The spatiotemporal pattern of surface ozone and its impact on agricultural productivity in China

The slowing of agricultural productivity growth globally over the past two decades has brought a new urgency to detect its drivers and potential solutions. We show that air pollution, particularly surface ozone (O₃), is strongly associated with declining agricultural total factor productivity (TFP) in China. We employ machine learning algorithms to generate estimates of high-resolution surface O₃ concentrations from 2002 to 2019. Results indicate that China's O₃ pollution has intensified over this 18-year period. We coupled these O₃ estimates with a statistical model to show that rising O₃ pollution during nonwinter seasons has reduced agricultural TFP by 18% over the 2002-2015 period. Agricultural TFP is projected to increase by 60% if surface O₃ concentrations were reduced to meet the WHO air quality standards. This productivity gain has the potential to counter expected productivity losses from 2°C warming.