Assessing air quality progress using on-road emissions inventories updates.

Area of Science:

• Environmental Science
• Atmospheric Chemistry
• Air Quality Management

Background:

• Air quality attainment relies on accurate emission inventories.
• Inconsistent inventory assumptions can obscure true progress.
• Previous studies highlight the sensitivity of air quality models to input data.

Purpose of the Study:

• To investigate how varying emission inventory assumptions impact air quality attainment assessments.
• To quantify the differences in expected carbon monoxide (CO) concentration changes based on different CO emission inventories.
• To evaluate the adequacy of current guidance for air quality conformity determinations.

Main Methods:

• Utilized ambient carbon monoxide data from the California South Coast Air Basin (1990-1995).
• Employed four distinct regional CO emission inventory estimates for the same period.
• Specified mixed-effects models to link ambient CO concentrations with estimated emissions.
• Calculated the expected increase in ambient CO concentration per ton of emitted CO for each inventory scenario.

Main Results:

• Statistically significant differences were observed in the calculated rates of expected CO concentration change across the four emission inventory scenarios.
• The choice of emission inventory assumptions directly influences the assessment of progress toward air quality attainment.
• Rollback relationships varied considerably depending on the underlying emission data used.

Conclusions:

• Emission inventory development assumptions significantly confound air quality attainment progress evaluations.
• Current guidance for conformity determinations is insufficient to account for uncertainties in emission inventories.
• Standardized methodologies for emission inventory development are crucial for reliable air quality management.