Scholarly article on topic 'Estimation of Carbon Footprint of Fuel Loss Due to Idling of Vehicles at Signalised Intersection in Delhi'

Estimation of Carbon Footprint of Fuel Loss Due to Idling of Vehicles at Signalised Intersection in Delhi Academic research paper on "Earth and related environmental sciences"

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Abstract of research paper on Earth and related environmental sciences, author of scientific article — Kirti Bhandari, Purnima Parida, Pragya Singh

Abstract Carbon footprint has become a broadly used term. CO2 emissions results in the global warming and subsequently climate change. It is one of the most significant of the six greenhouse gases (carbon dioxide, methane, nitrous oxide, hydrofluorocarbons, perfluorocarbons and sulphur hexafluoride). Transportation sector is one of the sources of GHG emissions. All means of transportation, apart from walking and cycling, which are negligible, cause emissions. In 2007, the transport sector emitted 142.04 million tons of CO2 eq. Road transport, being the dominant mode of transport in the country, emitted 87% of the total CO2 equivalent emissions from the transport sector. The main objective of this research is to quantify the carbon footprint due to fuel loss at signalized intersection. The methodology adopted is: i) Assortment of intersections with high, medium and low volumes ii) Examine the delays taking place at each intersection for individual modes of travel (car, buses, 2-wheeler and 4-wheeler) iii) Fuel consumption during idling of vehicles at signalised intersection has been calculated iv) Estimation of total carbon footprint of fuel loss in Delhi during idling of vehicles at selected intersections using IPCC Guidelines. The scope of the study is limited to the signalized intersections only. The results indicate that idling CO2 emission contribute 9% of the total emissions from transport sector in Delhi in 2004.Delay causes fuel loss, time loss and emissions. Thus to curb these losses it is very important to adopt proper policies and mitigation measures.

Academic research paper on topic "Estimation of Carbon Footprint of Fuel Loss Due to Idling of Vehicles at Signalised Intersection in Delhi"

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Procedia - Social and Behavioral Sciences 104 (2013) 1168 - 1177

2nd Conference of Transportation Research Group of India (2nd CTRG)

Estimation of Carbon Footprint of Fuel Loss Due to Idling of Vehicles at Signalised Intersection in Delhi

Kirti Bhandaria*, Purnima Paridab, Pragya Singhc

a(corresponding author) Principal Scientist, Transport Planning Division, Central Road Research Institute, New Delhi. 110 025, India bHead, Transport Planning Division, Central Road Research Institute, New Delhi. 110025, India cStudent, Madan Mohan Malaviya Engineering College,Gorakhpur,273010,India

Abstract

Carbon footprint has become a broadly used term. CO2 emissions results in the global warming and subsequently climate change. It is one of the most significant of the six greenhouse gases (carbon dioxide, methane, nitrous oxide, hydrofluorocarbons, perfluorocarbons and sulphur hexafluoride). Transportation sector is one of the sources of GHG emissions. All means of transportation, apart from walking and cycling, which are negligible, cause emissions. In 2007, the transport sector emitted 142.04 million tons of CO2 eq. Road transport, being the dominant mode of transport in the country, emitted 87% of the total CO2 equivalent emissions from the transport sector. The main objective of this research is to quantify the carbon footprint due to fuel loss at signalized intersection. The methodology adopted is: i) Assortment of intersections with high, medium and low volumes ii) Examine the delays taking place at each intersection for individual modes of travel (car, buses, 2-wheeler and 4-wheeler) iii) Fuel consumption during idling of vehicles at signalised intersection has been calculated iv) Estimation of total carbon footprint of fuel loss in Delhi during idling of vehicles at selected intersections using IPCC Guidelines. The scope of the study is limited to the signalized intersections only. The results indicate that idling CO2 emission contribute 9% of the total emissions from transport sector in Delhi in 2004.Delay causes fuel loss, time loss and emissions. Thus to curb these losses it is very important to adopt proper policies and mitigation measures.

© 2013 The Authors. Published by Elsevier Ltd.

