A performance evaluation of the National Air Quality Forecast Capability for the summer of 2007

This paper provides a performance evaluation of the real-time, CONUS-scale National Air Quality Forecast Capability (NAQFC) that supported, in part, its transition into operational status. This evaluation focuses primarily on discrete forecasts for the maximum 8-h O₃ concentrations covering the 4-month period, June through September, 2007, using measurements obtained from EPA's AIRNow network. Results indicate that the 2007 NAQFC performed as well or better than previous configurations, despite the expansion of the forecast domain into the western half of the nation that is dominated by complex terrain. The mean, domain-wide, season-long correlation was 0.70. When examined over time, the domain-wide correlations exhibit a fairly consistent nature, with values exceeding 0.60 (0.70) over 90% (55%) of the days. The NAQFC systematically over-predicted the 8-h O₃ concentrations, continuing a trend established by earlier NAQFC configurations, though to a lesser degree. The summer-long mean forecast value of 53.2 ppb was 4.2 ppb higher than the observed value, resulting in a domain-wide Normalized Mean Bias (NMB) of 8.7%. Most of the over-prediction is associated with observed concentrations less than 50 ppb. In fact the model tends to under-predict when concentrations exceed 70 ppb. As with the bias, the error associated with the latest configuration was also lower. The summer-long Root Mean Square Error of 13.0 ppb (Normalized Mean Error (NME) = 20.4%) represented marked improvements over earlier forecasts. Examination of the spatial distribution of both the NMB and NME reveals that the NAQFC was generally within 25% for the NME and 25% for the NMB over a majority of the domain. Several areas of poorer performance, where the NMB and NME often exceed 25% and in some cases 50%, were noted. These areas include southern California, where the NAQFC tended to under-predict concentrations (especially on weekends) and the southeast Atlantic and Gulf coasts regions, where the model over-predicted. Subsequent analysis revealed that the incorrect temporal allocation of precursor emissions was likely the source of the under-prediction in southern California, while inaccurate simulation of PBL heights likely contributed to the over-prediction in the coastal regions.     

A comparative performance evaluation of the AURAMS and CMAQ air-quality modelling systems

A harmonized comparative performance evaluation of A Unified Regional Air-quality Modelling System (AURAMS) v1.3.1b and Community Multiscale Air Quality (CMAQ) v4.6 air-quality modelling systems was conducted on the same North American grid for July 2002 using the same emission inventories, emissions processor, and input meteorology.Comparison of AURAMS- and CMAQ-predicted O₃ concentrations against hourly surface measurement data showed a lower normalized mean bias (NMB) of 20.7% for AURAMS versus 46.4% for CMAQ. However, AURAMS and CMAQ had more similar normalized mean errors (NMEs) of 46.9% and 54.2%, respectively. Both models did similarly well in predicting daily 1-h O₃ maximums; however, AURAMS performed better in calculating daily minimums. CMAQ's poorer performance for O₃ is partly due to its inability to correctly predict nighttime lows.Total PM_2.5 hourly surface concentration was under-predicted by both AURAMS and CMAQ with NMBs of ?10.4% and ?65.2%, respectively. However, as with O₃, both models had similar NMEs of 68.0% and 70.6%, respectively. In general, AURAMS performance was better than CMAQ for all major PM_2.5 species except nitrate and elemental carbon. Both models significantly under-predicted total organic aerosols (TOAs), although the mean AURAMS concentration was over four times larger than CMAQ's. The under-prediction of TOA was partly due to the exclusion of forest-fire emissions. Sea-salt aerosol made up approximately 50.2% of the AURAMS total PM_2.5 surface concentration versus only 6.2% in CMAQ when averaged over all grid cells. When averaged over land cells only, sea-salt still contributed 13.9% to the total PM_2.5 mass in AURAMS versus 2.0% in CMAQ.     

