Displaying publications 1 - 20 of 888 in total

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  1. An assessment of heavy metal bioaccumulation in Asian swamp eel, Monopterus albus, during plowing stages of a paddy cycle
    Sow AY, Ismail A, Zulkifli SZ
    Bull Environ Contam Toxicol, 2013 Jul;91(1):6-12.
    PMID: 23666324 DOI: 10.1007/s00128-013-1009-4
    Livers and muscles of swamp eels (Monopterus albus) were analyzed for bioaccumulation of heavy metals during the plowing stage of a paddy cycle. Results showed heavy metals were bioaccumulated more highly in liver than muscle. Zinc (Zn) was the highest bioaccumulated metal in liver (98.5 ± 8.95 μg/g) and in muscle (48.8 ± 7.17 μg/g). The lowest bioaccumulated metals were cadmium (Cd) in liver (3.44 ± 2.42 μg/g) and copper (Cu) in muscle (0.65 ± 0.20 μg/g). In sediments, Zn was present at the highest mean concentration (52.7 ± 2.85 μg/g), while Cd had the lowest mean concentration (1.04 ± 0.24 μg/g). The biota-sediment accumulation factor (BSAF) for Cu, Zn, Cd and nickel (Ni) in liver tissue was greater than the corresponding BSAF for muscle tissue. For the three plowing stages, metal concentrations were significantly correlated between liver and muscle tissues in all cases, and between sediment and either liver or muscle in most cases. Mean measured metal concentrations in muscle tissue were below the maximum permissible limits established by Malaysian and U.S. governmental agencies, and were therefore regarded as safe for human consumption.
    Matched MeSH terms: Environmental Monitoring
  2. Estimation and influence of physicochemical properties and chemical fractions of surface sediment on the bioaccessibility of Cd and Hg contaminant in Langat River, Malaysia
    Kadhum SA, Ishak MY, Zulkifli SZ
    Environ Geochem Health, 2017 Oct;39(5):1145-1158.
    PMID: 27848092 DOI: 10.1007/s10653-016-9883-4
    This study applied the use of sequential extraction technique and simple bioaccessibility extraction test to quantify the bioavailable fractions and the human bioaccessible concentration of metals collected from nine stations in surface sediment of the Langat River. The concentrations of total and bioaccessible metals from different stations were in the range of 0.49-1.04, 0.10-0.32 μg g-1 for T-Cd, Bio-Cd, respectively, and 12.9-128.03, 2.06-8.53 μg kg-1 for T-Hg, Bio-Hg, respectively. The results revealed highest R-Bio-Cd in Banting station (55.3 %), while the highest R-Bio-Hg was in Kajang station (49.61 %). The chemical speciation of Cd in most sampling stations was in the order of oxidisable-organic > residual > exchangeable > acid-reducible, while speciation of Hg was in the order of exchangeable > residual > oxidisable-organic > acid-reducible. The correlation matric of mean content showed that the TOM, particle size and Mg++ in polluted surface sediments was highly correlated with total mercury. The PCA showed that the main factors influencing the bioaccessibility of Hg in surface sediments were the sediment TOM, F1 (EFLE) and F3 (oxidation-organic), while the factor influencing the bioaccessibility of Cd was the F3 (oxidation-organic) and T-Cd.
    Matched MeSH terms: Environmental Monitoring
  3. Evaluation and assessment of baseline metal contamination in surface sediments from the Bernam River, Malaysia
    Kadhum SA, Ishak MY, Zulkifli SZ
    Environ Sci Pollut Res Int, 2016 Apr;23(7):6312-21.
