In the context of globalization, the 2030 sustainable development goals pose a huge challenge to the coordinated development of economy and environment in emerging economies. The purpose of this article is to investigate whether globalization contributes to balance water consumption and economic growth in emerging economies. China is the largest developing country and the largest trader of goods in the world. From holistic and representative perspectives, this article analyzes the mechanisms affecting economic growth and water consumption in BRICS countries, Next Eleven (N11) countries and China. Combining decoupling model and econometric models, fully modified ordinary least squares (FMOLS) linear model and threshold panel nonlinear model are constructed. Both linear and nonlinear effects of trade and foreign investment on economic growth and water consumption are considered. The results show that, from a holistic perspective, globalization helps balance economic growth and water consumption in emerging economies. The impact of trade on water consumption in BRICS countries is negative. And with the increase of trade, its positive coefficient on water consumption in N11 countries gradually decreases. Foreign direct investment (FDI) plays a positive role in the coordinated development of economic growth and water environment in BRICS and N11 countries. Taking China as a representative country, there is a decoupling phenomenon between economic growth and water use during the study period. With the trade crossing the threshold successively, the promoting effect on economy increases first and then decreases, and the inhibiting effect on water consumption weakens. With the increase of foreign investment, its positive effect on GDP increases, and its positive coefficient on water consumption decreases. The conclusions from representative country and holistic perspective are consistent. Finally, some policy recommendations are put forward.

Environmental degradation has profoundly impacted both human society and ecosystems. The environmental Kuznets curve (EKC) illuminates the intricate relationship between economic growth and environmental decline. However, the recent surge in trade protectionism has heightened global economic uncertainties, posing a severe threat to global environmental sustainability. This research aims to investigate the intricate pathways through which trade protection, assessed by available trade openness data, influences the nexus between economic growth and environmental degradation. Leveraging comprehensive global panel data spanning 147 countries from 1995 to 2018, this study meticulously examines the non-linear dynamics among trade, economy, and the environment, with a particular emphasis on validating the EKC hypothesis. This study encompasses exhaustive global and panel data regressions categorized across four income groups. The research substantiates the validity of the EKC hypothesis within the confines of this investigation. As income levels rise, the impact of economic growth on environmental degradation initially intensifies before displaying a diminishing trend. Additionally, trade protection manifests as a detriment to improving global environmental quality. The ramifications of trade protectionism display nuanced variations across income strata. In high-income nations, trade protection appears to contribute to mitigating environmental degradation. Conversely, within other income brackets, the stimulating effect of trade protection on environmental pressure is more conspicuous. In other words, trade protectionism exacerbates environmental degradation, particularly affecting lower-income countries, aligning with the concept of pollution havens. The study’s results illuminate nuanced thresholds in the relationship between trade, economic growth, and environmental degradation across income groups, emphasizing the heterogeneous impact and underlying mechanisms. These findings provide valuable insights for policymakers, urging collaborative efforts among nations to achieve a harmonious balance between economic advancement and environmental preservation on a global scale.

Research on the impact of foreign direct investment (FDI) on environmental quality has not reached consensus. This paper examines the potential structural break in the relationship between FDI and the environment from the perspective of economic scale. The results of the panel threshold estimation for 67 countries of different income groups show that the impact of FDI on carbon emissions shifts from positive to negative at different income level stages, using GDP as the threshold. This conclusion is further verified by the group regression results of the robustness test. When the GDP per capita is below $541.87, FDI shows a significant positive impact on carbon emissions, and this interval corresponds to a wide range of low-income economies today, however, when the GDP per capita exceeds $541.87, this positive impact almost disappears. The negative impact of FDI on carbon emissions manifests itself once the GDP per capita reaches $46515, and the sample countries corresponding to this interval since 2014 are mainly Switzerland, Iceland, Denmark, Sweden, the United States, Singapore, and Australia. Therefore, we call on countries to raise their income levels so that they can cross the lower threshold and thus take advantage of the emission reduction effect provided by FDI.

