Zhangjiakou City Science and Technology and Seismological Bureau

Ground-based microwave radiometers (MWR) are used to provide temperature and relative humidity (RH) profiles mainly at boundary layer with temporal resolution of 1–2 minutes. However, accuracy of MWR away from radiosondes locations is not satisfactory. In this study, we proposed temperature and RH retrieval models based on fifth-generation reanalysis (ERA5) data that allow the replacement of the original model based on adjacent radiosondes. The study focuses on how to resolve the unrepresentativeness of ERA5 data. A quality control scheme was proposed after analyzing the characteristics of ERA5 data, which was confirmed to have positive effects for retrieval results. Three retrieval models for MWR at Nanjiao site based on ERA5 data (ERA5-retrieval), co-located radiosondes (RS-retrieval 1), and adjacent radiosondes (RS-retrieval 2) were developed. An extensive validation that was carried out showed ERA5-retrieval improved the accuracy of temperature and RH profiles compared with the original method RS-retrieval 2 and LV2 product from MWR. Furthermore, the proposed retrieval method was applied to six MWR sites without radiosondes co-located in Beijing and illustrated the feasibility and accuracy of the proposed method. In overall, the retrieval approach proposed based on ERA5 data and data quality control can improve both temperature and RH accuracy for MWR sites away from radiosondes.

CT-based flow reserve fraction (CT-FFR) and CT perfusion (CTP), as a complement to coronary computed tomographic angiography (CCTA) have been revealed to be associated with the prognosis of patients with obstructive coronary artery disease (CAD). However, the prognostic value of coronary stenosis combined with CT-FFR and resting-state CTP based on CCTA for major adverse cardiac events (MACE) is not known and requires further investigation. Fifty-two patients with obstructive CAD (50%-90% stenosis) examined by CCTA were retrospectively collected and followed-up for the occurrence of MACE. Logistic regression was performed to analyze the effects of the degree of coronary stenosis, resting-state CTP, and CT-FFR in predicting the risk of MACE. MACE prediction models were developed, and the area under the receiver operating characteristic curve (AUC) was used to evaluate the predictive validity of different models for MACE. Ethics approval was provided by the First Affiliated Hospital of Hebei North University (Zhangjiakou, China; No. K2020237). Logistic regression analysis showed that coronary artery stenosis ≥ 70%, CT-FFR ≤ 0.80, and perfusion index (PI) were independent predictors for MACE in patients with obstructive CAD (P < .05). The model based on coronary stenosis combined with PI and CT-FFR (AUC = 0.944) was better than those based on the degree of coronary stenosis combined with PI (AUC = 0.874), coronary stenosis degree combined with CT-FFR (AUC = 0.895), and any single index (P < .05). The combined model established by coronary stenosis, CT-FFR, and resting-state CTP based on a "1-stop" CCTA examination for predicting MACE among patients with obstructive CAD has good diagnostic efficacy and shows incremental discriminatory power.

Chlorinated paraffins (CPs), especially short-chain (SCCPs) and medium-chain (MCCPs) homologues, have become a global concern due to their highly toxic and persistent. However, there remains a limited and fragmented understanding of their distribution and hotspots across diverse environmental matrices worldwide, and research on effective control measures is even more deficient. This study investigated the global occurrence of CPs in multiple environmental matrices and reviewed existing degradation technologies. Emissions from industrial activities, product usage and environmental matrices exchanges have led to widespread CPs contamination mainly encompassing SCCPs and MCCPs, with average concentrations of 10⁻³–10³ ng/m³ in atmosphere, 10–10³ ng/L in water and 1–10⁵ ng/g dw in sediment, as well as 1–10⁶ ng/g dw in soil. In contrast, data on long-chain CPs (LCCPs) remain extremely limited. The available long-term atmospheric monitoring demonstrated both the effectiveness of regulatory controls and the delayed environmental response due to long-range atmospheric transport. The environmental migration of CPs is strongly influenced by carbon chain length and degree of chlorination. Current degradation technologies primarily focus on pyrolysis, photolysis, photocatalysis, microbial degradation, and phytoremediation. Mechanisms and efficiency analyses revealed that major challenges include by-products and the limited scalability of technologies beyond laboratory settings. By systematically linking contaminations profiles to suitable treatment options, we proposed a targeted CPs pollution remediation strategy. These insights aim to advance global CPs government and support the implementation of the Stockholm Convention.

In alpine skiing, various meteorological conditions such as snow and weather can affect the performance of skiers and snowboarders and are thought to be potential risk factors for their injuries. PURPOSE:To evaluate meteorological factors in recreational skiing and snowboarding-related injuries. METHODS:A cohort study was conducted at a large ski resort in China during the 2019-2020 and 2020-2021 winter seasons. Cases were skiers or snowboarders who were injured in the ski resort and presented to either the ski patrol and/or the ski resort emergency department. Injury was defined as trauma directly caused by skiing or snowboarding, including damage to the musculoskeletal system and skin. Controls were uninjured skiers or snowboarders using the same ski resort. Daily meteorological conditions including temperature, wind speed, snowfall, snow base depth, snow conditions and weather were obtained from meteorological department. The patient’s injured time and ski time period records for non-injured persons were obtained from the ski patrol, emergency and management departments to determine the meteorological status at the corresponding time. Multivariable logistic regression determined if meteorological factors were associated with the odds of ski-related injury. RESULTS:In total, 976 injured and 1724 non-injured skiers and snowboarders have been included in this study. The logistic regression model and adjusted odds ratio (OR) and their 95% confidence interval (CI) revealed the following independent injury risk factors for skiers and snowboarders: muddy snow conditions (OR = 1.413, 95% CI, 1.003-1.956, P < 0.001), higher wind speeds (OR = 2.203, 95% CI, 2.123-2.289, P < 0.001), deeper snow bases (OR = 1.293, 95% CI, 0.744-2.241, P < 0.001) and sunny days (OR = 1.117, 95% CI, 0.997-1.252, P = 0.006). CONCLUSIONS:Meteorological conditions, particularly wind, weather, and snow, have a significant impact on ski injuries. Injury prevention work should consider meteorological factors to reduce the injury rate of skiers and snowboarders.