    PMID: 26614452 DOI: 10.1007/s11356-015-5853-0
    The Bernam River is one of the most important rivers in Malaysia in that it provides water for industries and agriculture located along its banks. The present study was conducted to assess the level of contamination of heavy metals (Cd, Ni, Cr, Sn, and Fe) in surface sediments in the Bernam River. Nine surface sediment samples were collected from the lower, middle, and upper courses of the river. The results indicated that the concentrations of the metals decreased in the order of Sn > Cr > Ni > Fe > Cd (56.35, 14.90, 5.3, 4.6, and 0.62 μg/g(1) dry weight). Bernam River sediments have moderate to severe enrichment for Sn, moderate for Cd, and no enrichment for Cr, Ni, and Fe. The contamination factor (CF) results demonstrated that Cd and Sn are responsible for the high contamination. The pollution load index (PLI), for all the sampling sites, suggests that the sampling stations were generally unpolluted with the exception of the Bagan Tepi Sungai, Sabak Bernam, and Tanjom Malim stations. Multivariate techniques including Pearson's correlation and hierarchical cluster analysis were used to apportion the various sources of the metals. The results suggested that the sediment samples collected from the upper course of the river had lower metal concentrations, while sediments in the middle and lower courses of the river had higher metal concentrations. Therefore, our results can be useful as a baseline data for government bodies to adopt corrective measure on the issues related to heavy metal pollution in the Bernam River in the future.
    Matched MeSH terms: Environmental Monitoring/methods
  4. Geofractionation of heavy metals and application of indices for pollution prediction in paddy field soil of Tumpat, Malaysia
    Sow AY, Ismail A, Zulkifli SZ
    Environ Sci Pollut Res Int, 2013 Dec;20(12):8964-73.
    PMID: 23757028 DOI: 10.1007/s11356-013-1857-9
    The present study investigates the concentration of Pb, Cd, Ni, Zn, and Cu in the paddy field soils collected from Tumpat, Kelantan. Soil samples were treated with sequential extraction to distinguish the anthropogenic and lithogenic origin of Pb, Cd, Ni, Zn, and Cu. ELFE and oxidizable-organic fractions were detected as the lowest accumulation of Pb, Cd, Ni, Zn, and Cu. Therefore, all the heavy metals examined were concentrated, particularly in resistant fraction, indicating that those heavy metals occurred and accumulated in an unavailable form. The utilization of agrochemical fertilizers and pesticides might not elevate the levels of heavy metals in the paddy field soils. In comparison, the enrichment factor and geoaccumulation index for Pb, Cd, Ni, Zn, and Cu suggest that these heavy metals have the potential to cause environmental risk, although they present abundance in resistant fraction. Therefore, a complete study should be conducted based on the paddy cycle, which in turn could provide a clear picture of heavy metals distribution in the paddy field soils.
    Matched MeSH terms: Environmental Monitoring/methods*
  5. Fulltext Microbiological Safety of Street-Vended Beverages in Chow Kit, Kuala Lumpur
    Mohd Nawawee NS, Abu Bakar NF, Zulfakar SS
    Int J Environ Res Public Health, 2019 11 13;16(22).
    PMID: 31766289 DOI: 10.3390/ijerph16224463
    Improper handling, poor hygienic practices, and lack of environmental control affect the safety of street-vended beverages. The objective of this study is to determine the bacterial contamination level of three types of beverages (cordial-based drinks, milk-based drinks, fruit juices) sold by street vendors at Chow Kit, Kuala Lumpur. A total of 31 samples of beverages were analyzed to determine total viable count (TVC), total coliform, Escherichia coli, and Staphylococcus aureus counts via the standard plate count method. The results showed that only 9.7% of the total samples were not contaminated with the tested microorganisms. All milk-based drink samples were positive for TVC and also had the highest average bacterial counts at 5.30 ± 1.11 log Colony Forming Unit/mL (CFU/mL). About 71% of the samples were contaminated with total coliform with the average readings ranging between 4.30 and 4.75 log CFU/mL, whereas 58.1% of the samples were positive with S. aureus, with fruit juices having the highest average reading (3.42 ± 1.15 log CFU/mL). Only one sample (milk-based drink) was E. coli positive. This study showed that the microbiological safety level of street-vended beverages in Chow Kit, Kuala Lumpur was average and needs to be improved. Provision of food safety education and adequate sanitary facilities at vending sites are suggested to increase the safety of food products.
