Antagonism between ambient ozone increase and urbanization-oriented population migration on Chinese cardiopulmonary mortality.

Ever-increasing ambient ozone (O3) pollution in China has been exacerbating cardiopulmonary premature deaths. However, the urban-rural exposure inequity has seldom been explored. Here, we assess population-scale O3 exposure and mortality burdens between 1990 and 2019 based on integrated pollution tracking and epidemiological evidence. We find Chinese population have been suffering from climbing O3 exposure by 4.3 ± 2.8 ppb per decade as a result of rapid urbanization and growing prosperity of socioeconomic activities. Rural residents are broadly exposed to 9.8 ± 4.1 ppb higher ambient O3 than the adjacent urban citizens, and thus urbanization-oriented migration compromises the exposure-associated mortality on total population. Cardiopulmonary excess premature deaths attributable to long-term O3 exposure, 373,500 (95% uncertainty interval [UI]: 240,600-510,900) in 2019, is underestimated in previous studies due to ignorance of cardiovascular causes. Future O3 pollution policy should focus more on rural population who are facing an aggravating threat of mortality risks to ameliorate environmental health injustice.

Lateral layered semiconductor multijunctions for novel electronic devices.

Layered semiconductors, represented by transition metal dichalcogenides, have attached extensive attention due to their unique and tunable electrical and optical properties. In particular, lateral layered semiconductor multijunctions, including homojunctions, heterojunctions, hybrid junctions and superlattices, present a totally new degree of freedom in research on electronic devices beyond traditional materials and their structures, providing unique opportunities for the development of new structures and operation principle-based high performance devices. However, the advances in this field are limited by the precise synthesis of high-quality junctions and greatly hampered by ambiguous device performance limits. Herein, we review the recent key breakthroughs in the design, synthesis, electronic structure and property modulation of lateral semiconductor multijunctions and focus on their application-specific devices. Specifically, the synthesis methods based on different principles, such as chemical and external source-induced methods, are introduced stepwise for the controllable fabrication of semiconductor multijunctions as the basics of device application. Subsequently, their structure and property modulation are discussed, including control of their electronic structure, exciton dynamics and optical properties before the fabrication of lateral layered semiconductor multijunction devices. Precise property control will potentially result in outstanding device performances, including high-quality diodes and FETs, scalable logic and analog circuits, highly efficient optoelectronic devices, and unique electrochemical devices. Lastly, we focus on several of the most essential but unresolved debates in this field, such as the true advantages of few-layer vs. monolayer multijunctions, how sharp the interface should be for specific functional devices, and the superiority of lateral multijunctions over vertical multijunctions, highlighting the next-phase strategy to enhance the performance potential of lateral multijunction devices.

Spatial Resolved Surface Ozone with Urban and Rural Differentiation during 1990-2019: A Space-Time Bayesian Neural Network Downscaler.

Long-term exposure to ambient ozone (O3) can lead to a series of chronic diseases and associated premature deaths, and thus population-level environmental health studies hanker after the high-resolution surface O3 concentration database. In response to this demand, we innovatively construct a space-time Bayesian neural network parametric regressor to fuse TOAR historical observations, CMIP6 multimodel simulation ensemble, population distributions, land cover properties, and emission inventories altogether and downscale to 10 km × 10 km spatial resolution with high methodological reliability (R2 = 0.89-0.97, RMSE = 1.97-3.42 ppbV), fair prediction accuracy (R2 = 0.69-0.77, RMSE = 5.63-7.97 ppbV), and commendable spatiotemporal extrapolation capabilities (R2 = 0.62-0.76, RMSE = 5.38-11.7 ppbV). Based on our predictions in 8-h maximum daily average metric, the rural-site surface O3 are 15.1±7.4 ppbV higher than urban globally averaged across 30 historical years during 1990-2019, with developing countries being of the most evident differences. The globe-wide urban surface O3 are climbing by 1.9±2.3 ppbV per decade, except for the decreasing trends in eastern United States. On the other hand, the global rural surface O3 tend to be relatively stable, except for the rising tendencies in China and India. Using CMIP6 model simulations directly without urban-rural differentiation will lead to underestimations of population O3 exposure by 2.0±0.8 ppbV averaged over each historical year. Our original Bayesian neural network framework contributes to the deep-learning-driven environmental studies methodologically by providing a brand-new feasible way to realize data fusion and downscaling, which maintains high interpretability by conforming to the principles of spatial statistics without compromising the prediction accuracy. Moreover, the 30-year highly spatial resolved monthly surface O3 database with multiple metrics fills in the literature gap for long-term surface O3 exposure tracing.