Grantee Research Project Results
2007 Progress Report: Effects of Climate Change on Human Health: Current and Future Impacts
EPA Grant Number: R832751Title: Effects of Climate Change on Human Health: Current and Future Impacts
Investigators: Hanna, Adel , Yeatts, Karin B. , Xiu, Aijun , Henderson, Fred , Robinson, Peter , Smith, Richard , Zhu, Zhengyuan
Institution: University of North Carolina at Chapel Hill
EPA Project Officer: Chung, Serena
Project Period: January 1, 2006 through December 31, 2008 (Extended to December 31, 2010)
Project Period Covered by this Report: January 1, 2007 through December 31,2007
Project Amount: $599,103
RFA: The Impact of Climate Change & Variability on Human Health (2005) RFA Text | Recipients Lists
Research Category: Climate Change
Objective:
The overall goal of this project is to define more precisely the interrelationships among (a) changes in climate and meteorological conditions, (b) air pollution, and (c) heat- and cold-related morbidity severe enough to warrant clinical contact. A secondary goal is to evaluate heat-related morbidity in a vulnerable population: children and adults under economic disadvantage.
Progress Summary:
We have examined the above interrelationships in five cities across North Carolina: Asheville, Charlotte, Greensboro, Raleigh, and Wilmington. The state’s varied terrain—mountain, Piedmont, coastal—makes it a good choice for examining the potential impacts of climate variability and air quality on health. During the first project year we performed our analysis for the Charlotte area. This year (project year 2) we extended the analysis to the other four cities. Ten years of data (1996-2005) were used, including (a) weather observations (daily maximum temperature, daily average wind speed, daily minimum temperature, surface pressure, dew point); (b) air quality measurements (O3, PM10, and, if available, NO2 and CO); and (c) hospital admissions records of asthma and myocardial infarction (MI). Daily weather and climate conditions in the five cities were classified in terms of eight air-mass types that characterize their origin (tropical or polar) and conditions (moist/dry/cloudy, and temperature). As described in the project’s year 1 report, most air-mass types show a seasonal cycle; the moist tropical and moist moderate air masses peak during summer, while the dry polar and dry moderate maximum occurrences fall during autumn and winter.
We used a generalized linear model (GLM) to study the relationship between current, 1-daylagged, 2-day-lagged, 3-day-lagged, 4-day-lagged, and 5-day-lagged O3, NO2, PM10, and CO concentrations, air-mass types, and asthma and MI hospital admissions in adults, after adjusting for meteorological variables, nonlinear seasonal effects, day of week effects, and long-term trend. We conducted the analysis for the selected five cities in North Carolina. We concluded from the results we obtained that three weather types (circulation patterns or synoptic air-mass patterns), in conjunction with ambient air pollution levels, are associated with increased asthma and MI hospital admissions. These are the dry moderate, dry tropical, and moist tropical circulation patterns.
We believe that additional health data (e.g., doctors’ office, emergency room, and hospital visits in children enrolled in Medicaid) may add further insights to such conclusions. We have obtained the Medicaid data and will be starting these analyses in spring 2008.
Also in year 2, we began our modeling analyses designed to assess the potential impacts of weather types (circulation patterns) and air quality on hospital admissions in future years. We used the Community Climate System Model (CCSM) to simulate current climate for the year 2003. We examined the CCSM model results in order to compare them with the daily weather analyses that were used for the weather classifications for the five cities in North Carolina. We will also compare the CCSM model results with the results from the PSU/NCAR Mesoscale Model (MM5). The latter is often used for preparing meteorology data for air quality simulations.
Future Activities:
During the project’s third year, we will apply the results of the statistical modeling, obtained from the ten-year (1996-2005) analyses for North Carolina, to the year 2030. We intend to initialize the MM5 model with the projected climate for 2030 to model the air quality, based on Intergovernmental Panel on Climate Change (IPCC) emissions scenarios for that year. We will use the CCSM model simulations for the base case (i.e., the case with climate based on current conditions) and the IPCC climate scenarios. We will quantify and assess the uncertainty in climate and health-related projections. We will also quantify potential economic losses due to projected emergency room visits, hospitalizations, and medication use.
Journal Articles:
No journal articles submitted with this report: View all 11 publications for this projectSupplemental Keywords:
global climate, air quality, human health, epidemiology, modeling, climate models, Southeastern U.S., Health, RFA, Scientific Discipline, Air, Ecological Risk Assessment, Health Risk Assessment, Risk Assessments, Atmosphere, Air Pollution Effects, Biochemistry, climate change, Environmental Monitoring, Global Climate Change, air quality modeling, human exposure, morbidity, statistical methods, climate models, human dimension, land use, air pollutionRelevant Websites:
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.