Traffic and Meteorological Impacts on Near-Road Air Quality: Summary of Methods and Trends from the Raleigh Near-Road Study

Abstract

A growing number of epidemiological studies conducted worldwide suggest an increase in the occurrence of adverse health effects in populations living, working, or going to school near major roadways. A study was designed to assess traffic emissions impacts on air quality and particle toxicity near a heavily traveled highway. In an attempt to describe the complex mixture of pollutants and atmospheric transport mechanisms affecting pollutant dispersion in this near-highway environment, several real-time and time-integrated sampling devices measured air quality concentrations at multiple distances and heights from the road. Pollutants analyzed included U.S. Environmental Protection Agency (EPA)-regulated gases, particulate matter (coarse, fine, and ultrafine), and air toxics. Pollutant measurements were synchronized with real-time traffic and meteorological monitoring devices to provide continuous and integrated assessments of the variation of near-road air pollutant concentrations and particle toxicity with changing traffic and environmental conditions, as well as distance from the road. Measurement results demonstrated the temporal and spatial impact of traffic emissions on near-road air quality. The distribution of mobile source emitted gas and particulate pollutants under all wind and traffic conditions indicated a higher proportion of elevated concentrations near the road, suggesting elevated exposures for populations spending significant amounts of time in this microenvironment. Diurnal variations in pollutant concentrations also demonstrated the impact of traffic activity and meteorology on near-road air quality. Time-resolved measurements of multiple pollutants demonstrated that traffic emissions produced a complex mixture of criteria and air toxic pollutants in this microenvironment. These results provide a foundation for future assessments of these data to identify the relationship of traffic activity and meteorology on air quality concentrations and population exposures.     

Impact of local traffic exclusion on near-road air quality: findings from the New York City "Summer Streets" campaign

We monitored curbside airborne particulate matter (PM) concentrations and its proinflammatory capacity during 3 weekends when vehicle traffic was excluded from Park. Ave., New York City. Fine PM concentration peaked in the morning regardless of traffic while ultrafine PM was 58% lower during mornings without traffic. Ultrafine PM concentration varied linearly with traffic flow, while fine PM spiked sharply in response to random traffic events that were weakly correlated with the traffic signal cycle. Ultrafine PM concentrations decayed exponentially with distance from a cross street with unrestricted traffic flow, reaching background levels within 100 m of the source. IL-6 induction was typically highest on Friday afternoons but showed no clear relationship to the presence of traffic. The coarse fraction (>2.5 μm) had the greatest intrinsic inflammatory capacity, suggesting that coarse PM still warrants attention even as the research focus is shifting to nano-particles.     

北京市燃煤的空气质量影响及其控制研究

建立了2005年北京市燃煤污染源排放清单,利用MM5-CMAQ模型计算了各区县各行业燃煤对北京市空气质量的影响。研究表明,2005年1月北京市燃煤源对各监测站点SO_2浓度的贡献在70%以上,对PM_(10)和NO_x浓度的贡献约为20%～40%和10%～30%;7月本地燃煤源对SO_2浓度的贡献在40%～50%左右。1月采暖锅炉对空气质量影响最大,占50%～70%;7月电厂的影响最大。依据北京市奥运空气质量保障方案以及"十一五"期间能源规划,建立了2010年燃煤污染源大气排放的规划情景,并模拟了各规划措施对大气质量的改善效果。通过实施电厂脱硫脱硝除尘、炼焦工业停产、钢铁行业和水泥行业搬迁减产、供热锅炉改造、平房用煤改造等措施,与2005年相比,SO_2平均浓度下降30%左右,NO_x和PM_(10)浓度的下降幅度15%。     

Effects of measurement uncertainty on air quality summary statistics

This paper examines the effects of measurement uncertainty on various summary statistics that are routinely used in air quality data analysis. Analytical approximations and computer simulation techniques are employed to illustrate and quantify how the uncertainty associated with an individual measurement results in an uncertainty for different summary statistics. Measurement uncertainty may be viewed as consisting of bias and imprecision. It is shown that even when there is no bias for individual measurements it is possible for imprecision alone to result in bias for certain commonly used summary statistics. Different types of statistics are shown to be less influenced by measurement imprecision and, consequently, a data set may be acceptable for some purpose but not for others. The desired precision of the summary statistic may be viewed as a guide in determining an acceptable level of imprecision for individual measurements.     

