Examining impacts of visibility and PM strategies before implementation

One of the major challenges facing the world today is defining paths to sustainable futures. Part of the challenge is developing a national energy strategy that promotes an adequate energy supply for the United States, while enhancing environmental quality and maintaining U.S. competitiveness in the world economy. To assist in this challenge, we have developed a screening technique to analyze the effectiveness of different proposed emissions reduction strategies. The technique, referred to as the visibility assessment screening technique (VAST), is designed to examine possible impacts on visibility of emission changes of sulfur oxides, nitrogen oxides, volatile organic compounds (i.e., SO2, NOx, and VOC) and fine and coarse particulate matter (PM). The influence of relative humidity, natural aerosols, and the chemical interconnections among sulfur and nitrogen components of aerosols in determining the effectiveness of Clean Air Act Amendment and other projected energy-related emissions changes on eastern and western visibility are explored. The effectiveness of these strategies on particulate matter impacts and potentially on ozone is also noted.     

Interpretation of Trends of PM25 and Reconstructed Visibility from the IMPROVE Network

ABSTRACT

Under the IMPROVE visibility monitoring network, federal land managers have monitored visibility and fine particle concentrations at 29 Class I area sites (mostly national parks and wilderness areas) and Washington, DC since 1988. This paper evaluates trends in reconstructed visibility and fine particles for the 10th (best visibility days), 50th (average visibility days), and 90th (worst visibility days) percentiles over the nine-year period from 1988-96. Data from these sites provides an indication of regional trends in air quality and visibility resulting from implementation of various emission reduction strategies.     

Modeling of Potential Power Plant Plume Impacts on Dallas-Fort Worth Visibility

ABSTRACT

During wintertime, haze episodes occur in the Dallas-Ft. Worth (DFW) urban area. Such episodes are characterized by substantial light scattering by particles and relatively low absorption, leading to so-called “white haze.” The objective of this work was to assess whether reductions in the emissions of SO₂ from specific coal-fired power plants located over 100 km from DFW could lead to a discernible change in the DFW white haze. To that end, the transport, dispersion, deposition, and chemistry of the plume of a major power plant were simulated using a reactive plume model (ROME). The realism of the plume model simulations was tested by comparing model calculations of plume concentrations with aircraft data of SF₆ tracer concentrations and ozone concentrations. A second-order closure dispersion algorithm was shown to perform better than a first-order closure algorithm and the empirical Pasquill-Gifford-Turner algorithm. For plume impact assessment, three actual scenarios were simulated, two with clear-sky conditions and one with the presence of fog prior to the haze. The largest amount of sulfate formation was obtained for the fog episode. Therefore, a hypothetical scenario was constructed using the meteorological conditions of the fog episode with input data values adjusted to be more conducive to sulfate formation. The results of the simulations suggest that reductions in the power plant emissions lead to less than proportional reductions in sulfate concentrations in DFW for the fog scenario. Calculations of the associated effects on light scattering using Mie theory suggest that reduction in total (plume + ambient) light extinction of less than 13% would be obtained with a 44% reduction in emissions of SO₂ from the modeled power plant.     

滤膜对PM2.5采样和组分分析准确性的影响

以大流量采样器采样为例,通过多个采样器应用不同滤膜多周期现场采样、滤膜的孔隙结构与组成分析以及不同采样介质背景下PM2.5组成分析,研究了不同滤膜对PM2.5浓度测定和组分分析的影响。结果表明：聚四氟乙烯（PTFE）滤膜和玻璃纤维滤膜、石英滤膜对于PM2.5浓度值的测定一致性很好,但PTFE滤膜的测定含量较玻璃纤维滤膜和石英滤膜略低;其原因与滤膜的微观结构和颗粒物在滤膜上的聚集状态有关;空白滤膜的背景值差异影响PM2.5中化学组分浓度的测定。     

