High indoor air quality is crucial for the health of human beings. The purpose of this work is to analyze the synergistic effect of particulate matter 2.5 (PM_2.5) and carbon dioxide (CO₂) concentration on occupant satisfaction and work productivity. This study carried out a real-scale experiments in a meeting room with exposures of up to one hour. Indoor environment parameters, including air temperature, relative humidity, illuminance, and noise level, were controlled at a reasonable level. Twenty-nine young participants were participated in the experiments. Four mental tasks were conducted to quantitatively evaluate the work productivity of occupants and a questionnaire was used to access participants’ satisfaction. The Spearman correlation analysis and two-way analysis of variance were applied. It was found that the overall performance declined by 1% for every 10 μg/m³ increase in PM_2.5 concentration. Moreover, for every 10% increase in dissatisfaction with air quality, productivity performance decreased by 1.1% or more. It should be noted that a high CO₂ concentration (800 ppm) has a stronger negative effect on occupant satisfaction towards air quality than PM_2.5 concentration in a non-ventilated room. In order to obtain optimal occupant satisfaction and work productivity, low concentrations of PM_2.5 (<50 μg/m³) and CO₂ (<700 ppm) are recommended.

Shared autonomous vehicles (SAVs) will be an important force to in reshaping urban morphology. The high operation rate and sharing degree of SAV are considered to result in a great reduction in parking area in future cities. Parking space is now a huge and widely distributed urban stock space type, which is bound to become a major challenge and opportunity for sustainable urban renewal in the digital era. Based on the SAV scenario, this paper reviews the current research on the sustainable renewal of urban public parking spaces, and proposes the four key issues involved: how much to renew (i.e., demand forecast analysis), when to renew (i.e., update time series evaluation), what to renew (i.e., function replacement decision) and how to update (i.e., design empirical research). Furthermore, it puts forward a preliminary idea on, and constructs a research framework for, the sustainable renewal methods of parking space under the SAV scenario. Finally, the theoretical, practical and policy implications of the research on sustainable renewal methods of urban public parking space are discussed. It will have great reference value for the redevelopment and reuse of the urban space types including fragmented, widely distributed and large-scale.

Campus spatial organization has potential impact on the multidisciplinary innovation (MDI). This research aims to establish an evaluation theory and a method for MDI adaptability of campus spatial organization. Based on the literature review, it first proposes theoretical assumptions regarding the correlation among MDI abilities, social networks, and spatiotemporal behaviors of individuals on campus. Then, data on the three aspects mentioned above was collected through online survey which was conducted from February 4th to March 15th, 2020. A total of 524 valid responses were obtained from 572 undergraduates and graduates of various majors in Zijingang Campus (East) of Zhejiang University. The correlation mechanism of these aspects was empirically analyzed by structural equation model (SEM). By integrating individual data, the research generated three overall networks whose nodes are linked according to spatial proximity, behavior routine, and disciplinary connection, respectively. Furthermore, an evaluation method is proposed for MDI adaptability of the campus spatial organization, which is based on the comparison of the structural similarity of the nodes in different networks. Accordingly, the evaluation results were validated by expert ratings and user satisfaction. Finally, design strategies for the renovation of an innovative campus are discussed.

Hangzhou is located in hot summer and cold winter climate zone, which is the non-central heating area in China. The indoor thermal comfort is usually poor in winter. Residents in this region have their own adaptive comfort behaviors. The air conditioner heating time, setting temperature and window opening habits of households in Hangzhou were investigated on large scale questionnaires. Heating and windows opening behaviors were clustered by SPSS. One household was selected for the simulation of indoor energy consumption in winter. Through the combination of different behavior modes, energy-saving pattern was found. The energy saving potential of different behavior was also clarified. The simulation results are helpful to guide Hangzhou residents to behavior adaptively to reduce air conditioning energy consumption and improve indoor thermal environment quality.