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1 10. 10. 12 1. 12 2. 12. 13 2 14 2.1 14 2.2 17 2.3 18 2.4 19 2.5 21 (1) 21 (2) DNA 23 (3) 24 (4) 16S rrna 25 (5) (Polymerase chain reaction, PCR) 26 (6) PCR Primer 27 2.6 28. / 28-4 -

(1) Bioaerosol 28 (2) Bioaerosol 32 (3) Microbial Risk Assessment 44 (4) 48 (5) Road map 50. 50 (1) 50 (2) NGS 52 (3) / 71 (4) NGS 73 (5) qpcr / Pathogen 74 (6) / Pathogen likeness 79 (7) NGS / 82. 89 (1) 90 (2) 90 (3) 91 (4) MLST 95 (5) API test 96. 98 2.7 121 2.8 122 3 124-5 -

< > < 2-1> 30 < 2-2> Bioaerosol 32 < 2-3> NGS 34 < 2-4> Data analysis pipeline 39 < 2-5> Road map 50 < 2-6> 51 < 2-7> DNA Purity 53 < 2-8> linker-barcode-primer set 58 < 2-9> PCR 59 < 2-10> Filtering sequence 62 < 2-11> T-test 73 < 2-12> qpcr primer set 76 < 2-13> Bacillus pathogen 81 < 2-14> Neisseria pathogen 81 < 2-15> Mock community error rate 88 < 2-16> / 90 < 2-17> / 91 < 2-18> Sequencing primer 92 < 2-19> / 92 < 2-20> B. cereus group MLST 95 < 2-21> 97 < 2-22> 2011 4, 5,, PM 2.5, PM 2.5 (r) 102 < 2-23> 4, 5 106 < 2-24> 2011 8, 9 PM 10,, PM 10 (r) 113 < 2-25> 8, 9 (ug/m 3 ) a 116-6 -

< 2-26> data data (r) 120 < > < 2-1> Bioaerosol 1 1 < 2-2> 41 < 2-3> DNA 3 2 < 2-4> DNA 4 2 < 2-5> DNA 5 2 < 2-6> 3 PCR 7 2 < 2-7> / 82 < 2-8> / PCA 9 2 < 2-9> Richness Length 1 3 < 2-10> 1 3 < 2-11> MLST 6 3 < 2-12> NGS error 7 3 < 2-13> Mock Community NGS error 7 3 < 2-14> 16S rrna data analysis pipeline 8 3 < 2-15> fungi 0 4 < 2-16> Fungi data base 1 4 < 2-17> Virus protocol 2 4 < 2-18> virus type 3 4 < 2-19> Virus data base 4 4 < 2-20> International Network 5 4 < 2-21> CAMRA 5 4 < 2-22> Longterm monitoring DB 6 4 < 2-23> 8 4 < 2-24> BioWatch system 8 4-7 -

< 2-25> Longterm monitoring Source control 9 4 < 2-26> Microbial risk early warning forecast system 9 4 < 2-27> NGS Process 2 5 < 2-28> RDP classification Accuracy 4 5 < 2-29> NGS 16S rrna tanderm region full length 5 5 < 2-30> NGS 16S rrna region detecting 6 5 < 2-31> High fidelity Taq polymerase(accuprime) Taq polymerase 7 5 < 2-32> Sequence 8 5 < 2-33> microbial community 1 2 7 < 2-34> microbial community 2 2 7 < 2-35> SYBR Green qpcr 5 7 < 2-36> Taqman probe qpcr 5 7 < 2-37> qpcr standard curve ( ) melting curve ( ) 7 7 < 2-38> qpcr 8 7 < 2-39> qpcr bcet 8 7 < 2-40> / pathogen likeness 0 8 < 2-41> Mock community control 2 8 < 2-42> Mock community 3 8 < 2-43> Mock community error process 4 8 < 2-44> Pylum level Mock community reproducibility 7 8 < 2-45> Genus level Mock community reproducibility 7 8 < 2-46> 16S rrna error rate pattern 9 8 < 2-47> B. thuringiensis (3-LB-3) database 6 9 < 2-48> 2011 4,5 9 9 < 2-49> 2011 4,5 PM 2.5 101 < 2-50> 4,5 3 72 40 1 < 2-51> 5/1-3 50 1 < 2-52> 4/30-5/3 Terra MODIS AOD, AE 9 0 1 < 2-53> 2011 8,9 PM 10 111-8 -

< 2-54> 8,9 72 115 < 2-55> / PCA 18-9 -

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샘플링지역선정 황사내미생물의 위해성평가 - 19 -

