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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 special issue sets out to revisit major bilingual and multilingual education policy and planning issues in key cities across the dynamic Greater Bay Area (GBA) of China (including Guangdong, Hong Kong, and Macau), as informed by the emerging insights from translanguaging theory (Li in Appl Linguist 39(1):9–30, 2018). Specifically, contributions are invited from the GBA and beyond to trace the milestone developments of relevant language policy and planning (LPP) initiatives featuring governmental policies on the language of instruction (e.g., English as Medium of Instruction, Chinese as Medium of Instruction) and the daily use of multiple linguistic resources or repertoires (e.g., language learner's L1 or mother tongue) in foreign/second language classrooms and/or in content-based classroom instruction. As such, major papers in the special issue not only set out to provide historical and analytical reviews of these related LPP issues across Hong Kong, Macau, and Guangdong Province but also reflect upon the language use and behaviors of the residents, showcasing their identity and attitudes and ideological stance toward the multiple languages that are being taught or used in daily life. Toward the end, we outline our research agendas for future endeavors in broader domains in the GBA and beyond through the translanguaging analytical tools. Overall, our position is that the GBA presents itself as an evolving, complex, and superdiverse zone of "Translanguaging Spaces" within which key LPP issues may need to be reconceptualized and implemented in such a way so as to fully reflect the dynamic and fluid multilingual, multicultural, and multisemiotic lived reality of the residents in this megapolis region. [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]

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]

In order to improve the analysis effect of traditional arts and crafts, this paper analyzes traditional arts and crafts combined with digital technology, builds an intelligent analysis system to improve the digital processing effect of traditional arts and crafts, and takes the Guangdong-Hong Kong-Macao Greater Bay Area as an example to verify the system effect. In order to improve the accuracy of subsequent image alignment and defect detection, this paper compares the effects of the pixel-level edge detection algorithm and the subpixel-level edge detection algorithm and finally selects the subpixel-based edge detection algorithm to extract the edge of the image. In addition, this paper compares the traditional defect detection algorithm through research and experiment and proposes an improved image phase difference method according to the actual situation. The experimental research shows that the traditional arts and crafts intelligent analysis system based on digital technology proposed in this paper has a very good effect. At the same time, with the support of this system, the intelligent analysis of traditional arts and crafts in the Guangdong-Hong Kong-Macao Greater Bay Area can be carried out efficiently. [ABSTRACT FROM AUTHOR]

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Synergistic development is the only way which must be passed and a key point to achieve high-quality economic development. This paper regards regional synergetic development as a composite system, builds up the evaluation indicator system, and calculates the level of economic synergetic development of Guangdong-Hong Kong-Macao Greater Bay Area Urban Agglomeration, by using the collaborative degree model of composite system. The results show that each subsystem of the composite system has a high degree of order from 2007 to 2019, but compared with Beijing-Tianjin-Hebei urban agglomeration and Yangtze River Delta urban agglomeration, the level of economic collaborative development of Guangdong-Hong Kong-Macao Greater Bay Area urban agglomeration in 2008–2019 is relatively low and has large spatial differences. The main reason is that under the background of "one country, two systems" policy, the institutional differences between Guangdong, Hong Kong, and Macao have not been effectively linked up and synergetic, Greater Bay Area urban agglomeration has not yet formed an organic whole, and the synergy effect of mutual support and promotion is relatively weak. Based on this, we should seize the great historical opportunity of the construction of Guangdong-Hong Kong-Macao Greater Bay Area, accelerate the construction of the mechanism for the synergetic economic development of the three areas, accelerate the establishment of an integrated market, build a reasonable division of labor system and collaborative innovation system, and jointly promote the synergetic economic development of Greater Bay Area. [ABSTRACT FROM AUTHOR]

With the continuous development of the economy, the trade volume of customs clearance by land transportation between Guangdong and Hong Kong is increasing, but there are many problems in customs clearance by land transportation between Guangdong and Hong Kong. Therefore, it is necessary to start with the logistics mode of land transportation between Guangdong and Hong Kong, reduce the cost of customs clearance by land transportation between Guangdong and Hong Kong, and increase the trade volume by land transportation between the two places. This paper systematically analyzes the present situation of customs clearance efficiency in China and introduces BPNN (BP neural network) algorithm to optimize customs clearance. The detailed idea and process of the algorithm are introduced, and the BPNN trained by the algorithm is applied to function approximation. The simulation results show that this scheme can not only improve the convergence speed of the algorithm in the training process but also the trained BPNN has strong adaptive and self-learning ability. Comparing the customs clearance efficiency before and after the improvement, the results show that the improved customs clearance efficiency is higher and can save a lot of time, thus verifying the effectiveness and applicability of the model-solving algorithm. [ABSTRACT FROM AUTHOR]

Objective. To carry out the research on the vulnerability evaluation and influencing factors of the tourism economic system is the objective requirement of formulating the scientific development strategy of the tourism economy and improving the quality of regional tourism development. Methods. Based on the vulnerability analysis of tourism economic system based on BP neural network (BPNN), this paper takes the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as the research object and selects 14 index data. The mean and standard deviation of the calculated weight values are used to formulate evaluation criteria for the tourism system. Results. The BP neural network (BPNN) model was used to predict the distribution law of vulnerability data within the standard range of the Greater Bay Area after 2020, obtained the spatial distribution law of vulnerability in the geographic structure distribution of the Greater Bay Area, and determined the vulnerability analysis framework and evaluation method. Conclusion. The cities in the Greater Bay Area should first pay attention to the industrial structure; increase financial investment; enhance the attractiveness of tourist destinations, in-depth development of tourism resources, and rational design of tourism products; help reduce the vulnerability of the tourism economic system; and improve regional self-recovery capabilities. [ABSTRACT FROM AUTHOR]

Regional tourism with urban agglomeration as the spatial carrier has become one of the flow characteristics of many tourists. Tourists visiting multiple cities at one time will certainly gain more value than visiting one city, but they will also pay more costs, thus affecting their emotions and willingness to travel. But the mechanism and theoretical boundaries have not been clarified. Based on the cognitive–affective–behavioral attitude model and the customer-delivered-value model, this paper takes the tourism destination tourists of the Guangdong–Hong Kong–Macao Greater Bay Area urban agglomeration as samples to explore the influence mechanism of tourists' perceived functional value, social value and knowledge value on positive emotion and travel intention, and to test the moderating mediating effect of monetary cost, energy cost and psychological cost on positive emotion. Social value and knowledge value positively affect travel intention. Functional value, knowledge value and social value positively affect positive emotion, and positive emotion positively affect travel intention. Positive emotion plays a complete mediating role between functional value, social value and travel intention, and plays a partial mediating role between knowledge value and travel intention. Monetary cost, energy cost and psychological cost respectively moderate the mediating effect of positive emotion between functional value and travel intention. Psychological cost moderates the mediating effect of positive emotion between social value and travel intention. Monetary cost and psychological cost respectively moderate the mediating effect of positive emotion between knowledge value and travel intention. Differences in the impact of consumers' perceived value at different levels on positive emotion and travel intentions. It opens up the differences in the effects of the interaction of different levels of perceived value and different types of perceived cost on positive emotion. From an empirical point of view, it is proved that the tourism boutique line design based on multicity destination combination in China is feasible as a method to promote tourism integration and regional tourism brand building. It also puts forward the management enlightenment of regional tourism integration and regional tourism brand building from the perspectives of enterprises, front-line service personnel, residents and government. [ABSTRACT FROM AUTHOR]

