Despite of our growing understanding of microplastic's implications, research on the effects of fibrous microplastic (FMPs) on the environment is still in its infancy. Some scientists have hypothesized the possibility of natural textile fibres, which may act as one of the emerging environmental pollutants prevalent among microplastic pollutants in the environment. Therefore, this review aims to critically evaluate the toxic effects of emerging FMPs, the presence, and sources of FMPs in the environment, identification and analytical techniques, and the potential impact or toxicity of the FMPs on the environment and human health. About175 publications (2011-2023) based on FMPs were identified and critically reviewed for transportation, analysis and ecotoxicological behaviours of FMPs in the environment. Textile industries, wastewater treatment plants, and household washing of clothes are significant sources of FMPs. In addition, various characterization techniques (e.g., FTIR, SEM, RAMAN, TGA, microscope, and X-Ray Fluorescence Spectroscopy) commonly used for the identification and analysis of FMPs are also discussed, which justifies the novelty aspects of this review. FMPs are pollutants of emerging concern due to their prevalence and persistence in the environment. FMPs are also found in the food chain, which is an alarming situation for living organisms, including effects on the nervous system, digestive system, circulatory system, and genetic alteration. This review will provide readers with a comparison of different analytical techniques, which will be helpful for researchers to select the appropriate analytical techniques for their study and enhance their knowledge about the harmful effects of FMPs.
This study analyzed the spatial-temporal change pattern and underlying factors in production-living-ecological space (PLES) of Nanchong City, China, over the past 20 years using historical land use data (2000, 2010, 2020). A land use transfer matrix was calculated from the historical land use maps, and spatial analysis was conducted to analyze changes in the land use dynamics degree, standard deviation ellipse, and center of gravity. The results showed that there was a rapid spatial evolution of the PLES in Nanchong from 2000 to 2010, followed by a stabilization in the second decade. The transfer of ecological-production space occurred mainly in the Jialing and Yilong River basins, while the reduction of production space and the increase of living space were most prominent in the intersection of three districts (Shunqing, Jialing, and Gaoping districts). The return of production-ecological space was observed in the south and northeast of Yingshan, and there was little notable transfer of other types. The distribution of production space in Nanchong evolved in a north-south to east-west trend, with the center of gravity moving from Yilong to Peng'an County. The living space and production space expanded in a north-south direction, and the center of gravity position was in Nanbu, indicating a more balanced growth or decrease in the last 20 years. The changes in the spatial-temporal pattern of PLES in Nanchong were attributed to the intertwined factors of national policies, economic development, population growth, and the natural environment. This study introduced a novel approach towards rational planning of land resources in Nanchong, which may facilitate more sustainable urban planning and development.
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.
Polycyclic aromatic hydrocarbons (PAHs) in a sediment core collected from Langkawi Island of the Andaman Sea, Malaysia were determined by GC/MS, the vertical variations of concentration and distributions of PAHs were investigated. In combining with 210Pb-dating, the PAHs sedimentary record in the last 100 years was reconstructed and their possible sources were also discussed. The sigmaPAH concentration ranged from 13.2-60.1 ng x g(-1) in the whole sedimentary section (0-56 cm) with the dominant compounds of phenanthrene, naphthalene and perylene. The sediments contaminated to a lesser extent comparing with the surrounding waters. Before the 1920s, the concentrations of PAHs were considered to be the background level, which was implied from the natural inputs. The historical records of PAHs in the core showed that two distinct peaks which represented the input time of 1960s and 1980s, respectively, inferred that there were some relatively dramatically land-based inputs, and human activities leaded a clear impact to these waters during these periods. Furthermore, PAHs diagnostic ratios indicated that PAHs in the core sediments were mainly of pyrolytic origin (combustion), accompanied with minor petroleum origin. These were related with agriculture, industry, ocean import and export, and shipping activities in the surrounding regions. Meanwhile as the vital communication line, the marine transportation of the Strait of Malacca had influenced the environmental quality of the Andaman Sea. Meanwhile, based on the sedimentary record, PAHs concentrations were found to correlate positively with humanism activities and socioeconomic development (Gross Domestic Production) in the surrounding regions.