    Matched MeSH terms: Environmental Monitoring
  6. Fulltext The Forest Observation System, building a global reference dataset for remote sensing of forest biomass
    Schepaschenko D, Chave J, Phillips OL, Lewis SL, Davies SJ, Réjou-Méchain M, et al.
    Sci Data, 2019 10 10;6(1):198.
    PMID: 31601817 DOI: 10.1038/s41597-019-0196-1
    Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.
    Matched MeSH terms: Environmental Monitoring/methods
  7. Modeling the spatio-temporal dynamics of air pollution index based on spatial Markov chain model
    Alyousifi Y, Ibrahim K, Kang W, Zin WZW
    Environ Monit Assess, 2020 Oct 21;192(11):719.
    PMID: 33083907 DOI: 10.1007/s10661-020-08666-8
    An environmental problem which is of concern across the globe nowadays is air pollution. The extent of air pollution is often studied based on data on the observed level of air pollution. Although the analysis of air pollution data that is available in the literature is numerous, studies on the dynamics of air pollution with the allowance for spatial interaction effects through the use of the Markov chain model are very limited. Accordingly, this study aims to explore the potential impact of spatial dependence over time and space on the distribution of air pollution based on the spatial Markov chain (SMC) model using the longitudinal air pollution index (API) data. This SMC model is pertinent to be applied since the daily data of API from 2012 to 2014 that have been gathered from 37 different air quality stations in Peninsular Malaysia is found to exhibit the property of spatial autocorrelation. Based on the spatial transition probability matrices found from the SMC model, specific characteristics of air pollution are studied in the regional context. These characteristics are the long-run proportion and the mean first passage time for each state of air pollution. It is found that the probability for a particular station's state to remain good is 0.814 if its neighbors are in a good state of air pollution and 0.7082 if its neighbors are in a moderate state. For a particular station having neighbors in a good state of air pollution, the proportion of time for it to continue being in a good state is 0.6. This proportion reduces to 0.4, 0.01, and 0 for the cell of moderate, unhealthy, and very unhealthy states, respectively. In addition, there exists a significant spatial dependence of API, indicating that air pollution for a particular station is dependent on the states of the neighboring stations.
    Matched MeSH terms: Environmental Monitoring*
  8. Current and future effects of global change on a hotspot's freshwater diversity
    Gallardo B, Bogan AE, Harun S, Jainih L, Lopes-Lima M, Pizarro M, et al.
    Sci Total Environ, 2018 Sep 01;635:750-760.
    PMID: 29680765 DOI: 10.1016/j.scitotenv.2018.04.056
    Deforestation, climate change and invasive species constitute three global threats to biodiversity that act synergistically. However, drivers and rates of loss of freshwater biodiversity now and in the future are poorly understood. Here we focus on the potential impacts of global change on freshwater mussels (Order Unionida) in Sundaland (SE Asia), a vulnerable group facing global declines and recognized indicators of overall freshwater biodiversity. We used an ensemble of distribution models to identify habitats potentially suitable for freshwater mussels and their change under a range of climate, deforestation and invasion scenarios. Our data and models revealed that, at present, Sundaland features 47 and 32 Mha of habitat that can be considered environmentally suitable for native and invasive freshwater mussels, respectively. We anticipate that by 2050, the area suitable for palm oil cultivation may expand between 8 and 44 Mha, representing an annual increase of 2-11%. This is expected to result in a 20% decrease in suitable habitat for native mussels, a drop that reaches 30% by 2050 when considering concomitant climate change. In contrast, the habitat potentially suitable for invasive mussels may increase by 44-56% under 2050 future scenarios. Consequently, native mussels may compete for habitat, food resources and fish hosts with invasive mussels across approximately 60% of their suitable range. Our projections can be used to guide future expeditions to monitor the conservation status of freshwater biodiversity, and potentially reveal populations of endemic species on the brink of extinction. Future conservation measures-most importantly the designation of nature reserves-should take into account trends in freshwater biodiversity generally, and particularly species such as freshwater mussels, vital to safeguard fundamental ecosystem services.
