Downbursts belong to sudden, local, and strong convection weather, which present significant destruction for structures. At any given time, there are approximately 2000 thunderstorms occurring on the Earth. Many studies have investigated the effects of downbursts on different structures. However, the extensive range of varying wind field parameters and the diverse representations of wind speeds render the study of structural wind effects complex and challenging under downbursts. This study firstly reviews the research of wind field properties of downbursts according to four common approaches, and the major findings, advantages, and disadvantages of which are concluded. Then, failure analysis of transmission line systems under stationary and moving downbursts is explored. The article also reviews the wind pressure on the roof of different kinds of low-rise buildings, and some dominant parameters, namely roof slope, distance of building from downburst center, wind direction angle, and so on, are discussed. Moreover, the wind effects caused by downbursts on high-rise buildings and some specialized structures are also considered because more and more wind hazards are related to downbursts. Finally, the limitations of the current study are pointed out, and recommendations for further research are given for the accurate assessment of the effects of wind on buildings, with a view to providing safer and more economical wind-resistant design solutions for structures.

The urban atmospheric boundary layer (UABL) is complex due to the heterogeneous underlying city surface. The nine anemometers installed at different heights along the 325 m meteorological tower provide an opportunity to carry out a refined study of wind properties in the UABL in central Beijing, China. Based on the recent 5-year high-resolution measured data, in total, 229,488 10-min length segments of wind records related to each anemometer are reliable for further analyses. Accordingly, the statistical properties of the wind speed and direction are first analyzed to present the local wind climate in a comprehensive way. Moreover, the pattern of the wind profiles related to two typical synoptic intense events are illustrated in order to give a preliminary perspective, then the statistical properties corresponding to a series of intense windstorms are described. Here, the deviations in the wind direction occur between 200 m and 280 m of the atmosphere, which might be due to the existence of an Ekman spiral; besides this, the laws of wind profiles based on open terrain are not suitable for the UABL, and the aerodynamic characteristic parameters of the UABL based on vertical stratified structures have to be considered. The results contribute to the establishment of revised models for the wind profile and are useful for the further understanding of the structure of UABL wind.

Understanding the characteristics of downburst wind fields is crucial for studying structural resistance to downbursts. Based on measured data from the 325 m meteorological tower in Beijing, this paper investigates the spatiotemporal evolution of mean and fluctuating winds during a non-stationary downburst. Key wind field parameters such as the mean wind speed, turbulence intensity, turbulence integral length scale, probability density function, power spectral density, evolutionary power spectral density, and gust factor are statistically analyzed. The results show that the wind speed of downburst undergoes rapid changes, with wind direction significantly influenced by outflow vortices at low altitudes and relatively stable at higher altitudes. When the event happens, the temperature decreases sharply. The mean wind speeds and turbulence integral length scale of the downburst exhibit pronounced “nose-shaped” profile characteristics at the moment when peak wind speed occurs. The turbulence intensity at lower altitudes predominantly exceeds that at higher altitudes. The probability density distribution function of the reduced fluctuating wind speed matches the standard Gaussian distribution curve. The fluctuating wind speeds of the downburst exhibit significant non-stationary characteristics, with their energy mainly distributing in the period of rapid change of wind speed in the time domain and concentrating in the vicinity of 0–0.1 Hz in the frequency domain. The gust factor reaches its maximum at the moment when the peak wind speed occurs.

The understanding of wind field characteristics during thunderstorms is key to structural design for resistance to thunderstorms. In this paper, the directional thunderstorm wind model is adopted to analyze the characteristics of vertical variations of the wind field in a typical thunderstorm event in the Beijing urban area, based on the measured data. First, the longitudinal and lateral fluctuating wind speed components were decoupled and the change of direction was obtained. Then, variation of the wind speed, wind direction, turbulence intensity, turbulence integral length scale, and gust factor with the height and time were studied. The measured thunderstorm wind spectrum and the coherence function of horizontal longitudinal reduced turbulent fluctuations were analyzed and compared with empirical models. The results showed that the wind speed profile presented an obvious “nose shape” near the peak wind speed. The longitudinal turbulence integral scale was larger than the lateral one. The Von Karman spectrum is relatively effective in fitting the thunderstorm wind spectrum. Compared with synoptic winds, the gust factor during the pass of thunderstorm wind is larger, so it seems necessary to consider the influence of thunderstorm wind in engineering design.

With the proposal of the dual carbon goals, it is of great significance to identify the causes of carbon emissions and reduce carbon emissions directly. There is a lack of analysis on the causes of carbon emissions considering the coupling effect of multiple factors and regional heterogeneity. The causes of carbon emissions are examined from multiple perspectives utilizing the panel data spanning from 1997 to 2022, encompassing 30 provinces in China. To further analyze the causes of carbon emissions, an enhanced feature and regularized gradient boosting tree (EG-Tree) model is constructed, and a scoring method for the tree structure is proposed. The coupling effect of multiple factors are analyzed such as coal, coke, crude oil, gasoline, kerosene, diesel oil, fuel oil, liquefied petroleum gas, natural gas, etc., on the carbon emission intensity of various industries and their regional heterogeneity. The results show that: (1) The EG-Tree model constructed in this study could accurately analyze the causes of carbon emissions under the coupling of multiple factors based on the cumulative iterative feature branching contribution values (impact factors), with an average model fitting precision of 0.30. This means the carbon emission intensity values were predicted by various industries in different regions based on different energy consumption levels and industry-specific carbon emissions, compared with the carbon emission intensity values calculated using the carbon emission measurement dataset. (2) The consumption of coal and coke has a significant impact on the average carbon emission factors of various industries, with values of 7139.95 and 7217.05, respectively. The consumption of natural gas and liquefied petroleum gas has a smaller impact on the average carbon emission intensity of various industries under the EG-Tree model with corresponding carbon emission intensity impact factors of 5057.90 and 2789.57, respectively. (3) The Northeast region is a low-carbon area, while the East region is a high-carbon area, with total carbon emissions of 2,238,646.60 million tons and 5,566,314.00 million tons of CO₂, respectively. The Northeast region has the lowest pollution intensity for heating and cooling, with carbon emissions of 155,661.73 million tons of CO₂; the industrial carbon emissions in the East region are relatively high at 1,623,835.62 million tons of CO₂. The research findings of this study are beneficial for relevant departments to focus on the main impact factors of carbon emissions in different regions and industries, and to develop targeted emission reduction policies.