Selectionandpeer-reviewunder responsibilityoflnternationalScientificCommittee.

Keywords: Idling emissions, Carbon footprint, Delhi;

* Corresponding author. Tel.: +91-011-26312268 E-mail address: kirti.bhandari7@gmail.com

1877-0428 © 2013 The Authors. Published by Elsevier Ltd.

Selection and peer-review under responsibility of International Scientific Committee. doi: 10.1016/j.sbspro.2013.11.213

1. Background

In recent years due to urbanization there has been rapid increase in the population of Delhi. The population of Delhi forms 1.38 percent of India in 2011.Due to ill planned escalation of urban centers large numbers of problems has occurred like traffic congestion, scarcity of water and electricity, declining environment and public health. The developing city has generated the high level of transport demand over the years. Total number of road vehicles in India as per the latest available statistics were 72.7 million and vehicular population in Delhi has increased from 0.01 million in 1951 to 3.5 million in 2001 and 7.4 million in 2012 (Census of India 2011). The number of signalized intersections in Delhi has augmented from 466 in 1996 to 600 in 2004 (Parida et. al. 2008). The registered two wheelers constitute nearly seventy percent of the vehicle population in almost all the cities. Due to higher income levels and greater needs for mobility in the urban areas, more automobiles are owned and operated in them. More than 90 percent of the automobiles are located in urban centres. This trend is observed to be changing in the recent past mainly due to the development of better quality road network connecting rural areas and richer communities of rural areas going in for the automobiles. Variety of road based transport modes catering to the transport demand ply in large numbers on the road system resulting in traffic and transportation problems in the form of increased traffic congestion, increased air and noise pollution, accidents, delays and subsequently results in emission of green house gases. The six greenhouse gases are CO2 (carbon dioxide), CH4 (methane), N20 (nitrous oxide), HFC's (hydrofluorocarbons), PFC's (perfluorocarbons) and SF6 (sulphur hexafluoride). Of these, CO2 is estimated to account for two thirds of global warming (DETR, 2000). It is present in the atmosphere in significant quantities, representing 99.4% of the six greenhouse gases, by tonnage CO2 emissions are the most significant of the greenhouse gases. Emission is on the increase due to enhanced trip lengths, shift of modal share towards personalized modes of travel and at signalized intersections (during the stoppage of vehicles during red signal phase). The aim of this research is to quantify the carbon footprint at signalized intersection. By developing a common understanding of how to calculate this, different measures could be adopted to reduce the emission.

2. Carbon footprint of road transport sector

Between 1994 and 2005, India's greenhouse gas emissions are estimated to have risen by approximately 50 percent (MoEF, 2004), ranking fourth globally in overall terms (behind the US, China, and the EU) and contributing around 5.5 per cent of global emissions (FIIA, 2009).The largest bulk of India's emissions come from the energy sector. In 1994 energy accounted for about 61 per cent of total CO2 eq emissions of which almost half came from electricity supply, 20 per cent from industrial fuel combustion and around 11 per cent from transport. Road transport accounted for nearly 90 per cent of transport emissions (the remaining 10 percent coming from rail, aviation and shipping). WRI estimates suggest that the overall contribution of the energy sector is rising (WRI CAIT 2009). Of the other sectors, agriculture accounted for 28 per cent of total emissions in 1994 (around 22 percent in 2005), industrial process emissions contributed around 6-8 percent, waste disposal accounted for 2 per cent (rising to nearly 7 percent in 2005), and land use and land use change accounted for 1 per cent (net carbon storage in 2000). Figure 1(a) shows a sectored breakdown of emissions for 1994. The transport sector emissions are reported from road transport, aviation, railways and navigation. In 2007, the transport sector emitted 142.04 million tons of CO2 eq. Road transport, being the dominant mode of transport in the country, emitted 87% of the total CO2 equivalent emissions from the transport sector. The aviation sector in comparison only emitted 7% of the total CO2 eq. emissions. The rest were emitted by railways (5%) and navigation (1%) sectors. The bunker emissions from aviation and navigation have also been estimated but are not counted in the national totals. (INCCA 2010) (Figure 1(b))

