Displaying publications 101 - 120 of 923 in total

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  1. 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
  2. Fulltext Machine learning algorithms for high-resolution prediction of spatiotemporal distribution of air pollution from meteorological and soil parameters
    Tao H, Jawad AH, Shather AH, Al-Khafaji Z, Rashid TA, Ali M, et al.
    Environ Int, 2023 May;175:107931.
    PMID: 37119651 DOI: 10.1016/j.envint.2023.107931
    This study uses machine learning (ML) models for a high-resolution prediction (0.1°×0.1°) of air fine particular matter (PM2.5) concentration, the most harmful to human health, from meteorological and soil data. Iraq was considered the study area to implement the method. Different lags and the changing patterns of four European Reanalysis (ERA5) meteorological variables, rainfall, mean temperature, wind speed and relative humidity, and one soil parameter, the soil moisture, were used to select the suitable set of predictors using a non-greedy algorithm known as simulated annealing (SA). The selected predictors were used to simulate the temporal and spatial variability of air PM2.5 concentration over Iraq during the early summer (May-July), the most polluted months, using three advanced ML models, extremely randomized trees (ERT), stochastic gradient descent backpropagation (SGD-BP) and long short-term memory (LSTM) integrated with Bayesian optimizer. The spatial distribution of the annual average PM2.5 revealed the population of the whole of Iraq is exposed to a pollution level above the standard limit. The changes in temperature and soil moisture and the mean wind speed and humidity of the month before the early summer can predict the temporal and spatial variability of PM2.5 over Iraq during May-July. Results revealed the higher performance of LSTM with normalized root-mean-square error and Kling-Gupta efficiency of 13.4% and 0.89, compared to 16.02% and 0.81 for SDG-BP and 17.9% and 0.74 for ERT. The LSTM could also reconstruct the observed spatial distribution of PM2.5 with MapCurve and Cramer's V values of 0.95 and 0.91, compared to 0.9 and 0.86 for SGD-BP and 0.83 and 0.76 for ERT. The study provided a methodology for forecasting spatial variability of PM2.5 concentration at high resolution during the peak pollution months from freely available data, which can be replicated in other regions for generating high-resolution PM2.5 forecasting maps.
    Matched MeSH terms: Environmental Monitoring/methods
  3. Critical review on airborne microplastics: An indoor air contaminant of emerging concern
    Kek HY, Tan H, Othman MHD, Nyakuma BB, Ho WS, Sheng DDCV, et al.
    Environ Res, 2024 Mar 15;245:118055.
    PMID: 38154562 DOI: 10.1016/j.envres.2023.118055
    Airborne Microplastics (MPs), an emerging environmental issue, have gained recent attention due to their newfound presence in indoor environments. Utilizing the Web of Science database for literature collection, the paper presents a comprehensive review of airborne MPs including emission sources, assessment methods, exposure risks, and mitigation strategies. This review delves into the diverse sources and mechanisms influencing indoor airborne MP pollution, underscoring the complex interplay between human activities, ventilation systems, and the characteristics of indoor environments. Major sources include the abrasion of synthetic textiles and the deterioration of flooring materials, with factors like carpeting, airflow, and ventilation significantly impacting MP levels. Human activities, such as increased movement in indoor spaces and the intensive use of plastic-based personal protective equipment (PPE) post-pandemic, notably elevate indoor MP concentrations. The potential health impacts of airborne MPs are increasingly concerning, with evidence suggesting their role in respiratory, immune, and nervous system diseases. Despite this, there is a scarcity of information on MPs in diverse indoor environments and the inhalation risks associated with the frequent use of PPE. This review also stresses the importance of developing effective strategies to reduce MP emissions, such as employing HEPA-filtered vacuums, minimizing the use of synthetic textiles, and enhancing indoor ventilation. Several future research directions were proposed, including detailed temporal analyses of indoor MP levels, interactions of MP with other atmospheric pollutants, the transport dynamics of inhalable MPs (≤10 μm), and comprehensive human exposure risk assessments.
    Matched MeSH terms: Environmental Monitoring/methods
  4. A meta-analysis highlighting the increasing relevance of the hair matrix in exposure assessment to organic pollutants
    Junaid M, Sultan M, Liu S, Hamid N, Yue Q, Pei DS, et al.