Catalyzed by global change and human activities, social and ecosystems are constantly under increasingly dynamic transformations. The Guangdong–Hong Kong–Macau Greater Bay Area (GBA), bordering the South China Sea and located in the Pearl River Delta Plain, is a typical region of complex SESs with rapid socioeconomic development but severe ecosystem degradation. Therefore, based on the relevant data of 11 GBA cities from 2010–2020, this paper constructs an indicator system for assessing land–sea SESs by extracting from three aspects: exposure, sensitivity, and adaptive capacity. Through the construction of a vulnerability assessment indicator system, via the explicit spatial vulnerability indicator calculation model, and vulnerability factor diagnostic model, this study comprehensively analyzes vulnerability levels, spatiotemporal evolution, and SES vulnerability factors. The study found that, since 2010, the SES vulnerability of the GBA has shown an overall trend of alleviation, and the overall geographical distribution of classified vulnerability levels is rather concentrated, with cities around the Pearl River Estuary relatively less vulnerable. The augmentation of per-capita fiscal expenditure, per-capita gross regional product, and decent air quality rate are the critical ingredients to remedy the vulnerability in the GBA. [ABSTRACT FROM AUTHOR]

Coastal areas are usually considered as pioneering areas for economic development and reform due to their unique geographical locations and ecological conditions. Correspondingly, rapid urbanization in coastal urban agglomerations has resulted in population concentration and land use/cover change (LUCC), leading to the decline of habitat quality and biodiversity. However, few studies have quantitatively explored the impacts of urban agglomeration expansion in coastal zones on habitat quality. Taking the Guangdong-Hong Kong-Macao-Great Bay Area (GBA) as a case study, we applied the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to assess the habitat quality based on land use data obtained from remote sensing images from 1980 to 2020 and developed a geographically weighted regression model to quantitatively analyze the response of habitat quality to urbanization. The results showed that (1) LUCC in the GBA was dramatic from 1980 to 2020, dominated by the shift from various land use types to construction land, which led to increased fragmentation; (2) the overall habitat quality showed a decreasing trend, characterized by low values in the central part and high values in the surrounding area; (3) population and construction land such urbanization elements had a more significantly negative effect on habitat quality changes, while the relationships among slope, road distance, and habitat quality changes were complex. Based on above analysis, this paper suggests that future land management in the GBA should develop in the direction of intensification, refinement, and regional integration. [ABSTRACT FROM AUTHOR]

Ozone (O3) pollution has negative impacts on human health and property. The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is facing severe O3 pollution problems due to rapid economic development. In this paper, we used sensitivity experiments and GeoDetector to analyze the effects of meteorological factors, anthropogenic emissions, and landscape patterns on O3 concentrations as well as the contributions of NOx and NMVOC (non-methane volatile organic compounds) to the variation of O3 concentrations and the causes of sectoral emissions in the GBA in 2017. The results revealed that, in GBA, the contribution of meteorology to the variation of O3 concentration was dominant both in terms of region and extent, and the contribution of emissions was relatively weak. The contribution of meteorology and emissions to O3 production was mainly contributory. Meteorology contributed significantly to O3, and its non-linear interaction with anthropogenic emissions and surface landscape affected O3 concentration changes. The degree of contribution of NOx and NMVOC varied widely among seasons, and the variation of their relative contribution areas was related to residential sector emissions and agricultural sector emissions. This article enriches the exploration of the O3 formation mechanism in the GBA and provides theoretical support for the implementation of differentiated regional and seasonal mitigation strategies for O3 concentration. [ABSTRACT FROM AUTHOR]

The notion of “agent bookkeeping” was proposed when the “Accounting Law of the People’s Republic of China” was updated in 1993. Since their business is specialized in serving small and micro-enterprises, this has created the industry characteristic of generally small in the size of company and low in the salary of employees in Chinese agent bookkeeping companies. Such characteristic results in a series of problems including negative work attitude of employees in the development process, which seriously limit the development of Chinese agent bookkeeping companies. However, issues occurred in the development of agent bookkeeping, such as negative employee attitudes, which severely hampered the growth of Chinese agent bookkeeping companies. Therefore, a model of three dimensions of work attitude has been set up in this paper to demonstrate the working attitude of the staff of the agent bookkeeping companies in China’s Guangdong-Hong Kong-Macao Greater Bay Area, including emotional dimension, behavioral dimension, and cognitive dimension which consists of eight factors: work environment, career satisfaction, interpersonal relationship, role engagement, work vitality, responsibility attitude, emotional identity, and retention attitude. The result indicates that (1) female employees outnumber male ones in agent bookkeeping companies, (2) most employees have a low sense of belonging to the company, (3) limited career development affects employees’ enthusiasm for work, (4) work attitudes are influenced by mediocre work performance among employees with a graduate degree or higher. [ABSTRACT FROM AUTHOR]

Under the background of "one belt, one road initiative" and the "Outline Development Plan for the Guangdong-Hong Kong-Macao Greater Bay Area," Guangdong, Hong Kong, and Macao port group development is facing new opportunities. The port group has a large throughput, covering the hinterland with dense population and high economic density, excellent transportation infrastructure, and broad consumption market. However, the port group internal competition is fierce, and the development level is different in space. Based on this, this paper uses the HHI index and spatial economics as research method and aims to study the spatial evolution characteristics and influencing factors of Guangdong-Hong Kong-Macao port group. Firstly, the HHI index is used to describe the aggregation status. Secondly, the development level index according to port throughput and container throughput is constructed. The spatial development and evolution process of the port group of Guangdong, Hong Kong, and Macao is analyzed by combining with spatial econometrics and economic geography. In summary, the influencing factor "diamond model" is constructed and took empirical research to verify its rationality and scientificity. The empirical results show a strong spatial correlation between the development of the Guangdong, Hong Kong, and Macao port group. The government intervention and the development of port industry have a negative correlation, and this impact will be weakened over time. There is a negative relationship between the level of marketization and the development of the port industry. There is a multiple and complex relationship between the port auxiliary industry and the development of the port industry, and it shows the short-term influence is smaller than the long-term impact. The level of port transportation infrastructure, the port industry competition, and the economic openness have significant and positive effects on the development of the port group. [ABSTRACT FROM AUTHOR]