    Matched MeSH terms: Environmental Monitoring
  9. Prevalence of Cryptosporidium and Giardia in the water resources of the Kuang River catchment, Northern Thailand
    Chuah CJ, Mukhaidin N, Choy SH, Smith GJD, Mendenhall IH, Lim YAL, et al.
    Sci Total Environ, 2016 08 15;562:701-713.
    PMID: 27110981 DOI: 10.1016/j.scitotenv.2016.03.247
    A catchment-scale investigation of the prevalence of Cryptosporidium and Giardia in the Kuang River Basin was carried out during the dry and rainy seasons. Water samples were collected from the Kuang River and its tributaries as well as a major irrigation canal at the study site. We also investigated the prevalence of gastrointestinal parasitic infection among dairy and beef cattle hosts. Cryptosporidium and/or Giardia were detected in all the rivers considered for this study, reflecting their ubiquity within the Kuang River Basin. The high prevalence of Cryptosporidium/Giardia in the upper Kuang River and Lai River is of a particular concern as both drain into the Mae Kuang Reservoir, a vital source of drinking-water to many local towns and villages at the research area. We did not, however, detected neither Cryptosporidium nor Giardia were in the irrigation canal. The frequency of Cryptosporidium/Giardia detection nearly doubled during the rainy season compared to the dry season, highlighting the importance of water as an agent of transport. In addition to the overland transport of these protozoa from their land sources (e.g. cattle manure, cess pits), Cryptosporidium/Giardia may also be re-suspended from the streambeds (a potentially important repository) into the water column of rivers during storm events. Faecal samples from dairy and beef cattle showed high infection rates from various intestinal parasites - 97% and 94%, respectively. However, Cryptosporidium and Giardia were only detected in beef cattle. The difference in management style between beef (freeranging) and dairy cattle (confined) may account for this disparity. Finally, phylogenetic analyses revealed that the Cryptosporidium/Giardia-positive samples contained C. ryanae (non-zoonotic) as well as Giardia intestinalis assemblages B (zoonotic) and E (non-zoonotic). With only basic water treatment facilities afforded to them, the communities of the rural area relying on these water supplies are highly at risk to Cryptosporidium/Giardia infections.
    Matched MeSH terms: Environmental Monitoring*
  10. Human health risk assessment of selected pharmaceuticals in the five major river basins, China
    Dai C, Li S, Duan Y, Leong KH, Tu Y, Zhou L
    Sci Total Environ, 2021 Dec 20;801:149730.
    PMID: 34467938 DOI: 10.1016/j.scitotenv.2021.149730
    Pharmaceuticals in aquatic environment have raised wide attention in recent years due to their potential adverse effects and bioaccumulation in biota. China has been a major producer and consumer of pharmaceuticals, however, the potential human health risk of these chemicals is yet to be determined in China. In this study, we evaluated available exposure data for twenty pharmaceuticals in surface waters from Chinese five major river basins (the Yangtze, Haihe, Pearl, Songliao, and Yellow River Basins), and human health risk assessment was performed. Based on the concentration data and risk data, we conducted research on the source, cause, and control measures of the pharmaceuticals. The twenty pharmaceuticals were found to be ubiquitous in China with median concentrations between 0.09 and 304 ng/L. The estimated daily intake of pharmaceuticals from drinking water and eating fish was calculated. The intake via drinking water was significantly lower than that via eating fish. The risk quotients via water intake and fish consumption ranged from 0 to 17.2, with estrogen and sulfapyridine highest among the twenty pharmaceuticals. High risks of exposure were mainly in North China, including the Haihe and Songliao River Basins. This is the first analysis in Chinese major river basins that has filled the gaps in the research on the human health risks of pharmaceuticals. The results of the study provide basic information of pharmaceutical intake from drinking water and eating fish in China and provide insights into the risk management guidance of pharmaceuticals, and will facilitate the optimization of health advisories and policy making.
