Synthesis of Harvard Environmental Protection Agency (EPA) Center studies on traffic-related particulate pollution and cardiovascular outcomes in the Greater Boston Area

The association between particulate pollution and cardiovascular morbidity and mortality is well established. While the cardiovascular effects of nationally regulated criteria pollutants (e.g., fine particulate matter [PM_2.5] and nitrogen dioxide) have been well documented, there are fewer studies on particulate pollutants that are more specific for traffic, such as black carbon (BC) and particle number (PN). In this paper, we synthesized studies conducted in the Greater Boston Area on cardiovascular health effects of traffic exposure, specifically defined by BC or PN exposure or proximity to major roadways. Large cohort studies demonstrate that exposure to traffic-related particles adversely affect cardiac autonomic function, increase systemic cytokine-mediated inflammation and pro-thrombotic activity, and elevate the risk of hypertension and ischemic stroke. Key patterns emerged when directly comparing studies with overlapping exposure metrics and population cohorts. Most notably, cardiovascular risk estimates of PN and BC exposures were larger in magnitude or more often statistically significant compared to those of PM_2.5 exposures. Across multiple exposure metrics (e.g., short-term vs. long-term; observed vs. modeled) and different population cohorts (e.g., elderly, individuals with co-morbidities, young healthy individuals), there is compelling evidence that BC and PN represent traffic-related particles that are especially harmful to cardiovascular health. Further research is needed to validate these findings in other geographic locations, characterize exposure errors associated with using monitored and modeled traffic pollutant levels, and elucidate pathophysiological mechanisms underlying the cardiovascular effects of traffic-related particulate pollutants.

Implications: Traffic emissions are an important source of particles harmful to cardiovascular health. Traffic-related particles, specifically BC and PN, adversely affect cardiac autonomic function, increase systemic inflammation and thrombotic activity, elevate BP, and increase the risk of ischemic stroke. There is evidence that BC and PN are associated with greater cardiovascular risk compared to PM_2.5. Further research is needed to elucidate other health effects of traffic-related particles and assess the feasibility of regulating BC and PN or their regional and local sources.     

Evaluation of gas well setback policy in the Marcellus Shale region of Pennsylvania in relation to emissions of fine particulate matter

Shale gas has become an important strategic energy source with considerable potential economic benefits and the potential to reduce greenhouse gas emissions in so far as it displaces coal use. However, there still exist environmental health risks caused by emissions from exploration and production activities. In the United States, states and localities have set different minimum setback policies to reduce the health risks corresponding to the emissions from these locations, but it is unclear whether these policies are sufficient. This study uses a Gaussian plume model to evaluate the probability of exposure exceedance from EPA concentration limits for PM2.5 at various locations around a generic wellsite in the Marcellus shale region. A set of meteorological data monitored at ten different stations across Marcellus shale gas region in Pennsylvania during 2015 serves as an input to this model. Results indicate that even though the current setback distance policy in Pennsylvania (500 ft. or 152.4 m) might be effective in some cases, exposure limit exceedance occurs frequently at this distance with higher than average emission rates and/or greater number of wells per wellpad. Setback distances should be 736 m to ensure compliance with the daily average concentration of PM2.5, and a function of the number of wells to comply with the annual average PM2.5 exposure standard.

Implications: The Marcellus Shale gas is known as a significant source of criteria pollutants and studies show that the current setback distance in Pennsylvania is not adequate to protect the residents from exceeding the established limits. Even an effective setback distance to meet the annual exposure limit may not be adequate to meet the daily limit. The probability of exceeding the annual limit increases with number of wells per site. We use a probabilistic dispersion model to introduce a technical basis to select appropriate setback distances.     

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.     

