they harvest energy from the surrounding environment and eliminate the use of batteries as power sources. As a green energy source, this study emphasizes the fabrication of biodegradable materials-based TENGs, which are eco-friendly and are related to clean and green energy as per the UN's sustainable development goals SDG 7 (affordable and clean energy). In the present work, a natural Ficus religiosa leaf (FRL) of the F. religiosa tree is used in designing and fabricating a TENG (FRL-TENG). Also, an approach is discussed to compare the performance of FRL-TENG with TENGs fabricated from other waste biodegradable materials such as garlic tunic, onion tunic, and eggshell membrane (ESM). During the experimental study, it is observed that the FRL-based TENG produced maximum voltage in comparison to other material combinations selected in this study. The generated electric output from these TENG combinations is also used to power an array of tens of green-light-emitting diodes (LEDs). Furthermore, this paper also proposes the use of FRL-TENG as a wearable sensor to collect information and monitor the physical activities of the user, viz., walk, jump, and run. To recognize the movement status, the FRL-TENG sensor is integrated with an extra randomized tree-based machine learning model for accurately distinguishing the user's three activities with an accuracy of 96%. The work showcases an innovative approach to encourage customized uses of TENG sensors in human motion monitoring and permits the development of intelligent, self-powered systems for new applications.

Machine Learning and Remote Sensing Applications for Assessing Land Use and Land Cover Changes for Under-monitored Basin

Urban sprawling caused by industrial and economic growth has significantly affected land use and land cover (LULC). Using satellite imagery for real-time examination in Kuantan has become exceedingly expensive due to the scarcity and obsolescence of real-time LULC data. With the advent of remote sensing and geographical information systems, LULC change assessment is feasible. A quantitative assessment of image classification schemes (supervised classification using maximum likelihood and deep learning classification using random forest) was examined using 2022 Sentinel-2 satellite imagery to measure its performance. Kappa coefficient and overall accuracy were used to determine the classification accuracy. Then, 32 years of LULC changes in Kuantan were investigated using Landsat 5 TM, Landsat 8 OLI, and Sentinel-2 based on the best classifier. Random forest classification outperformed maximum likelihood classification with an overall accuracy of 85% compared to 92.8%. The findings also revealed that urbanisation is the main factor contributing to land changes in Kuantan, with a 32% increase in the build-up region and 32% in forest degradation. Despite the subtle and extremely dynamic connection between ecosystems, resources, and settlement, these LULC changes can be depicted using satellite imagery. With the precision of using a suitable classification scheme based on comprehensive, accurate and precise LULC maps can be generated, capturing the essence of spatial dynamics, especially in under-monitored basins. This study provides an overview of the current situation of LULC changes in Kuantan, along with the driving factors that can help the authorities promote sustainable development goals.

An Analysis Examining the Way Supply Chain Management-Focused Third-Party Environmental Audits Contributed to Business Sustainability Efforts

A crucial instrument for improving openness and responsibility, third-party environmental audits have become more popular as the focus on corporate sustainability has grown. The role of these audits in propelling sustainability efforts within corporations is the subject of this study. To make sure a business is in line with regulations and finds ways to improve, it can get an impartial opinion by having a third party conduct an environmental audit. The impact of these audits on business practices and sustainability is investigated in this paper through an analysis of case studies and empirical data. Based on the results, it seems that third-party audits help improve environmental performance by encouraging responsibility and constant development. Better resource efficiency, less waste, and reduced emissions are common outcomes of audited companies' adoption of more stringent environmental management systems. In addition, third-party audits boost stakeholder trust—an essential quality for a company's public image and the faith of its investors—due to the audits' impartiality and reliability. The thoroughness of the audit, the auditors' knowledge and experience, and the firm's resolve to follow audit recommendations are the three most important variables that determine how useful these audits will be. Concerns raised by the research include the possibility of superficial compliance and the necessity for uniform audit frameworks to permit comparison and uniformity throughout businesses. Because they offer an impartial assessment of environmental performance and advocate for best practices, third-party environmental audits are crucial in propelling corporate sustainability efforts. It is critical to resolve the highlighted issues and continually improve audit procedures to enhance their efficacy. Policymakers, corporations, and stakeholders can use this research to better understand the value of third-party audits in reaching sustainable development goals and how to improve corporate sustainability initiatives.

