uri,href,identifier,attrs.Abstract,attrs.Author,attrs.DOI,attrs.Date,attrs.ISSN,attrs.Journal,attrs.Keywords,attrs.Pages,attrs.Title,attrs.Volume,attrs.Year,attrs._record_number,attrs._uuid,attrs.reftype,child_publication
/reference/176f1216-a5cf-4ad9-852d-3bf41a0d87ec,https://data.globalchange.gov/reference/176f1216-a5cf-4ad9-852d-3bf41a0d87ec,176f1216-a5cf-4ad9-852d-3bf41a0d87ec,"This paper introduces a scalable ""climate health justice"" model for assessing and projecting incidence, treatment costs, and sociospatial disparities for diseases with well-documented climate change linkages. The model is designed to employ low-cost secondary data, and it is rooted in a perspective that merges normative environmental justice concerns with theoretical grounding in health inequalities. Since the model employs International Classification of Diseases, Ninth Revision Clinical Modification (ICD-9-CM) disease codes, it is transferable to other contexts, appropriate for use across spatial scales, and suitable for comparative analyses. We demonstrate the utility of the model through analysis of 2008-2010 hospitalization discharge data at state and county levels in Texas (USA). We identified several disease categories (i.e., cardiovascular, gastrointestinal, heat-related, and respiratory) associated with climate change, and then selected corresponding ICD-9 codes with the highest hospitalization counts for further analyses. Selected diseases include ischemic heart disease, diarrhea, heat exhaustion/cramps/stroke/syncope, and asthma. Cardiovascular disease ranked first among the general categories of diseases for age-adjusted hospital admission rate (5286.37 per 100,000). In terms of specific selected diseases (per 100,000 population), asthma ranked first (517.51), followed by ischemic heart disease (195.20), diarrhea (75.35), and heat exhaustion/cramps/stroke/syncope (7.81). Charges associated with the selected diseases over the 3-year period amounted to US$5.6 billion. Blacks were disproportionately burdened by the selected diseases in comparison to non-Hispanic whites, while Hispanics were not. Spatial distributions of the selected disease rates revealed geographic zones of disproportionate risk. Based upon a down-scaled regional climate-change projection model, we estimate a >5% increase in the incidence and treatment costs of asthma attributable to climate change between the baseline and 2040-2050 in Texas. Additionally, the inequalities described here will be accentuated, with blacks facing amplified health disparities in the future. These predicted trends raise both intergenerational and distributional climate health justice concerns. (C) 2014 Elsevier Ltd. All rights reserved.","McDonald, Y. J.; Grineski, S. E.; Collins, T. W.; Kim, Y. A.",10.1016/j.socscimed.2014.10.032,May,0277-9536,"Social Science & Medicine","climate justice; Health",242-252,"A scalable climate health justice assessment model",133,2015,22786,176f1216-a5cf-4ad9-852d-3bf41a0d87ec,"Journal Article",/article/10.1016/j.socscimed.2014.10.032
/reference/17856bda-1c6a-4aeb-b0fb-9ffcfb8a55b4,https://data.globalchange.gov/reference/17856bda-1c6a-4aeb-b0fb-9ffcfb8a55b4,17856bda-1c6a-4aeb-b0fb-9ffcfb8a55b4,"This report provides estimates of operational water withdrawal and water consumption factors for electricity generating technologies in the United States. Estimates of water factors were collected from published primary literature and were not modified except for unit conversions. The water factors presented may be useful in modeling and policy analyses where reliable power plant level data are not available. Major