uri,href,identifier,attrs.Abstract,attrs.Author,attrs.DOI,attrs.ISSN,attrs.Issue,attrs.Journal,attrs.Notes,attrs.Pages,attrs.Title,attrs.Volume,attrs.Year,attrs.\.reference_type,attrs._record_number,attrs._uuid,attrs.reftype,child_publication
/reference/5bd8de26-58f4-44b9-9919-885bb217bfb1,https://data.globalchange.gov/reference/5bd8de26-58f4-44b9-9919-885bb217bfb1,5bd8de26-58f4-44b9-9919-885bb217bfb1,"BACKGROUND: Models of the effects of environmental factors on West Nile virus disease risk have yielded conflicting outcomes. The role of precipitation has been especially difficult to discern from existing studies, due in part to habitat and behavior characteristics of specific vector species and because of differences in the temporal and spatial scales of the published studies. We used spatial and statistical modeling techniques to analyze and forecast fine scale spatial (2000 m grid) and temporal (weekly) patterns of West Nile virus mosquito infection relative to changing weather conditions in the urban landscape of the greater Chicago, Illinois, region for the years from 2004 to 2008. RESULTS: Increased air temperature was the strongest temporal predictor of increased infection in Culex pipiens and Culex restuans mosquitoes, with cumulative high temperature differences being a key factor distinguishing years with higher mosquito infection and higher human illness rates from those with lower rates. Drier conditions in the spring followed by wetter conditions just prior to an increase in infection were factors in some but not all years. Overall, 80% of the weekly variation in mosquito infection was explained by prior weather conditions. Spatially, lower precipitation was the most important variable predicting stronger mosquito infection; precipitation and temperature alone could explain the pattern of spatial variability better than could other environmental variables (79% explained in the best model). Variables related to impervious surfaces and elevation differences were of modest importance in the spatial model. CONCLUSION: Finely grained temporal and spatial patterns of precipitation and air temperature have a consistent and significant impact on the timing and location of increased mosquito infection in the northeastern Illinois study area. The use of local weather data at multiple monitoring locations and the integration of mosquito infection data from numerous sources across several years are important to the strength of the models presented. The other spatial environmental factors that tended to be important, including impervious surfaces and elevation measures, would mediate the effect of rainfall on soils and in urban catch basins. Changes in weather patterns with global climate change make it especially important to improve our ability to predict how inter-related local weather and environmental factors affect vectors and vector-borne disease risk.Local impact of temperature and precipitation on West Nile virus infection in Culex species mosquitoes in northeast Illinois, USA.","Ruiz, M. O.; Chaves, L. F.; Hamer, G. L.; Sun, T.; Brown, W. M.; Walker, E. D.; Haramis, L.; Goldberg, T. L.; Kitron, U. D.",10.1186/1756-3305-3-19,1756-3305,1,"Parasites & Vectors","Ruiz, Marilyn O Chaves, Luis F Hamer, Gabriel L Sun, Ting Brown, William M Walker, Edward D Haramis, Linn Goldberg, Tony L Kitron, Uriel D eng England 2010/03/23 06:00 Parasit Vectors. 2010 Mar 19;3(1):19. doi: 10.1186/1756-3305-3-19.","Article 19","Local impact of temperature and precipitation on West Nile virus infection in Culex species mosquitoes in northeast Illinois, USA",3,2010,0,18034,5bd8de26-58f4-44b9-9919-885bb217bfb1,"Journal Article",/article/10.1186/1756-3305-3-19
