Résumé
Objective To study the composition and concentration of atmospheric particulate pollutants in four seasons in the industrial and clean living areas， and to provide a scientific basis for the strategy of controlling industrial pollution and atmospheric environment. Methods An industrial area dominated by the automobile industry in Shanghai and a relatively clean living area were selected. Samples were collected simultaneously in both areas and continuously for 7 days in the middle of each season. The composition and concentration of PM2.5 were determined， and the ecological risk of heavy metals in PM2.5 was evaluated by the potential ecological risk index method. Results We found PM2.5 concentration was associated with seasonal changes. The PM2.5 concentration in living areas was the highest in winter， followed by spring， and the lowest in summer. The PM2.5 concentration in industrial areas was the highest in spring， followed by winter， and the lowest in summer. The heavy metals in PM2.5 were the same， including Al， Cr， Mn， Ni， As， Cd， Hg and Pb. The content of Cr， Cd and Pb in PM2.5 in the industrial area is significantly higher than that in the living area. The potential ecological hazard coefficient of PM2.5 heavy metal Cd in the industrial zone was the highest， up to 189.47， and it was the main component of the total potential ecological hazard index of heavy metals. According to the total potential risk grade of heavy metals， the heavy metal Cd in the industrial area had different degrees of ecological harm with seasonal changes. The ecological harm degree of heavy metal Cd was the highest in winter， high in spring and autumn， and low in summer. Conclusion Although the concentration of PM2.5 in the industrial area is not higher than that in the living area， the content of Cr， Cd and Pb in the PM2.5 in the industrial area is significantly higher than that in the living area. The concentration of PM2.5 in the industrial area is mainly related to seasons， industrial production and human factors. The potential ecological harm coefficient of heavy metal Cd in PM2.5 is the highest in comparison with other heavy metals such as Cr， Hg and Pb， and it is the main component of the total potential ecological harm index ofheavy metals.
Résumé
Objective To study the composition and concentration of atmospheric particulate pollutants in four seasons in the industrial and clean living areas， and to provide a scientific basis for the strategy of controlling industrial pollution and atmospheric environment. Methods An industrial area dominated by the automobile industry in Shanghai and a relatively clean living area were selected. Samples were collected simultaneously in both areas and continuously for 7 days in the middle of each season. The composition and concentration of PM2.5 were determined， and the ecological risk of heavy metals in PM2.5 was evaluated by the potential ecological risk index method. Results We found PM2.5 concentration was associated with seasonal changes. The PM2.5 concentration in living areas was the highest in winter， followed by spring， and the lowest in summer. The PM2.5 concentration in industrial areas was the highest in spring， followed by winter， and the lowest in summer. The heavy metals in PM2.5 were the same， including Al， Cr， Mn， Ni， As， Cd， Hg and Pb. The content of Cr， Cd and Pb in PM2.5 in the industrial area is significantly higher than that in the living area. The potential ecological hazard coefficient of PM2.5 heavy metal Cd in the industrial zone was the highest， up to 189.47， and it was the main component of the total potential ecological hazard index of heavy metals. According to the total potential risk grade of heavy metals， the heavy metal Cd in the industrial area had different degrees of ecological harm with seasonal changes. The ecological harm degree of heavy metal Cd was the highest in winter， high in spring and autumn， and low in summer. Conclusion Although the concentration of PM2.5 in the industrial area is not higher than that in the living area， the content of Cr， Cd and Pb in the PM2.5 in the industrial area is significantly higher than that in the living area. The concentration of PM2.5 in the industrial area is mainly related to seasons， industrial production and human factors. The potential ecological harm coefficient of heavy metal Cd in PM2.5 is the highest in comparison with other heavy metals such as Cr， Hg and Pb， and it is the main component of the total potential ecological harm index ofheavy metals.
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Objective@#To investigate the value of MRI in the early diagnosis of diagnosis of dysbaric osteonecrosis.@*Methods@#Labor hygiene investigation and occupation health were examined on 52 high pressure operating personnel, were selected for the examination of both shoulders, hips and knees with X-ray and CT scan.@*Results@#The cystic sign in dysbaric osteonecrosis as an important imaging feature, which perform in the MRI examination for T1W I sequence showed low or slightly low signal and T2W I sequence showed high signal, and X-ray and CT have a lower detection rate than MRI. The Kappa consistency test showed a high consistency with the two methods. At the same time MRI examination also can discover the bone marrow cavity necrosis early pathological change.@*Conclusion@#MRI is an effective method for the diagnosis of early dysbaric osteonecrosis, which can improve the early diagnosis rate of dysbaric osteonecrosis.
Résumé
OBJECTIVE: To analyze the impact of revised version of GBZ 49-2014 Diagnostic of Occupational Noise-induced Deafness on the diagnosis of occupational noise-induced deafness( ONID). METHODS: A total of 77 patients applied for ONID diagnosis and identification were selected as study subjects by judgment sampling method. The pure tone audiometry data were collected and diagnosed based on the criteria of GBZ 49-2014 and GBZ 49-2007 Diagnostic Criteria of Occupational Noise-induced Deafness. The changes of the diagnostic audiometry and the ONID diagnostic classification were compared. RESULTS: The monaural threshold of weighted value of the good ear calculated by GBZ 49-2014 was higher than the speech frequency threshold average of the good ear of GBZ 49-2007 [( 32. 4 ± 10. 3) vs( 29. 8 ± 10. 6) dB,P <0. 01]. The binaural high frequency threshold average calculated by GBZ 49-2014 was higher than that of GBZ 49-2007[( 50. 5 ± 13. 3) vs( 49. 1 ± 13. 6) dB,P < 0. 01]. The ONID diagnosis conclusions diagnosed by using GBZ 49-2014 and GBZ 49-2007 were consistent( Kappa value = 0. 92,P < 0. 01). There was statistical difference in the ONID diagnostic classifications diagnosed by using GBZ 49-2014 and GBZ 49-2007( P < 0. 05). Three ONID patients diagnosed as non ONID by GBZ 49-2007 were diagnosed as mild ONID by using GBZ 49-2014,and five cases diagnosed as mild ONID by GBZ 49-2007 were diagnosed as moderate ONID by using GBZ 49-2014. CONCLUSION: The diagnostic audiometry calculated based on GBZ 49-2014 is higher than that based on GBZ 49-2007. The number of ONID patients increased and the diagnostic classification became serious when the diagnosis was made based on GBZ 49-2014.