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International Journal of u- and e- Service, Science and Technology
Vol.7, No.1 (2014), pp.19-36
http://dx.doi.org/10.14257/ijunesst.2014.7.1.03
Developing Matlab Scripts using Meteorological Data for
Environmental Monitoring and Assessment
S. A.Quadri, Othman Sidek, Hadi Jafar, Nur Amira binti Amran,
Ummi Nurulhaiza bt Zabah and Azizul bin Abdullah
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Abstract
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Collaborative Microelectronic Design Excellence Centre (CEDEC)
Universiti Sains Malaysia, Engineering Campus, Nibong Tebal
Malaysia, 14300
[email protected]
The world is facing the challenge of global warming and climate change issues. The
objective of the study is to examine the meteorological data that constitute the environment
and their balance has prevailing effect on the global warming. The meteorological data in
our study refers to temperature, humidity, carbon dioxide and oxygen. We deploy our own
customized hardware setup to obtain the data. Provided with this basic data, many significant
parameters such enthalpy, dew point, humidity ratio, actual vapor pressure, saturated vapor
pressure, partial vapor pressure and specific volume could be derived. We have presented
simple functions in Matlab programming to derive these parameters. Our concluding Matlab
program is as good as calculator, and the output is visualized by plotting function.
Keywords: Climate change, Global warming, Meteorological data, Matlab, Environment
monitoring device, Humidity, Temperature
1. Introduction
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The issues of global warming and climate change have become a subject of intense interest
all over the world since the last decade. Warming of the climate system is now evidenced
from observations of increases in global average air and ocean temperatures, widespread
melting of snow and ice, and rising global average sea level.
Climate change will affect numerous sectors and productive environments, including
agriculture, forestry, energy, and coastal zones. Moreover, failing to safeguard the
environment eventually threatens economic and social achievements.
The anthropogenic driver of climate change is the increasing concentration of greenhouse
gases (GHG) in the atmosphere. Carbon dioxide (CO2) is the most important anthropogenic
GHG, and the global increases in CO2 concentration are due primarily to fossil fuel use and
land use change. The increase in GHG concentrations in the atmosphere affects processes
and feedbacks in the climate system. Qualitatively, an increase of atmospheric GHG
concentrations will lead to an average increase of the temperature of the surface-troposphere
system [1-2].
The temperature trend in Malaysia, due to global warming is addressed by many
researchers in the literature [3-5]. All studies in this regard certainly affirm mean annual
increase of temperature. Thus showing perfect agreement with the report of the IPCC [6].
Our project has a lengthy procedure that encompasses development of hardware platform
by assembling various sensors on microcontroller board; Firmware programming to facilitate
sensors to obtain data and transmit data wirelessly; Matlab programming utilizing the
ISSN: 2005-4246 IJUNESST
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International Journal of u- and e- Service, Science and Technology
Vol.7, No.1 (2014)
equations and formula that relates these basic parameters (temperature and humidity), thus
presenting a calculator that output various derived parameters. Scientific analysis of each
derived parameters and its impact on the environment.
At the first stage of our study, we assemble all the sensors and deploy it to obtain the basic
parameters. Section 2 concisely outlines the hardware and software description. In the next
stage, we develop functions and programs to derive various temperature-humidity related
parameters. Section 3 briefly discuss the potential of Matlab programming and emphasize
how each relations and formulas are translated in Matlab. Finally, we visualize the output
obtained from the data by plotting the graphs.
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2. Experimental Setup
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In this section, we discuss the hardware and software issues involved in obtaining
meteorological data.
2.1. Environment Monitoring Device (EMD)
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Our project comprises of development of Environment Monitoring Device (EMD),
which is an assembly of commercial available sensors fixed on Arduino prototyping
hardware platform. The user-friendly nature of the platform provides us liberty such
that any number and any type of sensors could be accommodated on the board. Three
different types of sensors, namely Carbon dioxide sensor, temperature & humidity
sensor and oxygen sensor are fixed on the board. In order to send the output data
wirelessly the board is equipped inbuilt wifi facility. The hardware setup is shown in
Figure 1.
