Abstract. Health impact analyses are increasingly tapping the broad spatial coverage of satellite aerosol optical depth (AOD) products to estimate human exposure to fine particulate matter (PM2.5). We use a forward geophysical approach to derive ground-level PM2.5 distributions from satellite AOD at 1 km2 resolution for 2011 over the northeastern US by applying relationships between surface PM2.5 and column AOD (calculated offline from speciated mass distributions) from a regional air quality model (CMAQ; 12×12 km2 horizontal resolution). Seasonal average satellite-derived PM2.5 reveals more spatial detail and best captures observed surface PM2.5 levels during summer. At the daily scale, however, satellite-derived PM2.5 is not only subject to measurement uncertainties from satellite instruments, but more importantly to uncertainties in the relationship between surface PM2.5 and column AOD. Using 11 ground-based AOD measurements within 10 km of surface PM2.5 monitors, we show that uncertainties in modeled PM2.5∕AOD can explain more than 70 % of the spatial and temporal variance in the total uncertainty in daily satellite-derived PM2.5 evaluated at PM2.5 monitors. This finding implies that a successful geophysical approach to deriving daily PM2.5 from satellite AOD requires model skill at capturing day-to-day variations in PM2.5∕AOD relationships. Overall, we estimate that uncertainties in the modeled PM2.5∕AOD lead to an error of 11 µg m−3 in daily satellite-derived PM2.5, and uncertainties in satellite AOD lead to an error of 8 µg m−3. Using multi-platform ground, airborne, and radiosonde measurements, we show that uncertainties of modeled PM2.5∕AOD are mainly driven by model uncertainties in aerosol column mass and speciation, while model representation of relative humidity and aerosol vertical profile shape contributes some systematic biases. The parameterization of aerosol optical properties, which determines the mass extinction efficiency, also contributes to random uncertainty, with the size distribution being the largest source of uncertainty and hygroscopicity of inorganic salt the second largest. Future efforts to reduce uncertainty in geophysical approaches to derive surface PM2.5 from satellite AOD would thus benefit from improving model representation of aerosol vertical distribution and aerosol optical properties, to narrow uncertainty in satellite-derived PM2.5.

Lifestyle therapy is an integral part of type 2 diabetes (T2D) management, but there remains no consensus on an optimal diet. The objective of this study is to evaluate the efficacy of therapeutic fasting as a treatment for T2D. This case follows a male T2D patient treated at the Intensive Dietary Management Clinic in Scarborough, Ontario, over a 4-month period. The patient’s initial fasting regimen consisted of a 24-h fast, three times a week. Over the course of treatment, the patient gradually extended his fasting period, eventually fasting for 42 h, two to three times a week. By the end of treatment, the patient’s weight was reduced by 17.8% and his waist circumference was reduced by 11.0%. In addition, the patient’s glycated haemoglobin levels decreased from 7.7% to 7.2%, and he was able to completely discontinue his insulin treatment, despite over a decade of insulin usage. The patient did not find it difficult to adhere to the fasting schedule and did not experience any hypoglycaemic episodes or other significant adverse effects. These observations suggest that therapeutic fasting may be a viable treatment option for T2D patients.

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<p><strong>Abstract.</strong> Health impact analyses are increasingly tapping the broad spatial coverage of satellite aerosol optical depth (AOD) products to estimate human exposure to fine particulate matter (PM<sub>2.5</sub>). We use a forward geophysical approach to derive ground-level PM<sub>2.5</sub> distributions from satellite AOD at 1 km<sup>2</sup> resolution for 2011 over the Northeast USA by applying relationships between surface PM<sub>2.5</sub> and column AOD (calculated offline from speciated mass distributions) from a regional air quality model (CMAQ; 12 × 12 km<sup>2</sup> horizontal resolution). Seasonal average satellite-derived PM<sub>2.5</sub> reveals more spatial detail and best captures observed surface PM<sub>2.5</sub> levels during summer. At the daily scale, however, satellite-derived PM<sub>2.5</sub> is not only subject to measurement uncertainties from satellite instruments, but more importantly, to uncertainties in the relationship between surface PM<sub>2.5</sub> and column AOD. Using 11 ground-based AOD measurements within 10 km of surface PM<sub>2.5</sub> monitors, we show that uncertainties in modeled PM<sub>2.5</sub>/AOD can explain more than 70 % of the spatial and temporal variance in the total uncertainty in daily satellite-derived PM<sub>2.5</sub> evaluated at PM<sub>2.5</sub> monitors. This finding implies that a successful geophysical approach to deriving daily PM<sub>2.5</sub> from satellite AOD requires model skill at capturing day-to-day variations in PM<sub>2.5</sub>/AOD relationships. Overall, we estimate that uncertainties in the modeled PM<sub>2.5</sub>/AOD lead to an error of 11 μg/m<sup>3</sup> in daily satellite-derived PM<sub>2.5</sub>, and uncertainties in satellite AOD lead to an error of 8 μg/m<sup>3</sup>. Using multi-platform ground, airborne and radiosonde measurements, we show that uncertainties of modeled PM<sub>2.5</sub>/AOD are mainly driven by model uncertainties in aerosol column mass and speciation, while model uncertainties of relative humidity and aerosol vertical profile shape contribute some systematic biases. The parameterization of aerosol optical properties, which determines the mass-extinction efficiency, also contributes to random uncertainty, with the size distribution the largest source of uncertainty, and hygroscopicity of inorganic salt the second. Future efforts to reduce uncertainty in geophysical approaches to derive surface PM<sub>2.5</sub> from satellite AOD would thus benefit from improving model representation of aerosol vertical distribution and aerosol optical properties, to narrow uncertainty in satellite-derived PM<sub>2.5</sub>.</p>

Current implementations of federal and state regulations have relied heavily on regional-scale photochemical models which, however, reflect outdated emissions and have a level of uncertainly due to the coarse grid resolution used in typical applications. The purpose of this study is to refine the 12 km grid resolution from recent assessments to a 4 km grid level in a novel application of the Community Multiscale Air Quality (CMAQ) modelling system on an annual timescale. The main incentive was to determine the total acidic and mercury deposition over New York State (NYS) and the contribution of the NYS power sector point sources. To that end, the latest available United States Environmental Protection Agency's (USEPA) National Emissions Inventory (NEI) for 2011 and Weather Research Forecast (WRF) simulated meteorological data were generated on the 4 km grid domain over the Northeastern United States centred on NYS. For mercury, emissions of the elemental, oxidized and particulate species were characterized for source categories to allow for species-dependent wet removal factors and dry deposition velocities. The results for mercury deposition indicate very low contributions from all NYS, but showed the importance of the oxidized Hg from both wet and dry components. The impacts of Hg emissions outside the modelling domain were found to clearly dominate total depositions in NYS. For acidic deposition, the wet component controlled for sulphate, while for total sulphur and nitrates, dry deposition had a significant contribution. For the NYS power sector, the only large contribution was due to dry deposition of SO2 for total sulphur. The projected total wet depositions of sulphate, nitrate and mercury compare very favourably with observed levels at National Atmospheric Deposition Program (NADP) sites.