findings of the report include: water withdrawal and consumption factors vary greatly across and within fuel technologies, and water factors show greater agreement when organized according to cooling technologies as opposed to fuel technologies; a transition to a less carbon-intensive electricity sector could result in either an increase or a decrease in water use, depending on the choice of technologies and cooling systems employed; concentrating solar power technologies and coal facilities with carbon capture and sequestration capabilities have the highest water consumption values when using a recirculating cooling system; and non-thermal renewables, such as photovoltaics and wind, have the lowest water consumption factors. Improved power plant data and further studies into the water requirements of energy technologies in different climatic regions would facilitate greater resolution in analyses of water impacts of future energy and economic scenarios. This report provides the foundation for conducting water use impact assessments of the power sector while also identifying gaps in data that could guide future research.","Macknick, J.; R. Newmark; G. Heath; K. C. Hallett",10.1088/1748-9326/7/4/045802,,1748-9326,"Environmental Research Letters",,045802,"Operational water consumption and withdrawal factors for electricity generating technologies: A review of existing literature",7,2012,21330,17856bda-1c6a-4aeb-b0fb-9ffcfb8a55b4,"Journal Article",/article/10.1088/1748-9326/7/4/045802
/reference/17b3fccd-01ed-4261-b4df-7b612c90b47f,https://data.globalchange.gov/reference/17b3fccd-01ed-4261-b4df-7b612c90b47f,17b3fccd-01ed-4261-b4df-7b612c90b47f,"Mega-fires are often defined according to their size and intensity but are more accurately described by their socioeconomic impacts. Three factors – climate change, fire exclusion, and antecedent disturbance, collectively referred to as the “mega-fire triangle” – likely contribute to today's mega-fires. Some characteristics of mega-fires may emulate historical fire regimes and can therefore sustain healthy fire-prone ecosystems, but other attributes decrease ecosystem resiliency. A good example of a program that seeks to mitigate mega-fires is located in Western Australia, where prescribed burning reduces wildfire intensity while conserving ecosystems. Crown-fire-adapted ecosystems are likely at higher risk of frequent mega-fires as a result of climate change, as compared with other ecosystems once subject to frequent less severe fires. Fire and forest managers should recognize that mega-fires will be a part of future wildland fire regimes and should develop strategies to reduce their undesired impacts.","Stephens, Scott L; Burrows, Neil; Buyantuyev, Alexander; Gray, Robert W; Keane, Robert E; Kubian, Rick; Liu, Shirong; Seijo, Francisco; Shu, Lifu; Tolhurst, Kevin G; van Wagtendonk, Jan W",10.1890/120332,,,"Frontiers in Ecology and the Environment",,115-122,"Temperate and boreal forest mega-fires: Characteristics and challenges",12,2014,25986,17b3fccd-01ed-4261-b4df-7b612c90b47f,"Journal Article",/article/10.1890/120332
/reference/1854ce11-4ba4-44e3-ba53-86ce82277ec7,https://data.globalchange.gov/reference/1854ce11-4ba4-44e3-ba53-86ce82277ec7,1854ce11-4ba4-44e3-ba53-86ce82277ec7,,"Redmond, Miranda D.; Kelsey, Katharine C.; Urza, Alexandra K.; Barger, Nichole N.",10.1002/ecs2.1681,,2150-8925,Ecosphere,"climate change; climate–growth responses; climatic water deficit; dendrochronology; elevation; pinyon pine; plant population and community dynamics; semi-arid woodland; soil properties; tree growth",e01681,"Interacting effects of climate and landscape physiography on piñon pine growth using an individual-based approach",8,2017,23694,1854ce11-4ba4-44e3-ba53-86ce82277ec7,"Journal Article",/article/10.1002/ecs2.1681
