Grantee Research Project Results
2002 Progress Report: Modeling Heat and Air Quality Impacts of Changing Urban Land Uses and Climate
EPA Grant Number: R828733Title: Modeling Heat and Air Quality Impacts of Changing Urban Land Uses and Climate
Investigators: Kinney, Patrick L. , Soleki, William D. , Rosenthal, Joyce E. , Hogrefe, Christian , Small, Christopher , Rosenzweig, Cynthia , Werth, David , Civerolo, Kevin , Knowlton, Kim , Ku, Michael , Goldberg, Richard , Avissar, Roni , Gaffin, Stuart , Holloway, Tracey
Current Investigators: Kinney, Patrick L. , Soleki, William D. , Rosenthal, Joyce E. , Lynn, Barry , Hogrefe, Christian , Small, Christopher , Rosenzweig, Cynthia , Werth, David , Cox, Jennifer , Civerolo, Kevin , Knowlton, Kim , Ku, Michael , Goldberg, Richard , Avissar, Roni , Holloway, Tracey
Institution: Columbia University in the City of New York , The State University of New York , New York State Department of Environmental Conservation , Duke University
Current Institution: Columbia University in the City of New York , Duke University , NASA Goddard Institute for Space Studies , New York State Department of Environmental Conservation , The State University of New York , University of Wisconsin - Madison
EPA Project Officer: Chung, Serena
Project Period: September 1, 2000 through August 31, 2003 (Extended to March 14, 2006)
Project Period Covered by this Report: September 1, 2001 through August 31, 2002
Project Amount: $1,496,418
RFA: Assessing the Consequences of Interactions between Human Activities and a Changing Climate (2000) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Climate Change , Air
Objective:
The overall objective of the New York Climate and Health Project (NYCHP) is to develop a modeling framework that incorporates global and regional climate, regional land use, and regional ambient air quality changes to assess the human health impacts of alternative future scenarios for the New York City (NYC) metropolitan area.
Heat waves and elevated concentrations of atmospheric ozone represent two significant current public health stressors in the NYC metropolitan area. Both of these stressors may be impacted by future changes in the global climate, as well as continued expansion of human-dominated land uses in the region. The New York Climate and Health Project is linking models describing the behaviors of these systems to yield improved tools for assessing the future public health impacts of climate change in the context of existing environmental stressors. The model is being applied to the 31-county New York metropolitan east coast region. The project addresses the following questions. What changes in the frequency and severity of extreme heat events are likely to occur over the next 80 years as the result of a range of possible scenarios of changes in land use/landcover and climate in the region? How might the frequency and severity of episodic concentrations of ozone (O3) change over the next 80 years as the result of a range of possible scenarios of land use and climate change in the metropolitan region? What is the range of possible human health impacts of these changes? How might projected future human exposures and responses to heat stress and air quality differ as a function of socioeconomic status and race/ethnicity across the region?
Progress Summary:
Meeting the objective of this research project involves the use of the Goddard Institute for Space Studies (GISS) (4° x 5°) global climate model (GCM) to estimate meteorological parameters over the decade of the 2050s under two greenhouse gas scenarios: the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions (SRES) A2, relatively high emissions cases; and IPCC SRES B2, relatively low emissions cases. Landuse change is modeled using the Slope, Landcover, Exclusion, Urbanization, Transportation, and Hillshade (SLEUTH) model with parameters consistent with the A2 and B2 emissions scenarios. Outputs from these models are used as inputs to two alternative regional-scale meteorological models, the Regional Atmospheric Modeling System (RAMS) and the GISS Mesoscale Model, Version 5 (GISS-MM5), which downscale the GISS GCM results to a series of nested grids as fine as 4 km. The regional scale meteorological estimates then are used as inputs to an air quality simulation model, the community multiscale air quality (CMAQ) model, that produces ground-level ozone estimates. Public health impacts are assessed by applying concentration-response functions (e.g., percent increase in deaths per degree Fahrenheit increase in daily mean temperature above a threshold) derived from the existing epidemiological literature to the temperature and ozone estimates obtained from the models described above.
