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Generally, the central air conditioners are centralized in a refrigeration room in public buildings. The proportion of energy consumption of the refrigeration room is about 40% of entire building. This paper aims to propose an energy plus and self-designed simulator to reduce the energy consumption of a large electronic factory in Zhuhai City, Guangdong province, China. In this paper, the real data collected from the electronic factory in February and the group control method used in the refrigeration room based on the kernel ridge regression algorithm. The correctness of the kernel ridge regression algorithm was verified with the experimental results. Compared to traditional PID control method, the kernel ridge regression algorithm could dynamically adjust those parameters, such as temperature and frequency to match the high efficiency zone of each device. The overall average COP of the system is increased from 4.17 to 7.04. The electricity of the refrigeration room could save 64 MWh with the cooling load forecast error being below 7% in February. The power consumption is expected to reduce by 8.2% and 562.3 MWh in 2022. [ABSTRACT FROM AUTHOR]

• This study summarizes all existing and unpublished data on the Late Triassic plant fossils in Guangdong. • Four regional assemblages have been distinguished in the Late Triassic by marine fossils such as ammonites and bivalves. • The Late Triassic climate in the Guangdong region was mainly warm and humid, either tropical or subtropical. • During the Late Triassic, central and northern Guangdong were located at similar latitude, along the southern coastline of the South China Block. Triassic-Jurassic deposits are well developed in Guangdong Province, South China. In particular, the Upper Triassic coal-bearing strata which alternate between marine and terrestrial deposits yield diverse and abundant fossil plants, ammonites and bivalves. These strata provide a significant reference for the study of palaeoenvironmental variations in the lower latitude regions. In this paper, we review the major progress on Late Triassic floral studies in this area. Specifically, we compare the regional plant assemblages from different fossil sites in central and northern Guangdong which have been dated with marine fauna. 155 species belonging to 56 genera of fossil plants have been reported so far in northern and central Guangdong. The Late Triassic floras in Guangdong are mainly composed of Bennettitales and ferns, followed by horsetails, seed ferns, cycads, ginkgos and conifers. In ascending order, four regional plant fossil assemblages can be recognized in the Late Triassic deposits, namely the Pachypteris - Lindleycladus Assemblage (Julian), the Pterophyllum - Baiera Assemblage (late Julian), the Clathropteris - Otozamites Assemblage (Tuvalian), and the Danaeopsis - Anomozamites Assemblage (Rhaetian). In general, the Late Triassic climate in the Guangdong region was mainly humid and warm and either tropical or subtropical. The fossil plants corroborate palaeomagnetic evidence that the central and northern Guangdong region was located at approximately the same latitude as it is today and formed the southern coastline of the South China Block during the Late Triassic. Palaeogeographically, the transgression started at the end of the Julian and the south coastal terrane consisted of a western bay, a peninsula and an eastern bay. During the regression period, post-Rhaetian, the bays evolved into a gulf coastal plain. [ABSTRACT FROM AUTHOR]

In recent years, extreme rainfall events have frequently occurred frequently, and heavy rainfall can cause drastic changes in the troposphere. Therefore, achieving to achieve real-time high-precision numerical prediction of key tropospheric parameters during heavy rainfall has become a major problem in global navigation satellite system (GNSS) meteorology. In this paper, two extreme rainfall events in southern China (Guangdong region) and northern China (Shandong region) in 2022 are used as case studies. Twenty-four-hour real-time numerical forecasts of key tropospheric parameters (atmospheric weighted mean temperature (Tm), precipitable water vapor (PWV), and GNSS zenith tropospheric delay (ZTD)) are obtained using three models, namely, the HGPT2, GPT3, and WRF models. Two optimization models, i.e., WRFDA (am) and WRFDA (pre), are then constructed by assimilating two types of data (global upper air and surface weather observations and daily advanced microwave sounding unit A (AMSU-A) brightness temperature) based on the WRF model. The experimental results for heavy rainfall show that (1) the WRF model predicts the key tropospheric parameters with better accuracy than the HGPT2 and GPT3 models, and the WRFDA (pre) model predicts PWV and ZTD with the highest accuracy; (2) the WRFDA (pre) model achieves a higher accuracy than the WRF model in predicting PWV and ZTD, where the PWV prediction accuracy is improved relative to the WRF model (in the south: MAE: 32.7 %; RMSE: 33.9 %; MAPE: 36.8 %; in the north: MAE: 27.3 %; RMSE: 24.2 %; MAPE: 28.0 %); this model achieves an MAE of 2.17 cm and an RMSE of 2.70 cm in 24-h ZTD prediction in the south, while the MAE reaches 2.48 cm, and the RMSE is 3.18 cm in the north; (3) the models provide a higher forecast accuracy in the southern region than in the northern region for heavy rainfall. The WRFDA (pre) model provides a favourable ZTD accuracy at GNSS stations near the ocean, while the WRFDA (am) model provides a satisfactory ZTD accuracy at inland GNSS stations, and the WRFDA (am) model provides the highest ZTD prediction accuracy at GNSS stations above 100 m. [ABSTRACT FROM AUTHOR]

Hydrogen is a type of clean secondary energy, and the hydrogen energy supply is vital to regional energy development. Guangdong is at the forefront of hydrogen energy deployment in China, and aims to achieve peak carbon by 2030. However, hydrogen production research is challenging due to complex technical routes, technical maturity levels, life-cycle carbon emissions, and costs. Multi-time-scale research is necessary to explore optimal production paths and their contributions to CO 2 emission reduction. This study discussed key technologies and the technical maturity of five hydrogen production routes: production from industrial byproducts and coal, wind, hydro-, and photovoltaic power. Policy scenarios were designed to investigate the potential of these routes and technology deployment intensity under medium- and long-term scenarios. This paper proposes a roadmap for hydrogen development and provides a reference for hydrogen production planning in Guangdong. This methodology can be applied in other regions for hydrogen energy development research. • Key technology maturity of the hydrogen production routes was evaluated. • Roadmap of hydrogen production in Guangdong Province was designed. • A method for research of hydrogen supply scenarios was proposed. [ABSTRACT FROM AUTHOR]

The urgency of addressing climate change and reducing carbon emissions necessitates the establishment of effective carbon markets. Our paper focuses on assessing and interpreting the efficiency of carbon markets, which is a crucial aspect of their successful implementation. We selected Hubei, Shenzhen, and Guangdong carbon pilots as examples to measure their dynamic information efficiency by combining the rolling time window and wild-bootstrap variance ratio test. Furthermore, we combined SHapley Additive exPlanations (SHAP) and Extra Trees (ET) regressor to reveal the nonlinear relationship between market performance and efficiency. Our findings highlight the time-varying nature of carbon market efficiency and reveal that China's carbon market has not yet achieved stable weak-form efficiency. Additionally, we identified excessive trading volume volatility as a significant constraint on market efficiency, while the trading volume itself exhibits weak explanatory power. Our proposed hybrid model demonstrates superior predictive and explanatory capabilities, offering regulators a valuable tool for continuously monitoring and interpreting carbon market efficiency. Finally, we suggested that reducing trading volume volatility should be a major concern for regulators to optimize market operations at present. [ABSTRACT FROM AUTHOR]

A good risk warning model is an effective way to guarantee the stable operation of the carbon market and exert its emission reduction function. This paper takes the China's pilot carbon market as the research object and measures the carbon market risk by ARMA-GARCH-VaR. Then, influential factors are selected as non-market characteristics from the perspective of causality and incorporated into the risk warning model, and SMOTE and SMOTEENN are introduced to deal with the unbalanced samples. Results show that (1) The risk fluctuations of Beijing and Shenzhen carbon market are large, and the risk fluctuations of Guangdong carbon market are relatively smooth in the early period and larger in the recent period. (2) Air quality, average daily temperature, CSI 300, power coal, natural gas, European carbon market, exchange rate, and Baidu index are all important factors in the risk volatility of carbon market. (3) The Classification Decision Tree (CDT) has the best performance. CDT has the best performance in Guangdong carbon market, SMOTE-CDT has the best performance in Hubei carbon market, and SMOTEENN-CDT has the best performance in Shanghai carbon market, in which SMOTEENN-CDT has a 76% Recall. The non-equilibrium treatment improves the overall Recall, and the risk warning model after non-equilibrium treatment can avoid missing important risk points. This paper can provide a certain degree of reference for the improvement of carbon trading market and risk management. [Display omitted] • A carbon market warning model is constructed. • The average VaR of the carbon trading markets in Shenzhen and Beijing is larger. • CDT performs better in market risk warning. • The model improves 34.8% in the avoidance of risk compared with other models. [ABSTRACT FROM AUTHOR]

