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Scientific and technological innovation and ecological progress are important forces for China's high-quality development. Nevertheless, the current body of research seldom explores the mutual dependence and evolutionary patterns of the two regional systems when considering both historical and future perspectives. This paper aims to enhance the current theoretical research framework by focusing on the coastal region of China. It analyzes and predicts the co-evolution and space–time distribution process of two systems by constructing a coupled model and a gray prediction model. The results show the following: (1) the coupling and coordinated development level of the two coastal systems has basically reached the stage of good coupling and coordinated development, and the level has increased, but the gap has gradually increased, and Jiangsu and Guangdong have reached the leading level; (2) the spatial distribution in coastal areas is uneven, showing a convex spatial pattern of "high in the middle and low at both ends"; (3) during the forecast period, the overall coupling and coordination level of the two systems will continue to improve, but individual cities still cannot jump out of the development state of slow development processes. With the aim of fostering the harmonious growth of both systems at both regional and national levels, this paper proposes practical recommendations concerning the establishment of a sustainable interaction mechanism, the evolution of the industrial structure towards ecological sustainability, and the economic contribution to scientific and technological innovation. Furthermore, this article serves as a valuable reference for advancing the sustainable development of other nations. [ABSTRACT FROM AUTHOR]

With the rapid development of the world city network, the traditional location theory has gradually been disproven, and the advantages of the flow space over the traditional vertical organizational structure are gradually being revealed. Therefore, from corporate branch networks and corporate investment networks, 21 cities in urban agglomerations of Guangdong are taken as case studies for this paper. Furthermore, in this paper, 5 representative types of corporate contact data (catering service, financial service, life service, sports and leisure and accommodation service) are selected, the social network analysis (SNA) method is used to quantitatively analyze the network structure characteristics of urban agglomerations, and a spatial interaction model is constructed to explore the factors influencing. The results indicate that secondary networks have developed in Guangdong. The financial service network is the most complex, followed by the life services, sports and leisure and catering networks. The accommodation service network structure is the simplest. Among all kinds of networks, Guangzhou and Shenzhen have the highest status. The catering and accommodation corporations in Yangjiang in the west have a relatively major external development. Shantou in the east has many branches of various types, while most of the capital exchange in the region is concentrated in Heyuan and Qingyuan in the north. The coefficients of geographical proximity and the urban development level play a significant role in promoting the development of networks. However, administrative capacity limits the attractiveness of origin cities to a certain extent. [ABSTRACT FROM AUTHOR]

An increasing number of countries have launched their central bank digital currencies (CBDC) in recent years, but the economic impacts of CBDC adoption are underexplored. To empirically assess how CBDC adoption influences regional economic integration, this paper investigates the Greater Bay Area, where China carried out one of its first digital renminbi pilot programs. The Greater Bay Area provides a good example because the growing acceptance of digital renminbi in the area can potentially mitigate transaction costs and risks due to the exchange rate volatility of the Chinese renminbi, Hong Kong dollar, and Macao pataca. CBDC adoption can lead to greater real and financial integrations by facilitating cross-border trade in goods and services. This paper evaluates deviations from uncovered interest rate parity, purchasing power parity, and real interest rate parity across Guangdong, Hong Kong, and Macao based on monthly interest rate and price data from January 2016 to December 2022. The time series have mean values near zero, which validate the parity conditions and indicate high degrees of financial, real, and economic integrations. The Markov regime-switching regression model identifies three regimes: (1) pre-Covid, (2) post-Covid, and (3) post-CBDC. The Covid-19 outbreak brought lower integration and stability, but the launch of the CBDC restored some of the pre-Covid integration and stability. Regimes 1 and 2 are persistent, and transitions from Regime 3 back to Regime 1 are probable. Hence, this study finds evidence that CBDC adoption improves regional economic integration in the short and long run. [ABSTRACT FROM AUTHOR]

To ensure the safe operation and dispatching control of a low-voltage distributed photovoltaic (PV) power distribution network (PDN), the load forecasting problem of the PDN is studied in this study. Based on deep learning technology, this paper proposes a robot-assisted load forecasting method for low-voltage distributed photovoltaic power distribution networks using enhanced long short-term memory (LSTM). This method employs the frequency domain decomposition (FDD) to obtain boundary points and incorporates a dense layer following the LSTM layer to better extract data features. The LSTM is used to predict low-frequency and high-frequency components separately, enabling the model to precisely capture the voltage variation patterns across different frequency components, thereby achieving high-precision voltage prediction. By verifying the historical operation data set of a low-voltage distributed PV-PDN in Guangdong Province, experimental results demonstrate that the proposed “FDD+LSTM” model outperforms both recurrent neural network and support vector machine models in terms of prediction accuracy on both time scales of 1 h and 4 h. Precisely forecast the voltage in different seasons and time scales, which has a certain value in promoting the development of the PDN and related technology industry chain. [ABSTRACT FROM AUTHOR]

Based on the best-track dataset from the Shanghai Typhoon Institute/China Meteorological Administration, the paper provides a comprehensive summary and analysis of tropical cyclone (TC) activities in the Western North Pacific (WNP) and the South China Sea (SCS) for 2022. Using the historical climatology from 1951 to 2020, the anomalous conditions during 2022 in TC frequency, origin locations, tracks, intensity, and duration for the entire ocean basin as well as landfall events in China are examined. Results show that the overall TC frequency is slightly lower than normal, but the multiple TC events have a very high frequency of occurrence. Origin locations of TCs, which mark the starting points of their paths, show a large westward and northward deviation from climatology. Around 40% of the named TCs exhibit a shift in their direction of movement from westerly to easterly. Additionally, comparisons of the means, medians, upper and lower quartiles all indicate that the intensity of TCs in 2022 is generally lower than the climatology, with the duration of TCs at tropical storm intensity or above being shorter than usual. A notable observation is the fewer incidence of TC landfalls in China, but with a geographical concentration in Guangdong Province. These anomalous annual TC activities are influenced by related atmospheric and oceanic environmental conditions modulated by multi-scale climate variability. The findings provide useful information for enhancing disaster mitigation strategies in the Asia-Pacific region. [ABSTRACT FROM AUTHOR]

As the core system of rail transit to ensure traffic safety and improve transport efficiency, the train control system plays an important role in the design and implementation of multi-network integration. This paper focuses on analyzing the characteristics and differences of the mainstream train control systems from the aspects of construction objectives, system selection, technical routes and other aspects in combination with the construction needs of the multi-network integration of the Guangdong-Hong Kong-Macao Greater Bay Area urban express line, and expounds the integration scheme and difficulties, so as to provide certain ideas and references for the selection and design of the follow-up train control systems. [ABSTRACT FROM AUTHOR]

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Due to the imbalance in the supply and demand of agricultural land, there is an increasing trend of land resources being remoted utilized across regions. Within the context of regional trade, changes in the agroecosystem service value (ESV) can be used to assess consumer responsibility. However, the embodied flow of ESV and its driving factors have been largely unexplored. This paper, utilizing the latest Chinese multi-regional input-output tables and the equivalence factor method, explores the spatiotemporal characteristics of embodied agricultural land and ESV flow between Guangdong and 30 other provinces, and further seeks to construct three types of embodied ESV models to reveal the driving factors. The findings reveal that during the process of domestic trade in goods and services, Guangdong Province has an inflow of 2.10 × 107 hm2 of land from other provinces, with arable land, forestland, and grassland accounting for 25, 61, and 14%, respectively. Guangdong's utilization of ESV is mainly dependent on external inflows, with minimal local consumption and outflows. The embodied ESV between Guangdong and other provinces is 1626.10 billion yuan, with an outflow of 325.32 billion yuan. The "Y"-shaped region consisting of the northwest, northeast, southwest, and Hainan bears significant potential ESV losses for Guangdong Province. Population growth and the intensity of ESV loss will promote the flow of cropland and forestland ESV, while economic development has a certain inhibitory effect on ESV transfer. This paper provides a new analytical perspective on issues such as the spatial distribution mismatch of land resources and ecologically unequal exchange. These insights are pivotal for promoting sustainable utilization of land resources and regional equity. [ABSTRACT FROM AUTHOR]