A multiple-airport system (MAS) consists of more than two airports in a metropolitan area under a large block of terminal airspace that is managed by one or two air traffic control units. When the capacity of an airport or of the terminal airspace drops, flight delays occur in the MAS system. A quick estimation and predication of traffic congestion in the MAS is important yet challenging. This paper aims to develop a queuing network model of MAS using point-wise stationary queues. The model analyzes the changes of non-stationary queues under the principle of flow conservation to capture flight delay propagation in the system. Regression analyses are performed to examine the relationship between the arrival and departure efficiencies of different airports. The model is validated with the data of Guangdong–Hong Kong–Macao Greater Bay Area airports. Simulation results show that the model can effectively estimate flight delays in the MAS. [ABSTRACT FROM AUTHOR]

Based on the equivalent factor table of terrestrial ESV in China in 2010, this paper proposes a regionalized and interannual ESV correction method. Taking southern Guangzhou as the study area, which is located in the geometric center of the Guangdong–Hong Kong–Macao Greater Bay Area (GHM GBA), this study evaluated the ecosystem service equivalent value (ESEV) and ecosystem service value (ESV) and their changes in 2004, 2010 and 2016 and carried out grid processing, trend analysis and global/local spatial autocorrelation of the ecosystem service density (ESD) in the study area by using the Natural Resources Integrated Database of Guangdong Province (NRIDB). The results of data processing and spatial analysis computed in this study were published as Web services through the NRIDB and displayed in the visualization front-end. The results showed that (1) during 2004–2016, the urbanization process in the study area led to the expansion of built-up land, which occupied a large amount of ecological land and resulted in a decreasing trend of ESV. (2) Benefiting from socioeconomic development, the standard value volume of the ESEV (D value) kept increasing, which resulted in an increasing trend for the total ESV. (3) The spatial autocorrelation analysis results of ESD indicated that the spatial distribution of ESD in the study area had strong spatial agglomeration and positive spatial correlation. With the progress of urbanization and increases in research scale and interval distance, the spatial difference in ESD became larger over time. The research results provide a reference for the coordinated allocation of natural resources and environmental protection in the GHM GBA. [ABSTRACT FROM AUTHOR]

In the present era, people are facing enough challenges, either personally or technically, and some people do suffer from having to keep up with the current technological improvements. The Guangdong-Hong Kong-Macao Greater Bay Area (GHKMGBA) is one of the areas that has been highly managed for tourism with economic networks in it. Here, the exploitation results in underground spacing management automate the alleviation process using various methods. Apart from the characterization, it is one such mandatory consideration to create a master plan with the rise of utilization and urban underground spacing planned to be placed among large cities for tourism is considered. This paper focuses on the strategy to understand the concepts and popularisation of urban underground spacing. This matter is followed by a complementary approach with a supportive technical system. This research focuses on economic development in the cities of GHKMGBA, and the analysis is carried out with the implementation of the backpropagation neural network (BPNN). [ABSTRACT FROM AUTHOR]

The coordinated development of urban quality and technology innovation is an important element of China's technology innovation development strategy in the new era. Based on entropy TOPSIS, coupling coordination models, the gravity center and standard deviation ellipse method, the geographic probe, the GWR, and other methods, we explore the spatial variation and influencing factors of the coupling coordination relationship between urban quality and technology innovation in the Guangdong-Hong Kong-Macao Greater Bay Area from 2011 to 2020. It is found that: (1) the spatial distribution of the coupling coordination shows a characteristic of "high in the middle and low in the surroundings," and (2) the level of benign interaction in the central region is becoming more prominent. The center of gravity of coupling coordination moves toward the northeast, and the standard deviation ellipse shows a contraction trend away from the southwest. (3) Agglomeration capacity, human capital, cultural development, and infrastructure can significantly drive the improvement of the coupling coordination of urban quality and technology innovation, and the two-factor influence is significantly increased after the interaction. (4) The feedback effects of the coupling and coordination states of different cities on each factor have significant spatial differences and show the characteristics of hierarchical band distribution. [ABSTRACT FROM AUTHOR]

Guangdong-Hong Kong-Macao Greater Bay Area is one of the regions with the highest degree of openness and the strongest economic vitality in China. In this paper, the remote sensing ecological index (RSEI) model is used to calculate the Ecological Traffic footprint of the Greater Bay area of Guangdong-Hong Kong-Macao, and the remote sensing data of the Greater Bay area of Guangdong-Hong Kong-Macao is used to analyse and evaluate the development and evolution of Ecological Traffic in the Greater Bay area of Guangdong-Hong Kong-Macao. The results show that the ecological traffic environment of the Greater Bay area of Guangdong-Hong Kong-Macao is good, and it is getting better. The poor areas are mainly concentrated in the central region, which is also improving. [ABSTRACT FROM AUTHOR]

The urbanization impacts on surface air temperature (SAT) change in the Guangdong‐Hong Kong‐Macau region (GHMR) from 1979 to 2018 are examined using homogeneous surface observations, reanalysis, and remote sensing. Results show that the warming due to urbanization tends to be smaller or insignificant as the spatial scale increases. The urbanization contribution to the local warming can reach as high as 50% in the center of each metropolis, remains high (~25%) in the Greater Bay Area (GBA), and decreases to about 10% in the whole GHMR. The warming in GHMR is nearly uniform throughout the day, and therefore, the observed trend of the diurnal temperature range (DTR) is not statistically significant. However, the urbanization contribution exhibits distinct seasonal variations, large in summer and autumn while smaller in winter and spring. Plain Language Summary: The Guangdong‐Hong Kong‐Macau region (GHMR), especially the Greater Bay Area (GBA), is a region typical of China's economic development and rapid urbanization. To precisely assess how much the urbanization contributes to the regional warming, we comprehensively evaluate the urbanization warming and its uncertainties in GHMR by using more careful processed and assessed data (observations, reanalysis, and remote sensing) and different analysis methods. The results show that the warming due to urbanization tends to be smaller as the spatial scale increases: The contribution to the local warming can reach as high as 50% in the metropolis, remains high (~25%) in GBA, and decreases to about 10% in GHMR. In addition, this paper systematically discusses the uncertainty in urbanization contribution detection, which was often neglected in the past detection. Based on the significance tests, urbanization warming is nearly uniform throughout the day, while it exhibits distinct seasonal variation. Our study also has important implications for understanding the influences of human activities on regional climate change for other regions experiencing rapid urbanization processes. Key Points: The contribution of urbanization to regional warming is robust in homogenized SAT data and ERA5 reanalysis using different methodsThe spatial scale dependence of urbanization warming is investigated; the contribution of urbanization warming decreases when the scale increasesUrbanization contribution exhibits distinct seasonal variation based on the uncertainty assessment [ABSTRACT FROM AUTHOR]

