Development of operating mode distributions for different types of roadways under different congestion levels for vehicle emission assessment using MOVES

The Motor Vehicle Emission Simulator (MOVES) quantifies emissions as a function of vehicle modal activities. Hence, the vehicle operating mode distribution is the most vital input for running MOVES at the project level. The preparation of operating mode distributions requires significant efforts with respect to data collection and processing. This study is to develop operating mode distributions for both freeway and arterial facilities under different traffic conditions. For this purpose, in this study, we (1) collected/processed geographic information system (GIS) data, (2) developed a model of CO₂ emissions and congestion from observations, (3) implemented the model to evaluate potential emission changes from a hypothetical roadway accident scenario. This study presents a framework by which practitioners can assess emission levels in the development of different strategies for traffic management and congestion mitigation.

Implications: This paper prepared the primary input, that is, the operating mode ID distribution, required for running MOVES and developed models for estimating emissions for different types of roadways under different congestion levels. The results of this study will provide transportation planners or environmental analysts with the methods for qualitatively assessing the air quality impacts of different transportation operation and demand management strategies.     

Application of an integrated Weather Research and Forecasting (WRF)/CALPUFF modeling tool for source apportionment of atmospheric pollutants for air quality management: A case study in the urban area of Benxi,China

In this study, the authors endeavored to develop an effective framework for improving local urban air quality on meso-micro scales in cities in China that are experiencing rapid urbanization. Within this framework, the integrated Weather Research and Forecasting (WRF)/CALPUFF modeling system was applied to simulate the concentration distributions of typical pollutants (particulate matter with an aerodynamic diameter <10 μm [PM₁₀], sulfur dioxide [SO₂], and nitrogen oxides [NO_x]) in the urban area of Benxi. Statistical analyses were performed to verify the credibility of this simulation, including the meteorological fields and concentration fields. The sources were then categorized using two different classification methods (the district-based and type-based methods), and the contributions to the pollutant concentrations from each source category were computed to provide a basis for appropriate control measures. The statistical indexes showed that CALMET had sufficient ability to predict the meteorological conditions, such as the wind fields and temperatures, which provided meteorological data for the subsequent CALPUFF run. The simulated concentrations from CALPUFF showed considerable agreement with the observed values but were generally underestimated. The spatial-temporal concentration pattern revealed that the maximum concentrations tended to appear in the urban centers and during the winter. In terms of their contributions to pollutant concentrations, the districts of Xihu, Pingshan, and Mingshan all affected the urban air quality to different degrees. According to the type-based classification, which categorized the pollution sources as belonging to the Bengang Group, large point sources, small point sources, and area sources, the source apportionment showed that the Bengang Group, the large point sources, and the area sources had considerable impacts on urban air quality. Finally, combined with the industrial characteristics, detailed control measures were proposed with which local policy makers could improve the urban air quality in Benxi. In summary, the results of this study showed that this framework has credibility for effectively improving urban air quality, based on the source apportionment of atmospheric pollutants.

Implications: The authors endeavored to build up an effective framework based on the integrated WRF/CALPUFF to improve the air quality in many cities on meso-micro scales in China. Via this framework, the integrated modeling tool is accurately used to study the characteristics of meteorological fields, concentration fields, and source apportionments of pollutants in target area. The impacts of classified sources on air quality together with the industrial characteristics can provide more effective control measures for improving air quality.

Through the case study, the technical framework developed in this study, particularly the source apportionment, could provide important data and technical support for policy makers to assess air pollution on the scale of a city in China or even the world.     

