Provincial Perspective Research Articles

Carbon peak prediction in China based on Bagging-integrated GA-BiLSTM model under provincial perspective

Many studies have revealed potential carbon peaking pathways in China. However, to minimize the uncertainty inherent in forecasting studies, more accurate forecasting models as well as more segmented forecasting subjects are always necessary. Based on panel data of 30 Chinese provinces from 2000 to 2020, this study applies the STIRPAT model and ridge regression to examine the key influencing factors of carbon emissions in each province in China, further constructs an innovative Bagging-integrated GA-BiLSTM model for forecasting, and finally explores China's peak carbon pathways in conjunction with scenario analysis. The results show that: (1) increasing urbanization and population growth are the main reasons driving the increase of carbon emissions in most provinces; (2) there is significant variability in the carbon peaking dynamics of China's regions, which can be classified into three categories: autonomous earlier peaking, policy-guided peaking, and difficulty in peaking; (3) For most provinces, the green scenario is more effective than the development scenario in reducing the peak carbon level rather than advancing the peak time; (4) under the development and the green scenario, China's overall carbon peak will be reached in 2032 and 2028, with the peak carbon levels of 11.88 billion tons and 11.42 billion tons, respectively.

Acquisition Management in the University Libraries of Pakistan: A Provincial Perspective

Acquisition management is the kind of strategy that university libraries adopt to assist the information needs of the client population. This study attempted to understand the acquisition management in the university libraries in the Khyber Pakhtunkhwa region of Pakistan. The study adopted a survey method and included all those well-established public and private sector universities that were chartered by the Government of Khyber Pakhtunkhwa and recognized by HEC until December 31, 2012, in the province (Public = 17 and Private = 9; Total = 26 universities). The population of this study was the senior library professionals working in the central libraries of the main campuses of all the universities in the province. The study’s findings show that the acquisition management in the university libraries in Khyber Pakhtunkhwa is more focused on fulfilling the curriculum requirements of the parent institutions to which they are attached.

Assessment and Driving Factors of Embodied Carbon Emissions in the Construction Sector: Evidence from 2005 to 2021 in Northeast China

Reducing embodied carbon emissions in the construction sector is pivotal for achieving sustainable development goals, mainly those related to health and well-being, sustainable cities and communities, and climate action. Hence, it is crucial to delve into the trends and influencing factors of construction-embodied carbon, especially in countries like China, where extensive construction projects are underway. Previous studies have investigated carbon emissions at both national and regional levels, whereas research specific to the construction sector in Northeast China remains limited. This study assessed the embodied carbon of the construction sector in Northeast China from 2005 to 2021. The results indicated that embodied carbon initially rose before declining, peaking at 278.9 MtCO2e in 2012. Based on the Logistic Mean Divided Index (LMDI) approach, the variations in embodied carbon were decomposed into seven driving factors, including emission source structure, embodied carbon intensity, construction mechanization, machinery requirement, industrial structure, economic development, and population scale. While construction mechanization and economic development were identified as primary drivers of the changes in embodied carbon, carbon emission intensity and population scale exerted inhibiting effects on the rise. Moreover, potential strategies for mitigating construction-embodied carbon in Northeast China were delineated, underscoring the regionality across different provinces. The results and suggestions can help foster a low-carbon construction industry from a provincial perspective.

The role of digital financial inclusion in promoting entrepreneurship in China: A provincial perspective

This study examines the impact of DFI on entrepreneurship in China and across its regions (i.e., rural and urban) using province-level panel data from 2011 to 2019. Digital financial inclusion (DFI) serves as a catalyst for entrepreneurship by giving access to financial services. Entrepreneurs, both in urban centers and rural areas, gain fair and equitable platforms by unlocking opportunities for growth and innovation through the use of technology. We employed fixed effect Driscoll-Kraay standard errors (FE-DKSE) and feasible generalized least squares (FGLS) techniques for empirical analysis. The findings showed that there is an N-shaped relationship between the DFI and entrepreneurship in China and across its regions (i.e., rural and urban). Our estimates are robust and insensitive to the inclusion of other control variables such as economic growth, urbanization and trade openness. Economic growth and trade openness have a positive and significant impact on entrepreneurship, and a negative relationship between urbanization and entrepreneurship. The policy insinuation is that the government needs to actively expedite the growth of DFI and establish a favorable external environment for entrepreneurship. To enhance the attainment of entrepreneurial targets, it is essential to adapt DFI policies according to regions.

