Environmental Impact Assessment (EIA) of pH and Other Factors on

Organic Photovoltaic Performance Output

Abodunrin Temitope Jolaolu

, Emetere Moses Eterigho

and Ajayi Oluseyi Olanrewaju

Department of Physics, Covenant University, P.M.B. 1023, Ota, Nigeria

Department of Mechanical Engineering, Covenant University, P.M.B. 1023, Ota, Nigeria

corresponding author email address

Keywords: Dye-sensitized Solar Cell, Impact Assessment, Energy, pH.

Abstract: A methodical frame for evaluating the prospective ecological and health impacts of photovoltaics is necessary

to consider both their negative and positive underlying effects. These pros come with a probability to advance

carbon sequestration perspective. The cons are considered with a view to alleviate their negative consequences

or eliminating them altogether. In this work, we report the effect of pH and dye sol ambient temperature on

the environmental impact of three dye-sensitized solar cells, C.papaya, P.dulcis and C.longa to gauge their

environmental impact. In the wake of several generations of photovoltaic trends a precautionary check on

their effectiveness, stability, cost-competitiveness, storage time and ecological friendliness is a way of

isolating carbon for storage and transportation. Thus, although the objective of this project is to investigate

factors which are not tangible, discrete factors that impact photovoltaics will be analyzed using direct

qualitative techniques. Using valued environmental components with spatial boundaries, and software effort

estimation model to investigate the possibility for re-use, compactness and photo-corrosion among others.

The significance of this research is for subsequent moderation in planning, design and to redress newer models

of dye-sensitized solar cells technology for higher photovoltaic efficiency and lessen their photo-corrosive

influence on our ecological system.

1 INTRODUCTION

In the wake of so many hazardous emissions released

per second into the atmosphere from myriad

industrial and economical activities, it is imperative

to carry out a risk assessment on many of our research

efforts. This is in particular so because of the

dimensions of the changes involved; at the moment,

industry, transportation, and domestic uses routinely

discharge almost 10 Giga tons of carbondioxide

yearly to the atmosphere. It is equally notable that

there is no immediate hope for a radical change in the

spate of these emissions (Abdullahi et al., 2018).

Thus, a clarification of carbon sequestration and

carbon ‘sink’ needs to precede many of our lines of

research intervention. A carbon sink accumulates

more and more carbon into the atmosphere or ocean

whereas, a sequestrate serves as a carbon reservoir.

This artificial storage acts as a check for increasing

the atmospheric carbondioxide (Smit et al., 2014).

Real life scenario requires more cyclable carbon

reservoirs as fuel which readily get replenished as

they combust in oxygen to generate energy. In the

present circumstance, such a store should not act as a

trigger for global warming or its associative epidemic

hazardous effects. Consequently, calculation of the

risk involved in installation of any photovoltaic

becomes a standard measure of probability of any

harmful effects, such as its propensity for ‘carbon

sink or store’. The process of trapping and storing

carbondioxide as a means of decreasing its volume in

the atmosphere and mitigating climatic change is

defined as sequestration of carbon (Lal et al., 2013).

Inadvertently, there are natural carbon sequestration

processes but, that due to anthropogenic actions of

man leads to accruement of carbon dioxide in the

atmosphere. This follows up on carbon footprint and

is understandably a rising cause for concern in

climate issues (Park et al., 2011). Photovoltaics use

redox reactions, this by implication suggests innate

balance but, the nature of certain materials used

within their components reveals the contrary. An

illustration of electrolytes used is: leaky, volatile

compounds, corrosive or toxic liquids, this forms the

Jolaolu, A., Eterigho, E. and Olanrewaju, A.

Environmental Impact Assessment (EIA) of pH and Other Factors on Organic Photovoltaic Performance Output.

