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• Air quality data in Beijing during the Blue Sky Day period are re-estimated. • A Bayesian multi-task learning model is constructed for air quality re-estimation. • Official air quality data, US Embassy PM 2.5 data, and proxy data are utilized. • Re-estimated air quality values are higher than the official values on average. • Re-estimated air quality data exhibit reduced statistical irregularity. For over three decades, air pollution has been a major environmental challenge in many of the fast-growing cities of the world, including Beijing, China. Given that any long-term exposure to high levels of air pollution has devastating health consequences, accurately monitoring and reporting air pollution information to the public is critical for ensuring public health and safety, while facilitating rigorous air pollution and health-related scientific research. Recent statistical research examining China's air quality data has posed questions on data accuracy, especially data reported during the Blue Sky Day (BSD) period (2000–2012), even though the quality of publicly available air quality data in China has improved substantially over the recent years (2013–2017). Until now, no attempts have been made to re-estimate the air quality data during the BSD period. In this study, we propose a multi-task machine-learning model to re-estimate the official air quality data during the recent BSD period, from 2008 to 2012, utilizing PM 2.5 data reported by the US Embassy in Beijing and proxy data covering Aerosol Optical Depth (AOD) and meteorology. Results have shown that average re-estimated daily air qualities are respectively 56% and 55% higher than the official ones, for air quality index (AQI) and AQI equivalent PM 2.5 , during the BSD period, from 2008 to 2012. Moreover, the re-estimated BSD air quality data exhibit reduced statistical discontinuity and irregularity. Our novel data re-estimation methodology can be used to provide more credible historical air quality data for evidence-based environmental and public health studies. [ABSTRACT FROM AUTHOR]

Abstract Over the last three decades, rapid industrialization in China has generated an unprecedentedly high level of air pollution and associated health problems. Given that China accounts for one-fifth of the world population and suffers from severe air pollution, a comprehensive review of the indicators accounting for the health costs in relation to air pollution will benefit evidence-based and health-related environmental policy-making. This paper reviews the conventional static and the new dynamic approach adopted for air pollution-related health cost accounting in China and analyzes the difference between the two in estimating GDP loss. The advantages of adopting the dynamic approach for health cost accounting in China, with conditions guaranteeing its optimal performance are highlighted. Guidelines on how one can identify an appropriate approach for health cost accounting in China are put forward. Further, we outline and compare the globally-applicable and China-specific indicators adopted by different accounting methodologies, with their pros and cons being discussed. A comprehensive account of the available databases and methodologies for health cost accounting in China are outlined. Future directions to guide health cost accounting in China are provided. Our work provides valuable insights into future health cost accounting research in China. Our study has strengthen the view that the dynamic approach is comparatively more preferred than the static approach for health cost accounting in China, if more data is available to train the dynamic models and improve the robustness of the parameters employed. In addition, future dynamic model should address the socio-economic impacts, including benefits or losses of air pollution polices, to provide a more robust policy picture. Our work has laid the key principles and guidelines for selecting proper econometric approaches and parameters. We have also identified a proper estimation method for the Value of Life in China, and proposed the integration of engineering approaches, such as the use of deep learning and big data analysis for health cost accounting at the fine-grained level (city-district or sub-regional level). Our work has also identified the gap for more accurate health cost accounting at the fine-grained level in China, which will subsequently affect the quality of health-related air pollution policy decision-making at such levels, and the health-related quality of life of the citizens in China. Highlights • The dynamic health cost accounting a preferred approach in China • Future dynamic model should address parameter robustness and socio-economic impacts. • Guidelines for selecting proper econometric approaches and parameters stated • Estimation methods for Values of Life in China and integration of methods proposed • Accurate health cost accounting at fine spatial resolutions needed [ABSTRACT FROM AUTHOR]

The Fukushima Daiichi nuclear disaster has rekindled the world's attention to nuclear safety following the devastating nuclear accidents that occurred in the Three Mile Island and Chernobyl. As China continues to expand in nuclear power development, how it views and responds to nuclear safety carries significant implications on its nuclear safety and security in the future. This paper examines the Chinese authorities' response to nuclear safety pre- and post-Fukushima, based on (1) a longitudinal big-data discourse analysis of the Chinese newspaper articles published during the period 2008–2017, and (2) an in-depth comprehensive review of nuclear safety performance and safety governance based on credential and publicly available documents and websites, both locally and internationally. Our assessment reveals that (i) China's concerns over nuclear safety and accident surged immediately following the Fukushima crisis. Increasing attention towards nuclear emergency response has been observed since 2014, (ii) China has displayed strengths in reactor design and safety operation, and (iii) its safety governance has been constrained by institutional fragmentation, inadequate transparency, inadequate safety professionals, lack of a strong safety culture, amid its ongoing plans to increase nuclear capacity three-fold by 2050. To improve nuclear safety, China may further strengthen its safety standards, safety management and monitoring, improve institutional arrangements, increase the ratio of safety professionals, intensify its safety culture and transparency, develop process-based safety regulations, and champion international collaboration to keep itself abreast of the latest international best practices. • China's concerns over nuclear safety surged after the Fukushima crisis. • China displayed strengths in reactor technology design and safety operation. • China can benefit from better safety management culture, institutional integration and and and regulatory design, etc. [ABSTRACT FROM AUTHOR]