DAQM-Simulated Spatial and Temporal Differences Among Visibility,PM, and Other Air Quality Concerns Under Realistic Emission Change Scenarios

The Denver Air Quality Modeling Study (DAQMS) is a comprehensive modeling effort originally undertaken to apportion sources of visibility degradation and examine the visibility benefits of future emission strategies in the Denver metropolitan area. Because of the detailed treatment of the chemical and physical processes and high temporal, vertical, and horizontal resolution of the system, it is possible to examine other air-related issues and their relationships to visibility. The DAQMS analysis system consists of the Denver Air Quality Model (DAQM), a three-dimensional Eulerian chemical-transport model including aerosol and gas-phase transport and transformation processes, a three-dimensional mesoscale meteorological modeling system, visibility analysis procedures, and an emissions processing system. DAQM, the meteorological model, and the emissions information operate on a domain covering approximately the entire state of Colorado with 8-km grid resolution and 15 vertical levels from the surface to the stratosphere. Analysis from a winter visibility episode illustrates the differences between spatial and temporal distributions of light extinction, fine and coarse particle aerosol concentrations, oxidants, and carbon monoxide under various emission scenarios. Studies aimed at exploring interrelationships between these air quality concerns for different seasons, meteorological conditions, and emission management scenarios are outlined.     

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.     

Relationship between Sulfate Aerosol and Visibility

A PM₁₀ monitoring network was established throughout the South Coast Air Basin (SOCAB) in the greater Los Angeles region during the calendar year 1986. Annual average PM₁₀ mass concentrations within the Los Angeles metropolitan area ranged from 47.0 µg m^-3 along the coast to 87.4 µg m^-3 at Rubldoux, the furthest inland monitoring station. Measurements made at San Nicolas Island suggest that regional background aerosol contributes between 28 to 44 percent of the PM₁₀ aerosol at monitoring sites In the SOCAB over the long term average. Five major aerosol components (carbonaceous material, NO^- ₃, SO⁼ ₄, NH⁺ ₄, and soil-related material) account for greater than 80 percent of the annual average PM₁₀ mass at all on-land monitoring stations. Peak 24-h average mass concentrations of nearly 300 µg m^-3 were observed at inland locations, with lower peak values (?130–150 µg m^-3) measured along the coast. Peak-day aerosol composition was characterized by increased NO^- ₃ Ion and associated ammonium ion levels, as compared to the annual average. There appears to be only a weak dependence of PM₁₀ mass concentration on season of the year. This lack of a pronounced seasonal dependence results from the complex and contradictory seasonal variations in the major chemical components (carbonaceous material, nitrate, sulfate, ammonium ion and crustal material). At most sites within the Los Angeles metropolitan area, PM₁₀ mass concentrations exceeded both the annual and 24-h average federal and state of California PM₁₀ regulatory standards.     

Impacts of Meteorological Factors on PM10: Artificial Neural Networks (ANN) and Multiple Linear Regression (MLR) Approaches

In this study, prediction capacities of multi-linear regression (MLR) and artificial neural networks (ANN) onto coarse particulate matter (PM₁₀) concentrations were investigated. Different meteorological factors on particulate pollution were chosen for operating variables in the model analyses. Two different regions (urban and industrial) were identified in the region of Kocaeli, Turkey. All data sets were obtained from air quality monitoring network of the Ministry of Environment and Urban Planning, and 120 data sets were used in the MLR and ANN models. Regression equations explained the effects of the meteorological factors in MLR analyses. In the ANN model, backpropagation network with two hidden layers has achieved the best prediction efficiency. Determination coefficients and error values were examined for each model. ANN models displayed more accurate results compared to MLR.     

