A new screening measure to identify potential carbon monoxide hotspots

To demonstrate conformity of transportation projects to National Ambient Air Quality Standards in accordance with State Implementation Plans, the U.S. Environmental Protection Agency (EPA) uses intersection level of service (LOS) as one of its major criteria for screening for potential carbon monoxide (CO) hotspots. Although intersection LOS is a measure of traffic volume, signal timing, and related congestion and delay, the assigned level reflects only the computed averaged stopped delay (ASD) per vehicle at the intersection. Thus, intersections can often operate at the same LOS but produce vastly different levels of predicted CO concentrations. For example, a two-lane approach operating at LOS D will produce very different levels of CO than a five-lane approach also operating at LOS D. This study explores the effectiveness of the LOS D criterion as a screen for identifying potential CO hotspots. The study results indicate that LOS is a poor predictor of potential CO hotspots when compared to results generated with the EPA-recommended micro-scale model CAL3QHCr. To more consistently screen out those intersections that will not be identified as CO hotspots using the micro-scale models, a new criterion, equivalent red-time vehicles (ERTV), is introduced. The modeling results using ERTV suggest that it is a more robust measure for identifying potential CO hotspots, and conversely, screening out those intersections that are not likely to be identified as hotspots using micro-scale simulation results.     

Effects of advanced traffic signal status warning systems on vehicle emission reductions at signalized intersections

Signalized intersections have been identified as vehicle emission hotspots, where drivers decelerate, idle, and accelerate their vehicles in response to signal changes. Advanced traffic signal status warning systems (ATSSWSs) can be applied to reduce traffic emissions at intersections by mitigating unnecessary braking and acceleration. In this study, two types of ATSSWSs, variable message sign (VMS) based and vehicle-to-infrastructure (V2I) based, were designed, and their environmental effectiveness was evaluated through driving simulator-based experiments. Three scenarios were designed and tested: (1) baseline without an ATSSWS, (2) with the VMS-based ATSSWS, and (3) with the V2I-based ATSSWS. The Motor Vehicle Emission Simulator model was used to evaluate and compare the environmental effectiveness of these two types of ATSSWSs. The results indicate that the proposed ATSSWSs can reduce traffic emissions at signalized intersections. In particular, the V2I-based ATSSWS can substantially reduce CO₂, NOx, CO, and HC emissions. The results will help transportation practitioners with implementing advanced driver information systems and decision making on emission reduction policies.

Implications: Signalized intersection has been identified as one of hottest spots for vehicle emissions where signal control causes vehicles to frequently decelerate, idle, and accelerate. Advanced Traffic Signal Status Warning Systems (ATSSWS) can be applied to reduce traffic emission at intersections by decreasing vehicles’ unnecessary brakes and accelerations. The results of this study will assist transportation practitioners in implementing advanced driver information systems and making decisions on emission reduction policies.     

Carbon Monoxide Exposures Inside an Automobile Traveling on an Urban Arterial Highway

Carbon monoxide (CO) exposures were measured inside a motor vehicle during 88 standardized drives on a major urban arterial highway, El Camino Real (traffic volume of 30,500-45,000 vehicles per day), over a 13-1/2 month period. On each trip (lasting between 31 and 61 minutes), the test vehicle drove the same 5.9-mile segment of roadway in both directions, for a total of 11.8 miles, passing through 20 intersections with traffic lights (10 in each direction) in three California cities (Menlo Park, Palo Alto, and Los Altos). Earlier tests showed that the test vehicle was free of CO intrusion. For the 88 trips, the mean CO concentration was 9.8 ppm, with a standard deviation of 5.8 ppm. Of nine covariates that were examined to explain the variability in the mean CO exposures observed on the 88 trips (ambient CO at two fixed stations, atmospheric stability, seasonal trend function, time of day, average surrounding vehicle count, trip duration, proportion of time stopped at lights, and instrument type), a fairly strong seasonal trend was found. A model consisting of only a single measure of traffic volume and a seasonal trend component had substantial predictive power (R² = 0.68); by contrast, the ambient CO levels, although partially correlated with average exposures, contributed comparatively little predictive power to the model. The CO exposures experienced while drivers waited at the red lights at an intersection ranged from 6.8 to 14.9 ppm and differed considerably from intersection to intersection. A model also was developed to relate the short-term variability of exposures to averaging time for trip times ranging from 1 to 20 minutes using a variogram approach to deal with the serial autocorrelation. This study shows: (1) the mass balance equation can relate exterior CO concentrations as a function of time to interior CO concentrations; (2) CO exposures on urban arterial highways vary seasonally; (3) momentary CO exposures experienced behind red lights vary with the intersection; and (4) an averaging time model can simulate exposures during short trips (20 minutes or less) on urban arterial highways.     

