Spatial variability of PM2.5 in urban areas in the United States

Data from the U.S. Environmental Protection Agency's Aerometric Information Retrieval System (now known as the Air Quality System) database for 1999 and 2000 have been used to characterize the spatial variability of concentrations of particulate matter with aerodynamic diameter < or = 2.5 microg (PM2.5) in 27 urban areas across the United States. Different measures were used to quantify the degree of uniformity of PM2.5 concentrations in the urban areas characterized. It was observed that PM2.5 concentrations varied to differing degrees in the urban areas examined. Analyses of several urban areas in the Southeast indicated high correlations between site pairs and spatial uniformity in concentration fields. Considerable spatial variation was found in other regions, especially in the West. Even within urban areas in which all site pairs were highly correlated, a variable degree of heterogeneity in PM2.5 concentrations was found. Thus, even though concentrations at pairs of sites were highly correlated, their concentrations were not necessarily the same. These findings indicate that the potential for exposure misclassification errors in time-series epidemiologic studies exists.     

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.     

Assessing source characteristics of PM2.5 in the eastern United States using positive matrix factorization

Fine aerosol (PM2.5) measurements obtained from the first year of operation of the nationwide network of PM2.5 monitors were studied with the factor analysis technique of positive matrix factorization (PMF). PM2.5 mass concentration data were extracted from the Atmospheric Information Retrieval System (AIRS) database of the U.S. Environmental Protection Agency (EPA). PMF was applied to measurements at more than 350 monitoring locations in the eastern half of the United States. Data consisted of PM2.5 24-hr averaged concentrations measured every third day from April through December 1999. The PMF model suggested six factors representing source influences to the PM2.5 mass concentrations at measurement sites. Factor 5, covering much of the Appalachian states, exhibited significant seasonal behavior.     

Evaluation of Time-Resolved PM2.5 Data in Urban/Suburban Areas of New Jersey

ABSTRACT

Time-resolved data is needed for public notification of unhealthful air quality and to develop an understanding of atmospheric chemistry, including insights important to control strategies. In this research, continuous fine particulate matter (PM_2.5) mass concentrations were measured with tapered element oscillating microbalances (TEOMs) across New Jersey from July 1997 to June 1998. Data features indicating the influence of local sources and long-distance transport are examined, as well as differences between 1-hr maxima and 24-hr average concentrations that might be relevant to acute health effects. Continuous mass concentrations were not significantly different from filter-collected gravimetric mass concentrations with 95% confidence intervals during any season. Annual mean PM_2.5 concentrations from July 1997 to June 1998 were 17.3, 16.4, 14.1, and 15.3 μg/m³ at Newark, Elizabeth, New Brunswick, and Camden, NJ, respectively. Monthly averaged 24- and 1-hr daily maximum PM_2.5 concentrations suggest the existence of a high PM_2.5 (May-October) and a low PM_2.5 (November-April) season.

PM_2.5 magnitudes and temporal trends were very similar across the state during high PM_2.5 events. In fact, the between-site coefficients of determination (R²) for daily PM_2.5 measurements were 84-98% for June and July. Additionally, during the most pronounced PM_2.5 episode, PM_2.5 concentrations closely tracked the daily maximum 1-hr O₃ concentrations. These observations suggest the importance of transport and atmospheric chemistry (i.e., secondary formation) to PM_2.5 episodes in New Jersey. The influence of local sources was observed in diurnal concentration profiles and annual average between-site differences. Urban wintertime data illustrate that high 1-hr maximum PM_2.5 concentrations can occur on low 24-hr PM_2.5 days.     

Correlations between fine particulate matter (PM2.5) and meteorological variables in the United States: Implications for the sensitivity of PM2.5 to climate change

We applied a multiple linear regression (MLR) model to study the correlations of total PM_2.5 and its components with meteorological variables using an 11-year (1998–2008) observational record over the contiguous US. The data were deseasonalized and detrended to focus on synoptic-scale correlations. We find that daily variation in meteorology as described by the MLR can explain up to 50% of PM_2.5 variability with temperature, relative humidity (RH), precipitation, and circulation all being important predictors. Temperature is positively correlated with sulfate, organic carbon (OC) and elemental carbon (EC) almost everywhere. The correlation of nitrate with temperature is negative in the Southeast but positive in California and the Great Plains. RH is positively correlated with sulfate and nitrate, but negatively with OC and EC. Precipitation is strongly negatively correlated with all PM_2.5 components. We find that PM_2.5 concentrations are on average 2.6 μg m^?3 higher on stagnant vs. non-stagnant days. Our observed correlations provide a test for chemical transport models used to simulate the sensitivity of PM_2.5 to climate change. They point to the importance of adequately representing the temperature dependence of agricultural, biogenic and wildfire emissions in these models.     