Forest carbon sink efficiency refers to the efficiency of input-output indicators related to carbon sinks. This paper studies carbon sink efficiency from the perspective of resource allocation; guides the optimal allocation of resources; and selects forestry employees, forestry investment amount and afforestation area as input indicators; the forest carbon sink efficiency in China is calculated and analyzed based on a data envelopment analysis model by converting the forest volume into the forest carbon sink through the volume expansion factor method. The grey prediction model is used to estimate the change in the input indicator, and the production possibility set is constructed with the input indicator before and after the change and the current output indicator. The efficiency of the decision units before the change is calculated, and through the comparison of efficiency, the conditions of forest carbon sink increase in 15 provinces are obtained. The optimal allocation of the output indicator is calculated based on the inverse data envelopment analysis model. The largest increase in forestry carbon sink is 169,362 megatons in Guangdong, and the smallest is 619 megatons in Tianjin. Finally, some suggestions for the path of forest carbon sink increment are put forward. [ABSTRACT FROM AUTHOR]

Air-booster vacuum preloading (AVP) without sand blanket and surcharge vacuum preloading (SVP) methods were used to treat two adjacent areas in a foundation reinforcement project on Donghai Island, Zhanjiang City, Guangdong Province, China. In this study, engineering characteristics of the AVP foundation were obtained through analyzing monitoring data. Results showed that the AVP method obtained superior foundation consolidation results compared to SVP method. This study proposed a new simplified mechanical model for AVP, with a single PVD (prefabricated vertical drain) centered and the air-booster pipes symmetrically distributed around the PVD, applied equivalent air-booster pressure to the drainage boundary. Furthermore, this study established a mathematical analytical model for predicting consolidation settlement based on the proposed simplified model. By comparing the theoretical settlement value with the measured value, this paper verifies the rationality of the analytical solution. Finally, this study analyzed the effects of well resistance, smearing effect, compression index, and permeability index ratio on consolidation characteristics. Land reclamation projects will generate a large amount of dredged ultrasoft soil foundation. The AVP method can achieve superior foundation treatment effects by injecting gas into soil mass through air-booster pipes. The results of this case study demonstrate that the AVP method has substantial advantages compared to the conventional vacuum preloading method. The AVP method can increase foundation settlement, shorten the time for foundation treatment construction, and improve the foundation reinforcement effect. In addition, the AVP method can alleviate PVD clogging and maintain soil permeability, while simultaneously avoiding the excessive use of dredging sand. Therefore, the AVP method can lead to potential economic benefits and protect the natural environment, and it is a method worth considering. Moreover, the mathematical model for predicting consolidation settlement of the AVP method was proposed based on new mechanical assumptions, which can be applied as a reference for settlement prediction in relevant engineering, and the rationality has been verified through comparison with measured settlement results. [ABSTRACT FROM AUTHOR]

Multiple datasets related to pond and marine aquaculture have been published using diverse remote sensing technologies, yet a comprehensive dataset detailing spatial distribution on both land and sea sides is lacking. Firstly, a meticulous comparison of datasets which we selected related to aquaculture ponds and marine, ensuring consistency in trends. Subsequently, the datasets published by our team were edited and integrated to illustrate aquaculture activities on both sides of China's coastal zone. Finally, a spatial differentiation of coastal aquaculture in major provinces was analyzed. This analysis also utilizes the types of coastline and statistical data, guiding coordinated resource management efforts. The results unveil a distinctive spatial distribution pattern, concentrating aquaculture in the northern regions—Bohai Sea, Jiangsu, Fujian, and Pearl River coasts in Guangdong. The provinces rich in aquaculture resources, such as Shandong, Guangdong, and Liaoning, exhibit extensive coastlines. However, remote sensing monitoring suggests an underestimation of Liaoning's marine aquaculture compared to statistical yearbook data. Furthermore, southern provinces like Guangdong and Fujian exhibit significantly higher aquaculture output than Liaoning. Zhejiang leads in fishing output. The paper outlines the future development direction of coastal aquaculture, emphasizing a strategic, integrated land–sea approach for sustainable development. [ABSTRACT FROM AUTHOR]

As one of the four major bay areas in the world, the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is a highly integrated mega urban agglomeration and its unparalleled urbanization has induced prominent land contradictions between humans and nature, which hinders its sustainability and has become the primary concern in this region. In this paper, we probed the historical characteristics of land use and land cover change (LUCC) in the GBA from 2005 to 2015, and forecasted its future land use pattern for 2030, 2050, and 2070, using a cellular automata–Markov (CA–Markov) model, under three typical tailored scenarios, i.e., urban development (UD), cropland protection (CP), and ecology security (ES), for land use optimization. The major findings are as follows: (1) The encroachments of build-up land on the other land uses under rapid urbanization accounted for the leading forces of LUCCs in the past decade. Accordingly, the urban sprawl was up to 1441.73 km2 (23.47%), with cropland, forest land, and water areas reduced by 570.77 km2 (4.38%), 526.05 km2 (1.76%), and 429.89 km2 (10.88%), respectively. (2) Based on the validated CA–Markov model, significant differences are found in future land use patterns under multiple scenarios, with the discrepancy magnified over time and driven by different orientations. (3) Through comprehensive comparisons and tradeoffs, the ES scenario mode seems optimal for the GBA in the next decades, which optimizes the balance between socio-economic development and ecological protection. These results serve as an early warning for future land problems and can be applied to land use management and policy formulation to promote the sustainable development of the GBA. [ABSTRACT FROM AUTHOR]

The traditional medium-voltage distribution network fault location method uses mainly the voltage and current measurements of the medium-voltage side, which results in problems such as high installation costs at the measuring points and complicated postoperation and maintenance work. Therefore, a fault location idea based on the distributed measurement of low-voltage side voltage is proposed in this paper. First, the characteristic voltage is adaptively selected according to the fault type. Second, the suspected fault section is determined by comparing the characteristic voltage amplitude of each measuring point. Third, the fault section is located using the section unit characteristic voltage drop defined for each suspected fault section. Finally, fault distance estimation is achieved based on the voltage difference matrix and characteristic voltage analysis. This method achieves accurate fault distance identification based on the distribution difference of the characteristic voltage of the low-voltage side under the fault state. This work provides a new economical and practical idea for determining the fault locations of distribution networks. The effectiveness of this method is evaluated by considering a 10 kV distribution network in Guangdong Province built in PSCAD/EMTDC. [ABSTRACT FROM AUTHOR]

