Effect on direct injection naturally aspirated diesel engine characteristics fuelled by pine oil,ceiba pentandra methyl ester compared with diesel

This paper explores the experimental investigation of the performance, emission and combustion characteristics of bio fuels from ceiba pentandra methyl ester (CPME), ceiba pentandra methyl ester-pine oil blends (CPMEP) and pine oil and the results are compared with diesel. In ceiba pentandra seed oil the CPME yield is 92% by using transesterification process with the optimum conditions of 560 rpm, reaction time 58 min, catalyst concentration 13 g and methanol amount 500 ml. The viscosity of CPME is high when compare with diesel. So the low viscosity of pine oil is blended with CPME and it can be directly used in diesel engine without any modification. At different loads the Pine oil, CPME and CPMEP blends were used in direct injection naturally aspirated compression ignition engine. The outcomes exhibited that at full load conditions for CPME and CPMEP blends increased brake specific fuel consumption, and decreased brake thermal efficiency, CO, HC emissions. NOx emissions decreased and smoke emissions are increased on CPME and CPMEP blends, expect B25 blend compared with diesel. The combustion analysis like the heat release rate, peak cylinder pressure, cumulative heat release rate and ignition delay for CPME, CPMEP blends slightly lower and combustion duration higher than diesel and pine oil. At the Same engine operating condition, the engine fuelled with pine oil the values of brake thermal efficiency 4.79%, peak cylinder pressure, heat release rate, cumulative heat release rate and ignition delay are increased. Brake specific fuel consumption, CO, HC, and smoke were 9.46%, 16.66%, 14.89% and 8.33% decreased. However, the NOx emission is 8.29% higher than that of diesel. Experimental fuels up to B50 (50% pine oil and 50% CPME) blends have proved good potential for future energy is needed.     

Thermodynamic,environmental and economic effects of diesel and biodiesel fuels on exhaust emissions and nano-particles of a diesel engine

In this study, diesel (JIS#2) and various biodiesel fuels (BDF20, BDF50, BDF100) are used to operate the diesel engine at 100 Nm, 200 Nm and full load; while the engine speed is 1800 rpm. The system is experimentally studied, and the energy, exergy, sustainability, thermoeconomic and exergoeconomic analyses are performed to the system. The Engine Exhaust Particle Sizer is used to measure the size distribution of engine exhaust particle emissions. Also, the data of the exhaust emissions, soot, particle numbers, fuel consumptions, etc. are measured. It is found that (i) most of the exhaust emissions (except NO_x) are directly proportional to the engine load, (ii) maximum CO₂ and NO_x emissions rates are generally determined for the BDF100 biodiesel fuel; while the minimum ones are calculated for the JIS#2 diesel fuel. On the other hand, the maximum CO and HC emissions rates are generally computed for the JIS#2 diesel fuel; while the minimum ones are found for the BDF100 biodiesel fuel, (iii) fuel consumptions from maximum to minimum are BDF100 > BDF50 > BDF20 > JIS#2 at all of the engine loads, (iv) particle concentration of the JIS#2 diesel fuel is higher than the biodiesel fuels, (v) soot concentrations of the JIS#2, BDF20 and BDF50 fuels are directly proportional to the engine load; while the BDF100 is inversely proportional, (vi) system has better energy and exergy efficiency when the engine is operated with the biodiesel fuels (vii) sustainability of the fuels are BDF100 > BDF50 > BDF20 > JIS#2, (viii) thermoeconomic and exergoeconomic parameters rates from maximum to minimum are JIS#2 > BDF20 > BDF50 > BDF100.     

