https://ir.unisa.ac.za/handle/10500/2908 2026-06-19T21:31:23Z https://ir.unisa.ac.za/handle/10500/32573 Assessing the impact of landfill sites on soil and water quality in neighbouring communities : a case study of Ga-Rankuwa Township, Gauteng Province of South Africa Matlakala, Icaboth Tshwarelo Globally, solid waste generation is increasing due to accelerated population growth, rapid urbanisation, and economic activities. Consequently, the inadequate, absent, and poor planning and implementation of waste management in Ga-Rankuwa results in more waste in landfills. Although landfills carry a huge amount of waste, unmanaged waste can cause an increase in greenhouse gases, a reduction in the aesthetic of the environment, and untreated leachate pollutes surrounding water and soils, especially when proper procedures and maintenance are not followed. Regardless of how much research and awareness are done on this waste management method, environmental contamination is still evident due to inadequate/improper monitoring. The study aimed to assess the environmental impacts of the landfill site on soil and water quality in Ga-Rankuwa township. Soil samples were collected at the landfill perimeter in all 4 cardinal points and at 1 km and 2 km away from the 1st point, etcetera. Heavy metals, including Chromium, Mercury, and Lead, were assessed per sample for possible contamination by the landfill. Water samples were collected by directly dipping the containers in the nearby stream to collect water samples (upper river, mid river and lower river sections). The samples were taken to a laboratory for analysis, and further statistical tests and indices were used, and further analysis was conducted using XLSTAT. The water salinity and pollution indicators were assessed using pH, major cations (Na+, K+, Ca2+), phosphorus and heavy metals in soil and river samples near a landfill. Results showed significant variability in soil pH, with more acidic conditions closer to the landfill, likely due to leachate migration. Although heavy metal concentrations were elevated at certain sites, all values remained below WHO permissible limits and were classified as uncontaminated according to Müller's Geo-accumulation Index. River water showed slightly alkaline conditions, however, nutrient enrichment led to poor water quality. Trophic State Index (TSI) values for phosphorus exceeded 100 across all sites, classifying the river as hypereutrophic and identifying it as a pollution hotspot. While sodium values remained within acceptable limits for irrigation, microbial analysis revealed elevated amounts of E. coli and total coliforms downstream, indicating potential public health risks. It is recommended that landfill operators adopt advanced engineering solutions, such as state-of-the-art leachate collection and treatment systems, to minimise the release of harmful contaminants into adjacent soil and water bodies. Furthermore, the integration of waste segregation at source and comprehensive recycling programs should be prioritised to reduce the volume of non-biodegradable and hazardous waste entering landfills. vi 2025-11-28T00:00:00Z https://ir.unisa.ac.za/handle/10500/32572 LC–MS/MS profiling and machine learning–guided virtual screening of dual EGFR/HER2 inhibitors from Ceratonia siliqua L. pod extract for colorectal cancer Oku, Deli-Bright Nii Tettey Colorectal cancer (CRC), a malignancy that develops in the colon or rectum, is frequently associated with epidermal growth factor receptor (EGFR) overexpression, observed in up to 85% of cases, whereas human epidermal growth factor receptor 2 (HER2) amplification or overexpression is present in a smaller subset (approximately 2–6%, with increased prevalence in selected molecular subgroups). These molecular alterations highlight the therapeutic relevance of targeting EGFR and HER2 pathways in CRC management. Despite progress in targeted therapy development, most