This study quantifies worldwide health effects of the Fukushima Daiichi nuclear accident on 11 March 2011. Effects are quantified with a 3-D global atmospheric model driven by emission estimates and evaluated against daily worldwide Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) measurements and observed deposition rates. Inhalation exposure, ground-level external exposure, and atmospheric external exposure pathways of radioactive iodine-131, cesium-137, and cesium-134 released from Fukushima are accounted for using a linear no-threshold (LNT) model of human exposure. Exposure due to ingestion of contaminated food and water is estimated by extrapolation. We estimate an additional 130 (15-1100) cancer-related mortalities and 180 (24-1800) cancer-related morbidities incorporating uncertainties associated with the exposure-dose and dose-response models used in the study. We also discuss the LNT model's uncertainty at low doses. Sensitivities to emission rates, gas to particulate I-131 partitioning, and the mandatory evacuation radius around the plant are also explored, and may increase upper bound mortalities and morbidities in the ranges above to 1300 and 2500, respectively. Radiation exposure to workers at the plant is projected to result in 2 to 12 morbidities. An additional $600 mortalities have been reported due to non-radiological causes such as mandatory evacuations. Lastly, a hypothetical accident at the Diablo Canyon Power Plant in California, USA with identical emissions to Fukushima was studied to analyze the influence of location and seasonality on the impact of a nuclear accident. This hypothetical accident may cause $25% more mortalities than Fukushima despite California having one fourth the local population density due to differing meteorological conditions.

Abstract. Land use, vegetation, albedo, and soil-type data are combined in a global model that accounts for roofs and roads at near their actual resolution to quantify the effects of urban surface and white roofs on climate. In 2005, ~0.128% of the Earth's surface contained urban landcover, half of which was vegetated. Urban landcover was modeled over 20 years to increase gross global warming (warming before cooling due to aerosols and albedo change are accounted for) by 0.06-0.11 K and population-weighted warming by 0.16-0.31 K, based on two simulations under different conditions. As such, the urban heat island (UHI) effect may contribute to 2-4% of gross global warming, although the uncertainty range is likely larger than the model range presented, and more verification is needed. This may be the first estimate of the UHI effect derived from a global model while considering both UHI local heating and large-scale feedbacks.Previous data estimates of the global UHI, which considered the effect of urban areas but did not treat feedbacks or isolate temperature change due to urban surfaces from other causes of urban temperature change, imply a smaller UHI effect but of similar order. White roofs change surface albedo and affect energy demand. A worldwide conversion to white roofs, accounting for their albedo effect only, was calculated to cool population-weighted temperatures by ~0.02 K but to warm the Earth overall by ~0.07 K. White-roof local cooling may also affect energy use, thus emissions, a factor not accounted for here. As such, conclusions here regarding white roofs apply only to the assumptions made. 3 1.IntroductionUrban areas are generally warmer than vegetated areas around them since urban surfaces reduce evapotranspiration and have sufficiently different heat capacities, thermal conductivities, albedos, and emissivities to enhance urban warming [Howard, 1833;Oke, 1982]. Several studies have estimated, from data analysis, that the globally-averaged urban heat island (UHI) effect may contribute ≤0.1 K to global temperature changes since the preindustrial era [Jones, 1990;Easterling, 1997;Hansen et al., 1999;Peterson, 2003;Parker, 2006]. The IPCC Fourth Assessment Report concluded that the UHI may have increased temperatures ~0.065 over land and ~0.022 K globally from 1900-2008 [IPCC, 2007. The IPCC global estimate was scaled from the land estimate assuming no UHI heating or feedbacks over the ocean. Data analysis studies of the UHI do not account for feedbacks of changes in local temperatures, moisture, and their gradients to large-scale weather systems, either due to traceable effects or to deterministic chaotic variation. Furthermore, such studies cannot distinguish temperature changes in urban areas due to the UHI from those due to greenhouse gases, carbon dioxide domes over cities [Jacobson, 2010a], cooling or warming aerosol particles, transmission or use of electricity, stationary or mobile combustion, or human respiration, which also occur in urban areas. As such, numerical modeling is needed to ...