Sustainable agriculture is important for preserving environmental health and simultaneously gaining economic profits while maintaining social and economic equity. One way to evaluate sustainable agriculture is by studying agricultural eco-efficiency (AEE). Hence, this study constructed a data-driven method to evaluate and optimize AEE with the aim of providing a basis for improving the sustainable development of regional agriculture. Sixteen cities in Anhui Province, China, were considered in the study, and the variables used were agricultural resource inputs, environmental pollution, and agricultural economic development. Agricultural non-point source pollution (NPSP) emissions were considered the undesired output to build an AEE evaluation index system. Furthermore, a data envelopment analysis (DEA) model was established to analyse AEE from the static and dynamic perspectives. The spatial development and the temporal and spatial characteristics of AEE were also analysed. In addition, we applied a random effect (RE) panel Tobit model to quantitatively analyse the influencing factors of AEE from the input perspective and then proposed reasonable suggestions for improving the sustainable development of regional agriculture. Our findings show that the overall agricultural development in the 16 cities in Anhui Province has been continuously improving, even though there is an agglomeration of spatial development in some regions. In conclusion, this study provides suggestions and references for policy makers and agricultural practitioners regarding how to improve regional AEE and promote the sustainable development of the regional agricultural economy.
The importance of lianas through time and their effect on tree reproduction are evaluated for the first time in a Southeast Asian Dipterocarp forest. We quantified flower and seed production by lianas and trees for 13 years, assessed liana loads in the crowns of all trees larger than 30 cm in diameter at breast height (1.3 m) in 2002 and 2014, and assessed levels of reproduction for the same trees during a strong general flowering event in 2014 for the 50-ha forest dynamics plot at the Pasoh Forest Reserve, Malaysia. General flowering refers to synchronous reproduction by hundreds of plant species at irregular, multiyear intervals and only occurs in Southeast Asian Dipterocarp forests. Overall, lianas were present in 50% of tree crowns and comprised 31% of flower production and 46% of seed production. Lianas reduced growth, survival, and reproduction by their host trees. Lianas were less frequent in canopy- emergent trees, Dipterocarps comprised a disproportionately large proportion of canopy emergents, and, as a consequence, lianas were less frequent in Dipterocarps than in trees from other plant families. Lianas infested the crowns of significantly fewer trees in 2014 (47.9%) than in 2002 (52.3%); however, the decrease was restricted to trees with the lightest liana loads and sample sizes and statistical power were enormous. Lianas comprised a stable proportion of flower production and a highly variable proportion of seed production from 2002 through 2013. We conclude lianas have a huge impact on trees in this forest and were a stable component of the forest between 2002 and 2014. The emergent habit and associated ability to avoid lianas might contribute to the success of the Dipterocarpaceae.
The adverse effects of traffic-related air pollution on children's respiratory health have been widely reported, but few studies have evaluated the impact of traffic-control policies designed to reduce urban air pollution. We assessed associations between traffic-related air pollutants and respiratory/allergic symptoms amongst 8-9 year-old schoolchildren living within the London Low Emission Zone (LEZ). Information on respiratory/allergic symptoms was obtained using a parent-completed questionnaire and linked to modelled annual air pollutant concentrations based on the residential address of each child, using a multivariable mixed effects logistic regression analysis. Exposure to traffic-related air pollutants was associated with current rhinitis: NOx (OR 1.01, 95% CI 1.00-1.02), NO2 (1.03, 1.00-1.06), PM10 (1.16, 1.04-1.28) and PM2.5 (1.38, 1.08-1.78), all per μg/m3 of pollutant, but not with other respiratory/allergic symptoms. The LEZ did not reduce ambient air pollution levels, or affect the prevalence of respiratory/allergic symptoms over the period studied. These data confirm the previous association between traffic-related air pollutant exposures and symptoms of current rhinitis. Importantly, the London LEZ has not significantly improved air quality within the city, or the respiratory health of the resident population in its first three years of operation. This highlights the need for more robust measures to reduce traffic emissions.