DOI: 10.5220/0009782501590168

In Proceedings of the 9th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS 2020), pages 159-168

ISBN: 978-989-758-418-3

159

epic of our environmental quest (Martelli et al.,

2011). Incorporation of a photoanode usually

involves cataclysmic reactions with concentrated

acid, pungent gases are emitted in the vicinity, this

brings a second perspective on the environment

(Olateju and Kumar, 2013). Preparation of the

counter electrode through masking it with platinum or

other carbon-based compounds is also an obvious

intrusion of carbon into the atmosphere (Botero et al.,

2013). It thus poses a high-level risk if photovoltaics

become a significant source of carbon source sink,

which has informed this research - a prospect of

orchestrating more collective carbon detention and

storing from improved changes in photovoltaic

fabrication and application techniques (Wich et al.,

2020). One of the greatest milestones of this century

is a need to stabilize the greenhouse gas

concentrations of the atmosphere (Müller et al.,

2020). To regulate these gaseous discharges, human

race can either lessen fossil fuel emissions directly or

diagnose instruments to get rid of greenhouse gases

once they are emitted (Heek et al., 2018). In this way,

sequestration of atmospheric carbon dioxide becomes

an appealing option as a substitute to help truncate the

astronomical rate of greenhouse gases and

accompanying changes to climate patterns. A priority

factor for consideration in this ecological theme is

reusability, it is difficult to sustain any technology

without any possibility for reuse (Ani and Basri,

2013). In order to carry out an effective valuation, a

program software will have been used. Although

many algorithms have played dual or more roles in

past researches whether applied individually or

corporately, many more are ongoing to unravel the

scientific facts embedded in present and future

numerical data (Bettinger et al., 2017). A search for

suitable software suited to the demands of this

particular research led to environmental impact

assessment (EIA). This is because, it was initially

written as a software programming tool established to

scale environmental impact of human activities on the

environment (Amundson and Biardeau, 2018).

Consequently, modification of EIA comes to play in

prior assessment of the effect of fabrication of dye-

sensitized solar cell on the environment with a view

of taking better decisions (Broday, 2020). This begins

with prior collection of data on the manufacturing

process, different stages of completion ranging from

scope to completion governed by EIA tool with a

determination to improve on the present by exploring

even safer and better alternatives (Zeleňáková et al.,

2020). Comprehensively, many research works have

focused on the effect of pH, because altering the pH

level in any ecosystem affects all living organisms

(Barandiaran and Rubiano-Galvis, 2019). There are

very few highlights on hazard footprints with specific

mention of vulnerability resulting from concentrated

acid interactions with titanium oxide as a naturally-

induced hazard which is another factor considered for

quantification of the afore-mentioned risk factors

(Wang and Su, 2020). The expected outcome is

higher Quality photovoltaics even with onset of time,

solvent deals in which neither sol gel gets evaporated

nor washed off by degeneracy, cleaner air quality

from cost-effective photovoltaic devices.

2 METHODOLOGY

Stoichiometric quantities of C.papaya, P.dulcis and

C.longa plants were air dried under conditions of

standard air mass in the laboratory. Their dried extract

was mixed in (5mg/5ml) methanol proportion, the pH

and temperature of each sample was recorded before

being affixed onto three separate titanium

frameworks already assembled on the indium doped

(ITO) conducting slides following standard

procedures described in previous researches

(Abodunrin et al., 2019). This procedure describes

the photoanode preparation, the counter electrode

comprised of masking a second pair of ITO with co-

axial deposition of soot over a naked flame, in a

simulated vacuum-like enclave. Each pair of anode

and counter electrode was fastened together with

clips, 5ml syringes were used to insert three drops of

aqueous electrolyte in-between the resultant ITO

sandwich. Excess electrolyte was allowed to tun off

but was noted for subsequent assessment in the

ensuing section. Each pair of ITO were connected in

parallel to a multimeter and variable resistive load

with the aid of flexible connecting wires to obtain

photovoltaic parameters (Abodunrin et al., 2019).

