Fire smoke is a major contributor to both particulate matter (PM) and ozone exposure in urban centers. Epidemiological, clinical, and toxicological studies have demonstrated a casual relationship between these pollutants and cardiovascular and respiratory related deaths and illnesses. Given the expected increase in fire events due to climate and landscape changes, quantifying health effects of wildfire smoke and developing real-time tools to help air quality managers mitigate the effects of exposure are sorely needed. We propose to comprehensively assess the health risks posed by smoke exposure, and construct new tools to estimate and forecast smoke concentration levels and associated health effects. We will accomplish these goals with four specific aims. In Aim 1, we compare the chemical composition of fine PM emanating from fire smoke with typical urban PM in the US. This information fills an important gap in the literature, and may enable us to distinguish between smoke and non-smoke related exposures in air quality indices and health risks in epidemiological studies. In Aim 2, we will conduct a systematic review and meta analysis of epidemiological risk estimates to evaluate the risks of smoke exposure for all relevant health outcomes. Using meta-regression techniques, we will seek to identify populations that are particularly vulnerable or fire types (e.g., wild versus prescribed) that are particularly harmful. Using the identified risk estimates of the health effects of smoke exposure, in Aim 3 we will utilize the BenMAP-CE air pollution tool to characterize the health and economic value of the burden of fire smoke, such as the number of asthma exacerbations or hospital admissions and the associated economic cost. To illustrate this approach, we will conduct several case studies, including the 2008 and 2011 peat fires in rural North Carolina and the 2013 fire in Sydney, Australia. Finally, in Aim 4 we propose to combine model-based predicted smoke exposure with health and economic assessment tools to provide real-time forecasts of health risk over space and time. This new tool will give officials more specific and easily interpretable information about the magnitude of health risk from fires at various air quality thresholds, allowing them to issue targeted hourly advisories. This novel method will also be demonstrated using the North Carolina and Sydney cases studies, which will examine performance in both a rural area with few monitors (North Carolina) and in a densely-populated urban area with extensive monitors (Sydney). To accomplish these tasks, we have assembled a diverse team from US and Australian research institutions and government with extensive experience in air quality modeling, biostatistics, economics, and epidemiology.