The atmospheric particulate matter (PM) with a diameter of 2.5 μm or less (PM2.5) is one of the key indicators of air pollutants. Accurate prediction of PM2.5 concentration is very important for air pollution monitoring and public health management. However, the presence of noise in PM2.5 data series is a major challenge of its accurate prediction. A novel hybrid PM2.5 concentration prediction model is proposed in this study by combining complete ensemble empirical mode decomposition (CEEMD) method, Pearson's correlation analysis, and a deep long short-term memory (LSTM) method. CEEMD was employed to decompose historical PM2.5 concentration data to different frequencies in order to enhance the timing characteristics of data. Pearson's correlation was used to screen the different frequency intrinsic-mode functions of decomposed data. Finally, the filtered enhancement data were inputted to a deep LSTM network with multiple hidden layers for training and prediction. The results evidenced the potential of the CEEMD-LSTM hybrid model with a prediction accuracy of approximately 80% and model convergence after 700 training epochs. The secondary screening of Pearson's correlation test improved the model (CEEMD-Pearson) accuracy up to 87% but model convergence after 800 epochs. The hybrid model combining CEEMD-Pearson with the deep LSTM neural network showed a prediction accuracy of nearly 90% and model convergence after 650 interactions. The results provide a clear indication of higher prediction accuracy of PM2.5 with less computation time through hybridization of CEEMD-Pearson with deep LSTM models and its potential to be employed for air pollution monitoring.
Very little work has determined the relative importance of uncontrolled environmental factors for affecting fish biology, and how these might influence gillnet catches. This study addresses this deficit for an important Southeast Asian cyprinid (Barbonymus schwanenfeldii). Fish were caught monthly for 12 months using gillnets of three different mesh sizes, each of which was deployed in duplicate at the surface of one of three randomly selected sites in Lake Kenyir, Malaysia, concurrent with determining various environmental parameters and the abundance of phytoplankton (chlorophyll-a). Results indicated that growth co-efficient of B. schwanenfeldii was positively influenced by dissolved oxygen and negatively influenced by total inorganic nitrogen, whereas an opposite result was observed in case of the hepatosomatic index of fish. Water turbidity was a limiting factor only for small fish (mean total length: 15.74±1.10 cm). B. schwanenfeldii could best be caught during the period of high phytoplankton abundance or at the location of high phytoplankton density in the water. Water temperature negatively influenced the gillnet catches of the fish. The remaining environmental factors such as water depth, pH, and phosphate had a weak and insignificant influence (P >0.05) on the biology and gillnet catches of fish. The observed results can be very useful for the ecological monitoring and conservation plans for this species in relation to climate change. Furthermore, the utility of the similar data for other species would be useful not only for regional but also for international fishery by optimizing catches considering environmental conditions.
The 17 α-ethinylestradiol (EE2) adsorption from aqueous solution was examined using a novel adsorbent made from rice husk powder coated with CuO nanoparticles (CRH). Advanced analyses of FTIR, XRD, SEM, and EDSwere used to identify the classification parameters of a CRH-like surface morphology, configuration, and functional groups. The rice husk was coated with CuO nanoparticles, allowing it to create large surface area materials with significantly improved textural qualities with regard to functional use and adsorption performance, according to a detailed characterization of the synthesized materials. The adsorption process was applied successfully with elimination effectiveness of 100% which can be kept up to 61.3%. The parameters of adsorption were affecting the adsorption process significantly. Thermodynamic data stated that the process of adsorption was endothermic, spontaneous, chemisorption and the molecules of EE2 show affinity with the CRH. It was discovered that the adsorption process controlled by a pseudo-second-order kinetic model demonstrates that the chemisorption process was controlling EE2 removal. The Sips model is regarded as optimal for representing this practice, exhibiting a significantly high determination coefficient of 0.948. This coefficient implies that the adsorption mechanism indicates the occurrence of both heterogeneous and homogeneous adsorption. According to the findings, biomass can serve as a cheap, operative sorbent to remove estrogen from liquified solutions.
