The Mamut Copper Mine (MCM) located in Sabah (Malaysia) on Borneo Island was the only Cu-Au mine that operated in the country. During its operation (1975-1999), the mine produced 2.47 Mt of concentrate containing approximately 600,000 t of Cu, 45 t of Au and 294 t of Ag, and generated about 250 Mt of overburden and waste rocks and over 150 Mt of tailings, which were deposited at the 397 ha Lohan tailings storage facility, 15.8 km from the mine and 980 m lower in altitude. The MCM site presents challenges for environmental rehabilitation due to the presence of large volumes of sulphidic minerals wastes, the very high rainfall and the large volume of polluted mine pit water. This indicates that rehabilitation and treatment is costly, as for example, exceedingly large quantities of lime are needed for neutralisation of the acidic mine pit discharge. The MCM site has several unusual geochemical features on account of the concomitant occurrence of acid-forming sulphide porphyry rocks and alkaline serpentinite minerals, and unique biological features because of the very high plant diversity in its immediate surroundings. The site hence provides a valuable opportunity for researching natural acid neutralisation processes and mine rehabilitation in tropical areas. Today, the MCM site is surrounded by protected nature reserves (Kinabalu Park, a World Heritage Site, and Bukit Hampuan, a Class I Forest Reserve), and the environmental legacy prevents de-gazetting and inclusion in these protected area in the foreseeable future. This article presents a preliminary geochemical investigation of waste rocks, sediments, secondary precipitates, surface water chemistry and foliar elemental uptake in ferns, and discusses these results in light of their environmental significance for rehabilitation.
The objective of the study is to examine the impact of environmental indicators and air pollution on "health" and "wealth" for the low-income countries. The study used a number of promising variables including arable land, fossil fuel energy consumption, population density, and carbon dioxide emissions that simultaneously affect the health (i.e., health expenditures per capita) and wealth (i.e., GDP per capita) of the low-income countries. The general representation for low-income countries has shown by aggregate data that consist of 39 observations from the period of 1975-2013. The study decomposes the data set from different econometric tests for managing robust inferences. The study uses temporal forecasting for the health and wealth model by a vector error correction model (VECM) and an innovation accounting technique. The results show that environment and air pollution is the menace for low-income countries' health and wealth. Among environmental indicators, arable land has the largest variance to affect health and wealth for the next 10-year period, while air pollution exerts the least contribution to change health and wealth of low-income countries. These results indicate the prevalence of war situation, where environment and air pollution become visible like "gun" and "bullet" for low-income countries. There are required sound and effective macroeconomic policies to combat with the environmental evils that affect the health and wealth of the low-income countries.
This paper presents Gene-Expression Programming (GEP), which is an extension to the genetic programming (GP) approach to predict the total bed material load for three Malaysian rivers. The GEP is employed without any restriction to an extensive database compiled from measurements in the Muda, Langat, and Kurau rivers. The GEP approach demonstrated a superior performance compared to other traditional sediment load methods. The coefficient of determination, R(2) (=0.97) and the mean square error, MSE (=0.057) of the GEP method are higher than those of the traditional method. The performance of the GEP method demonstrates its predictive capability and the possibility of the generalization of the model to nonlinear problems for river engineering applications.
Urban environmental quality is vital to be investigated as the majority of people live in cities. However, given the continuous urbanization and industrialization in urban areas, heavy metals are continuously emitted into the terrestrial environment and pose a great threat to human. In this study, a total of 76 urban surface soil samples were collected in the Klang district (Malaysia), and analyzed for total and bioavailable heavy metal concentrations by inductively coupled plasma-optical emission spectrometry. Results showed that the concentrations of bioavailable heavy metals declined in the order of Al, Fe, Zn, Cu, Co, Cd, Pb, and Cr, and the concentrations of total heavy metals declined in the order of Fe, Al, Cu, Zn, Pb, Cr, Co, and Cd. Principal component analysis (PCA) showed that heavy metals could be grouped into three principal components, with PC1 containing Al and Fe, PC2 comprising Cd, Co, Cr, and Cu, and PC3 with only Zn. PCA results showed that PC1 may originate from natural sources, whereas PC2 and PC3 most likely originated from anthropogenic sources. Health risk assessment indicated that heavy metal contamination in the Klang district was below the acceptable threshold for carcinogenic and non-carcinogenic risks in adults, but above the acceptable threshold for carcinogenic and non-carcinogenic risks in children.