/reference/5c13bb5b-bd92-439c-ae58-4c226d28c0fd,https://data.globalchange.gov/reference/5c13bb5b-bd92-439c-ae58-4c226d28c0fd,5c13bb5b-bd92-439c-ae58-4c226d28c0fd,"Vibrio cholerae, the causative agent of cholera, is a naturally occurring inhabitant of the Chesapeake Bay and serves as a predictor for other clinically important vibrios, including Vibrio parahaemolyticus and Vibrio vulnificus. A system was constructed to predict the likelihood of the presence of V. cholerae in surface waters of the Chesapeake Bay, with the goal to provide forecasts of the occurrence of this and related pathogenic Vibrio spp. Prediction was achieved by driving an available multivariate empirical habitat model estimating the probability of V. cholerae within a range of temperatures and salinities in the Bay, with hydrodynamically generated predictions of ambient temperature and salinity. The experimental predictions provided both an improved understanding of the in situ variability of V. cholerae, including identification of potential hotspots of occurrence, and usefulness as an early warning system. With further development of the system, prediction of the probability of the occurrence of related pathogenic vibrios in the Chesapeake Bay, notably V. parahaemolyticus and V. vulnificus, will be possible, as well as its transport to any geographical location where sufficient relevant data are available.","Constantin de Magny, G.; Long, W.; Brown, C. W.; Hood, R. R.; Huq, A.; Murtugudde, R.; Colwell, R. R.",10.1007/s10393-009-0273-6,1612-9210,3,EcoHealth,"1612-9210 Constantin de Magny, Guillaume Long, Wen Brown, Christopher W Hood, Raleigh R Huq, Anwar Murtugudde, Raghu Colwell, Rita R 1 R01 A139129/PHS HHS/United States R01 AI039129/AI/NIAID NIH HHS/United States R01 AI039129-09/AI/NIAID NIH HHS/United States Journal Article Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S. United States Ecohealth. 2009 Sep;6(3):378-89. doi: 10.1007/s10393-009-0273-6. Epub 2010 Feb 10.",378-389,"Predicting the distribution of Vibrio spp. in the Chesapeake Bay: A Vibrio cholerae case study",6,2009,0,18416,5c13bb5b-bd92-439c-ae58-4c226d28c0fd,"Journal Article",/article/10.1007/s10393-009-0273-6
/reference/5cf35b72-dfa8-4f4d-825a-23e3c45f5895,https://data.globalchange.gov/reference/5cf35b72-dfa8-4f4d-825a-23e3c45f5895,5cf35b72-dfa8-4f4d-825a-23e3c45f5895,,"Sales-Ortells, Helena; Fernandez-Cassi, Xavier; Timoneda, Natàlia; Dürig, Wiebke; Girones, Rosina; Medema, Gertjan",10.1016/j.foodres.2014.08.018,1873-7145,,"Food Research International",,70-77,"Health risks derived from consumption of lettuces irrigated with tertiary effluent containing norovirus",68,2015,0,16209,5cf35b72-dfa8-4f4d-825a-23e3c45f5895,"Journal Article",/article/10.1016/j.foodres.2014.08.018
/reference/5d3a9428-c81f-4c38-bda4-0b475b07d947,https://data.globalchange.gov/reference/5d3a9428-c81f-4c38-bda4-0b475b07d947,5d3a9428-c81f-4c38-bda4-0b475b07d947,,"Künzli, Nino; Avol, Ed; Wu, Jun; Gauderman, W. James; Rappaport, Ed; Millstein, Joshua; Bennion, Jonathan; McConnell, Rob; Gilliland, Frank D.; Berhane, Kiros; Lurmann, Fred; Winer, Arthur; Peters, John M.",10.1164/rccm.200604-519OC,1535-4970,11,"American Journal of Respiratory and Critical Care Medicine","Ch3,7",1221-1228,"Health effects of the 2003 southern California wildfires on children",174,2006,0,16477,5d3a9428-c81f-4c38-bda4-0b475b07d947,"Journal Article",/article/10.1164/rccm.200604-519OC