Urbanization and population aging are key indicators of human-related social attributes. With economic progress and urban development, human living conditions and the level of medical and health care have been continuously improved. Population aging has become a global trend, which brings serious challenges to the world. Environmental sustainability is closely linked to both urbanization and aging. Most of the existing studies only focus on the linear relationship between urbanization and the environment, and the effect of aging on the ecological environment is also controversial. It is of great significance to conduct systematic research on urbanization-aging-environment. This paper aims to reconstruct the linear relationship between urbanization and the environment, investigating the nonlinear effect of population aging on the nexus of urbanization-environment in 156 countries. This paper focuses on exploring ways to improve environmental quality from the perspective of population aging. To this end, the panel threshold regression models of urbanization‑carbon emissions and urbanization-ecological footprint are developed respectively. In which, urbanization is set as the explanatory variable, carbon emissions and ecological footprint are set as the explained variables, and population aging is set as the threshold variable. This paper divides four income groups according to the income standard of the World Bank, and regresses the panel data of the global and four income groups respectively to reflect the comprehensiveness of this work. The results show that there is a threshold effect of population aging on the nexus of urbanization‑carbon emissions/ecological footprint both the global scale and different income groups. On a global scale, urbanization has a positive effect on carbon emissions and ecological footprint. When aging crosses the threshold in turn, the promotion effect of urbanization on carbon emissions gradually becomes smaller, and the influence coefficient of urbanization on the ecological footprint shows an inverted U-shaped change trend. Aging can reduce the environmental pressures related to urbanization. There is heterogeneity in the nonlinear regression results for different income groups. Population aging variable in high income group, upper middle income group helps to improve environmental quality. In lower middle income countries and low income countries, aging slightly increases the coefficients of urbanization and ecological footprint.

Past studies related to embodied pollutant accounting reported that free trade has increased the environmental pollution of developing economies, because the developed countries "outsource" their pollutants to developing nations. The COVID-19 pandemic has stimulated the rise of the most serious protectionism after World War II. This study is aimed to discuss whether protectionism improve the environment in developing countries by developing a comprehensive evaluation model, which integrates multi-regional input-output (MRIO), data envelopment analysis (DEA), and scenario analysis. We revealed the role of protectionism from two perspectives: the single impact on pollutant emissions and the comprehensive impact on environmental efficiency. Specifically, the capital inputs, labor inputs, energy consumption, economic output, carbon dioxide, sulfur dioxide and nitrogen oxides emissions related to global trade activities were simulated based on the MRIO. And then, sector-level trade environmental efficiency was computed by intergrading the MRIO and DEA using a non-radial directional distance function. Finally, the environmental efficiency of both developing and developed countries under two scenarios with and without trade were estimated. The results confirmed that trade has increased the CO2, SO2 and NOX emissions of developing economies by 12.9%, 9.8% and 12.3%, and has reduced that of developed economies by 6.0%, 29.4% and 21.2%, respectively. However, the results also uncovered that the environmental efficiency of developing and developed economies was dropped by 3% and 5%, respectively, under no-trade scenario. We contend that protectionism is not conducive to the sustainable development of developing countries because it lowers their environmental efficiency, although it may reduce their territorial pollutant emissions. For developed countries, the single impact of protectionism on pollutant emission reduction and the comprehensive impact on environmental efficiency are both negative.

Although there are many studies on the urbanization-environment nexus, a few studies are related to the least developed countries. To fill the research gap, the long-term equilibrium of urbanization-environment nexus in 37 sub-Saharan African countries, and the impact of official development assistance on the urbanization-environment nexus in these countries are investigated in this work. To this end, urbanization is set as the explanatory variable, carbon dioxide emissions and ecological footprint are set as the explained variables, and official development assistance is set as the threshold variable. The results of the proposed nonlinear panel regression models show that effect coefficients of urbanization on carbon emissions and ecological footprint are both positive, which means urbanization increases the environmental pressure in these 37 countries. In addition, there are double threshold effects in official development assistance on urbanization-carbon emissions and urbanization-ecological footprint nexus. As assistance crosses the threshold in turn, the promotion effect of urbanization on carbon emissions first increases and then weakens, and the regression coefficient shows an inverted “U” shaped change trend. The contribution of urbanization to ecological footprint decreases with the increase of assistance, and the coefficients show a decreasing trend. This indicates that official development assistance reshapes the urbanization-environment nexus in these sub-Saharan African countries, indicating the official development assistance helps sub-Saharan countries to alleviate environmental pressure in the process of urbanization. Some policy implications are proposed. Recipient countries should make rational use of aid and create favorable conditions for the inflow of foreign capital through their own efforts, so as to improve the level of environmental pollution control. Countries should work together to correctly grasp the development opportunities brought by urbanization, and promote the process of urbanization while ensuring the quality of smart cities to reduce carbon emissions.