In this paper, we focus on Guangdong province, which is a frontier area of Reform and Opening up, and analyze the variation of urban and rural temperature to detect the urbanization warming effect from 1951 to 2018, based on the daily temperature data of 85 weather stations. We classified the metrological stations into urban and rural stations according to the urbanization population size, population density and urban built-up area data. The combined methodology of mathematical statistics, trend analysis, urban/rural station comparison and spatial analysis was adopted to reveal the urbanization warming and its spatial–temporal heterogeneity. The results show that the warming process in Guangdong Province is very complex and has high temporal and spatial heterogeneity. From 1951 to 2018, the average temperature in the coldest month in Guangdong Province increased with the fastest (0.27 °C/10a) rate, and the annual average temperature increased slightly faster than the average temperature in the warmest month (0.15 °C/10a vs. 0.12 °C/10a). The comparative study on the temperature of urban and rural stations shows that the temperature increase rate of urban stations is faster than that of rural stations (0.30 °C/10a vs. 0.23 °C/10a), especially the average temperature in the coldest month, which is most significantly driven by urbanization, and the contribution rate of urbanization is about 24.09% in general. Affected by the background climate and the stages of urbanization, the warming effect of urbanization fluctuates obviously in different periods. Stronger urbanization effect can be witnessed during 1980–2000, when the urbanization developed into mid-level with highest rate. The spatial differentiation of urbanization warming effect is prominent. The temperature of urban stations in Eastern Guangdong increases most rapidly. The urbanization contribution rates to the coldest month average, annual average and the warmest month average temperature reach 33.86%, 25.70% and 17.64%, respectively, which are around 1.69, 1.50 and 1.19 times that of the Pearl River Delta. The average temperature of the warmest month in Western Guangdong shows a weak cooling effect. Multi-faceted, multi-level regulation of sustainable urbanization is the key to mitigating the warming caused by urbanization. [ABSTRACT FROM AUTHOR]

The genus KirinuaLi & Lin, 2021 belonging to the family Symphytognathidae was established based on the type species, Kirinua maguaiLi & Lin, 2021. A total of three cavedwelling Kirinua species were recorded from Guangxi, China. In this paper, another new troglobitic spider species from the limestone Jinlong Cave in southern China is described under the name Kirinua jinlong sp. nov. Detailed descriptions, illustrations, and diagnosis are given to this new species, as well as a distribution map for all known species of the genus Kirinua. [ABSTRACT FROM AUTHOR]

Recently, the economy in Guangdong province has ranked first in the country, maintaining a good growth momentum. The prediction of Gross Domestic Product (GDP) for Guangdong province is an important issue. Through predicting the GDP, it is possible to analyze whether the economy in Guangdong province can maintain high-quality growth. Hence, to accurately forecast the economy in Guangdong, this paper proposed an Elman neural network combining with wavelet function. The wavelet function not only stimulates the forecast ability of Elman neural network, but also improves the convergence speed of Elman neural network. Experimental results indicate that our model has good forecast ability of regional economy, and the forecast accuracy reach 0.971. In terms of forecast precision and errors, our model defeats the competitors. Moreover, our model gains advanced forecast results to both individual economic indicator and multiple economic indicators. This means that our model is independently of specific scenarios in regional economic forecast. We also find that the investment in education has a major positive impact on regional economic development in Guangdong province, and the both surges positive correlation. Experimental results also show that our model does not exhibit exponential training time with the augmenting of data volume. Consequently, we propose that our model is suitable for the prediction of large-scale datasets. Additionally, we demonstrate that using wavelet function gains more profits than using complex network architectures in forecast accuracy and training cost. Moreover, using wavelet function can simplify the designs of complexity network architectures, reducing the training parameter of neural networks. [ABSTRACT FROM AUTHOR]

Severe Typhoon Koinu passed south of Hong Kong on 8 and 9 October 2023, triggering the issuance of the Increasing Gale or Storm Signal No. 9, the second highest tropical cyclone (TC) warning signal in Hong Kong. Koinu was a difficult case for TC warning service due to its compact size and rather erratic movement over the coastal waters of Guangdong. To monitor Koinu's movement and wind structure, the Hong Kong Observatory utilized various observational platforms, including meteorological aircraft, ocean radar, and synthetic aperture radar on polar orbiting satellites. The paper presents major observations derived from these measurements. The aircraft probe and dropsonde data suggested boundary layer inflow, warm core structure, eyewall updraft, and high turbulence in the eyewall of the typhoon. The weather radar observations indicated the occurrence of a waterspout in the vicinity of the typhoon. Additionally, the study highlights the forecasting performance of the AI‐based Pangu‐Weather model, which could outperform the conventional global numerical weather prediction models in forecasting TC track in the region. The documentation of these observations aims to provide valuable references for weather forecasters and stimulate further research on forecasting this type of tropical cyclone. Key Points: Observations from meteorological aircraft, ocean radar, and synthetic aperture radar show the structure of Severe Typhoon KoinuWeather radar observations suggest the occurrence of a waterspout in the vicinity of KoinuAI‐based Pangu‐Weather model could outperform the conventional global numerical weather prediction models in forecasting Koinu's track [ABSTRACT FROM AUTHOR]

As development progresses over time and changes in the environment take place, carbon finance development has become a very interesting research topic for many scholars worldwide. This paper proposes a hybrid MCDM method that combines the distance solutions of the TOPSIS and VIKOR methods. The contribution of this paper combines TOPSIS and VIKOR, incorporating AISM models to obtain the development ranking of Chinese carbon finance pilot cities as related to the Chinese carbon finance development pilot provinces and cities. The conclusion notes that Guangdong and Beijing are the most preferred investment locations for carbon investors. In addition, technological innovation, financial sector development, and an active ETS market can effectively drive the level of local carbon finance. Additionally, the MCDM methodology in this paper provides new ideas in environmental and economic development assessment. [ABSTRACT FROM AUTHOR]

Change and persistence are often richly entangled facets of landscapes. While many studies use land use/land cover (depicted as polygons) to illustrate landscape evolution, this paper draws on approaches from landscape archaeology to investigate how lines and points can also be used to examine landscape morphologies. The study uses three distinct spatial elements: points (graves), lines (field boundaries), and polygons (land use) to represent landscape transformations and reflect time depth in the landscape. The paper aims to identify the most enduring landscape elements within the region and uncover the underlying mechanisms of persistence. It is suggested that the time depth exhibited in field boundaries surpasses that of land use in this case. Field boundaries provide a useful way to examine agricultural intensification, whereas land use is more sensitive to agricultural commercialization and urbanization. In addition, the Chinese Feng Shui funeral culture emerges as a stabilizing force that encourages landscape persistence. This cultural driver ensures the persistence of field patterns surrounding graves, making these fields the most ancient plots within the study area. In conclusion, representing the time depth of landscapes through linear features and points can serve as an important supplement to the study of landscape change based on land use. [ABSTRACT FROM AUTHOR]

Analysis of the spatial patterns and dynamics of tourism services and facilities is crucial for tourism and land use planning. However, most studies in the spatial analysis of tourism rely on the city- or regional-level data; limited research has used POI (point of interest) data to accurately uncover the spatial distribution of tourism, especially its interactive and coupling relationship with the local economy and population. Based on POI data, this paper, therefore, investigates the spatial patterns and driving forces of tourism services distribution and how tourism space is coupled with the local economy and population in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) of China. The results show the following: (1) Different categories of tourism services (catering, shopping, scenic spots, leisure, and sports) exhibit diverse spatial patterns and agglomerations, but they tend to align with the variables of economic level and population in a grid of 1 km2. (2) The spatial econometric models further reveal that population density, transportation, and hospitality facilities are positively correlated with the spatial distribution of tourism services, but GDP in a grid of 1 km2 shows a weak negative correlation with the POI of tourism services, which may be attributed to the incoordination between GDP and tourism in some areas. (3) The analysis of coupling degree further identifies the areas where tourism services have good interaction/coupling with the local GDP and population density, such that these areas can be viewed as hotspots suitable for tourism promotion. This paper thus offers meaningful policy implications by calling for an optimization of the coupling of tourism services with local social–economic factors in the GBA. [ABSTRACT FROM AUTHOR]