Updated methods for assessing the impacts of nearby gas drilling and production on neighborhood air quality and human health

An explosive growth in natural gas production within the last decade has fueled concern over the public health impacts of air pollutant emissions from oil and gas sites in the Barnett and Eagle Ford shale regions of Texas. Commonly acknowledged sources of uncertainty are the lack of sustained monitoring of ambient concentrations of pollutants associated with gas mining, poor quantification of their emissions, and inability to correlate health symptoms with specific emission events. These uncertainties are best addressed not by conventional monitoring and modeling technology, but by increasingly available advanced techniques for real-time mobile monitoring, microscale modeling and source attribution, and real-time broadcasting of air quality and human health data over the World Wide Web. The combination of contemporary scientific and social media approaches can be used to develop a strategy to detect and quantify emission events from oil and gas facilities, alert nearby residents of these events, and collect associated human health data, all in real time or near-real time. The various technical elements of this strategy are demonstrated based on the results of past, current, and planned future monitoring studies in the Barnett and Eagle Ford shale regions.

Implications: Resources should not be invested in expanding the conventional air quality monitoring network in the vicinity of oil and gas exploration and production sites. Rather, more contemporary monitoring and data analysis techniques should take the place of older methods to better protect the health of nearby residents and maintain the integrity of the surrounding environment.     

Evaluating the use of outputs from comprehensive meteorological models in air quality modeling applications

Currently used dispersion models, such as the AMS/EPA Regulatory Model (AERMOD), process routinely available meteorological observations to construct model inputs. Thus, model estimates of concentrations depend on the availability and quality of meteorological observations, as well as the specification of surface characteristics at the observing site. We can be less reliant on these meteorological observations by using outputs from prognostic models, which are routinely run by the National Oceanic and Atmospheric Administration (NOAA). The forecast fields are available daily over a grid system that covers all of the United States. These model outputs can be readily accessed and used for dispersion applications to construct model inputs with little processing. This study examines the usefulness of these outputs through the relative performance of a dispersion model that has input requirements similar to those of AERMOD. The dispersion model was used to simulate observed tracer concentrations from a Tracer Field Study conducted in Wilmington, California in 2004 using four different sources of inputs: (1) onsite measurements; (2) National Weather Service measurements from a nearby airport; (3) readily available forecast model outputs from the Eta Model; and (4) readily available and more spatially resolved forecast model outputs from the MM5 prognostic model. The comparison of the results from these simulations indicate that comprehensive models, such as MM5 and Eta, have the potential of providing adequate meteorological inputs for currently used short-range dispersion models such as AERMOD.     

Wildfire and prescribed burning impacts on air quality in the United States

ABSTRACT

Air quality impacts from wildfires have been dramatic in recent years, with millions of people exposed to elevated and sometimes hazardous fine particulate matter (PM _2.5 ) concentrations for extended periods. Fires emit particulate matter (PM) and gaseous compounds that can negatively impact human health and reduce visibility. While the overall trend in U.S. air quality has been improving for decades, largely due to implementation of the Clean Air Act, seasonal wildfires threaten to undo this in some regions of the United States. Our understanding of the health effects of smoke is growing with regard to respiratory and cardiovascular consequences and mortality. The costs of these health outcomes can exceed the billions already spent on wildfire suppression. In this critical review, we examine each of the processes that influence wildland fires and the effects of fires, including the natural role of wildland fire, forest management, ignitions, emissions, transport, chemistry, and human health impacts. We highlight key data gaps and examine the complexity and scope and scale of fire occurrence, estimated emissions, and resulting effects on regional air quality across the United States. The goal is to clarify which areas are well understood and which need more study. We conclude with a set of recommendations for future research.     

The Valley of Mexico: summary of observational studies on its air quality and effects on vegetation

Present day Mexico City was established on the banks of the now dead Lake Texcoco by Aztec Indians in a.d. 1325. Over time, increasing population growth, urbanization, vehicular traffic and the number of diverse stationary sources, coupled with its topography and the resultant frequency of prevalent stagnant air masses make Mexico City one of the most polluted areas in the world. Use of biological indicator plants since the early 1970s has shown the critical nature of phytotoxic photochemical oxidants in the region. More recent empirical studies with bean, soybean and pine species confirm these observations and raise concern regarding the geographic magnitude of the problem. Surface measurements of air quality in the region are inadequate and require much additional support. Ultimately, ambient air quality measurements must be coupled with the observations on responses of sensitive vegetation. While the results presented in this paper are primarily observational or qualitative, they hopefully serve the purpose of bringing attention to a critical air quality issue in a developing country.     