/reference/18bc8646-9568-4169-a526-daed1216a4f0,https://data.globalchange.gov/reference/18bc8646-9568-4169-a526-daed1216a4f0,18bc8646-9568-4169-a526-daed1216a4f0,,"Joyce, Linda A.; Briske, David D.; Brown, Joel R.; Polley, H. Wayne; McCarl, Bruce A.; Bailey, Derek W.",10.2111/REM-D-12-00142.1,2013/09/01/,1550-7424,"Rangeland Ecology & Management","carbon sequestration; land change science; social-ecological systems; social learning; sustainability; transformation",512-528,"Climate change and North American rangelands: Assessment of mitigation and adaptation strategies",66,2013,21589,18bc8646-9568-4169-a526-daed1216a4f0,"Journal Article",/article/10.2111/REM-D-12-00142.1
/reference/1a46c6a2-4b5f-408d-b3d0-21ebdd4f960b,https://data.globalchange.gov/reference/1a46c6a2-4b5f-408d-b3d0-21ebdd4f960b,1a46c6a2-4b5f-408d-b3d0-21ebdd4f960b,,"Perlwitz, J.; T. Knutson; J.P. Kossin; A.N. LeGrande",10.7930/J0RV0KVQ,,,,,161-184,"Large-Scale Circulation and Climate Variability",,2017,21563,1a46c6a2-4b5f-408d-b3d0-21ebdd4f960b,"Book Section",/report/climate-science-special-report/chapter/circulation-variability
/reference/1c00c3da-e935-4b16-b48c-ba6e1bab427f,https://data.globalchange.gov/reference/1c00c3da-e935-4b16-b48c-ba6e1bab427f,1c00c3da-e935-4b16-b48c-ba6e1bab427f,"While it has been recognized that actions reducing greenhouse gas (GHG) emissions can have significant positive and negative impacts on human health through reductions in ambient fine particulate matter (PM2.5) concentrations, these impacts are rarely taken into account when analyzing specific policies. This study presents a new framework for estimating the change in health outcomes resulting from implementation of specific carbon dioxide (CO2) reduction activities, allowing comparison of different sectors and options for climate mitigation activities. Our estimates suggest that in the year 2020, the reductions in adverse health outcomes from lessened exposure to PM2.5 would yield economic benefits in the range of $6 to $30 billion (in 2008 USD), depending on the specific activity. This equates to between $40 and $198 per metric ton of CO2 in health benefits. Specific climate interventions will vary in the health co-benefits they provide as well as in potential harms that may result from their implementation. Rigorous assessment of these health impacts is essential for guiding policy decisions as efforts to reduce GHG emissions increase in scope and intensity.","Balbus, John M.; Greenblatt, Jeffery B.; Chari, Ramya; Millstein, Dev; Ebi, Kristie L.",10.1007/s10584-014-1262-5,"November 01",1573-1480,"Climatic Change",,199-210,"A wedge-based approach to estimating health co-benefits of climate change mitigation activities in the United States",127,2014,23716,1c00c3da-e935-4b16-b48c-ba6e1bab427f,"Journal Article",/article/10.1007/s10584-014-1262-5
/reference/1c70d230-4931-4e0f-9664-088035a3ac33,https://data.globalchange.gov/reference/1c70d230-4931-4e0f-9664-088035a3ac33,1c70d230-4931-4e0f-9664-088035a3ac33,,"Kenney, Douglas S.; Klein, Roberta A.; Clark, Martyn P.",10.1111/j.1752-1688.2004.tb01011.x,,1752-1688,"JAWRA Journal of the American Water Resources Association","water conservation; drought; water restrictions; urban water management",77-87,"Use and effectiveness of municipal water restrictions during drought in Colorado",40,2004,23799,1c70d230-4931-4e0f-9664-088035a3ac33,"Journal Article",/article/10.1111/j.1752-1688.2004.tb01011.x