Research on the Agglomeration and Spatiotemporal Development of China's Green High-Tech Industries

Accurate understanding of the spatial and temporal development of the agglomeration of green high-tech industries holds significant importance for the scientific formulation of policies promoting industrial innovation and development. This has attracted increasing attention from scholars. Utilizing nearly a decade's worth of statistical data on China's green high-tech industries, this paper employs methods from spatial geography and other disciplines to analyze the temporal and spatial variations, as well as the agglomeration characteristics of these industries in China. A comprehensive analysis of the development levels of China's high-tech industries and their sub-sectors is conducted through calculations of spatial Gini coefficients, industrial concentration ratios, location quotients, and coefficients of variation.Results indicate that the four key indicators of the development of China's major high-tech industries, namely the number of enterprises, employment figures, operating income, and profits, exhibit linear growth trends. Overall, the agglomeration level of the industry shows a fluctuating downward trend. The regional agglomeration level follows a gradient distribution trend of "eastern region - central region - western region - northeastern region," with a decreasing concentration trend. Regional disparities in the agglomeration level of industries evolve over time, with an increasing concentration in the western and central regions, and a decreasing concentration in the eastern and northeastern regions. From a provincial perspective, Guangdong and Jiangsu provinces stand out with significantly higher levels of development in high-tech industries.Furthermore, distinct differences are observed in the development processes of four typical industries. The agglomeration levels, ranked from high to low, are as follows: computer and office equipment manufacturing, electronic information and communication equipment manufacturing, medical device manufacturing, and pharmaceutical manufacturing，the development of the four types of industries has undergone certain transfers and optimizations.

Investigating the unparalleled effects of economic growth and high-quality economic development on energy insecurity in China: A provincial perspective.

China has changed its focus from traditional high-speed economic growth to high-quality economic development (HQED) and the implementation of environmentally friendly practices. This transition can have parallel or unparallel impacts on energy insecurity (EIS). In this regards, HQED, inter Alia, is crucial in mitigating EIS and combating the energy crisis. Our study explores the impact of economic growth (EG) and HQED on EIS using the provincial panel data of China for the period 2011-2017. From the perspective of comparative analysis, the results reveal that HQED reduces EIS while EG increases it. The robustness checks indicate that industrial structure (IS) has a negative impact on EIS, whereas industrial structure upgrading (ISU) and green innovation (GI) have a positive influence. This implies that IS contributes to an increase in EIS, whereas ISU and GI result in a decrease in EIS. In addition, the analysis reveals that digital financial inclusion (DFI) exhibits a significant positive relation with EIS, albeit occasionally a negative but insignificant link. The policy implication is that the government should stimulate policies to promote HQED which reduces the EIS.

Analysis of spatial spillover effects and influencing factors of transportation carbon emission efficiency from a provincial perspective in China.

Globally, the transportation industry has become one of the leading sectors in carbon emission, and all countries are committed to environmental protection and energy conservation while experiencing rapid development. Under China's "dual-carbon" goal, the carbon emission problem hinders the construction of China's green transportation system and affects the high-quality development of transportation, so it is of great significance to study the spatial pattern of carbon emission efficiency in the transportation industry and the factors affecting it. Firstly, this paper measures the carbon emission value of transportation in 30 provinces in China from 2010 to 2020 based on the IPCC method and measures the carbon emission efficiency through the super-efficiency slack-based measurement model. Secondly, spatial autocorrelation analysis was conducted to determine the spatial clustering characteristics of the efficiency values. Finally, two spatial Durbin models are constructed to measure the spatial spillover effects and analyze the short-term immediate effects of each influencing factor on the static model and the long-term effects of the dynamic model considering the time lag of the transportation carbon emission efficiency. The results of the study show that (1) the average value of efficiency in the central and eastern regions is basically higher than 0.5; in the western and northeastern regions, it is basically lower than 0.3.The overall efficiency of carbon emission in the region shows a fluctuating upward trend but with increasing regional differences. (2) The number of regions with positive spatial correlation increased from 21 to 25 during the study period, and the degree of provincial transportation carbon emission efficiency agglomeration increased. (3) Although urbanization and energy intensity have a large detrimental influence on transportation carbon emission efficiency, environmental regulation has a major favorable effects on it both long and short term. Population scale, opening level, and urbanization all have significant spatial spillover effects. Accordingly, relevant policy recommendations are put forward to provide theoretical guidance for promoting the realization of low-carbon transportation.

