Spectral Identification of Lighting Type and Character

We investigated the optimal spectral bands for the identification of lighting types and the estimation of four major indices used to measure the efficiency or character of lighting. To accomplish these objectives we collected high-resolution emission spectra (350 to 2,500 nm) for forty-three different lamps, encompassing nine of the major types of lamps used worldwide. The narrow band emission spectra were used to simulate radiances in eight spectral bands including the human eye photoreceptor bands (photopic, scotopic, and “meltopic”) plus five spectral bands in the visible and near-infrared modeled on bands flown on the Landsat Thematic Mapper (TM). The high-resolution continuous spectra are superior to the broad band combinations for the identification of lighting type and are the standard for calculation of Luminous Efficacy of Radiation (LER), Correlated Color Temperature (CCT) and Color Rendering Index (CRI). Given the high cost that would be associated with building and flying a hyperspectral sensor with detection limits low enough to observe nighttime lights we conclude that it would be more feasible to fly an instrument with a limited number of broad spectral bands in the visible to near infrared. The best set of broad spectral bands among those tested is blue, green, red and NIR bands modeled on the band set flown on the Landsat Thematic Mapper. This set provides low errors on the identification of lighting types and reasonable estimates of LER and CCT when compared to the other broad band set tested. None of the broad band sets tested could make reasonable estimates of Luminous Efficacy (LE) or CRI. The photopic band proved useful for the estimation of LER. However, the three photoreceptor bands performed poorly in the identification of lighting types when compared to the bands modeled on the Landsat Thematic Mapper. Our conclusion is that it is feasible to identify lighting type and make reasonable estimates of LER and CCT using four or more spectral bands with minimal spectral overlap spanning the 0.4 to 1.0 um region

Ambient air pollution and thrombosis

Abstract Air pollution is a growing public health concern of global significance. Acute and chronic exposure is known to impair cardiovascular function, exacerbate disease and increase cardiovascular mortality. Several plausible biological mechanisms have been proposed for these associations, however, at present, the pathways are incomplete. A seminal review by the American Heart Association (2010) concluded that the thrombotic effects of particulate air pollution likely contributed to their effects on cardiovascular mortality and morbidity. The aim of the current review is to appraise the newly accumulated scientific evidence (2009–2016) on contribution of haemostasis and thrombosis towards cardiovascular disease induced by exposure to both particulate and gaseous pollutants. Seventy four publications were reviewed in-depth. The weight of evidence suggests that acute exposure to fine particulate matter (PM2.5) induces a shift in the haemostatic balance towards a pro-thrombotic/pro-coagulative state. Insufficient data was available to ascertain if a similar relationship exists for gaseous pollutants, and very few studies have addressed long-term exposure to ambient air pollution. Platelet activation, oxidative stress, interplay between interleukin-6 and tissue factor, all appear to be potentially important mechanisms in pollution-mediated thrombosis, together with an emerging role for circulating microvesicles and epigenetic changes. Overall, the recent literature supports, and arguably strengthens, the contention that air pollution contributes to cardiovascular morbidity by promoting haemostasis. The volume and diversity of the evidence highlights the complexity of the pathophysiologic mechanisms by which air pollution promotes thrombosis; multiple pathways are plausible and it is most likely they act in concert. Future research should address the role gaseous pollutants play in the cardiovascular effects of air pollution mixture and direct comparison of potentially susceptible groups to healthy individuals