existing treatment approaches focus on inhibiting either EGFR or HER2 individually. These single-target therapies frequently demonstrate reduced efficacy because of alterations in downstream effectors such as the Kirsten rat sarcoma viral oncogene homolog (KRAS) and the activation of alternative signalling pathways that promote continued tumour growth. Consequently, designing therapeutic approaches that can concurrently block both EGFR and HER2 represents an essential and promising area of research. In this research, an innovative machine learning (ML)-driven stacking ensemble framework was established to accurately identify dual EGFR and HER2 inhibitors based on Simplified Molecular-Input Line-Entry System (SMILES) representations. A comprehensive benchmark dataset comprising active and inactive compounds targeting EGFR and HER2 was compiled from the ChEMBL database. Utilising this dataset, forty baseline models were developed and fine-tuned using various molecular descriptors and ML algorithms. The predictions from these models were then integrated through logistic regression (LR) to produce a highly reliable stacking ensemble classifier. This predictive model was further applied to natural bioactive compounds obtained from liquid chromatography–tandem mass spectrometry (LC–MS/MS) profiling of Ceratonia siliqua L. pod 9 extract, which were annotated using established spectral libraries and subsequently subjected to machine learning–guided virtual screening. The cytotoxic activity of the Ceratonia siliqua L. pod extract was confirmed experimentally using the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide) assay against human colorectal carcinoma cell line (HCT116) and non-cancerous Vero cells. The extract exhibited an IC₅₀ (half maximal inhibitory concentration) value of 13.32 ± 1.09 μg/mL in HCT116 cells, underscoring its notable anti-cancer potential. To support the experimental outcomes, molecular docking and in silico ADMET (absorption, distribution, metabolism, excretion, and toxicity) evaluations were carried out on the compounds identified from the LC–MS/MS dataset using the stacking model, alongside four Food and Drug Administration (FDA) approved anticancer drugs for comparative analysis. Among all screened molecules, NCGC00385704-01, identified from LC–MS/MS spectral data through library matching, exhibited strong dual inhibitory potential against both EGFR and HER2. Overall, this study highlights Ceratonia siliqua L. as a valuable source of potential lead molecules for colorectal cancer therapy through dual EGFR/HER2 inhibition and underscores the power of integrating computational and experimental approaches in natural product-based drug discovery. 2025-09-01T00:00:00Z https://ir.unisa.ac.za/handle/10500/32560 Potential value of community-based water monitoring in water resource protection decision-making in a developing country context: South Africa Nyamande, Tovhowani Brenda Over the past two decades, most developing countries, especially in Africa, have been transitioning towards water sector reform. While new water legislation in many African countries – as in South Africa – has included the environmental protection and the Polluter Pays Principle as priorities, it has given little attention to community involvement. South Africa faces many water-related challenges, the most significant being water quality deterioration, which requires constant monitoring. Water resource monitoring is essential for protecting water resources but presents challenges that constitute research gaps this study aimed to address. Key gaps include: the lack of policy support for community stakeholder participation in water resource monitoring; the exclusion of community data from water resource protection decision-making; poor integration of monitoring programmes and information sharing among different institutions; and uncertainty about the effectiveness of stakeholder engagement in reaching the intended objectives. As a result of the identified gaps, a main research question was formulated: What is the potential value of community-based water monitoring (CBWM) in water resource protection decision-making in a developing country context such as South Africa?. The main research question was informed by the five sub- questions: 1. What are the benefits, values, pitfalls, and challenges of CBWM programmes? 