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And many Americans say that trend is a bad thing, the study found. Opinion by the Rev. Hey there, I think your website might be having browser compatibility issues. When I look at your website in Firefox, it looks fine but when opening in Internet Explorer, it has some overlapping. Structure activity relationships and information on the agent's structural analogs can provide insight into whether an association is causal. Similarly, information on mode of action for a chemical, as one of many structural analogs, can inform decisions regarding likely causality.
While these aspects provide a framework for assessing the evidence, they do not lend themselves to consideration in terms of simple formulas or fixed rules of evidence leading causality conclusions. A tallying of studies reporting statistically significant or nonsignificant results does not point toward credible conclusions about the relative weight of the evidence and the likelihood of causality.
Rather, these considerations are taken into account with the goal of producing an objective appraisal of the evidence, informed by peer and public comment and advice. The principles in Table 1. In particular, the absence of one or more of the principles does not automatically exclude a study from consideration e. Using a five-level hierarchy to classify the overall weight of evidence for causation, not just association see Table 1. Environmental Protection Agency, , and the U. Surgeon General's report on the benefits of smoking cessation Centers for Disease Control and Prevention, These efforts are presented in more detail in Annex AX1.
The weight of evidence evaluation is based on various lines of evidence from human clinical, epidemiologic, animal studies, and in vitro studies. The separate judgments are then integrated into a qualitative statement about the overall weight of the evidence and causality. Sufficient to infer a causal relationship Evidence is sufficient to conclude that there is a causal relationship between relevant pollutant exposure and the outcome.
Causality is supported when an association has been observed between the pollutant and the outcome in studies in which chance, bias, and confounding could be ruled out with reasonable confidence. That is, human clinical studies provide the strongest evidence for causality. Causality is also supported by findings from epidemiologic "natural experiments" or observational studies supported by other lines of evidence. Generally, determination is based on multiple studies from more than one research group.
Sufficient to infer a likely causal relationship i. Evidence is sufficient to conclude that there is a likely causal association between relevant pollutant exposures and the outcome. That is, an association has been observed between the pollutant and the outcome in studies in which chance, bias and confounding are minimized, but uncertainties remain.
Suggestive, but not sufficient to infer a causal relationship Evidence is suggestive of an association between relevant pollutant exposures and the outcome, but is weakened because chance, bias and confounding cannot be ruled out. For example, at least one high-quality study shows an association, while the results of other studies are inconsistent. Inadequate to infer the presence or absence of a causal relationship The available studies are inadequate to infer the presence or absence of a causal relationship.
That is, studies are of insufficient quality, consistency or statistical power to permit a conclusion regarding the presence or absence of an association between relevant pollutant exposure and the outcome. For example, studies which fail to control for confounding or which have inadequate exposure assessment, fall into this category. Suggestive of no causal relationship The available studies are suggestive of no causal relationship.
That is, several adequate studies, examining relationships between relevant population exposures and outcomes, and considering sensitive subpopulations, are mutually consistent in not showing an association between exposure and the outcome at any level of exposures.
In addition, the possibility of a small elevation in risk at the levels of exposure studied can never be excluded. Generally, the response is evaluated within the range of observation, which is determined by the type of study and methods of exposure measurement. Extensive human data to inform risk analyses exists for all criteria pollutants, unlike most other environmental pollutants.
Animal data also can inform concentration-response, particularly relative to dosimetry, mechanisms of action, and characteristics of sensitive subpopulations. An important consideration in characterizing the public health impacts associated with exposure to a pollutant is whether the concentration-response relationship is linear across the full concentration range encountered, or whether nonlinear relationships exist along any part of this range.
Of particular interest is the shape of the concentration-response curve at and below the level of the current standard. The complex molecular and cellular events that underlie cancer and noncancer toxicity are likely to be both linear and nonlinear, and vary depending on concentration. Additionally, many factors may act by perturbing naturally occurring background processes related to disease. At the human population level, various sources of variability and uncertainty tend to smooth and "linearize" the concentration-response function, such as low data density in the lower concentration range, possible influence of measurement error, and individual differences in susceptibility to air pollution health effects.
These attributes of population concentration-response may explain why the available human data at ambient concentrations for some environmental pollutants e. These attributes of human population concentration-response relationships have been extensively discussed in the broader epidemiologic literature e.
Introduction This chapter provides concepts and findings relating to emissions sources, atmospheric science, human exposure assessment, and human dosimetry. The order of these topics essentially follows that given in the National Research Council paradigm for integrating air pollutant research NRC, as shown in Figure 2.
This chapter is meant to serve as a prologue for detailed discussions on the evidence on health effects that follow in Chapters 3 and 4, and as a source of information to help interpret those effects against data about atmospheric concentrations and exposures. The definition of "nitrogen oxides," as it appears in the NAAQS legislation, differs from the one commonly used in air pollution research and control communities. NO2 can also react with toxic compounds such as poly cyclic aromatic hydrocarbons PAHs to form nitro-PAHs, some of which are more toxic than either reactant alone.
NO2 and SO2, another EPA criteria air pollutant, can also be oxidized to form the strong mineral acids nitric acid HNO3 and sulfuric acid H2SO4 , thereby contributing to the acidity of cloud, fog, and rainwater, as well as ambient particles. The category label used by this community for the sum of all forms of oxidized nitrogen compounds including those listed in Section c is NOY. Environmental Protection Agency, a. The chemistry of reactive, oxidized TV compounds in the atmosphere is summarized in Figure 2.
The major sources of NOX in the U. On-road mobile sources constitute the largest source of NOX followed by electricity generating units EGUs and non-road mobile sources. Stationary engines and industrial facilities also emit NOX, but because they are fewer in number or burn less fuel, their mass contribution is relatively smaller. It should be remembered in viewing Table 2. Relatedly, there are several methods for determining NOX emissions from these many sources.
