## 1 Introduction  
Recent decades have witnessed accelerating global climate change, with atmospheric CO\({}_{2}\) concentrations reaching a record high of 422.5 ppm in 2024 [1]. Urban areas have emerged as the primary drivers of greenhouse gas (GHG) emissions, and account for approximately 75% of global fossil fuel-related CO\({}_{2}\) emissions [2]; this trend is expected to intensify with ongoing urbanization. From 1978 to 2023, China's urban population surged from 17% to 67% (National Bureau of Statistics of China, 2024), consequently driving profound transformations in economic growth, industrial structures, and consumption, all of which have contributed to surging carbon emissions. Consequently, China remained the world's largest carbon emitter in 2023, ultimately generating 12.6 billion tons of CO\({}_{2}\) (34% of global emissions) (IEA 2024) [2]. The interplay between urbanization and carbon emissions underscores the urgency of urban carbon mitigation governance, particularly in developing economies. To address the climate challenge, China has strategically implemented green public procurement (GPP) as a key policy instrument that supports its UNGA (2020) commitment to achieve carbon peaking and neutrality by 2030 and 2060, respectively. As a demand-sideinstrument, GPP leverages the government's market power to systematically reorient supply chains (SCs) toward low-carbon alternatives through market mechanisms. According to China's Ministry of Finance (2024), annual expenditure on energy- and water-saving products has reached USD 5.1 billion, which represents 83.9% of the total procurement in these categories [3]. The design of GPP combines demand guarantees with price signals to embed decarbonization incentives in value chains, thus creating an integrated climate governance framework that aligns public procurement power with market-based incentives. Despite the growing recognition of the potential of GPP, its impact on reducing urban carbon emissions intensity remains underexplored. The current literature on carbon emissions is divided into two streams: (1) studies on socioeconomic determinants (e.g., economic development [4; 5] and industrial structure [6; 7]), digital finance [8], green innovation [7], and urbanization [9; 10; 11], with emerging attention to spatial spillovers [9]), and (2) analyses of formal regulatory mechanisms (e.g., emission standards, carbon pricing, and cap-and-trade systems). The latter has sparked vigorous debate: [PERSON] (2008) argues that due to design flaws, implementation issues, or corporate evasion, regulatory policies may fail to meet emissions reduction targets [12], while [PERSON] (2015) counters with the institutional solution of \"climate clubs\" to address collective action dilemmas [13]. Recent empirical studies have enriched the discourse. [PERSON] et al. (2023) demonstrate the synergistic effects between digital finance and environmental regulations in reducing industrial carbon intensity [14], and [PERSON] and [PERSON] (2023) identify an inverted U-shaped relationship in which regulatory policies initially increase but ultimately decrease emissions intensity [15]. However, these studies overwhelmingly focus on formal regulatory tools and ignore the roles of market-driven tools, such as GPP. Emerging micro-level studies have provided clues for revealing the relationship between GPP and carbon emissions. [PERSON] et al. (2023) demonstrates the dual-channel influence of GPP on residents' green consumption behavior through direct regulatory mechanisms (price and information regulation) and indirect peer effects [16]. [PERSON] et al. (2024) highlight its risk-mitigation effects on corporate green innovation [17], and [PERSON] et al. (2025) reveal its capacity to alleviate financing constraints and enhance environmental, social, and governance (ESG) performance [18].