Aviation, 7% Railways,

Fig 1(a) Emissions by sector, 1994 (based on data from MOEF, 2004) (b) GHG emissions from Transport Sector by mode of transport in 2007 (million tons of CO2 eq.) (INCCA 2010)

3. Literature Review

A literature review was performed of commonly used traffic models and methods for measuring CO2 emission. CMEM (COMPREHENSIVE MODAL EMISSION MODEL) is a microscopic emissions model that has been developed at the University of California, Riverside. It is capable of predicting second-by-second fuel consumption and tailpipe emissions of carbon dioxide (CO2), carbon monoxide (CO), hydrocarbons (HC), and nitrogen oxides (NOx) based on different modal operations from an in use vehicle fleet. CMEM is based on the power requirement and related fuel consumption, tailpipe emissions of CO2, CO, HC, and NOx (Barth et al., 1999).The GREET model (Greenhouse gases, Regulated Emissions and Energy in Transportation) is a publicly available spreadsheet model developed at the Argonne National Laboratory (ANL) that can be downloaded and run from a user's computer. GREET models emissions of the three traditional greenhouse gases (CO2, CH4 and N2O) and the criteria pollutants. Global warming potential values are used to aggregate the three GHG species emissions into a single carbon dioxide equivalent result (http://www.lifecycleassociates.com/lca-tools/greet-model/)

The model PHEM (Passenger car and Heavy duty Emission model) is capable of calculating fuel consumption and emissions for any vehicles and driving cycles with a high accuracy using engine emission maps and transient correction functions. The model interpolates the fuel consumption and the emissions from steady state engine emission maps for every second of given driving cycles. The results of the model are the engine power, the engine speed, the fuel consumption, and emissions of CO, CO2, HC, NOx and particles every second, as well as average values for the entire driving cycle. VRPTW (vehicle routing problem delivery time windows) software was originally developed with the premise of creating vehicle routes which minimise the distance travelled. It uses a range of heuristic methods to create the routes, starting with a construction heuristic based on a variation of the Clarke and Wright Savings algorithm. CO2 can be calculated from this software, and also any of the other VRP variants, by applying an average emission value per kilometre or mile, but these have been shown to be inaccurate (Van Woensel et al, 2001). COPERT methodology consists of vehicle-specific emission factors which are combined with activity data to calculate total emissions. The main activity data comprise number of vehicles distinguished into different emission categories/technologies, the travelling speed under urban, rural and highway conditions and the mileage driven over the same driving conditions.( Charis Kouridis et al.,2009) .COPERT 4 estimates emissions of all major air pollutants (CO, NOx, VOC, PM, NH3, SO2, heavy metals) produced by different vehicle categories (passenger cars, light commercial vehicles, heavy duty trucks, busses, motorcycles, and mopeds) as well as greenhouse gas emissions (CO2, N2O, and CH4). As this model estimates only the vehicle fleet emissions not the idling emissions this is not of our concern. Dynamometer Testing (Federal Test Procedure -FTP) is used to test vehicles for compliance with emission standards. The current test procedure used in the U.S. is referred to as FTP75. The FTP is conducted on a dynamometer for different driving cycles. The FTP is used to measure concentrations of different pollutants, like HC, CO, NOx and CO2. CO2 production is related to the amount of fuel combusted and the fuel's carbon content. A lesser consideration is the

fraction of the carbon oxidized, which is assumed to be 100 percent for emissions from transportation. After doing literature review on several emission estimated models and methods IPCC methodology was found best among them as it gives emission loss due to idling of vehicles.

For the petrol and diesel vehicles Intergovernmental Panel on Climate Change (IPCC) guidelines for calculating Carbon Footprint due to idling of vehicles emissions has been used. This requires an oxidation factor be applied to the carbon content to account for a small portion of the fuel that is not oxidized into CO2. For all oil and oil products, the oxidation factor used is 0.99 (99 % of the carbon in the fuel is eventually oxidized, while 1 % remains unoxidized. Finally, to calculate the CO2 emissions from a gallon of fuel, the carbon emissions are multiplied by the ratio of the molecular weight of CO2 (m.w. 44) to the molecular weight of carbon (m.w.12): 44/12.

