Displaying publications 21 - 40 of 890 in total

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  1. Recent progress on phytoremediation of urban air pollution
    Duan X, Gu H, Lam SS, Sonne C, Lu W, Li H, et al.
    Chemosphere, 2024 Feb;349:140821.
    PMID: 38042424 DOI: 10.1016/j.chemosphere.2023.140821
    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.
    Matched MeSH terms: Environmental Monitoring
  2. Enhancing subsurface contamination assessment via ensemble prediction of ground electrical property: A Colorado AMD-impacted wetland case study
    Kumar A, Singh UK, Pradhan B
    J Environ Manage, 2024 Feb;351:119943.
    PMID: 38169263 DOI: 10.1016/j.jenvman.2023.119943
    Acid mine drainage (AMD) is recognized as a major environmental challenge in the Western United States, particularly in Colorado, leading to extreme subsurface contamination issue. Given Colorado's arid climate and dependence on groundwater, an accurate assessment of AMD-induced contamination is deemed crucial. While in past, machine learning (ML)-based inversion algorithms were used to reconstruct ground electrical properties (GEP) such as relative dielectric permittivity (RDP) from ground penetrating radar (GPR) data for contamination assessment, their inherent non-linear nature can introduce significant uncertainty and non-uniqueness into the reconstructed models. This is a challenge that traditional ML methods are not explicitly designed to address. In this study, a probabilistic hybrid technique has been introduced that combines the DeepLabv3+ architecture-based deep convolutional neural network (DCNN) with an ensemble prediction-based Monte Carlo (MC) dropout method. Different MC dropout rates (1%, 5%, and 10%) were initially evaluated using 1D and 2D synthetic GPR data for accurate and reliable RDP model prediction. The optimal rate was chosen based on minimal prediction uncertainty and the closest alignment of the mean or median model with the true RDP model. Notably, with the optimal MC dropout rate, prediction accuracy of over 95% for the 1D and 2D cases was achieved. Motivated by these results, the hybrid technique was applied to field GPR data collected over an AMD-impacted wetland near Silverton, Colorado. The field results underscored the hybrid technique's ability to predict an accurate subsurface RDP distribution for estimating the spatial extent of AMD-induced contamination. Notably, this technique not only provides a precise assessment of subsurface contamination but also ensures consistent interpretations of subsurface condition by different environmentalists examining the same GPR data. In conclusion, the hybrid technique presents a promising avenue for future environmental studies in regions affected by AMD or other contaminants that alter the natural distribution of GEP.
    Matched MeSH terms: Environmental Monitoring/methods
  3. Fulltext Factors influencing occupational exposure to pyrethroids and glyphosate: An analysis of urinary biomarkers in Malaysia, Uganda and the United Kingdom
    Mueller W, Jones K, Fuhrimann S, Ahmad ZNBS, Sams C, Harding AH, et al.
    Environ Res, 2024 Feb 01;242:117651.
    PMID: 37996007 DOI: 10.1016/j.envres.2023.117651
    BACKGROUND: Long-term exposure to pesticides is often assessed using semi-quantitative models. To improve these models, a better understanding of how occupational factors determine exposure (e.g., as estimated by biomonitoring) would be valuable.

    METHODS: Urine samples were collected from pesticide applicators in Malaysia, Uganda, and the UK during mixing/application days (and also during non-application days in Uganda). Samples were collected pre- and post-activity on the same day and analysed for biomarkers of active ingredients (AIs), including synthetic pyrethroids (via the metabolite 3-phenoxybenzoic acid [3-PBA]) and glyphosate, as well as creatinine. We performed multilevel Tobit regression models for each study to assess the relationship between exposure modifying factors (e.g., mixing/application of AI, duration of activity, personal protective equipment [PPE]) and urinary biomarkers of exposure.

    RESULTS: From the Malaysia, Uganda, and UK studies, 81, 84, and 106 study participants provided 162, 384 and 212 urine samples, respectively. Pyrethroid use on the sampling day was most common in Malaysia (n = 38; 47%), and glyphosate use was most prevalent in the UK (n = 93; 88%). Median pre- and post-activity 3-PBA concentrations were similar, with higher median concentrations post-compared to pre-activity for glyphosate samples in the UK (1.7 to 0.5 μg/L) and Uganda (7.6 to 0.8 μg/L) (glyphosate was not used in the Malaysia study). There was evidence from individual studies that higher urinary biomarker concentrations were associated with mixing/application of the AI on the day of urine sampling, longer duration of mixing/application, lower PPE protection, and less education/literacy, but no factor was consistently associated with exposure across biomarkers in the three studies.

