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The Chinese government aims to mitigate climate change while also reducing local air pollution; this requires co-control of greenhouse gases and pollutants. Here, we develop a method combining an elasticity analysis and a multi-regional input–output model, to measure changes in the emissions of greenhouse gases and pollutants and corresponding socio-economic costs caused by the adjustments in intermediate input, inter-regional trade, and final demand transactions for 30 provinces in China. A filter framework is proposed to identify the key structural transactions that can significantly co-control both emission types with small socio-economic impacts. The results show that 13 effective co-control spots can simultaneously reduce greenhouse gases and pollutants. Among these, eight co-controls are associated with low economic costs, which we refer to as 'sweet spots'. Sweet spots cover agricultural inputs in the food and tobacco sectors of Inner Mongolia, Sichuan, Liaoning, and Hubei; self-inputs in the agriculture of Henan; self-inputs in the food and tobacco sector of Shandong; fixed capital formation of agriculture in Hebei; and urban household consumption of agricultural products in Guangdong. This finding is important, as climate measures mostly side-line the agricultural sector so far, both in China and in other parts of the world. • Structural adjustments could co-control multi-emissions with small economic impacts. • Thirteen effective co-control spots can simultaneously reduce GHGs and pollutants. • Of these, eight co-controls are associated with low economic costs (sweet spots). • Most sweet spots are related to agricultural goods and mostly reduce non-CO 2 GHGs. • All sweet spots have the strongest effect on NH 3 emission, followed by PM 2.5. [ABSTRACT FROM AUTHOR]