CO2 emissions from a gallon of gasoline = 2,421 grams x 0.99 x (44/12) = 8,788 grams = 8.8 kg/gallon = 19.4 pounds/gallon or litre equivalent

CO2 emissions from a gallon of diesel = 2,778 grams x 0.99 x (44/12) = 10,084 grams = 10.1 kg/gallon = 22.2 pounds/gallon or litre equivalent.

Natural gas can be divided into two categories: low and high calorific gas (L and H gas). CO2 emissions differ between both categories, and strongly depend on the composition and origin of the gas. For low calorific CNG gas 1 kg of L-gas consists for 61.4% of carbon, or 614 grams of carbon per kg of L-gas. In order to combust this carbon to CO2, 1638 grams of oxygen is needed. The sum is then 614 + 1638 = 2252 grams of CO2/kg of L-gas. In Delhi CNG used in vehicles is of high calorific value. Hence in our study we will use the following formula. For high calorific CNG gas 1 kg of H-gas consists for 72.7% of carbon, or 727 grams of carbon per kg of H-gas. In order to combust this carbon to CO2, 1939 grams of oxygen is needed. The sum is then 727 + 1939 =2666 grams of CO2/kg of H-gas. (Source: http://www.ecoscore.be/en/how-calculate-co2-emission-level-fuel-consumption)

3.1 Review of Standards for Carbon Footprint Estimation

These standards provide methodologies for transport sector. The most important draft for calculating carbon footprint from transport sector is European standard EN 16258. Methodology for calculation and declaration on energy consumptions and GHG emissions in transport services (good and passengers transport) (CEN 2011). The standard will provide voluntary technical specifications for methodology and requirements for calculating and reporting energy consumption and greenhouse gas emissions in transport services. A related draft for an international standard is ISO 14067 Carbon footprint of products (ISO 2011), that will, from a wider perspective, detail principles, requirements and guidance for the quantification and communication of the carbon footprint of products (including both goods and services), based on GHG emissions and removals over the life cycle of a product. Other relevant ISO standards belong mainly to the ISO 14000 series (environmental management), especially 1402x (environmental labelling), 1404x (LCA, life cycle assessment) and 1406x (climate change) (ISO, 2009). Other established standard-like items include, for example, PAS 2050 (BSI, 2008) and the GHG Protocol (WRI and WBCSD, 2011) specifications. In addition, the IPCC Guidelines for national greenhouse gas inventories (IPCC, 1996, 2006) provides guidance targeted for the compilation of national emission inventories, where transport is visible as one part.

Table 1 Overview of standards carbon footprint methodologies

Name Standards

EN 16258 Draft for a European standard: Methodology for calculation and declaration on energy consumptions and GHG

emissions in transport services (good and passengers transport). ISO 14067 Draft for a Carbon footprint of products (CFP) standard, to be published around year 2012

ISO 14000 series Several standards within the ISO 14000 series (environmental management), e.g. 1402x (environmental labelling), 1404x (LCA, life cycle assessment) and 1406x (climate change).

PAS 2050 and PAS 2060 GHG Protocol

1996 and 2006 IPCC Guidelines

Independent carbon footprint standard, methodology and guidance. Specification for the demonstration of carbon neutrality

Accounting framework (guidelines, tools, etc.) for established greenhouse gas standards and programs across different

sectors, including transport and logistics.

The IPCC Guidelines for National Greenhouse Gas

Inventories (1996 and 2006 Guidelines)._

(Source: CEN 2011, ISO 2011, ISO 2009, WRI and WBCSD 2011)

4. Study Framework

The framework is designed to be carried out in four phases as shown in Fig 2. The objective of the study is to estimate the carbon footprint of fuel loss at selected intersections in Delhi. With a view to achieve the above stated objectives, 3 intersections of varying traffic volumes were selected in Delhi. The intersections selected for the study according to total number of vehicles are low volume intersection i.e. Cannaught Place (Kasturba Gandhi Marg + Feroz Shah Road), medium volume intersection i.e Khanpur intersection and heavy volume intersection i.e. Paschim Vihar intersection.