Development and implementation of a remote-sensing and in situ data-assimilating version of CMAQ for operational PM2.5 forecasting. Part 1: MODIS aerosol optical depth (AOD) data-assimilation design and testing

This two-part paper reports on the development, implementation, and improvement of a version of the Community Multi-Scale Air Quality (CMAQ) model that assimilates real-time remotely-sensed aerosol optical depth (AOD) information and ground-based PM_2.5 monitor data in routine prognostic application. The model is being used by operational air quality forecasters to help guide their daily issuance of state or local-agency-based air quality alerts (e.g. action days, health advisories). Part 1 describes the development and testing of the initial assimilation capability, which was implemented offline in partnership with NASA and the Visibility Improvement State and Tribal Association of the Southeast (VISTAS) Regional Planning Organization (RPO). In the initial effort, MODIS-derived aerosol optical depth (AOD) data are input into a variational data-assimilation scheme using both the traditional Dark Target and relatively new “Deep Blue” retrieval methods. Evaluation of the developmental offline version, reported in Part 1 here, showed sufficient promise to implement the capability within the online, prognostic operational model described in Part 2. In Part 2, the addition of real-time surface PM_2.5 monitoring data to improve the assimilation and an initial evaluation of the prognostic modeling system across the continental United States (CONUS) is presented.

Implications: Air quality forecasts are now routinely used to understand when air pollution may reach unhealthy levels. For the first time, an operational air quality forecast model that includes the assimilation of remotely-sensed aerosol optical depth and ground based PM_2.5 observations is being used. The assimilation enables quantifiable improvements in model forecast skill, which improves confidence in the accuracy of the officially-issued forecasts. This helps air quality stakeholders be more effective in taking mitigating actions (reducing power consumption, ride-sharing, etc.) and avoiding exposures that could otherwise result in more serious air quality episodes or more deleterious health effects.     

Improved space–time forecasting of next day ozone concentrations in the eastern US

There is an urgent need to provide accurate air quality information and forecasts to the general public and environmental health decision-makers. This paper develops a hierarchical space–time model for daily 8-h maximum ozone concentration (O₃) data covering much of the eastern United States. The model combines observed data and forecast output from a computer simulation model known as the Eta Community Multi-scale Air Quality (CMAQ) forecast model in a very flexible, yet computationally fast way, so that the next day forecasts can be computed in real-time operational mode. The model adjusts for spatio-temporal biases in the Eta CMAQ forecasts and avoids a change of support problem often encountered in data fusion settings where real data have been observed at point level monitoring sites, but the forecasts from the computer model are provided at grid cell levels. The model is validated with a large amount of set-aside data and is shown to provide much improved forecasts of daily O₃ concentrations in the eastern United States.     

Ensemble and bias-correction techniques for air quality model forecasts of surface O3 and PM2.5 during the TEXAQS-II experiment of 2006

Several air quality forecasting ensembles were created from seven models, running in real-time during the 2006 Texas Air Quality (TEXAQS-II) experiment. These multi-model ensembles incorporated a diverse set of meteorological models, chemical mechanisms, and emission inventories. Evaluation of individual model and ensemble forecasts of surface ozone and particulate matter (PM) was performed using data from 119 EPA AIRNow ozone sites and 38 PM sites during a 50-day period in August and September of 2006. From the original set of models, two new bias-corrected model data sets were built, either by applying a simple running mean average to the past 7 days of data or by a Kalman-Filter approach. From the original and two bias-corrected data sets, three ensembles were created by a simple averaging of the seven models. For further improvements three additional weighted model ensembles were created, where individual model weights were calculated using the singular value decomposition method. All six of the ensembles are compared to the individual models and to each other in terms of root mean square error, correlation, and contingency and probabilistic statistics. In most cases, each of the ensembles show improved skill compared to the best of the individual models. The over all best ensemble technique was found to be the combination of Kalman-Filtering and weighted averaging. PM_2.5 aerosol ensembles demonstrated significant improvement gains, mostly because the original model's skill was very low.     

Modeling an air pollution episode in northwestern United States: Identifying the effect of nitrogen oxide and volatile organic compound emission changes on air pollutants formation using direct sensitivity analysis

