It is crucial to investigate the characteristics of fire danger in the areas around Beijing to increase the accuracy of fire danger monitoring,forecasting,and management.Using meteorological data from 17 national mete...It is crucial to investigate the characteristics of fire danger in the areas around Beijing to increase the accuracy of fire danger monitoring,forecasting,and management.Using meteorological data from 17 national meteorological stations in the areas around Beijing from 1981−2021,this study calculated the fire weather index(FWI)and analyzed its spatiotemporal characteristics.It was found that the high and low fire danger periods were in April−May and July−August,with spatial patterns of“decrease in the northwest−increase in the southeast”and a significant increase throughout the areas around Beijing,respectively.Next,the contributions of different meteorological factors were quantified by the multiple regression method.We found that during the high fire danger period,the northern and southern parts were affected by precipitation and minimum relative humidity,respectively.However,most areas were influenced by wind speed during the low fire danger period.Finally,comparing with the FWI characteristics under different SSP scenarios,we found that the FWI decreased during high fire danger period and increased during low fire danger period under different SSP scenarios(i.e.,SSP245,SSP585)for periods of 2021−2050,2071−2100,2021−2100,except for SSP245 in 2071−2100 with an increasing trend both in high and low fire danger periods.This study implies that there is a higher probability of FWI in the low fire danger period,threatening the ecological environment and human health.Therefore,it is necessary to enhance research on fire danger during the low fire danger period to improve the ability to predict summer fire danger.展开更多
Integrating urban spatial landscape(USL) parameters into refined climate environment assessment is important. By taking the central urban area(CUA) of Xi’an, China as an example, this study develops an evaluation met...Integrating urban spatial landscape(USL) parameters into refined climate environment assessment is important. By taking the central urban area(CUA) of Xi’an, China as an example, this study develops an evaluation method based on Urban Climatic Map(UCMap) technology. We define surface urban heat island intensity(SUHI) and surface ventilation potential coefficient(VPC), which can effectively reflect local urban climate. Based on SUHI and VPC,we analyze the influences of seven typical USL metrics including building height(BH), building density(BD), floor area ratio(FAR), sky view factor(SVF), frontal area index(FAI), surface roughness length(RL), and vegetation cover(VC). Then, we construct a comprehensive evaluation model and create an urban climate zoning map on a 100-m resolution. The climate optimization on the map is performed for configuration of possible ventilation corridors and identification of associated control indicators. The results show that the main factors affecting SUHI in the CUA of Xi’an are VC and BD, which explain 87.9% of the variation in SUHI, while VPC explains 50% of the variation in SUHI. The main factors affecting VPC are BH, FAR, FAI, and RL, all of which contribute to more than 95% of the variation in VPC. The evaluation model constructed by SUHI, VPC, and VC can divide the CUA into climate resource spaces, climate preservation spaces, climate sensitive spaces, and climate restoration spaces. On this basis, a ventilation corridor network of 3 level-1 corridors(each over 500 m wide), 6 level-2 corridors(each over 500 m wide) and 13 level-3 corridors(each over 50 m wide) is established. Meanwhile, the main quantitative control indicators selected from the USL metrics are proved to be capable of ensuring smooth implementation of the planned corridors at different levels.展开更多
Background As shown in previous studies,high brain natriuretic peptide(BNP)is one of common abnormal laboratory test results in some critical patients infected with 2019 novel coronavirus(2019-nCoV),while the role of ...Background As shown in previous studies,high brain natriuretic peptide(BNP)is one of common abnormal laboratory test results in some critical patients infected with 2019 novel coronavirus(2019-nCoV),while the role of BNP in the prognosis of coronavirus disease 2019(COVID-19)is still unknown.This study aims to investigate the effects of the increased BNP value on the outcomes of 2019-nCoV infected patients.Methods Our study initially included patients diagnosed with COVID-19 in Guangzhou Eighth People’s Hospital from January 20 th,2020 to February 24 th.After screening out the participants based on the exclusion criteria,a total of 34 participants were finally enrolled in our research for retrospective analysis.The primary outcome was severe pneumonia defined according to the international guidelines for community-acquired pneumonia.Clinical characteristics and laboratory data were collected from