Global Health and Economic Impacts of Future Ozone Pollution

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).We assess the human health and economic impacts of projected 2000-2050 changes in ozone pollution using the MIT Emissions Prediction and Policy Analysis-Health Effects (EPPA-HE) model, in combination with results from the GEOS-Chem global tropospheric chemistry model that simulated climate and chemistry effects of IPCC SRES emissions. We use EPPA to assess the human health damages (including acute mortality and morbidity outcomes) caused by ozone pollution and quantify their economic impacts in sixteen world regions. We compare the costs of ozone pollution under scenarios with 2000 and 2050 ozone precursor and greenhouse gas emissions (SRES A1B scenario). We estimate that health costs due to global ozone pollution above pre-industrial levels by 2050 will be $580 billion (year 2000$) and that acute mortalities will exceed 2 million. We find that previous methodologies underestimate costs of air pollution by more than a third because they do not take into account the long-term, compounding effects of health costs. The economic effects of emissions changes far exceed the influence of climate alone.United States Department of Energy, Office of Science (BER) grants DE-FG02-94ER61937 and DE-FG02-93ER61677, the United States Environmental Protection Agency grant EPA-XA-83344601-0, and the industrial and foundation sponsors of the MIT Joint Program on the Science and Policy of Global Change

Smart Toothbrushes: Inertial Measurement Sensors Fusion with Visual Tracking

A proper toothbrushing is a crucial aspect to preserve person's dental health. Furthermore dierent brushing techniques have been dened for kids, adults and people with dierent dental appliances, prostheses, partial dentures or oral pathologies. In order to provide a real-time feedback to the user there are, mainly, two approaches: the first one is based on intelligent toothbrushes (called smart toothbrushes) where Inertial Measurement Units, bristles pressure sensor, and also cameras are placed on the toothbrush; data acquired is then transmitted and processed on a smartphone or tablet that monitor the user's habit and provide him/her with brushing statistics together with suggestions to tune brushing timing and technique. The second approach simplifies the toothbrush device transferring the computational eorts to the handheld device: from the onboard camera it has to track both user's face and toothbrush in order to extract brushing parameters. In this paper we compare the two approaches concluding that only a fusion of their data can produce an all-around exhaustive analysis of the tooth brushing technique