Multidecadal ozone trends in China and implications for human health and crop yields: A hybrid approach combining chemical transport model and machine learning

Surface ozone (O3) poses great threats to both human health and crop production worldwide. However, a multi-decadal assessment of O3 impacts in China is lacking due to insufficient long-term continuous O3 observations. In this study, we used a machine learning (ML) algorithm to correct the biases of O3 concentrations simulated by the chemical transport model from 1981–2019 by integrating multi-source datasets. The ML-enabled bias-corrected O3 concentrations improve the estimates of O3 impacts on human health and crop yields. The warm-season increasing trend of O3 in Beijing-Tianjin-Hebei and its surroundings (BTHs), Yangtze River Delta (YRD), Sichuan Basin (SCB) and Pearl River Delta (PRD) regions are 0.32, 0.63, 0.84, and 0.81 μg m–3 yr–1 from 1981 to 2019, respectively. In more recent years, O3 concentrations experience more fluctuations in the four major regions. Our results show that only BTHs have a perceptible increasing trend of 0.81 μg m–3 yr–1 during 2013–2019. The estimated annual all-cause premature deaths induced by O3 increase from ~55,900 in 1981 to ~162,000 in 2019 with an increasing trend of ~2,980 deaths yr–1. The annual premature deaths related to respiratory and cardiovascular disease are ~34,200 and ~40,300 in 1998, and ~26,500 and ~79,000 in 2019, having a rate of change of –546 and +1,770 deaths yr–1 during 1998–2019, respectively. Using 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, and increases 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. Currently, estimating ozone-induced crop production losses still faces great uncertainties in magnitudes and/or spatial patterns when using different approaches, particularly in large-scale studies involving diverse ecological and climatic conditions. The averaged national annual mean RYLs for wheat are estimated to range from 4.3 to 24.6%, considering most available exposure metrics, including concentration-based and flux-based metrics. Our study, for the first time, used ML to provide a robust O3 dataset over the past four decades in China, enabling a long-term evaluation of O3-induced health impacts and crop losses. These findings are expected to fill the gap in the long-term O3 trend and impact assessment in China. Figure 1. Density scatter plots and linear regressions between O3 measurements and predictions of LightGBM and GEOS-Chem model at (a1, a2) daily level and (a3, a4) hourly level, respectively. The annual averaged MDA8 O3 concentrations of LightGBM bias-corrected predictions and corresponding anomalies from 1981 to 2019: (b1) BTHs, (b2) YRD, (b3) SCB, and (b4) PRD.  (c1) The mortality (thousand) for different health endpoints; (c2) The province-based mortality (thousand) attributed to different health endpoints; (c3) The annual province-based population (million). (d) Bar plot of the RYLs for crops using different metrics from 1981-2019: (left panel) LightGBM, and (right panel) GEOS-Chem.  Figure 2. Spatial distribution of averaged annual RYLs (%) for wheat: (a) AOT40, (b) FBB, (c) DO3SE_LRTAP, and (d) DO3SE_Feng. The spatial correlation coefficients (r) of estimated RYLs using different metrics (Table).