The role of tourism development in boosting export product diversification in China: A provincial perspective

Tourism has emerged as a major sector, and it is considered a significant contributor to the development of the host countries. Tourism development (TD) is believed, inter alia, to be a key promoter of export product diversification (EPD). This study explores the liaison between tourism development and export product diversification in China and across its regions (i.e., Eastern, Central, & Western) using the data for the period of 2011-2019. The Driscoll-Kraay standard errors (DKSEs) is adopted for empirical analysis along with feasible generalized least-squares (FGLS) and panel-corrected standard errors (PCSEs). The findings revealed an inverted U-shaped liaison between the TD and EPD. The estimates are robust and insensitive to econometric models, measures of tourism development, and the inclusion of other key covariates. The relationship between industrial structure, natural resource endowments, human capital, and economic growth is positive and statistically significant. The study revealed similar findings that were significant across regions. The policy insinuation is that the government should devise such policies to boost TD in order to promote EPD and sustainable development.

How diversification of products impact emissions in China: a provincial perspective.

Currently, global warming and air pollution are the world's most urgent issues partly caused by carbon dioxide (CO2) and sulfur dioxide (SO2) emissions, and prompt actions are needed to address these global concerns. Sustainable development cannot be attained until we reverse the negative impact of economic factors on the quality of the environment. It is noteworthy to offer a new indication on whether and how the empirical liaison between product diversification and environmental degradation evolved in China from 2008 to 2019. Product diversification (PD) is a remedy for reducing environmental degradation (ED). It is a crucial component of energy demand, which a significant impact on reducing energy consumption and ED. The purpose of this study is to investigate the impact of PD on ED in China using the provincial panel dataset. Employing the fixed effects-Driscoll-Kraay standard errors (FE-DKSE) and feasible generalized least squares (FGLS) methods, we discover an inverted U-shaped link between PD and ED. The control variable urbanization (URB) and technological innovation (TI) reduce ED significantly. However, industry value added (IVA) and energy consumption (EC) promote ED. Our results are robust with the addition of various controls in all models. The policy implication from our findings is that, to achieve a target of carbon neutrality, countries should adopt the product diversification strategy.

Prediction and balanced allocation of thermal power carbon emissions from a provincial perspective of China.

Carbon control in the thermal power generation industry is crucial for achieving the overall carbon peak target. How to predict, evaluate, and balance the allocation of inter provincial carbon emissions has a significant impact on the decision-making of reasonable allocation of inter provincial carbon emissions in the target year. Therefore, this paper uses Monte Carlo-ARIMA-BP neural network and ZSG-DEA model to conduct temporal trend prediction and carbon emission quota allocation research. We propose the "intra provincial and inter provincial" framework for carbon emissions trading in thermal power plants, which aims to break through the barriers in carbon emission rights exchange among provinces. The conclusions are as follows: (1) the growth trend of carbon emissions from thermal power is gradually slowing down and is expected to peak before 2030. (2) Inner Mongolia, Jiangsu, and Shandong have high input-output efficiency, and are all the main output provinces for carbon emission quota allocation. After being adjusted using the ZSG-DEA model, they can still be at the forefront of efficiency. (3) The "intra provincial and inter provincial" framework for carbon emissions trading can effectively predict and allocate the carbon emission demand of each province from time and space dimensions, balance the carbon emission rights and interests of each province, and provide forward-looking planning suggestions for inter provincial carbon emission rights exchange.