Effects of SO2 and NOx emission reductions on PM2.5 mass concentrations in the southeastern United States

Measurements from sites of the Southeastern Aerosol Research and Characterization (SEARCH) program, made from 1998 to 2001, are used with a thermodynamic equilibrium model, Simulating Composition of Atmospheric Particles at Equilbrium (SCAPE2), to extend an earlier investigation of the responses of fine particulate nitrate (NO3-) and fine particulate matter (PM2.5) mass concentrations to changes in concentrations of nitric acid (HNO3) and sulfate (SO42-). The responses were determined for a projected range of variations of SO42- and HNO3 concentrations resulting from adopted and proposed regulatory initiatives. The predicted PM2.5 mass concentration decreases averaged 1.8-3.9 microg/m3 for SO42- decreases of 46-63% from current concentrations. Combining the S042- decrease with a 40% HNO3 decrease from current concentrations (approximating expected mobile-source oxides of nitrogen [NOx] reductions by 2020) yielded additional incremental reductions of mean predicted PM2.5 mass concentration of 0.2 microg/m3 for three nonurban sites and 0.8-1 microg/m3 for one nonurban and two urban sites. Increasing the HNO3 reduction to 55% (an estimate of adding Clear Skies Phase II NOx reductions) yielded additional incremental reductions of mean predicted PM2.5 mass concentration of 0-0.4 microg/m3. Because of the well-documented losses of particulate NO3- from Federal Reference Method (FRM) filters, only a fraction of these incremental changes would be observed.     

Real-time bias-adjusted O3 and PM2.5 air quality index forecasts and their performance evaluations over the continental United States

The National Air Quality Forecast Capacity (NAQFC) system, which links NOAA’s North American Mesoscale (NAM) meteorological model with EPA’s Community Multiscale Air Quality (CMAQ) model, provided operational ozone (O₃) and experimental fine particular matter (PM_2.5) forecasts over the continental United States (CONUS) during 2008. This paper describes the implementation of a real-time Kalman Filter (KF) bias-adjustment technique to improve the accuracy of O₃ and PM_2.5 forecasts at discrete monitoring locations. The operational surface-level O₃ and PM_2.5 forecasts from the NAQFC system were post-processed by the KF bias-adjusted technique using near real-time hourly O₃ and PM_2.5 observations obtained from EPA’s AIRNow measurement network. The KF bias-adjusted forecasts were created daily, providing 24-h hourly bias-adjusted forecasts for O₃ and PM_2.5 at all AIRNow monitoring sites within the CONUS domain. The bias-adjustment post-processing implemented in this study requires minimal computational cost; requiring less than 10 min of CPU on a single processor Linux machine to generate 24-h hourly bias-adjusted forecasts over the entire CONUS domain.The results show that the real-time KF bias-adjusted forecasts for both O₃ and PM_2.5 have performed as well as or even better than the previous studies when the same technique was applied to the historical O₃ and PM_2.5 time series from archived AQF in earlier years. Compared to the raw forecasts, the KF forecasts displayed significant improvement in the daily maximum 8-h O₃ and daily mean PM_2.5 forecasts in terms of both discrete (i.e., reduced errors, increased correlation coefficients, and index of agreement) and categorical (increased hit rate and decreased false alarm ratio) evaluation metrics at almost all locations during the study period in 2008.     

Spatial PM2.5 mobile source impacts using a calibrated indicator method

Motor vehicles are major sources of fine particulate matter (PM_2.5), and the PM_2.5 from mobile vehicles is associated with adverse health effects. Traditional methods for estimating source impacts that employ receptor models are limited by the availability of observational data. To better estimate temporally and spatially resolved mobile source impacts on PM_2.5, we developed an approach based on a method that uses elemental carbon (EC), carbon monoxide (CO), and nitrogen oxide (NO_x) measurements as an indicator of mobile source impacts. We extended the original integrated mobile source indicator (IMSI) method in three aspects. First, we generated spatially resolved indicators using 24-hr average concentrations of EC, CO, and NO_x estimated at 4 km resolution by applying a method developed to fuse chemical transport model (Community Multiscale Air Quality Model [CMAQ]) simulations and observations. Second, we used spatially resolved emissions instead of county-level emissions in the IMSI formulation. Third, we spatially calibrated the unitless indicators to annually-averaged mobile source impacts estimated by the receptor model Chemical Mass Balance (CMB). Daily total mobile source impacts on PM_2.5, as well as separate gasoline and diesel vehicle impacts, were estimated at 12 km resolution from 2002 to 2008 and 4 km resolution from 2008 to 2010 for Georgia. The total mobile and separate vehicle source impacts compared well with daily CMB results, with high temporal correlation (e.g., R ranges from 0.59 to 0.88 for total mobile sources with 4 km resolution at nine locations). The total mobile source impacts had higher correlation and lower error than the separate gasoline and diesel sources when compared with observation-based CMB estimates. Overall, the enhanced approach provides spatially resolved mobile source impacts that are similar to observation-based estimates and can be used to improve assessment of health effects.