    Sci Total Environ, 2024 Mar 20;917:170535.
    PMID: 38307287 DOI: 10.1016/j.scitotenv.2024.170535
    Owing to a wide range of advantages, such as stability, non-invasiveness, and ease of sampling, hair has been used progressively for comprehensive biomonitoring of organic pollutants for the last three decades. This has led to the development of new analytical and multi-class analysis methods for the assessment of a broad range of organic pollutants in various population groups, ranging from small-scale studies to advanced studies with a large number of participants based on different exposure settings. This meta-analysis summarizes the existing literature on the assessment of organic pollutants in hair in terms of residue levels, the correlation of hair residue levels with those of other biological matrices and socio-demographic factors, the reliability of hair versus other biomatrices for exposure assessment, the use of segmental hair analysis for chronic exposure evaluation and the effect of external contamination on hair residue levels. Significantly high concentrations of organic pollutants such as pesticides, flame retardants, polychlorinated biphenyls and polycyclic aromatic hydrocarbon were reported in human hair samples from different regions and under different exposure settings. Similarly, high concentrations of pesticides (from agricultural activities), flame retardants (E-waste dismantling activities), dioxins and furans were observed in various occupational settings. Moreover, significant correlations (p 
    Matched MeSH terms: Environmental Monitoring/methods
  5. Fulltext Estimating biodiversity impacts without field surveys: A case study in northern Borneo
    Kitzes J, Shirley R
    Ambio, 2016 Feb;45(1):110-9.
    PMID: 26169084 DOI: 10.1007/s13280-015-0683-3
    In many regions of the world, biodiversity surveys are not routinely conducted prior to activities that lead to land conversion, such as development projects. Here we use top-down methods based on global range maps and bottom-up methods based on macroecological scaling laws to illuminate the otherwise hidden biodiversity impacts of three large hydroelectric dams in the state of Sarawak in northern Borneo. Our retrospective impact assessment finds that the three reservoirs inundate habitat for 331 species of birds (3 million individuals) and 164 species of mammals (110 million individuals). A minimum of 2100 species of trees (900 million individuals) and 17 700 species of arthropods (34 billion individuals) are estimated to be affected by the dams. No extinctions of bird, mammal, or tree species are expected due to habitat loss following reservoir inundation, while 4-7 arthropod species extinctions are predicted. These assessment methods are applicable to any data-limited system undergoing land-use change.
    Matched MeSH terms: Environmental Monitoring/methods*
  6. Environmental occurrence and assessment of organic pollutants in surface sediments of South Peninsular Malaysia
    Alkhadher SAA, Sidek LM, Zakaria MP, A Al-Garadi M, Suratman S
    Environ Geochem Health, 2024 Mar 15;46(4):140.
    PMID: 38488953 DOI: 10.1007/s10653-024-01916-5
    Organic pollution continues to be an important worldwide obstacle for tackling health and environmental concerns that require ongoing and prompt response. To identify the LAB content levels as molecular indicators for sewage pollution, surface sediments had obtained from the South region of Malaysia. The origins of the LABs were identified using gas chromatography-mass spectrometry (GC-MS). ANOVA and a Pearson correlation coefficient at p 
    Matched MeSH terms: Environmental Monitoring/methods
  7. Fulltext Role of morphological structure, doping, and coating of different materials in the sensing characteristics of humidity sensors
    Tripathy A, Pramanik S, Cho J, Santhosh J, Osman NA
    Sensors (Basel), 2014 Sep 03;14(9):16343-422.
    PMID: 25256110 DOI: 10.3390/s140916343
    The humidity sensing characteristics of different sensing materials are important properties in order to monitor different products or events in a wide range of industrial sectors, research and development laboratories as well as daily life. The primary aim of this study is to compare the sensing characteristics, including impedance or resistance, capacitance, hysteresis, recovery and response times, and stability with respect to relative humidity, frequency, and temperature, of different materials. Various materials, including ceramics, semiconductors, and polymers, used for sensing relative humidity have been reviewed. Correlations of the different electrical characteristics of different doped sensor materials as the most unique feature of a material have been noted. The electrical properties of different sensor materials are found to change significantly with the morphological changes, doping concentration of different materials and film thickness of the substrate. Various applications and scopes are pointed out in the review article. We extensively reviewed almost all main kinds of relative humidity sensors and how their electrical characteristics vary with different doping concentrations, film thickness and basic sensing materials. Based on statistical tests, the zinc oxide-based sensing material is best for humidity sensor design since it shows extremely low hysteresis loss, minimum response and recovery times and excellent stability.
