Synthetic plastics, which are lightweight, durable, elastic, mouldable, cheap, and hydrophobic, were originally invented for human convenience. However, their non-biodegradability and continuous accumulation at an alarming rate as well as subsequent conversion into micro/nano plastic scale structures via mechanical and physio-chemical degradation pose significant threats to living beings, organisms, and the environment. Various minuscule forms of plastics detected in water, soil, and air are making their passage into living cells. High temperature and ambient humidity increase the degradation potential of plastic polymers photo-catalytically under sunlight or UV-B radiations. Microplastics (MPs) of polyethylene terephthalate, polyethylene, polystyrene, polypropylene, and polyvinyl chloride have been detected in bottled water. These microplastics are entering into the food chain cycle, causing serious harm to all living organisms. MPs entering into the food chain are usually inert in nature, possessing different sizes and shapes. Once they enter a cell or tissue, it causes mechanical damage, induces inflammation, disturbs metabolism, and even lead to necrosis. Various generation routes, types, impacts, identification, and treatment of microplastics entering the water bodies and getting associated with various pollutants are discussed in this review. It emphasizes potential detection techniques like pyrolysis, gas chromatography-mass spectrometry (GC-MS), micro-Raman spectroscopy, and fourier transform infrared spectroscopy (FT IR) spectroscopy for microplastics from water samples.
The emergence of microplastics (MPs) pollution as a global environmental concern has attracted significant attention in the last decade. The majority of the human population spends most of their time indoors, leading to increased exposure to MPs contamination through various sources such as settled dust, air, drinking water and food. Although research on indoor MPs has intensified significantly in recent years, comprehensive reviews on this topic remain limited. Therefore, this review comprehensively analyses the occurrence, distribution, human exposure, potential health impact and mitigation strategies of MPs in the indoor air environment. Specifically, we focus on the risks associated with finer MPs that can translocate into the circulatory system and other organs, emphasizing the need for continued research to develop effective strategies to mitigate the risks associated with MPs exposure. Our findings suggest that indoor MPs impose potential risk to human health, and strategies for mitigating exposure should be further explored.
The generation of microplastics (MPs) has increased recently and become an emerging issue globally. Due to their long-term durability and capability of traveling between different habitats in air, water, and soil, MPs presence in freshwater ecosystem threatens the environment with respect to its quality, biotic life, and sustainability. Although many previous works have been undertaken on the MPs pollution in the marine system recently, none of the study has covered the scope of MPs pollution in the freshwater. To consolidate scattered knowledge in the literature body into one place, this work identifies the sources, fate, occurrence, transport pathways, and distribution of MPs pollution in the aquatic system with respect to their impacts on biotic life, degradation, and detection techniques. This article also discusses the environmental implications of MPs pollution in the freshwater ecosystems. Certain techniques for identifying MPs and their limitations in applications are presented. Through a literature survey of over 276 published articles (2000-2023), this study presents an overview of solutions to the MP pollution, while identifying research gaps in the body of knowledge for further work. It is conclusive from this review that the MPs exist in the freshwater due to an improper littering of plastic waste and its degradation into smaller particles. Approximately 15-51 trillion MP particles have accumulated in the oceans with their weight ranging between 93,000 and 236,000 metric ton (Mt), while about 19-23 Mt of plastic waste was released into rivers in 2016, which was projected to increase up to 53 Mt by 2030. A subsequent degradation of MPs in the aquatic environment results in the generation of NPs with size ranging from 1 to 1000 nm. It is expected that this work facilitates stakeholders to understand the multi-aspects of MPs pollution in the freshwater and recommends policy actions to implement sustainable solutions to this environmental problem.
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.