This paper addresses the significant challenges faced by distribution system operators (DSOs) in competitive electricity markets due to uncertainties arising from electricity markets, electric vehicles (EVs), and conventional loads. To tackle these challenges, this paper proposes a pseudo-local reserve market between the DSO and EVs, which enables the DSO to integrate EV flexibility into the overall market framework while compensating for deviations in the conventional load across the wholesale electricity market. Furthermore, a two-stage framework is developed to facilitate the participation of EVs in electricity markets. In the first stage, the reserve capacity of EVs is integrated into the decision-making process for day-ahead bidding, taking into account uncertainties of the load and electricity. In the second stage, the day-ahead results are coordinated to enable the efficient dispatch of EVs for real-time market participation. To assess the efficacy of the proposed framework, a case study is conducted within a 31-node distribution system situated on a university campus located in Guangdong, China. This paper investigates the economic impact of load deviation constraints on EV reserves, revealing a penalty reduction of 3100 CNY for a daily reservation of 1000 EVs and a net profit increase of 1300 CNY for DSOs utilizing reserves. It further introduces a method for quantifying reserve capacity, enhancing DSO decision-making accuracy. • A pseudo-local reserve market is established considering EV's reserve potential. • Optimal bidding strategy for DSO in China's electricity markets is constructed. • A framework for EV coordinated V2G operation is developed. • The proposed method can limit load deviation cost for more profits. [ABSTRACT FROM AUTHOR]

Accurate photovoltaic power prediction is crucial for optimizing the performance of photovoltaic power plants and ensuring the stability of the power grid. However, existing forecasting methods are challenged when predicting the power output of multiple plants with different geographical locations and environmental conditions simultaneously, due to the complexity of the underlying factors that affect power generation. To address this issue, this paper proposes a novel LightGBM-XGBoost photovoltaic power prediction model based on a pre-training and fine-tuning paradigm. The model leverages a large dataset to pre-train and learn rich feature representations within meteorological elements, which are then fine-tuned on specific downstream tasks to improve prediction accuracy and generalization ability. Experimental verification is conducted using data from three photovoltaic generators operating in Guangdong, China. Results demonstrate that the proposed model outperforms other methods when predicting the power output of multiple plants with different conditions simultaneously, highlighting the effectiveness of the proposed approach. Overall, this work contributes to advancing the state-of-the-art in photovoltaic power prediction and has practical implications for improving the control and scheduling of photovoltaic power plants, as well as ensuring the stability and security of the power grid. [ABSTRACT FROM AUTHOR]

• This paper studies bidder behavior in auctions with an uncertain quality threshold. • A high-quality index results in a higher bid. • High-quality bidders are more likely to withdraw from an auction. • Bidding strategies in auctions with an uncertain quality threshold are inefficient. Procuring high-quality goods at reasonable prices is a critical public sector concern. Yet, procurers often do not advertise clear weighting rules for price and quality but set a flexible quality threshold upon participation. This paper studies endogenous entry and bidding behavior in such procurement auctions. Using unique data on pharmaceutical procurement in Guangdong, China, we find that a high-quality index acts as a signal of high production costs. We also observe that high-quality bidders are more likely to withdraw from bidding because of their prior commitment to quality. The procurers who use quality indicators in price auctions need a carefully considered quality threshold. Our results have important implications for price-quality trade-offs in procurements that have uncertain quality thresholds. [ABSTRACT FROM AUTHOR]

This paper proposes a novel management scheme, namely, the distribution system operator (DSO) as a key player participating in China's electricity markets owing to its high value-added capability, high customer loyalty and robust risk resistance. In light of this, this paper discusses the maximal marginal revenue for DSO in uncertain electricity markets with vehicle-to-grid operation incorporated. Initially, considering different benefit expectations of electric vehicles (EVs) owners, DSO could provide preferential contracts, including the discount price contract (DPC) and revenue-sharing contract (RSC), in exchange for the management rights of EVs. Then, the stochastic optimization model considering the spatiotemporal uncertainties of EVs and electricity markets is built up, and the optimal bidding and coordinating strategy are proposed to maximize the marginal revenue of DSO. Comprehensive case studies are conducted in a 31-node distribution system of a university campus under the electricity markets in Guangdong, China. Results reveal that different distribution of EVs parking lots has a significant impact on the profit of DSO, and the revenue for DSO is 13,477 yuan more than that for EVA by scheduling 1400 EVs' charging/discharging behavior properly. Additionally, the DSO with RSCs is exposed to 25% less market volatility risk than that with DPCs. • Comparing EV aggregator(EVA) and distribution system operator(DSO) characteristics. • Discount price contracts and revenue-sharing contracts are compared. • The advantages of DSO over EVA in market participation are analyzed. [ABSTRACT FROM AUTHOR]

While urban redevelopment has been a global phenomenon for many decades, the redevelopment of urban villages (villages-in-the-city or c hengzhongcun) in China has attracted increasing scholarly attention in recent years. However, few studies focus on urban planning forces and their impacts on the redevelopment of urban villages, especially the transformation of open spaces. This paper therefore examines how urban planning transforms the space of urban villages through a case study of Yangji Village in Guangzhou City, Guangdong Province. The large increase in public spaces related to the transformation of Yangji results from collaborative governance driven by trends in urbanization and the work of urban planners. The latter are empowered by their strategic use of state support, professional knowledge and public interest incentives. However, in the Yangji redevelopment, as a state-hegemonic project, such planner-led collaborative governance remains limited in scope amid the exclusion of migrant tenants from decision-making. Although rarely regarded in the literature as playing a key role in redeveloping urban villages, this paper highlights urban planners as a salient force in the morphology of urban villages. Without challenging the hegemonic substance of urban village redevelopment, planners can coordinate with and occasionally manipulate other stakeholders to legitimate and facilitate negotiation during physical planning. Hence, redeveloped urban forms, rather than stakeholders' economic profits in short-term redevelopment, may influence urban lives in the long term due to planners' efforts. • Multiple stakeholders form collaborative governance in the physical planning of Yangji Village redevelopment to increase much open space. • The collaborative dynamics in the physical planning are built upon stakeholders' trust, fostered through informal meetings, led by planners, and fundamentally driven by urbanization. • Such collaborative governance is limited, largely due to the exclusion of migrant tenants. • Planners define the field of urban form beyond economic profit to improve redevelopment without challenging neoliberal and authoritarian hegemony. • State support, professional knowledge, and public interest ensure planners' leading role in collaboration. [ABSTRACT FROM AUTHOR]

Reasonable alignment control can simplify the bridge construction process, reduce the complexity and cost of construction, and improve construction efficiency. The prefabricated assembling construction method brings challenges to alignment control. This study proposes a method for predicting the alignment of concrete cable-stayed bridge assemblies in unstressed conditions to accelerate the construction process. The method uses the target paper to identify the 3D coordinates of control points and a coarse-to-accurate alignment method to achieve the virtual preassembly of precast concrete sections. The effectiveness of the method is demonstrated by comparing the errors in key parameters between virtual and physical preassembly and the predicted alignment results obtained through 3D coordinate conversion with the designed precast alignment. The method was applied to the construction of a large-span concrete cable-stayed bridge for a high-speed railroad in Guangdong, China, and the construction period was shortened by about 42 days. • A method to predict the alignment of a cable-stayed bridge constructed is proposed. • A method for identifying the 3D coordinates of geometric control points based on target paper. • The proposed method helps shorten the construction process at the construction site. • A point cloud alignment method from coarse to fine is proposed. • Monitoring of installation deviations of the girder segments relative to design status. [ABSTRACT FROM AUTHOR]

• A measurement campaign on the wheel profile evolution of a metro train was conducted. • This paper converts the wheel wear model calibrating problem into an optimization problem. • The RBF-PSO method is proposed to calibrate the Archard-local model. • The calibrated wear model can roughly estimate the wheel wear of similar metro vehicles. The accuracy of physics-based wheel wear prediction approaches depends not only on the vehicle-track dynamics model but more importantly on the wear model. The currently available wear models, however, were developed for specific wheel/rail materials and under fixed operational conditions, and they need to be calibrated when used in new operational conditions. In this paper we introduce a data-driven approach into the physics-based approach to automatically calibrate the existing wear model so that it can be extended to a new operational scenario. Specifically, based on a one-year follow-up measurement data on the wheel profile evolution of a metro train commuting on a Guangdong metro line, we introduce radial basis function (RBF) and particle swarm optimization (PSO) to determine the boundary of each wear regime and the wear coefficient for each wear regime in the Archard-local model. Finally, we present a calibrated Archard-local model and then apply it to two cases. One application case shows that the calibrated model can be used for long-term wear prediction and another case shows that the calibrated model can be used to roughly estimate the wear evolution over the tread region of vehicles operating on other China metro lines. [Display omitted] [ABSTRACT FROM AUTHOR]

This paper studies the economic and financial feasibility analysis of hydrogen energy projects in China to identify appropriate green financing solutions for them. Cost-benefit and sensitivity analysis approaches were carried out for the three hydrogen projects in Guangdong province (two cases) and Jiang Xi province (one case). The hydrogen projects are more sensitive to borrowing interest rates and income tax rates, amongst other financing costs. The main reasons are the capital-intensive nature of green energy projects and the role of tax in the rate of return of green projects in the long term. The optimal weight of bank loans for the studied hydrogen projects in China was calculated at nearly 56%, meaning the weight of green bonds is approximately 44%. In other words, diversifying financing channels instead of just relying on bank loans is recommended to reduce the financing risk and capital cost. As a major policy implication, we recommended various de-risking tools, such as the green credit guarantee corporation, to attract private investments in hydrogen projects. • Green Financing solutions can enhance the feasibility of hydrogen projects. • Hydrogen projects' feasibility is highly sensitive to borrowing interest rates and income tax rates. • We calculated the optimal financing of 3 hydrogen projects in China using bank loans and green bonds. • Diversifying channels of financing instead of just relying on bank loans is recommended. • De-risking tools, such as the green credit guarantee corporation, attract private investments in hydrogen projects. [ABSTRACT FROM AUTHOR]

