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.     

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.     

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.     

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.     

Purification characteristics of fine particulate matter treated by a self-flushing wet electrostatic precipitator equipped with a flexible electrode

A self-flushing wet electrostatic precipitator was developed to investigate the removal performance for fine particles. Flexible material (polypropylene, 840A) and carbon steel in the form of a spiked band were adopted as the collection plate and discharge electrode, respectively. The particle concentration, morphology, and trace-element content were measured by electric low-pressure impactor, scanning electron microscope, and energy-dispersive x-ray spectroscopy, respectively, before and after the electrostatic precipitator. With increasing gas velocity, the collection efficiency of fine particles (up to 0.8 μm in diameter) increased, while it decreased for particles with diameters larger than 0.8 μm. Increasing the dust inlet concentration increased the collection efficiency up to a point, from which it then declined gradually with further increases in the inlet concentration. The particulate matter after the wet electrostatic precipitator showed different degrees of agglomeration. The collection efficiency of trace elements within PM₁₀ was less than that of the PM₁₀ itself. Notably, the water consumption in the current setup was significantly lower than for other treatment processes of comparable collection efficiencies.

Implications: Wet electrostatic precipitators, as fine filtration equipment, were generally applicable to coal-fired plants to reduce PM_2.5 emissions in China. However, high energy consumption and unstable operation, such as water usage and spray washing directly in the electric field, seriously restricted the further development. The utilization of self-flushing wet electrostatic precipitator can solve these problems to some extent.     

Characterization of particulate emissions from Australian open-cut coal mines: Toward improved emission estimates

Given the significance of mining as a source of particulates, accurate characterization of emissions is important for the development of appropriate emission estimation techniques for use in modeling predictions and to inform regulatory decisions. The currently available emission estimation methods for Australian open-cut coal mines relate primarily to total suspended particulates and PM₁₀ (particulate matter with an aerodynamic diameter <10 μm), and limited data are available relating to the PM_2.5 (<2.5 μm) size fraction. To provide an initial analysis of the appropriateness of the currently available emission estimation techniques, this paper presents results of sampling completed at three open-cut coal mines in Australia. The monitoring data demonstrate that the particulate size fraction varies for different mining activities, and that the region in which the mine is located influences the characteristics of the particulates emitted to the atmosphere. The proportion of fine particulates in the sample increased with distance from the source, with the coarse fraction being a more significant proportion of total suspended particulates close to the source of emissions. In terms of particulate composition, the results demonstrate that the particulate emissions are predominantly sourced from naturally occurring geological material, and coal comprises less than 13% of the overall emissions. The size fractionation exhibited by the sampling data sets is similar to that adopted in current Australian emission estimation methods but differs from the size fractionation presented in the U.S. Environmental Protection Agency methodology. Development of region-specific emission estimation techniques for PM₁₀ and PM_2.5 from open-cut coal mines is necessary to allow accurate prediction of particulate emissions to inform regulatory decisions and for use in modeling predictions.

Implications: Development of region-specific emission estimation techniques for PM₁₀ and PM_2.5 from open-cut coal mines is necessary to allow accurate prediction of particulate emissions to inform regulatory decisions and for use in modeling predictions. Comprehensive air quality monitoring was undertaken, and corresponding recommendations were provided.     

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.     

Separation of brown carbon from black carbon for IMPROVE and Chemical Speciation Network PM2.5 samples

The replacement of the Desert Research Institute (DRI) model 2001 with model 2015 thermal/optical analyzers (TOAs) results in continuity of the long-term organic carbon (OC) and elemental carbon (EC) database, and it adds optical information with no additional carbon analysis effort. The value of multiwavelength light attenuation is that light absorption due to black carbon (BC) can be separated from that of brown carbon (BrC), with subsequent attribution to known sources such as biomass burning and secondary organic aerosols. There is evidence of filter loading effects for the 25% of all samples with the highest EC concentrations based on the ratio of light attenuation to EC. Loading corrections similar to those used for the seven-wavelength aethalometer need to be investigated. On average, nonurban Interagency Monitoring of PROtected Visual Environments (IMPROVE) samples show higher BrC fractions of short-wavelength absorption than urban Chemical Speciation Network (CSN) samples, owing to greater influence from biomass burning and aged aerosols, as well as to higher primary BC contributions from engine exhaust at urban sites. Sequential samples taken during an Everglades National Park wildfire demonstrate the evolution from flaming to smoldering combustion, with the BrC fraction increasing as smoldering begins to dominate the fire event.