Revisiting nitrous acid (HONO) emission from on-road vehicles: A tunnel study with a mixed fleet

Nitrous acid (HONO) is an important precursor of OH radicals in the atmosphere. In urban areas, emissions from vehicles are the main source of air pollutants, including reactive nitrogen. Previously reported emission ratios of HONO (HONO/NO_x) from vehicles were measured in the late 1990s and need to be updated due to the significant changes in emission control technologies. We measured the emission ratio of a fleet of vehicles (38% diesel on average) from March 11 to 21, 2015, in a road tunnel in Hong Kong. The emission ratio of 1.24% (±0.35%) obtained is greater than the commonly adopted 0.8% or 0.3%. The elevated emission ratio is found to be related to the presence of vehicles equipped with diesel particle filters (DPFs). Positive correlation between HONO and black carbon (BC) shows that HONO and BC were emitted together, while the lack of correlation or even anticorrelation between HONO/NO_x and BC indicates that the BC-mediated conversion of NO₂ to HONO in the dark was insignificant in the immediate vicinity of the emission sources.

Implications: Vehicular emission is a key source for HONO in the urban atmosphere. However, the most commonly used emission ratio HONO/NO_x in modeling studies was measured more than 15 years ago. Our tunnel study suggests that a mixed fleet nowadays has a higher emission ratio, possibly because of the diesel particle filter (DPF) retrofit program and the growing share of Euro IV or more advanced diesel vehicles. Our study also provides new insight into the role of black carbon in HONO formation from vehicles.     

Emission factors of fine particulate matter,organic and elemental carbon,carbon monoxide,and carbon dioxide for four solid fuels commonly used in residential heating by the U.S. Navajo Nation

Most homes in the Navajo Nation use wood as their primary heating fuel, often in combination with locally mined coal. Previous studies observed health effects linked to this solid-fuel use in several Navajo communities. Emission factors (EFs) for common fuels used by the Navajo have not been reported using a relevant stove type. In this study, two softwoods (ponderosa pine and Utah juniper) and two high-volatile bituminous coals (Black Mesa and Fruitland) were tested with an in-use residential conventional wood stove (homestove) using a modified American Society for Testing and Materials/U.S. Environmental Protection Agency (ASTM/EPA) protocol. Filter sampling quantified PM_2.5 (particulate matter with an aerodynamic diameter ≤2.5 μm) and organic (OC) and elemental (EC) carbon in the emissions. Real-time monitoring quantified carbon monoxide (CO), carbon dioxide (CO₂), and total suspended particles (TSP). EFs for these air pollutants were developed and normalized to both fuel mass and energy consumed. In general, coal had significantly higher mass EFs than wood for all pollutants studied. In particular, coal emitted, on average, 10 times more PM_2.5 than wood on a mass basis, and 2.4 times more on an energy basis. The EFs developed here were based on fuel types, stove design, and operating protocols relevant to the Navajo Nation, but they could be useful to other Native Nations with similar practices, such as the nearby Hopi Nation.

Implications: Indoor wood and coal combustion is an important contributor to public health burdens in the Navajo Nation. Currently, there exist no emission factors representative of Navajo homestoves, fuels, and practices. This study developed emission factors for PM_2.5, OC, EC, CO, and CO₂ using a representative Navajo homestove. These emission factors may be utilized in regional-, national-, and global-scale health and environmental models. Additionally, the protocols developed and results presented here may inform on-going stove design of the first EPA-certified wood and coal combination stove.     

Evaluation of light-duty vehicle mobile source regulations on ozone concentration trends in 2018 and 2030 in the western and eastern United States

To improve U.S. air quality, there are many regulations on-the-way (OTW) and on-the-books (OTB), including mobile source California Low Emission Vehicle third generation (LEV III) and federal Tier 3 standards. This study explores the effects of those regulations by using the U.S. Environmental Protection Agency's (EPA) Community Multiscale Air Quality (CMAQ) model for 8-hr ozone concentrations in the western and eastern United States in the years 2018 and 2030 during a month with typical high ozone concentrations, July. Alterations in pollutant emissions can be due to technological improvements, regulatory amendments, and changes in growth. In order to project emission rates for future years, the impacts of all of these factors were estimated. This study emphasizes the potential light-duty vehicle emission changes by year to predict ozone levels. The results of this study show that most areas have decreases in 8-hr ozone concentrations in the year 2030, although there are some areas with increased concentrations. Additionally, there are areas with 8-hr ozone concentrations greater than the current U.S. National Ambient Air Quality Standard level, which is 75 ppb.

