The interaction and the interplay of climate change with oil palm production in the Southeast Asia region are of serious concern. This particularly applies in Malaysia due to its rank as the second largest palm oil producer in the world. The anthropogenic activities and the agroecological practices in oil palm plantation, including excessive use of fertilisers, bush fire due to land clearing, and cultivation on peatland, have exacerbated the effects of climate change featuring extreme events, drought, flooding, heatwave, as well as infestation of pest and diseases. These adverse impacts on oil palm production highlight the significance of deploying effective adaptation strategies. The study aims to examine the impact of climate change on oil palm production and identify the farmers' adaptation strategies to the impacts of climate change in Malaysia. This study was conducted a comprehensive review of the articles published from 2000 to 2021 in the contexts of climate change and oil palm production in Malaysia. The review shows that climate change has a range of impacts on the oil palm production in Malaysia. As a result, several adaptation options were identified, such as breeding of hybrid varieties that are tolerant and resistant to heat; sustainable management of soil; pit and tranches to enhance water management in plantation areas; minimal use of fertilisers, herbicides, and pesticides; zero burning; and minimum tillage. The reviewed studies recommended the following to mitigate the adverse impacts of climate change: sustainable national policy on climate change, conservation of the existing carbon stock, effective management of tropical rainforest biodiversity, afforestation for carbon sequestration, and reduction in greenhouse gas (GHG) emission.
Improper treatment during recycling of e-waste materials by means of open burning is on the rise which has led to an increase in air pollution. This study looked at heavy metal concentrations, concentrations in relation to threshold values, and assessments of risk for noncarcinogenic and cancer risk threat. The Microwave Plasma-Atomic Emission Spectrometry (MP-AES 4210) series instrument of Agilent Technology, United States of America (USA), was used in analyzing heavy metal (Cd, Cu, and Pb) concentrations. The result of the analysis of the Kuka Bulukiya treatment point revealed that Pb has the highest mean concentration of 0.0693 ppm, Cu 0.0525 parts per million (PPM), and Cd 0.0042 ppm. The mean concentration at PRP Gidan Ruwa for Cd was found to be 0.0059 ppm, Cu 0.0363 ppm, and Pb 0.049 ppm. The result of the adult and children population calculated shows that the hazard quotient (HQ) and hazard index (HI) values are not up to 1 in all the pathways (inhalation, ingestion, and dermal) at both treatment points (1.2 ˟ 10-4 and 9.8 ˟ 10-5) and (6.4 ˟ 10-4 and 5.9 ˟ 10-4), respectively. The cancer risk for Kuka Bulukiya 6 ˟ 10-10 and PRP G/Ruwa 5 ˟ 10-10 for adults and 7 ˟ 10-10 and 4 ˟ 10-10 for children were both lower than the threshold set for cancer risk by the United States Environmental Protection Agency (USEPA). This meant that both adults and children were not at risk of cancer and noncarcinogenic threat based on the assessment in this study. The study concluded that informal e-waste burning has substantially helped in the relatively high levels of air pollution identified in the treatment points and in turn posed environmental and public health concerns to people around the area. This study recommends that samples of the vegetable products at the PRP G/Ruwa treatment point should be investigated immediately and adequate restrictions and regulations should be enacted and enforced in order to safeguard the environment and the populace. There is need for caution from the authorities to avert the possible implications (e-waste extractors and the public) of being affected with noncarcinogenic or carcinogenic ailments over time.
This study aimed at determining the presence and characterization of Escherichia coli and Shiga toxin-producing E. coli (STEC) from imported frozen beef meats. Seventy-four (74) frozen imported beef meat samples from two countries, India (42 samples) and Australia (32 samples), were collected and tested for E. coli. These samples were purchased from the frozen meat sections of five different supermarkets in different locations in Selangor, Malaysia, from April 2012 to October 2014. A total of 222 E. coli strains were isolated from the meat samples; 126 strains were isolated from country A (India), and 96 E. coli strains were from country of origin B (Australia), respectively. A total of 70 E. coli strains were identified and characterized. All E. coli strains were isolated into Fluorocult medium and identified using API 20E kit. All selected E. coli strains were characterized for Shiga toxin genes (stx1 and stx2). All biochemically identified E. coli in this study were further subjected to molecular detection through polymerase chain reaction (PCR) amplification and characterization using 16S ribosomal RNA (rRNA) gene of Shiga toxin-producing E. coli. Of the 70 E. coli strains, 11 strains were positive for both Shiga toxin genes (stx1 and stx2) and 11 (11/70) strains were positive for stx1 gene, while 25 (25/70) strains were positive for stx2 gene. The analysis of 16S rRNA gene of all the E. coli isolates in this study was successfully sequenced and analyzed, and based on sequence data obtained, a phylogenetic tree of the 16S rRNA gene was performed using Clustal W programme in MEGA 6.06 software. Phylogenetic tree showed that the E. coli isolates in our study cluster with the strain of E. coli isolated in other countries, which further confirm that the isolates of E. coli in this study are similar to those obtained in other studies. As a result, all the strains obtained in this study proved to be a strain of pathogenic E. coli, which may cause a serious outbreak of food-borne disease. The isolation of pathogenic E. coli strains from the imported meat samples calls for prudent management of imported meats by the relevant authorities.