The over-exploitation of mineral resources has led to increasingly serious dust pollution in mines, resulting in a series of negative impacts on the environment, mine workers (occupational health) and nearby residents (public health). For the environment, mine dust pollution is considered a major threat on surface vegetation, landscapes, weather conditions and air quality, leading to serious environmental damage such as vegetation reduction and air pollution; for occupational health, mine dust from the mining process is also regarded as a major threat to mine workers' health, leading to occupational diseases such as pneumoconiosis and silicosis; for public health, the pollutants contained in mine dust may pollute surrounding rivers, farmlands and crops, which poses a serious risk to the domestic water and food security of nearby residents who are also susceptible to respiratory diseases from exposure to mine dust. Therefore, the second section of this paper combines literature research, statistical studies, and meta analysis to introduce the public mainly to the severity of mine dust pollution and its hazards to the environment, mine workers (occupational health), and residents (public health), as well as to present an outlook on the management of mine dust pollution. At the same time, in order to propose a method for monitoring mine dust pollution on a regional scale, based on the Dense Dark Vegetation (DDV) algorithm, the third section of this paper analysed the aerosol optical depth (AOD) change in Dexing City of China using the data of 2010, 2014, 2018 and 2021 from the NASA MCD19A2 Dataset to explore the mine dust pollution situation and the progress of pollution treatment in Dexing City from 2010 to 2021. As a discussion article, this paper aims to review the environmental and health risks caused by mine dust pollution, to remind the public to take mine dust pollution seriously, and to propose the use of remote sensing technologies to monitor mine dust pollution, providing suggestions for local governments as well as mines on mine dust monitoring measures.
Most of the developing countries have solid waste management problems. Solid waste strategic planning requires accurate prediction of the quality and quantity of the generated waste. In developing countries, such as Malaysia, the solid waste generation rate is increasing rapidly, due to population growth and new consumption trends that characterize society. This paper proposes an artificial neural network (ANN) approach using feedforward nonlinear autoregressive network with exogenous inputs (NARX) to predict annual solid waste generation in relation to demographic and economic variables like population number, gross domestic product, electricity demand per capita and employment and unemployment numbers. In addition, variable selection procedures are also developed to select a significant explanatory variable. The model evaluation was performed using coefficient of determination (R(2)) and mean square error (MSE). The optimum model that produced the lowest testing MSE (2.46) and the highest R(2) (0.97) had three inputs (gross domestic product, population and employment), eight neurons and one lag in the hidden layer, and used Fletcher-Powell's conjugate gradient as the training algorithm.
This study presents the use of a wavelet-based time series model to forecast the daily average particulate matter with an aerodynamic diameter of less than 10 μm (PM10) in Peninsular Malaysia. The highlight of this study is the use of a discrete wavelet transform (DWT) in order to improve the forecast accuracy. The DWT was applied to convert the highly variable PM10 series into more stable approximations and details sub-series, and the ARIMA-GARCH time series models were developed for each sub-series. Two different forecast periods, one was during normal days, while the other was during haze episodes, were designed to justify the usefulness of DWT. The models' performance was evaluated by four indices, namely root mean square error, mean absolute percentage error, probability of detection and false alarm rate. The results showed that the model incorporated with DWT yielded more accurate forecasts than the conventional method without DWT for both the forecast periods, and the improvement was more prominent for the period during the haze episodes.