Sci-tech innovation is an important measure for the Guangdong– Hong Kong–Macao Greater Bay Area to achieve high-quality economic development. theoretically, there is a coupling coordination relationship between sci-tech innovation and high-quality economic development, and coordinating the relationship between the two is beneficial to building the Guangdong– Hong Kong–Macao Greater Bay Area into an international innovation and technology hub and promoting high-quality economic development. At present, the Guangdong–Hong Kong–Macao Greater Bay Area has seen a year-on-year increase in both the level of sci-tech innovation and the level of high-quality economic development, with a sound development trend. Its coupling coordination degree between sci-tech innovation and high-quality economic development has steadily improved from a slightly uncoordinated stage to a primarily coordinated stage, but the overall degree of coordination is still not high, with some gaps from realizing the excellently coordinated stage. From the perspective of spatial distribution, the internal development of the Guangdong-Hong Kong–Macao Greater Bay Area is unbalanced, with obvious differences in development level and coupling coordination degree among cities. e convergence analysis shows that the differences in the coupling coordination degree among the cities in the Guangdong Hong Kong–Macao Greater Bay Area have stabilized after narrowing during the study period. However, the difference among the cities with higher coupling coordination degrees tends to widen in recent years. therefore, necessary measures should be taken to promote the coordination between sci-tech innovation and high-quality economic development in the Guangdong–Hong Kong–Macao Greater Bay Area. [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 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]

When considering the economic growth of the Greater Bay Area, digital transformation stands out as a crucial catalyst. Given its significance, it is imperative to delve into both the theoretical and empirical aspects of how digital transformation affects the region's position in the global value chain. Theoretical hypotheses are put forward regarding the impact and mechanisms of digital transformation on the global value chain position of the Greater Bay Area based on a global value chain perspective. A three-tier nested input–output table that incorporates the Greater Bay Area is constructed, and trade decomposition and global value chain position measurement models specific to the area are developed for analyzing its current state in terms of global value chain position. Empirical testing was conducted to examine how digital transformation impacts this position. Digital transformation will significantly enhance the position of the Greater Bay Area in the division of global value chains, mainly through enhancing technological innovation transformation capabilities and value added by exports from the Greater Bay Area. Digital transformation within the Greater Bay Area has had a more substantial positive impact than the digital transformation in other provinces in China and digital transformation from foreign sources. In terms of city heterogeneity, it is evident that the global value chain from Hong Kong and Macao has experienced a more significant impact from digital transformation compared to cities in the Pearl River Delta. Therefore, the Greater Bay Area should increase the use of both digital transformation and differentiated use of digital transformation. PRD cities should actively learn from Hong Kong and Macao's forms of digital construction and promote the Greater Bay Area's global value chain status. [ABSTRACT FROM AUTHOR]

Energy consumption is an important indicator for measuring economic development and is closely related to the atmospheric environment. As a demonstration zone for China's high-quality development, the Guangdong–Hong Kong–Macao Greater Bay Area imposes higher requirements on ecological environment and sustainable development. Therefore, accurate data on energy consumption is crucial for high-quality green development. However, the statistical data on local energy consumption in China is insufficient, and the lack of data is severe, which hinders the analysis of energy consumption at the metropolitan level and the precise implementation of energy policies. Nighttime light data have been widely used in the inversion of energy consumption, but they can only reflect socio-economic activities at night with certain limitations. In this study, a random forest model was developed to estimate metropolitan-level energy consumption in the Guangdong–Hong Kong–Macao Greater Bay Area from 2000 to 2020 based on nighttime light data, population data, and urban impervious surface data. The estimation results show that our model shows good performance with an R2 greater than 0.9783 and MAPE less than 9%. A long time series dataset from 2000 to 2020 on energy consumption distribution at a resolution of 500 m in the Guangdong–Hong Kong–Macao Greater Bay Area was built using our model with a top-down weight allocation method. The spatial and temporal dynamics of energy consumption in the Greater Bay Area were assessed at both the metropolitan and grid levels. The results show a significant increase in energy consumption in the Greater Bay Area with a clear clustering, and approximately 90% of energy consumption is concentrated in 22% of the area. This study established an energy consumption estimation model that comprehensively considers population, urban distribution, and nighttime light data, which effectively solves the problem of missing statistical data and accurately reflects the spatial distribution of energy consumption of the whole Bay Area. This study provides a reference for spatial pattern analysis and refined urban management and energy allocation for regions lacking statistical data on energy consumption. [ABSTRACT FROM AUTHOR]

In the context of the digital information era, the impact of "The Internet Plus," "Big Data," and other technologies on urban social development has been far beyond any preceding era, under the influence of information technology, urban agglomeration space exhibits a new layout. Based on the search engine data of eleven cities in the Guangdong-Hong Kong-Macao Greater Bay Area from 2012 to 2021, this research constructs the inter-city information network strength linkage matrix to examine the evolution characteristics of city network structure and its driving causes. The results reveal that (1) the overall information linkage strength exhibits a pattern of steadily growing the radiating effect from the leading cities of Guangdong, Shenzhen, and Hong Kong to the surrounding cities, and a closer and more balanced information linkage network is gradually built. (2) Guangzhou-Shenzhen-Hong Kong-Guangdong-Hong Kong-Macao Greater Bay Area information linkage absolute control advantage, four cities Foshan, Dongguan, Zhuhai, Macao regional hub position steadily highlighted. The entire information connection network of the urban agglomerations tends to be flat and polycentric at the same time. (3) The regional core-edge hierarchy is well established, with the four cities of Guangzhou, Dongguan, Shenzhen, and Hong Kong creating a northwest-southeast orientation. The core metropolis regions of Guangdong, Hong Kong, and Macao in the Greater Bay Area increasingly exert a radiation spreading effect to the northeast and southwest. (4) The urban economy, transportation distance, and information infrastructure have substantial effects on the information connection intensity network of urban clusters. [ABSTRACT FROM AUTHOR]

