A statistical model for predicting PM2.5 for the western United States

ABSTRACT

A new statistical model for predicting daily ground level fine scale particulate matter (PM_2.5) concentrations at monitoring sites in the western United States was developed and tested operationally during the 2016 and 2017 wildfire seasons. The model is site-specific, using a multiple linear regression schema that relies on the previous day’s PM_2.5 value, along with fire and smoke related variables from satellite observations. Fire variables include fire radiative power (FRP) and the National Fire Danger Rating System Energy Release Component index. Smoke variables, in addition to ground monitored PM_2.5, include aerosol optical depth (AOD) and smoke plume perimeters from the National Oceanic and Atmospheric Administration’s Hazard Mapping System. The overall statistical model was inspired by a similar system developed for British Columbia (BC) by the BC Center for Disease Control, but it has been heavily modified and adapted to work in the United States. On average, our statistical model was able to explain 78% of the variance in daily ground level PM_2.5. A novel method for implementation of this model as an operational forecast system was also developed and was tested and used during the 2016 and 2017 wildfire seasons. This method focused on producing a continuously-updating prediction that incorporated the latest information available throughout the day, including both updated remote sensing data and real-time PM_2.5 observations. The diurnal pattern of performance of this model shows that even a few hours of data early in the morning can substantially improve model performance.

Implications: Wildfire smoke events produce significant air quality impacts across the western United States each year impacting millions. We present and evaluate a statistical model for making updating predictions of fine particulate (PM_2.5) levels during smoke events. These predictions run hourly and are being used by smoke incident specialists assigned to wildfire operations, and may be of interest to public health officials, air quality regulators, and the public. Predictions based on this model will be available on the web for the 2019 western U.S. wildfire season this summer.     

The environmental fate of the primary degradation products of alkylphenol ethoxylate surfactants in recycled paper sludge.

Alkylphenol ethoxylates (APEOs) are a group of non-ionic surfactants that are degraded microbially into more lipophilic degradation products with estrogenic potential, including nonylphenol monoethoxylate (NP1EO), nonylphenol diethoxylate (NP2EO), octylphenol (4-tOP) and nonylphenol (4-NP). Nonylphenol ethoxylates are used in paper recycling plants for de-inking paper and have the potential to be released into the environment through spreading of wastewater treatment sludge for soil amendment. Three samples of recycled paper sludge were collected from farmers' fields and analyzed for concentrations of NP1EO, NP2EO, 4-NP and 4-tOP. Each sample differed in the amount of time elapsed since the sludge was placed on farmers' fields. Primary degradation products of APEOs were present at low micrograms/g concentrations in the sludge samples. Differences in the concentrations of these analytes in sludge samples indicated that APEO concentrations declined by 84% over a period of 14 weeks on farmers' fields. Changes in the chromatographic patterns of acetylated 4-NP indicated that there is a group of recalcitrant nonylphenol isomers that degrades more slowly than other isomers. These data indicate that microbial degradation may reduce the risk of environmental contamination by these compounds, but more work is required to assess the toxic potential of APEOs in sludges used for soil amendment.     

Correlation analysis as a tool to investigate the bioaccessibility of nickel, vanadium and zinc in Northern Ireland soils

Correlation analyses were conducted on nickel (Ni), vanadium (V) and zinc (Zn) oral bioaccessible fractions (BAFs) and selected geochemistry parameters to identify specific controls exerted over trace element bioaccessibility. BAFs were determined by previous research using the unified BARGE method. Total trace element concentrations and soil geochemical parameters were analysed as part of the Geological Survey of Northern Ireland Tellus Project. Correlation analysis included Ni, V and Zn BAFs against their total concentrations, pH, estimated soil organic carbon (SOC) and a further eight element oxides. BAF data were divided into three separate generic bedrock classifications of basalt, lithic arenite and mudstone prior to analysis, resulting in an increase in average correlation coefficients between BAFs and geochemical parameters. Sulphur trioxide and SOC, spatially correlated with upland peat soils, exhibited significant positive correlations with all BAFs in gastric and gastro-intestinal digestion phases, with such effects being strongest in the lithic arenite bedrock group. Significant negative relationships with bioaccessible Ni, V and Zn and their associated total concentrations were observed for the basalt group. Major element oxides were associated with reduced oral trace element bioaccessibility, with Al₂O₃ resulting in the highest number of significant negative correlations followed by Fe₂O₃. spatial mapping showed that metal oxides were present at reduced levels in peat soils. The findings illustrate how specific geology and soil geochemistry exert controls over trace element bioaccessibility, with soil chemical factors having a stronger influence on BAF results than relative geogenic abundance. In general, higher Ni, V and Zn bioaccessibility is expected in peat soil types.