The ratio of NO2 to the sum of NO and NO2 in the exhaust from gasoline fueled vehicles is variable, but generally of the order of a few percent Heeb et al. Apart from these anthropogenic sources, there are also smaller natural sources which include microbial activity in soils particularly fertilized soils and lightning. Wildfires can be large but episodic and highly variable sources of NOX. Chemical Transformations NO and NO2 are often grouped together and given the category label "NOX" because they are emitted together and can rapidly interconvert as shown in the inner box in Figure 2.
The NO emitted from the sources shown in Figure 2. The timescale for the conversion of NO to NO2 is on the order of a minute. These products include inorganic species shown on the left side of the outer box in Figure 2. The concentrations and atmospheric lifetimes T of inorganic and organic products from reactions of NOX vary widely in space and time. While a broad range of organic TV compounds are emitted by combustion sources e. These include PANs and isoprene nitrates, other nitro-PAHs, and the more recently identified nitrated organic compounds in the quinone family.
Most of the mass of products shown in the outer box of Figure 2. These reactions can occur on the surfaces of suspended particles, soil, and buildings, and within aqueous media. Further details about these processes can be found in Annex section AX2.
PAN, and other peroxyacyl nitrates, both thermally decompose and photolyze back to reactants. Atmospheric lifetimes with respect to photolysis are a few hours during warm sunlit conditions. Thus, PAN can provide an effective sink of NOX at cold temperatures and high solar zenith angles; its lifetime is long enough at low temperatures so that PAN can be transported tens or hundreds of kilometers depending on meteorological conditions before decomposing to release NO2, which can then participate in O3 formation in these regions, remote from the original NOX source.
HNO3 can act similarly to some extent, but its high solubility and high deposition rate imply that it is removed from the gas phase faster than PAN, and thus would not be as important as a source of NOX in remote regions. As a result, morning rush hour emissions of NOX from motor vehicles can be converted almost completely to NOZ products by late afternoon during warm, sunny conditions.
Because the time required for mixing emissions down to the surface is similar to or longer than the time for oxidation of NOX, emissions of NOX from elevated sources like the stacks of electric utilities tend to be transformed to NOZ before they reach the surface. However, people live closer to emissions from on-road and off-road motor vehicles, fixed-site combustion engines e.
Ultimately, oxidized TV compounds are lost from the atmosphere by deposition to the earth's surface. Soluble species are taken up by aqueous aerosols and cloud droplets that can then be removed by either wet or dry deposition. Insoluble species are lost by dry deposition and washout. Discussions of the reactions in particles are beyond the scope of this review, but once in particles, a variety of organic and inorganic nitrates can be formed, which are then removed either by dry deposition to the surface or by rainout or washout.
Among combustion sources, diesel emissions have been identified as the major source of nitro-PAHs in ambient air Bezabeh et al. Direct emissions of nitro-PAHs vary with fuel type, vehicle maintenance, and ambient conditions Arey et al. Reactions involving OH radicals occur mainly during the day, while reactions with NO3 radicals occur mainly during the night.
The major loss process of nitro-PAHs is photodecomposition Fan et al. Os Formation At the low NOX concentrations found in most environments ranging from remote continental areas to rural and suburban areas downwind of urban centers , the net production of O3 increases with increasing NOX. At the high NOX concentrations found in downtown metropolitan areas, and especially near busy streets and roadways and in power plant plumes, net destruction of O3 is initiated with the excess NO found there.
Between these two regimes, there is a transition zone in which O3 shows only a weak dependence on NOX concentration. Both these measurements and hence the determination of NO2 by subtraction depend on the same technique for measuring NO. In that technique, NO is measured using the principle of gas-phase chemiluminescence induced by the reaction of NO with O3 at low pressure. Because the FRM monitor cannot detect NO2 specifically, the concentration of NO2 is determined as the difference between the air sample passed over the heated MoOx substrate the nitrogen oxides total and the air sample that has not passed over the substrate the NO.
Reduction of NO2 to NO on the MoOx substrate is not specific to NO2; hence, the chemiluminescence analyzers are subject to varying interferences produced by the presence in the sample of the other oxidized TV compounds the NOZ species shown in the outer box of Figure 2. This interference is often termed a "positive artifact" in the NO2 concentration estimate since the presence of NOZ always results in an over-estimate of the NO2 concentration in the reported measurement.
This interference by NOZ compounds has long been known Fehsenfeld et al. Environmental Protection Agency, , a; Crosley, ; Nunnermacker et al. These studies have relied on intercomparisons of measurements using the FRM and other techniques for measuring NO2. The sensitivity of the FRM to potential interference by individual NOZ compounds is variable and also depends in part on characteristics of individual monitors, such as the design of the instrument inlet, the temperature and composition of the reducing substrate, and on the interactions of atmospheric species with the reducing substrate.
Only recently have attempts been made to systematically quantify the magnitude and variability of the interference by NOZ species in ambient measurements of NO2. Dunlea et al. Comparable levels of NO2 are found in many locations in the U. In a study in rural Switzerland, Steinbacher et al. Another approach to estimating the measurement interference is to use model calculations in conjunction with known data on the reduction efficiencies of NOZ species on the MoOx converters as described above.
Lamsal et al. However, the current generation of satellite monitors are in low earth orbiting mode and so the NO2 values are restricted to time of satellite overpass in early afternoon. Future generations of geostationary satellites are planned that will obtain more continuous data across the U.
