International Intercomparison of In Situ Chlorophyll-a Measurements for Data Quality Assurance of the Swedish Monitoring Program

Chlorophyll-a is an essential climate variable. Chlorophyll-a in situ measurements are usually used for the validation of satellite images. Previous intercomparisons have shown that there can be substantial differences between in situ laboratories. In order to shed light on these differences, we arranged international chlorophyll-a intercomparisons with eight participating laboratories during 1–2 July 2021. We performed two dedicated transects through Bråviken bay (NW Baltic proper) and sampled four stations in each transect along a chlorophyll-a gradient. We took three surface replicates per laboratory and per station, i.e., 24 samples per laboratory. The samples were filtered through Whatman GF/F filters, and filters were frozen in liquid nitrogen and distributed in dry ice to all laboratories together with chlorophyll-a standards. The results between labs compared quite well. The mean normalized bias (MNB) of the standard measurements ranged between −23% and +19% for all laboratories and −7% to +19% for the Baltic Sea laboratories compared to high-performance liquid chromatography. The MNB of the two Bråviken transects ranged between −23 and +17% for all laboratories (compared to the median of all spectrophotometric and fluorometric measurements) and between −2 and +17% for the Baltic Sea laboratories. On average, the chlorophyll-a concentrations measured by the fluorometric method were about 13% higher than those measured by spectrophotometry, and fluorometry samples tended to have more scatter. The largest uncertainties seem to be caused by variable storage and extraction methods and are not fully captured in this intercomparison. This is demonstrated by analyzing historical comparisons revealing very large uncertainties (root mean square difference (RMSD) up to 109% and bias up to 68%), possibly due to too low filtration volumes and due to different extraction and storage methods. Our recommendation is to flash-freeze samples in liquid nitrogen and store them at −80°C. After storage, they should be extracted and measured at room temperature within 6–24 h. Our results also indicate that ethanol is much more efficient in extracting Chl-a than acetone. Last but not least, we would like to point out that the uncertainties in measuring chlorophyll-a by satellite are now within the range of in situ data, as shown here by comparing the in situ results from this study with published remote sensing results from the literature.publishedVersio

International Intercomparison of In Situ Chlorophyll-a Measurements for Data Quality Assurance of the Swedish Monitoring Program

Chlorophyll-a is an essential climate variable. Chlorophyll-a in situ measurements are usually used for the validation of satellite images. Previous intercomparisons have shown that there can be substantial differences between in situ laboratories. In order to shed light on these differences, we arranged international chlorophyll-a intercomparisons with eight participating laboratories during 1–2 July 2021. We performed two dedicated transects through Bråviken bay (NW Baltic proper) and sampled four stations in each transect along a chlorophyll-a gradient. We took three surface replicates per laboratory and per station, i.e., 24 samples per laboratory. The samples were filtered through Whatman GF/F filters, and filters were frozen in liquid nitrogen and distributed in dry ice to all laboratories together with chlorophyll-a standards. The results between labs compared quite well. The mean normalized bias (MNB) of the standard measurements ranged between −23% and +19% for all laboratories and −7% to +19% for the Baltic Sea laboratories compared to high-performance liquid chromatography. The MNB of the two Bråviken transects ranged between −23 and +17% for all laboratories (compared to the median of all spectrophotometric and fluorometric measurements) and between −2 and +17% for the Baltic Sea laboratories. On average, the chlorophyll-a concentrations measured by the fluorometric method were about 13% higher than those measured by spectrophotometry, and fluorometry samples tended to have more scatter. The largest uncertainties seem to be caused by variable storage and extraction methods and are not fully captured in this intercomparison. This is demonstrated by analyzing historical comparisons revealing very large uncertainties (root mean square difference (RMSD) up to 109% and bias up to 68%), possibly due to too low filtration volumes and due to different extraction and storage methods. Our recommendation is to flash-freeze samples in liquid nitrogen and store them at −80°C. After storage, they should be extracted and measured at room temperature within 6–24 h. Our results also indicate that ethanol is much more efficient in extracting Chl-a than acetone. Last but not least, we would like to point out that the uncertainties in measuring chlorophyll-a by satellite are now within the range of in situ data, as shown here by comparing the in situ results from this study with published remote sensing results from the literature

The Effect of Optical Properties on Secchi Depth and Implications for Eutrophication Management