/reference/5dbd8d4e-540b-4551-83e7-202589965032,https://data.globalchange.gov/reference/5dbd8d4e-540b-4551-83e7-202589965032,5dbd8d4e-540b-4551-83e7-202589965032,"OBJECTIVE: The associations between ozone concentrations measured outdoors and both morbidity and mortality may be partially due to indoor exposures to ozone and ozone-initiated oxidation products. In this article I examine the contributions of such indoor exposures to overall ozone-related health effects by extensive review of the literature as well as further analyses of published data. FINDINGS: Daily inhalation intakes of indoor ozone (micrograms per day) are estimated to be between 25 and 60% of total daily ozone intake. This is especially noteworthy in light of recent work indicating little, if any, threshold for ozone's impact on mortality. Additionally, the present study estimates that average daily indoor intakes of ozone oxidation products are roughly one-third to twice the indoor inhalation intake of ozone alone. Some of these oxidation products are known or suspected to adversely affect human health (e.g., formaldehyde, acrolein, hydroperoxides, fine and ultrafine particles). Indirect evidence supports connections between morbidity/mortality and exposures to indoor ozone and its oxidation products. For example, cities with stronger associations between outdoor ozone and mortality tend to have residences that are older and less likely to have central air conditioning, which implies greater transport of ozone from outdoors to indoors. CONCLUSIONS: Indoor exposures to ozone and its oxidation products can be reduced by filtering ozone from ventilation air and limiting the indoor use of products and materials whose emissions react with ozone. Such steps might be especially valuable in schools, hospitals, and childcare centers in regions that routinely experience elevated outdoor ozone concentrations.","Weschler, C. J.",,1552-9924,10,"Environmental Health Perspectives","Weschler, Charles J Journal Article Review United States Environ Health Perspect. 2006 Oct;114(10):1489-96.",1489-1496,"Ozone's impact on public health: Contributions from indoor exposures to ozone and products of ozone-initiated chemistry",114,2006,0,18572,5dbd8d4e-540b-4551-83e7-202589965032,"Journal Article",/article/pmc-1626413
/reference/5dda98ab-87a9-473e-ad09-7df6f6a9df5b,https://data.globalchange.gov/reference/5dda98ab-87a9-473e-ad09-7df6f6a9df5b,5dda98ab-87a9-473e-ad09-7df6f6a9df5b,,USGS,,,"December 2014",,,,"Dengue Fever (Locally Acquired) Human 2013. Cumulative data as of May 7, 2014",,2014,48,18349,5dda98ab-87a9-473e-ad09-7df6f6a9df5b,"Online Multimedia",/webpage/204e21e1-05a9-40b8-8a79-e92a7c893cff
/reference/5e1f1b01-4535-41fe-93cb-0a8c46b63645,https://data.globalchange.gov/reference/5e1f1b01-4535-41fe-93cb-0a8c46b63645,5e1f1b01-4535-41fe-93cb-0a8c46b63645,,"Kellogg, Joshua; Wang, Jinzhi; Flint, Courtney; Ribnicky, David; Kuhn, Peter; De Mejia, Elvira González; Raskin, Ilya; Lila, Mary Ann",10.1021/jf902693r,1520-5118,7,"Journal of Agricultural and Food Chemistry",,3884-3900,"Alaskan wild berry resources and human health under the cloud of climate change",58,2010,0,17642,5e1f1b01-4535-41fe-93cb-0a8c46b63645,"Journal Article",/article/10.1021/jf902693r
/reference/5f4db33c-1c7e-4129-9438-e5d8c9d589e4,https://data.globalchange.gov/reference/5f4db33c-1c7e-4129-9438-e5d8c9d589e4,5f4db33c-1c7e-4129-9438-e5d8c9d589e4,,"Yip, Fuyuen Y.; Flanders, W. Dana; Wolkin, Amy; Engelthaler, David; Humble, William; Neri, Antonio; Lewis, Lauren; Backer, Lorraine; Rubin, Carol",10.1007/s00484-008-0169-0,1432-1254,8,"International Journal of Biometeorology",,765-772,"The impact of excess heat events in Maricopa County, Arizona: 2000–2005",52,2008,0,17891,5f4db33c-1c7e-4129-9438-e5d8c9d589e4,"Journal Article",/article/10.1007/s00484-008-0169-0
/reference/5f587662-8664-420f-8045-196e2bb7ec0d,https://data.globalchange.gov/reference/5f587662-8664-420f-8045-196e2bb7ec0d,5f587662-8664-420f-8045-196e2bb7ec0d,,"Harlan, S.L.