Highest values were found during the afternoon, when photochemical activity is highest and production and accumulation of the higher oxidized NOZ compounds is greatest, and lowest values during the middle of the night when photochemistry stops. In general, the interference in the measurement of NO2 is greater downwind of urban source areas and in relatively remote areas away from concentrated sources as compared to the level of interference at measurements in urban cores with fresh NOX emissions.
There are approaches to measuring NO2 not affected by the artifacts mentioned above. This method requires additional development to ensure its cost effectiveness and reliability for extensive field deployment. The relatively low and variable conversion efficiency of this technique would necessitate more frequent calibration. However, these particular methods are more expensive than either the FRM monitors or photolytic reduction technique and require specialized expertise to operate.
Moreover, the DOAS obtains an integrated measurement over the instrument path length rather than a point measurement. However, this technique is not highly specific to NO2 and is subject to interference by other species absorbing at nm, such as the 1,2-dicarbonyl compounds.
The extent of this interference and the potential of the cavity attenuated phase shift technique for extensive field deployment have not been evaluated. However, in settings close to relatively high-concentration fresh emissions like those during urban rush hour, most of the NOY is present as NOX. It is worth reiterating that with the current FRM monitors, the direct measurements of NO are the most specific. Measurements of total NOY characterize the entire suite of oxidized TV compounds to which humans are exposed.
Reliable measurements of NOY and NO2, especially at the low concentrations observed in many areas remote from sources are also crucial for evaluating the performance of three-dimensional, chemical transport models of oxidant and acid production in the atmosphere described in Annex section AX2. To summarize this discussion of NO2 measurement techniques and interferences: the current method of determining ambient NOX and then reporting NO2 concentrations by subtraction of NO is subject to a consistently positive interference by NOX oxidation products, chiefly HNO3 and peroxyacetyl nitrate PAN as well as other oxidized TV-containing compounds, though the magnitude of this positive bias is largely unknown and can be rapidly changing.
Measurements of these oxidation products in urban areas are sparse. Concentrations of these oxidation products are expected to peak in the afternoon because of the continued oxidation of NO2 emitted during the morning rush hours and during conditions conducive to photochemistry in areas well downwind of sources, particularly during summer.
Within the urban core of metropolitan areas, where many of the ambient monitors are sited close to strong NOX sources such as motor vehicles on busy streets and highways i. As might be expected, criteria for siting monitors differ by pollutant.
NO2 monitors are meant to be representative of several scales: middle several city blocks, to m , neighborhood 0. Middle- and neighborhood-scale monitors are used to determine highest concentrations and source impacts, while neighborhood- and urban-scale monitors are used for monitoring population exposures. As can be seen, there is considerable overlap between monitoring objectives and scales of representativeness.
The distance of neighborhood- and urban-scale monitor inlets from roadways increases with traffic volume and can vary from 10 to m away from roadways as traffic volume increases. Where the distance of an inlet to a road is shorter than the value in this range for the indicated traffic volume on that road, that monitor is classified as middle scale.
Vertically, the inlets to NO2 monitors can be set at a height from 2 to 15 m. Location of ambient N02 monitors in the U. Shaded states have N02 monitors; unshaded states have none. Figures 2. These CMSAs were selected for this depiction to maintain consistency with CMSAs used elsewhere in this assessment for health effects studies or ambient concentration representations. MM An 65 years. N02 monitor locations in the Chicago, IL CMSA shown in relation to major roadways, point- source electric generating units, and population densities for total population, and fractions 65 years.
S5 N02 monitor locations in the Houston, TX CMSA shown in relation to major roadways, point- source electric generating units, and population densities for total population, and fractions 65 years. NOa monitor locations in the Steubenville, OH CMSA shown in relation to major roadways, point-source electric generating units, and population densities for total population, and fractions 65 years.
Census blocks served as the unit of analysis for population calculations. All geospatial analyses were performed in ArcMap Build NO2 monitor location data i. Monitors were mapped for a particular region if they were within 15 kms of its boundary. Information on point sources i. Environmental Protection Agency, b. Point sources were classified by their Source Classification Codes SCC : lOlOxxxx for electric generation: external combustion boilers, and xxxx for electric generation: internal combustion engines.
Point sources were mapped for a particular region if they were within 30 kms from its boundary. NO2 monitor and point source locations for a particular region were then imported into their respective maps and buffer zones of 1, 5, 10, and 15 kms were constructed around the monitor locations.
The total population and populations of 2 sensitive subgroups those 65 were then calculated for those areas using the population data contained within the census block maps. These values are about twice as high as the h avg. The highest maximum hourly concentration ppb found during the period of to was more than a factor often greater than the overall mean h concentrations.
The ratio of the 99th percentile concentration to the mean ranges from 2. Because ambient NO2 monitoring data are so sparse across the U. The short T of NO2 with respect to conversion to NOZ species and the concentrated nature of NO2 emissions result in steep gradients and low concentrations away from major sources that are not adequately captured by the existing monitoring networks.
Model predictions might be more useful for showing large-scale features in the distribution of NO2 and could be used in conjunction with the values shown in Figure 2. The high variation in NO2 concentrations of at least a factor of 10 is apparent in these model estimates. As expected, the highest NO2 concentrations are seen in large urban regions, such as the Northeast Corridor, and lowest values are found in sparsely populated regions located mainly in the West.
NO2 concentrations tend to be higher in January than in July. The white line shows the mean values and the upper and lower borders of the blue shaded areas represent the 10th and 90th percentile values. Information on trends at individual, local air monitoring sites can be found at www. Concentrations were substantially higher during earlier years in selected locations and contributed in those years to the "brown clouds" observed in many cities. Residents in Chattanooga, TN, for example, were exposed more than 30 years ago to high levels of NO2 from a munitions plant Shy and Love, Annual mean NO2 concentrations there declined from ppb in to ppb in With the implementation of control strategies, values dropped further.