The assessment of surface water quality is often laborious, expensive and tedious, as well as impractical, especially for the developing and middle-income countries in the ASEAN region. The application of the water quality index (WQI), which depends on several independent key parameters, has great potential and is a useful tool in this region. Therefore, this study aims to find out the spatial variability of various water quality parameters in geographical information system (GIS) environment and perform a comparative study among the ASEAN WQI systems. At present, there are four ASEAN countries which have implemented the WQI system to evaluate their surface water quality, which are (i) Own WQI system-Malaysia, Thailand and Vietnam-and (ii) Adopted WQI system: Indonesia. A spatial distribution of 12 water quality parameters in the Selangor river basin, Malaysia, was plotted and then applied into the different ASEAN WQI systems. The WQI values obtained from the different WQI systems have an appreciable difference, even for the same water samples due to the disparity in the parameter selection and the standards among them. WQI systems which consider all biophysicochemical parameters provide a consistent evaluation (Very Poor), but the system which either considers physicochemical or biochemical parameters gives a relatively lenient evaluation (Fair-Poor). The Selangor river basin is stressed and impacted by all physical, biological and chemical parameters caused by both the aridity of the climate and anthropogenic activities. Therefore, it is crucial to include all these aspects into the evaluation and corresponding actions should be taken.
Rivers in Malaysia are classified based on water quality index (WQI) that comprises of six parameters, namely, ammoniacal nitrogen (AN), biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), pH, and suspended solids (SS). Due to its tropical climate, the impact of seasonal monsoons on river quality is significant, with the increased occurrence of extreme precipitation events; however, there has been little discussion on the application of artificial intelligence models for monsoonal river classification. In light of these, this study had applied artificial neural network (ANN) and support vector machine (SVM) models for monsoonal (dry and wet seasons) river classification using three of the water quality parameters to minimise the cost of river monitoring and associated errors in WQI computation. A structured trial-and-error approach was applied on input parameter selection and hyperparameter optimisation for both models. Accuracy, sensitivity, and precision were selected as the performance criteria. For dry season, BOD-DO-pH was selected as the optimum input combination by both ANN and SVM models, with testing accuracy of 88.7% and 82.1%, respectively. As for wet season, the optimum input combinations of ANN and SVM models were BOD-pH-SS and BOD-DO-pH with testing accuracy of 89.5% and 88.0%, respectively. As a result, both optimised ANN and SVM models have proven their prediction capacities for river classification, which may be deployed as effective and reliable tools in tropical regions. Notably, better learning and higher capacity of the ANN model for dataset characteristics extraction generated better predictability and generalisability than SVM model under imbalanced dataset.
Presence of copper within water bodies deteriorates human health and degrades natural environment. This heavy metal in water is treated using a promising biochar derived from rambutan (Nephelium lappaceum) peel through slow pyrolysis. This research compares the efficacies of artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and multiple linear regression (MLR) models and evaluates their capability in estimating the adsorption efficiency of biochar for the removal of Cu (II) ions based on 480 experimental sets obtained in a laboratory batch study. The effects of operational parameters such as contact time, operating temperature, biochar dosage, and initial Cu (II) ion concentration on removing Cu (II) ions were investigated. Eleven different training algorithms in ANN and 8 different membership functions in ANFIS were compared statistically and evaluated in terms of estimation errors, which are root mean squared error (RMSE), mean absolute error (MAE), and accuracy. The effects of number of hidden neuron in ANN model and fuzzy set combination in ANFIS were studied. In this study, ANFIS model with Gaussian membership function and fuzzy set combination of [4 5 2 3] was found to be the best method, with accuracy of 90.24% and 87.06% for training and testing dataset, respectively. Contribution of this study is that ANN, ANFIS, and MLR modeling techniques were used for the first time to study the adsorption of Cu (II) ions from aqueous solutions using rambutan peel biochar.
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).
The identification of nitrogen sources and cycling processes is critical to the management of nitrogen pollution. Here, we used both stable (δ15N-NO3-, δ18O-NO3-, δ15N-NH4+) and radiogenic (222Rn) isotopes together with nitrogen concentrations to evaluate the relative importance of point (i.e. sewage) and diffuse sources (i.e. agricultural-derived NO3- from groundwater, drains and creeks) in driving nitrogen dynamic in a shallow coastal embayment, Port Phillip Bay (PPB) in Victoria, Australia. This study is an exemplar of nitrogen-limited coastal systems around the world where nitrogen contamination is prevalent and where constraining it may be challenging. In addition to surrounding land use, we found that the distributions of NO3- and NH4+ in the bay were closely linked to the presence of drift algae. Highest NO3- and NH4+ concentrations were 315 μmol L-1 and 2140 μmol L-1, respectively. Based on the isotopic signatures of NO3- (δ15N: 0.17 to 21‰; δ18O: 3 to 26‰) and NH4+ (δ15N: 30 to 39‰) in PPB, the high nitrogen concentrations were attributed to three major sources which varied between winter and summer; (1) nitrified sewage effluent and drift algae derived NH4+ mainly during winter, (2) NO3- mixture from atmospheric deposition, drains and creeks predominantly observed during summer and (3) groundwater and sewage derived NO3- during both surveys. The isotopic composition of NO3- also suggested the removal of agriculture-derived NO3- through denitrification was prevalent during transport. This study highlights the role of terrestrial-coastal interactions on nitrogen dynamics and illustrates the importance of submarine groundwater discharge as a prominent pathway of diffuse NO3- inputs. Quantifying the relative contributions of multiple NO3- input pathways, however, require more extensive efforts and is an important avenue for future research.