Experimental values of short circuit (I

), open circuit

voltage (V

), maximum power (P

max

), fill factor (ff)

and efficiency are the measurements taken. The

experimental set-up was taken outdoors and exposed

to conditions of standard airmass of 760mmHg. The

indoor air quality due to concentrated nitric acid

blended to a colloidal paste with titanium oxide

during preparation, calcination and subsequent

fabrication was determined by assigned values

consistent with EIA averages. The pH of the dye sol

of each dye was determined with using a pH meter

and the temperatures were recorded. In addition,

phytochemical screening of the extracts identified the

chromophores present in each dye (Abodunrin et al.,

2019). The Fourier Infrared spectroscopy of each dye

would be used to study the strong reactions and their

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160

Figure 1: Comparison of pH and temperature of three organic extracts.

possible consequent emissions into the environment.

Detailed analysis of their performances relative to

images from modelling their scanning electron

micrographs was used to obtain vital statistics for

computation of EIA.

3 RESULTS AND DISCUSSION

The pH and temperature of the three organic dyes are

as presented in Figure 1. P.dulcis dye records the least

value in temperature, 27.1

C. This is closely followed

by C.longa with a value of 27.8

C and the relative

highest temperature reading is given by C.papaya

with a temperature of 28.1

C. The average normal

surrounding temperature is 27

C, P.dulcis is the

nearest in ambient temperature while C.papaya is the

farthest in this context. The Environmental

Complexity factor is calculated as shown in

Equations 1-4 (Ani and Basri, 2013).

3.1 List of EIA Equations

𝐸𝐶𝐹  1.4  0.3  𝐸





(1)

𝑇𝐶𝐹  0.6  0.01  𝑇





(2)

𝑈𝑈𝐶𝑃  𝑈𝑈𝐶𝑊  𝑈𝑅𝑊

(3)

𝑈𝐶𝑃  𝑈𝑈𝐶𝑃  𝑇𝐶𝐹  𝐸𝐶𝐹

(4)

Where ECF is the Environmental Complexity Factor,

TCF represents Technical Case Factor, UUCP

denotes the unadjusted Use Case Point, UCP

connotes the Use Case Points and URW is Unadjusted

Reaction Weight.

3.1.1 Environmental Complexity Factor

(ECF)

Higher values of environmental factor imply greater

impact on the UCP equation. Thus, assigned value of

one implies the factor has a weak impact in this

venture, two is average while three signifies a strong

impact. This means that zero-value is of no

consequence on the environment. For example,

temperature of P.dulcis would be assigned 0.1,

C.longa would be given 0.8 while C.papaya is given

1.1. In addition, pH of C.papaya is 7.32, this is a little

above neutral on the Universal indicator scale hence,

its value would be 0.32. C.longa has a pH of 6.90, the

impact would be slightly negative on the

environment, it is assigned a value of -0.1 and

P.dulcis has a value of 5.49, this is even more

negative due to its acidity. It is assigned a value of -

Environmental Impact Assessment (EIA) of pH and Other Factors on Organic Photovoltaic Performance Output

161

1.51 while in this context basicity of an alkaline dye

would be assigned positive values. Another factor

that contributes to negatively to the environment are

the drops of electrolyte introduced in-between each

dye cell to facilitate charge transport. The cumulative

effect is accorded a value or weight comprising of the

sum of its ambient temperature factor with the pH

factor multiplied by its apparent impact to yield its

calculated impact factor. The calculated factors are

added together to produce the Environmental factor

as shown in Table 1.

Table 1: Break down of ECF parameters.

Factor Dye Weight Assessment Impact

 C.papaya 1.1+0.32

=1.42

3 4.26

 P.dulcis 0.1‐0.10

=0

3 0

 C.longa 0.8‐1.51

=0.71

3 ‐2.13

TotalE

factor

 ‐2.13

3.1.2 Technical Complexity Factors (TCF)

Arbitrary values between 0 to 3 are assigned

subjectively. The factors revolve around re-use, and

recycle viability. Responses for each application that

has a high influence like efficiency, 3 is awarded. The

higher the efficiency, the more viable it becomes in

its universal adoption. Response time infers how fast

the device responds to the required stimulus of

operation as this is paramount, it is allotted 3.