their medical records.Results The best cut-off value of BNP for predicting severe pneumonia was 97.5 pg/mL with the sensitivity for 80%and the specificity for 91.7%.The median age for high BNP level group(>97.5 pg/mL)was 60.5 years(interquartile range:40-80 years).The ratio of males in those patients was 60.0%.Compared with the normal BNP level group,higher temperature(P=0.09),higher values of aspartate aminotransferase(P=0.02),troponin I(P<0.001),C-reactive protein(P<0.001)and myoglobin(P=0.001)as well as lower levels of hemoglobin(P=0.04)and platelet count(P=0.001)were observed in the high BNP group.Multivariable logistic regression demonstrated that 2019-nCoV infected patients with high BNP were more likely to develop severe pneumonia(OR:17.368,P=0.025)and be admitted to the intensive care unit(OR:27.093,P=0.048).Conclusions The increased level of BNP is associated with the undesirable condition and disease aggravation of patients with COVID-19.BNP is expected to be an independent prognostic predictor of clinical outcomes for patients with COVID-19.展开更多
Background Even with percutaneous coronary intervention(PCI),patients with ST-segment elevation myocardial infarction(STEMI)faced a substantial mortality.We aimed to evaluate the relationship between the level of bili...Background Even with percutaneous coronary intervention(PCI),patients with ST-segment elevation myocardial infarction(STEMI)faced a substantial mortality.We aimed to evaluate the relationship between the level of bilirubin and mortality in patients with STEMI undergoing PCI.Methods Patients with the diagnosis of STEMI and subsequently treated with PCI was enrolled retrospectively in Guangzhou Eighth People's Hospital,from March2013 to October 2019.The primary clinical outcome was in-hospital death,and the secondary clinical outcome was one-year mortality.Results Overall,844 patients were included.The receiver-operation characteristics(ROC)curves analysis showed a higher discriminative ability for conjugated bilirubin(CB=0.805,95%CI:0.703-0.907,P<0.001)in predicting in-hospital death,compared to total bilirubin(TB).Patients were divided into a lower CB group(CB<5.7 umol/L,n=656)and a higher CB group(CB≥5.7 umol/L,n=188).There were 6(0.9%)patients died in the lower CB group,and 17(9.0%)patients died in the higher CB group(P<0.001).In the univariate Logistic regression analysis,CB≥5.7 umol/L were associated with in-hospital death(OR=10.77,P<0.001).After adjusting confounding factors,CB≥5.7 umol/L was independently correlated with in-hospital death(OR=5.13,95%CI:1.67-15.75,P=0.004).During one-year follow-up,there were 69(10.5%)patients died in the lower CB group and40(21.3%)patients died in the higher CB group(log-rank=41.90,P<0.001).The multivariate Cox regression analysis showed that CB≥5.7 umol/L was independently associated with one-year mortality(HR=2.45,95%CI:1.37-4.40,P=0.003).Conclusions CB could be a feasible biomarker in differentiating high-risk STEMI patients treated with PCI.展开更多
基金funded by the National Natural Science Foundation of China(Grant Nos.42305055,42171030 and 41901017)the Science and Technology Project of Beijing Meteorological Service(No.BMBKJ202302001)+1 种基金the Key Project of Beijing Academy of Emergency Management Science and Technology(No.Y2023046)Open Foundation of Key Laboratory of Land Surface Pattern and Simulation,Chinese Academy of Sciences.
文摘It is crucial to investigate the characteristics of fire danger in the areas around Beijing to increase the accuracy of fire danger monitoring,forecasting,and management.Using meteorological data from 17 national meteorological stations in the areas around Beijing from 1981−2021,this study calculated the fire weather index(FWI)and analyzed its spatiotemporal characteristics.It was found that the high and low fire danger periods were in April−May and July−August,with spatial patterns of“decrease in the northwest−increase in the southeast”and a significant increase throughout the areas around Beijing,respectively.Next,the contributions of different meteorological factors were quantified by the multiple regression method.We found that during the high fire danger period,the northern and southern parts were affected by precipitation and minimum relative humidity,respectively.However,most areas were influenced by wind speed during the low fire danger period.Finally,comparing with the FWI characteristics under different SSP scenarios,we found that the FWI decreased during high fire danger period and increased during low fire danger period under different SSP scenarios(i.e.,SSP245,SSP585)for periods of 2021−2050,2071−2100,2021−2100,except for SSP245 in 2071−2100 with an increasing trend both in high and low fire danger periods.This study implies that there is a higher probability of FWI in the low fire danger period,threatening the ecological environment and human health.Therefore,it is necessary to enhance research on fire danger during the low fire danger period to improve the ability to predict summer fire danger.
