Sustainability assessment of road marking systems

被引:32
|
作者
Cruz, Marisa [1 ]
Klein, Alexander [1 ]
Steiner, Viviana [1 ]
机构
[1] Evon Resource Efficiency GmbH, Rodenbacher Chaussee 4, D-63457 Hanau, Germany
来源
TRANSPORT RESEARCH ARENA TRA2016 | 2016年 / 14卷
关键词
Life Cycle Costs; road marking; cradle to grave; cold plastics; durability;
D O I
10.1016/j.trpro.2016.05.035
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
Environmental issues are becoming increasingly important in the domestic, business and public sectors. Due to population growth and growing number of megacities, Green Public Procurements concepts is also becoming an increasing trend in the road infrastructure sector. This study assessed the environmental impacts of road markings considering the whole life cycle from manufacturing to disposal. For the correctness of the study, an external expert panel reviewed the assessment. By using the LCA-Methodology based on DIN ISO 14040 and 14044, an objective comparison of the following line markings was performed: Solvent-borne paint; Water-based paint; Thermoplastic and Thermo Spray Plastic; Cold Plastic and Cold Spray Plastic. Typical material formulations in characteristic application scenarios have been modelled using the data of corresponding official approval test certificates held by a major local manufacturer of all evaluated technologies. Empirical data was used to determine a typical service life of the various road marking systems at a typical average daily traffic of 10,000-15,000 vehicles per day. The life cycle assessment results, i.e. considering the whole life cycle from manufacturing to disposal, showed that a global warming potential reduction of more than 50% can be achieved by a more durable road marking system. The study concluded that in order to access the actual environmental impact of road markings, a lifetime evaluation including, for instance, production, application, transport, service life, and disposal must be taken into consideration. (C) 2016 Published by Elsevier B.V.
引用
收藏
页码:869 / 875
页数:7
相关论文
共 50 条
  • [1] Performance and environmental assessment of prefabricated retroreflective spots for road marking
    Burghardt, Tomasz E.
    Babic, Darko
    Pashkevich, Anton
    CASE STUDIES IN CONSTRUCTION MATERIALS, 2021, 15
  • [2] An innovative road marking quality assessment mechanism using computer vision
    Lin, Kuo-Liang
    Wu, Tai-Chi
    Wang, Yu-Ren
    ADVANCES IN MECHANICAL ENGINEERING, 2016, 8 (06):
  • [3] Improved Road Marking Detection and Recognition
    Ding, Ling
    Zhang, Huyin
    Li, Bijun
    Xiao, Jinsheng
    Lu, Shejie
    Ding, Ling
    Klette, Reinhard
    2018 15TH INTERNATIONAL SYMPOSIUM ON PERVASIVE SYSTEMS, ALGORITHMS AND NETWORKS (I-SPAN 2018), 2018, : 247 - 252
  • [4] Artificial Intelligence-Enhanced Colorimetric Assessment of Self-Cleaning Road Marking Paints
    Lima Jr, Orlando
    Segundo, Iran Rocha
    Mazzoni, Laura
    Costa, Manuel F. M.
    Freitas, Elisabete
    Carneiro, Joaquim
    APPLIED SCIENCES-BASEL, 2024, 14 (21):
  • [5] Temporary Road Marking Paint for Vehicle Perception Tests
    Katzorke, Nils
    Langwaldt, Lisa-Marie
    Schunggart, Lara
    APPLIED SCIENCES-BASEL, 2024, 14 (16):
  • [6] Temporal and Contextual Aggregation for Road Marking Semantic Segmentation
    Aizawa, Hiroaki
    Ura, Yuto
    Kato, Kunihito
    INTERNATIONAL WORKSHOP ON ADVANCED IMAGING TECHNOLOGY (IWAIT) 2020, 2020, 11515
  • [7] Preparation and Use of Materials for Color Road Pavement and Marking
    N. N. Petrukhina
    N. P. Bezrukov
    S. V. Antonov
    Russian Journal of Applied Chemistry, 2021, 94 : 265 - 283
  • [8] Preparation and Use of Materials for Color Road Pavement and Marking
    Petrukhina, N. N.
    Bezrukov, N. P.
    Antonov, S., V
    RUSSIAN JOURNAL OF APPLIED CHEMISTRY, 2021, 94 (03) : 265 - 283
  • [9] Road marking retroreflectivity study via a visual algorithm
    Chou C.-P.
    Leong K.-W.
    Chen A.-C.
    Lee Y.-X.
    International Journal of Pavement Research and Technology, 2020, 13 (06) : 614 - 620
  • [10] Upsampling Matters for Road Marking Segmentation of Autonomous Driving
    Liu, Ye
    Zhang, Xi
    Liu, Lei
    Zhang, Lei
    IFAC PAPERSONLINE, 2020, 53 (05): : 232 - 237