The 1999 Regional Haze Rule provides a context for this review of visibility, the science that describes it, and the use of that science in regulatory guidance The scientific basis for the 1999 regulation is adequate The deciview metric that tracks progress is an imperfect but objective measure of what people see near the prevailing visual range The definition of natural visibility conditions is adequate for current planning, but it will need to be refined as visibility improves Emissions from other countries will set achievable levels above those produced by natural sources Some natural events, notably dust storms and wildfires, are episodic and cannot be represented by annual average background values or emission estimates Sulfur dioxide (SO2) emission reductions correspond with lower sulfate (SO4 2−) concentrations and visibility im-provements in the regions where these have occurred Non-road emissions have been growing more rapidly than emissions from other sources, which have remained

Visibility: Science and Regulation

Thermally derived carbon fractions including organic carbon (OC) and elemental carbon (EC) have been reported for the U.S. Interagency Monitoring of PROtected Visual Environments (IMPROVE) network since 1987 and have been found useful in source apportionment studies and to evaluate quartz-fiber filter adsorption of organic vapors. The IMPROVE_A temperature protocol defines temperature plateaus for thermally derived carbon fractions of 140 degrees C for OC1, 280 degrees C for OC2, 480 degrees C for OC3, and 580 degrees C for OC4 in a helium (He) carrier gas and 580 degrees C for EC1, 740 degrees C for EC2, and 840 degrees C for EC3 in a 98% He/2% oxygen (O2) carrier gas. These temperatures differ from those used previously because new hardware used for the IMPROVE thermal/optical reflectance (IMPROVE_TOR) protocol better represents the sample temperature than did the old hardware. A newly developed temperature calibration method demonstrates that these temperatures better represent sample temperatures in the older units used to quantify IMPROVE carbon fractions from 1987 through 2004. Only the thermal fractions are affected by changes in temperature. The OC and EC by TOR are insensitive to the change in temperature protocol, and therefore the long-term consistency of the IMPROVE database is conserved. A method to detect small quantities of O2 in the pure He carrier gas shows that O2 levels above 100 ppmv also affect the comparability of thermal carbon fractions but have little effect on the IMPROVE_TOR split between OC and EC.

https://www.tandfonline.com/doi/pdf/10.3155/1047-3289.57.9.1014

The IMPROVE_A Temperature Protocol for Thermal/Optical Carbon Analysis: Maintaining Consistency with a Long-Term Database

The Structure of Inference.

[1] In the spring of 1985 an interagency consortium of federal land management agencies and the Environmental Protection Agency established the Interagency Monitoring of Protected Visual Environments (IMPROVE) network to assess visibility and aerosol monitoring for the purpose of tracking spatial and temporal trends of visibility and visibility-impairing particles in rural areas. The program was initiated with 20 monitoring sites and was expanded to 165 sites between 2000 and 2003. This paper reports on fine aerosol data collected in the year 2001 at 143 sites. The major fine (dp < 2.5 μm) particle aerosol species, sulfates, nitrates, organics, light-absorbing carbon, and wind-blown dust, and coarse gravimetric mass are monitored, and at some sites, light scattering and/or extinction are measured. Sulfates, carbon, and crustal material are responsible for most of the fine mass at the majority of locations throughout the United States, while at sites in southern California and the midwestern United States, nitrates can contribute significantly. In the eastern United States, sulfates contribute between 50 and 60% of the fine mass. Sulfate concentrations tend to be highest in the summer months while organic concentrations can be high in the spring, summer, or fall seasons, depending upon fire-related emissions. However, at the two urban sites, Phoenix, Arizona, and Puget Sound, Washington, organics peak during the winter months. Nitrate concentrations also tend to be highest during the winter months. During the spring months in many areas of the western United States, fine soil can contribute as much as 40% of fine mass. The temporal changes in soil concentration that occur simultaneously over much of the western United States including the Rocky Mountain region suggest a large source region, possibly long-range transport of Asian dust.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2003JD003739

Spatial and monthly trends in speciated fine particle concentration in the United States

For a broad class of multilevel models, there exist two well-known competing parameterizations, the centered parameterization (CP) and the non-centered parameterization (NCP), for effective MCMC implementation. Much literature has been devoted to the questions of when to use which and how to compromise between them via partial CP/NCP. This article introduces an alternative strategy for boosting MCMC efficiency via simply interweaving—but not alternating—the two parameterizations. This strategy has the surprising property that failure of both the CP and NCP chains to converge geometrically does not prevent the interweaving algorithm from doing so. It achieves this seemingly magical property by taking advantage of the discordance of the two parameterizations, namely, the sufficiency of CP and the ancillarity of NCP, to substantially reduce the Markovian dependence, especially when the original CP and NCP form a “beauty and beast” pair (i.e., when one chain mixes far more rapidly than the other). The ancilla...