Miri River is a tropical river in Borneo that drains on flat terrain and urbanised area and debauches into the South China Sea. This paper documents the environmental status of this river, and provides an insight into the provenance using bulk chemistry of the sediments, and brings out the geochemical mobility, bioavailability, and potential toxicity of some critical elements based on BCR sequential extraction. The sediments are intense to moderately weathered and recycled products of Neogene sedimentary rocks. The hydrodynamic characteristics of the river favoured an upstream section dominated by fine sand, while the downstream sediments are medium silt. Based on the bulk geochemistry, the Miri River sediments are moderate to considerably contaminated by Cu, Mo, and As in the upstream and by Sb, As and Cu in the downstream. The potential ecological risk values are low except Cu and a significant biological impact is expected in downstream due to Cu, As, Zn and Cr. The mobility, bioavailability and Risk Assessment Code values for Zn and Mn are higher and thus may pose moderate to very high risk to aquatic organisms. Though a high bulk concentration of Cu is observed, the association of Cu with the bioavailable fraction is low.
Hospital wastewater has emerged as a major category of environmental pollutants over the past two decades, but its prevalence in freshwater is less well documented than other types of contaminants. Due to compound complexity and improper operations, conventional treatment is unable to remove pharmaceuticals from hospital wastewater. Advanced treatment technologies may eliminate pharmaceuticals, but there are still concerns about cost and energy use. There should be a legal and regulatory framework in place to control the flow of hospital wastewater. Here, we review the latest scientific knowledge regarding effective pharmaceutical cleanup strategies and treatment procedures to achieve that goal. Successful treatment techniques are also highlighted, such as pre-treatment or on-site facilities that control hospital wastewater where it is used in hospitals. Due to the prioritization, the regulatory agencies will be able to assess and monitor the concentration of pharmaceutical residues in groundwater, surface water, and drinking water. Based on the data obtained, the conventional WWTPs remove 10-60% of pharmaceutical residues. However, most PhACs are eliminated during the secondary or advanced therapy stages, and an overall elimination rate higher than 90% can be achieved. This review also highlights and compares the suitability of currently used treatment technologies and identifies the merits and demerits of each technology to upgrade the system to tackle future challenges. For this reason, pharmaceutical compound rankings in regulatory agencies should be the subject of prospective studies.
The main aim of this study was to assess the presence of microplastics in the water and sediments of the Surakarta city river basin in Indonesia. In order to accurately reflect the river basin, a deliberate selection process was employed to choose three separate sampling locations and twelve sampling points. The results of the study revealed that fragments and fibers were the primary types of microplastics seen in both water and sediment samples. Furthermore, a considerable percentage of microplastics, comprising 53.8 % of the total, had dimensions below 1 mm. Moreover, the prevailing hues identified in the water samples were blue and black, comprising 45.1 % of the overall composition. In contrast, same color categories accounted for 23.3 % of the microplastics found in the soil samples. The analysis of microplastic polymers was carried out utilizing ATR-FTIR spectroscopy, which yielded the identification of various types including polystyrene, silicone polymer, polyester, and polyamide.
Miners, factory workers, traders, end-users, and foodstuff consumers all run the risk of encountering health hazards derived from the presence of elevated levels of radiation in fertilizers, as these groups often come into direct or indirect contact with fertilizers as well as raw materials throughout various linked processes such as mineral extractions, fertilizer production, agricultural practices. A total of 30 samples of various kinds of fertilizer produced in different factories in Dhaka megacity were analyzed to quantify the concentrations of primordial radionuclides using HPGe detector. Among the analyzed samples, average (range) concentration of 40K was found to be 9920 ± 1091 (8700 ± 957-11,500 ± 1265), 9100 ± 1001 (8600 ± 946-9600 ± 1056), 2565 ± 282 (2540 ± 279-2590 ± 285), and 3560 ± 392 (2620 ± 288-4500 ± 495) Bq/kg in the samples of Muriate of Potash Fertilizer, Sulphate of Potash Fertilizer, Humic Acid Fertilizer, and NPKS Fertilizer, respectively. Elevated concentration of 226Ra was found in Triple Super Phosphate Fertilizer with a mean (range) of 335 ± 37 (290 ± 32-380 ± 42) Bq/kg. The higher activity of 40K can be linked to the greater levels of elemental potassium in phosphate fertilizer. Elevated concentrations of radionuclides may also result from variations in chemical processes as well as the local geology of the mining areas where the raw materials were extracted for fertilizer production. Numerous fertilizer brands surpass prescribed limits for various hazardous parameters, presenting significant health risks to factory workers, farmers, and consumers of agricultural products. This study provides baseline information on the radioactivity of fertilizers, which could be used to develop mitigation methods, establish national fertilizer usage limits, justify regulatory frameworks, and raise public awareness of fertilizer overuse. The findings of the study could potentially help to explore the impact of fertilizer on the food chain.
