Suppr超能文献

空气质量与交通行为:来自波兰华沙的传感器、实地及调查数据

Air quality and transport behaviour: sensors, field, and survey data from Warsaw, Poland.

作者信息

Hassani Amirhossein, Nicińska Anna, Drabicki Arkadiusz, Zawojska Ewa, Sousa Santos Gabriela, Kula Grzegorz, Grythe Henrik, Zawieska Jakub, Jaczewska Joanna, Rachubik Joanna, Archanowicz-Kudelska Katarzyna, Zagórska Katarzyna, Grzenda Maciej, Kubecka Magdalena, Luckner Marcin, Jakubczyk Michał, Wolański Michał, Castell Nuria, Gora Paweł, Skedsmo Pål Wilter, Rożynek Satia, Horosiewicz Szymon

机构信息

Stiftelsen NILU, PO box 100, 2007, Kjeller, Norway.

University of Warsaw, Faculty of Economic Sciences, Warsaw, 00-241, Poland.

出版信息

Sci Data. 2024 Nov 29;11(1):1305. doi: 10.1038/s41597-024-04111-4.

Abstract

The present study describes the data sets produced in Warsaw, Poland with the aim of developing tools and methods for the implementation of human-centred and data-driven solutions to the enhancement of sustainable mobility transition. This study focuses on school commutes and alternatives to private cars for children drop off and pick up from primary schools. The dataset enables the complex analysis of interactions between determinants of transport mode choice, revealed choices, and air quality impact. We draw on four data collection methods, namely, (i) air quality and noise sensors' measurements, (ii) in-person observations of transport behaviours, (iii) travel diaries, and (iv) social surveys. Moreover, all trip data from travel diaries are complemented with the calculated attributes of alternative travel modes. The data produced in the project can be also combined with publicly available information on air quality, public transport schedules, and traffic flows. The present data sets help to open new venues for interdisciplinary analyses of sustainable mobility transition effectiveness and efficiency.

摘要

本研究描述了在波兰华沙生成的数据集,旨在开发工具和方法,以实施以人为本、数据驱动的解决方案,促进可持续交通转型。本研究聚焦于学校通勤以及小学接送孩子时私家车的替代出行方式。该数据集能够对交通方式选择的决定因素、实际选择以及空气质量影响之间的相互作用进行复杂分析。我们采用了四种数据收集方法,即:(i)空气质量和噪声传感器测量;(ii)对交通行为的实地观察;(iii)出行日记;(iv)社会调查。此外,出行日记中的所有行程数据都补充了替代出行方式的计算属性。该项目生成的数据还可与空气质量、公共交通时刻表和交通流量等公开信息相结合。目前的数据集有助于为可持续交通转型的有效性和效率开展跨学科分析开辟新途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6561/11607380/51e1a5ff44aa/41597_2024_4111_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验