In recent years, ground-level ozone has become a severe ambient pollutant in major urban areas of China, which has adverse impacts on population health. However, in-situ measurements of the ozone concentration before 2013 in China are quite scarce, which cannot facilitate the assessment of the long-term trends and effects of ozone pollution. In this study, we used daily maximum 8-hour average (MDA8) ozone observations from 2013 to 2017 combined with concurrent ozone retrievals, aerosol reanalysis, meteorological parameters, and land-use data to establish a nationwide MDA8 prediction model based on the eXtreme Gradient Boosting (XGBoost) algorithm. The model achieves high prediction accuracy compared with other studies, with R2 values for the by-year, site-based, and sample-based cross-validation (CV) schemes of 0.61, 0.64, and 0.78, respectively, at the daily level. External testing with regional measurements from 2005 to 2012 and nationwide data in 2018 have shown that the model is robust and reliable for historical data prediction, with external model testing R2 values ranging from 0.60 to 0.87 at the month level in different years. Using the final estimator, we obtained nationwide monthly mean ozone concentrations from 2005 to 2012 and daily MDA8 ozone concentrations from 2013 to 2017 at a resolution of 0.1° × 0.1°. According to the average number of days exceeding the standard and the average of the 90th percentile of the MDA8 ozone concentrations, the Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta, the Pearl River Delta, the Jianghan Plain, the Sichuan Basin, and the Northeast Plain regions were identified as pollution hotspots. During the research period, the overall ozone levels fluctuated slightly, and their trends were not spatially continuous. There was a significant increasing trend in the BTH region by 1.37 (95% CI: 0.46,2.29) μg/m3/year between 2013 and 2017. In 2017, 26.24% of the population lived in areas exceeding the Chinese grade II national air quality standard, which shows that ozone pollution has posed an obvious threat to population health in China. Our products will provide reliable support for future long-term nationwide health impact studies and policy-making for pollution control and prevention.

Understanding the effectiveness of air pollution control policies is important for future policy making. China has implemented strict air pollution control policies since the 11th Five-Year Plan (FYP). There is still a lack of overall evaluation of the effects of air pollution control policies on PM_2.5 pollution improvement in China since the 11th FYP. In this study, we aimed to assess the effects of air pollution control policies from 2005 to 2017 on PM_2.5 using satellite remote sensing. We used the satellite-derived PM_2.5 of 2005–2013 from one of our previous studies. For the data of 2014–2017, we developed a two-stage statistical model to retrieve satellite PM_2.5 data using the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol optical depth (AOD), assimilated meteorology, and land use data. The first stage is a day-specific linear mixed effects (LME) model and the second stage is a generalized additive model (GAM). Results show that the Energy Conservation and Emissions Reduction (ECER) policy, implemented in the 11th FYP period and focused on SO₂ emissions control, had co-benefits with PM_2.5 reductions. The increasing trends of PM_2.5 pollution (1.88 and 3.14 µg m⁻³ year⁻¹ for all of China and the Jingjinji region in 2004–2007, p<0.005) were suppressed after 2007. The overall PM_2.5 trend for all of China was −0.56 µg m⁻³ year⁻¹ with marginal significance (p=0.053) and PM_2.5 concentrations in the Pearl River Delta region had a big drop (−4.81 µg m⁻³ year⁻¹, p<0.001) in 2007–2010. The ECER policy during the 12th FYP period was basically an extension of the 11th FYP policy. PM_2.5 is a kind of composite pollutant which comprises primary particles and secondary particles such as sulfate, nitrate, ammonium, organic carbon, elemental carbon, etc. Since the ECER policy focused on single-pollutant control, it had shown great limitation for PM_2.5 reductions. The PM_2.5 concentrations did not decrease from 2010 to 2013 in polluted areas (p values of the trends were greater than 0.05). Therefore, China implemented two stricter policies: the 12th FYP on Air Pollution Prevention and Control in Key Regions (APPC-KR) in 2012, and the Action Plan of Air Pollution Prevention and Control (APPC-AP) in 2013. The goal of air quality improvement (especially PM_2.5 concentration improvement) and measures for multi-pollutant control were proposed. These policies led to dramatic decreases in PM_2.5 after 2013 (−4.27 µg m⁻³ year⁻¹ for all of China in 2013–2017, p<0.001).

Vitamin D metabolism is essential in aging and can be affected by multiple environmental factors. However, most studies conducted single exposure analyses. We aim to assess the individual and combined effects of ultraviolet (UV) radiation, residential greenness, fine particulate matter (PM_2.5), and ozone (O₃) on vitamin D levels in a national cohort study of older adults in China. We used the 2012 and 2014 Chinese Longitudinal Healthy Longevity Survey data, and measured the environmental exposure in the same year. We interpolated the UV radiation from monitoring stations, measured residential greenness through satellite-derived Normalized Difference Vegetation Index (NDVI), modeled PM_2.5 with satellite data, and estimated O₃ using machine learning. We dichotomized serum 25-hydroxy vitamin D (25(OH)D), the primary circulating form of vitamin D, into non-deficiency (≥50 nmol/L) and deficiency (<50 nmol/L) categories. We used the generalized estimating equation for analysis, adjusted for sociodemographic information, lifestyle, physical condition, and season of blood draw, and calculated joint odds ratios based on the Cumulative Risk Index. We also explored the interaction between interested exposures, modification of participants' characteristics, and potential mediation. We included 1,336 participants, with a mean age of 83 at baseline. In single exposure models, the odds ratios of vitamin D deficiency (VDD) for per interquartile range increase in UV radiation, NDVI, PM_2.5, and O₃ and decrease were 0.39 (95 % CI:0.33,0.46), 0.90 (0.81,1.00), 1.65 (1.53,1.78), 1.67 (1.46,1.92), respectively. UV radiation mediated nearly 48 % and 78 % of the relationship between VDD and PM_2.5 and O₃, respectively. The association between UV radiation and VDD was stronger in females than men (OR: 2.25 vs 1.22). UV radiation, residential greenness can protect against VDD, while, PM_2.5 and O₃ increase the risk of VDD. UV radiation partly mediated the association between air pollution and VDD.