• From the perspective of spatial cross-sectional data, this study explores causal inference in the ecological environment. • Two primary causal pathways are identified. • The study unveils the intricate mechanisms among diverse factors within the ecological environment system. The ecological environment is closely related to natural conditions, climate change, and human activities. However, existing research predominantly concentrates on evaluating the direct impacts of various factors on the ecological environment, yet lacks an in-depth exploration of their causal relationships and pathways. This paper introduces a new perspective to research in this field by incorporating spatial cross-sectional data analysis methods. The study utilized the 2020 China's High-resolution Eco-Environmental Quality (CHEQ) dataset to evaluate the spatial differentiation characteristics of Ecological Environmental Quality (EEQ) within the western urban agglomeration of Guangdong Province. A framework of "terrain-urbanization-climate" influencing factors was constructed, and the Geographical convergent cross mapping (GCCM) method was employed to infer the causal relationship between EEQ and influencing factors. Additionally, the spatial distribution characteristics of influencing factors on ecological environment quality were studied using the Multiscale Geographically Weighted Regression Model (MGWR). The results indicate that seven influencing factors including Elevation, Population, Precipitation, TEMP, TMMX, TMMN, and Slope have clear causal relationships with EEQ and exhibit bidirectional coupling relationships. There exist complex causal relationships among influencing factors, revealing the interaction mechanisms and causal pathways among multiple factors in the ecological environment system. These analyses enrich our understanding of the intricate and complex relationships between the ecological environment and influencing factors, providing a valuable reference for ecological protection and sustainable development. [ABSTRACT FROM AUTHOR]

Carbon price prediction serves as a market indicator and economic driver, facilitating the adoption of more environmentally friendly production methods to achieve the emission reduction targets outlined in the Paris Agreement. In recent years, time series analysis and decomposition techniques have been widely applied to carbon price forecasting. However, few researchers have considered the issue of data feature drift caused by real-time decomposition. Specifically, as the sample size increases, data features undergo changes, rendering the trained models unable to fit the new data. This paper explains the underlying reasons for this phenomenon from new perspectives and proposes a novel paradigm that replaces the intrinsic mode function with a single-step fuzzy particle. This new paradigm corrects the issue of data feature drift and concentrates noise into a completely new sequence during the preprocessing stage. In the subsequent processing steps, the loss of correlation between the sequence and time lag, as well as the sequence and carbon prices, is addressed through multi-information association. This paradigm hybrid model can be applied to deterministic and interval multi-step predictions. Experimental results on the datasets from Guangdong and Hubei demonstrate that the proposed model outperforms other comparative models, achieving better predictive results than existing decomposition-based forecasting models. In the case of Guangdong, the normalized root mean square error (NRMSE%) for one-step, three-step, and five-step deterministic predictions are 2.18%, 2.51%, and 2.89%, respectively. The average interval score (AIS) for interval predictions are −0.357 and − 0.2375, respectively. • Provide new perspectives on the data feature drift caused by real-time decomposition. • Propose a novel paradigm to address the practical challenges of real-time decomposition. • Multi-information association solves the problem of correlation loss in traditional decomposition techniques. • This paradigm can be combined with secondary decomposition and applied to deterministic and interval multi-step prediction. [ABSTRACT FROM AUTHOR]

• Applying InVEST model to determine ecological sources. • Building ecological resistance surfaces for highly urbanized region. • Proposing a local evaluation model for ecological networks. • Summarizing the ecological network development suggestions. Metropolitan regions usually encounter sustainability difficulties such as overexploitation of resources, severe land scarcity, and ecological degradation, resulting in the progressive collapse of ecological networks (ENs). It is therefore essential to strengthen the construction and protection of ENs by integrating various resources, improving the quality of the urban ecological environment and creating a favourable living environment. Using the Guangdong-Hong Kong-Macao Greater Bay Area as a case study, in this paper, the ecological resistance indicator system that balances natural condition and human disturbance is rebuilt. In doing so, a construction scheme (applicable to highly urbanised areas) is established to simulate ENs at a more precise scale. Moreover, a local evaluation model of ENs is proposed and the spatial patterns of multiple indicators are fully summarised. The findings show that the ENs of the Guangdong-Hong Kong-Macao Greater Bay Area exhibit apparent spatial disparity. Disturbance through human activities seriously affects the spatial pattern of ENs, leading to structural imbalance and quality impairment of ecological corridors. Based on our assessment, the construction of complementary ecological corridors in the "two green belts" planning of the Guangdong-Hong Kong-Macao Greater Bay Area will improve structural problems. The findings of this paper can provide a reference to the harmonisation of urban development and ecological protection, by guiding the scientific management of ecological spaces in highly urbanised regions. [ABSTRACT FROM AUTHOR]

The routine water quality monitoring data from 2010 to 2015 were collected, and 24 routine water quality monitoring items were analyzed by single factor standard index method. The results show that the proportion of inferior V-type monitoring sections in the basin has reached 77.78%, which is generally severe pollution, and the main pollution factors are chemical oxygen demand, NH4 +-N and total phosphorus. After investigation, it was found that the basin was affected by some heavy pollution tributaries, and the upstream to downstream of the main stream showed a trend of gradual pollution, especially when flowing through densely populated urban areas. Through the monitoring of various indicators, according to its concentration, change law and on-site analysis, the main reasons for the occurrence of black and odor in the basin are lagging construction of sewage pipe networks and sewage treatment plants, many heavily polluting enterprises, direct discharge of domestic sewage, random disposal of garbage, and low bottom mud release and management ability. Aiming at the current situation and causes of the black and odorous water bodies in this basin, combined with the research of other scholars, this paper compared the removal effects of various methods on pollutants. Aeration and magnetic flocculation technology can be adopted as emergency treatment measures in the river basin, and the treatment effect of each pollution factor is estimated to reach 80%. At the same time, in the long-term improvement stage of water quality, corresponding rectification measures are proposed, and the comprehensive water environment improvement project system is scientifically planned. The environmental quality is conducive to the sustainable development of urban economy and society, which is of great significance for promoting the coordinated development of economy, society and environmental protection in Eastern Guangdong. [ABSTRACT FROM AUTHOR]

In recent years, China has been gradually consolidating the establishment of Low Carbon Communities (LCC) to minimize the emission of CO 2 and other greenhouse gasses. Guangdong Province, as one of the low-carbon pilot provinces, has also paid great attention to the building of LCC. However, currently Guangdong province, or even China as a whole, has no official evaluation system in place which can be employed to evaluate the degree of low carbon of urban LCC. This paper aimed to establish a system for evaluating the urban LCC of Guangdong Province based on their actual situations. The system divided the evaluation into six categories, applied the SMART criteria to select suitable indices, and set the reference values for two zones, i.e., the Pearl River Delta zone (PRD) and the non-PRD zone. Monte Carlo and AHP were combined for the calculation of index weights, thus ensuring that the weight judgment matrixes could all pass the consistency check. In addition, this paper also laid down detailed evaluation regulations to improve the operability of this system and guarantee its wide application and better generalization. Finally, one typical urban community was selected to test the operability of this system, and the One-At-a-Time (OAT) method was used to analyze the sensitivity of each index and explore the degree of influence of these indices on evaluation results. The results showed that three indicators corresponding to green building percentage, new energy vehicles percentage and low carbon public transportation had the highest sensitivity. After field test evaluation, the evaluation system was found to have strong operability, and a high accessibility to indicator data. This system cannot only be used as a tool by the Provincial People's Government of Guangdong to evaluate the construction progress and degree of low carbon in LCC, but can also provide a reference point and experience for the Chinese government to draw upon in establishing the evaluation system of LCC at a national level. [ABSTRACT FROM AUTHOR]

The citizenization of peasant migrants is key to understanding China's long-term urban-rural imbalance and ongoing rural transformations. The majority of existing literature focused on structural/institutional or agentive/subjective factors, while an integrated perspective examining both structural and agentive factors related to the citizenization process is rarely seen. Borrowing theories from the strategic-relational approach, this paper unfolds the matching and mismatching mechanisms between the policy design and peasant migrants' intentions of citizenization. Drawing on a case study in China's Guangdong Province, this study finds that: (1) citizenization policies prefer to offer citizenship to the new generation of peasant migrants, which matches the age structure of peasant migrants; (2) although municipal governments are prone to attract young peasant migrants with high educational level and strong competitiveness, peasant migrants generally have a relatively low educational level and weak professional training; (3) the high threshold of citizenization in mega-metropolitan and metropolitan cities mismatches peasant migrants' preference towards the first-tier cities. This paper describes the matching and mismatching mechanisms between structure and agency associated with the citizenization of peasant migrants. The policy reflections proposed by this study point towards enhancing nearby urbanization and in situ urbanization, so as to increase the attraction of young peasant migrants by ordinary cities. Besides, this paper calls for the promotion of rural-urban co-governance, making rural revitalization an alternative and supplement to the urbanization driven by rural-urban migration. • The strategic-relational approach is a critical perspective for understanding citizenization. • As a progressive and dynamic process, the citizenization of peasant migrants intersects with local strategies of urbanization. • Governments should realize that ordinary cities are critical places for most peasant migrants to realize citizenization. [ABSTRACT FROM AUTHOR]

