Passive sampling of ambient, gaseous air pollutants: an assessment from an ecological perspective

During some past two decades there has been a growing interest among air pollution-vegetation effects-scientists to use passive sampling systems for quantifying ambient, gaseous air pollutant concentrations, particularly in remote and wilderness areas. On the positive side, excluding the laboratory analysis costs, passive samplers are inexpensive, easy to use and do not require electricity to operate. Therefore, they are very attractive for use in regional-scale air quality assessments. Passive samplers allow the quantification of cumulative air pollutant exposures, as total or average pollutant concentrations over a sampling duration. Such systems function either by chemical absorption or by physical adsorption of the gaseous pollutant of interest onto the sampling medium. Selection of a passive sampler must be based on its known or tested characteristics of specificity and linearity of response to the chemical constituent being collected. In addition, the effects of wind velocity, radiation, temperature and relative humidity must be addressed in the context of absorbent/adsorbent performance and sampling rate. Because of all these considerations, passive samplers may provide under- or overestimations of the cumulative exposures, compared to the corresponding data from co-located continuous monitors or active samplers, although such statistical variance can be minimized by taking necessary precautions. On the negative side, cumulative exposures cannot identify short-term (相似文献   

Evaluation of air quality zone classification methods based on ambient air concentration exposure

Air quality zones are used by regulatory authorities to implement ambient air standards in order to protect human health. Air quality measurements at discrete air monitoring stations are critical tools to determine whether an air quality zone complies with local air quality standards or is noncompliant. This study presents a novel approach for evaluation of air quality zone classification methods by breaking the concentration distribution of a pollutant measured at an air monitoring station into compliance and exceedance probability density functions (PDFs) and then using Monte Carlo analysis with the Central Limit Theorem to estimate long-term exposure. The purpose of this paper is to compare the risk associated with selecting one ambient air classification approach over another by testing the possible exposure an individual living within a zone may face. The chronic daily intake (CDI) is utilized to compare different pollutant exposures over the classification duration of 3 years between two classification methods. Historical data collected from air monitoring stations in Kuwait are used to build representative models of 1-hr NO₂ and 8-hr O₃ within a zone that meets the compliance requirements of each method. The first method, the “3 Strike” method, is a conservative approach based on a winner-take-all approach common with most compliance classification methods, while the second, the 99% Rule method, allows for more robust analyses and incorporates long-term trends. A Monte Carlo analysis is used to model the CDI for each pollutant and each method with the zone at a single station and with multiple stations. The model assumes that the zone is already in compliance with air quality standards over the 3 years under the different classification methodologies. The model shows that while the CDI of the two methods differs by 2.7% over the exposure period for the single station case, the large number of samples taken over the duration period impacts the sensitivity of the statistical tests, causing the null hypothesis to fail. Local air quality managers can use either methodology to classify the compliance of an air zone, but must accept that the 99% Rule method may cause exposures that are statistically more significant than the 3 Strike method.

Implications: A novel method using the Central Limit Theorem and Monte Carlo analysis is used to directly compare different air standard compliance classification methods by estimating the chronic daily intake of pollutants. This method allows air quality managers to rapidly see how individual classification methods may impact individual population groups, as well as to evaluate different pollutants based on dosage and exposure when complete health impacts are not known.     

Air toxics in Canada measured by the National Air Pollution Surveillance (NAPS) program and their relation to ambient air quality guidelines