    Matched MeSH terms: Environmental Monitoring*
  8. 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
  9. Evaluating the properties that affect the quality of the charcoal product, determining the limits of toxic emissions during combustion, and studying their impact on human health
    Alzahrani A, Hassan MA, Alsubaie S
    Environ Geochem Health, 2024 Jul 09;46(8):295.
    PMID: 38980526 DOI: 10.1007/s10653-024-02065-5
    This research focuses on examining the potential impact of charcoal briquettes and lumps on human health due to the emissions they release, and verifying their quality standards. Quality assessment was conducted using a device capable of measuring toxic gases to identify contaminants from various sources such as biomass, synthetic resins, coal, metals, and mineral matter. Toxicity assessments were carried out on five types of briquettes and two varieties of lump charcoal. All charcoal samples were subjected to elemental analysis (SEM/EDAX), including the examination of Ca, Al, Cr, V, Cu, Fe, S, Sr, Si, Ba, Pb, P, Mn, Rb, K, Ti, and Zn. The results showed that burning lump charcoal had toxicity indexes ranging from 2.5 to 5, primarily due to NOx emissions. Briquettes, on the other hand, exhibited higher toxicity indices between 3.5 and 6.0, with CO2 being the main contributor to toxicity. The average 24-h CO content of all charcoal samples exceeded the World Health Organization's 24-h Air Quality Guideline of 6.34 ppm, with a measurement of 37 ppm. The data indicates that most of the products tested did not meet the prevailing quality standard (EN 1860-2:2005 (E) in Appliances, solid fuels and firelighters for barbecuing-Part 2: Barbecue charcoal and barbecue charcoal briquettes-Requirements and test method, 2005), which specifies a maximum of 1% contaminants, with some products containing as much as 21% impurities. The SEM analysis revealed irregularly shaped grains with an uneven distribution of particles, and the average particle size distribution is quite broad at 5 μm. Malaysia Charcoal had the highest calorific value at 32.80 MJ/Kg, with the value being influenced by the fixed carbon content-higher carbon content resulting in a higher calorific value.
    Matched MeSH terms: Environmental Monitoring/methods
  10. A review of heavy metals pollution in riverine sediment from various Asian and European countries: Distribution, sources, and environmental risk
    Zeb M, Khan K, Younas M, Farooqi A, Cao X, Kavil YN, et al.
    Mar Pollut Bull, 2024 Sep;206:116775.
    PMID: 39121593 DOI: 10.1016/j.marpolbul.2024.116775
    Riverine sediments are important reservoirs of heavy metals, representing both historical and contemporary anthropogenic activity within the watershed. This review has been conducted to examine the distribution of heavy metals in the surface sediment of 52 riverine systems from various Asian and European countries, as well as to determine their sources and environmental risks. The results revealed significant variability in heavy metal contamination in the world's riverine systems, with certain hotspots exhibiting concentrations that exceeded the permissible limits set by environmental quality standards. Among the studied countries, India has the highest levels of chromium (Cr), cobalt (Co), manganese (Mn), nickel (Ni), zinc (Zn), cadmium (Cd), copper (Cu), and lead (Pb) contamination in its riverine systems, followed by Iran > Turkey > Spain > Vietnam > Pakistan > Malaysia > Taiwan > China > Nigeria > Bangladesh > Japan. Heavy metal pollution in the world's riverine systems was quantified using pollution evaluation indices. The Contamination Factor (CF) revealed moderate contamination (1 ≤ CF  Pakistan > Bangladesh > China > Taiwan > Japan and Iron, while the potential risks of ∑non-carcinogenic Pb, Cr, Ni, Cu, Cd, Co, Zn, and Mn for exposed human children and adults through ingestion and dermal contact were significantly influenced between acceptable to high risk, necessitating special attention from pollution control agencies.