Elemental characterization of PM10, PM2.5 and PM1 in the town of Genoa (Italy)

The particulate matter (PM) concentration and composition, the PM10, PM2.5, PM1 fractions, were studied in the urban area of Genoa, a coastal town in the northwest of Italy. Two instruments, the continuous monitor TEOM and the sequential sampler PARTISOL, were operated almost continuously on the same site from July 2001 to September 2004. Samples collected by PARTISOL were weighted to obtain PM concentration and then analysed by PIXE (particle induced X-ray emission) and by ED-XRF (energy dispersion X-ray fluorescence), obtaining concentrations for elements from Na to Pb. Some of the filters used in the TEOM microbalance were analysed by ED-XRF to calculate Pb concentration values averaged over 7-30 d periods.     

贵阳市白云区大气PM_(10)和PM_(2.5)污染特征

使用β射线法在线监测仪连续监测了贵阳市白云区PM_(10)和PM_(2.5)浓度,分析了2014年6月1日—12月31日7个月内PM_(10)、PM_(2.5)的浓度水平、时变规律和PM_(2.5)/PM_(10)的变化情况。结果表明,监测时段内PM_(10)和PM_(2.5)的日均浓度平均值分别为76.8μg/m~3和40.0μg/m~3,均达到国家二级标准;浓度超标的天数占总观测天数的5.1%和9.3%,属污染轻微的地区。PM_(2.5)/PM_(10)在25.3%~78.8%之间周期性波动,平均值为52.1%。PM_(10)和PM_(2.5)的浓度变化具有很好的正相关性(r=0.919 8,p0.000 1);日均值在7个月中呈现明显的周期性变化,各月相对稳定,12月的PM_(10)和PM_(2.5)浓度最高且变化最为剧烈,6月最为平缓。PM_(10)和PM_(2.5)浓度小时变化总体上呈双峰型分布,最高值出现在出现在09:00—10:00和19:00—21:00前后,最低值出现在14:00—17:00之间。     

Visibility and Mass Concentration in a Nonurban Environment

Considerable interest is currently directed toward atmospheric visibility and its relationship to particle size and mass concentration. Previous work has been limited to heavily polluted urban areas, and visibility studies have not included particle size characterization. An air sampling program was carried out in a nonurban, low pollution area to relate: (a) total particulate mass concentration measured with a high-volume sampler, (b) particulate mass size distribution measured with aerodynamic size selective samplers, and (c) visual range measured by the integrating nephelometer. For low suspended particulate mass concentrations, the following relationship was defined between visual range (L_v) and mass concentration (M ? μg/m³):     

Sight Path Measurements for Visibility Monitoring and Research

The optical properties of sight paths in the atmosphere are reviewed, and it is shown that it is necessary to measure two optical parameters to characterize visibility. It is recommended that both the transmittance and path radiance be determined when the optical properties of sight paths are measured for visibility research studies. A practical method for monitoring these quantities is discussed and the calculations to derive the values of parameters related to human perception from these data are described. The limitations associated with monitoring visual parameters, such as contrast, are discussed.     

Statistical Comparisons between Teleradiometer-Derived and Slide-Derived Visibility Parameters

An automated scanning densitometer system developed to estimate visibility-related parameters from photographic slides was tested in comparison to similar teleradiometric measurements. Parameters such as target-sky contrast, visual range, atmospheric light extinction coefficient, and plume and layered contrast can be estimated using this system; however, only target-sky radiance ratios and standard visual ranges were compared. More than 1600 concurrent densitometer and teleradiometer data pairs from eight National Park Service air quality and visibility monitoring locations in the western United States were analyzed using the techniques of correlation, linear regression, average bias and difference calculation, and cumulative frequency distribution generation. Correlation coefficients were good, especially with middle-range camera vistas around 50 km distant. Regression slopes approached unity with intercepts near zero. Average bias introduced into the determination of radiance ratios from slides ranged from near zero to 6 percent, depending on target distance. Standard visual range data distributions compared favorably at the low end with some minor differences at the high end.     