Kinematics refers to the excitation state of the

reactants in a dye-sensitized solar cell, whether their

momentum is elastic and the principle of conservation

of energy and linear momentum is conserved. This

decides the equilibrium of the reaction, either the

forward or backward reaction is occurring and when

they nullify to reverse each other. Portability is the

degree of compactness and ease of transporting the

device which is a prerequisite to the realization in the

primary function of any photovoltaic. A bulky

photovoltaic would experience transportation

challenges and limitation in its universal adoption.

The output efficiency is directly associated to the

photovoltaic performance of each dye-sensitized

solar cell. A zero is given to any factor that does not

have any influence on the study. A midpoint value of

2 is assigned to factors that are neither so strong yet

have a measure of influence on this study. Individual

factor’s weight is multiplied by its perceived

complexity factor to give a resultant calculated factor.

The calculated factors are summed to produce the

Total Technical Factor.

Table 2: Technical Factors of EIA.

Factor D Wt Assessment Impact

Response

Time

3 3 9

End user

Efficienc

0 1 0

Kinematic

Reaction

2 3 6

Reusability 1 0 0

Usability 3 3 9

Portability 1 2 2

Output

Efficienc

3 3 9

Total T

Factor

Key: D stands for Description, Wt connotes

Weight

3.1.3 Phytochemical Result in Terms of EIA

The outcome of phytochemical screening of the three

dyes is as shown in Table 3. A phytochemical

screening refers to the process of extracting,

identifying the bioactive substances such as:

antioxidants, flavonoids, tannins and so on. Presence

of any phytoconstituent is assigned a value of 1, while

its absence has no value and is given zero. The

significance of phytochemicals in dye-sensitized

solar cells is that, they contribute to the ionic radical

available for the redox reaction. It implies that, the

measure of effectiveness in a dye-sensitized solar cell

is a direct consequence of the metabolites available in

its bio-constituents. They also provide necessary

immunity for preserving the life cycle of the dye-

sensitized solar cell throughout. Hence the UUCW is

calculated from the product obtained from the number

of phytochemicals, weight and the number of cases as

shown in Table 4. In this project, loss of potency in

the phytochemical constituents is not given a

consideration such as the absorbance in the UV/Vis

region over a period of time. Thus, by tacit agreement

the electrolyte activates the dye-sensitized solar cell

whenever it is in operation. Furthermore, since each

phytochemical assist in the electrochemical

equilibrium, each is awarded the same strength, a

value of unity.

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162

Table 3: Phytochemicals in organic extracts.

 Ch Ta Sa Fl Al Qu Gl Ca Te Ph St

C.p

+ ‐ + + + ‐ ‐ + ‐ + ‐

P.d

‐ + + + + ‐ ‐ + ‐ + ‐

C.l

+ ‐ + + + ‐ ‐ + ‐ ‐ ‐

Key: Ch (CHO); Ta (Tannin); Sa (Saponin); Fl

(Flavonoid); Al (Alkaloid); Qu (Quinone); Gl (Glycoside);

Ca (Cardiac Glycoside); Te (Terpenoid); Ph (Phenol); St

(Steroid); + indicates presence, - means absence

C.p represents C.papaya, P.d stands for P.dulcis, C.l

represents C.longa

The significance of this result is that, with respect

to their electrochemical index, C.longa < C.papaya =

P.dulcis as indicated on Table 4. Relating this to the

ECF, the electrolyte in C.longa would require more

energy to raise the Fermi potential for excitation.

Hence, the negative impact of -2.13.

Table 4: Phytochemicals in terms of UUCW.

Use case

complexity

Number of

phytochemicals

present

Wt Number

of use

cases

Pdt

C.papaya 6 1 11 66

P.dulcis 6 1 11 66

C.longa 5 1 11 55

Total UUCW 187

Key: Wt represents Weight, Pdt stands for Product

3.1.4 Unadjusted Reaction Weight (URW)

The appearance of each functional group in a Fourier

Infrared Spectrograph is a characteristic that

distinguishes it from others in a chemical reaction as

shown in Appendix I. In effect, each property

identified is assigned a weight: -1 is given to the

unidentified wavelength frequencies, 1 is assigned to

the weak (w) intensity, m is allotted 2 for medium

intensity while

3, 4 and 5 is given to strong (s), strong – narrow

(s,n) and strong -broad (n,s) intensities respectively.

