An exploration of the relationships between socioeconomics, land use and daily trip chain pattern among low-income residents

Daily trip chain complexity and type choices of low-income residents are examined based on activity travel diary survey data in Nanjing, China. Statistical tests reveal that non-work trip chain complexity is distinctly distinct between low-income residents and non-low-income residents. Low-income residents are inclined to make simple non-work chains. Two types of econometric models, a stereotype logit model and mixed logit model, are then developed to investigate the possible explanatory variables affecting their trip pattern. The number of stops within a chain and chain types are considered as dependent variables, while independent variables include household and personal characteristics as well as land use variables. Results show that once convenient and flexible conditions are supplied, low-income residents are more likely to make multiple activities in a trip chain. Areas with high population and employment densities are associated with complex work trip chains and more non-work activity involvement

Should bike sharing continue operating during the COVID-19 pandemic? Empirical findings from Nanjing, China

Coronavirus disease 2019 (COVID-19) has triggered a worldwide outbreak of pandemic, and transportation services have played a key role in coronavirus transmission. Although not crowded in a confined space like a bus or a metro car, bike sharing users will be exposed to the bike surface and take the transmission risk. During the COVID-19 pandemic, how to meet user demand and avoid virus spreading has become an important issue for bike sharing. Based on the trip data of bike sharing in Nanjing, China, this study analyzes the travel demand and operation management before and after the pandemic outbreak from the perspective of stations, users, and bikes. Semi-logarithmic difference-in-differences model, visualization methods, and statistic indexes are applied to explore the transportation service and risk prevention of bike sharing during the pandemic. The results show that pandemic control strategies sharply reduced user demand, and commuting trips decreased more significantly. Some stations around health and religious places become more important. Men and older adults are more dependent on bike sharing systems. Besides, the trip decrease reduces user contact and increases idle bikes. And a new concept of user distancing is proposed to avoid transmission risk and activate idle bikes. This study evaluates the role of shared micro-mobility during the COVID-19 pandemic, and also inspires the blocking of viral transmission within the city.Comment: 30 pages, 7 figures, 6 table

Structural equation models to analyze activity participation, trip generation, and mode choice of low-income commuters

Low-income commuters have distinct activity-travel characteristics from non-low-income commuters. This study examines low-income commuters' activity-travel pattern for a better understanding the mechanism of activity participation and travel behaviour based on the travel survey data collected in Nanjing, China. Structural equations modelling (SEM) methodology was adopted to estimate the complex relationships among socio-demographics, accessibility, activity participation, trip generation and mode choice. Results show that strong relationships do exist among socio-demographics, activity engagement and travel behavior. Specifically, we can understand travel behaviour better by including activity participation endogenously in the model. Furthermore, it allows us to better forecast how increasing any one type of activity will affect demand for other activities, as well as trip generation and mode choice. Lastly, the results reveal the effects of accessibility variables on activity participation and travel behaviour in which population density measure has more ubiquitous effects. Findings in this study might provide insightful policy implications for improving the travel environment of the low-income commuters

Modeling mode choice behavior incorporating household and individual sociodemographics and travel attributes based on rough sets theory

Most traditional mode choice models are based on the principle of random utility maximization derived from econometric theory. Alternatively, mode choice modeling can be regarded as a pattern recognition problem reflected from the explanatory variables of determining the choices between alternatives. The paper applies the knowledge discovery technique of rough sets theory to model travel mode choices incorporating household and individual sociodemographics and travel information, and to identify the significance of each attribute. The study uses the detailed travel diary survey data of Changxing county which contains information on both household and individual travel behaviors for model estimation and evaluation. The knowledge is presented in the form of easily understood IF-THEN statements or rules which reveal how each attribute influences mode choice behavior. These rules are then used to predict travel mode choices from information held about previously unseen individuals and the classification performance is assessed. The rough sets model shows high robustness and good predictive ability. The most significant condition attributes identified to determine travel mode choices are gender, distance, household annual income, and occupation. Comparative evaluation with the MNL model also proves that the rough sets model gives superior prediction accuracy and coverage on travel mode choice modeling

Coupling Efficiency Measurements for Long-pulsed Solid Sodium Laser Based on Measured Sodium Profile Data

