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Air pollutants, primarily PM2.5, have inflicted significant harm on public health and sustainable urban development in the Yangtze River Economic Belt (YREB). Previous studies often neglected the coordinated measurement of PM2.5 human and natural factors in this area. Therefore, this paper focuses on the YREB. Using a geographic information system (GIS) platform, along with remote sensing and statistical data spanning from 2000 to 2020, this study employs spatial analysis to uncover the spatial-temporal characteristics of PM2.5 and its spatial agglomeration patterns. Furthermore, this study further employs the spatial panel Durbin model to investigate the natural and anthropogenic factors driving PM2.5 concentrations across multiple scales. The analysis of the results reveals an "M"-shaped change trend in PM2.5 concentrations within the YREB. PM2.5 concentrations exhibit significant spatial agglomeration characteristics, whereby most urban agglomerations are high-pollution areas. Moreover, the changes in PM2.5 concentrations are jointly influenced by several factors, including the secondary industry, urban built-up area, population density, annual precipitation, and NDVI. Furthermore, the dominant factors influencing PM2.5 concentrations in the three major urban agglomerations exhibit both similarities and differences. In addition, for effective governance coordination across regions, policymakers should diligently consider both the shared predominant factors and the varying factors specific to each region in the future. This study expands the research content of watershed PM2.5 collaborative governance, and further provides practical support for other watershed environmental governance and urban sustainable management. [ABSTRACT FROM AUTHOR]

Rapid urbanization of the Belt and Road Initiative (BRI) region has undoubtedly led to changes in the scale, form, and pattern of cities to accommodate the expansion of industry, housing, and commerce and to produce sustained impacts on environmental sustainability. However, limited studies have yet to systematically investigate the urban expansion in this area. Based on a systematic research path of "pattern-mode-coordination-sustainability", this study quantified the urban expansion dynamics of BRI countries and 80 representative cities from 2000 to 2018 using multi-source remote sensing data and the Global Atlas of Urban Expansion. The results show that in terms of dynamic rules, the share of urban lands grew from 0.32 % in 2000 to 0.66 % in 2018 (an increase of 250,600 km2) and is estimated to increase to 1.68 % in 2018–2030. Countries in developing regions (i.e., West Asia, North Africa, and Southeast Asia) are predicted to become the new high-value centers of urban expansion intensity (UEI). The UEI of BRI cities showed a significant developing region orientation and "high in the east and low in the west" distribution pattern but would gradually shift towards a spatially homogeneous and discrete distribution. BRI cities can be divided into four expansion modes (center-periphery, double-winged strip, dual-core cluster, and single-winged mutation expansion), each with a different evolutionary dynamic mechanism. Regarding coordination, there is a great demand for land expansion by population and economic growth in BRI cities. This dependence increased as the city's UEI index rose; when the UEI exceeded 3 %, the dependence became more pronounced. The investigations also showed that the adverse ecological effects of urban land expansion are gradually increasing at the urban scale. Furthermore, the ecological impacts of population growth are usually the strongest for BRI's countries and cities, and the intensity showed a synergistic growth trend with the UEI index. This study provides new insights into the dynamic features of BRI's urban expansion from national to urban scales and historical to future periods, while also contributing new perspectives from the BRI to optimal global land management and sustainable urban development. • Provides new insights into BRI' s urban expansion from national to urban scales and from historical to future periods based on the research path of "pattern-mode-coordination-sustainability". • Dependence of population and economic growth on urban land use increased with city's UEI index. • Ecological impacts of population growth are the strongest for BRI region, and showed a synergistic growth trend with the UEI index. [ABSTRACT FROM AUTHOR]

The climate ambition led by the net zero goal has prompted growing concern among international organizations about the carbon emissions effects of urbanization and foreign direct investment (FDI) in the Belt and Road Initiative (BRI) region. Due to the limited data experiments, the direction and externalities of the impact of urbanization and FDI on carbon emissions in the BRI region remain largely unclear, and accounting for urbanization is also isolated. To address this knowledge gap, this study quantified the direct and spillover effects of multi-dimensional urbanization and FDI on carbon emissions using multiple remote sensing data from 2000 to 2018. The study explored the spatial distribution, evolutionary trends, bivariate evolutionary relationships, and influence mechanisms of carbon emissions with multi-dimensional urbanization and FDI by combining temporal trend (Slope), bivariate spatial autocorrelation, spatial Durbin model (SDM), and other methods. The results indicate that from 2000 to 2018, the total BRI carbon emissions added 253 million tons at an average annual growth rate of 3.68%; since 2013, the average annual growth rate has dropped sharply to 1.34%. East and South Asian countries (especially China and India) posted the highest increase in carbon emissions and had faster growth rates in multi-dimensional urbanization and FDI. Only some European countries, such as France and Germany, achieved overall carbon reduction. The results highlight the adaptability of the "Environmental Kuznets Curve" hypothesis. The "Low-Low" was the main cluster type of the evolutionary trends of carbon emissions associated with each variable. Multi-dimensional urbanization and FDI directly contributed to local carbon emissions, but the effects have gradually weakened over time (except for land urbanization). After controlling for the direct effects, we found a widespread consistently enhanced positive effects of population urbanization and land urbanization on carbon emissions in adjacent areas (especially after the BRI implementation), while FDI reduced the direct impact and strengthened the gain effect on carbon reduction in adjacent regions. Our findings confirm the importance of integrating policies to reduce emissions in population, economy, land, and foreign investment and provide strong evidence for joint governance of carbon emissions among BRI countries. [ABSTRACT FROM AUTHOR]