2. What criteria should be considered in CBWM in developing countries? 3. Based on the opinions of governance structures and the real-life experiences of communities, to what extent do the selected catchments in South Africa, as a developing country, benefit from CBWM? 4. What are the views of governance structures on the extent to which CBWM operates in South African communities? 5. How might a conceptual framework work by enhancing the use of CBWM data in decision making for developing countries? A case study research design utilising a mixed-methods research approach, incorporating both qualitative and quantitative methods, was followed to answer the research questions. The study integrated a literature review with primary data collection through three case studies. Data were gathered through interviews and a survey questionnaire. The study’s findings indicate that sustainable CBWM programmes promote community involvement in water monitoring while encouraging public ownership and trusteeship of water resources. However, the absence of appropriate guiding policy and CBWM-related challenges have hampered progress and prevented community data from contributing to decision-making. This study demonstrates the importance of a standardised protocol as a baseline for monitoring, managing data, ensuring value for money, and securing funding. The study highlighted the extent of catchments benefiting from CBWM initiatives as an early warning system and emphasised the importance of collaboration between different community governance structures for effective operation. A conceptual framework was developed for integrating CBWM data into the decision-making process to enhance the use of CBWM data for decision-making and to enhance sustainability and establish consistent information-sharing channels among relevant institutions. Engaging with the main research question yielded important insights into the role of CBWM data in decision-making. CBWM improves the capacity for monitoring water impacts, enabling more informed decisions through increased data availability. This helps bridge the gap between scientific knowledge and local community knowledge that traditional methods involving only professional scientists have overlooked. The integration of community data in water resource protection fosters a proactive management framework, allowing community members to identify potential water issues early and optimise resource allocation and protection. A key insight gained is that CBWM participation can guide both data collection and implementation of CBWM initiatives, ultimately promoting sustainable practices. This exploration underscores that CBWM not only enhances data collection, but also supports policy development and stakeholder engagement, thus filling critical gaps identified in both knowledge and practical applications within the field of sustainable water management; Kha mahumi mavhili a miṅwaha yo fhiraho, mashango a no khou bvelela, zwihulusa a dzhango ḽa Afurika, a khou shandukela kha tshanduko ya zwa maḓi. Musi milayo miswa kha mashango manzhi a dzhango ḽa Afurika, sa Afurika Tshipembe, yo katela na u tsireledza mupo na tshikafhadzo yawo i vhidzwaho “Polluter Pays Principle”, ya dovha hafhu ya katela zwiṱukuṱuku na u dzhenelela ha vhadzulapo. Afurika Tshipembe ḽi khou livhana na khaedu nnzhi dza maḓi, zwihulusa u kuna hao zwine zwa tea u dzula zwi tshi khou poswa iṱo. U ṱola zwiko zwa maḓi ndi zwa ndeme kha u tsireledza zwiko, fhedzi zwi na khaedu