The use of air quality forecasts to assess impacts of air pollution on crops: Methodology and case study

It has been reported that ambient ozone (O₃), either alone or in concurrence with acid rain precursors, accounts for up to 90% of US crop losses resulting from exposure to all major air pollutants. Crop damage due to O₃ exposure is of particular concern as ambient O₃ concentrations remain high in many major food-producing regions. Assessing O₃ damage to crops is challenging due to the difficulties in determining the reduction in crop yield that results from exposure to surface O₃, for which monitors are limited and mostly deployed in non-rural areas. This work explores the potential benefits of using operational air quality forecast (AQF) data to estimate rural O₃ exposure. Using the results from the first nationwide AQF as a case study, we demonstrate how the O₃ data provided by AQF can be combined with concurrent crop information to assess O₃ damages to soybeans in the United States. We estimate that exposure to ambient O₃ reduces the US soybean production by 10% in 2005.     

The impacts of reactive terpene emissions from plants on air quality in Las Vegas,Nevada

A three-part study was conducted to quantify the impact of landscaped vegetation on air quality in a rapidly expanding urban area in the arid southeastern United States. The study combines in situ, plant-level measurements, a spatial emissions inventory, and a photochemical box model. Maximum plant-level basal emission rates were moderate: 18.1 μgC gdw^?1 h^?1 (Washingtonia spp., palms) for isoprene and 9.56 μgC gdw^?1 h^?1 (Fraxinus velutina, Arizona ash) for monoterpenes. Sesquiterpene emission rates were low for plant species selected in this study, with no measurement exceeding 0.1 μgC gdw^?1 h^?1. The high ambient temperatures combined with moderate plant-level emission factors resulted in landscape emission factors that were low (250–640 μgC m^?2 h^?1) compared to more mesic environments (e.g., the southeastern United States). The Regional Atmospheric Chemistry Mechanism (RACM) was modified to include a new reaction pathway for ocimene. Using measured concentrations of anthropogenic hydrocarbons and other reactive air pollutants (NO_x, ozone), the box model employing the RACM mechanism revealed that these modest emissions could have a significant impact on air quality. For a suburban location that was downwind of the urban core (high NO_x; low anthropogenic hydrocarbons), biogenic terpenes increased time-dependent ozone production rates by a factor of 50. Our study demonstrates that low-biomass density landscapes emit sufficient biogenic terpenes to have a significant impact on regional air quality.     

Aircraft emissions and local air quality impacts from takeoff activities at a large International Airport

Real time number concentrations and size distributions of ultrafine particles (UFPs, diameter <100 nm) and time integrated black carbon, PM_2.5 mass, and chemical species were studied at the Los Angeles International Airport (LAX) and a background reference site. At LAX, data were collected at the blast fence (∼140 m from the takeoff position) and five downwind sites up to 600 m from the takeoff runway and upwind of the 405 freeway. Size distributions of UFPs collected at the blast fence site showed very high number concentrations, with the highest numbers found at a particle size of approximately 14 nm. The highest spikes in the time series profile of UFP number concentrations were correlated with individual aircraft takeoff. Measurements indicate a more than 100-fold difference in particle number concentrations between the highest spikes during takeoffs and the lowest concentrations when no takeoff is occurring. Total UFP counts exceeded 10⁷ particles cm⁻³ during some monitored takeoffs. Time averaged concentrations of PM_2.5 mass and two carbonyl compounds, formaldehyde and acrolein, were statistically elevated at the airport site relative to a background reference site. Peaks of 15 nm particles, associated with aircraft takeoffs, that occurred at the blast fence were matched with peaks observed 600 m downwind, with time lags of less than 1 min. The results of this study demonstrate that commercial aircraft at LAX emit large quantities of UFP at the lower end of currently measurable particle size ranges. The observed highly elevated UFP concentrations downwind of LAX associated with aircraft takeoff activities have significant exposure and possible health implications.     