Successful management of coastal environments requires reliable monitoring methods and indicators. Besides Chlorophyll-a concentration (Chl-a), water transparency measured as Secchi Depth (ZSD) is widely used in Baltic Sea management for water quality assessment as eutrophication indicator. However, in many coastal waters not only phytoplankton but also colored dissolved organic matter (CDOM) and suspended particulate matter (SPM) influence the under-water light field, and therefore the ZSD. In this study all three main optical variables (CDOM, Chl-a, and SPM [organic and inorganic]) as well as ZSD were measured in three Swedish regions: the Bothnian Sea, the Baltic Proper, and the Skagerrak in 2010–2014. Regional multiple regressions with Chl-a, CDOM, and inorganic SPM as predictors explained the variations in ZSD well (Radj2 = 0.53–0.84). Commonality analyses of the regressions indicated considerable differences between regions regarding the contribution of each factor to the variance, Radj2, in ZSD. CDOM explained most of the variance in the Bothnian Sea and the Skagerrak; in general, Chl-a contributed only modestly to the ZSD variance. In the Baltic Proper the largest contribution was from the interaction of all three variables. As expected, the link between Chl-a and ZSD was much weaker in the Bothnian Sea with high CDOM absorption and SPM concentration. When applying the Swedish EU Water Framework Directive threshold for Good/Moderate Chl-a status in the models it was shown that ZSD is neither a sufficient indicator for eutrophication, nor for changes in Chl-a. Natural coastal gradients in CDOM and SPM influence the reference conditions for ZSD and other eutrophication indicators, such as the depth distribution of macro-algae. Hence, setting targets for these indicators based on reference Chl-a concentrations and simple Chl-a to ZSD relationships might in some cases be inappropriate and misleading due to overestimation of water transparency under natural conditions

On equalizing school expenditures

A conflict between efficiency and equity exists in the provision of public education. We examine this conflict and consider a compromise approach to school finance, "district power equalization" (DPE). DPE has never been implemented in its "pure" form, which would require raising tax prices in wealthy districts as well as lowering them in poorer districts. We present simulations of districts' expenditure per pupil under two DPE plans in three states. We find that a "pure" DPE plan would reduce variance in expenditure among districts and have sometimes dramatic consequences for the rank ordering of districts within a state by expenditure per pupil.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28852/1/0000687.pd

Municipal overburden: an empirical analysis

The municipal overburden hypothesis asserts the existence of a causal relationship between high levels of non-school municipal expenditure or tax rates and low levels of school spending. We estimate demand for expenditure on education using a median voter model. The hypothesis is tested by including in the estimating equation several versions of a variable representing municipal overburden. We find no evidence in support of the hypothesis.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/26403/1/0000490.pd

Computational environment for modeling and enhancing community resilience: Introducing the center for risk-based community resilience planning

The resilience of a community is defined as its ability to prepare for, withstand, recover from and adapt to the effects of natural or human-caused disasters, and depends on the performance of the built environment and on supporting social, economic and public institutions that are essential for immediate response and long-term recovery and adaptation. The performance of the built environment generally is governed by codes, standards, and regulations, which are applicable to individual facilities and residences, are based on different performance criteria, and do not account for the interdependence of buildings, transportation, utilities and other infrastructure sectors. The National Institute of Standards and Technology recently awarded a new Center of Excellence (NIST-CoE) for Risk-Based Community Resilience Planning, which is headquartered at Colorado State University and involves nine additional universities. Research in this Center is focusing on three major research thrusts: (1) developing the NIST-Community Resilience Modeling Environment known as NIST-CORE, thereby enabling alternative strategies to enhance community resilience to be measured quantitatively; (2) developing a standardized data ontology, robust data architecture and data management tools in support of NIST-CORE; and (3) performing a comprehensive set of hindcasts on disasters to validate the data architecture and NIST-CORE

Retrieval of suspended particulate matter from turbidity – model development, validation, and application to MERIS data over the Baltic Sea