kana magake ane a ṱoḓa tsedzuluso ya zwine ngudo iyi ya khou ṱoḓa u bvisela khagala. Magake aya a ndeme a katela, u shaeya ha thikhedzo ya milayo kana mbekanyamaitele ya vhafaramikovhe vha tshitshavha kha u ṱhogomela zwiko zwa maḓi; u sa dzhielwa nṱha ha mawanwa a tshitshavha musi hu tshi dzhiiwa tsheo; u shaeya ha u ṱanganya mbekanyamushumo dza u ṱhogomela na u ṋekana zwidodombedzwa uya nga u fhambana ha madzangano na u sa shumisana ha vhafaramikovhe kha u swikelela zwipikwa. Nga nṱhani ha magake o waniwaho, ho bveledzwa mbudziso nthihi khulwane ya ṱhoḓuluso ‘Ndeme khulwane ya community-based water monitoring (CBWM) kha tsheo dza u tsireledza zwiko zwa maḓi kha shango li no khou bvelela sa shango la Afurika Tshipembe?’ Mbudziso khulwane nga ha thoduluso yo tutuwedzwa nga mbudziso thanu ṱhukhu dzine dza vha: 1. Ndi mbuelo, ndeme, khombo na khaedu dzifhio dza mbekanyamushumo dza CBWM? 2. Ndi nḓila dzifhio dzine dza fanela u tevhelwa kha CBWM kha mashango a no khou bvelela? 3. Zwo disendeka kha kuhumbulele kwa zwiko zwa mavhusele, na kuhumbulele kwa tshitshavha, ndi lini hune khuvhanganyo ya maḓi Afurika Tshipembe, sa shango ļi no khou bvelela ļa bindula u bva kha CBWM? 4. Ndi mbonalele ifhio uya nga ha zwiko zwa muvhuso zwine CBWM ya khou bveledzisa? 5. CBWM data I nga shumiswa hani kha u dzhiya tsheo kha mashango ane a khou bvelela? Ngudo ya tsumbo ya tsedzuluso ye ya shumisa tsedzuluso yo ṱanganelaho, yo katela tsedzuluso ya khwaļithethivi nay a khwanthithethivi ya tevhelwa nga u fhindula mbudziso dza tsedzuluso. Ngudo iyi yo shumisa nḓiļa ya ṱhoḓuluso yo ṱanganelanaho, yo katela tsedzuluso ya maṅwalwa and mawanwa o kuvhanganyiwaho kha ṱhoḓuluso tharu dza ngudo Mawanwa o wanala nga u ita nyambedzano na vhathu vho tou nangiwaho ha dovha hafhu ha netshedzwa dzinwe mbudziso. Mawanwa a tsedzuluso a sumbedza uri mbekanyamushumo dza CBWM dzi thusa tshitshavha kha u vha tshipiḓa na kha u lavhelesa kana tsireledzo ya maḓi, na u vha na vhuḓifhinduleli. Sa zwenezwo, u sa vha na milayo na khaedu dza CBWM zwi ita u ri hu sa vhe na mvelaphanḓa. Ngudo iyi I sumbedza ndeme ya u vha na ndaulo I ṱanganedzwaho nga nnyi na nnyi sa mutheo, u ri hu kone u vha na u londola kana u ṱhogomela, u ṱhogomela mawanwa (data), na u kona u vi wana ndambedzo ya masheleni. Ngudo yo bvisela khagala u ri CBWM I khou thusa tshitshavha u swika ngafhi ya dovha ya tsivhudza vhuṱhogwa ha u shumisana kha zwitshavha u ya nga u fhambana. Ho bveledzwa nḓila ya u dzhenisa mawanwa ya CBWM musi hu tshi dzhiiwa tsheo na u khwaṱhisa u ņekana nḓivho nga zwiimiswa uya nga u fhambana. Kha mbudziso khulwane ya ṱhoḓuluso, zwo bveledza u khwiņisea kha tshipida tsha u tsireledza zwiko zwa maḓi na u shumisa mawanwa a re hone. Mbuelo idzi dzi thusa u fhungudza magake vhukati ha nḓivho ya saintsi na ya vhadzulapo ya sialala. U ṱanganyisa mawanwa a vhadzulapo kha tsireledzo ya zwiko zwa maḓi zwi ṱuṱuwedza u shuma kana u langula, zwine zwa tendela vhadzulapo u kona u vhona zwi sa khou tshimbilaho zwavhuḓi na u kona u ņetshedza na u tsireledza maḓi. Mbuelo dzo wanwaho kha u shumisana na CBWM ndi u kona u sumba nḓila kha u kuvhanganya mawanwa na u sumbedza vhurangaphanḓa, zwine zwa ṱuṱuwedza tshumisano ya tshifhinga tshilapfu. Ṱhoḓulusa iyi I sumbedza vhuṱhogwa ha CBWM kha u ṱandavhudza ṱhoḓuluso na u kuvhanganya mawanwa na u tikedza kha u bveledza mbekanyamaitele na u katela vhafaramikovhe, zwine zwa vala gake vhukati ha nḓivho na nyito. Maipfi a ndeme: Tsedzuluso ya maḓi nga vhadzulapo, tsireledzo ya zwiko zwa maḓi. muangarane wa u dzhia tsheo, tshipirioni na vhupfiwa ha vhafaramikovhe, vhuṱhogwa ha u ṱola, u bindula na dzikhaudu kha vhadzulapo, ṱhanganyo ya mawanwa, Afurika Tshipembe.; Eka makume mambirhi ya malembe lama hundzeke, matiko yo tala lama hluvukaka, ngopfungopfu eAfrika, ya vile ya hundzukela eka mpfuxeto wa sekithara ya mati. Loko milawu leyintshwa ya mati ematikweni yo tala ya Afrika – tanihi le Afrika-Dzonga – yi katsa