Search

Two efficient methods to study relationships between particulate matter (PM) concentrations and emission sources are compared in the three-dimensional comprehensive air quality model with extensions (CAMx). Particulate source apportionment technology (PSAT) is a tagged species method that apportions concentrations of PM components to their respective primary precursors, e.g., sulfate is apportioned to SOx, nitrate to NOx, etc. The decoupled direct method (DDM) calculates first-order sensitivities of PM concentrations to model inputs. Both tools were applied to two month long (February and July) PM modeling episodes and evaluated against changes in PM concentrations due to various emission reductions. The results show that source contributions calculated by PSAT start to deviate from the actual model responses as indirect effects from limiting reactants or nonprimary precursor emissions become important The DDM first-order sensitivity is useful for determining source contributions only if the model response to input changes is reasonably linear. For secondary inorganic PM, the response is linear for emission reductions of 20% in all cases considered and reasonably linear for reductions of 100% inthe case of on-road mobile sources. The model response for secondary organic aerosols and primary PM remains nearly linear to 100% reductions in anthropogenic emissions.

The decoupled direct method (DDM) is an efficient and accurate way of performing sensitivity analysis to model inputs. As the impact of atmospheric particulate matter (PM) on human health and visibility became evident, the need to extend the DDM to PM sensitivity has grown. In this work, the DDM is implemented in the three PM modules employed in the Comprehensive Air-quality Model with extensions (CAMx): ISORROPIA for inorganic gas/aerosol partitioning, SOAP for secondary organic gas/aerosol partitioning, and RADM-AQ for aqueous-phase chemistry. The PM modules are complex and the DDM implementation is discussed in detail. Stand-alone tests are performed for each PM module in which first-order sensitivities computed bythe DDM are compared tothe traditional brute-force method (BFM). The DDM sensitivities are shown to be accurate and agree well with the BFM within the linear response range. The SOAP module showed nearly linear response for up to +/-30% changes in concentration inputs. The RADM-AQ module showed moderately nonlinear response in some tests but first-order sensitivities accounted for most of the response for input changes up to +/-20%. ISORROPIA shows greater deviation from linear response than the other PM modules and the near-linear range can be as restricted as +/-10% changes in concentration inputs. Nonlinearity in ISORROPIA results both from the equations that describe thermodynamic equilibrium and the computational approaches within ISORROPIA that are employed to boost efficiency.

The decoupled direct method (DDM) is an efficient and accurate way of performing sensitivity analysis to model inputs. As the impact of atmospheric particulate matter (PM) on human health and visibility became evident, the need to extend the DDM to PM sensitivity has grown. In this work, the DDM is implemented in the three PM modules employed in the Comprehensive Air-quality Model with extensions (CAMx): ISORROPIA for inorganic gas/aerosol partitioning, SOAP for secondary organic gas/aerosol partitioning, and RADM-AQ for aqueous-phase chemistry. The PM modules are complex and the DDM implementation is discussed in detail. Stand-alone tests are performed for each PM module in which first-order sensitivities computed by the DDM are compared to the traditional brute-force method (BFM). The DDM sensitivities are shown to be accurate and agree well with the BFM within the linear response range. The SOAP module showed nearly linear response for up to ±30% changes in concentration inputs. The RADM-AQ module showed moderately nonlinear response in some tests but first-order sensitivities accounted for most of the response for input changes up to ±20%. ISORROPIA shows greater deviation from linear response than the other PM modules and the near-linear range can be as restricted as ±10% changes in concentration inputs. Nonlinearity in ISORROPIA results both from the equations that describe thermodynamic equilibrium and the computational approaches within ISORROPIA that are employed to boost efficiency. [ABSTRACT FROM AUTHOR]

Abstract: Increased use of ethanol as a vehicle fuel worldwide warrants the need to understand air quality impacts of replacing gasoline with ethanol. This study evaluates the impacts of dedicated E85 (85% ethanol/15% gasoline) light-duty vehicles on emissions, ozone and particulate matter (PM) concentrations in the United States for a future year (2022) using a 3-D photochemical model, detailed emissions inventories that account for changes in all sectors studied, and winter and summer meteorology that occurred in 2002. Use of E85 introduces new emissions from ethanol production and distribution, reduces petrochemical industry emissions due to lower gasoline consumption, changes on-road vehicle emissions and alters biogenic emissions due to land use changes. Three scenarios with increased ethanol production for dedicated E85 light-duty vehicles were compared to a base case without increased ethanol production. Increased use of E85 caused both increases and decreases in ozone and PM, driven mainly by changes in NO x emissions related to biogenic and upstream petrochemical industry sources. In all states modeled, adoption of dedicated E85 vehicles caused negligible change in average higher ozone and PM concentrations of importance for air quality management strategies. Ozone and PM changes are relatively insensitive to how land area is allocated for switchgrass production. The findings are subject to various uncertainties, especially those in vehicle technology and emissions from cellulosic ethanol production. [Copyright &y& Elsevier]

Two efficient methods to study relationships between particulate matter (PM) concentrations and emission sources are compared in the three-dimensional comprehensive air quality model with extensions (CAMx). Particulate source apportionment technology (PSAT) is a tagged species method that apportions concentrations of PM components to their respective primary precursors, e.g., sulfate is apportioned to SOx, nitrate to NOx, etc. The decoupled direct method (DDM) calculates first-order sensitivities of PM concentrations to model inputs. Both tools were applied to two month long (February and July) PM modeling episodes and evaluated against changes in PM concentrations due to various emission reductions. The results show that source contributions calculated by PSAT start to deviate from the actual model responses as indirect effects from limiting reactants or nonprimary precursor emissions become important. The DDM first-order sensitivity is useful for determining source contributions only if the model response to input changes is reasonably linear. For secondary inorganic PM, the response is linear for emission reductions of 20% in all cases considered and reasonably linear for reductions of 100% in the case of on-road mobile sources. The model response for secondary organic aerosols and primary PM remains nearly linear to 100% reductions in anthropogenic emissions. [ABSTRACT FROM AUTHOR]