Implications:

To improve U.S. air quality, many regulations are on the way and on the books, including mobile source California LEV III and federal Tier 3 standards. This study explores the effects of those regulations for 8-hr ozone concentrations in the western and eastern United States in the years 2018 and 2030. The results of this study show that most areas have decreases in 8-hr ozone concentrations in 2030, although there are some areas with increased concentrations. Additionally, there are areas with 8-hr ozone concentrations greater than the current U.S. National Ambient Air Quality Standard level.     

Experimental and simulation study on bake-out with dilution ventilation technology for building materials

With recent improvements to living standards and renovations to many residential buildings, a large volume of new building materials have been utilized throughout China. Formaldehyde and other kinds of VOC pollutants, such as benzene, toluene and xylene found in new building materials, however, emit gases that may lead to some direct or potential health problems. Bake-out with dilution ventilation technology has the potential to shorten emission cycles of indoor air pollution, by which off-gassing from building materials can be reduced. In this paper, a test chamber was used to represent a newly renovated residential room in China. Experiments were conducted to study the applicability of the technology for removing of formaldehyde, benzene, toluene and xylene. A numerical method was used to simulate a 1 m3-chamber-TVOC removing amount under different operating conditions and the concentration change of TVOC during the bake-out exhaust dilution process. The effects of bake-out temperatures and times, ventilation times, and air change rates on removal are also discussed.

Implications: VOCs are the main study objective in this paper. With higher baking temperature, longer baking time and longer ventilation time, the removal efficiency is higher in experiment. Removal content of TVOC increases with the increasing number of ACH. With the consideration of energy consumption, it is more reasonable to choose a ventilation time of 4 hours if ACH is 1.2 times/h.     

Trends in onroad transportation energy and emissions

Globally, 1.3 billion on-road vehicles consume 79 quadrillion BTU of energy, mostly gasoline and diesel fuels, emit 5.7 gigatonnes of CO₂, and emit other pollutants to which approximately 200,000 annual premature deaths are attributed. Improved vehicle energy efficiency and emission controls have helped offset growth in vehicle activity. New technologies are diffusing into the vehicle fleet in response to fuel efficiency and emission standards. Empirical assessment of vehicle emissions is challenging because of myriad fuels and technologies, intervehicle variability, multiple emission processes, variability in operating conditions, and varying capabilities of measurement methods. Fuel economy and emissions regulations have been effective in reducing total emissions of key pollutants. Real-world fuel use and emissions are consistent with official values in the United States but not in Europe or countries that adopt European standards. Portable emission measurements systems, which uncovered a recent emissions cheating scandal, have a key role in regulatory programs to ensure conformity between “real driving emissions” and emission standards. The global vehicle fleet will experience tremendous growth, especially in Asia. Although existing data and modeling tools are useful, they are often based on convenience samples, small sample sizes, large variability, and unquantified uncertainty. Vehicles emit precursors to several important secondary pollutants, including ozone and secondary organic aerosols, which requires a multipollutant emissions and air quality management strategy. Gasoline and diesel are likely to persist as key energy sources to mid-century. Adoption of electric vehicles is not a panacea with regard to greenhouse gas emissions unless coupled with policies to change the power generation mix. Depending on how they are actually implemented and used, autonomous vehicles could lead to very large reductions or increases in energy consumption. Numerous other trends are addressed with regard to technology, emissions controls, vehicle operations, emission measurements, impacts on exposure, and impacts on public health.