As the primary source sector of carbon emissions, the power industry's green innovation is an indispensable component of China's low-carbon transformation. This paper took China's Carbon Emission Trading Scheme as a quasi-natural experience and adopted the synthetic control method to evaluate the impact of Carbon Emission Trading Scheme pilot policy on power industry's green innovation based on the provincial industrial level data. Furthermore, this paper examined the impact mechanisms of Carbon Emission Trading Scheme on the power industry's green innovation through policy comparison, moderating and mediating effect analyses. The research findings show that: 1) there is heterogeneity in Carbon Emission Trading Scheme's effectiveness in inducing green innovation in China, the power industry only in Beijing and Guangdong has been significantly promoted, while other pilots have not; 2) the success of Beijing and Guangdong can be attributed to distinctive features of their carbon market and power industry, including the refined quota accounting mechanism, the application of paid quota allocation, the larger enterprise scale and more research and development investment; 3) enterprise scale and research and development investment have positive moderating effect and mediating effect in the promotional effect of the Carbon Emission Trading Scheme on green innovation respectively. Finally, some policy recommendations are put forward to promote the power industry's green innovation and carbon market construction. • Evaluate the impact of China's CETS on the power industry's green innovation in each pilot. • The CETS effects among pilots are heterogeneous, only significant in Beijing and Guangdong. • Rational CETS mechanism design could improve the power industry's green innovation. • Enterprise scale and R&D investment positively moderate and mediate the CETS effect. [ABSTRACT FROM AUTHOR]

The construction of an ecological security pattern (ESP) is an important undertaking in ensuring the stability of the ecosystem and the long-term growth of humanity. Existing research, However, existing research often overlooks the quantification of policy implications in ESP development. The objective of this paper was to bridge this gap by integrating policy quantification analysis (PQA) with nature, society and into ESP construction and providing targeted ecological management recommendations. The policy texts were quantified into reusable research data, which served as a foundation for the selection of indicators and the optimization of ecological security patterns, by using machine learning techniques. The methodology "Patch-matrix-corridor" was used to create a spatially correlated ecological security pattern. Through factor analysis and Random Forest (RF), the impact of each indicator on ecological security was thoroughly examined, offering substantial support for policy development and ESP construction planning. The Guangdong-Hong Kong-Macao Greater Bay Area(GBA) was selected as the study area, the study found that: (1) The proposed framework PQA based-ESP could provide a useful eco-management tools. (2) Policy adaptability had a substantial impact on environmental security in the GBA, but the ecosystem service index has the highest impact. (3) Applying the framework, we identified a total of 1,993 km2 of ecological sources, 23 key ecological corridors, 58 general ecological corridors, and 31 ecological nodes. An improved ESP, characterized as "one circle, two bays, three rivers, multiple areas, corridors, and nodes," was constructed in the GBA. (4) Given the multi-scale analysis, tailored ecological management policy recommendations were proposed for each city in the GBA. The study's findings offer actionable solutions for the international community facing growing ecological challenges. [ABSTRACT FROM AUTHOR]

Nasopharyngeal carcinoma is one of the most prevalent malignant tumors in Guangdong, China. In the field of medicine, predicting the recurrence of early-stage nasopharyngeal carcinoma after radiotherapy holds significant importance. Our objective was to develop a novel classification model aimed at predicting recurrence following radiotherapy for early nasopharyngeal carcinoma. This paper introduces an innovative approach by combining unsupervised diagnostic feature learning (biclustering algorithm) with Adaboost ensemble learning to create a novel classification model. Notably, the nasopharyngeal carcinoma dataset underwent biclustering algorithm application for the first time. Initially, the Borderline-SMOTE oversampling algorithm was employed to address the dataset's imbalance issue. Subsequently, the biclustering algorithm, which is based on an improved multi-objective genetic algorithm (NSGA-II), was utilized to seek bicluster outcomes exhibiting consistent representation patterns. The attributes of these bicluster outcomes were assessed and employed as diagnostic rules for constructing weak classifiers. Ultimately, the Adaboost ensemble learning technique was employed to amalgamate the weak classifiers into a robust classifier. Following the application of 10-fold cross-validation, the model exhibited an accuracy of 80.33%, sensitivity of 79.55%, specificity of 80.43%, and GMean of 79.99%, accompanied by an AUC value of 0.904. The presented classification model outperformed alternative classification models in terms of classification accuracy and generalization when applied to the nasopharyngeal carcinoma dataset. Consequently, it serves as a valuable tool to aid medical professionals in predicting the likelihood of recurrence in the cervical lymph nodes following radiotherapy for early-stage nasopharyngeal carcinoma. • Developed a novel classification model for nasopharyngeal carcinoma MR feature data. • Using the Borderline-SMOTE algorithm to address the imbalance issue. • Innovatively combining a biclustering algorithm with FSDND. • Experimental results demonstrate the effectiveness of this classification model. [ABSTRACT FROM AUTHOR]

Along with habitat destruction and the intensification of climate change, economic and social development is threatening the living of species. In the context of China's domestic economic circulation, the spatial structure of biodiversity loss is complicated by the decentralization of production, with many regions affecting the survival of species in other regions. Based on the environmentally extended MRIO model, this paper calculated the subnational biodiversity loss footprint through structural path analysis and social network analysis, identified the regional linkages and spatial networks of species loss, and traced the conservation responsibility to specific sectors. Our findings indicate that Yunnan, Tibet, Guangdong, and Sichuan possess the most significant biodiversity footprints, comprising over 40% of the total footprint. In terms of threat patterns, Yunnan and Tibet have the largest intra-regional footprints, indicating their important impact on species within the region; Guangdong and Zhejiang have the largest extra-regional footprints, indicating their role in threatening other species through cross-regional trades. The primary industry, tap water and food and tobacco sectors are major biodiversity footprint producers. Overall, some eastern and coastal areas are the final drivers of biodiversity loss in China, driven by increasingly complex trade links. Notably, the directionality of species loss in biodiversity hotspots is evident, with Shandong and Guangdong significantly influencing the biodiversity of Yunnan and Guangxi, respectively. This study systematically analyzed the complete network of biodiversity loss and divided four biodiversity protection communities to promote the realization of trans-regional protection and compensation. Examining the biodiversity loss through the lens of networks, and connecting economic activities to species, serves as a warning to decision-making bodies that a future of increasingly intricate domestic trade could pose a critical threat to biodiversity, necessitating collaborative conservation efforts. [Display omitted] • 1.Inter-provincial trade contributes to the complex structure of biodiversity loss. • The characteristics of biodiversity footprints vary widely among provinces. • Some eastern and coastal provinces are the final drivers of biodiversity loss. • Four protection communities are established through social network analysis. [ABSTRACT FROM AUTHOR]

• A method based on Neural Network is proposed for provincial-level CO 2 emissions estimation. • An autoencoder is proposed to downscale the provincial-level CO 2 emissions to city-level. • A complete city-level CO 2 emissions inventory of GBA and surrounding cities is complied. • Spatial dependence and agglomeration characteristics of CO 2 emissions are analyzed. • Spatio-temporal heterogeneity of factors affecting CO 2 emissions is investigated. Significant attention has been given to the issue of CO 2 emissions worldwide, especially for China as the largest emitter. Cities, as the main carriers of China's economic development, account for up to 85 % of CO 2 emissions from energy use in the country. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) and surrounding cities play important leading roles in low-carbon development. However, compiling city-level CO 2 emissions is challenging due to the limited availability of data. In this paper, a new idea is proposed by using SSA-BP for estimating provincial-level CO 2 emissions and downscaling provincial-level CO 2 emissions to city-level CO 2 emissions by reconstructing missing values of city-level CO 2 emissions with an autoencoder. This study compiles a city-level CO 2 emissions inventory and conducts a spatio-temporal analysis of CO 2 emissions in the GBA and surrounding cities. The results show that CO 2 emissions exhibit a spatial distribution pattern with spatial dependence. Furthermore, according to the analysis of spatio-temporal heterogeneity, GDP influenced CO 2 emissions the most within the five influencing factors, and the influences of GDP, population, and energy intensity were mainly positive, while the influence of patents was mainly negative, and that of trade was both positive and negative. [ABSTRACT FROM AUTHOR]

Entities in the power supply chain usually tend to cooperate with each other for higher profits. The inter mechanism between the entities and power supply chain is an urgent research subject. To consider the power supply chain and entities better, a extended model of bilateral contract mechanism is proposed in this paper. Utilizing a Stackelberg game, this paper studies dynamic coordination and strategic interactions between power plants, power retailers, and consumers in the electricity trading process under demand uncertainty. An improved coordination model is proposed to help entities get potential profits as well as improve the stability of the power supply. The model is applied to power trading data from Guangdong, China which imposes penalties for inaccuracies in demand variation. Simulations suggest the model's solution exhibits higher reliability and minimizes fines. [ABSTRACT FROM AUTHOR]