This paper presents the global research landscape and scientific progress on occupant thermal comfort in naturally ventilated buildings (OTC-NVB). Despite the growing interest in the area, comprehensive papers on the current status and future developments on the topic are currently lacking. Hence, the publication trends, bibliometric analysis, and systematic literature review of the published documents on OTC-NVB were examined. The search query "Thermal Comfort" AND "Natural Ventilation" AND "Buildings" was designed and executed to recover related documents on the topic from the Elsevier Scopus database. Results showed that 976 documents (comprising articles, conference papers, reviews, etc.) were published on the topic from 1995 to 2021. Further analysis showed that 97.34% of the publications were published in the English language. Richard J.de Dear (University of Sydney, Australia) is the most prolific researcher on OTC-NVB research, while Energy and Buildings has the highest publications. Bibliometric analysis showed high publications, citations, keywords, and co-authorships among researchers, whereas the most occurrent keywords are ventilation, natural ventilation, thermal comfort, buildings, and air conditioning. Systematic literature review demonstrated that OTC-NVB research has progressed significantly from empirical to computer-based studies involving complex mathematical equations, programs, or software like artificial neural networks (ANN) and computational fluid dynamics (CFD). In general, OTC-NVB research findings indicate that physiological, social, and environmental factors considerably influence OTC in NVBs. Future studies will likely employ artificial intelligence or building performance simulation (BPS) tools to examine relationships between OTC and indoor air/environmental quality, human behavior, novel clothing, or building materials in NVBs.
Leachate is one of the main surface water pollution sources in Selangor State (SS), Malaysia. The prediction of leachate amounts is elementary in sustainable waste management and leachate treatment processes, before discharging to surrounding environment. In developing countries, the accurate evaluation of leachate generation rates has often considered a challenge due to the lack of reliable data and high measurement costs. Leachate generation is related to several factors, including meteorological data, waste generation rates, and landfill design conditions. The high variations in these factors lead to complicating leachate modeling processes. This study aims at identifying the key elements contributing to leachate production and developing various AI-based models to predict leachate generation rates. These models included Artificial Neural Network (ANN)-Multi-linear perceptron (MLP) with single and double hidden layers, and support vector machine (SVM) regression time series algorithms. Various performance measures were applied to evaluate the developed model's accuracy. In this study, input optimization process showed that three inputs were acceptable for modeling the leachate generation rates, namely dumped waste quantity, rainfall level, and emanated gases. The initial performance analysis showed that ANN-MLP2 model-which applies two hidden layers-achieved the best performance, then followed by ANN-MLP1 model-which applies one hidden layer and three inputs-while SVM model gave the lowest performance. Ranges and frequency of relative error (RE%) also demonstrate that ANN-MLP models outperformed SVM models. Furthermore, low and peak flow criterion (LFC and PFC) assessment of leachate inflow values in ANN-MLP model with two hidden layers made more accurate values than other models. Since minimizing data collection and processing efforts as well as minimizing modeling complexity are critical in the hydrological modeling process, the applied input optimization process and the developed models in this study were able to provide a good performance in the modeling of leachate generation efficiently.