This paper investigates the economic development within the Guangdong-Hong Kong-Macao Greater Bay Area from two perspectives--spatial pattern and influencing factors--to promote coordinated development across the area. This paper employs Moran's I test and local Getis-Ord G statistic from spatial statistics. Furthermore, it constructs a hierarchical spatial econometric model to facilitate empirical investigation. It is found that the overall economic development of the Guangdong-Hong Kong-Macao Greater Bay Area exhibits a "mountain-shaped" spatial pattern of the high-level homogeneous regions with "high-high correlation" and the low-level homogeneous regions with "low-low correlation." The internal difference in economic density is moderate, with an obvious trend of decrease year by year. Economic density shows a significant spatial positive correlation, with the expansion of the scope of areas exhibiting "high-high correlation." The differences in economic density between hotspots and sub-hotspots have decreased, but the economic density of cold spots has failed to keep up with the development of other regions. The difference in factor input density among the influencing factors explains most of the differences in economic density among different regions. The results from the R&D capital investment coefficient indicate that in recent years, the effect of investments in urban scientific and technological innovation factors has been more extensive and uniform among the regions under its jurisdiction, but the spatial spillover effect of innovation factors at both layers is not significantly positive. Apart from the city's location within the Greater Bay Area, the relative location of the jurisdictions within the city equally influences the economic development configuration of the Greater Bay Area. Although economic density in regions adjacent to cities outside the Greater Bay Area is notably lower than in other regions, their growth rate and production efficiency remain on par with other regions. T-test and model results underscore the rapid development of the areas encircling the bay. The coefficient of location dummy variables in areas adjacent to cities in the Greater Bay Area varies among cities. At a particular factor input density, some cities have higher output efficiency in areas contiguous to cities in the Greater Bay Area. This study uniquely adopts low-level city jurisdictions and high-level cities to shape a two-tiered hierarchical dataset with nested geographic units. This innovative approach fully leverages insights from distinct layers, delving into spatial interdependence and interplay across layers. This paper aims to explore the spatial pattern and influencing factors steering economic development in the Guangdong-Hong Kong-Macao Greater Bay Area. In doing so, it aims to identify problems and present pertinent policy recommendations. [ABSTRACT FROM AUTHOR]

In the field of world heritage conservation, there has been broad consensus on carrying out heritage conservation research on the basis of spatial integration and interregional and international cooperation. However, there are still many deficiencies in the integration of culture with the environment, regional economic and social development, and the regional, holistic and multimodal conservation and utilization of cultural heritage sites. In China, the Dongjiang-Hanjiang River Basin is a representative area of substantial cultural and ecological value for both Guangdong Province and the whole country. This paper uses the morphological spatial pattern analysis and the minimum cumulative resistance model to integrate cultural ecology sources and establish a cross-regional and large-scale cultural ecology network system that includes 1 main corridor, 22 important corridors and 17 secondary corridors. In addition, based on identified cultural landscape nodes and cultural ecology services, the economy of the cultural ecology corridor could be developed with large-scale co-construction, co-governance and shared working mechanisms to overcome administrative limits and realize the conservation and utilization of multimodal and large-scale heritage sites. This approach has strong theoretical and practical significance for innovative methods in cultural ecology research, as well as for new content in the research of Lingnan culture, ecosystem restoration, and the economic and social development of towns and villages. This article supplements unilateral studies of regional culture and ecology and demonstrates an in-depth application of cultural ecology theory. [ABSTRACT FROM AUTHOR]

The spatial-temporal mismatch of water resources and socio-economic development in rapidly urbanized regions has been the focus of water resource management, and is one of the main limitations to sustainable development goals (SDGs). Guangdong Province is represented by a highly developed economy and society, and has been undergoing disproportionately rapid population growth during the past two decades. The uneven distribution and spatial mismatch of water resources have aggravated the contradictions between water supply demand. In this paper, we evaluate the matching degree of water resources and social economic elements, detect the spatial-temporal changing pattern of the matching degree, and reveal the changing mechanism using the combined methods of the Thiel index, the space–time Gini coefficient, and the Lorenz curve. The results show that (1) the temporal matching is relatively balanced and reasonable, while the spatial mismatch is prominent and deteriorating constantly, especially the connection between the amount of water and GDP; (2) the water volume pressure is mainly concentrated in the Peral River Delta and eastern and western Guangdong, while water consumption stress is relatively lower in northeastern Guangdong; and (3) the water volume inequality is dominated by an intercity difference and is primarily caused by regional differences. Based on the results, policy implications, such as the implementation of integrated water resource management plans, investment in the development of alternative water sources, as well as enhanced public education and the establishment of a water saving society, have been provided to alleviate the mismatch issue between water elements and socio-economic parameters, and to push the realization of water-related SDGs. [ABSTRACT FROM AUTHOR]

As a unit hydrograph method widely used in engineering practice, the synthetic unit hydrograph of Guangdong is obtained from the analysis and synthesis of rain and flood data before 1983, which reflects the production-confluence relationship before urbanization in Guangdong Province. However, there are few studies on the evaluation and modification of its applicability in urbanized areas. Taking Jing-tian Watershed of Shenzhen City, Guangdong Province as an example, based on the rainstorm and flood records of Jingtian Hydrology Station from 2011 to 2019, this paper evaluates the applicability of the comprehensive unit line in Guangdong Province by using evaluation indexes such as Nash efficiency coefficient, identification index and correlation coefficient, and conducts a sensitivity analysis of important parameters by Spearman rank correlation coefficient method. Based on Latin hypercube sampling method and constrained least square method, the comprehensive unit line method of Guangdong Province is modified. The results show that the Jingtian Basin has experienced rapid urban expansion since the 1980s, and the proportion of impervious surface has exceeded 90%. The comprehensive unit line method in Guangdong Province has obvious shortcomings in describing the storm-flood process in this basin. The two schemes proposed in this paper can improve the simulation effect of the model by determining important parameters and modifying the unit line. Among them, the cross-validation parameter optimization method based on grid search and the unit line correction method based on constrained least square method proposed for small samples show a good simulation performance, and the indexes such as Nash efficiency coefficient, identification index and correlation coefficient are significantly improved, which better reflects the characteristics of production and convergence in Jingtian Basin. Compared with the recommended unit line of the integrated unit line method in Guangdong Province, the modified unit hydrograph method shows the characteristics of larger peak discharge, earlier peak time and smaller total duration, which is more in line with the law of production and confluence of urbanization. [ABSTRACT FROM AUTHOR]

Climate change is a global challenge with multiple far-reaching consequences, including the intensification and increased frequency of many extreme weather events. In response to this pressing issue, we present ClimaMeter, a platform designed to assess and contextualise extreme weather events relative to climate change. The platform offers near real-time insights into the dynamics of extreme events, serving as a resource for researchers, policymakers, and being a science dissemination tool for the general public. ClimaMeter currently analyses heatwaves, cold spells, heavy precipitation and windstorms. This paper elucidates the methodology, data sources, and analytical techniques on which ClimaMeter relies, providing a comprehensive overview of its scientific foundation. To illustrate Climameter, we provide four examples, the December 2022 North American Winter Storm, the August 2023 Guangdong – Hong Kong Flood, the late 2023 French Heatwave and the July 2023 windstorm Poly. They underscore the role of ClimaMeter in fostering a deeper understanding of the complex interactions between climate change and extreme weather, with the hope of ultimately contributing to informed decision-making and climate resilience. [ABSTRACT FROM AUTHOR]

