A novel approach for the modelling of air quality dynamics in underground railway stations

Indoor air quality in subterranean train stations is a concern in many places around the globe. However, due to the specificity of each case, numerous parameters of the problem remain unknown, such as the braking discs particle emission rate, the ventilation rate of the station or the complete particle size distribution of the emitted particles. In this study the problem of modelling PM₁₀ concentration evolution in relation with train traffic is hence addressed with a particle-mass conservation model which parameters are fitted using a genetic algorithm. The parameters of the model allow to reproduce the dynamics and amplitude of four field data sets from the French and Swedish underground contexts and comply with realistic bounds in terms of emissions, deposition and ventilation rate.     

Levels of ultrafine particles in the Taipei Rapid Transit System

Ultrafine particle number concentrations are measured at five stations and inside trains on four routes in the Taipei Rapid Transit System during October–December 2007. The results indicate that there are no additional emission sources of ultrafine particle on the platforms. Ultrafine particle levels at a ground level station were, however, adversely affected by traffic outside of the station. Moreover, particles can enter the underground stations via the subway tunnels resulting in high levels during weekdays.     

A heuristic for the train pathing and timetabling problem

In a railroad system, train pathing is concerned with the assignment of trains to links and tracks, and train timetabling allocates time slots to trains. These important tasks were traditionally done manually, but there is an increasing move toward automated software based on mathematical models and algorithms. Most published models in the literature either focus on train timetabling only, or are too complicated to solve when facing large instances. In this paper, we present an optimization heuristic that includes both train pathing and train timetabling, and has the ability to solve real-sized instances. This heuristic allows the operation time of trains to depend on the assigned track, and also lets the minimum headway between the trains to depend on the trains’ relative status. It generates an initial solution with a simple rule, and then uses a four-step process to derive the solution iteratively. Each iteration starts by altering the order the trains travel between stations, then it assigns the services to the tracks in the stations with a binary integer program, determines the order they pass through the stations with a linear program, and uses another linear program to produce a timetable. After these four steps, the heuristic accepts or rejects the new solution according to a Threshold Accepting rule. By decomposing the original complex problem into four parts, and by attacking each part with simpler neighborhood-search processes or mathematical programs, the heuristic is able to solve realistic instances. When tested with two real-world examples, one from a 159.3 km, 29-station railroad that offers 44 daily services, and another from a 345 km, eight-station high-speed rail with 128 services, the heuristic obtained timetables that are at least as good as real schedules.     

浙江省沿海典型码头大气污染水平及影响因素分析

本文选择浙江省沿海典型油气码头、干散货码头、件杂货码头和集装箱专用码头作为监测点,在一个自然年中分别选取代表日进行空气质量监测。根据污染物浓度水平,结合气象条件参数和交通流量参数,对大气污染物进行影响因素分析。结果表明:码头空气质量优于当地整体情况;SO_2、NO_2、PM_2.5和PM₁₀浓度变化与气温、湿度、风速呈负相关关系,与气压呈正相关关系,CO浓度受气象条件影响较小;靠港船舶和码头内作业车辆尾气是码头空气污染物的重要来源。     

Characteristics of particulate matter (PM) concentrations influenced by piston wind and train door opening in the Shanghai subway system

More than 9 million passengers take Shanghai’s subway system every work day. The system’s air quality has caused widespread concern because of the potential harm to passengers’ health. We measured the particulate matter (PM) concentrations at three kinds of typical underground platform (side-type, island-type, and stacked-type platforms) and inside the trains in Shanghai’s metro during 7 days of measurements in April and July 2015. Our results demonstrated that the patterns of air quality variation and PM concentrations were similar at the side-type and island-type platforms. We also found that the PM concentrations were higher on the platforms than inside the train and that the PM concentrations in the subway system were positively correlated with those in the ambient air. Piston wind generated by vehicle motion pushes air from the tunnel to the platform, so platform PM concentrations increase when trains approach the platform. However, the piston wind effect varies greatly between locations on the platform. In general, the effect of the piston wind is weaker at the middle of the platform than at both ends. PM concentrations inside the train increase after the doors open, during which time dirty platform air floods into the compartments. PM_1.0 and PM_2.5 were significantly correlated both inside the train and on the platforms. PM_1.0 accounted for 71.9% of PM_2.5 inside the train, which is higher than the corresponding platform values. Based on these results, we propose some practical suggestions to minimize air pollution damage to passengers and staff from the subway system.     

