Exploring Health Risks of Solar PV Waste: A Study in Indonesian Students′ Knowledge and Practices

Abstract

The rapid expansion of solar photovoltaic (PV) technology in Indonesia marks a significant step toward sustainable and green energy solutions. However, the end‐of‐life phase of solar PV panels poses emerging socioenvironmental burdens, particularly due to the presence of hazardous and heavy metal–containing waste. Despite its importance, the management of solar PV waste remains underdeveloped in Indonesia. This study is aimed at identifying knowledge gaps and assessing university students′ knowledge, attitudes, perceptions, and practices (KAPP) regarding the potential health impacts of solar PV waste in Surabaya, Indonesia. Using a structured questionnaire, data were collected from 329 respondents to explore their understanding of exposure pathways, health risks, and proper waste management practice. The survey results indicate that while the majority of students demonstrate moderate to high awareness of solar PV recycling and associated health risks, this awareness is largely theoretical. The reliance on online information sources appears to shape their knowledge, yet actual exposure to implementation and recycling practices remains limited. Attitudes reflected strong environmental concern, with respondents expressing support for sustainable initiatives, such as premium pricing for recyclable panels. However, perceptions also revealed skepticism toward the government′s preparedness and public awareness, and practical engagement, such as attending training or participating in recycling programs, was notably low. The results point to a gap between awareness and practical action. Bridging this gap through targeted educational efforts and supportive policies is essential to ensure responsible management of solar PV waste in Indonesia as the technology continues to grow.

1. Introduction

Solar photovoltaic (PV) systems have become one of the most widely adopted renewable energy technologies due to their ability to convert sunlight into electricity with far lower carbon emissions than fossil fuels [1–5]. Global solar electricity generation exceeded 2000 TWh in 2024 and now contributes around 7% of global power production, highlighting the rapid growth of PV deployment worldwide [6–8]. Declining costs and increasing policy support have also made solar energy more accessible in developing countries, including Indonesia. Indonesia has set a national target for renewable energy to account for 23% of final energy consumption by 2025, with solar power expected to play a major role in achieving this goal [9, 10]. The country receives an average solar irradiation of 4.80 kWh/m²/day and has an estimated technical potential of more than 200 GW [11–13]. Although current installed capacity remains low, government initiatives—such as rooftop solar programs, solar street lighting, and solar-based services in remote areas—are gradually increasing adoption [12, 14].

Recent assessments indicate that Indonesia′s overall solar energy potential is even larger, reaching more than 3000 GWp across the archipelago. As of late 2023, total installed PV capacity stood at 573.8 MW, with an annual addition of 290.69 MW from ground-mounted, rooftop, and floating systems. The 145 MW Cirata floating solar power plant in West Java is currently the country′s largest project. With national capacity projected to exceed 8.5 GW by 2030, Indonesia may generate more than one million tons of end-of-life (EoL) solar panel waste by 2050 as panels reach their 25–30-year lifespan [15]. This projected waste stream presents a serious emerging challenge. Solar panels are classified as B3 (Bahan Berbahaya dan Beracun/hazardous and toxic waste) hazardous waste due to the presence of heavy metals and toxic compounds such as lead, cadmium, and arsenic. Improper disposal can lead to the leaching of these substances into the soil and water, posing serious threats to ecosystems and human health [16]. While current EoL volumes remain low, the rapid expansion of solar installations indicates that Indonesia will soon face a substantial waste burden. At present, formal collection and recycling infrastructure for both e-waste and solar PV waste is limited, and many regions still rely on open dumping and burning, practices that can worsen environmental contamination.

The government and private sector have begun to explore frameworks for safer PV waste management. For example, PT Surya Energi Indotama is developing procedures for environmentally sound disposal in collaboration with certified hazardous waste processors such as PT Prasadha Pamunah Limbah Industri (PPLI). However, experts consistently emphasize the need for clearer regulations, standardized disposal pathways, and greater investment in domestic recycling technologies to recover valuable materials such as glass, aluminum, silicon, cadmium, and tellurium [17, 18]. Experiences from other countries show that weak coordination, limited facilities, and the absence of comprehensive policies remain major barriers to effective PV waste management [1, 19, 20]. Extended producer responsibility (EPR) has been identified as a promising approach to ensure that manufacturers take responsibility for product take-back and recycling [1, 21]. Despite the increasing use of solar energy, public awareness of the health and environmental impacts of PV waste remains limited. Many people still view solar power as entirely clean and may not recognize the toxic components or the consequences of improper disposal, including contamination of soil, water, and food sources [22]. These gaps make targeted education essential, particularly for university students who will become future engineers, policymakers, and environmental professionals. Previous studies show that students can play a significant role in promoting sustainable practices through academic learning, campus initiatives, and community engagement [23–26]. Against this background, this study examines the knowledge, attitudes, perceptions, and practices (KAPP) of university students′ awareness in Indonesia regarding solar PV waste and its potential effects on human health. Although students are often exposed to renewable energy concepts, their understanding of PV-related hazards and safe disposal practices may be incomplete. Identifying these gaps is critical for designing educational programs and policy interventions that support Indonesia′s transition to safe and sustainable solar energy management.

2. Methodology

2.1. Study Location

This study was conducted in Surabaya, a major coastal city situated in the northeastern region of Java Island, East Java Province, Indonesia. As the second-largest city in the country and a prominent financial and educational hub, Surabaya hosts a diverse population, including university students originating from various provinces across Indonesia. The city′s rapid urbanization, population growth, and expanding industrial sector have driven the adoption of solar PV systems as part of the national shift toward renewable energy. Consequently, this transition has also raised concerns regarding the accumulation and management of solar PV waste, making Surabaya an appropriate setting for assessing KAPP related to solar PV waste among university students.

