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• The proposed tropical cyclone model is completely driven by a set of environmental variables. • This model reproduces the spatial and temporal characteristics of observed tropical cyclones. • The model achieves remarkable balance between computational complexity and efficiency. • This model will provide decision-makers with valuable information regarding potential wind-induced hazards. • When future climate data are fed into this model, the impact of climate change on tropical cyclones can be evaluated. This paper presents an environment-driven tropical cyclone (TC) model for the Western North Pacific basin, which comprises a revised Poisson regression genesis model, a tailored beta-advection track model, and a fast intensity model. The TC model reproduces the temporal and spatial distributions of genesis events, the motion pattern of tracks, as well as the intensity evolutions along tracks. Risk analyses for Hong Kong and along the southeast coastline of mainland China demonstrate that this model can simulate extreme TC events with high fidelity. And the Gaussian mixture model outperforms the Frank Copula in approximating the joint distributions of the annual maximum wind speeds and the corresponding wind directions. This model is driven by a set of environmental variables including relative vorticity, relative humidity, sea surface temperature, vertical wind shear, potential intensity, sub mixed layer depth stratification, mixture layer depth and so on. This enables the model to not only reproduce historical records, but also make predictions for future TC behaviors under climate change with combination of global climate models. Besides, the computational efficiency of the TC model is comparable to traditional purely statistical models. The proposed model can also be coupled with other natural hazard models to conduct multi-hazard analysis. [ABSTRACT FROM AUTHOR]

Radiative cooling coating technology is gaining increasing attention in the context of mitigating urban heat island and tackling global climate change. This paper is concerned with the development of an inorganic geopolymer-based radiative cooling coating using red mud, incorporating varying sizes of TiO 2 and hollow glass beads. The developed colored coating demonstrates its radiative cooling capability in reducing the surface temperature by harnessing the potential of red mud. The physico-chemical properties, surface morphology, and element distribution of the coating were characterized by XRD, FTIR, TG-DAT, SEM and EDS. The coating exhibited lower UV (0.0844) and visible reflectance (0.5275) but high NIR reflectance (0.7536), as well as high infrared emissivity of 0.9455, enabling a red color with a CIE value of L* = 74.56, a* = 9.55, and b* = 11.98, and a maximum temperature reduction of 7.3 °C under the climate of Hong Kong. Additionally, the skid resistance, abrasive resistance and adhesion strength of the proposed coating could meet the requirements of standards, indicating a great potential for footway applications. [ABSTRACT FROM AUTHOR]

Carbon emission trading mechanism is an important market-based instrument to address global climate change. The auction ratio and price of carbon emission allowances (CEA) are cores of the carbon emission trading mechanism. What combination of CEA auction ratio and auction price is most conducive to carbon emission reduction for emission control enterprises? There are still relatively few studies conducted on this issue, and there is no clear answer from the views of theory and practice. In this paper, the AIM/Enduse model was used to analyze the changes and differences of installed power capacity, power supply, energy consumption and carbon emissions in the Guangdong-Hong Kong-Macao Great Bay Area (GBA) with different combinations of CEA auction ratios and prices. Moreover, the best pathway of energy transition was explored in the power industry of the GBA, and the best combination of CEA auction ratios and prices was identified in the GBA. The results show that: (1)The carbon emission constraint starts to work only when the auction ratio of CEA is increased to 50% and the auction price is increased to 60 CNY/ton (Scenario p 3). When the auction ratio of CEA is 100% and the auction price reaches 120 CNY/ton (Scenario p 5), a low-carbon transition of the power sector in the GBA can be achieved. (2) Under scenario p 5 , the total cost of power transition rises and then falls. And the cost of carbon in the power sector increases exponentially as the auction ratio of CEA and the auction price rise. However, the growth in the cost of power supply is relatively flat, which shows that appropriate carbon trading mechanism can improve the economic benefits of power sectors. With the increase of installed capacity of clean low-carbon energy generation and power supply, as well as the decrease of local power cost in the GBA, the proportion of outsourcing power can be appropriately reduced in the future, with an aim to reduce the external dependence of electricity to ensure the security of energy supply. In the end, it suggests that cities in the GBA should give full play to their regional advantages and establish a unified carbon emission trading market in the GBA as soon as possible. This study provides a theoretical basis for the supplementation and improvement of China's carbon emission trading mechanism. • What is the best combinations of CEA auction ratios and auction prices in the GBA? This paper gives a clear answer. • The best transition pathway of the power industry under technological progress and carbon trading policy was suggested. • With the decrease of local power cost, the proportion of outsourcing power can be appropriately reduced in the future. • Provides a theoretical basis for the supplementation and improvement of China's carbon emission trading mechanism. [ABSTRACT FROM AUTHOR]

• A multi-model and multi-method ensemble approach for wind resource projection is proposed. • Future wind potential in Hong Kong is assessed for the first time. • Robustness of the climate change signal is evaluated. • An increase in wind power density during summer (+23.7 %) and a decrease during autumn (–15.1 %) in 2081–2100 are projected for SSP5-8.5. Harvesting renewable wind energy is among the most cost-efficient means of reducing carbon emissions and achieving carbon neutrality. However, wind resource is susceptible to climate change impacts since the global temperature increase will reshape atmospheric circulation patterns. To facilitate the evaluation of fine-scale wind energy potential under climate variability, this paper proposes and validates a multi-model and multi-method ensemble wind resource projection approach. Then this approach is utilized to investigate the future variation of wind resources in Hong Kong based on the combined use of global climate models from Coupled Model Intercomparison Project Phase 6 and long-term observations from meteorological stations. It is found that there is a significant increase in future wind resources during summer, while a remarkable decline is projected during autumn. Nevertheless, the variations of wind resources in winter and spring are relatively insignificant. The outcomes of this study are expected to offer a framework for fine-scale wind resource assessment under climate change, and facilitate the economic and risk assessments of future wind farm projects. [ABSTRACT FROM AUTHOR]