Background Context: Lumbar autonomic nerve injury is an underappreciated complication of anterior lumbar spinal surgery. A detailed description of lumbar autonomic nerve anatomy would be helpful for surgeons to minimize the risk of this complication.Purpose: This study was designed to investigate the anatomical characteristics of lumbar autonomic nerves and provide a better understanding of these nerves for anterior lumbar spinal surgery.Study Design: A dissection-based study of 10 embalmed male cadavers.Methods: The lumbar autonomic nerves from 10 embalmed male cadavers were dissected in this study. The position of the lumbar sympathetic trunks was recorded. Distance between the initial sites of the lumbar splanchnic nerves (LSNs) and the corresponding lumbar vertebral inferior endplate, distance between the ipsilateral and adjacent LSNs, angles formed by the LSNs and the vertical axis were measured. This study has been supported by grants from Science and Technology Planning Project of Guangdong Province (CN) (Grant No. 2017B020210010) without potential conflict of interest-associated biases in the text of the paper.Results: In this study, a total of 72 LSNs were identified in the 10 human cadavers. On average, the investigation found that the initial sites of the first, second, third, and fourth LSNs were 9 mm distal, 5 mm distal, 9 mm proximal, and 9 mm distal to the inferior endplates of the L1, L2, L3, and L4 vertebrae, respectively, with variations from 6 to 11 mm for each nerve among specimens. There was no significant difference in the angle between each lumbar splanchnic nerve and the vertical axis (H=2.461, p=.482), with an angle of approximately 50°±6°. The distance between the first and the second LSNs, the second and the third LSNs, or the third and the fourth LSNs were 24±6 mm, 22±8 mm, and 55±11 mm, respectively. The bilateral lumbar sympathetic trunks (N=57, 95%) were more likely to be located in the first third of the sagittal plane at the level of the L2/3, L3/4, and L4/5 intervertebral discs.Conclusions: The study found the same number and parallel courses of LSNs on each side, and on both the left and right side, the distance between the third and the fourth LSNs was much larger than the distance between the other two adjacent LSNs. The initial sites of 80.6% (n=58) of LSNs were superior to the inferior endplate of the L3 vertebra. Improved knowledge of lumbar autonomic nerve anatomy may be of great significance in reducing complications and improving surgical safety. [ABSTRACT FROM AUTHOR]

Background: Postoperative C5 palsy is not an uncommon complication in patients who undergo expansive open-door laminoplasty. However, the etiology is unclear and likely multifactorial. Nerve root lesions and spinal cord lesions have been previously proposed theories.Purpose: To investigate the anatomical mechanism of postoperative C5 palsy after cervical expansive open-door laminoplasty.Study Design: A dissection-based study of eight embalmed human cadavers.Methods: The anatomy was studied in eight whole cervical cadavers (three females, five males), prepared with formaldehyde, whose ages at the time of death ranged from 54 to 78 years. Dissection was performed on the intervertebral foramen and spinal canal. In the C3-C7 of the cervical vertebra, the extraforaminal ligaments and the meningovertebral ligaments were observed. The length, width, and thickness of the ligaments were measured with a Vernier caliper. After an expansive open-door laminoplasty was performed, the shape of the dural sac was changed, and displacement of the nerve root was observed. In addition, the lengths of the anterior rootlets were measured. This study has been supported by grants from Science and Technology Planning Project of Guangdong Province (CN) (Grant No. 2017B020210010) without potential conflict of interest-associated biases in the text of the paper.Results: One hundred seventy-seven extraforaminal ligaments were found to connect the spinal nerve to the surrounding structures. After an expansive open-door laminoplasty was performed, posterior distension of the dural sac and movement of the spinal cord and nerve root were found. The spinal cord was closely attached to the ligamentum flavum by meningovertebral ligaments. In addition, the length of the C5 intradural rootlets (5.81-10.59 mm) was the shortest among the vulnerable segments.Conclusion: Traction on and posterior movement of the extradural roots may be the main pathologic mechanism of postoperative C5 palsy when expansive open-door laminoplasty is performed. The meningovertebral ligaments and extraforaminal ligaments might play an important role in the occurrence of postoperative C5 palsy.Clinical Significance: This study provides clinicians with a more detailed understanding of the anatomic structure and potential mechanism of C5 palsy. Consideration of the meningovertebral ligaments and the intervertebral foramen may provide new directions for reducing the incidence of this complication. [ABSTRACT FROM AUTHOR]

When the ionosphere is strongly disturbed, the performances of satellite navigation and positioning systems as well as various radio communication systems are reduced due to the electronic density gradient and ionospheric irregularities. However, the characteristics and coupling mechanism of ionospheric disturbances caused by meteorological activities in the lower atmosphere are still unclear. Therefore, as one of the most severe surface weather changes, it is of great practical significance to study the influence of typhoons on the ionosphere. In this paper, the ionospheric irregularities during 20 typhoons landing in Taiwan, Guangdong Province and the Philippines during the quiet solar and geomagnetic activities from 2006 to 2018 were analyzed by using the rate of change in the total electron content (ROTI). Through a statistical analysis of 20 typhoons, it was found that there are ionospheric irregularities during 15 typhoons. There was a certain correlation between ionospheric disturbances and the typhoons. Both typhoons MANGKHUT and HAIMA landed in Guangdong Province, but ROTI > 0.5 T E C · m i n - 1 was detected only when typhoon HAIMA made landfall in Guangdong. This phenomenon can be explained by the influence of terrain on the acoustic gravity waves. The HAIMA typhoon passed through Lianhua Mountain (altitude: 1336 m). When the typhoon landed in higher terrain, due to the resistance effect of the high terrain, the high rate of decline in the air creates an ideal condition for the development of the acoustic gravity waves. During the impact of the typhoon, the acoustic gravity waves can spread to the ionosphere height and have an impact on the ionosphere. [ABSTRACT FROM AUTHOR]

Using the available information and a standard econometric approach analyzing the time series dataset, this study identifies the interactions between electricity, fossil fuel and carbon market prices in Guangdong, China. The result confirms a long running co-integration between carbon market prices and the prices of coal, diesel and liquid natural gas (LNG). Conversely, fossil fuel prices have no impact on the short term dynamics of carbon prices. The price of electricity on the monthly forward market in Guangdong is significantly and positively associated with the first difference of the price of coal, but has no significant relationship with the first differences of carbon, diesel and LNG prices. This analysis provides certain implications for ongoing power sector reform and nationwide carbon market development in China. The liberalization of the power industry should be further advanced to create conditions for carbon cost pass-through on to the electricity market. Meanwhile, the national emissions trading scheme (ETS) should apply simpler and stricter benchmarks to allocate emissions allowances for the power sector. Fewer categories of benchmarks promote competition among different types of power generators and a shift to an electricity supply portfolio with lower carbon intensity. Stricter benchmarks create more demand for emissions allowances and result in higher carbon market prices. To increase the ratio of emissions allowances by auctioning is also necessary to put substantial pressure on thermal power plants to pass their carbon costs on to end users. • This paper identifies the interactions between electricity, fossil fuel and carbon market prices. • A standard econometric approach is used to analyze the time series data in Guangdong, China. • The result confirms a long run co-integration between the prices of carbon and fossil fuels. • Carbon price change is not a significant factor to electricity prices of the monthly forward market. • This study gives insights to China's power sector reform and national carbon market development. [ABSTRACT FROM AUTHOR]

Evaluating the rural population hollowing (RPH) caused by the massive out-migration of rural laborers is essential for China's rural land use policy formulation and rural revitalization. Existing studies mainly assessed the RPH based on survey data or statistical data. The former is mainly based on selected local villages and towns, and cannot be replicated on a large scale, while the latter is usually at the county or city scale and cannot reveal the cyclical migration of rural labors at fine spatial resolutions such as townships. To fill this gap, this paper proposed a social media data based-rural population hollowing (SM-RPH) index, which was calculated by Tencent User Density big data on holidays and non-holidays and was used to characterize the "migratory bird" process of rural laborers. Taking Guangdong Province, China as the case, this study employed the proposed novel index to evaluate the RPH at the county and township scales. This was integrated with a GWR model to explore how the important contributing factors of RPH vary across the province. The results showed a trend of transition from the cold spot areas in the core regions of PRD to the hot spot areas around the PRD. Additionally, this study revealed that distance to the nearest prefecture-level city, total nighttime lighting per capita, fiscal expenditure per unit of GDP and road network density were dominant factors in affecting rural population hollowing, and the influence of these four variables vary considerably throughout the province. Further, k-means cluster was used to group the hollowing towns according to the local coefficients of the influencing factors, and policy zoning was suggested to provide differentiated countermeasures and suggestions for rural revitalization. This methodological framework can be easily applied to other regions, and is expected to be used to evaluate the return characteristics of migrant workers in real time to help monitor the progress of rural revitalization in China and provide decision support for policy makers. • This study proposed a social media data-based index for assess rural population hollowing (RPH). • The index is effective in evaluating the RPH at fine spatial resolutions such as townships. • We revealed the spatially non-stationary relationship between RPH and the associated factors. • We further put forwards the policy zoning and planning implications for rural revitalization. [ABSTRACT FROM AUTHOR]