Towards a low-carbon future for China’s power supply chain: Critical sectors identification and scenario analysis

The power sector is a significant contributor to global carbon emissions and has received widespread attention from scholars; however, the path to achieving supply chain-wide carbon reductions in China from a provincial perspective remains unclear. This study combined multi-regional input–output and betweenness-based methods to identify the critical upstream sectors that indirectly drive large amounts of carbon emissions through power supply chains. The point source data of coal-fired units were collected to ensure the accuracy of the disaggregated input–output table. In addition, a scenario analysis was conducted to examine the effects of different electricity policy combinations on supply chain-wide emissions during the 14th Five-Year Plan (FYP). Our findings indicate that the embodied carbon intensity of the coal-fired power sector in Northwest China is among the highest in the country, ranging from 36.39 to 82.10 tons/10000 CNY. Therefore, the shift of the power sector to Western China during the 14th FYP will partially offset the positive emission reduction effect of the structural transformation of the power system. To achieve a low-carbon power supply chain, it is necessary to improve the production efficiency of critical transmission sectors and the low-carbon technology levels of major emitting sectors. Our results provide valuable insights for provincial governments to plan low-carbon transformation paths for the power sector.

Corrigendum: Water Supply 1 June 2023; 23 (6): 2404–2425. Spatio-temporal evaluation of water-energy-food nexus system risk from the provincial perspective: A case study of China. Tonghui Ding, Junfei Chen

Corrigendum: <i>Water Supply</i> 1 June 2023; 23 (6): 2404–2425. Spatio-temporal evaluation of water-energy-food nexus system risk from the provincial perspective: A case study of China. Tonghui Ding, Junfei Chen

Emission reduction analysis of China’s building operations from provincial perspective: Factor decomposition and peak prediction

Emission reduction analysis of China’s building operations from provincial perspective: Factor decomposition and peak prediction

A new machine learning-based approach for cross-region coupled wind-storage integrated systems identification considering electricity demand response and data integration: A new provincial perspective of China

Faced with the growing renewable energy requirements, there is increased interest in cross-region of large-scale renewable energy market, which provides an alternative path for building sustainable power systems. Critically, the development of a renewable energy-dominated electricity market is an important way to achieve global climate goals and energy conversion. Despite improved achievement of electricity demand response (EDR) market, only limited development in the coordination capacity and development scale of EDR are dominated by renewable energy. Moreover, the normal operation and work efficiency of the system is greatly affected due to data transmission errors and other human factors. Thus, it is of great importance for the State Grid to accurately identify the data sources and realize the interactive development of cross-region power systems. This paper presents a new cross-region (province) electricity demand response (CR-EDR) model in China for large-scale renewable energy participating in EDR market. This model is applied to three provinces in China based on renewable energy, and fully consider how wind power is integrated with EDR in terms of operation, grid connection and optimization. Presently, China is in the initial stage of development, and the identification of data anomalies is inevitable for the CR-EDR. To solve this problem, a novel machine learning (ML)-based approach is proposed for effective identification of EDR. By calculating wind power output and customers’ EDR results, reliable feature sequences can be obtained. Finally, all the feature sequences are uploaded to cross-region system operators (CR-SO) for classification and identification by ML. In the case studies and discussions, we integrated all feature sequences to CR-SO for identification and present a novel process approach to implement EDR, the random forest (RF) enables 100% accuracy for training set and 99.7685% for testing set with small training samples. Compared with RF, support vector machine only achieves 79.1667% for testing set with small training samples. With accurate RF identification results, the stable operation capability and management level of the system can be effectively improved. The proposed methodology creates a new provincial perspective of China and the establishment of CR-EDR, which provides a theoretical and methodological guidance for all countries and regions to develop CR-EDR.