General statistics of diesel engines’ idle time: Shunting locomotives in industrial sidings in Poland 2009…2013

Shunting locomotive/switcher (AmE)/utilization profiles are analyzed in this paper, in particular on the basis of idle time data collected in nineteen Polish industrial sidings and yards. 40 years old, diesel-electric locomotives are observed during 1000 h. Idle times related to work cycles are analyzed statistically. The percentage of the shunting locomotive daily operating time that the engine is operating at idle amounts to 70% (from 55% to 90%), and average daily idle fuels consumption amounts to 150 l a day (from 90 to 240 l a day).Many European and Asian countries still operate a significant number of similar (ChME3, e.g. S200) old, diesel-electric locomotives (almost 8000 locomotives have been produced), for moving trains over long distances and as shunting locomotives.Observed frequent short idle time periods suggest necessity of widening future scope of idling times’ analysis. Adaptation of Polish rolling stock will be possible using prior general public education about dangerous carcinogens in diesel exhaust smoke and fuel waste related to diesel engines’ idling. Simple simultaneous depiction of diesel engine power time series together with idle time could be used for educational visualization of idling among a wider audience. In the future classical aggregated idle time statistics should be supplemented by models that are more related to the variability of shunting locomotives diesel generator’s power time series, e.g. distribution of frequent short individual idle time cases.     

Environmental effect of CI engine using microalgae methyl ester with doped nano additives

Algae are organisms that grow in marine environments and use carbon dioxide and light to create bio-mass. There are two groupings of algae: microalgae and macroalgae. Macroalgae are the large, multi-cellular algae often seen growing in ponds. Microalgae, on the other hand, are tiny, unicellular algae that normally grow in suspension within a body of water. Algae oil from microalgae has the possible to become a sustainable fuel source as biodiesel. Microalgae are produced through photosynthesis by utilizing sunlight, water, carbon dioxide and other nutrients. The Botryococcus braunii algal oil was extracted by mechanical extraction method. The transesterification reaction of Botryococcus braunii algal oil with methanol and base catalyst was used for the production of biodiesel. The samples B20 were prepared for each methyl ester obtained from Botryococcus braunii algal oil separately and then the doping of TiO₂ and SiO₂ nanoparticles were added to the each B20 blend samples at a dosage of 50 ppm and 100 ppm with an aid of ultrasonicator. Moreover, in the absence of any engine modifications, the performance and emission characteristics of those blend samples have been investigated from the experimentally measured values such as density, viscosity, calorific value, etc. while the engine performance was also analyzed through the parameters like BSFC, BTH, exhaust emission of CO, HC, NOx and CO₂. The experimental results reveal that the use of biodiesel blend with nano additives in diesel engine has exhibited good improvement in performance characteristic and reduction in exhaust emissions.     

Performance and emission characteristics of a spark ignition engine fuelled with butanol isomer-gasoline blends

The heavy reliance on petroleum-derived fuels such as gasoline in the transportation sector is one of the major causes of environmental pollution. For this reason, there is a critical need to develop cleaner alternative fuels. Butanol is an alcohol with four different isomers that can be blended with gasoline to produce cleaner alternative fuels because of their favourable physicochemical properties compared to ethanol. This study examined the effect of butanol isomer-gasoline blends on the performance and emission characteristics of a spark ignition engine. The butanol isomers; n-butanol, sec-butanol, tert-butanol and isobutanol are mixed with pure gasoline at a volume fraction of 20 vol%, and the physicochemical properties of these blends are measured. Tests are conducted on a SI engine at full throttle condition within an engine speed range of 1000–5000 rpm. The results show that there is a significant increase in the engine torque, brake power, brake specific fuel consumption and CO₂ emissions with respect to those for pure gasoline. The butanol isomers-gasoline blends give slightly higher brake thermal efficiency and exhaust gas temperature than pure gasoline at higher engine speeds. The iBu20 blend (20 vol% of isobutanol in gasoline) gives the highest engine torque, brake power and brake thermal efficiency among all of the blends tested in this study. The isobutanol and n-butanol blend results in the lowest CO and HC emissions, respectively. In addition, all of the butanol isomer-gasoline blends yield lower NO emissions except for the isobutanol-gasoline blend.     