/reference/1d09c643-e588-4d94-8f85-e786dabb1f18,https://data.globalchange.gov/reference/1d09c643-e588-4d94-8f85-e786dabb1f18,1d09c643-e588-4d94-8f85-e786dabb1f18,"The authors examined two competing hypotheses regarding the cause of the 1993 Cryptosporidium outbreak in Milwaukee, Wisconsin. The first was that oocyst contamination of the drinking-water influent, coupled with a treatment plant failure, resulted in a point-source outbreak. The second was that the outbreak was the result of transmission processes that amplified the oocyst concentration in the drinking-water effluent. Analysis of the model suggested that 1) transmission directly from person to person contributed 10% (95% confidence interval: 6%, 21%) of the total cases; 2) closing the drinking-water plant prevented 19% (95% confidence interval: 17%, 21%) of the additional cases of disease that occurred compared with the scenario in which the plant had not been closed, a result primarily driven by conferred immunity that resulted in depletion of the susceptible population; and 3) the outbreak was caused by a transmission cycle due to infectious persons shedding pathogens into the sewage, environmental transport of these pathogens via Lake Michigan to the drinking-water plant, and infection of susceptible persons via exposure to drinking water. The incidence data were consistent with this hypothesis. Further simulations suggested that increasing the distance between the wastewater effluent and the drinking-water influent may have prevented the outbreak.","Eisenberg, Joseph N. S.; Lei, Xiudong; Hubbard, Alan H.; Brookhart, M. Alan; Colford, Jr John M.",10.1093/aje/kwi005,,0002-9262,"American Journal of Epidemiology",,62-72,"The role of disease transmission and conferred immunity in outbreaks: Analysis of the 1993 Cryptosporidium outbreak in Milwaukee, Wisconsin",161,2005,23759,1d09c643-e588-4d94-8f85-e786dabb1f18,"Journal Article",/article/10.1093/aje/kwi005
/reference/1dd3d472-0bf3-4fa6-8b2b-2f62745680b5,https://data.globalchange.gov/reference/1dd3d472-0bf3-4fa6-8b2b-2f62745680b5,1dd3d472-0bf3-4fa6-8b2b-2f62745680b5,"This special issue of Climatic Change, dedicated to the examination of impacts of climate change on indigenous peoples and their homelands, and proposed strategies of adaptation, constitutes a compelling and timely report on what is happening in Native homelands and communities. Indigenous peoples and marginalized populations are particularly exposed and sensitive to climate change impacts due to their resource-based livelihoods and the location of their homes in vulnerable environments.","Wildcat, Daniel R.",10.1007/978-3-319-05266-3_1,,,,,1-7,"Introduction: Climate change and indigenous peoples of the USA",,2014,23884,1dd3d472-0bf3-4fa6-8b2b-2f62745680b5,"Book Section",/book/7e3db480-cc70-45fa-8077-958a717a8b92
/reference/1de89e27-5e1d-4b66-b40d-fc9cab8c3882,https://data.globalchange.gov/reference/1de89e27-5e1d-4b66-b40d-fc9cab8c3882,1de89e27-5e1d-4b66-b40d-fc9cab8c3882,,"Ekstrom, Julia A.; Moser, Susanne C.",10.1016/j.uclim.2014.06.002,2014/09/01/,2212-0955,"Urban Climate","Climate change; Adaptation; Governance; Barriers; Institutions; San Francisco",54-74,"Identifying and overcoming barriers in urban climate adaptation: Case study findings from the San Francisco Bay Area, California, USA",9,2014,25610,1de89e27-5e1d-4b66-b40d-fc9cab8c3882,"Journal Article",/article/10.1016/j.uclim.2014.06.002