However, New York City, with the second-highest annual mean concentration in the U. Nationwide trend in NOa concentrations. The white line shows the mean values, and the upper and lower borders of the blue shaded areas represent the 10th and 90th percentile values. Information on trends at local air monitoring sites: www. In contrast to most urban areas in the U. For example, annual mean NO2 concentrations in central London increased during the s from ppb in to ppb in at the background measurement site and from to ppb at the roadside site.
Corresponding NO concentrations increased from ppb to ppb at the background site and from to ppb at the roadside site Elsom, Increased use of motor vehicles may have contributed to much of these increases in NO2 levels. Variability at other individual sites in selected urban areas is shown in Annex Figures AX3.
As might be expected from an atmospheric species that behaves essentially like a primary pollutant emitted from surface sources, there is strong seasonal variability in NO2 concentrations in the data shown in Figures 2.
Higher concentrations are found during winter, consistent with the lowest mixing layer heights found during the year. Lower concentrations are found during summer, consistent with higher mixing layer heights and increased rates of photochemical oxidation of NO2 to NOZ.
Note also the day-to-day variability in NO2 concentration, which also tends to be larger during the winter. There appears to be a somewhat regular pattern for the other southern cities examined with their winter maxima and summer minima. Atlanta, GA. A natural spline function with 9 degrees of freedom was fit and overlaid to the data dark solid line. However, in Los Angeles and Riverside, CA, monthly maxima tend to occur from autumn through early winter, with minima occurring from spring through early summer.
Mean and peak NO2 concentrations during winter can be up to a factor of two greater than those during the summer at sites in Los Angeles. Diurnal Variability in N02 Concentrations The diurnal variability in NO2 concentrations at the same two sites in the Atlanta metropolitan area shown in Figure 2. As can be seen from these figures, NO2 typically exhibits daily maxima during the morning rush hours, although they can occur at other times of day.
In addition, there are differences between weekdays and weekends. At both sites, NO2 concentrations are generally lower and the diurnal cycles more compressed on weekends than on weekdays. The diurnal variability of NO2 at these sites is typical of that observed at other urban sites.
Monitor siting plays a role in determining diurnal variability in the sense that monitors located farther from traffic will measure lower concentrations and show a flatter overall distribution of data compared to monitors located closer to traffic. Atlanta, GA Suburban. A and B refer to a suburban site, and C and D refer to a site classified as urban and city center.
Upper panel: Annual mean N02 concentrations in ppb in the U. The lower panel shows PRB concentrations expressed as a percentage of total N02 concentrations shown in the upper panel. See text in Annex section AX2. Maximum concentrations in the base case simulation occur along the Ohio River Valley and in the Los Angeles basin. These distinctions are important because health effects caused by long-term, low-level exposures may differ from those caused by short-term, peak exposures.
In this equation, it is assumed that microenvironments do not exchange air with each other, but only with the ambient environment. In the case where microenvironmental exposures occur mainly in a single microenvironment, Equation 2.
Other symbols have the same definitions in Equation 2. If microenvironmental concentrations are considered, then Equation 2. The symbols in brackets have the same meaning as in Equation 2. Microenvironments in which people are exposed to air pollutants such as NO2 typically include residential indoor environments, other indoor locations, near-traffic outdoor environments, other outdoor locations, and in vehicles, as shown in Figure 2.
Indoor combustion sources such as gas stoves and space heaters need to be considered when evaluating exposures to NO2. Exposure misclassification may result when total human exposure is not disaggregated between various microenvironments, and this may obscure the true relationship between ambient air pollutant exposure and health outcome.
Time-activity diaries, completed by study participants, are often used in exposure models and assessments. Eleven different human activity pattern studies were evaluated to obtain over 22, person-days of h human activities in CHAD McCurdy et al. These data can be useful in assembling population cohorts to be used in exposure modeling and analysis.
In general, the relationship between personal exposures to pollutants of ambient origin and ambient concentrations can be modified by microenvironments. In practice, it is extremely difficult to characterize community exposure by individual personal exposure. Variations in community-level personal exposures are determined by cross- community variations in ambient pollutant concentrations and the physical and exposure factors mentioned above.
These factors also determine the strength of the association between population exposure to NO2 of ambient origin and ambient NO2 concentrations. Of major concern is the ability of NO2 as measured by ambient monitors to serve as a reliable indicator of personal exposure to NO2 of ambient origin. There are three aspects of this issue: 1 ambient and personal sampling issues; 2 the spatial variability of ambient NO2 concentrations; 3 the associations between ambient concentrations and personal exposures as influenced by exposure factors, e.
These issues are treated individually in the following subsections. Personal Sampling of N02 Personal exposures in human exposure and panel studies of NO2 health effects are monitored by passive samplers. Their performance is evaluated by comparison to the chemiluminescence monitoring method. Some form of evaluation is crucial for determining measurement errors associated with exposure estimates.
However, measurements of NO2 are subject to artifacts both at the ambient level and at the personal level. As discussed in Section 2. The most widely used passive samplers are Palmes tubes Palmes et al. Descriptions of other commercialized samplers are given in Annex section AX3. These samplers do not use a pump to bring air into contact with the sampling substrate; rather, they rely on diffusion or small scale turbulence to transport NO2 to a sorbent Krupa and Legge, The sorbent can be either physically sorptive e.
The sorbent is extracted and analyzed for one or more reactive derivatives; the mass of NO2 collected is derived from the concentration of the derivative s based on the stoichiometry of the reaction. NO2 concentrations measured outdoors by Palmes tube passive samplers were a factor of 1. Campbell et al. Deposition driven by turbulence would raise the uptake rate on the tube surface compared to the theoretical value, which is based on molecular diffusion along the length of the tube.
