# Presentation: 200379

## University of Illinois at Urbana-Champaign

**Application of an Integrated Modeling System for****Climate and Air Quality Change Studies****at Regional to Local Scales**

**Xin-Zhong Liang (PI), xliang@uiuc.edu**
***Illinois State Water Survey *****(ISWS)**
**Co-PIs:**
**Ho-Chun Huang, Allen Williams, **
**Michael Caughey, Kenneth Kunkel (ISWS)**
**Donald J. Wuebbles**
***Department of Atmospheric Sciences *****(DAS)**
**Other Investigators:**
**Jinhong Zhu, Zhining Tao, Min Xu (ISWS)**
**Kenneth O. Patten, Jintai Lin (DAS)**

**University of Illinois at Urbana-Champaign**

## Objective

**To quantify, and understand the uncertainties of, the individual and combined impacts of global climate and emission changes on U.S. air quality, from the present to 2050 and 2100.**

## Hypothesis

- U.S. air quality is determined by complex interactions over a range of spatial and temporal scales from
- chemical processes and emissions on local to regional scales
- long-range transport of global pollutants and precursors
- global and regional climate changes and variability

## Regional Model System

**Resolution: 30 km**

**Present Climate & GCM Projections**

**Intercontinental **
**Chemical Transport**
**Model**

**Global Emissions & Projections**

**Regional**
**Air Quality Model**

**Regional Climate Model**

**Emissions Model**
**U.S. NEI99 & Projections**

_**Focal Areas**_

**Northeast**
**Midwest**
**West Coast**
**Texas**

**  ****O****3**
- NOx  VOCs  CO

**  ****PM****2.5**
- SO42-  NO3-  NH3 EC OC

**Global Model System**
**Resolution: 150-300 km**

**The nested global-regional modeling system: its components and their interactions**

**Target Areas**
**Resolution: 10 km**

## D1

**D2c**

**D1**

**Regional computational domain design. ****The global models provide the regional models with lateral boundary conditions in ****the buffer zones (shaded outer edges)****.**** The climate model uses a grid spacing of 30-km over domain D1, while the air quality model uses 90-km in D1 and 30-km in subdomains D2a-d.**

**D2b**

**D2d**

**D2a**

## Uncertainty

- Biases in the climate and chemistry arising from the driving global models and the incomplete physics of the regional models
- Different climate sensitivities of the driving global models and the regional models
- Inconsistencies in the coupled global-regional modeling system
- Pollutant emissions error
- Natural variability

## Global Climate Models

**LOW**  climate sensitivity:
- Parallel Climate Model (**PCM**) of the National Center for Atmospheric Research/U.S. Department of Energy
**HIGH** climate sensitivity:
- Hadley Centre third generation climate model (**HAD**)

## Future Projections

**PCM simulations for 2050 and 2100**
**A1Fi : high emissions scenario**
**B1: low emissions scenario**
**HAD simulations for 2100**
**A2: intermediate high emissions scenario**
**B2: intermediate low emissions scenario**

## Climate Model Results

- The following examples show
- the difference between GCMs in simulating the present climate and projecting future changes
- the effect of the RCM downscaling on regional climate simulations and projections

## Slide 10

## Summary for Climate Simulations

- GCMs produce substantial regional climate biases and inter-model differences
- RCM downscaling reduces GCM climate biases and inter-model differences
- RCM downscaling projects smaller warming trends, particularly in the central U.S.

## Air Quality Model Results

- the AQM ozone projections for 2100 under different emissions scenarios and incorporating climate changes
- the effect of the RCM climate sensitivity on AQM simulations and projections

**Air Quality Model Results**

## Slide 13

## Summary for AQ Simulations

- Ozone concentration depends sensitively on temperature as expected, but this sensitivity is regionally variable
- This sensitivity is particularly high in the Southeast U.S. where the difference between high and low emissions scenarios is pronounced
- If the high emissions scenarios are realized in the future, the Southeast U.S. may have a difficult time meeting the NAAQS O3 standard as a result of substantial O3 increase due to the *projected* warmer climate and more biogenic VOC emissions

## Overall Regional Uncertainty

- the spread among models of Midwest temperature and ozone biases and future projections under various emissions scenarios
- the sensitivity of ozone temperature-dependence to regional emission changes

**Overall Regional Uncertainty**

## U.S. Midwest regional temperature biases and future projections by GCMs (PCM, HAD) and their downscaling RCMs (GR, KF)

**U.S. Midwest regional temperature biases and future projections by GCMs (PCM, HAD) and their downscaling RCMs (GR, KF)**

## U.S. Midwest regional ozone biases and future projections by GCMs (PCM, HAD) and their downscaling RCMs (GR, KF)

**U.S. Midwest regional ozone biases and future projections by GCMs (PCM, HAD) and their downscaling RCMs (GR, KF)**

## Long-range transport can exacerbate local and regional air quality problems by elevating the background and loading during episodes.

**Long-Range Transport Impact on Local-Regional AQ**

## Conclusions

- The regional model downscaling can significantly reduce biases of the driving global models in simulating the present climate/air quality patterns and that this improvement has important consequences for future projections of regional climate/air quality changes.
- For both the present and future climate simulations, the regional model results are sensitive to the planetary forcings imposed by outputs from different global models as well as to its own physical process representations, especially different cumulus parameterizations, with strong regional dependence.

## Conclusions

- Due to these sensitivities, there are large uncertainties involved in application of model projections of future climate/air quality changes for decision making at regional to local scales.
- Given significant uncertainties in estimating/projecting surface emissions and important contributions from long-range pollutant transport, decision making on U.S. air quality regulation is challenging.

- Thanks