Figure 1. Hardware Setup of Environment Monitoring Device (EMD)
The microcontroller on the board is programmed using the Arduino programming
language. Arduino [7] is open-source software. Its flexible and easy-to-use platform provides
a means to coordinate hardware components on the board. It is a potential tool for software
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programmers and hardware designers that facilitate in creating interactive objects or
environments for numerous applications. Functional block diagram of EMD is shown in
Figure 2.
Figure 2. Functional Block Diagram of Environment Monitoring Device
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Arduino projects can be stand-alone or they can communicate with software running on a
computer. In our case, all the sensor output data is wirelessly transmitted to a laptop where we
have preinstalled Arduino Software. A graphical user interface displays online current
readings, as shown in the Figure 3. The measurements could be easily recorded in comma
separated vales (CSV) using data logger facility.
Figure 3. Graphical User Interface Display of Sensor Output
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3. Software Development Approach
3.1. Matlab Programming
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The problem of global warming and climate change is massive and complex. In our
opinion, collaborative effort is required from various disciples like environment experts,
statisticians, hardware engineers and software programmers.
Software programmers could contribute by developing programs for data abstraction, data
mining, data processing and data visualization etc., thus providing a better means for indepth
scientific data analysis.
In this section, we make an effort to show how Matlab could be used as a prospective tool
in metrological data analysis.
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Matlab© is a high-level language and interactive environment for numerical computation,
visualization, and programming. Matlab (matrix laboratory) is a numerical computing
environment and fourth-generation programming language developed by MathWorks [8].
Using Matlab, one can analyze data, develop algorithms, and create models and applications.
Matlab has wide range of applications, including signal processing and communications,
image and video processing, control systems, test and measurement, computational finance,
and computational biology.
3.2. Key Features of Matlab
a) High-level language for numerical computation, visualization, and application
development.
b) Interactive environment for iterative exploration, design, and problem solving.
c) Mathematical functions for linear algebra, statistics, Fourier analysis, filtering,
optimization, numerical integration, and solving ordinary differential equations.
d) Built-in graphics for visualizing data and tools for creating custom plots.
e) Development tools for improving code quality and maintainability and maximizing
performance.
f) Tools for building applications with custom graphical interfaces.
g) Functions for integrating Matlab based algorithms with external applications and
languages such as C, Java, .NET, and Microsoft ®Excel.
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h) Programming is elegant, user friendly and appealing.
3.3. Matlab Coding - Examples
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The language, tools, and built-in math functions enable us to explore multiple approaches
and reach a solution faster than with spreadsheets or traditional programming languages, such
as C/C++ or Java © .
In this discussion, various interrelated formulas were utilized to derive these temperaturehumidity related factors, for each of these factors, respective functions are written, which are
called by the main program during execution.
3.3.1. Temperature Unit Conversion: We will start with a simple and most frequently used
program. The commonly used temperature units are Fahrenheit and Celsius. Many a times we
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require conversion. When the unit of interest is degree Celsius, we require converting
Fahrenheit to Celsius and vice versa. From the basic resources [9], we have the basic formula:
[°C] = ([°F] − 32) / (1.8)
[°F] = [°C] ×1.8 + 32
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A simple code illustrating the same is shown in Figure 4.
Figure 4. Program to Convert Temperature Units
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3.3.2. Saturated Vapor Pressure: The saturation vapor pressure is the pressure of a vapor
when it is in equilibrium with the liquid phase. It is solely dependent on the temperature. As
temperature rises, the saturation vapor pressure rises as well. Vapor pressure is a
measurement of the amount of moisture in the air. It is technically the pressure of water vapor
above a surface of water. When air reaches the saturation vapor pressure, the water vapor in it
will be condensed [10].
The calculation is complex and requires ample knowledge of Algebra. The known
parameters are temperature and humidity, obtained from the EMD kit.
We proceed our calculation by using the relation among, actual vapor pressure (e),
saturated vapor pressure (pvs) and partial vapor pressure (pvp), expressed in Equation 1 and 2
[11].