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샘플링관련 황사내미생물의 위해성평가관련 - 21 -

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μ - 59 -

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1) Ritalahti et al., 2006, Appl. Environ. Microbiol. 2) Ferris et al., 1996, Appl. Environ. Microbiol. 3) Lane, 1991, John Wiley & Sons. 4) Shannon et al., 2007-76 -

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2011. 8.19~8. 20 2011. 9.02~9. 03 1-B-1- New New New 37 14 44 25 2 (8) (2) (7) 1-B-2 37 New New New 14 44 25 (8) (2) (7) 3-B-3 87 New New New New 78 41 (26) (42) (91) (30) 3-LB-1 New New 133 46 4 114 37-1 (126) (7) New 3-LB-2 New New New 36 New New (118) (49) New New New (505) New (509) New 3-LB-3 12 8 8 14 9 12 7 184-95 -

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μ μ - 98 -

μ μ μ μ μ 300 PM 10 WS Precipitation 5 80 PM 10 (mg/m 3 ) 4 200 3 100 2 1 0 0 4/3 4/10 4/17 4/24 5/1 5/8 5/15 5/22 SO 2 CO 8 1 Wind Speed (m/s) 60 40 20 0 Precipitation (mm) SO 2 (ppb) 6 4 0.8 0.6 0.4 CO (ppm) NO 2, O 3 (ppb) 2 0.2 4/3 4/10 4/17 4/24 5/1 5/8 5/15 5/22 NO 2 O 3 60 50 40 30 20 10 0 4/3 4/10 4/17 4/24 5/1 5/8 5/15 5/22-99 -

μ - 100 -

300 PM 10 PM 2.5 Precipitation 60 80 PM 10 (mg/m 3 ) 200 100 0 0 4/3 4/10 4/17 4/24 5/1 5/8 5/15 5/22 40 20 PM 2.5 (mg/m 3 ) 60 40 20 0 Precipitation (mm) SO 4 2- (mg/m 3 ) 20 16 12 8 4 SO 4 2- NO 3 - Ca 2+ 16 12 8 4 NO 3 - (mg/m 3 ) 4 3 2 1 Ca 2+ (mg/m 3 ) 0 0 4/3 4/10 4/17 4/24 5/1 5/8 5/15 5/22 OC EC 8 0 OC, EC (mg/m 3 ) 6 4 2 0 4/3 4/10 4/17 4/24 5/1 5/8 5/15 5/22-101 -

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μ (a) 4/17-23 4/20 4/19 4/22 4/21-103 -

(b) 4/24-30 4/29 4/28 4/26 4/27 4/30 (c) 5/1-7 5/3 5/4 5/2 5/1 5/7-104 -

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μ μ μ μ μ μ μ μ μ μ μ μ - 106 -

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PM 10 WS Precipitation 80 5 25 PM 10 (mg/m 3 ) 60 4 3 40 2 20 1 0 0 8/14 8/21 8/28 9/4 9/11 9/18 9/25 10/2 Wind Speed (m/s) 20 15 10 5 0 Precipitation (mm) SO 4 2- (mg/m 3 ) 25 20 15 10 5 SO 4 2- NO 3 - Ca 2+ 8 6 4 2 NO 3 - (mg/m 3 ) 4 3 2 1 Ca 2+ (mg/m 3 ) 0 8/14 8/21 8/28 9/4 9/11 9/18 9/25 10/2 0 0 12 OC EC OC, EC (mg/m 3 ) 8 4 0 8/14 8/21 8/28 9/4 9/11 9/18 9/25 10/2-111 -

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(a) 8/14-20 8/20 8/18-19 8/17 8/14-16 (b) 8/21-27 8/21-23 - 114 -

μ - 116 -

μ μ μ μ μ μ μ μ μ μ μ - 117 -

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Characterizing Bacterial Community in Seoul during Asian Dust - 122 -

시간일정비고 15:30 ~ 16:00 등록인사말 16:00 ~ 16:10 ( 참석자소개 ) New technologies for assessing 16:10 ~ 16:50 microbial risk from aerial transport 김종춘과장국립환경과학원 James M. Tiedje Michigan State University 16:50 ~ 17:00 Coffee Break 17:00 ~ 18:00 황사의미생물위해도평가를위한기반연구 18:00 ~ 19:00 토의및자문 박준홍연세대학교 James M. Tiedje (MSU) 김용표교수 ( 이화여대 ) 김영성교수 ( 외국어대 ) 임영운교수 ( 서울대 ) 배진우교수 ( 경희대 ) - 123 -

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