乌鲁木齐市疫情期间交通流量对空气质量影响的分析

选取环境空气中PM2.5、PM10、CO、NO₂、O₃污染物及空气质量指数(AQI)分析乌鲁木齐市疫情期间交通流量对空气质量的影响。结果表明,在乌鲁木齐市两次疫情交通管制期间,交通流量显著降低,环境空气中PM2.5、PM10、CO、NO₂、O₃污染物浓度及AQI随之降低,尤其是PM10、CO和NO₂浓度下降较为显著。自乌鲁木齐市解除交通管制,车辆恢复正常通行后,PM10、CO及NO2浓度逐渐增加甚至反超同期。鉴于PM、CO及NO₂是汽车尾气的主要污染物,因此可推测交通流量增加或降低,环境空气质量也会随之发生变化,尤其是空气中PM10、CO及NO₂污染物浓度呈正相关变化。     

Estimation of road transport related air pollution in Saint Petersburg using European and Russian calculation models

The paper analyzes Russian and European emission and dispersion models aimed at the estimation of road transport related air pollution on street and regional scale as exemplified with St. Petersburg, Russia. It demonstrates the results of model calculations of peak concentrations of main harmful substances (NО_X, CO and PM₁₀) along the St. Petersburg Ring Road at high traffic volume and adverse meteorological conditions (calm, temperature inversion) executed by means of a Russian street pollution model, and it evaluates the computed results against the measurements from monitoring stations. The paper also examines the ways of adaptation of the COPERT IV model – a software tool for calculation of air pollutant and greenhouse gas emissions from road transport on regional or country scale – to the inventory conditions of the Russian Federation, compares the COPERT IV numerical estimates with the national inventory data. It also reveals the obstacles and possibilities in the harmonization of the Russian and European approaches.     

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.     

Atmospheric impact of ship traffic in four Adriatic-Ionian port-cities: Comparison and harmonization of different approaches

Shipping is a growing transport sector representing a relevant share of atmospheric pollutant emissions at global scale. In the Mediterranean Sea, shipping affects air quality of coastal urban areas with potential hazardous effects on both human health and climate. The high number of different approaches for investigating this aspect limits the comparability of results. Furthermore, limited information regarding the inter-annual trends of shipping impacts is available. In this work, an approach integrating emission inventory, numerical modelling (WRF-CAMx modelling system), and experimental measurements at high and low temporal resolution is used to investigate air quality shipping impact in the Adriatic/Ionian area focusing on four port-cities: Brindisi and Venice (Italy), Patras (Greece), and Rijeka (Croatia). Results showed shipping emissions of particulate matter (PM) and NOx comparable to road traffic emissions at all port-cities, with larger contributions to local SO₂ emissions. Contributions to PM_2.5 ranged between 0.5% (Rijeka) and 7.4% (Brindisi), those to PM₁₀ were between 0.3% (Rijeka) and 5.8% (Brindisi). Contributions to particle number concentration (PNC) showed an impact 2–4 times larger with respect to that on mass concentrations. Shipping impact on gaseous pollutants are larger than those to PM. The contribution to total polycyclic aromatic hydrocarbon (PAHs) concentrations was 82% in Venice and 56% in Brindisi, with a different partition gas-particle because of different meteorological conditions. The inter-annual trends analysis showed the primary contribution to PM concentrations decreasing, due to the implementation of the European legislation on the use of low-sulphur content fuels. This effect was not present on other pollutants like PAHs.     

Probabilistic analysis of the release of liquefied natural gas (LNG) tenders due to freight-train derailments

Liquefied natural gas (LNG) has emerged as a possible alternative fuel for freight railroads in the United States, due to the availability of cheap domestic natural gas and continued pursuit of environmental and energy sustainability. A safety concern regarding the deployment of LNG-powered trains is the risk of breaching the LNG tender car (a special type of hazardous materials car that stores fuel for adjacent locomotives) in a train accident. When a train is derailed, an LNG tender car might be derailed or damaged, causing a release and possible fire. This paper describes the first study that focuses on modeling the probability of an LNG tender car release incident due to a freight train derailment on a mainline. The model accounts for a number of factors such as FRA track class, method of operation, annual traffic density level, train length, the point of derailment, accident speed, the position(s) of the LNG tender(s) in a train, and LNG tender car design. The model can be applied to any specified route or network with LNG-fueled trains. The implementation of the model can be undertaken by the railroad industry to develop proactive risk management solutions when using LNG as an alternative railroad fuel.     

