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In this paper, the Photoacoustic Aerosol Absorption Spectrometer (PAAS-4λ) is introduced. PAAS-4λ was specifically developed for long-term monitoring tasks in (unattended) air quality stations. It uses four wavelengths coupled to a single acoustic resonator in a compact and robust set-up. The instrument has been thoroughly characterized and carefully calibrated in the laboratory using NO2/air mixtures and Nigrosin aerosol. It has an ultimate 1σ detection limit below 0.1 Mm−1, at a measurement precision and accuracy of 3 % and 10 %, respectively. In order to demonstrate the PAAS-4λ suitability for long-term monitoring tasks, the instrument is currently validated at the air quality monitoring station Pallas in Finland, about 140 km north of the Arctic circle. A total of 11 months of PAAS-4λ data from this deployment are presented and discussed in terms of instrument performance. Intercomparisons with the filter-based photometers of a continuous soot monitoring system (COSMOS), the Multi-Angle Absorption Photometer (MAAP), and Aethalometer (AE33) demonstrate the capabilities and value of PAAS-4λ, as well as for the validation of the widely used filter-based instruments.

Long-term measurements of atmospheric mass concentrations of black carbon (BC) are needed to investigate changes in its emission, transport, and deposition. However, depending on instrumentation, parameters related to BC such as aerosol absorption coefficient (babs) have been measured instead. Most ground-based measurements of babs in the Arctic have been made by filter-based absorption photometers, including particle soot absorption photometers (PSAPs), continuous light absorption photometers (CLAPs), Aethalometers, and multi-angle absorption photometers (MAAPs). The measured babs can be converted to mass concentrations of BC (MBC) by assuming the value of the mass absorption cross section (MAC; MBC= babs/ MAC). However, the accuracy of conversion of babs to MBC has not been adequately assessed. Here, we introduce a systematic method for deriving MAC values from babs measured by these instruments and independently measured MBC. In this method, MBC was measured with a filter-based absorption photometer with a heated inlet (COSMOS). COSMOS-derived MBC (MBC (COSMOS)) is traceable to a rigorously calibrated single particle soot photometer (SP2), and the absolute accuracy of MBC (COSMOS) has been demonstrated previously to be about 15 % in Asia and the Arctic. The necessary conditions for application of this method are a high correlation of the measured babs with independently measured MBC and long-term stability of the regression slope, which is denoted as MACcor (MAC derived from the correlation). In general, babs–MBC (COSMOS) correlations were high (r2= 0.76–0.95 for hourly data) at Alert in Canada, Ny-Ålesund in Svalbard, Barrow (NOAA Barrow Observatory) in Alaska, Pallastunturi in Finland, and Fukue in Japan and stable for up to 10 years. We successfully estimated MACcor values (10.8–15.1 m2 g−1 at a wavelength of 550 nm for hourly data) for these instruments, and these MACcor values can be used to obtain error-constrained estimates of MBC from babs measured at these sites even in the past, when COSMOS measurements were not made. Because the absolute values of MBC at these Arctic sites estimated by this method are consistent with each other, they are applicable to the study of spatial and temporal variation in MBC in the Arctic and to evaluation of the performance of numerical model calculations.

Aerosol light absorption was measured during a 1-month field campaign in June–July 2019 at the Pallas Global Atmospheric Watch (GAW) station in northern Finland. Very low aerosol concentrations prevailed during the campaign, which posed a challenge for the instruments' detection capabilities. The campaign provided a real-world test for different absorption measurement techniques supporting the goals of the European Metrology Programme for Innovation and Research (EMPIR) Black Carbon (BC) project in developing aerosol absorption standard and reference methods. In this study we compare the results from five filter-based absorption techniques – aethalometer models AE31 and AE33, a particle soot absorption photometer (PSAP), a multi-angle absorption photometer (MAAP), and a continuous soot monitoring system (COSMOS) – and from one indirect technique called extinction minus scattering (EMS). The ability of the filter-based techniques was shown to be adequate to measure aerosol light absorption coefficients down to around 0.01 Mm−1 levels when data were averaged to 1–2 h. The hourly averaged atmospheric absorption measured by the reference MAAP was 0.09 Mm−1 (at a wavelength of 637 nm). When data were averaged for >1 h, the filter-based methods agreed to around 40 %. COSMOS systematically measured the lowest absorption coefficient values, which was expected due to the sample pre-treatment in the COSMOS inlet. PSAP showed the best linear correlation with MAAP (slope=0.95, R2=0.78), followed by AE31 (slope=0.93). A scattering correction applied to PSAP data improved the data accuracy despite the added noise. However, at very high scattering values the correction led to an underestimation of the absorption. The AE31 data had the highest noise and the correlation with MAAP was the lowest (R2=0.65). Statistically the best linear correlations with MAAP were obtained for AE33 and COSMOS (R2 close to 1), but the biases at around the zero values led to slopes clearly below 1. The sample pre-treatment in the COSMOS instrument resulted in the lowest fitted slope. In contrast to the filter-based techniques, the indirect EMS method was not adequate to measure the low absorption values found at the Pallas site. The lowest absorption at which the EMS signal could be distinguished from the noise was >0.1 Mm−1 at 1–2 h averaging times. The mass absorption cross section (MAC) value measured at a range 0–0.3 Mm−1 was calculated using the MAAP and a single particle soot photometer (SP2), resulting in a MAC value of 16.0±5.7 m2 g−1. Overall, our results demonstrate the challenges encountered in the aerosol absorption measurements in pristine environments and provide some useful guidelines for instrument selection and measurement practices. We highlight the need for a calibrated transfer standard for better inter-comparability of the absorption results.