    CONCLUSIONS: Our results suggest a need for AI-specific interpretation of exposure modifying factors as the relevance of exposure routes, levels of detection, and farming systems/practices may be very context and AI-specific.

    Matched MeSH terms: Environmental Monitoring/methods
  4. Biomonitoring of Exposures to Solvents and Metals in Electronics Manufacturing Facilities in Batam, Indonesia
    Lee JH, Gatera VA, Smith T, Panimbang F, Gonzalez A, Abdulah R, et al.
    New Solut, 2024 Feb;33(4):220-235.
    PMID: 38112404 DOI: 10.1177/10482911231218478
    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.
    Matched MeSH terms: Environmental Monitoring
  5. Assessment of radioactivity level and associated radiological hazard in fertilizer from Dhaka
    Siraz MMM, Al Mahmud J, Alam MS, Rashid MB, Hossain Z, Osman H, et al.
    Environ Monit Assess, 2024 Jan 23;196(2):192.
    PMID: 38263472 DOI: 10.1007/s10661-024-12328-4
    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.
    Matched MeSH terms: Environmental Monitoring
  6. Assessing radioactive contaminants in Kathmandu soils: measurement and risk analysis
    Upadhyay DR, Koirala G, Shah BR, Tajudin SM, Khanal R
    Environ Monit Assess, 2024 Jan 23;196(2):190.
    PMID: 38261087 DOI: 10.1007/s10661-023-12284-5
    Soil samples from vegetable farmland in densely populated wards of Nepal were analyzed for natural radionuclide levels, employing a NaI(Tl) 3" [Formula: see text] 3" gamma detector. The study aimed to evaluate the causes of radiation risk, attributing it to soil contamination resulting from the rapid urbanization and concretization that followed the earthquake in 2015. The activity concentration of radium-226, thorium-232, and potassium-40 and the ranges observed are 2.080±0.084-33.675±1.356 Bq kg[Formula: see text], 17.222±0.198-119.949±1.379 Bq kg[Formula: see text], and 11.203 ± 0.325-748.828±21.716 Bq kg[Formula: see text], respectively. The average values obtained for hazard indices are as follows: radium equivalent activity (82.779 Bq kg[Formula: see text]), absorbed dose rate (36.394 nGy h[Formula: see text]), annual effective dose equivalent (0.045 mSv yearr[Formula: see text]), gamma index (0.291), external hazard index (0.224), internal hazard index (0.253), excess lifetime cancer risk (0.159), annual gonadal dose equivalent (243.278 mSv year[Formula: see text]), alpha index (0.054), and activity utilization index (0.716). However, in most places, thorium-232 concentration is greater than those of the world average and recommended values. In specific locations such as Ward 4 in Baluwatar, the soil was found to have concentrations of Ra[Formula: see text] and K[Formula: see text] exceeding recommended limits. Despite this localized concern, the overall analysis of hazard indices across the studied areas revealed that most values were within permissible limits. This suggests that, on a broader scale, radiation exposure may not be a significant concern in the investigated regions. Nonetheless, the study recommends regular monitoring in additional locations to ensure a comprehensive and ongoing assessment of radiation levels.
    Matched MeSH terms: Environmental Monitoring*
  7. Occurrence and characteristics of microplastics pollution in tropical agricultural soils in Klang Valley, Malaysia
    Shanmugam SD, Praveena SM, Wahid SA, Liew JYC
    Environ Monit Assess, 2024 Jan 12;196(2):144.
