Under the goals of carbon peaking and carbon neutrality (“dual carbon”), achieving greater socio-economic well-being benefits within limited carbon emission constraints has emerged as a critical challenge for low-carbon development in territorial spatial planning. This study addresses this challenge by integrating the theoretical framework of “ecological well-being performance” with ecosystem service value measurement to construct a carbon emission wellbeing performance (WPCE) model, which establishes an analytical linkage between carbon emissions and the comprehensive well-being level of territorial spaces. Focusing on 64 countylevel units in Jiangsu Province—a region characterized by pronounced economic disparities and ecological diversity—the research employs spatial autocorrelation analysis and a threedimensional matrix model to explore the spatial differentiation characteristics of WPCE and classify low-carbon competitiveness types, thereby providing actionable insights for optimizing territorial spatial planning and advancing dual carbon goals. The findings reveal significant structural disparities in WPCE across the province, with Southern Jiangsu (Sunan) demonstrating a “leading” performance by generating 55.01% of the total well-being benefits while accounting for only 22.96% of provincial carbon emissions, translating to WPCE values of 291 200 yuan/ton, which starkly contrasts with central Jiangsu (suzhong) and northern Jiangsu (subei), where WPCE values drop to 84 400 yuan/ton and 65 300 yuan/ton, respectively. These regional imbalances are further compounded by distinct spatial clustering patterns, as WPCE exhibits a “south-high, northlow” distribution with dual-core agglomerations: high-high (H-H) clusters concentrate in the Pukou District-Jiangning District corridor of Nanjing and the Zhangjiagang-Jiangyin industrial belt spanning Suzhou and Wuxi, forming two innovation-driven cores characterized by advanced manufacturing and service-oriented economies, while low-low (L-L) clusters dominate Huai’an, Suqian, and surrounding areas in subei, reflecting structural challenges in ecological-economic efficiency due to reliance on energy-intensive industries and fragmented land-use planning. To systematically address these disparities, the study introduces a low-carbon competitivenesstypology based on the "emission-performance-well-being" nexus, classifying counties into four categories: High-competitive (Class I, 11 units) such as Pukou and Kunshan, which exemplify low emissions, high WPCE, and high well-being through integrated green infrastructure and circular economy practices; Opportunistic (Class II, five units) like Jiangning and Jingjiang, which exhibit mixed traits with transitional potential due to proximity to innovation hubs but face institutional barriers to decarbonization; Challenged (Class III, 27 units), representing 42.18% of counties, including Xinyi and Suyu, where high emissions and low performance stem from outdated industrial structures and weak environmental governance; and Low-competitive (Class IV, 21 units), prevalent in Subei (e. g., Suining and Xiangshui), marked by multi-dimensional deficiencies in technology, policy coherence, and public participation. Methodologically, the study advances existing approaches by integrating ecosystem service valuation—quantified through equivalence factor and functional value methods—with spatial econometrics, enabling a granular assessment of county-level welfare-carbon dynamics that captures both biophysical and socioeconomic dimensions. The three-dimensional matrix model further decouples emission efficiency, welfare output, and spatial competitiveness, offering a novel framework for diagnosing systemic bottlenecks and prioritizing interventions. For instance, the model identifies that Subei’s low WPCE is driven not only by inefficient energy use but also by undervalued ecosystem services, such as carbon sequestration in wetlands and agricultural lands, which remain excluded from regional accounting systems. Policy implications emphasize the urgency of cross-regional synergy, leveraging sunan’s technological and financial expertise to foster green infrastructure investment and knowledge transfer in suzong and subei, particularly in sectors like renewable energy integration and smart agriculture. Additionally, functional zoning strategies are proposed to designate innovation hubs in H-H clusters for piloting carbon-neutral industrial parks while establishing ecological restoration zones in L-L areas to rehabilitate degraded ecosystems and monetize their service value. The study also advocates for smart spatial governance through digital tools, such as geospatial AI platforms, to enable real-time monitoring of emissions and dynamic resource allocation, thereby enhancing adaptive management. By operationalizing the dual carbon agenda into measurable territorial strategies, this research contributes to the global discourse on sustainable spatial planning, with Jiangsu’s empirical insights offering a replicable framework for regions undergoing similar transitions. The integration of ecosystem service valuation with low-carbon competitiveness metrics not only enriches the theoretical understanding of ecological wellbeing performance but also provides policymakers with a data-driven roadmap to reconcile economic growth with emission reduction targets, ultimately fostering inclusive and resilient development pathways in the era of climate urgency.