| 摘要: |
| 为了解京津冀地区在职人员交通出行模式影响因素，深入研究交通出行中空气污染暴露水平，通过网络平台对京津冀地区在职人员展开出行模式影响因素问卷调查。利用描述性分析、独立样本t检验和完全随机的单因素方差分析，描述出行模式影响因素的重要程度，并对不同人群间的差异进行比较。结果显示：个人因素、交通因素、气象因素对选择出行模式影响的重要程度得分为2.53±0.99、3.02±1.05、3.21±1.07，气象因素是出行选择的关键影响因素。降雪、拥有交通工具、出行时长、出行距离等因素对京津冀在职人员出行选择有较大影响。不同年龄、学历、家庭年收入群体受个人因素、交通因素和气象因素影响程度存在差异，以上差异有统计学意义（P＜0.05）。开展人群交通出行模式判定研究时，应综合考虑上述各方面因素，以提高判定结果的准确性。 |
| 关键词: 时间 — 活动模式 交通出行 空气污染 |
| DOI：10.7515/JEE242004 |
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| 基金项目:国家自然科学基金项目（21906156）；中国疾病预防控制中心空气污染健康影响监测技术支撑项目 |
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| Investigation on the inf luencing factors of the travel mode of incumbents in Beijing-Tianjin-Hebei region |
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YUE Shuai, HUANG Qiang, LI Yaoling, SUN Qinghua, LI Tiantian, DU Yanjun
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1. China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
2. National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
3. Tianjin Medical College, Tianjin 300000, China
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| Abstract: |
| Background, aim, and scope The process of travel involves a high level of exposure, and understanding influencing factors of the travel mode is crucial for assessing travel exposure. This study aims to identify and quantify key factors affecting the travel modes of employees in Beijing-Tianjin-Hebei region through questionnaire survey and data analysis. The research provides a scientific basis for constructing the model simulation of travel and realizing the real-time monitoring of the travel mode of large-scale people. Materials and methods This survey utilizes a questionnaire to investigate the factors influencing travel modes of the incumbents. The respondents are employed individuals aged 16 and above, who work in the Beijing-Tianjin-Hebei region. It was a self-designed web-based questionnaire voluntarily completed by the survey participants through online platforms. Descriptive analysis, t-test, and one-way ANOVA are adopted to assess the significance of the influencing factors on travel modes. Results Among the personal factors, more respondents regard the income factor (44.60%) and the transportation factor (42.86%) to have a greater impact on travel choice. 49.19% of the respondents believed that congestion had a greater impact on travel, followed by travel time (48.07%) and travel distance (47.58%). Among the meteorological factors, 59.01% of the respondents believe that snowfall had a greater impact on travel choice, followed by rainfall (49.69%), dust (43.98%), and haze (42.48%). The respondents who do not own transportation believe that personal factors and meteorological conditions have a greater impact on their travel choices. There are differences in scores for both personal factors and traffic factors among different educational groups as well as differences in scores for traffic factors among people with different annual household incomes. Different age groups also show varying levels of influence from personal factors, traffic factors, and meteorological factors on their travel choices. The above differences are statistically significant ( P ＜0.05). Discussion Personal factors, traffic factors, and meteorological factors will affect travel choices to varying degrees. There is a finding that has been consistently confirmed in previous studies that transportation ownership and income are two most influential factors on travel modes. Although age and educational background do not significantly impact travel modes in people’s subjective consciousness, individuals may have different sensitivities to various influencing factors when comparing employees of different ages and educational backgrounds hierarchically. The Beijing-Tianjin-Hebei region experiences high congestion levels and long commuting distance, thus the congestion situation, travel distance, and purpose have a greater impact on employee travel modes. Snowfall, rainfall, and haze are meteorological factors that greatly influence employee travel patterns; this maybe attributed to the weather conditions prevalent in the Beijing-Tianjin-Hebei region. Conclusions Factors such as snowfall, means of transportation, travel time and travel distance have a great impact on the travel choices of employees in the Beijing-Tianjin-Hebei region. Moreover, groups of different ages, educational backgrounds and household annual incomes are affected differently by personal factors, traffic factors and meteorological factors. All the above factors should be comprehensively considered when determining the traffic modes of people. Recommendations and perspectives This study has some limitations. It only focuses on the factors affecting the travel patterns of working people; therefore its results may not be applicable to other groups. Additionally, sampling bias is not taken into account during distribution on an online platform which results in a low response rate from males. Future studies with larger sample sizes that include the entire population and more reasonable sampling methods can provide a more reliable basis for determining travel modes. |
| Key words: time — activity pattern travel pattern air pollution |