A detailed traffic volume count proforma was prepared with a detailed classification of vehicles. 15 motorized and 4 non motorized vehicles were included in the study for the classified traffic volume count along with turning movements. The fuel consumption experiments were also conducted on all the classified motorized modes of transport.

Fig 2 Research Framework

To estimate the delays occurring at intersections the data required are the hourly traffic volume at intersection,

the average delays experienced by the vehicles and idling fuel consumption. To know the traffic volume at the

intersections a 24 hour classified traffic volume and turning movement survey was conducted at high and

medium volume intersection and 16 hour traffic survey at low volume intersections. To assess the average delays

to the vehicles, stopped delay surveys and speed delay surveys were conducted at the intersections in tandem

with traffic volume survey. The above two surveys were carried out in field while the fuel consumption

experiment was done using fuel meter on various types of vehicles in the Institute's premises.

The stop delays surveys were conducted at 3 intersections. The intersections were divided as low, medium and

high with the following criteria.

Low volume intersection <75,000 vehicles

Medium Volume Intersection 75,000-1, 08,000

High Volume intersection >1, 00,000

The methodology adopted in conducting stopped delay study is based on total number of vehicles enumerated at three locations i.e. entering, exiting left and exiting straight and right of each of the approach of an intersection. The average delay per vehicle (in seconds) is determined for each of intersection arm separately. Vehicular delays during different hours of the day were calculated by multiplying the average hourly classified traffic flow with the corresponding average delay

In the present study fuel consumption tests at idling were performed by the use of flow detectors (FP Series). The flow detectors CFP Series allow measurement of flow (i.e. fuel consumption) along with optional pressure and temperature measurement in combination with suitable flow meters (D F Series). The combination can be used to determine the fuel consumption of different categories of vehicles on a variety of liquids including gasoline, light

oil, Kerosene and general petroleum oils. Depending upon the engine technology (e.g. two stroke or four stroke engines in two wheelers or carburettor or multipoint fuel injection in four wheelers) or diesel fuel injection different combination of flow detector and flow meters are employed. In the present fuel consumption tests at idling flow measurement system comprising FP 213S detectors DF 210A flow meters supplied by M/s. Ono Sokki, Japan has been employed for two wheelers including two stroke and four stroke engine. Whereas flow measurement system comprising FP 214OH flow detector and DF 210 a flow meter has been employed for fuel consumption studies of four wheelers. Since this combination/system of equipments can't measure fuel consumption by vehicles using gaseous fuels like CNG and LPG (mostly CNG) separate studies were carried out for the vehicles. In these experiments, CNG vehicle tanks were filled completely and the engines were run at idling conditions. CNG were refilled in vehicles to test fuels. The capacity exercise was for one hour and the repeated several times to determine the average fuel consumption of these CNG Vehicles at idling. The amount of CNG filled will directly give the fuel consumption.

The idling fuel consumption in ml. /hour of different type of vehicle is given in Table 2.

Table 2 Idling Fuel Consumption (in ml. /hour and gm. /hour)

S.no Vehicle Type Fuel Consumption Remark

1 Maruti Gypsy 1045 Petrol

2 Maruti Van 692 Petrol

3 LML Freedom Motor cycle 129 4-stroke

4 Pulsar Motor cycle 166 4-stroke

5 Bajaj Scooter 216 2-stroke

6 Ambassador Car 957 Diesel

7 Jeep 1052 Diesel

8 Maruti Van 563 MPF 1

9 Fiat Car 657 Petrol

10 Tata Sumo 717 Turbo change

11 Indica 547 Diesel

12 Esteem 740 MPF 1

13 LCV 690 Diesel

14 HCV 920 Diesel

15 RTV 800 CNG

16 Bus 3610 CNG

17 Auto rickshaw 700 CNG

18 Taxi 1010 CNG

The fuel loss for each vehicle in each arm has been calculated by multiplying delay for each vehicle with the idling fuel consumption of corresponding vehicle. The economic loss of fuel for each vehicle in each arm has been calculated by multiplying fuel loss for each vehicle with the prevailing cost of corresponding vehicle.