Their occurrences connote the number of times they

appear, the product symbolizes their cumulative

frequency. The significance of the strength of

reaction determines the direction of the kinematics of

the overall dye-sensitized solar redox reaction and the

Fermi level in the photovoltaic.

Table 5: FTIR of P.dulcis dye.

P.dulcis

Wavelength FunctionalGroup Intensity

3423.76; 2926.11;

2852.84

O‐Hstretching



s,b

2426.53 Unidentified 

2085.12 CO

stretching s

1741.78 C=Ostretching s

1658.84;1608.69 C=C stretching in

alkene di‐

substitution

w

1498.74 Unidentified 

1456.30 Unidentified 

1384.94; 1346.36;

1298.14; 1253.77;

1207.48; 1182.40;

1084.03;1043.52

O‐H bending in

carboxylicacid

m

931.65 Unidentified 

842.92;715.61;

642.32;574.81

C‐Cl stretching in

alkylhalides

s

522.73; Unidentified 

s: strong; w: weak; n: narrow; m: medium; b: broad

Table 6: FTIR of C.longa.

C.longa

Wavelength Functional Group Intensit

3853.90; 3421.83 O-H stretchin

, b

2926.11; 2852.81 Aci

O-H

, n

2426.53 O-H stretchin

2285.72; 2085.12 O=C=O in CO

1741.78; 1658.84 C-H bending in

aromatics

1608.69 C=C stretch in

alkene

disubstitute

1498.74; 1456.30 C-C stretch in ring

aromatics

1384.94;

1346.36

Symmetric nitro

compounds

1298.14;

1253.77;

1207.48; 1182.40

Acyl stretching s

1084.03; 1043.52 C-O stretching in

Alkoxy

931.65 Unidentifie

842.92 C-Cl stretching in

alkyl

715.61; 642.32 Meta di-substituted

C-H

574.81; 522.73 C-Br Stretching in

alk

424.35 Unidentifie

Key: s: strong; w: weak; n: narrow; m: medium; b: broad

Environmental Impact Assessment (EIA) of pH and Other Factors on Organic Photovoltaic Performance Output

163

Table 7: FTIR of C.papaya.

Wavelen

th Functional Grou

Intensit

3429.55; 2926.11 N-H stretching in

amine

2854.74 C-H stretchin

2729.37; 2507.54 O-H stretching in

carboxylic aci

s,b

2019.54 Unidentifie

1735.99; 1637.62 C-H

endin

1458.23 Unidentifie

1377.22;

1244.13; 1168.90;

1072.46; 1037.74

C-F stretching in

Fluoric

compounds

873.78 C=C bending in

alkene di-

substitute

839.06; 723.33;

665.46

C-Cl stretching

in alkyl

compounds

597.95; 515.01 C-Br stretching

in alkyl

com

ounds

437.86 Unidentifie

Table 8: FTIR of dyes in terms URW.

Dye Weight Occurrences Pdt

P.d S m w U s m w U

3-5 2 1 -1 3,0,1 2 1 4 15

C.l

m w U

3-5 2 1 -1 4,1,1 3 4 2

C.p

m w U

3-5 2 1 -1 3,0,1 1 3 3

URW

Total

C.p represents C.papaya, P.d stands for P.dulcis, C.l

represents C.longa

3.1.5 Stereochemistry of Dyes on EIA

The interpretation of the dye molecular structure with

regards to their atomic position in 3-dimensional

space is required for the EIA. Thus, the

phytochemicals will be investigated for their reaction

in the applied photovoltaic. In particular,

carbohydrate presence would be examined as

illustrated in Figure 2.

The chemical formula differs from the

characteristic C

due to the chemical reaction in

the photovoltaic. Element composition conforms with

the standard CHO in organic compounds, in effect

these elements have a positive photo degeneracy

quotient.

