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Previous studies show that the popularity of bike-sharing systems has a significant impact on public transit ridership, mainly reflected in two aspects: substitution and supplement. However, a mode choice of the users between bike-sharing and bus for the last-mile connection to urban rails has not been sufficiently studied using actual traffic sensor data. Therefore, in this study, the binomial choice behavior between bike-sharing and buses as a last-mile connection to urban rails in Beijing, China, is analyzed and modeled using the feeder subchain information of bus and bike-sharing for 1 week that is extracted from transit smart card data, cycling record data, and station location information data. We specifically focus on the moderate distance (0.5–3 km), within which distance the bike-sharing is a rival and suitable alternative to the bus. A binomial logit model is constructed to examine the mode choice between buses and shared bikes as a last-mile connection to urban rail. In addition to the general explanatory variables (i.e., travel distance, travel time, and cost), built environments such as housing density, land uses, and bike-lane conditions are also considered in our study. Results show that the walking distance from the metro station has a stronger effect on the users’ mode choice than the total subchain distance. A longer travel time increases the preference for taking the bus. We also find that users are most likely to choose the bus in the evening rush hours, followed by off peak times and the morning rush hours. The existence of bike lanes, especially with isolation belts alongside them, increases the probability that people choose shared bikes. As bus and bike-sharing are the two most popular and economically competitive urban rail egress modes for a moderate distance in China, understanding the determinants of mode choice contributes to better planning and operational strategies for both feeder bus and bike-sharing systems. [ABSTRACT FROM AUTHOR]

The purpose of this paper was to present the occupants' perception and preferences of thermal environments in free-running buildings in China. A study of the thermal environments in eight university dormitory buildings was conducted from September 2008 to July 2009 in Chongqing, China. A total of 1829 returned questionnaires were collected. Indoor and outdoor air temperatures, relative humidity and air velocities were measured while the questionnaire surveys were conducted. The scores were given based on the subjective scales used for the study on the students' indoor thermal perception and preferences. The accepted temperature range was 15.9-28.2°C. The preferred temperature was about 23.2°C. The neutral temperature was 22.1°C. A higher tolerance of temperature was shown by the occupants in this sub-tropical climatic region of China. The relationship between thermal preference and actual thermal sensation in different seasons was also analysed. People's air movement sensation was related to their thermal sensation. The majority of subjects (53%) were satisfied with their indoor air humidity when the thermal sensation was neutral. The relationship between humidity sensation and preferences showed that the effect of humidity on thermal comfort should not be ignored at high and low temperatures. Student dormitory buildings were used in this study to provide comparatively worse case information on occupants' thermal comfort characteristics in residential buildings in China. [ABSTRACT FROM AUTHOR]

A physiological experiment was carried out in a naturally ventilated, non-HVAC indoor environment of a spacious experimental room. More than 300 healthy university students volunteered for this study. The purpose of the study was to investigate the human physiological indicators which could be used to characterise the indoor operative temperature changes in a building and their impact on human thermal comfort based on the different climatic characteristics people would experience in Chongqing, China. The study found that sensory nerve conduction velocity (SCV) could objectively provide a good indicator for assessment of the human response to changes in indoor operative temperatures in a naturally ventilated situation. The results showed that with the changes in the indoor operative temperatures, the changing trend in the nerve conduction velocity was basically the same as that of the skin temperature at the sensory nerve measuring segment (Tskin(scv)). There was good coherent consistency among the factors: indoor operative temperature, SCV and Tskin(scv) in a certain indoor operative temperature range. Through selfadaptation and self-feedback regulation, the human physiological indicators would produce certain adaptive changes to deal with the changes in indoor operative temperature. The findings of this study should provide the baseline data to inform guidelines for the development of thermal environment-related standards that could contribute to efficient use of energy in buildings in China. [ABSTRACT FROM AUTHOR]

Under the background of "carbon peaking and carbon neutrality goals" in China, the Highway Self-Consistent Energy System (HSCES) with renewable energy as the main body has become a key research object. To study the operational status of the HSCES in a specific region and realize the economically optimal operation of the HSCES, an HSCES model in a low-load, abundant-renewable-energy and no-grid scenario is established, and a two-stage optimal scheduling method for the HSCES is proposed. Moreover, in the day-ahead stage, uncertainty optimization scenarios are generated by Latin hypercube sampling, and a definition of the self-consistent coefficient is proposed, which is used as one of the constraints to establish a day-ahead economic optimal scheduling model. Through the case comparison analysis, the validity of the day-ahead scheduling model is confirmed and the optimal day-ahead scheduling plan is attained. Furthermore, in the intra-day stage, an intra-day rolling optimization method is proposed, which can effectively track the day-ahead scheduling plan and reduce the impact of forecast errors and energy fluctuations by coordinating the unit output within the HSCES system. It is verified that the HSCES can operate economically and safely in Western China, and self-consistently, without grid support. [ABSTRACT FROM AUTHOR]