Air quality impacts of volatile organic compound (VOC) and nitrogen oxide (NO_x) emissions from major sources over the northwestern United States are simulated. The comprehensive nested modeling system comprises three models: Community Multiscale Air Quality (CMAQ), Weather Research and Forecasting (WRF), and Sparse Matrix Operator Kernel Emissions (SMOKE). In addition, the decoupled direct method in three dimensions (DDM-3D) is used to determine the sensitivities of pollutant concentrations to changes in precursor emissions during a severe smog episode in July of 2006. The average simulated 8-hr daily maximum O₃ concentration is 48.9 ppb, with 1-hr O₃ maxima up to 106 ppb (40 km southeast of Seattle). The average simulated PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm) concentration at the measurement sites is 9.06 μg m^?3, which is in good agreement with the observed concentration (8.06 μg m^?3). In urban areas (i.e., Seattle, Vancouver, etc.), the model predicts that, on average, a reduction of NO_x emissions is simulated to lead to an increase in average 8-hr daily maximum O₃ concentrations, and will be most prominent in Seattle (where the greatest sensitivity is??0.2 ppb per % change of mobile sources). On the other hand, decreasing NO_x emissions is simulated to decrease the 8-hr maximum O₃ concentrations in remote and forested areas. Decreased NO_x emissions are simulated to slightly increase PM_2.5 in major urban areas. In urban areas, a decrease in VOC emissions will result in a decrease of 8-hr maximum O₃ concentrations. The impact of decreased VOC emissions from biogenic, mobile, nonroad, and area sources on average 8-hr daily maximum O₃ concentrations is up to 0.05 ppb decrease per % of emission change, each. Decreased emissions of VOCs decrease average PM_2.5 concentrations in the entire modeling domain. In major cities, PM_2.5 concentrations are more sensitive to emissions of VOCs from biogenic sources than other sources of VOCs. These results can be used to interpret the effectiveness of VOC or NO_x controls over pollutant concentrations, especially for localities that may exceed National Ambient Air Quality Standards (NAAQS).

Implications: The effect of NO_x and VOC controls on ozone and PM_2.5 concentrations in the northwestern United States is examined using the decoupled direct method in three dimensions (DDM-3D) in a state-of-the-art three-dimensional chemical transport model (CMAQ). NO_x controls are predicted to increase PM_2.5 and ozone in major urban areas and decrease ozone in more remote and forested areas. VOC reductions are helpful in reducing ozone and PM_2.5 concentrations in urban areas. Biogenic VOC sources have the largest impact on O₃ and PM_2.5 concentrations.     

Evaluation of the SO2 and NOX offset ratio method to account for secondary PM2.5 formation

The U.S. Environmental Protection Agency (EPA), state and local agencies have focused their efforts in assessing secondary fine particulate matter (aerodynamic diameter ≤2.5 µm; PM_2.5) formation in prevention of significant deterioration (PSD) air dispersion modeling. The National Association of Clean Air Agencies (NACAA) developed a method to account for secondary PM_2.5 formation by using sulfur dioxide (SO₂) and nitrogen oxides (NO_x) offset ratios. These ratios are used to estimate the secondary formation of sulfate and nitrate PM_2.5. These ratios were first introduced by the EPA for nonattainment areas in the Implementation of the New Source Review (NSR) Program for Particulate Matter Less than 2.5 Micrometers (PM_2.5), 73 FR 28321, to offset emission increases of direct PM_2.5 emissions with reductions of PM_2.5 precursors and vice versa. Some regulatory agencies such as the Minnesota Pollution Control Agency (MPCA) have developed area-specific offset ratios for SO₂ and NO_x based on Comprehensive Air Quality Model with Extensions (CAMx) evaluations for air dispersion modeling analyses. The current study evaluates the effect on American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) predicted concentrations from the use of EPA and MPCA developed ratios. The study assesses the effect of these ratios on an electric generating utility (EGU), taconite mine, food processing plant, and a pulp and paper mill. The inputs used for these four scenarios are based on common stack parameters and emissions based on available data. The effect of background concentrations also evaluates these scenarios by presenting results based on uniform annual PM_2.5 background values. This evaluation study helps assess the viability of the offset ratio method developed by NACAA in estimating primary and secondary PM_2.5 concentrations. An alternative Tier 2 approach to combine modeled and monitored concentrations is also presented.

Implications:

On January 4, 2012, the EPA committed to engage in rulemaking to evaluate updates to the Guideline on Air Quality Models (Appendix W of 40 CFR 51) and, as appropriate, incorporate new analytical techniques or models for secondary PM_2.5. As a result, the National Association of Clean Air Agencies (NACAA) developed a screening method involving offset ratios to account for secondary PM_2.5 formation. The use of this method is promising to evaluate total (direct and indirect) PM_2.5 impacts for permitting purposes. Therefore, the evaluation of this method is important to determine its viability for widespread use.     