2.2. Study Design and Population

This cross-sectional study was conducted among university-level students enrolled at various higher education institutions in Surabaya, East Java Province, Indonesia. Participants were selected based on the following inclusion criteria: aged 18 years or older, currently residing in Surabaya, and actively enrolled as university students. The respondents represented a diverse background, with many originating from different regions across Indonesia, providing broader insight into nationwide awareness and perceptions related to solar PV waste.

2.3. Sample Size

The selection of participants was nonrandomized, based on the simple random sampling method. The number of participants as the sample size for this study was considered based on Cochran’s formula. The Cochran formula is as follows: $\begin{array}{}N=\frac{Z^{2}pq}{e^2}=\left({\left(1.962\right)}^2\right)\times \left.\mathrm{0.50.5}\times \right)/{\left(0.05\right)}^2=385\end{array}$

where N is the total sample size, Z is a 95% confidence level which gives us Z values of 1.96, e is the desired level of precision or the margin of error, p is the estimated proportion of the population which has the attribute in question, and q = 1–p.

In practice, a total of 329 valid responses were collected. The shortfall from the target sample was mainly due to limited participation, as data collection relied on voluntary responses through Google Forms distributed via social media platforms (e.g., WhatsApp, Facebook, and student groups). Although the achieved sample size was slightly lower than the calculated requirement, it still provides sufficient power for analysis. Nevertheless, the reduced number of participants may slightly increase the margin of error and should be considered when generalizing the findings to the broader population.

2.4. Data Collection Tool and Procedure

Data were collected using a structured questionnaire distributed via Google Forms. The questionnaire consisted of three main sections. The first section gathered basic demographic information such as age, gender, and current residence. The second section assessed participants′ knowledge, attitudes, and perceptions regarding solar PV waste, including its environmental and health impacts. Topics covered included awareness of hazardous materials in solar panels, contamination pathways, and potential risks to ecosystems and human health. The third section focused on behavioral practices related to solar PV waste, including waste disposal habits, usage of solar technologies, and awareness of manufacturing and recycling processes.

2.5. Ethical Clearance

This research followed the ethical guidelines and the ethical approval was obtained from the Faculty of Nursing, Airlangga University (Reference No. 3082-KEPK). The study subjects were given a detailed explanation of the purpose of the study, and they had to sign a consent form before they began the study. The respondents were assured about the confidentiality and anonymity of the information details obtained for the research. The respondents were free to withdraw from the study at any stage. By signing the consent form, all subjects were authorized for the record, review, information storage, and data processing.

2.6. Data Quality Control

The questionnaire was prepared in English at the first stage, and later, it was translated into the local language (Indonesian). After data collection, the data from the questionnaire in the local language was translated back into English. Moreover, the completeness of the questionnaire was checked by the principal investigator regularly.

2.7. Data Management and Analysis

All questionnaire data extracted from Google Forms were exported to Microsoft Excel for data cleaning and management, and subsequently analyzed using R Studio (Version 2023.06.01). Descriptive statistical analyses were performed, including frequencies and percentages for categorical variables. A heat map was also generated in R to provide a visual representation of variable distributions and relationships. Bivariate analyses were conducted using the Chi-square test and Fisher′s exact test, while multivariable analysis was performed using multiple logistic regression. Multiple logistic regression was applied to examine the relationship between a binary dependent variable and multiple independent variables.

3. Results

3.1. Sociodemographic Information

The study included 329 respondents (Table 1), with the majority being female (63.5%). The mean age of respondents was 20.52 years (SD = 4.25), and most fell into the age group of 17–29 years (96.7%). Participants were predominantly enrolled in public universities (74.8%), with 58.4% pursuing diploma programs and 38.0% enrolled in bachelor’s degrees. A smaller proportion were postgraduate students (3.6%). Regarding study levels, 50.8% were first-year students, 31.3% were in their second year, and 17.9% were in their third year or higher. In terms of employment, the majority (73.9%) reported being unemployed, while 26.1% were engaged in full-time, part-time, or irregular employment.

Table 1 Demographic characteristics of the respondents (n = 329).

Characteristics of the respondents	Frequency (n)	Percentage (%)
Sex
Male	120	36.47
Female	209	63.53
Age (mean ± SD : 20.52 ± 4.25)
17–19 years	154	46.81
20–29 years	164	49.85
30+ years	11	3.34
Type of university
Public	246	74.77
Private	83	25.23
Study level
Diploma	192	58.36
Bachelor	125	37.99
Postgraduate (master/PhD)	12	3.65
Year of study (mean ± SD : 3.34 ± 1.61)
First	167	50.76
Second	103	31.31
Third or above	59	17.93
Employment
Full time/part time/irregular	86	26.14
Not employed	243	73.86
Living area
City center/urban	137	41.64
City periphery/rural	180	54.71
Both	12	3.65
Individual cost of living (median/IQR: IDR 1,000,000 [500,000–1,500,000])
≤ 500,000	95	28.90
500,001–1,000,000	92	28.00
1,000,001–1,500,000	57	17.30
> 1,500,000	65	19.80
Not answer	20	6.10
Family cost of living (median/IQR: IDR 3,000,000 [2,000,000–5,000,000])
≤ 2,000,000	98	29.80
2,000,001–3,500,000	47	14.30
3,500,001–5,000,000	65	19.80
> 5,000,000	41	12.50
Not answer	78	23.70
Individual monthly income (median/IQR: IDR 1,000,000 [475,000–1,775,000])
≤ 500,000	43	13.10
500,001–1,000,000	18	5.50
1,000,001–1,500,000	12	3.60
> 1,500,000	27	8.20
Not answer	229	69.60
Family monthly income (median/IQR: IDR 4,000,000 [2,000,000–6,000,000])
≤ 2,000,000	67	20.40
2,000,001–3,500,000	47	14.30
3,500,001–5,000,000	56	17.00
> 5,000,000	81	24.60
Not answer	78	23.70

Most respondents lived in rural or peripheral city areas (54.7%), while 41.6% resided in urban areas. The monthly individual living costs varied widely, with 56.9% reporting costs of ≤ 1,000,000 IDR and only 37.1% reporting costs above this threshold. The median family monthly income was 4,000,000 IDR, with 71.4% of families earning ≤ 5,000,000 IDR and 24.6% earning more than 5,000,000 IDR.