Monitoring birds of prey in Finland: a summary of methods, trends, and statistical power

In Finland, Comprehensive Surveys to monitor numbers and productivity of four endangered species of birds of prey were started in the early 1970s. In 1982, the Ringing Center launched the Raptor Grid, a nationwide monitoring program for all other bird-of-prey species based on 10 x 10 km study plots of the Finnish National Grid. The annual total of study plots surveyed by voluntary raptor ringers has averaged 120. Since 1986, additional information on breeding performance has been collected using the Raptor Questionnaire. In 2006, more than 44 262 potential nest sites of birds of prey were inspected, and 12 963 occupied territories, including 8149 active nests, were found and reported by ringers. The population trend during 1982-2006 has been significantly negative in six species and positive or neutral in 18 species. Statistical power of the time series of numbers and productivity has been adequate for all species except the microtine specialists.     

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.     

Strategic environmental assessment of mining activities: A methodology for quantification of cumulative impacts on the air quality

Environmental impact assessments in Brazil have usually focused solely on project-related issues without considering the regional context. Although required by current environmental legislation, cumulative impact assessments have not been included in the overall environmental assessment of projects. However, in recent Strategic Environmental Assessment (SEA) studies of policies, plans, and programs undertaken on a voluntary basis in support of the decision-making process, this kind of assessment has been performed especially with respect to air quality. This paper presents the application of a methodology for the quantification of cumulative impacts on air quality under high uncertainty caused by various mining activities in a single region that is recommended for SEA studies. In this way, the methodology presented here is suitable for areas lacking detailed modeling information. The developed approach uses a relatively simplified mathematical model, lowering information gathering costs and requiring little processing time. The application of the methodology is illustrated in the case of a SEA of the Corumbá Mining and Industrial Complex Development Program. Despite the lack of data needed for a minimum characterization of conditions of the area surrounding the region modeled, the quantification of impact cumulativeness on air quality has played an important role in the context of the SEA.     

Assessment of air quality benefits from national air pollution control policies in China. Part I: Background,emission scenarios and evaluation of meteorological predictions

Under the 11th Five Year Plan (FYP, 2006–2010) for national environmental protection by the Chinese government, the overarching goal for sulfur dioxide (SO₂) controls is to achieve a total national emissions level of SO₂ in 2010 10% lower than the level in 2005. A similar nitrogen oxides (NO_x) emissions control plan is currently under development and could be enforced during the 12th FYP (2011–2015). In this study, the U.S. Environmental Protection Agency (U.S.EPA)’s Community Multi-Scale Air Quality (Models-3/CMAQ) modeling system was applied to assess the air quality improvement that would result from the targeted SO₂ and NO_x emission controls in China. Four emission scenarios — the base year 2005, the 2010 Business-As-Usual (BAU) scenario, the 2010 SO₂ control scenario, and the 2010 NO_x control scenario—were constructed and simulated to assess the air quality change from the national control plan. The Fifth-Generation NCAR/Penn State Mesoscale Model (MM5) was applied to generate the meteorological fields for the CMAQ simulations. In this Part I paper, the model performance for the simulated meteorology was evaluated against observations for the base case in terms of temperature, wind speed, wind direction, and precipitation. It is shown that MM5 model gives an overall good performance for these meteorological variables. The generated meteorological fields are acceptable for using in the CMAQ modeling.     

Ozone air quality over North America: part I--a review of reported trends

Ozone and precursor trends can be used to measure the effectiveness of regulatory programs that have been implemented. In this paper, we review trends in the concentrations of O3 NOx, and HCs over North America that have been reported in the literature. Although most existing trend studies are confounded by meteorological variability, both the raw data trends and the trends adjusted for meteorology collectively indicate a general decreasing trend in O3 concentrations in most areas of the United States during 1985-1996. In Canada, mean daily maximum 1-hr O3 concentrations at urban sites show mixed trends with a majority of sites showing an increase from 1980 to 1993. Mean daily maximum 1-hr O3 at most regionally representative Canadian sites appears to decrease from 1985 to 1993 or shows no significant change. There are far fewer data and analyses of NOx and HC trends. Available studies covering various ranges of years indicate decreases in ambient NO and HC concentrations in Los Angeles, CA, decreases in HC concentrations in northeastern U.S. cities, and decreases in NOx concentrations in Canadian cities. Two key needs are long-term HC and NOx measurements, particularly at rural sites, and a systematic comparison of trend detection techniques on a reference data set.     

