Precipitation in light extinction reconstruction

The U.S. Environmental Protection Agency (EPA) published the Regional Haze Rule (RHR) in 1999. The RHR default goal is to reduce haze linearly to natural background in 2064 from the baseline period of 2000-2004. The EPA default method for estimating natural and baseline visibility uses the Interagency Monitoring of Protected Visual Environments (IMPROVE) formula. The IMPROVE formula predicts the light extinction coefficient from aerosol chemical concentrations measured by the IMPROVE network. The IMPROVE light scattering coefficient formula using data from 1994-2002 underestimated the measured light scattering coefficient by 700 Mm(-1), on average, on days with precipitation. Also, precipitation occurred as often on the clearest as haziest days. This led to estimating the light extinction coefficient of precipitation, averaged over all days, as the light scattering coefficient on days with precipitation (700 Mm(-1)) multiplied by the percent of precipitation days in a year. This estimate added to the IMPROVE formula light extinction estimate gives a real world estimate of visibility for the 20% clearest, 20% haziest, and all days. For example, in 1993, the EPAs Report to Congress projected visibility in Class I areas would improve by 3 deciviews by 2010 across the haziest portions of the eastern United States because of the 1990 Clean Air Act Amendments. Omitted was the light extinction coefficient of precipitation. Adding in the estimated light extinction coefficient of precipitation, the estimated visibility improvement declines to <1 deciview.     

Precipitation in Light Extinction Reconstruction

Abstract

The U.S. Environmental Protection Agency (EPA) published the Regional Haze Rule (RHR) in 1999.¹ The RHR default goal is to reduce haze linearly to natural background in 2064 from the baseline period of 2000–2004. The EPA default method^2,3 for estimating natural and baseline visibility uses the Interagency Monitoring of Protected Visual Environments (IMPROVE) formula. The IMPROVE formula predicts the light extinction coefficient from aerosol chemical concentrations measured by the IMPROVE network. The IMPROVE light scattering coefficient formula using data from 1994–2002 underestimated the measured light scattering coefficient by 700 Mm^?1, on average, on days with precipitation. Also, precipitation occurred as often on the clearest as haziest days. This led to estimating the light extinction coefficient of precipitation, averaged over all days, as the light scattering coefficient on days with precipitation (700 Mm^?1) multiplied by the percent of precipitation days in a year. This estimate added to the IMPROVE formula light extinction estimate gives a real world estimate of visibility for the 20% clearest, 20% haziest, and all days. For example, in 1993, the EPAs Report to Congress projected visibility in Class I areas would improve by 3 deciviews by 2010 across the haziest portions of the eastern United States because of the 1990 Clean Air Act Amendments. Omitted was the light extinction coefficient of precipitation. Adding in the estimated light extinction coefficient of precipitation, the estimated visibility improvement declines to <1 deci-view.     

Air pollutant source characterization using the revised regional haze tracking metric and a photochemical grid model and implications for regional haze planning

The 2017 revisions to the Regional Haze Rule clarify that visibility progress at Class I national parks and wilderness areas should be tracked on days with the highest anthropogenic contributions to haze (impairment). We compare the natural and anthropogenic contributions to haze in the western United States in 2011 estimated using the Environmental Protection Agency (EPA) recommended method and using model projections from the Comprehensive Air Quality Model with Extensions (CAMx) and the Particulate Source Apportionment Tool (PSAT). We do so because these two methods will be used by states to demonstrate visibility progress by 2028. If the two methods assume different natural and anthropogenic contributions, the projected benefits of reducing U.S. anthropogenic emissions will differ. The EPA method assumes that episodic elevated carbonaceous aerosols greater than an annual 95th percentile threshold are natural events. For western U.S. IMPROVE monitoring sites reviewed in this paper, CAMx-PSAT confirms these episodes are impacted by carbon from wildfire or prescribed fire events. The EPA method assumes that most of the ammonium sulfate is anthropogenic in origin. At most western sites CAMx-PSAT apportions more of the ammonium sulfate on the most impaired days to global boundary conditions and anthropogenic Canadian, Mexican, and offshore shipping emissions than to U.S. anthropogenic sources. For ammonium nitrate and coarse mass, CAMx-PSAT apportions greater contributions to U.S. anthropogenic sources than the EPA method assigns to total anthropogenic contributions. We conclude that for western IMPROVE sites, the EPA method is effective in selecting days that are likely to be impacted by anthropogenic emissions and that CAMx-PSAT is an effective approach to estimate U.S. source contributions. Improved inventories, particularly international and natural emissions, and further evaluation of global and regional model performance and PSAT attribution methods are recommended to increase confidence in modeled source characterization.