As the power generation mode with the lowest carbon emissions, wind power generation plays an indispensable role in achieving the goal of carbon neutralization. To optimize the wind power density (WPD), forecasting is crucial to improve wind power utilization and power system stability. However, because near-surface wind is characterized by notable randomness, diversity, intermittence, and uncontrollability, accurately forecasting the WPD on wind farms remains a challenging task. In this study, we attempted to improve the WPD forecast in the middle- and high-latitude regions of China (wind energy resources are abundant there) by selecting the relatively optimal planetary boundary layer (PBL) scheme, as the PBL processes exert notable effects on the near-surface wind field directly. Based on a whole month in the summer (July 2021), seven PBL schemes were compared quantitatively by using the Weather Research and Forecasting (WRF) model for a total of 70 runs (for each run, the forecast period was 3 days). The results show that no PBL schemes could always show the best performance in forecasting all variables, and the forecast accuracy showed a notable dependence on the evolution of the weather systems. Among the seven PBL schemes, the Medium-Range Forecast (MRF) scheme showed the overall best performance in forecasting the 100 m wind speed, sea level pressure, and 2 m temperature, which ensured that it had the highest forecast skill for the WPD in the middle- and high-latitude regions of China. Further analyses indicate that the background conditions were also well forecasted by the MRF scheme (ranked first or second). This was a crucial reason why the WPD forecast was the best for the MRF scheme. [ABSTRACT FROM AUTHOR]

Despite the abundance of highly sustainable bamboo, people tend to overlook its structural performance for construction purposes. This paper therefore explores the potential of bamboo architecture to develop light-weight building systems and also to create an effect of lightness. Developed by a team at the School of Architecture of Southeast University, Bamboo Canopy is an outdoor stage canopy in Anji, China, that pushes the boundaries of bamboo as a material for building woven gridshell structure. The work is designed as a long-lifespan bamboo structure, with the design team and locals participating in its construction. Positioned on a public stage, Bamboo Canopy experiments with the combination of sustainable construction and local craftsmanship to produce a highly engaging architectural intervention that activates the existing place. With its wing-like form, it invites visitors to join the performance scene--as they approach the shell, the structure reveals itself--with a 12.4-metre span and 6-metre roof overhang, the canopy covers more than 150 square metres with only 1.2 square metres touching the ground. Through analysing the form, structure and details of this experimental project, this paper clarifies not only the potentiality but also the feasibilities in using bamboo for light construction. [ABSTRACT FROM AUTHOR]

Under the background of 'the Belt and Road' initiative, the economic cooperation has great potential between China and Russia. The railway accessibility has an important influence on the economic connections of cities along the railway line. This paper studied the Sino-Russian transnational economic connection based on the railway class accessibility along Trans-Siberian railway (the transnational China railway branch line). The results are as following. First, the railway accessibility of the Chinese nodes is stronger than that of the Russian nodes, which in general displays a tendency of space attenuation from China to the Sino-Russian border, then to Russia. Spatially, the railway accessibility within the study area shows a 'High East, Low West' and 'High South, Low North' spatial pattern. The railway accessibility of the nodes, which are located at the beginning and end of the railway line, is weaker than those nodes located in the middle of the line. Second, the railway accessibility and external economic connection intensity summation of the nodes show a positive relationship along the railway line. The economic connection intensity summation of different nodes presents obvious regional differentiation. Finally, as economic connection network has evolved, the small world effect of Sino-Russian railway economic connection network becomes strong. [ABSTRACT FROM AUTHOR]

This paper aims to conduct an empirical study to evaluate the influence of built environment features and socioeconomic factors on commuters’ simultaneous choice of departure time and travel mode. Using Kunming, China, as the study region, the 2015 Regional Household Travel Survey and 2016 Point of Interest data are used in the analysis. The results show that, in addition to socioeconomic factors, built environment, such as the density of residential building, employment, and service facility are correlated with joint choice behavior. Moreover, there exist differences regarding the influence of built environment and socioeconomic factors on departure time and travel mode choice. The dissimilarity parameters show that commuters prefer to shift travel mode than departure time generally when travel condition alters. In order to examine the policy measures’ potential performance, the paper conducts simulation tests based on the Monte Carlo method. The simulation results show that congestion pricing of car travel during peak hours can reduce the number of commuting trips, and reducing travel time of public transit would be a better strategy to attract more passengers during peak hours. Moreover, reasonable land use planning, such as building more bus stops around commuters’ home location, would be a long term and fundamental approach to reduce mobile-source emissions and attract more public transit passengers. [ABSTRACT FROM AUTHOR]

Potassium (K) fertilizer plays a crucial role in the formation of the biological and economic yield of cotton (Gossypium hirsutum L.). Here we investigated the effects of the amount of K on biomass accumulation and cotton fiber quality with lowered N amounts (210 kg ha−1) under late sowing, high density and fertilization once at 2 weeks after squaring. A 2-year field experiment was performed with three K fertilizer amounts (168 kg ha−1 (K1), 210 kg ha−1 (K2), and 252 kg ha−1 (K3)) using a randomized complete block design in 2016 and 2017. The results showed correspondingly, K3 accumulated cotton plant biomass of 7913.0 kg ha−1, next to K2 (7384.9 kg ha−1) but followed by K1 (6985.1 kg ha−1) averaged across two growing seasons. Higher K amounts (K2, K3) increased biomass primarily due to a higher accumulation rate (32.68%–74.02% higher than K1) during the fast accumulation period (FAP). Cotton fiber length, micronaire, and fiber strength in K2 were as well as K3 and significantly better than K1. These results suggest that K fertilizer of 210 kg ha−1 should be optimal to obtain a promising benefit both in cotton biomass and fiber quality and profit for the new cotton planting model in the Yangtze River Valley, China and similar climate regions. [ABSTRACT FROM AUTHOR]