Implications: Without specific policies to the contrary, fossil fuels are likely to continue to be the major source of on-road vehicle energy consumption. Fuel economy and emission standards are generally effective in achieving reductions per unit of vehicle activity. However, the number of vehicles and miles traveled will increase. Total energy use and emissions depend on factors such as fuels, technologies, land use, demographics, economics, road design, vehicle operation, societal values, and others that affect demand for transportation, mode choice, energy use, and emissions. Thus, there are many opportunities to influence future trends in vehicle energy use and emissions.     

Carbon monoxide emission rates from roasted whole bean and ground coffee

Carbon monoxide (CO) emitted from roasted coffee is a potential occupational respiratory exposure hazard to workers within the coffee industry. The current study objective was to estimate CO emission factors from commercially available roasted whole bean and ground coffee measured in loose form, not packaged, and to assess the utility of CO monitoring in nonventilated storage spaces such as within coffee roasting and packaging facilities, transport vessels, and cafés. Determinants affecting CO emissions from coffee were investigated, including form (whole bean vs. ground), roast level (light, medium, medium-dark, dark), and age (time since the package was opened). CO emission factors were estimated for roasted coffee samples from a variety of manufacturers purchased from local grocery stores and online. Emission tests were performed on 36 brands of coffee, some with more than one sample per brand and with various roast levels. Decaying source equations or smoothing functions were fitted to the CO concentration measurements. Maximum observed emission factors at the peak of the predicted concentration curve were adjusted by the time required to reach the maximum CO concentration and reported as emission factors (EF_buildup). Ground coffee had a significantly increased EF_buildup (P < 0.0001) compared with whole bean. Roast level did not significantly affect emissions for whole bean (P = 0.72) but did for ground (P < 0.001) coffee. For ground coffee, medium-dark and dark roasts had significantly higher emissions than medium and light roasts. Worst-case emission factors from commercially available whole bean and ground coffee measured in loose form, not packaged, showed that roasted coffee can rapidly emit CO. CO concentrations should be monitored in storage spaces in service and manufacturing facilities as well as transport vessels to ensure exposures do not exceed occupational exposure limits. Storage spaces may need to be ventilated to control CO concentrations to safe levels.

Implications: Emission rates of carbon monoxide (CO) from roasted coffee showed that unventilated or underventilated storage spaces should be monitored and ventilated, if necessary, to control CO concentrations to safe levels.     

Radon versus other lung cancer risk factors: How accurate are the attribution estimates?

This notebook paper provides a brief overview of attribution estimates for some key lung cancer risk factors, focusing on indoor radon gas exposure in the U.S., UK, and Canada. Tobacco smoking represents the primary cause of lung cancer worldwide. Radon is regarded as the second leading lung cancer risk factor in the U.S. and Canada. It can be observed, however, that the reported estimates appear not to add up to the maximum cumulative attribution of 100%.

Implications: Limitations and uncertainties associated with published epidemiological studies and the observed lack of consistency in lung cancer attribution estimates for radon and other non-smoking lung cancer risk factors should be taken into consideration by policy makers in setting population health protection priorities.     