The role of nano additives for biodiesel and diesel blended transportation fuels

The energy crisis is due to two reasons, one is the rapid increase in worldwide population and the other is changing living style of human beings. The fossil fuel is also a major contributor to add the harmful pollutants into the atmosphere. Fuel modifications play a major role in increasing engine efficiency and reducing emissions. In the present investigation focused on fuel modifications in diesel engine. Initially the single cylinder diesel engine was operated with 20MEOM, 40MEOM, 60MEOM, 8MEOM and 100MEOM without additives with diesel at different loads at constant rated speed. From the experimental study proved that 20MEOM is the best fuel ratio compared to other blends. In second phase based upon first phase results the engine was operated 20MEOM blended fuel with adding 50 ppm copper oxide nano additives with diesel using solgel process. From the results, the brake thermal efficiency was 2.19% improved compared than 20MEOM blend without additive at full load condition. Emissions of HC, CO and smoke were considerably reduced. The present analysis reveals that the biofuel from mahua oil with nano additives is quite suitable as an alternate fuel for diesel engine.     

Development of optimum friction new nano hybrid composite liner for biodiesel fuel engine

This work presents the preparation of aluminum (Al) 6061 nano hybrid composite samples reinforced with equal weight percentage of nano-ZrO₂, micro-SiC, micro-Gr particles of 0%, 0.75%, 1.5%, 2.25%, and 3% using stir casting method. Friction characteristics of the composite samples under reciprocating conditions were studied at 125 °C using L₂₇ orthogonal array and Taguchi method. The results of analysis of variance showed the influencing parameter for friction coefficient in the order of applied load and reciprocating sliding speed, followed by sliding distance and percent reinforcement. Hence, the total combined reinforcement sample of 6.75% was found to be optimum in terms of frictional characteristics and tensile strength. It was selected to synthesize lightweight nano hybrid composite cylinder liner (NL) and to replace the present cast iron cylinder liner (CL) used in biodiesel engine application. The developed NL had a 43.75% reduced weight than the currently used CL. Neat diesel and biodiesel from Jatropha oil and its diesel blends were used as test fuels. Experimental results proved that NL improved brake thermal efficiency, in-cylinder pressure, heat release rate and reduced carbon monoxide, hydrocarbon, and smoke emission in comparison with the existing liner. The results also showed that emission of the oxides of nitrogen (NO_x) increased marginally with the new liner. Thus, the newly developed NL was found suitable for both diesel- and biodiesel-operated internal combustion engines.     

Carbon emission from urban passenger transportation in Beijing

Urban passenger transport significantly contributes to global greenhouse gas emissions, especially in developing countries owing to the rapid motorization, thus making it an important target for carbon reduction. This article established a method to estimate and analyze carbon emission from urban passenger transport including cars, rail transit, taxis and buses. The scope of research was defined based on car registration area, transport types and modes, the stages of rail transit energy consumption. The data availability and gathering were fully illustrated. A city level emission model for the aforementioned four modes of passenger transport was formulated, and parameters including emission factor of electricity and fuel efficiency were tailored according to local situations such as energy structure and field survey. The results reveal that the emission from Beijing’s urban passenger transport in 2012 stood at 15 million tonnes of CO₂, of which 75.5% was from cars, whereas car trip sharing constitutes only 42.5% of the total residential trips. Bus travel, yielding 28.6 g CO₂, is the most efficient mode of transport under the current situations in terms of per passenger kilometer (PKM) emission, whereas car or taxi trips emit more than 5 times that of bus trips. Although a decrease trend appears, Beijing still has potential for further carbon reduction in passenger transport field in contrast to other cities in developed countries. Development of rail transit and further limitation on cars could assist in reducing 4.39 million tonnes CO₂ emission.     

