A variety of trace metals were measured in the egg contents of three clutches of Chelonia mydas collected from Kuala Terengganu state in Peninsular Malaysia. We quantified Mn, Cu, Zn, Se (essential trace metals) and As (anthropogenic pollutant) at several developmental stages obtained by incubating eggs at two different temperatures (27 °C and 31 °C). The incubation temperatures were chosen because they produce predominantly male or predominantly female hatchlings, respectively. The eggs were removed from the sand and washed before being placed in incubators, to ensure that the only possible source of the detected metals was maternal transfer. Other metals: Mo, Co, Ni, Cd, Sn, Sb, Hg, Tl and Pb (all non-essential metals) were detected at concentrations below the lower limit of quantitation (LLOQ). Trace metal concentrations, particularly [Zn], increased during development, other metals (Cu, As, Se and Cr) accumulated to a lesser degree than zinc but no significant differences were observed between the incubation temperatures at any stage of incubation. To date, only a few studies on trace metals in turtle embryos and hatchlings have been reported; this study will provide basic knowledge on the accumulation of trace metals during development at two different incubation temperatures.
In this project, several surrogate surfaces designed to directly measure Hg dry deposition were investigated. Static water surrogate surfaces (SWSS) containing deionized (DI), acidified water, or salt solutions, and a knife-edge surrogate surface (KSS) using quartz fiber filters (QFF), KCl-coated QFF and gold-coated QFF were evaluated as a means to directly measure mercury (Hg) dry deposition. The SWSS was hypothesized to collect deposited elemental mercury (Hg⁰), reactive gaseous/oxidized mercury (RGM), and mercury associated with particulate matter (Hg(p)) while the QFF, KCl-coated QFF, and gold-coated QFF on the KSS were hypothesized to collect Hg(p), RGM+Hg(p), and Hg⁰+RGM+Hg(p), respectively. The Hg flux measured by the DI water was significantly smaller than that captured by the acidified water, probably because Hg⁰ was oxidized to Hg²+ which stabilized the deposited Hg and decreased mass transfer resistance. Acidified BrCl, which efficiently oxidizes Hg⁰, captured significantly more Hg than other solutions. However, of all collection media, gold-coated QFFs captured 6 to 100 times greater Hg mass than the other surfaces, probably because there is no surface resistance for Hg⁰ deposition to gold surfaces. In addition, the Hg⁰ concentration is usually 100-1000 times higher than RGM and Hg(p). For all other media, co-located samples were not significantly different, and the combination of daytime plus nighttime results were comparable to 24-h samples, implying that Hg⁰, RGM and Hg(p) were not released after they deposited nor did the surfaces reach equilibrium with the atmosphere. Based on measured Hg ambient air concentrations and fluxes, dry deposition velocities of RGM and Hg⁰ to DI water and other surfaces were 5.6±5.4 and 0.005-0.68 cm s⁻¹ in this study, respectively. These results suggest surrogate surfaces can be used to measure Hg dry deposition; however, extrapolating the results to natural surface can be challenging.
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.
A new home-made diffusive bag-type passive sampler called Lanwatsu was developed for benzene, toluene, ethylbenzene and xylene monitoring in roadside air. The passive samplers were outdoor validated and deployed together with two commercial passive samplers, Ultra I SKC Inc. and Radiello, for daily roadside air monitoring in East Asian cities including HoChiMinh, Hanoi, Cantho, Danang, Vungtau, Hue (Vietnam), Kuala Lumpur (Malaysia), Kyoto, Osaka (Japan), Nanjing (China) and Singapore in 2011. High daily benzene concentrations of 87, 52, 32, 23, 13, 12 and 48 µg/m³ were observed in HoChiMinh, Hanoi, Cantho, Danang, Hue, Vung Tau (Vietnam), and Kuala Lumpur (Malaysia), respectively. Kyoto and Osaka (Japan) were clean with daily benzene concentrations below 2.3 μg/m³. The daily benzene concentrations in Nanjing (China) and Singapore were 5.6 and 6.9 μg/m³, respectively. The three passive samplers were equivalent. Passive sampling by the Lanwatsu passive sampler is acceptable for daily outdoor benzene monitoring.
