Laboratory and field evaluation of real-time and near real-time PM2.5 smoke monitors.

Increases in large wildfire frequency and intensity and a longer fire season in the western United States are resulting in a significant increase in air pollution, including concentrations of PM2.5 (particulate matter <2.5 µm in aerodynamic diameter) that pose significant health risks to nearby communities. During wildfires, government agencies monitor PM2.5 mass concentrations providing information and actions needed to protect affected communities; this requires continuously measuring instruments. This study assessed the performance of seven candidate instruments: (1) Met One Environmental beta attenuation monitor (EBAM), (2) Met One ES model 642 (ES642), (3) Grimm Environmental Dust Monitor 164 (EDM), (4) Thermo ADR 1500 (ADR), (5) TSI DRX model 8543 (DRX), (6) Dylos 1700 (Dylos), and (7) Purple Air II (PA-II) in comparison with a BAM 1020 (BAM) reference instrument. With the exception of the EBAM, all candidates use light scattering to determine PM2.5 mass concentrations. Our comparison study included environmental chamber and field components, with two of each candidate instrument operating next to the reference instrument. The chamber component involved 6 days of comparisons for biomass combustion emissions. The field component involved operating all instruments in an air monitoring station for 39.5 days with hourly average relative humidity (RH) ranging from 19% to 98%. Goals were to assess instrument precision and accuracy and effects of RH, elemental carbon (EC), and organic carbon (OC) concentrations. All replicate candidate instruments showed high hourly correlations (R2 ≥ 0.80) and higher daily average correlations (R2 ≥ 0.90), where all instruments correlated well (R2 ≥ 0.80) with the reference. The DRX and Purple Air overestimated PM2.5 mass concentrations by a factor of ~two. Differences between candidates and reference were more pronounced at higher PM2.5 concentrations. All optical instruments were affected by high RH and by the EC/OC ratio. Equations to convert candidate instruments data to FEM BAM type data are provided to enhance the usability of data from candidate instruments.Implications: This study tested the performance of seven candidate PM2.5 mass concentration measuring instruments in two settings - environmental chamber and field. The instruments were tested to determine their suitability for use during biomass combustion events and the effects of RH, PM mass concentrations, and concentrations of EC and OC on their performance. The accuracy and precision of each monitor and effect of RH, PM concentration, EC and OC concentrations are varied. The data show that most of these candidate instruments are suitable for measuring PM2.5 concentration during biomass combustions with a proper correction factor for each instrument type.

A statistical model for determining impact of wildland fires on Particulate Matter (PM2.5) in Central California aided by satellite imagery of smoke.

As the climate in California warms and wildfires become larger and more severe, satellite-based observational tools are frequently used for studying impact of those fires on air quality. However little objective work has been done to quantify the skill these satellite observations of smoke plumes have in predicting impacts to PM2.5 concentrations at ground level monitors, especially those monitors used to determine attainment values for air quality under the Clean Air Act. Using PM2.5 monitoring data from a suite of monitors throughout the Central California area, we found a significant, but weak relationship between satellite-observed smoke plumes and PM2.5 concentrations measured at the surface. However, when combined with an autoregressive statistical model that uses weather and seasonal factors to identify thresholds for flagging unusual events at these sites, we found that the presence of smoke plumes could reliably identify periods of wildfire influence with 95% accuracy.

Estimating contribution of wildland fires to ambient ozone levels in National Parks in the Sierra Nevada, California.

Data from four continuous ozone and weather monitoring sites operated by the National Park Service in Sierra Nevada, California, are used to develop an ozone forecasting model and to estimate the contribution of wildland fires on ambient ozone levels. The analyses of weather and ozone data pointed to the transport of ozone precursors from the Central Valley as an important source of pollution in these National Parks. Comparisons of forecasted and observed values demonstrated that accurate forecasts of next-day hourly ozone levels may be achieved by using a time series model with historic averages, expected local weather and modeled PM values as explanatory variables. Results on fire smoke influence indicated occurrence of significant increases in average ozone levels with increasing fire activity. The overall effect on diurnal ozone values, however, was small when compared with the amount of variability attributed to sources other than fire.

Real-world particulate matter and gaseous emissions from motor vehicles in a highway tunnel.

Recent studies have linked atmospheric particulate matter with human health problems. In many urban areas, mobile sources are a major source of particulate matter (PM) and the dominant source of fine particles or PM2.5 (PM smaller than 2.5 pm in aerodynamic diameter). Dynamometer studies have implicated diesel engines as being a significant source of ultrafine particles (< 0.1 microm), which may also exhibit deleterious health impacts. In addition to direct tailpipe emissions, mobile sources contribute to ambient particulate levels by brake and tire wear and by resuspension of particles from pavement. Information about particle emission rates, size distributions, and chemical composition from in-use light-duty (LD) and heavy-duty (HD) vehicles is scarce, especially under real-world operating conditions. To characterize particulate emissions from a limited set of in-use vehicles, we studied on-road emissions from vehicles operating under hot-stabilized conditions, at relatively constant speed, in the Tuscarora Mountain Tunnel along the Pennsylvania Turnpike from May 18 through 23, 1999. There were five specific aims of the study. (1) obtain chemically speciated diesel profiles for the source apportionment of diesel versus other ambient constituents in the air and to determine the chemical species present in real-world diesel emissions; (2) measure particle number and size distribution of chemically speciated particles in the atmosphere; (3) identify, by reference to data in years past, how much change has occurred in diesel exhaust particulate mass; (4) measure particulate emissions from LD gasoline vehicles to determine their contribution to the observed particle levels compared to diesels; and (5) determine changes over time in gas phase emissions by comparing our results with those of previous studies. Comparing the results of this study with our 1992 results, we found that emissions of C8 to C20 hydrocarbons, carbon monoxide (CO), and carbon dioxide (CO2) from HD diesel emissions substantially decreased over the seven-year period. Particulate mass emissions showed a similar trend. Considering a 25-year period, we observed a continued downward trend in HD particulate emissions from approximately 1,100 mg/km in 1974 to 132 mg/km (reported as PM2.5) in this study. The LD particle emission factor was considerably less than the HD value, but given the large fraction of LD vehicles, emissions from this source cannot be ignored. Results of the current study also indicate that both HD and LD vehicles emit ultrafine particles and that these particles are preserved under real-world dilution conditions. Particle number distributions were dominated by ultrafine particles with count mean diameters of 17 to 13 nm depending on fleet composition. These particles appear to be primarily composed of sulfur, indicative of sulfuric acid emission and nucleation. Comparing the 1992 and 1999 HD emission rates, we observed a 48% increase in the NOx/CO2 emissions ratio. This finding supports the assumption that many new-technology diesel engines conserve fuel but increase NOx emissions.