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The importance of the sustainability concept has gained increasing attention from scholars and practitioners. In this context, the aim of this study was to examine the determinants of intention to continue to use the new Metro in Qatar, which is considered a sustainable mode of travel. Therefore, in this paper, a special attention was paid to certain variables, such as environmental concern, perceived quality, and perceived benefits. A quantitative method approach was employed, in which data were collected based on self-administered questionnaires. A total of 1334 Qatar residents responded to the survey questionnaire, and Structural Equation Modeling (SEM) was used for hypothesis testing. The results confirmed the direct effects of perceived behavioral control, social influence, and attitudes on the intention of residents to continue to use the Metro network in their travel. Moreover, perceived behavioral control was found to play a mediating role, enhancing the indirect relationship between perceived benefits and intention to continue to use the Metro network. More importantly, environmental concerns significantly and positively affected the attitudes and perceived behavioral control of travelers; furthermore, these variables presented a mediated influence—through service quality—on the intention to continue to use the Metro network. This study enriched the sustainability behavior literature by examining the influences of crucial factors. Thus, this study is considered of great value for policy-makers who hope to maximize the awareness level of environmental sustainability among the population, in order to encourage them to embrace changes in their lifestyle towards becoming more environmentally responsible.

The COVID-19 pandemic has tremendously affected the whole of human society worldwide. Travel patterns have greatly changed due to the increased risk perception and the governmental interventions regarding COVID-19. This study aimed to identify contributing factors to the changes in public and private transportation mode choice behavior in China after COVID-19 based on an online questionnaire survey. In the survey, travel behaviors in three periods were studied: before the outbreak (before 27 December 2019), the peak (from 20 January to 17 March 2020), and after the peak (from 18 March to the date of the survey). A series of random-parameter bivariate Probit models was developed to quantify the relationship between individual characteristics and the changes in travel mode choice. The key findings indicated that individual sociodemographic characteristics (e.g., gender, age, ownership, occupation, residence) have significant effects on the changes in mode choice behavior. Other key findings included (1) a higher propensity to use a taxi after the peak compared to urban public transportation (i.e., bus and subway); (2) a significant impact of age on the switch from public transit to private car and two-wheelers; (3) more obvious changes in private car and public transportation modes in more developed cities. The findings from this study are expected to be useful for establishing partial and resilient policies and ensuring sustainable mobility and travel equality in the post-pandemic era.

To effectively address the sustainability crises our planet faces, decision-makers at different levels of government worldwide will have to get a handle on three key challenges: learning from Global North and South initiatives in tandem, taking stock of social innovations alongside technological fixes, and nurturing grassroots sustainable development initiatives next to, or in place of, top-down corporate and government interventions. Current scientific literature and grant-making institutions have often reinforced the compartmentalized fashion in which we learn and draw policy lessons from North/South, social/technical, and bottom-up/top-down sustainability initiatives, including local food system innovations. The strategic levers for global sustainable development lying in-between are thus left out. This paper uses exploratory, multiple case study analysis to address this omission. By concurrently drawing lessons from grassroots innovations in Brazil, New York, and Senegal—three profoundly different socioeconomic and geographic contexts—we identify common pressure points that have enabled local communities to drive system-wide transformations toward climate adaptation, resilience, and sustainability in the agri-food system. The findings of this paper would be of value to scholars, government officials, and community groups engaged in agri-food systems sustainability and interested in the processes of change that have allowed budding innovations to stabilize and scale up.

With China’s urban renewal, parks have developed into significant green recreational areas in cities. This paper analyzed social media texts and compared the evaluation outcomes of the 50 most popular urban parks in Beijing from various perspectives, such as the characteristics of various groups of people, park types, and the spatial and temporal distribution characteristics of recreational activities. The importance–performance analysis method was used to analyze the main factors affecting visitors’ satisfaction with parks. The research found the following: (1) Positive evaluation of parks was related to environmental construction, event organization, etc., and negative evaluations focused on ticket supply, consumer spending, etc. (2) Visitors of different genders and from different regions focused on different aspects of parks. (3) In terms of traffic accessibility, historical and cultural display, parent–child activity organization, and ecological environment experience, people had diverse demands from various types of parks. (4) People were more likely to visit parks located within the range of all green belts in springs and parks located in the second green isolation belt in the fall. (5) The number of non-holiday reviews of parks was higher than that of holiday reviews. (6) Managers could improve visitor satisfaction by improving the infrastructure and management of parks.