Long-term associations of morbidity with air pollution: A catalog and synthesis

I searched the National Institutes of Health MEDLINE database through January 2017 for long-term studies of morbidity and air pollution and cataloged them with respect to cardiovascular, respiratory, cancer, diabetes, hospitalization, neurological, and pregnancy-birth endpoints. The catalog is presented as an online appendix. Associations with PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm), PM₁₀ (PM with an aerodynamic diameter <10 μm), and nitrogen dioxide (NO₂) were evaluated most frequently among the 417 ambient air quality studies identified. Associations with total suspended particles (TSP), carbon, ozone, sulfur, vehicular traffic, radon, and indoor air quality were also reported. I evaluated each study in terms of pollutant significance (yes, no), duration of exposure, and publication date. I found statistically significant pollutant relationships (P < 0.05) in 224 studies; 220 studies indicated adverse effects. Among 795 individual pollutant effect estimates, 396 are statistically significant. Pollutant associations with cardiovascular indicators, lung function, respiratory symptoms, and low birth weight are more likely to be significant than with disease incidence, heart attacks, diabetes, or neurological endpoints. Elemental carbon (EC), traffic, and PM_2.5 are most likely to be significant for cardiovascular outcomes; TSP, EC, and ozone (O₃) for respiratory outcomes; NO₂ for neurological outcomes; and PM₁₀ for birth/pregnancy outcomes. Durations of exposure range from 60 days to 35 yr, but I found no consistent relationships with the likelihood of statistical significance. Respiratory studies began ca. 1975; studies of diabetes, cardiovascular, and neurological effects increased after about 2005. I found 72 studies of occupational air pollution exposures; 40 reported statistically significant adverse health effects, especially for respiratory conditions. I conclude that the aggregate of these studies supports the existence of nonlethal physiological effects of various pollutants, more so for non–life-threatening endpoints and for noncriteria pollutants (TSP, EC, PM_2.5 metals). However, most studies were cross-sectional analyses over limited time spans with no consideration of lag or disease latency. Further longitudinal studies are thus needed to investigate the progress of disease incidence in association with air pollution exposure.

Implications: Relationships of air pollution with excess mortality are better known than with long-term antecedent morbidity. I cataloged 489 studies of cardiovascular, respiratory, cancer, and neurological effects, diabetes, and birth outcomes with respect to 12 air pollutants. About half of the studies reported statistically significant relationships, more frequently with noncriteria than with criteria pollutants. Indoor and cumulative exposures, coarse or ultrafine particles, and organic carbon were seldom considered. Significant relationships were more likely with less-severe endpoints such as blood pressure, lung function, or respiratory symptoms than with incidence of cancer, chronic obstructive pulmonary disease (COPD), heart failure, or diabetes. Most long-term studies are based on spatial relationships; longitudinal studies are needed to link the progression of pollution-related morbidity to mortality, especially for the cardiovascular system.     

Comparative statistical study of hourly precipitation determined by radar-based Stage IV and ground-based methods in the North Central United States

Detailed hourly precipitation data are required for long-range modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants using the CALPUFF model. In sparsely populated areas such as the north central United States, ground-based precipitation measurement stations may be too widely spaced to offer a complete and accurate spatial representation of hourly precipitation within a modeling domain. The availability of remotely sensed precipitation data by satellite and the National Weather Service array of next-generation radars (NEXRAD) deployed nationally provide an opportunity to improve on the paucity of data for these areas. Before adopting a new method of precipitation estimation in a modeling protocol, it should be compared with the ground-based precipitation measurements, which are currently relied upon for modeling purposes. This paper presents a statistical comparison between hourly precipitation measurements for the years 2006 through 2008 at 25 ground-based stations in the north central United States and radar-based precipitation measurements available from the National Center for Environmental Predictions (NCEP) as Stage IV data at the nearest grid cell to each selected precipitation station. It was found that the statistical agreement between the two methods depends strongly on whether the ground-based hourly precipitation is measured to within 0.1 in/hr or to within 0.01 in/hr. The results of the statistical comparison indicate that it would be more accurate to use gridded Stage IV precipitation data in a gridded dispersion model for a long-range simulation, than to rely on precipitation data interpolated between widely scattered rain gauges.

Implications:

The current reliance on ground-based rain gauges for precipitation events and hourly data for modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants results in potentially large discontinuity in data coverage and the need to extrapolate data between monitoring stations. The use of radar-based precipitation data, which is available for the entire continental United States and nearby areas, would resolve these data gaps and provide a complete and accurate spatial representation of hourly precipitation within a large modeling domain.     