Suspended particulate matter (SPM) causes most of the scattering in natural waters and thus has a strong influence on the underwater light field, and consequently on the whole ecosystem. Turbidity is related to the concentration of SPM which usually is measured gravimetrically, a rather time-consuming method. Measuring turbidity is quick and easy, and therefore also more cost-effective. When derived from remote sensing data the method becomes even more cost-effective because of the good spatial resolution of satellite data and the synoptic capability of the method. Turbidity is also listed in the European Union’s Marine Strategy Framework Directive as a supporting monitoring parameter, especially in the coastal zone. In this study, we aim to provide a new Baltic Sea algorithm to retrieve SPM concentration from in situ turbidity and investigate how this can be applied to satellite data. An in situ dataset was collected in Swedish coastal waters to develop a new SPM model. The model was then tested against independent datasets from both Swedish and Lithuanian coastal waters. Despite the optical variability in the datasets, SPM and turbidity were strongly correlated (r = 0.97). The developed model predicts SPM reliably from in situ turbidity (R2 = 0.93) with a mean normalized bias (MNB) of 2.4% for the Swedish and 14.0% for the Lithuanian datasets, and a relative error (RMS) of 25.3% and 37.3%, respectively. In the validation dataset, turbidity ranged from 0.3 to 49.8 FNU (Formazin Nephelometric Unit) and correspondingly, SPM concentration ranged from 0.3 to 34.0 g m–3 which covers the ranges typical for Baltic Sea waters. Next, the medium-resolution imaging spectrometer (MERIS) standard SPM product MERIS Ground Segment (MEGS) was tested on all available match-up data (n = 67). The correlation between SPM retrieved from MERIS and in situ SPM was strong for the Swedish dataset with r = 0.74 (RMS = 47.4 and MNB = 11.3%; n = 32) and very strong for the Lithuanian dataset with r = 0.94 (RMS = 29.5% and MNB = −1.5%; n = 35). Then, the turbidity was derived from the MERIS standard SPM product using the new in situ SPM model, but retrieving turbidity from SPM instead. The derived image was then compared to existing in situ data and showed to be in the right range of values for each sub-area. The new SPM model provides a robust and cost-efficient method to determine SPM from in situ turbidity measurements (or vice versa). The developed SPM model predicts SPM concentration with high quality despite the high coloured dissolved organic matter (CDOM) range in the Baltic Sea. By applying the developed SPM model to already existing remote sensing data (MERIS/Envisat) and most importantly to a new generation of satellite sensors (in particular OLCI on board the Sentinel-3), it is possible to derive turbidity for the Baltic Sea

Årsovervåkning med FerryBox og satellittdata- Indre Oslofjord 2022 - Datarapport

Prosjektleder: Wenche EikremDenne rapporten presenterer resultatene fra årsovervåkningen utført for Fagrådet for vann- og avløpsteknisk samarbeid i indre Oslofjord i 2022 med bruk av NIVAs FerryBox system for måling og prøveinnsamling og fjernmålingsdata fra Copernicus-satellittene Sentinel-2 og 3. Høyoppløselige sensor-data fra FerryBox med observasjoner hver andre dag illustrerer frekvensen og intensiteten til algeblomstringene i fjorden godt og at de kan ha en varighet på under 2 uker. Med månedlig prøvetagning kan man miste informasjon om flere oppblomstringer. De øvrige sensordataene viser utviklingen av andre miljøog klimavariabler. Satellittdata ga en god romslig dekning av fjorden og gjorde det mulig å følge utviklingen av klorofyll-a i tid og rom. Det var god overensstemmelse mellom in situ data og satellitt data, men satellitt data viste i perioder (april og oktober) høyere verdier. For mange stasjoner kunne antallet observasjoner fordobles og for andre med få eller ingen in situ observasjoner ga satellitt nye data. Samsvaret mellom satellittdata og in situ data var god.Fagrådet for vann- og avløpsteknisk samarbeid i indre OslofjordpublishedVersio

Undersøkelse av hydrografiske og biologiske forhold i Indre Oslofjord Årsrapport 2021

Prosjektleder/Hovedforfatter André StaalstrømVannkvaliteten er moderat på alle målestasjonene i Indre Oslofjord, inkludert Drøbaksundet. Det var dypvannsfornyelse i Bunnefjorden i 2021, kun litt over to år etter forrige dypvannsfornyelse. NFR sitt nye dypvannsutslipp i Bunnefjorden har gitt signifikant mer vertikal omrøring, som sannsynligvis var medvirkende til at dypvannet ble fornyet tidligere enn forventet. Drøbakjetéen har en positiv virkning på den vertikale omrøringen i fjorden og må bevares. I november 2021 ble det observert den største planteplanktonoppblomstringen i Oslofjorden på flere tiår.publishedVersio