Implications: The inclusion of seven wavelengths in thermal/optical carbon analysis of speciated PM_2.5 (particulate matter with an aerodynamic diameter ≤2.5 μm) samples allows contributions from biomass burning and secondary organic aerosols to be estimated. This separation is useful for evaluating control strategy effectiveness, identifying exceptional events, and determining natural visibility conditions.     

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.     

Autonomous mobile platform for monitoring air emissions from industrial and municipal wastewater ponds

Significant amounts of volatile organic compounds and greenhouse gases are generated from wastewater lagoons and tailings ponds in Alberta, Canada. Accurate measurements of these air pollutants and greenhouse gases are needed to support management and regulatory decisions. A mobile platform was developed to measure air emissions from tailings pond in the oil sands region of Alberta. The mobile platform was tested in 2015 in a municipal wastewater treatment lagoon. With a flux chamber and a CO₂/CH₄ sensor on board, the mobile platform was able to measure CO₂ and CH₄ emissions over two days at two different locations in the pond. Flux emission rates of CO₂ and CH₄ that were measured over the study period suggest the presence of aerobic and anaerobic zones in the wastewater treatment lagoon. The study demonstrated the capabilities of the mobile platform in measuring fugitive air emissions and identified the potential for the applications in air and water quality monitoring programs.

Implications: The Mobile Platform demonstrated in this study has the ability to measure greenhouse gas (GHG) emissions from fugitive sources such as municipal wastewater lagoons. This technology can be used to measure emission fluxes from tailings ponds with better detection of spatial and temporal variations of fugitive emissions. Additional air and water sampling equipment could be added to the mobile platform for a broad range of air and water quality studies in the oil sands region of Alberta.     

Visibility impacts at Class I areas near the Bakken oil and gas development

Oil and gas activities have occurred in the Bakken region of North Dakota and nearby states and provinces since the 1950s but began increasing rapidly around 2008 due to new extraction methods. Three receptor-based techniques were used to examine the potential impacts of oil and gas extraction activities on airborne particulate concentrations in Class I areas in and around the Bakken. This work was based on long-term measurements from the Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring network. Spatial and temporal patterns in measured concentrations were examined before and after 2008 to better characterize the influence of these activities. A multisite back-trajectory analysis and a receptor-based source apportionment model were used to estimate impacts. Findings suggest that recent Bakken oil and gas activities have led to an increase in regional fine (PM_2.5—particles with aerodynamic diameters <2.5 µm) soil and elemental carbon (EC) concentrations, as well as coarse mass (CM = PM₁₀–PM_2.5). Influences on sulfate and nitrate concentrations were harder to discern due to the concurrent decline in regional emissions of precursors to these species from coal-fired electric generating stations. Impacts were largest at sites in North Dakota and Montana that are closest to the most recent drilling activity.

Implications: The increase in oil and gas activities in the Bakken region of North Dakota and surrounding areas has had a discernible impact on airborne particulate concentrations that impact visibility at protected sites in the region. However, the impact has been at least partially offset by a concurrent reduction in emissions from coal-fired electric generating stations. Continuing the recent reductions in flaring would likely be beneficial for the regional visual air quality.     