Analyzing the impact of urban land expansion efficiency (ULEE) on ecosystem services (ESs) is crucial to constructing high-quality territorial spatial patterns within urban agglomerations (UAs). While numerous studies have investigated the coercion and disturbance of urban sprawl on the ecological environment, research examining the impact of urban sprawl from an efficiency perspective remains relatively rare. In this study, ten UAs of different levels of development in China are selected as the research objects, and prefecture-level cities are used as the primary research units. CO 2 emissions are included as undesired outputs in the measurement and research framework of expansion efficiency to reflect the vision and requirements of emission reduction and carbon neutrality. At the same time, the Spatial Durbin Model (SDM) is used to reveal the impact of ULEE on ESs in years 2005–2021. The main results are as follows: (1) The ULEE within the entire UAs areas exhibited a fluctuating trend across different periods. Efficiency variations were evident among UAs with different development levels. Spatially, the UAs in the central region showed relatively low ULEE, while the northwest and southeast UAs displayed relatively high ULEE. Besides, the expansion efficiency of core cities in each UA exceeded that of surrounding cities. (2) The ecosystem service value (ESV) within the ten UAs demonstrated a consistent downward trend. In terms of the rate of ESV decline among UAs with varying developmental levels, breeding UAs exhibited the most rapid decline, followed by growing UAs, while mature UAs experienced the slowest decline. (3) Over the study period, the ULEE in UA areas positively contributed to enhancing ESs, with varying effects observed across different time frames. Natural factors directly influenced ES changes, thereby affecting both ULEE and Es dynamics. In contrast, changes in social factors indirectly caused changes in ESs. This study underscores the importance of a comprehensive assessment of ULEE and ESs to provide a scientific reference for formulating high-quality social and economic development and territorial spatial planning. [ABSTRACT FROM AUTHOR]

Escalating global human activities elicit diverse ecosystem service responses, yet understanding remains limited. This study establishes a framework to clarify these responses, focusing on the Yangtze River Economic Belt in China. Analyzing 2000–2020 data, it calculates ecosystem service economic value and human footprint index. It introduces the ecosystem services response index and comprehensive responsiveness index to assess response characteristics and intensity to anthropogenic pressures. Results show a fluctuating decline in ecosystem services and an increase in anthropogenic pressures. There is a nonlinear relationship: ecosystem services decline with rising pressures, following a U-shaped trend. Notably, nonurban agglomerations experience more significant ecosystem service evolution than urban agglomerations due to differing environmental conditions. This highlights regional disparities in human activity impacts on ecosystems, crucial for planning. [ABSTRACT FROM AUTHOR]

[Display omitted] • Established a new theoretical framework to explain the relationship between ITU and ESSD. • Compared the supply and demand relationships of four types of ESs. • The temporal scale effect and spatial spillover effect of ITU on the supply and demand of different ESs exhibit significant variations. • Land use shifts, consumer preference changes, and industrial material flows resulted in direct, time-lagged, and indirect effects, respectively. • Introduced a potential zonal management approach to alleviate the contradictions in ESSD. Traditional industrial development models have already caused an imbalance in ecosystem services supply and demand (ESSD). As a response strategy, industrial transformation and upgrading (ITU) are increasingly playing a vital role in regulating the relationship among ESSD. However, research on the interplay and impact of these two aspects remains insufficient. Therefore, a comprehensive analysis of the complex effects of ITU on ESSD is essential for industrial planning and environmental management. We developed a theoretical framework to interpret how ITU impacts ESSD, from the perspective of the natural-social-economic composite ecosystem. Using the Yangtze River Economic Belt (YREB) as an example, we employed the Dynamic Spatial Durbin model (DSDM) to reveal the spatiotemporal effects of ITU on ESSD for four distinct types. The results indicated that from 2010 to 2021, the total supply of ecosystem services in the YREB exceeded the demand. The kernel density curves of ESSD ratios related to food production, carbon sequestration, water conservation, and soil conservation all show a trend of peak shifting to the bottom right over time. Additionally, pronounced spatial heterogeneity was observed in the ESSD ratios, with a notable clustering trend over time. Furthermore, the analysis of spatiotemporal effects decomposition revealed that ITU had a detrimental influence on the equilibrium between the supply and demand of food production, with this adverse effect intensifying and manifesting a stronger spatial spillover as time progressed. Positive effects were observed in the supply and demand for carbon sequestration and water conservation, both demonstrating significant spatial spillover effects. Steady negative spatiotemporal effects were noted for soil conservation supply and demand. Finally, we clarified the principal pathways through which ITU impacts ESSD. It offers policy recommendations for industrial development and ecosystem stewardship to mitigate the ESSD imbalance. [ABSTRACT FROM AUTHOR]

