Elsevier

Journal of Transport Geography

Volume 59, February 2017, Pages 49-58
Journal of Transport Geography

Impacts of adverse weather on Arctic road transport

https://doi.org/10.1016/j.jtrangeo.2017.01.007Get rights and content

Highlights

  • Quantifies, using structural equation modelling, how weather impacts traffic volume

  • Differentiates between freight and passenger traffic in a rural arctic context

  • Reveals low day-to-day variations in traffic volume due to adverse weather

  • Suggests incorporating the impact of weather on traffic in transport models

  • Suggests extensions of the current cost-benefit analyses tool

Abstract

Arctic regions are geographically peripheral and characterized by cold climate, constantly changing weather conditions and strong seasonal variations. This article examines variations in road traffic volume due to adverse weather in an arctic region, a topic that has received little attention in the transportation literature. The subject of the case study is northern Norway's Saltfjellet mountain pass, which is part of European Highway 6 (Ev6). A succinct econometric structural equation model was used to test hypotheses regarding the impacts of fluctuations in temperature, precipitation and wind speed on passenger and freight traffic volumes. The findings indicate that there was some reduction in traffic volume during adverse weather, particularly with respect to passenger traffic. However, the day-to-day variations in traffic volumes were relatively low at the studied section of road, although it is known that generalized transport costs increase significantly in adverse weather due to delays related to poor driving conditions and closed roads. The studied region is rural with limited access to alternative routes or transport modes, thus making this portion of the road particularly important for the communities in the region. Hence, the road users have few other options than using this high-cost road in order to maintain their activities. The use of standardized parameters in transport models to predict the effect of adverse weather on traffic volume, would not be appropriate in the studied context. However, it is recommended that the benefits of reducing the extra costs that adverse weather impose on traffic are estimated and included in road-project assessment tools to capture the burden and strain imposed on road users. This to ensure that appropriate decisions are made regarding the development and improvement of transportation facilities, particularly in rural areas.

Introduction

One of the main objectives of countries with long-term transport plans is to have efficient and reliable transportation systems (see, for instance, the Norwegian National Transport Plan (2013) and National Plan for Sweden's Transport System (2010)). However, extant literature indicates that transport systems are vulnerable to adverse weather,1 as such conditions may reduce the efficiency and reliability of the system (Datla and Sharma, 2008, Keay and Simmonds, 2005, Khattak et al., 1998, Lam et al., 2008, Maze et al., 2006). To facilitate decision makers in improving the operations and maintenance of existing infrastructure and in planning new infrastructure and to identify adaptation and mitigation strategies to address weather-related problems of today and those of the future, it is critical to know and understand how weather conditions affect transportation (Jaroszweski et al., 2010, Jaroszweski et al., 2013). Many road sections in Norway are particularly vulnerable to adverse weather conditions because of the combination of challenging topography, vast mountain areas, deep fjords and adverse climatic conditions. A consensus among climate researchers reveals that the global weather-related problems are not likely to diminish in the near future (Doran and Zimmerman, 2009). Moreover, they project that in Norway, the intensity and duration of precipitation are expected to increase, and while temperatures may increase and result in less snow in lower areas, it is expected that the mountain areas will still receive heavy precipitation in the form of snow during the winter months (NOU 2010: 10, 2010). The probability of an increased number of events with strong winds do also exists.

The aim of this article is to investigate the variability in road traffic volume under varied weather conditions on a rural road section, the Saltfjellet mountain pass, which is part of the main transport corridor of European Highway 6 (Ev6) that connects southern and northern Norway. A better understanding of how adverse weather impacts traffic in the rural context will help policy makers make better decisions regarding the development and improvement of transportation facilities in these areas. Only two alternatives exist to the part of Ev6 studied, and both have significantly higher transport costs. Similar to many other mountain passes, the Saltfjellet mountain pass is often affected by adverse weather that impairs driver ability and causes road closures, both of which increase travel time and thereby reduce arrival time reliability (Bardal and Mathisen, 2015). Assuming that drivers seek to minimize their transport costs, the hypothesis is that adverse weather conditions affect the number of drivers who choose to use this mountain pass. In addition, the literature indicates that various types of road transport respond differently to adverse weather (Button, 2010, De Jong et al., 2010, Graham and Glaister, 2004, Litman, 2013). Accordingly, the two research questions explored in this study are as follows:

  • 1.