The present work analyzes the effect of antioxidants on engine combustion performance of a multi-cylinder diesel engine fueled with PB30 and PB50 (30 and 50 vol.% palm biodiesel (PB)). Four antioxidants namely N,N'-diphenyl-1,4-phenylenediamine (DPPD), N-phenyl-1,4-phenylenediamine (NPPD), 2(3)-tert-Butyl-4-methoxyphenol (BHA), and 2-tert-butylbenzene-1,4-diol (TBHQ) were added at concentrations of 1000 and 2000 ppm to PB30 and PB50. TBHQ showed the highest activity in increasing oxidation stability in both PB30 and PB50 followed by BHA, DPPD, and NPPD respectively, without any negative effect on physical properties. Compared to diesel fuel, PB blends showed 4.61-6.45% lower brake power (BP), 5.90-8.69% higher brake specific fuel consumption (BSFC), 9.64-11.43% higher maximum in cylinder pressure, and 7.76-12.51% higher NO emissions. Carbon monoxide (CO), hydrocarbon (HC), and smoke opacity were reduced by 36.78-43.56%, 44.12-58.21%, and 42.59-63.94%, respectively, than diesel fuel. The start of combustion angles (SOC) of PB blends was - 13.2 to - 15.6 °CA BTDC, but the combustion delays were 5.4-7.8 °CA short compared to diesel fuel which were - 10 °CA BTDC and 11°CA respectively. Antioxidant fuels of PB showed higher BP (1.81-5.32%), CO (8.41-24.60%), and HC (13.51-37.35%) with lower BSFC (1.67-7.68%), NO (4.32-11.53%), maximum in cylinder pressure (2.33-4.91%) and peak heat release rates (HRR) (3.25-11.41%) than baseline fuel of PB. Similar SOC of - 13 to - 14 °CA BTDC was observed for PB blended fuels and antioxidants. It can be concluded that antioxidants' addition is effective in increasing the oxidation stability and in controlling the NOx emissions of palm biodiesel fuelled diesel engine.
In the face of mounting climate change challenges, reducing emissions has emerged as a key driver of environmental sustainability and sustainable growth. Despite the fact that research has been conducted on the environmental Kuznets curve (EKC), few researchers have analyzed this in the light of economic complexity. Thus, the current research assesses the effect of economic complexity on CO2 emissions in the MINT nations while taking into account the role of financial development, economic growth, and energy consumption for the period between 1990 and 2018. Using the novel method of moments quantile regression (MMQR) with fixed effects, an inverted U-shape interrelationship is found between economic growth and CO2 emissions, thus validating the EKC hypothesis. Energy consumption and economic complexity increase CO2 emissions significantly from the 1st to 9th quantiles. Furthermore, there is no significant interconnection between financial development and CO2 emissions across all quantiles (1st to 9th). The outcomes of the causality test reveal a feedback causal connection between economic growth and CO2, while a unidirectional causality is established from economic complexity and energy use to CO2 emissions in the MINT nations. Based on the findings, we believe that governments should stimulate the financial sector to provide domestic credit facilities to industrialists, investors, and other business enterprises on more favorable terms so that innovative technologies for environmental protection can be implemented with other policy recommendations.
Since the inception of global industrialization, the growth of steroid estrogens becomes a matter of emerging serious concern for the rapid population. Steroidal estrogens are potent endocrine-upsetting chemicals that are excreted naturally by vertebrates (e.g., humans and fish) and can enter natural waters through the discharge of treated and raw sewage. Steroidal estrogens in plants may enter the food web and become a serious threat to human health. We evaluated the uptake and accumulation of ethinylestradiol (EE2) and 17β-estradiol (17β-E2) in lettuce plants (Lactuca sativa) grown under controlled environmental condition over 21 days growth period. An effective analytical method based on ultrasonic liquid extraction (ULE) for solid samples and solid phase extraction (SPE) for liquid samples with gas chromatography-mass spectrometry (GC/MS) has been developed to determine the steroid estrogens in lettuce plants. The extent of uptake and accumulation was observed in a dose-dependent manner and roots were major organs for estrogen deposition. Unlike the 17β-E2, EE2 was less accumulated and translocated from root to leaves. For 17β-E2, the distribution in lettuce was primarily to roots after the second week (13%), whereas in leaves it was (10%) over the entire study period. The distribution of EE2 at 2000 μg L-1 in roots and leaves was very low (3.07% and 0.54%) during the first week and then was highest (12% in roots and 8% in leaves) in last week. Bioaccumulation factor values of 17β-E2 and EE2 in roots were 0.33 and 0.29 at 50 μg L-1 concentration as maximum values were found at 50 μg L-1 rather than 500 and 2000 in all observed plant tissues. Similar trend was noticed in roots than leaves for bioconcentration factor as the highest bioconcentration values were observed at 50 μg L-1 concentration instead of 500 and 2000 μg L-1 spiked concentration. These findings mainly indicate the potential for uptake and bioaccumulation of estrogens in lettuce plants. Overall, the estrogen contents in lettuce were compared to the FAO/WHO recommended toxic level and were found to be higher than the toxic level which is of serious concern to the public health. This analytical procedure may aid in future studies on risks associated with uptake of endocrine-disrupting chemicals in lettuce plants.