Middle England’s empire: Social reproduction in the colonial global economy

This article brings feminist critiques of capitalism into conversation with race-conscious International Political Economy to highlight the place of social reproduction in the colonial global economy. It does so by taking a provincial perspective, using Royal Leamington Spa as a case study to reveal how the provision of care for the elderly and the ill sustained colonial elites across the life course, while religious and educational practices helped transmit cultural values across generations and reproduce imperialism as an institutionalised social order. Whereas the finance houses of London, the factories of Manchester, and the ports of Liverpool and Bristol constitute nodal points for imperial circuits of capital, the spa town condenses the everyday practices through which bourgeois metropolitan empire was lived and made liveable. These findings point to a functional differentiation of economic space within the metropole and offer a critical reinterpretation of Middle England as a Whitened site of middle-class respectability.

Transmission dynamics, responses, and clinical features for the first 1100 COVID-19 cases in South Batinah, Oman: Major lessons from a provincial perspective

ObjectivesThis study was aimed at exploring and analyzing the epidemiological profile, surveillance, and response to COVID-19, including transmission dynamics and cluster formation. MethodologyThis was a retrospective analysis of surveillance data, including contact tracing, risk factors, and clinical information. Binary logistic regressions were used to assess the likelihood of admission, cluster formation, and of each individual being an index patient. Clusters were demonstrated through geographic data systems, network analysis, and visualization software. ResultsA total of 1100 COVID-19 cases were diagnosed from 20 March to 7 June 2020, of which 144 (13.1%) were asymptomatic. The median time from symptom onset to admission was 7 days (IQR, 4.5–10), and the median symptom duration was 5 days (IQR, 3–9). Eighty-nine clusters containing 736 patients were identified. The surveillance and control actions were divided into three phases. Clusters began to form in phase 2 and became more pronounced in phase 3. Patients ≥50 years of age and patients presenting with fever had relatively higher odds of admission: OR = 12.85 (95% CI 5.13–32.19) and 2.53 (95% CI 1.24–5.17), respectively. Cluster formation was observed among females, asymptomatic patients, and people living in Awabi: OR = 2.3 (95% CI 1.7–3.1), 6.39 (95% CI 2.33–17.2), and 3.54 (95% CI 2.06–6.07), respectively. Patients working in the police and defense sectors had higher odds of being an index patient: OR = 7.88 (95% CI 3.35–18.52). ConclusionCase-based interventions should be supported by population-wide measures, particularly movement restrictions. Establishing prevention teams or district units, or primary care will be crucial for the control of future pandemics. Prevention should always be prioritized for vulnerable populations.

Spatio-temporal evaluation of water-energy-food nexus system risk from the provincial perspective: A case study of China

Abstract This study first defined the concept of the water–energy–food nexus system risk (WEF-R). Then, the WEF-R evaluation index system was established from three aspects: stability, coordination, and sustainability subsystems. Finally, the set pair analysis-variable fuzzy set model was used to evaluate the risk levels of subsystems, and the risk matrix was applied to assess provincial WEF-R levels in China from 2009 to 2018. The results showed that the stability subsystem had the greatest influence on provincial WEF-R, followed by the sustainability subsystem. The provinces with a higher risk of the stability subsystem and lower risk of the sustainability subsystem were mainly centralized in southeast coastal and central regions, which were consistent with the provinces with better socio-economic development. The provinces with lower risk of the stability subsystem and higher risk of the sustainability subsystem were mainly concentrated in northwest regions, which correspond with the provinces with better natural resources endowment but lower socio-economic development. As for the temporal evolution of risk levels, the risk levels of the coordination and sustainability subsystems showed downward trends during the study period, while the risk level of the stability subsystem displayed a small fluctuation, and the provincial WEF-R level in China presented a decreasing trend.