Investigation of the effects of using single-wall carbon nanotubes (SWCNTs) in ozone measurement with passive samplers

Passive samplers are used in air quality monitoring for many years to compete in terms of being economical with continuous measurement systems. In this study, different amounts of single-wall carbon nanotubes (SWCNTs) were added in the impregnation solution of the filters of passive samplers and the effect on the absorption of ozone studied. The results of the measurement of ozone with varying amounts of SWCNTs added to the impregnation solution of the filters of the passive samplers were compared with the results of the continuous ozone measurement system (CS). Measurements were performed for 7 days and 14 days at two different exposure times. The increase of the amount of SWCNTs on the filters of the passive samplers, however, did not have an effect on the measurement of ozone. The measurement results of the passive samplers of the 14-day exposure periods, alternating with the 7-day exposure periods, were lower considerably than the results of the 7-day exposure.

Implications: The accuracy and the use of passive samplers in SWCNTs are expected to provide high measurement results. Observing the effect of the change in the amount of diffusion of pollutants held in the SWCNT is also one of the expected implications.     

Analysis of short-term ozone and PM2.5 measurements: Characteristics and relationships for air sensor messaging

Air quality sensors are becoming increasingly available to the general public, providing individuals and communities with information on fine-scale, local air quality in increments as short as 1 min. Current health studies do not support linking 1-min exposures to adverse health effects; therefore, the potential health implications of such ambient exposures are unclear. The U.S. Environmental Protection Agency (EPA) establishes the National Ambient Air Quality Standards (NAAQS) and Air Quality Index (AQI) on the best science available, which typically uses longer averaging periods (e.g., 8 hr; 24 hr). Another consideration for interpreting sensor data is the variable relationship between pollutant concentrations measured by sensors, which are short-term (1 min to 1 hr), and the longer term averages used in the NAAQS and AQI. In addition, sensors often do not meet federal performance or quality assurance requirements, which introduces uncertainty in the accuracy and interpretation of these readings. This article describes a statistical analysis of data from regulatory monitors and new real-time technology from Village Green benches to inform the interpretation and communication of short-term air sensor data. We investigate the characteristics of this novel data set and the temporal relationships of short-term concentrations to 8-hr average (ozone) and 24-hr average (PM_2.5) concentrations to examine how sensor readings may relate to the NAAQS and AQI categories, and ultimately to inform breakpoints for sensor messages. We consider the empirical distributions of the maximum 8-hr averages (ozone) and 24-hr averages (PM_2.5) given the corresponding short-term concentrations, and provide a probabilistic assessment. The result is a robust, empirical comparison that includes events of interest for air quality exceedances and public health communication. Concentration breakpoints are developed for short-term sensor readings such that, to the extent possible, the related air quality messages that are conveyed to the public are consistent with messages related to the NAAQS and AQI.

Implications: Real-time sensors have the potential to provide important information about fine-scale current air quality and local air quality events. The statistical analysis of short-term regulatory and sensor data, coupled with policy considerations and known health effects experienced over longer averaging times, supports interpretation of such short-term data and efforts to communicate local air quality.     

The development of sulfur dioxide and ozone exposure profiles that mimic ambient conditions in the rural southeastern united states

A design for constructing experimental mixed-pollutant exposure profiles that reflect regional O₃ and SO₂ ambient air quality is described. The profiles were developed using hour-by-hour O₃ and SO₂ concentration data from monitoring sites in the southeastern United States where slash pine is indigenous. Only sites designated rural or remote, with co-monitored O₃ and SO₂, and at least 75% of the hourly values reported for the period April– October, were used. Each site was characterized by concentration, frequency of occurrence and duration of concentration values, length of time between episodes, and frequency of cooccurrence. A base profile, a 30-day hour-by-hour concentration regime, was constructed using averaged air quality characteristics from the selected sites. Using the base profile, additional regimes were constructed by increasing the concentration of all hourly values above a designated minimum, or by increasing the frequency of occurrence of selected hourly concentrations.     