    PMID: 38214797 DOI: 10.1007/s10661-024-12330-w
    Presently, microplastic pollution has emerged as a growing environmental risk around the world. Nevertheless, knowledge of the occurrence and characteristics of microplastics in tropical agricultural soil is limited. This study investigated the pollution of surface soil microplastics in two agricultural farms located at Klang Valley, Malaysia. An extraction method based on density separation by using saturated extraction solution (sodium sulfate, ρ = 2 g cm-3 and sucrose, ρ = 1.59 g cm-3 with a ratio 1:1, v/v) was carried out. The study revealed the mean particle size of soil microplastics with 3260.76 ± 880.38 μm in farm A and 2822.31 ± 408.48 μm in farm B. The dominant types of soil microplastics were fragments and films with major colors of white (59%) and transparent (28%) in farm A, while black (52%) and white (37.6%) in farm B. Representatives of soil microplastics detected polymers of polyvinyl chloride (PVC), high density polyethylene (HDPE), polycarbonate (PC), and polystyrene (PS). The sources of plastic products were black and white plastic pipes, black plastic films for vegetation, fertilizer bottles, plastic water containers and polystyrene storage boxes, and the breakdown processes, contributed to the microplastic pollution in these farms. The outcomes of this study will establish a better understanding of microplastic pollution in tropical agricultural soil in the Southeast Asian region. The findings would be beneficial as supportive reference for the endeavor to reduce microplastic pollution in agricultural soil.
    Matched MeSH terms: Environmental Monitoring
  8. Assessment of spatiotemporal variability of ultraviolet index (UVI) over Kerala, India, using satellite remote sensing (OMI/AURA) data
    Valappil NKM, Mammen PC, de Oliveira-Júnior JF, Cardoso KRA, Hamza V
    Environ Monit Assess, 2024 Jan 03;196(2):106.
    PMID: 38168710 DOI: 10.1007/s10661-023-12239-w
    The spatial and temporal dynamics of daily ultraviolet index (UVI) for a period of 18 years (2004-2022) over the Indian state of Kerala were statistically characterised in the study. The UVI measurements used for the study were derived from the ultraviolet-B (UVB) irradiance measured by the Ozone Monitoring Instrument (OMI) of the AURA satellite and classified into different severity levels for analysis. Basic statistics of daily, monthly and seasonal UVI as well as Mann-Kendall (MK) statistical trend characteristics and the rate of change of daily UVI using Theil-Sen's slope test were also evaluated. A higher variability of UVI characteristics was observed in the Kerala region, and more than 79% of the measurements fell into the categories of very high and extreme UVI values, which suggests the need of implementation of appropriate measures to reduce health risks. Although the UVI measured during the study period shows a slight decrease, most of the data show a seasonal variation with undulating low and peak values. Higher UVI are observed during the months of March, April and September. The region also has higher UVI during the southwest monsoon (SWM) and summer seasons. Although Kerala region as a single whole unit, UVI show a non-significant decreasing trend (-0.83), the MK test revealed the increasing and decreasing trends of UVI ranging from -1.96 to 0.41 facilitated the delineation of areas (domains) where UVI are increasing or decreasing. The domain of UVI increase occupies the central and southern (S) parts, and the domains of decrease cover the northern (N) and S parts of the Kerala region. The rate of change of daily UVI in domain of increase and decrease shows an average rate of 0.34 × 10-5 day-1 and -2 × 10-5 day-1, respectively. The parameters (rainfall, air temperature, cloud optical depth (COD) and solar zenith angle (SZA)) that affect the strength of UV rays reaching the surface indicate that a cloud-free atmosphere or low thickness clouds prevails in the Kerala region. Overall, the study results indicate the need for regular monitoring of UVI in the study area and also suggest appropriate campaigns to disseminate information and precautions for prolonged UVI exposure to reduce the adverse health effects, since the study area has a high population density.
    Matched MeSH terms: Environmental Monitoring
  9. The spatial distribution and physico-chemical characteristic of microplastics in the sediment and cockle (Anadara granosa) from the coastal waters of East Java, Indonesia, and the health hazards associated with cockle consumption
    Rahmatin NM, Soegianto A, Irawan B, Payus CM, Indriyasari KN, Marchellina A, et al.
    Mar Pollut Bull, 2024 Jan;198:115906.
    PMID: 38070399 DOI: 10.1016/j.marpolbul.2023.115906
    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.
    Matched MeSH terms: Environmental Monitoring
  10. Exploring the microplastic pollution: Unveiling origins and varieties in coastal sediments and waters of the Bushehr Province, Persian Gulf, Iran
    Gholizadeh M, Shadi A, Abadi A, Nemati M, Senapathi V, Karthikeyan S, et al.
    Mar Pollut Bull, 2024 Jan;198:115939.
