# Properties of Arctic Aerosol Based on Sun Photometer Long-Term Measurements in Ny-Ålesund, Svalbard

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## Abstract

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## 1. Introduction

## 2. Instruments, Methods, and Data

## 3. A New Model for the Ångström Exponent

#### 3.1. Mie Calculus

#### 3.2. Case Study: Sun Photometer-Lidar

## 4. Results

#### 4.1. Trends in the AOD

#### 4.2. Histograms of Aerosol Load and Properties

## 5. Discussion Concerning the Aerosol Origin

#### 5.1. FLEXTRA Five-Day Back-Trajectories

#### 5.1.1. Aerosol Origin Due to Arriving Air Pollution

#### 5.1.2. Aerosol Sources and Sinks

#### 5.1.3. Remarks on the Advection Altitude

## 6. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## Appendix A. Definition of the Aerosol Distribution

## Appendix B. Additional Mie Calculus

**Figure A1.**Mie calculus for a homogeneous aerosol layer with a refractive index on $n=1.44+{10}^{-5}i$ and a standard deviation of $\sigma =1.05$.

## Appendix C. Trend of Both Modified Ångström Exponents

**Figure A2.**Trend of the traditional and modified Ångström exponents $AE$ (upper row), $\alpha $, and $\beta $ (lower row) for the years 2009–2017.

## References

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**Figure 1.**Green circles are individual measurements, the colored lines the fitted exponential law. Left: The data were fitted with the traditional Ångström law of Equation (1). Right: Equation (2) with two wavelength ranges of the UV and visible (<700 nm) and the near-infrared (>700 nm) were used for the same dataset.

**Figure 3.**30th and 70th percentile for traditional and modified Ångström parameters $AE$, $\alpha $, and $\beta $ depending on the noise level $\Delta AOD$.

**Figure 4.**Radius dependency of the traditional and modified Ångström exponent $AE$, $\alpha $, and $\beta $ for different refractive indexes and standard derivations $\sigma $.

**Figure 5.**Example of a clear day with a small cloud appearing at 14:30 with changes in the computed Ångström parameters afterwards.

**Figure 6.**Monthly means in AOD for the years 1994–2000 (first row), 2001–2009 (bottom, left), and 2009–2017 (bottom, right). The dashed magenta lines are the monthly means of the corresponding time interval. Note that the year 2009 is plotted as well in both plots (bottom) as a reference.

**Figure 7.**Left: Monthly mean $AO{D}_{500}$ for the years 1994–2000 (already published in Herber et al. [13]).

**Figure 8.**Histogram of one-minute photometer data of $AO{D}_{500}$ for April 2013 (left) and April 2017 (right).

**Figure 9.**Histograms of the spectral slope $\beta $ for April 2013 (left) and April 2017 (right). The blue bars are the total amount of measurements, whereas the yellow and red bars only represent the fraction of $\alpha >1.5$ and $\alpha <1.5$, respectively.

**Figure 10.**Correlation between the modified Ångström exponent $\alpha $ and its spectral slope $\beta $ for the haze season (April) and for summer conditions (August) of the years 2009–2017. The grey area indicates the possible combinations for $\alpha $ and $\beta $ using the Mie calculus of Figure 4.

**Figure 11.**Five-day back-trajectories arriving at a 1500 m altitude over Zeppelin Station for days with “low AOD” (left) and “high AOD” (right) for April 2013. Thick grey dots mark areas with a relative humidity >90% as an indication of hygroscopic growth of the aerosol.

**Figure 12.**Fraction of how long the air parcel was over land, ocean, or ice for the months of April, May, and August and arrived at a height of 1500 m over Ny-Ålesund for the years 2013–2017. The numbers below the bars indicate the total number of points for each category.

**Figure 13.**Fraction of how long the air parcel was over land, ocean, or ice. Left: All data points are plotted, independent of the height of the air parcel. Right: Only the cases are plotted where the air parcel was within the boundary layer (defined as $p>900$ hPa). This plot only shows the data for the arriving heights of 500 m and 1500 m above Zeppelin Station for all Aprils, 2013–2016. The numbers below the bars indicate the total number of points for each category.