Multivariate analysis including correlation, multiple stepwise linear regression, and cluster analyses were applied to investigate the heavy metal concentrations (Cd, Cu, Fe, Ni, Pb, and Zn) in the different parts of bivalves and gastropods. It was also aimed to distinguish statistically the differences between the marine bivalves and the gastropods with regards to the accumulation of heavy metals in the different tissues. The different parts of four species of bivalves and four species of gastropods were obtained and analyzed for heavy metals. The multivariate analyses were then applied on the data. From the multivariate analyses conducted, there were correlations found between the soft tissues of bivalves and gastropods, but none was found between the shells and the soft tissues of most of the molluscs (except for Cerithidea obtusa and Puglina cochlidium). The significant correlations (P < 0.05) found between the soft tissues were further complemented by the multiple stepwise linear regressions where heavy metals in the total soft tissues were influenced by the accumulation in the different types of soft tissues. The present study found that the distributions of heavy metals in the different parts of molluscs were related to their feeding habits and living habitats. The statistical approaches proposed in this study are recommended for use in biomonitoring studies, since multivariate analyses can reduce the cost and time involved in identifying an effective tissue to monitor the heavy metal(s) bioavailability and contamination in tropical coastal waters.
The distributions of Cu, Zn, and Pb concentrations in the selected soft tissues (foot, cephalic tentacle, mantle, muscle, gill, digestive caecum, and remaining soft tissues) and shells of the mud-flat snail Telescopium telescopium were determined in snails from eight geographical sites in the south-western intertidal area of Peninsular Malaysia. Generally, the digestive caecum compared with other selected soft tissues, accumulated higher concentration of Zn (214.35+/-14.56 microg/g dry weight), indicating that the digestive caecum has higher affinity for the essential Zn to bind to metallothionein. The shell demonstrated higher concentrations of Pb (41.23+/-1.20 microg/g dry weight) when compared to the selected soft tissues except gill from Kuala Sg. Ayam (95.76+/-5.32 microg/g dry weight). The use of different soft tissues also can solve the problem of defecation to reduce error in interpreting the bioavailability of heavy metals in the intertidal area.
Concentrations of cadmium (Cd), lead (Pb) and zinc (Zn) in total soft tissues (ST) and byssus (BYS) of the green-lipped mussel Perna viridis from 11 different geographical locations off the west coast of Peninsular Malaysia were determined. The metal concentrations distributed between the BYS and ST were compared. The results of this study indicated that higher levels of Cd (1.31 microg/g), Pb (38.49 microg/g) and Zn (206.52 microg/g) were accumulated in the BYS than in the total ST (Cd: 0.29 microg/g; Pb: 8.27 microg/g; Zn: 102.6 microg/g). Semi-static and short period controlled laboratory experiments were also conducted for the accumulation and depuration of Cd, Pb and Zn in the total ST and BYS of P. viridis. The ratios (BYS/ST) for Pb and Cd from the laboratory experiments showed that the total ST accumulated more metals than the BYS. Therefore, these laboratory results disagreed with those found for the field samples. However, the laboratory results for the Zn ratio (BYS/ST) agreed with those of the field samples. It was evident that when compared to the ST, the BYS was a more sensitive biomonitoring organ for Zn while it could be a complementary organ for Cd and Pb in the total ST. Since total ST of P. viridis had been reported to have regulative mechanism for Zn, its BYS can be used as a biomonitoring organ for the identification of coastal areas exposed to Zn pollution.
Today, insular Southeast Asia is important for both its remarkably rich biodiversity and globally significant roles in atmospheric and oceanic circulation. Despite the fundamental importance of environmental history for diversity and conservation, there is little primary evidence concerning the nature of vegetation in north equatorial Southeast Asia during the Last Glacial Period (LGP). As a result, even the general distribution of vegetation during the Last Glacial Maximum is debated. Here we show, using the stable carbon isotope composition of ancient cave guano profiles, that there was a substantial forest contraction during the LGP on both peninsular Malaysia and Palawan, while rainforest was maintained in northern Borneo. These results directly support rainforest "refugia" hypotheses and provide evidence that environmental barriers likely reduced genetic mixing between Borneo and Sumatra flora and fauna. Moreover, it sheds light on possible early human dispersal events.
