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Rural mobility inequality is an important aspect of inequality-focused Sustainable Development Goals. To reduce inequality and promote global sustainable development, more insight is needed into human mobility patterns in rural areas. However, studies on rural human mobility are scarce, limiting our understanding of the spatial and social gaps in rural human mobility and our ability to design policies for social equality and global sustainable development. This study, therefore, explores human mobility patterns in rural China using mobile phone data. Mapping the relative frequency of short-distance trips across rural towns, we observed that geographically peripheral populations tend to have a low percentage of short-distance flows. We further revealed social gaps in mobility by fitting statistical models: as travel distances increased, human movements declined more rapidly among vulnerable groups, including children, older people, women, and low-income people. In addition, we found that people living with low street density, or in rural towns in peripheral cities with long distances to city borders, are more likely to have low intercity movement. Our results show that children, older adults, women, low-income individuals, and geographically peripheral populations in rural areas are mobility-disadvantaged, providing insights for policymakers and rural planners for achieving social equality by targeting the right groups. [ABSTRACT FROM AUTHOR]

This study compares the atmosphere-only HighResMIP simulations from FGOALS-f3-H (FGOALS) and MRI-AGCM3-2-S (MRI) with respect to tropical cyclone (TC) characteristics over the Western North Pacific (WNP) for the July–October months of 1985–2014. The focus is on investigating the role of the tropical easterly jet over the Western Pacific (WP_TEJ) in modulating the simulation biases in terms of their climatological distribution and interannual variability of WNP TC genesis frequency (TCGF) based on the analysis of the genesis potential index (GPI). Results show that the two models reasonably capture the main TC genesis location, the maximum center of frequency, and track density; however, their biases mainly lie in simulating the intense TCs and TCGF distributions. The MRI better simulates the wind-pressure relationship (WPR) but overestimates the proportion of super typhoons (SSTYs). At the same time, FGOALS underestimates the WPR and the proportion of SSTYs but better simulates the total WNP TC precipitation. In particular, FGOALS overestimates the TCGF in the northeastern WNP, which is strongly tied to an overestimated WP_TEJ and the enhanced vertical circulation to the north of its entrance region. In contrast, the MRI simulates a weaker WP_TEJ and vertical circulation, leading to a negative TCGF bias in most of the WNP. Both models exhibit comparable capability in simulating the interannual variability of WP_TEJ intensity, but the composite difference of large-scale atmospheric factors between strong and weak WP_TEJ years is overestimated, resulting in larger interannual anomalies of WNP TCGF, especially for FGOALS. Therefore, accurate simulations of the WP_TEJ and the associated oceanic and atmospheric factors are crucial to further improving WNP TC simulations for both models. [ABSTRACT FROM AUTHOR]

This correction notice is for an article titled "Unravelling the spatial directionality of urban mobility" published in Nature Communications. The correction addresses an error in the introduction of the original article, where the concept of the population mobility vector (PMV) was introduced without a proper citation. The corrected version now includes a citation to reference 21. The correction has been made in both the PDF and HTML versions of the article. The authors of the article are Pengjun Zhao, Hao Wang, Qiyang Liu, Xiao-Yong Yan, and Jingzhong Li. [Extracted from the article]

The household is usually an essential element for activity-based travel decision-making of individuals. From the perspective of household context, activities are often allocated to individuals based on their household roles, thereby affecting individuals’ travel behavior. By defining the household role using spatial-temporal constraints which are associated with individual activities and household activities, this paper investigates the travel mode choice of individuals considering the effect of different household roles. The descriptive statistics of the household roles and their corresponding travel mode choice are presented using the data from Kunming, China. The statistical results show that the modal splits between females and males perform a significant difference in the same household roles. Furthermore, the travel mode choice of females and males are estimated separately using multinomial logistic regression model. The results show that those who face more space-time constraints associated with household tasks are less willing to travel by car. While with the increase of commuting constraints, household heads, especially female-heads, tend to use car to meet the travel demands of household activity. Besides, individuals’ age, education level, the number of cars and bikes in household also have a significant impact on travel mode choices of individuals. [ABSTRACT FROM AUTHOR]