Preliminary investigation of PM1, PM2.5, PM10 and its metal elemental composition in tunnels at a subway station in Shanghai,China

In this study, real-time monitoring campaigns were conducted in two tunnels (Line A and Line B) at a subway station in Shanghai, including temperature, relative humidity, PM₁, PM_2.5 and PM₁₀, in order to understand the climate and PM characteristics in the transportation microenvironment. In addition, collected floor dust particles in the tunnel were analyzed by ICP for their metal elemental composition. Strong correlations occurred between all PM levels and meteorological parameters in the tunnel of Line A (with platform screen doors), in comparison with the weak correlations between such parameters in the tunnel of Line B (without platform screen doors). PM_2.5 and PM₁₀ between peak hours and off-peak hours for both lines presented significant differences (p < 0.05), respectively. Nevertheless, PM₁ showed a different pattern, with p > 0.05 for Line A and p < 0.05 for Line B, respectively. In addition, statistical results concluded that PM had an evident weekly variation for both lines. Friday was the highest day of all particulate matters in monitoring periods for both lines. Ratios of PM₁/PM₁₀ and PM_2.5/PM₁₀ were high when trains were out of service and low when trains were in service. Relative abundance of metal elements detected from floor dust particles proved that floor dust particles in tunnels might be a major source of airborne PM in the subway microenvironments, with Fe as the most abundant metal element, followed by Ca, Al, Mg, Mn, Zn, Cu, Cr, Ni, Pb and Hg.     

Commuters’ exposure to PM2.5 and CO2 in metro carriages of Shanghai metro system

Air quality inside transportation carriages has become a public concern. A comprehensive measurement campaign was conducted to examine the commuters’ exposure to PM_2.5 (d_p ⩽ 2.5 μm) and CO₂ in Shanghai metro system under different conditions. The PM_2.5 and CO₂ concentrations inside all the measured metro lines were observed at 84 ± 42 μg/m³ and 1253.1 ± 449.1 ppm, respectively. The factors that determine the in-carriage PM_2.5 and CO₂ concentrations were quantitatively investigated. The metro in-carriage PM_2.5 concentrations were significantly affected by the ventilation systems, out-carriage PM_2.5 concentrations and the passenger numbers. The largest in-carriage PM_2.5 and CO₂ concentrations were observed at 132 μg/m³ and 1855.0 ppm inside the carriages equipped with the oldest ventilation systems. The average PM_2.5 and CO₂ concentrations increased by 24.14% and 9.93% as the metro was driven from underground to overground. The average in-carriage PM_2.5 concentrations increased by 17.19% and CO₂ concentration decreased by 16.97% as the metro was driven from urban to the suburban area. It was found that PM_2.5 concentration is proportional to the on-board passenger number at a ratio of 0.4 μg/m³·passenger. A mass-balance model was developed to estimate the in-carriage PM_2.5 concentration under different driving conditions.     

The cost of convenience; Air pollution and noise on freeway and arterial light rail station platforms in Los Angeles

Light rail transit (LRT) systems constitute one of the most sustainable public transportation modes and transit agencies have increasingly constructed LRT lines along the median of roadways to reduce land acquisition costs and traffic conflicts. Despite these conveniences, few studies have examined the air pollution and noise exposures for passengers on LRT station platforms within freeway or arterial medians. In response, we monitored particle number count (PNC) concentrations and noise levels on 17 station platforms in the Los Angeles metro system in summer 2012 and assessed differences between freeway and arterial platforms. We visited each station on average 7 times for approximately 19 min with two teams carrying a full set of instruments. As expected, impacts were higher on green line platforms in the center of a grade-separated freeway compared to blue line platforms in the center of an arterial due to being in close proximity to greater traffic volumes. Overall, freeway-arterial platform differences were 35,100 versus 20,000 particles/cm³ for PNC and 83 versus 62 dBA for noise. This average noise intensity on green line platforms was four times that on blue line stations. We also found that PNC concentrations were significantly higher at open air monitoring platform positions compared to standing under a shade canopy (about 2000 particles/cm³ higher), but that noise levels were significantly lower at open air positions compared to under canopy positions (about 3.2 dBA lower). Results identify important factors for transport planners to consider when locating and designing in-roadway LRT platforms.     

