Agricultural HANPP Embodied in Consumption: Tracing Pressure on Ecosystems Based on an MRIO Analysis.

Agriculture is one of humankind's most significant sources of biomass; it also places tremendous pressure on ecosystems through its increasing demand for agricultural products. However, few studies have assessed human pressures on ecosystems from agricultural production and consumption based on a whole-supply-chain perspective. Based on the concept of human appropriation of net primary productivity (HANPP), we evaluate trends of agricultural HANPP embodied in consumption from a global perspective and trace the pressure from agriculture production that is exerted on the environment using an environmentally extended multiregional input-output (MRIO) model. The results show that agricultural HANPP embodied in consumption accounted for over two-thirds of total HANPP but brought about less than 7% of global value added. India, Brazil, and China were found to have the highest level of agricultural HANPP embodied in consumption. Agricultural net exporters were found to usually be low- and lower-income countries, while net importers are found to be high-income countries. According to the driving factor analysis, high-income and low-income countries should cooperate by adjusting consumption patterns and sharing agricultural technology to alleviate the pressure from agricultural production. Our study highlights the importance of agrarian expertise sharing and the need to develop sustainable and green agricultural production.

Impact of International Trade on the Carbon Intensity of Human Well-Being.

There has been a longstanding debate about the impact of international trade on the environment and human well-being, yet there is little known about such environment and human well-being trade-off. Here, we explore the effect of international trade on the carbon intensity of human well-being (CIWB) globally under the current global trade system and a hypothetical no-trade scenario. We found that between 1995 and 2015, CIWB of 41% of countries declined and 59% of countries increased, caused by international trade, and this resulted in a reduction of the global CIWB and a decline in CIWB inequality between countries. International trade decreased CIWB for high- and upper-middle-income countries and increased CIWB for lower- and middle-income countries. In addition, our results also show that decreases in emission intensity are the most important driver of lower CIWB and the percentage contribution of emission intensity to the improvement in CIWB increases with income. The reduction of emission intensity, population growth, and increase in life expectancy all contribute to CIWB reduction, while the consumption level is the primary factor driving CIWB growth. Our results underscore the importance of studying the impact of international trade on the CIWB of countries at different stages of development.

Evolution and control of the COVID-19 pandemic: A global perspective.

We investigated the factors influencing the progression of the pandemic from a global perspective by using the Geodetector and Correlation methods and explored the pandemic response policies and effects in different countries. The results yielded three notable findings. First, empirical results show the COVID-19 pandemic is influenced by various factors, including demographic and economic parameters, international travelers, urbanization ratio, urban population, etc. Among them, the correlation between urban population and confirmed cases is strongest. Cities become the key factor affecting the COVID-19 pandemic, with high urbanization levels and population mobility increases the risk of large-scale outbreaks. Second, among control measures, School-closures, International-travel-restrictions, and Public-gathering-restriction have the best control effect on the epidemic. In addition, the combination of different types of control measures is more effective in controlling the outbreak, especially for Public-gathering-restrictions ∩ School-closures, International-travel-restrictions ∩ Workplace-closures, Public-transport-restrictions ∩ International-travel-restrictions. Third, implementing appropriate control measures in the first month of an outbreak played a critical role in future pandemic trends. Since there are few local cases in this period and the control measures have an obvious effect.

Emission reduction target, complexity and industrial performance.

To tackle climate change, Chinese government has applied an array of mitigating measures to reduce CO2 emissions. During the 11th Five-year Plan, Chinese government set the emission reduction target policy to reduce energy consumption per unit of gross domestic product (GDP) by 20%. This paper attempts to estimate the effect of this emission reduction target policy on industrial performance from complexity perspective. The result shows more complex industrial structure is related to less coal consumption. In general, emission reduction target policy has a negative effect on the probability of branching into new industries and lower the productivity and profitability of a given industry. However, this negative effect is weaker for more complex industries. Only for industries with very high complexity, emission reduction target policy can improve the performance of an industry rather than exerting a negative effect. Our finding not only helps to design a more effective policy to achieve industrial development strategy, but also provides a potential way to achieve economic growth while reduce the emission of greenhouse gases at the same time.