Potential of low viscosity oils to reduce CO2 emissions and fuel consumption of urban buses fleets

This paper shows the results of a comparative fleet test the main objective of which was to measure the influence of Low Viscosity Oils (LVO) over the fuel consumption and CO₂ emissions of urban buses. To perform this test, 39 urban buses, classified into candidate and reference groups depending on the engine oil viscosity, covered a 60,000 km mileage corresponding to two rounds of standard Oil Drain Interval (ODI). In the same way, for 9 buses of the 39 buses, the effect of differential LVO over fuel consumption and their interaction with engine LVO was assessed during the second ODI.Test results confirm that the use of LVO could reduce fuel consumption, hence CO₂ emissions. However, special attention should be taken prior to its implementation in a fleet, particularly if the vehicles are powered by engines with high mechanical and thermal stresses during vehicle operation because this could lead to friction loss increase, loss of the potential fuel consumption reduction of LVO and, in the worst scenario, higher rates of engine wear.     

Estimation of nitrogen oxides emissions from petrol and diesel passenger cars by means of on-board monitoring: Effect of vehicle speed,vehicle technology,engine type on emission rates

NO_X emission rates of 13 petrol and 3 diesel passenger cars as a function of average speed from 10 to 120 km/h, emission class (pre-Euro 1 – Euro 5), engine type were investigated by on-board monitoring on roads and highways of St. Petersburg using a portative Testo XXL 300 gas analyzer. The highest level of NO_X emission 0.5–2.5 g/km was inherent to old pre-Euro 1 petrol cars without a catalytic converter. NO_X emissions rates of Euro 1 and Euro 2 petrol cars changed within 0.15–0.9 g/km, Euro 3 – 0.015–0.27 g/km, Euro 4 – 0.013–0.1 g/km, Euro 5 – 0.002–0.043 g/km. Euro 3 – Euro 4 petrol cars generally satisfied corresponding NO_X Emission Standards (ES), except cold-start period, Euro 5 petrol cars did not exceed ES. Warmed, stabilized engines of Euro 3 – Euro 5 petrol cars showed 5–10 times lower NO_X emission rates than corresponding ES in the range of speed from 20 to 90 km/h. NO_X emission rates of diesel Euro 3 and Euro 4 cars varied from 0.45 to 1.1 g/km and from 0.31 to 1.1 g/km, respectively. Two examined diesel Euro 3 and one Euro 4 passenger vehicles did not satisfy NO_X ES at real use. Euro 3 diesel cars showed 28.9 times higher NO_X emissions than Euro 3 petrol cars and Euro 4 diesel car demonstrated 17.6 times higher NO_X emissions than Euro 4 petrol cars at warmed and stabilized engine at a cruise speed ranging from 30 to 60 km/h.     

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.     

Characteristics of gaseous and particulate pollutants exhaust from logistics transportation vehicle on real-world conditions

On-road vehicle tests of three heavy duty diesel trucks were conducted by a portable emission measurement system (PEMS) in Chengdu, China. SEMTECH-ECOSTAR provided by Sensors Inc. was employed to detect gaseous emissions and MI2, an emissions measuring instrument powered by the Pegasor Particulate Sensor (PPS) was used to detect particulate emissions during the tests. The impacts of speed, acceleration and engine load on emissions were analyzed. The average nitrogen oxides (NOx) emission factors of the heavy duty diesel truck (HDDT), medium-duty diesel truck (MDDT), light duty diesel truck (LDDT) were 7.29, 5.29 and 5.53 g/km. The particulate emission factors were 0.60, 0.30 and 0.14 g/km respectively, higher than the similar reported in the previous studies. Both gaseous and particulate emission exhibit significant correlations with the change in vehicle speed, acceleration and power demand. The highest emission was generally in high VSPs and higher loads. High engine load caused by aggressive driving was the main factor of high emissions for the vehicles on real-world conditions.     