Particulate matter concentrations and heavy metal contamination levels in the railway transport system of Sydney,Australia

Sampling campaign was conducted over six weeks to determine particulate matter (PM) concentrations from Sydney Trains airport line (T2) at both underground and ground levels using DustTrak. Dust samples were collected and analysed for 12 metals (Fe, Ca, Mn, Cr, Zn, Cu, Pb, Al, Co, Ni, Ba and Na) by atomic emission spectroscopy. Average underground PM₁₀ and PM_2.5 concentrations from inside the trains were 2.8 and 2.5 times greater than at ground level. Similarly, PM₁₀ and PM_2.5 concentrations on underground platforms were 2.7 and 2.5 times greater than ground level platforms. Average underground PM concentrations exceeded the national air quality standards for both PM₁₀ (50 µg/m³) and PM_2.5 (25 µg/m³). Correlation analysis showed a strong to moderate association between PM concentrations at ground level and background PM concentrations (r² from 0.952 to 0.500). The findings suggested that underground PM concentrations were less influenced by the ambient background than at ground level. The metal concentrations decreased in the order of Fe, Cr, Ca, Al, Na, Ba, Mn, Zn, Cu, Ni, Co and Pb. The pollution index (PI) and enrichment factor (EF) values were calculated to identify the levels and sources of contamination in the underground railway microenvironments. PM was remarkably rich in Fe with a mean concentration of 73.51 mg/g and EF of 61.31, followed by Ni and Cr. These results noticeably indicated a high level of metal contamination in the underground environments, with the principal contribution from track abrasion and wear processes.     

Implications of climate change for thermal discomfort on underground railways

Hot weather events, ventilation assets, changing passenger demand and service expectations have all caused increased attention on thermal comfort on London’s Tube. This study provides estimates of the future number of days when passengers travelling on sections of the Tube could be subjected to thermal discomfort under future scenarios of climate change, and the potential number of passengers dissatisfied. A risk based methodology is presented, integrating a spatial weather generator modified for urban areas and a thermal comfort model. The study provides an initial assessment of adaptation options by considering the implications of lowering train temperatures by 2 °C and 4 °C to represent saloon cooling. Median results under a 2050 high scenario indicate that all Tube lines assessed could experience near-complete passenger dissatisfaction with the thermal environment in trains in the unlikely event that nothing else were to change. Adaptation aimed at lowering train temperatures has the potential to provide tangible improvements in thermal comfort. However, this was not projected to be sufficient to maintain comfortable thermal conditions for many of the lines in the 2050s under high emission scenarios, requiring a combination of other infrastructure cooling measures to be implemented in parallel.     

A bi-level model for single-line rail timetable design with consideration of demand and capacity

This paper proposes a bi-level model to solve the timetable design problem for an urban rail line. The upper level model aims at determining the headways between trains to minimize total passenger cost, which includes not only the usual perceived travel time cost, but also penalties during travel. With the headways given by the upper level model, passengers’ arrival times at their origin stops are determined by the lower level model, in which the cost-minimizing behavior of each passenger is taken into account. To make the model more realistic, explicit capacity constraints of individual trains are considered. With these constraints, passengers cannot board a full train, but wait in queues for the next coming train. A two-stage genetic algorithm incorporating the method of successive averages is introduced to solve the bi-level model. Two hypothetical examples and a real world case are employed to evaluate the effectiveness of the proposed bi-level model and algorithm. Results show that the bi-level model performs well in reducing total passenger cost, especially in reducing waiting time cost and penalties. And the section loading-rates of trains in the optimized timetable are more balanced than the even-headway timetable. The sensitivity analyses show that passenger’s desired arrival time interval at destination and crowding penalty factor have a high influence on the optimal solution. And with the dispersing of passengers' desired arrival time intervals or the increase of crowding penalty factor, the section loading-rates of trains become more balanced.     