Implications: The western states intend to use the CAMx model to project visibility progress by 2028. Modeled visibility response to changes in U.S. anthropogenic emissions may be less than estimated using the EPA assumptions based on total U.S. and international anthropogenic contributions to visibility impairment. Additional model improvements are needed to better account for contributions to haze from natural and international emissions in current and future modeling years. These improvements will allow more direct comparison of model and EPA estimates of natural and anthropogenic contributions to haze and future visibility progress.     

A statistical analysis of visibility-impairing particles in federal Class I areas

It is widely agreed that visibility conditions in many Class I areas are impaired to some extent. This paper provides an estimate of the degree of impairment in many of the Class I areas with respect to each of the six haze-forming aerosol classes as described in the supporting documents to the U.S. Environmental Protection Agency Regional Haze Rule. Analyses are performed comparing data from the Interagency Monitoring of Protected Visual Environments network to a modified version of the default natural conditions estimates from the Regional Haze Rule. Uncertainties in the measured annual mean concentrations and biases in the default natural condition estimates because of the effects of geography and meteorology are discussed. It is determined that all of the Class I areas in the contiguous 48 United States are significantly impaired with respect to sulfate aerosols, most of the Class I areas are significantly impaired with respect to nitrate and elemental carbon aerosols, and impairment with respect to organic mass, soil mass, and coarse mass is generally less discernable. No attempt is made to determine adverse impacts with respect to any specific source or group of sources.     

Evaluation of the IMPROVE Equation for estimating aerosol light extinction

The [revised] IMPROVE Equation for estimating light extinction from aerosol chemical composition was evaluated considering new measurements at U.S. national parks. Compared with light scattering (Bsp) measured at seven IMPROVE sites with nephelometer data from 2003–2012, the [revised] IMPROVE Equation over- and underestimated Bsp in the lower and upper quintiles, respectively, of measured Bsp. Underestimation of the worst visibility cases (upper quintile) was reduced by assuming an organic mass (OM)/organic carbon (OC) ratio of 2.1 and hygroscopic growth of OM, based on results from previous field studies. This assumption, however, tended to overestimate low Bsp even more. Assuming that sulfate was present as ammonium bisulfate rather than as ammonium sulfate uniformly reduced estimated Bsp. The split-mode model of concentration- and size-dependent dry mass scattering efficiencies in the [revised] IMPROVE Equation does not eliminate systematic biases in estimated Bsp. While the new measurements of OM/OC and OM hygroscopicity should be incorporated into future iterations of the IMPROVE Equation, the problem is not well constrained due to a lack of routine measurements of sulfate neutralization and the water-soluble fraction of OM in the IMPROVE network.

Implications: Studies in U.S. national parks showed that aerosol organics contain more mass and absorb more water as a function of relative humidity than is currently assumed by the IMPROVE Equation for calculating chemical light extinction. Consideration of these results could significantly shift the apportionment of light extinction to water-soluble organic aerosols and therefore better inform pollution control strategies under the U.S. Environmental Protection Agency Regional Haze Rule.     

Use of the Deciview Haze Index as an Indicator for Regional Haze

ABSTRACT

The U.S. Environmental Protection Agency (EPA) Notice of Proposed Rulemaking (NPR) for regional haze uses the deciview haze index (dv) as the indicator for visibility impairment and proposes a change of 1 dv as "a small but noticeable change in haziness under most circumstances." All previous visibility rules have specified human perception as the indicator for visibility impairment. This article examines the technical basis cited in the NPR for this new indicator for visibility impairment and for the perception threshold of approximately 1 dv. Derivations based on the assumptions and approximations cited in the NPR show that the deciview haze index does not have the correct functional form to relate changes in haze within federal Class I areas to the visual perception of those changes. The just-noticeable change in light extinction is, in most cases, inversely proportional to the sight path length instead of proportional to the light-extinction coefficient. These derivations also indicate that a 1-dv change in haziness is typically too small to be perceived in most Class I areas.     