Combined effect of boundary layer recirculation factor and stable energy on local air quality in the Pearl River Delta over southern China

Atmospheric boundary layer (ABL) has a significant impact on the spatial and temporal distribution of air pollutants. In order to gain a better understanding of how ABL affects the variation of air pollutants, atmospheric boundary layer observations were performed at Sanshui in the Pearl River Delta (PRD) region over southern China during the winter of 2013. Two types of typical ABL status that could lead to air pollution were analyzed comparatively: weak vertical diffusion ability type (WVDAT) and weak horizontal transportation ability type (WHTAT). Results show that (1) WVDAT was featured by moderate wind speed, consistent wind direction, and thick inversion layer at 600~1000 m above ground level (AGL), and air pollutants were restricted in the low altitudes due to the stable atmospheric structure; (2) WHTAT was characterized by calm wind, varied wind direction, and shallow intense ground inversion layer, and air pollutants accumulated in locally because of strong recirculation in the low ABL; (3) recirculation factor (RF) and stable energy (SE) were proved to be good indicators for horizontal transportation ability and vertical diffusion ability of the atmosphere, respectively. Combined utilization of RF and SE can be very helpful in the evaluation of air pollution potential of the ABL.

Implications: Air quality data from ground and meteorological data collected from radio sounding in Sanshui in the Pearl River Delta showed that local air quality was poor when wind reversal was pronounced or temperature stratification state was stable. The combination of horizontal and vertical transportation ability of the local atmosphere should be taken into consideration when evaluating local environmental bearing capacity for air pollution.     

Public health and components of particulate matter: The changing assessment of black carbon

In 2012, the WHO classified diesel emissions as carcinogenic, and its European branch suggested creating a public health standard for airborne black carbon (BC). In 2011, EU researchers found that life expectancy could be extended four to nine times by reducing a unit of BC, vs reducing a unit of PM_2.5. Only recently could such determinations be made. Steady improvements in research methodologies now enable such judgments.

In this Critical Review, we survey epidemiological and toxicological literature regarding carbonaceous combustion emissions, as research methodologies improved over time. Initially, we focus on studies of BC, diesel, and traffic emissions in the Western countries (where daily urban BC emissions are mainly from diesels). We examine effects of other carbonaceous emissions, e.g., residential burning of biomass and coal without controls, mainly in developing countries.

Throughout the 1990s, air pollution epidemiology studies rarely included species not routinely monitored. As additional PM_2.5. chemical species, including carbonaceous species, became more widely available after 1999, they were gradually included in epidemiological studies. Pollutant species concentrations which more accurately reflected subject exposure also improved models.

Natural “interventions” - reductions in emissions concurrent with fuel changes or increased combustion efficiency; introduction of ventilation in highway tunnels; implementation of electronic toll payment systems – demonstrated health benefits of reducing specific carbon emissions. Toxicology studies provided plausible biological mechanisms by which different PM species, e.g., carbonaceous species, may cause harm, aiding interpretation of epidemiological studies.

Our review finds that BC from various sources appears to be causally involved in all-cause, lung cancer, and cardiovascular mortality, morbidity, and perhaps adverse birth and nervous system effects. We recommend that the U.S. EPA rubric for judging possible causality of PM_2.5. mass concentrations, be used to assess which PM_2.5. species are most harmful to public health.

Implications: Black carbon (BC) and correlated co-emissions appear causally related with all-cause, cardiovascular, and lung cancer mortality, and perhaps with adverse birth outcomes and central nervous system effects. Such findings are recent, since widespread monitoring for BC is also recent. Helpful epidemiological advances (using many health relevant PM_2.5 species in models; using better measurements of subject exposure) have also occurred. “Natural intervention” studies also demonstrate harm from partly combusted carbonaceous emissions. Toxicology studies consistently find biological mechanisms explaining how such emissions can cause these adverse outcomes. A consistent mechanism for judging causality for different PM_2.5 species is suggested.

A list of acronyms will be found at the end of the article.     

Long-term dust aerosol production from natural sources in Iceland

Iceland is a volcanic island in the North Atlantic Ocean with maritime climate. In spite of moist climate, large areas are with limited vegetation cover where >40% of Iceland is classified with considerable to very severe erosion and 21% of Iceland is volcanic sandy deserts. Not only do natural emissions from these sources influenced by strong winds affect regional air quality in Iceland (“Reykjavik haze”), but dust particles are transported over the Atlantic ocean and Arctic Ocean >1000 km at times. The aim of this paper is to place Icelandic dust production area into international perspective, present long-term frequency of dust storm events in northeast Iceland, and estimate dust aerosol concentrations during reported dust events.