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.     

A Mercury Vapor Detector Based upon the Automatic Adjustment of Lamp Intensity to the Mercury Concentration

An office containing about 65 employees was found to have 8-h average CO concentrations of 18-26 ppm during a week in winter. On one Friday afternoon, 20 nonsmoking office workers had alveolar CO levels of 23 ± 3 ppm compared to levels of 8 ± 2 ppm in six nonsmoking workers in other offices in the same building. After a weekend at home, the affected office workers displayed reduced alveolar CO levels of 7 ± 2 ppm. The source of the high CO levels was attributed to a parking garage on the same level as the office. Closing fire doors and activating garage fans rectified the situation. The breath sampling method is found to require a correction factor based on the difference between the true alveolar CO and the CO level in the surrounding air. The methods and equipment employed in this study (personal air monitors, electronic data loggers, breath sampling) are recommended for screening and identifying potential CO problems in buildings with similar conditions.     

Flow and dispersion in street intersections

Street intersections play an important role in determining pollutant concentrations in the urban canopy – vehicle emissions often increase in the vicinity of road intersections, and the complex flow patterns that occur within the intersection determine the pollutant fluxes into adjoining streets and into the atmosphere. Operational models for urban air quality therefore need to take account of the particular characteristics of street intersections. We have performed an experimental and numerical investigation of flow and dispersion mechanisms within an urban intersection, and on the basis of our observations and results, we have developed a new operational model for pollutant exchanges in the intersection, which takes account of the non-uniformity of the pollutant fluxes entering and leaving the intersection. The intersection is created by two streets of square cross-section, crossing orthogonally; concentrations were measured by releasing a neutrally buoyant tracer gas from a line source located in one of the streets. As a general result, the numerical simulations agree well with the measurements made in the wind tunnel experiments, except for the case of ground-level concentrations, where the computed concentrations far from the axis of the line source are significantly lower than the measured values. In the first part of the study we investigate the influence of an intersection on the velocity and concentration fields in the adjoining streets; we show that the immediate influence of the intersection extends within the adjoining streets, to a distance of the order of the characteristic size of the streets. A large recirculating vortex is formed at the entrance to the cross-wind streets, and this determines the exchange of pollutants between the streets and the intersection. For some wind directions the average velocity in the street segment between intersections is the same as that which occurs in an infinitely long street with the same wind, but for other angles the average velocity in the finite-length street is significantly lower. The average concentration along a finite-length street is significantly different from that observed in an infinitely long street. In the second part of the study we investigate how the pollutant fluxes in the incoming streets are redistributed amongst the outgoing streets. An analysis of the mean streamlines shows that the flows remain relatively planar, with little variation over the vertical, and we have exploited this result to develop a simple operational model for the redistribution of pollutant fluxes within the intersection. This model has been further adapted to take account of the influence of fluctuations in wind direction over typical averaging periods. The resulting model is used in the street network model SIRANE.     

