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In recent years, promoting regional synergistic development has become the shared objective in city-regions during the new stages of development. This paper aims to uncover the dynamics of synergistic development in urban agglomerations by constructing an index measurement system based on four dimensions: industrial synergy, innovation synergy, infrastructure synergy, and institutional synergy. By comprehensively employing theories and methods such as "space of flow" big data analysis, network analysis, and interlocking network models, this study examines patterns and capacities of synergistic development in the Guangdong-Hong Kong-Macao Greater Bay Area. The main instances of industrial cooperation between cities are observed in Hong Kong-Shenzhen and Guangzhou-Shenzhen; capital flows primarily concentrate in Guangzhou-Shenzhen and Hong Kong-Shenzhen. Research paper and patent collaborations between cities are predominantly concentrated in Hong Kong-Shenzhen; joint laboratories are mainly established in Hong Kong-Macao and Hong Kong-Guangzhou; inter-city co-construction of higher education institutions is mainly focused on Guangzhou-Foshan and Shenzhen-Hong Kong. Infrastructure synergistic development performs best in Guangzhou-Shenzhen, Guangzhou-Foshan, and Shenzhen-Dongguan. Cross-border collaboration benefits from institutional advantages held by Hong Kong and Macao. Urban interactions with outstanding performance include Guangzhou-Shenzhen, Hong Kong-Shenzhen, Guangzhou-Foshan, Shenzhen-Dongguan. Additionally, increasing interaction trends can be observed between Guangzhou-Dongguan as well as Shenzhen-Zhuhai/Shenzen-Foshan partnerships. Understanding the typical characteristics and potential trends of synergetic development within the GBA holds significant practical value for establishing a first-class bay area along with a world-class urban agglomeration. • Concept and connotation of synergistic development in urban agglomeration area was examined. • Indicators and methods for evaluation of synergistic development in the GBA were conducted. • Patterns and capacities of synergistic development at urban scale in the GBA were explained. • Urban interaction with highest synergistic development level is Guangzhou-Shenzhen. [ABSTRACT FROM AUTHOR]

The train generates regenerative braking energy (RBE) during braking. When the RBE generated by the braking train is too large to be absorbed and utilized, the OCS voltage will rise rapidly. It may even exceed the rated voltage threshold, resulting in hidden dangers for driving safety. How to use RBE efficiently and reasonably has become a hot issue in recent years. This paper presents a metro timetable optimization method for multi-train operation to improve the RBE utilization efficiency of trains. Firstly, an energy-saving multi-objective model for multi-train operation is established, which takes the total energy consumption and travel time as the objective functions and the dwell time and departure interval as the constraints. Then, the genetic algorithm (GA) is used to generate the composition sequence of dwell time and departure interval, and the multi-node nonlinear model is used to calculate the total energy consumption of the metro line. Finally, Guangzhou metro line 7 is selected as an example to illustrate the effectiveness of the developed optimization model. The results show that the energy consumption of the whole line can be effectively reduced by adjusting the dwell time and departure interval. Meanwhile, the timetable optimization model with GA has better energy-saving effects by comparative analysis. • A metro timetable optimization method based on improved genetic algorithm is developed. • The multi-node nonlinear model is developed to calculate the total energy consumption. • The developed optimization model has better energy-saving effects than previous methods. [ABSTRACT FROM AUTHOR]

