Displaying publications 61 - 80 of 881 in total

Abstract:
Sort:
  1. Rezvani SM, Abyaneh HZ, Shamshiri RR, Balasundram SK, Dworak V, Goodarzi M, et al.
    Sensors (Basel), 2020 Nov 12;20(22).
    PMID: 33198414 DOI: 10.3390/s20226474
    Optimum microclimate parameters, including air temperature (T), relative humidity (RH) and vapor pressure deficit (VPD) that are uniformly distributed inside greenhouse crop production systems are essential to prevent yield loss and fruit quality. The objective of this research was to determine the spatial and temporal variations in the microclimate data of a commercial greenhouse with tomato plants located in the mid-west of Iran. For this purpose, wireless sensor data fusion was incorporated with a membership function model called Optimality Degree (OptDeg) for real-time monitoring and dynamic assessment of T, RH and VPD in different light conditions and growth stages of tomato. This approach allows growers to have a simultaneous projection of raw data into a normalized index between 0 and 1. Custom-built hardware and software based on the concept of the Internet-of-Things, including Low-Power Wide-Area Network (LoRaWAN) transmitter nodes, a multi-channel LoRaWAN gateway and a web-based data monitoring dashboard were used for data collection, data processing and monitoring. The experimental approach consisted of the collection of meteorological data from the external environment by means of a weather station and via a grid of 20 wireless sensor nodes distributed in two horizontal planes at two different heights inside the greenhouse. Offline data processing for sensors calibration and model validation was carried in multiple MATLAB Simulink blocks. Preliminary results revealed a significant deviation of the microclimate parameters from optimal growth conditions for tomato cultivation due to the inaccurate timer-based heating and cooling control systems used in the greenhouse. The mean OptDeg of T, RH and VPD were 0.67, 0.94, 0.94 in January, 0.45, 0.36, 0.42 in June and 0.44, 0.0, 0.12 in July, respectively. An in-depth analysis of data revealed that averaged OptDeg values, as well as their spatial variations in the horizontal profile were closer to the plants' comfort zone in the cold season as compared with those in the warm season. This was attributed to the use of heating systems in the cold season and the lack of automated cooling devices in the warm season. This study confirmed the applicability of using IoT sensors for real-time model-based assessment of greenhouse microclimate on a commercial scale. The presented IoT sensor node and the Simulink model provide growers with a better insight into interpreting crop growth environment. The outcome of this research contributes to the improvement of closed-field cultivation of tomato by providing an integrated decision-making framework that explores microclimate variation at different growth stages in the production season.
    Matched MeSH terms: Environmental Monitoring/instrumentation*
  2. Bong CH, Lau TL, Ab Ghani A, Chan NW
    Water Sci Technol, 2016 Oct;74(8):1876-1884.
    PMID: 27789888
    The understanding of how the sediment deposit thickness influences the incipient motion characteristic is still lacking in the literature. Hence, the current study aims to determine the effect of sediment deposition thickness on the critical velocity for incipient motion. An incipient motion experiment was conducted in a rigid boundary rectangular flume of 0.6 m width with varying sediment deposition thickness. Findings from the experiment revealed that the densimetric Froude number has a logarithmic relationship with both the thickness ratios ts/d and ts/y0 (ts: sediment deposit thickness; d: grain size; y0: normal flow depth). Multiple linear regression analysis was performed using the data from the current study to develop a new critical velocity equation by incorporating thickness ratios into the equation. The new equation can be used to predict critical velocity for incipient motion for both loose and rigid boundary conditions. The new critical velocity equation is an attempt toward unifying the equations for both rigid and loose boundary conditions.
    Matched MeSH terms: Environmental Monitoring/methods*
  3. Sakai N, Yamamoto S, Matsui Y, Khan MF, Latif MT, Ali Mohd M, et al.
    Sci Total Environ, 2017 May 15;586:1279-1286.