Oil palm agriculture has caused extensive land cover and land use changes that have adversely affected tropical landscapes and ecosystems. However, monitoring and assessment of oil palm plantation areas to support sustainable management is costly and labour-intensive. This study used an unmanned aerial vehicles (UAV) to map smallholder farms and applied multi-criteria analysis to data generated from orthomosaics, to provide a set of sustainability indicators for the farms. Images were acquired from a UAV, with structure from motion (SfM) photogrammetry then used to produce orthomosaics and digital elevation models of the farm areas. Some of the inherent problems using high spatial resolution imagery for land cover classification were overcome by using texture analysis and geographic object-based image analysis (OBIA). Six spatially explicit environmental metrics were developed using multi-criteria analysis and used to generate sustainability indicator layers from the UAV data. The SfM and OBIA approach provided an accurate, high-resolution (~5 cm) image-based reconstruction of smallholder farm landscapes, with an overall classification accuracy of 89%. The multi-criteria analysis highlighted areas with lower sustainability values, which should be considered targets for adoption of sustainable management practices. The results of this work suggest that UAVs are a cost-effective tool for sustainability assessments of oil palm plantations, but there remains the need to plan surveys and image processing workflows carefully. Future work can build on our proposed approach, including the use of additional and/or alternative indicators developed through consultation with the oil palm industry stakeholders, to support certification schemes such as the Roundtable on Sustainable Palm Oil (RSPO).
Contamination by endocrine disrupting compounds (EDCs) concerns the security and sustainability of a drinking water supply system and human exposure via water consumption. This study analyzed the selected EDCs in source (river water, n = 10) and supply (tap water, n = 155) points and the associated risks. A total of 14 multiclass EDCs was detected in the drinking water supply system in Malaysia. Triclosan (an antimicrobial agent) and 4-octylphenol (a plasticizer) were only detected in the tap water (up to 9.74 and 0.44 ng/L, respectively). Meanwhile, chloramphenicol and 4-nonylphenol in the system were below the method detection limits. Bisphenol A was observed to be highest in tap water at 66.40 ng/L (detection: 100%; median concentration: 0.28 ng/L). There was a significant difference in triclosan contamination between the river and tap water (p
The progress of novel sorbents and their function in preconcentration techniques for determination of trace elements is a topic of great importance. This review discusses numerous analytical approaches including the preparation and practice of unique modification of solid-phase materials. The performance and main features of ion-imprinting polymers, carbon nanotubes, biosorbents, and nanoparticles are described, covering the period 2007-2012. The perspective and future developments in the use of these materials are illustrated.
In order to evaluate the water quality of one of the most polluted urban river in Malaysia, the Penchala River, performance of eight biotic indices, Biomonitoring Working Party (BMWP), BMWPThai, BMWPViet, Average Score Per Taxon (ASPT), ASPTThai, BMWPViet, Family Biotic Index (FBI), and Singapore Biotic Index (SingScore), was compared. The water quality categorization based on these biotic indices was then compared with the categorization of Malaysian Water Quality Index (WQI) derived from measurements of six water physicochemical parameters (pH, BOD, COD, NH3-N, DO, and TSS). The river was divided into four sections: upstream section (recreational area), middle stream 1 (residential area), middle stream 2 (commercial area), and downstream. Abundance and diversity of the macroinvertebrates were the highest in the upstream section (407 individual and H' = 1.56, respectively), followed by the middle stream 1 (356 individual and H' = 0.82). The least abundance was recorded in the downstream section (214 individual). Among all biotic indices, BMWP was the most reliable in evaluating the water quality of this urban river as their classifications were comparable to the WQI. BMWPs in this study have strong relationships with dissolved oxygen (DO) content. Our results demonstrated that the biotic indices were more sensitive towards organic pollution than the WQI. BMWP indices especially BMWPViet were the most reliable and could be adopted along with the WQI for assessment of water quality in urban rivers.