Understanding the patterns of energy usage through simulation and prediction from multiple perspectives is crucial for alleviating energy-environmental conflicts and achieving sustainable energy system development. Despite their importance, multidimensional interactions among the production, demand, and supply sides have not been systematically characterized, thus representing a significant research gap. This paper aims to address this gap by developing a a multidimensional factorial enviro-economic (MFEE) model, which offers an in-depth investigation of Guangdong's energy system. This model, designed for retrospective decomposition (1997–2017) and prospective projections (2035), uniquely links historical and future analysis from systematic and sectoral perspectives through structural decomposition analysis, sectoral evolution analysis, and the Biproportional Scaling RAS method. Our findings reveal that the final demand level and Research & development (R & D) are the principal drivers of increased energy usage. We also found that the wholesale and retail sector have the most significant impact on demand and input sides, accounting for over 70 %. Furthermore, the interaction of key sectors from the production-based perspective notably influences system symbiosis. To effectively manage these dynamics, our study recommends regulating and controlling measures for the circulation sector that consider the benefits of both the energy sector and the accommodation and catering sector. This comprehensive analysis, therefore, offers scientifically-supported guidance for sustainable energy system development. • A multidimensional factorial enviro-economic (MFEE) model from Guangdong perspective is developed. • Approaches of retrospective decomposition and prospective projection for energy systems are conducted. • Interactive effects of various socioeconomic activities on economy and environment are characterized. • The main effects of wholesale and retail sector is the strongest, accounting for more than 70 %. [ABSTRACT FROM AUTHOR]

To address the deficiencies in traditional communication towers in mobile communication engineering, such as heavy weight, easy corrosion and poor durability, this study proposes replacing traditional communication towers with GFRP communication lattice towers with lightweight, high-strength and good durability. Firstly, GFRP material test and GFRP circle tube bending capacity test are conducted. The maximum bending moment that can be subjected to the anchorage end of GFRP circular tube is 18.20 kN·m. Finite element analysis of GFRP circular tubes verifies the accuracy of the bending test results. Secondly, a GFRP communication lattice tower with a height of 25 m is designed adopting GFRP circular tubes as tower columns. Through the bending test of the GFRP tower, it is verified that the connection between the columns and web members of the GFRP tower is reliable and the force pattern of the GFRP tower is reasonable. The large deflection theory can be adopted to the displacement of GFRP towers accurately. Thirdly, according to the actual engineering requirements, the finite element analysis of 25 m-high GFRP tower under the basic wind pressure of 0.45 kN/m2 is carried out by using 3D3S (a spatial structure design software). It can be obtained that the vibration mode of the GFRP communication tower shows two forms of lateral bending and axial torsion. 0° wind load direction has the greatest influence on the displacement of the GFRP tower. The stress ratio of each component in the GFRP tower is less than 1, indicating that no damage occurs in the GFRP tower. Finally, GFRP towers have good economic benefits, good environmental performance and wide range of application after comparing the GFRP tower and traditional steel tower. The demonstration project of the GFRP communication lattice tower is established in Qingyuan City, Guangdong Province, China. When subjected to a typhoon with a wind speed of 17.26 m/s, The horizontal displacement of the GFRP tower top is 10 m, which is about 2/5 of the height of GFRP tower. Although the displacement is large, the GFRP tower is still not destroyed. It can be concluded from the research in this paper that GFRP towers have low cost, good mechanical properties, good durability, and wide application range, which can promote the rapid construction of 5 G communication base stations. [Display omitted] • The bending moment of the GFRP tube can reach 18.20 kN·m. The finite element analysis match well with bending test. • A 25-m-high GFRP lattice tower is designed. The deformation of GFRP tower can be calculated by large deflection theory. • The vibration mode of the GFRP tower shows two deformation forms: lateral bending and axial torsion around the z-axis. • The GFRP tower has a large displacement but no damage, when subjected wind with the speed of 17.26 m/s. • Applying GFRP tower can effectively improve the construction efficiency of 5 G communication base station. [ABSTRACT FROM AUTHOR]

[Display omitted] • Groundwater vulnerability zonation investigation is conducted for GHM Greater Bay Area. • Three different perspectives are comprehensively considered in this study. • Groundwater risk, function value and contamination status are superposed using the AHP method. • Quantification and visualization of groundwater contamination prevention regionalization. • The AHP-DRASTICH model is an effective method to evaluate the groundwater risk in shallow aquifers. The groundwater contamination assessment and prevention regionalization are an important part of groundwater investigation, which is of great significance to groundwater environmental management and contamination control. Although the Guangdong-Hong Kong-Macao Greater Bay Area (GHM Greater Bay Area) has faced significant groundwater contamination since 2020, there's been no investigation into its vulnerability zonation. In this paper, groundwater in a typical area of south China was taken as the research object. We analyzed groundwater contamination risk by considering both the groundwater vulnerability and the load from contamination sources. Using the analytic hierarchy process (AHP) method, we superposed the groundwater risk, function value and contamination status, and realized the quantification and visualization of groundwater contamination prevention regionalization. Based on the DRASTIC model, the zones of low, moderate, high, and very high vulnerability are respectively 14.2 %, 24.28 %, 37.67 %, and 20.45 % of the study area. Results show that the groundwater vulnerability grade in the area is III-IV, which means it is easy to be polluted. The functional value of groundwater in the south-central part of the region is relatively high. Most of the areas with high prevention and control levels are located in plain areas and the Piedmont plain area with an area of 460 km2. The secondary control levels (key protection area) are mainly located in the middle, southwest, and northeast of the plain, with an area of 6944 square kilometers. Consequently, the ideas and contamination prevention zone maps might provide a scientific foundation for long-term planning and management and groundwater conservation in the Guangdong-Hong Kong-Macao Greater Bay Area and peripheral zones. [ABSTRACT FROM AUTHOR]

As the population and industries continue to gather in cities, such cities face acute shocks caused by various natural disasters and high pressure caused by human interference. The means of accurately assessing and improving the level of urban resilience (UR) to cope with disturbances and shocks, enhance regional resilience, and improve sustainable urban development has become a hot topic. In this study, we constructed an UR assessment framework using "social-economic-institutional-ecological-engineering" to explore the dynamic evolution of spatial and temporal patterns in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China, to reveal the main factors influencing the evolution of this spatial pattern and the strength and interaction mechanisms among such influencing factors and to dynamically simulate the spatial and temporal evolution characteristics in the next 16 years. The results show that from 2000 to 2019, the difference in UR level in the GBA is obvious. Hong Kong and Macao are obviously ahead of other cities, and the comprehensive resilience level of Guangzhou and Shenzhen cities in the mainland is developing rapidly. The difference in per capita consumption capacity, industrial structure optimization, foreign trade vitality, infrastructure support and other factors are the main causes of the spatial differentiation of UR in the GBA. In the future, the UR level of the GBA urban agglomeration will show an overall upwards trend. The three development poles of Guangzhou-Foshan, Shenzhen-Hong Kong, and Zhuhai-Macao have obvious advantages in spatial distribution. The results of the study can enrich regional UR research, and also provide theoretical references to facilitate the high-quality development of the area. [Display omitted] • We constructed a "social-economic-institutional-ecological-engineering" urban resilience assessment framework. • The paper developed an evaluation system for the urban resilience to reveal its spatial and temporal evolution patterns. • The main factors influencing the evolution of the spatial patterns of urban resilience is investigated. • Our results provide a basis for the development of comprehensive management framework for urban resilient. [ABSTRACT FROM AUTHOR]

In this paper, the typical 10-lane highway in the reconstruction and expansion project is taken as an example to clarify the noise propagation and distribution characteristics of ultra-wide cross section. With the aid of the highway noise prediction model based on the acoustic environment guidelines and field measurements, the noise propagation and distribution characteristics under ultra-wide cross section were summarized through visualized noise maps and quantitative data analysis. The results show that for the highway with ultra-wide cross section, reducing the speed of small vehicles can improve noise reduction in the horizontal direction by about 1 dB(A) than reducing the speed of large and medium-sized vehicles. In addition, the noise reduction effect of all floors can be improved by 0.2–0.9 dB(A) in the vertical direction, which proves that the noise reduction effect is more obvious by reducing the speed of small vehicles. Besides, the noise sound pressure level variation range on low-rise floors increases more significantly with increased traffic volume than high-rise floors. The variation between different building floors is also similar to the increase in traffic volume in the vertical direction. The result can provide theoretical guidance for the prevention of highway noise under ultra-wide cross section. • The noise propagation of highway under ultra-wide cross section was investigated. • 2D and 3D spatiotemporal noise maps were presented to analyze traffic noise. • Noise reduction effect of reducing small vehicles' speed was more obvious. • Provide reference for the prevention of highway noise of extension engineering. [ABSTRACT FROM AUTHOR]

• The paper proposes a data processing method based on data cleaning and multi-sensor fusion, which can greatly reduce the impact of background noise. • The intelligent feature recognition of vibration acceleration time-domain signals based on an improved 1DCNN algorithm can improve the monitoring accuracy and speed significantly. • An online monitoring technology for transmission towers bolt looseness has been developed and successfully applied to the Guangdong power grid. Minor damages such as tower bolt looseness are difficult to detect through manual inspections. Operational modal analysis plays an important role in the online monitoring of transmission tower structure safety. However, the traditional analysis methods select feature parameters manually, and the deviation generated will directly affect the estimation accuracy of structural modal parameters. This article proposes a method for diagnosing tower bolt looseness without human intervention. This method can reduce the influence of background noise greatly through data cleaning and data fusion. Besides, the intelligent feature recognition of vibration acceleration time-domain signals based on an improved 1DCNN algorithm can improve the monitoring accuracy and speed significantly. The effectiveness of the method has been validated by conducting dynamic response tests on a 110KV transmission tower under different bolt loosening conditions. In the end, an online monitoring technology for transmission towers bolt looseness has been developed and successfully applied to the Guangdong power grid. The results show that this method has high identification accuracy and provides a new approach for online monitoring of tower bolt looseness. [ABSTRACT FROM AUTHOR]