With the rising concern about climate change, there has been an increased public awareness that has resulted in new government policies to support scientific research for mitigating these problems. Malaysia is among the major energy-intense countries and is under an excessive burden to advance its energy efficiency and to also work towards the reduction of its carbon emission. Plug-in hybrid electric vehicles (PHEVs) have the potential to lessen the carbon emission and gasoline consumption in order to alleviate environmental problems. Most of the energy problems linked to the increasing transportation pollution are now being reduced with the solution of the adoption of PHEVs. PHEVs are seen as a solution to cut carbon emission, which prevents environmental damages. Furthermore, PHEVs' driving range and performance can be comparable to the other hybrid vehicles as well as the conventional IC engines that have gasoline and diesel tanks. Thus, many efforts are being initiated to promote the use of PHEVs as an innovative and affordable transportation system. In order to achieve making the consumers aware of the adoption of PHEVs, we used a model which is based on the extended theory of planned behavior (TPB). This review is based on the factors affecting the adoption of PHEVs among Malaysian consumers. The model takes into account the ten key features that influence the adoption of PHEVs, such as environmental concern, personal norm, attitude, vehicle ownership costs, driving range, charging time, intention, subjective norm, perceived behavioral control, and personal norm. All these constructs are drivers towards the adoption of PHEVs. These factors affect the relationship between the adoption of PHEVs and how consumers intend to protect the environment. This review is based on improving how the "attitude-action" gap is understood as it is an important element for further studies on PHEVs. The aim of the research is to come up with a framework that examines how to modify the consumer's environmental concerns in acquiring PHEVs. This will pave the way for more academic research and future works that can emphasize how to obtain empirical results. The authors' recommendation is that, before a consumer's behavior is assessed and considered, an observation of the current technology is needed with methods and knowledge of the existing technology adoption aspect.
One of the innovations introduced toward tackling the heightening of environmental impact is green technology. In the agricultural industry, the implementation of green fertilizer technology (GFT) for the modern development of environmentally friendly technology is a necessity. Within the Malaysian agriculture sector, the GFT application is needed to increase production levels among all crops. One of the essential commodities of all crops has always been paddy, given its status as the staple food among the country's population. Paddy production with the adoption of GFT potentially opens the path toward sustainable development in the industry as well as it also provides the food safety aspect. Moreover, this helps farmers to improve their productivity on paddy production in Malaysia. This paper attempts to evaluate the contributing socio-psychological factors, innovation attributes of environmental factors, and channels of communication to decision-making among farmers in Malaysia on GFT. Furthermore, this research also aims to assess the moderating role of cost between the farmer's behavioral intention and the adoption of GFT. The sampling process followed the stratified sampling technique-overall, 600 survey questionnaires were dispersed and 437 effective responses were received. The structural analysis results obtained have revealed significant positive effect for perceived awareness, attitude, group norm, perceived behavioral control, environmental concern, agro-environmental regulations, relative advantage, compatibility, trialability, and observability, and on farmer's behavioral intention, a significant effect for paddy farmer's behavioral intention in order to adopt of GFT. Further, the interaction effects of cost on the link between farmer's behavioral intention and adoption of GFT are statistically significant. Though, the finding could not back an outcome for the subjective norm, complexity, and mass media on farmer's behavioral intention. Finally, critical outcomes obtained in this research contribute to deepening the thoughtfulness of paddy farmers' adoption of GFT. This study concludes with policy recommendations and future directions of the research.
A new commercial cationic polyelectrolyte chitosan (CM), obtained from the waste of mushroom production, was examined using models of water and wastewater namely kaolin and palm oil mill effluent (pome). As it is biocompatible, widely available, and economically feasible, chitosan mushroom has high potential to be a suitable replacement for alum. Also, it can be a promising alternative to chitosan obtained traditionally from Crustaceans due to its higher zeta potential and homogeneity based on the raw material required for its production. A wide range of coagulant dose (5-60 mg l(-1)) and wastewater pH (2-12) were taken into account to find the optimal conditions of coagulation. The optimal doses are 10 and 20 mg l(-1) at best pH (11 and 3) when treated with kaolin and palm oil mill effluent, respectively, while 1200 mg l(-1) of alum was not enough to reach the efficiency of chitosan mushroom. On the other hand, the optimum dose of chitosan mushroom (20 mg l(-1)) at pH 3 of pome produced (75, 73, and 98%) removal of chemical oxygen demand (COD), biological oxygen demand (BOD), and total suspended solids (TSS), respectively. The significant potential of chitosan mushroom was proved by zeta potential measurement. Indeed, it possesses the highest zeta potential (+70 mV) as compared to the traditional chitosan produced from crustaceans. In short, chitosan mushroom as a biocoagulant is eco-friendly and it enhances water quality that meets the requirements of environmental conservatives.