Simulating the meteorology and PM10 concentrations in Arizona dust storms using the Weather Research and Forecasting model with Chemistry (Wrf-Chem)

Nine dust storms in south-central Arizona were simulated with the Weather Research and Forecasting with Chemistry model (WRF-Chem) at 2 km resolution. The windblown dust emission algorithm was the Air Force Weather Agency model. In comparison with ground-based PM₁₀ observations, the model unevenly reproduces the dust-storm events. The model adequately estimates the location and timing of the events, but it is unable to precisely replicate the magnitude and timing of the elevated hourly concentrations of particles 10 µm and smaller ([PM₁₀]).Furthermore, the model underestimated [PM₁₀] in highly agricultural Pinal County because it underestimated surface wind speeds and because the model’s erodible fractions of the land surface data were too coarse to effectively resolve the active and abandoned agricultural lands. In contrast, the model overestimated [PM₁₀] in western Arizona along the Colorado River because it generated daytime sea breezes (from the nearby Gulf of California) for which the surface-layer speeds were too strong. In Phoenix, AZ, the model’s performance depended on the event, with both under- and overestimations partly due to incorrect representation of urban features. Sensitivity tests indicate that [PM₁₀] highly relies on meteorological forcing. Increasing the fraction of erodible surfaces in the Pinal County agricultural areas improved the simulation of [PM₁₀] in that region. Both 24-hr and 1-hr measured [PM₁₀] were, for the most part, and especially in Pinal County, extremely elevated, with the former exceeding the health standard by as much as 10-fold and the latter exceeding health-based guidelines by as much as 70-fold. Monsoonal thunderstorms not only produce elevated [PM₁₀], but also cause urban flash floods and disrupt water resource deliveries. Given the severity and frequency of these dust storms, and conceding that the modeling system applied in this work did not produce the desired agreement between simulations and observations, additional research in both the windblown dust emissions model and the weather research/physicochemical model is called for.

Implications: While many dust storms can be considered to be natural, in semi-arid climates such storms often have an anthropogenic component in their sources of dust. Applying the natural, exceptional events policy to these storms with strong signatures of anthropogenic sources would appear not only to be misguided but also to stifle genuine regulatory efforts at remediation. Those dust storms that have resulted, in part, from passage over abandoned farm land should no longer be considered “natural”; policymakers and lawmakers need to compel the owners of such land to reduce its potential for windblown dust.     

The relationship between atmospheric pollutant emissions and fuel qualities of inland vessels in Jiangsu Province,China

Air pollution caused by ship exhaust emission is receiving more and more attention. The physical and chemical properties of fuels, such as sulfur content and PAHs content, potentially had a significant influence on air pollutant emissions from inland vessels. In order to investigate the effects of fuel qualities on atmospheric pollutant emissions systematically, a series of experiments was conducted based on the method of actual ship testing. As a result, SO2, PM and NOx emission rates all increased with the increase of main engine rotating speed under cruise mode, while PM and NOx emission factors were inversely proportional to the main engine rotating speed. Moreover, SO2 emission factor changed little with the increase of the main engine rotating speed. In summary, the fuel-dependent specific emission of SO2 was a direct reflection of the sulfur content in fuel. The PM emission increased with the increase of sulfur content and PAHs content in fuel. However, fuel qualities impacted little on NOx emissions from inland vessels because of NOx formation mechanisms and conditions.

Implications: Ship activity is considered to be the third largest source of air pollution in China. In particular, air pollutants emitted from ships in river ports and waterways have a direct impact on regional air quality and pose threat on the health of local residents owing to high pollutants concentration and poor air diffusion. The study on the relationship between air pollutant emissions and fuel quality of inland vessels can provide foundational data for local authority to formulate reasonable and appropriate policies for reducing atmospheric pollution due to inland vessels.     

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.     