Characteristics of air pollutants at near and far field regions of a national highway located at an industrial complex

This paper presents the characterization of air quality monitored at near field region (NFR) and far field region (FFR) of a national highway located at an industrial complex. The pollutants such as PM₁₀, SO₂ and NO₂ were monitored in two campaigns (11th September to 18th October 2012 and 18th January to 17th February 2013). The 24 h average PM₁₀ concentration at NFR and FFR were found to be 86.69 ± 18.56 μg/m³; 73.16 ± 16.21 μg/m³ and 89.44 ± 18.69 μg/m³; 81.91 ± 16.42 μg/m³, respectively during first and second campaign. In both the campaigns PM₁₀, SO₂ and NO₂ concentration at NFR was higher than FFR. The chemical characterization of PM₁₀ at NFR and FFR indicated the abundance of major elements such as Na (NFR = 30% and FFR = 32%), Ca (NFR = 12% and FFR = 14%) and ions namely NO₃⁻ (NFR = 71% and FFR = 68%) and NH₃⁺ (NFR = 15% and FFR = 19%). Further, at FFR, SO₄²⁻ and NO₃⁻ were found to be 18% and 35% higher than NFR indicating the conversions of SO₂ and NO₂ concentration into secondary particles. The measured SO₂ and NO₂ concentrations were 23 and 21% lower at FFR when compared to NFR confirms the secondary formation.The CALPUFF, EPA regulatory model was set up to understand the dynamics of air pollutants at the industrial complex. The predicted PM₁₀, SO₂ and NO₂ concentrations at NFR and FFR were found to be 32.31 ± 1.56 μg/m³ and 31.35 ± 1.27 μg/m³; 0.37 ± 0.21 μg/m³ and 0.06 ± 0.04 μg/m³; 12.83 ± 6.55 μg/m³ and 4.67 ± 2.77 μg/m³, respectively. The model showed moderate predictions for PM₁₀ (R² = 0.44–0.52), SO₂ (R² = 0.41–0.51) and NO₂ (R² = 0.45–0.61) concentrations.     

Mining missing train logs from Smart Card data

This paper shows how to recover the arrival times of trains from the gate times of metro passengers from Smart Card data. Such technique is essential when a log, the set of records indicating the actual arrival and departure time of each bus or train at each station and also a critical component in reliability analysis of a transportation system, is missing partially or entirely. The procedure reconstructs each train as a sequence of the earliest exit times, called S-epochs, among its alighting passengers at each stations. The procedure first constructs a set of passengers, also known as reference passengers, whose routing choices are easily identifiable. The procedure then computes, from the exit times of the reference passengers, a set of tentative S-epochs based on a detection measure whose validity relies on an extreme-value characteristic of the platform-to-gate movement of alighting passengers. The tentative S-epochs are then finalized to be a true one, or rejected, based on their consistencies with bounds and/or interpolation from prescribed S-epochs of adjacent trains and stations. Tested on 12 daily sets of trains, with varying degrees of missing logs, from three entire metro lines, the method restored the arrival times of 95% of trains within the error of 24 s even when 100% of logs was missing. The mining procedure can also be applied to trains operating under special strategies such as short-turning and skip-stop. The recovered log seems precise enough for the current reliability analysis performed by the city of Seoul.     

Personal exposures to PM during short distance highway travel in India

Traffic is the largest contributor (37%) to urban air pollution in India. During commuting, passengers are significantly exposed to pollutants. We carried out a study on a National Highway (NH) in India to measure personal exposure to Particulate Matter (PM) in five travel modes. PM_2.5 concentrations showed the following trend: Bus > Car FA (fresh air mode of air condition) > Bus AC > Car > Car RC (re-circulation mode of air condition). Highest and lowest concentrations of PM₁₀ were observed in Bus (134 ± 47 µg m⁻³) and Car RC (20 ± 5 µg m⁻³), respectively. The exposures were highest at the rear seats during the Bus AC journeys. In Car FA, the contribution of PM₁ to total concentrations was dominant (61%). Travel modes explained highest variabilities in PM₁₀, PM_2.5 and PM₁ concentrations. In all travel modes, the highest particle counts were observed for PM_0.3–0.5. PM_>0.5–5.0 counts during Bus journeys were comparatively higher than remaining modes. Deposition doses of passengers were as high as 3.22 µg of PM₁₀ (in Bus), 0.66 µg of PM_2.5 (in Bus) and 0.06 µg of PM₁ (in Bus AC) during the ~1 h journey. Our study revealed that Car RC is the safest mode of travel, both in terms of personal exposures and PM depositions in respiratory system. The results from this study can be used to target efforts to reduce personal exposure of highway commuters.     