Examining the effects of education level inequality on energy consumption: Evidence from Guangdong Province.

The dramatic economic growth and urbanization witnessed in China have been accompanied by a range of social and environmental problems. To comprehensively understand the influence of social inequality on climate change, the study analyzed the mechanism and pathways of the effects of education level on energy consumption, selecting typical indicators to reflect (i) the education quality within the population and (ii) the level of education development in order to evaluate the impact of education inequality and disparity. Under the framework of a STIRPAT model hypothesis, we investigated how the education level in Guangdong Province influenced energy consumption, using panel data from 2002 to 2017 and making a distinction between the Pearl River Delta region and the "non-Pearl River Delta" region. The empirical results show a significant disparity between the education level and energy consumption of the two regions. The education level has exerted significant effects in relation to energy consumption in the whole of Guangdong province. In cities with lower education levels, this impact was more obvious. However, in places with higher levels of education, this impact was overshadowed by other more significant factors, such as income level. The quality of the education within the population was found to increase energy consumption in the non-Pearl River Delta region, while this did not significantly impact on energy consumption within the Pearl River Delta. Our results hold implications for policy makers that they should adopt education methods and interventions to promote low-carbon knowledge and awareness that reflect the different stages of education development of regions. In this way, residents can be encouraged to develop low-carbon lifestyles, thereby reducing energy consumption and mitigating CO2 emissions.

How global value chain participation affects China's energy intensity.

China is currently the world's largest energy consumer and, at the same time, a huge trading power. With the increasing complexity of production processes along global value chains (GVCs), it is of great significance to study the impact of GVC participation on energy intensity. By using production length to measure GVC participation, this study first calculates China's manufacturing industry's total average production length of GVC activities and its three segments: length of pure domestic production, length of traditional trade production, and production length of GVC activities. Next, this study explains the influence mechanisms of GVC participation on energy intensity, proposes three research hypotheses, and conducts econometric analyses to examine the influence of production length and its three segments on energy intensity for a sample of China's manufacturing sector from 2000 to 2014. The results indicate that the total average production length of GVC activities significantly affects energy intensity and presents an inverted U-shaped, non-linear relationship wherein China has passed the critical point. The interactions between the three segments of production length and energy intensity also present an inverted U-shaped, non-linear relationship, where the impacts of the pure domestic segment and the "traditional" trade related segment on energy intensity have passed the critical point, while that of the segment related to GVC production has not yet crossed the critical point. It is suggested that further promoting China's manufacturing industry towards the mid-to-high end of the GVCs and breaking through its captive and "squeezed" position in the GVCs could significantly contribute toward curtailing energy intensity.

Dynamics, differences, influencing factors of eco-efficiency in China: A spatiotemporal perspective analysis.

Eco-efficiency can effectively measure the relationship between economy, resources, environment, and development. Understanding eco-efficiency is of great practical significance for decision makers tasked with addressing and delivering sustainable socioeconomic development. Based on an "undesirable output Slacks-Based Measure models," this study evaluated the eco-efficiency of 285 Chinese cities during the period 2004-2014, analyzing spatiotemporal dynamics and influencing factors using a Spatial Autocorrelation Panel Data Model. The main results are as follows: From the spatial perspective, eco-efficiency in Chinese cities generally evidenced an M-shaped trend (increasing-decreasing-increasing-decreasing), and imbalanced spatiotemporal dynamics. Furthermore, the urban eco-efficiency generally presented a distinct convergence of HH cluster and LL cluster clubs, with the latter being the most dominant. From the regional point of view, there existed a decreasing trend in the efficiencies of cities, from eastern China to central and western China. In addition, we identified significant differences in the eco-efficiency of different cities in China, and the coefficient of variation of eco-efficiency showed a general decrease. The results of our estimation of the factors affecting urban eco-efficiency showed that the economic development level, the industrial structure, import and export trade, and the information level all had significant positive influence, and local government expenditure, social retail sales of consumer goods, and infrastructure all had a negative effect on urban eco-efficiency. This paper puts forward numbers of suggestions for ways to promote social, ecological, and economic development in Chinese cities, based on our findings.