This study reports ambient concentrations of 63 air toxics that were measured in Canada by the National Air Pollution Surveillance (NAPS) program over the period 2009–2013. Measured concentrations are compared with ambient air quality guidelines from Canadian jurisdictions, and compounds that exceeded guidelines are identified and discussed. Although this study does not assess risk or cumulative effects, air toxics that approached guidelines are also identified so that their potential contribution to ambient air toxics pollution can be considered. Eleven air toxics exceeded at least one guideline, and an additional 16 approached guidelines during the study period. Four compounds were measured using methods whose detection limits exceeded a guideline value, three of which could not be compared with guidelines, since they were not detected in any samples. The assessment of several metal(loid) concentrations is tentative, since they were measured only in fine particulate matter (PM) but compared with guidelines based on coarse or total PM. Improvements to sampling and analysis techniques for the latter compounds as well as for those whose methods are subject to known uncertainties would improve confidence in reported concentrations and their relation to applicable guidelines. Analysis of sampling strategies for all compounds found to exceed or approach guidelines would contribute to ensuring that their spatiotemporal coverage is adequate. Examination of the air toxics not measured by NAPS but having guidelines in Canadian jurisdictions or being included in other programs such as the U.S. National-Scale Air Toxics Assessment (NATA) would contribute to ensuring that the full suite of pollutants relevant to ambient air quality in Canada is subject to adequate study. The results of this study can be applied to evaluating the effectiveness of toxic substances management in Canada.

Implications: Recent measurements of 63 air toxics in Canada by the National Air Pollution Surveillance (NAPS) program showed that 11 compounds exceeded daily or annual ambient air quality guidelines and that an additional 16 compounds approached such guidelines within an order of magnitude. The results of this study can be applied to evaluating the effectiveness of toxic substances management in Canada and to identifying compounds that merit further investigation.     

Evaluation of PNEC values: extrapolation from Microtox, algae, daphnid, and fish data to HC5

In order to evaluate the risk to the environment from long term exposure of any discharged substance, toxicity thresholds are estimated, and particularly the Predicted No Effect Concentration (PNEC). This concentration can be estimated by the classic assessment factor approach or by statistical methods. These are more scientifically sound but they require several (at least 5-6) chronic ecotoxicity data, implying greater cost and time. New extrapolation methods derived from the statistical concept but requiring less data have been studied. Results show that methods based on chronic data are more reliable than methods based on acute data but the improvement is quite small. Considering the costs of chronic tests compared to acute tests, approaches based on acute data are an attractive alternative. A simple regression on the mean of the acute data gives the best results.     

A re-examination of ambient air ozone monitor interferences

Attaining the National Ambient Air Quality Standard (NAAQS) for ozone (O3) could cost billions of dollars nationwide. Attainment of the NAAQS is judged on O3 measurements made by the Federal Reference Method (FRM), ethylene chemiluminescence, or a Federal Equivalent Method (FEM), predominantly ultraviolet (UV) absorption. Starting in the 1980s, FRM monitors were replaced by FEMs so that today virtually all monitoring in the United States uses the UV methodology. This report summarizes a laboratory and collocated ambient air monitoring study of interferences in O3 monitors. Potential interferences examined in the laboratory included water vapor, mercury, o-nitrophenol, naphthalene, p-tolualdehyde, and mixed reaction products from smog chamber simulations of urban atmospheric photochemistry. UV absorption O3 monitors modified for humidity equilibration were also collocated with UV FEM O3 monitors at six sites in Houston, TX, during the 2007 summer O3 season. The results suggest that humidity and interfering species can positively bias (overestimate) O3 measured by FEM monitors used to determine compliance with the O3 standards. The results also suggest that humidity equilibration can mitigate this bias.     

A context-intensive approach to imputation of missing values in data sets from networks of environmental monitors

Although networks of environmental monitors are constantly improving through advances in technology and management, instances of missing data still occur. Many methods of imputing values for missing data are available, but they are often difficult to use or produce unsatisfactory results. I-Bot (short for “Imputation Robot”) is a context-intensive approach to the imputation of missing data in data sets from networks of environmental monitors. I-Bot is easy to use and routinely produces imputed values that are highly reliable. I-Bot is described and demonstrated using more than 10 years of California data for daily maximum 8-hr ozone, 24-hr PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm), mid-day average surface temperature, and mid-day average wind speed. I-Bot performance is evaluated by imputing values for observed data as if they were missing, and then comparing the imputed values with the observed values. In many cases, I-Bot is able to impute values for long periods with missing data, such as a week, a month, a year, or even longer. Qualitative visual methods and standard quantitative metrics demonstrate the effectiveness of the I-Bot methodology.Implications: Many resources are expended every year to analyze and interpret data sets from networks of environmental monitors. A large fraction of those resources is used to cope with difficulties due to the presence of missing data. The I-Bot method of imputing values for such missing data may help convert incomplete data sets into virtually complete data sets that facilitate the analysis and reliable interpretation of vital environmental data.     