3.2. Knowledge About Solar PV Waste Effect on Human Health

Participants demonstrated varying levels of knowledge about the health and environmental impacts of solar PV waste. Figure 1 presents participants′ knowledge of the impact of solar PV waste on human health. Respondents showed high awareness of the importance of proper disposal to prevent health risks (Q7: 42.6% agree, 36.8% strongly agree; mean 4.07) and the recyclability of solar PV waste to reduce environmental impact (Q5: 50.2% agree, 18.2% strongly agree). They also recognized the harmful nature of broken solar panels leaching toxic substances (Q4: 47.7% agree, 11.6% strongly agree) and the projected increase in solar PV waste due to growing installations (Q9: 53.5% agree, 15.2% strongly agree). However, knowledge of specific toxic byproducts like silicon tetrachloride and cadmium telluride (Q2 and Q3) was slightly lower, reflected in smaller agreement percentages. Overall, the data highlights a moderate to high level of awareness regarding general risks and disposal practices associated with solar PV waste.

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Regarding the primary components of solar panels, a majority (61.7%) correctly identified silicon, while 22.2% believed copper was the main material, and 16.1% thought aluminum played this role (Table 2). None of the respondents selected gold. Knowledge about toxic chemicals associated with thin-film solar panels varied: 59.6% correctly identified cadmium telluride as harmful, while 33.7% selected silicon tetrachloride, a byproduct of solar panel production. Only a small fraction (6.1%) mistakenly chose polycarbonate or bisphenol as the primary toxic chemicals.

Table 2 Knowledge level among respondents.

Knowledge	Frequency (%)
What is the primary component of solar panels?
Copper	73 (22.19)
Silicon	203 (61.70)
Aluminum	53 (16.11)
Gold	0 (0.00)
Which toxic chemical is commonly associated with thin-film solar panels?
Silicon tetrachloride	111 (33.74)
Cadmium telluride	196 (59.57)
Polycarbonate	20 (6.08)
Bisphenol	2 (0.61)
How many years is the typical lifespan of a solar PV system before it becomes waste?
5–10 years	25 (7.60)
10–20 years	83 (25.23)
20–25 years	125 (37.99)
30–40years	96 (29.18)
How can solar panels be safely disposed of at the end of their life?
Thrown in regular trash	6 (1.82)
Buried in the backyard	12 (3.65)
Taken to a specialized recycling facility	311 (94.53)
Left out in open spaces	0 (0.00)

The lifespan of solar PV systems before they become waste also revealed some gaps in understanding. While 67.2% correctly identified the typical lifespan as 20–40 years, 25.2% underestimated it as 10–20 years, and 7.6% thought it was only 5–10 years. Encouragingly, the vast majority (94.5%) showed awareness of the correct method of disposal, stating that solar panels should be taken to specialized recycling facilities. However, a small proportion believed panels could be buried in backyards (3.7%) or thrown in regular trash (1.8%). These results highlight both strengths and areas for improvement in public knowledge about the safe handling and disposal of solar PV waste, particularly given the anticipated increase in waste due to the rising popularity of solar energy installations.

3.3. Attitude About Solar PV Waste Effect on Human Health

Figure 2 highlights participants′ attitudes toward solar PV waste and its impact on human health. Most respondents expressed concern about waste management (Q1: 51.06% agree, 17.33% strongly agree) and a strong willingness to learn more (Q2: 53.19% agree, 18.84% strongly agree). There was broad agreement on the importance of managing solar PV waste for environmental health (Q4: mean 4.12) and adopting sustainable practices (Q5: mean 3.98). While many recognized the shared responsibility of managing costs (Q7: 44.68% agree, 20.36% strongly agree), fewer participants were willing to discuss the issue with others (Q3: 38.91% neutral, mean 2.53). Encouragingly, over half supported paying a premium for panels with guaranteed recycling or disposal plans (Q8: 53.50% agree, 24.62% strongly agree), reflecting a positive attitude toward sustainability.

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3.4. Perception About Solar PV Waste Effect on Human Health

Figure 3 summarizes participants′ perceptions regarding the effects of solar PV waste on human health. Many respondents disagreed with statements minimizing the significance of solar PV waste, such as it not being a significant health concern (Q1 and Q2: mean scores 2.41, 2.46, with over 40% disagreement). While some agreed that environmental benefits outweigh waste concerns (Q3: 43.16% agree, mean 3.32) or that solar PV waste is fully recyclable and poses no health risk (Q4: 46.5% agree, mean 3.11), skepticism remains high. A significant portion perceived a lack of public awareness about solar PV waste (Q5: 39.51% agree, mean 3.63), yet few believed there is sufficient public understanding or that local authorities are equipped to manage the growing waste volume (Q6 and Q7: mean 2.44, 2.69). These results reveal gaps in awareness and readiness to address solar PV waste issues.