Levels and trends of maternal death in Baoan district, Shenzhen, China, 1999–2022

China had achieved impressive success in improving maternal health, while the progress of reducing maternal mortality ratio (MMR) varied across regions. Some studies had reported maternal mortality from national or provincial perspective, but researches of the MMR on long-term period at the city or county level rare been reported. Shenzhen has experienced significant socioeconomic and health changes, reflecting the typical development of China's coastal city. This study mainly introduced the levels and trends of maternal death in Baoan district, Shenzhen from 1999 to 2022. Maternal mortality data were extracted from registration forms and the Shenzhen Maternal and Child Health Management System. Linear-by-Linear Association tests were used to evaluate the trends of MMR among different groups. The study periods were divided into three stages by 8-year interval and χ2 test or Fisher's test was used to test the difference in maternal deaths of different periods. During 1999-2022, a total of 137 maternal deaths occurred in Baoan, the overall MMR was 15.91 per 100,000 live births, declined by 89.31% with an annualized rate of 9.26%. The MMR declined by 68.15% in migrant population, with an annualized rate of 5.07%, faster than that in permanent population (48.73%, 2.86%). The MMR due to direct and indirect obstetric causes shown a downward trend (P<0.001) and the gap between them narrowed to 14.29% during 2015-2022. The major causes of maternal deaths were obstetric hemorrhage (4.41 per 100,000 live births), amniotic fluid embolism (3.37 per 100,000 live births), medical complications (2.44 per 100,000 live births) and pregnancy-induced hypertension (1.97 per 100,000 live births), the MMR due to the above causes all shown decreasing trends (P < 0.01), pregnancy-induced hypertension became the leading cause of deaths during 2015-2022. The constituent ratio of maternal deaths with advanced age significantly increased by 57.78% in 2015-2022 compared with in 1999-2006. Baoan district had made encouraging progress in improving maternal survival, especially in migrant population. To further reduce the MMR, strengthening professional training to improve the capacity of obstetricians and physicians, increasing the awareness and ability of self-help health care among elderly pregnant women were in urgent need.

The impact of provincial port integration on port efficiency: Empirical evidence from China's Coastal Provinces

Port integration with the provincial territory as the primary spatial carrier has become an important initiative to implement port reform in China. Objectively evaluating and verifying its effectiveness is essential for refining and promoting this policy. This study empirically examines the effect of provincial port integration (PPI) on port efficiency from a provincial perspective by constructing the multi-period difference-in-differences (DID) model with the panel dataset of China's 9 coastal provinces from 2004 to 2019. The results show that: (1) Implementing PPI can significantly improve provincial port efficiency (PPE), but its impact on green provincial port efficiency (GPPE) is not significant, implying a lack of coordination between port integration and regional ecological protection. This conclusion remains robust to multiple scenarios, including truncated double bootstrapping approach test, placebo test, and endogeneity check. (2) The heterogeneity analysis demonstrates that PPI has a more significant incentive effect on PPE in smaller-scale provinces, provinces with lower levels of port specialization, provinces with larger port size, and provinces that implemented PPI after 2015. (3) Moderate administrative participation is more conducive to exerting the effect of PPI on PPE, and this effect presents an “inverted U-shaped” change characteristic as PPE increases.

Analysis of the Impact of Industrial Structure Upgrading and Energy Structure Optimization on Carbon Emission Reduction

In China, there has been a significant increase in carbon emissions in the new era. Therefore, evaluating the influence of industrial structure upgrades and energy structure optimization on reducing carbon emissions is the objective of this research. Based on the provincial panel data of 30 provinces and cities across China from 1997 to 2019, this paper builds up a fixed-effect panel quantile STIRPAT model to investigate the differences in the impact of industrial structure on carbon emission intensity at different quantile levels from the provincial perspective, and as a way of causality test, the mediation effect model is adopted to empirically test the transmission path of “industrial structure upgrading—energy structure optimization—carbon emission reduction”. The research results show that: (1) Both industrial structure upgrades and energy structure optimization have significant inhibitory effects on carbon emissions, and there are regional heterogeneities. (2) The upgrading of industrial structure has a significant positive effect on optimizing energy structure. (3) The upgrading of industrial structure can not only directly restrain carbon emissions but also indirectly have a significant inhibitory effect on carbon emissions by promoting the optimization of energy structure. Based on the above conclusions, corresponding policy recommendations are proposed to provide suggestions for China to achieve the goal of carbon neutrality.