Design and characterization of human exposure to generated sulfate and soot particles in a pilot chamber study

A number of literatures have documented adverse health effects of exposure to fine particulate matter (PM_2.5), and secondary sulfate aerosol and black carbon may contribute to health impacts of PM_2.5 exposure. We designed an exposure system to generate sulfate and traffic soot particles, and assessed the feasibility of using it for human exposure assessment in a pilot human exposure study. In the designed exposure system, average mass concentrations of generated sulfate and soot particles were 74.19μg/m³ and 11.54μg/m³ in the chamber and did not vary significantly during two-hour human exposure sessions. The size ranges of generated sulfate were largely between 20 to 200 nm, whereas those of generated soot particles were in the size ranges of 50 to 200nm. Following two-hour exposure to generated sulfate and soot particles, we observed significant increases in fractional exhaled NO (FeNO) in young and health subjects. Building on established human exposure system and health response follow-up methods, future full-scale studies focusing on the effects of mixed particulates and individual PM_2.5 components would provide data in understanding the underpinning cardio-respiratory outcomes in relation to air pollution mixture exposure.

Implications: Controlled exposure is a useful design to measure the biological responses repeatedly following particulate exposures of target components and set exposure at target levels of health concerns. Our study provides rational and establishes method for future full-scale studies to focus on examining the effects of mixed particulates and individual PM_2.5 components.     

Association of PM2.5 pollution with the pattern of human activity: A case study of a developed city in eastern China

Recently, air pollution has attracted a substantial amount of attention in China, which can be influenced by a variety of factors, but the association between air pollution and human activity is not quite clear. Based on real-time online data (January 1, 2014, to December 31, 2014) of air pollution and meteorology reported by official sites, and demographic, economic, and environmental reform data in a statistical yearbook, the influences of meteorological factors (temperature, relative humidity, precipitation intensity, and wind force) and human activities on PM_2.5 pollution were explored. After correlation analysis, logistic regression analysis, and a nonparametric test, weak negative correlations between temperature and PM_2.5 pollution were found. In most cases, festival and morning peak hours were protection and risk factors of PM_2.5 pollution, respectively. In addition, government actions, such as an afforestation project and increasing financial expenditure for energy saving and environmental protection, could greatly contribute to alleviating pollution of PM_2.5. The findings could help officials formulate effective laws and regulations, and then PM_2.5 pollution related to the pattern of human activity would be ameliorated.

Implications: Most of the time, festival and morning peak hours are protection and risk factors for PM_2.5 pollution, respectively. Increasing the percentage of afforestation area and financial expenditure for energy saving and environmental protection could significantly reduce PM_2.5 pollution. The findings can help officials formulate effective laws and regulations, and then PM_2.5 pollution related to the pattern of human activity, especially government action, will be ameliorated.     

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.     

Multiobjective optimization model of intersection signal timing considering emissions based on field data: A case study of Beijing

Most existing signal timing models are aimed to minimize the total delay and stops at intersections, without considering environmental factors. This paper analyzes the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. First, considering the different operating modes of cruising, acceleration, deceleration, and idling, field data of emissions and Global Positioning System (GPS) are collected to estimate emission rates for heavy-duty and light-duty vehicles. Second, multiobjective signal timing optimization model is established based on a genetic algorithm to minimize delay, stops, and emissions. Finally, a case study is conducted in Beijing. Nine scenarios are designed considering different weights of emission and traffic efficiency. The results compared with those using Highway Capacity Manual (HCM) 2010 show that signal timing optimized by the model proposed in this paper can decrease vehicles delay and emissions more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development.

Implications: Vehicle emissions are heavily at signal intersections in urban area. The multiobjective signal timing optimization model is proposed considering the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. The results indicate that signal timing optimized by the model proposed in this paper can decrease vehicle emissions and delays more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development.     

Technology selection for infectious medical waste treatment using the analytic hierarchy process

The overall objective of this paper was to evaluate five different technologies used for infectious medical waste treatment and select the optimum one by means of multicriteria analysis. Steam disinfection was selected as the optimum treatment technology, among others using incineration, microwave disinfection, chemical disinfection with sodium hypochlorite, and reverse polymerization with microwaves. The evaluation was based on four groups of criteria, specifically, environmental, economic, technical, and social criteria, using the analytic hierarchy process. Selection among four commercial systems using steam disinfection was not possible, because it required additional site-specific criteria, e.g., loading capacity and requirements of local regulations.