A land use regression model for predicting ambient volatile organic compound concentrations in Toronto,Canada

More than 25 studies have employed land use regression (LUR) models to estimate nitrogen oxides and to a lesser extent particulate matter indicators, but these methods have been less commonly applied to ambient concentrations of volatile organic compounds (VOCs). Some VOCs have high plausibility as sources of health effects and others are specific indicators of motor vehicle exhaust. We used LUR models to estimate spatial variability of VOCs in Toronto, Canada. Benzene, n-hexane and total hydrocarbons (THC) were measured from July 25 to August 9, 2006 at 50 locations using the TraceAir organic vapor monitors. Nitrogen dioxide (NO₂) was also sampled to assess its spatial pattern agreement with VOC exposures. Buffers for land use, population density, traffic density, physical geography, and remote sensing measures of greenness and surface brightness were also tested. The remote sensing measures have the highest correlations with VOCs and NO₂ levels (i.e., explains >36% of the variance). Our regression models explain 66–68% of the variance in the spatial distribution of VOCs, compared to 81% for the NO₂ model. The ranks of agreement between various VOCs range from 48 to 63% and increases substantially – up to 75% – for the top and bottom quartile groups. Agreements between NO₂ and VOCs are much smaller with an average rank of 36%. Future epidemiologic studies may therefore benefit from using VOCs as potential toxic agents for traffic-related pollutants.     

Impact of three interactive Texas state regulatory programs to decrease ambient air toxic levels

The Federal Clean Air Act (FCAA) framework envisions a federal-state partnership whereby the development of regulations may be at the federal level or state level with federal oversight. The U.S. Environmental Protection Agency (EPA) establishes National Ambient Air Quality Standards to describe “safe” ambient levels of criteria pollutants. For air toxics, the EPA establishes control technology standards for the 187 listed hazardous air pollutants (HAPs) but does not establish ambient standards for HAPs or other air toxics. Thus, states must ensure that ambient concentrations are not at harmful levels. The Texas Clean Air Act authorizes the Texas Commission on Environmental Quality (TCEQ), the Texas state environmental agency, to control air pollution and protect public health and welfare. The TCEQ employs three interactive programs to ensure that concentrations of air toxics do not exceed levels of potential health concern (LOCs): air permitting, ambient air monitoring, and the Air Pollutant Watch List (APWL). Comprehensive air permit reviews involve the application of best available control technology for new and modified equipment and ensure that permits protect public health and welfare. Protectiveness may be demonstrated by a number of means, including a demonstration that the predicted ground-level concentrations for the permitted emissions, evaluated on a case-by-case and chemical-by-chemical basis, do not cause or contribute to a LOC. The TCEQ's ambient air monitoring program is extensive and provides data to help assess the potential for adverse effects from all operational equipment in an area. If air toxics are persistently monitored at a LOC, an APWL area is established. The purpose of the APWL is to reduce ambient air toxic concentrations below LOCs by focusing TCEQ resources and heightening awareness. This paper will discuss examples of decreases in air toxic levels in Houston and Corpus Christi, Texas, resulting from the interactive nature of these programs.

Implications: Texas recognized through the collection of ambient monitoring data that additional measures beyond federal regulations must be taken to ensure that public health is protected. Texas integrates comprehensive air permitting, extensive ambient air monitoring, and the Air Pollutant Watch List (APWL) to protect the public from hazardous air toxics. Texas issues air permits that are protective of public health and also assesses ambient air to verify that concentrations remain below levels of concern in heavily industrialized areas. Texas developed the APWL to improve air quality in those areas where monitoring indicates a potential concern. This paper illustrates how Texas engaged its three interactive programs to successfully address elevated air toxic levels in Houston and Corpus Christi.     

