Displaying publications 1 - 20 of 143 in total

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  1. A climate distribution model of malaria transmission in Sudan
    Musa MI, Shohaimi S, Hashim NR, Krishnarajah I
    Geospat Health, 2012 Nov;7(1):27-36.
    PMID: 23242678
    Malaria remains a major health problem in Sudan. With a population exceeding 39 million, there are around 7.5 million cases and 35,000 deaths every year. The predicted distribution of malaria derived from climate factors such as maximum and minimum temperatures, rainfall and relative humidity was compared with the actual number of malaria cases in Sudan for the period 2004 to 2010. The predictive calculations were done by fuzzy logic suitability (FLS) applied to the numerical distribution of malaria transmission based on the life cycle characteristics of the Anopheles mosquito accounting for the impact of climate factors on malaria transmission. This information is visualized as a series of maps (presented in video format) using a geographical information systems (GIS) approach. The climate factors were found to be suitable for malaria transmission in the period of May to October, whereas the actual case rates of malaria were high from June to November indicating a positive correlation. While comparisons between the prediction model for June and the case rate model for July did not show a high degree of association (18%), the results later in the year were better, reaching the highest level (55%) for October prediction and November case rate.
    Matched MeSH terms: Rain/parasitology
  2. A clonal selection algorithm model for daily rainfall data prediction
    Noor Rodi NS, Malek MA, Ismail AR, Ting SC, Tang CW
    Water Sci Technol, 2014;70(10):1641-7.
    PMID: 25429452 DOI: 10.2166/wst.2014.420
    This study applies the clonal selection algorithm (CSA) in an artificial immune system (AIS) as an alternative method to predicting future rainfall data. The stochastic and the artificial neural network techniques are commonly used in hydrology. However, in this study a novel technique for forecasting rainfall was established. Results from this study have proven that the theory of biological immune systems could be technically applied to time series data. Biological immune systems are nonlinear and chaotic in nature similar to the daily rainfall data. This study discovered that the proposed CSA was able to predict the daily rainfall data with an accuracy of 90% during the model training stage. In the testing stage, the results showed that an accuracy between the actual and the generated data was within the range of 75 to 92%. Thus, the CSA approach shows a new method in rainfall data prediction.
    Matched MeSH terms: Rain*
  3. A comparative study of extreme rainfall in Peninsular Malaysia: with reference to partial duration and annual extreme series
    Wan Zin Wan Zawiah, Abdul Aziz Jemain, Kamarulzaman Ibrahim, Jamaludin Suhaila, Mohd Deni Sayang
    Sains Malaysiana, 2009;38.
    Statistical distributions of annual extreme (AE) and partial duration (PD) for rainfall events are analysed using a database of 50 rain-gauge stations in Peninsular Malaysia, involving records of time series data which extend from 1975 to 2004. The generalised extreme value (GEV) and generalised Pareto (GP) distributions are considered to model the series of annual extreme and partial duration. In both cases, the three parameter models such as GEV and GP distributions are fitted by means of L-moments method, which is one of the commonly used methods for robust estimation. The goodness-of-fit of the theoretical distribution to the data is then evaluated by means of L-moment ratio diagram and several goodness-of-fit (GOF) tests for each of the 50 stations. It is found that for the majority of stations, the AE and PD series are well fitted by the GEV and GP models, respectively. Based on the models that have been identified, we can reasonably predict the risks associated with extreme rainfall for various return periods.
    Matched MeSH terms: Rain
  4. A comparison of various approaches used in source apportionments for precipitation nitrogen in a mountain region of southwest China
    Cui J, Zhou F, Gao M, Zhang L, Zhang L, Du K, et al.
    Environ Pollut, 2018 Oct;241:810-820.
    PMID: 29909307 DOI: 10.1016/j.envpol.2018.06.028
    Six different approaches are applied in the present study to apportion the sources of precipitation nitrogen making use of precipitation data of dissolved inorganic nitrogen (DIN, including NO3- and NH4+), dissolved organic nitrogen (DON) and δ15N signatures of DIN collected at six sampling sites in the mountain region of Southwest China. These approaches include one quantitative approach running a Bayesian isotope mixing model (SIAR model) and five qualitative approaches based on in-situ survey (ISS), ratio of NH4+/NO3- (RN), principal component analysis (PCA), canonical-correlation analysis (CCA) and stable isotope approach (SIA). Biomass burning, coal combustion and mobile exhausts in the mountain region are identified as major sources for precipitation DIN while biomass burning and volatilization sources such as animal husbandries are major ones for DON. SIAR model results suggest that mobile exhausts, biomass burning and coal combustion contributed 25.1 ± 14.0%, 26.0 ± 14.1% and 27.0 ± 12.6%, respectively, to NO3- on the regional scale. Higher contributions of both biomass burning and coal combustion appeared at rural and urban sites with a significant difference between Houba (rural) and the wetland site (p 
    Matched MeSH terms: Rain/chemistry*
  5. A modelling study of the event-based retention performance of green roof under the hot-humid tropical climate in Kuching
    Chai CT, Putuhena FJ, Selaman OS
    Water Sci Technol, 2017 Dec;76(11-12):2988-2999.
