Evaluation of Proposed Winter PM Concentration Reduction Strategies Using the MM5 and CAMx4 Modelling System-Christchurch, New Zealand, 2005–2013

Mikhail Titov；Andrew Sturman

MM5-CAMx4 ； PM10 ； Complex chemical scenario ； Linear and non-linear reduction ； Christchurch ； SLiP-CLiP

Aerosol and Air Quality Research

8卷2期（2008 / 06 / 01）

201 - 217

英文

Mesoscale Model (MM5) and Eulerian Comprehensive Air quality Model (CAMx4) were used to evaluate dispersion of particulate matter (PM) generated by ”Total” emissions for Christchurch (New Zealand) for winter 2005. ”Total” emissions consist of the ”Domestic”, ”Transport” and ”Industry” emissions. A composite chemical scenario generated from transport-related (day-time) and domestic-related (night-time) chemical scenarios was shown to be an optimal chemical split of input gridded emissions for predicting PM concentrations with minimal error when compared with ambient data. Reduction of gridded emissions of fine (PM2.5) and total (PM10) aerosol from domestic and transport sources can be achieved by linear reduction of the PM emissions in the emissions groups, as well as by non-linear reduction in the groups by varying the percentage of each chemical component of the scenario used to chemically split the PM input gridded emissions. Results of comparison of the linear and non-linear reduction for winter 2005 heavy smog episodes support the reliability of the 1999 inventory. The predicted linear and non-linear reduced PM values belong to the same population with correlation coefficients of 0.88 to 0.98. Based on these results, a sequence of experiments has been conducted to evaluate the potential decrease of PM winter concentrations over the 2005-2013 time period, using proposed reduction of PM winter emissions (in both the ”Domestic” and ”Transport” groups) using the linear reduction scheme. Two different abatement strategies outlined by the New Zealand Ministry for the Environment (MfE) to reduce aerosol concentrations and to achieve compliance with the PM reduction plan (target year 2013) were studied numerically using proposed aerosol emissions reductions.