Diurnal and seasonal variations of carbon monoxide and nitrogen dioxide in Delhi city

Motor vehicle exhaust emissions are one of the major causes of air quality deterioration in most of the cities of the developing world. Carbon monoxide (CO) and nitrogen dioxide (NO₂) are significant contributors to this adverse effect on the environment. This study analyses air quality data for three years from 1997 to 1999, at two air quality control regions in Delhi city. The regions are a major traffic intersection and the moderately busy straight Khelgaon Marg road. The data were obtained from the Central Pollution Control Board (CPCB), Delhi. The results show that the highest ground-level concentrations of CO and NO₂ occurred during winter (November to March) and the lowest during the tropical monsoon period (July to September) at both regions. Typical average monthly, weekly and diurnal cycles of CO at both regions have also been analysed, and show that CO concentrations are higher at the intersection than along the road. Further, the monthly average NO₂ concentrations were also found to be higher at the intersection.     

Comparison of multi-criteria analysis methodologies for the prioritization of arsenic-contaminated sites in the southwest of China

The issue of contaminated sites has been highlighted as an immediate priority in the 13th Five-Year Plan of China. Identification and prioritization of contaminated sites are of key importance for proposing effective strategies for the regional management of contaminated sites. In this study, three advanced multi-attribute methodologies, the risk-based priority methodology, the regional risk assessment methodology, and the dominance-based rough set approach (DRSA), were comparatively employed to screen contaminated sites in, Guangxi, Southwest of China. The results of the three prioritizations show that the highest ranking site identified by the three methods had great agreement. In regard to the screening attributers, while the risk-based prioritization methodology and regional risk assessment methodology allowed a high discrimination in the screening of contaminated sites associated with different attributes, such as farmland, residential areas, contaminant level, number of people, area, storage quality, site service life, and surrounding communities, the DRSA allowed the identification of contamination strength (CS) and contamination potential (CP).

     

Analysis and Modeling of Air Quality at Street Intersections

Four roadway intersection air pollution models were compared to experimental data and evaluated. The models included the recently developed Texas Intersection Model (TEXIN), The Intersection Midblock Model (IMM), the program MICRO and the Indirect Source Guidelines. Data obtained by Texas A&M University at two intersections in Texas and by CALTRANS at an intersection in California were used for the evaluation. The TEXIN Model performed best in all comparisons to the data. The IMM was almost as accurate as TEXIN but required an order of magnitude more input information and computer time. MICRO and the Indirect Source Guidelines performed poorly.     

Assessing the representativeness of monitoring data from an urban intersection site in central London,UK

The wind flow field around urban street-building configurations has an important influence on the microscale pollutant dispersion from road traffic, affecting overall dilution and creating localised spatial variations of pollutant concentration. As a result, the “representativeness” of air quality measurements made at different urban monitoring sites can be strongly dependent on the interaction of the local wind flow field with the street-building geometry surrounding the monitor. The present study is an initial attempt to develop a method for appraising the significance of air quality measurements from urban monitoring sites, using a general application computational fluid dynamics (CFD) code to simulate small-scale flow and dispersion patterns around real urban building configurations. The main focus of the work was to evaluate routine CO monitoring data collected by Westminster City Council at an intersection of street canyons at Marylebone Road, Central London. Many monitors in the UK are purposely situated at urban canyon intersections, which are thought to be local “hot spots” of pollutant emissions, however very limited information exists in the literature on the flow and dispersion patterns associated with them. With the use of simple CFD simulations and the analysis of available monitoring data, it was possible to gain insights into the effect of wind direction on the small-scale dispersion patterns at the chosen intersection, and how that can influence the data captured by a monitor. It was found that a change in wind direction could result in an increase or decrease of monitored CO concentration of up to 80%, for a given level of traffic emissions and meteorological conditions. Understanding and de-coupling the local effect of wind direction from monitoring data using the methods presented in this work could prove a useful new tool for urban monitoring data interpretation.     