Clean air is critical component for health and survival of human and wildlife, as atmospheric pollution is associated with a number of significant diseases including cancer. However, due to rapid industrialization and population growth, activities such as transportation, household, agricultural, and industrial processes contribute to air pollution. As a result, air pollution has become a significant problem in many cities, especially in emerging countries like India. To maintain ambient air quality, regular monitoring and forecasting of air pollution is necessary. For that purpose, machine learning has emerged as a promising technique for predicting the Air Quality Index (AQI) compared to conventional methods. Here we apply the AQI to the city of Visakhapatnam, Andhra Pradesh, India, focusing on 12 contaminants and 10 meteorological parameters from July 2017 to September 2022. For this purpose, we employed several machine learning models, including LightGBM, Random Forest, Catboost, Adaboost, and XGBoost. The results show that the Catboost model outperformed other models with an R2 correlation coefficient of 0.9998, a mean absolute error (MAE) of 0.60, a mean square error (MSE) of 0.58, and a root mean square error (RMSE) of 0.76. The Adaboost model had the least effective prediction with an R2 correlation coefficient of 0.9753. In summary, machine learning is a promising technique for predicting AQI with Catboost being the best-performing model for AQI prediction. Moreover, by leveraging historical data and machine learning algorithms enables accurate predictions of future urban air quality levels on a global scale.
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 rapid growth of population and economy has led to an increase in urban air pollutants, greenhouse gases, energy shortages, environmental degradation, and species extinction, all of which affect ecosystems, biodiversity, and human health. Atmospheric pollution sources are divided into direct and indirect pollutants. Through analysis of the sources of pollutants, the self-functioning of different plants can be utilized to purify the air quality more effectively. Here, we explore the absorption of greenhouse gases and particulate matter in cities as well as the reduction of urban temperatures by plants based on international scientific literature on plant air pollution mitigation, according to the adsorption, dust retention, and transpiration functions of plants. At the same time, it can also reduce the occurrence of extreme weather. It is necessary to select suitable tree species for planting according to different plant functions and environmental needs. In the context of tight urban land use, the combination of vertical greening and urban architecture, through the rational use of plants, has comprehensively addressed urban air pollution. In the future, in urban construction, attention should be paid to the use of heavy plants and the protection and development of green spaces. Our review provides necessary references for future urban planning and research.
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.
Organophosphate esters (OPEs) have received considerable attention in environmental research due to their extensive production, wide-ranging applications, prevalent presence, potential for bioaccumulation, and associated ecological and health concerns. Low efficiency of OPE removal results in the effluents of wastewater treatment plants emerging as a significant contributor to OPE contamination. Their notable solubility and mobility give OPEs the potential to be transported to coastal ecosystems via river discharge and atmospheric deposition. Previous research has indicated that OPEs have been widely detected in the atmosphere and water bodies. Atmospheric deposition across air-water exchange is the main input route for OPEs into the environment and ecosystems. The main processes that contribute to air-water exchange is air-water diffusion, dry deposition, wet deposition, and the air-water volatilization process. The present minireview links together the source, occurrence, and exchange of OPEs in water and air, integrates the occurrence and profile data, and summarizes their air-water exchange in the environment.
Due to the rapid development of economy and society around the world, the most urban city is experiencing tropospheric ozone or commonly known as ground-level air pollutants. The concentration of air pollutants must be identified as an early precaution step by the local environmental or health agencies. This work aims to apply the artificial neural network (ANN) in estimating the ozone concentration forecast in Bangi. It consists of input variables such as temperature, relative humidity, concentration of nitrogen dioxide, time, UVA and UVB rays obtained from routine monitoring, and data recorded. Ten hidden layer is utilized to obtain the optimized ozone concentration, which is the output layer of the ANN framework. The finding showed that the meteorology condition and emission patterns play an important part in influencing the ozone concentration. However, a single network is sufficient enough to estimate the concentration despite any circumstances. Thus, it can be concluded that ANN is able to give reliable and satisfactory estimations of ozone concentration for the following day.
In this study, the air quality index (AQI) of Indian cities of different tiers is predicted by using the vanilla recurrent neural network (RNN). AQI is used to measure the air quality of any region which is calculated on the basis of the concentration of ground-level ozone, particle pollution, carbon monoxide, and sulphur dioxide in air. Thus, the present air quality of an area is dependent on current weather conditions, vehicle traffic in that area, or anything that increases air pollution. Also, the current air quality is dependent on the climate conditions and industrialization in that area. Thus, the AQI is history-dependent. To capture this dependency, the memory property of fractional derivatives is exploited in this algorithm and the fractional gradient descent algorithm involving Caputo's derivative has been used in the backpropagation algorithm for training of the RNN. Due to the availability of a large amount of data and high computation support, deep neural networks are capable of giving state-of-the-art results in the time series prediction. But, in this study, the basic vanilla RNN has been chosen to check the effectiveness of fractional derivatives. The AQI and gases affecting AQI prediction results for different cities show that the proposed algorithm leads to higher accuracy. It has been observed that the results of the vanilla RNN with fractional derivatives are comparable to long short-term memory (LSTM).