Promoting Sustainability: Land Transfer and Income Inequality Among Farm Households

The United Nations Sustainable Development Goals emphasize the dangers of inequality and initiatives on how to reduce it. Income inequality is an important part of this and can cause many social problems. This study aims to investigate the impact of land transfer on income inequality of Chinese farm households and its mechanism of action. This study empirically analyzes the impact of land transfer on farm household income inequality based on the OLS model using 27,134 samples from the 2018–2020 China Family Panel Study (CFPS) data. The study finds that land transfer can effectively reduce income inequality among farm households. However, only land transfers out affect income inequality; the effect of land transfers in is not significant. At the same time, there is some heterogeneity in the impact of land transfers on farm household income inequality. The effect is greater in the east and west than in the center. The effect is greater in the north than in the south. The role is greater in food-producing areas than in non-food-producing areas. Mechanism testing shows that land transfer impacts income inequality among farm households by promoting entrepreneurship. Farm households who use the Internet and have stronger social capital gain more from the impact of land transfer on income inequality.

“I Pink I Can” Breast Cancer Intervention Program: Its Effectiveness in Raising Knowledge among Junior High School Students of San Pablo City Integrated High School

As incidence rates rise from one in ten women to one in eight by 2023, breast cancer continues to be a serious worldwide health concern. Regardless of its rarity in men, this study included men in addition to women who frequently get breast cancer. Both sexes are affected by breast cancer, and its effects frequently get worse when discovered in advanced stages. This study highlights the importance of breast cancer education for people of all genders, in order to improve early detection and treatment outcomes. It aims to support the Sustainable Development Goal of "Good Health and Well-Being" by increasing Junior High Students' knowledge about breast cancer through an intervention program. Using a quasi- experimental design, 156 students' knowledge was assessed via a pre-test and post-test after exposure to leaflets, posters, and health teaching. A rigorously tested questionnaire focused on: breast cancer, signs and symptoms, risk factors, risk populations, and breast cancer screening showed that while students had basic knowledge initially, misconceptions were common. Post-intervention results demonstrated a significant increase in correct responses, indicating that the program effectively improved knowledge and corrected misconceptions. This underscores the value of targeted health education in promoting breast health and encouraging preventive measures.

Sustainable development goals in emerging markets: Aligning the role of financial inclusion in promoting environmental quality of the Next‐11 economies

AbstractPursuing sustainable development has emerged as a paramount global objective, with the United Nations' Sustainable Development Goals (SDGs) serving as a guiding framework. Increasing environmental degradation is associated with increased greenhouse gas emissions, deforestation, industrial waste, fossil fuel depletion, and loss of biodiversity. This study has analyzed the effect of financial inclusion on ecological sustainability while controlling the effect of financial development, energy consumption, economic growth, urbanization, and trade openness in the Next‐11 economies from 1995 to 2019. The study develops the financial inclusion index through principal components analysis by inculcating three demand‐side and three supply‐side factors of financial inclusion. To analyze the developed model, various first‐generation and second‐generation techniques are applied. The results of Westerlund co‐integration reveal significant long‐run co‐integration among the series. The long‐run elasticities are estimated through dynamic common correlated effect estimation and generalized method of moments where results reveal that FI helps to secure environmental sustainability by reducing the ecological footprint, hence it works on the SDG framework. Economic growth and financial development are found to be the root causes of increasing ecological footprint. So, it is the penetration of excessive credit, not the financial inclusivity which needs to be directed toward sustainability. It is suggested that the governments of Next‐11 countries should steer the capital toward sustainable usage and should continue facilitating financial services to curtail environmental degradation. Our findings have significant repercussions for Next‐11 countries, giving decision makers fresh perceptions of financial inclusion and development implications.

How green strategies and policies influence production‐based emissions, industrial development and sustainable development goals?