    PMID: 28236484 DOI: 10.1016/j.scitotenv.2017.02.139
    Volatile Organic Compounds (VOCs) in indoor air were investigated at 39 private residences in Selangor State, Malaysia to characterize the indoor air quality and to identify pollution sources. Twenty-two VOCs including isomers (14 aldehydes, 5 aromatic hydrocarbons, acetone, trichloroethylene and tetrachloroethylene) were collected by 2 passive samplers for 24h and quantitated using high performance liquid chromatography and gas chromatography mass spectrometry. Source profiling based on benzene/toluene ratio as well as statistical analysis (cluster analysis, bivariate correlation analysis and principal component analysis) was performed to identify pollution sources of the detected VOCs. The VOCs concentrations were compared with regulatory limits of air quality guidelines in WHO/EU, the US, Canada and Japan to clarify the potential health risks to the residents. The 39 residences were classified into 2 groups and 2 ungrouped residences based on the dendrogram in the cluster analysis. Group 1 (n=30) had mainly toluene (6.87±2.19μg/m3), formaldehyde (16.0±10.1μg/m3), acetaldehyde (5.35±4.57μg/m3) and acetone (11.1±5.95μg/m3) at background levels. Group 2 (n=7) had significantly high values of formaldehyde (99.3±10.7μg/m3) and acetone (35.8±12.6μg/m3), and a tendency to have higher values of acetaldehyde (23.7±13.5μg/m3), butyraldehyde (3.35±0.41μg/m3) and isovaleraldehyde (2.30±0.39μg/m3). The 2 ungrouped residences showed particularly high concentrations of BTX (benzene, toluene and xylene: 235μg/m3 in total) or acetone (133μg/m3). The geometric mean value of formaldehyde (19.2μg/m3) exceeded an 8-hour regulatory limit in Canada (9μg/m3), while those in other compounds did not exceed any regulatory limits, although a few residences exceeded at least one regulatory limit of benzene or acetaldehyde. Thus, the VOCs in the private residences were effectively characterized from the limited number of monitoring, and the potential health risks of the VOCs exposure, particularly formaldehyde, should be considered in the study area.
    Matched MeSH terms: Environmental Monitoring*
  4. Jabal MH, Abdulmunem AR, Abd HS
    J Air Waste Manag Assoc, 2019 01;69(1):109-118.
    PMID: 30215577 DOI: 10.1080/10962247.2018.1523070
    Plant (vegetable) oil has been evaluated as a substitute for mineral oil-based lubricants because of its natural and environmentally friendly characteristics. Availability of vegetable oil makes it a renewable source of bio-oils. Additionally, vegetable oil-based lubricants have shown potential for reducing hydrocarbon and carbon dioxide (CO2) emissions when utilized in internal combustion (IC) engines and industrial operations. In this study, sunflower oil was investigated to study its lubricant characteristics under different loads using the four-ball tribometer and the exhaust emissions were tested using a four-stroke, single-cylinder diesel engine. All experimental works conformed to American Society for Testing and Materials standard (ASTM D4172-B). Under low loads, sunflower oil showed adequate tribological characteristics (antifriction and antiwear) compared with petroleum oil samples. The results also demonstrated that the sunflower oil-based lubricant was more effective in reducing the emission levels of carbon monoxide (CO), CO2, and hydrocarbons under different test conditions. Therefore, sunflower oil has the potential to be used as lubricant of mating components.Implications: An experimental investigation of the characteristics of nonedible sunflower oil tribological behaviors and potential as a renewable source for biofluids alternative to the petroleum oils was carried out. The level of emissions of a four-stroke, single-cylinder diesel engine using sunflower oil as a biolubricant was evaluated.
    Matched MeSH terms: Environmental Monitoring*
  5. Ashikin CN, Rozaimi M, Arina N, Fairoz M, Hidayah N
    Mar Pollut Bull, 2020 Jan;150:110628.
    PMID: 31740184 DOI: 10.1016/j.marpolbul.2019.110628
    Nitrogen is essential for seagrass productivity but excesses in nitrogen exposure contribute to declines in meadow health. This study reports baseline data of bulk nitrogen loadings and contents in surficial sediments and seagrass tissues to determine the extent of nitrogen inputs in meadows of Sungai Pulai estuary (Johor, Malaysia). The sediment contained relatively low nitrogen loadings (mean range of 91-94 g N m-2) with likely origins from land-based sources. At the meadow-level, Enhalus acoroides, Cymodocea serrulata and Thalassia hemprichii are the most important species as nitrogen sinks. The highest δ15N values of seagrass tissues were recorded for T. hemprichii (10.7 ± 0.4‰), which indicated an elevated capacity for internal recycling of nitrogen. The data demonstrates the provision of ecosystem services by the meadows in mitigating excess nitrogen imported into the estuary. Seagrasses health, however, needs to be at optimum levels for the effectiveness of the meadow as a nutrient sink.