An extended approach to calculate the ozone relative response factors used in the attainment demonstration for the National Ambient Air Quality Standards

With the promulgation of the National Ambient Air Quality Standards (NAAQS or standard) for 8-hr ozone (O₃), the U.S. Environmental Protection Agency (EPA) issued modeling guidance that advocated the use of results from photochemical air quality models in a relative sense. In doing so, the EPA provided guidance on how to calculate relative response factors (RRFs) that can project current design value (DV) mixing ratios into the future for the purpose of determining the attainment status with respect to the O₃ standard. The RRFs recommended by the EPA represent the average response of the photochemical model over a broad range of O₃ mixing ratios above a specified cutoff threshold. However, it is known that O₃ response to emission reductions of limiting precursors (i.e., NO_x and/or VOC) is greater on days with higher O₃ mixing ratios compared to days with lower mixing ratios. In this study, we present a segmented RRF concept termed band-RRF, which takes into account the different model responses at different O₃ mixing ratios. The new band-RRF concept is demonstrated in the San Joaquin Valley (SJV) region of California for the 1-hr and 8-hr O₃ standards. The 1-hr O₃ analysis is relevant to work done in support of the SJV O₃ State Implementation Plan (SIP) submitted to the EPA in 2013. The 8-hr example for the future year of 2019 is presented for illustrative purposes only. Further work will be conducted with attainment deadline of 2032 as part of upcoming SIPs for the 0.075 parts per million (ppm) 8-hr O₃ standard. The applicability of the band-RRF concept to the particulate matter (PM_2.5) standards is also discussed.

Implications:Results of photochemical models are used in regulatory applications in a relative sense using relative response factors (RRFs), which represent the impacts of emissions reductions over a wide range of ozone (O₃) values. It is possible to extend the concept of RRFs to account for the fact that higher O₃ mixing ratios (both 1-hr and 8-hr) respond more to emissions controls of limiting precursors than do lower O₃ mixing ratios. We demonstrate this extended concept, termed band-RRF, for the 1-hr and 8-hr O₃ National Ambient Air Quality Standard (NAAQS or standard) in the San Joaquin Valley of California. This extension can also be made applicable to the 24-hr PM_2.5 and annual PM_2.5 standards.     

Delineation of air-quality basins utilizing multivariate statistical methods in Taiwan

This study analyzed time-series data of air pollutants, O₃ and PM₁₀, to determine the division of air-quality basins in Taiwan by employing multivariate statistical methods, Varimax rotational method and cluster analysis. The databases of air pollutants, daily maximum 1-h O₃ and daily mean PM₁₀ concentrations, were obtained from the ROC Environmental Protection Administration (ROC EPA) for the period from 1 July 1993 to 30 June 1998. The Varimax rotational method allowed us to delineate five homogenous PM₁₀ subregions that cumulatively accounted for 85.6% of the total variance. The time-series analysis of rotated component scores associated with the PM₁₀ subregions revealed that all divided subregions presented a strong seasonal cycle. Four of five subregions had higher component scores and PM₁₀ concentrations from November to January. One subregion experienced higher values from March to May. The use of Varimax approach and cluster analysis on the O₃ and PM₁₀ confirmed that O₃ was more demonstrative of the air-quality basins in Taiwan. Both the Varimax rotational method and the cluster analysis have specific advantages for the division of air-quality basins. This study also proposes a delineation of five air-quality basins having homogenous O₃ features as an alternative assignment of atmospheric carrying capacity control regions.     

Design of a Cost-Effective Weighing Facility for PM2.5 Quality Assurance

Abstract

The U.S. Environmental Protection Agency (EPA) Quality Assurance (QA) Guidance Document 2.12: Monitoring PM_2.5 in Ambient Air Using Designated Reference or Class I Equivalent Methods¹ (Document 2.12) requires conditioning of PM_2.5 filters at 20-23 °C and 30-40% relative humidity (RH) for 24 hr prior to gravimetric analysis. Variability of temperature and humidity may not exceed ±2 °C and ±5% RH during the conditioning period. The quality assurance team at EPA Region 2’s regional laboratory designed a PM_2.5 weighing facility that operates well within these strict performance requirements.