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3.5. Practices About Solar PV Waste Effect on Human Health

Figure 4 highlights respondents′ practices regarding solar PV waste and its effect on human health. Most respondents showed limited engagement in direct actions, such as visiting recycling facilities (Q7: mean 2.41, 35.9% neutral, 35.3% disagree) or attending discussions on solar PV waste management (Q5: mean 2.60, 35.6% disagree). Some were aware of environmentally friendly manufacturers with clear waste policies (Q6: mean 3.86, 35.6% agree, 29.8% strongly agree) and considered EoL management in purchases (Q4: mean 3.45, 42.6% agree). However, practical awareness of recycling options and inquiries about disposal remained low (Q2 and Q1: means 2.91, 3.01). Respondents generally agreed that solar energy is environmentally friendly, despite waste concerns (Q3: mean 3.08). These findings suggest a gap between knowledge and proactive practices in managing solar PV waste.

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3.6. Awareness About Solar PV Waste Effect on Human Health

According to Table 3, the sources of information about solar PV waste and its implications varied significantly among respondents, with most learning through internet platforms (76.3%) and social media (69.9%). Traditional media, including newspapers and TV news, were cited by 21.3%, while 16.4% gained awareness from textbooks or formal education. Only 13.1% learned through awareness-building activities organized by the government or society, and smaller proportions mentioned word-of-mouth interactions (12.2%), conferences (7.9%), or other unspecified means (12.8%).

Table 3 Awareness about solar PV waste effect on human health.

Awareness	Frequency (%)
Source of information, how you knew about solar PV waste and its implications
Internet	251 (76.29)
Social media	230 (69.91)
Newspaper/TV news	70 (21.28)
Textbook/formal education	54 (16.41)
Awareness-building activity by government or society	43 (13.07)
Word of mouth by friends, family	40 (12.16)
Conference	26 (7.90)
Others	42 (12.77)
Strong way to build awareness about solar PV waste and its implications
Social media	292 (88.75)
Newspaper/TV news	171 (51.98)
Awareness events	135 (41.03)
Conference	92 (27.96)
Others	43 (13.07)
Have you ever attended any workshops or webinars specifically discussing solar PV waste management
Yes	28 (8.51)
No	301 (91.49)

When asked about the most effective ways to build awareness, social media was overwhelmingly identified as the strongest medium by 88.8% of respondents, followed by newspapers or TV news (52%) and organized awareness events (41%). Conferences were seen as effective by 28%, and other methods by 13%. Despite these varied sources of information, only 8.5% of respondents reported having attended workshops or webinars focused on solar PV waste management, indicating a significant gap in specialized educational initiatives. The findings suggest the importance of leveraging popular digital platforms and increasing formal engagement opportunities to enhance public awareness about solar PV waste and its implications for human health and the environment.

3.7. Bivariate Analysis

Figure 5 presents the Pearson′s correlation coefficients between knowledge, attitude, and practices scores. The correlation between knowledge and attitude was r = 0.57, indicating a moderate to strong positive relationship—higher knowledge was associated with more positive attitudes. The correlation between knowledge and practices was r = 0.29 and between attitude and practices r = 0.31, both suggesting low to moderate positive relationships. All correlations were statistically significant (p < 0.001).

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Participants′ scores were then categorized into two groups based on the median for each variable: KAPP (Table 4). Overall, 53.8% had good knowledge, 59.6% had positive attitudes, 64.7% demonstrated good practices, and 60.8% held true perceptions.

Table 4 Participants′ scores based on the median for each variable: knowledge, attitude, practices, and perception.

Variables	Frequency	Percent
Knowledge
Good	177	53.8
Poor	152	46.2
Attitude
Positive	196	59.6
Negative	133	40.4
Practices
Good	213	64.7
Poor	116	35.3
Perception
True	200	60.8
False	129	39.2

3.8. Bivariate Analysis: Knowledge

Bivariate analyses (Table 5) revealed several significant associations with knowledge level. Participants with higher education (Bachelor′s, Master′s, and PhD) had significantly better knowledge than those with lower education levels (p < 0.001). Knowledge was also significantly associated with obtaining information from newspapers or TV news (p = 0.0014) and perceiving these media as strong tools for awareness (p = 0.0028). Additionally, participants who considered conferences as effective for awareness had better knowledge (p = 0.0486). Finally, those with true perceptions about solar PV waste demonstrated significantly higher knowledge levels (p = 0.007).

Table 5 Bivariate analysis: knowledge.