Meteorological observations with dust presence codes and related visibility were used to identify the frequency and the long-term changes in dust production in northeast Iceland. There were annually 16.4 days on average with reported dust observations on weather stations within the northeastern erosion area, indicating extreme dust plume activity and erosion within the northeastern deserts, even though the area is covered with snow during the major part of winter. During the 2000s the highest occurrence of dust events in six decades was reported. We have measured saltation and Aeolian transport during dust/volcanic ash storms in Iceland, which give some of the most intense wind erosion events ever measured.

Icelandic dust affects the ecosystems over much of Iceland and causes regional haze. It is likely to affect the ecosystems of the oceans around Iceland, and it brings dust that lowers the albedo of the Icelandic glaciers, increasing melt-off due to global warming. The study indicates that Icelandic dust may contribute to the Arctic air pollution.

Implications: Long-term records of meteorological dust observations from Northeast Iceland indicate the frequency of dust events from Icelandic deserts. The research involves a 60-year period and provides a unique perspective of the dust aerosol production from natural sources in the sub-Arctic Iceland. The amounts are staggering, and with this paper, it is clear that Icelandic dust sources need to be considered among major global dust sources. This paper presents the dust events directly affecting the air quality in the Arctic region.     

Validation of a new method for measuring and continuously monitoring the efficiency of industrial flares

A new method has been developed for a direct and remote measurement of industrial flare combustion efficiency (CE). The method is based on a unique hyper-spectral or multi-spectral Infrared (IR) imager which provides a high frame rate, high spectral selectivity and high spatial resolution. The method can be deployed for short-term flare studies or for permanent installation providing real-time continuous flare CE monitoring.

In addition to the measurement of CE, the method also provides a measurement for level of smoke in the flare flame regardless of day or night. The measurements of both CE and smoke level provide the flare operator with a real-time tool to achieve “incipient smoke point” and optimize flare performance.

The feasibility of this method was first demonstrated in a bench scale test. The method was recently tested on full scale flares along with extractive sampling methods to validate the method. The full scale test included three types of flares – steam assisted, air assisted, and pressure assisted. Thirty-nine test runs were performed covering a CE range of approximately 60-100%. The results from the new method showed a strong agreement with the extractive methods (r²=0.9856 and average difference in CE measurement=0.5%).

Implications: Because industrial flares are operated in the open atmosphere, direct measurement of flare combustion efficiency (CE) has been a long-standing technological challenge. Currently flare operators do not have feedback in terms of flare CE and smoke level, and it is extremely difficult for them to optimize flare performance and reduce emissions. The new method reported in this paper could provide flare operators with real-time data for CE and smoke level so that flare operations can be optimized. In light of EPA’s focus on flare emissions and its new rules to reduce emissions from flares, this policy-relevant development in flare CE monitoring is brought to the attention of both the regulating and regulated communities.     

In-vehicle carbon dioxide concentration in commuting cars in Bangkok,Thailand

It is known that in-vehicle carbon dioxide (CO₂) concentration tends to increase due to occupant exhalation when the HVAC (heating, ventilation, and air conditioning) air is in recirculation mode. Field experiments were conducted to measure CO₂ concentration during typical commute in Bangkok, Thailand. The measured concentrations agreed with the concentration predicted using first-order mass balance equation, in both recirculating and outside air modes. The long-term transient decay of the concentration when the vehicle was parked and the HVAC system was turned off was also studied. This decay was found to follow Fickian diffusion process. The paper also provides useful operational details of the automotive HVAC system and fresh air ventilation exchange between cabin interior and exterior.

Implications: Drivers in tropical Asian countries typically use HVAC recirculation mode in their automobiles. This behavior leads to excessive buildup of cabin CO₂ concentration levels. The paper describes the CO₂ buildup in a typical commute in Bangkok, Thailand. Auto manufacturers can potentially take measures to alleviate such high concentration levels. The paper also discusses the diffusion of CO₂ through the vehicle envelope, an area that has never been investigated before.     