The traditional approach to meeting the performance requirements of Document 2.12 for PM_2.5 filter analysis is to build a walk-in room, with costs typically exceeding $100,000. The initial one-time capital cost for the laboratory at EPA’s Edison, NJ, facility was approximately $24,000. Annual costs [e.g., National Institute of Standards and Technology (NIST) recertifications and nitrogen replacement cylinders used for humidity control] are approximately $500. The average 24-hr variabilities in temperature and RH in the Region 2 weighing chamber are small, ±0.2 °C and ±0.8% RH, respectively. The mass detection limit for the PM_2.5 weighing system of 47-mm stretched Teflon (lab blank) filters is 6.3 μg. This facility demonstrates an effective and economical example for states and other organizations planning PM_2.5 weighing facilities.     

Responses of future air quality to emission controls over North Carolina,Part II: Analyses of future-year predictions and their policy implications

The MM5/CMAQ system evaluated in Part I paper is applied to study the impact of emission control on future air quality over North Carolina (NC). Simulations are conducted at a 4-km horizontal grid resolution for four one-month periods, i.e., January, June, July, and August 2009 and 2018. Simulated PM_2.5 in 2009 and 2018 show distribution patterns similar to those in 2002. PM_2.5 concentrations over the whole domain in January and July reduced by 5.8% and 23.3% in 2009 and 12.0% and 35.6% in 2018, respectively, indicating that the planned emission control strategy has noticeable effects on PM_2.5 reduction in this region, particularly in summer. More than 10% and 20% of 1-h and 8-h O₃ mixing ratios are reduced in July 2009 and 2018, respectively, demonstrating the effectiveness of emission control for O₃ reduction in summer. However, O₃ mixing ratios in January 2009 and 2018 increase by more than 5% because O₃ chemistry is VOC-limited in winter and the effect of NO_x reduction dominates over that of VOC reduction under such a condition. The projected emission control simulated at 4-km will reduce the number of sites in non-attainment for max 8-h O₃ from 49 to 23 in 2009 and to 1 in 2018 and for 24-h average PM_2.5 from 1 to 0 in 2009 and 2018 based on the latest 2008 O₃ and 2006 PM_2.5 standards. The variability in model predictions at different grid resolutions contributes to 1–3.8 ppb and 1–7.9 μg m^?3 differences in the projected future-year design values for max 8-h O₃ and 24-h average PM_2.5, respectively.     

Assessment of air quality benefits from national air pollution control policies in China. Part II: Evaluation of air quality predictions and air quality benefits assessment

Following the meteorological evaluation in Part I, this Part II paper presents the statistical evaluation of air quality predictions by the U.S. Environmental Protection Agency (U.S. EPA)’s Community Multi-Scale Air Quality (Models-3/CMAQ) model for the four simulated months in the base year 2005. The surface predictions were evaluated using the Air Pollution Index (API) data published by the China Ministry of Environmental Protection (MEP) for 31 capital cities and daily fine particulate matter (PM_2.5, particles with aerodiameter less than or equal to 2.5 μm) observations of an individual site in Tsinghua University (THU). To overcome the shortage in surface observations, satellite data are used to assess the column predictions including tropospheric nitrogen dioxide (NO₂) column abundance and aerosol optical depth (AOD). The result shows that CMAQ gives reasonably good predictions for the air quality.The air quality improvement that would result from the targeted sulfur dioxide (SO₂) and nitrogen oxides (NO_x) emission controls in China were assessed for the objective year 2010. The results show that the emission controls can lead to significant air quality benefits. SO₂ concentrations in highly polluted areas of East China in 2010 are estimated to be decreased by 30–60% compared to the levels in the 2010 Business-As-Usual (BAU) case. The annual PM_2.5 can also decline by 3–15 μg m^?3 (4–25%) due to the lower SO₂ and sulfate concentrations. If similar controls are implemented for NO_x emissions, NO_x concentrations are estimated to decrease by 30–60% as compared with the 2010 BAU scenario. The annual mean PM_2.5 concentrations will also decline by 2–14 μg m^?3 (3–12%). In addition, the number of ozone (O₃) non-attainment areas in the northern China is projected to be much lower, with the maximum 1-h average O₃ concentrations in the summer reduced by 8–30 ppb.     