Implications: An approach is developed based on an integrated mobile source indicator method to estimate spatiotemporal PM_2.5 mobile source impacts. The approach employs three air pollutant concentration fields that are readily simulated at 4 and 12 km resolutions, and is calibrated using PM_2.5 source apportionment modeling results to generate daily mobile source impacts in the state of Georgia. The estimated source impacts can be used in investigations of traffic pollution and health.     

Analysis of PM10 Trends in the United States from 1988 through 1995

ABSTRACT

Because the U. S. Environmental Protection Agency (EPA) has changed the National Ambient Air Quality Standards (NAAQS) for ambient particulate matter (PM), there is a great deal of interest in determining recent PM trends. This paper examines trends in PM₁₀ (i.e., particulate matter less than 10 micrometers in diameter) for areas of the United States based on their attainment status—for PM₁₀ and ozone nonattainment and attainment areas. The analysis also focuses on urban, suburban, and rural areas, and eastern and western areas. The time period of evaluation is from 1988 through 1995. To shed further light on the ambient PM₁₀ trends, trends in ambient SO₂, NO₂, and volatile organic compounds (VOCs) are also analyzed. Finally, trends in emission inventories of SO₂, NO_x, VOCs, and PM₁₀ are evaluated. Results of the analysis show that widespread and similar reductions in PM₁₀ levels have occurred over the last seven years. Annual reductions range from 3.0% to 3.8%, with the greatest reductions coming in PM₁₀ nonattainment areas, but with very significant reductions also in PM₁₀ attainment areas, ozone attainment areas, and rural areas. The widespread reductions appear to be due to a set of controls or common factors that are having a fairly uniform effect in all of the areas. The consistency of the reductions in different areas suggests that the reductions may also be primarily in the fine particles (i.e., those less than 2.5 micrometers in diameter, or PM_2.5), which are more readily transported than coarse particles.     

关于PM2.5的综述

综述了大气PM25的来源,样品采集分析,化学组成,病毒机理,对人类健康和大气能见度的影响,以及国内外的研究进展.     

A consistent method for modelling PM10 and PM2.5 concentrations across the United Kingdom in 2004 for air quality assessment

A modelling method has been developed to map PM₁₀ and PM_2.5 concentrations across the UK at background and roadside locations. Separate models have been calibrated using gravimetric measurements and Tapered Element Oscillating Microbalance instruments (TEOM) using source apportionments appropriate to the size fractions and sampling methods. Maps have been prepared for a base year of 2004 and predictions have been calculated for 2010 and 2020 on the basis of current policies. Comparisons of the modelling results with air quality regulations suggest that exceedences of the EU Daughter Directive stage 1 24-h limit value for PM₁₀ at the roadside in 2004 will be largely eliminated by 2020. The concentration cap of 25 μg m⁻³ for PM_2.5 proposed within the CAFÉ Directive is expected to be met at all locations. Projections for 2010 and 2020 suggest that the proposed exposure reduction (ER) target is likely to be considerably more stringent and require additional measures beyond current policies. Thus the model results suggest that the balance between the stringency of the concentration cap and the ER target in the proposed directive is appropriate. Measures to achieve greater reductions should therefore have the maximum public health benefit and air quality policy is not driven by the need to reduce concentrations at isolated ‘hotspots’.     