In recent years, a great number of studies have convincingly shown that diffusion influences states' probability to democratise. The primary interest of most of these studies has been on how diffusion influences democracy at the national level. The effect of democratic diffusion on the local level has largely been neglected. This paper thus investigates how and to what extent diffusion influ- ences the density and conflict orientation of non-governmental labour organisations (LNGOs), comprising a typical case of civil society groups channelling democratic freedoms, in China's Guangdong province. Since the province is close to the relatively liberal city of Hong Kong, there is reason to believe that support from international civil society groups based in Hong Kong may be critical for the survival and growth of conflict-oriented LNGOs in Guangdong. In the article, the research question is studied by both comparative analysis of cross-regional data and qualitative analysis of interview data. Both methods confirm that diffusion -- or, more precisely, diffusion through international civil society networks -- is a prominent factor for explaining the density and conflict orientation of LNGOs in Guangdong. The study demonstrates that democratic diffusion not only has an impact at the state level but also on the regional, intrastate level. [ABSTRACT FROM AUTHOR]

In practical engineering projects, overconsolidation plays an irreplaceable role in the calculation of silt consolidation settlement. Based on a series of systematic consolidation tests conducted on reconstituted soft clay in different cities of the Guangdong-Hong Kong-Macao Greater Bay Area, the overconsolidation behavior of soft clay under different depths was studied. According to these tests, the shape of the curves of the overconsolidation ratio with depth was similar to that of the compression curves. Moreover, the deeper the silt depth is, the smaller the overconsolidation ratio is. Hence, the overconsolidation state eventually changes to the underconsolidation state. On this basis, the depths of normal consolidation were calculated through the fitting curves of the overconsolidation ratio with depth by CurveExpert1.4, which is strongly dependent on both the average thickness of the overfill and the range of water level. Based on the results, a polynomial relationship between overconsolidation ratio (OCR) and sampling depth (h) is established. This study can serve as a basis for predicting the consolidation settlement of the silt layer more accurately in practical engineering applications. [ABSTRACT FROM AUTHOR]

Tracking long-term tidal flat dynamics is crucial for coastal restoration decision making. Accurately capturing the loss and gain of tidal flats due to human-induced disturbances is challenging in the micro-tidal areas. In this study, we developed an automated method for mapping the annual tidal flat changes in the micro-tidal areas under intense human activities, by integrating spectral harmonization, time series segmentation from dual spectral indices, and the tide-independent hierarchical classification strategy. Our method has two key novelties. First, we adopt flexible temporal segments for each pixel based on the dual full-time series spectral indices, instead of solely using a fixed period window, to help obtain more reliable inundation frequency features. Second, a tide-independent hierarchical classification strategy based on the inundation features and the Otsu algorithm capture the tidal flat changes well. Our method performed well in Guangdong, Hong Kong, and Macao (GHKM), a typical area with micro-tidal range and intense human activities, with overall accuracies of 89% and 92% for conversion types and turning years, respectively. The tidal flats in GHKM decreased by 24% from 1986 to 2021, resulting from the loss of 504.45 km2, partially offset by an accretion of 179.88 km2. Further, 70.9% of the total loss was in the Great Bay Area, concentrated in 1991–1998 and 2001–2016. The historical trajectories of tidal flat loss were driven by various policies implemented by the national, provincial, and local governments. Our method is promising for extension to other micro-tidal areas to provide more scientific support for coastal resource management and restoration. [ABSTRACT FROM AUTHOR]

The aim of this study is to comprehensively evaluate the economic network patterns and their influencing factors of the Guangdong–Hong Kong–Macao Greater Bay Area (GHMGBA) in China, considering population scale, economic development level, and land-resource endowment. By employing a modified gravity model and a social-network method, we quantitatively analyzed urban agglomeration integrity indices, such as network density, edge–core structure, cohesive-subgroup index, and urban individual index (e.g., centrality degree) of this region, encompassing nine cities in Guangdong Province and two special administrative regions. The results revealed significant changes in the economic network patterns within the GHMGBA over time. Furthermore, the quadratic assignment procedure correlation analysis index was used to identify the various factors affecting the strength of the economic interaction. The findings demonstrated an annual increase in the strength of economic interaction between cities and regions within the GHMGBA over the past 20 years, along with the emergence of a polycentric economic development pattern. The results also suggest that the spatial location and level of economic development are key determinants influencing the strength of economic linkages in this area. This study supports the conclusion that deepening exchanges and cooperation among core cities, bolstering economic development in sub-core cities, and facilitating the construction of an integrated regional transportation network will expedite the process of economic integration. [ABSTRACT FROM AUTHOR]

As a major carbon emitter, the power sector plays a crucial role in realizing the goal of carbon peaking and carbon neutrality. This study constructed a low-carbon power system based on the LEAP model (LEAP-GBA) with 2020 as a statistic base aiming of exploring the low-carbon transformation pathway of the power sector in the Guangdong–Hong Kong, and Macao Greater Bay Area (GBA). Five scenarios are set up to simulate the demand, power generation structure, carbon emissions, and power generation costs in the power sector under different scenarios. The results indicate that total electricity demand will peak after 2050, with 80% of it coming from industry, buildings and residential use. To achieve net-zero emissions from the power sector in the GBA, a future power generation mix dominated by nuclear and renewable energy generation and supplemented by fossil energy generation equipped with CCUS technologies. BECCS technology and nuclear power are the key to realize zero carbon emissions from the power sector in the GBA, so it should be the first to promote BECCS technology testing and commercial application, improve the deployment of nuclear power sites, and push forward the construction of nuclear power and technology improvement in the next 40 years. [ABSTRACT FROM AUTHOR]