The New England Air Quality Forecasting Pilot Program: Development of an Evaluation Protocol and Performance Benchmark

Abstract

The National Oceanic and Atmospheric Administration recently sponsored the New England Forecasting Pilot Program to serve as a “test bed” for chemical forecasting by providing all of the elements of a National Air Quality Forecasting System, including the development and implementation of an evaluation protocol. This Pilot Program enlisted three regional-scale air quality models, serving as prototypes, to forecast ozone (O₃) concentrations across the northeastern United States during the summer of 2002. A suite of statistical metrics was identified as part of the protocol that facilitated evaluation of both discrete forecasts (observed versus modeled concentrations) and categorical forecasts (observed versus modeled exceedances/nonexceedances) for both the maximum 1-hr (125 ppb) and 8-hr (85 ppb) forecasts produced by each of the models. Implementation of the evaluation protocol took place during a 25-day period (August 5–29), utilizing hourly O₃ concentration data obtained from over 450 monitors from the U.S. Environment Protection Agency’s Air Quality System network.     

Air Quality Measurements from the Fresno Supersite

ABSTRACT

The Fresno Supersite intends to 1) evaluate non-routine monitoring methods, establishing their comparability with existing methods and their applicability to air quality planning, exposure assessment, and health effects studies; 2) provide a better understanding of aerosol characteristics, behavior, and sources to assist regulatory agencies in developing standards and strategies that protect public health; and 3) support studies that evaluate relationships between aerosol properties, co-factors, and observed health end-points. Supersite observables include in-situ, continuous, short-duration measurements of 1) PM_2.5, PM₁₀, and coarse (PM₁₀ minus PM_2.5) mass; 2) PM_2.5 SO₄ ^-2, NO₃ ^-, carbon, light absorption, and light extinction; 3) numbers of particles in discrete size bins ranging from 0.01 to ~10μm; 4) criteria pollutant gases (O₃, CO, NO_x); 5) reactive gases (NO₂, NO_y, HNO₃, peroxyacetyl nitrate [PAN], NH₃); and 6) single particle characterization by time-of-flight mass spectrometry. Field sampling and laboratory analysis are applied for gaseous and particulate organic compounds (light hydrocarbons, heavy hydrocarbons, carbonyls, polycyclic aromatic hydrocarbons [PAH], and other semi-volatiles), and PM_2.5 mass, elements, ions, and carbon. Observables common to other Supersites are 1) daily PM_2.5 24-hr average mass with Federal Reference Method (FRM) samplers; 2) continuous hourly and 5-min average PM_2.5 and PM₁₀ mass with beta attenuation monitors (BAM) and tapered element oscillating microbalances (TEOM); 3) PM_2.5 chemical specia-tion with a U.S. Environmental Protection Agency (EPA) speciation monitor and protocol; 4) coarse particle mass by dichotomous sampler and difference between PM₁₀ and PM_2.5 BAM and TEOM measurements; 5) coarse particle chemical composition; and 6) high sensitivity and time resolution scalar and vector wind speed, wind direction, temperature, relative humidity, barometric pressure, and solar radiation. The Fresno Supersite is coordinated with health and toxicological studies that will use these data in establishing relationships with asthma, other respiratory disease, and cardiovascular changes in human and animal subjects.     

Difference in concentration trends of airborne particulate matter during rush hour on weekdays and Sundays in Tokyo,Japan

Suspended particulate matter (SPM) and fine particulate matter (less than or equal to 2.5 μm: PM_2.5) have generally been decreasing for the last decade in Tokyo, Japan. To elucidate the major cause of this decrease, the authors investigated the different trends of airborne particulates (both SPM and PM_2.5 concentrations) by evaluating comparisons based on the location of the monitoring stations (roadside vs. ambient), days of the week (weekdays vs. Sundays), and daily fluctuation patterns (2002 vs. 2010). Hourly mean SPM and PM_2.5 concentrations were obtained at four monitoring stations (two roadside stations, two ambient stations) in Tokyo, Japan. Annual mean concentrations of each day of the week and of each hour of the day from 2002 to 2010 were calculated. The results showed that (1) the daily differences in annual mean concentration decreased only at the two roadside monitoring stations; (2) the high hourly mean concentrations observed on weekdays during the daily rush hour at the two roadside monitoring stations observed in 2002 diminished in 2010; (3) the SPM concentration that decreased the most since 2002 was the PM_2.5 concentration; and (4) the fluctuation of hourly concentrations during weekdays at the two roadside monitoring stations decreased. A decreasing trend of airborne particulates during the daily rush hour in Tokyo, Japan, was observed at the roadside monitoring stations on weekdays since 2002. The decreasing PM_2.5 concentration resulted in this decreasing trend of airborne particulate concentrations during the daily rush hours on weekdays, which indicates fewer emissions were produced by diesel vehicles.