Chemical Formula: C

Exact Mass: 270.20

Molecular Weight: 270.37

m/z: 270.20 (100.0%), 271.21 (13.0%). 272.21 (1.2%)

Elemental Analysis: C, 53.31; H, 11.18; O, 35.51

Figure 2: Analysis of Carbohydrate in dyes.

It is pertinent to also explore the sole presence of

tannins in P.dulcis, the reaction interpretation is as

shown in Figure 3. The presence of tannins influenced

the unadjusted reaction weight (URW) to give the

least value. It is also noteworthy that, tannins

probably assisted P.dulcis in actualizing the zero

impact on the environmental complexity factor

(ECF). This is attributable to its numerous ligands

which facilitate its articulation with other bio-

molecules. Hence, it has better photo degeneracy than

Carbohydrates.

Chemical Formula: C

Exact Mass: 1261.36

Molecular Weight: 1262.16

m/z: 1261.36 (100.0%), 1262.36 (66.0%), 1263.37

(21.4%), 1263.37 (6.0%), 1264.37 (4.6%), 1264.37 (3.9%)

Elemental Analysis: C, 58.05; H, 5.19; O, 36.76

Figure 3: Analysis of Tannin in P.dulcis dye.

The presence of flavonoid in all three organic

dyes makes available bio-catalysts in the respective

photovoltaic reactions. It also offers a large store of

carbon atoms from the C

-C

molecular

framework. The three organic photovoltaic cells act

as a form of carbon sequestrate as shown in Figure 4.

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164

Figure 4: Interaction of Flavonoid in dyes.

The interaction of saponins in the three

photovoltaic cells will be considered in order to

assess the environmental impact. Saponins provide

the underlying foundation for the assortment of

functional groups attachment and determines the

general shape of the molecule. Saponins serve a

steroidal physiological function keeping the other

bio-substances active. Their ligands combine with

other functional groups during the chemical reaction

in the photovoltaic as shown in Figure 5.

Chemical Formula: C

Exact Mass: 516.56

Molecular Weight: 516.98

m/z: 516.56 (100.0%), 517.57 (40.0%), 518.57 (7.8%)

Elemental Analysis: C, 85.96; H, 14.04

Figure 5: Analysis of Saponin Effect on Photovoltaic.

Interestingly, the phenolic ring is a recurrent

feature in both saponins and flavonoids. A third

consistent functional group in the dyes is the

Alkaloid. Phenols constitute the major class of

secondary metabolites in plants. Their aromatic

nature is responsible for pigmentation, flavour (not

applicable in this study) and acerbity. Although they

possess -OH functional group similar to alkaloids,

they exhibit stronger potency in chemical reactions.

These interactions with the concentrated

trioxonitrate (V) acid and titanium will be discussed

with a focus on their EIA impact. The energy and

gradient of applying the concentrated trioxonitrate

(V) acid on the titanium was run with CHEM DRAW

and the output is as shown in Figure 6.

Figure 6: A model of Concentrated HNO

The Energy (MMFF94) and Gradient was

determined using software program estimate. The

total energy for this frame was given as, 15.976

kcal/mol. The RMS Gradient was given as 44.260.

Thus, the MM2 Calculation completed successfully.

The MM2 Dynamics was obtained from Pi

System: 5 4 6.

Some parameters are assigned (Quality = 1). The

remaining associated properties were calculated and

the result is as shown on Table 9.

Table 9: Dynamics of Reaction.

Stretch 4.6807

Bend 3.1011

Stretch-Bend -0.2023

Torsion -0.5171

Non-1,4 VDW -0.0943

1,4 VDW 2.2077

Charge/Charge 0.0000

Charge/Dipole -5.7107

Dipole/Dipole 6.3333

The total energy for this frame: 9.799 kcal/mol

The energy of the reaction was the second value determined, in

this context of the photovoltaic reaction and the environmental

impact.