Visibility: science and regulation

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 improvements in the regions where these have occurred. Non-road emissions have been growing more rapidly than emissions from other sources, which have remained stable or decreased since 1970. Simpler models representing transport, limiting precursor pollutants, and gas-to-particle equilibrium should be used to understand where and when emission reductions will be effective, rather than large complex models that have insufficient input and validation measurements. Examples of model-based source attribution show large differences among estimates from various modeling systems and with ambient measurements.     

Improved light extinction reconstruction in interagency monitoring of protected visual environments

The U.S. Environmental Protection Agency (EPA) published the Regional Haze Rule (RHR) in 1999. The RHR default goal is to reduce haze linearly from the baseline period of 2000 through 2004 to natural background in 2064. EPA-recommended method for estimating baseline and natural haze uses the Interagency Monitoring of Protected Visual Environments (IMPROVE) light extinction formula. The IMPROVE formula predicts light extinction from measured aerosol chemical concentrations and estimates of the relative humidity multiplier. On average, the IMPROVE formula overpredicts 6156 nephelometer days (24-hr average measured particle light scattering, bsp) of data by 25%. A new IMPROVED method that reconstructs light extinction using a concentration power law model overpredicts these nephelometer days of data by just 2%. Ignoring the 20% lowest light scattering days, this new IMPROVED formula has a 3% underprediction bias over the 4925 highest nephelometer days with light scattering > or =8 inverse megameters. For comparison, the IMPROVE formula has a 12% overprediction bias for the same days. The IMPROVE formula overprediction averages 77%, 27%, 17%, 9%, and -5% broken down by quintile from lowest to highest nephelometer measured light scattering days. The new IMPROVED formula average overprediction is 21%, -5%, -5%, -2%, and 0%. So, agreement between measured and predicted light scattering improves by modifying the current IMPROVE light extinction formula.     

Critique of "Precipitation in light extinction reconstruction" by P.A. Ryan

The goal of the Regional Haze Rule (RHR) is to return visibility in class I areas (CIAs) to natural levels, excluding weather-related events, by 2064. Whereas visibility, the seeing of scenic vistas, is a near instantaneous and sight-path-dependent phenomenon, reasonable progress toward the RHR goal is assessed by tracking the incremental changes in 5-yr average visibility. Visibility is assessed using a haze metric estimated from 24-hr average aerosol measurements that are made at one location representative of the CIA. It is assumed that, over the 5-yr average, the aerosol loadings and relative humidity along all of the site paths are the same and can be estimated from the 24-hr measurements. It is further assumed that any time a site path may be obscured by weather (e.g., clouds and precipitation), there are other site paths within the CIA that are not. Therefore, when calculating the haze metric, sampling days are not filtered for weather conditions. This assumption was tested by examining precipitation data from multiple monitors for four CIAs. It is shown that, in general, precipitation did not concurrently occur at all monitors for a CIA, and precipitation typically occurred 3-8 hr or less in a day. In a recent paper in this journal, Ryan asserts that the haze metric should include contributions from precipitation and conducted a quantitative assessment incorrectly based on the assumption that the Optec NGN-2 nephelometer measurements include the effects of precipitation. However, these instruments are programmed to shut down during rain events, and any data logged are in error. He further assumes that precipitation occurs as often on the haziest days as the clearest days and that precipitation light scattering (bprecip) is independent of geographic location and applied an average bprecip derived for Great Smoky Mountains to diverse locations including the Grand Canyon. Both of these assumptions are shown to be in error.     