Aerosolized black carbon is monitored worldwide to quantify its impact on air quality and climate. Given its importance, measurements of black carbon mass concentrations must be conducted with instruments operating in quality-checked and ensured conditions to generate data which are reliable and comparable temporally and geographically. In this study, we report the results from the largest characterization and intercomparison of filter-based absorption photometers, the Aethalometer model AE33, belonging to several European monitoring networks. Under controlled laboratory conditions, a total of 23 instruments measured mass concentrations of black carbon from three well-characterized aerosol sources: synthetic soot, nigrosin particles, and ambient air from the urban background of Leipzig, Germany. The objective was to investigate the individual performance of the instruments and their comparability; we analyzed the response of the instruments to the different aerosol sources and the impact caused by the use of obsolete filter materials and the application of maintenance activities. Differences in the instrument-to-instrument variabilities from equivalent black carbon (eBC) concentrations reported at 880 nm were determined before maintenance activities (for soot measurements, average deviation from total least square regression was −2.0 % and the range −16 % to 7 %; for nigrosin measurements, average deviation was 0.4 % and the range −15 % to 17 %), and after they were carried out (for soot measurements, average deviation was −1.0 % and the range −14 % to 8 %; for nigrosin measurements, the average deviation was 0.5 % and the range −12 % to 15 %). The deviations are in most of the cases explained by the type of filter material employed by the instruments, the total particle load on the filter, and the flow calibration. The results of this intercomparison activity show that relatively small unit-to-unit variability of AE33-based particle light absorbing measurements is possible with well-maintained instruments. It is crucial to follow the guidelines for maintenance activities and the use of the proper filter tape in the AE33 to ensure high quality and comparable black carbon (BC) measurements among international observational networks.

A semi-operative approach to retrieve chlorophyll-a concentration from airborne/spaceborne spectrometer observations has been developed and tested using the airborne imaging spectrometer (AISA) data from 11 lakes located in southern Finland. The retrieval approach is empirical and requires nearly simultaneous in situ training data on water quality for the determination of regression coefficients. However, the training data does not have to be collected from every lake under investigation. Instead, the results obtained indicate that reliable estimates on the level of chlorophyll-a (chl-a) for an individual lake can be achieved without employing in situ data representing this specific lake. This enables the estimation of water quality from remotely sensed data for numerous lakes with the aid of reference data only for a few selected lakes representing the region under investigation. In addition, it is shown that the remotely sensed spectrum shape characteristics are highly affected by the trophic and humic state of the lake water.

Chlorophyll-a (chl-a) concentration of lake water can be measured with airborne (or spaceborne) optical remote sensing instruments. The rmse obtained here with empirical algorithms and 122 measurement points was 8.9 microg/l (all points used for training and testing). Airborne Imaging Spectrometer for Applications (AISA) was used in four lake water quality measurement campaigns (8 measurement days) in southern Finland during 1996-1998 with other airborne instruments and extensive in situ data collection. As empirical algorithms are employed for chl-a retrieval from remote sensing data, temporally varying factors such as surface reflection and atmospheric effects degrade the estimation accuracy. This paper analyzes the quantitative accuracy of empirical chl-a retrieval algorithms available as methods to correct temporal disturbances are either included or excluded. The aim is to evaluate the usability of empirical chl-a retrieval algorithms in cases when no concurrent reference in situ data are available. Four methods to reduce the effects of temporal variations are investigated. The methods are: (1) atmospheric correction; (2) synchronous radiometer data; (3) wind speed data; and (4) bidirectional scattering model based on wind speed and sun angle data. The effects of different correction methods are analyzed by using single-date test data and multi-date training data sets. The results show that the use of a bidirectional scattering model and atmospheric correction reduces the bias component of the measurement error. Radiometer data also appear to improve the accuracy. However, if concurrent in situ reference data are not available, the retrieval algorithms and correction methods should be improved for reducing the bias error.