Evaluating the social cost of cruise ships air emissions in major ports of Greece

Detailed NO_x, SO₂ and PM_2.5 emissions have been estimated for cruise ships in the five busiest Greek ports (i.e. Piraeus, Santorini, Mykonos, Corfu and Katakolo) for year 2013. The emissions were analyzed in terms of gas species, seasonality and activity. The total in-port inventory of cruise shipping accounted to 2742.7 tons: with NO_x being dominant (1887.5 tons), followed by SO₂ and PM_2.5 (760.9 and 94.3 tons respectively). Emissions during hotelling corresponded to 88.5% of total and have significantly outweighed those produced during ships’ maneuvering activities (11.5% of total). Seasonality was found to play a major role, as summer emissions and associated impacts were significantly augmented. The anticipated health impacts of ship emissions can reach to €24.3 million or to €5.3 per passenger proving the necessity of control of the emissions produced by cruise ships in port cities or policy and measures towards a more efficient cruise industry.     

Total water requirements of passenger transport modes

With a growing urban population, it is crucial to maintain and develop environmentally friendly transport modes. However, while one of the most important indicators of environmental performance is water use, very few studies have quantified the total water requirements associated with different transport modes.This study uses input-output analysis to quantify the total water requirements of different passenger-transport modes in Melbourne, Australia, including the direct and indirect water requirements of petrol cars, regional diesel trains and electric metropolitan trains.Results show that urban electric trains are the least water intensive transport mode (3.4 L/pkm) followed by regional diesel trains (5.2 L/pkm) and petrol cars (6.4 L/pkm). These intensities result in average daily per capita transport-related water use that can be greater than residential water use. Findings also show that occupancy rates greatly affect the water intensity of transport modes and that when occupied by five passengers, cars are the least water intensive transport mode. Finally, this study shows that water use associated with transport depends on a range of factors across the supply chain and that indirect requirements associated with operations, including administration, advertisement, servicing and others, can represent a significant share of the total. Reducing the total water requirements of transport modes is therefore a shared responsibility between all the actors involved and integrated action plans are needed in order to reduce water use associated with transport.     

Effects of the 80 km/h and variable speed limits on air pollution in the metropolitan area of barcelona

In 2008 the regional government of Catalonia (Spain) reduced the maximum speed limit on several stretches of congested urban motorway in the Barcelona metropolitan area to 80 km/h, while in 2009 it introduced a variable speed system on other stretches of its metropolitan motorways. We use the differences-in-differences method, which enables a policy impact to be measured under specific conditions, to assess the impact of these policies on emissions of NO_x and PM₁₀. Empirical estimation indicate that reducing the speed limit to 80 km/h causes a 1.7–3.2% increase in NO_x and 5.3–5.9% in PM₁₀. By contrast, the variable speed policy reduced NO_x and PM₁₀ pollution by 7.7–17.1% and 14.5–17.3%. As such, a variable speed policy appears to be a more effective environmental policy than reducing the speed limit to a maximum of 80 km/h.     

