Figure 2.4: Flue Gas Analyzer Experimental Setup
Internal combustion engines burn fuel in the presence of air, producing CO2, H2O, and N2 as by-products.
- Exhaust
- Manifold
CO2, an essential greenhouse gas that contributes to global warming, is emitted from complete combustion. Combustion processes also produce pollutants such as CO2, NOx, SO2, PM, and HC as by-products.
The general equation for complete combustion is as follows:
Ca Hb + (a + b4) (O2 + 3.772N2) = aCO2 + b2 H2O + 3.773 (a + b4) N2
The study found that diesel engine CO levels average 50.66 ppm, which is near-standard air quality when tested for 20-25 minutes. As a result, gasoline engines produced 72.33 ppm on average, while CNG engines produced 46 ppm. In diesel engines, NO2 production averages 14.66 parts per million. The amount of NO2 in gasoline and CNG was relatively low. The diesel engine had an SO2 level of 1 ppm, whereas the others were inconsequential. For a gasoline engine, one ppm is negligible. CNG had a concentration of 75 parts per million. According to the experiment, Dhaka's car emissions are within Bangladesh's new ambient air quality requirements.
This study was limited to a single city and a small number of vehicles. No emission standards found in this study could be applied across the country. Another disadvantage of this study is the length of time spent analyzing the data. The combustion analysis takes only 20 to 25 minutes, insufficient time to estimate or create an emission inventory. On the other hand, this study provides a clear understanding of vehicle combustion and pollutant exhaustion.
2.6 Review of COPERT Emission Inventory-Based Studies:
COPERT is a mathematical model based on an extensive database that comprises information on the national vehicular fleet and numerous characteristics connected to this fleet, such as speed-dependent emission activities, fuel consumption, average speed, and miles for each vehicle. Saija, Salvatore, and Daniela Romano conducted a study in Italy in 2002. This research looked at anticipating local road transport emissions using a top-down approach. A bottom-up strategy proved helpful when the data and information needed for estimating techniques were available at the regional territorial level. Emissions were scaled down from national to regional levels using proxy variables without regional data. The importance of strengthening the top-down strategy was highlighted in this study, which included a corrective index to identify local road transport emissions better. A set of factors related to transportation activities is utilized to determine homogeneous zones in the Italian territory. The COPERT (Computer Program to Estimate Emissions from Road Traffic) method was used to estimate the air emissions of various contaminants for each location. The same methodology was used to calculate national road transport emissions. The results are compared to those produced from a geographical disaggregation of national data using simple surrogate variables determined by vehicle type and driving mode. This research was carried out by contrasting the COPERT approach with a novel methodology for improving urban emission inventories.
There has previously been researching based on several emission inventories in which the COPERT and MOVES methodologies were examined. T. Zachariadis and Z. Samaras (1999) researched estimating motor vehicle emissions. This study compiled information on past and current motor vehicle emission modeling in Europe. These researches resulted in developing a collection of computer-based models and approaches that address all motor vehicle emission challenges of interest to policymakers, institutions, and the automotive and oil industries. The COPERT model was described and compared to other methods for calculating road vehicle emissions. In the case of examples, a COPERT-based technique for microscopic traffic emission estimation was defined and briefly discussed. The goal of this study was to present a straightforward process for compiling an emission inventory.
Different methodologies for estimating traffic emissions with the high geographical and temporal resolution are shown in Figure 2.5.
The procedure is depicted in Figure 2.3. Each street or road is treated as a single line source in the bottom-up method, and hourly vehicle emissions are calculated. Top-down simulations annually duplicate the entire region. COPERT is the top-down strategy in this paradigm. The top-down and bottom-up estimations of emissions are separate. The starting point in each scenario is "hard data" (such as traffic counts, car registration figures, and measured emission factors). Undefined parameters are then assessed using available data and assumptions. The FOREMOVE concept and results from its implementation in the European Auto/Oil project were supplied. Finally, a list of the major areas of automotive emissions research in Europe is provided.
Previously, Burón, José M., et al. (2004) used COPERT III to undertake a study on assessing road transport emissions in Spain. This study reviewed the emissions of pollutants generated by automobile traffic in Spain from 1988 to 1999 and published the findings. The investigation has concentrated on two main stages: input data compilation and program execution (COPERT III). The essential models and algorithms have been created, and various assumptions based on statistical criteria and the most recent research in the field have been established. They provided the input data for COPERT III. They served as a result in and of themselves, giving solid assessments on various vehicles and other situational factors. Because the COPERT software version was too outdated at the time, several functionalities were unavailable. As a result, the earlier version may not display accurate results.
Then, using the COPERT emission model, Guo, Dong, and colleagues studied gasoline vehicle inventory. This study revealed a method for generating a list of gasoline automobiles with regional variations to provide gasoline vehicle emission inventory that reflected the reality in various places. The corresponding adjustment factors were established after a thorough analysis and assessment of several parameters affecting vehicle emissions. The entire emission factor approach was used to construct the gasoline vehicle emission inventory in Zibo. This method could be used to estimate gasoline-powered vehicle emissions in different cities more accurately and provide theoretical justification for gasoline car emission regulation schemes. This study studied and compared diverse inventory to determine the mistake percentage.
Real-world emissions from a broad sample of the most recent Euro 6 diesel passenger cars were provided in this study, with a focus on NOx and primary NO2. The results revealed a wide range of NOx emissions, from 1 to 22 times the type-approval limit. NOx emissions averaged 0.36 g/km (standard deviation: 0.36), 4.5 times the Euro 6 limit. An increase in acceleration occurrences in the route's urban section was blamed for the higher emissions. PEMS readings were 1.6 times higher for NOx and 2.5 times higher for NO2 compared to COPERT speed-dependent emissions factors.
Condurat et al. (2017) did another
study on the environmental impact of vehicle transport traffic. The ecological
impact of road transportation traffic, as measured by air pollutant emissions,
was highlighted in this article for specific road networks in Romania's
North-East Region. The current study focused on the exponential growth of
greenhouse gas emissions and fuel consumption about traffic pollution,
advocating particular methods to improve road network sustainability based on
the study's findings. A quantitative assessment of electricity consumption and
CO2 emissions caused by vehicle traffic is required for environmental impact
assessments. In this regard, the yearly daily average traffic for the year in
question was utilized to quantify air pollution caused by traffic recorded in
2010. Using traffic evolution parameters, the pollution status for 2015, 2020,
and 2030 has been forecasted. According to the assessment for this case study,
the existing vehicle fleet and average vehicle speed have the lowest
environmental impact, as evaluated by pollutant emissions. The second case
study's assessment focuses on the ecological effects of road traffic based on
the current state of the road network's pavement. Road hardship has resulted in
increased traffic congestion and pollution.
