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Transport is an important source of air pollution and greenhouse gas emissions. Although the applications of information and communication technologies (ICTs) for transport, also known as intelligent transport systems, are seen as having great potential to help reduce emissions from road transport, their exact impact on CO2 emissions are uncertain for decision makers from government to industry. This uncertainty hinders the deployment of such applications. Therefore there is a need for a common evaluation approach to assess the CO2 impact of ICT measures in a systemic and realistic way. In this study, a methodology framework to evaluate the impact of ICT measures on CO2 emissions is explained. The methodology was developed within the European Union FP7 project Amitran. In particular, this study focuses on the outline and the framework architecture of the methodology as well as the required interfaces between the required models. The use of the methodology is demonstrated by applying it to a use case of dynamic traffic light systems. Finally, the efforts made to validate the methodology and make it accessible to users are explained.

Abstract The concept of smart mobility and tourism has evolved from a technology-driven approach to one that focuses on sustainable solutions to address economic, social, and environmental issues. The United Nations (UN) sustainable development goals (SDGs) provide a framework for measuring and tracking progress toward sustainability goals. Key performance indicators (KPIs) are a useful tool for measuring and tracking progress towards these goals, allowing for continuous monitoring and evaluation of progress, identification of areas for improvement, and directing targeted interventions. This research aims to develop an indicators-based framework to evaluate the sustainability of smart and sustainable mobility and tourism in rural areas. Rural areas have often been neglected, or at least less prioritized, in the sustainability development of the mobility sector. The study also seeks to identify the overlap of KPIs between rural tourism and mobility, and how improved green mobility services can enhance sustainable rural tourism. Smart mobility and tourism indicators have a strong mutual relationship in rural communities, driving economic development, improving the quality of life for residents and visitors, and creating more sustainable and livable communities. Smart mobility and tourism indicators also play a crucial role in supporting the UN SDGs by providing data and insights that can inform policy and decision-making. The results of this research conclude how the target and performance setting of projects on sustainable mobility and tourism in rural communities support each other, and how they support achieving SDGs.

The Human Mobility Transition model describes shifts in mobility dynamics and transport systems. The aspirational stage, ‘human urbanism’, is characterised by high active travel, universal public transport, low private vehicle use and equitable access to transport. We explored factors associated with travel behaviour in Africa and the Caribbean, investigating the potential to realise ‘human urbanism’ in this context. We conducted a mixed-methods systematic review of ten databases and grey literature for articles published between January 2008 and February 2019. We appraised study quality using Critical Appraisal Skills Programme checklists. We narratively synthesized qualitative and quantitative data, using meta-study principles to integrate the findings. We identified 39,404 studies through database searching, mining reviews, reference screening, and topic experts’ consultation. We included 129 studies (78 quantitative, 28 mixed-methods, 23 qualitative) and 33 grey literature documents. In marginalised groups, including the poor, people living rurally or peripheral to cities, women and girls, and the elderly, transport was poorly accessible, travel was characterised by high levels of walking and paratransit (informal public transport) use, and low private vehicle use. Poorly controlled urban growth (density) and sprawl (expansion), with associated informality, was a salient aspect of this context, resulting in long travel distances and the necessity of motorised transportation. There were existing population-level assets in relation to ‘human urbanism’ (high levels of active travel, good paratransit coverage, low private vehicle use) as well as core challenges (urban sprawl and informality, socioeconomic and gendered barriers to travel, poor transport accessibility). Ineffective mobility systems were a product of uncoordinated urban planning, unregulated land use and subsequent land use conflict. To realise ‘human urbanism’, integrated planning policies recognising the linkages between health, transport and equity are needed. A shift in priority from economic growth to a focus on broader population needs and the rights and wellbeing of ordinary people is required. Policymakers should focus attention on transport accessibility for the most vulnerable.

Automation carries paradigm-shifting potential for urban transport and has critical sustainability dimensions for the future of our cities. This article examines the diverse environmental and energy-related dimensions of automated mobility at the city level by reviewing an emerging and increasingly diversified volume of literature for road, rail, water, and air passenger transport. The multimodal nature of this investigation provides the opportunity for a novel contribution that adds value to the literature in four distinctive ways. It reviews from a sustainability angle the state of the art underpinning the transition to a paradigm of automated mobility, identifies current knowledge gaps highlighting the scarcity of non-technical research outside the autonomous car's realm, articulates future directions for research and policy development, and proposes a conceptual model that contextualizes the automation-connectivity-electrification-sharing-multimodality nexus as the only way forward for vehicle automation to reach its pro-environmental and resource-saving potential.