    Matched MeSH terms: Environmental Monitoring*
  6. Md Amin R, Sohaimi ES, Anuar ST, Bachok Z
    Mar Pollut Bull, 2020 Jan;150:110616.
    PMID: 31707243 DOI: 10.1016/j.marpolbul.2019.110616
    This study investigates the presence of microplastics in surface seawater and zooplankton at five different locations off the Terengganu coast in Malaysia, southern South China Sea. A total of 983 microplastic particles, with an average abundance of 3.3 particles L-1 were found in surface seawater. An average of one plastic particle was detected in 130 individuals from 6 groups of zooplankton. These groups include fish larvae, cyclopoid, shrimps, polychaete, calanoid and chaetognath where they ingested 0.14, 0.13, 0.01, 0.007, 0.005 and 0.003 particle per individual, respectively. Microplastics in the form of fragments are the most common type of ingested microplastics that ranged between 0.02 mm (cyclopoid) - 1.68 mm (shrimp and zoea). Contrastingly, fibers, which are identified as polyamide are the main type of microplastics that dominate in seawater.
    Matched MeSH terms: Environmental Monitoring*
  7. Ajab H, Ali Khan AA, Nazir MS, Yaqub A, Abdullah MA
    Environ Res, 2019 09;176:108563.
    PMID: 31280029 DOI: 10.1016/j.envres.2019.108563
    Environmental monitoring is important to determine the extent of eco-system pollution and degradation so that effective remedial strategies can be formulated. In this study, an environmentally friendly and cost-effective sensor made up of novel carbon electrode modified with cellulose and hydroxyapatite was developed for the detection of trace lead ions in aqueous system and palm oil mill effluent. Zinc, cadmium, and copper with lead were simultaneously detected using this method. The electrode exhibited high tolerance towards twelve common metal ions and three model surface active substances - sodium dodecyl sulfate, Triton X-100, and cetyltrimethylammonium bromide. Under optimum conditions, the sensor detected lead ions in palm oil mill effluent in the concentration range of 10-50 μg/L with 0.11 ± 0.37 μg/L limit of detection and 0.37 ± 0.37 μg/L limit of quantification. The validation using tap water, blood serum and palm oil mill effluent samples and compared with Atomic Absorption Spectroscopy, suggested excellent sensitivity of the sensor to detect lead ions in simple and complex matrices. The cellulose produced based on "green" techniques from agro-lignocellulosic wastes, in combination with hydroxyapatite, were proven effective as components in the carbon electrode composite. It has great potential in both clinical and environmental use.
    Matched MeSH terms: Environmental Monitoring/methods*
  8. Hamid HHA, Latif MT, Uning R, Nadzir MSM, Khan MF, Ta GC, et al.
    Environ Monit Assess, 2020 May 08;192(6):342.
    PMID: 32382809 DOI: 10.1007/s10661-020-08311-4
    Benzene, toluene, ethylbenzene and xylenes (BTEX) are well known hazardous volatile organic compounds (VOCs) due to their human health risks and photochemical effects. The main objective of this study was to estimate BTEX levels and evaluate interspecies ratios and ozone formation potentials (OFP) in the ambient air of urban Kuala Lumpur (KL) based on a passive sampling method with a Tenax® GR adsorbent tube. Analysis of BTEX was performed using a thermal desorption (TD)-gas chromatography mass spectrometer (GCMS). OFP was calculated based on the Maximum Incremental Reactivity (MIR). Results from this study showed that the average total BTEX during the sampling period was 66.06 ± 2.39 μg/m3. Toluene (27.70 ± 0.97 μg/m3) was the highest, followed by m,p-xylene (13.87 ± 0.36 μg/m3), o-xylene (11.49 ± 0.39 μg/m3), ethylbenzene (8.46 ± 0.34 μg/m3) and benzene (3.86 ± 0.31 μg/m3). The ratio of toluene to benzene (T:B) is > 7, suggesting that VOCs in the Kuala Lumpur urban environment are influenced by vehicle emissions and other anthropogenic sources. The average of ozone formation potential (OFP) value from BTEX was 278.42 ± 74.64 μg/m3 with toluene and xylenes being the major contributors to OFP. This study also indicated that the average of benzene concentration in KL was slightly lower than the European Union (EU)-recommended health limit value for benzene of 5 μg/m3 annual exposure.