    Matched MeSH terms: Environmental Monitoring
  11. Occurrence of microplastics in the seawater and atmosphere of the South China Sea: Pollution patterns and interrelationship
    Liu B, Lu Y, Deng H, Huang H, Wei N, Jiang Y, et al.
    Sci Total Environ, 2023 Sep 01;889:164173.
    PMID: 37201824 DOI: 10.1016/j.scitotenv.2023.164173
    Microplastic (MP) pollution is a serious global environmental problem, particularly in marine ecosystems. However, the pollution patterns of MPs in the ocean and atmosphere, particularly the sea-air interrelationship, remain unclear. Therefore, the abundance, distribution patterns, and sources of MPs in the seawater and atmosphere of the South China Sea (SCS) were comparatively investigated. The results showed that MPs were prevalent in the SCS with an average abundance of 103.4 ± 98.3 items/m3 in the seawater and 4.62 ± 3.60 items/100 m3 in the atmosphere. The spatial analysis indicated that the pollution patterns of seawater MPs were mainly determined by land-based discharge and sea surface currents, whereas atmospheric MPs were predominantly determined by air parcel trajectory and wind conditions. The highest MP abundance of 490 items/m3 in seawater was found at a station near Vietnam with current vortices. However, the highest MP abundance of 14.6 items/100 m3 in the atmosphere was found in air parcels with low-speed southerly winds from Malaysia. Similar MP compositions (e.g., polyethylene terephthalate, polystyrene, and polyethylene) were observed in the two environmental compartments. Furthermore, similar MP characteristics (e.g., shape, color, and size) in the seawater and atmosphere of the same region suggested a close relationship between the MPs in the two compartments. For this purpose, cluster analysis and calculation of the MP diversity integrated index were performed. The results showed an obvious dispersion between the two compartment clusters and a higher diversity integrated index of MPs in seawater than in the atmosphere, thus implying higher compositional diversity and more complex sources of MPs in seawater relative to the atmosphere. These findings deepen our understanding of MP fate and patterns in the semi-enclosed marginal sea environment and highlight the potential interrelationship of MPs in the air-sea system.
    Matched MeSH terms: Environmental Monitoring
  12. Impact of socioeconomic and meteorological factors on reservoirs' air quality: a case in the Three Gorges Reservoir of Chongqing (TGRC), China over a 10-year period
    Peng Y, Zhou F, Cui J, Du K, Leng Q, Yang F, et al.
    Environ Sci Pollut Res Int, 2017 Jul;24(19):16206-16219.
    PMID: 28540543 DOI: 10.1007/s11356-017-9221-0
    The Three Gorges Dam's construction and industrial transfer have resulted in a new air pollution pattern with the potential to threaten the reservoir eco-environment. To assess the impact of socioeconomic factors on the pattern of air quality vairation and economical risks, concentrations of SO2, NO2, and PM10, industry genres, and meteorological conditions were selected in the Three Gorges Reservoir of Chongqing (TGRC) during 2006-2015. Results showed that air quality had improved to some extent, but atmospheric NO2 showed an increased trend during 2011-2015. Spatially, higher atmospheric NO2 extended to the surrounding area. The primary industry, especially for agriculture, had shown to be responsible for the remarkable increase of atmospheric NO2 (p 
    Matched MeSH terms: Environmental Monitoring
  13. Fulltext Temperature vegetation dryness index (TVDI) for drought monitoring in the Guangdong Province from 2000 to 2019
    Chen A, Jiang J, Luo Y, Zhang G, Hu B, Wang X, et al.
    PeerJ, 2023;11:e16337.