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 recent years, paper-based point-of-care testing (POCT) has been widely used in medical diagnostics, food safety and environmental monitoring. However, a high-cost, time-consuming and equipment-dependent sample pretreatment technique is generally required for raw sample processing, which are impractical for low-resource and disease-endemic areas. Therefore, there is an escalating demand for a cost-effective, simple and portable pretreatment technique, to be coupled with the commonly used paper-based assay (e.g. lateral flow assay) in POCT. In this review, we focus on the importance of using paper as a platform for sample pretreatment. We firstly discuss the beneficial use of paper for sample pretreatment, including sample collection and storage, separation, extraction, and concentration. We highlight the working principle and fabrication of each sample pretreatment device, the existing challenges and the future perspectives for developing paper-based sample pretreatment technique.
In oil palm plantations, the fungicide hexaconazole is used to control Ganoderma infection that threatens to destroy or compromisethe palm. The application of hexaconazole is usually through soil drenching, trunk injection, or a combination of these two methods. It is therefore important to have a method to determine the residual amount of hexaconazole in the field such as in samples of water, soil, and leaf to monitor the use and fate of the fungicide in oil palm plantations. This study on the behaviour of hexaconazole in oil palm agro-environment was carried out at the UKM-MPOB Research Station, Bangi Lama, Selangor. Three experimental plots in this estate with 7-year-old Dura x Pisifera (DxP) palms were selected for the field trial. One plot was sprayed with hexaconazole at the manufacturer's recommended dosage, one at double the recommended dosage, and the third plot was untreated control. Hexaconazole residues in the soil, leaf, and water were determined before and after fungicide treatment. Soil samples were randomly collected from three locations at different depths (0-50 cm) and soil collected fromthe same depth were bulked together. Soil, water, and palm leaf were collected at -1 (day before treatment), 0 (day of treatment), 1, 3, 7, 14, 21, 70, 90, and 120 days after treatment. Hexaconazole was detected in soil and oil palm leaf, but was not detected in water from the nearby stream.
Cypermethrin is a pyrethroid insecticide commonly used to control bagworm infestation in oil palm plantations. It is applied through spraying onto the leaves where the bagworms reside. This article reports the fate of cypermethrin used in a Malaysian oil palm plantation during a typical dry season through the analysis of cypermethrin residue in environmental and palm oil samples collected from a supervised field trial. Residues of cypermethrin were not detected in the soil samples collected at different depths, water samples collected at different points in the experimental plots, and oil samples extracted from fresh fruit bunches (FFB) harvested from each plot for both single and double dosages of treatment throughout the study interval. Analysis of leaf samples, however, revealed that cypermethrin residue was detected for both pesticide treatments up to day 2 after cypermethrin application.
A key driver of rain forest degradation is rampant commercial logging. Reduced-impact logging (RIL) techniques dramatically reduce residual damage to vegetation and soils, and they enhance the long-term economic viability of timber operations when compared to conventionally managed logging enterprises. Consequently, the application of RIL is increasing across the tropics, yet our knowledge of the potential for RIL also to reduce the negative impacts of logging on biodiversity is minimal. We compare the impacts of RIL on birds, leaf-litter ants, and dung beetles during a second logging rotation in Sabah, Borneo, with the impacts of conventional logging (CL) as well as with primary (unlogged) forest. Our study took place 1-8 years after the cessation of logging. The species richness and composition of RIL vs. CL forests were very similar for each taxonomic group. Both RIL and CL differed significantly from unlogged forests in terms of bird and ant species composition (although both retained a large number of the species found in unlogged forests), whereas the composition of dung beetle communities did not differ significantly among forest types. Our results show little difference in biodiversity between RIL and CL over the short-term. However, biodiversity benefits from RIL may accrue over longer time periods after the cessation of logging. We highlight a severe lack of studies investigating this possibility. Moreover, if RIL increases the economic value of selectively logged forests (e.g., via REDD+, a United Nations program: Reducing Emissions from Deforestation and Forest Degradation in Developing Countries), it could help prevent them from being converted to agricultural plantations, which results in a tremendous loss of biodiversity.