    Matched MeSH terms: Environmental Monitoring*
  9. Wong YJ, Arumugasamy SK, Chung CH, Selvarajoo A, Sethu V
    Environ Monit Assess, 2020 Jun 17;192(7):439.
    PMID: 32556670 DOI: 10.1007/s10661-020-08268-4
    Presence of copper within water bodies deteriorates human health and degrades natural environment. This heavy metal in water is treated using a promising biochar derived from rambutan (Nephelium lappaceum) peel through slow pyrolysis. This research compares the efficacies of artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and multiple linear regression (MLR) models and evaluates their capability in estimating the adsorption efficiency of biochar for the removal of Cu (II) ions based on 480 experimental sets obtained in a laboratory batch study. The effects of operational parameters such as contact time, operating temperature, biochar dosage, and initial Cu (II) ion concentration on removing Cu (II) ions were investigated. Eleven different training algorithms in ANN and 8 different membership functions in ANFIS were compared statistically and evaluated in terms of estimation errors, which are root mean squared error (RMSE), mean absolute error (MAE), and accuracy. The effects of number of hidden neuron in ANN model and fuzzy set combination in ANFIS were studied. In this study, ANFIS model with Gaussian membership function and fuzzy set combination of [4 5 2 3] was found to be the best method, with accuracy of 90.24% and 87.06% for training and testing dataset, respectively. Contribution of this study is that ANN, ANFIS, and MLR modeling techniques were used for the first time to study the adsorption of Cu (II) ions from aqueous solutions using rambutan peel biochar.
    Matched MeSH terms: Environmental Monitoring*
  10. Hojo A, Tsuji N, Kasuga T, Osaki M
    Environ Monit Assess, 2021 Nov 12;193(12):793.
    PMID: 34767121 DOI: 10.1007/s10661-021-09434-y
    We have pragmatically but accurately evaluated the natural capital of a small northern town, Shimokawa, Hokkaido, Japan. The key industries are forestry, wood manufacturing, and agriculture. From an environmental perspective, Shimokawa was nominated as a Japanese FutureCity. Consequently, the total natural capital value (NCV) of the forest and agricultural lands was calculated to be 1.326 billion USD/year (or 24,161 USD/ha/year) and 44 million USD/year (or 19,692 USD/ha/year), respectively, in 2012. The sum of these NCVs was more than 7 times greater than the yearly gross production of the town, although the forest had a higher NCV because of the larger area (54,862 ha for forest area), compared with 2953 ha for agricultural area. This substantial NCV is mainly generated by sustainable forest management. The timber account showed that the annual tree growth was greater than the annual harvest of trees. The CO2 account derived from a one-year calculation showed that the town served as a CO2 sink at 107,249 t-CO2/year due to the large amount of annual tree growth and CO2 storage in the harvested wood products even if CO2 was emitted from industries and households. The forestry and wood manufacturing industries, as well as agriculture, created socioeconomic effects for the townspeople, ranging from job creation, study tours, and social welfare. This NCV accounting for Shimokawa town ensures the sustainable use of valuable environmental assets and will help other communities recognize their own NCV accounts.
    Matched MeSH terms: Environmental Monitoring*
  11. Aburas MM, Ho YM, Ramli MF, Ash'aari ZH
    Environ Monit Assess, 2018 Feb 20;190(3):156.
