city proper, which is indicative of the compactness and walkability of Kinshasa. The lowest two income deciles, whose population tend to live farther from the main opportunity centers, only have 20% of their population independent of travel budget to reach 10% of the total jobs in the city. Although lower than other income deciles, this share of the population is much higher than in the case of the same income deciles in Rio, which highlights the role a compact city can play in mitigating the impacts of fuel price increases on people’s ability to reach jobs, particularly the most economically vulnerable.

The excluded population is concentrated on the periphery of the city limits and stretches Eastward through the satellite settlements in Mikala and Bombala. Many of these residents would need to spend substantial amounts of time and money to reach their jobs in the city and do not have many transit services operating in these areas. There are some slightly better located, lower income areas around Selembao and Mpasa, that become excluded with high fuel price increases, and while there is not much change in the excluded population between fuel price increase scenarios, there are increases in these areas raising the excluded population in the bottom two deciles from approximately 50% to 70% of the population. These are people that have limited access to transit services and have lower incomes and are particularly sensitive to fuel price increases. While we had previously showed (See section 3.3) that the lowest income deciles were less impacted in Kinshasa, this was because many of these residents were excluded and this excluded population will increase in these deciles with the fuel price increases, suggesting that they will be disproportionately impacted without any intervention in the event a carbon tax is introduced.

As with Rio, the areas that were sensitive to fuel price increases remained the same across scenarios. However, the population living in these areas were much more sensitive to fuel price increases than their Rio counterparts, resulting in much higher travel budgets required to reach 10% of total jobs at higher fuel prices. This highlights the sensitivity of Kinshasa residents to fuel price increases, as transport is relatively expensive against incomes and all modes are dependent on fossil fuels. The only area that was relatively unaffected was parts of Socimat and Binza, where some of the wealthiest residents that cannot walk to 10% of jobs live.

# 4 Discussion and conclusion

This study evaluated how transit-based access to economic opportunities are impacted by carbon pricing in the form of a fuel-based levy in Kinshasa and Rio de Janeiro with varying travel time and budget thresholds. The goals of this study were to assess how average accessibility would be impacted in two cities of different economic status and with different spatial layouts, to understand which were the heaviest hit communities both in terms of their locations within the urban area and their economic status, to investigate how carbon pricing would impact inequality in accessibility, and shed some light on who and where the households excluded from the use of transit services are located. An overarching goal of the study was to understand whether the most commonly discussed climate policy, a carbon tax, would be regressive or progressive on accessibility to job opportunities, keeping in mind the fact that regressive policies tend to be resisted, regardless of their aggregate economic impacts.

The usage of Pareto frontiers to identify the optimal different itineraries between different origindestination pairs provides a computationally efficient way to conduct this analysis using both travel time and travel budget thresholds and could be used to assess the impacts of different pricing mechanisms or proposed new services in different cities. While GTFS feeds and socio-economic survey information that 28