In the context of China's dual‑carbon goals and electricity market reforms, the high penetration of renewable energy sources (RES) in a single microgrid (MG) imposes challenges to its flexible operation. This paper addresses the cooperation within a virtual power plant (VPP) aggregated by multiple MGs. The VPP, managed by the VPP operator, acts as an intermediate entity to facilitate MGs' economic and low-carbon operation. To ensure the interests of various stakeholders in the VPP, this work proposes a low carbon oriented tri-stage collaborative energy management framework. In the 1st stage, the day-ahead optimal scheduling of individual MGs and the bidding strategy of the VPP operator are modeled, where an internal pricing method is incorporated. The 2nd stage addresses the real-time redispatch of the VPP operator using a receding horizon-based model predictive control (MPC) solution. This aims to satisfy the real-time operational requirements of MGs and reduce adjustment costs. Furthermore, in the 3rd stage, a penalty allocation mechanism is established for MGs based on their forecasting errors, to protect the VPP operator's interests. The effectiveness of the proposed solution is evaluated through comparative simulations in the context of the Guangdong electricity market. • The virtual power plant (VPP) aggregated by multiple microgrids (MG) is studied. • The quantification of carbon emission is involved in the whole scheduling process. • An peer-to-peer (P2P) electricity trading pricing method is improved and adopted. • A penalty allocation mechanism is proposed to guarantee interests of each entity. • The Guangdong electricity market is considered as the market mechanism. [ABSTRACT FROM AUTHOR]

In theory, replacing workers with robots in dangerous working environments can protect workers' safety. Therefore, a higher frequency of occupational injuries (OIs) may force more industrial robot applications (IRAs). Based on panel data from cities in Guangdong Province from 2003 to 2015, this paper uses a fixed effects panel Tobit model to test the impact of OIs on IRAs. Considering the possibility of a reverse causal relationship between IRAs and OIs, we also use the number of urban cultural academies as an instrumental variable to overcome the endogeneity problem. This study shows that more frequent OIs force more IRAs. The government's industrial policies promote industrial intellectualization but also weaken the promotion effect of OIs on IRAs to a certain extent. The mechanism analysis shows that the heavy burden of public medical expenditure is an important mechanism of OIs forcing IRAs. This paper confirms the driving mechanism of OIs on IRAs, reveals the moderating effect of industrial policy on the impact of OIs on IRAs, and clarifies the mechanism of OIs on IRAs from the perspective of public medical expenditure. • Frequent occupational injuries force more robot applications. • The industrial policy weakens this effect. • The heavy burden of public medical expenditure is an important mechanism. • Urban cultural atmosphere is used as an instrumental variable. [ABSTRACT FROM AUTHOR]

• An incentive mechanism is introduced to improve the responsive load model. • A real-time price mechanism is proposed based on the balance of supply and demand in flexible islanded microgrid (FIMG). • The definitions of FIMG flexibility and flexibility insufficiency rate (FIR) are given, and the importance of FIR in the hybrid energy storage system (HESS) capacity optimization is verified by a case study. • The NSGA-II and the improved TOPSIS are used to obtain the optimal solution. The islanded microgrid (IMG) is universally accepted as an important method to solve the island power supply problem. The optimal capacity of the hybrid energy storage system (HESS) is necessary to improve safety, reliability, and economic efficiency in an IMG. To improve the IMG ability to deal with uncertainty, this paper proposed a flexible islanded microgrid (FIMG) model with real-time price (RTP)-based demand response (DR). Through RTP to guide users' electricity consumption behaviors more in line with renewable energy sources (RES) output law, the capacity allocation of the HESS was optimized and the system had sufficient flexibility in each scheduling period. In this paper, two decision variables of the HESS, the number of lead-acid batteries and supercapacitors, were determined based on the objective of comprehensive operating cost (COC) and flexibility insufficiency rate (FIR) minimization. Firstly, the non-dominated sorting genetic algorithm II (NSGA-II) was devoted to obtaining the Pareto set that satisfies the FIMG day-ahead scheduling. Then, both the loss of produced power probability (LPPP) and the loss of power supply probability (LPSP) corresponding to each Pareto solution were gotten based on the real-time dispatch strategy. Finally, taking COC, FIR, LPPP, and LPSP as evaluation indicators, the improved Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) was applied to select the optimal solution from the Pareto set. In the case study, a FIMG on an island in Guangdong province was analyzed and discussed. By studying typical days in winter and summer of the FIMG, the superiority of the proposed model and methods was verified. [ABSTRACT FROM AUTHOR]

Abstract: Since China's economic reforms began in 1978, rural–urban migration has accelerated urban growth and the consequential need for regional planning. In order to make effective strategic decisions on regional planning, it is essential to identify the determinants that promote or restrain urban growth. Based on the theoretical underpinnings of classical economics, spatial economics and sustainable development, this paper establishes a theoretical model of urban population growth and uses a case study of China's Guangdong Province to test a hypothesis. The driving force of urban population growth is derived from natural and mechanical increases that include original urban size, living environment, industrial agglomeration, and location. Regression results from the case study reveal that during the period 2000–2010, factor of dominant industry significantly and consistently impacted urban growth, whereas the influence of living conditions and location on urban growth varied from year to year. These findings imply that local government pays less attention to residents' livelihood and more to the effect of location on urban growth. The paper concludes by proposing some regional planning policies for sustainable development. [Copyright &y& Elsevier]

Abstract: Providing Information and Communication Technologies (ICT) to rural areas often involves a complex interplay among economic development, bureaucratic systems, technical training and support. Nowhere are these dynamics more pronounced than in China, where a wide range of economic and institutional factors characterize the highly uneven state of informatization 2 [2] Defined as the transformation of an economy and society through the effective deployment of information and communication technologies in business, social, and public functions (Qiang, Bhavnani, Hanna, Kimura, & Sudan, 2009). This paper uses the terms informatization and ICT interchangeably depending on the context. throughout the country. Through a case study on Guangdong Province, China, this paper offers an in-depth examination of institutional issues in rolling out advanced information services (such as Internet) in rural China. The experiences from Guangdong help identify a number of systemic issues: (1) inefficient and wasteful spending resulting from interdepartmental rivalry (2) lack of policy continuity and institutional learning (3) lack of accountability and credible measurements (4) central planning resulting in gap between services and local needs. This paper calls for more emphasis on outcome assessment and coordination. First of all, in order to reduce waste and more fully exploit the benefits of system-wide reform, the incorporation of better assessment methods into policy measures should precede large-scale network rollout. Meanwhile, high level officials should be appointed to coordinate various departments and legislation may help to achieve coordination and policy continuity. [Copyright &y& Elsevier]

Abstract: This paper is the second in a series of three papers aimed at understanding the emissions of vehicles in China by conducting on-board emission measurements. This paper focuses on light-duty gasoline vehicles. In this study, we measured 57 light-duty gasoline vehicles (LDGVs) in three Chinese mega-cites (Beijing, Guangzhou, and Shenzhen), covering Euro 0 through Euro IV technologies, and generated CO, HC, and NOx emission factors and deterioration rates for each vehicle technology. The results show that the vehicle emission standards have played a significant role in reducing vehicle emission levels in China. The vehicle emission factors are reduced by 47–81%, 53–64%, 46–71%, and 78–82% for each phase from Euro I to Euro IV. Euro 0 vehicles have a considerably high emission level, which is hundreds of times larger than that of Euro IV vehicles. Three old taxis and four other Euro I and Euro II LDGVs are also identified as super emitters with equivalent emission levels to Euro 0 vehicles. Of the measured fleet, 23% super emitters were estimated to contribute 50–80% to total emissions. Besides vehicle emission standards, measures for restricting super emitters are equally important to reduce vehicle emissions. This study is intended to improve the understanding of the vehicle emission levels in China, but some key issues such as emission deterioration rates are yet to be addressed with the presence of a sufficient amount of vehicle emission measurements. [Copyright &y& Elsevier]

Abstract: The purpose of this paper is to analyze the impact of organizational features and context variables on the proneness of University-Industry cooperation (UIC) in the R&D and engineering process. Using survey data of manufacturing enterprises in Guangdong province of China, the paper shows that the probability of cooperation with university significantly depends on various organizational factors including firm size and enterprise absorptive capacity. In addition, the actually pay tax the collection of business-to-market and technical information, and market position are also important driving factors to the engineering research cooperation between enterprises and universities, but their influences vary with the type of product innovation and process innovation. [Copyright &y& Elsevier]