Spatial and temporal variability in outdoor,indoor, and personal PM2.5 exposure

Outdoor, indoor and personal PM_2.5 measurements were made in a population of nonsmoking adults from three communities in the Minneapolis–St. Paul metropolitan area between April and November 1999. Thirty-two healthy adult subjects (23 females, 9 males; mean age 42±10, range: 24–64 yr) were monitored for 2–15 days during the spring, summer, and fall monitoring seasons. Twenty-four hour average gravimetric PM_2.5 samples were collected using a federal reference monitor (Anderson RAAS2.5-300) located at outdoor (O) central sites in the Battle Creek (BCK), East St. Paul (ESP) and Phillips (PHI) communities. Concurrent 24-h average indoor (I) and personal (P), and a limited number of outdoor-at-home (O@H) samples were collected using inertial impactors (PEM™ Model 200, MSP, Inc). The O (geometric mean {GM}=8.6; n=271; range: 1.0–41 μg/m³) were lower than I concentrations (GM=10.7; n=294; range 1.3–131 μg/m³), which were lower than P concentrations (GM=19.0; n=332; range 2.2–298 μg/m³). Correlation coefficients between O concentrations in the three communities were high and measured GM O levels in BCK were significantly lower than ESP, most likely because of local sources, but GM concentrations in PHI were not significantly different from BCK or ESP. On days with paired samples (n=29), O concentrations were significantly lower (mean difference 2.9 μg/m³; p=0.026) than O@H measurements (GM=11.3; range: 3.5–33.8 μg/m³), likely due to local sources in communities. Observed I and P concentrations were more variable, probably because of residential central air conditioning and hours of household ventilation for I and P, and occupational and environmental tobacco smoke exposures outside the residence for P. Across all individuals and days the median PM_2.5 “personal cloud” was 5.7 μg/m³, but the mean of the average for each participant was 15.7 μg/m³, with very low values in participants who did not work outside the home and much higher values in subjects with active lifestyles. Across all households and individuals the correlation between P and O concentrations was not significant, but the overall I–O correlation (0.27) and P–I correlation (0.51) were significant (p<0.05). Relatively little spatial variability was observed in O PM_2.5 concentrations across the three communities compared to the variability associated with I and P samples, and the measured O levels were relatively low compared to other large metropolitan areas in the United States.     

Spatial and seasonal variation of outdoor BC and PM2.5 in densely populated urban slums

Environmental Science and Pollution Research - A large proportion of residents in urban centers of low- and middle-income countries live in low-socioeconomic neighborhoods called...     

Spatial and temporal characterization of PM2.5 mass concentrations in California, 1980-2007

Systematic measurement of fine particulate matter (aerodynamic diameter less than 2.5 microm [PM2.5]) mass concentrations began nationally with implementation of the Federal Reference Method (FRM) network in 1998 and 1999. In California, additional monitoring of fine particulate matter (PM) occurred via a dichotomous sampler network and several special studies carried out between 1982 and 2002. The authors evaluate the comparability of FRM and non-FRM measurements of PM2.5 mass concentrations and establish conversion factors to standardize fine mass measurements from different methods to FRM-equivalent concentrations. The authors also identify measurements of PM2.5 mass concentrations that do not agree with FRM or other independent PM2.5 mass measurements. The authors show that PM2.5 mass can be reconstructed to a high degree of accuracy (r2 > 0.9; mean absolute error approximately 2 microg m(-3)) from PM with an aerodynamic diameter < or =10 microm (PM10) mass and species concentrations when site-specific and season-specific conversion factors are used and a statewide record of fine PM mass concentrations by combining the FRM PM2.5 measurements, non-FRM PM2.5 measurements, and reconstructions of PM2.5 mass concentrations. Trends and spatial variations are evaluated using the integrated data. The rates of change of annual fine PM mass were negative (downward trends) at all 22 urban and 6 nonurban (Interagency Monitoring of Protected Visual Environments [IMPROVE]) monitoring locations having at least 15 yr of data during the period 1980-2007. The trends at the IMPROVE sites ranged from -0.05 to -0.25 microg m(-3) yr(-1) (median -0.11 microg m(-3) yr(-1)), whereas urban-site trends ranged from -0.13 to -1.29 microg m(-3) yr(-1) (median -0.59 microg m(-3) yr(-1)). The urban concentrations declined by a factor of 2 over the period of record, and these decreases were qualitatively consistent with changes in emissions of primary PM2.5 and gas-phase precursors of secondary PM. Mean PM2.5 mass concentrations ranged from 3.3 to 7.4 microg m(-3) at IMPROVE sites and from 9.3 to 37.1 microg m(-3) at urban sites.     

