Assessment of perceptions and practices of electronic waste management among commercial consumers in Ho, Ghana

Figures & data

Figure 1. Map showing Ho Municipal Area (Ho—Google Maps, 2021).

Table 1. Demographic characteristics of respondents

Gender		Age (Yrs)		Qualification		Experience (Yrs)
Male	49.0%	20–30	18.0%	SHS	11.5%	Below 2	14.5%
Female	51.0%	31–40	29.0%	Diploma	15.0%	2–10	45.0%
		41–50	41.0%	Bachelors	69.0%	11–20	23.0%
		>50	12.0%	Masters	4.5%	Above 20	17.5%

Source: Fieldwork, 2021

Table 2. Awareness level of e-waste

Binary Logistic Regression Results
Test of Model Coefficient	Chi-square		df		Sig.
	14.913		4		0.005
Step 1	B	Sig.	Exp(B)	95.0% C.I.for EXP(B)
				Lower	Upper
Gender(1)	0.531	0.249	1.700	0.689	4.193
Age	−0.176	0.462	0.839	0.526	1.339
Qualification	0.905	0.001	2.472	1.476	4.142
Experience	−0.177	0.441	0.838	0.533	1.316
Constant	0.308	0.744	1.360

Table 3. Awareness level of the harmful effect of e-waste

S/N	Knowledge and Awareness	No (%)	Yes (%)	Mean
1.	Are you aware of any health risk(s) associated with electronic waste?	28.5	71.5	1.72
2.	Does electronic waste pose a serious threat to the environment?	25.0	75.0	1.75
Mean Response (M.R)				1.74

Source: Fieldwork 2021

Table 4. Awareness level of laws and government legislation

S/N	Knowledge and Awareness	No (%)	Yes (%)	Mean
1.	Do you know of any local or international laws about electronic waste management?	72.0	28.0	1.28
2.	Do you know of any legislation on e-waste management passed by the parliament of Ghana?	74.0	26.0	1.26
Mean Response (M.R)				1.27

Source: Fieldwork 2021

Figure 2. Usage of equipment in an institution/organization.

Table 5. Overall setting and storage condition of e-waste

Binary Logistic Regression Results
Tests of Model coefficients	Chi-square		df		Sig.
	4.829		1		0.028
Step 1	B	Sig.	Exp(B)	95.0% C.I.for EXP(B)
				Lower	Upper
Experience	−0.374	0.029	0.688	0.492	0.963
Constant	1.959	0.000	7.093

Figure 3. Disposing of e-waste products.

Figure 4. Challenges in disposing of e-waste.

Table 6. Awareness of toxic/hazardous material from e-waste

Binary Logistic Regression Results
Hosmer and Lemeshow Test	Chi-square		df		Sig.
	11.100		8		0.196
Step 1	B	Sig.	Exp(B)	95.0% C.I.for EXP(B)
				Lower	Upper
Gender	−0.263	0.393	0.769	0.420	1.405
Age	−0.116	0.482	0.890	0.643	1.232
Qualification	0.111	0.493	1.118	0.813	1.814
Experience	0.194	0.343	1.214	0.813	1.537
Constant	0.615	0.000	1.849

Table 7. Impact of E-Waste on the Environment

Code	Items	No. of respondents
1	No Effect	84
2	Fairly	41
3	Strong	19
4	Very Strong	56

Source: Fieldwork 2021

Figure 5. Overview of the e-waste treatment process in Ho municipality.

Figure 6. Valuable and readily removed components from obsolete equipment.

Figure 7. Typical sites dealing with e-waste and other scraps in Ho.

Figure 8. Open burning of e-waste after recovery of valuable materials.

Figure 9. Storage of old and obsolete appliances.

Ho - Google Maps. https://www.google.com/maps/place/Ho/@6.6178716,0.2689526,11.25z/data=!4m5!3m4!1s0x102725152a227ba1:0x9da6ad4a4c9a2107!8m2!3d6.6101493!4d0.4785495 (accessed Jul. 18, 2021)

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Data availability statement

The data that support the findings of this study are available from the corresponding authorupon request.