This assessment by the Environmental Effects Assessment Panel (EEAP) of the United Nations Environment Programme (UNEP) provides the latest scientific update since our most recent comprehensive assessment (Photochemical and Photobiological Sciences, 2019, 18, 595–828). The interactive effects between the stratospheric ozone layer, solar ultraviolet (UV) radiation, and climate change are presented within the framework of the Montreal Protocol and the United Nations Sustainable Development Goals. We address how these global environmental changes affect the atmosphere and air quality; human health; terrestrial and aquatic ecosystems; biogeochemical cycles; and materials used in outdoor construction, solar energy technologies, and fabrics. In many cases, there is a growing influence from changes in seasonality and extreme events due to climate change. Additionally, we assess the transmission and environmental effects of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is responsible for the COVID-19 pandemic, in the context of linkages with solar UV radiation and the Montreal Protocol.

Differential pigmentation between phytoplankton allows use of fluorescence excitation spectroscopy for the discrimination and classification of different taxa. Here, we describe the design and performance of a fluorescence imaging photometer that exploits taxonomic differences for discrimination and classification. The fluorescence imaging photometer works by illuminating individual phytoplankton cells through an asynchronous spinning filter wheel, which produces bar code-like streaks in a fluorescence image. A filter position is covered with an opaque filter to create a reference dark position in the filter wheel rotation that is used to match each fluorescence streak with the corresponding filter. Fluorescence intensities of the imaged streaks are then analyzed for the purpose of spectral analysis, which allows taxonomic classification of the organism that produced the streaks. The theoretical performance and signal-to-noise ratio (SNR) specifications of these MOEs are described in Part I of this series. This report describes optical layout, flow cell design, magnification, depth of field, constraints on filter wheel and flow velocities, procedures for blank subtraction and flat-field correction, the measurement scheme of the instrument, and measurement of SNR as a measurement of filter wheel frequency. This is followed by an analysis of the sources of variance in measurements made by the photometer on the coccolithophore Emiliania huxleyi. We conclude that the SNR of E. huxleyi measurements is not limited by the sensitivity or noise attributes of the measurement system, but by dynamics in the fluorescence efficiency of the E. huxleyi cells. Even so, the minimum SNR requirements given in Part I for the instrument are met.

A better understanding of the degradation modes and rates for photovoltaic (PV) modules is necessary to optimize and extend the lifetime of these modules. Lifetime and degradation science (L&DS) is used to understand degradation modes, mechanisms and rates of materials, components and systems to predict lifetime of PV modules. A PV module lifetime and degradation science (PVM L&DS) model is an essential component to predict lifetime and mitigate degradation of PV modules using reproducible open data science. Previously published accelerated testing data from Underwriter Laboratories on PV modules with fluorinated polyester backsheets, which included eight modules that were exposed up to 4000 hrs of damp heat (85% relative humidity at 85 • C) and eight exposed up to 4000 hrs of ultraviolet light (80 W/m 2 of 280-400 nm wavelengths at 60 • C) (UV preconditioning) were used to determine statistically significant relationships between the applied stresses and measured responses. There were 15 different variables tracking aspects of system performance, degradation mechanisms, component metrics and time. Modules were analyzed for three system performance metrics (fill factor, peak power, and wet insulation). The results were statistically analyzed to identify variable transformations, statistically significant relationships (SSRs) and to develop the PVM L&DS model informed by a generalization of structural equation modeling techniques. The SSRs and significant model coefficients, combined with domain analytics, incorporating materials science, chemistry, and physics expertise, produced a pathway diagram ranking the variables' impact on the system performance, which were iteratively examined using sound statistical analysis and diagnostics. The SSRs determined from the damp heat exposure for the system response of Pmax corresponded to the degradation pathway of polyester terephthalate (PET) and ethylene vinyl acetate (EVA) hydrolysis. A linear change point for the damp heat exposure with the system response of Pmax was determined to be 1890 hrs. The UV preconditioning exposure did not induce sufficient degradation shown by the quality of the R 2 values for many of the best fitting models. This exemplifies the development of a methodology to determine rank ordered lifetime and degradation pathways present in modules and their effects on module performance over lifetime.

