Due to rapid urban expansion, urban agglomerations face enormous challenges on their way to carbon neutrality. Regarding China’s urban agglomerations, 25% of the land contains 75% of the population, and all types of land are used efficiently and intensively. However, few studies have explored the spatiotemporal link between changes in land use and land cover (LULC) and carbon storage. In this work, the carbon storage changes from 1990 to 2020 were estimated using the InVEST model in China’s Beijing–Tianjin–Hebei (BTH) region. By coupling the Future Land Use Simulation (FLUS) model and InVEST model, the LULC and carbon storage changes in the BTH region in 2035 and 2050 under the natural evolution scenario (NES), economic priority scenario (EPS), ecological conservation scenario (ECS), and coordinated development scenario (CDS). Finally, the spatial autocorrelation analysis of regional carbon storage was developed for future zoning management. The results revealed the following: (1) the carbon storage in the BTH region exhibited a cumulative loss of 3.5 × 10⁷ Mg from 1990 to 2020, and the carbon loss was serious between 2000 and 2010 due to rapid urbanization. (2) Excluding the ECS, the other three scenarios showed continued expansion of construction land. Under the EPS, the carbon storage was found to have the lowest value, which decreased to 16.05 × 10⁸ Mg in 2035 and only 15.38 × 10⁸ Mg in 2050; under the ECS, the carbon storage was predicted to reach the highest value, 18.22 × 10⁸ Mg and 19.00 × 10⁸ Mg, respectively; the CDS exhibited a similar trend as the NES, but the carbon storage was found to increase. (3) The carbon storage under the four scenarios was found to have a certain degree of similarity in terms of its spatial distribution; the high-value areas were found to be clustered in the northwestern part of Beijing and the northern and western parts of Hebei. As for the number of areas with high carbon storage, the ECS was found to be the most abundant, followed by the CDS, and the EPS was found to be the least. The findings of this study can help the BTH region implement the “dual carbon” target and provide a leading example for other urban agglomerations.

Commuting carbon emissions are an essential component of urban carbon emissions, and determining how to reduce them is an area of great debate among researchers. The current research lacks a tool and instrument that can extensively account for residents’ commuting. Traditional methods are mainly based on questionnaire surveys, which have low accuracy at spatial and temporal aspects. High accuracy carbon emission accounting methods can effectively assist urban planning and achieve precise urban emissions reductions. This study applies a taxi commuting carbon emissions accounting method divided into two main steps. Firstly, the carbon emissions of taxi trajectories are calculated using taxi trajectory data and a carbon emission calculation method developed based on VSP. Secondly, the taxi trajectory and POI data are used to filter the commuter trajectory with the help of a two-step moving search method. In this way, the taxi commuting carbon emissions were obtained. Then, the spatial distribution characteristics of residential taxi commuting carbon emissions are analysed by spatial autocorrelation tools, which could facilitate low carbon zoning management. A typical working day in Hangzhou was selected as the research object of this study. The results show that (1) morning peak commuting carbon emissions in the main urban area of Hangzhou reached 2065.14 kg per hour, accounting for 13.73% of all taxi travel carbon emissions; and evening peak commuting carbon emissions reached 732.2 kg per hour, accounting for 4% of all taxi travel carbon emissions; (2) At the grid level, the spatial distribution of commuting carbon emissions in Hangzhou shows a single central peak that decays in all directions; and (3) The results at the resident community scale show that urban public transport facilities influence resident community commuting carbon emissions. In areas such as at the urban-rural border, resident community commuting carbon emissions show high levels of aggregation, and in the main urban area, resident community commuting carbon emissions show low levels of aggregation. This study not only provides a new method of commuting investigation but also offers constructive suggestions for future carbon emission reduction under Hangzhou’s urban planning.

To understand the changing pattern of urban carbon metabolism from the perspective of urban “production–living–ecological” (PLE) space, taking Suzhou City as an example, this study constructed a carbon metabolic network model in urban PLE space, analyzed the changes of horizontal carbon flow, and evaluated the comprehensive effect of the PLE space changes using the ecological network analysis method. The results showed that the total carbon sequestration showed a fluctuating change of increasing and then decreasing, while the total carbon emissions grew dramatically. Production spaces were the key nodes for the generation of horizontal carbon flow. The exploitation relationship was the dominant ecological relationship in the network, the mutualism relationship was abundant from 2005 to 2010 and gradually decreased from 2010 to 2018, and the frequency of competition relationship appeared gradually increased. The ecological network hierarchy evolved from an irregular shape dominated by primary consumers in 2000–2005 to a pyramidal shape dominated by producers in 2010–2018 at the driving weight end, and the pull weight showed a declining trend, with pull weight of producers increasing from 1.72% to 24.33%. The results can provide a theoretical basis for planning adjustments to the city’s PLE space structure to achieve low-carbon goals.