    PMID: 29464400 DOI: 10.1007/s10661-018-6522-9
    The identification of spatio-temporal patterns of the urban growth phenomenon has become one of the most significant challenges in monitoring and assessing current and future trends of the urban growth issue. Therefore, spatio-temporal and quantitative techniques should be used hand in hand for a deeper understanding of various aspects of urban growth. The main purpose of this study is to monitor and assess the significant patterns of urban growth in Seremban using a spatio-temporal built-up area analysis. The concentric circles approach was used to measure the compactness and dispersion of built-up area by employing Shannon's Entropy method. The spatial directions approach was also utilised to measure the sustainability and speed of development, while the gradient approach was used to measure urban dynamics by employing landscape matrices. The overall results confirm that urban growth in Seremban is dispersed, unbalanced and unsustainable with a rapid speed of regional development. The main contribution of using existing methods with other methods is to provide several spatial and statistical dimensions that can help researchers, decision makers and local authorities understand the trend of growth and its patterns in order to take the appropriate decisions for future urban planning. For example, Shannon's Entropy findings indicate a high value of dispersion between the years 1990 and 2000 and from 2010 to 2016 with a growth rate of approximately 94 and 14%, respectively. Therefore, these results can help and support decision makers to implement alternative urban forms such as the compactness form to achieve an urban form that is more suitable and sustainable. The results of this study confirm the importance of using spatio-temporal built-up area and quantitative analysis to protect the sustainability of land use, as well as to improve the urban planning system via the effective monitoring and assessment of urban growth trends and patterns.
    Matched MeSH terms: Environmental Monitoring/methods
  12. 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
  13. Madadi R, Mohamadi S, Rastegari M, Karbassi A, Rakib MRJ, Khandaker MU, et al.
    Sci Rep, 2022 Nov 17;12(1):19736.
    PMID: 36396803 DOI: 10.1038/s41598-022-21242-z
    Rapid industrialization and urbanization have resulted in environmental pollution and unsustainable development of cities. The concentration of 12 potentially toxic metal(loid)s in windowsill dust samples (n = 50) were investigated from different functional areas of Qom city with the highest level of urbanization in Iran. Spatial analyses (ArcGIS 10.3) and multivariate statistics including Principal Component Analysis and Spearman correlation (using STATISTICA-V.12) were adopted to scrutinize the possible sources of pollution. The windowsill dust was very highly enriched with Sb (50 mg/kg) and Pb (1686 mg/kg). Modified degree of contamination (mCd) and the pollution load indices (PLIzone) indicate that windowsill dust in all functional areas was polluted in the order of industrial > commercial > residential > green space. Arsenic, Cd, Mo, Pb, Sb, Cu, and Zn were sourced from a mixture of traffic and industrial activities, while Mn in the dust mainly stemmed from mining activities. Non-carcinogenic health risk (HI) showed chronic exposure of Pb for children in the industrial zone (HI = 1.73). The estimations suggest the possible carcinogenic risk of As, Pb, and Cr in the dust. The findings of this study reveal poor environmental management of the city. Emergency plans should be developed to minimize the health risks of dust to residents.
    Matched MeSH terms: Environmental Monitoring/methods
  14. Rendana M, Idris WMR, Rahim SA
    Environ Monit Assess, 2022 Dec 17;195(1):205.
    PMID: 36527450 DOI: 10.1007/s10661-022-10833-y
    Mining activities in the Chini Lake catchment area have been extensive for several years, contributing to acid mine drainage (AMD) events with high concentrations of iron (Fe) and other heavy metals impacting the surface water. However, during the restriction period due to the COVID-19 outbreak, anthropogenic activities have been suspended, which clearly shows a good opportunity for a better environment. Therefore, we aimed to analyze the variation of AMD-associated water pollution in three main zones of the Chini Lake catchment area using Sentinel-2 data for the periods pre-movement control order (MCO), during MCO, and post-MCO from 2019 to 2021. These three zones were chosen due to their proximity to mining areas: zone 1 in the northeastern part, zone 2 in the southeastern part, and zone 3 in the southern part of the Chini Lake area. The acid mine water index (AMWI) was a specific index used to estimate acid mine water. The AMWI values from Sentinel-2 images exhibited that the mean AMWI values in all zones during the MCO period decreased by 14% compared with the pre-MCO period. The spatiotemporal analysis found that the highest polluted zones were recorded in zone 1, followed by zone 3 and zone 2. As compared with during the MCO period, the maximum percentage of increment during post-MCO in all zones was up to 25%. The loosened restriction policy has resulted in more AMD flowing into surface water and increased pollution in Chini Lake. As a whole, our outputs revealed that Sentinel-2 data had a major potential for assessing the AMD-associated pollution of water.
    Matched MeSH terms: Environmental Monitoring/methods
  15. Khairul Hasni NA, Anual ZF, Rashid SA, Syed Abu Thahir S, Veloo Y, Fang KS, et al.
    Environ Pollut, 2023 May 01;324:121095.