The study of a Posidonia australis sedimentary archive has provided a record of changes in element concentrations (Al, Fe, Mn, Pb, Zn, Cr, Cd, Co, As, Cu, Ni and S) over the last 3000 years in the Australian marine environment. Human-derived contamination in Oyster Harbor (SW Australia) started ~100 years ago (AD ~1900) and exponentially increased until present. This appears to be related to European colonization of Australia and the subsequent impact of human activities, namely mining, coal and metal production, and extensive agriculture. Two contamination periods of different magnitude have been identified: Expansion period (EXP, AD ~1900-1970) and Establishment period (EST, AD ~1970 to present). Enrichments of chemical elements with respect to baseline concentrations (in samples older than ~115 cal years BP) were found for all elements studied in both periods, except for Ni, As and S. The highest enrichment factors were obtained for the EST period (ranging from 1.3-fold increase in Cu to 7.2-fold in Zn concentrations) compared to the EXP period (1.1-fold increase for Cu and Cr to 2.4-fold increase for Pb). Zinc, Pb, Mn and Co concentrations during both periods were 2- to 7-fold higher than baseline levels. This study demonstrates the value of Posidonia mats as long-term archives of element concentrations and trends in coastal ecosystems. We also provide preliminary evidence on the potential for Posidonia meadows to act as significant long-term biogeochemical sinks of chemical elements.
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.
Biomass burning (BB) has significant impacts on air quality and climate change, especially during harvest seasons. In previous studies, levoglucosan was frequently used for the calculation of BB contribution to PM2.5, however, the degradation of levoglucosan (Lev) could lead to large uncertainties. To quantify the influence of the degradation of Lev on the contribution of BB to PM2.5, PM2.5-bound biomass burning-derived markers were measured in Changzhou from November 2020 to March 2021 using the thermal desorption aerosol gas chromatography-mass spectrometry (TAG-GC/MS) system. Temporal variations of three anhydro-sugar BB tracers (e.g., levoglucosan, mannosan (Man), and galactosan (Gal)) were obtained. During the sampling period, the degradation level of air mass (x) was 0.13, indicating that ~87 % of levoglucosan had degraded before sampling in Changzhou. Without considering the degradation of levoglucosan in the atmosphere, the contribution of BB to OC were 7.8 %, 10.2 %, and 9.3 % in the clean period, BB period, and whole period, respectively, which were 2.4-2.6 times lower than those (20.8 %-25.9 %) considered levoglucosan degradation. This illustrated that the relative contribution of BB to OC could be underestimated (~14.9 %) without considering degradation of levoglucosan. Compared to the traditional method (i.e., only using K+ as BB tracer), organic tracers (Lev, Man, Gal) were put into the Positive Matrix Factorization (PMF) model in this study. With the addition of BB organic tracers and replaced K+ with K+BB (the water-soluble potassium produced by biomass burning), the overall contribution of BB to PM2.5 was enhanced by 3.2 % after accounting for levoglucosan degradation based on the PMF analysis. This study provides useful information to better understand the effect of biomass burning on the air quality in the Yangtze River Delta region.
Owing to a wide range of advantages, such as stability, non-invasiveness, and ease of sampling, hair has been used progressively for comprehensive biomonitoring of organic pollutants for the last three decades. This has led to the development of new analytical and multi-class analysis methods for the assessment of a broad range of organic pollutants in various population groups, ranging from small-scale studies to advanced studies with a large number of participants based on different exposure settings. This meta-analysis summarizes the existing literature on the assessment of organic pollutants in hair in terms of residue levels, the correlation of hair residue levels with those of other biological matrices and socio-demographic factors, the reliability of hair versus other biomatrices for exposure assessment, the use of segmental hair analysis for chronic exposure evaluation and the effect of external contamination on hair residue levels. Significantly high concentrations of organic pollutants such as pesticides, flame retardants, polychlorinated biphenyls and polycyclic aromatic hydrocarbon were reported in human hair samples from different regions and under different exposure settings. Similarly, high concentrations of pesticides (from agricultural activities), flame retardants (E-waste dismantling activities), dioxins and furans were observed in various occupational settings. Moreover, significant correlations (p
In Malaysia, inexpensive toys are sold in various urban and rural shops. Although safety regulations for toys are available in Malaysia there are limited reports about the chemicals in toys. Thus, this study aimed to assess the levels of phthalates (bis-[2-ethylhexyl] phthalate [DEHP], diethyl phthalate [DEP], diisobutyl phthalate [DiBP] and dibutyl phthalate [DBP]) in inexpensive toys sold at local markets in Kuala Lumpur (Malaysia) and its health risks to children. All 30 toys analysed exceeded the European Union limit (0.1 % by mass) indicating that the phthalate used as plasticizers is still prominent in toys. Bis-[2-ethylhexyl] phthalate (DEHP) was the highest detected phthalate in toy sample which was manufactured in Malaysia and sold without Malaysian Conformity Mark. Significant association was found between phthalate levels and country, indicating a need to monitor and raise public awareness about potential toxic chemicals in inexpensive toys and children's products. There are few inexpensive toys that have a hazard index value of more than one, which is associated with developmental toxicity and causes developmental effects in children. Given the severity and complexity of these toys to children health, there is a need for regular monitoring and effective enforcements to develop an acceptable baseline level of children toys products manufactured in or imported to Malaysia. Furthermore, risk management efforts should also include all the stakeholders involved in toy production, policy makers as well as consumers to ensure only toy products with proper labels being sole and purchased.
Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. Even though frequent cloud cover has been a challenge for mapping tropical forests, our MODIS land use classification map found that 2008 ISODATA-1 performed well with overall accuracy of 94%, with the highest Producer's Accuracy of Forest with 86%, and were consistent with MODIS Land Cover 2008 (MOD12Q1), respectively. The MODIS land use classification was able to distinguish young oil palm groves from open areas, rubber and mature oil palm plantations, on the Advanced Land Observing Satellite (ALOS) map, whereas rubber was more easily distinguished from an open area than from mixed rubber and forest. This study provides insight on the potential for integrating regional databases and temporal MODIS data, in order to map land use in tropical forest regions.
Demand for online and real-time measurements techniques to meet environmental regulation and treatment compliance are increasing. However the conventional techniques, which involve scheduled sampling and chemical analysis can be expensive and time consuming. Therefore cheaper and faster alternatives to monitor wastewater characteristics are required as alternatives to conventional methods. This paper reviews existing conventional techniques and optical and fibre optic sensors to determine selected wastewater characteristics which are colour, Chemical Oxygen Demand (COD) and Biological Oxygen Demand (BOD). The review confirms that with appropriate configuration, calibration and fibre features the parameters can be determined with accuracy comparable to conventional method. With more research in this area, the potential for using FOS for online and real-time measurement of more wastewater parameters for various types of industrial effluent are promising.
In this paper, we present the effect of varying humidity levels on the electrical parameters and the multi frequency response of the electrical parameters of an organic-inorganic composite (PEPC+NiPc+Cu2O)-based humidity sensor. Silver thin films (thickness ~200 nm) were primarily deposited on plasma cleaned glass substrates by the physical vapor deposition (PVD) technique. A pair of rectangular silver electrodes was formed by patterning silver film through standard optical lithography technique. An active layer of organic-inorganic composite for humidity sensing was later spun coated to cover the separation between the silver electrodes. The electrical characterization of the sensor was performed as a function of relative humidity levels and frequency of the AC input signal. The sensor showed reversible changes in its capacitance with variations in humidity level. The maximum sensitivity ~31.6 pF/%RH at 100 Hz in capacitive mode of operation has been attained. The aim of this study was to increase the sensitivity of the previously reported humidity sensors using PEPC and NiPc, which has been successfully achieved.
Microfluidics-based lab-on-chip (LOC) systems are an active research area that is revolutionising high-throughput sequencing for the fast, sensitive and accurate detection of a variety of pathogens. LOCs also serve as portable diagnostic tools. The devices provide optimum control of nanolitre volumes of fluids and integrate various bioassay operations that allow the devices to rapidly sense pathogenic threat agents for environmental monitoring. LOC systems, such as microfluidic biochips, offer advantages compared to conventional identification procedures that are tedious, expensive and time consuming. This paper aims to provide a broad overview of the need for devices that are easy to operate, sensitive, fast, portable and sufficiently reliable to be used as complementary tools for the control of pathogenic agents that damage the environment.
The rapid spread of the SARS-CoV-2 in the COVID-19 pandemic had raised questions on the route of transmission of this disease. Initial understanding was that transmission originated from respiratory droplets from an infected host to a susceptible host. However, indirect contact transmission of viable virus by fomites and through aerosols has also been suggested. Herein, we report the involvement of fine indoor air particulates with a diameter of ≤ 2.5 µm (PM2.5) as the virus's transport agent. PM2.5 was collected over four weeks during 48-h measurement intervals in four separate hospital wards containing different infected clusters in a teaching hospital in Kuala Lumpur, Malaysia. Our results indicated the highest SARS-CoV-2 RNA on PM2.5 in the ward with number of occupants. We suggest a link between the virus-laden PM2.5 and the ward's design. Patients' symptoms and numbers influence the number of airborne SARS-CoV-2 RNA with PM2.5 in an enclosed environment.