/reference/1deccb49-e3fa-4195-8d50-fe2264401101,https://data.globalchange.gov/reference/1deccb49-e3fa-4195-8d50-fe2264401101,1deccb49-e3fa-4195-8d50-fe2264401101,,"Colby, Bonnie G.; Thorson, John E.; Britton, Sarah",,,,,,,"Negotiating Tribal Water Rights: Fullfilling Promises in the Arid West",,2005,25342,1deccb49-e3fa-4195-8d50-fe2264401101,Book,/book/negotiating-tribal-water-rights-fullfilling-promises-arid-west
/reference/1e2a389a-fee3-4241-a6e7-06da64e8fa15,https://data.globalchange.gov/reference/1e2a389a-fee3-4241-a6e7-06da64e8fa15,1e2a389a-fee3-4241-a6e7-06da64e8fa15,,"Dieter, Cheryl A.; Maupin, Molly A.; Caldwell, Rodney R.; Harris, Melissa A.; Ivahnenko, Tamara I.; Lovelace, John K.; Barber, Nancy L.; Linsey, Kristin S.",10.3133/cir1441,,,,,76,"Estimated use of water in the United States in 2015",,2018,26408,1e2a389a-fee3-4241-a6e7-06da64e8fa15,Report,/report/estimated-use-water-united-states-2015
/reference/1e5f1603-ff90-4158-8ed0-22126ef90c59,https://data.globalchange.gov/reference/1e5f1603-ff90-4158-8ed0-22126ef90c59,1e5f1603-ff90-4158-8ed0-22126ef90c59,,"Starrs, Paul; Peter Goin",,,,,,,"Field Guide to California Agriculture",,2010,23863,1e5f1603-ff90-4158-8ed0-22126ef90c59,Book,/book/field-guide-california-agriculture
/reference/1edbbd47-21a6-4ab7-8dbb-4a11394e08c3,https://data.globalchange.gov/reference/1edbbd47-21a6-4ab7-8dbb-4a11394e08c3,1edbbd47-21a6-4ab7-8dbb-4a11394e08c3,,"Redmond, Miranda D.; Forcella, Frank; Barger, Nichole N.",10.1890/ES12-00306.1,,2150-8925,Ecosphere,"climate change; mast seeding; Pinus edulis; pinyon-juniper woodlands; regeneration; reproduction",1-14,"Declines in pinyon pine cone production associated with regional warming",3,2012,23693,1edbbd47-21a6-4ab7-8dbb-4a11394e08c3,"Journal Article",/article/10.1890/ES12-00306.1
/reference/1f19738a-f4ec-4a51-8478-b88163d6dea6,https://data.globalchange.gov/reference/1f19738a-f4ec-4a51-8478-b88163d6dea6,1f19738a-f4ec-4a51-8478-b88163d6dea6,,"NOAA,",,,,,,,"Mean sea level trend: 9410170 San Diego, California.",,2017,23930,1f19738a-f4ec-4a51-8478-b88163d6dea6,"Web Page",/webpage/435fb49d-cbcf-41ee-bc2f-8d9b0276fd37
/reference/1f4ec538-27f4-4a34-9d75-2d4cf9d2e960,https://data.globalchange.gov/reference/1f4ec538-27f4-4a34-9d75-2d4cf9d2e960,1f4ec538-27f4-4a34-9d75-2d4cf9d2e960,,"Ye, X.
Wolff, R.
Yu, W.
Vaneckova, P.
Pan, X.
Tong, S.",10.1289/ehp.1003198,,1552-9924,"Environmental Health Perspectives",,19-28,"Ambient temperature and morbidity: A review of epidemiological evidence",120,2012,3505,1f4ec538-27f4-4a34-9d75-2d4cf9d2e960,"Journal Article",/article/10.1289/ehp.1003198
/reference/1f5f3984-e46b-4ac3-a656-bd5a1f6ea505,https://data.globalchange.gov/reference/1f5f3984-e46b-4ac3-a656-bd5a1f6ea505,1f5f3984-e46b-4ac3-a656-bd5a1f6ea505,,"Howitt, Richard; Josué Medellín-Azuara; Duncan MacEwan; Jay R. Lund; Daniel Sumner",,,,,,various,"Economic analysis of the 2014 drought for California agriculture",,2014,26365,1f5f3984-e46b-4ac3-a656-bd5a1f6ea505,Report,/report/economic-analysis-2014-drought-california-agriculture
/reference/1f8c0eab-9564-4064-bd8e-b98c135744e9,https://data.globalchange.gov/reference/1f8c0eab-9564-4064-bd8e-b98c135744e9,1f8c0eab-9564-4064-bd8e-b98c135744e9,,"Xcel Energy,",,,,,,11,"Public Service Company of Colorado: 2016 Electric Resource Plan. 2017 All Source Solicitation 30-Day Report. (Public Version) ",,2017,26396,1f8c0eab-9564-4064-bd8e-b98c135744e9,Report,/report/public-service-company-colorado-2016-electric-resource-plan-2017-all-source-solicitation-30-day-report-public-version
/reference/1fe81b82-9ff8-4e7d-8b25-b37bdace45fe,https://data.globalchange.gov/reference/1fe81b82-9ff8-4e7d-8b25-b37bdace45fe,1fe81b82-9ff8-4e7d-8b25-b37bdace45fe,,"Middleton, Beth Rose",,,,"Smoke Signals",,7-9,"Fuels: Greenville rancheria",24,2012,23826,1fe81b82-9ff8-4e7d-8b25-b37bdace45fe,"Journal Article",/generic/b44b5369-5676-4a55-a39b-9579ea803494