The alarming rate of the mangrove ecosystem loss poses a threat of losing valuable carbon sinks. This study was conducted to (i) determine the growth structure in different vegetation types and (ii) compare the aboveground biomass (AGB) and carbon storage in different vegetation types. The study was conducted at four vegetation types within the Rajang-Belawai-Paloh delta i.e., Matured Bakau-Berus Forest (MBBF), Bakau-Nipah Forest (BNF), Regenerating Forests (Debris pile) [RF-D], and Regenerating Forests (Machinery track) [RF-M]. Inventory plots (20 m × 20 m) are systematically located along the main waterways and smaller rivers/streams. Trees (≥ 5 cm diameter-at-breast height [DBH]), seedlings (< 2-cm stem diameter), and saplings (2-4.9-cm stem diameter) were measured. The trend of total trees per hectare is found to be decreasing across the least disturbed vegetation (MBBF) to the most disturbed vegetation (RF-M). The trends of total seedlings and saplings per hectare are found to be going upwards from the least disturbed vegetation to the most disturbed vegetation. Kruskal-Wallis H-test showed that there is a significant difference in the AGB and carbon storage between different vegetation types, χ2(2) = 43.98, p = 0.00 with the highest mean rank AGB and carbon storage in BNF (612.20 t/ha) and lowest in RF-M (287.85 t/ha). It can be concluded that although the most disturbed vegetations have higher regeneration, it may not contribute to the forest's carbon storage The naturally regenerated seedlings may not grow beyond the sapling stage unless sustainable forest management is conducted to ensure survivability and growth.
This study evaluated microplastic (MP) abundances and physico-chemical characteristics in sediments and Anadara granosa along the East Java coast and their health implications. Fibers (74 %) dominated sediment MPs at south coast, while fragments (49-61 %) dominated north coast. Fiber (43-52 %) is the predominant MP in cockle tissues in all locations. Most MP in sediments (31-47 %) and cockle tissues (41-49 %) is black. The majority of microplastics (100-1500 μm) are found in sediment (73-90 %), and cockles (77-79 %). Very weak correlations found between the amount of MP and the length of the cockle shell. However, Spearman correlation shows that as the amount of MP in sediment increases, so does the amount of MP in cockle tissue. Each year, individuals of varying ages consume an average of 20,800 to 156,000 MP items. Cockles contain plasticizer components and microplastic polymers which are classified from II to V regarding of hazard levels, with V being the most hazardous.
Concerns about chemical exposure in the electronics manufacturing industry have long been recognized, but data are lacking in Southeast Asia. We conducted a study in Batam, Indonesia, to evaluate chemical exposures in electronics facilities, using participatory research and biological monitoring approaches. A convenience sample of 36 workers (28 exposed, 8 controls) was recruited, and urine samples were collected before and after shifts. Five solvents (acetone, methyl ethyl ketone, toluene, benzene, and xylenes) were found in 46%-97% of samples, and seven metals (arsenic, cadmium, cobalt, tin, antimony, lead, and vanadium) were detected in 60%-100% of samples. Biological monitoring and participatory research appeared to be useful in assessing workers' exposure when workplace air monitoring is not feasible due to a lack of cooperation from the employer. Several logistical challenges need to be addressed in future biomonitoring studies of electronics workers in Asia in factories where employers are reluctant to track workers' exposure and health.