    PMID: 38128339 DOI: 10.1016/j.marpolbul.2023.115939
    In this study, microplastic (MP) pollution in the coastal sediments and tidal waters of Bushehr province in the Persian Gulf was comprehensively investigated. The sampling stations were selected based on their proximity to various human activities in January and February 2022, such as tourism, fishing, urban development and industry. The results showed that the abundance of MP associated with different human activities varied. The highest concentrations were observed near the petrochemical industry in Asaluyeh, followed by the densely populated Bushehr and the fishing port of Dayyer. Other areas such as Ganaveh, Deylam and Mand also showed varying levels of MP contamination. The average MP concentration was 1.67 × 104 particles/km2 in surface water and 1346.67 ± 601.69 particles/kg in dry sediment. Fiber particles were in the majority in both sediment and water samples, mainly black. The sediment samples had a size range of 100-500 μm (41.34 %), while the water samples were between 500 and 1000 μm (33.44 %). The main polymers found were polyethylene (PE) and polypropylene (PP). This assessment highlights the widespread problem of microplastic pollution in the coastal and intertidal zones of Bushehr province in the Persian Gulf.
    Matched MeSH terms: Environmental Monitoring/methods
  11. Fulltext Gas concentration mapping and source localization for environmental monitoring through unmanned aerial systems using model-free reinforcement learning agents
    Husnain AU, Mokhtar N, Mohamed Shah NB, Dahari MB, Azmi AA, Iwahashi M
    PLoS One, 2024;19(2):e0296969.
    PMID: 38394180 DOI: 10.1371/journal.pone.0296969
    There are three primary objectives of this work; first: to establish a gas concentration map; second: to estimate the point of emission of the gas; and third: to generate a path from any location to the point of emission for UAVs or UGVs. A mountable array of MOX sensors was developed so that the angles and distances among the sensors, alongside sensors data, were utilized to identify the influx of gas plumes. Gas dispersion experiments under indoor conditions were conducted to train machine learning algorithms to collect data at numerous locations and angles. Taguchi's orthogonal arrays for experiment design were used to identify the gas dispersion locations. For the second objective, the data collected after pre-processing was used to train an off-policy, model-free reinforcement learning agent with a Q-learning policy. After finishing the training from the training data set, Q-learning produces a table called the Q-table. The Q-table contains state-action pairs that generate an autonomous path from any point to the source from the testing dataset. The entire process is carried out in an obstacle-free environment, and the whole scheme is designed to be conducted in three modes: search, track, and localize. The hyperparameter combinations of the RL agent were evaluated through trial-and-error technique and it was found that ε = 0.9, γ = 0.9 and α = 0.9 was the fastest path generating combination that took 1258.88 seconds for training and 6.2 milliseconds for path generation. Out of 31 unseen scenarios, the trained RL agent generated successful paths for all the 31 scenarios, however, the UAV was able to reach successfully on the gas source in 23 scenarios, producing a success rate of 74.19%. The results paved the way for using reinforcement learning techniques to be used as autonomous path generation of unmanned systems alongside the need to explore and improve the accuracy of the reported results as future works.
    Matched MeSH terms: Environmental Monitoring*
  12. Fulltext Assessment of coastal river water quality in Bangladesh: Implications for drinking and irrigation purposes
    Uddin MR, Khandaker MU, Ahmed S, Abedin MJ, Hossain SMM, Al Mansur MA, et al.
    PLoS One, 2024;19(4):e0300878.
    PMID: 38635835 DOI: 10.1371/journal.pone.0300878
    Saltwater intrusion in the coastal areas of Bangladesh is a prevalent phenomenon. However, it is not conducive to activities such as irrigation, navigation, fish spawning and shelter, and industrial usage. The present study analyzed 45 water samples collected from 15 locations in coastal areas during three seasons: monsoon, pre-monsoon, and post-monsoon. The aim was to comprehend the seasonal variation in physicochemical parameters, including water temperature, pH, electrical conductivity (EC), salinity, total dissolved solids (TDS), hardness, and concentrations of Na+, K+, Mg2+, Ca2+, Fe2+, HCO3-, PO43-, SO42-, and Cl-. Additionally, parameters essential for agriculture, such as soluble sodium percentage (SSP), sodium absorption ratio (SAR), magnesium absorption ratio (MAR), residual sodium carbonate (RSC), Kelly's ratio (KR), and permeability index (PI), were examined. Their respective values were found to be 63%, 16.83 mg/L, 34.92 mg/L, 145.44 mg/L, 1.28 mg/L, and 89.29%. The integrated water quality index was determined using entropy theory and principal component analysis (PCA). The resulting entropy water quality index (EWQI) and SAR of 49.56% and 63%, respectively, indicated that the samples are suitable for drinking but unsuitable for irrigation. These findings can assist policymakers in implementing the Bangladesh Deltaplan-2100, focusing on sustainable land management, fish cultivation, agricultural production, environmental preservation, water resource management, and environmental protection in the deltaic areas of Bangladesh. This research contributes to a deeper understanding of seasonal variations in the hydrochemistry and water quality of coastal rivers, aiding in the comprehension of salinity intrusion origins, mechanisms, and causes.