Charcoal production activities at the Matang Mangrove Forest Reserve (MMFR) in Peninsular Malaysia have a potential to emit volatile compounds such as Hg back into the ambient environment, raising concerns on the public health and safety. The present study was aimed at analyzing Hg concentration from different plant/animal tissues and sediment samples (in total 786 samples) to understand clearly the Hg distribution at the MMFR. Leaves of Rhizophora spp. showed higher Hg concentration with an increasing trend from young, to mature, to senescent and decomposing stages, which was possibly due to accumulation of Hg over time. The low Hg concentration in Rhizophora roots and bark suggests a limited absorption from the sediments and a meagre accumulation/partitioning by the plant tissue, respectively. In the case of mangrove cockles the concentration of Hg was lower than the permissible limits for seafood consumption. Although the mangrove gastropod - Cassidula aurisfelis Bruguière had rather elevated Hg in the muscle tissue, it is still less than the environmental safely limit. Beside the chances of atmospheric deposition for Hg, the sediment samples were found to be unpolluted in nature, indicating that in general the MMFR is still safe in terms of Hg pollution.
Environmental exposure to active pharmaceutical ingredients (APIs) can have negative effects on the health of ecosystems and humans. While numerous studies have monitored APIs in rivers, these employ different analytical methods, measure different APIs, and have ignored many of the countries of the world. This makes it difficult to quantify the scale of the problem from a global perspective. Furthermore, comparison of the existing data, generated for different studies/regions/continents, is challenging due to the vast differences between the analytical methodologies employed. Here, we present a global-scale study of API pollution in 258 of the world's rivers, representing the environmental influence of 471.4 million people across 137 geographic regions. Samples were obtained from 1,052 locations in 104 countries (representing all continents and 36 countries not previously studied for API contamination) and analyzed for 61 APIs. Highest cumulative API concentrations were observed in sub-Saharan Africa, south Asia, and South America. The most contaminated sites were in low- to middle-income countries and were associated with areas with poor wastewater and waste management infrastructure and pharmaceutical manufacturing. The most frequently detected APIs were carbamazepine, metformin, and caffeine (a compound also arising from lifestyle use), which were detected at over half of the sites monitored. Concentrations of at least one API at 25.7% of the sampling sites were greater than concentrations considered safe for aquatic organisms, or which are of concern in terms of selection for antimicrobial resistance. Therefore, pharmaceutical pollution poses a global threat to environmental and human health, as well as to delivery of the United Nations Sustainable Development Goals.
Livestock farms are commonly regarded as the main sources of antibiotic resistance genes (ARGs), emerging pollutants with potential implications for human health, in the environment. This study investigated the occurrence and contamination profiles of nine ARGs of three types from swine manure to receiving environments (soil and water) in Guangdong Province, southern China. All ARGs occurred in 100% of swine manure samples. Moreover, the absolute concentration of total ARGs varied from 3.01 × 108 to 7.18 × 1014 copies/g, which was significantly higher than that in wastewater and manured soil (p 0.05). However, the number of ARGs (ermB, qnrS, acc(6')-Ib, tetM, tetO and tetQ) decreased but were not eliminated by wastewater treatment components (p
The marine aquaculture industry has caused a suite of adverse environmental consequences, including offshore eutrophication. However, little is known about the extent to which aquaculture effluents affect nearby wetland ecosystems. We carried out a field experiment in a mangrove stand located between two effluent-receiving creeks to estimate the extent to which marine aquaculture affects the soil nutrient distribution and plant nutrient status of adjacent mangroves. Carbon (C), nitrogen (N), and phosphorus (P) contents and C isotopic signatures were determined seasonally in creeks, pore water, surface soils, and in the leaves of the dominant mangrove species Kandelia obovata. The creeks exhibited nutrient enrichment (2.44 mg N L-1 and 0.09 mg P L-1 on average). The soils had N (from 1.40 to 2.70 g kg-1) and P (from 0.58 to 2.76 g kg-1) much greater than those of pristine mangrove forests. Combined analyses of the N:P ratio, nutrient resorption efficiency, and proficiency indicated that soil P met plant demands, but plants in most plots showed N limitation, suggesting that soil nutrient accumulation did not fundamentally impact the plant nutrient status. Collectively, this case study shows that marine aquaculture farms can affect adjacent mangrove stands even though their effluents are not directly discharged into the mangrove stands, but mangrove forests may have substantial buffering capabilities for long-term nutrient loading.
