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.     

Formation of aerobic granules in the presence of a synthetic chelating agent

This paper examines the development of aerobic granular sludge in the presence of a synthetic chelating agent, nitrilotriacetic acid (NTA), in sequencing batch reactors (SBR). The growth of seed sludge at 0.26 mM, 0.52 mM and 1.05 mM of NTA was found to be significantly lower as compared to that in the absence of NTA. Aerobic granulation was significantly enhanced in the three SBRs (R2, R3 and R4), which were fed with 0.26 mM, 0.52 mM and 1.05 mM of NTA as a co-substrate, in comparison to the acetate-alone fed SBR (R1). After 2 months of operation, the mean diameter of the biomass stabilized at 0.35 mm in R1 (acetate alone), as compared to 2.18 mm in R4 (1.05 mM NTA+acetate). NTA degradation was established in SBRs, with almost complete removal during the SBR cycle. Batch experiments also showed efficient degradation of NTA by the aerobic granules.     

Development and Testing of a Physically Based Model of Streambank Erosion for Coupling with a Basin‐Scale Hydrologic Model SWAT

A comprehensive streambank erosion model based on excess shear stress has been developed and incorporated in the hydrological model Soil and Water Assessment Tool (SWAT). It takes into account processes such as weathering, vegetative cover, and channel meanders to adjust critical and effective stresses while estimating bank erosion. The streambank erosion model was tested for performance in the Cedar Creek watershed in north‐central Texas where streambank erosion rates are high. A Rapid Geomorphic field assessment (RAP‐M) of the Cedar Creek watershed was done adopting techniques developed by the Natural Resources Conservation Service (NRCS), and the stream segments were categorized into various severity classes. Based on the RAP‐M field assessment, erosion pin sites were established at seven locations within the severely eroding streambanks of the watershed. A Monte Carlo simulation was carried out to assess the sensitivity of different parameters that control streambank erosion such as critical shear stress, erodibility, weathering depth, and weathering duration. The sensitive parameters were adjusted and the model was calibrated based on the bank erosion severity category identified by the RAP‐M field assessment. The average observed erosion rates were in the range 25‐367 mm year^?1. The SWAT model was able to reasonably predict the bank erosion rates within the range of variability observed in the field (R² = 0.90; E = 0.78). Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho1

Stratton, Benjamin T., Venakataramana Sridhar, Molly M. Gribb, James P. McNamara, and Balaji Narasimhan, 2009. Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho. Journal of the American Water Resources Association (JAWRA) 45(6):1390‐1408. Abstract: The distributed Soil Water Assessment Tool (SWAT) hydrologic model was applied to a research watershed, the Dry Creek Experimental Watershed, near Boise Idaho to investigate its water balance components both temporally and spatially. Calibrating and validating SWAT is necessary to enable our understanding of the water balance components in this semiarid watershed. Daily streamflow data from four streamflow gages were used for calibration and validation of the model. Monthly estimates of streamflow during the calibration phase by SWAT produced satisfactory results with a Nash Sutcliffe coefficient of model efficiency 0.79. Since it is a continuous simulation model, as opposed to an event‐based model, it demonstrated the limited ability in capturing both streamflow and soil moisture for selected rain‐on‐snow (ROS) events during the validation period between 2005 and 2007. Especially, soil moisture was generally underestimated compared with observations from two monitoring pits. However, our implementation of SWAT showed that seasonal and annual water balance partitioning of precipitation into evapotranspiration, streamflow, soil moisture, and drainage was not only possible but closely followed the trends of a typical semiarid watershed in the intermountain west. This study highlights the necessity for better techniques to precisely identify and drive the model with commonly observed climatic inversion‐related snowmelt or ROS weather events. Estimation of key parameters pertaining to soil (e.g., available water content and saturated hydraulic conductivity), snow (e.g., lapse rates, melting), and vegetation (e.g., leaf area index and maximum canopy index) using additional field observations in the watershed is critical for better prediction.     

Carbohydrate metabolism in the leg muscles of the fresh-water field crab Paratelphusa hydrodromous adapted to high salinities

Utilization of marine plants and their constituents by bacteria isolated from the guts of echinoids was investigated to determine the potential role bacteria may have in carbohydrate digestion in echinoids. Bacteria from the guts of the regular echinoids Lytechinus variegatus (Lamarck) and Arbacia punctulata (Lamarck) could physically degrade the marine plants Ulva lactuca and Eucheuma nudum, but not Caulerpa prolifera. Diplanthera wrightii and Thalassia testudinum were only slightly degraded by the gut bacteria. Bacteria from the guts of the irregular echinoids Mellita quinquiesperforata (Leske) and Encope aberrans (Martens) could not physically degrade any of these marine plants. Mixed and some isolated bacteria from the gut of L. variegatus could utilize xylose, rhamnose, glucose, galactose, laminarin, carageenan, starch and agar, but not cellulose or chitin. The results with isolates suggest that the bacteria of the echinoid gut are fairly non-selective. The bacteria of the guts of the two regular echinoids could utilize certain marine plants that the echinoids eat and certain of the plant constituents. The bacteria could not utilize plant fibers.     