In Year 2 of the project, we assessed mortality impacts of temperature changes in the 2050s as compared with the 1990s, based on temperature outputs from the GISS GCM interpolated to NYC. Because the GCM output provided data covering the entire year, we were able to assess the net effects of summer-season increases in heat impacts in conjunction with winter-season decreases in cold impacts. Under the A2 scenario, we estimated a net increase of 26 percent in temperature-related mortality in the 2050s, corresponding to about 1,100 annual additional deaths in the 31-county region. Under the B2 scenario, the estimated impacts were smaller: a 15-percent increase in temperature-related mortality, corresponding to about 700 annual deaths. These estimates assumed no change in the population. When regional population growth rates projected for the two scenarios (53 percent growth in population for A2, and 24 percent for B2, by 2055) were considered, the net temperature effects were estimated to increase 93 percent and 43 percent for A2 and B2, respectively.
Extensive efforts were made during Year 2 of the project to develop and validate the regional-scale modeling capability for the study area. The GISS-MM5 model produces more realistic results because of the simulation of local features (such as seabreezes, heat island effect, etc.) than the coarse-grid GISS GCM. This capability represents a significant improvement over previous downscaling techniques using interpolation of the coarse resolution results to the region of interest to examine local impacts of climate change. The improved grid-resolution of the GISS-MM5 and the use of model physics appropriate to higher resolution models simulate potential changes in local weather in response to changes in greenhouse gases or landuse change. This allows greater confidence in the results than obtained solely with the GISS GCM. The output from the GISS-MM5 model has been used to obtain projected changes in ozone concentration in the 2050s as compared with the 1990s in the CMAQ model, and the combined output will be used to evaluate the impact of changes in heat stress and ozone on health.
Using the MM5, we obtained county-specific temperature estimates, run on a 36-km grid for five summers in the 1990s and 2050s. Using this output, we obtained 36-km ozone simulations for input to our public health risk assessment model. Our preliminary results suggest that exposure to environmental conditions that increases the relative risk of mortality depends on location within the domain of interest; e.g., residents of urban areas were at higher risk than residents of outlying areas. Furthermore, the growth of urban land uses in the future has the potential to exacerbate this risk.
Future Activities:
We will complete modeling simulations for the New York Climate and Health Project. During 2003, we ran simulations to evaluate the performance of the MM5 model for the 1990s, and now MM5 will produce a series of nested runs for selected years in the 2020s, 2050s, and 2080s (down to at least a 36-km horizontal resolution), incorporating the A2 landuse change scenario for selected runs at a finer resolution of 4-km for the 2050s (see Table 1). The RAMS team will complete evaluation runs for two summers in the 1990s at a coarse resolution (144/48 km), and select time periods in the 2050s for 4-km simulations with improved vegetative fraction data provided by Landsat data.
Status | Resolution km |
Duration of Simulation | |
1990s/2050s | Done | 108 |
10 years, Multiple Model Configurations |
A2 1993 National Centers for Environmental Prediction | Done | 108 |
June-July-August (JJA) |
A2 1990s Single Nest | Done | 108 |
5 years (JJA) |
A2 1990s Double Nest | Done | 108/36 |
5 years (JJA) |
A2 2050s Single Nest | Done | 108 |
5 years (JJA) |
A2 2050s Double Nest | Done | 108/36 |
5 years (JJA) |
A2 1993 Triple Nest A2 1993 Fourth Nest |
In Process Planned |
108/36/12 4 |
JJA Week in July |
A2 1996 Triple Nest A2 1996 Fourth Nest |
Planned Planned |
108/36/12 4 |
JJA Week in July |
A2 205X Triple Nest A2 205X Fourth Nest |
Planned Planned |
108/36/12 4 |
JJA Week in July |
B2 205X Triple Nest B2 205X Fourth Nest |
Planned Planned |
108/36/12 4 |
JJA Week in July |
A2 2080s Double Nest | Planned | 108/36 |
5 years (JJA) |
A2 2050s Triple, Fourth NestLanduse changes |
Planned | 108/36/12 4 |
JJAWeek in July |
A2 2020s Double Nest | Planned | 108/36 |
5 Years (JJA) |
B2 2050sTriple, Fourth NestLanduse changes | Planned | 108/36/12 4 |
JJA1 week |
The landuse modeling team led by Bill Solecki will finish the A2 and B2 SLEUTH model runs to 2050, and work with Chris Small to convert SLEUTH output to parameter grids for the MM5 and RAMS models. The SLEUTH team also is seeking to apply the SLEUTH model to project population and demographic change within the metropolitan region. Bill Solecki's group is moving from Montclair State University, New Jersey, to Hunter College-City College of New York during the summer of 2003.
