Date of Award

12-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Statement

Doctor of Philosophy in Environmental Chemistry

Department

Department of Chemistry & Biochemistry

Granting Institution

University of Alaska Fairbanks

Committee Chair

Mao, Jingqiu

Committee Member

Simpson, William R.

Committee Member

Euskirchen, Eugénie

Committee Member

Collins, Richard

Table of Contents

Chapter 1: Introduction

1.1 What is formaldehyde

1.2 Remote sensing of formaldehyde in the past and near future

1.3 Formaldehyde is a powerful tool of understanding arctic change

1.4 Remote sensing and modeling of wildfire smoke

1.5 Diurnal cycle of photochemistry and air quality

1.7 Summary

1.8 References

Chapter 2: Source and variability of formaldehyde (HCHO) at northern high latitudes: an integrated satellite, aircraft, and model study

2.1 Introduction

2.2 Observations and model

2.3 Model evaluation by ATom-1

2.4 Evaluating TROPOMI HCHO product

2.5 Discussion and conclusions

2.6 References

Chapter 3: Interannual variability of summertime formaldehyde (HCHO) vertical column density and its main drivers in northern high latitudes

3.1 Introduction

3.2 Observations and model

3.3 Evaluation on spatial distribution of HCHO VCD and BVOC emissions

3.4 Examination on the interannual variabilities of HCHO VCD

3.5 SIF evaluation on dVCDbio,GC interannual variability

3.6 Conclusions and discussions

3.7 Code, data, availability and supplementary

3.8 Author contributions

3.9 References

Chapter 4: Observational constraints on AOD-surface PM2.5 relationship during Alaskan wildfire seasons

4.1 Introduction

4.2 Materials and methods

4.2.1 Ground-based observations

4.2.2 Satellite aerosol retrievals

4.2.3 GEOS-chem simulations

4.2.4 Workflow

4.3 Results

4.3.1 Evaluation of AOD and surface-level PM2.5 in Alaska summertime

4.3.2 Evaluation on AOD-PM2.5 relationship in Alaska summer

4.3.3 Evaluation of aerosol vertical profiles

4.3.4 Estimating surface PM2.5 using observational ηobs-AOD relationship

4.4 Discussion

4.5 Associated context

4.6 References

Chapter 5: Summertime diurnal variability of formaldehyde (HCHO) over CONUS: constraints from Pandonia Global Network (PGN)

5.1 Introduction

5.2 Observations and model

5.3 HCHO diurnal variation from PGN

5.4 Evaluation of GEOS-CF modelled HCHO diurnal variations

5.5 Discussion and conclusions

5.6 Data availability

5.7 References

Chapter 6: Conclusions and future work

6.1 Conclusions

6.2 Future work

Abstract

Formaldehyde (HCHO) is a trace gas primarily found in the planetary boundary layer. It is a first-generation oxidation product of a wide range of volatile organic compounds (VOCs) during their reaction with hydroxyl radicals (OH) and serves as a key precursor for major air pollutants, including surface ozone (O3) and secondary organic aerosols (SOA). Despite its significance, HCHO remains poorly constrained in North America, particularly in the northern high latitudes. My Ph.D. research focuses on elucidating the variability of HCHO across the Arctic and the contiguous United States (CONUS), spanning temporal scales from diurnal cycles to interannual variability, and identifying the key drivers in these regions. My findings underscore the dominant influence of biomass burning on HCHO vertical column density (VCD) in Alaska during summer fire seasons. Furthermore, wildfires have been the primary driver of interannual variability in HCHO VCD across much of the pan-Arctic, encompassing Alaska, Siberia, and northern Canada, over the past 15 years. In CONUS, the diurnal cycle of HCHO is generally weak across most regions, except for Houston, where emissions of highly reactive anthropogenic VOCs lead to a pronounced diurnal variation. The GEOS-CF (GEOS Composition Forecasts, a NASA global atmospheric composition forecasting system), which provides the a priori input for trace gas products of NASA TEMPO satellite mission, systematically overestimates HCHO VCD in the northeastern and southeastern United States. This overestimation likely arises from biased VOC emission inventories and limitations in the representation of turbulence-chemistry interactions within the model. Notably, the spatial pattern of HCHO model bias mirrors that of surface ozone, suggesting a shared underlying cause. During heatwaves, these biases in HCHO and surface ozone become significantly amplified, highlighting the urgent need to improve constraints on the vertical distribution of ozone precursors at the continental scale. Such advancements are crucial to mitigate the severe skill degradation in air quality estimation under future extreme heat scenarios.

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