The concept of sustainable transportation of goods as the primary paradigm for designing contemporary logistics systems assumes the use of energy-efficient and affordable modes of transport in a way that guarantees the most cost-efficient variant of the delivery scheme. That especially applies to road transport deliveries, where the number of alternatives for organizing the transportation process is numerous and the choice of the optimal solution is complicated by the multiple stochastic influences of the environment on the technological processes. In this paper, we contribute to solving the problem of shaping the sustainable delivery schemes by proposing an approach to shape the complete set of alternative transport and technological schemes for packaged cargo delivery by road transport. The developed mathematical model allows estimating the efficiency of each alternative delivery scheme for the given request and chooses the best variant that minimizes the total costs of all participants in the delivery process. The proposed algorithms are implemented in the C# programming language within the frame of a class library for modeling transport delivery processes. A case of transport processes for Delivery Ltd. (Kharkiv, Ukraine) is applied to illustrate the procedure of using the developed approach to choose the optimal transport and technological schemes for long-distance deliveries. As the result of simulating the goods transportation processes, we show the regression models that represent dependencies of the total costs for the implementation of a delivery scheme from the parameters of demand for the transportation of goods. These regression models allow estimating the most efficient delivery schemes based on the functional analysis of the obtained dependencies for the given demand parameters.

Smart sustainable cities represent a great challenge for the modern world. Generation Z (Gen Z), whose representatives are now entering adult life, will play a key role in the implementation of this concept. The purpose of this study is to investigate the nature of the relationship between the evaluation of smart mobility’s importance for a smart city and the attitudes and behaviours of Generation Z members in the context of sustainability, use of ICT, and their declarative and actual participation in smart city activities. The diagnostic survey method was used to achieve the research objective. The authors designed the questionnaire based on a literature analysis. The research sample consisted of 484 representatives of Generation Z—students of universities located in a smart city, Lublin (Poland). The collected data was statistically analysed using the following methods and statistical tests: Cronbach’s alpha, Pearson’s chi-square test for independence, symmetric measures: Cramer’s V, and the contingency coefficient. The analysis of the obtained research results confirms that the conscious approach of Generation Z to sustainability has a significant and positive impact on their evaluation of actions taken in the field of smart mobility for a smart city. A similar relationship was confirmed with regard to the relationship between ICT use and smart mobility evaluation. The significant and positive impact of young people’s participation in smart cities on their evaluation of smart mobility solutions’ importance was not fully and unequivocally confirmed. In conclusion, the Generation Z representatives’ awareness of the importance of sustainability and caring for the natural environment was confirmed by their desire to be pro-ecological in the areas of smart mobility studied in the paper. Moreover, young people who constantly use the latest technologies see their huge potential for the development of smart mobility in cities. However, despite the growing expectations of citizens’ active attitudes and their increasing participation in smart mobility development, it seems that the representatives of Generation Z are not really interested in it. Their declarations of willingness to join various opinion-forming and decision making processes do not actually transform them into active co-creators of smart mobility solutions. Changing this approach can be an educational, organisational and technological challenge for smart city authorities. The obtained research results could be used as guidelines for facilitating the search for innovative solutions in the area of smart mobility, improving the quality of life of smart city residents based on the principle of sustainable development.

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the "global carbon budget" – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of our imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2007–2016), EFF was 9.4 ± 0.5 GtC yr−1, ELUC 1.3 ± 0.7 GtC yr−1, GATM 4.7 ± 0.1 GtC yr−1, SOCEAN 2.4 ± 0.5 GtC yr−1, and SLAND 3.0 ± 0.8 GtC yr−1, with a budget imbalance BIM of 0.6 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1. Also for 2016, ELUC was 1.3 ± 0.7 GtC yr−1, GATM was 6.1 ± 0.2 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1 and SLAND was 2.7 ± 1.0 GtC yr−1, with a small BIM of −0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the higher fossil emissions and smaller SLAND for that year consistent with El Niño conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data indicate a renewed growth in EFF of +2.0 % (range of 0.8 % to 3.0 %) based on national emissions projections for China, USA, and India, and projections of Gross Domestic Product corrected for recent changes in the carbon intensity of the economy for the rest of the world. For 2017, initial data indicate an increase in atmospheric CO2 concentration of around 5.3 GtC (2.5 ppm), attributed to a combination of increasing emissions and receding El Niño conditions. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016; 2015b; 2015a; 2014; 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017.