Dynamic blocking for railyards: Part I. Homogeneous traffic

This paper and its companion present a study of railroad classification yard strategies that allow for blocks of destinations to be assigned to classification tracks in different ways, depending on the time of day, week or month. With the same number of tracks, more classifications can be handled by this method. The paper examines homogeneous traffic; that is, traffic patterns where all blocks have the same amount of traffic, where cars for all blocks depart equally frequently from the yard and where the overall traffic flow does not change with time. The results represent the beginning of a better understanding of yard operations, which should be useful for designing new yards, planning expansions of existing ones and evaluating the impact of changes (planned and unplanned) on traffic patterns. The paper concentrates on two sorting strategies: sorting by train (perhaps the most commonly used strategy in the United States today), and triangular sorting. For both strategies, formulas are given for the minimum number of tracks, number of switches and for the total space requirements. For triangular sorting, the yard delay and total space depend on the time chosen between reswitches. These two measures of performance can be reduced if one is willing to accept a sorting effort slightly higher than minimum. The trade-off can be explored numerically. For sorting by train, yard delay and total space are not significantly affected by the sorting method; there is no such trade-off. It appears that sorting by train results in less work, delay and space requirements than triangular sorting, at least in most instances when either could be used. Triangular sorting, however, can be used when there are not enough tracks to allow sorting by train.     

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.     

Railroad noise: economic valuation and policy

In developed countries noise annoyance is an important source of environmental concern. Research on noise annoyance caused by railroad traffic is relatively underdeveloped. Here, a causal chain model is presented in which railroad traffic density, noise emission, noise immission and noise annoyance are causally related. Noise level, habituation and railroad usage are determinant factors. Noise annoyance causes social and economic costs, such as property value depreciation. Policy measures, aimed at reducing social and economic costs, are incorporated in various stages of the causal model. These measures can be subdivided into noise regulation and direct prevention measures. Stricter threshold values lead to higher total costs, but may lower social costs per capita. Economic feasibility of policy measures is usually analyzed by means of a cost-benefit case study. Methods of analysis used are diverse and ad hoc. Therefore, results of different case studies are not easily compared in terms of research synthesis.     

Comparing rail fuel efficiency with truck and waterway

This paper presents a railroad energy efficiency model used to estimate the fuel economies for classes of trains transporting various commodities. Comparable procedures are used to estimate truck and waterway fuel consumption. The results show that coal unit trains are 4.5–5.0 times more energy efficient than movements in the largest trucks allowed in the eastern and western regions of the US, unit grain train movements in the central US are 4.6 times more fuel efficient, soda ash unit train and non-unit train shipments are 4.9 and 3.2 times more efficient, and ethanol unit train and non-unit train movements are 4.8 and 3.0 times more efficient. In terms of barge traffic, coal unit train and non-unit train are 1.3 and 0.9 times as energy efficient in the eastern US, grain unit train and non-unit train movements are 1.7 and 1.0 times more efficient from Minneapolis to the Gulf of Mexico, and grain unit train and non-unit train movements are 1.0 and 0.7 times more fuel efficient from the Upper Ohio River to the Gulf of Mexico.     

Correlation between automotive CO, HC, NO, and PM emission factors from on-road remote sensing: implications for inspection and maintenance programs

Carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NO) emission factors (EFs) are measured with a commercial vehicle emissions remote sensing system (VERSS) during a large-scale vehicle exhaust emissions study in Las Vegas. Particulate matter (PM) EFs are simultaneously measured for individual vehicles with a newly developed PM-VERSS based on ultraviolet backscatter light detection and ranging (Lidar). The effectiveness of CO and HC EFs as proxy for NO and PM EFs for spark-ignition vehicles is evaluated. Poor correlations were found between EFs for pollutants on an individual vehicle basis indicating that high EFs for one or more pollutants cannot be used as a predictor of high EFs for other pollutants. Stronger functional relationships became evident after averaging the EF data in bins based on rank-order of a single pollutant EF. Low overlap between the highest 10% emitters for CO, HC, NO, and PM was found. These results imply that for an effective reduction of the four pollutants, inspection and maintenance (I/M) programs, including clean screening, should measure all four pollutants individually. Fleet average CO and HC concentrations determined by gaseous VERSS were compared with fleet average CO and HC concentrations measured at low-idle and at high-idle during local I/M tests for spark-ignition vehicles. The fleet average CO concentrations measured by I/M tests at either idle were about half of those measured by remote sensing. The fleet average high-idle HC concentration measured by I/M tests was about half of that measured by VERSS while low-idle I/M and VERSS HC average concentrations were in better agreement. For a typical vehicle trip, most of the fuel is burned during non-idle conditions. I/M measurements collected during idling conditions may not be a good indicator of a vehicle’s potential to be a high emitter. VERSS measurements, when the vehicle is under a load, should more effectively identify high emitting vehicles that have a large contribution to the mobile emissions inventory.     