    PMID: 29210686 DOI: 10.2166/wst.2017.472
    The influences of climate on the retention capability of green roof have been widely discussed in existing literature. However, knowledge on how the retention capability of green roof is affected by the tropical climate is limited. This paper highlights the retention performance of the green roof situated in Kuching under hot-humid tropical climatic conditions. Using the green roof water balance modelling approach, this study simulated the hourly runoff generated from a virtual green roof from November 2012 to October 2013 based on past meteorological data. The result showed that the overall retention performance was satisfactory with a mean retention rate of 72.5% from 380 analysed rainfall events but reduced to 12.0% only for the events that potentially trigger the occurrence of flash flood. By performing the Spearman rank's correlation analysis, it was found that the rainfall depth and mean rainfall intensity, individually, had a strong negative correlation with event retention rate, suggesting that the retention rate increases with decreased rainfall depth. The expected direct relationship between retention rate and antecedent dry weather period was found to be event size dependent.
    Matched MeSH terms: Rain*
  6. A review of bioretention components and nutrient removal under different climates-future directions for tropics
    Goh HW, Lem KS, Azizan NA, Chang CK, Talei A, Leow CS, et al.
    Environ Sci Pollut Res Int, 2019 May;26(15):14904-14919.
    PMID: 30977005 DOI: 10.1007/s11356-019-05041-0
    Bioretention systems have been implemented as stormwater best management practices (BMPs) worldwide to treat non-point sources pollution. Due to insufficient research, the design guidelines for bioretention systems in tropical countries are modeled after those of temperate countries. However, climatic factors and stormwater runoff characteristics are the two key factors affecting the capacity of bioretention system. This paper reviews and compares the stormwater runoff characteristics, bioretention components, pollutant removal requirements, and applications of bioretention systems in temperate and tropical countries. Suggestions are given for bioretention components in the tropics, including elimination of mulch layer and submerged zone. More research is required to identify suitable additives for filter media, study tropical shrubs application while avoiding using grass and sedges, explore function of soil faunas, and adopt final discharged pollutants concentration (mg/L) on top of percentage removal (%) in bioretention design guidelines.
    Matched MeSH terms: Rain
  7. Fulltext A time-series prediction model of acute myocardial infarction in northern of Iran: the risk of climate change and religious mourning
    Sharif Nia H, Gorgulu O, Naghavi N, Froelicher ES, Fomani FK, Goudarzian AH, et al.
    BMC Cardiovasc Disord, 2021 11 23;21(1):563.
    PMID: 34814834 DOI: 10.1186/s12872-021-02372-0
    BACKGROUND: Although various studies have been conducted on the effects of seasonal climate changes or emotional variables on the risk of AMI, many of them have limitations to determine the predictable model. The currents study is conducted to assess the effects of meteorological and emotional variables on the incidence and epidemiological occurrence of acute myocardial infarction (AMI) in Sari (capital of Mazandaran, Iran) during 2011-2018.

    METHODS: In this study, a time series analysis was used to determine the variation of variables over time. All series were seasonally adjusted and Poisson regression analysis was performed. In the analysis of meteorological data and emotional distress due to religious mourning events, the best results were obtained by autoregressive moving average (ARMA) (5,5) model.

    RESULTS: It was determined that average temperature, sunshine, and rain variables had a significant effect on death. A total of 2375 AMI's were enrolled. Average temperate (°C) and sunshine hours a day (h/day) had a statistically significant relationship with the number of AMI's (β = 0.011, P = 0.014). For every extra degree of temperature increase, the risk of AMI rose [OR = 1.011 (95%CI 1.00, 1.02)]. For every extra hour of sunshine, a day a statistically significant increase [OR = 1.02 (95% CI 1.01, 1.04)] in AMI risk occurred (β = 0.025, P = 0.001). Religious mourning events increase the risk of AMI 1.05 times more. The other independent variables have no significant effects on AMI's (P > 0.05).