    PMID: 38130929 DOI: 10.7717/peerj.16337
    Drought monitoring is crucial for assessing and mitigating the impacts of water scarcity on various sectors and ecosystems. Although traditional drought monitoring relies on soil moisture data, remote sensing technology has have significantly augmented the capabilities for drought monitoring. This study aims to evaluate the accuracy and applicability of two temperature vegetation drought indices (TVDI), TVDINDVI and TVDIEVI, constructed using the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) vegetation indices for drought monitoring. Using Guangdong Province as a case, enhanced versions of these indices, developed through Savitzky-Golay filtering and terrain correction were employed. Additionally, Pearson correlation analysis and F-tests were utilized to determine the suitability of the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) in correlation with TVDINDVI and TVDIEVI. The results show that TVDINDVI had more meteorological stations passing both significance test levels (P 
    Matched MeSH terms: Environmental Monitoring/methods
  14. ADA-SR: Activity detection and analysis using security robots for reliable workplace safety
    Zhang G, Jing W, Tao H, Rahman MA, Salih SQ, Al-Saffar A, et al.
    Work, 2021;68(3):935-943.
    PMID: 33612535 DOI: 10.3233/WOR-203427
    BACKGROUND: Human-Robot Interaction (HRI) has become a prominent solution to improve the robustness of real-time service provisioning through assisted functions for day-to-day activities. The application of the robotic system in security services helps to improve the precision of event detection and environmental monitoring with ease.

    OBJECTIVES: This paper discusses activity detection and analysis (ADA) using security robots in workplaces. The application scenario of this method relies on processing image and sensor data for event and activity detection. The events that are detected are classified for its abnormality based on the analysis performed using the sensor and image data operated using a convolution neural network. This method aims to improve the accuracy of detection by mitigating the deviations that are classified in different levels of the convolution process.

    RESULTS: The differences are identified based on independent data correlation and information processing. The performance of the proposed method is verified for the three human activities, such as standing, walking, and running, as detected using the images and sensor dataset.

    CONCLUSION: The results are compared with the existing method for metrics accuracy, classification time, and recall.

    Matched MeSH terms: Environmental Monitoring
  15. Polychlorinated biphenyls (PCBs) and hexachlorobenzene (HCB) in the equatorial Indian Ocean: temporal trend, continental outflow and air-water exchange
    Huang Y, Li J, Xu Y, Xu W, Cheng Z, Liu J, et al.
    Mar Pollut Bull, 2014 Mar 15;80(1-2):194-9.
    PMID: 24462236 DOI: 10.1016/j.marpolbul.2014.01.007
    Nineteen pairs of air and seawater samples collected from the equatorial Indian Ocean onboard the Shiyan I from 4/2011 to 5/2011 were analyzed for PCBs and HCB. Gaseous concentrations of ∑(ICES)PCBs (ICES: International Council for the Exploration of the Seas) and HCB were lower than previous data over the study area. Air samples collected near the coast had higher levels of PCBs relative to those collected in the open ocean, which may be influenced by proximity to source regions and air mass origins. Dissolved concentrations of ∑(ICES)PCBs and HCB were 1.4-14 pg L⁻¹ and 0.94-13 pg L⁻¹, with the highest concentrations in the sample collected from Strait of Malacca. Fugacity fractions suggest volatilization of PCBs and HCB from the seawater to air during the cruise, with fluxes of 0.45-34 ng m⁻² d⁻¹ and 0.36-18 ng m⁻² d⁻¹, respectively.
    Matched MeSH terms: Environmental Monitoring
  16. Distribution of black carbon and PAHs in sediments of Peninsular Malaysia
    Vaezzadeh V, Yi X, Rais FR, Bong CW, Thomes MW, Lee CW, et al.
    Mar Pollut Bull, 2021 Nov;172:112871.