A Value-at-Risk (VAR) approach to routing rail hazmat shipments

Hazardous materials (hazmat) accidents are rare though the consequences could be disastrous. Given the possibility of low probability – high consequence event, a risk-averse routing hazmat shipment is necessary. We propose a value-at-risk (VaR) approach to route rail hazmat shipments, using the best train configuration, over a given railroad network with limited number of train services such that the transport risk as measured by VaR is minimized. Freight train derailment reports of the Federal Railroad Administration were analyzed to develop expressions that would incorporate characteristics of railroad accidents, and then to estimate the different inputs. The proposed methodology was used to study several problem instances generated using the realistic network of a railroad operator, and to demonstrate that it is possible to develop different routes for shipments depending on the risk preference of the decision maker.     

Enhancing intelligent agent collaboration for flow optimization of railroad traffic

Intelligent agents have successfully solved the train pathing problem on a small portion of railroad network [Tsen, 1995, Ph.D. Thesis, Carnegie Mellon University, USA]. As the railroad network grows, it is imperative that the agents collaborate to operate as efficiently as possible. In this paper, the authors demonstrate a collaboration protocol based on a conditional measure of agent effectiveness. Because agent effectiveness is not directly measurable, a suitable metric for agent effectiveness is introduced. Where typically agents run with uniform frequency, the collaboration protocol schedules the agents with a frequency proportional to their expected effectiveness. This protocol introduced a 10-fold improvement in the agent efficiency when tested with a simulation program on a portion of the Burlington Northern railroad.     

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.     

The relationship between property values and railroad proximity: a study based on hedonic prices and real estate brokers' appraisals

We study the relationship between the price of residential property value and proximity to railroads in Oslo, by two different methods, namely a) through a hedonic price study where the statistical relationship between property prices and railroad proximity is estimated, and b) through a multi-attribute utility investigation of real estate agents' evaluation of such a relationship. We find in both cases that there are strong effects of proximity to railroad lines on property prices, at distances less than 100 meters from the lines. In the statistical study log-linear relationships fit the data best, and our estimates indicate that a doubling of the distance from the railroad line, within a 100 meter bound, increases the property price by about 10%. With real estate agents only a linear relationship is probed. This yields an increase in the price of an average relevant housing unit by about 182,000 NOK, due to a increase in the distance to a railroad track from 20 to 100 meters. The equivalent figure from the statistical study is in the range 120–150,000 NOK. The two figures are thus of the same magnitude.     

Non-exhaust particle emissions under various driving conditions: Implications for sustainable mobility

Non-exhaust particle (NEP) emissions from road traffic contribute significantly to Particulate Matter (PM) pollution in urban areas. The primary objective herein is to develop the knowledge required to move toward more sustainable mobility. NEP emissions are studied by means of complementary experiments on chassis dynamometers, on test tracks and at the roadside. Laboratory tests demonstrate that brake wear particles (BWP) emissions can change with braking force and frequency. A brake pad temperature threshold exists, above which the rate of ultrafine particle emissions is quite high. Below this threshold, the BWP emissions are dominant in the accumulation and coarse modes. Test track measurements have demonstrated that tire-road contact particle (TRCP) emissions considerably modify the atmospheric PM background especially for the supermicron fraction. Their number size distribution highlighted an ultrafine and accumulation modes centered at about 40 nm and 200 nm, respectively. The TRCP level increases with vehicle speed and during the acceleration and deceleration phases. Roadside measurements in the urban environment confirm the presence of NEP in significant proportions, in both the accumulation and coarse modes. The chemical composition of NEP differs depending on the size mode: BWP mainly stem from the degradation of brake pad lining materials, while TRCP are a mixture of tire tread wear and re-suspended dust. The presence of Fe-rich particles nevertheless serves as a good indicator of the NEP contribution to PM at the roadside. Lastly, in considering the parameters influencing NEP emissions, a series of recommendations are offered in order to achieve a more sustainable mobility.