    CONCLUSION: Results demonstrate that sunshine hours and the average temperature had a significant effect on the risk of AMI. Moreover, emotional distress due to religious morning events increases AMI. More specific research on this topic is recommended.

    Matched MeSH terms: Rain
  8. Achieving pro-poor growth and environmental sustainability agenda through information technologies: as right as rain
    Imran M, Khan KB, Zaman K, Musah MB, Sudiapermana E, Aziz ARA, et al.
    Environ Sci Pollut Res Int, 2021 Aug;28(30):41000-41015.
    PMID: 33774795 DOI: 10.1007/s11356-021-13630-1
    The pro-poor growth and environmental sustainability are the twin agendas widely discussed in environmental science literature. The technology-embodied growth helps to attain both agendas through knowledge sharing and technology transfer, which trickle down to the poor income group and improve their living standards. Hence, the role of information and communication technologies (ICTs) is deemed crucial in boosting economic growth and is under deep consideration to establish its role in reducing poverty and environmental pollution. The current study examines the long-run relationship between ICTs, poverty reduction, and ecological degradation in Pakistan using time series data from 1975-2018. The short- and long-run parameter estimates were obtained through the Autoregressive Distributed Lag (ARDL) model for robust inferences. The results substantiate the inverted U-shaped Environmental Kuznets Curve relationship between income and emissions with a turning point at US$1000 in the short-run and US$800 in the long-run. The results confirmed the decisive intervention of ICTs factors in the poverty reduction, i.e., computer communications and mobile-telephone-broadband subscriptions support to reduce poverty incidence with the mediation of inbound FDI in a country. As far as income inequality is concerned, it shows that computer services support minimizing income inequality via a channel of high-technology exports in a country. The technology embodied emissions verified in the long-run, where mobile-telephone-broadband subscriptions increase carbon emissions. Finally, mobile-telephone-broadband subscriptions and inbound FDI both are significant contributors to amplify the country's economic growth. The results conclude that poverty reduction and environmental sustainability agenda are achieved by developing green ICT infrastructure in a country.
    Matched MeSH terms: Rain
  9. Ant-gardens of tropical Asian rainforests
    Kaufmann E, Maschwitz U
    Naturwissenschaften, 2006 May;93(5):216-27.
    PMID: 16544124
    Ant-garden (AG) associations are systems of epiphytic plants and arboricolous (i.e., tree-living) ants, in which the ants build fragile carton nests containing organic material. They collect and incorporate seeds or fruits of epiphytes that then germinate and grow on the nest [sensu Corbara et al. (1999) 38:73-89]. The plant roots stabilize the nest carton. AGs have been well-known in the neotropics for more than 100 years. In contrast, reports on similar associations in the paleotropics are scarce so far. After discovering a first common AG system on giant bamboo [Kaufmann et al. (2001) 48:125-133], we started a large-scale survey for AGs in Peninsular Malaysia, Borneo, Java, and southern Thailand. A great variety of AG systems (altogether including 18 ant species and 51 plant species) was discovered and is described in the present paper. The high number of species participating in AG associations was reflected by a great variability in the specific appearances of the nest gardens. Frequently, further groups of organisms (e.g., hemipteran trophobionts, fungi) were also involved. Preference patterns of particular ant and epiphyte species for each other and for particular phorophytes (carrier trees) were detected. We integrate domatia-producing, so-called ant-house epiphytes in our study and compare their phases of establishment, as well as other characteristics, to "classical" AGs, coming to the conclusion that they should be regarded only as a special type of AG epiphyte and not as a separate ecological category.
    Matched MeSH terms: Rain
  10. Fulltext Antifungal efficacy of crude aqueous weed extracts against pathogen of cocoa black pod rot
    Nor Amerulah Nor Mohamad, Suhaida Salleh, Hamzah Abdul Aziz
    Borneo Akademika, 2019;3(2):12-22.
    MyJurnal
    Black pod rot is the most economically important disease of cocoa in Malaysia which is
    mainly caused by a highly polyphagous Phytophthora species, called Phytophthora palmivora.