ImplicationsThe authors compared the trends of SPM and PM_2.5 in Tokyo by location (roadside vs. ambient), days of the week (weekdays vs. Sundays), and daily fluctuation patterns (2002 vs. 2010). The high hourly mean concentrations observed at the roadside location during rush hour on weekdays in 2002 diminished in 2010. The SPM concentration that decreased during rush hour the most was the PM_2.5 concentration. This significant decrease in the PM_2.5 concentration resulted in the general decreasing trend of SPM concentrations during the rush hours on weekdays, which indicates fewer emissions were produced from diesel vehicles.     

A Simple Methodology for the Determination of Back Trajectories

Abstract

This study comprehensively characterizes hourly fine particulate matter (PM_2.5) concentrations measured via a tapered element oscillating microbalance (TEOM), β-gauge, and nephelometer from four different monitoring sites in U.S. Environment Protection Agency (EPA) Region 5 (in U.S. states Illinois, Michigan, and Wisconsin) and compares them to the Federal Reference Method (FRM). Hourly characterization uses time series and autocorrelation. Hourly data are compared with FRM by averaging across 24-hr sampling periods and modeling against respective daily FRM concentrations. Modeling uses traditional two-variable linear least-squares regression as well as innovative nonlinear regression involving additional meteorological variables such as temperature and humidity. The TEOM shows a relationship with season and temperature, linear correlation as low as 0.7924 and nonlinear model correlation as high as 0.9370 when modeled with temperature. The β-gauge shows no relationship with season or meteorological variables. It exhibits a linear correlation as low as 0.8505 with the FRM and a nonlinear model correlation as high as 0.9339 when modeled with humidity. The nephelometer shows no relationship with season or temperature but a strong relationship with humidity is observed. A linear correlation as low as 0.3050 and a nonlinear model correlation as high as 0.9508 is observed when modeled with humidity. Nonlinear models have higher correlation than linear models applied to the same dataset. This correlation difference is not always substantial, which may introduce a tradeoff between simplicity of model and degree of statistical association. This project shows that continuous monitor technology produces valid PM_2.5 characterization, with at least partial accounting for variations in concentration from gravimetric reference monitors once appropriate nonlinear adjustments are applied. Although only one regression technically meets new EPA National Ambient Air Quality Standards (NAAQS) Federal Equivalent Method (FEM) correlation coefficient criteria, several others are extremely close, showing optimistic potential for use of this nonlinear adjustment model in garnering EPA NAAQS FEM approval for continuous PM_2.5 sampling methods.     

Projected changes in particulate matter concentrations in the South Coast Air Basin due to basin-wide reductions in nitrogen oxides,volatile organic compounds,and ammonia emissions

An ozone abatement strategy for the South Coast Air Basin (SoCAB) has been proposed by the South Coast Air Quality Management District (SCAQMD) and the California Air Resources Board (ARB). The proposed emissions reduction strategy is focused on the reduction of nitrogen oxide (NO_x) emissions by the year 2030. Two high PM_2.5 concentration episodes with high ammonium nitrate compositions occurring during September and November 2008 were simulated with the Community Multi-scale Air Quality model (CMAQ). All simulations were made with same meteorological files provided by the SCAQMD to allow them to be more directly compared with their previous modeling studies. Although there was an overall under-prediction bias, the CMAQ simulations were within an overall normalized mean error of 50%; a range that is considered acceptable performance for PM modeling. A range of simulations of these episodes were made to evaluate sensitivity to NO_x and ammonia emissions inputs for the future year 2030. It was found that the current ozone control strategy will reduce daily average PM_2.5 concentrations. However, the targeted NO_x reductions for ozone were not found to be optimal for reducing PM_2.5 concentrations. Ammonia emission reductions reduced PM_2.5 and this might be considered as part of a PM_2.5 control strategy.