Ultrafine particle infiltration into passenger vehicles. Part II: Model analysis

Experimental studies showed that infiltration and passive ventilation are important air exchange mechanisms inside vehicles but previous mathematical models did not consider either one. In this study, we incorporated infiltration and passive ventilation to advance the existing mathematical models and evaluated how different transport mechanisms affect passenger exposures at increasing speeds. Infiltration was formulated using Bernoulli’s equation and passive ventilation was derived empirically. The new model describes ultrafine particle (UFP) and carbon dioxide (CO₂) transport for a wide range of driving speed under any ventilation conditions. Unlike statistical models, this mathematical model can also provide vehicle-specific and transport mechanism-specific information. The model predictions were in a good agreement with data collected from 10 different vehicle models with an average discrepancy of less than 16% for UFPs and less than 3% for CO₂. Under outdoor air (OA) mode, when the fan is off, the model simulation showed that the infiltration and passive ventilation can substantially increase the UFP I/O (in-cabin/on-road concentrations) ratio from 0.15 at 0 km/h to 0.57 at 130 km/h. At medium fan setting, mechanical ventilation dominates and UFP I/O stays at 0.58 regardless of driving speed. Under recirculation (RC) mode, infiltration increases and the RC-mode filtration only removed 44% and 69% of the infiltrated particles at the lowest and medium fan settings, respectively. Model simulations under OA mode show that infiltration starts to occur above 115 km/h with the lowest fan setting; whereas, medium and higher fan settings prevent infiltration up to 145 km/h.     

How wide should be the adjacent area to an urban motorway to prevent potential health impacts from traffic emissions?

In recent years, several studies show that people who live, work or attend school near the main roadways have an increased incidence and severity of health problems that may be related with traffic emissions of air pollutants. The concentrations of near-road atmospheric pollutants vary depending on traffic patterns, environmental conditions, topography and the presence of roadside structures. In this study, the vertical and horizontal variation of nitrogen dioxide (NO₂) and benzene (C₆H₆) concentration along a major city ring motorway were analysed. The main goal of this study is to try to establish a distance from this urban motorway considered “safe” concerning the air pollutants human heath limit values and to study the influence of the different forcing factors of the near road air pollutants transport and dispersion. Statistic significant differences (p = 0.001, Kruskal–Wallis test) were observed between sub-domains for NO₂ representing different conditions of traffic emission and pollutants dispersion, but not for C₆H₆ (p = 0.335). Results also suggest significant lower concentrations recorded at 100 m away from roadway than at the roadside for all campaigns (p < 0.016 (NO₂) and p < 0.036 (C₆H₆), Mann–Whitney test). In order to have a “safe” life in homes located near motorways, the outdoor concentrations of NO₂ must not exceed 44–60.0 μg m⁻³ and C₆H₆ must not exceed 1.4–3.3 μg m⁻³. However, at 100 m away from roadway, 81.8% of NO₂ receptors exceed the annual limit value of human health protection (40 μg m⁻³) and at the roadside this value goes up to 95.5%. These findings suggest that the safe distance to an urban motorway roadside should be more at least 100 m. This distance should be further studied before being used as a reference to develop articulated urban mobility and planning policies.     

AERMOD for near-road pollutant dispersion: Evaluation of model performance with different emission source representations and low wind options

The performance of the regulatory dispersion model AERMOD in simulating vehicle-emitted pollutant concentrations near-roadway using area or volume source representation of emissions and with different low wind options was assessed using the SF₆ tracer data from the General Motors (GM) Sulfur Dispersion Experiment. At downwind receptor locations, AERMOD, using either area or volume source emissions, can reasonably predict the tracer concentrations near the surface (0.5 m) but the model performance decreases at higher elevations (3.5m and 9.5m above the surface). For upwind receptors, using an area source representation leads to significant under-predictions due to AERMOD’s lack of treatment of lateral plume meander, but using volume source representation leads to over-predictions of upwind concentrations regardless of the low wind options for plume meander. Among the three low wind options currently available in AERMOD, best model performance is obtained with low wind option 3, which treats plume meander with a higher minimal standard deviation of the horizontal crosswind component (σ_v,min = 0.3 m s⁻¹), eliminates upwind component of dispersion and uses an effective lateral dispersion parameter (σ_y) to replicate centerline concentration. The optional adjustment of the surface friction velocity in the meteorological preprocessor AERMET does not lead to obvious improvements in predicted near-road concentrations for this application.     

Computer simulation of impacts of a chlorine tanker truck accident

The aim of the study was to present the author’s original modelling programs of pollution dispersion in an urban environment. The programs outlined herein are based on a diagnostic model of air velocity field and Langrangian particle model. In both modelling programs author’s elements of mathematical modelling were applied. The models have been validated and verified. Geographic Information System (GIS) Idrisi Andes was applied in the pre-processing stage.The development of author’s original computer program and stages of hazardous material propagation modelling were discussed.The results of computations and analysis of pollution dispersion caused by a chlorine tanker truck collision and chlorine release into atmosphere were presented. It was simulated that the accident took place in the city of Bielsko-Biała, on a bypass in a built-up area causing leakage of 10 t of chlorine. The computer simulations conducted for two wind direction scenarios allow to conclude that the total area affected by the pollutant cloud with concentrations above threshold levels could be over 2 km², with 5000 lethally exposed people.     

