Grantee Research Project Results
2004 Progress Report: Impacts of Climate Change and Global Emissions on US Air Quality: Development of an Integrated Modeling Framework and Sensitivity Assessment
EPA Grant Number: R830961Title: Impacts of Climate Change and Global Emissions on US Air Quality: Development of an Integrated Modeling Framework and Sensitivity Assessment
Investigators: Adams, Peter , Pandis, Spyros N.
Institution: Carnegie Mellon University
EPA Project Officer: Chung, Serena
Project Period: March 23, 2003 through March 22, 2006 (Extended to March 22, 2007)
Project Period Covered by this Report: March 23, 2004 through March 22, 2005
Project Amount: $900,000
RFA: Assessing the Consequences of Global Change for Air Quality: Sensitivity of U.S. Air Quality to Climate Change and Future Global Impacts (2002) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Air , Climate Change
Objective:
The objectives of this project are to:
1. Develop a comprehensive modeling system for the description of the interactions between climate and local/regional air quality. This system will use a global climate-chemistry model, a regional meteorological model, and a regional air quality model to describe the relevant timescales (hours to decades) and length-scales (kilometers to global scales). It will also include an emissions processing system that will estimate climate-dependent emissions.
2. Determine the sensitivity of ozone, particulate matter (PM), acid deposition, and visibility to individual meteorological parameters by performing a set of sensitivity experiments in the context of regional chemical transport models (CTMs, e.g., Particulate Matter Comprehensive Air Quality Model with Extensions [PMCAMx] and Community Multiscale Air Quality Model).
3. Evaluate the ability of the modeling system to describe current air quality in the United States, including annual average pollutant concentrations, their probability distributions, and the frequency of extreme air pollution episodes.
4. Develop a set of future (year 2050) scenarios (meteorological fields, emissions, and chemical boundary conditions). These scenarios will include climate change and/or global emissions changes and will bound the space of system responses (best, mean, and worst case scenarios).
5.Use the comprehensive modeling system and these scenarios to assess air quality in the year 2050 with and without climate change and with and without changes in global emissions.
6. Investigate reduced form models and methodologies for incorporating the effects of climate change and global emission changes in future planning and assessment.
Progress Summary:
In this past year, progress towards achieving the above objectives was made along the fronts described below.
1. Evaluation of an Annual Ammonia Emissions Inventory for the United States
One of the outstanding issues in PM2.5 modeling has been improving the ability of CTMs to predict correctly the formation of ammonium nitrate aerosol. Ammonium nitrate is a significant portion of PM2.5 in the winter in the Northeast and must be well simulated if a CTM is to predict annual average PM2.5 levels. This, in turn, depends on knowledge of wintertime ammonia emissions, as ammonia is often the limiting factor in nitrate formation.
In the past year, we have evaluated the Carnegie Mellon University inventory and one developed by Alice Gilliland at the U.S. Environmental Protection Agency using measurements of total (gas plus aerosol) ammonia made at the Pittsburgh Air Quality Study, aerosol ammonium measured by the Speciation Trends Network, and ammonia wet deposition fluxes and concentrations from the National Atmospheric Deposition Program. These comparisons demonstrate a significant improvement in predicted total ammonia concentrations from the new estimates of wintertime ammonia emissions. Spring and fall emissions continue to be problematic for both the Carnegie Mellon University and Gilliland inventories because of a lack of information regarding the monthly timing of manure application at livestock operations in the former and because of uncertainties in the inversion process in the latter.
2. Regional CTM Simulations of Sensitivity to Climate Parameters
This activity directly addresses Objective 2 outlined above: the determination of the sensitivity of average and peak PM2.5 and ozone concentrations to individual meteorological parameters. These simulations have been performed with the regional CTM, PMCAMx, using a domain that covers the eastern United States. The base case meteorology for these simulations is taken from July 2001. The sensitivity scenarios impose uniform changes on individual meteorological parameters including temperature, humidity, wind speed, mixing height, cloud cover, cloud thickness, precipitation rate, and area. Detailed results of these simulations are given in the full progress report.
We have investigated the physical mechanisms that account for ozone and PM sensitivities to each meteorological variable. For example, we have confirmed that the effect of temperature on ozone results from peroxyacetyl nitrate-NOx chemistry. Similarly, higher/lower wind speeds reduce/increase pollutant concentrations via changes in transport of pollutants out of the model domain. Other meteorological parameters have more complex impacts on air quality. For example, an increase in cloud cover has both positive and negative effects on PM2.5 in different parts of the domain as the effect of increased aqueous oxidation of SO2 competes with decreased gas-phase oxidation of SO2. Another complex change is that increased humidity tends to decrease background ozone concentrations but worsen peak ozone levels.
As the project progresses, we will use these sensitivity results in various ways. First, we are combining them with ranges of projected changes in each parameter to assess which parameters are likely to have the most significant effects on air quality. As we develop the coupled global-regional climate and air quality modeling framework (see Development of a Coupled Global to Regional Climate and Air Quality Modeling System below), we will use these results to select time periods from multiyear global climate simulations for more detailed simulation with the regional CTM. The sensitivity simulations with changes in individual meteorological parameters will also be useful for understanding the results from the fully coupled model where all parameters change simultaneously.
