Figure 2.1: Spatial Distribution of the Mean Annual (1) Relative Humidity and (2) Dew Point Temperature From 1961 to 2010.
The analysis found that the proportion of stations
suggesting a discernible trend in relative humidity is modest at the 95 percent
confidence level but substantially higher in the dew point temperature series.
Relative humidity in the western United States increased by 0.53, 0.86, and
1.18 percent each decade on an annual, winter, and pre-monsoon scale,
respectively. Significant negative patterns in the relative humidity series
could be noticed during the monsoon season. The time-series data for seasonal
and annual dew point temperatures at any station, on the other hand, show no
discernible downward trend. The magnitude of the relevant trends was once again
more significant in the country's western regions. Most of the slopes are well
above zero, indicating that the dew point temperatures in Bangladesh were
increasing year after year and season after season.
2.4.2 Correction Factors for Emission Degradation
Only gasoline and light-duty vehicles (LGVs) are subject
to emission degradation. It's also only used to change emission factors for
Euro 1-4 cars, with no degradation factors for Euro 5 and 6. Diesel vehicles
and LGVs do not require degradation corrections. The emission factor obtained
from the speed-emission coefficients is multiplied by the degradation
correction factor, according to COPERT methodology. With increasing mileage,
the degradation factors increase, but only up to 120,000km for Euro 1 and 2
vehicles and 160,000km for Euro 3 and 4 vehicles. At mileages greater than
this, the value of the adjustment factor provided remains constant. A linear
equation calculates a degradation adjustment factor for a given cumulative mileage
using COPERT 5 coefficients. In Euro 1 and 2 petrol cars, there is just one set
of coefficients for all engine sizes. In Euro 3 and 4 autos, there is a range
of coefficients for vehicles 1.4l and cars >1.4l. A set of coefficients is
utilized for each vehicle class to determine a deterioration factor for speeds
less than 19 kph and another location for speeds greater than 63 kph. An
interpolation approach is used for intermediate rates to derive a degradation
factor.
2.4.3 Age of the Vehicle
T. Zachariadis, L. Ntziachristos, and Z. Samaras (2001)
studied the influence of age on vehicle emissions, which showed relationships
between age, mileage, and speed. The study examined the long-term effects of
vehicle aging and technology replacement on air pollution. An existing model
that studies the internal dynamics of car fleets and calculates emissions
supported the inquiry. The sensitivity of the system to different ages and
technical aspects was explored. The consequences of deteriorating emissions,
installing inspection and maintenance programs, and using cleaner fuels were
investigated.
Figure 2.2: Outline
the Parameters Affecting Vehicle Emissions Connected to Age and Technological Level.
The interdependencies of age, technology, and vehicle emissions
are depicted in Figure 2.2. By accounting for all these factors, the model can
predict the potential influence of emission abatement solutions aiming at
technical and non-technical interventions in the vehicle stock's age and
technology structure. Because of its use in various countries and situations,
the clarity of its built-in mathematical correlations, and its phenomenological
approach, the technique presented here is advantageous. This study created a
graph to show the relationship between mileage and vehicle age.
Figure 2.3: Estimated specific mileage for six European
countries as a function of vehicle age. NL-Netherlands; UK-United Kingdom;
D-Germany. DK-Denmark; F-France; I-Italy; NL-Netherlands; UK-United Kingdom;
D-Germany. (1999, Hickman)
Data from road traffic in various countries shows that
when cars grow in size, they are driven less. Furthermore, experimental
emissions data from in-use autos demonstrate an apparent worsening of emissions
behavior as vehicles age, mainly owing to the depreciation of catalytic
converters and emission control systems. These factors must be considered in
modeling research to achieve appropriate emission estimations.
2.5 Review of Studies on Vehicle Exhaust Emissions:
According to various studies on pollutant emissions,
vehicle emissions are one of the most significant sources of fine particles
(PM2.5). It accounts for 15–50 percent of metropolitan areas' fine aerosol
mass. The bulk of primary particles in automobile exhaust emissions is organic
carbon OC and elemental carbon EC, with hazardous elements and inorganic ions
accounting for the balance.
El Haddad, Imad, et al. (2009) previously conducted a
study on automobile exhaust emissions in France. They described a primary
particle organic characterization (PM2.5 and PM10). According to the survey,
carbonaceous aerosols comprised 70% of the total mass, with elemental carbon
accounting for 60%. (EC). The water-soluble percentage of OC was determined, as
well as its functionalization. To construct an organic emission profile for
chemical mass balance modeling, alkanes, PAH, petroleum biomarkers, and
carboxylic acids were measured. The chemical profile is comparable to diesel
emissions, with a high EC relative to OC (EC/OC = 1.8) and low PAH contents. These
figures are consistent with France's high proportion of diesel vehicles (about
49 percent ). These findings suggest that organic component profiles from
vehicle exhaust emissions are unaffected by geography and could be utilized in
large-area aerosol source apportionment models. This study does not provide a
clear picture of vehicle-related greenhouse gas emissions, nor does it explain
the impact of climate change on a national basis.
In Bangladesh, a similar study was conducted on vehicle exhaust pollution. Iqbal et al. (2013) used a Gas Analyzer to perform a survey in Dhaka on several types of vehicles. In this study, the Flue Gas Analyzer was used to evaluate various kinds of automobiles and compute several toxic chemicals extremely detrimental to human health and the environment. The primary goal of this research is to look at different technologies and approaches for reducing vehicle emissions. Compressed natural gas (CNG) vehicles have reduced traffic congestion and pollution in Dhaka. C, NOx, and SOx levels in Dhaka's automobile emissions are very high.
