Plug-in hybrid electric vehicles (PHEVs) offer an immediate solution for emissions reduction and fuel displacement within the current infrastructure. Targeting PHEV powertrain optimization, a plethora of energy management strategies (EMSs) have been proposed. Although these algorithms present various levels of complexity and accuracy, they find a limitation in terms of availability of future trip information, which generally prevents exploitation of the full PHEV potential in real-life cycles. This paper presents a comprehensive analysis of EMS evolution toward blended mode (BM) and optimal control, providing a thorough survey of the latest progress in optimization-based algorithms. This is performed in the context of connected vehicles and highlights certain contributions that intelligent transportation systems (ITSs), traffic information, and cloud computing can provide to enhance PHEV energy management. The study is culminated with an analysis of future trends in terms of optimization algorithm development, optimization criteria, PHEV integration in the smart grid, and vehicles as part of the fleet. Index Terms-Connected vehicles, energy management strategy (EMS), intelligent transportation systems (ITS), optimal control, plug-in hybrid electric vehicle (PHEV). I. INTRODUCTION A IR quality has become a serious concern in cities and urban areas in recent years. This has promoted new legislation, affecting the European automotive sector through Euro I-VI, which limits emissions of CO, HC, NO x , and particulate matter [1]. As Euro VI became into force, the spotlight is nowadays on CO 2 emissions. The European Commission has established a 130 g CO 2 /km target for 2015, which will be reduced to 95 g CO 2 /km in 2021 [2]. Similar policies have been imposed in other automotive markets, such as the USA, China, and Japan. This legislation has encouraged the introduction of Manuscript

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The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will carry into space the Ocean Color Instrument (OCI), a spectrometer measuring at 5 nm spectral resolution in the ultraviolet (UV) to near infrared (NIR) with additional spectral bands in the shortwave infrared (SWIR), and two multi-angle polarimeters that will overlap the OCI spectral range and spatial coverage, i. e., the Spectrometer for Planetary Exploration (SPEXone) and the Hyper-Angular Rainbow Polarimeter (HARP2). These instruments, especially when used in synergy, have great potential for improving estimates of water reflectance in the post Earth Observing System (EOS) era. Extending the topof-atmosphere (TOA) observations to the UV, where aerosol absorption is effective, adding spectral bands in the SWIR, where even the most turbid waters are black and sensitivity to the aerosol coarse mode is higher than at shorter wavelengths, and measuring in the oxygen A-band to estimate aerosol altitude will enable greater accuracy in atmospheric correction for ocean color science. The multi-angular and polarized measurements, sensitive to aerosol properties (e.g., size distribution, index of refraction), can further help to identify or constrain the aerosol model, or to retrieve directly water reflectance. Algorithms that exploit the new capabilities are presented, and their ability to improve accuracy is discussed. They embrace a modern, adapted heritage two-step algorithm and alternative schemes (deterministic, statistical) that aim at inverting the TOA signal in a single step. These schemes, by the nature of their construction, their robustness, their generalization properties, and their ability Frouin et al. Atmospheric Correction of Ocean-Color Imagery to associate uncertainties, are expected to become the new standard in the future. A strategy for atmospheric correction is presented that ensures continuity and consistency with past and present ocean-color missions while enabling full exploitation of the new dimensions and possibilities. Despite the major improvements anticipated with the PACE instruments, gaps/issues remain to be filled/tackled. They include dealing properly with whitecaps, taking into account Earth-curvature effects, correcting for adjacency effects, accounting for the coupling between scattering and absorption, modeling accurately water reflectance, and acquiring a sufficiently representative dataset of water reflectance in the UV to SWIR. Dedicated efforts, experimental and theoretical, are in order to gather the necessary information and rectify inadequacies. Ideas and solutions are put forward to address the unresolved issues. Thanks to its design and characteristics, the PACE mission will mark the beginning of a new era of unprecedented accuracy in ocean-color radiometry from space.

The conventional Lorenz-Mie formalism is extended to the case for a coated sphere embedded in an absorbing medium. The apparent and inherent scattering cross sections of a particle, derived from the far field and near field, respectively, are different if the host medium is absorptive. The effect of absorption within the host medium on the phase-matrix elements associated with polarization depends on the dielectric properties of the scattering particle. For the specific cases of a soot particle coated with a water layer and an ice sphere containing an air bubble, the phase-matrix elements ϪP 12 ͞P 11 and P 33 ͞P 11 are unique if the shell is thin. The radiative transfer equation for a multidisperse particle system embedded within an absorbing medium is discussed. Conventional multiple-scattering computational algorithms can be applied if scaled apparent single-scattering properties are applied.

We present here the results of chlorophyll-a (chl-a) concentration estimation using the red and near infrared (NIR) spectral bands of a Hyperspectral Imager for the Coastal Ocean (HICO) in productive turbid waters of the Azov Sea, Russia. During the data collection campaign in the summer of 2010 in Taganrog Bay and the Azov Sea, water samples were collected and concentrations of chl-a were measured analytically. The NIR-red models were tuned to optimize the spectral band selections and chl-a concentrations were retrieved from HICO data. The NIR-red three-band model with HICO-retrieved reflectances at wavelengths 684, 700, and 720 nm explained more than 85% of chl-a concentration variation in the range from 19.67 to 93.14 mg m −3 and was able to estimate chl-a with root mean square error below 10 mg m −3 . The results indicate the high potential of HICO data to estimate chl-a concentration in turbid productive (Case II) waters in real-time, which will be of immense value to scientists, natural resource managers, and decision makers involved in managing the inland and coastal aquatic ecosystems.