/reference/2042ab8a-6a82-40a2-99ba-7e67babf8ffc,https://data.globalchange.gov/reference/2042ab8a-6a82-40a2-99ba-7e67babf8ffc,2042ab8a-6a82-40a2-99ba-7e67babf8ffc,,"Meixner, Thomas; Manning, Andrew H.; Stonestrom, David A.; Allen, Diana M.; Ajami, Hoori; Blasch, Kyle W.; Brookfield, Andrea E.; Castro, Christopher L.; Clark, Jordan F.; Gochis, David J.; Flint, Alan L.; Neff, Kirstin L.; Niraula, Rewati; Rodell, Matthew; Scanlon, Bridget R.; Singha, Kamini; Walvoord, Michelle A.",10.1016/j.jhydrol.2015.12.027,2016/03/01/,0022-1694,"Journal of Hydrology","Groundwater recharge; Recharge mechanisms; Climate change; Western United States",124-138,"Implications of projected climate change for groundwater recharge in the western United States",534,2016,23825,2042ab8a-6a82-40a2-99ba-7e67babf8ffc,"Journal Article",/article/10.1016/j.jhydrol.2015.12.027
/reference/21aa7761-7792-4b6a-b172-7fe3ecd83d13,https://data.globalchange.gov/reference/21aa7761-7792-4b6a-b172-7fe3ecd83d13,21aa7761-7792-4b6a-b172-7fe3ecd83d13,"The near-term progression of ocean acidification (OA) is projected to bring about sharp changes in the chemistry of coastal upwelling ecosystems. The distribution of OA exposure across these early-impact systems, however, is highly uncertain and limits our understanding of whether and how spatial management actions can be deployed to ameliorate future impacts. Through a novel coastal OA observing network, we have uncovered a remarkably persistent spatial mosaic in the penetration of acidified waters into ecologically-important nearshore habitats across 1,000 km of the California Current Large Marine Ecosystem. In the most severe exposure hotspots, suboptimal conditions for calcifying organisms encompassed up to 56% of the summer season, and were accompanied by some of the lowest and most variable pH environments known for the surface ocean. Persistent refuge areas were also found, highlighting new opportunities for local adaptation to address the global challenge of OA in productive coastal systems.","Chan, F.; Barth, J. A.; Blanchette, C. A.; Byrne, R. H.; Chavez, F.; Cheriton, O.; Feely, R. A.; Friederich, G.; Gaylord, B.; Gouhier, T.; Hacker, S.; Hill, T.; Hofmann, G.; McManus, M. A.; Menge, B. A.; Nielsen, K. J.; Russell, A.; Sanford, E.; Sevadjian, J.; Washburn, L.",10.1038/s41598-017-02777-y,2017/05/31,2045-2322,"Scientific Reports",,2526,"Persistent spatial structuring of coastal ocean acidification in the California Current System",7,2017,23671,21aa7761-7792-4b6a-b172-7fe3ecd83d13,"Journal Article",/article/10.1038/s41598-017-02777-y
/reference/21f384a2-0dcf-4c1a-b1c0-add8b0e7506c,https://data.globalchange.gov/reference/21f384a2-0dcf-4c1a-b1c0-add8b0e7506c,21f384a2-0dcf-4c1a-b1c0-add8b0e7506c,,"Knowlton, K.
Rotkin-Ellman, M.
Geballe, L.
Max, W.
Solomon, G.M.",10.1377/hlthaff.2011.0229,,0278-2715,"Health Affairs",,2167-2176,"Six climate change-related events in the United States accounted for about $14 billion in lost lives and health costs",30,2011,1545,21f384a2-0dcf-4c1a-b1c0-add8b0e7506c,"Journal Article",/article/10.1377/hlthaff.2011.0229
/reference/22344c1d-cee2-4f9d-91c0-60ceb6e9ca57,https://data.globalchange.gov/reference/22344c1d-cee2-4f9d-91c0-60ceb6e9ca57,22344c1d-cee2-4f9d-91c0-60ceb6e9ca57,,"Ostro, B.D.
Roth, L.A.
Green, R.S.
Basu, R.",10.1016/j.envres.2009.03.010,,0013-9351,"Environmental Research",,614-619,"Estimating the mortality effect of the July 2006 California heat wave",109,2009,2380,22344c1d-cee2-4f9d-91c0-60ceb6e9ca57,"Journal Article",/article/10.1016/j.envres.2009.03.010