From 2013 to 2017, with the implementation of the toughest-ever clean air policy in China, significant declines in fine particle (PM2.5) concentrations occurred nationwide. Here we estimate the drivers of the improved PM2.5 air quality and the associated health benefits in China from 2013 to 2017 based on a measure-specific integrated evaluation approach, which combines a bottom-up emission inventory, a chemical transport model, and epidemiological exposure-response functions. The estimated national population–weighted annual mean PM2.5 concentrations decreased from 61.8 (95%CI: 53.3–70.0) to 42.0 µg/m3 (95% CI: 35.7–48.6) in 5 y, with dominant contributions from anthropogenic emission abatements. Although interannual meteorological variations could significantly alter PM2.5 concentrations, the corresponding effects on the 5-y trends were relatively small. The measure-by-measure evaluation indicated that strengthening industrial emission standards (power plants and emission-intensive industrial sectors), upgrades on industrial boilers, phasing out outdated industrial capacities, and promoting clean fuels in the residential sector were major effective measures in reducing PM2.5 pollution and health burdens. These measures were estimated to contribute to 6.6- (95% CI: 5.9–7.1), 4.4- (95% CI: 3.8–4.9), 2.8- (95% CI: 2.5–3.0), and 2.2- (95% CI: 2.0–2.5) µg/m3 declines in the national PM2.5 concentration in 2017, respectively, and further reduced PM2.5-attributable excess deaths by 0.37 million (95% CI: 0.35–0.39), or 92% of the total avoided deaths. Our study confirms the effectiveness of China’s recent clean air actions, and the measure-by-measure evaluation provides insights into future clean air policy making in China and in other developing and polluting countries.

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Abstract. The mixing layer is an important meteorological factor that affects air pollution. In this study, the atmospheric mixing layer height (MLH) was observed in Beijing from July 2009 to December 2012 using a ceilometer. By comparison with radiosonde data, we found that the ceilometer underestimates the MLH under conditions of neutral stratification caused by strong winds, whereas it overestimates the MLH when sand-dust is crossing. Using meteorological, PM2.5, and PM10 observational data, we screened the observed MLH automatically; the ceilometer observations were fairly consistent with the radiosondes, with a correlation coefficient greater than 0.9. Further analysis indicated that the MLH is low in autumn and winter and high in spring and summer in Beijing. There is a significant correlation between the sensible heat flux and MLH, and the diurnal cycle of the MLH in summer is also affected by the circulation of mountainous plain winds. Using visibility as an index to classify the degree of air pollution, we found that the variation in the sensible heat and buoyancy term in turbulent kinetic energy (TKE) is insignificant when visibility decreases from 10 to 5 km, but the reduction of shear term in TKE is near 70 %. When visibility decreases from 5 to 1 km, the variation of the shear term in TKE is insignificant, but the decrease in the sensible heat and buoyancy term in TKE is approximately 60 %. Although the correlation between the daily variation of the MLH and visibility is very poor, the correlation between them is significantly enhanced when the relative humidity increases beyond 80 %. This indicates that humidity-related physicochemical processes is the primary source of atmospheric particles under heavy pollution and that the dissipation of atmospheric particles mainly depends on the MLH. The presented results of the atmospheric mixing layer provide useful empirical information for improving meteorological and atmospheric chemistry models and the forecasting and warning of air pollution.

Construction of heterojunctions has aroused great interest recently in the photocatalysis field because of the special electronic band structure and unique physicochemical properties. In this work, a novel 0D/3D CuO/ZnO heterojunction was obtained via in situ deposition of CuO nanoparticles on the flowerlike ZnO surface using the wet chemistry method. After depositing CuO nanoparticles onto the ZnO, the CuO/ZnO heterojunction exhibits enhanced visible-light harvesting and effective separation of the photogenerated electron–hole pairs compared with those in the pure ZnO. The photocatalytic removal efficiency of phenol over the CuO/ZnO heterojunction is up to 78% under the irradiation of the light, which is ∼2 and ∼4 times higher than those of the pristine ZnO and CuO, respectively. This composite also presents good durability and stability for phenol degradation in the photocatalytic reactions. Additionally, in the photodegradation system of the CuO/ZnO heterojunction, the superoxide radicals (•O2 –) and hydroxyl radicals (•OH) are confirmed as the active species by the trapping experiments. This research provides a promising way to achieve 0D/3D heterojunctions for the application in environmental purification and remedy.

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Exosomes contain cell-and cell-state-specific cargos of proteins, lipids, and nucleic acids and play significant roles in cell signaling and cell−cell communication. Current research into exosome-based biomarkers has relied largely on analyzing candidate biomarkers, i.e., specific proteins or nucleic acids. However, this approach may miss important biomarkers that are yet to be identified. Alternative approaches are to analyze the entire exosome system, either by "omics" methods or by techniques that provide "fingerprints" of the system without identifying each individual biomolecule component. Here, we describe a platform of the latter type, which is based on surface-enhanced Raman spectroscopy (SERS) in combination with multivariate analysis, and demonstrate the utility of this platform for analyzing exosomes derived from different biological sources. First, we examined whether this analysis could use exosomes isolated from fetal bovine serum using a simple, commercially available isolation kit or necessitates the higher purity achieved by the "gold standard" ultracentrifugation/filtration procedure. Our data demonstrate that the latter method is required for this type of analysis. Having established this requirement, we rigorously analyzed the Raman spectral signature of individual exosomes using a unique, hybrid SERS substrate made of a graphenecovered Au surface containing a quasi-periodic array of pyramids. To examine the source of the Raman signal, we used Raman mapping of low and high spatial resolution combined with morphological identification of exosomes by scanning electron microscopy. Both approaches suggested that the spectra were collected from single exosomes. Finally, we demonstrate for the first time that our platform can distinguish among exosomes from different biological sources based on their Raman signature, a promising approach for developing exosome-based fingerprinting. Our study serves as a solid technological foundation for future exploration of the roles of exosomes in various biological processes and their use as biomarkers for disease diagnosis and treatment monitoring.

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