    PMID: 34428623 DOI: 10.1016/j.marpolbul.2021.112871
    Concentrations, sources and interactions between black carbon (BC) and polycyclic aromatic hydrocarbons (PAHs) were investigated in 42 sediment samples collected from riverine, coastal and shelf areas in Peninsular Malaysia. The concentrations of BC measured by benzene polycarboxylic acid (BPCA) method and PAHs showed broad spatial variations between the relatively pristine environment of the East coast and developed environment of the West and South coast ranging from 0.02 to 0.36% dw and 57.7 ng g-1 dw to 19,300 ng g-1 dw, respectively. Among diagnostic ratios of PAHs, the ratios of Ant/(Ant+Phe) and LMW/HMW drew the clearest distinctions between the East coast versus the West and South coast sediments indicating the predominance of petrogenic sources in the former versus pyrogenic sources in the latter. PAHs significantly correlated with BC and total organic carbon (TOC) in the sediments (p 
    Matched MeSH terms: Environmental Monitoring
  17. Temporal patterns and source apportionment of nitrate-nitrogen leaching in a paddy field at Kelantan, Malaysia
    Hussain H, Yusoff MK, Ramli MF, Abd Latif P, Juahir H, Zawawi MA
    Pak J Biol Sci, 2013 Nov 15;16(22):1524-30.
    PMID: 24511695
    Nitrate-nitrogen leaching from agricultural areas is a major cause for groundwater pollution. Polluted groundwater with high levels of nitrate is hazardous and cause adverse health effects. Human consumption of water with elevated levels of NO3-N has been linked to the infant disorder methemoglobinemia and also to non-Hodgkin's disease lymphoma in adults. This research aims to study the temporal patterns and source apportionment of nitrate-nitrogen leaching in a paddy soil at Ladang Merdeka Ismail Mulong in Kelantan, Malaysia. The complex data matrix (128 x 16) of nitrate-nitrogen parameters was subjected to multivariate analysis mainly Principal Component Analysis (PCA) and Discriminant Analysis (DA). PCA extracted four principal components from this data set which explained 86.4% of the total variance. The most important contributors were soil physical properties confirmed using Alyuda Forecaster software (R2 = 0.98). Discriminant analysis was used to evaluate the temporal variation in soil nitrate-nitrogen on leaching process. Discriminant analysis gave four parameters (hydraulic head, evapotranspiration, rainfall and temperature) contributing more than 98% correct assignments in temporal analysis. DA allowed reduction in dimensionality of the large data set which defines the four operating parameters most efficient and economical to be monitored for temporal variations. This knowledge is important so as to protect the precious groundwater from contamination with nitrate.
    Matched MeSH terms: Environmental Monitoring/methods
  18. Assessment of groundwater vulnerability to anthropogenic pollution and seawater intrusion in a small tropical island using index-based methods
    Kura NU, Ramli MF, Ibrahim S, Sulaiman WN, Aris AZ, Tanko AI, et al.
    Environ Sci Pollut Res Int, 2015 Jan;22(2):1512-33.
    PMID: 25163562 DOI: 10.1007/s11356-014-3444-0
    In this work, the DRASTIC and GALDIT models were employed to determine the groundwater vulnerability to contamination from anthropogenic activities and seawater intrusion in Kapas Island. In addition, the work also utilized sensitivity analysis to evaluate the influence of each individual parameter used in developing the final models. Based on these effects and variation indices of the said parameters, new effective weights were determined and were used to create modified DRASTIC and GALDIT models. The final DRASTIC model classified the island into five vulnerability classes: no risk (110-140), low (140-160), moderate (160-180), high (180-200), and very high (>200), covering 4, 26, 59, 4, and 7 % of the island, respectively. Likewise, for seawater intrusion, the modified GALDIT model delineates the island into four vulnerability classes: very low (<90), low (90-110), moderate (110-130), and high (>130) covering 39, 33, 18, and 9 % of the island, respectively. Both models show that the areas that are likely to be affected by anthropogenic pollution and seawater intrusion are within the alluvial deposit at the western part of the island. Pearson correlation was used to verify the reliability of the two models in predicting their respective contaminants. The correlation matrix showed a good relationship between DRASTIC model and nitrate (r = 0.58). In a similar development, the correlation also reveals a very strong negative relationship between GALDIT model and seawater contaminant indicator (resistivity Ωm) values (r = -0.86) suggesting that the model predicts more than 86 % of seawater intrusion. In order to facilitate management strategy, suitable areas for artificial recharge were identified through modeling. The result suggested some areas within the alluvial deposit at the western part of the island as suitable for artificial recharge. This work can serve as a guide for a full vulnerability assessment to anthropogenic pollution and seawater intrusion in small islands and will help policy maker and manager with understanding needed to ensure sustainability of the island's aquifer.