Variables	Good ( n = 177 )	Poor ( n = 152 )	Total ( n = 329 )	p value
Sexa	0.1639
Male	58 (32.77)	62 (40.79)	120 (36.47)
Female	119 (67.23)	90 (59.21)	209 (63.53)
Age groupa	0.1548
17–19 years	83 (46.89)	71 (46.71)	154 (46.81)
20–29 years	85 (48.02)	79 (51.97)	164 (49.85)
30+ years	9 (5.08)	2 (1.32)	11 (3.34)
Current study levelb	< 0.001 ∗
Diploma	116 (65.54)	76 (50)	192 (58.36)
Bachelor	53 (29.94)	72 (47.37)	125 (37.99)
Master	0 (0)	3 (1.97)	3 (0.91)
PhD	8 (4.52)	1 (0.66)	9 (2.74)
Semester/yearsb	0.5806
1st year student	85 (48.02)	82 (53.95)	167 (50.76)
2nd year student	61 (34.46)	42 (27.63)	103 (31.31)
3rd year student	29 (16.38)	26 (17.11)	55 (16.72)
4th year student	2 (1.13)	2 (1.32)	4 (1.22)
Living areaa	0.9642
City center/urban	74 (41.81)	63 (41.45)	137 (41.64)
City periphery/rural	97 (54.8)	83 (54.61)	180 (54.71)
Both	6 (3.39)	6 (3.95)	12 (3.65)
Employeda	0.3338
Full time	17 (9.6)	15 (9.87)	32 (9.73)
Employed—part time	14 (7.91)	6 (3.95)	20 (6.08)
Irregular employment	15 (8.47)	19 (12.5)	34 (10.33)
Not employed	131 (74.01)	112 (73.68)	243 (73.86)
Awareness: source of information, how you knew about solar PV waste and its implications
Social mediaa	0.2510
No	48 (27.12)	51 (33.55)	99 (30.09)
Yes	129 (72.88)	101 (66.45)	230 (69.91)
Textbook/formal educationa	0.0117 ∗
No	139 (78.53)	136 (89.47)	275 (83.59)
Yes	38 (21.47)	16 (10.53)	54 (16.41)
Interneta	0.0523
No	34 (19.21)	44 (28.95)	78 (23.71)
Yes	143 (80.79)	108 (71.05)	251 (76.29)
Newspaper/TV newsa	0.0014 ∗
No	127 (71.75)	132 (86.84)	259 (78.72)
Yes	50 (28.25)	20 (13.16)	70 (21.28)
Conferencea	0.3031
No	160 (90.4)	143 (94.08)	303 (92.1)
Yes	17 (9.6)	9 (5.92)	26 (7.9)
Awareness-building activity by government or societya	0.2694
No	150 (84.75)	136 (89.47)	286 (86.93)
Yes	27 (15.25)	16 (10.53)	43 (13.07)
Word of mouth by friends and familya	0.9947
No	156 (88.14)	133 (87.5)	289 (87.84)
Yes	21 (11.86)	19 (12.5)	40 (12.16)
Awareness: which is the strong way to build awareness about solar PV waste and its implications
Social mediaa	0.3997
No	17 (9.6)	20 (13.16)	37 (11.25)
Yes	160 (90.4)	132 (86.84)	292 (88.75)
Newspaper/TV newsa	0.0028 ∗
No	71 (40.11)	87 (57.24)	158 (48.02)
Yes	106 (59.89)	65 (42.76)	171 (51.98)
Conferencea	0.0486 ∗
No	119 (67.23)	118 (77.63)	237 (72.04)
Yes	58 (32.77)	34 (22.37)	92 (27.96)
Awareness eventsa	0.1224
No	97 (54.8)	97 (63.82)	194 (58.97)
Yes	80 (45.2)	55 (36.18)	135 (41.03)
Have you ever attended any workshops or webinars specifically discussing solar PV waste managementa	0.8232
Yes	14 (7.91)	14 (9.21)	28 (8.51)
No	163 (92.09)	138 (90.79)	301 (91.49)
Perceptiona	0.007 ∗
True	57 (32.2)	72 (47.37)	129 (39.21)
False	120 (67.8)	80 (52.63)	200 (60.79)

3.9. Bivariate Analysis: Attitude

Table 6 presents participants′ attitudes categorized as “positive” or “negative” across various demographic and awareness-related variables. The p values indicate the statistical significance of associations between each variable and attitude level. Significant associations were observed for several variables. Sex was significantly associated with attitude (p = 0.0051), with females showing more positive attitudes than males. Current study level was also significant (p = 0.0060); participants pursuing higher education (Bachelor′s, Master′s, and PhD) tended to have more positive attitudes than those in lower levels (diploma).

Table 6 Bivariate analysis: attitude.