The upper catchment region of the Baram River in Sarawak (Malaysian Borneo) is undergoing severe land degradation due to soil erosion. Heavy rainfall with high erosive power has led to a number of soil erosion hotspots. The goal of the present study is to generate an understanding about the spatial characteristics of seasonal and annual rainfall erosivity (R), which not only control sediment delivery from the region but also determine the quantity of material potentially eroded. Mean annual rainfall and rainfall erosivity range from 2170 to 5167 mm and 1632 to 5319 MJ mm ha-1 h-1 year-1, respectively. Seasonal rainfall and rainfall erosivity range from 848 to 1872 mm and 558 to 1883 MJ mm ha-1 h-1 year-1 for the southwest (SW) monsoon, 902 to 2200 mm and 664 to 2793 MJ mm ha-1h-1year-1 for the northeast (NE) monsoon and 400 to 933 mm and 331 to 1075 MJ mm ha-1 h-1 year-1 during the inter-monsoon (IM) period. Linear regression, Spearman's Rho and Mann Kendall tests were applied. Considering the regional mean rainfall erosivity in the study area, all the methods show an overall non-significant decreasing trend (- 9.34, - 0.25 and - 0.30 MJ mm ha-1 h-1 year-1, respectively for linear regression, Spearman's Rho and Mann Kendall tests). However, during SW monsoon and IM periods, rainfall erosivity showed a non-significant decreasing trend (- 25.45, - 0.52, - 0.40, and - 8.86, - 1.07, - 0.77 MJ mm ha-1 h-1 year-1, respectively) whereas in NE, monsoon season erosivity showed a non-significant increasing trend (14.90, 1.59 and 1.60 MJ mm ha-1 h-1 year-1, respectively). The mean erosivity density ranges from 0.77 to 1.38 MJ ha-1 h-1 year-1 and shows decreasing trend. Spatial distribution pattern of erosivity density indicates significantly higher occurrence of erosive rainfall in the lower elevation portion of the study area. The spatial pattern of mean rainfall erosivity trends (linear, Spearman's Rho and Mann Kendall) suggests that the study area can be divided into two zones with increasing rainfall erosivity trends in the northern zone and decreasing trends in the southern zone. These results can be used to plan conservation measures to reduce sediment delivery from localized soil erosion hotspots.
Polycyclic Aromatic Hydrocarbons (PAHs) profoundly impact public and environmental health. Gaining a comprehensive understanding of their intricate functions, exposure pathways, and potential health implications is imperative to implement remedial strategies and legislation effectively. This review seeks to explore PAH mobility, direct exposure pathways, and cutting-edge bioremediation technologies essential for combating the pervasive contamination of environments by PAHs, thereby expanding our foundational knowledge. PAHs, characterised by their toxicity and possession of two or more aromatic rings, exhibit diverse configurations. Their lipophilicity and remarkable persistence contribute to their widespread prevalence as hazardous environmental contaminants and byproducts. Primary sources of PAHs include contaminated food, water, and soil, which enter the human body through inhalation, ingestion, and dermal exposure. While short-term consequences encompass eye irritation, nausea, and vomiting, long-term exposure poses risks of kidney and liver damage, difficulty breathing, and asthma-like symptoms. Notably, cities with elevated PAH levels may witness exacerbation of bronchial asthma and chronic obstructive pulmonary disease (COPD). Bioremediation techniques utilising microorganisms emerge as a promising avenue to mitigate PAH-related health risks by facilitating the breakdown of these compounds in polluted environments. Furthermore, this review delves into the global concern of antimicrobial resistance associated with PAHs, highlighting its implications. The environmental effects and applications of genetically altered microbes in addressing this challenge warrant further exploration, emphasising the dynamic nature of ongoing research in this field.
