the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
25 Mar 2021
25 Mar 2021
Estimation of ship emission rates at a major shipping lane by long path DOAS measurements
- 1Institute of Environmental Physics, University of Bremen, Germany
- 2Federal Maritime and Hydrographic Agency (BSH), Hamburg, Germany
- 3Institute of Environmental Physics, University of Heidelberg, Germany
- 4Airyx GmbH, Heidelberg, Germany
- 1Institute of Environmental Physics, University of Bremen, Germany
- 2Federal Maritime and Hydrographic Agency (BSH), Hamburg, Germany
- 3Institute of Environmental Physics, University of Heidelberg, Germany
- 4Airyx GmbH, Heidelberg, Germany
Abstract. Ships are an important source of SO2 and NOx, which are key parameters of air quality. Monitoring of ship emissions is usually carried out using in situ instruments on land, which depend on favourable wind conditions to transport the emitted substances to the measurement site. Remote sensing techniques such as long path DOAS (LP-DOAS) measurements can supplement those measurements, especially in unfavourable meteorological conditions. In this study one year of LP-DOAS measurements made across the river Elbe close to Hamburg (Germany) have been evaluated. Peaks (i.e. elevated concentrations) in the NO2 and SO2 time series were assigned to passing ships and a method to derive emission rates of SO2, NO2 and NOx from those measurements using a Gaussian plume model is presented. 7402 individual ship passages have been monitored and their respective NOx, SO2 and NO2 emission rates have been derived. The emission rates, coupled with the knowledge of the ship type, ship size and ship speed have been analysed. Emission rates are compared to emission factors from previous studies and show good agreement. In contrast to emission factors (in gram per kilogram fuel) the derived emission rates (in gram per second) do not need further knowledge about the fuel consumption of the ship. To our knowledge this is the first time emission rates of air pollutants from individual ships have been derived from LP-DOAS measurements.
Kai Krause et al.
Status: final response (author comments only)
-
RC1: 'Comment on amt-2021-65', Anonymous Referee #1, 07 Apr 2021
The authors reported a new program for studying ship emission rates based on active remote sensing observations. Monitoring of ship emissions is usually carried out using in situ instruments on land, which depend on favourable wind conditions to transport the emitted substances to the measurement site. LP-DOAS measurements overcomes this shortcoming, and it realized real-time observation. However, there are some issues that need to be explained by the authors. After these minor corrections, this manuscript can be accepted by AMT.
- The measured NOx and SO2 concentration and their emission rates should be validated with the measured data.
- How to characterize the emission concentration and emission rates of NOx and SO2 at the ship chimney mouth?
- During the analysis, the authors should quantify the impact of NOx
-
AC1: 'Reply on RC1', Kai Krause, 18 Jun 2021
The comment was uploaded in the form of a supplement: https://amt.copernicus.org/preprints/amt-2021-65/amt-2021-65-AC1-supplement.pdf
-
RC2: 'Comment on amt-2021-65', Anonymous Referee #2, 15 Apr 2021
The paper presented by Krause et al. reported a novel approach to derive ship emission rates of NO2, NOx and SO2 from LP-DOAS measurements combing a Gaussian plume model. It falls into the scope of AMT journal and well written. It can be accepted after addressing the following concerns.
Sect. 2.4.: Please describe generally the spectral analysis performance, e.g. how about the residual and the fit errors for each species? And any filtering applied for measured data before introducing the inversion program.
Sect. 2.4.1: If there were averagely 110 ship passages per day and >200 days measured data were analyzed, does it mean that only 30% success rate of the identification, e.g. 7402/(110*233). I think the authors could discuss more details about this or any explanations, which may be related the performance of the identification algorithm.
Sect. 2.4.2: If I do understand correctly, the authors used NO2/NOx ratio is provide by the in-situ measurement at river side, which is the aged plume rather than the fresh plume at the chimney. The difference of NO2/NOx ratio between fresh and aged plume will result in the larger uncertainties on the conversion of NO2 to NOx. In addition, the authors need to check the dependence of in-situ measured NO2/NOx on the ship position and wind direction.
Sect. 2.4.3: Any introduction for Equation 6 and relevant parameters? Moreover, considering the movements of ships and continuous emission of chimney, the detected plume by LP-DOAS at given time is not only the pure emission of the start point, but also mixed with the subsequent ship plume during the cruise. Did the authors consider this condition in the Gaussian plume model estimation? If not, at least the authors should take an example to evaluate the effects on the model evaluation.
Table 2, please specify the temperature of the used absorption cross section
-
AC2: 'Reply on RC2', Kai Krause, 18 Jun 2021
The comment was uploaded in the form of a supplement: https://amt.copernicus.org/preprints/amt-2021-65/amt-2021-65-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Kai Krause, 18 Jun 2021
Kai Krause et al.
Kai Krause et al.
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 312 | 130 | 11 | 453 | 3 | 7 |
- HTML: 312
- PDF: 130
- XML: 11
- Total: 453
- BibTeX: 3
- EndNote: 7
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1