The Equations of the redox reaction in the

photovoltaic cells is as indicated in Equations 5-7

(Cadien and Nolan, 2012). The dye (D) absorbs

photons of energy from the sun and becomes excited

𝐷

∗

as shown in Equation 5, the dye is affixed to the

titanium frame. The oxidized or excited dye gets

reduced by iodide as illustrated in Equation 6. The

Environmental Impact Assessment (EIA) of pH and Other Factors on Organic Photovoltaic Performance Output

165

formation of iodide radical on the oxide surface is

shown in Equation 7.

𝑇𝑖𝑂



𝐷

⁄

ℎ𝑣→𝑇𝑖𝑂



𝐷

∗

⁄

(5)

𝑇𝑖𝑂



𝐷

∗

⁄

2𝐼



→𝑇𝑖𝑂



𝐷

⁄

𝐼





(6)

2𝐼





→𝐼



𝐼





(7)

The effect of concentrated nitric acid on the

environment is shown in the Appendix. The graph

illustrates a sine crest, depicted by an initial rise in the

density of the molecules of the acid as it reaches a

peak. As diffusion occurs with air molecules colliding

with the fumes given off from the acid, the peak

gradually slopes down until there is equilibrium.

4 CONCLUSIONS

Environmental Complexity Factor (ECF) from

Equation 1 gives 2.639, Technical Complexity Factor

gives 0.95 from Equation 2, Unadjusted case product

in Equation 3 is given as 247, Use Case Point from

Equation 4 gives 421.55 in 2 decimal places. It is

generally difficult to gauge the environmental effect

based on this outcome unless there is a standard for

comparison. Hence, at this point it is imperative to

introduce an index. The first is a comparison of each

dye relative to the sum-total of the effect of all the

dyes. On this basis, individual assessment for the dyes

give 8.544, 8.468 and 15.68 for C.papaya, P.dulcis

and C.longa respectively. C.longa dye has close to the

addition of the individual effects of C.papaya and

P.dulcis dyes. This is a direct consequence of the

unadjusted reaction weight (URW) factor. Converse

to conventionality, this project reveals that all organic

dyes have an effect on the environment, although

their impact varies for different photovoltaics.

Another salient factor becomes measuring the level of

impact, in terms of photo degeneracy relative to fossil

fuels. In terms of degradation, each organic dye

produces negligible effect but the combination of

dyes has a multiplicity effect on the environment

which is minimal with respect to fossils. C.longa has

almost double the environmental footprint of

C.papaya and P.dulcis as indicated in this result. The

photo degeneracy of C.longa is double in its

consequence. In terms of the FTIR spectroscopy,

C.longa shows CO

at two wavelength frequency

peaks, C.papaya shows in just one, P.dulcis shows

none. This is a direct consequence of their carbon

sequestration characteristic, P.dulcis is not a carbon

sequestrate. Eventually, this study shows a direct

correlation between the environmental footprint of

the dyes through their CO

reaction. In terms of

carbon sequestration, C.longa dye is determinedly the

best of all three dyes in ultimately reducing the

greenhouse effect.

The outcome of this project prescribes the

following measures:

1. The environmental footprint of dyes should

be one of the foundational studies carried out

before their subsequent use in photovoltaics.

2. A preliminary information on Fourier

Infrared spectroscopy of any extract should

be a prerequisite source of information on

the reaction that each dye content would

promote.

3. Promoting the natural photovoltaic

processes is a simple but effective means of

reducing the atmospheric carbondioxide

levels. This is because, dispersed

carbondioxide sources are very challenging

to harness for cost effective carbon

separation and capture methods.

ACKNOWLEDGEMENTS

The authors of this work are immensely grateful to

Covenant University for providing an appropriate

ambience required for the investigation of this

research. They also wish to appreciate the

technologists at the Chemistry department of

Redeemers’ University, Ede for the Fourier Infrared

spectroscopy of the organic dyes. Their gratitude goes

to the technologists at the Biochemistry laboratory of

Covenant University for their expertise in identifying

the phytochemicals present in each of the dye.

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APPENDIX

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