    How does adverse weather affect road traffic volume on the Saltfjellet mountain pass?

  • 2.

    Do passenger and freight traffic volumes differ in their sensitivity to adverse weather on the Saltfjellet mountain pass?

Though the impact of weather on road transportation has been the subject of much research, the variations in context are limited. The majority of the extant studies have been conducted in densely populated areas where congestion and road capacity are the primary problems, while travel concerns in rural areas have received limited attention (Böcker et al., 2013). One important feature of rural areas is that they often lack, or have limited access to, alternative transport modes and routes. Therefore, interruptions in the available transport system may have substantial impacts on transport costs as well as on competition in the product, service and labour markets in these areas (Laird and Mackie, 2009). The climate zones covered in the literature are also limited. For example, all of the mountain passes in Norway have polar climates,2 a climate zone that is virtually ignored in the literature (Böcker et al., 2013). Though roads in mountain areas in some other countries, such as the northern parts of the US, Canada, and some EU countries, experience similar winter problems, the areas are not classified as polar climates. In these cases, local knowledge of the relationship between transportation and weather conditions is essential because this relationship may differ extensively between locations (Böcker et al., 2013, Liu et al., 2014).

This article is structured as follows. In Section 2, the theoretical background and hypotheses regarding the relationships between traffic volume and adverse weather are provided. The case study and data are then described in Section 3. Section 4 presents the model, and Section 5 discusses the results. Concluding remarks and possible implications are provided in Section 6.

Section snippets

General theory

In this study, several factors are found to affect traffic volume (Button, 2010, Litman, 2013). Time costs and costs related to discomfort and risk are among the most important factors. These are followed by the high price and limited availability of other transport modes and routes at the section of road studied herein. Additionally, the amount and type of freight transport in the region and the quality of road maintenance and operations affect traffic volume on the studied mountain pass. It

The Saltfjellet mountain pass

The road section studied herein is part of European Highway 6 (Ev6), which is located at the Arctic Circle and connects the cities Mo i Rana and Fauske in the county of Nordland (see Fig. 2 for a map of the area). It is the main transport corridor between northern and southern Norway, and as such, it is important for the transport of perishable goods such as fresh fish from the fisheries along the coast, etc. The highest altitude on the road between Mo i Rana and Fauske is  700 m above sea level.

The model

With respect to count data, the regression method of choice is the Poisson regression (Bhaskaran et al., 2013). However, for counts as large as those in this study (the number of vehicles per day on the Saltfjellet mountain pass), normal distribution can be approximated based on the central limit theorem, which enables the use of other econometric approaches (Wooldridge, 2013). Structural equation modelling (SEM) is selected as the statistical modelling technique because of its ability to

Results and discussion

When estimating the theoretical model, several of the paths were found to be insignificant.16 Therefore, most of the insignificant paths were removed in the final model. Goodness-of-fit statistics, summarized in Table 3 (Kline, 2011), all indicate that the model is appropriate with the exception of the Chi-square statistic (Hooper et al., 2008). However, the Chi-square statistics are derived under the assumption that the observed variables are

Conclusions and implications

The results reveal that the effects of adverse weather conditions on traffic volume on the studied road section are limited compared to the results from other studies and that freight traffic volume is less affected than passenger traffic volume. Earlier studies have demonstrated that it would be appropriate to include the effects of adverse weather in transport models in order to predict traffic volume more precisely. However, the results from this study imply that standardized parameters from

Acknowledgements

This work has been funded by the County Administration of Nordland (273/09) and the Norwegian Public Roads Administration (NPRA). The NPRA has kindly provided data on traffic and regularity. The author thanks Finn Jørgensen, Terje Andreas Mathisen and the anonymous reviewers of this journal for their valuable comments on previous versions of the article.

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