On May 11, 2022, despite the favorable upper and lower-level circulation patterns of the high-altitude trough, shear line, and southwest jet stream, the urban cluster of the Guangdong-Hong Kong-Macao Greater Bay Area experienced light to moderate rainfall, deviating significantly from the forecasted heavy rain and local heavy rainstorm. This study explores the reasons for false alarms and predictability using ground observation data, radar data, ECMWF-ERA5 reanalysis field data, and ECMWF and CMA-TRAMS forecast data. The results indicate that the warm and moist airflow transported by the low-level jet stream was intercepted by the upstream MCS (mesoscale convective system) along the coastal area of western Guangdong, and inadequate conditions of negative vorticity dynamics led to insufficient moisture, thermodynamic, and dynamic conditions over the urban cluster, preventing the triggering of heavy precipitation. In addition, the 700 hPa westerly flow guiding the airflow and the stable low-level shear line, coupled with surface convergence lines, influenced the northward or southward movement of MCSs along the coastal and inland regions of western Guangdong. The weak and discontinuous intensity of echoes in the upstream Zhaoqing region further hindered the influence of surrounding echoes on the urban cluster. Numerical forecast models ECMWF and CMA-TRAMS overestimated the 850 hPa windspeed and 925 hPa meridional windspeed, resulting in the forecasted urban cluster experiencing heavy rain. Sensitivity tests of wind fields indicate that the 850 hPa wind field information is more sensitive to precipitation in the urban cluster. In this process, weak signal correction can be achieved in strong precipitation forecasts using the distinct signal of lower 850 hPa water vapor flux divergence compared to 925 hPa. Therefore, in the future, when the Guangdong-Hong Kong-Macao Greater Bay Area encounters similar warm-sector heavy rainfall events, adjustments to model forecasts can be made using specific 850 hPa elements such as wind speed, water vapor flux divergence, or specific humidity to enhance predictive accuracy. [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 recent times, a new wave of scientific and technological advancements has significantly reshaped the global economic structure. This shift has redefined the role of regional innovation, particularly in its contribution to developing the Guangdong–Hong Kong–Macao Greater Bay area (GBA) into a renowned center for science, technology, and innovation. This study constructs a comprehensive evaluation system for the Regional Innovation Ecosystem (RIE). By applying the coupling coordination degree model and social network analysis, we have extensively analyzed the spatial structure and network attributes of the coupled and coordinated innovation ecosystem in the GBA from 2010 to 2019. Our findings reveal several key developments: (1) There has been a noticeable rightward shift in the kernel density curve, indicating an ongoing optimization of the overall coupling coordination level. Notably, the center of gravity for coupling coordination has progressively moved southeast. This shift has led to a reduction in the elliptical area each year, while the trend surface consistently shows a convex orientation toward the center. The most significant development is observed along the 'Guangdong–Shenzhen–Hong Kong–Macao Science and Technology Innovation Corridor', where the level of coupling coordination has become increasingly pronounced. (2) The spatial linkages within the GBA have been strengthening. There are significant spatial transaction costs in the regional innovation ecological network. In the context of the 2019 US-China trade war, the cities of Jiangmen and Zhaoqing experienced a notable decrease in connectivity with other cities, raising concerns about their potential marginalization. (3) Guangzhou, Shenzhen, and Hong Kong have emerged as core nodes within the network. The network exhibits a distinctive "core–edge" spatial structure, characterized by both robustness and vulnerability in various aspects. [ABSTRACT FROM AUTHOR]

Understanding the economic impact of COVID-19 is the foundation for formulating targeted policies promoting economic recovery. This study uses panel data of the county economy in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) from 2017 to 2022. Firstly, the evolution characteristics of the economic structure in the GBA were analyzed using the standard deviation ellipse, geographical concentration, and spatial autocorrelation methods. Then, we revealed the changes in various economic indicators. Finally, a spatial Durbin model was constructed to study the factors affecting economic growth and spatial spillover effects in different periods. The results reveal that the economic distribution in the GBA presents a "core–edge" structure. The FDI, consumption, and exports of the Greater Bay Area fluctuate greatly, while investment growth is relatively stable. There is a significant spatial spillover effect in the county economy of the GBA. Investment, consumption, exports, labor, and innovation all have significant positive effects on economic growth, with investment having the greatest impact, while FDI has a significant negative impact. The impact of COVID-19 on the economy of the GBA is mainly reflected in the weakening of spatial spillovers, the strengthening of economic agglomeration, the decline in factor growth, and the change in the driving effect of factors on the economy. These findings can provide a reference for formulating targeted economic development policies. [ABSTRACT FROM AUTHOR]

The spatiotemporal distribution of ecosystem service values (ESVs) and ecological risk are critical indicators to represent the regional ecological protection level and potential of sustainable development, which largely depend on land-use patterns. Aiming to contribute to global climate mitigation, China has proposed dual-carbon goals that would remarkably influence the land-use/cover change (LUCC) distribution. Based on the Landsat land cover data of 2000, 2010 and 2020 and multisource satellite products, several driving factors are integrated into the patch-generating land use simulation (PLUS) model to simulate future LUCC patterns for the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) under rapid urbanization, cropland protection and carbon neutral (CN) scenarios from 2020 to 2050. Spatial–temporal ecosystem service and ESVs are allocated using INVEST and the equivalent factor method and thus ecological risks are evaluated using the entropy method. Results indicate that forest growth is the largest under the CN scenario, especially in the northwestern and northeastern GBA, exceeding 25,800 km2 in 2050, which results in both the highest habitat quality and carbon storage. The largest ESVs, reaching higher than 5210 yuan/pixel, are found in the CN scenario, particularly expanding toward the suburban area, leading to the lowest ecological risks. From 2020 to 2050, habitat quality, carbon storage and ESVs improve, while ecological risks decline in the CN scenario. This research provides implications for economic and ecological balanced development and gives references to the carbon-neutral pathway for the GBA. [ABSTRACT FROM AUTHOR]

Wen, M.; Liu, C.; Galina, P.; Tao, C.; Hou, X.; Bai, F., and Zhao, H., 2020. Efficiency analysis of the marine economy in the Guangdong–Hong Kong–Macao Greater Bay Area based on a DEA model. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 225–228. Coconut Creek (Florida), ISSN 0749-0208. This paper aims to study the marine economic efficiency based on a data envelopment analysis (DEA) model. The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) was taken as the research object, and an input-output index system was established. The research results show that the GBA is developing rapidly, and the spatial layout of the marine economy continues to optimize. In the established input-output index system, the input indicators include the three aspects of marine resources, human resources, and scientific and technological inputs, while the output indicators include marine economic output and environmental output. The marine economic efficiency of the GBA was not high, and the average efficiency values of all regions were less than 1; the average value of Guangdong's marine economic efficiency was the highest, and that of Hong Kong's was the lowest, indicating that they are in an inefficient state. Finally, countermeasures and suggestions are put forward for improving the marine economic investment and enhancing the efficiency of marine economic development. The research findings provide useful reference for the sustainable development of the marine economy in the GBA and throughout the country. [ABSTRACT FROM AUTHOR]

• 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]