A theoretical framework for the episodic-urban air quality management plan (e-UAQMP)

The present research proposes the local urban air quality management plan which combines two different modelling approaches (hybrid model) and possesses an improved predictive ability including the ‘probabilistic exceedances over norms’ and their ‘frequency of occurrences’ and so termed, herein, as episodic-urban air quality management plan (e-UAQMP). The e-UAQMP deals with the consequences of ‘extreme’ concentrations of pollutant, mainly occurring at urban ‘hotspots’ e.g. traffic junctions, intersections and signalized roadways and are also influenced by complexities of traffic generated ‘wake’ effects. The e-UAQMP (based on probabilistic approach), also acts as an efficient preventive measure to predict the ‘probability of exceedances’ so as to prepare a successful policy responses in relation to the protection of urban environment as well as disseminating information to its sensitive ‘receptors’. The e-UAQMP may be tailored to the requirements of the local area for the policy implementation programmes. The importance of such policy-making framework in the context of current air pollution ‘episodes’ in urban environments is discussed. The hybrid model that is based on both deterministic and stochastic based approaches predicting the ‘average’ as well as ‘extreme’ concentration distribution of air pollutants together in form of probability has been used at two air quality control regions (AQCRs) in the Delhi city, India, in formulating and executing the e-UAQMP—first, the income tax office (ITO), one of the busiest signalized traffic intersection and second, the Sirifort, one of the busiest signalized roadways.     

A field study of factors influencing the concentrations of a traffic-related pollutant in the vicinity of a complex urban junction

The paper describes a field study focused on the dispersion of a traffic-related pollutant within an area close to a busy intersection between two street canyons in Central London. Simultaneous measurements of airflow, traffic flow and carbon monoxide concentrations ([CO]) are used to explore the causes of spatial variability in [CO] over a full range of background wind directions. Depending on the roof-top wind direction, evidence of both flow channelling and recirculation regimes were identified from data collected within the main canyon and the intersection. However, at the intersection, the merging of channelled flows from the canyons increased the flow complexity and turbulence intensity. These features, coupled with the close proximity of nearby queuing traffic in several directions, led to the highest overall time-average measured [CO] occurring at the intersection. Within the main street canyon, the data supported the presence of a helical flow regime for oblique roof-top flows, leading to increased [CO] on the canyon leeward side. Predominant wind directions led to some locations having significantly higher diurnal average [CO] due to being mostly on the canyon leeward side during the study period. For all locations, small changes in the background wind direction could cause large changes in the in-street mean wind angle and local turbulence intensity, implying that dispersion mechanisms would be highly sensitive to small changes in above roof flows. During peak traffic flow periods, concentrations within parallel side streets were approximately four times lower than within the main canyon and intersection which has implications for controlling personal exposure. Overall, the results illustrate that pollutant concentrations can be highly spatially variable over even short distances within complex urban geometries, and that synoptic wind patterns, traffic queue location and building topologies all play a role in determining where pollutant hot spots occur.     

Assessing the impact of converting roundabouts to traffic signals on vehicle emissions along an urban arterial corridor in Qatar

The type of control at intersections has a major effect on the operation of any urban corridor. Different predefined procedures are available to calculate some of the main operational characteristics, such as capacity, delay, and level of service, in order to select the best type of control. However, there are other important factors that affect major arterials operational characteristics, factors that are not fully addressed, such as the impact of emissions. In this study, a microscopic simulation approach using VISSIM and MOVES was developed to assess the environmental effect of converting four three-lane roundabouts to signalized intersections along a heavily congested urban corridor in Qatar. A decision was made to switch all roundabouts to traffic signals for better operations. Preliminary results indicated that the signal control outperformed the roundabout in the range of 37% to 43% reduction in emissions. A more detailed analysis revealed that roundabout corridor operations’ effects on emission rates are divergent from those of signalized corridors, particularly upstream and downstream of the intersections. Immediate roundabout upstream approaches are driver behavior dependent, characterized by substantial coasting at lower speeds and subsequent re-accelerating with less idling, described as acceleration events, which resulted in high emission rates, while signalized corridors are signal timing dependent, characterized by ample idling with less coasting and re-acceleration, resulting in reduced emission rates. The results also revealed that there was no significant difference between emission rates in the vicinity of the two types of control. Both recorded nearly the same emission rate.

Implications: A microscopic simulation approach using VISSIM and MOVES was developed to assess the environmental effect of converting four three-lane roundabouts to signalized intersections along a heavily congested urban corridor in Doha, Qatar. Intersection geometries along with the control type have significant impact on emission rates and play a major role in assessing environmental impacts. US EPA MOVES was calibrated to Qatar conditions which can be used to estimate emission factors and quantify vehicular emissions along other corridors in the country. The results can also be beneficial for other countries within the region.     