The energy crisis caused by climate change is the most significant challenge of the 21st century. Single-objective and multi-objective optimization studies for buildings often only consider the building itself, without considering the impacts of climate change. However, in the future, energy-efficient design and appropriate operating parameters will be crucial considerations in the face of global climate change. This paper aims to discuss the impact of climate change in the humid-hot region over the past 60 years on the energy consumption of office buildings and propose countermeasures. Firstly, the meteorological data of Guangzhou from 1960 to 2020 is statistically analyzed, and four typical meteorological years and corresponding air conditioning design days are established. Secondly, Energyplus is used to simulate the building's energy consumption, and the energy consumption factors are analyzed for sensitivity using jEplus. Finally, a multi-objective optimization is performed using jEPlus + EA with the Non-dominated Sorting Genetic Algorithm (NSGA-II). The results found that climate change led to a significant increase in the duration of high outdoor temperatures during summer. Specifically, the daily dry-bulb temperature for air conditioning design increased by 0.4–0.7 °C, and due to climate change, the energy consumption of the office building increased by about 4.6 %. The main factor affecting the cooling energy consumption in summer was the indoor cooling set point (8.29%–30%), infiltration air volume (1.0%–8.6%), fresh air volume (3.2%–16.06%), the glazing solar transmission rate (1.25%–9.0%), building orientation (0%–1.43%), and relatively small influence of envelope insulation performance. The operation scheme determined by multi-objective optimization can reduce the cooling energy consumption of the building by 10.6%–16.8%, which can mitigate the rise in energy consumption resulting from climate change to a greater extent. [Display omitted] • Discuss the impact of climate change over the past 60 years on the energy consumption of office buildings. • There was a significant increase in the duration of high outdoor temperatures during the summer. • Multi-objective optimization is performed using jEPlus + EA. • Climate change caused energy consumption to increase by about 4.6 %. • Optimal solutions can reduce the cooling energy consumption of the building by 10.6%–16.8%. [ABSTRACT FROM AUTHOR]

As the financialization of carbon emission right, developing effective carbon asset trading strategy is important for both investors and regulators. Traditional trading strategy based on technical analysis is hardly profitable due to high complexity inherent in carbon markets. In order to increase investment returns and reduce risk in carbon market, this paper introduces PSO-VMD-DRL, an innovative carbon asset trading strategy that integrates signal decomposition technology and deep reinforcement learning (DRL). Firstly, the carbon price is decomposed into multiple components by variational mode decomposition (VMD) optimized through particle swarm optimization (PSO) to extract frequency features and reduce noise. Then state representation of the environment (state space) is constructed based on the components and transaction data. Finally, deep reinforcement learning (PPO, A2C, DDPG) are performed separately based on state space to learn optimal trading strategy. Empirical studies based on the data from carbon markets of Hubei and Guangzhou validate that PSO-VMD-DRL can adapt to carbon asset with the better profitability and risk resistance. The PSO-VMD-DRL outperform the other comparison strategies with superiority in all evaluation indices, achieving annual return of 21.39%, 17.67%, 25.50% and 46.34%, 44.55%, 43.03% in carbon market of Hubei and Guangzhou. [ABSTRACT FROM AUTHOR]

Unsustainable production and consumption patterns in China's metropolitan areas have resulted in an increase in the production of waste materials for which local governments have to find solutions, one of which is the construction of waste incineration power plants. These plans often meet resistance from residents who fear negative environmental impacts. This paper presents an in-depth study of how Chinese local governments responded to an environmental conflict regarding the construction of an incineration power plant in Panyu district, Guangzhou City, PRC, using a typology to identify and categorize these government responses. The empirical analysis shows that local governments engage in various new ways of dealing with these conflicts. The article aims to enhance insight into the response of Chinese local governments to these conflicts and provide building block for further research. [ABSTRACT FROM AUTHOR]

It is important for Chinese cities to advance sustainable energy consumption and ensure that they achieve their carbon emission peak and carbon neutrality. This paper develops a comprehensive assessment of the spatial variability and influencing factors of the quantity of household energy consumption per capita in mega-cities. Based on microlevel household survey data from Guangzhou, Guangdong Province, China (N = 1082), we analyze the spatial effects and factors of urban residents' energy consumption. A spatial econometric model with four spatial weight matrices is employed, and the nested spatial weight matrix, which holds practical economic and geographical significance, is set. We find that (1) the quantity of energy consumption per capita of all households in Guangzhou is 189.57 kgce/year and shows a spatial difference, with 177.5 kgce/year in the central urban area and 203.47 kgce/year in the outskirts urban area. In particular, households in the outskirts of urban areas present a higher percentage of "high" and "medium-high" energy consumption per capita than those in central urban areas. (2) The quantity of household energy consumption per capita of urban residents is characterized by significant spatial correlation and agglomeration, with "high-high" and "low-low" agglomeration in central urban areas. (3) The household labor force, the housing area and household income are the core factors that drive the quantity of household energy consumption per capita, while the region and educational level are also main factors. We observe the diversity of the energy transition by comparing the patterns of the quantity of household energy consumption per capita within the city. A comprehensive picture of the diversity underlying the energy transition applied across cases can be distilled. [ABSTRACT FROM AUTHOR]