Impacts of Urban Expansion on Terrestrial Carbon Storage in China.

Urban expansion is one of the main factors driving terrestrial carbon storage (TCS) changes. Accurate accounting of TCS and rigorous quantification of its changes caused by historical urban expansion may help us to better predict its changes in the future. This study focuses on the carbon impacts of urbanization in China where the share of the urban population has increased from 18% in 1978 to 59% in 2017 and the growing will continue in the coming decades. Our results show that China's TCS decreased at an accelerating pace over the past three decades with an average reduction of 0.72TgC/y in 1980-1990 and 8.72TgC/y in 2000-2010, mostly due to conversion from cropland and woodland to urban land. Through simulating urban expansion under four scenarios from 2010 to 2050, we found a potential increasing trend in land conversion from woodland to urban land. This conversion trend would result in carbon storage loss at an average rate of 9.31TgC/y ∼ 12.94TgC/y in 2010-2050. The increasing trend in both land conversion and carbon storage loss is especially visible in the population centers of the Yangtze River Delta and the Pearl River Delta. Considering that the indirect emission effects of urbanization, such as farmland displacement, population migration, and land degradation, may be much larger, the overall emission impact of forthcoming urban expansion in China would increase the uncertainty of the nation's carbon emissions and potentially undermine China's targets as committed in the Paris Climate Agreement.

Does migration of pollution-intensive industries impact environmental efficiency? Evidence supporting "Pollution Haven Hypothesis".

The existence of Pollution Haven Hypothesis (PHH) is still being hot debated due to its importance in environmental and industrial policymaking. However, research concerning the PHH in relation to local areas and regions within country borders is limited. Therefore, this research focused on the relationship between the migration of pollution-intensive industries (PIIs) and environmental efficiency (EE) at the prefecture level throughout China's Guangdong Province from 2001 to 2014. Firstly, this research found that many PIIs migrated from the core industrial region of the Pearl River Delta (PRD) to peripheral Non-Pearl River Delta (NPRD) areas after 2006. A Data Envelopment Analysis (DEA) model was used to evaluate industrial EE of a range of different cities. Then, analysis using PMG/ARDL regression model shows that industrial EE maintained a negative long run equilibrium relationship with PII migration in the NPRD region where PIIs have moved out, but had little correlation with PII migration in the PRD where PIIs have moved in. The results show pollution transfer caused by migration of PIIs from the PRD to the NPRD region in Guangdong Province that supports the PHH. The NPRD had become a pollution haven for PIIs in the PRD. This study proposes that policymakers should build a series of environmental regulatory policies and industrial developing policies to avoid the creation of pollution havens in the developing area in China, instead of simply pollution emission control policies.

Changing and Differentiated Urban Landscape in China: Spatiotemporal Patterns and Driving Forces.

Urban landscape spatiotemporal change patterns and their driving mechanisms in China are poorly understood at the national level. Here we used remote sensing data, landscape metrics, and a spatial econometric model to characterize the spatiotemporal patterns of urban landscape change and investigate its driving forces in China between 1990 and 2005. The results showed that the urban landscape pattern has experienced drastic changes over the past 15 years. Total urban area has expanded approximately 1.61 times, with a 2.98% annual urban-growth rate. Compared to previous single-city studies, although urban areas are expanding rapidly, the overall fragmentation of the urban landscape is decreasing and is more irregular and complex at the national level. We also found a stair-stepping, urban-landscape changing pattern among eastern, central, and western counties. In addition, administrative level, urban size, and hierarchy have effects on the urban landscape pattern. We also found that a combination of landscape metrics can be used to supplement our understanding of the pattern of urbanization. The changes in these metrics are correlated with geographical indicators, socioeconomic factors, infrastructure variables, administrative level factors, policy factors, and historical factors. Our results indicate that the top priority should be strengthening the management of urban planning. A compact and congregate urban landscape may be a good choice of pattern for urban development in China.

The Effect of Economic Growth, Urbanization, and Industrialization on Fine Particulate Matter (PM2.5) Concentrations in China.

