Abstract
Traffic as the main source of urban air pollution created severe problems for human health and sustainability. To propose a bottom-up method in emissions reduction, accurate emission inventories of vehicles in a medium-sized city are developed. Traffic emission factors were obtained using traffic flow data, traffic control cameras, and International Vehicle Emission (IVE) model to calculate CO, VOCs, NOx, SOx, and PM of passenger cars, taxis, and urban buses emission inventory. Annual overall emissions of CO, VOCs, NOx, SOx, and PM pollutants, respectively, are 346, 20.9, 25, 44.4, and 0.5 kt/year. VOC and CO emissions in the start-up phase are in the scale of the running phase, while NOx, SOx, and PM allocate much less than the running phase. The highest emission value of SOx and PM occurs in arterials while CO, VOC, and NOx in highways. Eight renovation scenarios have been designed to evaluate their environmental and economic efficiency. Two scenarios entitled “renovation of carbureted, Euro 1 and Euro 2 LDV” and “renovation of high mileage Euro 1 and Euro 2 standard urban buses” showed the highest decrease in pollution emission and pollution social costs. For these two important scenarios, implementation costs were calculated at 477 and 46 M$, while social costs decrease are calculated to be 172.6 and 77.5 M$, respectively. Renovation of vehicles could benefit both the government and society by reducing fuel consumption and pollutant emission. The emission mitigation scenarios considering mobile sources could be a guide for adopting policies in developing countries. Governmental and social cost-share and governmental and social repayment because of fuel-saving costs have also been calculated.
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Notes
Pickups were examined in this group due to the similarity of their engines to passenger cars.
Based on average gasoline and diesel Persian Gulf FOB prices on December 2019–January 2020.
Abbreviations
- ARC’s:
-
Auckland Regional Council’s
- VEPM:
-
Vehicle Emissions Prediction Model
- ARTEMIS:
-
Assessment and Reliability of Transport Emission Models and Inventory Systems
- BAU:
-
Business As Usual
- CFD:
-
Computational Fluid Dynamics
- CMEM:
-
Comprehensive Modal Emission Model
- CNG:
-
Compressed Natural Gas
- COPERT:
-
Computer Programme to calculate Emission from Road Transport
- DMRB:
-
Design Manual for Roads and Bridges
- DPF:
-
Diesel Particulate Filter
- EMFAC:
-
Emission Factor Model
- ECV:
-
Elimination of Carburetor equipped Vehicle
- FQE:
-
Fuel Quality Enhancement
- HBEFA:
-
Handbook Emission Factors for Road Transport
- HES:
-
Higher Emission Standard
- IVE:
-
International Vehicle Emission
- kt:
-
Kilo metric ton
- MIDC:
-
Modified Indian Drive Cycle
- MOBILE:
-
Mobile Source Emissions Factor
- MOT’s:
-
Ministry of Transport’s
- VFEM :
-
Vehicle Fleet Emissions Model
- MOVES:
-
Multi-scale mOtor Vehicle and equipment Emission System
- MPFI:
-
Multi Point Fuel Injection
- NEM:
-
New Energy Motorcycles
- OETR:
-
Odd–Even Traffic Rationing
- PARMICS:
-
Parallel Microscopic
- PCs:
-
Passenger Cars
- PEMS:
-
Portable Emissions Measurement System
- PHEM:
-
Passenger car and Heavy-duty Emission Model
- TRANSIMS:
-
Transportation Analysis and Simulation System
- TREMOD:
-
Transport Emission Model
- TSA:
-
Total Scenarios Aggregation
- VAPI:
-
Vehicular Air Pollution Inventory
- VCR:
-
Vehicle Catalyst Replacement
- VT-micro:
-
Virginia Tech Microscopic energy and emission model
- WHO:
-
World Health Organization
- WLTC:
-
Worldwide harmonized Light vehicles Test Cycles
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This worked has been supported by the Center for International Scientific Studies and Collaboration (CISSC).
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Leila Khazini: Conceptualization, Data Curation, Supervision, Validation.
Mina Jamshidi Kalajahi: Investigation, Writing-Original draft preparation, Methodology.
Nadège Blond: Validation.
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Highlights
• Transport management is highly dependent on traffic related pollution emission.
• Improvement in driving cycle significantly reduces vehicle emissions.
• We calculated local emission factors for transport policy development.
• A medium-sized city traffic produces 346, 20.9, 25, 44.4, and 0.5 KT/year CO, VOCs, NOx, SOx, and PM.
• Fuel saving due to renovation of fleets has considerable repayment for government and society.
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Khazini, L., Kalajahi, M.J. & Blond, N. An analysis of emission reduction strategy for light and heavy-duty vehicles pollutions in high spatial–temporal resolution and emission. Environ Sci Pollut Res 29, 23419–23435 (2022). https://doi.org/10.1007/s11356-021-17497-0
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DOI: https://doi.org/10.1007/s11356-021-17497-0