Chris Small, who is analyzing Landsat data for trends in changes in land use over the last 3 decades, will work with the SLEUTH output of landcover classes to generate parameter distributions for each landcover class, with the Montclair State University team. He recently has provided vegetative fraction landcover parameters for use in 4-km grid cells by the MM5 and RAMS models.
The CMAQ model has been run with MM5 output for five summers in the 1990s and 2050s at 36-km resolution. The CMAQ team, led by Christian Hogrefe, is working with the health investigators to choose time periods from these runs for simulation of ozone episodes in the 1990s and 2050s at 4-km resolution, with both base and changed landcover for the 2050s. The CMAQ model also will be run with the mesoscale meteorological model output, from RAMS and MM5, for selected time periods in the 2020s and 2080s.
Areas for continued public health impact (PHI) analyses in Year 3 of the project include:
1. Expanding temperature impacts analyses to the 2020s and 2080s, and inclusion of B2 climate scenario output from mesoscale meteorological models, MM5 and RAMS;
2. Applying the PHI model to projections for ozone in 2020s, 2050s, 2080s, versus 1990s;
3. PHI modeling for morbidity-evaluating respiratory and cardiovascular hospitalizations versus environmental risk factors (temperature and ozone).
4. Applying the PHI model to alternative scenarios of demographic change in two different study areas:
- (a) with demographics and population constant (at Census 2000 levels), geographically
distribute health impacts at county level, using a range of exposure-risk coefficients
for at-risk subpopulations (percent population 65+, percent population with
air conditioning, percent population living in poverty, and percent population
not completing high school) from the epidemiology literature;
(b) with demographics and population changing in the decade of the 2020s, in a manner consistent with the IPCC A2 and B2 scenarios (as modeled with the SLEUTH landuse model by Bill Solecki), change the number of residents in at-risk subpopulations in our case study areas, and apply a range of appropriate exposure-risk coefficients from the heat-mortality epidemiological literature.
In addition to the analysis planned for temperature-related health impacts, we will: (1) compare mortality projections derived from the use of mesoscale climate models versus the GCM output (and for the use of the MM5 at different scales of horizontal resolution); (2) define and model "heat wave" mortality; (3) model early-season heat mortality; and (4) use specific exposure-risk coefficients for at-risk populations in selected case study areas, and apply the landuse and demographic changes modeled by the SLEUTH team for the 2020s.
Model projections of public health impacts related to changing climate and landuse patterns in the region will reveal which of these environmental risk factors-heat or air quality-could have the greatest effect on the NYC metropolitan region in the future decades of the 2020s, 2050s, and 2080s. These research findings should be useful to decision makers and county health departments in the NYCHP study area, as these agencies primarily are responsible for local health care infrastructure planning and health emergency preparedness.
In addition to the research planned for the future, the project investigators are working on several publications of project results.
Journal Articles on this Report : 1 Displayed | Download in RIS Format
Other project views: | All 64 publications | 26 publications in selected types | All 22 journal articles |
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Type | Citation | ||
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|
Small C. A global analysis of urban reflectance. International Journal of Remote Sensing 2005;26(4):661-681. |
R828733 (2002) |
not available |
Supplemental Keywords:
ambient air, ozone, global climate, exposure, risk assessment, human health, modeling, general circulation models, GCM, climate models, satellite, Landsat, remote sensing, Northeast, New York, NY, New Jersey, NJ, Connecticut, CT, air toxics, climate change, particulate matter, tropospheric ozone, PM 2.5, air pollution models, air quality, airborne particulate matter, ambient air pollution, climate variations, ecosystem models, environmental stressors, exposure and effects, extreme heat events, fine particle sources, fine particles, global change, green house gas concentrations, human activity, human exposure, integrated assessments, landuse, landscape characterization, ozone concentrations, public health effects, remote sensing, stratospheric ozone., RFA, Scientific Discipline, Air, Geographic Area, particulate matter, climate change, State, Environmental Monitoring, tropospheric ozone, Atmospheric Sciences, ecosystem models, integrated assessments, remote sensing, air quality modeling, urban air, fine particles, PM 2.5, global change, airborne particulate matter, ambient air, climate variations, ozone, green house gas concentrations, New Jersey (NJ), air pollution models, climate models, extreme heat events, fine particle sources, human exposure, environmental stressors, Connecticut (CT), PM, human activity, landscape characterization, air quality, ambient air pollution, land use, public health effects, ozone concentrations, New York (NY)Relevant Websites:
http://www.csam.montclair.edu/luca/index.html Exit
http://www.mailman.hs.columbia.edu/ehs/research.html Exit
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.