Will technological progress be sufficient to stabilize CO2 emissions from air transport in the mid-term?

This article investigates whether anticipated technological progress can be expected to offset the CO₂ emissions resulting from rapid air traffic growth. Global aviation CO₂ emissions projections are examined for eight geographical zones until 2025. Air traffic flows are forecast using a dynamic panel-data econometric model, and then converted into corresponding quantities of air traffic CO₂ emissions using specific hypotheses and energy factors. None of our nine scenarios appears compatible with the objective of 450 ppm CO₂-eq. recommended by the Intergovernmental Panel on Climate Change. Nor is any compatible with the Panel’s aim of limiting global warming to 3.2 °C.     

Indoor air quality and passenger thermal comfort in Beijing metro transfer stations

In this study, particulate matter was investigated as the primary pollutant in the air quality of Beijing Metro transfer stations, and passenger thermal comfort during the transfer process was evaluated by using the relative warmth index (RWI). Passenger thermal comfort level is not ideal in 87% of the measured space and is slightly hot overall, with an RWI range of 0.20–0.43. Although 20% of the measured space has lower values than ASHRAE’s cooling comfort class, the thermal comfort level of most measured space is good in winter morning rush hours, with an RWI range from −0.18 to 0.28. The particulate matter (PM) concentration is related not only to the season and spatial depth but also to the transfer design of the metro station. During the morning rush period, the concentration ranges difference of PM₁₀ and PM_2.5 in winter are 262.9 μg/m³ and 125.5 μg/m³, respectively, which are 1.43 and 1.46 times higher than those of in summer. There are significant differences in the PM concentration and RWI values between the island and lateral platforms of Beijing Metro transfer stations, and the design of the lateral platform is superior to that of the island platform. Another exploratory experiment is conducted to determine if the PM concentration has a potential effect on human metabolic rate. The data in this paper provide a valuable reference for further comfort research and environmental control in metro station, and the conclusions may guide the further underground space design of metro transfer stations.     

Biofuels in aviation: Fuel demand and CO2 emissions evolution in Europe toward 2030

This article presents the results of a scenario-based study carried out at the European Commission’s Joint Research Centre aimed at analyzing the future growth of aviation, the resulting fuel demand and the deployment of biofuels in the aviation sector in Europe. Three scenarios have been produced based on different input assumptions and leading to different underlying patterns of growth and resulting volumes of traffic. Data for aviation growth and hence fuel demand have been projected on a year by year basis up to 2030, using 2010 as the baseline. Data sources are Eurostat statistics and actual flight information from EUROCONTROL. Relevant variables such as the number of flights, the type of aircrafts, passengers or cargo tonnes and production indicators (RPKs) are used together with fuel consumption and CO₂ emissions data. The target of the European Advanced Biofuels Flightpath to ensure the commercialization and consumption of 2 million tons of sustainably produced paraffinic biofuels in the aviation sector by 2020, has also been taken into account. Results regarding CO₂ emission projections to 2030, reveal a steady annual increase in the order of 3%, 1% and 4% on average, for the three different scenarios, providing also a good correlation compared to the annual traffic growth rates that are indicated in the three corresponding scenarios. In absolute values, these ratios correspond to the central, the pessimistic and the optimistic scenarios respectively, corresponding to 360 million tonnes CO₂ emissions in 2030, ranging from 271 to 401 million tonnes for the pessimistic and optimistic scenarios, respectively. This article also reports on the supply potential of aviation biofuels (clustered in HEFA/HVOs and biojet) based on the production capacity of facilities around the world and provides an insight on the current and future trends in aviation based on the European and national policies, innovations and state-of-the art technologies that will influence the future of sustainable fuels in aviation.