Brazel, A.J.
Prashad, L.
Stefanov, W.L.
Larsen, L.",10.1016/j.socscimed.2006.07.030,0277-9536,11,"Social Science & Medicine",,2847-2863,"Neighborhood microclimates and vulnerability to heat stress",63,2006,0,1165,5f587662-8664-420f-8045-196e2bb7ec0d,"Journal Article",/article/10.1016/j.socscimed.2006.07.030
/reference/5f6029f9-9de1-4d32-b772-cf836ac4e048,https://data.globalchange.gov/reference/5f6029f9-9de1-4d32-b772-cf836ac4e048,5f6029f9-9de1-4d32-b772-cf836ac4e048,,"Callaghan, William M.; Rasmussen, Sonja A.; Jamieson, Denise J.; Ventura, Stephanie J.; Farr, Sherry L.; Sutton, Paul D.; Mathews, Thomas J.; Hamilton, Brady E.; Shealy, Katherine R.; Brantley, Dabo; Posner, Sam F.",10.1007/s10995-007-0177-4,1573-6628,4,"Maternal and Child Health Journal","Ch8,9",307-311,"Health concerns of women and infants in times of natural disasters: Lessons learned from Hurricane Katrina",11,2007,0,16495,5f6029f9-9de1-4d32-b772-cf836ac4e048,"Journal Article",/article/10.1007/s10995-007-0177-4
/reference/5fd34d06-188b-4a26-9a7c-40b440c261dc,https://data.globalchange.gov/reference/5fd34d06-188b-4a26-9a7c-40b440c261dc,5fd34d06-188b-4a26-9a7c-40b440c261dc,,"Curtis, Dennis; Hill, Arthur; Wilcock, Anne; Charlebois, Sylvain",10.1111/1750-3841.12646,0022-1147,10,"Journal of Food Science",,R1871-R1876,"Foodborne and waterborne pathogenic bacteria in selected Organisation for Economic Cooperation and Development (OECD) countries",79,2014,0,19109,5fd34d06-188b-4a26-9a7c-40b440c261dc,"Journal Article",/article/10.1111/1750-3841.12646
/reference/5fe6c1ab-b3eb-4181-ae3c-f42afbf13079,https://data.globalchange.gov/reference/5fe6c1ab-b3eb-4181-ae3c-f42afbf13079,5fe6c1ab-b3eb-4181-ae3c-f42afbf13079,,"Bouzid, Maha; Hooper, Lee; Hunter, Paul R.",10.1371/journal.pone.0062041,1932-6203,4,"PLoS ONE",,e62041,"The effectiveness of public health interventions to reduce the health impact of climate change: A systematic review of systematic reviews",8,2013,0,19140,5fe6c1ab-b3eb-4181-ae3c-f42afbf13079,"Journal Article",/article/10.1371/journal.pone.0062041
/reference/6013994a-8717-4a99-935a-8a13800fcdc5,https://data.globalchange.gov/reference/6013994a-8717-4a99-935a-8a13800fcdc5,6013994a-8717-4a99-935a-8a13800fcdc5,"A rapidly growing body of research examines whether human conflict can be affected by climatic changes. Drawing from archaeology, criminology, economics, geography, history, political science, and psychology, we assemble and analyze the 60 most rigorous quantitative studies and document, for the first time, a striking convergence of results. We find strong causal evidence linking climatic events to human conflict across a range of spatial and temporal scales and across all major regions of the world. The magnitude of climate's influence is substantial: for each one standard deviation (1sigma) change in climate toward warmer temperatures or more extreme rainfall, median estimates indicate that the frequency of interpersonal violence rises 4% and the frequency of intergroup conflict rises 14%. Because locations throughout the inhabited world are expected to warm 2sigma to 4sigma by 2050, amplified rates of human conflict could represent a large and critical impact of anthropogenic climate change.","Hsiang, S. M.; Burke, M.; Miguel, E.",10.1126/science.1235367,1095-9203,6151,Science,"Hsiang, Solomon M Burke, Marshall Miguel, Edward Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. United States Science. 2013 Sep 13;341(6151):1235367. doi: 10.1126/science.1235367. Epub 2013 Aug 1.",1235367,"Quantifying the influence of climate on human conflict",341,2013,0,4568,6013994a-8717-4a99-935a-8a13800fcdc5,"Journal Article",/article/10.1126/science.1235367