    Matched MeSH terms: Environmental Monitoring/methods*; Environmental Monitoring/statistics & numerical data
  19. Fulltext Phylogenetic classification of the world's tropical forests
    Slik JWF, Franklin J, Arroyo-Rodríguez V, Field R, Aguilar S, Aguirre N, et al.
    Proc Natl Acad Sci U S A, 2018 02 20;115(8):1837-1842.
    PMID: 29432167 DOI: 10.1073/pnas.1714977115
    Knowledge about the biogeographic affinities of the world's tropical forests helps to better understand regional differences in forest structure, diversity, composition, and dynamics. Such understanding will enable anticipation of region-specific responses to global environmental change. Modern phylogenies, in combination with broad coverage of species inventory data, now allow for global biogeographic analyses that take species evolutionary distance into account. Here we present a classification of the world's tropical forests based on their phylogenetic similarity. We identify five principal floristic regions and their floristic relationships: (i) Indo-Pacific, (ii) Subtropical, (iii) African, (iv) American, and (v) Dry forests. Our results do not support the traditional neo- versus paleotropical forest division but instead separate the combined American and African forests from their Indo-Pacific counterparts. We also find indications for the existence of a global dry forest region, with representatives in America, Africa, Madagascar, and India. Additionally, a northern-hemisphere Subtropical forest region was identified with representatives in Asia and America, providing support for a link between Asian and American northern-hemisphere forests.
    Matched MeSH terms: Environmental Monitoring
  20. Fulltext Using satellite-measured relative humidity for prediction of Metisa plana's population in oil palm plantations: A comparative assessment of regression and artificial neural network models
    Ruslan SA, Muharam FM, Zulkafli Z, Omar D, Zambri MP
    PLoS One, 2019;14(10):e0223968.
    PMID: 31626637 DOI: 10.1371/journal.pone.0223968
    Metisa plana (Walker) is a leaf defoliating pest that is able to cause staggering economical losses to oil palm cultivation. Considering the economic devastation that the pest could bring, an early warning system to predict its outbreak is crucial. The state of art of satellite technologies are now able to derive environmental factors such as relative humidity (RH) that may influence pest population's fluctuations in rapid, harmless, and cost-effective manners. This study examined the relationship between the presence of Metisa plana at different time lags and remote sensing (RS) derived RH by using statistical and machine learning approaches. Metisa plana census data of cumulated larvae instar 1, 2, 3, and 4 were collected biweekly in 2014 and 2015 in an oil palm plantation in Muadzam Shah, Pahang, Malaysia. Relative humidity values derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images were apportioned to 6 time lags; 1 week (T1), 2 weeks (T2), 3 week (T3), 4 weeks (T4), 5 week (T5) and 6 weeks (T6) and paired with the respective census data. Pearson's correlation was carried out to analyse the relationship between Metisa plana and RH at different time lags. Regression analyses and artificial neural network (ANN) were also conducted to develop the best prediction model of Metisa plana's outbreak. The results showed relatively high correlations, positively or negatively, between the presences of Metisa plana with RH ranging from 0.46 to 0.99. ANN was found to be superior to regression models with the adjusted coefficient of determination (R2) between the actual and predicted Metisa plana values ranging from 0.06 to 0.57 versus 0.00 to 0.05. The analysis on the best time lags illustrated that the multiple time lags were more influential on the Metisa plana population than the individual time lags. The best Metisa plana prediction model was derived from T1, T2 and T3 multiple time lags modelled using the ANN algorithm with R2 value of 0.57, errors below 1.14 and accuracies above 93%. Based on the result of this study, the elucidation of Metisa plana's landscape ecology was possible with the utilization of RH as the predictor variable in consideration of the time lag effects of RH on the pest's population.
    Matched MeSH terms: Environmental Monitoring/methods
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