The adsorption properties of microporous activated carbon prepared from pistachio nut shell for low-concentration VOCs under low-medium temperatures

Environmental Science and Pollution Research - The control of low-concentration VOCs in coal-fired flue gas is one of the research hotspots at present. In this work, K2CO3 and K2CO3-KCl were...     

The Autothermal Pyrolysis of Waste Tires

Abstract

The growing amount of rubber waste, such as that from tires and cables, has resulted in serious environmental problems. Since rubber waste is not easily biodegradable even after a long period of landfill treatment, material and energy recovery is the preferable alternative to disposal. The potential offered by waste tire pyrolysis for solving both energy and waste treatment problems is widely recognized. Pyrolysis is one method of inducing thermal decomposition without using any oxidizing agent, or using such a limited supply of the agent that oxidization does not proceed to an appreciable extent. The latter may be described as autothermal pyrolysis and will be studied in the present work.

The main objective of this research was to study the operating parameters of autothermal pyrolysis of scrap tires in a laboratory-scale fluidized bed reactor with a 100-cm bed height (10 cm I.D.) and a 100-cm freeboard (25 cm I.D.). Scrap tires were pyrolyzed in a limited oxygen supply, so that the heat for pyrolysis of the scrap tires was provided by combustion of some portion of the scrap tires. The operating parameters evaluated included the effect on the pyrolysis oil products and their relative proportions of (1) the air factor (O.O7–O35); (2) the pyrolysis temperature (370–570 °C); and (3) the catalyst added (zeolite and calcium carbonate). The results show that: (1) the composition of the liquid hydrocarbon obtained is affected significantly by the air factor; (2) the higher operating temperature caused a higher yield of gasoline and diesel; (3) the yield of gasoline increased due to the catalyst zeolite added, and the yield of diesel increased due to the addition of the catalyst calcium carbonate; (4) the principal constituents of gasoline included dipentene and diprene.     

The rate of soil reduction as affected by levels of methyl parathion and 2, 4‐D

Abstract

A simple technique was demonstrated for determining the potential for synthetic organics to stress microbial populations. Oxidized Crowley and Cecil soil materials were amended with varying concentrations of 2,4‐D and methyl parathion, flooded, and then analyzed for changes in pH, redox potential, and levels of soluble plus exchangeable Fe, Mn, and Zn, all of which may be directly or indirectly influenced by the activity of soil microorganisms. At the concentrations tested (up to 75 ppm), there was little effect of 2,4‐D, but methyl parathion apparently did affect microbial activity contributing to changes in the measured soil properties upon flooding. This approach may be a useful technique for screening various compounds for their potential to stress microbial activity that, for many researchers, would be easier than direct observations of microbial parameters such as population numbers and classifications, and enzyme levels.     

Bench-scale gasification of cedar wood – Part I: Effect of operational conditions on product gas characteristics

The present study was conducted within the framework of R&D activities on the development of gasification and reforming technologies for energy and chemical recovery from biomass resources. Gasification of the Japanese cedar wood has been investigated under various operating conditions in a bench-scale externally heated updraft gasifier; this was followed by thermal reforming. Parametric tests by varying the residence times, gasification temperatures, equivalence ratios (ERs) and steam-to-carbon (S/C) ratios were performed to determine their effects on the product gas characteristics. Thermodynamic equilibrium calculations were preformed to predict the equilibrium gas composition and compared with the experimental value.We found that the product gas characteristics in terms of the H₂/CO ratio, CO₂/CO ratio, and CH₄ and lighter hydrocarbons concentrations are significantly affected by the operating conditions used. Increasing the residence time decreased the CO₂/CO ratio; however, a nominal effect was noticed on H₂ concentration as a function of the residence time. At sufficient residence time, increasing the temperature led to higher H₂ yields, CO efficiency and higher heating value (HHV) of the product gas. The presence of steam during gasification effectively enhanced the proportion of H₂ in the product gas. However, higher S/C ratio reduced the HHV of the product gas. Increasing the ER from 0 to 0.3 increased the H₂ yields and CO efficiency and decreased the HHV of the product gas.The evolution of CH₄ and lighter hydrocarbons at low gasification temperatures was relatively higher than that at high temperature gasification. The evolution of CH₄ and lighter hydrocarbons at high gasification temperatures hardly varied over the investigated operating conditions.     

