Associations and lags between air pollution and acute respiratory visits in an ambulatory care setting: 25-month results from the aerosol research and inhalation epidemiological study

Particulate matter (PM) has been associated with adverse respiratory outcomes in numerous studies that utilized data from emergency room visits, hospital admissions, and mortality records. This study is unique in its investigation of associations of air pollution measures, including components of PM, with health outcomes in an ambulatory-care setting. Visit data were collected from Kaiser Permanente, a not-for-profit health maintenance organization in the metropolitan Atlanta, GA, area. Kaiser Permanente collaborated on the Aerosol Research Inhalation Epidemiological Study (ARIES), which provided detailed information on the characteristics of air pollutants. The Kaiser Permanente study was a time-series investigation of the possible associations between daily levels of suspended PM, inorganic gases, and polar volatile organic compounds and ambulatory care acute visit rates during the 25-month period from August 1, 1998, to August 31, 2000. For this interim analysis, the a priori 0-2 days lagged moving average, as well as the 3-5 days and 6-8 days lagged moving averages, of air quality measures were investigated. Single-pollutant Poisson general linear modeling was used to model daily visit counts for asthma and upper and lower respiratory infections (URI and LRI) by selected air quality metrics, controlling for temporal trends and meteorological variables. Most of the statistically significant positive associations were for the 3-5 days lagged air quality metrics with child asthma and LRI.     

Development of the crop residue and rangeland burning in the 2014 National Emissions Inventory using information from multiple sources

Biomass burning has been identified as an important contributor to the degradation of air quality because of its impact on ozone and particulate matter. One component of the biomass burning inventory, crop residue burning, has been poorly characterized in the National Emissions Inventory (NEI). In the 2011 NEI, wildland fires, prescribed fires, and crop residue burning collectively were the largest source of PM_2.5. This paper summarizes our 2014 NEI method to estimate crop residue burning emissions and grass/pasture burning emissions using remote sensing data and field information and literature-based, crop-specific emission factors. We focus on both the postharvest and pre-harvest burning that takes place with bluegrass, corn, cotton, rice, soybeans, sugarcane and wheat. Estimates for 2014 indicate that over the continental United States (CONUS), crop residue burning excluding all areas identified as Pasture/Grass, Grassland Herbaceous, and Pasture/Hay occurred over approximately 1.5 million acres of land and produced 19,600 short tons of PM_2.5. For areas identified as Pasture/Grass, Grassland Herbaceous, and Pasture/Hay, biomass burning emissions occurred over approximately 1.6 million acres of land and produced 30,000 short tons of PM_2.5. This estimate compares with the 2011 NEI and 2008 NEI as follows: 2008: 49,650 short tons and 2011: 141,180 short tons. Note that in the previous two NEIs rangeland burning was not well defined and so the comparison is not exact. The remote sensing data also provided verification of our existing diurnal profile for crop residue burning emissions used in chemical transport modeling. In addition, the entire database used to estimate this sector of emissions is available on EPA’s Clearinghouse for Inventories and Emission Factors (CHIEF, http://www3.epa.gov/ttn/chief/index.html).Implications: Estimates of crop residue burning and rangeland burning emissions can be improved by using satellite detections. Local information is helpful in distinguishing crop residue and rangeland burning from all other types of fires.     

Childhood asthma acute primary care visits,traffic, and traffic-related pollutants

Previous studies have found associations between traffic-related air pollution and asthma exacerbation in children, where exacerbations were measured according to emergency department visits and hospital admissions. Fewer studies have been undertaken that look at asthma exacerbations in a less severe primary care setting. Therefore, the authors sought to examine the associations between childhood asthma exacerbations, measured as acute visits to a primary care setting, and vehicular-traffic measures in a population of children aged 18 and under in the metropolitan Atlanta area. Statistical tests for differences of mean monthly visits for members with traffic measures above the median compared with below the median and for the upper quartile compared with the lower quartile were conducted. We also compared the odds of having one or more visits in a month for those who lived closer to a major roadway were compared with those who lived farther (greater than 300 m) from a major roadway. Poisson general linear modeling was used to determine associations between daily levels of acute visits for childhood asthma and traffic-related pollutants (zinc, EC [elemental carbon], and PM₁₀ and PM_2.5 [particulate matter with an aerodynamic diameter of ≤10 and ≤2.5 μm, respectively]) for different levels of traffic and distance measures. This analysis found that both larger traffic volumes and smaller distances to the nearest major roadway were positively and significantly associated with larger numbers of childhood asthma visits, when compared with less traffic and larger distances. Our findings point to motor vehicle traffic as an important contributor to childhood asthma exacerbations.