Virtual water flows have a profound impact on the natural water system of a country or region, and they may help conserve local water resources or exacerbate water scarcity in some areas. However, current research has only focused on the measurement of virtual water flows, without analysis of the causes of virtual water flow patterns. This study first obtained virtual water flow patterns across provinces by constructing a multi-regional input–-output (MRIO) model of the Yellow River basin in 2012 and 2017, and then analyzed its driving factors by applying the extended STIRPAT model to provide directions for using virtual water trade to alleviate water shortages in water-scarce areas of the basin. We found the following: (1) The Yellow River basin as a whole had a net virtual water inflow in 2012 and 2017, and the net inflow has increased from 2.14 billion m3 to 33.67 billion m3. (2) Different provinces or regions assume different roles in the virtual water trade within the basin. (3) There is an obvious regional heterogeneity in the virtual water flows in different subsectors. (4) Per capita GDP, tertiary industry contribution rate, consumer price index, and water scarcity are the main positive drivers of virtual water inflow in the Yellow River Basin provinces, while primary industry contribution rate, per capita water resources, and water use per unit arable area promote virtual water outflow. The results of this paper present useful information for understanding the driving factors of virtual water flow, which could promote the optimal allocation of water resources in the Yellow River basin and achieve ecological protection and high-quality development in this area.

The Hyrcanian forests of Iran are mainly managed with the single-selection silvicultural technique. Despite significant ecological benefits associated with selection cutting, this type of forest management leads towards more challenging situations where it is difficult to maintain and practice successful forestry than in even-aged systems. Therefore, this study provides relevant management tools in the form of models to estimate low growth levels in Hyrcanian forests. In the present study, estimation of the population growth rate and then the allowable cut rate of these forests using a matrix model have been calculated in the Gorazbon district. For this purpose, the data of 256 permanent sample plots measured during the years between 2003 and 2012, as well as the data recorded about the trees harvested according to the forestry plan, have been used. As a first step, the most frequently occurring tree species were divided into four groups (beech, hornbeam, chestnut-leaved oak, and other species). Compartments of the district were divided into two groups of logged and unlogged compartments. The purpose of this division was to estimate the allowable cut and compare its volume with the volumes of observed and predicted allowable cuts obtained from forestry plans. The results showed that the total operated allowable cut (OAC) in logged compartments was more than the estimated allowable cut (EAC). In unlogged compartments, the total predicted allowable cut (PAC) was more than EAC. A comparison of EAC and OAC showed that hornbeam has been harvested more than its potential. However, chestnut-leaved oak and other species group have depicted opposite trends. Our models provide important advancements for estimating allowable cut that can enhance the goal of practicing sustainable forestry.

An uncertainty analysis is required to be carried out in formal safety assessment (FSA) by the International Maritime Organization. The purpose of this article is to introduce the uncertainty analysis technique into the FSA process. Based on the uncertainty identification of input parameters, probability and possibility distributions are used to model the aleatory and epistemic uncertainties, respectively. An approach which combines the Monte Carlo random sampling of probability distribution functions with the a-cuts for fuzzy calculus is proposed to propagate the uncertainties. One output of the FSA process is societal risk (SR), which can be evaluated in the two-dimensional frequency–fatality (FN) diagram. Thus, the confidence-level-based SR is presented to represent the uncertainty of SR in two dimensions. In addition, a method for time window selection is proposed to estimate the magnitude of uncertainties, which is an important aspect of modeling uncertainties. Finally, a case study is carried out on an FSA study on cruise ships. The results show that the uncertainty analysis of SR generates a two-dimensional area for a certain degree of confidence in the FN diagram rather than a single FN curve, which provides more information to authorities to produce effective risk control measures.

In this study, the Transit Network Design Problem (TNDP) is studied to determine the set of routes and frequency on each route for public transportation systems. To ensure the important concerns of planners like route length, route configuration, demand satisfaction, and attractiveness of the transit routes, the TNDP is solved to generate a set of routes by proposing an initial route set generation (IRSG) procedure embedded into the NSGA-II algorithm. The proposed IRSG algorithm aims to produce high-quality initial route set solutions to reach better optimization procedures. Moreover, the Multi-Objective Mixed-Integer Non-Linear Programming (MOMINLP) model is proposed to formulate the frequency setting problem on each route by minimizing the total travel time of passengers (user costs) and operator costs simultaneously, while maximizing the service coverage area near all the bus stops. The MOMINLP model is solved by applying the NSGA-II algorithm to produce a Pareto front between the first and the second objective functions. The model was applied to the Fargo-Moorhead Area (FMA), a small urban area. Results were compared with the existing transit network to measure the efficiency of the NSGA-II solution methodology. The proposed algorithm was found to considerably decrease the total travel time of passengers.