# Presentation: 113869

## Sensitivity Analysis of Weekday/Weekend Differences in Photochemical Air Pollution

**Laurent Vuilleumier,**
**Lawrence Berkeley National Laboratory**

- <date/time>

## Collaborators

**Robert A. Harley**
**University of California, Berkeley**
**Nancy J. Brown**
**Lawrence Berkeley National Laboratory**

## Presentation Outline

**Motivations**
**The weekend effect: What is it? Why choosing it?**
**What can sensitivity analysis bring?**
**Model description**
**Emissions.**
**Results**
**Is it possible to model the weekend effect?**
**Using sensitivity analysis to understand the weekend effect.**
**Accuracy of sensitivity analysis prediction.**

## Motivations

**	****Despite lower emissions and concentration of NO****x****, VOC (volatile organic compound) and CO on weekend, average ozone concentrations are higher on weekend than on weekdays in many California urban areas.**
**Provide the detailed understanding of weekend effect needed for designing strategies to attain National Ambient Air Quality Standard for ozone.**
**Demonstrate the usefulness of sensitivity analysis for obtaining detailed understanding of model mechanism.**
**Develop and evaluate sensitivity analysis techniques to be used in model assessment and uncertainty analysis.**

## The Model

**	****Lagrangian box model**
**	****Equations for both the pollutant concentrations and their**** ****sensitivities to the model input parameters are solved in**** ****parallel.**
**	****Model governing equation:**

## Sensitivities

**	****Analytical derivation of sensitivities:**
**	****The model governing equation is derived with respect to input parameters under the assumption that they are constant within a simulation.**

## The solution of the sensitivity equation is given by:

The Green’s function is computed as follows:

- The Green’s function is computed as follows:

**Solution with a Green’s function method**

## Emissions

**Vehicle and stationary source emissions are**
**treated separately.**
**The pollutant concentration changes due to**
**emissions are computed with:**
**Emphasis was put on vehicle emissions when**
**analyzing weekday/weekend differences.**

- Emission fluxes (g m-2 day-1)

- Emission time profile

- Mixing height

## Emission Fluxes

- 	Alameda County, CA, emission fluxes are used. Vehicle emissions fluxes for weekdays, Saturday and Sunday are different. For stationary sources, the same value is used for weekdays, Saturday and Sunday.

**A published emission inventory for California is used.**

## Vehicle Emission Time Profile

**	**Time profiles are derived from traffic intensity measurements at 3 sites.
- 	The sum of two gaussians is fitted to the data.
- 	The average site-to-site variability is used as a measure of the error.

## Site to site variability

- 	Data from the 3 sites were averaged. The residuals between the individual site measurements and the averages were used to estimate the error.

## Chemical mechanism

**	****Used two published mechanisms:**
**	****The Carbon Bond IV mechanism (CB4) and the condensed version of the surrogate species mechanism of Lurmann, Carter and Coyner (LCC)**.
**	****The chemical mechanism is the only part that allows influence of one species on another:**

- Parameter vector

- Concentration vector

## Tropospheric ozone production

## Dilution and Mixing Height

- 	Due to surface air heating, the height of the well-mixed layer above ground varies during the day.
- 	Resulting in dilution, entrainment of pollutants aloft, and changing the volume of air in which the pollutants are emitted.
- 	A mixing height profile was produced with data from acoustic sounding in Claremont, CA.

## Results

**	****Simulations conducted with weekend conditions resulted in ozone concentrations about 20% higher than simulations with weekday conditions.**

**A**

## Ozone concentration (ppm) vs. time (hour) for weekdays, Saturday and Sunday

**Environmental Energy Technologies Division**

- <date/time>

## Results

**	****Ozone sensitivities to emission fluxes and initial conditions are typical of a VOC-limited system.**

**B**

## Ozone sensitivities (ppm) to emissions and initial concentrations vs. time (hour)

**Environmental Energy Technologies Division**

- <date/time>

## Results

**	****Sensitivity analysis estimation of the differences in peak ozone concentrations between weekdays and weekend are of correct sign and correct order-of-magnitude. Sensitivity analysis shows that the decrease in NO****x**** emissions on weekends is the main cause for the ozone concentration increase.**

**C**

## Sensitivity analysis predictions for weekday/Saturday differences in [O3]

**Environmental Energy Technologies Division**

- <date/time>

## Sensitivity analysis predictions for weekday/Sunday differences in [O3]

**Environmental Energy Technologies Division**

- <date/time>

## Validity of sensitivity analysis approximations

**	****Why is the sensitivity analysis approximation for the Sunday ozone concentration change   ******** 60%higher than the real prediction?**
**	****Is it possible to resolve the discrepancy by computing higher orders?**

## First- and second-order sensitivity analysis approximations

- First-order:
- Second-order:

## Test of sensitivity approximations for [O3] when ESNO value is changed

**Environmental Energy Technologies Division**

- <date/time>

## To be or not to be VOC-limited?

- 	A change in model mechanism is often the reason for sensitivity analysis inaccuracies.
- 	The VOC to NOx ratio suggest that the model is less likely to be in VOC-limited mode on weekend days than on weekdays.
- 	Green’s function analysis can reveal the mechanistic information.

## Green’s function relating [O3](t) to [NO] (t’) for weekdays and Sunday

**Environmental Energy Technologies Division**

- <date/time>

## Conclusions

**It is possible to reproduce the weekend effect with a simulation.**
**Sensitivity analysis showed the reason for these differences.**
**Green’s function analysis is a powerful tool to obtain a detailed picture of the model mechanism.**