A number of factors could affect the performance of passive samplers. Passive sampler performance has not been extensively studied over a wide range of concentrations, wind velocities, temperatures, and relative humidities Varshney and Singh, Variability in environmental conditions e.
Chemical reactions between O3 and NO occur in the diffusion tube especially at roadsides where NO concentrations are relatively high and when sufficient O3 is present for interconversion between the species resulting in an overestimate of NO2 Heal et al. However, the kinetics and stoichiometry of interferent compound reactions have not been well established. The lack of specificity of the substrate towards uptake of NO2 could also be an issue, as SO2 can interfere with the uptake of NO2 Cox, Another aspect of passive sampler performance is that, compared with ambient chemiluminescence monitors, passive samplers give relatively longer time-averaged concentrations from days to weeks , with higher detection limits over short sampling periods.
Consequently, diffusive samplers including those used for NO2 monitoring provide integrated but not high time-resolution concentration measurements. Hourly fluctuations in NO2 concentrations may be important to the evaluation of exposure-health effects relationships, and continuous monitors, such as the chemilumine scent monitors, remain the only approach for estimating short-term, peak exposures.
Variability of N02 Concentrations across Ambient Monitoring Sites Summary statistics for the spatial variability in several urban areas across the U. These areas were chosen because they are major urban areas with at least five monitors operating from to Values in parentheses indicate the number of monitoring sites in that particular city.
The second column shows the 3-year mean concentration across all monitors and the range in these means at individual monitor sites. Metrics for characterizing spatial variability include the use of Pearson correlation coefficients r; column 3 , the 90th percentile of the absolute difference in concentrations column 4 , and coefficient of divergence COD; column 5. The ranges represent results of pairwise monitor comparisons. These three metrics are calculated based on measurements of daily avg concentrations at individual site pairs.
The COD provides an indication of the variability across the monitoring sites in each city and is defined in Equation 2. A COD of 0 indicates there are no differences between concentrations at paired sites spatial homogeneity , while a COD approaching 1 indicates extreme spatial heterogeneity. Environmental Protection Agency, ; Pinto et al. Because of relative sparseness in data coverage for NO2, spatial variability in all cities considered for PM2 5 and O3 could not be considered here.
Thus, the number of cities included here is much smaller than for either O3 24 urban areas or PM2 5 27 urban areas. For urban areas with monitors for all three pollutants, data may have been collected at different locations, with different responses to local sources. For example, concentrations of NO2 collected near traffic will be highest in an urban area, but concentrations of O3 will tend to be lowest there because of titration by NO forming NO2.
However, some general observations can still be made. Mean concentrations of NO2 at individual monitoring sites are not as highly variable as for O3 but are more highly variable than PM2 5. Lower bounds on intersite correlation coefficients for PM2 5 and for O3 tend to be much higher than for NO2 in the same areas shown in Table 2.
The greater spatial variability for NO2 compared to O3 and PM2 5 could lead to larger exposure error in epidemiologic studies. Small-Scale Horizontal Variability Large gradients in NO2 concentrations near roadways have been observed in several studies, and NO2 concentrations have been found to be correlated or inversely correlated with distance from roadway, traffic volume, season, road length, open space, and population density Bignal et al.
A sample gradient is shown in Figure 2. Singer et al. An exponential decay model e. Gilbert et al. Small-scale spatial variations in NO2 concentrations are more pronounced during spring and summer seasons due to meteorology and increased photochemical activity Monn, N02 and NOx concentrations normalized to ambient values, plotted as a function of downwind distance from the freeway. Symbols indicate freeway closest to each monitor. Localized effects of roadway sources lead to variability in NO2 concentrations that is not captured by the regulatory monitoring network.
This variation affects population-level exposure estimates and adds exposure error to time-series epidemiologic studies relying on ambient concentrations as indicators of exposure. Elevated concentrations near roadways also increase exposure of anyone residing, working, or attending school in the vicinity. As discussed in Chapter 4, these elevated concentrations found near roadways may lead to increased vulnerability among those exposed to high near-roadway concentrations ofNO2.
Small-Scale Vertical Variability Inlets to instruments for monitoring gas-phase criteria pollutants can be located from 3 to 15m above ground level CFR, Depending on the pollutant, there can be a positive, negative, or no vertical gradient from the surface to the monitor inlet.
Positive gradients i. Pollutants that are emitted by sources at or just above ground level show negative vertical gradients. Pollutants with area sources widely dispersed surface sources and that have minimal deposition velocities show little or no vertical gradient. Restrepo et al. As shown in Figure 2. Because tail pipe emissions occur at lower heights, NO2 values could have been much higher nearer to the surface and the underestimation of NO2 values by monitoring at 15 m even larger.
This situation is not unique to the South Bronx and could arise in other large urban areas in the U. This adds another dimension to the exposure assessment, namely, the exposure of pedestrians who spend time walking in these street canyons, and urban residents, who have windows opening onto these canyons. These groups may experience high exposures to near-road concentrations of the same magnitude as exposures that occur on or adjacent to arterial and interstate roadways.
These meteorological factors also help determine the relative importance of turbulence induced by traffic, in addition to traffic volume and speed. Detailed descriptions of the effects for many of these factors are available only from complex numerical models such as large eddy simulations and very fine grid resolution computational fluid dynamics CFD models.
A semi-empirical integral model with simplifying assumptions has shown reasonable correlation to measured NO2 concentrations over moderate time scales 1 month Berkowicz et al. By constructing simplified geometries, investigators can obtain good agreement between the performance of integral and CFD models; however, generalization and quantitative application of these results to complex urban situations, even at the same location at different times, is difficult due to multi-scale variability in meteorological conditions, traffic composition and flow, building geometry, street dimensions, street canyon aspect ratios, and building packing density Di Sabatino et al.
