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Considering that the decision-making and planning of large-scale highway network under the condition of limited funds, there are some problems such as complex algorithm of feasible solution of maintenance scheme and low efficiency of optimisation process, a heuristic maintenance planning optimisation algorithm based on budget is introduced. This paper focuses on the performance prediction, the determination of treatment measures and the optimisation of the optimal scheme. Firstly, through the analysis of the technical process of prediction and treatment measures, the pavement performance degradation models of pavement condition index, riding quality index and rut depth index based on treatment level are established. Then, based on the characteristics of pavement performance degradation in China, the concept of maintenance benefit based on pavement performance index is proposed, and the cost-benefit optimisation model of highway asphalt pavement is established. A budget-based heuristic algorithm is proposed to solve the optimisation model for maintenance planning with budget constraints. Finally, taking Lian-Xu highway network in a case study, the optimal scheme of treatment measures and fund allocation for the maintenance section of the large-scale highway network is realised under the condition of limited funds, so as to verify the feasibility of the optimisation model. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to discuss the strengths and limitations of Zhao et al. (2022). The author also provides suggestions for future research. Design/methodology/approach: The author initially reviews prior literature studies relevant to this study, i.e. the literature on the relation between geographic proximity and information transfer/acquisition, to better position this paper in existing literature and then briefly discusses the strengths and weaknesses of this paper to provide more insights. Finally, the author presents some possible directions for future research, highlighting the importance of separately examining headquarters and plants in this research setting, and motivating future research on the development of information technology. [ABSTRACT FROM AUTHOR]

To investigate the topographic effects on precipitation in the Liupan Mountains Area of Northwest China, three micro rain radars, located at a ridge, west valley, and east valley in the area, respectively, were used to observe precipitation processes. By comparing the characteristics of stratiform precipitation at three sites, it was found that (i) the effective radar reflectivity and characteristic falling velocity of hydrometeors at the ridge and east valley were larger than those at the west valley; (ii) the diameter and density of solid hydrometeors at the ridge and east valley were slightly larger than those at the west valley; and (iii) there was also a higher occurrence frequency of larger graupel at the ridge. It is inferred that the precipitable water vapor at the ridge and east valley is richer than at the west valley, which leads to a larger aggregation efficiency and degrees of riming at the former than the latter. Besides, forced uplifting of water vapor over the mountain area around the ridge may play a part in topographic supercooling, which leads to enhanced riming of supercooled liquid water. The conclusions will contribute to a better understanding of the mechanisms of precipitation–terrain interactions in the area. [ABSTRACT FROM AUTHOR]

The Liupan Mountain (LPM) area is located on the northeast margin of the Qinghai–Tibet Plateau, which is the western part of the second ladder of China's terrain. It is also an intersection area of two air currents, which are caused by the combined action of the Qinghai–Tibet Plateau, the middle and lower levels of the westerly belt and the edge of the monsoon area. LPM is one of the main air water vapour transport pathways in Northwest China as well as a main water conservation area for nearly ten million people. Research on atmospheric precipitable water vapour (PWV) variation characteristics in LPM is beneficial for understanding the mechanisms of orographic precipitation and improving the effects of weather modification. Based on the data from 10 Global Navigation Satellite System Meteorology (GNSS/MET) stations for 6 years and the data of automatic weather stations in the LPM, the temporal and spatial variation characteristics of PWV in the LPM were analysed, and the differences in PWV in the 24 h before and after precipitation were compared in this study. The results showed that the hourly, monthly and seasonal variations in PWV displayed obvious patterns. PWV increased rapidly 10 h ahead of precipitation, while it decreased rapidly within 10 h after precipitation, which was slower than that before precipitation. In terms of spatial distribution, PWV was larger in the south than in the north and larger in the east than in the west. Although the precipitation on the LPM peak was the highest in the whole LPM area, its PWV was always the lowest, indicating that the PWV was obviously affected by the air temperature. This showed that under the same water vapour condition, precipitation was more likely to form in the area with low temperature, and the precipitation was larger, which also provided a train of thought for improving the method of artificial precipitation enhancement by using the condensation catalyst. [ABSTRACT FROM AUTHOR]