Evaluation and comparison of continuous fine particulate matter monitors for measurement of ambient aerosols

To provide a scientific basis for the selection and use of continuous monitors for exposure and/or health effects studies, and for compliance and episode measurements at strategic locations in the State of New Jersey, we evaluated the performance of seven continuous fine particulate matter (PM2.5) monitors in the present study. Gravimetric samplers, as reference methods, were collocated with realtime instruments in both laboratory and field tests. The results of intercomparison of real-time monitors showed that the two nephelometers used in this study correlated extremely well (r2 approximately 0.97), and two tapered element oscillating monitors (TEOM 1400 and TEOM filter dynamics measurement system [FDMS]) correlated well (r2 > 0.85), whereas two beta gauges displayed a weaker correlation (r2 < 0.6). During a summertime controlled (laboratory) evaluation, the measurements made with the gravimetric method correlated well with the 24-hr integrated measurements made with the real-time monitors. The SidePak nephelometer overestimated the particle concentration by a factor of approximately 3.4 compared with the gravimetric method. During a summertime field evaluation, the TEOM FDMS monitor reported approximately 30% higher mass concentration than the Federal Reference Method (FRM); and the difference could be explained by the loss of semi-volatile materials from the FRM sampler. Results also demonstrated that 24-hr average PM2.5 mass concentrations measured by beta gauges and TEOM (50 degrees C) in winter correlated well with the integrated gravimetric method. Seasonal differences were observed in the performance of the TEOM (50 degrees C) monitor in measuring the particle mass attributed to the higher semi-volatile material loss in the winter weather. In applying the realtime particulate matter monitoring data into Air Quality Index (AQI) reporting, the Conroy method and the 8-hr end-hour average method were both found to be suitable.     

Flexibility of X-Ray Emission Spectrography as Adapted to Microanalysis of Air Pollutants

Methods previously published by this laboratory for analyzing thin dust coatings of airborne particulates have been further evaluated, as applied to vast air pollution surveys. It was demonstrated that choice of glass fiber filters adapted to high-volume samplers restricts the analysis to a limited number of elements, such as lead. More flexibility and versatility are attained through the use of organic membrane filters mounted in small plastic monitors which permit multi-elemental analysis at least as accurately as with other popular but time-consuming techniques. These qualities of speed and accuracy allow shorter intervals of sampling which are normally required for better statistical assessment of broad air pollution surveys. Sensitivity of the technique reaches a value close to 0.05 μg/m³, while time of analysis required is about five minutes per element after receipt of the sample.     

Forecasts using neural network versus Box-Jenkins methodology for ambient air quality monitoring data

This study explores ambient air quality forecasts using the conventional time-series approach and a neural network. Sulfur dioxide and ozone monitoring data collected from two background stations and an industrial station are used. Various learning methods and varied numbers of hidden layer processing units of the neural network model are tested. Results obtained from the time-series and neural network models are discussed and compared on the basis of their performance for 1-step-ahead and 24-step-ahead forecasts. Although both models perform well for 1-step-ahead prediction, some neural network results reveal a slightly better forecast without manually adjusting model parameters, according to the results. For a 24-step-ahead forecast, most neural network results are as good as or superior to those of the time-series model. With the advantages of self-learning, self-adaptation, and parallel processing, the neural network approach is a promising technique for developing an automated short-term ambient air quality forecast system.     

An evaluation of measurement methods for organic, elemental and black carbon in ambient air monitoring sites