Weak associations might be found between concentrations at ambient monitors and other outdoor locations and between concentrations in indoor microenvironments and personal exposures in part because of the spatial horizontal and vertical variability in NO2. This variability is itself location- and time-dependent, and can lead to either over- or underestimates of exposure, depending on the siting of monitors and location of the exposed population.
NO2 ambient monitors may be less representative of community or personal exposures than are ambient monitors for O3 or PM25 for their respective exposures. Environmental Protection Agency, a , indicating generally lower correlations and larger relative spreads in concentrations than for O3 or PM2 5.
As mentioned earlier, there are far fewer monitors for NO2 than for O3 or PM2 5, making estimation of the spatial variability in NO2 levels more difficult. N02 On or Near Roads Lee et al. Westerdahl et al. People in traffic can potentially experience high concentrations of NO2 as a result of the high air exchange rates in vehicles. Park et al. These results imply that the NO2 concentration inside a vehicle could rapidly approach the level outside the vehicle during commuting.
While driving, concentrations for personal exposure in a vehicle cabin could be substantially higher than ambient concentrations measured nearby. Sabin et al. Lewne et al. These levels were 1. Riediker et al. The authors found that the mean and maximum NO2 concentrations in a patrol car were Due to high peak exposures while driving, total personal exposure could be underestimated if exposures while commuting are not considered, and sometimes exposure in traffic can dominate personal exposure to NO2 Lee et al.
Variations in traffic-related expo- sure could be attributed to time spent in traffic, type of vehicle, ventilation in the vehicle, and distance from major roads Chan et al. Distance to major roadways could be another factor affecting indoor and outdoor NO2 concentra- tion and personal NO2 exposure.
Many studies show that outdoor NO2 levels are strongly associated with distance from major roads i. Meteorological factors wind direction and wind speed and traffic density are also important in interpreting measured NO2 concentrations Aim et al.
For example, Roorda-Knape et al. The authors found that NO2 concentrations increased with de- creasing downwind distance for school and neighborhood sites within m downwind of a freeway, and schools located upwind or far downwind of freeways were generally indistinguishable from one another or by regional pollution levels. Personal exposure is associated with traffic density and proximity to traffic, although personal ex- posure is also influenced by indoor sources. Aim et al. Within the urban area of Helsinki, Rotko et al.
The average exposure level of subjects having low or moderate traffic near their homes was Gauvin et al. After controlling for indoor source impacts on personal exposure, Kodama et al. Although traffic is a major source of ambient NO2, industrial point sources are also contributors to ambient NO2.
Nerriere et al. As might be expected, indoor concentrations of NO2 in the absence of combustion sources are determined by the infiltration of outdoor NO2 Levy et al, b; Spengler et al. Contributions to indoor NO2 from the reaction of NO in exhaled breath with O3 could potentially be important in certain circumstances see Annex section AX3.
It should be noted that indoor sources can affect ambient NO2 levels, particularly in areas in which atmospheric mixing is unlikely, such as in valleys. Combustion of fossil and biomass fuels is the major indoor source of nitrogen oxides.
Combustion of fossil fuels occurs in appliances used for cooking, heating, and drying clothes, e. Motor vehicles and various types of generators in structures attached to living areas also contribute NO2 to indoor environments. Indoor sources of NO2 from combustion of biomass include wood-burning fireplaces and wood stoves and tobacco. Many studies have noted the importance of gas cooking appliances as sources of NO2 emissions. Gas cooking appliances remain significantly associated with indoor NO2 concentrations after adjusting for several factors that influence exposures, including season, type of community, socioeconomic status, use of extractor fans, household smoking, and type of heating Garcia Algar et al.
Secondary heating appliances are additional sources of NO2 in indoor environments, particularly if the appliances are unvented or inadequately vented. As heating costs increase, the use of these secondary heating appliances tends to increase. Gas heaters, particularly when unvented or inadequately vented, produce high levels of indoor NO2 Kodama et al.
Results summarized by Brauer et al. Self-cleaning gas range. Avgs are over the entire cycle. Natural gas unvented fireplace, 0. Room concentration with kerosene heater operating for 46 min. Room concentration with gas heater operating for 10 min. Calculated steady-state concentration from specific unvented gas space heaters1 operating in a ft2 house, 1. Values represent 2-wk avgs Gas space heaters No indoor combustion sources Fireplaces Kerosene heaters Gas space heaters Wood stoves All values represent 2-wk avgs in living rooms Bedrooms Living rooms Outdoors Almost all homes had gas stoves.
A main conclusion from the NOX AQCD was that properly vented wood stoves and fireplaces would make only minor contributions to indoor NO2 levels, and several studies have concluded that using wood-burning appliances does not increase indoor NO2 concentrations Levesque et al. Other indoor combustion sources of NO2 are candle burning and smoking. In a study of students living in Copenhagen, S0rensen et al.
Results of studies relating NO2 concentrations and exposures to environmental tobacco smoke ETS have been mixed. NO2 is produced by reactions of NO with O3 or peroxyl radicals, while NO2 is removed by gas-phase reactions with O3 and assorted free radicals and by surface-promoted hydrolysis and reduction reactions. The latter are generated by indoor air chemistry involving O3 and unsaturated hydrocarbons such as terpenes found in air fresheners and other household products Sarwar et al.
At an indoor O3 concentration of 10 ppb and an indoor NO concentration that is significantly smaller than that of O3, the half-life of NO is 2. This reaction is sufficiently fast to compete with even relatively fast air exchange rates. NO2 reacts with O3 to produce nitrate radicals NO3. To date, there have been no indoor measurements of the concentration of NO3 radicals in indoor settings.