A comprehensive understanding of the impact of renewable/non-renewable energy consumption on ecological quality and economic growth can serve to the sustainability of energy, ecology, and economy. This paper provides a new perspective of the comprehensive system of the 3E model, and introduces indicator of social factor to examine the non-linear effects of urbanization on energy, economy, and the environment. A threshold panel regression model is developed using the data of 120 countries in the last 20 years. In the proposed model, renewable energy and non-renewable energy are explanatory variables, economic growth and ecological footprint are explained variables, and urbanization are threshold variable. Non-linear relationships are concretized and quantified in the research of global and different income groups. The results show that global renewable energy can promote economic growth while improving the environment. As the urbanization rate increases, the negative effect of renewable energy on the ecological footprint first weakens and then increases, and the positive coefficient on the economy maintains a growth trend. Non-renewable energy has a more obvious positive effect on economic growth, but it increases the ecological footprint. The development of urbanization strengthens its promotion of the economy and reduces its pressure on the environment. From the perspective of different income groups, renewable energy does not always suppress the ecological footprint. The energy transition reduces economic growth in the initial stages of urbanization in certain regions. After crossing the threshold, the coefficient changes of different income groups have similarities and differences. Based on the conclusions, some recommendations are put forward, including promoting the transformation of energy consumption structure, improving energy efficiency and accelerating the process of urbanization. The model in this paper is suitable for investigating the nonlinear impact of urbanization on the 3E system through panel data, and can provide theoretical support for studying the threshold effect of a country or economy. This study also shows the importance of renewable energy and the indirect effects of urbanization, which is helpful for formulating global sustainable and coordinated development policies.

The purpose of this article is to explore the impact of urbanization on the coupling of economic growth and environmental quality. The traditional environmental Kuznets curve (EKC) hypothesis explains the inverted Ushaped relationship between the economy and the environment. This study expands the traditional EKC theory by adding social indicator, which also corresponds to the three aspects (social, economic, and environmental) required for sustainable development in 2030. Based on the panel data of 134 countries from 1996 to 2015, the threshold regression model is applied to investigate the non-linear causality between the variables. The threshold variable is urbanization, and the impact mechanism of economic growth on carbon dioxide emissions and ecological footprint is tested. The results show that: urbanization strengthens the positive correlation between the economy and carbon emissions and ecological footprint. The positive effect of economic growth on the ecological footprint is greater than that of carbon emissions. Trade openness and natural resource rents increase environmental pressure. Population aging and renewable energy improve the quality of the environment. There is heterogeneity in the values and change trend of the regression coefficients of different income groups. Unlike the coefficient growth trend in the results of all countries, the following situations occur. As urbanization successively crosses the threshold, the positive effect of economic growth on carbon dioxide emissions in high income countries diminishes. The coefficient of the lower middle income group has an inverted U-shape. When the ecological footprint is the explained variable, the coefficient of the high income group becomes U-shaped.

A more comprehensive understanding of the impact of the COVID-19 pandemic on changes in pollution could serve us to better deal with the environmental challenges caused by the pandemic. Existing studies mainly focused on the linear impact of the pandemic on the pollutants without considering the impact of other factors. To fill the research gap, the nonlinear relationship between pandemic and pollutants with considering the temperature factor was explored by developing panel threshold regression approach. In the proposed approach, the number of confirmed cases was set as explanatory variable, concentrations of NO2 and PM2.5 were set as explained variables, temperature was used as threshold variable, and other air pollution indicators were used as control variables. The results showed that there is a threshold effect between the changes in confirmed COVID-19 cases and the concentrations of PM2.5 and NO2, confirming the impact of the pandemic on pollutions was nonlinear. The results also show that the negative impact of pandemic on pollution increased when the temperature was rising. This work had theoretical and practical significance. The nonlinear research perspective of this article provided a methodological reference for exploring the relationship between epidemic and pollutant-related variables. Furthermore, this study expanded the scope of application of the threshold panel regression model and enriched the quantitative analysis of epidemics and pollutants.