The carbonaceous components of Particulate Matter samples form a substantial fraction of their total mass, but their quantification depends strongly on the instruments and methods used. United Kingdom monitoring networks have provided many relevant data sets that are already in the public domain. Specifically, hourly organic carbon (OC) and elemental carbon (EC) were determined at four sites between 2003 and 2007 using Rupprecht and Pattashnik (R & P) 5400 automatic instruments. Since 2007, daily OC/EC measurements have been made by manual thermo-optical analysis of filter samples using a Sunset Laboratory Carbon Aerosol Analysis instrument. In parallel, long term daily measurements of Black Smoke, a quantity directly linked to black carbon (measured by aethalometers) and indirectly related to elemental carbon, have been made at many sites. The measurement issues associated with these techniques are evaluated in the context of UK measurements, making use of several sets of parallel data, with the aim of aiding the interpretation of network results. From the results available, the main conclusions are that the R & P 5400 instruments greatly under-read EC and total carbon (TC = OC + EC) at kerbside sites, probably due to the fact that the smaller particles are not sampled by the instrument; the R & P 5400 instrument is inherently difficult to characterise, so that all quantitative results need to be treated with caution; both aethalometer and Black Smoke (converted to black carbon) measurements can show reasonable agreement with elemental carbon results; and manual thermo-optical OC/EC results may under-read EC (and hence over-read OC), whether either transmittance or reflectance is used for the pyrolysis correction, and this effect is significant at rural sites.     

Air toxics in ambient air of Delhi

Volatile organic compounds (VOCs) are major group of air pollutants which play critical role in atmospheric chemistry. It contributes to toxic oxidants which are harmful to ecosystem human health and atmosphere. Data on levels of VOCs in developing countries is lacking. In India information at target VOCs as defined in USEPA compendium method TO-14 is almost totally lacking. The present work deals with estimation of target VOCs at 15 locations in five categories namely residential, industrial, commercial, traffic intersections and petrol refueling stations in Delhi, the capital of India. The monitoring was carried out during peak hours in morning and evening each month for a year in 2001. Ambient air was adsorbed on adsorbent tubes, thermally desorbed and analyzed on GC–MS. The results show that levels of VOCs are high and stress the need for regular monitoring programme of VOCs in urban environment.     

Detecting plant effects is necessary to give biological significance to ambient ozone monitoring data and predictive ozone standards

The use of mechanical monitors and passive samplers has made it possible to assess concentrations of ozone over wide areas and to develop air quality standards, like AOT40 and SUM60. Monitored ozone data and AOT40 and SUM60 are also used to predict ozone injury on local and regional scales. The data and the standards do not include or account for environmental and biological variables that affect ozone uptake and plant injury. Ground proofing via vegetation surveys must be done to verify and validate plant injury predictions. If this is not done, then the standards have no biological significance and are only exercises in air quality assessment.     

Spatial heterogeneity of PM10 and O3 in São Paulo, Brazil, and implications for human health studies

Developing exposure estimates is a challenging aspect of investigating the health effects of air pollution. Pollutant levels recorded at centrally located ambient air quality monitors in a community are commonly used as proxies for population exposures. However, if ample intraurban spatial variation in pollutants exists, city-wide averages of concentrations may introduce exposure misclassification. We assessed spatial heterogeneity of particulate matter with an aerodynamic diameter < or = 10 microm (PM10) and ozone (O3) and evaluated implications for epidemiological studies in S?o Paulo, Brazil, using daily (24-hr) and daytime (12-hr) averages and 1-hr daily maximums of pollutant levels recorded at the regulatory monitoring network. Monitor locations were also analyzed with respect to a socioeconomic status index developed by the municipal government. Hourly PM10 and O3 data for the Sāo Paulo Municipality and Metropolitan Region (1999-2006) were used to evaluate heterogeneity by comparing distance between monitors with pollutants' correlations and coefficients of divergence (CODs). Both pollutants showed high correlations across monitoring sites (median = 0.8 for daily averages). CODs across sites averaged 0.20. Distance was a good predictor of CODs for PM10 (p < 0.01) but not O3, whereas distance was a good predictor of correlations for O3 (p < 0.01) but not PM10. High COD values and low temporal correlation indicate a spatially heterogeneous distribution of PM10. Ozone levels were highly correlated (r > or = 0.75), but high CODs suggest that averaging over O3 levels may obscure important spatial variations. Of municipal districts in the highest of five socioeconomic groups, 40% have > or = 1 monitor, whereas districts in the lowest two groups, representing half the population, have no monitors. Results suggest that there is a potential for exposure misclassification based on the available monitoring network and that spatial heterogeneity depends on pollutant metric (e.g., daily average vs. daily 1-hr maximum). A denser monitoring network or alternative exposure methods may be needed for epidemiological research. Findings demonstrate the importance of considering spatial heterogeneity and differential exposure misclassification by subpopulation.     