Air quality modeling for effective environmental management in the mining region

Air quality in the mining sector is a serious environmental concern and associated with many health issues. Air quality management in mining regions has been facing many challenges due to lack of understanding of atmospheric factors and physical removal mechanisms. A modeling approach called the mining air dispersion model (MADM) is developed to predict air pollutants concentration in the mining region while considering the deposition effect. The model takes into account the planet’s boundary conditions and assumes that the eddy diffusivity depends on the downwind distance. The developed MADM is applied to a mining site in Canada. The model provides values for the predicted concentrations of PM₁₀, PM_2.5, TSP, NO₂, and six heavy metals (As, Pb, Hg, Cd, Zn, Cr) at various receptor locations. The model shows that neutral stability conditions are dominant for the study site. The maximum mixing height is achieved (1280 m) during the evening in summer, and the minimum mixing height (380 m) is attained during the evening in winter. The dust fall (PM coarse) deposition flux is maximum during February and March with a deposition velocity of 4.67 cm/sec. The results are evaluated with the monitoring field values, revealing a good agreement for the target air pollutants with R-squared ranging from 0.72 to 0.96 for PM_2.5, from 0.71 to 0.82 for PM₁₀, and from 0.71 to 0.89 for NO₂. The analyses illustrate that the presented algorithm in this model can be used to assess air quality for the mining site in a systematic way. Comparisons of MADM and CALPUFF modeling values are made for four different pollutants (PM_2.5, PM₁₀, TSP, and NO₂) under three different atmospheric stability classes (stable, neutral, and unstable). Further, MADM results are statistically tested against CALPUFF for the air pollutants and model performance is found satisfactory.

Implications: The mathematical model (MADM) is developed by extending the Gaussian equation particularly when examining the settling process of important pollutants for the industrial region. Physical removal effects of air pollutants with field data have been considerred for the MADM development and for an extensive field case study. The model is well validated in the field of an open pit mine to assess the regional air quality. The MADA model helps to facilitate the management of the mining industry in doing estimation of emission rate around mining activities and predicting the resulted concentration of air pollutants together in one integrated approach.     

Assessment of indoor levels of volatile organic compounds and carbon dioxide in schools in Kuwait

Indoor air quality (IAQ) in schools is a matter of concern because children are most vulnerable and sensitive to pollutant exposure. Conservation of energy at the expense of ventilation in heating, ventilation, and air conditioning (HVAC) systems adversely affects IAQ. Extensive use of new materials in building, fitting, and refurbishing emit various pollutants such that the indoor environment creates its own discomfort and health risks. Various schools in Kuwait were selected to assess their IAQ. Comprehensive measurements of volatile organic compounds (VOCs) consisting of 72 organic compounds consisting of aliphatic (C₃–C₆), aromatic (C₆–C₉), halogenated (C₁–C₇), and oxygenated (C₂–C₉) functional groups in indoor air were made for the first time in schools in Kuwait. The concentrations of indoor air pollutants revealed hot spots (science preparation rooms, science laboratories, arts and crafts classes/paint rooms, and woodworking shops/decoration rooms where local sources contributed to the buildup of pollutants in each school. The most abundant VOC pollutant was chlorodifluoromethane (R22; ClF₂CH), which leaked from air conditioning (AC) systems due to improper operation and maintenance. The other copious VOCs were alcohols and acetone at different locations due to improper handling of the chemicals and their excessive uses as solvents. Indoor carbon dioxide (CO₂) levels were measured, and these levels reflected the performance of HVAC systems; a specific rate or lack of ventilation affected the IAQ. Recommendations are proposed to mitigate the buildup of indoor air pollutants at school sites.

Implications: Indoor air quality in elementary schools has been a subject of extreme importance due to susceptibility and sensibility of children to air pollutants. The schools were selected based on their surrounding environment especially downwind direction from the highly industrialized zone in Kuwait. Extensive sampling from different sites in four schools for comprehensive VOCs and CO₂ were completed for an extended period of over a year. Different hot spots were identified where leaked refrigerant and inadequate handling of laboratory solvents contributed to the high VOCs in the respective locations. CO₂ levels reflected HVAC performance and poor ventilation. A list of recommendations has been proposed to eradicate these high levels of air pollution.