/reference/603533d6-fc3b-479b-b9d5-3b690e9622c9,https://data.globalchange.gov/reference/603533d6-fc3b-479b-b9d5-3b690e9622c9,603533d6-fc3b-479b-b9d5-3b690e9622c9,,"Normand, Sharon-Lise T.",10.1002/(SICI)1097-0258(19990215)18:3<321::AID-SIM28>3.0,,3,"Statistics in Medicine",,321-359,"Meta-analysis: Formulating, evaluating, combining, and reporting",18,1999,0,19269,603533d6-fc3b-479b-b9d5-3b690e9622c9,"Journal Article",/article/10.1002/(SICI)1097-0258(19990215)18:3%3C321::AID-SIM28%3E3.0.CO;2-P
/reference/6038a20c-1651-4ec8-a0c3-67f9568ce32b,https://data.globalchange.gov/reference/6038a20c-1651-4ec8-a0c3-67f9568ce32b,6038a20c-1651-4ec8-a0c3-67f9568ce32b,,"Polley, Lydden; Thompson, R. C. Andrew",10.1016/j.pt.2009.03.007,1471-4922,6,"Trends in Parasitology",,285-291,"Parasite zoonoses and climate change: Molecular tools for tracking shifting boundaries",25,2009,0,17936,6038a20c-1651-4ec8-a0c3-67f9568ce32b,"Journal Article",/article/10.1016/j.pt.2009.03.007
/reference/603e74e7-cfae-45ff-bf78-4c38f32aa678,https://data.globalchange.gov/reference/603e74e7-cfae-45ff-bf78-4c38f32aa678,603e74e7-cfae-45ff-bf78-4c38f32aa678,"This study is the first to report a quantitative microbial risk assessment (QMRA) on pathogens detected in stormwater discharges-of-concern, rather than relying on pathogen measurements in receiving waters. The pathogen concentrations include seven ""Reference Pathogens"" identified by the U.S. EPA: Cryptosporidium, Giardia, Salmonella, Norovirus, Rotavirus, Enterovirus, and Adenovirus. Data were collected from 12 sites representative of seven discharge types (including residential, commercial/industrial runoff, agricultural runoff, combined sewer overflows, and forested land), mainly during wet weather conditions during which times human health risks can be substantially elevated. The risks calculated herein therefore generally apply to short-term conditions (during and just after rainfall events) and so the results can be used by water managers to potentially inform the public, even for waters that comply with current criteria (based as they are on a 30-day mean risk). Using an example waterbody and mixed source, pathogen concentrations were used in QMRA models to generate risk profiles for primary and secondary water contact (or inhalation) by adults and children. A number of critical assumptions and considerations around the QMRA analysis are highlighted, particularly the harmonization of the pathogen concentrations measured in discharges during this project with those measured (using different methods) during the published dose-response clinical trials. Norovirus was the most dominant predicted health risk, though further research on its dose-response for illness (cf. infection) is needed. Even if the example mixed-source concentrations of pathogens had been reduced 30 times (by inactivation and mixing), the predicted swimming-associated illness rates - largely driven by Norovirus infections - can still be appreciable. Rotavirus generally induced the second-highest incidence of risk among the tested pathogens while risks for the other Reference Pathogens (. Giardia, Cryptosporidium, Adenovirus, Enterovirus and Salmonella) were considerably lower. Secondary