the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Investigating processes influencing simulation of local Arctic wintertime anthropogenic pollution in Fairbanks, Alaska during ALPACA-2022
Abstract. Lagrangian tracer simulations are deployed to investigate processes influencing vertical and horizontal dispersion of anthropogenic pollution in Fairbanks, Alaska, during the ALPACA-2022 field campaign. Simulations of carbon monoxide (CO), sulphur dioxide (SO2) and nitrogen oxides (NOx), including surface and elevated emissions, are highest at the surface under very cold stable conditions. Regional enhancements, simulated up to 200 m, are due to elevated power plant emissions above 50 m, with south-westerly pollutant outflow. Fairbanks regional pollution may be contributing to wintertime Arctic haze. Inclusion of a novel power plant plume rise treatment that considers the presence of surface and elevated temperature inversion layers leads to improved agreement with observed CO and NOx plumes with discrepancies attributed to, for example, displacement of plumes by modelled winds. At the surface, model results show that observed CO variability is largely driven by meteorology and to a lesser extent by emissions, although simulated tracers are sensitive to modelled vertical dispersion. Modelled underestimation of surface NOx during very cold polluted conditions is considerably improved following the inclusion of substantial increases in diesel vehicle NOx emissions at cold temperatures (e.g. a factor of 6 at -30 °C). In contrast, overestimation of surface SO2 is attributed to issues related to the vertical dispersion of elevated space heating emissions during strongly and weakly stable conditions. This study highlights the need for improvements to local wintertime Arctic anthropogenic surface and elevated emissions and improved simulation of Arctic stable boundary layers.
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Status: open (until 24 Aug 2024)
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RC1: 'Comment on egusphere-2024-1450', Anonymous Referee #1, 22 Jul 2024
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The authors present a modeling analysis of CO, NOx, and SO2 concentrations in Fairbanks, Alaska to align with the ALPACA-2022 measurement campaign. They use the FLEXPART Langrangian tracer model driven by meteorology from WRF and emissions from local power plants and the local environmental regulator. The model performance is better under some conditions than others, and a number of sensitivity analyses are presented to identify potential reasons for poor performance.
Overall, I find the analysis thorough and compelling. I only have minor suggestions and questions to improve clarity.
170: I found this description of the inversion diagnosis confusing. For example, the statement “no inversions are observed” is very peculiar given the importance of inversions noted throughout the rest of the study. I recommend rethinking how this diagnosis is presented.
Step changes introduced by calculating new injection heights every 12 hours is a limitation. The authors may consider the influence of smoothly varying heights between 12 hours calculated ones, e.g., using linear interpolation.
The point made on lines 369-370 need more context. It is unclear how the quoted concentrations of SO2 and SO4 relate to the local and regional influence noted in the beginning of the paragraph.
380-386 is unclear – please clarify what was done to estimate dCO and dNOx
416: note/clarify why only NOx observations are available
Table 4: green and red assignments are unclear – are these designated across simulations? If so, why are multiple values highlighted in each column and row?
Figure 10: “surface emission mixing ratios” are unclear. Are these concentration contributions from each sector calculated with sensitivitiy analyses? The description in lines 580-585 is not sufficient to interpret the figure.
Citation: https://doi.org/10.5194/egusphere-2024-1450-RC1
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