The combined effect of tourism economic growth has presented an important catalytic and driving role in modern urban development, especially in China's urban regeneration and industrial restructuring. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is a new attempt by China's government to comprehensively promote a new pattern of economic opening for metropolitan areas, and tourism development has assumed the role of a window to showcase the quality of the GBA's cities to the world. How to promote the coordinated development of tourism and cities is particularly important in shaping new industries and enhancing the quality of urban development in the GBA. This paper constructs an evaluation index system and uses the improved entropy-weighted Topsis model to calculate the Coordinated Level between Tourism and Urban Development (TUDCL) and applies it to analyze the impact of tourism on promoting urban development in the GBA. The study finds that the TUDCL changes steadily from 2000 to 2019 and currently remains at a medium level, with large differences between cities of different levels, and that there is more room to improve the TUDCL of peripheral cities in the GBA such as Huizhou, Jiangmen, and Zhaoqing. When the tourism industry grows to a certain size, it can in turn lead to the synergistic growth of other industries in the city. Different cities need to formulate appropriate optimization policies according to their own industry type, tourism resource endowment, economic openness, and location conditions. This study proposes a scientific and effective evaluation index system to identify the level of coordination between tourism and urban development in the GBA and distils the contribution of different factors and the time sequence of their influence in stages, which is of positive significance in understanding the synergistic relationship between tourism and urban development and provides theoretical reference for planning a quality living circle suitable for living, working, and traveling in the GBA. [ABSTRACT FROM AUTHOR]

Scientific analysis of regional agricultural carbon emission prediction models and empirical studies are of great practical significance to the realization of low-carbon agriculture, which can help revitalize and build up ecological and beautiful countryside in China. This paper takes agriculture in Guangdong Province, China, as the research object, and uses the extended STIPAT model to construct an indicator system for the factors influencing agricultural carbon emissions in Guangdong. Based on this system, a combined Isomap–ACO–ET prediction model combing the isometric mapping algorithm (Isomap), ant colony algorithm (ACO) and extreme random tree algorithm (ET) was used to predict agriculture carbon emissions in Guangdong Province under five scenarios. Effective predictions can be made for agricultural carbon emissions in Guangdong Province, which are expected to fluctuate between 11,142,200 tons and 11,386,000 tons in 2030. And compared with other machine learning and neural network models, the Isomap–ACO–ET model has a better prediction performance with an MSE of 0.00018 and an accuracy of 98.7%. To develop low-carbon agriculture in Guangdong Province, we should improve farming methods, reduce the intensity of agrochemical application, strengthen the development and promotion of agricultural energy-saving and emission reduction technologies and low-carbon energy sources, reduce the intensity of carbon emissions from agricultural energy consumption, optimize the agricultural planting structure, and develop green agricultural products and agro-ecological tourism according to local conditions. This will promote the development of agriculture in Guangdong Province in a green and sustainable direction. [ABSTRACT FROM AUTHOR]

It is essential to predict carbon prices precisely in order to reduce CO2 emissions and mitigate global warming. As a solution to the limitations of a single machine learning model that has insufficient forecasting capability in the carbon price prediction problem, a carbon price prediction model (GWO–XGBOOST–CEEMDAN) based on the combination of grey wolf optimizer (GWO), extreme gradient boosting (XGBOOST), and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is put forward in this paper. First, a random forest (RF) method is employed to screen the primary carbon price indicators and determine the main influencing factors. Second, the GWO–XGBOOST model is established, and the GWO algorithm is utilized to optimize the XGBOOST model parameters. Finally, the residual series of the GWO–XGBOOST model are decomposed and corrected using the CEEMDAN method to produce the GWO–XGBOOST–CEEMDAN model. Three carbon emission trading markets, Guangdong, Hubei, and Fujian, were experimentally predicted to verify the model's validity. Based on the experimental results, it has been demonstrated that the proposed hybrid model has enhanced prediction precision compared to the comparison model, providing an effective experimental method for the prediction of future carbon prices. [ABSTRACT FROM AUTHOR]

In the face of an increasingly complex and unstable external development environment, enhancing economic resilience has become a key task in the construction of the Guangdong-Hong Kong-Macao Greater Bay Area. This paper analyzes the changes in the economic resilience of the Guangdong-Hong Kong- Macao Greater Bay Area and its constituent cities after the 2008 global financial crisis by virtue of the regional economic resilience assessment method proposed by Martin et al. It constructs an economic connection network for the Guangdong-Hong Kong- Macao Greater Bay Area using the data from corporate headquarters and branches of A-share listed companies to analyze its impact on the economic resilience of the Area. The study reveals the three following conclusions. Firstly, the economic resilience of the Guangdong-Hong Kong-Macao Greater Bay Area generally outperforms the national average level, seeing a rapid boost over the recent years and exceeding the level witnessed during the 2008 financial crisis. However, there are marked disparities in the economic resilience of various cities within the Greater Bay Area, with Shenzhen, Guangzhou, and Dongguan emerging as the most robust in this regard. Secondly, the economic connection network has a positive impact on the economic resilience of the cities in the Guangdong-Hong Kong-Macao Greater Bay Area. Specifically, there is a positive correlation between a city's economic resilience and its centrality in the economic connection network. Such centrality exerts a positive spillover effect on the economic resilience of surrounding cities. Thirdly, from the perspective of industry-specific networks, circulation and service industry networks are more conducive to improving the economic resilience of a city. Given the significant role of the economic connection network in shaping regional and urban economic resilience, it is imperative for the Guangdong-Hong Kong-Macao Greater Bay Area to prioritize ensuring economic development security and enhancing economic resilience, promote the development of the economic connection network, and enhance the network centrality of its constituent cities. This can improve the economic resilience of itself and its constituent cities in an effective manner. [ABSTRACT FROM AUTHOR]

The Guangdong-Hong Kong-Macao Greater Bay Area comprises a regional economy encompassing nine cities located in the Pearl River Delta region, in addition to the two special administrative regions of Hong Kong and Macao. The process of regional economic integration within the Guangdong-Hong Kong- Macao Greater Bay Area traces its origins back to the commencement of China's reform and opening up policies in 1978. It evolves from an initially spontaneous collaborative model, where front-end commercial activities are paired with rear-end manufacturing facilities, to a deliberate form of collaboration underpinned by institutional interventions. This paper examines the fundamental characteristics of the regional economic integration within the Guangdong-Hong Kong-Macao Greater Bay Area. It specifically delves into an extensive analysis of the construction and development of this area. The discussion encompasses four significant theoretical and practical facets that shape the progress of the Greater Bay Area's construction. These aspects include the synchronization of market integration within the Greater Bay Area, the harmonization of institutional frameworks, the convergence of the eastern and western sections of the Pearl River Estuary, and the amalgamation of regional innovations. Furthermore, the paper engages in an exploration of strategies designed to propel the advancement of the Greater Bay Area's development. These strategies encompass collaborative initiatives, such as the joint development of the Shenzhen-Hong Kong adjacent region, the cooperative advancement of Hengqin Island by Zhuhai and Macao, the approach to integrating adjacent areas, and the interlock strategy aiming to connect the two pivotal urban centers of Guangzhou and Shenzhen. [ABSTRACT FROM AUTHOR]

