DOI: 10.3390/land15102001 ISSN: 2073-445X

Temperature as a Nonlinear Moderator of Land-Use Carbon Emissions Across China’s Temperature Zones: Drivers and Differentiated Governance

Yiqun Li, Jian Yu, Li Fang, Yuqing Miao, Lisha Tao, Yuesheng Lin

Land-use carbon emissions are typically analyzed within administrative or economic regions; however, natural temperature gradients may modulate how socioeconomic and policy drivers translate into emissions. Using China’s land-use, energy, and meteorological data (1990–2022), we applied a coupled nature–economy–policy modeling framework across six temperature zones to test whether temperature acts as a nonlinear moderator rather than a direct determinant. The warm temperate zone accounted for >55% of national emissions and, together with the mid-temperate zone, this share reached ~80%, while the Qinghai–Tibet Plateau remained a net sink. Driver contributions varied systematically: economic factors dominated tropical and subtropical zones (74.3%), natural constraints dominated the plateau (41.7%), and policy interactions dominated mid- and warm-temperate zones (58.4%). Temperature acted nonlinearly, with emission effects rising from 0.277 to 1.212 t CO2 per °C above a 26.65 °C summer mean (a 4.4-fold amplification). A generalized additive model confirms this significant nonlinearity. Scenario simulations suggest that the business-as-usual scenario peaks in 2035–2040, whereas the ecological protection and low-carbon scenarios peak around 2030. Under RCP4.5, the model projects a potential shift of the plateau from sink to source, but this result is conditional on simplified climate–carbon feedbacks and should be interpreted as a plausible risk rather than a prediction. These findings indicate that temperature zones offer a complementary natural gradient—not a replacement for administrative divisions—for understanding how similar human activities produce different carbon outcomes under contrasting thermal conditions. Given the use of partly uniform emission factors, the results represent macro-scale differentiation; governance implications are therefore conditional on scenario assumptions and require local feasibility assessment.

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