Implications: Previous studies have found associations between traffic-related air pollution and asthma exacerbation in children. However, these studies were mainly conducted in emergency department or hospital admission settings; little is known regarding less acute health effects. This analysis of the association between vehicular traffic measures and childhood asthma in a primary care setting suggests that motor vehicle traffic is a contributor to less acute asthma episodes in children. The present analysis of traffic-related air pollutants and childhood asthma were less conclusive, likely due to methods limitations outlined in the paper. The implication is that further evidence of adverse respiratory health effects in children due to motor vehicle traffic can be found in a primary care setting and similar studies should be considered.     

A semi-automated tool for identifying agricultural roadway crashes in crash narratives

Objective: Crash reports contain precoded structured data fields and a crash narrative that can be a source of rich information not included in the structured data. The narrative can be useful for identifying vulnerable roadway users, such as agricultural workers. However, using the narratives often requires manual reviews that are time consuming and costly. The objective of this research was to develop a simple and relatively inexpensive, semi-automated tool for screening crash narratives and expediting the process of identifying crashes with specific characteristics, such as agricultural crashes.

Methods: Crash records for Louisiana from 2010 to 2015 were obtained from the Louisiana Department of Transportation (LaDOTD). Records with narratives were extracted and stratified by vehicle type. The majority of analyses focused on a vehicle type of farm equipment (Type T). Two keyword lists, an inclusion list and an exclusion list, were created based on the published literature, subject-matter experts, and findings from a pilot project. Next, a semi-automated tool was developed in Microsoft Excel to identify agricultural crashes. Lastly, the tool’s performance was assessed using a gold standard set of agricultural narratives identified through manual review.

Results: The tool reduced the search space (e.g., number of narratives that need manual review) for narratives requiring manual review from 6.7 to 59.4% depending on the research question. Sensitivity was high, with 96.1% of agricultural crash narratives being correctly classified. Of the gold standard agricultural narratives, 58.3% included an equipment keyword and 72.8% included a farm equipment brand.

Conclusion: This article provides information on how crash narratives can supplement structured crash data. It also provides an easy-to-implement method to facilitate incorporating narratives into safety research along with keyword lists for identifying agricultural crashes.     

Surrogate Measures for Providing High Frequency Estimates of Total Suspended Solids and Total Phosphorus Concentrations1

Spackman Jones, Amber, David K. Stevens, Jeffery S. Horsburgh, and Nancy O. Mesner, 2010. Surrogate Measures for Providing High Frequency Estimates of Total Suspended Solids and Total Phosphorus Concentrations. Journal of the American Water Resources Association (JAWRA) 1‐15. DOI: 10.1111/j.1752‐1688.2010.00505.x Abstract: Surrogate measures like turbidity, which can be observed with high frequency in situ, have potential for generating high frequency estimates of total suspended solids (TSS) and total phosphorus (TP) concentrations. In the semiarid, snowmelt‐driven, and irrigation‐regulated Little Bear River watershed of northern Utah, high frequency in situ water quality measurements were recorded in conjunction with periodic chemistry sampling. Site‐specific relationships were developed using turbidity as a surrogate for TP and TSS at two monitoring locations. Methods are presented for employing censored data and for investigating categorical explanatory variables (e.g., hydrologic conditions). Turbidity was a significant explanatory variable for TP and TSS at both sites, which differ in hydrologic and water quality characteristics. The relationship between turbidity and TP was stronger at the upper watershed site where TP is predominantly particulate. At both sites, the relationships between turbidity and TP varied between spring snowmelt and base flow conditions while the relationships between TSS and turbidity were consistent across hydrological conditions. This approach enables the calculation of high frequency time series of TP and TSS concentrations previously unavailable using traditional monitoring approaches. These methods have broad application for situations that require accurate characterization of fluxes of these constituents over a range of hydrologic conditions.