Concentrations and trends of benzene in ambient air over New York State during 1990–2003

Since 1990s, a systematic program to measure air toxics has been active in New York State with monitors located both in urban and rural areas. In this study we examined the spatial and temporal characteristics of benzene, a known human carcinogen that is emitted by many source categories. The analysis indicates that ambient concentration levels of benzene have decreased by as much as 60% over this period not only in the ozone non-attainment area of New York City that had the reformulated gas (RFG) requirements, but also over the rest of the state as well. Although the rate of decrease appears to have flattened out in recent years, the annual average concentration levels are found to be above the health risk threshold even at the remote location, Whiteface Mountain, suggesting the need for further reductions in benzene emissions.     

Personal exposures of preschool children to carbon monoxide: Roles of ambient air quality and gas stoves

Personal 1 h mean CO exposures of preschool children in two day care centers (Töölö and Vallila) in Helsinki were measured with continuously recording personal exposure monitors. In Vallila, the median CO exposure of children from homes with gas stoves was 2.0 mg m⁻³, and with electric stoves, 0.9 mg m⁻³. In Töölö, the corresponding values were 1.9 and 1.0 mg m⁻³, respectively. The national ambient air quality guidelines for CO in Finland were exceeded in a few percent of the exposure measurements. The results were compared to fixed-site ambient air monitoring data and related to the presence of town-gas fired stoves in the children's homes. The results show that fixed-site ambient air monitors are of little value in predicting personal exposures of children or even their relative differences between areas. They also show that town-gas fired stoves may have a profound effect on the CO exposures of the children.     

interpretation of air quality data with respect to the national ambient air quality standards

San Diego Gas &; Electric has developed a quality assurance program for continuous emission monitors (CEM). Extractive, rather than in situ, monitors were selected as a result of an in-house evaluation program. Two extractive systems have been certified and a good operating and maintenance record has been established on these systems. A successful program requires the involvement and support of all affected personnel. It is desirable to have one or two key personnel coordinate the development of the program. It is also highly desirable to have good in-house source testing capabilities.     

Evaluating the effectiveness of air quality regulations: A review of accountability studies and frameworks

Assessments of past environmental policies—termed accountability studies—contribute important information to the decision-making process used to review the efficacy of past policies, and subsequently aid in the development of effective new policies. These studies have used a variety of methods that have achieved varying levels of success at linking improvements in air quality and/or health to regulations. The Health Effects Institute defines the air pollution accountability framework as a chain of events that includes the regulation of interest, air quality, exposure/dose, and health outcomes, and suggests that accountability research should address impacts for each of these linkages. Early accountability studies investigated short-term, local regulatory actions (for example, coal use banned city-wide on a specific date or traffic pattern changes made for Olympic Games). Recent studies assessed regulations implemented over longer time and larger spatial scales. Studies on broader scales require accountability research methods that account for effects of confounding factors that increase over time and space. Improved estimates of appropriate baseline levels (sometimes termed “counterfactual”—the expected state in a scenario without an intervention) that account for confounders and uncertainties at each link in the accountability chain will help estimate causality with greater certainty. In the direct accountability framework, researchers link outcomes with regulations using statistical methods that bypass the link-by-link approach of classical accountability. Direct accountability results and methods complement the classical approach. New studies should take advantage of advanced planning for accountability studies, new data sources (such as satellite measurements), and new statistical methods. Evaluation of new methods and data sources is necessary to improve investigations of long-term regulations, and associated uncertainty should be accounted for at each link to provide a confidence estimate of air quality regulation effectiveness. The final step in any accountability is the comparison of results with the proposed benefits of an air quality policy.

Implications: The field of air pollution accountability continues to grow in importance to a number of stakeholders. Two frameworks, the classical accountability chain and direct accountability, have been used to estimate impacts of regulatory actions, and both require careful attention to confounders and uncertainties. Researchers should continue to develop and evaluate both methods as they investigate current and future air pollution regulations.