contact or inhalation resulted in considerable reductions in risk compared to primary contact. Measurements of Norovirus and careful incorporation of its concentrations into risk models (harmonization) should be a critical consideration for future QMRA efforts. The discharge-based QMRA approach presented herein is particularly relevant to cases where pathogens cannot be reliably detected in receiving waters with detection limits relevant to human health effects. © 2013 Elsevier Ltd.","McBride, G. B.; Stott, R.; Miller, W.; Bambic, D.; Wuertz, S.",10.1016/j.watres.2013.06.001,1879-2448,14,"Water Research","Export Date: 7 November 2013 Source: Scopus CODEN: WATRA Language of Original Document: English Correspondence Address: McBride, G.B.; NIWA (National Institute of Water and Atmospheric Research), P.O. Box 11-115, Hamilton 3251, New Zealand; email: Graham.McBride@niwa.co.nz",5282-5297,"Discharge-based QMRA for estimation of public health risks from exposure to stormwater-borne pathogens in recreational waters in the United States",47,2013,0,4814,603e74e7-cfae-45ff-bf78-4c38f32aa678,"Journal Article",/article/10.1016/j.watres.2013.06.001
/reference/605336f7-2093-4f4b-af58-fb7a1e0f2566,https://data.globalchange.gov/reference/605336f7-2093-4f4b-af58-fb7a1e0f2566,605336f7-2093-4f4b-af58-fb7a1e0f2566,,"Ebbeling, Cara B.; Swain, Janis F.; Feldman, Henry A.; Wong, William W.; Hachey, David L.; Garcia-Lago, Erica; Ludwig, David S.",10.1001/jama.2012.6607,0098-7484,24,"JAMA: The Journal of the American Medical Association",,2627-2634,"Effects of dietary composition on energy expenditure during weight-loss maintenance",307,2012,0,16186,605336f7-2093-4f4b-af58-fb7a1e0f2566,"Journal Article",/article/10.1001/jama.2012.6607
/reference/6066212c-7cfd-46af-8255-e6c75647167a,https://data.globalchange.gov/reference/6066212c-7cfd-46af-8255-e6c75647167a,6066212c-7cfd-46af-8255-e6c75647167a,,CDC,,,,,,,"Lyme Disease: Data and Statistics: Maps- Reported Cases of Lyme Disease – United States, 2001-2014",2014c,2015,16,18328,6066212c-7cfd-46af-8255-e6c75647167a,"Web Page",/webpage/eee6fd2b-9f99-47da-99db-7a1057e33343
/reference/60783c5d-29e5-4c49-9c08-95e9bdfabf1d,https://data.globalchange.gov/reference/60783c5d-29e5-4c49-9c08-95e9bdfabf1d,60783c5d-29e5-4c49-9c08-95e9bdfabf1d,,"Samoli, Evangelia; Analitis, Antonis; Touloumi, Giota; Schwartz, Joel; Anderson, Hugh R.; Sunyer, Jordi; Bisanti, Luigi; Zmirou, Denis; Vonk, Judith M.; Pekkanen, Juha; Goodman, Pat; Paldy, Anna; Schindler, Christian; Katsouyanni, Klea",10.1289/ehp.7387,1552-9924,1,"Environmental Health Perspectives",,88-95,"Estimating the exposure-response relationships betwen particulate matter and mortality within the APHEA multicity project",113,2005,0,19270,60783c5d-29e5-4c49-9c08-95e9bdfabf1d,"Journal Article",/article/10.1289/ehp.7387
/reference/60be18ee-b5bc-4503-8f77-102561b193fb,https://data.globalchange.gov/reference/60be18ee-b5bc-4503-8f77-102561b193fb,60be18ee-b5bc-4503-8f77-102561b193fb,,"Du, Weiwei; FitzGerald, Gerard Joseph; Clark, Michele; Hou, Xiang-Yu",10.1017/S1049023X00008141,1945-1938,03,"Prehospital and Disaster Medicine",,265-272,"Health impacts of floods",25,2010,0,17818,60be18ee-b5bc-4503-8f77-102561b193fb,"Journal Article",/article/10.1017/S1049023X00008141
/reference/60c1199f-692f-4e77-bd9b-15ae136141e7,https://data.globalchange.gov/reference/60c1199f-692f-4e77-bd9b-15ae136141e7,60c1199f-692f-4e77-bd9b-15ae136141e7,,"Pastor, M.