A quantitative approach to the traffic air quality problem: the Traffic Air Quality index

The Traffic Air Quality (TAQ) model is a simple tool to estimate traffic fine particulate emissions on roadways (g/km) and can be used for both real-time analysis and for localized conformity analysis ("hot-spot" analysis for nonattainment areas) as defined by 40 CFR 93.123. This paper is a follow-up to a study published earlier regarding the development of the TAQ model. This paper shows how local air quality levels can be a factor in traffic management in nonattainment areas. Similar to the industrial source quotas measured in tons per year, it is proposed that road segments are to be assigned emission quotas (or TAQ indices) measured in pollutant mass emitted per road length (g/km) above which traffic-measures have to be taken to reduce the fine-particulates emissions on such road links. The TAQ model as well as traffic-rerouting measures along with the Intelligent Transportation System (ITS) protocols can be used to have a real-time control of the traffic conditions along expressways to maintain the fine-particulates emissions below the quota assigned per road link and consequently improving the over all local air quality in nonattainment areas.     

Assessment of the emissions and air quality impacts of biomass and biogas use in California

It is estimated that there is sufficient in-state “technically” recoverable biomass to support nearly 4000 MW of bioelectricity generation capacity. This study assesses the emissions of greenhouse gases and air pollutants and resulting air quality impacts of new and existing bioenergy capacity throughout the state of California, focusing on feedstocks and advanced technologies utilizing biomass resources predominant in each region. The options for bioresources include the production of bioelectricity and renewable natural gas (NG). Emissions of criteria pollutants and greenhouse gases are quantified for a set of scenarios that span the emission factors for power generation and the use of renewable natural gas for vehicle fueling. Emissions are input to the Community Multiscale Air Quality (CMAQ) model to predict regional and statewide temporal air quality impacts from the biopower scenarios. With current technology and at the emission levels of current installations, maximum bioelectricity production could increase nitrogen oxide (NO_x) emissions by 10% in 2020, which would cause increases in ozone and particulate matter concentrations in large areas of California. Technology upgrades would achieve the lowest criteria pollutant emissions. Conversion of biomass to compressed NG (CNG) for vehicles would achieve comparable emission reductions of criteria pollutants and minimize emissions of greenhouse gases (GHG). Air quality modeling of biomass scenarios suggest that applying technological changes and emission controls would minimize the air quality impacts of bioelectricity generation. And a shift from bioelectricity production to CNG production for vehicles would reduce air quality impacts further. From a co-benefits standpoint, CNG production for vehicles appears to provide the best benefits in terms of GHG emissions and air quality.

Implications:?This investigation provides a consistent analysis of air quality impacts and greenhouse gas emissions for scenarios examining increased biomass use. Further work involving economic assessment, seasonal or annual emissions and air quality modeling, and potential exposure analysis would help inform policy makers and industry with respect to further development and direction of biomass policy and bioenergy technology alternatives needed to meet energy and environmental goals in California.     

Evaluating the air quality impacts of the 2008 Beijing Olympic Games: On-road emission factors and black carbon profiles

The aggressive traffic interventions and emission control measures implemented to improve air quality during the 2008 Beijing Olympic Games created a valuable case study to evaluate the effectiveness of these measures on mitigating air pollution and protecting public health. In this paper, we report the results from our field campaign in summer 2008 on the on-road emission factors of carbon monoxide, black carbon (BC) and ultrafine particles (UFP) as well as the ambient BC concentrations. The fleet average emission factors for light-duty gasoline vehicles (LDGV) showed considerable reduction in the Olympic year (2008) compared to the pre-Olympic year (2007). Our measurement of Black Carbon (BC), a primary pollutant, at different elevations at the ambient site suggests consistent decrease in BC concentrations as the height increased near the ground level, which indicates that the nearby ground level sources, probably dominated by traffic, contributed to a large portion of BC concentrations in the lower atmospheric layer in Beijing during summertime. These observations indicate that people living in near ground levels experience higher exposures than those living in higher floors in Beijing. The BC diurnal patterns on days when traffic control were in place during the Olympic Games were compared to those on non-traffic-control days in both 2007 and in 2008. These patterns strongly suggest that diesel trucks are a major source of summertime BC in Beijing. The median BC concentration on Olympic days was 3.7 μg m⁻³, which was dramatically lower than the value on non-traffic-control days, indicating the effectiveness of traffic control regulations in BC reduction in Beijing.