    PMID: 36682614 DOI: 10.1016/j.envpol.2023.121095
    Contamination of water systems with endocrine disrupting chemicals (EDCs) is becoming a major public health concern due to their toxicity and ubiquity. The intrusion of EDCs into water sources and drinking water has been associated with various adverse health effects on humans. However, there is no comprehensive overview of the occurrence of EDCs in Malaysia's water systems. This report aims to describe the occurrence of EDCs and their locations. Literature search was conducted electronically in two databases (PubMed and Scopus). A total of 41 peer-reviewed articles published between January 2000 and May 2021 were selected. Most of the articles dealt with pharmaceuticals (16), followed by pesticides (7), hormones (7), mixed compounds (7), and plasticisers (4). Most studies (40/41) were conducted in Peninsular Malaysia, with 60.9% in the central region and almost half (48.8%) in the Selangor State. Only one study was conducted in the northern region and East Malaysia. The Langat River, the Klang River, and the Selangor River were among the most frequently studied EDC-contaminated surface waters, while the Pahang River and the Skudai River had the highest concentrations of some of the listed compounds. Most of the risk assessments resulted in a hazard quotient (HQ) and a risk quotient (RQ)  1 in the Selangor River. An RQ > 1 for combined pharmaceuticals was found in Putrajaya tap water. Overall, this work provides a comprehensive overview of the occurrence of EDCs in Malaysia's water systems. The findings from this review can be used to mitigate risks and strengthen legislation and policies for safer drinking water.
    Matched MeSH terms: Environmental Monitoring/methods
  16. Chen HL, Selvam SB, Ting KN, Gibbins CN
    Environ Monit Assess, 2023 Jan 18;195(2):307.
    PMID: 36652034 DOI: 10.1007/s10661-022-10856-5
    Recent increase in awareness of the extent of microplastic contamination in marine and freshwater systems has heightened concerns over the ecological and human health risks of this ubiquitous material. Assessing risks posed by microplastic in freshwater systems requires sampling to establish contamination levels, but standard sampling protocols have yet to be established. An important question is whether sampling and assessment should focus on microplastic concentrations in the water or the amount deposited on the bed. On three dates, five replicated water and bed sediment samples were collected from each of the eight sites along the upper reach of the Semenyih River, Malaysia. Microplastics were found in all 160 samples, with mean concentrations of 3.12 ± 2.49 particles/L in river water and 6027.39 ± 16,585.87 particles/m2 deposited on the surface of riverbed sediments. Fibres were the dominant type of microplastic in all samples, but fragments made up a greater proportion of the material on the bed than in the water. Within-site variability in microplastic abundance was high for both water and bed sediments, and very often greater than between-site variability. Patterns suggest that microplastic accumulation on the bed is spatially variable, and single samples are therefore inadequate for assessing bed contamination levels at a site. Sites with the highest mean concentrations in samples of water were not those with the highest concentrations on the bed, indicating that monitoring based only on water samples may not provide a good picture of either relative or absolute bed contamination levels, nor the risks posed to benthic organisms.
    Matched MeSH terms: Environmental Monitoring/methods
  17. Tao H, Al-Hilali AA, Ahmed AM, Mussa ZH, Falah MW, Abed SA, et al.
    Chemosphere, 2023 Mar;317:137914.
    PMID: 36682637 DOI: 10.1016/j.chemosphere.2023.137914
    Heavy metals (HMs) are a vital elements for investigating the pollutant level of sediments and water bodies. The Murray-Darling river basin area located in Australia is experiencing severe damage to increased crop productivity, loss of soil fertility, and pollution levels within the vicinity of the river system. This basin is the most effective primary production area in Australia where agricultural productivity is increased the gross domastic product in the entire mainland. In this study, HMs contaminations are examined for eight study sites selected for the Murray-Darling river basin where the inverse Distance Weighting interpolation method is used to identify the distribution of HMs. To pursue this, four different pollution indices namely the Geo-accumulation index (Igeo), Contamination factor (CF), Pollution load index (PLI), single-factor pollution index (SPLI), and the heavy metal pollution index (HPI) are computed. Following this, the Pearson correlation matrix is used to identify the relationships among the two HM parameters. The results indicate that the conductivity and N (%) are relatively high in respect to using Igeo and PLI indexes for study sites 4, 6, and 7 with 2.93, 3.20, and 1.38, respectively. The average HPI is 216.9071 that also indicates higher level pollution in the Murray-Darling river basin and the highest HPI value is noted in sample site 1 (353.5817). The study also shows that the levels of Co, P, Conductivity, Al, and Mn are mostly affected by HMs and that these indices indicate the maximum HM pollution level in the Murray-Darling river basin. Finally, the results show that the high HM contamination level appears to influence human health and local environmental conditions.