The synchronised phasor measurement units (PMUs), serving as 'GridEye', provide data that improve the observability and controllability of the power grid due to its high accuracy and high‐upload rate. However, missing or abnormal data may seriously affect its applications. This study proposes a method to recover the missing or abnormal amplitude data in PMU measurements (i.e. the active power, reactive power, positive sequence current, and voltage amplitude), based on the historical PMU data obtained from both ends of the line, which is independent of the transmission line parameters and the phase angle that may be influenced by synchronisation. First, the issues in the quality of measured PMU data are analysed, and the motivation of the proposed method is stated. Then, a method to screen out the bad data from the historical data is proposed based on the density‐based spatial clustering of applications with noise. Furthermore, the model of data recovery is established, and the recovery method, which recovers the voltage amplitude, active power, reactive power, and current amplitude in sequence, using historical amplitude data to calculate related recovery coefficients is proposed. Finally, the effectiveness and practicability of the proposed method are verified by examples of simulation and measured data. [ABSTRACT FROM AUTHOR]

Abstract Particles with a diameter of <2.5 μm (PM 2.5) have serious adverse-effects on human health, which have caused widespread public concern in recent decades. Currently, most of the existing research on PM 2.5 have used linear regression analysis; very few studies on the subject have been conducted using non-linear models. This study adopts a panel threshold model, which is seldom used in environmental studies, to examine the non-linear effects of environmental regulation and economic growth on PM 2.5 in 30 OECD countries, and we also explore the key driving socio-economic factors for PM 2.5 emissions. The results of our analysis show that, along with an increase in environmental policy stringency, PM 2.5 emissions first rise and then show no significant correlations, and thus a reduction in emissions can be expected if current trends continue. As for GDP per capita, significant and negative correlations are found across the three phases divided by the panel threshold model, indicating a promoting effect for PM 2.5 mitigation. In addition, public expenditure on the air sector correlated positively with PM 2.5 concentrations, expanding the share of service economy reward to reduce air pollution, and urban population ratio exhibits an inverted U-shaped pattern. Future studies may shed more light on the regulation-PM 2.5 nexus, and more studies are needed to confirm the existence of bi-directional correlations between economic development and air pollution. Graphical abstract Unlabelled Image Highlights • Environmental regulation show different impacts on PM 2.5 at high-, mid- and low-level phases; • GDP per capita is negatively correlated with PM 2.5 at 1% level; • Expansion of service industry reduces pollution; • An inverted U-shaped relationship exist between urbanization and pollution. [ABSTRACT FROM AUTHOR]

Africa has been undergoing a rapid urbanization process, which is critical to the achievement of the 11th Sustainable Development Goal (SDG11). Using population density data from LandScan, we proposed a population density-based thresholding method to generate urban land and urban population data in Africa from 2001 to 2019, which were further applied to detect the spatiotemporal characteristics of Africa's urbanization. The results showed that urban land and urban population have both grown rapidly in Africa, which increased by about 5.92% and 4.91%, respectively. The top three countries with the most intense urbanization process in Africa are Nigeria, the Democratic Republic of the Congo, and Ethiopia. The coupling relationship index of urban land expansion and population growth was 0.76 in Africa during 2001–2019. Meanwhile, the total proportion of uncoordinated development types at the provincial level was getting higher, which indicated an uncoordinated relationship between urban land expansion and population growth in Africa. Cropland, grassland, rural land, and forests were the most land-use types occupied by urban expansion. The proportion of cropland, grassland, and forests occupied was getting higher and higher from 2001 to 2019. The extensive urban land use may have an impact on the environmental and economic benefits brought by urbanization, which needs further research. [ABSTRACT FROM AUTHOR]