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.     

Changes in weather and climate extremes: State of knowledge relevant to air and water quality in the United States

Air and water quality are impacted by extreme weather and climate events on time scales ranging from minutes to many months. This review paper discusses the state of knowledge of how and why extreme events are changing and are projected to change in the future. These events include heat waves, cold waves, floods, droughts, hurricanes, strong extratropical cyclones such as nor'easters, heavy rain, and major snowfalls. Some of these events, such as heat waves, are projected to increase, while others, with cold waves being a good example, will decrease in intensity in our warming world. Each extreme's impact on air or water quality can be complex and can even vary over the course of the event.

Implications:

Because extreme weather and climate events impact air and water quality, understanding how the various extremes are changing and are projected to change in the future has ramifications on air and water quality management.     

A review of polychlorinated biphenyls (PCBs) pollution in indoor air environment

Polychlorinated biphenyls (PCBs) were widely used in industrial production due to the unique physical and chemical properties. As a kind of persistent organic pollutants, the PCBs would lead to environment pollution and cause serious problems for human health. Thus, they have been banned since the 1980s due to the environment pollution in the past years. Indoor air is the most direct and important environment medium to human beings; thus, the PCBs pollution research in indoor air is important for the protection of human health. This paper introduces the industrial application and potential harm of PCBs, summarizes the sampling, extracting, and analytical methods of environment monitoring, and compares the indoor air levels of urban areas with those of industrial areas in different countries according to various reports. This paper can provide a basic summary for PCBs pollution control in the indoor air environment.

Implications: The review of PCBs pollution in indoor air in China is still limited. In this paper, we introduce the industrial application and potential harm of PCBs, summarize the sampling, extracting, and analytical methods of environment monitoring, and compare the indoor air levels of urban areas with industrial areas in different countries according to various reports.     

Modeling to Evaluate Contribution of Oil and Gas Emissions to Air Pollution

Oil and gas production in the Western United States has increased considerably over the past 10 years. While many of the still limited oil and gas impact assessments have focused on potential human health impacts, the typically remote locations of production in the Intermountain West suggests that the impacts of oil and gas production on national parks and wilderness areas (Class I and II areas) could also be important. To evaluate this, we utilize the Comprehensive Air quality Model with Extensions (CAMx) with a year-long modeling episode representing the best available representation of 2011 meteorology and emissions for the Western United States. The model inputs for the 2011 episodes were generated as part of the Three State Air Quality Study (3SAQS). The study includes a detailed assessment of oil and gas (O&G) emissions in Western States. The year-long modeling episode was run both with and without emissions from O&G production. The difference between these two runs provides an estimate of the contribution of the O&G production to air quality. These data were used to assess the contribution of O&G to the 8 hour average ozone concentrations, daily and annual fine particulate concentrations, annual nitrogen deposition totals and visibility in the modeling domain. We present the results for the Class I and II areas in the Western United States. Modeling results suggest that emissions from O&G activity are having a negative impact on air quality and ecosystem health in our National Parks and Class I areas.

Implications: In this research, we use a modeling framework developed for oil and gas evaluation in the western United States to determine the modeled impacts of emissions associated with oil and gas production on air pollution metrics. We show that oil and gas production may have a significant negative impact on air quality and ecosystem health in some national parks and other Class I areas in the western United States. Our findings are of particular interest to federal land managers as well as regulators in states heavy in oil and gas production as they consider control strategies to reduce the impact of development.     