    Matched MeSH terms: Environmental Monitoring*
  11. Fulltext Research Priorities of Applying Low-Cost PM2.5 Sensors in Southeast Asian Countries
    Lung SC, Thi Hien T, Cambaliza MOL, Hlaing OMT, Oanh NTK, Latif MT, et al.
    Int J Environ Res Public Health, 2022 Jan 28;19(3).
    PMID: 35162543 DOI: 10.3390/ijerph19031522
    The low-cost and easy-to-use nature of rapidly developed PM2.5 sensors provide an opportunity to bring breakthroughs in PM2.5 research to resource-limited countries in Southeast Asia (SEA). This review provides an evaluation of the currently available literature and identifies research priorities in applying low-cost sensors (LCS) in PM2.5 environmental and health research in SEA. The research priority is an outcome of a series of participatory workshops under the umbrella of the International Global Atmospheric Chemistry Project-Monsoon Asia and Oceania Networking Group (IGAC-MANGO). A literature review and research prioritization are conducted with a transdisciplinary perspective of providing useful scientific evidence in assisting authorities in formulating targeted strategies to reduce severe PM2.5 pollution and health risks in this region. The PM2.5 research gaps that could be filled by LCS application are identified in five categories: source evaluation, especially for the distinctive sources in the SEA countries; hot spot investigation; peak exposure assessment; exposure-health evaluation on acute health impacts; and short-term standards. The affordability of LCS, methodology transferability, international collaboration, and stakeholder engagement are keys to success in such transdisciplinary PM2.5 research. Unique contributions to the international science community and challenges with LCS application in PM2.5 research in SEA are also discussed.
    Matched MeSH terms: Environmental Monitoring/methods
  12. Mapping pollution dynamics: utilizing GNOME to model oil spill trajectories in tanker terminals
    Farzingohar M, Bagheri M, Gholami I, Ibrahim ZZ, Akhir MF
    Environ Sci Pollut Res Int, 2024 May;31(25):37404-37427.
    PMID: 38777973 DOI: 10.1007/s11356-024-33506-4
    The aim of this study is to uncover the multifaceted environmental threats posed by Oil Spill Water Pollution (OSWP) originating from tanker terminals situated in the Qeshm and Hormozgan regions of Iran. In this region, water pollution arises from diverse sources, mostly from ruptured pipelines, corroded valves, unforeseen accidents, and aging facilities. The Qeshm Canal and Qeshm Tanker Terminal emerged as pivotal sites for investigation within this study. The focus is directed towards pinpointing vulnerable areas at risk of water contamination and delving into the intricate pathways and impacts associated with oil spills. Utilizing the sophisticated modeling capabilities of the National Oceanic and Atmospheric Administration's (NOAA) GNOME model, the research explores various scenarios extrapolated from seasonal atmospheric and oceanic data through 2022. The findings show the OSWP hazard zones located northeast of Qeshm. Notably, the wind and currents greatly affect how OSWPs are destined and dispersed. This underscores the intricate interplay between environmental factors and spill dynamics. In essence, this study not only sheds light on the imminent environmental threats posed by OSWP but also underscores the critical need for proactive measures and comprehensive strategies to mitigate the adverse impacts on marine ecosystems and coastal communities.
    Matched MeSH terms: Environmental Monitoring*
  13. Remote sensing-based seasonal surface urban heat island analysis in the mining and industrial environment
    Halder B, Bandyopadhyay J, Ghosh N
    Environ Sci Pollut Res Int, 2024 May;31(25):37075-37108.
