The rapid urbanization in China has resulted in significant differences between urban and rural areas. The emergence of urban villages is inevitable in this context, for which complex problems regarding land use, industrial management and ecological environment have arisen. This study performed a case study on a typical urban village, by assessing heavy metal pollution and ecological risk in soil. It detected a total of 80 basic units through portable X-ray fluorescence (XRF) instrument. A total of 25 high-risk contaminated points were selected, sampled and analyzed in laboratory as confirmation. The results showed the mean concentrations of Pb, Cu, Zn and Ni in soil were significantly higher than background values. Pb, Zn and Ni showed obvious pairwise correlation, and the high-value zones could be attributed to automobile traffic and industrial activities. In addition, the pollution problem is complicated by a combination of agricultural activities, the absence of clear division between different functional zones, as well as a general lack of environmental awareness. All of these lead to increased ecological risk and are a serios threaten to public health.

Land use, as one of the major sources of carbon emissions, has profound implications for global climate change. County-level land-use systems play a critical role in national carbon emission management and control. Consequently, it is essential to explore the spatiotemporal effects and optimization strategies of land-use carbon emissions at the county scale to promote the achievement of regional dual carbon targets. This study, focusing on Shaanxi Province, analyzed the spatiotemporal characteristics of land use from 2000 to 2020. By establishing a carbon emission evaluation model, the spatiotemporal effects of county-level carbon emissions were clarified. Utilizing Geodetector and K-means clustering methods, the driving mechanisms and clustering characteristics of county-level carbon emissions were elucidated, and optimization strategies for land use carbon emission were explored. The results showed that during 2000–2020, land use in Shaanxi Province underwent significant spatiotemporal changes, with constructed land increasing by 97.62%, while cultivated land and grassland were substantially reduced. The overall county-level carbon emissions exhibited a pattern of North > Central > South. The total carbon emissions within the province increased nearly fourfold over 20 years, reaching 1.00 × 10⁸ tons. Constructed land was the primary source of emissions, while forest land contributed significantly to the carbon sink of the study area. Interactions among factors had significant impacts on the spatial differentiation of total county-level carbon emissions. For counties with different types of carbon emissions, differentiated optimization strategies were recommended. Low-carbon emission counties should intensify ecological protection and rational utilization, medium-carbon emission counties need to strike a balance between economic development and environmental protection, while high-carbon emission counties should prioritize profound emission reduction and structural transformation.

County-level ecological space, as a crucial level in optimizing the land spatial system, plays a pivotal role in “undertaking superior planning and guiding subordinate implementation”. From a spatial optimization perspective, effectively implementing the dual-carbon goal by increasing carbon sinks in specific ecological space units is essential. This study focused on 107 districts and counties in Shaanxi Province, China, aiming to construct a comprehensive multivariate identification system for ecological space under the dual-carbon target based on an analysis of the spatiotemporal distribution characteristics and driving factors of county-level carbon sinks. Furthermore, by analyzing the ecological spatial distribution pattern, carbon sink land structure, and county clustering characteristics, the study explored differential optimization strategies for ecological spaces of different county types to enhance carbon sinks in the ecosystem. The results demonstrated that: (1) From 2000 to 2020, the total carbon sink in Shaanxi Province exhibited an initial increase followed by a decrease, with a decline from 864.39 × 10⁴ t to 863.21 × 10⁴ t. The county-level distribution of total carbon sink displayed significant spatial heterogeneity, with an overall pattern of south > north > central. (2) The interaction among factors enhanced the explanatory power for spatial differentiation of county-level carbon sinks compared to individual factors, exerting an important impact on the spatial distribution pattern of carbon sinks. (3) The distribution of ecological space in Shaanxi Province was highly uneven, with the core ecological space primarily concentrated in the southern and north-central regions. The proportions of low carbon sink (Type I), medium carbon sink (Type II), and high carbon sink (Type III) counties were 35.51%, 18.69%, and 45.80%, respectively. For different types of county-level ecological spaces, this study proposed a differentiated optimization strategy aimed at reducing carbon emissions and enhancing carbon sink. The results will provide theoretical and technical support for regional ecological construction and land spatial optimization, holding significant practical implications for achieving the dual-carbon goal and addressing climate change.

Ecological carbon sinks, pivotal in mitigating carbon emissions, are indispensable for climate change mitigation. Counties, as the fundamental units of ecological space management, directly impact the achievement of regional dual carbon targets through their levels of carbon sink. However, existing research has overlooked the intricate relationship between terrain features and ecological spaces, leading to a lack of specific guidance on enhancing the carbon sink for counties with diverse landform characteristics. This study focused on Jingbian County (Loess Plateau), Fuping County (Guanzhong Plain), and Chenggu County (Qinba Mountains), each characterized by distinct landform characteristics. This study proposes a comprehensive identification model for ecological space within the context of dual carbon targets. Utilizing this model as a basis, the land use structure, carbon sink potential, and ecological spatial patterns of different counties were systematically analyzed. The results indicated substantial disparities in land use structure, carbon sink capabilities, and ecological space distributions among counties with different landform types. Specifically, Jingbian County was predominantly covered by grassland, exhibiting a moderate overall carbon sink capacity, with baseline ecological spaces playing a significant role. Conversely, Fuping County, dominated by cultivated land and construction land, exhibited the lowest carbon sink capacity, with non-ecological spaces accounting for a staggering 85.93%. Chenggu County, on the other hand, was characterized by the dominance of forestland, with nearly all its carbon sink originating from forestland, and core ecological spaces occupying a leading position. Tailored optimization strategies are recommended based on varying terrain features: Jingbian County should prioritize ecosystem restoration and conservation, while Fuping County should concentrate on optimizing land use structure and promoting urban greening. Reinforcing the carbon sink capacity of existing ecosystems is crucial for Chenggu County. This study broadens the perspective on ecological space optimization and provides scientific guidance and pragmatic insights tailored to regional disparities, which are instrumental in assisting various regions to achieve their dual carbon targets.