    Matched MeSH terms: Environmental Monitoring/methods
  13. Spatial-temporal pattern of change in production-living-ecological space of Nanchong City from 2000 to 2020 and underlying factors
    Xu H, Zhang F, Li W, Shi J, Johnson BA, Tan ML
    Environ Monit Assess, 2023 Dec 27;196(1):94.
    PMID: 38150164 DOI: 10.1007/s10661-023-12249-8
    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.
    Matched MeSH terms: Environmental Monitoring*
  14. High regeneration may not contribute to the forest's carbon storage: a case study in the mangrove forest of Rajang-Belawai-Paloh delta, Sarawak
    Noweg T, Nelson J, Lip HM, Yeo SJ, Keleman A, Philip B
    Environ Monit Assess, 2023 Dec 06;196(1):15.
    PMID: 38055089 DOI: 10.1007/s10661-023-12191-9
    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.
    Matched MeSH terms: Environmental Monitoring
  15. A review of personal exposure studies in selected Asian countries' public transport microenvironments: lessons learned and future directions
    Otuyo MK, Nadzir MSM, Latif MT, Din SAM
    Environ Sci Pollut Res Int, 2023 Dec;30(58):121306-121337.
    PMID: 37993649 DOI: 10.1007/s11356-023-30923-9
    This comprehensive paper conducts an in-depth review of personal exposure and air pollutant levels within the microenvironments of Asian city transportation. Our methodology involved a systematic analysis of an extensive body of literature from diverse sources, encompassing a substantial quantity of studies conducted across multiple Asian cities. The investigation scrutinizes exposure to various pollutants, including particulate matters (PM10, PM2.5, and PM1), carbon dioxide (CO2), formaldehyde (CH2O), and total volatile organic compounds (TVOC), during transportation modes such as car travel, bus commuting, walking, and train rides. Notably, our review reveals a predominant focus on PM2.5, followed by PM10, PM1, CO2, and TVOC, with limited attention given to CH2O exposure. Across the spectrum of Asian cities and transportation modes, exposure concentrations exhibited considerable variability, a phenomenon attributed to a multitude of factors. Primary sources of exposure encompass motor vehicle emissions, traffic dynamics, road dust, and open bus doors. Furthermore, our findings illuminate the influence of external environments, particularly in proximity to train stations, on pollutant levels inside trains. Crucial factors affecting exposure encompass ventilation conditions, travel-specific variables, seat locations, vehicle types, and meteorological influences. The culmination of this rigorous review underscores the need for standardized measurements, enhanced ventilation systems, air filtration mechanisms, the adoption of clean energy sources, and comprehensive public education initiatives aimed at reducing pollutant exposure within city transportation microenvironments. Importantly, our study contributes to the growing body of knowledge surrounding this subject, offering valuable insights for policymakers and researchers dedicated to advancing air quality standards and safeguarding public health.
    Matched MeSH terms: Environmental Monitoring/methods
  16. Fulltext Improving PM2.5 prediction in New Delhi using a hybrid extreme learning machine coupled with snake optimization algorithm
    Masood A, Hameed MM, Srivastava A, Pham QB, Ahmad K, Razali SFM, et al.
    Sci Rep, 2023 Nov 29;13(1):21057.
    PMID: 38030733 DOI: 10.1038/s41598-023-47492-z
    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.
    Matched MeSH terms: Environmental Monitoring/methods
  17. The presence of toxic heavy metals in tuna fishes from Laccadive sea and concomitant health risk
    Nadhiya A, Khandaker MU, Mahmud S, Abdullah WH
    Radiat Prot Dosimetry, 2023 Nov 02;199(18):2224-2228.
