Evaluation of the new ESR network software for the retrieval of direct sun products from cimel ce318 and prede pom01 sun-sky radiometers.

The European Skynet Radiometers network (EuroSkyRad or ESR) has been recently established as a research network of European PREDE sun-sky radiometers. Moreover, ESR is federated with SKYNET, an international network of PREDE sun-sky radiometers mostly present in East Asia. In contrast to SKYNET, the European network also integrates users of the CIMEL CE318 sky–sun photometer. Keeping instrumental duality in mind, a set of open source algorithms has been developed consisting of two modules for (1) the retrieval of direct sun products (aerosol optical depth, wavelength exponent and water vapor) from the sun extinction measurements; and (2) the inversion of the sky radiance to derive other aerosol optical properties such as size distribution, single scattering albedo or refractive index. In this study we evaluate the ESR direct sun products in comparison with the AERosol RObotic NETwork (AERONET) products. Specifically, we have applied the ESR algorithm to a CIMEL CE318 and PREDE POM simultaneously for a 4-yr database measured at the Burjassot site (Valencia, Spain), and compared the resultant products with the AERONET direct sun measurements obtained with the same CIMEL CE318 sky–sun photometer. The comparison shows that aerosol optical depth differences are mostly within the nominal uncertainty of 0.003 for a standard calibration instrument, and fall within the nominal AERONET uncertainty of 0.01–0.02 for a field instrument in the spectral range 340 to 1020 nm. In the cases of the Ångström exponent and the columnar water vapor, the differences are lower than 0.02 and 0.15 cm, respectively. Therefore, we present an open source code program that can be used with both CIMEL and PREDE sky radiometers and whose results are equivalent to AERONET and SKYNET retrievals.

Repeated mapping of reefs constructed by Sabellaria spinulosa Leuckart 1849 at an offshore wind farm site

Sabellaria spinulosa reefs are considered to be sensitive and of high conservation status. This article evaluates the feasibility of using remote sensing technology to delineate S. spinulosa reefs. S. spinulosa reef habitats associated with the Thanet Offshore Windfarm site were mapped using high resolution sidescan sonar (410 kHz) and multibeam echo sounder (<1 m2) data in 2005 (baseline), 2007 (pre-construction baseline) and 2012 (post-construction). The S. spinulosa reefs were identified in the acoustic data as areas of distinct irregular texturing. Maps created using acoustic data were validated using quantitative measures of reef quality, namely tube density (as a proxy for the density of live S. spinulosa), percentage cover of S. spinulosa structures (both living and dead) and associated macrofauna derived from seabed images taken across the development site. Statistically significant differences were observed in all physical measures of S. spinulosa as well the number (S) and diversity (H׳) of associated species, derived from seabed images classified according to the presence or absence of reef, validating the use of high resolution sidescan sonar to map these important biogenic habitats. High precision mapping in the early stages allowed for the micro-siting of wind turbines in a way that caused minimal damage to S. spinulosa reefs during construction. These habitats have since recovered and expanded in extent. The surveys undertaken at the Thanet Offshore Windfarm site demonstrate the importance of repeat mapping for this emerging industry, allowing habitat enhancement to be attributed to the development whilst preventing background habitat degradation from being wrongly attributed to the development.

Satellite discrimination of Karenia mikimotoi and Phaeocystis harmful algal blooms in European coastal waters: Merged classification of ocean colour data

The detection of dense harmful algal blooms (HABs) by satellite remote sensing is usually based on analysis of chlorophyll-a as a proxy. However, this approach does not provide information about the potential harm of bloom, nor can it identify the dominant species. The developed HAB risk classification method employs a fully automatic data-driven approach to identify key characteristics of water leaving radiances and derived quantities, and to classify pixels into “harmful”, “non-harmful” and “no bloom” categories using Linear Discriminant Analysis (LDA). Discrimination accuracy is increased through the use of spectral ratios of water leaving radiances, absorption and backscattering. To reduce the false alarm rate the data that cannot be reliably classified are automatically labelled as “unknown”. This method can be trained on different HAB species or extended to new sensors and then applied to generate independent HAB risk maps; these can be fused with other sensors to fill gaps or improve spatial or temporal resolution. The HAB discrimination technique has obtained accurate results on MODIS and MERIS data, correctly identifying 89% of Phaeocystis globosa HABs in the southern North Sea and 88% of Karenia mikimotoi blooms in the Western English Channel. A linear transformation of the ocean colour discriminants is used to estimate harmful cell counts, demonstrating greater accuracy than if based on chlorophyll-a; this will facilitate its integration into a HAB early warning system operating in the southern North Sea.

Lipid productivity and cell wall ultrastructure of six strains of Nannochloropsis: Implications for biofuel production and downstream processing

Microalgae are generating considerable interest for third generation biodiesel production. However, appropriate strain selection is proving challenging due to the significant variation in cellular physiology, metabolic potential and genetics observed even amongst strains deemed morphologically similar. Six strains of Nannochloropsis from the CCAP culture collection were assessed for their lipid productivity and cellular structure, as proxies for oil production and harvesting ease, to assess their suitability as biodiesel production platforms. Differences in growth rate and lipid accumulation across the strains were observed. Nannochloropsis oculata strain 849/7 showed significantly reduced doubling time compared to Nannochloropsis salina strain 849/3, whilst Nannochloropsis oceanica 849/10 produced the highest lipid content. In addition the six strains could be differentiated into 3 distinct classes based on their cell wall thickness, which varied across the strains from 63 to 119 nm and which is independent of both species and geographical isolation location. The importance of these variations in ultrastructure and physiology for biodiesel production is discussed.