Abstract: Precursor emissions of air pollution can be reduced at emitting sources by end-of-pipe control policies or as co-benefits of climate policies that limit fossil fuel. Identifying cost-effective control strategies requires understanding policy costs, chemical non-linearities in pollution formation, and the value of health benefits. China suffers from severe air pollution, and is implementing both policies, but relevant studies are limited. This thesis incorporates three studies that examine the air quality co-benefits of China's recent climate policy for China and transboundary countries, and the potential changes in the sensitivities of inorganic PM_2.5 to precursor emissions in China. The first study quantifies co-benefits of China's climate policy from reducing PM_2.5 using a modeling framework that couples an energy-economic model with sub-national detail for China (C-RE\1) and an atmospheric chemical transport model GEOS­Chem. The effects of an illustrative climate policy, a price on CO₂ emissions, are simulated under three stringencies. In a policy scenario consistent with China's recent pledge to peak CO₂ emissions by 2030 (the 4% Policy scenario), national health co-benefits from improved PM_2.5 pollution can partially or fully offset policy costs depending on chosen health valuation. This study also suggests co-benefits would rise with increasing policy stringency. Using the same model simulations. the second study further compares co-benefits from PM_2.5 and ozone in China and three downwind countries (South Korea, Japan and the United States). This study suggests that under the 4% Policy scenario, avoided premature deaths from reducing ozone are about half of those from PM_2.5 in China, and the total avoided deaths in trans boundary countries are about 4% of those in China. The third study examines the potential changes in the sensitivities of inorganic PM_2.5 to precursor emissions in China in response to the current and projected national reductions in SO₂ and NOx emissions. Under scenarios that reduce SO₂ and NOx emissions, sensitivities to SO₂ and NOx, emissions would increase, but sensitivity to NH₃ emissions would decrease in January and July. The largest absolute changes in sensitivities are found in January for NOx and NH₃.