Variables	Positive ( n = 196 )	Negative ( n = 133 )	Total ( n = 329 )	p value
Sexa	0.0051 ∗
Male	59 (30.1)	61 (45.86)	120 (36.47)
Female	137 (69.9)	72 (54.14)	209 (63.53)
Age groupa	0.0731
17–19 years	98 (50)	56 (42.11)	154 (46.81)
20–29 years	89 (45.41)	75 (56.39)	164 (49.85)
30+ years	9 (4.59)	2 (1.5)	11 (3.34)
Current study levelb	0.0060 ∗
Diploma	125 (63.78)	67 (50.38)	192 (58.36)
Bachelor	61 (31.12)	64 (48.12)	125 (37.99)
Master	3 (1.53)	0 (0)	3 (0.91)
PhD	7 (3.57)	2 (1.5)	9 (2.74)
Semester/yearsb	0.1829
1st year student	98 (50)	69 (51.88)	167 (50.76)
2nd year student	68 (34.69)	35 (26.32)	103 (31.31)
3rd year student	27 (13.78)	28 (21.05)	55 (16.72)
4th year student	3 (1.53)	1 (0.75)	4 (1.22)
Living areaa	0.0816
City center/urban	72 (36.73)	65 (48.87)	137 (41.64)
City periphery/rural	117 (59.69)	63 (47.37)	180 (54.71)
Both	7 (3.57)	5 (3.76)	12 (3.65)
Employeda	0.3300
Full time	15 (7.65)	17 (12.78)	32 (9.73)
Employed—part time	12 (6.12)	8 (6.02)	20 (6.08)
Irregular employment	18 (9.18)	16 (12.03)	34 (10.33)
Not employed	151 (77.04)	92 (69.17)	243 (73.86)
Awareness: source of information, how you knew about solar PV waste and its implications
Social mediaa	0.1125
No	52 (26.53)	47 (35.34)	99 (30.09)
Yes	144 (73.47)	86 (64.66)	230 (69.91)
Textbook/formal educationa	0.1891
No	159 (81.12)	116 (87.22)	275 (83.59)
Yes	37 (18.88)	17 (12.78)	54 (16.41)
Interneta	< 0.001 ∗
No	31 (15.82)	47 (35.34)	78 (23.71)
Yes	165 (84.18)	86 (64.66)	251 (76.29)
Newspaper/TV newsa	0.0157 ∗
No	145 (73.98)	114 (85.71)	259 (78.72)
Yes	51 (26.02)	19 (14.29)	70 (21.28)
Conferencea	0.0369 ∗
No	175 (89.29)	128 (96.24)	303 (92.1)
Yes	21 (10.71)	5 (3.76)	26 (7.9)
Awareness-building activity by government or societya	0.1956
No	166 (84.69)	120 (90.23)	286 (86.93)
Yes	30 (15.31)	13 (9.77)	43 (13.07)
Word of mouth by friends and familya	1
No	172 (87.76)	117 (87.97)	289 (87.84)
Yes	24 (12.24)	16 (12.03)	40 (12.16)
Awareness: which is the strong way to build awareness about solar PV waste and its implications
Social mediaa	< 0.001 ∗
No	11 (5.61)	26 (19.55)	37 (11.25)
Yes	185 (94.39)	107 (80.45)	292 (88.75)
Newspaper/TV newsa	0.001 ∗
No	79 (40.31)	79 (59.4)	158 (48.02)
Yes	117 (59.69)	54 (40.6)	171 (51.98)
Conferencea	0.3555
No	137 (69.9)	100 (75.19)	237 (72.04)
Yes	59 (30.1)	33 (24.81)	92 (27.96)
Awareness eventsa	0.1062
No	108 (55.1)	86 (64.66)	194 (58.97)
Yes	88 (44.9)	47 (35.34)	135 (41.03)
Have you ever attended any workshops or webinars specificallydiscussing solar PV waste managementa	0.3799
Yes	14 (7.14)	14 (10.53)	28 (8.51)
No	182 (92.86)	119 (89.47)	301 (91.49)
Perceptiona	< 0.001 ∗
True	47 (23.98)	82 (61.65)	129 (39.21)
False	149 (76.02)	51 (38.35)	200 (60.79)

Regarding sources of information, participants who obtained information from the Internet (p < 0.001) or newspapers/TV news (p = 0.0157) exhibited more positive attitudes. Awareness-building preferences were also related to attitude: those who considered social media (p < 0.001) and newspapers/TV news (p = 0.001) as strong tools for awareness tended to have more positive attitudes. Finally, perception showed a strong association with attitude (p < 0.001), as participants holding true perceptions about solar PV waste were more likely to have positive attitudes.

3.10. Bivariate Analysis: Practice

Table 7 presents participants′ practices categorized as “good” or “poor” across various demographic and awareness-related variables. The p values indicate the statistical significance of associations between each variable and practice level. Significant associations were found for living area, employment status, information source (newspaper/TV news), and perception. Participants living in urban areas were more likely to have good practices than those in rural areas (p = 0.0254). Part time employed participants demonstrated better practices than those not employed (p = 0.0301). Obtaining information from newspapers or TV news was also associated with better practices (p = 0.0096). In addition, participants with true perceptions of solar PV waste showed significantly better practices (p = 0.0183).

Table 7 Bivariate analysis: practice.

Variables	Good ( n = 213 )	Poor ( n = 116 )	Total ( n = 329 )	p value
Sexa	0.2489
Male	83 (38.97)	37 (31.9)	120 (36.47)
Female	130 (61.03)	79 (68.1)	209 (63.53)
Age groupa	0.1566
17–19 years	96 (45.07)	58 (50)	154 (46.81)
20–29 years	107 (50.23)	57 (49.14)	164 (49.85)
30+ years	10 (4.69)	1 (0.86)	11 (3.34)
Current study levelb	0.4049
Diploma	120 (56.34)	72 (62.07)	192 (58.36)
Bachelor	83 (38.97)	42 (36.21)	125 (37.99)
Master	2 (0.94)	1 (0.86)	3 (0.91)
PhD	8 (3.76)	1 (0.86)	9 (2.74)
Semester/yearsb	0.3613
1st year student	111 (52.11)	56 (48.28)	167 (50.76)
2nd year student	60 (28.17)	43 (37.07)	103 (31.31)
3rd year student	39 (18.31)	16 (13.79)	55 (16.72)
4th year student	3 (1.41)	1 (0.86)	4 (1.22)
Living areaa	0.0254 ∗
City center/urban	100 (46.95)	37 (31.9)	137 (41.64)
City periphery/rural	105 (49.3)	75 (64.66)	180 (54.71)
Both	8 (3.76)	4 (3.45)	12 (3.65)
Employeda	0.0301 ∗
Full time	20 (9.39)	12 (10.34)	32 (9.73)
Employed—part time	19 (8.92)	1 (0.86)	20 (6.08)
Irregular employment	23 (10.8)	11 (9.48)	34 (10.33)
Not employed	151 (70.89)	92 (79.31)	243 (73.86)
Awareness: source of information, how you knew about solar PV waste and its implications
Social mediaa	0.8812
No	63 (29.58)	36 (31.03)	99 (30.09)
Yes	150 (70.42)	80 (68.97)	230 (69.91)
Textbook/formal educationa	0.1573
No	173 (81.22)	102 (87.93)	275 (83.59)
Yes	40 (18.78)	14 (12.07)	54 (16.41)
Interneta	0.1750
No	45 (21.13)	33 (28.45)	78 (23.71)
Yes	168 (78.87)	83 (71.55)	251 (76.29)
Newspaper/TV newsa	0.0096 ∗
No	158 (74.18)	101 (87.07)	259 (78.72)
Yes	55 (25.82)	15 (12.93)	70 (21.28)
Conferencea	0.1168
No	192 (90.14)	111 (95.69)	303 (92.1)
Yes	21 (9.86)	5 (4.31)	26 (7.9)
Awareness-building activity by government or societya	0.9076
No	186 (87.32)	100 (86.21)	286 (86.93)
Yes	27 (12.68)	16 (13.79)	43 (13.07)
Word of mouth by friends and familya	0.6219
No	189 (88.73)	100 (86.21)	289 (87.84)
Yes	24 (11.27)	16 (13.79)	40 (12.16)
Awareness: which is the strong way to build awareness about solar PV waste and its implications
Social mediaa	0.8682
No	23 (10.8)	14 (12.07)	37 (11.25)
Yes	190 (89.2)	102 (87.93)	292 (88.75)
Newspaper/TV newsa	0.3812
No	98 (46.01)	60 (51.72)	158 (48.02)
Yes	115 (53.99)	56 (48.28)	171 (51.98)
Conferencea	0.4501
No	150 (70.42)	87 (75)	237 (72.04)
Yes	63 (29.58)	29 (25)	92 (27.96)
Awareness eventsa	1.000
No	126 (59.15)	68 (58.62)	194 (58.97)
Yes	87 (40.85)	48 (41.38)	135 (41.03)
Have you ever attended any workshops or webinars specifically discussing solar PV waste managementa	0.0706
Yes	23 (10.8)	5 (4.31)	28 (8.51)
No	190 (89.2)	111 (95.69)	301 (91.49)
Perceptiona	0.0183 ∗
True	94 (44.13)	35 (30.17)	129 (39.21)
False	119 (55.87)	81 (69.83)	200 (60.79)