Several multi-walled carbon nanotubes supported Ni-Ce catalysts were synthesized, and their performance in carbon dioxide reforming of methane (CDRM) for syngas production was evaluated. The attachment of Ni-Ce nanoparticles to the functionalized carbon nanotube (fCNT) support was carried out using four synthesis routes, i.e., impregnation (I), sol-gel (S), co-precipitation (C), and hydrothermal (H) methods. Results indicated that synthesis method influences the properties of the NiCe/fCNT catalysts in terms of homogeneity of metal dispersion, size of crystallites, and metal-support interaction. The activity of the catalysts followed the order of NiCe/fCNT(H) > NiCe/fCNT(S) > NiCe/fCNT(C) > NiCe/fCNT(I). The NiCe/fCNT(H) catalyst exhibited the highest catalytic activity with CH4 and CO2 conversions of 92 and 96%, respectively, and resulted in syngas product with consistent H2/CO ratio of 0.91 at reaction temperature of 800 °C without notable deactivation up to 30 h of reaction. Moreover, the growth of carbon on the spent catalyst was only 2% with deposition rate of 4.08 mg/gcat·h; this was plausibly due to the well-dispersed distribution of nanoparticles on fCNT surface and abundant presence of oxygenated groups on the catalyst surface.
Mining activities are responsible for the elevated input levels of suspended sediment and hazardous metals into the riverine ecosystem. These have been shown to threaten the riverine fish populations and can even lead to localized population extinction. To date, research on the effects of mining activities on fish has been focused within metal contamination and bioaccumulation and its threat to human consumption, neglecting the effects of suspended sediment. This paper reviews the effects of suspended sediment and metal pollution on riverine ecosystem and fish population by examining the possibilities of genetic changes and population extinction. In addition, possible assessments and studies of the riverine fish population are discussed to cope with the risks from mining activities and fish population declines.
The focus of this study is to analyze the level of knowledge, awareness, and attitude toward plastic waste and to distinguish the key drivers that encourage the households in Kuala Lumpur, Malaysia, to participate in "No plastic campaign," This study used the logistic regression model to explain the factors that may affect the willingness to participate (WTP) of households in the campaign. In this study, it is found that 35 % of households are willing to participate in the campaign. The results of the study also indicate that people who are more informed and more convinced of their knowledge have a more positive attitude toward recycling than their counterparts do. Furthermore, this study provides additional evidence of the level and classification of importance of motivating factors for plastic recycling, using the modified average and coefficient of variation of the models. From the analysis, the factor "helps reduce landfill use" is found as the most important factor and the factor of "raising money for charity" is found as the least important factor that motivates households to participate in recycling. The determinations of the study suggest some strategies that could hold implications for government and households to boost them to participate in the campaign "No Plastic Bag."
This paper examines whether attitudes towards electric vehicles (ATEVs), subjective norms (SNs) and perceived behavioural control (PBC) have significant associations with consumer purchase intention (PI) and the purchase behaviour of environmentally friendly vehicles (EFVs). The results from the survey questionnaires are analysed using confirmatory factor analysis (CFA) and structural equation modelling (SEM). The findings of this paper indicate that ATEV, SN and PBC significantly influence PI. This finding also indicates that environmental consequence and individual preferences do not influence the PI of the respondents. We found that Malaysian car owners are largely unaware of the greenhouse effects on the environment or attach to it little importance, which is reflected in their PI towards EFVs. The outcomes of this study could help policymakers design programmes to influence attitudes, subjective norms, perceived behavioural control and purchase behaviour to prevent further air pollution and reduce CO2 emissions from the transportation sector.
