Although global cities only covered 0.63% of global terrestrial area, 55% of global people lived there and 80% of economic activities occurred there (Liu et al., 2018). More convenient conditions attracted a huge number of people immigrating into cities, and thus global urban area has been expanding since last a few decades (Li et al., 2020). This increasing trend has been continuing; it was reported that 68% of global people would live in cities by 2050 and global urban area would expand to 3.6 million km2 by 2100 (Gao and O'Neill, 2020; UN, 2018). Nevertheless, this accelerating urbanization and anthropogenic activities have brought great challenges for urban development, such as accelerated demands for affordable housing and well-connected transport system (Guo and Wilson, 2011; Zhang et al., 2003). Consequently, traffic congestion at present turns to be a serious problem in cities, especially for megacities and populated cities (Dadashova et al., 2021).
Traffic congestion can greatly increase travel time and fuel consumption, which lead to a great deal of economic costs (Chen et al., 2020; Litman, 2013; Winston and Langer, 2006). For example, traffic congestion in the USA led to 8.8 billion more hours and 3.3 billion more gallons of oil consumption in 2017, which totaled to 23.7 billion dollars of economic costs (Lasley, 2019); the total economic costs of traffic congestion could amount to 0.9% and 1.3% of their GDPs in Germany and France (Nash, 2003). Besides, traffic congestion can result in serious air pollution and huge greenhouse gas emissions, with about 2–4 folds of CO, HC and NOx emissions than normal levels (Sjodin et al., 1998); moreover, traffic congestion at peak hours could lead to 14.3%~30.4% of more pollutant emissions (Wen et al., 2020). Therefore, it is of great significance to pay more attentions on traffic congestion and its associated economic losses.
Climate condition would have impacts on local traffic systems, and bad weather (like rainfall) could cause more serious traffic congestion (Papakonstantinou et al., 2020). Due to more slippery roads and worse visibility, rainfall can reduce car speed and traffic capacity, and thus it could exacerbate traffic congestion to some degree (Ivey et al., 1975). Compared with sunny days, light rainfall can reduce 2 ~ 13% of freeway speed and 4 ~ 10% of freeway capacity, but they could increase to 17% and 30% under heavy rainfall (FHWA, 2012; Smith et al., 2004). Therefore, heavy rainfalls would cause more serious traffic congestion. Global climate change would bring more intensive extreme weathers in future (Guhathakurta et al., 2011), and it was estimated that China will face 2–3 times more extreme rainfall events due to climate change (Wang et al., 2020a). Combined urban development, population increase and more extreme rainfalls, cities will undoubtedly and inevitably face increased traffic burdens and more serious traffic congestion in future, leading to more economic losses (Kc et al., 2021). Hereby, it is significant to explore how rainfall influence traffic congestion and its associated economic losses, especially considering future climate change.
Previous studies have already achieved a lot on traffic congestion in cities, like their influences, social and economic costs, mitigation practices and so on (Guo et al., 2015; Sarzynski et al., 2016; Sweet, 2014). However, these studies were mainly based on field investigation in specific cities (Ali et al., 2014), and it was hard to explore their differences among cities. Thanks to the development of big data, traffic congestion can be evaluated by Taxis' GPS trajectory data (Kan et al., 2019) and car-sharing data (Sun et al., 2018). Thus, some websites (like AutoNavi Map) provided some valuable traffic congestion information, based on their travel data. Based on data from the AutoNavi Map, Li et al. (2019) explored how urban landscape influenced traffic congestion. In spite of some achievements, limited studies focused on exploring differences of traffic congestion among cities, as well as their associated economic costs. Besides, it is also highly urgent to study how rainfalls influence urban traffic congestion among cities at present and in future.
As a highly-populated area, the Beijing-Tianjin-Hebei region (BTH) is facing serious traffic congestion; traffic congestion in Beijing, one of the most congested cities in China, resulted in 58 billion yuan of economic losses in 2010 (Chen et al., 2020; Litman, 2013; Winston and Langer, 2006). What’s more, the extreme rainfall event on July 21st in 2012 caused transportation paralyzed in Beijing, leading to a total economic loss of 10 billion yuan. Thus, it is of high importance to explore how rainfalls influence traffic congestion and its associated economic losses in the BTH region at present and in future. However, limited studies focused on above issues, and thus our study aimed to bridge above gaps, based on detailed hourly traffic congestion data from the AutoNavi Map. More detailed, we aimed (1) to illustrate their differences of urban traffic congestion among cities and among time windows in the BTH region; (2) to explore how rainfall influence traffic congestion there; (3) to estimate the recurrent traffic congestion cost and the extra economic loss due to rainfall in the BTH region, comprising direct economic, social and environmental costs; (4) and finally to discuss how climate change influence traffic congestion and its associated economic losses in future.