A series of initiatives have been adopted in the European Union to address greenhouse gas emissions and establish a society that is resilient to climate change. In response to these initiatives, the implementation of mobility budgets offers a more precise strategy for addressing carbon footprints associated with travel. Prioritizing localized carbon footprint control, mobility budgets are calculated and customized according to distinct regions, goals, and target demographics. When prioritizing the mobility budget as the central objective in municipal transport route planning, the focus should encompass principles of fairness and equity in travel. This entails considering factors such as accessibility, variety of mobility choices, inclusivity of transportation modes, and social justice. Therefore, this article aims to formulate an enhanced activity modelling methodology that would aid data-driven decision-making in municipal transport route planning, while upholding the principles of travel fairness and equity. Тhe results obtained from scrutinizing data related to public bus services and mobile networks are presented. The evaluation of Jelgava’s city transportation network to facilitate mobility budget reduction is undertaken, and this assessment is based on an analysis of data derived from a survey on public transport use coupled with an examination of the city’s mobility budget. The research presents the communication challenges that municipalities will face in planning and implementing changes that are needed to meet the greenhouse gas emission targets and outlines the possible use of visualization tools for modelling, explanation and communication of scenarios.

Human capital development is increasingly gaining policy relevance especially with the implementation of the Sustainable Development Goals (SDGs). This study examined the correlates of human capital expenditure in rural Nigeria. General Household Survey dataset collected by the National Bureau of Statistics was used for this study. Descriptive statistical tools, principal components analysis and the Heckman selection model were used to analyse relevant data. The study found majority of the households were maleheaded, with an average size of 7 people. In terms of access to education, 62.1% of the surveyed households had access to education and spent an average of NGN 12,570.56 on education. The age of household head, access to loans, marital status and household size were the correlates of human capital expenditure in rural Nigeria. Also, school fees and registration accounted for 41.2% of households’ expenditure on education. The study found paucity of funds, low priority placed on education and low interest were the main constraints to human capital expenditure. The study recommended the design and implementation of pro-poor educational interventions especially for children from rural households. Also, there is the need for government, multilateral organisations and financial institutions to position rural households for financial inclusion.