/pdf/to-center-or-not-to-center-that-is-not-the-question-an-i7vl3ga456.pdf

To Center or Not to Center: That Is Not the Question—An Ancillarity–Sufficiency Interweaving Strategy (ASIS) for Boosting MCMC Efficiency

Generalized pivotal quantities (GPQs) and generalized confidence intervals (GCIs) have proven to be useful tools for making inferences in many practical problems. Although GCIs are not guaranteed to have exact frequentist coverage, a number of published and unpublished simulation studies suggest that the coverage probabilities of such intervals are sufficiently close to their nominal value so as to be useful in practice. In this article we single out a subclass of generalized pivotal quantities, which we call fiducial generalized pivotal quantities (FGPQs), and show that under some mild conditions, GCIs constructed using FGPQs have correct frequentist coverage, at least asymptotically. We describe three general approaches for constructing FGPQs—a recipe based on invertible pivotal relationships, and two extensions of it—and demonstrate their usefulness by deriving some previously unknown GPQs and GCIs. It is fair to say that nearly every published GCI can be obtained using one of these recipes. As an inte...

https://www.jstor.org/stable/info/30047454

Fiducial Generalized Confidence Intervals

Understanding the response of air quality parameters such as visibility to the implementation of new air quality regulations, population growth and redistribution, and federal land managing practices is essential to the evaluation of air quality management plans on air quality in federal Class I areas. For instance, the reduction of SO2 emissions from large single point sources should result in the decrease of extreme sulfate concentrations, while population growth in geographic areas outside of urban centers could cause a slow widespread increase of sulfate and organic concentrations. The change in federal land managing practice of increased prescribed fire on a year-round basis in lieu of large naturally occurring wild fires could have the same effect; that is, the frequency of high sulfur days increase and low sulfur days decrease as the result of the management practice. Therefore, it is of interest to examine the trends associated with the proportion of days during which the concentration of...

Trends in the extremes of sulfur concentration distributions.

An apparent increasing trend in the summer concentrations of particulate sulfur at Shenandoah (for the time period 1982-1995) and at Great Smoky Mountains (for the time period 1984-1995) has been pointed out by some researchers. Others have suggested that these increasing trends may be an analytical artifact resulting from the switch from the Stacked Filter Units (SFU) measurement system to the IMPROVE (Interagency Monitoring of Protected Visual Environments) measurement system that occurred during the winter of 1987. To obtain a better understanding of the effect of the protocol change, we investigate the changes in the seasonal averages of sulfur concentrations for successive pairs of years for the period 1980-1996 for about 20 national park sites in the United States. For the period 1980-1987, we use sulfur data from the old (SFU) database and for the period 1988-1996, we use the IMPROVE database. Changes from one year to the next similar to that between 1987 and 1988 occurred during other years and seasons suggesting that chance causes alone could perhaps explain it, the degree to which chance could have caused the changes was measured using the permutation test for matched. At the very least, additional information such as side by side readings using SFU and IMPROVE measurement methods, may be needed to better understand any systematic effect in the sulfur measurements that may be ascribable to the protocol change.

An analysis of the yearly changes in sulfur concentrations at various national parks in the United States, 1980-1996.

Routine air quality monitoring produces filter samples that, when analyzed, yield the total amount of the aerosol present in the volume of air drawn by the pump in the monitoring device during the given sampling period. From this we obtain an average concentration of the aerosol for the given duration. The samples are therefore really aggregate samples. A natural question then is "what is the effect of the duration of aggregation on the accuracy and precision of the estimate of the quantity of interest?" The answer depends on a number of factors, such as the quantity that is being estimated: a mean, or an extreme value, or some other quantity; the nature of the measurement error--additive versus multiplicative; the costs of laboratory analyses, and so on. In this paper, we investigate these issues when the interest is in estimating the mean concentration of a specified aerosol species over a fixed time period. In particular, we propose a method for determining a sampling duration that will yield the "best estimate" of the mean concentration for a given cost whenever appropriate statistical assumptions hold.

Sampling duration calculations.

/pdf/a-sas-macro-for-theil-regression-38tpyfo89v.pdf

Paul Patterson

Papers

Fiducial Generalized Confidence Intervals

Trends in the extremes of sulfur concentration distributions.

An analysis of the yearly changes in sulfur concentrations at various national parks in the United States, 1980-1996.

Sampling duration calculations.

A SAS Macro for Theil Regression