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
Coral cover on reefs is declining globally due to coastal development, overfishing and climate change. Reefs isolated from direct human influence can recover from natural acute disturbances, but little is known about long term recovery of reefs experiencing chronic human disturbances. Here we investigate responses to acute bleaching disturbances on turbid reefs off Singapore, at two depths over a period of 27 years. Coral cover declined and there were marked changes in coral and benthic community structure during the first decade of monitoring at both depths. At shallower reef crest sites (3-4 m), benthic community structure recovered towards pre-disturbance states within a decade. In contrast, there was a net decline in coral cover and continuing shifts in community structure at deeper reef slope sites (6-7 m). There was no evidence of phase shifts to macroalgal dominance but coral habitats at deeper sites were replaced by unstable substrata such as fine sediments and rubble. The persistence of coral dominance at chronically disturbed shallow sites is likely due to an abundance of coral taxa which are tolerant to environmental stress. In addition, high turbidity may interact antagonistically with other disturbances to reduce the impact of thermal stress and limit macroalgal growth rates.
Although coastal water marine algae have been popularly used by others as indicators of heavy metal pollution, data within the Bay of Bengal for the estuarine Cox's Bazar region and Saint Martin's Island has remained scarce. Using marine algae, the study herein forms an effort in biomonitoring of metal contamination in the aforementioned Bangladesh areas. A total of 10 seaweed species were collected, including edible varieties, analyzed for metal levels through the use of the technique of EDXRF. From greatest to least, measured mean metal concentrations in descending order have been found to be K > Fe > Zr > Br > Sr > Zn > Mn > Rb > Cu > As > Pb > Cr > Co. Potential toxic heavy metals such as Pb, As, and Cr appear at lower concentration values compared to that found for essential mineral elements. However, the presence of Pb in Sargassum oligocystum species has been observed to exceed the maximum international guidance level. Given that some of the algae species are cultivated for human consumption, the non-carcinogenic and carcinogenic indices were calculated, shown to be slightly lower than the maxima recommended by the international organizations. Overall, the present results are consistent with literature data suggesting that heavy metal macroalgae biomonitoring may be species-specific. To the best of our knowledge, this study represents the first comprehensive macroalgae biomonitoring study of metal contamination from the coastal waters of Cox's Bazar and beyond.
Rapid industrialization and urbanization have resulted in environmental pollution and unsustainable development of cities. The concentration of 12 potentially toxic metal(loid)s in windowsill dust samples (n = 50) were investigated from different functional areas of Qom city with the highest level of urbanization in Iran. Spatial analyses (ArcGIS 10.3) and multivariate statistics including Principal Component Analysis and Spearman correlation (using STATISTICA-V.12) were adopted to scrutinize the possible sources of pollution. The windowsill dust was very highly enriched with Sb (50 mg/kg) and Pb (1686 mg/kg). Modified degree of contamination (mCd) and the pollution load indices (PLIzone) indicate that windowsill dust in all functional areas was polluted in the order of industrial > commercial > residential > green space. Arsenic, Cd, Mo, Pb, Sb, Cu, and Zn were sourced from a mixture of traffic and industrial activities, while Mn in the dust mainly stemmed from mining activities. Non-carcinogenic health risk (HI) showed chronic exposure of Pb for children in the industrial zone (HI = 1.73). The estimations suggest the possible carcinogenic risk of As, Pb, and Cr in the dust. The findings of this study reveal poor environmental management of the city. Emergency plans should be developed to minimize the health risks of dust to residents.
Fine particulate matter (PM2.5) is a significant air pollutant that drives the most chronic health problems and premature mortality in big metropolitans such as Delhi. In such a context, accurate prediction of PM2.5 concentration is critical for raising public awareness, allowing sensitive populations to plan ahead, and providing governments with information for public health alerts. This study applies a novel hybridization of extreme learning machine (ELM) with a snake optimization algorithm called the ELM-SO model to forecast PM2.5 concentrations. The model has been developed on air quality inputs and meteorological parameters. Furthermore, the ELM-SO hybrid model is compared with individual machine learning models, such as Support Vector Regression (SVR), Random Forest (RF), Extreme Learning Machines (ELM), Gradient Boosting Regressor (GBR), XGBoost, and a deep learning model known as Long Short-Term Memory networks (LSTM), in forecasting PM2.5 concentrations. The study results suggested that ELM-SO exhibited the highest level of predictive performance among the five models, with a testing value of squared correlation coefficient (R2) of 0.928, and root mean square error of 30.325 µg/m3. The study's findings suggest that the ELM-SO technique is a valuable tool for accurately forecasting PM2.5 concentrations and could help advance the field of air quality forecasting. By developing state-of-the-art air pollution prediction models that incorporate ELM-SO, it may be possible to understand better and anticipate the effects of air pollution on human health and the environment.
Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.