Mud crab, one of the aquatic organisms found in estuary areas, has become a significant economic source of seafood for communities due to its delectable taste. However, they face the threat of heavy metal contamination, which may adversely affect their biological traits. This study explored the comparison of the mud crabs collected from Setiu Wetland as a reference site, while Kuala Sepetang is an area that contains a higher concentration of heavy metals than Setiu Wetlands. Heavy metal levels were quantified using inductively coupled plasma mass spectrometry (ICP-MS), while proteomes were assessed using sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and 1H nuclear magnetic resonance (NMR)-based metabolomics, respectively. Heavy metal contamination affects the proteome, metabolome, and putative molecular targets in mud crabs (Scylla olivacea), leading to oxidative stress. Mud crabs collected from the metal-polluted area of Kuala Sepetang in Perak had considerably elevated concentrations of nickel (Ni), copper (Cu), zinc (Zn), lead (Pb), chromium (Cr), and cadmium (Cd) in comparison to the reference site of Setiu Wetlands in Terengganu. The proteome analysis revealed an upregulation of the stress-response protein Hsp70, which triggered superoxide dismutase (SOD) and increased arginine kinase expression (5.47 fold) in the muscle tissue, results in the alteration of metabolite regulation in the mud crab from Kuala Sepetang. Additionally, in the muscle tissues of mud crabs obtained from Kuala Sepetang, uncharacterized myosin-tail 1 domain proteins and sarcoplasmic calcium-binding proteins were downregulated. The metabolomic investigation identified changes in metabolites associated with energy metabolism and osmoregulation. Exploration of docking analysis suggests potential connections between methylarsonic acid and essential proteins in mud crabs. These findings suggest that the presence of heavy metals disrupts physiological processes and highlights potential molecular targets that warrant further investigation.
A novel coronavirus disease (COVID-19) continues to challenge the whole world. The disease has claimed many fatalities as it has transcended from one country to another since it was first discovered in China in late 2019. To prevent further morbidity and mortality associated with COVID-19, most of the countries initiated a countrywide lockdown. While physical distancing and lockdowns helped in curbing the spread of this novel coronavirus, it led to massive economic losses for the nations. Positive impacts have been observed due to lockdown in terms of improved air quality of the nations. In the current research, ten tropical and subtropical countries have been analysed from multiple angles, including air pollution, assessment and valuation of health impacts and economic loss of countries during COVID-19 lockdown. Countries include Brazil, India, Iran, Kenya, Malaysia, Mexico, Pakistan, Peru, Sri Lanka, and Thailand. Validated Simplified Aerosol Retrieval Algorithm (SARA) binning model is used on data collated from moderate resolution imaging spectroradiometer (MODIS) for particulate matters with a diameter of less than 2.5 μm (PM2.5) for all the countries for the month of January to May 2019 and 2020. The concentration results of PM2.5 show that air pollution has drastically reduced in 2020 post lockdown for all countries. The highest average concentration obtained by converting aerosol optical depth (AOD) for 2020 is observed for Thailand as 121.9 μg/m3 and the lowest for Mexico as 36.27 μg/m3. As air pollution is found to decrease in the April and May months of 2020 for nearly all countries, they are compared with respective previous year values for the same duration to calculate the reduced health burden due to lockdown. The present study estimates that cumulative about 100.9 Billion US$ are saved due to reduced air pollution externalities, which are about 25% of the cumulative economic loss of 435.9 Billion US$.
Microplastic pollution has become a major global environmental issue, negatively impacting terrestrial and aquatic ecosystems as well as human health. Tackling this complex problem necessitates a multidisciplinary approach and collaboration among diverse stakeholders. Within this context, the Quintuple Helix framework, which highlights the involvement of academia, government, industry, civil society, and the environment, provides a comprehensive and inclusive perspective for formulating effective policies to manage atmospheric microplastics. This paper discusses each helix's roles, challenges, and opportunities and proposes strategies for collaboration and knowledge exchange among them. Furthermore, the paper highlights the importance of interdisciplinary research, innovative technologies, public awareness campaigns, regulatory frameworks, and corporate responsibility in achieving sustainable and resilient microplastic management policies. The Quintuple Helix approach can mitigate microplastics, safeguard ecosystems, and preserve planetary health by fostering collaboration and coordination among diverse stakeholders.