Critique of “Precipitation in Light Extinction Reconstruction” by P.A. Ryan

Abstract

The goal of the Regional Haze Rule (RHR) is to return visibility in class I areas (CIAs) to natural levels, excluding weather-related events, by 2064. Whereas visibility, the seeing of scenic vistas, is a near instantaneous and sight-path-dependent phenomenon, reasonable progress toward the RHR goal is assessed by tracking the incremental changes in 5-yr average visibility. Visibility is assessed using a haze metric estimated from 24-hr average aerosol measurements that are made at one location representative of the CIA. It is assumed that, over the 5-yr average, the aerosol loadings and relative humidity along all of the site paths are the same and can be estimated from the 24-hr measurements. It is further assumed that any time a site path may be obscured by weather (e.g., clouds and precipitation), there are other site paths within the CIA that are not. Therefore, when calculating the haze metric, sampling days are not filtered for weather conditions. This assumption was tested by examining precipitation data from multiple monitors for four CIAs. It is shown that, in general, precipitation did not concurrently occur at all monitors for a CIA, and precipitation typically occurred 3-8 hr or less in a day. In a recent paper in this journal, Ryan asserts that the haze metric should include contributions from precipitation and conducted a quantitative assessment incorrectly based on the assumption that the Optec NGN-2 nephelometer measurements include the effects of precipitation. However, these instruments are programmed to shut down during rain events, and any data logged are in error. He further assumes that precipitation occurs as often on the haziest days as the clearest days and that precipitation light scattering (bprecip) is independent of geographic location and applied an average bprecip derived for Great Smoky Mountains to diverse locations including the Grand Canyon. Both of these assumptions are shown to be in error.     

Trends in speciated fine particulate matter and visibility across monitoring networks in the Southeastern United States

Trends in fine particulate matter <2.5 microm in diameter (PM2.5) and visibility in the Southeastern United States were evaluated for sites in the Interagency Monitoring of Protected Visual Environments, Speciated Trends Network, and Southeastern Aerosol Research and Characterization Study networks. These analyses are part of the technical assessment by Visibility Improvement-State and Tribal Association of the Southeast (VISTAS), the regional planning organization for the southeastern states, in support of State Implementation Plans for the regional haze rule. At all of the VISTAS IMPROVE sites, ammonium sulfate and organic carbon (OC) are the largest and second largest contributors, respectively, to light extinction on both the 20% haziest and 20% clearest days. Ammonium nitrate, elemental carbon (EC), soils, and coarse particles make comparatively small contributions to PM2.5 mass and light extinction on most days at the Class I areas. At Southern Appalachian sites, the 20% haziest days occur primarily in the late spring to fall, whereas at coastal sites, the 20% haziest days can occur through out the year. Levels of ammonium sulfate in Class I areas are similar to those in nearby urban areas and are generally higher at the interior sites than the coastal sites. Concentrations of OC, ammonium nitrate, and, sometimes, EC, tend to be higher in the urban areas than in nearby Class I areas, although differences in measurement methods complicate comparisons between networks. Results support regional controls of sulfur dioxide for both regional haze and PM2.5 implementation and suggest that controls of local sources of OC, EC, or nitrogen oxides might also be considered for urban areas that are not attaining the annual National Ambient Air Quality Standard for PM2.5.     

Which visibility indicators best represent a population’s preference for a level of visual air quality?

Several studies have been carried out over the past 20 or so years to assess the level of visual air quality that is judged to be acceptable in urban settings. Groups of individuals were shown slides or computer-projected scenes under a variety of haze conditions and asked to judge whether each image represented acceptable visual air quality. The goal was to assess the level of haziness found to be acceptable for purposes of setting an urban visibility regulatory standard. More recently, similar studies were carried out in Beijing, China, and the more pristine Grand Canyon National Park and Great Gulf Wilderness. The studies clearly showed that when preference ratings were compared to measures of atmospheric haze such as atmospheric extinction, visual range, or deciview (dv), there was not a single indicator that represented acceptable levels of visual air quality for the varied urban or more remote settings. For instance, using a Washington, D.C., setting, 50% of the observers rated the landscape feature as not having acceptable visual air quality at an extinction of 0.19 km^?1 (21 km visual range, 29 dv), while the 50% acceptability point for a Denver, Colorado, setting was 0.075 km^?1 (52 km visual range, 20 dv) and for the Grand Canyon it was 0.023 km^?1 (170 km visual range, 7 dv). Over the past three or four decades, many scene-specific visibility indices have been put forth as potential indicators of visibility levels as perceived by human observers. They include, but are not limited to, color and achromatic contrast of single landscape features, average and equivalent contrast of the entire image, edge detection algorithms such as the Sobel index, and just-noticeable difference or change indexes. This paper explores various scene-specific visual air quality indices and examines their applicability for use in quantifying visibility preference levels and judgments of visual air quality.