Simulating this ecological risk transmission process helps to judge the key path and propose the accurate urban risk control measures. This paper develops an urban ecological risk transmission conceptual framework based on Bayesian Network to quantify the non-linear transmission paths via HA (human activity) — ES (ecosystem service) — ER (ecological risk). Ecosystem services are used as ecological risk measurement endpoints to quantify service provision and possible adverse effects from human activities. Direct and indirect impacts of urban human activities that threaten ecosystem services were considered. Nine cities in the Pearl River Delta (China) are selected as a case to simulate the ecological risk transmission process. Results show that: (1) Zhongshan and Guangzhou tied for the city most at ecological risk and Foshan jumped to the city with the highest ecological risk after considering the impact of pollution; (2) After analyzing the sensitive of human activities to ecological risks, the key risk transmission path of each city can be judged. There are three types of key paths: pollution dominant path (including Guangzhou, Foshan, Dongguan and Zhuhai), ES dominant path (including Shenzhen, Zhongshan and Jiangmen) and dual dominant path (including Zhaoqing and Huizhou); (3) Buildup area, afforestation area and wetland protection & restoration investment are the top three key human activities that impact the urban ecological risk. Adjusting these key variables can be simulated to effectively reduce the urban ecological risk. The model can be used as a useful tool to guide policy and risk management decisions, and to engage and negotiate with stakeholders with different views. [ABSTRACT FROM AUTHOR]

The analysis of historical changes, exploration of driving forces, and understanding of future changes in ecological land can provide a scientific basis for sustainable development in rapidly urbanizing areas. In this paper, with the support of GIS spatial analysis, the landscape index, the Moran's index and multiple logistic regression models, we constructed an integrated ecological land analysis framework, which included historical trajectories, driving factors and future simulation projections. A comprehensive analysis was carried out in the case city of Guangzhou, China, and the results showed the following: (1) In the past 25 years, the ecological land of Guangzhou has shown a decreasing trend, with its area decreasing by 59.7 km2. Dramatic changes occurred between 2000 and 2010. (2) The quality of the urban ecological environment has two opposite trends at the same time: improvement and degeneration. The agglomeration of ecological land is weakened, heterogeneity is enhanced, and the diversity and uniformity of landscape are slightly reduced. (3) Altitude, GDP per unit area, and distance to the nearest road were the main driving factors for ecological land changes. To alleviate the pressure of urban expansion on ecological land, the downtown, Huangpu and Nansha districts must pay more attention to improving the level of intensive land use in the future. The study results have reference value for the Department of Guangzhou Urban Planning and offer an analysis framework for similar studies. • A comprehensive technical framework for urban ecological land assessment was constructed. • The spatial-temporal distribution and change trajectory of ecological land in Guanzhou was detected and modeled. • DEM altitude, economic development, and distribution of roads influence the ecological land changes. • The downtown, Huangpu and Nansha districts will face severe pressure in terms of ecological land protection. [ABSTRACT FROM AUTHOR]