Rapid economic growth, industrialization, and urbanization in China have led to extremely severe air pollution that causes increasing negative effects on human health, visibility, and climate change. However, the influence mechanisms of these anthropogenic factors on fine particulate matter (PM2.5) concentrations are poorly understood. In this study, we combined panel data and econometric methods to investigate the main anthropogenic factors that contribute to increasing PM2.5 concentrations in China at the prefecture level from 1999 to 2011. The results showed that PM2.5 concentrations and three anthropogenic factors were cointegrated. The panel Fully Modified Least Squares and panel Granger causality test results indicated that economic growth, industrialization, and urbanization increased PM2.5 concentrations in the long run. The results implied that if China persists in its current development pattern, economic growth, industrialization and urbanization will inevitably lead to increased PM2.5 emissions in the long term. Industrialization was the principal factor that affected PM2.5 concentrations for the total panel, the industry-oriented panel and the service-oriented panel. PM2.5 concentrations can be reduced at the cost of short-term economic growth and industrialization. However, reducing the urbanization level is not an efficient way to decrease PM2.5 pollutions in the short term. The findings also suggest that a rapid reduction of PM2.5 concentrations relying solely on adjusting these anthropogenic factors is difficult in a short-term for the heavily PM2.5-polluted panel. Moreover, the Chinese government will have to seek much broader policies that favor a decoupling of these coupling relationships.

Assessing the spatiotemporal evolution and socioeconomic determinants of PM2.5-related premature deaths in China from 2000 to 2021.

China's swift socioeconomic development has led to extremely severe ambient PM2.5 levels, the associated negative health outcomes of which include premature death. However, a comprehensive explanation of the socioeconomic mechanism contributing to PM2.5-related premature deaths has not yet to be fully elucidated through long-term spatial panel data. Here, we employed a global exposure mortality model (GEMM) and the system generalized method of moments (Sys-GMM) to examine the primary determinants contributing to premature deaths in Chinese provinces from 2000 to 2021. We found that in the research period, premature deaths in China increased by 46 %, reaching 1.87 million, a figure that decreased somewhat after the COVID-19 outbreak. 62 thousand premature deaths were avoided in 2020 and 2021 compared to 2019, primarily due to the decline in PM2.5 concentrations. Premature deaths have increased across all provinces, particularly in North China, and a discernible spatial agglomeration effect was observed, highlighting effects on nearby provinces. The findings also underscored the significance of determinants such as urbanization, import and export trade, and energy consumption in exacerbating premature deaths, while energy intensity exerted a mitigating influence. Importantly, a U-shaped relationship between premature deaths and economic development was unveiled for the first time, implying the need for vigilance regarding potential health impact deterioration and the implementation of countermeasures as the per capita GDP increases in China. Our findings deserve attention from policymakers as they shed fresh insights into atmospheric control and Health China action.

Urban population density and energy conservation: Empirical evidence from 276 cities in China.

Reducing urban energy consumption is a crucial step towards achieving sustainable urban development. Urban energy plays a fundamental role in urban development, and while previous studies have examined the relationship between population size and energy conservation, the impact of increasing population density on per capita energy consumption (PCEC) remains unclear. To achieve urban energy conservation in China, it is vital to comprehend this significant relationship. This study constructs a spatial regression model to examine the relationship between population density and PCEC using 9 years of balanced panel data from 276 cities to fill a gap in the literature. The results of spatial autocorrelation indicate a significant negative relationship and heterogeneity between population density and PCEC. The results of spatial regression show that for every 1% increase in population density, there is a subsequent increase in PCEC of 0.074%. Our findings suggest that lower PCEC correlation is associated with higher urban population density. This study can be a reference for policymakers seeking new energy conservation strategies for urban development.

Do development zones increase carbon emission performance of China's cities?