The Guangdong-Hong Kong-Macao Greater Bay Area (the Greater Bay Area, the GBA) aims to facilitate in-depth cooperation among the Guangdong, Hong Kong, and Macao regions to create a world-class bay area-based urban agglomeration. This endeavor seeks to guide China's economy toward high-quality development and comprehensive opening-up. This paper examines the challenges and obstacles faced by Guangdong, Hong Kong, and Macao regarding regional coordinated development, thus putting forward the following standpoints. It proposes enhancing infrastructure interconnectivity to establish the GBA 1-hour Express Traffic Circle, thereby driving the construction of a world-class international shipping and logistics hub. Furthermore, the paper advocates for establishing an industrial collaborative development system in the GBA, jointly creating a pilot zone for industrial transformation and upgrading, and further advancing market integration. Creating an international innovation corridor and innovation center for science and technology (S&T) industry is also essential. This initiative would center around critical sectors, improving S&T innovation chain, and building a talent cooperation demonstration zone. The paper also emphasizes the establishment of a transport and logistics hub for the Belt and Road Initiative, along with the joint development of a cultural, economic, and trade exchange platform under the "Belt and Road" framework. Leveraging the comparative advantages of the three regions, the paper underscores the importance of innovative collaboration models, fostering a mutually beneficial and complementary mechanism for synergistic development. These approaches aim to realize the integrated and innovative development of the GBA. [ABSTRACT FROM AUTHOR]

This paper constructs a novel stress measurement system of carbon market from the perspective of trading, emission reduction, and external shocks and simulates the stress indices of national and pilot carbon markets of China with the methods of functional data analysis and criteria importance through intercriteria correlation. It concludes that the overall carbon market stress is in the shape of "W" and still at a high level, with frequent fluctuations and an upward trend. In addition, the stress of Hubei, Beijing, and Shanghai carbon market fluctuates and rises, while the stress of Guangdong carbon market decreases. Moreover, carbon market stress mainly comes from trading and emission reduction. Furthermore, stress fluctuation of Guangdong and Beijing carbon market is more prone to "big waves," indicating that the two markets are sensitive to big events. Finally, the pilot carbon markets are divided into stress-driven and stress-release market and the type of which keeps change in different period. [ABSTRACT FROM AUTHOR]

With the development of science and technology, the biometric market is developing rapidly. This paper analyzes the problems of the general rules of biometric technology, including the difficulty of information subjects participating in rule-making, the lack of provisions of general rules, and insufficient legal regulation. Drawing on the provisions of personal information related to biometrics in Europe and the United States and the protection of personal information related to biometrics in China, the paper suggests that biometric information protection should be improved and connected with the existing laws. The results show that the top three provinces in the number of cases based on biometric technology are Guangdong Province, Beijing Municipality and Jiangsu Province, with a total of 102 cases, accounting for 52.41% of the total number of cases, among which Guangdong Province tops the list with 75 cases in 10 years, far ahead of other provinces, indicating that the legal regulation of biometric technology is a pressing need. This paper explores a legal regulation path of biometric technology application economic law suitable for China's socio-economic development, intending to realize a healthy, safe, green digital society. [ABSTRACT FROM AUTHOR]

As China's economy transitions from a stage of high-speed growth to a stage of high-quality development, the concept of low-carbon and green economic development has gained increasing popularity. Mastering the regional differences and changing patterns of low-carbon economy and economic growth quality is an important prerequisite for further promoting low-carbon economic development and improving the quality of economic growth. Taking the data of 21 prefecture-level cities in Guangdong Province from 2008 to 2019 as examples, we calculated the low-carbon economy and the quality index of economic growth, and analyzed the convergences between them through coefficient of variation analysis and a panel data convergence model with fixed effects. The results showed that: First, the convergence of low-carbon economy was better than the convergence of economic growth quality. Second, the low-carbon economy of Guangdong Province had σ convergence, and the imbalance between regions of low-carbon economy was alleviated, but the quality of economic growth of Guangdong Province did not have σ convergence. Third, there was absolute and conditional β convergence in the quality of low-carbon economy and economic growth in Guangdong Province. Fourth, the convergence rate of low-carbon economy in Guangdong Province showed "club difference"; the same was true of σ convergence, absolute β convergence, conditional β convergence, and dimensional convergence of economic growth quality in various regions of Guangdong Province. The exploration conducted in this article was conducive to better grasping the changing patterns of low-carbon economy and economic growth quality, enriching relevant research. The conclusions of this paper can provide decision-making basis for China to formulate urban and regional economic policies, achieve high-quality economic development, and "double carbon goal". [ABSTRACT FROM AUTHOR]

As China has become the largest user of industrial robots, the need to understand how workers perceive robot-human substitution and how their perceptions influence their job behaviors is becoming increasingly crucial. This paper examined whether workers' fear of being replaced by robots (FRR) is correlated with one aspect of job behavior: turnover intention, which refers to the extent to which an individual intends to change their job within a specific time period. Using a dataset covering 1512 manufacturing workers in Guangdong province of China, we found that workers who fear losing their jobs to robots report significantly higher turnover intention. We also found that the positive effect of FRR on turnover intention increased when robots were already utilised in the workplace. This effect was also found to be increase when workers perceived that their wages did not increase with the rise in productivity due to robotisation. Based on these findings, we provide practical recommendations to organizations on effectively addressing the turnover intention arising from the FRR. [ABSTRACT FROM AUTHOR]

Macao's academic book publishing industry has a rich history and has grown significantly over the past two decades. This study employs a semi‐structured in‐depth interview to evaluate the current and prospective state of Macao's academic book publishing industry. The SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis and the PEST (Political, Economic, Social, and Technological) analysis are used in this study. The strengths of Macao's academic book publishing industry include that requesting an ISBN in Macao is easy and quick under the principle of 'One Country, Two Systems' and financial support from the Macao SAR government. However, the industry faces several weaknesses, including an underdeveloped cultural industry, a small seller market and a talent shortage, and less copyright output. Opportunities for the industry exist through constructing a Culture‐based Bay Area in the Guangdong–Hong Kong–Macao Greater Bay Area and developing an international hub for digital trade in the Guangdong–Macao In‐Depth Cooperation Zone–Hengqin. However, Macao's academic book publishing industry is threatened by emerging Internet technologies, such as augmented reality, the metaverse, and ChatGPT. This paper also proposes strategies for future practice, such as taking the initiative to encourage a group of top‐tier publishers to establish branches in Macao and improve publications' cultural elements. The findings of this study provide valuable insights into the strategic management of Macao's academic book publishing industry and will be of interest to publishers, academic researchers, and policymakers. [ABSTRACT FROM AUTHOR]

Transmitting traditional music for sustainability has been a common theme in global music education. Recently, the school systems of Hong Kong and Guangdong have been encouraged by governmental authorities to teach Cantonese opera aiming at enhancing the sustainability of the genre and promote a Chinese cultural identity within students. This paper details a survey of school music teachers working in Hong Kong and Guangdong examining the current state of Cantonese opera teaching in the schools of both regions and investigate how it is affected by teacher variables including their interest in Chinese opera, the confidence in teaching the subject, and their perceptions of their Chinese cultural identities. A total of 1,974 valid questionnaires were received and examined. Descriptive and inferential statistics including MANOVA and chi-square tests were used to analyze the data. Findings reveal that Cantonese opera teaching is limited in both regions. While teachers are modestly interested, confident, and knowledgeable about teaching the genre, there is a significant relationship between the music backgrounds of teachers and their interest in Cantonese opera. The article discusses the findings within the context of a historical predominance of Western music within music education curricula and wider societies. Implications for policy makers are proposed. [ABSTRACT FROM AUTHOR]