Equation (1)
The value of e can be calculated by using the exponential rules in Algebra.
We write a function named (function_pvs) with series of coefficients (a1 to a13 shown in
code, see Figure 5) in order to find the value of PVS. Once, we get the value of PVS we can
find PVP by using the relation:
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Equation (2) [11]
Figure 5. Program to Calculate Saturated Vapor Pressure
3.3.3. Dew Point Temperature: The dew point is the temperature below which the water
vapor in air at constant barometric pressure condenses into liquid water at the same rate at
which it evaporates. The condensed water is called dew, when it forms on a solid surface. It is
a water-to-air saturation temperature. The dew point is associated with relative humidity. A
high relative humidity indicates that the dew point is closer to the current air temperature.
Relative humidity is at all temperatures and pressures defined as the ratio of the water vapor
pressure to the saturation water vapor pressure (over water) at the gas temperature.
Dew point temperature is calculated using the Equation (3) [12], equivalent function in
Matlab is shown in Figure 6.
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Equation (3)
Figure 6. Program to Calculate Dew Point
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3.3.4. Humidity Ratio: Humidity ratio (HR) is expressed as the ratio between the actual mass
of water vapor present in moist air to the mass of the dry air. It can also be expressed with the
partial pressure of water vapor. The relationship of HR with atmospheric pressure and partial
vapor pressure is given below [12]:
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HR = 0.622 (Partial vapor pressure) / (Pressure of moist air - Partial vapor pressure)
Thus, we encode the relationship in Matlab as shown in Figure 7.
Figure 7. Single Line Instruction to Calculate Humidity Ratio
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3.3.5. Enthalpy: Enthalpy is a measure of the total energy of a thermodynamic system. It
includes the system's internal energy, as well as its volume and pressure. It is the preferred
expression of system energy changes in many chemical, biological, and physical
measurements, because it simplifies certain descriptions of energy transfer. Enthalpy change
accounts for energy transferred to the environment at constant pressure through expansion or
heating [13].
Enthalpy is the amount of heat content used or released in a system at constant pressure.
Enthalpy is usually expressed as the change in enthalpy. The change in enthalpy is related to a
change in internal energy (U) and a change in the volume (V), which is multiplied by the
constant pressure of the system. Enthalpy (H) is the sum of the internal energy (U) and the
product of pressure and volume (PV) given by the equation:
H = U + PV
Equation (4) [14]
When a process occurs at constant pressure, the heat evolved (either released or absorbed)
is equal to the change in enthalpy.
Enthalpy is a state function which depends entirely on the state functions T, P and U. It is
usually expressed as the change in enthalpy (ΔH) for a process between initial and final
states:
ΔH = ΔU + ΔPV
Equation (5) [14]
If temperature and pressure remain constant through the process and the work is limited to
pressure-volume work, then the enthalpy change is given by the equation:
ΔH = ΔU + PΔV
Equation (6) [14]
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Enthalpy can also be expressed as a molar enthalpy, ΔHm, by dividing the enthalpy or
change in enthalpy by the number of moles. Enthalpy is a state function. This implies that
when a system changes from one state to another, the change in enthalpy is independent of
the path between two states of a system.
If there is no non-expansion work on the system and the pressure is still constant, then the
change in enthalpy will equal the heat consumed or released by the system (q).
ΔH=q
(Equation 7) [14]
This relationship can help to determine whether a reaction is endothermic or exothermic.
At constant pressure, an endothermic reaction is when heat is absorbed. This means that the
system consumes heat from the surroundings, so q is greater than zero. Therefore, according
to the second equation, the ΔH will also be greater than zero. On the other hand, an
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exothermic reaction at constant pressure is when heat is released. This implies that the system
gives off heat to the surroundings, so q is less than zero. Furthermore, ΔH will be less than
zero.
When the temperature increases, the amount of molecular interactions also increases.
When the number of interactions increase, then the internal energy of the system rises.
According to the first equation given, if the internal energy (U) increases then the ΔH
increases as temperature rises.