Understanding the emission impacts of high-occupancy vehicle (HOV) to high-occupancy toll (HOT) lane conversions: Experience from Atlanta,Georgia

Converting a congested high-occupancy vehicle (HOV) lane into a high-occupancy toll (HOT) lane is a viable option for improving travel time reliability for carpools and buses that use the managed lane. However, the emission impacts of HOV-to-HOT conversions are not well understood. The lack of emission impact quantification for HOT conversions creates a policy challenge for agencies making transportation funding choices. The goal of this paper is to evaluate the case study of before-and-after changes in vehicle emissions for the Atlanta, Georgia, I-85 HOV/HOT lane conversion project, implemented in October 2011. The analyses employed the Motor Vehicle Emission Simulator (MOVES) for project-level analysis with monitored changes in vehicle activity data collected by Georgia Tech researchers for the Georgia Department of Transportation (GDOT). During the quarterly field data collection from 2010 to 2012, more than 1.5 million license plates were observed and matched to vehicle class and age information using the vehicle registration database. The study also utilized the 20-sec, lane-specific traffic operations data from the Georgia NaviGAtor intelligent transportation system, as well as a direct feed of HOT lane usage data from the State Road and Tollway Authority (SRTA) managed lane system. As such, the analyses in this paper simultaneously assessed the impacts associated with changes in traffic volumes, on-road operating conditions, and fleet composition before and after the conversion. Both greenhouse gases and criteria pollutants were examined.

Implications: A straight before-after analysis showed about 5% decrease in air pollutants and carbon dioxide (CO₂). However, when the before-after calendar year of analysis was held constant (to account for the effect of 1 yr of fleet turnover), mass emissions at the analysis site during peak hours increased by as much as 17%, with little change in CO₂. Further investigation revealed that a large percentage decrease in criteria pollutants in the straight before-after analysis was associated with a single calendar year change in MOVES. Hence, the Atlanta, Georgia, results suggest that an HOV-to-HOT conversion project may have increased mass emissions on the corridor. The results also showcase the importance of obtaining on-road data for emission impact assessment of HOV-to-HOT conversion projects.     

The effects of deterioration and technological levels on pollutant emission factors for gasoline light-duty trucks

Vehicle deterioration and technological change influence emission factors (EFs). In this study, the impacts of vehicle deterioration and emission standards on EFs of regulated pollutants (carbon monoxide [CO], hydrocarbon [HC], and nitrogen oxides [NO_x]) for gasoline light-duty trucks (LDTs) were investigated according to the inspection and maintenance (I/M) data using a chassis dynamometer method. Pollutant EFs for LDTs markedly varied with accumulated mileages and emission standards, and the trends of EFs are associated with accumulated mileages. In addition, the study also found that in most cases, the median EFs of CO, HC, and NO_x are higher than those of basic EFs in the International Vehicle Emissions (IVE) model; therefore, the present study provides correction factors for the IVE model relative to the corresponding emission standards and mileages.

Implications: Currently, vehicle emissions are great contributors to air pollution in cities, especially in developing countries. Emission factors play a key role in creating emission inventory and estimating emissions. Deterioration represented by vehicle age and accumulated mileage and changes of emission standards markedly influence emission factors. In addition, the results provide collection factors for implication in the IVE model in the region levels.     

Probability analyses of combining background concentrations with model-predicted concentrations

In order to calculate total concentrations for comparison to ambient air quality standards, monitored background concentrations are often combined with model predicted concentrations. Models have low skill in predicting the locations or time series of observed concentrations. Further, adding fixed points on the probability distributions of monitored and predicted concentrations is very conservative and not mathematically correct. Simply adding the 99th percentile predicted to the 99th percentile background will not yield the 99th percentile of the combined distributions. Instead, an appropriate distribution can be created by calculating all possible pairwise combinations of the 1-hr daily maximum observed background and daily maximum predicted concentration, from which a 99th percentile total value can be obtained. This paper reviews some techniques commonly used for determining background concentrations and combining modeled and background concentrations. The paper proposes an approach to determine the joint probabilities of occurrence of modeled and background concentrations. The pairwise combinations approach yields a more realistic prediction of total concentrations than the U.S. Environmental Protection Agency's (EPA) guidance approach and agrees with the probabilistic form of the National Ambient Air Quality Standards.