Integrating models to predict regional haze from wildland fire

Visibility impairment from regional haze is a significant problem throughout the continental United States. A substantial portion of regional haze is produced by smoke from prescribed and wildland fires. Here we describe the integration of four simulation models, an array of GIS raster layers, and a set of algorithms for fire-danger calculations into a modeling framework for simulating regional-scale smoke dispersion. We focus on a representative fire season (2003) in the northwestern USA, on a 12 km domain, and track the simulated dispersion and concentration of PM_2.5 over the course of the season. Simulated visibility reductions over national parks and wilderness areas are within the ranges of measured values at selected monitoring sites, although the magnitudes of peak events are underestimated because these include inputs other than fire. By linking the spatial and temporal patterns of haze-producing emissions to climatic variability, particularly synoptic weather patterns, and the stochastic nature of fire occurrence across the region, we can provide a robust method for estimating the quantity and distribution of fire-caused regional haze under climate-warming scenarios.     

Synthesis of manganese zinc ferrite using ferrous pickle liquor and pyrolusite ore

The possibility of utilizing hydrochloric acid-based waste pickle liquor (WPL) and medium-grade pyrolusite ore to synthesize manganese zinc ferrite was explored. The excess acidity of the WPL was neutralized using mild steel turnings. The unreacted mild steel scrap and suspended solids were removed by filtration. Partial precipitation technique was employed to reduce the impurities. The purified WPL was treated with medium-grade pyrolusite ore to prepare the leach liquor to which the required quantities of ferrous chloride and zinc granules were added to maintain stoichiometry in the resultant compound. The hydroxy carbonate of manganese, zinc and iron was precipitated by the addition of a hot solution (70°C) of sodium carbonate (20% v/v), which upon sintering in argon atmosphere yielded manganese zinc ferrite. The addition of sodium lauryl sulfate (SLS) helped in preventing agglomeration of the particles. Sintering at 450°C for 30 min in argon atmosphere has resulted in mixed phases of (Zn,Mn,Fe) (Fe,Mn)₂O₄ and Mn₃O₄, which indicates lack of phase purity. Sintering at temperatures higher than 950°C for 5 h in argon atmosphere enabled complete ferritization. The extent of ferritization was found to be a function of sintering time at 950°C. The manganese zinc ferrites synthesized using WPL and medium-grade pyrolusite ore exhibited soft magnetic characteristics.     

Estimating wildfire growth from noisy and incomplete incident data using a state space model

Wildfire behaviors are complex and are of interest to fire managers and scientists for a variety of reasons. Many of these important behaviors are directly measured from the cumulative burn area time series of individual wildfires; however, estimating cumulative burn area time series is challenging due to the magnitude of measurement errors and missing entries. To resolve this, we introduce two state space models for reconstructing wildfire burn area using repeated observations from multiple data sources that include different levels of measurement error and temporal gaps. The constant growth parameter model uses a few parameters and assumes a burn area time series that follows a logistic growth curve. The non-constant growth parameter model uses a time-varying logistic growth curve to produce detailed estimates of the burn area time series that permit sudden pauses and pulses of growth. We apply both reconstruction models to burn area data from 13 large wildfire incidents to compare the quality of the burn area time series reconstructions and computational requirements. The constant growth parameter model reconstructs burn area time series with minimal computational requirements, but inadequately fits observed data in most cases. The non-constant growth parameter model better describes burn area time series, but can also be highly computationally demanding. Sensitivity analyses suggest that in a typical application, the reconstructed cumulative burn area time series is fairly robust to minor changes in the prior distributions.     

Effective uptake of decontaminating agent (citric acid) from aqueous solution by mesoporous and microporous materials: an adsorption process

The presence of citric acid in decontamination waste can cause complexation of the radioactive cations resulting in interferences in their removal by various treatment processes such as chemical precipitation, ion-exchange, etc., which are employed for the removal of radioactivity and may cause potential danger to the environment. Mesoporous Al-MCM-41 (Si/Al=30, 51, 72 and 97) and Si-MCM-41 molecular sieves were synthesized hydrothermally and characterized by XRD, BET (surface area) and FT-IR to evaluate the removal of citric acid through an adsorption process. Adsorption of citric acid over Al-MCM-41 shows the applicability of Freundlich and Langmuir isotherm and follows first order kinetics. The effects of contact time, concentration of citric acid, adsorbents (various Si/Al ratios of Al-MCM-41, Si-MCM-41, Hbeta zeolite and commercial carbon) and pH have been investigated. It has been found that the amount of citric acid adsorbed per unit gram of catalyst followed the order Al-MCM-41 (Si/Al=30)>Al-MCM-41 (Si/Al=51)>activated charcoal>Al-MCM-41 (Si/Al=72)>Al-MCM-41 (Si/Al=97)>Si-MCM-41>Hbeta zeolite.