This paper describes the concentration of selected heavy metals (Co, Cu, Ni, Pb, and Zn) in the Mamut river sediments and evaluate the degree of contamination of the river polluted by a disused copper mine. Based on the analytical results, copper showed the highest concentration in most of the river samples. A comparison with Interim Canadian Sediment Quality Guidelines (ICSQG) and Germany Sediment Quality Guidelines (GSQG) indicated that the sediment samples in all the sampling stations, except Mamut river control site (M1), exceeded the limit established for Cu, Ni, and Pb. On the contrary, Zn concentrations were reported well below the guidelines limit (ICSQG and GSQG). Mineralogical analysis indicated that the Mamut river sediments were primarily composed of quartz and accessory minerals such as chalcopyrite, pyrite, edenite, kaolinite, mica, and muscovite, reflected by the geological character of the study area. Enrichment factor (EF) and geoaccumulation index (Igeo) were calculated to evaluate the heavy metal pollution in river sediments. Igeo values indicated that all the sites were strongly polluted with the studied metals in most sampling stations, specifically those located along the Mamut main stream. The enrichment factor with value greater than 1.5 suggested that the source of heavy metals was mainly derived from anthropogenic activity such as mining. The degree of metal changes (δfold) revealed that Cu concentration in the river sediments has increased as much as 20 to 38 folds since the preliminary investigation conducted in year 2004.
An advanced image processing approach integrated with communication technologies and a camera for waste bin level detection has been presented. The proposed system is developed to address environmental concerns associated with waste bins and the variety of waste being disposed in them. A gray level aura matrix (GLAM) approach is proposed to extract the bin image texture. GLAM parameters, such as neighboring systems, are investigated to determine their optimal values. To evaluate the performance of the system, the extracted image is trained and tested using multi-layer perceptions (MLPs) and K-nearest neighbor (KNN) classifiers. The results have shown that the accuracy of bin level classification reach acceptable performance levels for class and grade classification with rates of 98.98% and 90.19% using the MLP classifier and 96.91% and 89.14% using the KNN classifier, respectively. The results demonstrated that the system performance is robust and can be applied to a variety of waste and waste bin level detection under various conditions.
Surface water is one of the essential resources for supporting sustainable development. The suitability of such water for a given use depends both on the available quantity and tolerable quality. Temporary status for a surface water quality has been identified extensively. Still the suitability of the water for different purposes needs to be verified. This study proposes a water quality evaluation system to assess the aptitude of the Selangor River water for aquatic biota, drinking water production, leisure and aquatic sport, irrigation use, livestock watering, and aquaculture use. Aptitude of the water has been classified in many parts of the river segment as unsuitable for aquatic biota, drinking water production, leisure and aquatic sport as well as aquaculture use. The water quality aptitude classes of the stream water for nine locations along the river are evaluated to contribute to decision support system. The suitability of the water for five different uses and its aquatic ecosystem are verified.
A priori assessments of a site's biophysical and socio-economic capacity for accommodating tourism are less common than tourism impact studies. A priori evaluations can provide a contextual understanding of ecological, economic and socio-cultural forces, which shape the prospects for sustainable tourism development at the host destination, and can avert adverse impacts of tourism. We conduct an a priori assessment of the biophysical environment of Pulau Banggi, in the Malaysian state of Sabah for sustainable tourism development. We characterise baseline conditions of the island's marine biodiversity, seasonality, and infrastructure. We then evaluate how existing biophysical conditions will influence options for sustainable tourism development. In particular, we suggest conditions, if there are any, which constitute a limit to future tourism development in terms of compatibility for recreation and resilience to visitor impacts. We find that the biggest constraint is the lack of adequate water and sanitation infrastructure. Blast fishing, although occurring less than once per hour, can potentially destroy the major attraction for tourists. We conclude that while Pulau Banggi possesses natural qualities that are attractive for ecotourism, financial and institutional support must be made available to provide facilities and services that will enable local participation in environmental protection and enhance prospects for future sustainable tourism.
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.
Adult mosquito collections were conducted for 12 weeks in two residential areas in Kuala Lumpur. The CDC light traps were compared using dry ice and yeast as sources of carbon dioxide attractants for mosquitoes. The efficacy of the dry ice baited trap was significant over yeast generated CO2 trap. The predominant species obtained were Culex quinquefasciatus, Stegomyia albopicta and Armigeres subalbatus.
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.
Matched MeSH terms: Environmental Monitoring/methods*; Environmental Monitoring/statistics & numerical data