Implications: Visibility acceptability studies clearly show that visibility become more unacceptable as haze increases. However, there are large variations in the preference levels for different scenes when universal haze indicators, such as atmospheric extinction, are used. This variability is significantly reduced when the sky–landscape contrast of the more distant landscape features in the observed scene is used. Analysis suggest that about 50% of individuals would find the visibility unacceptable if at any time the more distant landscape features nearly disappear, that is, they are at the visual range. This common metric could form the basis for setting an urban visibility standard.     

Variation of mass scattering efficiencies in IMPROVE

The Interagency Monitoring of Protected Visual Environments (IMPROVE) equation used to assess compliance under the U.S. Environmental Protection Agency (EPA) Haze Rule assumes that dry mass scattering efficiencies for aerosol chemical components are constant. However, examination of aerosol size distributions and chemical composition during the Big Bend Regional Aerosol and Visibility Observational Study and the Southeastern Aerosol and Visibility Study suggests that volume and mass scattering efficiencies vary directly with increasing particle light scattering and aerosol mass concentration. This is consistent with the observation that particle distributions were shifted to larger sizes under more polluted conditions and appears to be related to aging of the aerosol during transport to remote locations.     

Variation of Mass Scattering Efficiencies in IMPROVE

Abstract

The Interagency Monitoring of Protected Visual Environments (IMPROVE) equation used to assess compliance under the U.S. Environmental Protection Agency (EPA) Haze Rule assumes that dry mass scattering efficiencies for aerosol chemical components are constant. However, examination of aerosol size distributions and chemical composition during the Big Bend Regional Aerosol and Visibility Observational Study and the Southeastern Aerosol and Visibility Study suggests that volume and mass scattering efficiencies vary directly with increasing particle light scattering and aerosol mass concentration. This is consistent with the observation that particle distributions were shifted to larger sizes under more polluted conditions and appears to be related to aging of the aerosol during transport to remote locations.     

Revised algorithm for estimating light extinction from IMPROVE particle speciation data

The Interagency Monitoring of Protected Visual Environments (IMPROVE) particle monitoring network consists of approximately 160 sites at which fine particulate matter (PM2.5) mass and major species concentrations and course particulate matter (PM10) mass concentrations are determined by analysis of 24-hr duration sampling conducted on a 1-day-in-3 schedule A simple algorithm to estimate light extinction from the measured species concentrations was incorporated in the 1999 Regional Haze Rule as the basis for the haze metric used to track haze trends. A revised algorithm was developed that is more consistent with the recent atmospheric aerosol literature and reduces bias for high and low light extinction extremes. The revised algorithm differs from the original algorithm in having a term for estimating sea salt light scattering from Cl(-) ion data, using 1.8 instead of 1.4 for the mean ratio of organic mass to measured organic carbon, using site-specific Rayleigh scattering based on site elevation and mean temperature, employing a split component extinction efficiency associated with large and small size mode sulfate, nitrate and organic mass species, and adding a term for nitrogen dioxide (NO2) absorption for sites with NO2 concentration information. Light scattering estimates using the original and the revised algorithms are compared with nephelometer measurements at 21 IMPROVE monitoring sites. The revised algorithm reduces the underprediction of high haze periods and the overprediction of low haze periods compared with the performance of the original algorithm. This is most apparent at the hazier monitoring sites in the eastern United States. For each site, the PM10 composition for days selected as the best 20% and the worst 20% haze condition days are nearly identical regardless of whether the basis of selection was light scattering from the original or revised algorithms, or from nephelometer-measured light scattering.     