Spatial and temporal variations in PM10 and PM2.5 source contributions and comparison to emissions during the 1995 integrated monitoring study

The ambient PM₁₀ and PM_2.5 data collected during the fall and winter portions of the 1995 Integrated Monitoring Study (IMS95) were used to conduct Chemical Mass Balance (CMB) Modeling to determine source contribution estimates. Data from the core and saturation monitoring sites provided an extensive database for evaluating the spatial and temporal variations of contributing sources. Geological sources dominated fall samples, while secondary ammonium nitrate and carbonaceous sources were the largest contributors for winter samples. Secondary ammonium nitrate concentrations were uniform across all sites during both the fall and winter. Site-to-site variability was primarily due to differences in geological contributions in the fall, and carbonaceous source contributions in the winter. During the winter, diurnal profiles of particulate matter (PM) were driven by variations in carbonaceous sources at urban sites, and by variations in secondary ammonium nitrate at rural sites. Although records of day-specific PM activities were recorded during the study, no correlation was observed between 24-h CMB results and specific activities. The ambient data collected during IMS95 was also used to evaluate the adequacy of the emissions inventory. Comparison of ambient and emissions based ratios of NMHC/NO_x, PM/NO_x, CO/NO_x, and SO_x/NO_x suggested that emissions of NMHC and CO in some locations may be underestimated, while emissions for PM and SO_x may be overestimated. Comparison of fractional primary CMB source contribution estimates to corresponding fractional emissions estimates indicated that geological sources were overemphasized in the inventory, while carbonaceous sources were underrepresented.     

Levoglucosan in PM2.5 at the Fresno supersite

Ambient air monitoring for PM2.5 has been conducted on a daily basis at the Fresno, CA, supersite since 1999. It has been found that PM2.5 concentrations routinely exceed the National Ambient Air Quality Standards during the winter months. In an effort to determine the effect of biomass burning on PM2.5 concentrations, samples during 2000 were analyzed for levoglucosan, palmitic acid, and stearic acid. The results of this study are presented.     

Spatial and temporal distributions of airborne sulfate in parts of the United States

The current knowledge of the spatial and temporal distribution of airborne, water soluble sulfate is surveyed for two “scales” of atmospheric activity. The “urban” scale with episodes extending over a day or two over distances of about 100 km is illustrated for two comparable American cities, Los Angeles and New York. The regional scale with episodes extending up to several days over distances of 1000 km is exemplified by case studies in the greater eastern United States. Examination of available data reveals several features of the spatial and temporal variation in sulfate occurrence, including seasonal changes, and correlations with aerometric parameters. The importance of water vapor and air mass character on sulfate concentrations is assessed in both the urban and regional conditions. The results of initial attempts to simulate the impact of sulfur oxide emissions on ambient sulfate distributions are compared with an episode case extending over several days in July 1974.     

Governmental Provisions to Manage and Eradicate Feral Swine in Areas of the United States

Feral swine (wild hogs) are one of the most widely distributed free-ranging mammals in the world. In the United States, feral swine serve as game animals for the sport of hunting in some areas, while they are nuisance species at other locations. Increasing feral swine populations creates negative impacts to growing crops, native plant communities, and wildlife. Feral swine can also serve as reservoirs for a number of bacterial and viral diseases that can infect wild animals, livestock, and humans. The US state governments are adopting statutes and regulations to reduce the growth and dispersal of feral swine populations. An analysis of these provisions suggests that while they seek to control feral swine populations, they are unlikely to provide any significant relief from damages to crops and native ecosystems. More localized reduction plans and a national disease control program are suggested to assuage damages being wrought by these invasive animals.     

Semi-volatile species in PM2.5: comparison of integrated and continuous samplers for PM2.5 research or monitoring

Fine particles in urban atmospheres contain substantial quantities of semi-volatile material [e.g., NH4NO3 and semi-volatile organic compounds (SVOCs)] that are lost from particles during collection on a filter. Several diffusion denuder samplers have been developed for the determination of both NO3- and organic semi-volatile fine particulate components. The combination of technology used in the BOSS diffusion denuder sampler and the Harvard particle concentrator has resulted in the Particle Concentrator-Brigham Young University Organic Sampling System (PC-BOSS) for the 24-hr (or less) integrated collection of PM2.5, including NH4NO3 and semi-volatile organic material. Modification of the BOSS sampler allows for the weekly determination of these same species. Combination of BOSS denuder and tapered element oscillating microbalance (TEOM) monitor technology has resulted in the real-time ambient mass sampler (RAMS) for the continuous measurement of PM2.5, including the semi-volatile components. Comparison of the results obtained with the BOSS and with each of the newly developed modifications of the BOSS indicates that the modified versions can be used for the continuous, daily, or weekly monitoring of PM2.5, including semi-volatile species, as appropriate to the design of each sampler.