Synthetic dyes used in the textile and paper industries pose a major threat to the environment. In the present research work, the adsorption efficiency of the natural adsorbent Strychnos potatorum Linn (Fam: Loganiaceae) seeds were examined against the reactive orange-M2R dye from aqueous solution by varying the process conditions such as contact time, pH, adsorbent dosage, and initial dye concentration on adsorption of anionic azo dye. This study compares different types of artificial neural networks which are feedforward artificial neural network (FANN) and nonlinear autoregressive exogenous (NARX) model to predict the efficiency of a cost-effective natural adsorbent Strychnos potatorum Linn seeds on removing reactive orange-M2R dye from aqueous solution. Twelve training algorithms of neural network were compared, and the prediction on the adsorption performance of anionic azo dye from aqueous solution using Strychnos potatonum Linn seeds was evaluated by using the root mean squared error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and accuracy. For FANN model, Levenberg-Marquardt (LM) backpropagation with 19 hidden neurons was selected as the optimum FANN model, with R2 of 0.994 and accuracy of 87.20%, 98.21%, and 66.60% for training, testing, and validation datasets, respectively. For NARX model, LM with 8 hidden neurons was selected as the most suitable training algorithm, with R2 value of more than 0.99 and accuracy of 88.00%, 90.91%, and 75.00% for training, testing, and validation datasets, respectively. NARX model accurately predicted the adsorption of anionic azo dye from aqueous solution using Strychnos potatonum Linn seeds with better performance than FANN model.
Contamination of endocrine disrupting compounds (EDCs) in tap water is an emerging global issue, and there are abundant influencing factors that have an ambivalent effect on their transportation and fate. Different housing types vary in terms of water distribution system operation and design, water consumption choices, and other hydraulic factors, which potentially affect the dynamics, loadings, and partitioning of pollutants in tap water. Thus, this study analyzed 18 multiclass EDCs in tap water from different housing types (i.e., landed and high-rise) and the associated health risks. Sample analyses revealed the presence of 16 EDCs, namely hormones (5), pharmaceuticals (8), a pesticide (1), and plasticizers (2) in tap water, with the prevalent occurrence of bisphenol A up to 66.40 ng/L in high-rise housing. The presence of caffeine and sulfamethoxazole distribution in tap water was significantly different between landed and high-rise housings (t(152) = -2.298, p = 0.023 and t(109) = 2.135, p = 0.035). Moreover, the salinity and conductivity of tap water in high-rise housings were significantly higher compared to those in landed housings (t(122) = 2.411, p = 0.017 and t(94) = 2.997, p = 0.003, respectively). Furthermore, there were no potential health risks of EDCs (risk quotient
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
Active pharmaceutical ingredients (APIs) are typical endocrine disruptors found in common pharmaceuticals and personal care products, which are frequently detected in aquatic environments, especially surface water treated for drinking. However, current treatment technologies are inefficient for removing emerging endocrine disruptors, leading to the potential contamination of tap water. This study employed an optimized analytical method comprising solid-phase extraction and liquid chromatography-tandem mass spectrometry (SPE-LC-MS/MS) to detect APIs in tap water in Putrajaya, Malaysia. Several therapeutic classes of pharmaceuticals and personal care products, including anti-inflammatory drugs (dexamethasone and diclofenac), antibiotics (sulfamethoxazole and triclosan), antiepileptics (primidone), antibacterial agents (ciprofloxacin), beta-blockers (propranolol), psychoactive stimulants (caffeine), and antiparasitic drugs (diazinon), were detected in the range of