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.     

Engaging stakeholders in research to address water–energy–food (WEF) nexus challenges

The water–energy–food (WEF) nexus has become a popular, and potentially powerful, frame through which to analyse interactions and interdependencies between these three systems. Though the case for transdisciplinary research in this space has been made, the extent of stakeholder engagement in research remains limited with stakeholders most commonly incorporated in research as end-users. Yet, stakeholders interact with nexus issues in a variety of ways, consequently there is much that collaboration might offer to develop nexus research and enhance its application. This paper outlines four aspects of nexus research and considers the value and potential challenges for transdisciplinary research in each. We focus on assessing and visualising nexus systems; understanding governance and capacity building; the importance of scale; and the implications of future change. The paper then proceeds to describe a novel mixed-method study that deeply integrates stakeholder knowledge with insights from multiple disciplines. We argue that mixed-method research designs—in this case orientated around a number of cases studies—are best suited to understanding and addressing real-world nexus challenges, with their inevitable complex, non-linear system characteristics. Moreover, integrating multiple forms of knowledge in the manner described in this paper enables research to assess the potential for, and processes of, scaling-up innovations in the nexus space, to contribute insights to policy and decision making.     

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.     

Estimation of Efficiency of Processing Soil Samples for Pesticide Residues Analysis

The efficiency of four sample processing methods was tested with eight different types of soils representing the major proportion of cultivated soils. The principle of sampling constant was applied for characterizing the efficiency of the procedures and testing the well-mixed status of the prepared soil. The test material was 14C-labeled atrazine that enabled keeping the random error of analyses ≤ about 1%. Adding water to the soil proved to be the most efficient and generally applicable procedure resulting in about 6% relative sample processing uncertainty for 20 g test portions. The expected error is inversely proportional to the mass of test portion. Smashing and manual mixing of soil resulted in about four times higher uncertainty than mixing with water. Grinding of soil is applicable for dry soils only, but the test procedure applied was not suitable for estimating a typical uncertainty of processing dry soil samples. Adding dry ice did not improve the efficiency of sample processing.     

Links among nitrification, nitrifier communities, and edaphic properties in contrasting soils receiving dairy slurry

Soil biotic and abiotic factors strongly influence nitrogen (N) availability and increases in nitrification rates associated with the application of manure. In this study, we examine the effects of edaphic properties and a dairy (Bos taurus) slurry amendment on N availability, nitrification rates and nitrifier communities. Soils of variable texture and clay mineralogy were collected from six USDA-ARS research sites and incubated for 28 d with and without dairy slurry applied at a rate of ~300 kg N ha(-1). Periodically, subsamples were removed for analyses of 2 M KCl extractable N and nitrification potential, as well as gene copy numbers of ammonia-oxidizing bacteria (AOB) and archaea (AOA). Spearman coefficients for nitrification potentials and AOB copy number were positively correlated with total soil C, total soil N, cation exchange capacity, and clay mineralogy in treatments with and without slurry application. Our data show that the quantity and type of clay minerals present in a soil affect nitrifier populations, nitrification rates, and the release of inorganic N. Nitrogen mineralization, nitrification potentials, and edaphic properties were positively correlated with AOB gene copy numbers. On average, AOA gene copy numbers were an order of magnitude lower than those of AOB across the six soils and did not increase with slurry application. Our research suggests that the two nitrifier communities overlap but have different optimum environmental conditions for growth and activity that are partly determined by the interaction of manure-derived ammonium with soil properties.     

Flight speeds observed with radar,a correction: slow “birds” are insects

Summary Based upon new data and re-analysis of previous data, some results concerning migration of birds at night are now attributed to insects. In particular, slowly flying radar targets over land (Larkin and Thompson 1980) and, by analogy, over the ocean (Larkin et al. 1979) are shown to lack wing beat patterns of birds and the appearance of birds when viewed with a radar-controlled high-power telescope and spotlamp. The insect targets overlap with birds in the amount of radar echo returned, are abundant in warmer months, and fly even in March and November in temperate North America. Other previous results are largely substantiated; however, a previous report (Larkin 1980) that migrating birds can detect the wind direction over the ocean is not substantiated.     

THE ADOPTION OF MUNICIPAL WATER CONSERVATION: AN UNLIKELY EVENT?1

ABSTRACT: It is contended that water conservation measures that reduce a water system's net revenues are unlikely to be adopted. Pricing policies that induce conservation can be designed to increase net revenues. Management practices that lead to conservation and pure conservation measures may reduce net revenues; consequently, they are unlikely to be adopted. Recent experience in five southwestern cities supports these contentions. It is argued that the managers of a municipal water enterprise are particularly sensitive to short term variation in revenues. Consequently, to increase the likelihood of the adoption of measures that reduce net revenues it is necessary to remove either the decision to adopt measures that reduce net revenue or the adverse revenue effect from the water enterprise. Finally, to make higher rates for conservation palatable, imaginative use for the funds generated must be developed.     

Viruses in wastewater sludges and in effluents used for irrigation

Disposal of sewage wastes is a problem of increasing magnitude in the United States. New control measures enacted by Congress require consideration of land disposal of sludges and effluents. The volume of wastes involved and the possibility of contaminating ground water supplies and vegetation has great public health significance. The effectiveness of the sewage treatment process to remove chemical and biological contaminants and the operational efficiency of many sewage treatment plants are factors that must be given careful consideration before final selection of disposal methodology. The quality of our future water and food supplies will be affected either beneficially or adversely by current management decisions.