Experimental investigation of evaporation rate and exhaust emissions of diesel engine fuelled with cotton seed methyl ester and its blend with petro-diesel

An experimental study to measure the evaporation rates, engine performance and emission characteristics of cotton seed biodiesel (cotton seed oil methyl ester) and its blends in different volumetric proportions with diesel is presented. The thermo-physical properties of all the fuel blends have been measured and presented. Evaporation rates of neat cotton seed biodiesel, neat diesel and their bends have been measured under slow convective environment of air flowing with a constant temperature. Evaporation constants have been determined by using the droplet regression rate data. The neat fuels and fuel blends have been utilized in a test engine with different load conditions to evaluate the performance, combustion and emission characteristics of the fuels. The specific fuel consumption values of the two blends, viz. B25 and B75 are found to be same. At the highest load, B0 records the lowest CO volume followed by B100. From the observed evaporation, performance and emissions characteristics, it is suggested that a blend of B50 and B75 can be optimally used in standard diesel engine settings.     

The future mobility of the world population

On average a person spends 1.1 h per day traveling and devotes a predictable fraction of income to travel. We show that these time and money budgets are stable over space and time and can be used for projecting future levels of mobility and transport mode. The fixed travel money budget requires that mobility rises nearly in proportion with income. Covering greater distances within the same fixed travel time budget requires that travelers shift to faster modes of transport. The choice of future transport modes is also constrained by path dependence because transport infrastructures change only slowly. In addition, demand for low-speed public transport is partially determined by urban population densities and land-use characteristics. We present a model that incorporates these constraints, which we use for projecting traffic volume and the share of the major motorized modes of transport—automobiles, buses, trains and high speed transport (mainly aircraft)—for 11 regions and the world through 2050. We project that by 2050 the average world citizen will travel as many kilometers as the average West European in 1990. The average American's mobility will rise by a factor of 2.6 by 2050, to 58,000 km/year. The average Indian travels 6000 km/year by 2050, comparable with West European levels in the early 1970s. Today, world citizens move 23 billion km in total; by 2050 that figure grows to 105 billion.     

Energy use and emissions of two stroke-powered tricycles in Metro Manila

CO, CO₂, NO_x and HC emissions of two stroke-powered tricycles in Metro Manila are examined using an instantaneous emissions model. Results show that fuel consumption and HC emissions in middle class residential areas and main roads are similar but lower than levels in low income residential areas. On the average, tricycles in Metro Manila consume 24.41 km/l of fuel and produces 9.5, 9.7, 40.5 and 0.07 g/km of HC, CO, CO₂ and NO_x, respectively. They fail to satisfy HC, CO and NO_x emission limits set by reference standards in the Philippines and other Asian countries. They produce greater HC and CO emissions than gasoline fueled private cars and diesel powered public jeepneys, taxis and buses on a per passenger-km basis but significantly lower NO_x emissions. Tricycles account for 15.4% of the total HC emissions from mobile sources in the metropolis while their contributions to CO, CO₂ and NO_x are minimal.     

Truck versus pipeline transportation cost analysis of wastewater sludge

Domestic and industrial sludge generated at wastewater treatment facilities is considered a potential biomass source for producing biodiesel. However, transportation of large amounts of sludge from wastewater treatment facilities to a biorefinery is expensive. The objective of this paper is to identify the proper transportation mode to use as a function of the volume shipped and transportation distances. Currently, sludge is mainly shipped by truck and pipeline. We estimated that the fixed and variable cost components of pipeline transportation for a volume such as 480 m³/day and a distance of 100 miles are $0.116/m³ and $0.089/m³/mile, respectively. We estimated the biomass (sludge) transportation cost per gallon of biodiesel, and observed the changes in these costs as a function of distance traveled and volume shipped. The outcomes of this study have the potential to help biofuel plants make better biomass transportation decisions, and consequently reduce the price of biodiesel significantly.     