Monitoring of PM10 and PM2.5 around primary particulate anthropogenic emission sources

Investigations on the monitoring of ambient air levels of atmospheric particulates were developed around a large source of primary anthropogenic particulate emissions: the industrial ceramic area in the province of Castelló (Eastern Spain). Although these primary particulate emissions have a coarse grain-size distribution, the atmospheric transport dominated by the breeze circulation accounts for a grain-size segregation, which results in ambient air particles occurring mainly in the 2.5–10 μm range. The chemical composition of the ceramic particulate emissions is very similar to the crustal end-member but the use of high Al, Ti and Fe as tracer elements as well as a peculiar grain-size distribution in the insoluble major phases allow us to identify the ceramic input in the bulk particulate matter. PM2.5 instead of PM10 monitoring may avoid the interference of crustal particles without a major reduction in the secondary anthropogenic load, with the exception of nitrate. However, a methodology based in PM2.5 measurement alone is not adequate for monitoring the impact of primary particulate emissions (such as ceramic emissions) on air quality, since the major ambient air particles derived from these emissions are mainly in the range of 2.5–10 μm. Consequently, in areas characterised by major secondary particulate emissions, PM2.5 monitoring should detect anthropogenic particulate pollutants without crustal particulate interference, whereas PM10 measurements should be used in areas with major primary anthropogenic particulate emissions.     

Pollution characteristics and toxic effects of PM1.0 and PM2.5 in Harbin,China

Environmental Science and Pollution Research - In 2019, PM2.5 and PM1.0 samples were collected in Harbin City, Heilongjiang Province, China, to research their mass concentration, number...     

Wintertime PM2.5 and PM10 Source Apportionment at Sacramento,California

ABSTRACT

The chemical mass balance (CMB) model was applied to winter (November through January) 1991–1996 PM2.5 and PM10 data from the Sacramento 13th and T Streets site in order to identify the contributions from major source categories to peak 24-hr ambient PM_2.5 and PM₁₀ levels. The average monthly PM₁₀ monitoring data for the nine-year period in Sacramento County indicate that elevated concentrations are typical in the winter months. Concentrations on days of highest PM₁₀ are dominated by the PM2.5 fraction. One factor contributing to increased PM_2.5 concentrations in the winter is meteorology (cool temperatures, low wind speeds, low inversion layers, and more humid conditions) that favors the formation of secondary nitrate and sulfate aerosols. Residential wood burning also elevates fine particulate concentrations in the Sacramento area.

The results of the CMB analysis highlight three key points. First, the source apportionment results indicate that primary motor vehicle exhaust and wood smoke are significant sources of both PM_2.5 and PM₁₀ in winter. Second, nitrates, secondarily formed as a result of motor-vehicle and other sources of nitrogen oxide (NO_x), are another principal cause of the high PM_2.5 and PM₁₀ levels during the winter months. Third, fugitive dust, whether it is resuspended soil and dust or agricultural tillage, is not the major contributor to peak winter PM_2.5 and PM10 levels in the Sacramento area.     

Elemental composition of PM10 and PM2.5 in urban environment in South Brazil

The purpose of the present study is to analyze the elemental composition and the concentrations of PM₁₀ and PM_2.5 in the Guaíba Hydrographic Basin with HV PM₁₀ and dichotomous samplers. Three sampling sites were selected: 8° Distrito, CEASA and Charqueadas. The sampling was conducted from October 2001 to December 2002. The mass concentrations of the samplers were evaluated, while the elemental concentrations of Si, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu and Zn were determined using the Particle-Induced X-ray Emission (PIXE) technique. Factor Analysis and Canonical Correlation Analysis were applied to the chemical and meteorological variables in order to identify the sources of particulate matter. Industrial activities such as steel plants, coal-fired power plants, hospital waste burning, vehicular emissions and soil were identified as the sources of the particulate matter. Concentration levels higher than the daily and the annual average air quality standards (150 and 50 μg m⁻³, respectively) set by the Brazilian legislation were not observed.