3.11. Multivariate Analysis

Factors associated with knowledge about solar PV waste and its implications were analyzed using multiple logistic regression (Table 8). Regarding the source of information, individuals who learned about solar PV waste from newspapers or TV news had a significantly higher adjusted odds ratio (OR) of 1.99 (95% CI: 1.09–3.64; p = 0.025) compared to those who did not use these sources. Similarly, those who believed that newspapers or TV news are effective means of building awareness demonstrated a higher adjusted OR of 1.63 (95% CI: 1.03–2.59; p = 0.038) relative to those who did not share this belief. In terms of perception, individuals with false perceptions about Solar PV waste had an adjusted OR of 1.63 (95% CI: 1.03–2.58; p = 0.039) compared to those with accurate perceptions. These findings indicate that awareness through newspapers or TV news and certain misperceptions are significantly associated with increased knowledge about solar PV waste, highlighting the importance of media exposure and accurate perceptions in educational interventions.

Table 8 Factors associated with knowledge.

Factors	Crude OR (95% CI)	Adj. OR (95% CI)	p value
(Wald′s test)	(LR-test)
Awareness: source of information, how you knew about solar PV waste and its implications: newspaper/TV news	0.022 ∗
No (ref.)	1	1
Yes	2.6 (1.47, 4.61)	1.99 (1.09, 3.64)	0.025 ∗
Awareness: which is the strong way to build awareness about solar PV waste and its implications: newspaper/TV news	0.038 ∗
No (ref.)	1	1
Yes	2 (1.29, 3.10)	1.63 (1.03, 2.59)	0.038 ∗
Perception	0.039 ∗
True (ref.)	1	1
False	1.89 (1.21, 2.97)	1.63 (1.03, 2.58)	0.039 ∗

Factors associated with attitudes toward solar PV waste and its implications were analyzed using multiple logistic regression (Table 9). Regarding gender, females had a significantly higher adjusted OR of 1.96 (95% CI: 1.17–3.27; p = 0.010) compared to males. For the source of information, individuals who learned about Solar PV waste from conferences had a significantly higher adjusted OR of 2.61 (95% CI: 1.45–4.72; p = 0.001) compared to those who did not attend conferences. Those who believed that social media is a strong means of building awareness about solar PV waste had an adjusted OR of 2.52 (95% CI: 1.09–5.80; p = 0.030) compared to those who did not hold this belief. Finally, individuals with false perceptions about solar PV waste had a significantly higher adjusted OR of 4.72 (95% CI: 2.86–7.81; p < 0.001) compared to those with accurate perceptions. These findings indicate that gender, conference attendance, belief in the efficacy of social media, and false perceptions are significantly associated with attitudes toward solar PV waste.

Table 9 Factors associated with attitude.

Factors	Crude OR (95% CI)	Adj. OR (95% CI)	p value
(Wald′s test)	(LR-test)
Sex		0.010 ∗
Male (ref.)	1	1
Female	1.97 (1.24, 3.11)	1.96 (1.17, 3.27)	0.010 ∗
Awareness: source of information, how you knew about solar PV waste and its implications: conference		0.001 ∗
No (ref.)	1	1
Yes	2.91 (1.72, 4.91)	2.61 (1.45, 4.72)	0.001 ∗
Awareness: which is the strong way to build awareness about solar PV waste and its implications: social media		0.026 ∗
No (ref.)	1	1
Yes	4.09 (1.94, 8.6)	2.52 (1.09, 5.8)	0.030 ∗
Perception		< 0.001 ∗
True (ref.)	1	1
False	5.1 (3.16, 8.23)	4.72 (2.86, 7.81)	< 0.001 ∗

Factors associated with practices related to solar PV waste and its implications were analyzed using multiple logistic regression (Table 10). Regarding living area, individuals residing in city peripheries or rural areas had a significantly lower adjusted OR of 0.56 (95% CI: 0.34–0.93; p = 0.026) compared to those living in city centers or urban areas. In terms of employment status, part-time employees had a significantly higher adjusted OR of 15.32 (95% CI: 1.77–132.53; p = 0.013) compared to full-time employees. For awareness, individuals who learned about solar PV waste from newspapers or TV news had a significantly higher adjusted OR of 2.84 (95% CI: 1.48–5.45; p = 0.002) compared to those who did not. Regarding perception, individuals with false perceptions about solar PV waste had a significantly lower adjusted OR of 0.51 (95% CI: 0.30–0.85; p = 0.009) compared to those with accurate perceptions. These findings indicate that living area, employment status, awareness through newspapers or TV news, and accurate perceptions are significantly associated with practices related to solar PV waste.