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In the development of materials for enhanced photovoltaic (PV) performance, it is critical to have quantitative knowledge of both their initial performance and their performance over the required 25-year warranted lifetime of the PV system. Lifetime and degradation science, based on an environmental stress and response framework, is being developed to link the intensity and net stress to which materials, components, and systems are exposed to the responses observed and their subsequent degradation and damage accumulation over the lifetime. Induced absorbance to dose (IAD), a metric developed for solar radiation durability studies of solar and environmentally exposed materials, is defined as the rate of photodarkening or photobleaching of a material as a function of radiation dose. Quantitative degradation rates like IAD, determined over a wide range of stress intensities and net stresses, have the potential to predict degradation, failure, and power loss rates in photovoltaic systems over time caused by damage accumulation. Two grades of poly(methyl methacrylate) were exposed and evaluated in two cases of highintensity ultraviolet exposures. A three-to six-fold increase in photodarkening was observed for one acrylic formulation when exposed to UVA-340 light when compared with concentrated xenon-arc exposure. The other, more highly stabilized acrylic formulation, showed up to three times more photodarkening in the same exposure. Downloaded From: http://photonicsforenergy.spiedigitallibrary.org/ on 05/14/2015 Terms of Use: http://spiedl.org/terms Murray, Bruckman, and French: Photodegradation in a stress and response framework . Downloaded From: http://photonicsforenergy.spiedigitallibrary.org/ on 05/14/2015 Terms of Use: http://spiedl.org/terms Murray, Bruckman, and French: Photodegradation in a stress and response framework . Downloaded From: http://photonicsforenergy.spiedigitallibrary.org/ on 05/14/2015 Terms of Use: http://spiedl.org/terms Murray, Bruckman, and French: Photodegradation in a stress and response framework . Downloaded From: http://photonicsforenergy.spiedigitallibrary.org/ on 05/14/2015 Terms of Use: http://spiedl.org/terms Murray, Bruckman, and French: Photodegradation in a stress and response framework . Downloaded From: http://photonicsforenergy.spiedigitallibrary.org/ on 05/14/2015 Terms of Use: http://spiedl.org/terms Murray, Bruckman, and French: Photodegradation in a stress and response framework . Downloaded From: http://photonicsforenergy.spiedigitallibrary.org/ on 05/14/2015 Terms of Use: http://spiedl.org/terms Murray, Bruckman, and French: Photodegradation in a stress and response framework . Downloaded From: http://photonicsforenergy.spiedigitallibrary.org/ on 05/14/2015 Terms of Use: http://spiedl.org/terms Murray, Bruckman, and French: Photodegradation in a stress and response framework . Downloaded From: http://photonicsforenergy.spiedigitallibrary.org/ on 05/14/2015 Terms of Use: http://spiedl.org/terms Murray, Bruckman, and French: Photodegradation in a stress and response fram...

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Phytoplankton are single-celled, photosynthetic algae and cyanobacteria found in all aquatic environments. Differential pigmentation between phytoplankton taxa allows use of fluorescence excitation spectroscopy for discrimination and classification. For this work, we applied multivariate optical computing (MOC) to emulate linear discriminant vectors of phytoplankton fluorescence excitation spectra by using a simple filter-fluorometer arrangement. We grew nutrient-replete cultures of three differently pigmented species: the coccolithophore Emiliania huxleyi, the diatom Thalassiosira pseudonana, and the cyanobacterium Synechococcus sp. Linear discriminant analysis (LDA) was used to determine a suitable set of linear discriminant functions for classification of these species over an optimal wavelength range. Multivariate optical elements (MOEs) were then designed to predict the linear discriminant scores for the same calibration spectra. The theoretical performance specifications of these MOEs are described.