As one of the world's four Greater Bay Areas, the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) faces many environmental challenges along with rapid economic development, causing significant degradation of aquatic ecosystems. However, there is limited knowledge on long-term environmental changes (i.e., >50 years), and restoration of the degraded aquatic ecosystems in the GBA has become increasingly difficult. This study selects a typical inland water body, the Miaotan Reservoir, from Huizhou City in the GBA, to explore long-term changes in water and the eco-environment over the past 70 years and to provide some restoration and management strategies for degrading aquatic ecosystems in the region. We collected a sediment core from the reservoir center and established an age–depth profile by integrating 210Pb and 137Cs dating. We then set up high-resolution diatom community succession stratigraphy and multiple indicators (grain size, element, geochemical and social indicators) as responses to environmental changes in the reservoir. Our results show that significant changes have occurred in the ecosystem and environment of the Miaotan Reservoir and its catchment over the past 70 years. The diatom community underwent a gradual transition from absolute dominance of the mesotrophic species Aulacoseira granulata to dominance of the eutrophic species Nicizschia gracilis, Nicizschia palea and Achanathes sp., indicating the onset of water quality degradation and ecosystem changes in the 1990s due to eutrophication. The RDA (Redundancy analysis) results demonstrate that exogenous pollutant inputs into the Miaotan Reservoir resulting from agricultural activities over the period led to serious environmental changes, e.g., toxic algal bloom and heavy metal pollution. This study enriches our understanding of long-term environmental changes in inland lakes and reservoirs in South China and provides insights into the restoration and management of aquatic ecosystems in the GBA. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) pose a significant threat in terms of wind-induced damage and storm risk to the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) of China. In this research, annual power dissipation index (PDI) and storm surge and wave destructive potential (SDP) index from June to November were used to estimate the damage caused by the TC events in the buffer zone of the GBA. The regime shifts in 1993 and 2013 were identified through the Bayesian changepoint detection in six TC datasets. The TC-induced damage during 1994–2012 (the low-damage period) was weaker than that in 1977–1993 and 2013–2020 (the high-damage periods). The intensity and size of stronger TCs are the dominant factors responsible for the interdecadal changes in the TC damage. This may be explained by the influences of sea surface temperature (SST), surface latent heat flux and mid-level relative humidity. During high-damage periods, TCs can extract more energy from the ocean, leading to increased TC intensity and larger size. Conversely, during low-damage periods, TCs undergo a decrease in energy intake, resulting in reduced TC power and smaller size. The variations in the SST are relative to the Luzon Strait transport. In addition, the reduction in TC translation speed is unfavorable for the development of TCs in low-damage periods. Further research suggested that mid-level steering flow affects the TC movement velocity. The results offer valuable insights into the variations in the TC-induced damage in the GBA. [ABSTRACT FROM AUTHOR]

• We compared the structural characteristics of 18 urban agglomerations in China. • Our framework contained analysis of 3 different scales based on 4 elements' flows. • Guangdong-Hong Kong-Macao urban Agglomeration had the greatest average flow (5.15). • Shandong Peninsula Urban Agglomeration had the best performance in overall network. • Cities with high centrality were in the bidirectional or main spillover subgroups. Flows of different elements among cities can affect urban organizational structures, leading to specific links between and roles for cities within urban agglomerations. Previous studies have mainly focused on flows produced by specific elements in a single urban agglomeration, and they cannot reveal differences in organizational structures affected by multiple elements among different urban agglomerations. Therefore we selected 18 typical urban agglomerations in China and explored their structural characteristics under comprehensive effects of four elements: economy, resources, population and technology, with gravity model and social network analysis. Guangdong-Hong Kong-Macao Urban Agglomeration had a maximum flow intensity of 5.15, this concentration range was the largest from 0.65 to 3.75, indicating that more elements flowed internally. Shandong Peninsula Urban Agglomeration had the largest network density at 0.412, the lowest efficiency at 0.567, and the lowest hierarchy at 0.000, showing that intercity relationships within SP were the tightest among the18 urban agglomerations. Geographical proximity and topological structure of subgroups proved that connections among subgroups were not complex, and cities of different provinces lacked close interactions. Furthermore, most of the key cities with high centrality indexes were municipalities directly under the Central Government or provincial capitals; these cities played important roles in networks and were distributed into "main spillover" and "bidirectional spillover" subgroups. This paper provides a unified analytical framework aimed at urban agglomerations that accounts for flows of multiple types of elements and explores urban organizational structures, and our results could provide scientific guidance for promoting the coordinated and sustainable development of urban agglomerations. [ABSTRACT FROM AUTHOR]

Macroalgae provide food for microbial, meio- and macro-faunal communities in coastal ecosystems, thus mediating nutrient dynamics and functions in these ecosystems. Because of this vital role, it is important to clarify physiological information about macroalgae as it reflects their growth potential in the field. In this study, we examined the biomass, pigment content, and photosynthetic O2 evolution rate versus irradiance curves of 18 macroalgal species from the intertidal zone of the Guangdong–Hong Kong–Macao Greater Bay Area, China, and investigated their photosynthetic patterns in relation to phyla characteristics, morphology, and growth locations. The results showed that green algae had the highest maximum photosynthetic O2 evolution rate (Pmax), light utilization efficiency (α), and dark respiration (Rd) among the three macroalgal phyla; the sheet-like macroalgal species had the highest Pmax, α, and Rd among the four morphological categories. The macroalgal species in the upper intertidal zone showed higher Pmax and α and lower saturation irradiance (EK) and compensation irradiance (EC) than those species in the lower intertidal location. The PCA results showed that the biomass of sheet-like macroalgal species was positively correlated with factor PC1 (50.34%), and that of finely branched species was negatively correlated with factor PC2 (25.17%). In addition, our results indicate that the light absorption and utilization capabilities of macroalgae could determine whether they could dominate the intertidal zone and that their photosynthetic characteristics could be used as a potential indicator of their biomass distribution in the Greater Bay Area. [ABSTRACT FROM AUTHOR]

The change of spatial and temporal distribution of precipitation has an important impact on urban water security. The effect of land cover land use change (LCLUC) on the spatial and temporal distribution of precipitation needs to be further studied. In this study, transfer matrix, standard deviation ellipse and spatial autocorrelation analysis techniques were used. Based on the data of land cover land use and precipitation, this paper analyzed the land cover land use change and its influence on the spatial and temporal distribution pattern of precipitation in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). The results showed that from 2001 to 2019, the area of cropland, water, barren, forest/grassland in the GBA decreased by 44.03%, 8.05%, 50.22%, 0.43%, respectively, and the area of construction land increased by 20.05%. The precipitation in the GBA was mainly concentrated in spring and summer, and the precipitation in spring tended to increase gradually, while the precipitation in summer tended to decrease gradually, while the precipitation in autumn and winter has no obvious change. It was found that with the change of land cover land use, the spatial distribution of precipitation also changed. Especially in the areas where the change of construction land was concentrated, the spatial distribution of precipitation changed most obviously. [ABSTRACT FROM AUTHOR]

Urban land optimization in urban agglomerations plays an important role in promoting territorial spatial planning to achieve high-quality development, land ecological suitability (LES) is one of the important variables influencing its urbanization and needs to be considered in urban growth simulation and modeling. This research proposed a multi-objective urban land optimization (MULO) model based on the non-dominated sorting genetic algorithm II (NSGA-II) which integrates the LES assessment. MULO starts with LES analysis based on a fuzzy analytical hierarchy process (AHP) and a minimum cumulative resistance (MCR) model. Then, two-step linear regression is used to optimize the quantity structure of built-up land. Finally, suitability and compactness are assigned to NSGA-II as objectives to obtain optimal spatial patterns. Taking the example of the Guangdong–Hong Kong–Macao Greater Bay Area, we found that all the newly added built-up land in 2030 is distributed in peri-urban areas around the original settlements, with approximate clustering in the northern part of Guangzhou and the southern part of Foshan under a balanced development scenario. This study highlights the importance of LES in urban growth modeling, and MULO can provide effective support for the spatial planning of urban agglomerations. [ABSTRACT FROM AUTHOR]