    PMID: 37934996 DOI: 10.1093/rpd/ncad213
    Concentrations of heavy metals in Yellowfin and Skipjack tuna fishes from the Laccadive sea were determined by inductively coupled plasma optical emission spectroscopy (ICP-OES) to evaluate the human health hazards via their consumption. The samples were collected from different atolls of Maldives to ensure a good representation of sample distribution. The metal concentration in tuna fish is found to be below the maximum tolerable limit set by different international organisations. The target hazard quotient values for individual metals were well below the limiting value of 1, indicating an insignificant health risk via the dietary intake of fish. The maximum targeted cancer risk value was 10 -4, indicating low carcinogenic risk from the consumption of tuna fish from the Maldives. Hence, the consumption of tuna from the Laccadive Sea is safe for human health.
    Matched MeSH terms: Environmental Monitoring
  18. An evaluation of spatial and seasonal distributions of dissolved trace metals in the water of the natural wetlands
    Alkhadher SAA, Suratman S, Mohd Sallan MIB
    J Environ Manage, 2023 Nov 01;345:118464.
    PMID: 37454570 DOI: 10.1016/j.jenvman.2023.118464
    The spatial and temporal distributions of trace metals in dissolved forms mainly result from anthropogenic and lithogenic contributions. Surface water samples (∼0.5 m) were collected monthly at respective stations from Setiu Wetland. In this study, the behaviour of trace metals in the dissolved phases along the water column from sampling sites in the Setiu Wetland, Malaysia was investigated. In addition, dissolved organic carbon (DOC) and physical parameters such as salinity, temperature, pH and dissolved oxygen (DO) of the surface water were measured in order to evaluate the relationship between trace metals fractionation with different water quality parameters. Size fractionation study of dissolved trace metals using ultrafiltration technique were also carried out and analysed using inductively coupled plasma mass spectrometry (ICP-MS). Correlation of trace metals with other measured parameters was made to furthermore understand the dynamics of trace metals and its fractionated components in this area. The concentration of dissolved trace metals was in the range of 0.001-0.16 μg/L for Cd, 0.12-2.81 μg/L for Cu, 0.01-1.84 μg/L for Pb, 3-17 μg/L for Fe and 1-34 μg/L for Zn, suggesting the input of anthropogenic sources for trace metals such as municipal, industrial, agricultural and domestic discharge. The periodic monitoring and evaluation of trace metals in wetlands and protected tropical areas is highly recommended.
    Matched MeSH terms: Environmental Monitoring/methods
  19. Fulltext First evidence of microplastics in the water and sediment of Surakarta city river basin, Indonesia
    Ismanto A, Hadibarata T, Sugianto DN, Zainuri M, Kristanti RA, Wisha UJ, et al.
    Mar Pollut Bull, 2023 Nov;196:115677.
    PMID: 37862842 DOI: 10.1016/j.marpolbul.2023.115677
    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.
    Matched MeSH terms: Environmental Monitoring
  20. Fulltext A novel report on the occurrence of microplastics in Pekalongan River Estuary, Java Island, Indonesia
    Ismanto A, Hadibarata T, Kristanti RA, Sugianto DN, Widada S, Atmodjo W, et al.
    Mar Pollut Bull, 2023 Nov;196:115563.
    PMID: 37797535 DOI: 10.1016/j.marpolbul.2023.115563
    This study aimed to address the pressing issue of plastic pollution in aquatic ecosystems by assessing the prevalence and distribution of microplastics (MPs) in water and riverbank sediments of the Pekalongan River, a vital water source in Indonesia. From the present findings, MP concentrations in water ranged from 45.2 to 99.1 particles/L, while sediment concentrations ranged from 0.77 to 1.01 particles/g. This study revealed that fragment and film MPs constituted 30.1 % and 25.4 % of the total, respectively, with MPs measuring <1 mm and constituting 51.4 % of the total. Colored MPs, particularly blue and black MPs, accounted for 34 % of the total. The primary polymer components, as determined via Fourier transform infrared spectroscopy, were identified as polystyrene, polyester, and polyamide. In response to the escalating plastic waste crisis caused by single-use plastics, Pekalongan's local government implemented refuse segregation and recycling programs as part of its efforts to transition toward zero-waste practices.
    Matched MeSH terms: Environmental Monitoring/methods
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