    The fungus could attack all parts of the cocoa plant organs and caused various diseases at
    any growth stage from seedling until the mature stages, especially during raining season. The
    application of synthetic fungicides has been widely recommended to manage the disease but
    their repeated use had led to other problems such as environmental, human health and
    development of fungicide resistance issues. This study isolated and identified Phytopththora
    isolate from a cocoa pod sample based on micro-morphological characters. Besides, the
    present investigation was undertaken to screen for the antifungal potency of different weed
    extracts against the Phytophthora pathogen using poisoned food technique. The fungal isolate
    was successfully recovered from pod tissues of clone PBC123 on 20% tomato juice agar
    culture (20T). Only one out of ten weed extracts tested showed a significant in vitro inhibitory
    effect towards mycelial growth of Phytophthora isolate, which was aqueous crude leaf extract
    of Solanum torvum (42.68%). This study indicated that the potential of weed extracts in the
    management of Phytophthora diseases, and may offer more natural, effective and economical
    control methods.
    Matched MeSH terms: Rain
  11. Application of CHIRPS dataset in the selection of rain-based indices for drought assessments in Johor River Basin, Malaysia
    Sa'adi Z, Yusop Z, Alias NE, Shiru MS, Muhammad MKI, Ramli MWA
    Sci Total Environ, 2023 Sep 20;892:164471.
    PMID: 37257620 DOI: 10.1016/j.scitotenv.2023.164471
    This paper aims to select the most appropriate rain-based meteorological drought index for detecting drought characteristics and identifying tropical drought events in the Johor River Basin (JRB). Based on a multi-step approach, the study evaluated seven drought indices, including the Rainfall Anomaly Index (RAI), Standardized Precipitation Index (SPI), China-Z Index (CZI), Modified China-Z Index (MCZI), Percent of Normal (PN), Deciles Index (DI), and Z-Score Index (ZSI), based on the CHIRPS rainfall gridded-based datasets from 1981 to 2020. Results showed that CZI, MCZI, SPI, and ZSI outperformed the other indices based on their correlation and linearity (R2 = 0.96-0.99) along with their ranking based on the Compromise Programming Index (CPI). The historical drought evaluation revealed that MCZI, SPI, and ZSI performed similarly in detecting drought events, but SPI was more effective in detecting spatial coverage and the occurrence of 'very dry' and 'extremely dry' drought events. Based on SPI, the study found that the downstream area, north-easternmost area, and eastern boundary of the basin were more prone to higher frequency and longer duration droughts. Furthermore, the study found that prolonged droughts are characterized by episodic drought events, which occur with one to three months of 'relief period' before another drought event occurs. The study revealed that most drought events that coincide with El Niño, positive Indian Ocean Dipole (IOD), and negative Madden-Julian Oscillation (MJO) events, or a combination of these events, may worsen drought conditions. The application of CHIRPS datasets enables better spatiotemporal mapping and prediction of drought for JRB, and the output is pertinent for improving water management strategies and adaptation measures. Understanding spatiotemporal drought conditions is crucial to ensuring sustainable development and policies through better regulation of human activities. The framework of this research can be applied to other river basins in Malaysia and other parts of Southeast Asia.
    Matched MeSH terms: Rain
  12. Application of loglinear models in estimating wet category in monthly rainfall
    Wahidah Sanusi, Kamarulzaman Ibrahim
    Sains Malaysiana, 2012;41:1345-1353.
    Climate changes have become serious issues that have been widely discussed by researchers. One of the issues concerns with the study in changes of rainfall patterns. Changes in rainfall patterns affect the dryness and wetness conditions of a region. In this study, the three-dimensional loglinear model was used to fit the observed frequencies and to model the expected frequencies of wet class transition on eight rainfall stations in Peninsular Malaysia. The expected frequency values could be employed to determine the odds value of wet classes of each station. Further, the odds values were used to estimate the wet class of the following month if the wet class of the previous month and current month were identified. The wet classification based on SPI index (Standardized Precipitation Index). For station that was analyzed, there was no difference found were between estimated and observed wet classes. It was concluded that the loglinear models can be used to estimate the wetness classes through the estimates of odds values.
    Matched MeSH terms: Rain
  13. Applying a random parameters Negative Binomial Lindley model to examine multi-vehicle crashes along rural mountainous highways in Malaysia
    Rusli R, Haque MM, Afghari AP, King M
    Accid Anal Prev, 2018 Oct;119:80-90.