We can use the equation for heat capacity and Equation (7) to derive this relationship.
C=q/ΔT
Equation (8) [15]
Cp=ΔH/ΔT
Equation (9)
Enthalpy can be calculated from mixing ratio equation [15]:
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h = T • (1.01 + 0.00189X) + 2.5X (kJ/kg)
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At constant pressure, substitute Equation (7):
Equation (10)
Where T= Temperature (°C) and X= Mixing ratio (g/kg)
The mixing ratio is the mass of water vapor in a particular mass of dry air .The unit is g/kg.
The mixing ratio (mass of water vapor/mass of dry gas) is calculated using relation [15]:
X = B•Pw /(Ptot -P w )
(Equation 11)
Where Pw = vapor pressure and Ptot = Total ambient pressure
The value of B depends on the gas. The value 621.9907 g/kg is valid for air [16].
B = 621.9907 g/kg
Thus, the equations are first simplified and then encoded in Matlab as shown in Figure 8
Figure 8. Code Line to Calculate Enthalpy Change
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3.3.6. Specific Volume: Specific volume of a substance is the ratio of the substance's volume
to its mass. It is inversely proportional to density. If the density of a substance doubles, its
specific volume, as expressed in the same base units, is cut in half. If the density drops to 1/10
its former value, the specific volume, as expressed in the same base units, increases by a
factor of 10.
The density of gases changes with even slight variations in temperature, while densities of
liquid and solids, which are generally thought of as incompressible, with change to a very
little. Specific volume is the inverse of the density of a substance; therefore, careful
consideration must be taken account when dealing with situations that involve gases. Small
changes in temperature will have a noticeable effect on specific volumes.
Specific volume for an ideal gas is also equal to the gas constant (R) multiplied by the
temperature and then divided by the pressure.
Vh= RT/P
Equation (12) [17]
The specific gas constant (R) for dry air is 287.058 J/ (kg • K) in SI units [9].
Thus, the relation is encoded in Matlab function shown in Figure 9.
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Figure 9. Function to Calculate Specific Volume
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3.3.7. Main Program: The main program is shown below, it starts requesting the user to
input temperature and relative humidity values. The programs thus calling various functions
executes and stores all the final values in a file.
Figure 10. Main Program
4. Results
Graphs are means of visual representation depicting relationship between variables. They
are very useful for researchers; facilitate better analysis and understanding that would not
come from mere lists of values. In this section, we present graphs of various environmental
effecting parameters plotted against time.
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4.1. Plotting the Graphs
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The successful execution of the main program ends up in safely saving the respective
output values in a file; in our case, we have named it as ‘output-data’ file. Simple plot
functions are executed to get the graphs; the already saved file (output-data) should be loaded
as a prerequisite. Thus, a set all graphs depicting various temperature-humidity parameters are
plotted. Figure 11 shows few lines of code to obtain graph of enthalpy versus time, in the
same way we can plot graphs for vapor pressure at saturation (pvs), partial vapor
pressure(pvp), humidity ratio (hr), enthalpy (enthal), dew point (dp) and specific volume (vh).
All these parameters were plotted considering the readings for one complete day, thus 24
hours x 60 minutes makes 1440 values, shown along X-axis. Figures 12 to 16 show graphs for
basic parameters (temperature, relative humidity, carbon dioxide and oxygen) versus time,
Figures 16 - 20 illustrate graphs for derived parameters.