nsirhelelo wa mbango na Nsinya wa Nawu wa Nthyakiso wa Ntshikelelo tanihi swilo leswi rhangisaka emahlweni, wu nyikile nyingiso wutsongo eka ku nghenelela ka vaaki. Afrika-Dzonga ri langutane na mintlhontlho yo tala leyi fambelanaka na mati, leyi nga ya nkoka swinene i ku hohloka ka khwalithi ya mati, leswi lavaka ku vekiwa tihlo nkarhi hinkwawo. Ku vekiwa tihlo ka switirhisiwa swa mati i swa nkoka eka ku sirhelela switirhisiwa swa mati kambe swi tisa mintlhontlho leyi vumbeke swivandla swa ndzavisiso leswi ndzavisiso lowu a wu kongomisiwile ku swi lulamisa. Swivandla swa nkoka swi katsa: ku pfumaleka ka nseketelo wa pholisi eka ku nghenelela ka vakhomaxiave va vaaki eka ku vekiwa tihlo ka switirhisiwa swa mati; ku hlongoriwa ka datha ya vaaki eka ku tekiwa ka swiboho swa nsirhelelo wa switirhisiwa swa mati; ku hlanganisiwa loku nga riki kahle ka minongonoko yo veka tihlo na ku avelana mahungu exikarhi ka swivandla swo hambana; na ku nga tiyiseki mayelana na ku humelela ka ku nghenelela ka vakhomaxiave eku fikeleleni ka swikongomelo leswi kunguhatiweke. Hikwalaho ka swivandla leswi hlawuriweke, xivutiso lexikulu xa ndzavisiso xi vumbiwile ‘Hi wihi nkoka lowu nga vaka kona wa community-based water monitoring (CBWM) eka ku tekiwa ka swiboho swa nsirhelelo wa switirhisiwa swa mati eka xiyimo xa tiko leri hluvukaka ku fana na Afrika-Dzonga?’. Xivutisonkulu xa ndzavisiso xi tivisiwile hi swivutiso leswitsongo swa ntlhanu: 1. Hi yihi mimpfuno, mimpimanyeto, mintlhamu, na mintlhontlho ya minongonoko ya CBWM? 2. Hi swihi swipimelo leswi faneleke ku tekeriwa enhlokweni eka CBWM ematikweni lama hluvukaka? 3. Hi ku ya hi mavonelo ya swivumbeko swa vulawuri na mintokoto ya xiviri ya miganga, xana swihlovo leswi hlawuriweke eAfrika-Dzonga, tanihi tiko leri hluvukaka, swi vuyeriwa ku fikela kwihi eka CBWM? 4. Hi wahi mavonelo ya swivumbeko swa vulawuri eka mpimo lowu CBWM yi tirhaka ha wona eka miganga ya Afrika-Dzonga? 5. Xana rimba ra miehleketo ri nga tirha njhani hi ku ndlandlamuxa matirhiselo ya datha ya CBWM eka ku teka swiboho eka matiko lama hluvukaka? Dizayini ya ndzavisiso wa dyondzo ya xiyimo leyi tirhisaka endlelo ra ndzavisiso wa maendlelo yo hlangana, leyi katsaka maendlelo ya xiyimo na ya nhlayo, yi landzeriwile ku hlamula swivutiso swa ndzavisiso. Dyondzo yi hlanganisa nkambisiso wa matsalwa na nhlengeleto wa datha ya masungulo hi ku tirhisa tidyondzo tinharhu ta timhaka. Data yi hlengeletiwile hi ku tirhisa mimbulavurisano na ndzavisiso. Swikumiwa swa ndzavisiso swi kombisa leswaku minongonoko ya CBWM leyi nga ta tshama nkarhi wo leha yi tlakusa ku nghenelela ka vaaki eka ku vekiwa tihlo ka mati loko yi ri karhi yi hlohlotela vun’wini bya mfumo na vutshembeki bya switirhisiwa swa mati. Hambiswiritano, ku ix pfumaleka ka pholisi yo kongomisa leyi faneleke na mintlhontlho leyi fambelanaka na CBWM swi kavanyetile nhluvuko na ku sivela datha ya vaaki ku hoxa xandla eka ku teka swiboho. Dyondzo leyi yi kombisa nkoka wa phurotokholo leyi ringaniseriweke tanihi masungulo yo veka tihlo, ku lawula datha, ku tiyisisa nkoka wa mali, na ku kuma mali. Dyondzo yi kombisile mpimo wa swihlovo leswi vuyeriwaka eka migingiriko ya CBWM tanihi sisiteme ya xitsundzuxo xa le mahlweni naswona yi kandziyisile nkoka wa ntirhisano exikarhi ka swivumbeko swo hambana swa vulawuri bya vaaki ku endlela matirhelo lama humelelaka. Rimba ra miehleketo ri tumbuluxiwile ro hlanganisa datha ya CBWM eka phurosese yo teka swiboho ku ndlandlamuxa matirhiselo ya datha ya CBWM ku teka swiboho na ku ndlandlamuxa ku kondletela na ku simeka tindlela leti nga cincekiki to avelana mahungu exikarhi ka swivandla leswi faneleke. Ku nghenelela na xivutiso xa ndzavisiso, swi humesile vutivi bya nkoka lebyi ndlandlamuxaka ku twisisa ntirho wa datha ya CBWM eka ku teka swiboho. CBWM yi antswisa vuswikoti byo langutisisa ku khumbeka ka mati, ku endla leswaku ku va na swiboho leswi nga na vutivi byo tala hi ku engetela ku