Estimating the probability of the public perceiving a decrease in atmospheric haze

Regional haze regulations require progress toward reducing atmospheric haze as measured by particle scattering coefficient of visible light. From a practical perspective, this raises the following question: Given a decrease in extinction, what is the probability that people will notice an improvement in visibility? This paper proposes a quantitative definition of the probability of a perceptible increase in visibility given a decrease in light extinction and a general method to estimate this probability from perception measurements made in the field under realistic conditions. Using data from a recent study of visibility perception by 8 observers, it is estimated that a 2-4 deciview change gives a 67% maximum probability of detecting the improvement. Stated another way, the odds of seeing a difference are at most 2:1 for a change of 2-4 deciviews. A 90% probability requires a change of at least 3.5-7.0 deciviews. The limitations and possible bias in the results of this study are discussed. These results may have a major effect on the cost-benefit analysis of regulatory actions to improve visibility.     

Development of visibility forecasting modeling framework for the Lower Fraser Valley of British Columbia using Canada’s Regional Air Quality Deterministic Prediction System

Visibility degradation, one of the most noticeable indicators of poor air quality, can occur despite relatively low levels of particulate matter when the risk to human health is low. The availability of timely and reliable visibility forecasts can provide a more comprehensive understanding of the anticipated air quality conditions to better inform local jurisdictions and the public. This paper describes the development of a visibility forecasting modeling framework, which leverages the existing air quality and meteorological forecasts from Canada’s operational Regional Air Quality Deterministic Prediction System (RAQDPS) for the Lower Fraser Valley of British Columbia. A baseline model (GM-IMPROVE) was constructed using the revised IMPROVE algorithm based on unprocessed forecasts from the RAQDPS. Three additional prototypes (UMOS-HYB, GM-MLR, GM-RF) were also developed and assessed for forecast performance of up to 48 hr lead time during various air quality and meteorological conditions. Forecast performance was assessed by examining their ability to provide both numerical and categorical forecasts in the form of 1-hr total extinction and Visual Air Quality Ratings (VAQR), respectively. While GM-IMPROVE generally overestimated extinction more than twofold, it had skill in forecasting the relative species contribution to visibility impairment, including ammonium sulfate and ammonium nitrate. Both statistical prototypes, GM-MLR and GM-RF, performed well in forecasting 1-hr extinction during daylight hours, with correlation coefficients (R) ranging from 0.59 to 0.77. UMOS-HYB, a prototype based on postprocessed air quality forecasts without additional statistical modeling, provided reasonable forecasts during most daylight hours. In terms of categorical forecasts, the best prototype was approximately 75 to 87% correct, when forecasting for a condensed three-category VAQR. A case study, focusing on a poor visual air quality yet low Air Quality Health Index episode, illustrated that the statistical prototypes were able to provide timely and skillful visibility forecasts with lead time up to 48 hr.

Implications: This study describes the development of a visibility forecasting modeling framework, which leverages the existing air quality and meteorological forecasts from Canada’s operational Regional Air Quality Deterministic Prediction System. The main applications include tourism and recreation planning, input into air quality management programs, and educational outreach. Visibility forecasts, when supplemented with the existing air quality and health based forecasts, can assist jurisdictions to anticipate the visual air quality impacts as perceived by the public, which can potentially assist in formulating the appropriate air quality bulletins and recommendations.     

Long-term dust aerosol production from natural sources in Iceland

Iceland is a volcanic island in the North Atlantic Ocean with maritime climate. In spite of moist climate, large areas are with limited vegetation cover where >40% of Iceland is classified with considerable to very severe erosion and 21% of Iceland is volcanic sandy deserts. Not only do natural emissions from these sources influenced by strong winds affect regional air quality in Iceland (“Reykjavik haze”), but dust particles are transported over the Atlantic ocean and Arctic Ocean >1000 km at times. The aim of this paper is to place Icelandic dust production area into international perspective, present long-term frequency of dust storm events in northeast Iceland, and estimate dust aerosol concentrations during reported dust events.

Meteorological observations with dust presence codes and related visibility were used to identify the frequency and the long-term changes in dust production in northeast Iceland. There were annually 16.4 days on average with reported dust observations on weather stations within the northeastern erosion area, indicating extreme dust plume activity and erosion within the northeastern deserts, even though the area is covered with snow during the major part of winter. During the 2000s the highest occurrence of dust events in six decades was reported. We have measured saltation and Aeolian transport during dust/volcanic ash storms in Iceland, which give some of the most intense wind erosion events ever measured.

