Roles of informal housing and job-housing balance in commuting carbon emissions: Evidence from big data in Shenzhen

Urban commuting's carbon footprint constitutes a major part of transport emissions. Although numerous studies have addressed commuting carbon emissions, the spatial patterns of how informal housing influences commuting carbon emissions remain unclear. Utilizing commuting big data from Baidu Huiyan platform based on the Density-Based Spatial Clustering of Applications with Noise algorithm, we conducted an extensive analysis to calculate commuting carbon emissions and performed spatial analysis of their influencing factors in Shenzhen, China. First, our findings indicate a positive relationship between housing prices and per capita commuting carbon emissions, while showing a negative impact of land use mix. These effects gradually decrease from the city center to the suburbs. Second, moderating analysis reveals that informal housing, by providing affordable housing options, enables residents to have shorter commuting distances, thereby reducing per capita carbon emissions. Third, mediation analysis highlights that increasing land use diversity and decreasing housing prices contribute to a better job-housing balance, which in turn reduces long commutes and lowers per capita carbon emissions. Drawing from these research outcomes, policymakers are encouraged to devise and implement strategies that promote the availability of affordable housing solutions and foster greater land use diversity.