Classroom indoor PM2.5 sources and exposures in inner-city schools

被引:68
作者
Carrion-Matta, Aleshka [1 ]
Kang, Choong-Min [1 ]
Gaffin, Jonathan M. [2 ,3 ]
Hauptman, Marissa [2 ,4 ]
Phipatanakul, Wanda [2 ,5 ]
Koutrakis, Petros [1 ]
Gold, Diane R. [1 ,2 ,6 ]
机构
[1] Harvard TH Chan Sch Publ Hlth, Dept Environm Hlth, Boston, MA 02115 USA
[2] Harvard Med Sch, Boston, MA 02115 USA
[3] Boston Childrens Hosp, Div Resp Dis, Boston, MA USA
[4] Boston Childrens Hosp, Div Gen Pediat, Boston, MA USA
[5] Boston Childrens Hosp, Div Allergy & Immunol, Boston, MA USA
[6] Brigham & Womens Hosp, Channing Div Network Med, 75 Francis St, Boston, MA 02115 USA
基金
美国国家卫生研究院;
关键词
Source apportionment; Sulfur ratio; Inner-city environment; Classrooms; Indoor air quality; Schools; POSITIVE MATRIX FACTORIZATION; PARTICULATE MATTER; AIR-POLLUTION; ELEMENTAL COMPOSITION; CHILDREN; QUALITY; FINE; INFILTRATION; SULFUR; IMPACT;
D O I
10.1016/j.envint.2019.104968
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Children spend over 6 h a day in schools and have higher asthma morbidity from school environmental exposures. The present study aims to determine indoor and outdoor possible sources affecting indoor PM2.5 in classrooms. Weeklong indoor PM2.5 samples were collected from 32 inner-city schools from a Northeastern U.S. community during three seasons (fall, winter and spring) during the years 2009 to 2013. Concurrently, daily outdoor PM2.5 samples were taken at a central monitoring site located at a median distance of 4974m (range 1065-11,592 m) from the schools. Classroom indoor concentrations of PM2.5 (an average of 5.2 mu g/m(3)) were lower than outdoors (an average of 6.5 mu g/m(3)), and these averages were in the lower range compared to the findings in other schools' studies. The USEPA PMF model was applied to the PM2.5 components measured simultaneously from classroom indoor and outdoor to estimate the source apportionment. The major sources (contributions) identified across all seasons of indoor PM2.5 were secondary pollution (41%) and motor vehicles (17%), followed by Calcium (Ca)-rich particles (12%), biomass burning (15%), soil dust (6%), and marine aerosols (4%). Likewise, the major sources of outdoor PM2.5 across all seasons were secondary pollution (41%) and motor vehicles (26%), followed by biomass burning (17%), soil dust (7%), road dust (3%), and marine aerosols (1%). Secondary pollution was the greatest contributor to indoor and outdoor PM2.5 over all three seasons, with the highest contribution during spring with 53% to indoor PM2.5 and 45% to outdoor PM2.5. Lower contributions of this source during fall and winter are most likely attributed to less infiltration indoors. In contrast, the indoor contribution of motor vehicles source was highest in the fall (29%) and winter (25%), which was presumably categorized by a local source. From the relationship between indoor-to-outdoor sulfur ratios and each source contribution, we also estimated the local and regional influence on indoor PM2.5 concentration. Overall, the observed differences to indoor PM2.5 are related to seasonality, and the distinct characteristics and behavior of each classroom/school.
引用
收藏
页数:15
相关论文
共 49 条
[1]   Children exposure to atmospheric particles in indoor of Lisbon primary schools [J].
Almeida, Susana Marta ;
Canha, Nuno ;
Silva, Ana ;
Freitas, Maria do Carmo ;
Pegas, Priscilla ;
Alves, Celia ;
Evtyugina, Margarita ;
Pio, Casimiro Adriao .
ATMOSPHERIC ENVIRONMENT, 2011, 45 (40) :7594-7599
[2]   Impact of commuting exposure to traffic-related air pollution on cognitive development in children walking to school [J].
Alvarez-Pedrerol, Mar ;
Rivas, Ioar ;
Lopez-Vicente, Monica ;
Suades-Gonzalez, Elisabet ;
Donaire-Gonzalez, David ;
Cirach, Marta ;
de Castro, Montserrat ;
Esnaola, Mikel ;
Basagana, Xavier ;
Dadvand, Payam ;
Nieuwenhuijsen, Mark ;
Sunyer, Jordi .
ENVIRONMENTAL POLLUTION, 2017, 231 :837-844
[3]   Sources of indoor and outdoor PM2.5 concentrations in primary schools [J].
Amato, F. ;
Rivas, I. ;
Viana, M. ;
Moreno, T. ;
Bouso, L. ;
Reche, C. ;
Alvarez-Pedrerol, M. ;
Alastuey, A. ;
Sunyer, J. ;
Querol, X. .
SCIENCE OF THE TOTAL ENVIRONMENT, 2014, 490 :757-765
[4]  
[Anonymous], 2016, ATMOSPHERIC CHEM PHY
[5]   Neurodevelopmental Deceleration by Urban Fine Particles from Different Emission Sources: A Longitudinal Observational Study [J].
Basagana, Xavier ;
Esnaola, Mikel ;
Rivas, Ioar ;
Amato, Fulvio ;
Alvarez-Pedrerol, Mar ;
Forns, Joan ;
Lopez-Vicente, Monica ;
Pujol, Jesus ;
Nieuwenhuijsen, Mark ;
Querol, Xavier ;
Sunyer, Jordi .
ENVIRONMENTAL HEALTH PERSPECTIVES, 2016, 124 (10) :1630-1636
[6]   Personal exposure to PM2.5 among high-school students in Milan and background measurements: The EuroLifeNet study [J].
Borgini, A. ;
Tittarelli, A. ;
Ricci, C. ;
Bertoldi, M. ;
De Saeger, E. ;
Crosignani, P. .
ATMOSPHERIC ENVIRONMENT, 2011, 45 (25) :4147-4151
[7]   Indoor/Outdoor Relationships and Anthropogenic Elemental Signatures in Airborne PM2.5 at a High School: Impacts of Petroleum Refining Emissions on Lanthanoid Enrichment [J].
Bozlaker, Ayse ;
Peccia, Jordan ;
Chellam, Shankararaman .
ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2017, 51 (09) :4851-4859
[8]   Impact of wood burning on indoor PM2.5 in a primary school in rural Portugal [J].
Canha, Nuno ;
Almeida, Susana Marta ;
Freitas, Maria do Carmo ;
Wolterbeek, Hubert Th ;
Cardoso, Joao ;
Pio, Casimiro ;
Caseiro, Alexandre .
ATMOSPHERIC ENVIRONMENT, 2014, 94 :663-670
[9]  
Chatzidiakou L, 2012, INTELL BUILD INT, V4, P228, DOI [10.1080/17508975.2012.725530, 10.1080/17508975.2012.72530]
[10]   Indoor air quality investigations in a naturally ventilated school building located close to an urban roadway in Chennai, India [J].
Chithra, V. S. ;
Nagendra, S. M. Shiva .
BUILDING AND ENVIRONMENT, 2012, 54 :159-167