    PMID: 38760605 DOI: 10.1007/s11356-024-33603-4
    Cooling spaces have an optimistic influence on surface urban heat islands (SUHI). Blue spaces benefit from balancing the changing climate and heat variations. Because of the rapid deforestation and SUHI increase, the climate is gradually changing in Paschim Bardhhaman, West Bengal state, India. Paschim Bardhhaman has two sectors: specifically, Durgapur is the main industrial centre and Asansol has coal mines. This investigation aims to categorize spatiotemporal variations and seasonal differences in cooling spaces and their influence on SUHI, land use and land cover (LULC), and thermal differences using Landsat datasets for the years 1992, 2004, 2012, and 2022 in summer and winter. The coal mining and industrial range decreased from 10,391.92 (1992) to 3591.1 ha (2022), respectively. Open pit mining distresses fresh water by heavy water uses in ore processing, and mining water was applied to excerpt minerals. Among the two sub-divisions, the blue space amount was higher in Asansol because mining actions were higher in Asansol than in Durgapur. The open vegetation volume has reduced from 46,441.03 (1992) to 25,827.55 ha (2022) and dense vegetation has erased from 7368.02 (1992) to 15,608.56 ha (2022). Dense vegetation improved because of heavy precipitation in those regions. Mostly, Raghunathpur, Saraswatiganja, Bhagabanpur, Bistupur, Paschim Gangaram, Garkilla Kherobari, and Gourbazar have dense vegetation. The outcomes similarly demonstrate that the total built-up part has increased by 8412.82 ha in between 30 years. The built-up zone changes near the southeast and western Paschim Bardhhaman district. Those region needs appropriate attention and planning to survive soon.
    Matched MeSH terms: Environmental Monitoring*
  14. Fulltext Air Quality Prediction Using the Fractional Gradient-Based Recurrent Neural Network
    Arora S, Sawaran Singh NS, Singh D, Rakesh Shrivastava R, Mathur T, Tiwari K, et al.
    Comput Intell Neurosci, 2022;2022:9755422.
    PMID: 36531923 DOI: 10.1155/2022/9755422
    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).
    Matched MeSH terms: Environmental Monitoring/methods
  15. Assessment of transboundary macro-litter on the remote island of Andaman and Nicobar: Unveiling the governing factors and risk assessment
    Shankar VS, De K, Mandal S, Jacob S, Satyakeerthy TR
    Mar Pollut Bull, 2024 Dec;209(Pt A):117145.
    PMID: 39461182 DOI: 10.1016/j.marpolbul.2024.117145
    The increasing occurrence of mismanaged plastic litter along India's coastline and the ominous challenges it poses to biodiversity and ecosystem health is a growing environmental concern. To address this issue, we comprehensively investigated the abundance, composition, and probable sources of marine litter on North Cinque Island, a remote uninhabited island in the Andaman and Nicobar archipelago, Bay of Bengal. This island is a designated wildlife sanctuary and serves as an important nesting site for Green, Hawksbill and Leatherback turtles. A total of 6227 litter items were enumerated, with an average concentration of 0.12 items/m2, representing 20 diverse litter types, with plastic dominating the litter composition (86 %). The cleanliness and environmental hazards of the coast due to the litter were assessed using different indices such as the Clean Coast Index (CCI), Plastic Accumulation Index (PAI), Hazardous Item Index (HII), and Clean Environment Index (CEI). CCI indicates the moderately clean-to-clean status of the surveyed sites. PAI points to low to moderate accumulation of plastic litter. HII of all five coasts fell in category II, suggesting a moderate abundance of hazardous items that can inflict injuries to the foraging turtle and their hatchlings. The CEI articulates the moderately clean to very clean status of the sites. Litter brand audit suggests a considerable amount of stranded litter on the coasts was transboundary and originated from six Indian Ocean Rim Countries (IORC), namely Thailand, Myanmar, Malaysia, Indonesia, Sri Lanka, and UAE. Joint solid waste management by the IORC is the need of the hour to avert litter accumulation on the pristine, remote islands.
    Matched MeSH terms: Environmental Monitoring*
  16. Selecting a probability distribution for extreme rainfall series in Malaysia
    Zalina MD, Desa MN, Nguyen VT, Kassim AH
    Water Sci Technol, 2002;45(2):63-8.
    PMID: 11890166
    This paper discusses the comparative assessment of eight candidate distributions in providing accurate and reliable maximum rainfall estimates for Malaysia. The models considered were the Gamma, Generalised Normal, Generalised Pareto, Generalised Extreme Value, Gumbel, Log Pearson Type III, Pearson Type III and Wakeby. Annual maximum rainfall series for one-hour resolution from a network of seventeen automatic gauging stations located throughout Peninsular Malaysia were selected for this study. The length of rainfall records varies from twenty-three to twenty-eight years. Model parameters were estimated using the L-moment method. The quantitative assessment of the descriptive ability of each model was based on the Probability Plot Correlation Coefficient test combined with root mean squared error, relative root mean squared error and maximum absolute deviation. Bootstrap resampling was employed to investigate the extrapolative ability of each distribution. On the basis of these comparisons, it can be concluded that the GEV distribution is the most appropriate distribution for describing the annual maximum rainfall series in Malaysia.