The purpose of this paper is to investigate the links between renewable energy (RE), non-renewable energy (NRE), capital, labour and economic growth, using the nonlinear autoregressive distributive lag (NARDL) model in Malaysia for the period of 1980-2018. The results of NARDL confirm the asymmetric effect of RE and NRE consumption on the economic growth in the long run as well as the short run in Malaysia. The findings also show that in the long and short run, positive shocks of NRE are greater than the positive shocks of RE. It indicates that Malaysia's economic growth is highly dependent on NRE which is not a good indication as NRE consumption increases carbon dioxide (CO2) emission in the country. Moreover, the empirical results of this study demonstrated that RE consumption reduction accelerates economic growth, whereas NRE consumption reduction decreases economic growth. It can have claimed that in Malaysia, RE is still more expensive than NRE. In conclusion, this study offered a variety of measures to develop RE to reduce the dependency on NRE consumption.
Environmental sustainability is an umbrella approach depending on various climatic and economic policies. In doing so, the current study empirically evaluates the role of green finance, eco-innovation, and environmental policy stringency on the ecological footprint in China. To meet the objectives, the novel quantile autoregressive distributed lag (QARDL) approach was employed from 2000 to 2017. The outcomes reveal heterogeneous associations between the proposed variables. Manifestly, the QARDL estimation results demonstrate a positive impact between eco-innovation, green finance, and environmental policy stringency with the ecological footprints of China; however, the extent of the relationship is quantile dependent. The outcomes are further validated through the Wald test of parameter constancy. The bi-direction causality is observed among all variables at several quantiles. The current study offers policymakers helpful suggestions on enhancing the positive effects of environmentally supported innovation, green finance, and stringent environmental policies on the ecosystem.
Given the significance of fostering sustainable climate conditions for long-term economic stability and financial resilience, this study probes the connection between climate-related policy ambiguity and its implications for currency valuation. In doing so, the current study investigates the interconnected effects of climate policy on economic policy uncertainty and geopolitical risk with the currency valuation in ASEAN countries. Employing wavelet coherence analysis and partial wavelet coherence analysis, the paper highlights the complex relationships among these factors and their implications for exchange rate fluctuations. Using data from 2000 to 2022, the findings reveal that climate policy uncertainty is an important driver of exchange rate movements, amplifying the impact of economic policy uncertainty and geopolitical risk. Furthermore, the study identifies a vicious cycle between climate policy uncertainty and exchange rates, potentially impacting the region's macroeconomic stability and long-term economic growth. The study presents several policy recommendations to address economic and climate policy uncertainties comprehensively based on the findings. These recommendations include establishing national frameworks for climate risk management, enhancing policy credibility and macroeconomic stability, and promoting regional integration to mitigate the influence of geopolitical risk on exchange rates.
Energy is one of the prime factors in influencing the sustainable development of a country. Different energy sources play important roles in driving the income growth of different economic sectors such as industrial, agricultural, and services. Fossil fuels, however, have come under strong criticism for actively accelerating climate change. As such, it is imperative to investigate the contributions of various energy sources toward sustainable growth. With Malaysia as the test-bed, the present study analyzes the impact of energy prices on economic stability using the novel wavelet-based analysis. Specifically, the study analyzed the impact of crude oil, natural gas, and gasoline prices on the economic (brown) and green growth from 1995 to 2020. The results show that in continuous wavelet transform, the cone of influence of all five factors exhibits strong short-run variance and fluctuations from 2005 to 2013. However, the intensity of brown growth is more influential than green growth. Similarly, in wavelet coherence graphs, the downward right arrows indicate positively significant associations between crude oil prices, natural gas prices, and gasoline prices with brown and green growth. Additionally, wavelet-based Granger causality reveals a bidirectional causal relationship between all variables. The results thus strongly suggest that energy prices predominantly affect the economic (brown) and green growth progression of the Malaysian economy. The study concludes with some suggested implications to augment the country's sustainable growth.
For the synthesis of a highly active TiO2-chitosan nanocomposite, pH plays a crucial role towards controlling its morphology, size, crystallinity, thermal stability, and surface adsorption properties. The presence of chitosan (CS) biopolymer facilitates greater sustainability to the photoexcited electrons and holes on the catalysts' surface. The variation of synthesis pH from 2 to 5 resulted in different physico-chemical and photocatalytic properties, whereby a pH of 3 resulted in TiO2-chitosan nanocomposite with the highest photocatalytic degradation (above 99 %) of methylene orange (MO) dye. This was attributed to the efficient surface absorption properties, high crystallinity, and the presence of reactive surfaces of -NH2 and -OH groups, which enhances the adsorption-photodegradation effect. The larger surface oxygen vacancies coupled with reduced electron-hole recombination further enhanced the photocatalytic activity. It is undeniable that the pH during synthesis is critical towards the development of the properties of the TiO2-chitosan nanocomposite for the enhancement of photocatalytic activity.