Table 10 Factors associated with practice.

Factors	Crude OR (95% CI)	Adj. OR (95% CI)	p value
(Wald′s test)	(LR-test)
Living area		0.079
City center/urban	1	1
City periphery/rural	0.52 (0.32, 0.84)	0.56 (0.34, 0.93)	0.026 ∗
Both	0.74 (0.21, 2.60)	0.82 (0.23, 2.98)	0.766
Employed		0.005 ∗
Full time	1	1
Employed—part time	11.4 (1.35, 96.35)	15.32 (1.77, 132.53)	0.013 ∗
Irregular employment	1.25 (0.46, 3.46)	1.23 (0.42, 3.62)	0.705
Not employed	0.98 (0.46, 2.11)	1.18 (0.53, 2.65)	0.681
Awareness: source of information, how you knew about solar PV waste and its implications: newspaper/TV news		< 0.001 ∗
No	1	1
Yes	2.34 (1.26, 4.37)	2.84 (1.48, 5.45)	0.002 ∗
Perception		0.009 ∗
True (ref.)	1	1
False	0.55 (0.34, 0.88)	0.51 (0.30, 0.85)	0.01

4. Discussion

This study examined university students′ KAPP related to solar PV waste and its potential impact on human health. The results show good general awareness but clear gaps in technical knowledge and practical engagement. More than half of the respondents demonstrated good knowledge, especially about the need for proper disposal of solar PV waste and the risks of toxic substances leaking from damaged panels. Most participants were also aware that solar panels should be recycled at specialized facilities. However, many were less familiar with specific hazardous materials, such as silicon tetrachloride or cadmium telluride, and some underestimated the expected lifespan of solar systems. These gaps suggest that while broad awareness exists, technical knowledge about materials and long-term waste generation remains limited. Attitudes toward solar PV waste were largely positive. Respondents expressed concern about improper disposal and showed interest in learning more, and many supported policies such as paying a premium for panels with guaranteed recycling. Still, willingness to discuss waste issues with others was relatively low. This may reflect limited confidence or a lack of accessible information. Attitudes were strongly related to knowledge and perception, indicating that a better understanding of risks can help build stronger public support for responsible waste management. Perceptions also revealed mixed views. Many respondents did not believe that the public or local authorities are adequately prepared to handle the growing volume of solar PV waste. At the same time, some assume that solar PV waste is fully recyclable and poses little health risk, suggesting misunderstandings that may reduce caution in real-world situations. In addition, results also highlight the need for clearer communication on both the benefits and risks of solar technologies. Although participants understood the importance of safe disposal, few had taken part in recycling activities, facility visits, or awareness events. Knowledge and attitude scores were only weakly correlated with practices, showing that awareness does not automatically lead to action. Limited exposure to formal training and a lack of community-level opportunities may be contributing factors. Bivariate and regression analyses provided additional insights. Higher education levels, media exposure (especially newspapers and TV), and accurate perceptions were strongly linked with better knowledge. Positive attitudes were more common among females and among those who gained information through conferences and social media. For practices, urban residents and part time workers showed better engagement, while false perceptions were associated with poorer practices. These findings point to the role of access to information, environmental context, and perceived risk in shaping behavior. From an integrated perspective, the study shows that while young people are increasingly aware of solar PV waste issues, they need better access to technical information, practical guidance, and real opportunities to participate in recycling activities. Strengthening education programs, expanding community awareness events, and improving communication through trusted media channels could help close these gaps. As solar installations continue to grow, improving public understanding and practice will be essential for preventing health risks and ensuring sustainable waste management in the future.

4.1. Conclusion and Recommendation

This study emphasizes the importance for enhanced public knowledge and targeted educational initiatives on the health and environmental risks associated with solar PV waste. Although university students demonstrated a basic understanding of solar PV waste management, significant gaps persist in their knowledge of specific hazardous components, their health impacts, and proper management. To address these issues, we recommend the integration of solar PV waste topics into university curricula, especially within environmental, engineering, and public health programs. National awareness campaigns led by educational institutions, in collaboration with government agencies such as the Ministry of Environment and Forestry, can amplify outreach. Digital platforms, including social media and e-learning tools, should be leveraged to disseminate accurate information effectively.

Further recommendations include establishing pilot recycling programs in collaboration with local governments and the private sector, starting within academic institutions. Such initiatives would not only raise awareness but also create practical pathways for responsible solar PV waste management. Strengthened cooperation among educational institutions, decision-makers, and industries is essential to address this emerging environmental challenge and to support Indonesia′s sustainable energy transition.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Disclosure

Universitas Airlangga had no role in the design of the study; in the collection, analysis, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Conflicts of Interest

The authors declare no conflicts of interest.

Funding

This work was supported by the Universitas Airlangga under SATU Joint Research Scheme (JRS), 1619/UN3.LPPM/PT.01.03/2023.

Acknowledgments

We acknowledge Universitas Airlangga and SATU-JRS for the research opportunity.

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