As a special industrial cluster policy, "development zones" (DZs) represent the growth poles of the regions in which they are located; in China, they fulfill the dual tasks of industrial upgrading and green transformation. While the existing literature has paid close attention to the economic effects of development zones, few efforts have been made to examine their climate effects. Therefore, in the context of China's efforts to achieve "carbon peaking and carbon neutrality", this paper for the first time provides evidence of the effect of development zones on urban carbon emission performance; it does this by constructing a difference-in-difference (DID) model, which is based on panel data for Chinese cities in the period 1997-2017. The findings of the study indicate that the establishment of development zones had a positive influence on urban carbon emission performance without time lag effects. Our heterogeneity analysis of city groups indicated that development zones located in eastern region, or in large or coastal cities, exerted a more significant impact. The mechanism analysis that we conducted demonstrates that development zones promote carbon emissions performance by increasing GDP and reducing carbon emissions. Finally, this paper puts forward a series of policy measures, which are intended to strengthen the environmental benefit of development zones within the context of an urban green transition.

Measurement and Coupling Coordination of High-Quality Development in Guangdong Province of China: A Spatiotemporal Analysis.

Regional high-quality coordination plays a crucial role in promoting high-quality national development. Guangdong province is a trailblazer in China's reform and opening-up policies and high-quality development. This study analyzes the high-quality development of the economic, social, and ecological environments from 2010 to 2019 in Guangdong with the entropy weight TOPSIS model. Meanwhile, the coupling coordination degree model is used to investigate the spatial-temporal pattern of the coupling and coordinated development of the three-dimensional system in 21 prefecture-level cities. The results show that the high-quality development index of Guangdong increased from 0.32 to 0.39, a 21.9% increase during 2010-2019. The Pearl River Delta had the highest value of the high-quality development index, whereas Western Guangdong had the lowest level in 2019. Guangzhou, Shenzhen, Zhuhai, and Dongguan are the core cities in the high-quality development of Guangdong, with the index decreasing from the Pearl River Delta estuary cities to the province's edge. We also found that the coupling degree and coupling coordination of high-quality development of the three-dimensional system grew slowly during the study period. Half of the cities in Guangdong entered the stage of benign coupling. Except for Zhaoqing, all cities in the Pearl River Delta have a high coupling coordination degree of high-quality development of the three-dimensional system. This study provides valuable references for the high-quality, coordinated development of Guangdong province and some policy suggestions for other regions.

Investigation on Thermal Barrier Coating Damages for Ultrafast Laser Drilling of Cooling Holes.

To mitigate the challenges pertaining to coating damage and processing defects arising from the utilization of ultrafast laser drilling for microhole creation in thermal barrier coatings (TBCs), thereby exerting substantial influence on the long-term durability of these microholes, the investigation proposes a comprehensive methodology. It encompasses the design of a two-factor four-level full factorial experiment and the execution of experimental research on picosecond laser drilling of TBC microholes. By meticulously analyzing the morphology of the microholes and the coating interface, the damage mechanisms associated with picosecond laser drilling of TBC microholes, as well as the influence of laser process parameters on coating damage, are revealed. The findings reveal that the optimal microhole entrance quality and the lowest roughness along the hole perimeter are attained at a laser power of 12 W and a scanning speed of 320 mm/s. Moreover, at a laser power of 30 W and a scanning speed of 320 mm/s, the minimal crack length on the blunt angle side of the hole and the highest machining quality are observed.

Patterns and driving forces of the agricultural water footprint of Chinese cities.

The patterns and determinants of different types of agricultural water footprints in China are poorly understood at the prefecture-city level. In this paper, we evaluate Chinese agricultural water footprints from 2000 to 2017 and analyzed their spatio-temporal characteristics. Our estimation results show that the annual average agricultural water footprint in China was 5.038 × 109 m3, and the proportions of green water, blue water, and gray water were 70%, 9%, and 21%, respectively. In addition, high agricultural water-footprint cities with obvious urban agglomeration effects are mainly located in the Northeast, the Huanghuai River, the Yangtze River Basin, and Northwestern of Xinjiang, while low agricultural water-footprint cities are concentrated in high coastal urbanization-level areas or less developed agricultural areas of the west. We also investigate their determinants using a spatio-temporal fixed-effect model and find that GDP per capita, total investment in fixed assets, the income level of rural residents, the proportion of food grown, spray and drip irrigation technology, low-pressure pipe irrigation technology and seepage control irrigation technology have significant positive impacts on the agricultural water footprint. In contrast, the proportion of secondary and tertiary industries, social retail consumption, urbanization, technology expenditure, and the effective irrigation area proportion have a significant inhibitory effect. The primary determinants of the agricultural water footprint also vary substantially across water footprint categories (green, blue, and gray water footprints) and regions. Our findings imply that the agricultural water footprint should be incorporated into city water resource management and monitoring system.