Modeling studies by Nazaroff and Cass , Weschler et al. Once formed, NO3 can oxidize organic compounds by either adding to an unsaturated carbon bond or abstracting a hydrogen atom Wayne et al. In certain indoor settings, the NO3 radical may be a more important indoor oxidant than either O3 or the OH radical Nazaroff and Weschler, ; Wayne et al. Thus, NO3 radicals and the products of NO3 radical chemistry could contribute to uncertainty in NO2 exposure-health outcome studies Reactions between NO2 and various free radicals can be an indoor source of organo-nitrates, analogous to the chain-terminating reactions observed in photochemical smog Weschler and Shields, Additionally, based on laboratory measurements and measurements in outdoor air Finlayson-Pitts and Pitts, , one would anticipate that NO2, in the presence of trace amounts of HNO3, can react with PAHs sorbed onto indoor surfaces to produce mono- and dinitro-PAHs.
NO2 can also be reduced on certain surfaces, forming NO. Spicer et al. Weschler and Shields, found that the amount of NO2 removed by charcoal filters used in buildings were almost equally matched by the amount of NO subsequently emitted by the same filters. HONO has been observed to form on surfaces containing partially oxidized aromatic structures Stemmler et al.
Indoors, surface-to-volume ratios are much larger than they are outdoors, and the surface-mediated hydrolysis of NO2 is a major indoor source of HONO Brauer et al. Lee et al. Indoor HONO levels were higher in homes with humidifiers compared to homes without humidifiers 5. This last observation is consistent with the studies of Brauer et al. A person's total exposure to NO2 cannot be estimated based on consideration of the estimates of emissions given in emissions inventories.
Indoor and other microenvironmental sources and a person's activity pattern must be considered in determining the sources that exert the largest influence on a person's total exposure to NO2. Associations between Personal Exposure and Ambient and Outdoor Concentrations Results of studies reporting associations between ambient concentrations and personal exposures are shown in Table 2.
Results of studies reporting associations between outdoor concentrations and personal exposures are shown in Table 2. Study designs longitudinal, daily-averaged, and pooled used in these studies are summarized in Tables 2. Type: Longitudinal Subjects: 56 seniors, schoolchildren, and people with COPD Method: 14 of 56 subjects participated in both sampling seasons; all subjects were monitored for 12 consecutive days h avg samples in each of the one or two seasons, except children, who were measured for 8 consecutive days during the summer.
Type: Longitudinal Subjects: 43 seniors and schoolchildren Method: Similar study design as Sarnat et al. Association between personal exposure and ambient concentration pooled correlation coefficients. Type: Longitudinal Subjects: children aged yrs old Method: 1-wk averaged sample for each person, 6 consecutive wks in the winter and 7 consecutive wks in the spring. Type: Pooled Subjects: 13 in 1st campaign, 31 in 2nd Method: two h sampling periods 1on workdays; 1on weekends for each subject in each campaign; during each sampling period, each subject received 4 samplers to measure personal exposure in 4 different microenvironments home, other indoor, transport, and outdoors.
Subjects: children aged yrs old Method: 1-wk averaged sample for each person for 6 consecutive wks in the winter and 7 consecutive wks in the spring. Subjects: subjects Method: each home was monitored for 3 periods of 1 mo; in the 1st wk of each period, personal, indoor rand outdoor levels were measured, and in the next 3 consecutive wks, only outdoor levels were measured 1-wk averaged measurement.
Subjects: junior-high school students and their family members Method: 3-day avg, personal exposures were monitored on the same day. Subjects: probability-based sample, 70 subjects Method: each participant was monitored during each of 8 cycles h avg sampling period throughout the yr in the microenvironmental component of the study.
Subjects: 50 adults Method: one h avg measurement per person. Gas stove Downtown. Eteclric stove Suburban. Longitudinal correlations1 are calculated when data from a study includes consecutive multiple measurements for each subject longitudinal study design. Longitudinal correlations describe the temporal relationship between personal NO2 exposure or microenvironment concentration and ambient NO2 concentration for the same subject.
The longitudinal correlation coefficient can differ between subjects i. The distribution of correlations for each subject across a population could be obtained with this type of data e. A longitudinal correlation coefficient between the ambient component of personal exposures and ambient concentrations is relevant to the panel epidemiologic study design.
In Table 2. The weak personal and ambient associations do not necessarily mean that ambient concentrations are not a good surrogate for personal exposures, because the weak associations could have resulted from the day-to-day variation in the nonambient component of total personal exposure.
The type of correlation analysis can have a substantial effect on the value of the resultant correlation coefficient. Mage et al. The ambient concentration ay could be measured by one ambient monitor or the average of several ambient monitors. Pooled correlations describe the relationship between daily personal NO2 exposure and daily ambient NO2 concentration across all subjects in the study e.
Daily-average correlations2 are calculated by averaging exposure across subjects for each day. Daily-average correlations then describe the relationship between the daily average exposure and daily ambient NO2 concentration e. This type of correlation i. However, exposure of the population to NO2 of ambient origin has not been reported in all the studies examined. The following two European studies reported the associations between population total exposures and ambient or outdoor concentrations of NO2.
Liard et al. Measurements were made during three 4-day-long measurement periods for each group. Apart from occasional lapses, data from the same participants were collected during each period. For different types of correlation coefficients, the components of the variance of these physical factors are different, and therefore the strength of different types of correlation coefficients is different.
Longitudinal correlation coefficients reflect the intra-personal variations of these physical factors; pooled correlation coefficient reflect both inter- and intra- personal variations of these physical factors; and for the association between community average exposures and ambient concentrations, inter-personal variations of these physical factors are reduced by averaging personal exposures across a community.