• A big data computational text analysis based on a corpus of 2.4 million words. • Comparison of major themes on air pollution in stakeholder discourse in Hong Kong. • Three stakeholder groups are studied; all focus on emissions and pollution control. • Public health is a greater concern in MEDIA compared with other groups. • More personalized health information to be shared with the vulnerable groups. Stakeholder engagement is critical to the successful formulation and implementation of environmental policies. Text analysis can serve as an important means to decipher stakeholder (dis)agreements. Traditionally, researchers analyze texts using qualitative text analysis. Relying only on qualitative text analysis can no longer be sufficient to handle very large amounts of textual data. Now computational methods can be applied to help extract opinions in electronic texts. Our paper adopts a big data computational text analysis approach (keyword analysis, keyword co-occurrence, thematic analysis), based on a corpus of 2.4 million words, to compare concerns towards air pollution among three stakeholder groups (i.e. the government (GOV), the environmental groups (NGO) and the news media (MEDIA)) in Hong Kong, between 2002 and 2012, a period when air pollution was subject to rigorous policy debates and discussions. Our analysis shows the somewhat different concerns of the stakeholders. The stakeholders focus heavily on emissions and end-of-pipe pollution control. Though the advocation of sustainability since 1990s, the government-led command-and-control approach still dictates the discourse. Sustainability is featured more intensively by the Hong Kong Special Administrative Region (HKSAR) Government. Transboundary pollution (e.g. from Guangdong, China) is not a major concern for all stakeholder groups. Public health is a greater concern in MEDIA, as compared to the other two stakeholder groups. Future air pollution policy-making may direct more of its attention to the pressing concerns over the negative impacts of air pollution on health and its associated costs, with health experts getting more closely involved in the regulatory decision-makings. More information should be given to vulnerable groups, such as young children or workers in polluted environments. To better relate differential health risks of pollution in everyday life, both local and international governments should consider developing more personalized air pollution monitoring and health management systems for their citizens in future. [ABSTRACT FROM AUTHOR]

Rapid urbanization results in energy shortage and unreasonable energy metabolism structure. The goal of this research is to take Guangdong, China as a special case study to illustrate the influence of energy classification differences on the energy metabolism system. To do so, we introduced the concept of "urban metabolism", and treated sectors and energy flows as nodes and paths in a network model. We used the input output analysis to compile the physical input output table through the embodied energy element intensity. Building on this, we used ecological network analysis to quantify the urban metabolic processes and energy metabolism levels within the urban system. In addition, the alternative indicators are first introduced to explore the best alternative energy in various sectors to avoid a short-term energy crisis. In this paper, different energy groups are considered on the energy metabolism system, including all energy, primary energy, secondary energy and six specific energy, which will fill the research gap about the influence of energy classification on urban energy metabolism. It is found that the energy metabolism of Guangdong is now in the state of sub-health. The energy metabolism hierarchy atlas shows that the pulling force is hardly affected by the energy classification but the driving force is very sensitive, which further illustrate that producers can choose different energy according to their production structure. Facing the shortage of energy supply, the secondary energy with the highest substitutability of all energy value is the better alternative energy for advanced manufacturing sector (containing twelve industries such as Manufacture of transportation equipment and Manufacture of metal products). More specifically, the nonrenewable properties of primary energy make it particularly important to find the corresponding alternative energy. Heat is the best alternative energy for crude oil, while electricity is irreplaceable. It is expected that the results will provide scientific support to guide the reform of urban energy metabolic system in an attempt to coordinate the energy development strategy, improve the energy consumption structure and maintain energy security and stability. • An Energy Metabolism Network (EMN) model from a Guangdong perspective is developed. • Different energy types have a great impact on the level of energy metabolism. • The inherent mechanism of energy ecosystems are revealed by the energy hierarchy atlas. • In-depth analysis is conducted to investigate the energy interactions between different industries. • Scientific basis for supporting the formulation of the effective reform of urban energy metabolism system. [ABSTRACT FROM AUTHOR]

Site selection is a key factor to the success of ocean thermal energy conversion (OTEC) project. It is a multi-criteria decision making (MCDM) problem with a series of conflicting criteria involved. However, limited studies were found concerning this area and problems existing in classical MCDM methods tended to fail OTEC site selection decisions. Therefore, this paper proposes an extended MCDM method and establishes a new decision-making framework to select the optimal location. First, a comprehensive evaluation criteria system for OTEC site selection from the view of sustainability with 16 criteria involved is established. Second, feasible alternative sites for OTEC project are identified by PEST analysis. Third, an extended PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation) under intuitionistic fuzzy environment is proposed to avoid compensation assumptions. During the decision process, seven groups of experts shared the work and cooperated with each other according to their backgrounds. Finally, a real case is studied and sensitive analysis is conducted, demonstrating the robustness and effectiveness of the proposed method. This study can effectively improve OTEC site selection decision making quality and also extends the domains of intuitionistic fuzzy PROMETHEE applications. • A novel multi-criteria decision-making framework for site selection is proposed. • The criteria system for ocean thermal energy conversion site selection is constructed. • A case study is carried out in areas of Guangdong and Guangxi Provinces in China. [ABSTRACT FROM AUTHOR]

• Couples of multiparameter screening and compositional simulation are useful for site optimization for CO 2 -EOR and storage. • Miscible CO 2 flooding with one or two injection wells are the best operation for M10 reservoir. • Well pattern and bottom pressures of CO 2 injection control the mechanism and efficiency of CO 2 flooding. • HZ21-1 field has considerable potential for applying offshore CO 2 -EOR and CO 2 storage technology of Guangdong CCUS project. CO 2 -enhanced oil recovery (CO 2 -EOR) and storage is currently the most effective and economic technology for reducing CO 2 emissions from burning fossil fuels in large scale. This paper is the first effort of proposing a modelling assessment of CO 2 -EOR and storage in the HZ2-1 oilfield in the Pearl River Mouth Basin in northern South China Sea offshore Guangdong Province. We attempt to couple the multi-parameter dimensionless quick screening model and reservoir compositional simulation for optimization of site screen and injection simulation. Through the quick screening, the reservoirs are ranked by EOR dimensionless recovery R D , and by CO 2 storage in pore volume S CO2. Our results indicate that S CO2 is highly pressure dependent and not directly related to R D. Of these reservoirs, CO 2 -EOR and storage potential of the M10 was estimated through a compositional simulation as a case study based on a 3D geological model. Nine scenarios of CO 2 injection operations have been simulated for 20 years with different well patterns and injection pressures. The simulation results represent an obvious improvement in oil production by CO 2 flooding over No−CO 2 production. The best operation for M10 is miscible CO 2 flooding, which led to the higher recovery factors of 52%˜58% and CO 2 stored masses of 8.1×106˜10.8×106t. The optimum operation for CO 2 injection should be set well pattern in region of injector I1 and high injection pressure for miscible flooding. In a whole, the HZ21-1 field can be used as a candidate geological site for GDCCUS project. We are fully aware of the limitation in the primary modelling including reservoir and fluid properties and production history matching, and regard this study as a general and hypothetic proposal. [ABSTRACT FROM AUTHOR]

There is increasing concern about phenolic environmental estrogens (PEEs) in river systems, especially in economically developed regions, because of their potential to impact ecological systems. We studied the distribution of, ecological risks from, and factors that influenced PEEs in the sediments from the Duliujian River in the Beijing-Tianjin-Hebei Urban Agglomeration and the Pearl River in Guangdong Province in China. The three target PEEs, nonyl phenol (4-NP), octyl phenol (4-t-OP), and bisphenol A (BPA), were detected in the sediments at concentrations ranging from 204.4 to 12604.3, 32.6 to 297.3, and from 12.8 to 298.4 ng g−1 in the Pearl River, and from 153.5 to 3614.9, 90.7 to 990.0, and 83.5–913.3 ng g−1 in the Duliujian River, respectively. The PEE concentrations were significantly and positively correlated with total organic carbon in the river sediments (p < 0.1). Urbanization influenced the distribution of PEEs and applications and discharges of PEEs were associated with large populations and industries. Rainfall and wastewater discharge patterns also influenced how PEEs were distributed in river sediments. The potential ecological risks from 4-NP, 4-t-OP, and BPA in these two rivers were high. Measures should be put in place to control the transport and storage of these compounds in river systems. Image 1 • We evaluated the distribution of, and risks from, PEEs in river sediments. • 4-NP dominated the PEEs found in the river sediments. • The PEE distribution was influenced by urbanization, rainfall, and organic carbon. • The ecological risks from PEEs in the river sediments were high. This paper investigates the effects of urbanization and rainfall on the distribution and risk of PEEs in river sediments, which could support the development of guidelines to control the PEEs in river systems in China. [ABSTRACT FROM AUTHOR]

Abstract Manufacturing industry is an important part of economic development. Recognizing the sustainable development of regional manufacturing has an important guiding role in the formulation of environmental policies. Based on the meta-frontier Malmquist-Luenberger (MML) productivity index, this paper uses Chinese provincial panel data (2003–2015) to measure the green total factor productivity (TFP) of China's manufacturing. It is decomposed into the following: efficiency change (EC), change of the best practice gap ratio (BPC) and change of technical gap ratio (TGC). We compared the regional differences in green TFP growth in manufacturing in all provinces, analyzed regional and time differences in green TFP and the decomposition of manufacturing between regions and identified innovative regions. The results show that: (1) The average annual growth rate of green TFP in Chinese manufacturing is 0.85% with technological progress playing a key role. (2) There are differences in the causes of the increase in green TFP in all regions. The eastern region and the western region are driven by technological progress while the central region depends on technology catch-up effects. (3) Guangdong and Qinghai are two different types of global innovation regions with Guangdong driven by technological innovation and Qinghai driven by strict environmental protection systems. [ABSTRACT FROM AUTHOR]