Agricultural expansion is the largest threat to global biodiversity. In particular, the rapid spread of tree plantations is a primary driver of deforestation in hyperdiverse tropical regions. Plantations tend to support considerably lower biodiversity than native forest, but it remains unclear whether plantation traits affect their ability to sustain native wildlife populations, particularly for threatened taxa. If animal diversity varies across plantations with different characteristics, these traits could be manipulated to make plantations more "wildlife friendly." The degree to which plantations create edge effects that degrade habitat quality in adjacent forest also remains unclear, limiting our ability to predict wildlife persistence in mixed-use landscapes. We used systematic camera trapping to investigate mammal occurrence and diversity in oil palm plantations and adjacent forest in Sabah, Malaysian Borneo. Mammals within plantations were largely constrained to locations near native forest; the occurrence of most species and overall species richness declined abruptly with decreasing forest proximity from an estimated 14 species at the forest ecotone to -1 species 2 km into the plantation. Neither tree height nor canopy cover within plantations strongly affected mammal diversity or occurrence, suggesting that manipulating tree spacing or planting cycles might not make plantations more wildlife friendly. Plantations did not appear to generate strong edge effects; mammal richness within forest remained high and consistent up to the plantation ecotone. Our results suggest that land-sparing strategies, as opposed to efforts to make plantations more wildlife-friendly, are required for regional wildlife conservation in biodiverse tropical ecosystems.
Strong global demand for tropical timber and agricultural products has driven large-scale logging and subsequent conversion of tropical forests. Given that the majority of tropical landscapes have been or will likely be logged, the protection of biodiversity within tropical forests thus depends on whether species can persist in these economically exploited lands, and if species cannot persist, whether we can protect enough primary forest from logging and conversion. However, our knowledge of the impact of logging and conversion on biodiversity is limited to a few taxa, often sampled in different locations with complex land-use histories, hampering attempts to plan cost-effective conservation strategies and to draw conclusions across taxa. Spanning a land-use gradient of primary forest, once- and twice-logged forests, and oil palm plantations, we used traditional sampling and DNA metabarcoding to compile an extensive data set in Sabah, Malaysian Borneo for nine vertebrate and invertebrate taxa to quantify the biological impacts of logging and oil palm, develop cost-effective methods of protecting biodiversity, and examine whether there is congruence in response among taxa. Logged forests retained high species richness, including, on average, 70% of species found in primary forest. In contrast, conversion to oil palm dramatically reduces species richness, with significantly fewer primary-forest species than found on logged forest transects for seven taxa. Using a systematic conservation planning analysis, we show that efficient protection of primary-forest species is achieved with land portfolios that include a large proportion of logged-forest plots. Protecting logged forests is thus a cost-effective method of protecting an ecologically and taxonomically diverse range of species, particularly when conservation budgets are limited. Six indicator groups (birds, leaf-litter ants, beetles, aerial hymenopterans, flies, and true bugs) proved to be consistently good predictors of the response of the other taxa to logging and oil palm. Our results confidently establish the high conservation value of logged forests and the low value of oil palm. Cross-taxon congruence in responses to disturbance also suggests that the practice of focusing on key indicator taxa yields important information of general biodiversity in studies of logging and oil palm.
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.
To manage and conserve biodiversity, one must know what is being lost, where, and why, as well as which remedies are likely to be most effective. Metabarcoding technology can characterise the species compositions of mass samples of eukaryotes or of environmental DNA. Here, we validate metabarcoding by testing it against three high-quality standard data sets that were collected in Malaysia (tropical), China (subtropical) and the United Kingdom (temperate) and that comprised 55,813 arthropod and bird specimens identified to species level with the expenditure of 2,505 person-hours of taxonomic expertise. The metabarcode and standard data sets exhibit statistically correlated alpha- and beta-diversities, and the two data sets produce similar policy conclusions for two conservation applications: restoration ecology and systematic conservation planning. Compared with standard biodiversity data sets, metabarcoded samples are taxonomically more comprehensive, many times quicker to produce, less reliant on taxonomic expertise and auditable by third parties, which is essential for dispute resolution.