This paper studies when and under what conditions the actions undertaken by the power plants involved in China's emission trading scheme (ETS) pilot became cost effective. Based on unique plant-level panel data and the difference-in-differences strategy, we identify that an insignificant initial reduction in cost efficiency occurred at the announcement stage for power plants in the pilot provinces; however, the cost efficiency of the pilot plants increased significantly following formal policy implementation. Additionally, the by-stage treatment effects differed across the pilot provinces due to localized market and non-market variations. Localized conditions of higher marketization, stricter policy enforcement, and lower carbon dependence enhanced this positive effect. The synthetic control results confirmed this variation in the policy effects. The carbon trading pilots resulted in improved efficiency in power plants in Shanghai, Guangdong, and Tianjin during the period 2013--2017, with an associated total cost saving of approximately 29.75 million RMB. To enhance the efficacy of the ETS policy, our findings suggest that the design of the policy should consider localized external factors. [ABSTRACT FROM AUTHOR]

In China, Hebei Province and Guangdong Province have many pollution-intensive industries; yet Hebei suffers more serious atmospheric or environmental pollution than Guangdong. To explain the phenomenon, this paper chooses the statistical data of 286 prefecture-level cities in the Chinese mainland from 2005 to 2018 and empirically tests the spatial effect and threshold characteristics of atmospheric self-purification capacity on environmental pollution by using the spatial autoregression model (SAR), spatial Durbin model (SDM), and panel threshold model. As evinced, the local atmospheric self-purification capacity has a significant inhibitory effect on environmental pollution, and the absolute value of the direct effect coefficient reaches 1.337. Simultaneously, atmospheric self-purification capacity has a threshold effect on environmental pollution. The threshold value of environmental regulation as a threshold variable is 11.6349. This means that when the level of environmental regulation proves higher than 11.6349, it attenuates the inhibitory effect of the atmospheric self-purification capacity on environmental pollution. As the heterogeneity research unveils, atmospheric self-purification capacities in various regions form a significant correlation with environmental pollution. This paper suggests that local governments should strengthen environmental regulation and construct an inter-regional joint prevention and control system for atmospheric-pollution governance to enhance the atmospheric self-purification capacity. [ABSTRACT FROM AUTHOR]

The study of the architectural heritage of the Chinese diaspora has an important role and significance in China's historical and cultural background in the preservation of cultural data, the restoration of images, and in the analysis of human social and ideological conditions. The images from the architectural heritage of the Chinese diaspora usually include frescos, decorative patterns, chandelier base patterns, various architectural styles and other major types of architecture. Images of the architectural heritage of the Chinese diaspora in Jiangmen City, Guangdong Province, China are the research object of this study. A total of 5073 images of diaspora Chinese buildings in 64 villages and 16 towns were collected. In view of the fact that different types of image vary greatly in features while there are only small differences among the features of the same type of image, this study uses the depth learning method to design the Convolutional Neural Network Attention Retrieval Framework (CNNAR Framework). This approach can be divided into two stages. In the first stage, the transfer learning method is used to classify the image in question by transferring the trained parameters of the Paris500K datasets image source network to the target network for training, and thus the classified image is obtained. The advantage of this method is that it narrows the retrieval range of the target image. In the second stage, the fusion attention mechanism is used to extract the features of the images that have been classified, and the distance between similar images of the same type is reduced by loss of contrast. When we retrieve images, we can use the features extracted in the second stage to measure the similarities among them and return the retrieval results. The results show that the classification accuracy of the proposed method reaches 98.3% in the heritage image datasets of the JMI Chinese diaspora architectures. The mean Average Precision (mAP) of the proposed algorithm can reach 76.6%, which is better than several mainstream model algorithms. At the same time, the image results retrieved by the algorithm in this paper are very similar to those of the query image. In addition, the CNNAR retrieval framework proposed in this paper achieves accuracies of 71.8% and 72.5% on the public data sets Paris500K and Corel5K, respectively, which can be greatly generalized and can, therefore, also be effectively applied to other topics datasets. The JMI architectural heritage image database constructed in this study, which is rich in cultural connotations of diaspora Chinese homeland life, can provide strong and reliable data support for the follow-up study of the zeitgeist of the culture reflected in architecture and the integration of Chinese and Western aesthetics. At the same time, through the rapid identification, classification, and retrieval of precious architectural images stored in the database, similar target images can be retrieved reasonably and accurately; then, accurate techniques can be provided to restore old and damaged products of an architectural heritage. [ABSTRACT FROM AUTHOR]

Scientific analysis of regional agricultural carbon emission prediction models and empirical studies are of great practical significance to the realization of low-carbon agriculture, which can help revitalize and build up ecological and beautiful countryside in China. This paper takes agriculture in Guangdong Province, China, as the research object, and uses the extended STIPAT model to construct an indicator system for the factors influencing agricultural carbon emissions in Guangdong. Based on this system, a combined Isomap–ACO–ET prediction model combing the isometric mapping algorithm (Isomap), ant colony algorithm (ACO) and extreme random tree algorithm (ET) was used to predict agriculture carbon emissions in Guangdong Province under five scenarios. Effective predictions can be made for agricultural carbon emissions in Guangdong Province, which are expected to fluctuate between 11,142,200 tons and 11,386,000 tons in 2030. And compared with other machine learning and neural network models, the Isomap–ACO–ET model has a better prediction performance with an MSE of 0.00018 and an accuracy of 98.7%. To develop low-carbon agriculture in Guangdong Province, we should improve farming methods, reduce the intensity of agrochemical application, strengthen the development and promotion of agricultural energy-saving and emission reduction technologies and low-carbon energy sources, reduce the intensity of carbon emissions from agricultural energy consumption, optimize the agricultural planting structure, and develop green agricultural products and agro-ecological tourism according to local conditions. This will promote the development of agriculture in Guangdong Province in a green and sustainable direction. [ABSTRACT FROM AUTHOR]

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The ICT service industry has become a burgeoning industry at a high and stable speed. Their equitable distribution can improve national and global positive peace. This paper aimed to verify the characteristics of spatio-temporal evolution and its influencing factors in the ICT service industry. Based on the data from 31 Provinces in China from 2015 to 2019, this paper uses location quotient, spatial autocorrelation methods and spatial econometric analysis to explore the development characteristics, evolution and influencing factors of the ICT service industry, respectively. The main results are shown as follows: (1) China's ICT service industry is mainly concentrated in Beijing, Shanghai, Zhejiang, Tibet, and Guangdong, with a trend of specialisation development. They are not only distributed in cities with relatively superior overall development but also those with superior industrial and development carrier elements. Technological relevance, aggregation, and political difference might have an impact on promoting the emergence and development of these industries. (2) ICT service industry is characterised by stable and highly concentrated development. Numbers between three to five significant provinces and types with high-high (HH) and high-low (HL) clusters of local spatio-temporal association kept stable in the period. The HH was in eastern coastal areas, including Zhejiang, Shanghai, Jiangsu, and Shandong, and the HL was in Guangdong in 2015. There is a definite spatial correlation in spatial distribution with constant strengthening. (3) TUR, NDN, MIAT and the area were shown to have a significant role in promoting the ICT service industry, while NW, GDP and ICT Employment were shown to have a significant negative impact on this industry. Correspondingly, two strategies were put forward here: (1) accelerating the inter-provincial networking development of the ICT service industry, and (2) strengthening government policy guidance for the ICT service industry. These outcomes can not only provide a scientific basis and theoretical support for the distribution of strategies and resources for these industries at the theoretical level but also improve resource integration from the national perspective and the efficiency of resource use at the practical level. [ABSTRACT FROM AUTHOR]

