As urbanization continues to accelerate worldwide, the consequential rise in CO₂ emissions has caused substantial environmental challenges. Urban regeneration has emerged as a promising approach to reducing carbon emissions and developing low-carbon cities. Even though both urban regeneration and carbon emissions reduction have been researched from various perspectives, a thorough review is still required to completely reveal their multifaceted relationship. Based on 231 papers published between 2001 and 2023, a bibliometric analysis was conducted to understand the overall trajectory and main focus of the existing research. Then, we qualitatively analyzed the main findings from bibliometric results in terms of key regeneration elements, specific regeneration strategies, research methodologies, as well as research trends and agendas. The results indicated that research in this field is gradually becoming more specialized and comprehensive. Buildings and energy have always been two key urban regeneration elements and research hotspots. Additionally, as a systematic project, reducing carbon emissions requires further exploration of other regeneration elements’ contributions and their interactions in the urban system, which needs the corresponding support of more specific regeneration strategies and research methodologies. These findings can advance the development of innovative and impactful pathways for low-carbon oriented urban regeneration, leading ultimately to sustainable cities.

The status of soil microbiome has become global concern for earth sustainability. The pool size of microbial biomass carbon (MBC) provides a basic tool to generally assess the soil microbes related to soil health in global terrestrial ecosystems. Albeit, the variation of topsoil MBC pool remains largely uncertain with land use patterns across China. In this study, data of topsoil (0−20 cm) MBC measurements were retrieved from 468 observations published in Chinese journals from 2000−2022. With linking to soil organic carbon, microbial quotient (MQ) was calculated as a portion of MBC content as a percentage of SOC content. Meta-analysis showed that, on average, topsoil MBC pool was the greatest (470.8 mg·kg⁻¹) for forest land but the lowest (179.9 mg·kg⁻¹) for dry croplands. MQ was higher (2.7%) for rice paddies with waterlogged conditions than for other land use types (2.0% on average). Integrating the values from all land use patterns, mean MBC pool of China’s topsoil was quantified as 323.2−384.3 mg·kg⁻¹ while MQ as 1.7%−2.3%, at 95% confidence. Upscaling with the area data of the land use types allowed a prediction of an overall MBC pool of China’s topsoil of 635.8 Tg C (in a range of 614.4−657.1 Tg C). MQ was on average of 2.1% for whole China's topsoil, being prominently higher than the reported global mean of 1.2%. Furthermore, topsoil MBC contents exerted a wide variation (CV of 40%) while MQ showed a much narrow variation (CV of 19%) with land use types across mainland China. The MBC pool was affected significantly by edaphic factors related to organic matter status such as SOC, total N, C/N ratio and bulk density. For environmental drivers, however, MBC was significantly, but less strongly impacted with mean annual precipitation while MQ significantly but slightly influenced with mean annual temperature. The former could be generally ascribed to soil-resource dependent ecosystem productivity though the latter could be related to temperature-sensitive of organic carbon decomposition and microbial carbon assimilation through SOC turnover in soil. To predict a topsoil MBC pool, a statistical linear model was developed with three key edaphic attributes of bulk density, organic carbon and total nitrogen plus one climate attribute of mean annual precipitation, which had an explanatory of 48% of the total variance for soils with varying land conditions. Our study highlights the importance of integrating soil microbial biomass carbon pool into global biogeochemical models of carbon cycles with strong reference to microbial community structure and activity across hierarchical scales.

Developing low-carbon cities (LCC) is a strategic measure to mitigate climate change. This study proposes to diagnose LCC performance from a dual perspective in order to identify problematic areas for improvement. The dual perspective refers to management processes (including Plan, Do, Check, and Act) and low carbon city performance dimensions (namely, energy structure, economic development, production efficiency, urban population, water carbon sink, forest carbon sink, green space carbon sink, and low carbon technology). A diagnosis model has been introduced based on the dimension-process dual perspective. The model has been applied for diagnosing the LCC performance in four municipalities in China. It has been found that the performance in the economic development dimension is much better than in other LCC dimensions, and the performance in Plan and Do stages are better than that in other stages. This reflects the traditional practice in China where more attention and resources are often given to urban planning and implementation with less attention to checks and feedback. The findings from this study provide important references for both further research in the discipline and practical application in promoting LCC in other cities.