Influence of Oxygenated Fuels on the Emissions from Three Pre-1985 Light-Duty Passenger Vehicles

Tailpipe and evaporative emissions from three pre-1985 passenger motor vehicles operating on an oxygenated blend fuel and on a nonoxygenated base fuel were characterized. Emission data were collected for vehicles operating over the Federal Test Procedure at 40,75, and 90°F to simulate ambient driving conditions. The two fuels tested were a commercial summer grade regular gasoline (the nonoxygenated base fuel) and an oxygenated fuel containing 9.5 percent methyl tert-butyl ether (MTBE), more olefins, and fewer aromatics than the base fuel. The emissions measured were total hydrocarbons (THCs), speciated hydrocarbons, speciated aldehydes, carbon monoxide (CO), oxides of nitrogen (NO_x), benzene, and 1,3-butadiene.

This study showed no pattern of tailpipe regulated emission reduction when oxygenated fuel was used. Tailpipe emissions from the 1984 Buick Century without a catalyst and the 1977 Mustang with catalyst decreased with the MTBE fuel. However, emissions from the 1984 Buick Century and the 1980 Chevrolet Citation, both fitted with catalysts increased. The vehicles emitted more 1,3- butadiene and, in general, more NO_x when operated with the base fuel.

THC, CO, benzene, and 1,3-butadiene emissions from both fuels and all vehicles, in general, decreased with increasing test temperature, whereas NO_x emissions, in general, increased with increasing test temperature. Formaldehyde, acetaldehyde, and total aldehydes also showed a decrease in emissions as test temperature increased. More formaldehyde was emitted when the MTBE fuel was used.

Evaporative, diurnal, and hot soak emissions from the base fuel were greater than those from the MTBE fuel. The evaporated emissions from both fuels increased with increasing test temperatures. Diurnal data indicate that canister conditioning (bringing the evaporative charcoal canister to equilibrium) is required before testing.     

Prediction of PM10 concentrations at urban traffic intersections using semi-empirical box modelling with instantaneous velocity and acceleration

At urban traffic intersections, vehicles frequently stop with idling engines during the red-light period and speed up rapidly during the green-light period. The changes of driving patterns (i.e., idle, acceleration, deceleration and cruising patterns) generally produce uncertain emission. Additionally, the movement of pedestrians and the influence of wind further result in the random dispersion of pollutants. It is, therefore, too complex to simulate the effects of such dynamics on the resulting emission using conventional deterministic causal models.For this reason, a modified semi-empirical box model for predicting the PM₁₀ concentrations on roadsides is proposed in this paper. The model constitutes three parts, i.e., traffic, emission and dispersion components. The traffic component is developed using a generalized force traffic model to obtain the instantaneous velocity and acceleration when vehicles move through intersections. Hence the distribution of vehicle emission in street canyon during the green-light period is calculated. Then the dispersion component is investigated using a semi-empirical box model combining average wind speed, box height and background concentrations. With these considerations, the proposed model is applied and evaluated using measured data at a busy traffic intersection in Mong Kok, Hong Kong. In order to test the performance of the model, two situations, i.e., the data sets within a sunny day and between two sunny days, were selected to examine the model performance. The predicted values are generally well coincident with the observed data during different time slots except several values are overestimated or underestimated. Moreover, two types of vehicles, i.e., buses and petrol cars, are separately taken into account in the study. Buses are verified to contribute most to the emission in street canyons, which may be useful in evaluating the impact of vehicle emissions on the ambient air quality when there is a significant change in a specific vehicular population.