AbstractSustainable development is a global imperative; however, it is unattainable without a transformation of the production sector. Therefore, the study examines the impact of green strategies [Industrial innovation, Eco‐tech imports‐IMPT, and Green finances‐GFN] and policy interventions [Environmental policy‐EPY and Environmental taxes‐ETX] on production‐based emissions (PBE), industrial value addition (IVA), and sustainable development goals (SDG). The study covers the years 1990–2022 and focuses on 25 European nations. In addition, the pooled mean grouped (PMG)‐ARDL and mean group (MG) techniques were used to assess the short‐ and long‐term parameters. The country‐specific relationships are evaluated using the Bootstrap Granger Causality test. The results affirm that green strategies and policy interventions mitigated PBE and increased the IVA and SDG in Europe. However, globalization and energy use increase the PBE and IVA while impeding progress toward the SDGs. The mitigation technologies fueled with green energy (MPRE) came out as the ultimate solution, which requires green technologies and sustainable practices across all sectors. Therefore, it is suggested that governments implement eco‐friendly policies that boost GFN, reduce pollution, increase green output, and meet the Sustainable Development Goals.

Linking sustainability reporting and energy use through global reporting initiative standards and sustainable development goals

AbstractThis paper addresses the critical need for an integrated approach to sustainability reporting by examining the transition from internal combustion engine vehicles to electric vehicles within the automotive industry. By focusing on the top 8 highest-revenue global automakers in 2022, the study utilizes the Global Reporting Initiative (GRI) standards and United Nations Sustainable Development Goals to assess contributions to SDG 7 (affordable and clean energy) and other pertinent indicators. A comprehensive content analysis and logistic regression analysis are employed to explore the correlation between energy use and compliance with GRI standards from 2018 to 2022. The findings reveal significant trends in sustainability reporting, with a noted decrease in quality in the final year analyzed. Specifically, GRI 302-3 (energy intensity) shows a significant negative relationship with energy consumption, indicating higher energy usage correlates with lower compliance. The study reinforces the necessity for more transparent and effective sustainability reporting frameworks to enhance corporate practices and drive progress toward sustainability goals. Graphical abstract

Eco-innovation minimizes the carbon footprint of wine production

Wine industry faces significant sustainability challenges in the wake of climate change. Life cycle assessments for carbon footprint in wineries suggest that the conventional farming exhibits higher values of 0.06–3.0 kg CO2-eq bottle–1 of 750 mL wine as compared to mixed and organic farming. Life cycle assessment findings highlight that most studies often overlooked the resources in farming practices, biogenic emissions, and wastewaters in the overall reduction of winery carbon footprint. We demonstrate that the adoption of eco-innovations such as constructed wetlands and Phycosol utilize the overlooked resource loop and significantly reduce the winery carbon footprint. Empirical data analysis suggests that the use of these eco-innovative models results in 25‒30% reduction of CO2 emissions bottle–1 of 750 mL wine besides embracing Sustainable Development Goal 9, and effectively synergizing with Sustainable Development Goals 6 and 12, thus emphasizing their critical role in ensuring the sustainability of wine production.

Multidimensional spatial inequality in China and its relationship with economic growth

Spatial inequality erodes social cohesion and political stability, impacting global sustainable development and human well-being. This study examines spatial inequality in China across economic, social, environmental, infrastructural, and innovation dimensions, exploring how these inequalities evolve with economic development. Drawing on the Sustainable Development Goals and Chinese planning goals, we selected 13 indicators pertinent to human well-being. We employed the population-weighted coefficient of variation, Gini coefficient, and Moran’s I to assess spatial inequalities and analyzed their relationship with economic growth. The findings reveal that China currently exhibits the highest spatial inequality in innovation and the lowest in the social dimension. Since 1990, most indicators have trended towards decreasing spatial inequality, except for unemployment rates and carbon emissions, which have increased. The economic and innovation gap between the eastern coastal regions and the central and western regions has widened, whereas disparities in housing, healthcare, roads, and digitalization have narrowed. China’s experience demonstrates that Williamson’s inverted U-shaped hypothesis extends beyond the economic domain to encompass education, healthcare, infrastructure, and digitalization, providing policy insights for addressing regional inequalities in China in the post-pandemic era.