Icelandic dust affects the ecosystems over much of Iceland and causes regional haze. It is likely to affect the ecosystems of the oceans around Iceland, and it brings dust that lowers the albedo of the Icelandic glaciers, increasing melt-off due to global warming. The study indicates that Icelandic dust may contribute to the Arctic air pollution.

Implications: Long-term records of meteorological dust observations from Northeast Iceland indicate the frequency of dust events from Icelandic deserts. The research involves a 60-year period and provides a unique perspective of the dust aerosol production from natural sources in the sub-Arctic Iceland. The amounts are staggering, and with this paper, it is clear that Icelandic dust sources need to be considered among major global dust sources. This paper presents the dust events directly affecting the air quality in the Arctic region.     

PM2.5 mass and light extinction reconstruction in IMPROVE

Compliance under the Regional Haze Rule of 1999 is based on Interagency Monitoring of Protected Visual Environments (IMPROVE) protocols for reconstructing aerosol mass and light extinction from aerosol chemical concentrations measured in the IMPROVE network. The accuracy, consistency, and potential biases in these formulations were examined using IMPROVE aerosol chemistry and light extinction data from 1988-1999. Underestimation of particulate matter with an aerodynamic diameter < 2.5 microm (PM2.5) by the IMPROVE mass reconstruction formula by 12%, on average, appears to be related to the exclusion of sodium, chlorine, and other elements and to artifacts associated with the measurement of organic carbon, but not to absorption of water by sulfates and nitrates on IMPROVE Teflon filters during weighing. Light scattering measured by transmissometry is not consistent with nephelometer scattering or single-scatter albedos expected for remote locations. Light scattering was systematically overestimated by 34%, on average, with the IMPROVE particle scattering (Bsp) reconstruction formula. The use of climatologically based hygroscopic growth factors f(RH) suggested for compliance with the Haze Rule contributes significantly to this overestimation and increases the amount of light extinction attributable to sulfates for IMPROVE samples between 1993 and 1999 by 5 percentage points.     

Improving the correlations of ambient tapered element oscillating microbalance PM2.5 data and SHARP 5030 Federal Equivalent Method in Ontario: A multiple linear regression analysis

Tapered element oscillating microbalances equipped with sample equilibration system (TEOM-SES) used by the province of Ontario for the ambient monitoring of PM_2.5 (particulate matter with an aerodynamic diameter ≤2.5 µm) in its air quality index (AQI) network were collocated with the Synchronized Hybrid Ambient Real-time Particulate monitor (SHARP 5030) at two monitoring sites for a period spanning approximately 2 years to determine the similarities and differences between the measurement outputs of both instrumental systems. Due mainly to mass loss observed with the TEOM-SES in cooler months, the province has recently switched its PM_2.5 instrumentation at all stations in its monitoring network from the TEOM-SES to the SHARP 5030, which has the U.S. Environmental Protection Agency (EPA) Federal Equivalent Method (FEM) Class III designation. Thus, it has become imperative to develop corrections for historical and future TEOM measurements for the purpose of making them more agreeable to the new FEM method. This work details the authors’ multiple linear regression analyses (MLRAs) of particulate matter data from both instrumental monitors, with the inclusion of operational parameters of physicochemical relevance for both cases of transformations of historical TEOM and TEOM measurements to be made in the future. For historical TEOM data, it was observed that the transformations only benefited winter and fall months. Furthermore, comparisons of the transformed historical TEOM data with PM_2.5 concentrations determined from the Federal Reference Method (FRM) sampler at seven locations within the province showed marked improvements over the observed TEOM-FRM comparisons.

Implications:This work provides a path to correcting the historically observed underreporting of particulate mass in winter and fall in Ontario by making the TEOM-based continuous data resemble the new FEM outputs (in this case, more SHARP-like). It is possible that the transformation of mainly winter TEOM data as detailed in this work may potentially lead to revisions in historical annual composite mean PM_2.5 concentrations and total annual number of days PM_2.5 exceeded the Canada-wide Standard (CWS) metric across the province.