    PMID: 30007211 DOI: 10.1016/j.aap.2018.07.006
    Road safety in rural mountainous areas is a major concern as mountainous highways represent a complex road traffic environment due to complex topology and extreme weather conditions and are associated with more severe crashes compared to crashes along roads in flatter areas. The use of crash modelling to identify crash contributing factors along rural mountainous highways suffers from limitations in data availability, particularly in developing countries like Malaysia, and related challenges due to the presence of excess zero observations. To address these challenges, the objective of this study was to develop a safety performance function for multi-vehicle crashes along rural mountainous highways in Malaysia. To overcome the data limitations, an in-depth field survey, in addition to utilization of secondary data sources, was carried out to collect relevant information including roadway geometric factors, traffic characteristics, real-time weather conditions, cross-sectional elements, roadside features, and spatial characteristics. To address heterogeneity resulting from excess zeros, three specialized modelling techniques for excess zeros including Random Parameters Negative Binomial (RPNB), Random Parameters Negative Binomial - Lindley (RPNB-L) and Random Parameters Negative Binomial - Generalized Exponential (RPNB-GE) were employed. Results showed that the RPNB-L model outperformed the other two models in terms of prediction ability and model fit. It was found that heavy rainfall at the time of crash and the presence of minor junctions along mountainous highways increase the likelihood of multi-vehicle crashes, while the presence of horizontal curves along a steep gradient, the presence of a passing lane and presence of road delineation decrease the likelihood of multi-vehicle crashes. Findings of this study have significant implications for road safety along rural mountainous highways, particularly in the context of developing countries.
    Matched MeSH terms: Rain*
  14. Assessment on inflow and infiltration in sewerage systems of Kuantan, Pahang
    Yap HT, Ngien SK
    Water Sci Technol, 2017 Dec;76(11-12):2918-2927.
    PMID: 29210679 DOI: 10.2166/wst.2017.463
    Inflow and infiltration are important aspects of sewerage systems that need to be considered during the design stage and constantly monitored once the sewerage system is in operation. The aim of this research is to analyse the relationship of rainfall as well as inflow infiltration with sewage flow patterns through data collected from fieldwork. Three sewer pipelines were selected at the residential areas of Taman Lepar Hilir Saujana, Bandar Putra and Kota Sas for data collection. Sewage flow data were collected in terms of flowrate, velocity and depth of flow using flowmeters with ultrasonic sensors that utilize the continuous Doppler effect in the sewer pipelines, while rainfall intensity data were collected using rain gauges installed at the study locations. Based on the result, the average infiltration rates of Qpeak and Qave for the locations were 17% and 21%, which exceeded the respective values of 5% and 10% stated in Hammer and Hammer. The flowrate of wastewater in the sewer pipelines was found to be directly proportional to rainfall. These findings indicate that the sewer pipelines in the study areas may have been affected by capacity reduction, whereas the sewerage treatment plants receiving the wastewater influent may have been overloaded.
    Matched MeSH terms: Drainage, Sanitary*; Rain*
  15. Fulltext Asthma and climatic conditions--experience from Kuantan, Malaysia
    Lim TO, Looi HW, Harun K, Marzida
    Med J Malaysia, 1991 Sep;46(3):230-4.
    PMID: 1839917
    Data on number of cases of acute asthma seen at casualty department in 1987 as well as daily metereological data for 1987 were obtained and analysed for relation between climatic factors and acute asthma. Ambient temperature was significantly associated with acute asthma; the lower the temperature, the more the number of cases of asthma were seen. No association however was observed between asthma and the other climatic factors viz, rainfall, humidity, daily change in humidity and daily drop in temperature. We further discuss our finding.
    Matched MeSH terms: Rain
  16. Fulltext Birdsong Denoising Using Wavelets
    Priyadarshani N, Marsland S, Castro I, Punchihewa A
    PLoS One, 2016;11(1):e0146790.
    PMID: 26812391 DOI: 10.1371/journal.pone.0146790
    Automatic recording of birdsong is becoming the preferred way to monitor and quantify bird populations worldwide. Programmable recorders allow recordings to be obtained at all times of day and year for extended periods of time. Consequently, there is a critical need for robust automated birdsong recognition. One prominent obstacle to achieving this is low signal to noise ratio in unattended recordings. Field recordings are often very noisy: birdsong is only one component in a recording, which also includes noise from the environment (such as wind and rain), other animals (including insects), and human-related activities, as well as noise from the recorder itself. We describe a method of denoising using a combination of the wavelet packet decomposition and band-pass or low-pass filtering, and present experiments that demonstrate an order of magnitude improvement in noise reduction over natural noisy bird recordings.
    Matched MeSH terms: Rain
  17. Fulltext Carbon stocks and fluxes in tropical lowland dipterocarp rainforests in Sabah, Malaysian Borneo
    Saner P, Loh YY, Ong RC, Hector A
    PLoS One, 2012;7(1):e29642.