In 2013, a serial sky test has been held on 1.8 meter telescope in Yunnan observation site after 2011-2012 Laser guide star photon return test. In this test, the long-pulsed sodium laser and the launch telescope have been upgraded, a smaller and brighter beacon has been observed. During the test, a sodium column density lidar and atmospheric coherence length measurement equipment were working at the same time. The coupling efficiency test result with the sky test layout, data processing, sodium beacon spot size analysis, sodium profile data will be presented in this paper

The Sihailongwan Maar Lake, northeastern China as a candidate Global Boundary Stratotype Section and Point for the Anthropocene Series

Sihailongwan Maar Lake, located in Northeast China, is a candidate Global boundary Stratotype Section and Point (GSSP) for demarcation of the Anthropocene. The lake’s varved sediments are formed by alternating allogenic atmospheric inputs and authigenic lake processes and store a record of environmental and human impacts at a continental-global scale. Varve counting and radiometric dating provided a precise annual-resolution sediment chronology for the site. Time series records of radioactive (239,240Pu, 129I and soot 14C), chemical (spheroidal carbonaceous particles, polycyclic aromatic hydrocarbons, soot, heavy metals, δ13C, etc), physical (magnetic susceptibility and grayscale) and biological (environmental DNA) indicators all show rapid changes in the mid-20th century, coincident with clear lithological changes of the sediments. Statistical analyses of these proxies show a tipping point in 1954 CE. 239,240Pu activities follow a typical unimodal globally-distributed profile, and are proposed as the primary marker for the Anthropocene. A rapid increase in 239,240Pu activities at 88 mm depth in core SHLW21-Fr-13 (1953 CE) is synchronous with rapid changes of other anthropogenic proxies and the Great Acceleration, marking the onset of the Anthropocene. The results indicate that Sihailongwan Maar Lake is an ideal site for the Anthropocene GSSP

The Solar Activity Monitor Network – SAMNet

The Solar Activity Magnetic Monitor (SAMM) Network (SAMNet) is a future UK-led international network of ground-based solar telescope stations. SAMNet, at its full capacity, will continuously monitor the Sun’s intensity, magnetic, and Doppler velocity fields at multiple heights in the solar atmosphere (from photosphere to upper chromosphere). Each SAMM sentinel will be equipped with a cluster of identical telescopes each with a different magneto-optical filter (MOFs) to take observations in K I, Na D, and Ca I spectral bands. A subset of SAMM stations will have white-light coronagraphs and emission line coronal spectropolarimeters. The objectives of SAMNet are to provide observational data for space weather research and forecast. The goal is to achieve an operationally sufficient lead time of e.g., flare warning of 2–8 h and provide many sought-after continuous synoptic maps (e.g., LoS magnetic and velocity fields, intensity) of the lower solar atmosphere with a spatial resolution limited only by seeing or diffraction limit, and with a cadence of 10 min. The individual SAMM sentinels will be connected to their master HQ hub where data received from all the slave stations will be automatically processed and flare warning issued up to 26 h in advance

Should bike-sharing continue operating during the COVID-19 pandemic? Empirical findings from Nanjing, China

Introduction: Coronavirus disease 2019 (COVID-19) has triggered a worldwide outbreak of pandemic, and transportation services have played a key role in coronavirus transmission. Although not crowded in a confined space like a bus or a metro car, bike-sharing users are exposed to the bike surface and take the transmission risk. During the COVID-19 pandemic, how to meet user demand and avoid virus spreading has become an important issue for bike-sharing. Methods: Based on the trip data of bike-sharing in Nanjing, China, this study analyzes the travel demand and operation management before and after the pandemic outbreak from the perspectives of stations, users, and bikes. Semi-logarithmic difference-in-differences model, visualization methods, and statistic indexes are applied to explore the transportation service and risk prevention of bike-sharing during the pandemic. Results: Pandemic control strategies sharply reduced user demand, and commuting trips decreased more significantly. Some stations around health and religious places become more important. Men and older adults may be more dependent on bike-sharing systems. The declined trips reduce user contacts and transmission risk. Central urban areas have more user close contacts and higher transmission risk than suburban areas. Besides, a new concept of user distancing is proposed to decrease transmission risk and the number of idle bikes. Conclusions: This paper is the first research focusing on both user demand and transmission risk of bike-sharing during the COVID-19 pandemic. This study evaluates the mobility role of bike sharing during the COVID-19 pandemic, and also provides insights into curbing the viral transmission within the city