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Abstract. With frequent air pollution episodes in China, growing research emphasis has been put on quantifying meteorological influences on PM 2.5 concentrations. However, these studies mainly focus on isolated cities, whilst meteorological influences on PM 2.5 concentrations at the national scale have not yet been examined comprehensively. This research employs the CCM (convergent cross-mapping) method to understand the influence of individual meteorological factors on local PM 2.5 concentrations in 188 monitoring cities across China. Results indicate that meteorological influences on PM 2.5 concentrations have notable seasonal and regional variations. For the heavily polluted North China region, when PM 2.5 concentrations are high, meteorological influences on PM 2.5 concentrations are strong. The dominant meteorological influence for PM 2.5 concentrations varies across locations and demonstrates regional similarities. For the most polluted winter, the dominant meteorological driver for local PM 2.5 concentrations is mainly the wind within the North China region, whilst precipitation is the dominant meteorological influence for most coastal regions. At the national scale, the influence of temperature, humidity and wind on PM 2.5 concentrations is much larger than that of other meteorological factors. Amongst eight factors, temperature exerts the strongest and most stable influence on national PM 2.5 concentrations in all seasons. Due to notable temporal and spatial differences in meteorological influences on local PM 2.5 concentrations, this research suggests pertinent environmental projects for air quality improvement should be designed accordingly for specific regions.

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Highlights d FGF15 activates Mst1/2 through hepatic FGFR4 in response to increased bile acids d NF2 switches FGFR4's role from pro-oncogenic to anti-tumor signaling via Mst1/2 d Mst1/2 acts as a key negative feedback suppressor of bile acid synthesis via SHP d Depletion of bile acids retards Mst1/2-mutant-driven liver growth and oncogenesis

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BackgroundSome studies found out that TC/HDL-C ratio is a predictor of Cardiovascular disease (CVD) and Nonalcoholic fatty liver (NAFLD) is related to CVD. And some researches have already studied that Apolipoprotein B to Apolipoprotein A1 ratio (ApoB/ApoA1) and Triglyceride to High-density lipoprotein cholesterol ratio (TG/HDL-C) were both related with CVD and NAFLD, but few studied the association between TC/HDL-C ratio and NAFLD. So, we suspected the ratio was also related to NAFLD. The research aims to study the predictive value of TC/HDL-C to NAFLD and to help the early detection of NAFLD.MethodsBased on the Jinchang Cohort, the study contained 32,121 participants. We assessed the incidence of NAFLD by the quartiles of TC, HDL-C and TC/HDL-C. Then, the does-response relationship between these indicators and the risk of NAFLD was obtained. Finally, the receiver operator characteristic curve (ROC) was applied to decide the predictive value of TC/HDL-C.ResultsAmong the study participants, the cumulative incidence of NAFLD was 6.30% and the rate of dyslipidemia was 40.37%. The biochemical indicators of NAFLD had a difference with general population. The incidence of NAFLD raised with the quartiles of TC, TG and LDL-C raising, while decreased with the HDL-C′ quartiles raising. After controlling confounding factors, TC and TC/HD-C had a positive relationship with NAFLD, while HDL-C had the opposite. Finally, the ROC analysis showed the area under the curve (AUC) of TC/HDL-C (0.645) was greater than TC (0.554), HDL-C (0.627) and Apolipoprotein B to Apolipoprotein A1 (ApoB/ApoA1) (0.613).ConclusionsThe TC/HDL-C ratio has significant predictive value to NAFLD.Electronic supplementary materialThe online version of this article (10.1186/s12944-019-0984-9) contains supplementary material, which is available to authorized users.

Abstract. Wet scavenging is one of the most efficient processes for removing aerosols from the atmosphere. This process is not well constrained in chemical transport models (CTMs) due to a paucity of localized parameterization regarding the below-cloud wet scavenging coefficient (BWSC). Here we conducted field measurements of the BWSC during the Atmospheric Pollution and Human Health Beijing (APHH-Beijing) campaign of 2016. Notably, the observed BWSC values based on the updated aerosol mass balance agree well with another estimation technique, and they fall in a range of 10−5 s−1. The measurement in this winter campaign, combined with that in summer of 2014, supported an exponential power distribution of BWSCs with rainfall intensity. The observed parameters were also compared with both the theoretical calculations and modeling results. We found that the theoretical estimations can effectively characterize the observed BWSCs of aerosols with sizes smaller than 0.2 µm and larger than 2.5 µm. However, the theoretical estimations were an order of magnitude lower than observed BWSCs within 0.2–2.5 µm, a domain size range of urban aerosols. Such an underestimation of BWSC through a theoretical method has been confirmed not only in APHH-Beijing campaign but also in all the rainfall events in summer of 2014. Since the model calculations usually originated from the theoretical estimations with simplified scheme, the significantly lower BWSC could well explain the underprediction of wet depositions in polluted regions as reported by the Model Inter-Comparison Study for Asia (MICS-Asia) and the global assessment of the Task Force on Hemispheric Transport of Atmospheric Pollutants (TF-HTAP). The findings highlighted that the wet deposition module in the CTMs requires improvement based on field measurement estimation to construct a more reasonable simulation scheme for BWSC, especially in polluted regions.