    Matched MeSH terms: Environmental Monitoring/methods
  18. Li Q, Zhang K, Li R, Yang L, Yi Y, Liu Z, et al.
    Sci Total Environ, 2023 May 10;872:162071.
    PMID: 36775179 DOI: 10.1016/j.scitotenv.2023.162071
    Biomass burning (BB) has significant impacts on air quality and climate change, especially during harvest seasons. In previous studies, levoglucosan was frequently used for the calculation of BB contribution to PM2.5, however, the degradation of levoglucosan (Lev) could lead to large uncertainties. To quantify the influence of the degradation of Lev on the contribution of BB to PM2.5, PM2.5-bound biomass burning-derived markers were measured in Changzhou from November 2020 to March 2021 using the thermal desorption aerosol gas chromatography-mass spectrometry (TAG-GC/MS) system. Temporal variations of three anhydro-sugar BB tracers (e.g., levoglucosan, mannosan (Man), and galactosan (Gal)) were obtained. During the sampling period, the degradation level of air mass (x) was 0.13, indicating that ~87 % of levoglucosan had degraded before sampling in Changzhou. Without considering the degradation of levoglucosan in the atmosphere, the contribution of BB to OC were 7.8 %, 10.2 %, and 9.3 % in the clean period, BB period, and whole period, respectively, which were 2.4-2.6 times lower than those (20.8 %-25.9 %) considered levoglucosan degradation. This illustrated that the relative contribution of BB to OC could be underestimated (~14.9 %) without considering degradation of levoglucosan. Compared to the traditional method (i.e., only using K+ as BB tracer), organic tracers (Lev, Man, Gal) were put into the Positive Matrix Factorization (PMF) model in this study. With the addition of BB organic tracers and replaced K+ with K+BB (the water-soluble potassium produced by biomass burning), the overall contribution of BB to PM2.5 was enhanced by 3.2 % after accounting for levoglucosan degradation based on the PMF analysis. This study provides useful information to better understand the effect of biomass burning on the air quality in the Yangtze River Delta region.
    Matched MeSH terms: Environmental Monitoring/methods
  19. Sugumaran D, Blake WH, Millward GE, Yusop Z, Mohd Yusoff AR, Mohamad NA, et al.
    Environ Sci Pollut Res Int, 2023 Jun;30(28):71881-71896.
    PMID: 35411514 DOI: 10.1007/s11356-022-19904-6
    Pristine tropical river systems are coming under increasing pressure from the development of economic resources such as forestry and mining for valuable elements. The Lebir catchment, north eastern Malaysia, is now under development as a result of unregulated tree felling and mining for essential and rare metals. Two sediment cores, one in the upstream reaches and the other from the downstream reaches, were taken from flood prone area of the Lebir River, Malaysia, and analysed for their elemental composition by XRF, specifically Al, Si, Fe, Ca, K, Mg, Mn, V, Cu, Ni, Pb, Cr, Zn, As, Th and U. Activities of fallout radionuclides, 137Cs and 210Pb were also determined to from a geochronological context. The elemental concentrations in the soils were assessed in terms of their enrichment factor and Si, Ca, K, Mg, Mn, V, Cu, Ni and Zn were found not to be enriched, whereas As, Th and U had elevated enrichment factors. The Th and U were particularly enriched in the downstream core indicating inputs from a tributary that drains a catchment with known deposits of Th and possibly U. The results suggest that the growth in economic development is fostering the transport of contaminants by the major rivers which, in turn, is contaminating the riverine floodplains. This points to the need for a more integrated and holistic approach to river basin management to maintain the environmental quality of these fragile aquatic systems.
    Matched MeSH terms: Environmental Monitoring/methods
  20. 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
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links