Bullard, R.D.
Boyce, J.K.
Fothergill, A.
Morello-Frosch, R.
Wright, B.",,,,,,,"In the Wake of the Storm: Environment, Disaster, and Race After Katrina",,2006,1,2437,60c1199f-692f-4e77-bd9b-15ae136141e7,Book,/report/russellsagefoundation-in-the-wake-of-the-storm-2006
/reference/60c98535-ad37-43fa-b0fd-e7c850782d13,https://data.globalchange.gov/reference/60c98535-ad37-43fa-b0fd-e7c850782d13,60c98535-ad37-43fa-b0fd-e7c850782d13,,"Hoshiko, Sumi; English, Paul; Smith, Daniel; Trent, Roger",10.1007/s00038-009-0060-8,1661-8564,2,"International Journal of Public Health",,133-137,"A simple method for estimating excess mortality due to heat waves, as applied to the 2006 California heat wave",55,2010,0,17600,60c98535-ad37-43fa-b0fd-e7c850782d13,"Journal Article",/article/10.1007/s00038-009-0060-8
/reference/60d14b73-614b-4375-96cd-623566b329f4,https://data.globalchange.gov/reference/60d14b73-614b-4375-96cd-623566b329f4,60d14b73-614b-4375-96cd-623566b329f4,,"Murazaki, K.; Hess, P.",10.1029/2005JD005873,2169-8996,D5,"Journal of Geophysical Research: Atmospheres",,D05301,"How does climate change contribute to surface ozone change over the United States?",111,2006,0,19309,60d14b73-614b-4375-96cd-623566b329f4,"Journal Article",/article/10.1029/2005JD005873
/reference/60f709c9-4868-477a-9904-d585f844c256,https://data.globalchange.gov/reference/60f709c9-4868-477a-9904-d585f844c256,60f709c9-4868-477a-9904-d585f844c256,,"Choi, Hyunok; Rauh, Virginia; Garfinkel, Robin; Tu, Yihsuan; Perera, Frederica P.",10.1289/ehp.10958,1552-9924,5,"Environmental Health Perspectives",,658-665,"Prenatal exposure to airborne polycyclic aromatic hydrocarbons and risk of intrauterine growth restriction",116,2008,0,16392,60f709c9-4868-477a-9904-d585f844c256,"Journal Article",/article/10.1289/ehp.10958
/reference/60fcb251-3b4a-4606-9436-a12e13afac67,https://data.globalchange.gov/reference/60fcb251-3b4a-4606-9436-a12e13afac67,60fcb251-3b4a-4606-9436-a12e13afac67,,CDC,,,32,"MMWR. Morbidity and Mortality Weekly Report",,702-715,"Notice to readers: Final 2013 Reports of Nationally Notifiable Infectious Diseases",63,2014,0,16521,60fcb251-3b4a-4606-9436-a12e13afac67,"Journal Article",/article/pmid-25272402