3. Results from Global Climate-Chemistry Simulations
In parallel to the regional-scale simulations just described, we have performed global-scale simulations of atmospheric chemistry under future climate using a “unified model” of global climate and chemistry. We perform two simulations with the global model: one with present climate and one with a projected future climate for the 2050s decade. In both simulations, emissions are held at present day levels to isolate the effects of climate change itself. The future climate is driven by changes in sea surface temperatures taken from a coupled atmospheric-ocean general circulation model simulation of the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios A2 scenario (Richard Healy, personal communication). These simulations are a necessary step towards Objective 4 outlined above and also provide substantial insight in their own right into impacts of climate change on air quality at global and regional scales.
The results of the global simulation show that a majority of the globe’s surface experiences a decrease in average ozone concentrations. Analysis of the ozone budget shows that the major explanation for the ozone decrease is the increased humidity of the future climate, which lowers the ozone lifetime via the following loss reaction sequence:
O3 + hν → O2 + O(1D)
O(1D) + H2O → 2 ·OH
The future climate simulation shows a much more complex response for PM2.5 constituents. A major factor in the global tropospheric PM2.5 budget is overall lower burdens as a result of increased precipitation. On a regional scale, however, increased PM2.5 concentrations may result at the surface for a variety of reasons. For example, regional increases in sulfate occur primarily because of increased oxidant (OH radical and H2O2) concentrations.
4. Sensitivity of Extreme Temperature Events to Precipitation and SSTs
This work uses climate observations for the present day United States to understand reasons for anomalously high summertime temperatures. It also examines the ability of a coupled global climate model (GCM) and regional climate model (RCM) to represent these extreme temperatures. Specifically, it evaluates relationships between June-August anomalies of the maximum surface air temperature (T) in the eastern United States and other climate variables to better understand the potential for extreme climate change. The study analyzes observational climate data for 1980-1999 and results from a nested GCM/regional climate model system. The warmest seasonal T anomalies during the 20-year observational period occurred when Atlantic sea-surface temperatures (SSTs) were anomalously warm and Pacific SSTs were colder than the long-term mean. Warm summers also featured less frequent precipitation and lower accumulated rainfall than anomalously cool summers. Almost 70 percent of the interannual variability of the regional June/July/August anomaly of maximum T is accounted for by the precipitation frequency and Atlantic minus Pacific sea-surface anomaly (SSA) differences. GCM climate change simulations downscaled with the Mesoscale Model 5 (MM5) regional model were evaluated to assess the impact of precipitation characteristics on the future climate. Some climate change scenarios for the 2080s included summertime mean maximum surface air temperatures that exceeded 40°C over areas from the Midwest to the major cities along the Atlantic coast. The study suggests that to project the potential for extreme climate change, models will need to realistically simulate changes in the surface energy balance caused by the inter-annual variation of precipitation characteristics.
5. Development of a Coupled Global to Regional Climate and Air Quality Modeling System
To address Objective 1, we are in the final stages of developing a coupled modeling system that treats both climate and air quality from global to regional (4 km grid cells) scales. This coupled modeling system consists of the following components: (1) a “unified” model of global climate and chemistry; (2) MM5, an RCM; and (3) PMCAMx, a regional air quality model (RAQM).
In the coupled modeling system, the global “unified” model predicts both climate and meteorological fields, which are passed to the RCM and RAQM, respectively. MM5, the RCM, downscales the global climate to the PMCAMx domain and passes these downscaled meteorological parameters to PMCAMx. All of the couplings have been developed and tested with the exception of passing the chemical boundary conditions from the global model to PMCAMx, which is the last piece under development. Once this is complete, we will evaluate the ability of the coupled modeling system to predict the present-day air quality (Objective 3 above).
Manuscripts for each of sections 1, 3, and 4 described above have either been submitted or are undergoing final proofing. Additionally, a manuscript describing the work in section 2 will be submitted in the coming 2 months.
Future Activities:
Our plan is to continue working on the tasks outlined in the proposal. Specifically, we will test the fully coupled modeling system described in section 5, “Development of a Coupled Global to Regional Climate and Air Quality Modeling System,” to simulate present-day air quality and compare its performance against observations. Subsequently, we will apply this system to future (2050s) air quality scenarios with various permutations of changed climate, changed climate-sensitive emissions, and changed other emissions. After analyzing fully the results of these simulations, we will investigate the potential to develop a simplified tool (i.e., something less demanding than the fully coupled model) for future researchers and policymakers to use to estimate how climate change will affect their future projections of air quality.
Journal Articles:
No journal articles submitted with this report: View all 9 publications for this projectSupplemental Keywords:
ambient air, atmosphere, ozone, particulates, visibility, acid deposition, global climate, tropospheric, chemical transport, oxidants, nitrogen oxides, sulfates, organics, modeling, general circulation models, climate models,, RFA, Scientific Discipline, Air, Ecosystem Protection/Environmental Exposure & Risk, particulate matter, Air Quality, Air Pollutants, Chemistry, climate change, Air Pollution Effects, Monitoring/Modeling, Environmental Monitoring, Atmospheric Sciences, Atmosphere, anthropogenic stress, aerosol formation, ambient aerosol, atmospheric particulate matter, atmospheric dispersion models, ecosystem models, environmental measurement, meteorology, climatic influence, emissions monitoring, global change, ozone, air quality models, climate, modeling, climate models, greenhouse gases, airborne aerosols, atmospheric aerosol particles, atmospheric transport, neural networks, environmental stress, regional emissions model, ecological models, climate model, greenhouse gas, aerosols, atmospheric models, Global Climate Change, atmospheric chemistry, ambient air pollutionRelevant Websites:
http://www.ce.cmu.edu/~adams/index.html Exit
http://www.cheme.cmu.edu/who/faculty/pandis.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.