**Figure 14.**Fraction of how long the air parcel was over land, ocean, or ice. Left: All data points are plotted, independent of the height of the air parcel. Right: Only the cases are plotted where the air parcel was within the boundary layer (defined as $p>900$ hPa). This plot only shows the data for the arriving heights of 500 m and 1500 m above Zeppelin Station for all Augusts, 2013–2017. The numbers below the bars indicate the total number of points for each category.

**Table 1.**Different possibilities for an effective radius, ${r}_{eff}$, depending on the standard deviation $\sigma $ of the distribution and refractive indexes ${n}_{1}$ and ${n}_{2}$ for given parameters $\alpha =1$, $\beta =-1.5$, and $AE=1$. The best matching combination of $\alpha $ and $\beta $ is highlighted in red.

Refractive Index${\mathit{n}}_{1}=1.60+0.01\mathit{i}$ | |||
---|---|---|---|

$\mathit{\sigma}$ | $\mathit{AE}$ | $\mathit{\alpha}$ | $\mathit{\beta}$ |

1.3 | ${r}_{eff,1}=0.01\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | ${r}_{eff}=0.13\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | ${r}_{eff,1}=0.11\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m |

${r}_{eff,2}=0.18\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | ${r}_{eff,2}=0.34\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | ||

1.5 | ${r}_{eff}=0.14\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | ${r}_{eff}=0.09\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | ${r}_{eff,1}=0.09\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m |

${r}_{eff,2}=0.20\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | |||

1.7 | ${r}_{eff}=0.10\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | ${r}_{eff}=0.07\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | ${r}_{eff,1}=0.11\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m |

${r}_{eff,2}=0.34\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | |||

Refractive Index${\mathit{n}}_{\mathbf{2}}=\mathbf{1}.\mathbf{44}+{\mathbf{10}}^{-\mathbf{5}}\mathit{i}$ | |||

$\mathit{\sigma}$ | $\mathit{AE}$ | $\mathit{\alpha}$ | $\mathit{\beta}$ |

1.3 | ${r}_{eff}=0.16\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | ${r}_{eff}=0.10\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | ${r}_{eff,1}=0.09\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m |

${r}_{eff,2}=0.16\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | |||

1.5 | ${r}_{eff}=0.21\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | ${r}_{eff}=0.14\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | ${r}_{eff,1}=0.06\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m |

${r}_{eff,2}=0.35\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | |||

1.7 | ${r}_{eff}=0.28\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | ${r}_{eff}=0.19\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m | ${r}_{eff,1}=0.05\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m |

${r}_{eff,2}=0.16\phantom{\rule{3.33333pt}{0ex}}\mathsf{\mu}$m |

**Table 2.**$AO{D}_{500}$ thresholds to distinguish back-trajectories arriving at Zeppelin Station with high and low AOD. They are the minima in the bimodal $AO{D}_{500}$ distributions.

Year | April | May | August |
---|---|---|---|

2013 | 0.07 | 0.04 | 0.035 |

2014 | 0.07 | 0.056 | 0.08 |

2015 | 0.085 | 0.09 | 0.07 |

2016 | 0.08 | 0.05 | 0.1 |

2017 | - | 0.08 | 0.035 |

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**MDPI and ACS Style**

Graßl, S.; Ritter, C. Properties of Arctic Aerosol Based on Sun Photometer Long-Term Measurements in Ny-Ålesund, Svalbard. *Remote Sens.* **2019**, *11*, 1362.
https://doi.org/10.3390/rs11111362

**AMA Style**

Graßl S, Ritter C. Properties of Arctic Aerosol Based on Sun Photometer Long-Term Measurements in Ny-Ålesund, Svalbard. *Remote Sensing*. 2019; 11(11):1362.
https://doi.org/10.3390/rs11111362

**Chicago/Turabian Style**

Graßl, Sandra, and Christoph Ritter. 2019. "Properties of Arctic Aerosol Based on Sun Photometer Long-Term Measurements in Ny-Ålesund, Svalbard" *Remote Sensing* 11, no. 11: 1362.
https://doi.org/10.3390/rs11111362