A study was conducted to determine the suitability of using selected aquatic dipterian larvae for biomonitoring bioassays. The organisms included a member of the biting midge family that was identified as Culicoides furens and a member of the non-biting midge family, identified as Chironomus plumosus. Median lethal toxicity tests were conducted to observe the variation between metal sensitivities between the two larval forms and how variations in temperature could affect the experimental setup. Nine heavy metals were used in the study. It was observed that the 96 h LC(50) (in mg/L) for the different metals was found to be Zn-16.21 (18.55 +/- 13.87); Cr-0.96 (1.08 +/- 0.84); Ag-4.22 (6.87 +/- 1.57); Ni-0.42 (0.59 +/- 0.25); Hg-0.42 (0.59 +/- 0.25); Pb-16.21 (18.31 +/- 14.11); Cu-42.24 (45.18 +/- 39.30); Mn-4.22 (7.19 +/- 1.25); Cd-0.42 (0.59 +/- 0.25) for the Chironomus plumosus and Zn-4.22 (6.56 +/- 1.88); Cr-0.42 (0.54 +/- 0.30); Ag-0.42 (0.54 +/- 0.30); Ni-0.42 (0.54 +/- 0.30); Hg-0.04 (0.07 +/- 0.01); Pb-0.42 (0.54 +/- 0.30); Cu-42.24 (45.18 +/- 39.30); Mn-4.22 (6.56 +/- 1.88); Cd-0.42 (0.54 +/- 0.30) in the case of the Culicoides furens. With temperature as a variable the LC(50) values were observed to increase from 2.51 mg/L at 10 degrees C to 4.22 ppm at 30 degrees C and to reduce slightly to 3.72 mg/L at 35 degrees C as seen in the case of Zn. It was also observed that at 40 degrees C thermal toxicity and chemical toxicity overlapped as 100% mortality was observed in the controls. This trend was observed in all metals for both C. plumosus and C. furens. Thus indicating temperature played an important role in determining LC(50) values of toxicants.
In this study, we assess the intense pollution episode of June 2013, in Riau province, Indonesia from land clearing. We relied on satellite retrievals of aerosols and Carbon monoxide (CO) due to lack of ground measurements. We used both the yearly and daily data for aerosol optical depth (AOD), fine mode fraction (FMF), aerosol absorption optical depth (AAOD) and UV aerosol index (UVAI) for characterizing variations. We found significant enhancement in aerosols and CO during the pollution episode. Compared to mean (2008-2012) June AOD of 0.40, FMF-0.39, AAOD-0.45, UVAI-1.77 and CO of 200 ppbv, June 2013 values reached 0.8, 0.573, 0.672, 1.77 and 978 ppbv respectively. Correlations of fire counts with AAOD and UVAI were stronger compared to AOD and FMF. Results from a trajectory model suggested transport of air masses from Indonesia towards Malaysia, Singapore and southern Thailand. Our results highlight satellite-based mapping and monitoring of pollution episodes in Southeast Asia.
This study investigates hydrocarbon pollution in the Ahoada community of the Niger Delta region of Nigeria. The study uses a geographic information system (GIS) for mapping oil spill hotspots in the region. The resistivity method was used to delineate the extent of hydrocarbon pollution to a depth of 19.7 m in the Ahoada area of the region. Three categories of soil samples, impacted soil (IMS), remediated soil (RS), and control soil (CS), were collected and analyzed for the presence of BTEX, PAH, TPH, TOC, and TOG. The concentrations of the samples from the IMS and RS were compared to that of the CS to determine the extent of pollution. The GIS mapping shows that the most polluted areas in the Niger Delta Region are Rivers, Bayelsa, and Delta states. Results of the geophysical images revealed contaminants' presence to depths beyond 20 m at some locations in the study area. The highest depth of contaminant travel was at Ukperede. Soil samples' analysis showed that the range of concentrations of TPH in IMS at Oshie was 17.27-58.36 mg/kg; RS was 11.73-50.78 mg/kg which were higher than the concentrations of 0.68 mg/kg in the CS. PAHs are more prevalent in Ukperede, ranging from 54.56 to 77.54 mg/kg. BTEX concentrations ranged from 0.02 to 0.38 mg/kg for IMP and 0.01-2.7 mg/kg for RS against a CS value of 0.01 mg/kg. The study revealed that there are characteristically high resistivity values in the samples which were corroborated by the findings from the resistivity survey. TOC was found to be higher in the IMS and RS than in the CS, demonstrating that a significant quantity of the hydrocarbon has undergone appreciable decomposition.