The time loss has been estimated by multiplying delay in hours and occupancy of the vehicle with per day income. The annual per capita income in Delhi was taken as Rs. 201083 and per day income is Rs. 550.9. The idling fuel consumption cost of fuel and occupancy of each vehicle is given in table 3.

Table 3 Idling Fuel Consumption, prevailing cost & occupancy

Vehicle Buses Mini Autos Motor Scooter HCV LCV _Buses_Cycle_

Fuel Consumption (ml/hr. & gm/hr.) 3610 800 700 147.5 216 920 690

Prevailing cost of fuel (Rs) 39.9 39.9 39.9 63.99 63.99 50.25 50.25

Occupancy 35 10 2 1 1 1 1

Vehicle MAV Taxi Old Brand New Brand

Petrol Diesel Jeep Diesel B seg C seg

Fuel Consumption (ml/hr. & gm/hr.) 920 1010 657 1049 717 547 563 740

Prevailing cost of fuel (Rs) 50.25 39.9 63.99 50.25 63.99 50.25 63.99 63.99

Occupancy 1 3 2 2 2 2 2 2

* cost of the fuel in the year 2013

For estimating the carbon footprint we have used the IPCC methodology explained in section 3. 5. RESULTS AND DISCUSSIONS

5.1 Fuel loss (in rupees) at signalised intersections due to idling of vehicles in Delhi

Total fuel loss per day in rupees at CP intersection , Khanpur Intersection and Paschim Vihar Intersection is Rs 32286.91,50312.56 and 65960.94 respectively.There are 413 , 118 and 69 high , medium and low volume signalised intersections in Delhi. Hence fuel loss per day in rupees from heavy , medium and low volume intersections is Rs 27241868.22, 5936882.08 and 2227796.79 respectively. This is shown in fig 3. There are 600 Intersections in Delhi so fuel loss (in rupees) per day due to idling of vehicles in Delhi (2013) is Rs 35406547.09.

Fuel loss in Rs/day

22% rv,i">v ■ Heavy Volume

^^^ Intersections

LI ■ Medium Volume

34% Intersections

i Low Volume Intersections

Fig. 3. Fuel loss per day in Rs at signalised intersections in Delhi

It was estimated that total fuel loss (in Rs) due to idling of vehicles from 600 signalised intersections per day in Delhi in the year 2004 was Rs 20451414.15.Thus there is 57.76 % increase in Fuel loss in terms of Rs from year 2004 to 2013.

5.2 Time Loss at Signalised Intersections due to idling of vehicles in Delhi

Total time loss per day in rupees at CP intersection , Khanpur intersection and Paschim Vihar intersection is Rs 137609.78, 259912.9 and 287112.5 respectively.There are 413 , 118 and 69 high , medium and low volume

signalised intersections in Delhi. Hence time loss per day in rupees from heavy , medium and low volume intersections is Rs 118577462.5, 30669722.2 and 9495074.82 respectively which is shown in fig 3.There are 600 Intersections in Delhi so time loss per day in Rs due to idling of vehicles in Delhi (2013) is Rs 158742259.5.

Fig. 4. Total time loss per day in Rs at signalised intersections in Delhi.