基金Supported by the National Key Research and Development Program of China (2018YFB1502801)Innovation and Development Project of China Meteorological Administration (CXFZ2021J046)+1 种基金Beijing Municipal Science and Technology Project (Z201100008220002)High-Level Technology and Innovative Talent Program of Beijing Meteorological Service (2021)。
文摘Integrating urban spatial landscape(USL) parameters into refined climate environment assessment is important. By taking the central urban area(CUA) of Xi’an, China as an example, this study develops an evaluation method based on Urban Climatic Map(UCMap) technology. We define surface urban heat island intensity(SUHI) and surface ventilation potential coefficient(VPC), which can effectively reflect local urban climate. Based on SUHI and VPC,we analyze the influences of seven typical USL metrics including building height(BH), building density(BD), floor area ratio(FAR), sky view factor(SVF), frontal area index(FAI), surface roughness length(RL), and vegetation cover(VC). Then, we construct a comprehensive evaluation model and create an urban climate zoning map on a 100-m resolution. The climate optimization on the map is performed for configuration of possible ventilation corridors and identification of associated control indicators. The results show that the main factors affecting SUHI in the CUA of Xi’an are VC and BD, which explain 87.9% of the variation in SUHI, while VPC explains 50% of the variation in SUHI. The main factors affecting VPC are BH, FAR, FAI, and RL, all of which contribute to more than 95% of the variation in VPC. The evaluation model constructed by SUHI, VPC, and VC can divide the CUA into climate resource spaces, climate preservation spaces, climate sensitive spaces, and climate restoration spaces. On this basis, a ventilation corridor network of 3 level-1 corridors(each over 500 m wide), 6 level-2 corridors(each over 500 m wide) and 13 level-3 corridors(each over 50 m wide) is established. Meanwhile, the main quantitative control indicators selected from the USL metrics are proved to be capable of ensuring smooth implementation of the planned corridors at different levels.
文摘Background As shown in previous studies,high brain natriuretic peptide(BNP)is one of common abnormal laboratory test results in some critical patients infected with 2019 novel coronavirus(2019-nCoV),while the role of BNP in the prognosis of coronavirus disease 2019(COVID-19)is still unknown.This study aims to investigate the effects of the increased BNP value on the outcomes of 2019-nCoV infected patients.Methods Our study initially included patients diagnosed with COVID-19 in Guangzhou Eighth People’s Hospital from January 20 th,2020 to February 24 th.After screening out the participants based on the exclusion criteria,a total of 34 participants were finally enrolled in our research for retrospective analysis.The primary outcome was severe pneumonia defined according to the international guidelines for community-acquired pneumonia.Clinical characteristics and laboratory data were collected from their medical records.Results The best cut-off value of BNP for predicting severe pneumonia was 97.5 pg/mL with the sensitivity for 80%and the specificity for 91.7%.The median age for high BNP level group(>97.5 pg/mL)was 60.5 years(interquartile range:40-80 years).The ratio of males in those patients was 60.0%.Compared with the normal BNP level group,higher temperature(P=0.09),higher values of aspartate aminotransferase(P=0.02),troponin I(P<0.001),C-reactive protein(P<0.001)and myoglobin(P=0.001)as well as lower levels of hemoglobin(P=0.04)and platelet count(P=0.001)were observed in the high BNP group.Multivariable logistic regression demonstrated that 2019-nCoV infected patients with high BNP were more likely to develop severe pneumonia(OR:17.368,P=0.025)and be admitted to the intensive care unit(OR:27.093,P=0.048).Conclusions The increased level of BNP is associated with the undesirable condition and disease aggravation of patients with COVID-19.BNP is expected to be an independent prognostic predictor of clinical outcomes for patients with COVID-19.
文摘Background Even with percutaneous coronary intervention(PCI),patients with ST-segment elevation myocardial infarction(STEMI)faced a substantial mortality.We aimed to evaluate the relationship between the level of bilirubin and mortality in patients with STEMI undergoing PCI.Methods Patients with the diagnosis of STEMI and subsequently treated with PCI was enrolled retrospectively in Guangzhou Eighth People's Hospital,from March2013 to October 2019.The primary clinical outcome was in-hospital death,and the secondary clinical outcome was one-year mortality.Results Overall,844 patients were included.The receiver-operation characteristics(ROC)curves analysis showed a higher discriminative ability for conjugated bilirubin(CB=0.805,95%CI:0.703-0.907,P<0.001)in predicting in-hospital death,compared to total bilirubin(TB).Patients were divided into a lower CB group(CB<5.7 umol/L,n=656)and a higher CB group(CB≥5.7 umol/L,n=188).There were 6(0.9%)patients died in the lower CB group,and 17(9.0%)patients died in the higher CB group(P<0.001).In the univariate Logistic regression analysis,CB≥5.7 umol/L were associated with in-hospital death(OR=10.77,P<0.001).After adjusting confounding factors,CB≥5.7 umol/L was independently correlated with in-hospital death(OR=5.13,95%CI:1.67-15.75,P=0.004).During one-year follow-up,there were 69(10.5%)patients died in the lower CB group and40(21.3%)patients died in the higher CB group(log-rank=41.90,P<0.001).The multivariate Cox regression analysis showed that CB≥5.7 umol/L was independently associated with one-year mortality(HR=2.45,95%CI:1.37-4.40,P=0.003).Conclusions CB could be a feasible biomarker in differentiating high-risk STEMI patients treated with PCI.