Therefore, the strength of the associations between personal exposures and ambient concentrations may not be comparable directly, although these associations are determined by the same set of physical factors but affected in different ways. Since correlations are standardized quantities that depend on multiple features of the data, in a correlation, not only is the linear "relatedness" covariance of the two quantities important, but so is the variability of each, which can be affected by exposure factors in various ways.
In the following assessments, the effects of these physical factors on the strength of correlation coefficients are primarily examined within a study, and the purpose of the inter-study comparison is to examine the consistency of the effects across different types of studies. Home ventilation is an important factor modifying the personal-ambient relationships; one would expect to observe the strongest associations for subjects spending time indoors with open windows.
However, Sarnat et al. The mixed results serve as a reminder that the association between personal exposures and ambient concentrations is complex and determined by many factors. Local and indoor sources also affect the strength of the association between personal exposures and ambient concentrations. However, Kim et al. The lack of improvement in the strength of the association by choosing the closest ambient monitor could be in part due to the differences in the small-scale spatial heterogeneity of NO2 in different urban areas, as shown in Table 2.
Higher personal to ambient correlations have been found for subjects living in rural areas and lower correlations for subjects living in urban areas Aim et al. Spengler et al. This might reflect the highly heterogeneous distribution or the effect of local sources of NO2 in an urban area. Associations between ambient concentrations and personal exposures for the studies examined for NO2 were not stratified by the presence of indoor sources except in Aim et al.
When there is little or no contribution from indoor sources, ambient concentrations primarily determine exposure; however, if there are indoor sources, the importance of outdoor levels in determining personal exposures decreases. The association between ambient or outdoor concentrations and personal exposures strengthens after controlling for indoor sources. Raaschou-Nielsen et al. The strength of the associations between personal exposures and ambient and outdoor concentrations could also be affected by the quality of the data collected during the exposure studies.
Unfortunately, not all studies reported the aspects of the data quality issue. Correlation coefficients would be biased low if data used in their calculation are below detection limits. Sampling interferences caused by some NOY compounds and other gas species associated with both ambient see Section 2. Therefore, caution must be exercised when interpreting the results in Tables 2. In summary, the evidence relating ambient levels to personal exposures is inconsistent.
Some of the longitudinal studies examined found that ambient levels of NO2 were reliable proxies of personal exposures to NO2. However, a number of studies did not find significant associations between ambient and personal levels of NO2. The differences in results are related in large measure to differences in study design and in exposure determinants.
Measurement artifacts and differences in analytical measurement capabilities could also have contributed to the inconsistent results. Indeed, in a number of the studies examined, the majority of measurements of personal NO2 concentrations were beneath detection limits, and in all studies some personal measurements were beneath detection limits.
The infiltration factor Firj and alpha a are the keys to evaluate personal NO2 exposure of ambient origin. As defined in Equations 2. Alpha a is a function of Finf and the fraction of time people spend outdoors y , and the physical meaning of a is the ratio of personal ambient exposure concentration to ambient concentration, i. The values for a and FinfCan be calculated physically using Equations 2. However, the values ofP and k for NO2 are rarely reported, and in most mass balance modeling work, P is assumed to equal 1 and k is assumed to equal 0.
Loupa et al. It is well known that P and k are dependent on a large number of indoor parameters, such as temperature, relative humidity, surface properties, surface-to-volume ratio, the turbulence of airflow, building type, and coexisting pollutants Cotterill and Kingham, ; Garcia-Algar et al. As a result, using a fixed value, as mentioned above, would either over- or underestimate the true a or Finf. Although specific P, k, and a were not reported by most studies, a number of studies investigated factors affecting P, k, and a or indicators ofP, k, and a , and their effects on indoor and personal exposures Cotterill and Kingham, ; Garcia-Algar et al.
Garcia-Algar et al. Homes with double-glazed windows had lower indoor concentrations 6 ppb lower than homes with single-glazed windows. Cotterill and Kingham reported that having single- or double-glazed windows was a significant factor affecting NO2 concentrations in kitchens in homes with gas-cookers The reduction of ventilation resulting from the presence of double- glazed windows can block outdoor NO2 from coming into the indoor environment, and at the same time can also increase the accumulation of indoor generated NO2.
The authors also observed that the use of a humidifier would reduce indoor NO2 by 6 ppb. House type was another factor reported affecting ventilation Garcia-Algar et al. Zota et al. Steady state models based on equations 2. However, the assumption of steady state could result in missing peak exposures and obscuring the real short-term outdoor contribution to indoor and personal exposure.
For example, the NO2 concentrations at locations close to busy streets vary with traffic density, wind direction and speed etc. The time dependence of indoor and outdoor sources and meteorological conditions can affect P, k, and a, and thus affect the relationships between indoor and outdoor NO2 concentration and between personal exposure and outdoor NO2 concentrations on short time scales. Thus, relationships among P, k, and a derived using a steady state model might not be representative of short term values.
It should also be pointed out that both P and k are functions of complex physical and chemical processes that occur on indoor surfaces and therefore are associated with indoor-outdoor air exchange, which in turn affects indoor air flows. Alternatively, the ratio of personal exposure to ambient concentration can be regarded as a in the absence of indoor or nonambient sources. Only a few studies have reported the value and distribution of the ratio of personal NO2 exposure to ambient NO2 concentration, and even fewer studies have reported the value and distribution of a based on sophisticated study designs.
Rojas-Bracho et al. The random component superposition RCS model is an alternative way to calculate Finfor a using observed ambient and personal exposure concentrations Ott et al. The RCS statistical model shown in Equations 2.
As shown in Annex Table AX3. Similarly, as shown in Annex Table AX3.
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