The summertime air pollution events endangering public health in the Guangdong–Hong Kong–Macao Greater Bay Area are connected with typhoons. The wind of the typhoon periphery results in poor diffusion conditions and favorable conditions for transboundary air pollution. Random forest models are established to predict typhoon-associated air quality in the area. The correlation coefficients and the root mean square errors in the air quality index (AQI) and PM 2.5 , PM 10 , SO 2 , NO 2 and O 3 concentrations are 0.84 (14.88), 0.86 (10.31 µgm-3), 0.84 (17.03 µgm-3), 0.51 (8.13 µgm-3), 0.80 (13.64 µgm-3) and 0.89 (22.43 µgm-3), respectively. Additionally, the prediction models for non-typhoon days are established. According to the feature importance output of the models, the differences in the meteorological drivers of typhoon days and non-typhoon days are revealed. On typhoon days, the air quality is dominated by local source emission and accumulation as the sink of pollutants reduces significantly under stagnant weather, while it is dominated by the transportation and scavenging effect of sea breeze on non-typhoon days. Therefore, our findings suggest that different air pollution control strategies for typhoon days and non-typhoon days should be proposed. [ABSTRACT FROM AUTHOR]

The spatiotemporal distributions and physical–optical properties of aerosols are of great scientific significance for the study of climate change and atmospheric environment. What are the characteristics of aerosols in constant high humidity? Continuous wet weather (CWW) is a special weather phenomenon that occurs frequently during the late winter and early spring in South China. In this study, the CALIPSO satellite data and the ERA5 and MERRA-2 reanalysis data are used to analyze the aerosol optical properties of a total of 68 CWW processes from 2012 to 2021 in the Guangdong–Hong Kong–Macau Greater Bay Area (GBA). We attempt to explore the variations in meteorological conditions and physical–optical properties of aerosols during the before-stage, wet-stage, and after-stage under different humidity levels. The results show that the prevailing wind direction is northeasterly and that the temperature and humidity are lower under the influence of cold high pressure in the before-stage. Moreover, the high aerosol optical depth (AOD) mainly results from regional transport. During the wet-stage, clean ocean airflow causes AOD to remain at a low level, whereas temperature and humidity increase significantly. The wet-stage ends with coldness when it is controlled by cold high pressure again. The atmospheric circulation in the after-stage is similar to that in the before-stage. However, a remarkable feature is that there is a temperature and humidity inversion layer, which results in a significant increase in AOD. This study reveals the physical–optical properties of aerosols during the three stages and the influence mechanism of meteorological factors on aerosols, which can provide a scientific basis for the study of CWW in the future. [ABSTRACT FROM AUTHOR]

Land subsidence, a common geological phenomenon in deltaic regions, poses significant risks to infrastructures, environments, and human lives. Monitoring and understanding land subsidence are crucial for establishing resilient, adaptive, and sustainable environments. In this study, a robust multi-temporal interferometric synthetic aperture radar (MTInSAR) method was employed to monitor land subsidence in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) using 541 Sentinel-1 SAR images. Spatial auto- and cross-correlation analysis were applied to select the most reasonable explanatory variables from nine candidates in each city of the GBA. City-level geographically weighted regression (GWR) models were then constructed to explore the spatially nonstationary effects of natural and human-induced factors. The findings revealed subsidence velocities ranging from 0 to 83.7 mm/yr in the GBA from 2015 to 2021, with the dominant factors affecting subsidence varying among regions. Natural and human-related factors accounted for 51.13% and 48.87%, respectively. Further analysis of representative subsidence areas highlights the importance of continuous monitoring of ground deformation using MTInSAR, region-specific land subsidence mitigation strategies, and regular maintenance of urban infrastructure. These insights are valuable for policymakers and urban planners in comprehending the complex processes underlying land subsidence and informing decision-making processes for sustainable and resilient urban development. [ABSTRACT FROM AUTHOR]

The port groups of the Guangdong-Hong Kong-Macao Greater Bay Area faces a new competitive and cooperative game structure concerning global competition, making it is necessary to build a comprehensive port coordination and development mechanism. In this study, we apply the logistics model to conduct parameter estimation and evolution trend analysis on the development of the port group and highlight that the current container throughput of the Guangdong-Hong Kong-Macao Greater Bay Area port group will reach the maximum and the new impetus is needed to push it into the next round of development and evolution. Combined with the theory of ecological population, the Lotka–Volterra model of multiple groups is introduced to study competition and cooperation game, explore their interaction, and provide quantitative support for the formation of different central port groups in the Guangdong-Hong Kong-Macao Greater Bay Area. The study provides references for strengthening the construction of complementary resources and coordinated mechanism within the port group, realizing the differential development between ports in the Guangdong-Hong Kong-Macao Greater Bay Area. [ABSTRACT FROM AUTHOR]

In the background of constructing a wold-class Guangdong-Hong Kong-Macao Great Bay Area (GBA), the growing demand for industrial, transportation and energy development in the Pearl River Delta (PRD) will put considerable pressure on improvement of regional air quality. It is important to choose a scientific development path to achieve both economic goal and air quality improvement target. This study uses scenario analysis method to construct three "industry-transport-energy" development scenarios within the region while the improvement level of air quality is simulated and analyzed. The results show that: (1) Considering the mutual constraints and influence relations between industry, transportation and energy in scenario analysis, the "industry-transport-energy" development scenario can be established to meets the same economic goal but has different development paths. (2) Along the historical track and established policy path, concentration of fine particulate matter (PM2.5) in the PRD can be reduced to 16.2 µg/m3 by 2035 as regional gross domestic product (GDP) reaching about 23.5 trillion. (3) Under the same economic goals, raising the proportion of emerging industries, freight by rail, public transport travel and non-fossil power to 95%, 10%, 73%, and 46% respectively leads to 29.6~49.2% reductions in the emissions of sulphur dioxide (SO2), nitrous oxides (NOx), primary PM2.5 and volatile organic compounds (VOCs) compared with those in 2017 that the regional PM2.5 concentration will further drop to 14.1 µg/m3. The results show that, under the constraints of economic development objectives, deepening structural adjustment can improve air quality, which gives advice for the PRD to choose its development path. Furthermore, this study can provide reference for the PRD to promote the transformation of industrial, transportation and energy development modes and structural adjustment under the dual objective of promoting the world-class bay area economic level and high-quality air level. [ABSTRACT FROM AUTHOR]