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Figure 11. Plotting Instructions to obtain Enthalpy versus Time Graph
Figure 12. Graph Shows Temperature Versus Time Plot
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Figure 13. Graph Shows Relative Humidity Versus Time Plot
Figure 14. Graph Shows Atmospheric Carbon dioxide Versus Time Plot
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Figure 15. Graph Shows Atmospheric Oxygen Versus Time Plot
Figure 16. Graph Shows Saturation Vapor Pressure Versus Time Plot
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Figure 17. Graph Shows Dew point Versus Time Plot
Figure 18. Graph Shows Humidity Ratio Versus Time Plot
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Figure 19. Graph Shows Enthalpy Versus Time Plot
Figure 20. Graph Shows Specific Volume Versus Time Plot
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4.2. Comparison with other Online Calculators
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In order to crosscheck the results, the output obtained from the Matlab scripts is compared
with two online available humidity calculators. These are available on websites
[http://www.vaisala.com] and [http://easycalculation.com]. The comparison confirms the
output values are almost same. Thus, translation of equations and formulas into Matlab scripts
did not sacrifice the accuracy and precision of the derived parameters. As an example to
illustrate, we have plotted the graph of dew point versus time taking into account for all three
set of output. Let us call the output from [www.vaisala.com] as online calculator 1, shown in
red color; output from [www.easycalculation.com] as online calculator 2, shown in black
color; Matlab program output is shown in blue color. Figure 21 shows all the three output
lines (values) almost overlapping with each other.
Figure 21. Graph plotted for Dew Points obtaining Three Different Set of
Readings
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5. Conclusion and Future Work
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The issue of global warming is one of the most critical problems of the era. Extensive
research is required to be focused on scientific facts and figures. Evidence has surfaced that
there is substantial increment in carbon dioxide and temperature levels; moreover, their
correlation cannot be ignored. In this paper, we presented Matlab as a potential tool to study
various temperature-humidity related factors. The individual contribution of each factor to
cumulative effluence could be explored. Scientific data analysis and interpretation would lead
to helpful conclusions about climate change. Visualization of data and appropriate decision
tools, complementing level-risk analysis, could establish overall safety policies and
acceptable levels.
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One of the critical concerns of the project is about real time performance of the sensors
after deployment. Issue of calibration accuracy, precision and hysteresis, has to be taken in to
account in order to avoid incorrect data and false alarms, this task has been kept as a future
work.
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Authors
S. A. Quadri graduated as Bachelor of Engineering in Electronics &
Communication from Karnataka University Dharwad. He completed his
M.Tech (Computer Science & Engineering) from VTU Belgaum. He
served as Assistant professor in various Engineering colleges. Before
joining as Research associate in CEDEC he served 3 years as HOD of
Computer Science & Engineering department in SIET College, affiliated
to VTU, approved by AICTE Delhi, India. His research domain includes
multisensor data fusion & neural networks.
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Professor Othman bin Sidek an esteemed Malaysian scientist holds a
PhD (Info. Sys. Eng.) from Bradford University, UK. He has served
Universiti Sains Malaysia since 1984 as a lecturer, researcher, &
administrator. Prior to joining USM, he was a trainee engineer with
Multinational Companies & continued to take very active role in both
academic & university-industry research collaborations. Professor is also
the Founder of the Collaborative Micro-electronic Design Excellence
Centre (CEDEC), an approved centre at USM by the Malaysian Ministry
of Finance in 2005 out of his own initiative.
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Hadi Jafar graduated from USM with Electronic Engineering Degree
in the year of 2010. Currently doing his Masters in Embedded System
title Design, Development and Test of Structure Sensor and are the one
who build the sensors system.
Nur Amira binti Amran graduated from USM with Electrical
Engineering Degree in the year of 2010. Currently doing Masters in
Power Electronic and Device title Energy Reservoir Management System
for WSN.
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Ummi Nurulhaiza bt Za’bah graduated from Universiti Sains
Malaysia with Degree in Electrical & Electronic Engineering in 2010.
Currently doing Masters in RF system & Electromagnetic Compatibility.
In this project, she is the one building the wireless communication &
networking system.
Azizul bin Abdullah graduated from USM with Aerospace
Engineering Degree & Masters in the year of 2008 & 2012 respectively.
Currently doing his research in ‘Development of wide secured wireless
sensor network (WSN) with unmanned aerial vehicle (UAV) deployment
for the monitoring of ecology & global warming studies towards
environment sustainability’ and are the one who analysis designs of
Agrotech 2020 UAV.
Copyright ⓒ 2014 SERSC
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International Journal of u- and e- Service, Science and Technology
Vol.7, No.1 (2014)
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Copyright ⓒ 2014 SERSC