Implications: The paper can help health care facilities to select the system for infectious waste treatment that best fits their needs. It was concluded that steam disinfection was the optimum technology, using environmental, economic, technical, and social criteria.     

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.     

Outdoor tobacco smoke exposure at the perimeter of a tobacco-free university

There are few studies measuring exposure to outdoor tobacco smoke (OTS). Tobacco users often gather at the boundaries of tobacco-free campuses, resulting in unintended consequences. The objective of this study was to measure exposure levels from OTS on sidewalks bordering a tobacco-free university campus. Data were collected while walking along a sidewalk adjacent to a medium traffic road between May and August 2011. Monitoring occurred during “background,” “stop,” and “walk-through” conditions at and near hot spot area to measure fine particulate matter (<2.5 μm; PM_2.5) from OTS using a portable aerosol monitor. The average PM_2.5 levels during stop and walk-through conditions were significantly higher than during background conditions. PM_2.5 peak occurrence rate and magnitude of peak concentration were significantly different depending on smoking occurrence. The peak occurrence rate during the stop condition was 10.4 times higher than during the background condition, and 3.1 times higher than during the walk-through condition. Average peak PM_2.5 concentrations during the stop condition were 48.7% higher than during the background condition. In conclusion, individuals could be exposed to high levels of PM_2.5 when stopping or even passing by smokers outdoors at the perimeter of tobacco-free campuses. The design and implementation of tobacco-free campus policies need to take into account the unintended consequences of OTS exposure at the boundaries.

Implications:In this study, outdoor tobacco smoke (OTS) exposure was measured at the perimeter of tobacco-free campus. OTS exposure could be determined by peak analysis. Peak occurrence rate and peak concentration for OTS exposure were identified by using peak analysis. People could be exposed to high levels of PM_2.5 when standing or even passing by smokers at the perimeter of tobacco-free campus. OTS exposure measurement in other outdoor locations with smokers is needed to support outdoor smoking regulation.     

Forecasting of particulate matter time series using wavelet analysis and wavelet-ARMA/ARIMA model in Taiyuan,China

Particulate matter with aerodynamic diameter below 10 μm (PM₁₀) forecasting is difficult because of the uncertainties in describing the emission and meteorological fields. This paper proposed a wavelet-ARMA/ARIMA model to forecast the short-term series of the PM₁₀ concentrations. It was evaluated by experiments using a 10-year data set of daily PM₁₀ concentrations from 4 stations located in Taiyuan, China. The results indicated the following: (1) PM₁₀ concentrations of Taiyuan had a decreasing trend during 2005 to 2012 but increased in 2013. PM₁₀ concentrations had an obvious seasonal fluctuation related to coal-fired heating in winter and early spring. (2) Spatial differences among the four stations showed that the PM₁₀ concentrations in industrial and heavily trafficked areas were higher than those in residential and suburb areas. (3) Wavelet analysis revealed that the trend variation and the changes of the PM₁₀ concentration of Taiyuan were complicated. (4) The proposed wavelet-ARIMA model could be efficiently and successfully applied to the PM₁₀ forecasting field. Compared with the traditional ARMA/ARIMA methods, this wavelet-ARMA/ARIMA method could effectively reduce the forecasting error, improve the prediction accuracy, and realize multiple-time-scale prediction.

Implications: Wavelet analysis can filter noisy signals and identify the variation trend and the fluctuation of the PM₁₀ time-series data. Wavelet decomposition and reconstruction reduce the nonstationarity of the PM₁₀ time-series data, and thus improve the accuracy of the prediction. This paper proposed a wavelet-ARMA/ARIMA model to forecast the PM₁₀ time series. Compared with the traditional ARMA/ARIMA method, this wavelet-ARMA/ARIMA method could effectively reduce the forecasting error, improve the prediction accuracy, and realize multiple-time-scale prediction. The proposed model could be efficiently and successfully applied to the PM₁₀ forecasting field.