    Matched MeSH terms: Environmental Monitoring
  17. Forest fires cause pollution crisis in Asia
    Swinbanks D
    Nature, 1997 Sep 25;389(6649):321.
    PMID: 9311764
    Matched MeSH terms: Environmental Monitoring
  18. Fulltext Overviewing the air quality models on air pollution in Sichuan Basin, China
    Li X, Hussain SA, Sobri S, Md Said MS
    Chemosphere, 2021 May;271:129502.
    PMID: 33465622 DOI: 10.1016/j.chemosphere.2020.129502
    Most developing countries in the world face the common challenges of reducing air pollution and advancing the process of sustainable development, especially in China. Air pollution research is a complex system and one of the main methods is through numerical simulation. The air quality model is an important technical method, it allows researchers to better analyze air pollutants in different regions. In addition, the SCB is a high-humidity and foggy area, and the concentration of atmospheric pollutants is always high. However, research on this region, one of the four most polluted regions in China, is still lacking. Reviewing the application of air quality models in the SCB air pollution has not been reported thoroughly. To fill these gaps, this review provides a comprehensive narration about i) The status of air pollution in SCB; ii) The application of air quality models in SCB; iii) The problems and application prospects of air quality models in the research of air pollution. This paper may provide a theoretical reference for the prevention and control of air pollution in the SCB and other heavily polluted areas in China and give some1inspirations for air pollution forecast in other countries with complex terrain.
    Matched MeSH terms: Environmental Monitoring
  19. A preliminary investigation of marine litter pollution along Mandvi beach, Kachchh, Gujarat
    Behera DP, Kolandhasamy P, Sigamani S, Devi LP, Ibrahim YS
    Mar Pollut Bull, 2021 Apr;165:112100.
    PMID: 33581571 DOI: 10.1016/j.marpolbul.2021.112100
    Marine debris is a global issue with adverse impacts on marine organisms, ecological processes, aesthetics, and economies of nations. Several studies have been conducted to quantify the plastic debris along Indian beaches. This baseline study describes the results of a survey conducted on the types of plastic litters and their quantification during January to March 2020 along Mandvi beach in Gujarat. A quadrate having 10 × 10 m size was used for sampling the plastic litter on the shoreline. A total of 10 quadrates along the shore was considered for quantification of the plastic materials based on their density, color, and weight. The plastic material observed includes gutkha pouches, food wrappers, and fragments, along with plastic straws, cutleries, and fragments of various dimensions and thickness. The major contributing factors for the debris abundance in Mandvi beach are land-based sources and recreational activities. The results suggest that similar long-term projects covering extensive areas should be undertaken for accurate quantification of available debris and their impacts on coastal habitats of Gujarat.
    Matched MeSH terms: Environmental Monitoring
  20. Emerging contaminants and biological effects in Arctic wildlife
    Sonne C, Dietz R, Jenssen BM, Lam SS, Letcher RJ
    Trends Ecol Evol, 2021 05;36(5):421-429.
    PMID: 33602568 DOI: 10.1016/j.tree.2021.01.007
    Recent advances in environmental analytical chemistry have identified the presence of a large number of chemicals of emerging Arctic concern (CEACs) being transported long range to the region. There has been very limited temporal monitoring of CEACs and it is therefore unknown whether they are of increasing or decreasing concern. Likewise, information on potential biological adverse effects from CEACs on Arctic wildlife is lacking compared with legacy persistent organic pollutants (POPs) found at levels associated with health effects in marine mammals. Hence, there is a need to monitor CEACs along with POPs to support risk and regulatory CEAC assessments. We suggest pan-Arctic temporal trend studies of CEACs in wildlife including the establishment of toxicity thresholds to evaluate their potential effects on populations, biodiversity, and ecosystem services.
    Matched MeSH terms: Environmental Monitoring
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