Determining the major sources of particles that act as cloud condensation nuclei (CCN) represents a critical step in the development of a more fundamental understanding of aerosol impacts on cloud formation and climate. Reported herein are direct measurements of the CCN activity of newly formed ambient particles, measured at a remote rural site in the Sierra Nevada Mountains of Northern California. Nucleation events in the winter of 2009 occurred during two pristine periods following precipitation, with higher gas-phase SO(2) concentrations during the second period, when faster particle growth occurred (7-8 nm/h). Amines, as opposed to ammonia, and sulfate were detected in the particle phase throughout new particle formation (NPF) events, increasing in number as the particles grew to larger sizes. Interestingly, long-range transport of SO(2) from Asia appeared to potentially play a role in NPF during faster particle growth. Understanding the propensity of newly formed particles to act as CCN is critical for predicting the effects of NPF on orographic cloud formation during winter storms along the Sierra Nevada Mountain range. The potential impact of newly formed particles in remote regions needs to be compared with that of transported urban aerosols when evaluating the impact of aerosols on clouds and climate.

[1] Biomass burning (BB) aerosol particles affect clouds through competing microphysical and radiative (semi-direct and cloud absorption) effects, each of which dominates at different degrees of aerosol loading. Here, we analyze the influence of competing aerosol effects on mixed-phase clouds, precipitation, and radiative fields over the Amazon with a climate-air pollution-weather forecast model that treats aerosol-cloud-radiative interactions physically. Extensive comparisons with remotely sensed observations and in situ measurements are performed. Both observations and model results suggest an increase in cloud optical depth (COD) with increasing aerosol optical depth (AOD) at low AODs, and a decrease in COD with increasing AOD at higher AODs in accord with previous observational and modeling studies. The increase is attributed to a combination of microphysical and dynamical effects, whereas the decrease is attributed to a dominance of radiative effects that thin and darken clouds. An analogous relationship is shown for other modeled cloud variables as well. The similarity between the remotely sensed observations and model results suggests that these correlations are physically based and are not dominated by satellite retrieval artifacts. Cloud brightening due to BB is found to dominate in the early morning, whereas cloud inhibition is found to dominate in the afternoon and at night. BB decreased the net top of the atmosphere solar+IR irradiance modestly, but with large diurnal variation. We conclude that models that exclude treatment of aerosol radiative effects are likely to over-predict the microphysical effects of aerosols and underestimate the warming due to aerosols containing black and brown carbon.

Aerosol, cloud, water vapor, and temperature profile data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are utilized to examine the impact of aerosols on clouds during the Amazonian biomass burning season in Rondônia, Brazil. It is found that increasing background column water vapor (CWV) throughout this transition season between the Amazon dry and wet seasons likely exerts a strong effect on cloud properties. As a result, proper analysis of aerosol-cloud relationships requires that data be stratified by CWV to account better for the influence of background meteorological variation. Many previous studies of aerosol-cloud interactions over Amazonia have ignored the systematic changes to meteorological factors during the transition season, leading to possible misinterpretation of their results. Cloud fraction (CF) is shown to increase or remain constant with aerosol optical depth (AOD), depending on the value of CWV, whereas the relationship between cloud optical depth (COD) and AOD is quite different. COD increases with AOD until AOD ~ 0.3, which is assumed to be due to the first indirect (microphysical) effect. At higher values of AOD, COD is found to decrease with increasing AOD, which may be due to: (1) the inhibition of cloud development by absorbing aerosols (radiative effect/semi-direct effect) and/or (2) a possible retrieval artifact in which the measured reflectance in the visible is less than expected from a cloud top either from the darkening of clouds through the addition of carbonaceous biomass burning aerosols within or above clouds or subpixel dark surface contamination in the measured cloud reflectance. If (1) is a contributing mechanism, as we suspect, then an empirically-derived increasing function between cloud drop number and aerosol concentration, assumed in a majority of global climate models, is inaccurate since these models do not include treatment of aerosol absorption in and around clouds. The relationship between aerosols and both CWV and clouds over varying land surface types is also analyzed. The study finds that the difference in CWV between forested and deforested land is not correlated with aerosol loading, supporting the assumption that temporal variation of CWV is primarily a function of the larger-scale meteorology. However, a difference in the response of CF to increasing AOD is observed between forested and deforested land. This suggests that dissimilarities between other meteorological factors, such as atmospheric stability, may have an impact on aerosol-cloud correlations between different land cover types