Innovation platforms can be useful for promoting the diversification of regional industrial paths. Until recently, the literature had depicted such platforms primarily as a tool for enabling local knowledge recombination – and not for anchoring non-local knowledge. In many regions, however, 'smart specialisation strategies' for modernising and transforming industrial structures are difficult to implement without transplantation of non-local knowledge. This paper explores innovation platforms as a tool for anchoring non-local knowledge. We elaborate on recent Chinese experiences by studying diversification-oriented regional innovation policy in Guangdong province. We employ an embedded single-case study design, involving a regionally typical diversification strategy, which we substantiate by tracing platform development with two non-local actors, a university and a technology firm. The paper reveals that non-local actors can play an important role in unlocking regional industrial development potential, especially if platforms enable these actors to relate to local industry by performing desired intermediary functions. [ABSTRACT FROM AUTHOR]

Purpose: The impact of a mixture of positive and negative media coverage on long-run hotel survival remains unknown. This paper aims to investigate how the mixed positive and negative media coverage, namely, inconsistent media coverage, influences long-run hotel survival. Design/methodology/approach: A yearly panel data set covering 792 news-reported hotels in Guangdong province of China, over the period 2010–2020, is analyzed using an inconsistency analysis framework consisting of text mining and survival analysis. The estimates of exponential models on the same observations and Cox estimates on alternative observations are used for robustness checks. Findings: The inconsistency calculation method proposed here can measure the controversy degree well. There exists a U-shaped relationship between inconsistency of media coverage and hotel longevity, and hotel survival is significantly reduced only when the degree of inconsistency is within the range of 17.8%–53.6%. The U-shaped relationship is moderated by negative hotel image and by online media coverage on hotel operation strategy topics. Practical implications: This study provides suggestions for hotel managers to use media coverage inconsistency to increase long-run hotel survival in the digital era. Originality/value: To the best of the authors' knowledge, this paper is one of the first to investigate long-run hotel survival factors from the perspective of media coverage inconsistency. It also proposes a method to calculate the degree of media coverage controversy, which helps to quantify the relationship between the degree of inconsistency and hotel survival. [ABSTRACT FROM AUTHOR]

Since 2020, China has been dedicated to the goal of "carbon peak and carbon neutrality" in the international community, demonstrating its commitment to energy conservation and emissions control. In 2021, in response to the guidance of the State Council, all provinces in China included the creation of a low-carbon economic system as one of their key development goals. This paper aims at investigating the low-carbon economic development efficiency and the redundancy of inefficient areas of Guangdong Province by using the three-stage DEA-Malmquist index model. Panel data of 21 cities from 2011 to 2020 in Guangdong Province were selected. Results revealed that the low-carbon economic development efficiency in the whole province rises, but the growth rate has slowed down in the past three years. Pearl River Delta area is better-developed in low-carbon economy than others. It is recommended to improve the efficiency of scale, make use of environmental advantages and develop energy-saving and emission reduction technologies. [ABSTRACT FROM AUTHOR]

The Guangdong‐Hong Kong‐Macao Greater Bay Area (GBA), a cluster of world‐class cities, is undergoing rapid urbanization. However, the heterogeneity of the urban thermal environment resulting from the diversity of urban forms is not yet fully understood. This paper assesses the heterogeneity of the urban heat island (UHI) effect in the GBA using the coupled Weather Research and Forecasting (WRF) model/multi‐layer urban canopy and building energy model (BEP/BEM), with high‐resolution local climate zone (LCZ) map as urban land use/land cover data. The average UHI intensity is found to peak at 1.8 ± 0.4°C in the evening, when the average UHI intensity of LCZ 2 can reach a maximum of 2.4 ± 0.58°C. Properly setting air‐conditioning temperatures can effectively prevent the enhancement of the UHI phenomenon at night by the anthropogenic heat (AH) released from air‐conditioning. The UHI‐induced local circulations and enhanced surface roughness inhibit the penetration of sea breezes inland, and surface wind speed decreases in all LCZs, with a maximum change of more than 0.8 m s−1. However, the increased thermal difference between land and sea leads to enhanced sea breezes offshore, especially in the Pearl River estuary. In addition, a series of sensitivity experiments have been conducted in this paper on initial and boundary conditions, building drag coefficients and urban fractions, which paves the way for further analyzing urban climate in GBA using WRF model and LCZs. Plain Language Summary: With the rapid urbanization of the world, the demand for functional buildings has increased. Along with the diversification of urban forms, the differences in the thermal environment within cities are becoming more and more significant. This study therefore provides an in‐depth study of the urban thermal environment in the Guangdong‐Hong Kong‐Macao Greater Bay Area (GBA) based on numerical simulation and local climate zones (LCZs). It was found that the urban heat island (UHI) intensity in different urban forms has obvious differences, and may vary by 1°C. However, the daily variation trends are similar, all showing a stronger UHI intensity at night than during the day, and reasonable setting of air‐conditioning temperature can effectively mitigate the UHI intensity at night. The UHI‐induced local circulations and enhanced surface roughness weaken the surface wind speed and inhibit the penetration of sea breeze inland, but enhance the sea breezes offshore, especially in the Pearl River estuary. This study provides references for urban planning and future sustainable development, especially for areas located along the coast that are undergoing rapid development. In addition, a series of sensitivity experiments on initial and boundary conditions, building drag coefficients and urban fractions provide useful suggestions for numerical model configuration in the GBA. Key Points: Tests of initial and boundary conditions, building drag coefficient and urban fractions provide recommendations for Weather Research and Forecasting configurationUrban heat island (UHI) varies between different local climate zones, but all peak in evening, and proper setting of air‐conditioning temperatures can mitigate UHI at nightUrbanization weakens surface wind speeds and inhibits the penetration of sea breezes inland, but strengthens the sea breezes offshore [ABSTRACT FROM AUTHOR]

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The variation in the urban spatial structure (USS) has profound impacts on carbon emissions. Studying the relationship between the two can provide guidance for carbon neutrality strategies and the construction of low-carbon cities in China. However, there is currently a lack of comparative research on the different regions within a province. In this paper, the spatiotemporal evolution of the USS and carbon emissions, at five-year intervals from 2000 to 2020, is investigated in 21 prefecture-level cities in Guangdong Province, China, and the overall relationship of the USS to carbon emissions and their spatiotemporal variations are analyzed by using a two-way fixed-effects model and a geographically and temporally weighted regression model, respectively. The results show that, first, over the past twenty years, the scale of cities has continued to expand, with increasing continuity and aggregation in the built-up areas, while the complexity and fragmentation of their shapes have gradually decreased. Second, the gap in carbon emissions between the Pearl River Delta and other regions in Guangdong shows a trend of first decreasing and then increasing, with high values concentrated in the Pearl River Delta region and the city of Shantou in the east. Third, compared to socio-economic factors, the USS has a more direct and pronounced impact on carbon emissions. Urban expansion and the increased complexity of land patches promote carbon emissions, whereas improving urban spatial continuity and compactness can reduce carbon emissions. Fourth, the dominant spatial structure indicators of carbon emissions differ among the regions of eastern, western, and northern Guangdong and the Pearl River Delta. This study proposes spatial optimization strategies for the low-carbon development of cities in Guangdong Province, providing a new perspective for integrating urban layout and emission reduction policies. [ABSTRACT FROM AUTHOR]