Achieving equality in water usage is part of the sixth goal of the 2030 Agenda for Sustainable Development. A comprehensive understanding evolution of inequality in water use and the driving factors behind the inequality can facilitate to implement equality in water consumption. In this work, the inequality index was used to measure China's water consumption inequality from 2004 to 2018 and the decomposition technique was used to decompose the status of inequality and the evolution of inequality. The results show the inequality in its water consumption was not reduced obviously despite China's rapid economic growth. There were 38.71% of provinces in China whose per capita water consumption was greater than the national average, mainly in the western region. For the three regions of China, the intraregional inequality was much greater than the interregional inequality. The western index was the largest and the eastern was the smallest. Among the factors that cause the inequality in water consumption, no one factor has been dominant at all times. Moreover, the effects of different factors changed over time. It is almost impossible to reduce inequality in water consumption through policy adjustment to several factors. China's example show that economic development cannot reduce the inequality in water consumption. More targeted policies and more efforts are required to reduce the inequality in water consumption.

This work is aimed to explore the impact of structural changes in economy (primary industry/total GDP), population (population aged 15-64/total population), and resource (groundwater resource/total water) on the correlation between urbanization and water consumption at national and subnational level. To this end, a fixed effect panel regression approach and three panel threshold regression approaches are developed using updated data of China's 31 provinces. The results show that there is a threshold between urbanization changes and water consumption, which means that there is a nonlinear relationship between changes in social structure and water consumption. There is a significant negative non-linear correlation between urbanization changes and water consumption. From a national scale, when the economic structure and resource structure change, the value of the negative non-linear coefficient between urbanization change and water consumption becomes larger. When the population structure changes, the negative non-linear correlation between urbanization changes and water consumption shows a "U"-shaped change. The threshold effect and structural mutation points in different regions are heterogeneous. There are differences in coefficient change trends for the three threshold variables. Some policy implications are put forward related to our empirical results.

Increasing water consumption from various economic activities has posed increasing challenges for the sustainability of developing countries. In particular, China is facing a sharp conflict between rapid economic development and water shortage. Evaluating the decoupling state between economic growth and water consumption and exploring the driving factors behind this could serve to develop strategy to moving to economic growth without water use growth. To this end, this work uses the Tapio decoupling and LMDI decomposition methods to evaluate the decoupling performance between China's water consumption and economic growth at the national and provincial levels, and six driving factors are decomposed, namely water consumption intensity, industrial structure, economic development, water resource utilization rate, water resource endowment and population size. Results show that: (1) Only two decoupling states, strong decoupling and weak decoupling, occurred at national level, and the decoupling index shows a decreasing trend. (2) 31 provinces showed only two states of strong decoupling and weak decoupling. More than 60% of the provinces showed strong decoupling after 2011, and the decoupling effect was significantly better than that of 2004-2011. (3) The effects of water consumption intensity and industrial structure drive the occurrence of decoupling. Economic level and population size have a positive incremental effect on water consumption. Finally, we propose policy recommendations such as developing water-saving technologies and optimizing industrial structure to promote water sustainability. The comprehensive methodology in this paper provides a theoretical reference for research in other countries or other environmental issues. Governments in various regions can formulate effective measures to achieve sustainable use of water resources, responding to the 2030 Agenda for Sustainable Development.

Water issue is one of the challenges of urban sustainability in developing countries. To address the conflict between urban water use and economic development, it is required to better understand the decoupling states between them and the driving forces behind these decoupling states. The transformed Tapio decoupling model is applied in this paper to study the decoupling relationship between urban industrial water consumption and economic growth in Beijing and Shanghai, two megacities in China, in 2003–2016. The factors driving decoupling are divided into industrial structure effect, industrial water utilization intensity effect, economic development level effect, and population size effect through Logarithmic Mean Divisia Index (LMDI) method. The results show that: (1) the decoupling states of total water consumption and economic growth in Beijing and Shanghai are mainly strong decoupling and weak decoupling. In comparison, Shanghai’s decoupling effect is better than Beijing; (2) regarding decoupling elasticity, Beijing is higher than that of Shanghai in tertiary industry and lower in primary industry and secondary industry. As a result, Beijing’s decoupling level is worse than Shanghai in tertiary industry, while better in primary industry and secondary industry; (3) The common factors that drive the two megacities’ decoupling are industrial structure effect and industrial water utilization intensity effect. The effects of economic development level and population size mainly present weak decoupling in two megacities, but the decoupling state is optimized year by year. Finally, based on the results, some suggestions for achieving the sustainable development of urban water use are proposed.