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Surface ozone (O 3) is well known for posing significant threats to both human health and crop production worldwide. However, a multidecadal assessment of the impacts of O 3 on public health and crop yields in China is lacking due to insufficient long-term continuous O 3 observations. In this study, we used a machine learning (ML) algorithm to correct the biases of O 3 concentrations simulated by a chemical transport model from 1981–2019 by integrating multi-source datasets. The ML-enabled bias correction offers improved performance in reproducing observed O 3 concentrations and thus further improves our estimates of the impacts of O 3 on human health and crop yields. The warm-season trends of increasing O 3 in Beijing–Tianjin–Hebei and its surroundings (BTHs) as well as in the Yangtze River Delta (YRD), Sichuan Basin (SCB), and Pearl River Delta (PRD) regions are 0.32, 0.63, 0.84, and 0.81 µ g m -3 yr -1 from 1981 to 2019, respectively. In more recent years, O 3 concentrations experienced more fluctuations in the four major regions. Our results show that only BTHs have a perceptible increasing trend of 0.81 µ g m -3 yr -1 during 2013–2019. Using accumulated O 3 over a threshold of 40 ppb (AOT40-China) exposure–yield response relationships, the estimated relative yield losses (RYLs) for wheat, rice, soybean, and maize are 17.6 %, 13.8 %, 11.3 %, and 7.3 % in 1981, increasing to 24.2 %, 17.5 %, 16.3 %, and 9.8 % in 2019, with an increasing rate of +0.03 % yr -1 , +0.04 % yr -1 , +0.27 % yr -1 , and +0.13 % yr -1 , respectively. The estimated annual all-cause premature deaths induced by O 3 increased from ∼55900 in 1981 to ∼162000 in 2019 with an increasing trend of ∼2980 deaths per year. The annual premature deaths related to respiratory and cardiovascular disease are ∼34200 and ∼40300 in 1998 and ∼26500 and ∼79000 in 2019, having a rate of change of -546 and +1770 deaths per year during 1998–2019, respectively. Our study, for the first time, used ML to provide a robust dataset of O 3 concentrations over the past 4 decades in China, enabling a long-term evaluation of O 3 -induced crop losses and health impacts. These findings are expected to fill the gap of the long-term O 3 trend and impact assessment in China. [ABSTRACT FROM AUTHOR]

Fugitive road dust (FRD) particles emitted by traffic-generated turbulence are an important contributor to urban ambient fine particulate matter (PM 2.5 ). Especially in urban areas of developing countries, FRD PM 2.5 emissions are a serious environmental threat to air quality and public health. FRD PM 2.5 emissions have been neglected or substantially underestimated in previous study, resulting in the underestimation of modeling PM concentrations and estimating their health impacts. This study constructed the FRD PM 2.5 emissions inventory in a major inland city in China (Lanzhou) in 2017 at high-resolution (500 × 500 m 2 ), investigated the spatiotemporal characteristics of the FRD emissions in different urban function zones, and quantified their health impacts. The FRD PM 2.5 emission was approximately 1141 ± 71 kg d -1 , accounting for 24.6% of total PM 2.5 emission in urban Lanzhou. Spatially, high emissions exceeding 3 × 10 4 μg m -2 d -1 occurred over areas with smaller particle sizes, larger traffic intensities, and more frequent construction activities. The estimated premature mortality burden induced by FRD PM 2.5 exposure was 234.5 deaths in Lanzhou in 2017. Reducing FRD emissions are an important step forward to protect public health in many developing urban regions.