BackgroundThe frequency and intensity of wildfires is anticipated to increase as climate change creates longer, warmer, and drier seasons. Particulate matter (PM) from wildfire smoke has been linked to adverse respiratory and possibly cardiovascular outcomes. Children, older adults, and persons with underlying respiratory and cardiovascular conditions are thought to be particularly vulnerable. This study examines the healthcare utilization of Medi-Cal recipients during the fall 2007 San Diego wildfires, which exposed millions of persons to wildfire smoke.Methods and findingsRespiratory and cardiovascular International Classification of Diseases (ICD)-9 codes were identified from Medi-Cal fee-for-service claims for emergency department presentations, inpatient hospitalizations, and outpatient visits. For a respiratory index and a cardiovascular index of key diagnoses and individual diagnoses, we calculated rate ratios (RRs) for the study population and different age groups for 3 consecutive 5-day exposure periods (P1 [October 22–26], P2 [October 27–31], and P3 [November 1–5]) versus pre-fire comparison periods matched on day of week (5-day periods starting 3, 4, 5, 6, 8, and 9 weeks before each exposed period). We used a bidirectional symmetric case-crossover design to examine emergency department presentations with any respiratory diagnosis and asthma specifically, with exposure based on modeled wildfire-derived fine inhalable particles that are 2.5 micrometers and smaller (PM2.5). We used conditional logistic regression to estimate odds ratios (ORs), adjusting for temperature and relative humidity, to assess same-day and moving averages. We also evaluated the United States Environmental Protection Agency (EPA)’s Air Quality Index (AQI) with this conditional logistic regression method. We identified 21,353 inpatient hospitalizations, 25,922 emergency department presentations, and 297,698 outpatient visits between August 16 and December 15, 2007. During P1, total emergency department presentations were no different than the reference periods (1,071 versus 1,062.2; RR 1.01; 95% confidence interval [CI] 0.95–1.08), those for respiratory diagnoses increased by 34% (288 versus 215.3; RR 1.34; 95% CI 1.18–1.52), and those for asthma increased by 112% (58 versus 27.3; RR 2.12; 95% CI 1.57–2.86). Some visit types continued to be elevated in later time frames, e.g., a 72% increase in outpatient visits for acute bronchitis in P2. Among children aged 0–4, emergency department presentations for respiratory diagnoses increased by 70% in P1, and very young children (0–1) experienced a 243% increase for asthma diagnoses. Associated with a 10 μg/m3 increase in PM2.5 (72-hour moving average), we found 1.08 (95% CI 1.04–1.13) times greater odds of an emergency department presentation for asthma. The AQI level “unhealthy for sensitive groups” was associated with significantly elevated odds of an emergency department presentation for respiratory conditions the day following exposure, compared to the AQI level “good” (OR 1.73; 95% CI...

Climate warming is projected to result in increases in total annual precipitation in northeastern North America. The response of runoff to increases in precipitation is likely to be more complex because increasing evapotranspiration (ET) could counteract increasing precipitation. This study was conducted to examine these competing trends in the historical record for 22 rivers having >70 yr of runoff data. Annual (water year) average precipitation increased in all basins, with increases ranging from 0.9 to 3.12 mm yr−1. Runoff increased in all basins with increases ranging from 0.67 to 2.58 mm yr−1. The ET was calculated by using a water balance approach in which changes in terrestrial water storage were considered negligible. ET increased in 16 basins and decreased in 6 basins. Temporal trends in temperature, precipitation, runoff, and ET were also calculated for each basin over their respective periods of record for runoff and for the consistent period (1927–2011) for the area-weighted average of the nine largest non-nested basins. From 1927 through 2011, precipitation and runoff increased at average rates of 1.6 and 1.7 mm yr−1, respectively, and ET increased slightly at a rate of 0.18 mm yr−1. For the more recent period (1970–2011), there was a positive trend in ET of 1.9 mm yr−1. The lack of a more consistent increase in ET, compared with the increases in precipitation and runoff, for the full periods of record, was unexpected, but may be explained by various factors including decreasing wind speed, increasing cloudiness, decreasing vapor pressure deficit, and patterns of forest growth.

BackgroundA study of the impacts on respiratory health of the 2007 wildland fires in and around San Diego County, California is presented. This study helps to address the impact of fire emissions on human health by modeling the exposure potential of proximate populations to atmospheric particulate matter (PM) from vegetation fires. Currently, there is no standard methodology to model and forecast the potential respiratory health effects of PM plumes from wildland fires, and in part this is due to a lack of methodology for rigorously relating the two. The contribution in this research specifically targets that absence by modeling explicitly the emission, transmission, and distribution of PM following a wildland fire in both space and time.MethodsCoupled empirical and deterministic models describing particulate matter (PM) emissions and atmospheric dispersion were linked to spatially explicit syndromic surveillance health data records collected through the San Diego Aberration Detection and Incident Characterization (SDADIC) system using a Generalized Additive Modeling (GAM) statistical approach. Two levels of geographic aggregation were modeled, a county-wide regional level and division of the county into six sub regions. Selected health syndromes within SDADIC from 16 emergency departments within San Diego County relevant for respiratory health were identified for inclusion in the model.ResultsThe model captured the variability in emergency department visits due to several factors by including nine ancillary variables in addition to wildfire PM concentration. The model coefficients and nonlinear function plots indicate that at peak fire PM concentrations the odds of a person seeking emergency care is increased by approximately 50% compared to non-fire conditions (40% for the regional case, 70% for a geographically specific case). The sub-regional analyses show that demographic variables also influence respiratory health outcomes from smoke.ConclusionsThe model developed in this study allows a quantitative assessment and prediction of respiratory health outcomes as it relates to the location and timing of wildland fire emissions relevant for application to future wildfire scenarios. An important aspect of the resulting model is its generality thus allowing its ready use for geospatial assessments of respiratory health impacts under possible future wildfire conditions in the San Diego region. The coupled statistical and process-based modeling demonstrates an end-to-end methodology for generating reasonable estimates of wildland fire PM concentrations and health effects at resolutions compatible with syndromic surveillance data.

Globally peatlands store large amounts of carbon belowground with 80% distributed in boreal regions of the northern hemisphere. Climate warming and drying of the boreal region has been documented as affecting fire regimes, with increased fire frequency, severity and extent. While much research is dedicated to assessing changes in boreal uplands, few research efforts are focused on the vulnerability of boreal peatlands to wildfire. In this case study, an integration of field data collection, land cover mapping of peatland types and Landsat-based fire severity mapping was conducted for four early season (May to mid-June) wildfires where peatlands are abundant in northeastern Alberta Canada. The goal was to better understand if peatlands burn more or less preferentially than uplands in fires and how severely the organic soil layers (peat) of different peatland ecotypes burn. The focus was on early season wildfires because they dominated the research area in the decade of study. To do this, a novel Landsat-5 metric was developed to retrieve fire severity of the organic surface layer. Spatial comparisons and statistical analysis showed that proportionally bogs are more likely to burn in early season Alberta wildfires than other ecosystem types, even fire-prone upland conifer. Although for a small sample, we found that when fire weather conditions for the duff layers are severe, the fens of this study appear to become more susceptible to burning. In addition, overall bogs experienced greater severity of burn to the peat layers than fens. Due to the small sample size of peat loss from fire in uplands and limited geographic area of this case study, we were unable to assess if bogs are burning more severely than uplands. Further analysis and Landsat algorithm development for organic soil fire severity in peatlands and uplands are needed to more fully understand trends in belowground consumption for wildfires of all seasons and boreal ecotypes.