High-Resolution Modeling of Air Pollution in Denmark: With the DAnish Lagrangian Model (DALM)

TY - BOOK

T1 - High-Resolution Modeling of Air Pollution in Denmark

T2 - With the DAnish Lagrangian Model (DALM)

AU - Andersen, Christopher

N1 - Published 28th April 2023.

PY - 2023/8

Y1 - 2023/8

N2 - Air pollution is a global problem with severe implications for public health, climate, and biodiversity. The issues are complex because of the many sources contributing to the environmental exposures, the combination of long-range transported pollutants and contributions from local sources, and complicated atmospheric processes. To support the development of environmental policy to mitigate the impacts of air pollution on public health and the environment, it is essential to continuously develop improved tools and generate more and better data to advance our understanding. The main objective of this thesis is to considerably contribute to this endeavor through the construction of the new Lagrangian particle dispersion model, the DAnish Lagrangian Model (DALM). DALM aims to more accurately model the concentrations of air pollutants on local scale in Denmark compared to the Gaussian plume model, the Urban Background Model (UBM). This will be achieved by applying more realistic and comprehensive descriptions of important atmospheric processes suitable for long-term model simulations. Firstly, a large set of physical parameterizations and numerical solutions, mainly related to atmospheric transport, were implemented in DALM, and the model was set up to handle requisite input in form of meteorology, chemical boundary conditions, and emissions. DALM was validated against measurements at several Danish monitoring stations by applying different combinations of the implemented parameterizations, and the setup consisting of the best-performing combination of these was determined. Secondly, land use categories, dry deposition of nitrogen oxides (NOx) and carbon monoxide (CO), simple linear NOx chemistry, and vertical emission profiles were implemented in DALM. The model was thoroughly validated and compared against UBM for a four-year period where DALM generally showed the best performance. For daily averaged NOx concentrations, the mean Pearson correlation coefficient was 0.73 (ranging from 0.63 to 0.77) (DALM) and 0.63 (0.54 to 0.74) (UBM) while the normalized mean bias (NMB) was -0.19 (-0.41 to -0.03) (DALM) and 0.12 (-0.35 to 0.67) (UBM). Thirdly, a relatively simple equilibrium mechanism for the photochemical reactions between nitrogen monoxide (NO), nitrogen dioxide (NO2), and ozone (O3) was implemented in DALM alongside very high-resolution (200 m × 200 m) traffic emissions for a domain covering Copenhagen and its surrounding areas. Validations against measurements showed that DALM was able to satisfactorily compute concentrations of NO2 and O3, and the feasibility of using DALM for very high-resolution local-scale modeling. In conclusion, this thesis demonstrates that DALM is capable of simulating the local-scale air pollution over Denmark for multiple years, performing better than or comparably to UBM. A final study is included that presents an extensive evaluation of UBM for a domain covering Denmark, Finland, Norway, and Sweden for a 40-year period. This study highlights a future application of DALM but would involve considerable model optimization and/or limitations of the model domain or simulation period because of the higher computational cost related to the more advanced atmospheric parameterizations and the large number of Lagrangian particles used by DALM. Overall, we are confident that the development of DALM significantly contributes to the air pollution modeling landscape and we will work on further developing the model in order to improve human exposure assessments to provide more accurate health impact estimates.

AB - Air pollution is a global problem with severe implications for public health, climate, and biodiversity. The issues are complex because of the many sources contributing to the environmental exposures, the combination of long-range transported pollutants and contributions from local sources, and complicated atmospheric processes. To support the development of environmental policy to mitigate the impacts of air pollution on public health and the environment, it is essential to continuously develop improved tools and generate more and better data to advance our understanding. The main objective of this thesis is to considerably contribute to this endeavor through the construction of the new Lagrangian particle dispersion model, the DAnish Lagrangian Model (DALM). DALM aims to more accurately model the concentrations of air pollutants on local scale in Denmark compared to the Gaussian plume model, the Urban Background Model (UBM). This will be achieved by applying more realistic and comprehensive descriptions of important atmospheric processes suitable for long-term model simulations. Firstly, a large set of physical parameterizations and numerical solutions, mainly related to atmospheric transport, were implemented in DALM, and the model was set up to handle requisite input in form of meteorology, chemical boundary conditions, and emissions. DALM was validated against measurements at several Danish monitoring stations by applying different combinations of the implemented parameterizations, and the setup consisting of the best-performing combination of these was determined. Secondly, land use categories, dry deposition of nitrogen oxides (NOx) and carbon monoxide (CO), simple linear NOx chemistry, and vertical emission profiles were implemented in DALM. The model was thoroughly validated and compared against UBM for a four-year period where DALM generally showed the best performance. For daily averaged NOx concentrations, the mean Pearson correlation coefficient was 0.73 (ranging from 0.63 to 0.77) (DALM) and 0.63 (0.54 to 0.74) (UBM) while the normalized mean bias (NMB) was -0.19 (-0.41 to -0.03) (DALM) and 0.12 (-0.35 to 0.67) (UBM). Thirdly, a relatively simple equilibrium mechanism for the photochemical reactions between nitrogen monoxide (NO), nitrogen dioxide (NO2), and ozone (O3) was implemented in DALM alongside very high-resolution (200 m × 200 m) traffic emissions for a domain covering Copenhagen and its surrounding areas. Validations against measurements showed that DALM was able to satisfactorily compute concentrations of NO2 and O3, and the feasibility of using DALM for very high-resolution local-scale modeling. In conclusion, this thesis demonstrates that DALM is capable of simulating the local-scale air pollution over Denmark for multiple years, performing better than or comparably to UBM. A final study is included that presents an extensive evaluation of UBM for a domain covering Denmark, Finland, Norway, and Sweden for a 40-year period. This study highlights a future application of DALM but would involve considerable model optimization and/or limitations of the model domain or simulation period because of the higher computational cost related to the more advanced atmospheric parameterizations and the large number of Lagrangian particles used by DALM. Overall, we are confident that the development of DALM significantly contributes to the air pollution modeling landscape and we will work on further developing the model in order to improve human exposure assessments to provide more accurate health impact estimates.

KW - air pollution

KW - Lagrangian particle dispersion model

KW - local-scale modeling

KW - PBL parameterizations

KW - emissions

M3 - Ph.D. thesis

BT - High-Resolution Modeling of Air Pollution in Denmark

PB - Aarhus University

ER -