Through dynamic analysis of the train-track-bridge (TTB) system, vehicle induced vibration responses of a rail transit continuous rigid bridge on Guangzhou Metro Line 14 are obtained. Aiming to expand the frequency bandwidth and harvest vehicle-induced vibration energy efficiently from different vibration peaks, 3 types of multi-frequency electromagnetic vibration energy harvesters (EM-VEHs) with 4 submodules are designed in this paper. Based on this, energy harvesting and conversion performance of the proposed multi-frequency EM-VEHs are fully investigated. Energy harvesting analysis show that the harvested vibration energy of each type is up to 90% in the first 50 s during the 5-min train running period. Average power output for 24 h of the 3 types of EM-VEHs are 0.91 W, 1.41 W and 0.84 W in sequence, each of which could meet the normal working requirements of the above sensor unit. Compared with SDOF EM-VEH, all the 3 types of MDOF devices win perfectly in harvesting vibration energy efficiency from different vibration peaks, energy conversion stability with no decrease in power output. Due to the unneglectable mass of the lead blocks in the 4 submodules, the EM-VEHs perform an additional function of being tuned mass damper. Proper matching between the gross mass and vibration energy harvesting efficiency is significant during the design procedure of multi-frequency EM-VEH. • Proposed 3 types of multi-frequency EM-VEHs to harvest vehicle induced vibration energy at different frequency peaks. • Stable and continuous vibration excitation is critical for the working efficiency of EM-VEHs. • The proposed EM-VEHs are improved by orders of magnitude in energy harvesting efficiency than most exsiting EM-VEHs. • Proper matching between the gross mass and energy harvesting efficiency is considerable while proposing an MDOF EM-VEH. [ABSTRACT FROM AUTHOR]

Load matching is an inevitable problem that restricts the development of photovoltaic (PV) system used in buildings. The objective of this paper is to solve this problem by conducting a load matching assessment and optimization of PV system in different climate zones of China. The influences of the tilt angle, orientation, PV plot ratio and building height on the achievement of zero energy buildings (ZEBs) were evaluated. The PV potentials of roofs and facades were analyzed and optimized based on self-sufficiency and self-consumption. Net load variance and the maximum electricity import were employed as indices to evaluate the performance of PV systems in different climate zones of China. The results of the load matching assessment show that electricity generations from roof PV systems in low-rise buildings can meet most of the energy demand (at least 70%) in all climate zones of China. East and west facades of mid-rise buildings have an advantage over south façades in Kunming and Guangzhou in terms of load matching. It is necessary to combine roofs, south, east and west facades to meet the ZEBs requirement of for high-rise building. When the heating/cooling demand is dominant, the tilt angle should be higher/lower than the latitude of the specific location. This research will be helpful in designing building PV systems in different climate zones of China. Load matching analysis is helpful in designing building PV system in different climate zones of China. The results show that east and west facades of mid-rise buildings have an advantage over south façade in Kunming and Guangzhou. It is necessary to combine roof, south, east and west facades to meet the requirement of ZEBs for high-rise building. Image 1 • Load matching with PV system were analyzed for zero energy buildings. • PV potential were investigated based on self-sufficiency and self-consumption. • The optimal combinations of PV system were obtained in different climate zones. • East and west facades have advantages over south façade in Kunming and Guangzhou. [ABSTRACT FROM AUTHOR]

In recent years, the sustainability of many metropolitan areas has been degraded due to rapid economic development. Zengcheng, as a satellite city of Guangzhou, has been developed as a demonstration area for improving regional urban sustainability and expanding the overall ecological capacity of Guangzhou. In this paper, an integrated evaluation based on emergy synthesis theory was conducted to examine whether Zengcheng can fulfill its role in providing ecological services and improving regional sustainability. Based on emergy indices, we assessed the sustainability of the social, economic, and ecological subsystems of Zengcheng. The results showed that the total emergy used (U), the emergy used per person (Ucap) and the empower density (ED) of Zengcheng were all at a low level compared to a selection of developed cities. However, the Ucap and the ED were higher than the national average. The emergy investment ratio (EMR) of Zengcheng was lower than all the selected areas in this study, suggesting that the development of Zengcheng is mainly reliant on the consumption of local resources. The Emergy Sustainable Index (ESI) of Zengcheng is 0.72 which is lower than many highly developed areas. Furthermore, three categories of ecological services of Zengcheng were also evaluated based on emergy. The results show that the total emergy-dollar value of ecosystem services and the ecological services empower density (ESED) in Zengcheng were $6.17E+09 and 1.20E+13 sej/m 2 , respectively. This indicates that Zengcheng can provide substantial ecological services and increase the overall ecological capacity of the Guangzhou region. [ABSTRACT FROM AUTHOR]