Land use regression （LUR） model was employed to predict the spatial concentration distribution of NO2 and PM10 in the Tianjin region based on the environmental air quality monitoring data. Four multiple linear regre...Land use regression （LUR） model was employed to predict the spatial concentration distribution of NO2 and PM10 in the Tianjin region based on the environmental air quality monitoring data. Four multiple linear regression （MLR） equations were established based on the most significant variables for NO2 in heating season （R2 = 0.74）, and non-heating season （R2 = 0.61） in the whole study area; and PM10 in heating season （R2 = 0.72）, and non-heating season （R2 = 0.49）. Maps of spatial concentration distribution for NO2 and PM10 were obtained based on the MLR equations （resolution is 10 krn）. Intercepts of MLR equations were 0.050 （NOz, heating season）, 0.035 （NO2, non-heating season）, 0.068 （PM10, heating season）, and 0.092 （PM10, non-beating season） in the whole study area. In the central area of Tianjin region, the intercepts were 0.042 （NO2, heating season）, 0.043 （NO2, non-heating season）, 0.087 （PM10, heating season）, and 0.096 （PMl0, non-heating season）. These intercept values might imply an area＇s background concentrations. Predicted result derived from LUR model in the central area was better than that in the whole study area. Rz values increased 0.09 （heating season） and 0.18 （non-heating season） for NO2, and 0.08 （heating season） and 0.04 （non-heating season） for PMl0. In terms of R2, LUR model performed more effectively in heating season than non-heating season in the study area and gave a better result for NOz compared with PM10.展开更多
The loss of a pregnancy,including ectopic pregnancy(EP)and early pregnancy loss(EPL),significantly impacts women’s quality of life.Unfortunately,definitive causes can be identified in less than half of EP and EPL cas...The loss of a pregnancy,including ectopic pregnancy(EP)and early pregnancy loss(EPL),significantly impacts women’s quality of life.Unfortunately,definitive causes can be identified in less than half of EP and EPL cases,presenting a substantial challenge for clinical treatment.Previous studies have revealed a significant relationship between the history of EPL and the increased risk of EP.1 Nevertheless,the interplay between EPL and EP remains unclear,highlighting the need to discover novel biomarkers to guide personalized treatment and clinical management.展开更多
PM2.5 samples for 24h were collected during winter in Tianjin, China. The ambient mass concentration and chemical composition of the PM2.5 were determined. Ionic species were analyzed by ion chromatography, while carb...PM2.5 samples for 24h were collected during winter in Tianjin, China. The ambient mass concentration and chemical composition of the PM2.5 were determined. Ionic species were analyzed by ion chromatography, while carbonaceous species were determined with the IMPROVE thermal optical reflectance （TOR） method, and inorganic elements were measured by inductively coupled plasma-atomic emission spectrometer. The daily PM2.5 mass concentrations ranged from 48.2 to 319.2 μg/m^3 with an arithmetic average of 144.6 μg/m^3. The elevated PM2.5 in winter was mostly attributed to combustion sources such as vehicle exhaust, heating, cooking and industrial emissions, low wind speeds and high relative humidity （RH）, which were favorable for pollutant accumulation and formation of secondary pollutants. By chemical mass balance, it was estimated that about 89.1% of the PM2.5 mass concentrations were explained by carbonaceous species, secondary particles, crustal matters, sea salt and trace elements. Organic material was the largest contributor, accounting for about 32.7% of the total PM2.5 mass concentrations. SO4^2-, NO3^-, Cl^- and NH4^＋ were four major ions, accounting for 16.6%, 11.5%, 4.7% and 6,0%, respectively, of the total mass of PM2.5.展开更多
基金supported by the Special Environmental Research Funds for Public Welfare (No. 200709048,200909005)the National Natural Science Foundation of China (No. 20677030)
文摘Land use regression （LUR） model was employed to predict the spatial concentration distribution of NO2 and PM10 in the Tianjin region based on the environmental air quality monitoring data. Four multiple linear regression （MLR） equations were established based on the most significant variables for NO2 in heating season （R2 = 0.74）, and non-heating season （R2 = 0.61） in the whole study area; and PM10 in heating season （R2 = 0.72）, and non-heating season （R2 = 0.49）. Maps of spatial concentration distribution for NO2 and PM10 were obtained based on the MLR equations （resolution is 10 krn）. Intercepts of MLR equations were 0.050 （NOz, heating season）, 0.035 （NO2, non-heating season）, 0.068 （PM10, heating season）, and 0.092 （PM10, non-beating season） in the whole study area. In the central area of Tianjin region, the intercepts were 0.042 （NO2, heating season）, 0.043 （NO2, non-heating season）, 0.087 （PM10, heating season）, and 0.096 （PMl0, non-heating season）. These intercept values might imply an area＇s background concentrations. Predicted result derived from LUR model in the central area was better than that in the whole study area. Rz values increased 0.09 （heating season） and 0.18 （non-heating season） for NO2, and 0.08 （heating season） and 0.04 （non-heating season） for PMl0. In terms of R2, LUR model performed more effectively in heating season than non-heating season in the study area and gave a better result for NOz compared with PM10.
基金supported by the Hangzhou Joint Fund of the Zhejiang Provincial Natural Science Foundation of China(No.LHZSD24H290001).
文摘The loss of a pregnancy,including ectopic pregnancy(EP)and early pregnancy loss(EPL),significantly impacts women’s quality of life.Unfortunately,definitive causes can be identified in less than half of EP and EPL cases,presenting a substantial challenge for clinical treatment.Previous studies have revealed a significant relationship between the history of EPL and the increased risk of EP.1 Nevertheless,the interplay between EPL and EP remains unclear,highlighting the need to discover novel biomarkers to guide personalized treatment and clinical management.
基金supported by National Natural Science Foundation of China (Grant No. 20677030)Tianjin Science and Technology Development Commission (Grant No. 06YFSYSF02900)
文摘PM2.5 samples for 24h were collected during winter in Tianjin, China. The ambient mass concentration and chemical composition of the PM2.5 were determined. Ionic species were analyzed by ion chromatography, while carbonaceous species were determined with the IMPROVE thermal optical reflectance （TOR） method, and inorganic elements were measured by inductively coupled plasma-atomic emission spectrometer. The daily PM2.5 mass concentrations ranged from 48.2 to 319.2 μg/m^3 with an arithmetic average of 144.6 μg/m^3. The elevated PM2.5 in winter was mostly attributed to combustion sources such as vehicle exhaust, heating, cooking and industrial emissions, low wind speeds and high relative humidity （RH）, which were favorable for pollutant accumulation and formation of secondary pollutants. By chemical mass balance, it was estimated that about 89.1% of the PM2.5 mass concentrations were explained by carbonaceous species, secondary particles, crustal matters, sea salt and trace elements. Organic material was the largest contributor, accounting for about 32.7% of the total PM2.5 mass concentrations. SO4^2-, NO3^-, Cl^- and NH4^＋ were four major ions, accounting for 16.6%, 11.5%, 4.7% and 6,0%, respectively, of the total mass of PM2.5.