Implications: EPA's current approaches to determining background concentrations for compliance modeling purposes often lead to “double counting” of background concentrations and actual plume impacts and thus lead to overpredictions of total impacts. Further, the current Tier 1 approach of simply adding the top ends of the background and model predicted concentrations (e.g., adding the 99th percentiles of these distributions together) results in design value concentrations at probabilities in excess of the form of the National Ambient Air Quality Standards.     

The study on biomass fraction estimate methodology of municipal solid waste incinerator in Korea

In Korea, the amount of greenhouse gases released due to waste materials was 14,800,000 t CO₂eq in 2012, which increased from 5,000,000 t CO₂eq in 2010. This included the amount released due to incineration, which has gradually increased since 2010. Incineration was found to be the biggest contributor to greenhouse gases, with 7,400,000 t CO₂eq released in 2012. Therefore, with regards to the trading of greenhouse gases emissions initiated in 2015 and the writing of the national inventory report, it is important to increase the reliability of the measurements related to the incineration of waste materials.

This research explored methods for estimating the biomass fraction at Korean MSW incinerator facilities and compared the biomass fractions obtained with the different biomass fraction estimation methods. The biomass fraction was estimated by the method using default values of fossil carbon fraction suggested by IPCC, the method using the solid waste composition, and the method using incinerator flue gas.

The highest biomass fractions in Korean municipal solid waste incinerator facilities were estimated by the IPCC Default method, followed by the MSW analysis method and the Flue gas analysis method. Therefore, the difference in the biomass fraction estimate was the greatest between the IPCC Default and the Flue gas analysis methods. The difference between the MSW analysis and the flue gas analysis methods was smaller than the difference with IPCC Default method. This suggested that the use of the IPCC default method cannot reflect the characteristics of Korean waste incinerator facilities and Korean MSW.

Implications: Incineration is one of most effective methods for disposal of municipal solid waste (MSW). This paper investigates the applicability of using biomass content to estimate the amount of CO₂ released, and compares the biomass contents determined by different methods in order to establish a method for estimating biomass in the MSW incinerator facilities of Korea. After analyzing the biomass contents of the collected solid waste samples and the flue gas samples, the results were compared with the Intergovernmental Panel on Climate Change (IPCC) method, and it seems that to calculate the biomass fraction it is better to use the flue gas analysis method than the IPCC method. It is valuable to design and operate a real new incineration power plant, especially for the estimation of greenhouse gas emissions.     

A fuel-based approach for emission factor development for highway paving construction equipment in China

The objective of this paper is to develop and demonstrate a fuel-based approach for emissions factor estimation for highway paving construction equipment in China for better accuracy. A highway construction site in Chengdu was selected for this study with NO emissions being characterized and demonstrated. Four commonly used paving equipment, i.e., three rollers and one paver were selected in this study. A portable emission measurement system (PEMS) was developed and used for emission measurements of selected equipment during real–world highway construction duties. Three duty modes were defined to characterize the NO emissions, i.e., idling, moving, and working. In order to develop a representative emission factor for these highway construction equipment, composite emission factors were estimated using modal emission rates and the corresponding modal durations in the process of typical construction duties. Depending on duty mode and equipment type, NO emission rate ranged from 2.6–63.7mg/s and 6.0–55.6g/kg–fuel with the fuel consumption ranging from 0.31–4.52 g/s correspondingly. The NO composite emission factor was estimated to be 9–41mg/s with the single-drum roller being the highest and double-drum roller being the lowest and 6–30g/kg-fuel with the pneumatic tire roller being the highest while the double-drum roller being the lowest. For the paver, both time-based and fuel consumption-based NO composite emission rates are higher than all of the rollers with 56mg/s and 30g/kg-fuel, respectively. In terms of time–based quantity, the working mode contributes more than the other modes with idling being the least for both emissions and fuel consumption. In contrast, the fuel-based emission rate appears to have less variability in emissions. Thus, in order to estimate emission factors for emission inventory development, the fuel-based emission factor may be selected for better accuracy.

Implications: The fuel-based composite emissions factors will be less variable and more accurate than time-based emission factors. As a consequence, emissions inventory developed using this approach will be more accurate and practical.     