Implications: The SCAQMD and the ARB have proposed an ozone abatement strategy for the SoCAB that focuses on NO_x emission reductions. Their strategy will affect both ozone and PM_2.5. Two episodes that occurred during September and November 2008 with high PM_2.5 concentrations and high ammonium nitrate composition were selected for simulation with different levels of nitrogen oxide and ammonia emissions for the future year 2030. It was found that the ozone control strategy will reduce maximum daily average PM_2.5 concentrations but its effect on PM_2.5 concentrations is not optimal.     

Characteristics and origins of air pollutants in Wuhan,China, based on observations and hybrid receptor models

To identify the characteristics of air pollutants and factors attributing to the formation of haze in Wuhan, this study analyzed the hourly observations of air pollutants (PM_2.5, PM₁₀, NO₂, SO₂, O₃, and CO) from March 1, 2013, to February 28, 2014, and used hybrid receptor models for a case study. The results showed that the annual average concentrations for PM_2.5, PM₁₀, NO₂, SO₂, O₃, and CO during the whole period were 89.6 μg m^?3, 134.9 μg m^?3, 54.9 μg m^?3, 32.4 μg m^?3, 62.3 μg m^?3, and 1.1 mg m^?3, respectively. The monthly variations revealed that the peak values of PM_2.5, PM₁₀, NO₂, SO₂, and CO occurred in December because of increased local emissions and severe weather conditions, while the lowest values occurred in July mainly due to larger precipitation. The maximum O₃ concentrations occurred in warm seasons from May to August, which may be partly due to the high temperature and solar radiation. Diurnal analysis showed that hourly PM_2.5, PM₁₀, NO₂, and CO concentrations had two ascending stages accompanying by the two traffic peaks. However, the O₃ concentration variations were different with the highest concentration in the afternoon. A case study utilizing hybrid receptor models showed the significant impact of regional transport on the haze formation in Wuhan and revealed that the mainly potential polluted sources were located in the north and south of Wuhan, such as Baoding and Handan in Hebei province, and Changsha in Hunan province. Implications: Wuhan city requires a 5% reduction of the annual mean of PM_2.5 concentration by the end of 2017. In order to accomplish this goal, Wuhan has adopted some measures to improve its air quality. This work has determined the main pollution sources that affect the formation of haze in Wuhan by transport. We showed that apart from the local emissions, north and south of Wuhan were the potential sources contributing to the high PM_2.5 concentrations in Wuhan, such as Baoding and Handan in Hebei province, Zhumadian and Jiaozuo in Henan province, and Changsha and Zhuzhou in Hunan province.     

Physicochemical variations in atmospheric aerosols recorded at sea onboard the Atlantic–Mediterranean 2008 Scholar Ship cruise (Part I): Particle mass concentrations,size ratios,and main chemical components

We report on ambient atmospheric aerosols present at sea during the Atlantic–Mediterranean voyage of Oceanic II (The Scholar Ship) in spring 2008. A record was obtained of hourly PM₁₀, PM_2.5, and PM₁ particle size fraction concentrations and 24-h filter samples for chemical analysis which allowed for comparison between levels of crustal particles, sea spray, total carbon, and secondary inorganic aerosols. On-board monitoring was continuous from the equatorial Atlantic to the Straits of Gibraltar, across the Mediterranean to Istanbul, and back via Lisbon to the English Channel. Initially clean air in the open Atlantic registered PM₁₀ levels <10 μg m^?3 but became progressively polluted by increasingly coarse PM as the ship approached land. Away from major port cities, the main sources of atmospheric contamination identified were dust intrusions from North Africa (NAF), smoke plumes from biomass burning in sub-Saharan Africa and Russia, industrial sulphate clouds and other regional pollution sources transported from Europe, sea spray during rough seas, and plumes emanating from islands. Under dry NAF intrusions PM₁₀ daily mean levels averaged 40–60 μg m^?3 (30–40 μg m^?3 PM_2.5; c. 20 μg m^?3 PM₁), peaking briefly to >120 μg m^?3 (hourly mean) when the ship passed through curtains of higher dust concentrations amassed at the frontal edge of the dust cloud. PM₁/PM₁₀ ratios ranged from very low during desert dust intrusions (0.3–0.4) to very high during anthropogenic pollution plume events (0.8–1).