5.3 Carbon footprint due to idling at intersections

Total CO2 Emission per day from Paschim Vihar, Khanpur and CP Intersection is 2973.79, 2445.54 and 1531.49 kg respectively from cars, buses, two wheelers, three wheeler, commercial vehicles and trucks. There are 413, 118 and 69 heavy, medium and low volume intersections respectively. Thus 1228175.27, 288573.72 and 105672.81 kg of CO2 is emitted from cars, buses, two wheelers, three wheeler, commercial vehicles and trucks at heavy, medium and low volume intersections in a day respectively. Hence total CO2 emission from 600 signalized intersections per day in Delhi (2004) is 1622421.8 kg per day (table 4). According to UNEP total CO2 emission in Delhi for year 2004 is 6146651 tonnes due to transport sector. It was also find out that out of total CO2 emission caused by transport sector per day in 2004, 9% is contributed by idling of vehicles at signalised intersections in Delhi (2004).( Source*http://www.unep.org/transport/lowcarbon/Pdfs/LowCarbonMobilityPlans.pdf)

Table 4: Total CO2 emission at intersections in Delhi

Category

Total CO2 emission due to idling of vehicles in Delhi(kg/day)

Heavy Volume Intersections Medium Volume Intersections Low Volume Intersections Total

1228175.27 288573.72 105672.81 1622421.8

6. CONCLUSION ANSD RECOMMENDATIONS

Delhi faces the same transportation challenges as other megacities of the developing world: how to balance limited resources with strong desire for personal transport. Already, all but the poorest households in Delhi own a motor vehicle, usually a two-wheeler. The transport sector has a potential impact on GHG emission and hence, Climate Change. This sector contributes about 14% to the global GHG emissions. This study focused on estimating the carbon footprint due to idling of vehicles at signalized intersections. For estimating the carbon

footprint due to idling of vehicles at intersections three intersections were selected i.e. CP, Khanpur and Paschim Vihar intersection and categorized into low, medium and heavy volume intersection depending on the traffic volume count. Delay and fuel loss in terms of liters or kg was estimated at these intersections. It was estimated that total CO2 emission from 600 signalized intersections per day in Delhi in 2004 is 1622421.8 kg. It was also estimated that there was 57% increase in fuel loss in terms of rupees from year 2004 to 2013 .It was also find out that out of total CO2 emission caused by transport sector in 2004, 9% is contributed by idling of vehicles at signalised intersections in Delhi. Thus, curbing these emissions has become an area of concern for transport planner, engineers and environmentalists.

Further measures could be adopted in the future for reducing the carbon footprint due to idling of vehicles at signalized intersection in Delhi:-

• Switching off behaviour: This must be adopted by all the drivers in order to reduce the carbon footprint due to idling of vehicles at signalized intersections.

• Guidelines to Reduce Bus Exhaust Emissions

• When bus drivers arrive at loading or unloading areas to drop off or pick up passengers, they should turn off their buses as soon as possible to eliminate idling time and reduce harmful emissions. The bus should not be restarted until it is ready to depart and there is a clear path to exit the pick-up area.

• Vehicles should not be left running while unattended. The operator of the vehicle/equipment should turn off the unit and remove the keys from the ignition.

• Signs should be prominently posted on university grounds to remind all (car, bus, truck) drivers of the university idling policy.

• Encouraging the Public Transport: Following measures must be adopted for encouraging the public transport

• Separate bus lanes/bus ways on major arterials

• Provision of bus priority signals, encouragement of battery operated buses

• It should offer accessibility and comfort

• Enhancement of private participation to bring capacity augmentation and price discrimination etc. are to be taken to strengthen the road based public transport and to induce the individual vehicle owners to use the public transport.

• Encouraging Non-Motorized Modes

Increasing the modal share of zero emission transport modes i.e. cycle and cycle rickshaws. These modes are an essential part of the sustainable and suitable transport modal mix for Indian cities. NMT modes being labour intensive and non-fuel dependent are best suited for Indian conditions and the infrastructure requirements for their operations are minimal

• Policy Implementation

Government should enforce the policy that no vehicles shall remain idle at intersections for more than three (3) minutes. This policy shall be posted in the Safety and Security Departments "Traffic Guide".

• Imparting Traffic education

Traffic education is a very important tool in achieving the traffic discipline. Traffic education needs to be imparted at school level so that the habit of following rules and discipline is inculcated at a very tender age.

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