With the process of urbanization in China, the urban waterlogging caused by rainstorms occurs frequently and often leads to serious damage to the natural environment, human life, and the city economy. Rapid detection of rainstorm and urban waterlogging disasters is an essential step to minimize these losses. Weibo, a popular microblog service in China, can provide many real-time Weibo posts for rapid detection. In this paper, we propose a method to identify microblogs with rainstorm and waterlogging information and apply them to waterlogging risk assessment. After pre-processing the microblog texts, we evaluate the performance of clustering (k -means) and classification (support vector machine, SVM) algorithms in the classification task. Apart from word vector features, we also introduce sentiment and publisher features for more real-time and accurate results. Furthermore, we build a waterlogging intensity dictionary to assess the waterlogging risk from the Weibo texts and produce a risk map with ArcGIS. To examine the efficacy of this approach, we collect Weibo data from two rainstorms and waterlogging disasters in Beijing city as examples. The results indicate that the SVM algorithm can be applied for a real-time rainstorm and waterlogging information detection. Compared to official-authentication and personal-certification users, the microblogs posted by general users can better indicate the intensity and timing of rainstorms. The location of waterlogging points is consistent with the risk assessment results, which proves our proposed risk assessment method can be used as a reference for timely emergency response. [ABSTRACT FROM AUTHOR]

Two years of data on cloud condensation nuclei (CCN) measured at the Liupan Mountain (LPS) Meteorological Station from August 2020 to November 2021 were analyzed in this study. The results show that the mean annual CCN concentration was 851 cm−3 and that the mean concentration of CCN increases with the supersaturation degree. The curves of the diurnal variation in CCN concentration show one peak and one valley, which correspond to the diurnal variation in the mixed-layer height and valley wind. Regarding seasonal variations, the CCN concentration, as well as the degree of internal mixing, is higher in the spring and winter, while the degree of external mixing is higher in the summer and autumn. The transport of CCN is closely related to the wind transport evolution, and the southeast and southwest sides of the LPS station contribute more to the CCN concentration in the spring and winter due to central heating in the wintertime. Though correlations between CCN concentration and pressure are scarce, the CCN concentration and temperature (or humidity) are positively (or negatively) correlated, especially in the spring. Furthermore, the 48-h backward trajectory analysis indicates that the sources in the northwest direction are a major contributor to the CCN concentration. The pollutants mainly came from the northwest and southwest sides, according to the analysis of potential sources using the PSCF and CWT approach. The study of CCN evolution and contribution area is beneficial for further research on the physical properties of cloud droplets, the influence of mountains on CCN changes and the role of CCN in terrain cloud precipitation, which are significant for the improvement of weather modification techniques. [ABSTRACT FROM AUTHOR]

Four kinds of polymer modifier widely used in China are selected to modify the performance of asphalt mixture: styrene butadiene styrene (China), PR PLAST.S (France), Domix (Germany), and Rad Spunrie (China). The main objective of this paper is to evaluate the influence of these polymer modifiers on the performance of asphalt mixture with the dynamic modulus |E*| indicator through simple performance test. Dynamic modulus is adopted as the primary material property of hot mix asphalt mixtures in the M-E Pavement Design Guide 2002. In this study, the influences of temperature, frequency, and confining pressure on the dynamic characteristic of asphalt mixture are analyzed, and the master curves of dynamic modulus are developed and interpreted. The Witczak |E*| predictive model, which is used in the M-E Pavement Design Guide, is also applied to predict the dynamic modulus, and the predicted values are compared with the examined results. Results show that all these polymer modifiers, especially Domix, can strengthen the mixture stiffness, and that high frequency, low temperature, and high confining pressure increase the dynamic modulus of asphalt mixtures. Additionally, the Witczak |E*| model can soundly predict the dynamic modulus of polymer-modified asphalt mixtures. [ABSTRACT FROM AUTHOR]

Before (2019), during (2020), and after (2021) the COVID-19 outbreak, different response methods and measures were taken on campuses to control the spread of COVID-19 within schools. These response methods may have changed the outdoor bioaerosol characteristics, which may affect staff and student health. Therefore, we analyzed the bacterial concentrations, particle size distribution, microbial populations, exposure risks, and environmental influences of bioaerosols at a campus before, during, and after the COVID-19 outbreak. This study used eight-stage Andersen samplers to collect and analyze culturable bacteria in bioaerosols from various locations, high-throughput sequencing to analyze microbial species, principal component analysis to compare differences in samples, RDA to investigate the effects of environmental factors on bioaerosols, and hazard quotient (HQ) and BugBase to evaluate human health risks. The study findings revealed that average bacterial concentrations before, during, and after COVID-19 were 75 CFU m -3 , 136 CFU m -3 , and 78 CFU m -3 , respectively. Moreover, the average percentage of bacteria attached to PM 2.5 was 49.2%, 42.7%, and 29.9%, respectively. High-throughput sequencing revealed that species composition changed significantly during the three years of COVID-19. The proportion of Pantoea and Bacillus increased with the development of COVID-19 and these became the dominant strains after COVID-19, whereas Pseudomonas had the maximum proportion during COVID-19. Both risk assessment and BugBase phenotype prediction results indicated that the potential pathogenic risk was the highest in the outdoor environment of the campus during COVID-19 and that bioaerosol contamination was the most severe compared to the outdoor bioaerosol characteristics of the campus recovered after COVID-19.