kumeka ka datha. Leswi swi pfuneta ku hlanganisa xivandla exikarhi ka vutivi bya sayense na vutivi bya vaaki va ndhawu lebyi tindlela ta ndhavuko to katsa vativi va sayense va xiphurofexinali ntsena ti honiseke. Ku hlanganisiwa ka datha ya vaaki eka nsirhelelo wa switirhisiwa swa mati swi kurisa rimba ra vulawuri lebyi nga na vuxiyaxiya, ku pfumelela swirho swa vaaki ku kuma timhaka leti nga vaka kona ta mati ka ha ri na nkarhi na ku antswisa avelo na nsirhelelo wa switirhisiwa. Vutivi bya nkoka lebyi kumiweke hileswaku ku nghenelela ka CBWM ku nga kongomisa havumbirhi bya nhlengeleto wa datha na ku tirhisiwa ka migingiriko ya CBWM, eku heteleleni ku tlakusa maendlelo lama nga ta tshama nkarhi wo leha. Ku lavisisa loku ku kandziyisa leswaku CBWM a yi ndlandlamuxi ntsena nhlengeleto wa datha, kambe yi tlhela yi seketela nhluvukiso wa pholisi na ku nghenelela ka vakhomaxiave, xisweswo yi tata swivandla swa nkoka leswi hlawuriweke eka vutivi na matirhiselo lama tirhaka endzeni ka xiyenge xa vulawuri bya mati lebyi nga heriki. Marito ya nkoka: Ku vekiwa tihlo ka mati loku simekiweke eka vaaki, nsirhelelo wa switirhisiwa swa mati, ku teka swiboho, rimba ra miehleketo, mavonelo na ntokoto wa vakhomaxiave, not yak u hlawuleka, mabindza na mintlhontlho ya nhlayo, hlanganiso, Afrika-Dzonga Abstract in English with Venda and Tsonga translations 2026-03-01T00:00:00Z https://ir.unisa.ac.za/handle/10500/32555 Assessing the degree of pollution of groundwater by heavy metals in and around Kolomela Mine, Northern Cape Province Tsele, Goitseone Precious This study has assessed the extent of heavy metal contamination in groundwater around the Kolomela iron ore mine in the Northern Cape Province of South Africa. A case study research design was employed, focusing on four existing groundwater monitoring boreholes (BH1–BH4) located in and around the mine. Groundwater samples were collected repeatedly over an eight-month period, thus covering different seasonal conditions to capture temporal variability or similarity in metal concentrations. Sampling followed standardised groundwater collection procedures, and laboratory analyses were conducted to determine concentrations of selected heavy metals, including Lead (Pb), Calcium (Ca), Copper (Cu), Chromium (Cr); Manganese (Mn); Nickel (Ni), Thallium (Tl); and Zinc (Zn). The data were analysed in the laboratory by means of Inductively Coupled Plasma–Optical Emission Spectroscopy and their patterns and trends were summarised by the use of descriptive statistical methods. The results were evaluated against South African drinking water standards (SANS 241) and World Health Organization (WHO) guideline values to assess groundwater quality. The results revealed a spatially and seasonally heterogeneous distribution of heavy metals across the monitored boreholes. While several metal concentrations remained within acceptable limits, elevated levels of certain metals were observed at specific boreholes and sampling periods, thus exceeding recommended guideline values and indicating potential risks to groundwater quality. These findings demonstrate that groundwater quality in mining environments may vary significantly over space and time, even within a single mining operation. The study highlights the need for improved groundwater management and regulatory oversight at Kolomela Mine, particularly in semi-arid regions where communities rely heavily on groundwater as a primary water source. The research indicates the importance of routine groundwater monitoring, adherence to national water quality standards, and transparent reporting of water quality data to regulatory authorities and affected communities. Thus, the findings provide an empirical basis to support evidence-based mine water management and policy implementation aimed at protecting groundwater resources and safeguarding environmental and public health in South Africa’s mining sector. 2026-05-01T00:00:00Z