Investigating the real-world emission characteristics of light-duty gasoline vehicles and their relationship to local socioeconomic conditions in three communities in Los Angeles,California

This paper discusses results from a vehicular emissions research study of over 350 vehicles conducted in three communities in Los Angeles, CA, in 2010 using vehicle chase measurements. The study explores the real-world emission behavior of light-duty gasoline vehicles, characterizes real-world super-emitters in the different regions, and investigates the relationship of on-road vehicle emissions with the socioeconomic status (SES) of the region. The study found that in comparison to a 2007 earlier study in a neighboring community, vehicle emissions for all measured pollutants had experienced a significant reduction over the years, with oxides of nitrogen (NO_X) and black carbon (BC) emissions showing the largest reductions. Mean emission factors of the sampled vehicles in low-SES communities were roughly 2–3 times higher for NO_X, BC, carbon monoxide, and ultrafine particles, and 4–11 times greater for fine particulate matter (PM_2.5) than for vehicles in the high-SES neighborhood. Further analysis indicated that the emission factors of vehicles within a technology group were also higher in low-SES communities compared to similar vehicles in the high-SES community, suggesting that vehicle age alone did not explain the higher vehicular emission in low-SES communities.

Evaluation of the emission factor distribution found that emissions from 12% of the sampled vehicles were greater than five times the mean from all of the sampled fleet, and these vehicles were consequently categorized as “real-world super-emitters.” Low-SES communities had approximately twice as many super-emitters for most of the pollutants as compared to the high-SES community. Vehicle emissions calculated using model-year-specific average fuel consumption assumptions suggested that approximately 5% of the sampled vehicles accounted for nearly half of the total CO, PM_2.5, and UFP emissions, and 15% of the vehicles were responsible for more than half of the total NO_X and BC emissions from the vehicles sampled during the study.

Implications: This study evaluated the real-world emission behavior and super-emitter distribution of light-duty gasoline vehicles in California, and investigated the relationship of on-road vehicle emissions with local socioeconomic conditions. The study observed a significant reduction in vehicle emissions for all measured pollutants when compared to an earlier study in Wilmington, CA, and found a higher prevalence of high-emitting vehicles in low-socioeconomic-status communities. As overall fleet emissions decrease from stringent vehicle emission regulations, a small fraction of the fleet may contribute to a disproportionate share of the overall on-road vehicle emissions. Therefore, this work will have important implications for improving air quality and public health, especially in low-SES communities.     

Ambient air concentrations exceeded health-based standards for fine particulate matter and benzene during the Deepwater Horizon oil spill

The Deepwater Horizon oil spill is considered one of the largest marine oil spills in the history of the United States. Air emissions associated with the oil spill caused concern among residents of Southeast Louisiana. The purpose of this study was to assess ambient concentrations of benzene (n=3,887) and fine particulate matter (n=102,682) during the oil spill and to evaluate potential exposure disparities in the region. Benzene and fine particulate matter (PM2.5) concentrations in the targeted parishes were generally higher following the oil spill, as expected. Benzene concentrations reached 2 to 19 times higher than background, and daily exceedances of PM2.5 were 10 to 45 times higher than background. Both benzene and PM2.5 concentrations were considered high enough to exceed public health criteria, with measurable exposure disparities in the coastal areas closer to the spill and clean-up activities. These findings raise questions about public disclosure of environmental health risks associated with the oil spill. The findings also provide a science-based rationale for establishing health-based action levels in future disasters.

Implications: Benzene and particulate matter monitoring during the Deepwater Horizon oil spill revealed that ambient air quality was a likely threat to public health and that residents in coastal Louisiana experienced significantly greater exposures than urban residents. Threshold air pollution levels established for the oil spill apparently were not used as a basis for informing the public about these potential health impacts. Also, despite carrying out the most comprehensive air monitoring ever conducted in the region, none of the agencies involved provided integrated analysis of the data or conclusive statements about public health risk. Better information about real-time risk is needed in future environmental disasters.     

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.