Spatiotemporal patterns of global carbon intensities and their driving forces.

Carbon intensity (CI) is a valuable indicator of the balances struck by the world's governments between economic growth and environmental issues. This study investigates spatiotemporal variations in the CI levels related to energy consumption, as well as the spatial heterogeneity of its driving forces, in 208 countries globally during 2000-2018. To do this, we obtained data from the International Energy Agency (IEA) and the World Bank, employing methods of exploratory spatial data analysis (ESDA) and standard deviation ellipse (SDE) in order to analyze CI's spatiotemporal variations. We also performed a geographically weighted regression (GWR) analysis to determine the spatial heterogeneity of CI and the strength of its influencing factors. Our results reveal that: (1) Carbon emissions from energy consumption increased, while CI decreased globally, with the CI of most countries and regions declining significantly. (2) Global CI evidenced a heterogeneous spatial distribution, with higher-value areas concentrated in Asia and lower-value areas in Africa and Western Europe; obvious spatial agglomeration was also presented, especially with respect to High-High and Low-Low agglomerations, and the gravity center point moved from the northeast to the southwest. (3) The 8 influencing factors investigated in this study all had effective explanatory power in relation to CI globally. These factors showed significant spatial heterogeneity, and energy structure was the only factor to have a fully positive influence on CI, while foreign direct investment, foreign trade openness, industrial structure, total population, and energy intensity, mainly exerted a positive influence, and the urbanization rate and GDP per capita exerted a negative influence. By clarifying the spatiotemporal variations characteristics of global CI and the spatial heterogeneity of its influencing factors, this study provides a targeted reference for reducing CI and promoting sustainable development, globally.

The varying driving forces of urban land expansion in China: Insights from a spatial-temporal analysis.

The impacts of socioeconomic development on urban land expansion in China vary across space and time; however, comprehensive investigation of this issue remains scarce in the existing literature. This study used a geographically and temporally weighted regression model (GTWR) to examine the spatiotemporally heterogeneous impacts of socioeconomic factors on urban land expansion in China using a newly available annual urban land-use dataset from 2000 to 2015. We found that although the eastern region has maintained its leading role (53.79%) in terms of urban expansion, the share of the central (20.34%) and western (16.13%) regions is gradually increasing. Cities with a higher administrative status tended to expand more rapidly; however, increasingly expansion has also taken place in the prefecture-level cities in recent years. We further found that Gross domestic product (GDP) growth, population density, and capital investment positively contributed to the expansion, although the directions and strengths of association between these factors and urban expansion varied across space and time. Industrial structure and foreign direct investment (FDI) showed a similar variation change trend, with the number of cities evidencing a negative relationship rapidly expanding and increasingly being seen not just in northwest China but also in the southeast during the study period. We also found that the correlation between public finance expenditure and urban expansion presented significant north-south differentiation. It is worth noting that governmental behavior plays a significant role in driving urban land expansion. Our empirical study confirmed the spatiotemporal heterogeneous effects of socioeconomic factors on urban expansion in China, providing useful insights for city governments and urban planners.

A global North-South division line for portraying urban development.

Rapid urbanization has tremendously changed the global landscape with profound impacts on our society. Nighttime light (NTL) data can provide valuable information about human activities and socioeconomic conditions thus has become an effective proxy to measure urban development. By using NTL-derived urban measures from 1992 to 2018, we analyzed the spatiotemporal patterns of global urban development from country to region to city scales, which presented a distinct North-South divergence characterized by the rising and declining patterns. A global North-South division line was identified to partition the globe into the Line-North and the Line-South geographically, which accorded with the socioeconomic difference from the aspects of urban population and economy. This line may keep a certain degree of stability deriving from the trends of population and economic information but also bears uncertainties in the long term.