Effects of e-bikes on bicycle use and mode share

In Norway, as in many countries, a political goal is to increase bicycle use, and the e-bike is promising in this respect. However, concerns have been raised about mode-share effects. It has been argued that if the e-bike’s only function is in cycling becoming cycling with electric assistance, there would be no benefit to either the environment or public health. Little is yet known about the use of the e-bike, or of its potential in reducing motorized travel. In the current study, 66 randomly selected participants were given an e-bike to use for a limited period of time and the results compared with those of a control group (N = 160). E-bike cycling trips increased from 0.9 to 1.4 per day, distance from 4.8 km to 10.3 km and, as a share of all transport, from 28% to 48%, whereas with the control group there was no increase in cycling. The effect of the e-bike increased with time, indicating a learning effect among users, and was greater for female than for male cyclists. There were no differences with age. Overall, the results suggest that the e-bike is indeed practical for everyday travel.     

Stochastic dynamic switching in fixed and flexible transit services as market entry-exit real options

The first analytical stochastic and dynamic model for optimizing transit service switching is proposed for “smart transit” applications and for operating shared autonomous transit fleets. The model assumes a region that requires many-to-one last mile transit service either with fixed-route buses or flexible-route, on-demand buses. The demand density evolves continuously over time as an Ornstein-Uhlenbeck process. The optimal policy is determined by solving the switching problem as a market entry and exit real options model. Analysis using the model on a benchmark computational example illustrates the presence of a hysteresis effect, an indifference band that is sensitive to transportation system state and demand parameters, as well as the presence of switching thresholds that exhibit asymmetric sensitivities to transportation system conditions. The proposed policy is computationally compared in a 24-hour simulation to a “perfect information” set of decisions and a myopic policy that has been dominant in the flexible transit literature, with results that suggest the proposed policy can reduce by up to 72% of the excess cost in the myopic policy. Computational experiments of the “modular vehicle” policy demonstrate the existence of an option premium for having flexibility to switch between two vehicle sizes.     

Assessing the impact of cornering losses on the energy consumption of electric city buses

In view of the increasing electrification of public city transport, an accurate energy consumption prediction for Battery Electric Buses (BEBs) is essential. Conventional prediction algorithms do not consider energy losses that occur during turning of the vehicle. This is especially relevant for electric city buses, which have a limited battery capacity and often drive curvy routes.In this paper, the additional energy consumption during steering of a BEB is modeled, measured, and assessed. A nonlinear steady-state cornering model is developed to establish the additional energy losses during cornering. The model includes large steer angles, load transfer, and a Magic Formula tire model. Model results show that both cornering resistance and tire scrub of the rear tires cause additional energy losses during cornering, depending on the corner radius and vehicle velocity.The energy consumption model is validated with full scale vehicle tests and shows an average deviation of 0.8 kW compared to the measurements. Analysis of recorded real-world bus routes reveals that on average these effects constitute 3.1% of the total powertrain energy. The effect is even more significant for routes crossing city centers, reaching values up to 5.8%. In these cases, cornering losses can be significant and should not be neglected in an accurate energy consumption prediction.     

Inferring patterns in the multi-week activity sequences of public transport users

The public transport networks of dense cities such as London serve passengers with widely different travel patterns. In line with the diverse lives of urban dwellers, activities and journeys are combined within days and across days in diverse sequences. From personalized customer information, to improved travel demand models, understanding this type of heterogeneity among transit users is relevant to a number of applications core to public transport agencies’ function. In this study, passenger heterogeneity is investigated based on a longitudinal representation of each user’s multi-week activity sequence derived from smart card data. We propose a methodology leveraging this representation to identify clusters of users with similar activity sequence structure. The methodology is applied to a large sample (n = 33,026) from London’s public transport network, in which each passenger is represented by a continuous 4-week activity sequence. The application reveals 11 clusters, each characterized by a distinct sequence structure. Socio-demographic information available for a small sample of users (n = 1973) is combined to smart card transactions to analyze associations between the identified patterns and demographic attributes including passenger age, occupation, household composition and income, and vehicle ownership. The analysis reveals that significant connections exist between the demographic attributes of users and activity patterns identified exclusively from fare transactions.