    PMID: 22235319 DOI: 10.1371/journal.pone.0029642
    Deforestation in the tropics is an important source of carbon C release to the atmosphere. To provide a sound scientific base for efforts taken to reduce emissions from deforestation and degradation (REDD+) good estimates of C stocks and fluxes are important. We present components of the C balance for selectively logged lowland tropical dipterocarp rainforest in the Malua Forest Reserve of Sabah, Malaysian Borneo. Total organic C in this area was 167.9 Mg C ha⁻¹±3.8 (SD), including: Total aboveground (TAGC: 55%; 91.9 Mg C ha⁻¹±2.9 SEM) and belowground carbon in trees (TBGC: 10%; 16.5 Mg C ha⁻¹±0.5 SEM), deadwood (8%; 13.2 Mg C ha⁻¹±3.5 SEM) and soil organic matter (SOM: 24%; 39.6 Mg C ha⁻¹±0.9 SEM), understory vegetation (3%; 5.1 Mg C ha⁻¹±1.7 SEM), standing litter (<1%; 0.7 Mg C ha⁻¹±0.1 SEM) and fine root biomass (<1%; 0.9 Mg C ha⁻¹±0.1 SEM). Fluxes included litterfall, a proxy for leaf net primary productivity (4.9 Mg C ha⁻¹ yr⁻¹±0.1 SEM), and soil respiration, a measure for heterotrophic ecosystem respiration (28.6 Mg C ha⁻¹ yr⁻¹±1.2 SEM). The missing estimates necessary to close the C balance are wood net primary productivity and autotrophic respiration.Twenty-two years after logging TAGC stocks were 28% lower compared to unlogged forest (128 Mg C ha⁻¹±13.4 SEM); a combined weighted average mean reduction due to selective logging of -57.8 Mg C ha⁻¹ (with 95% CI -75.5 to -40.2). Based on the findings we conclude that selective logging decreased the dipterocarp stock by 55-66%. Silvicultural treatments may have the potential to accelerate the recovery of dipterocarp C stocks to pre-logging levels.
    Matched MeSH terms: Rain*
  18. Causes of variation between months in the distance traveled daily of gibbons
    Raemaekers J
    Folia Primatol., 1980;34(1-2):46-60.
    PMID: 7439871
    The monthly medians of the distances traveled daily by siamang and lar gibbons are negatively correlated with rainfall and positively correlated with the separate and combined abundance of different food categories. The latter correlations indicate that the apes follow a policy of cutting their losses by reducing travel when food abundance falls.
    Matched MeSH terms: Rain
  19. Characterization and source identification of stormwater runoff in tropical urban catchments
    Chow MF, Yusop Z
    Water Sci Technol, 2014;69(2):244-52.
    PMID: 24473291 DOI: 10.2166/wst.2013.574
    The characteristics of urban stormwater pollution in the tropics are still poorly understood. This issue is crucial to the tropical environment because its rainfall and runoff generation processes are so different from temperate regions. In this regard, a stormwater monitoring program was carried out at three urban catchments (e.g. residential, commercial and industrial) in the southern part of Peninsular Malaysia. A total of 51 storm events were collected at these three catchments. Samples were analyzed for total suspended solids, 5-day biochemical oxygen demand, chemical oxygen demand (COD), oil and grease, nitrate nitrogen, nitrite nitrogen, ammonia nitrogen (NH3-N), soluble reactive phosphorus and total phosphorus. Principal component analysis (PCA) and hierarchical cluster analysis were used to interpret the stormwater quality data for pattern recognition and identification of possible sources. The most likely sources of stormwater pollutants at the residential catchment were from surface soil and leachate of fertilizer from domestic lawns and gardens, whereas the most likely sources for the commercial catchment were from discharges of food waste and washing detergent. In the industrial catchment, the major sources of pollutants were discharges from workshops and factories. The PCA factors further revealed that COD and NH3-N were the major pollutants influencing the runoff quality in all three catchments.
    Matched MeSH terms: Rain
  20. Characterization of rainwater chemical composition after a Southeast Asia haze event: insight of transboundary pollutant transport during the northeast monsoon
    Nadzir MSM, Lin CY, Khan MF, Latif MT, Dominick D, Hamid HHA, et al.
    Environ Sci Pollut Res Int, 2017 Jun;24(18):15278-15290.
    PMID: 28500553 DOI: 10.1007/s11356-017-9131-1
    Open biomass burning in Peninsula Malaysia, Sumatra, and parts of the Indochinese region is a major source of transboundary haze pollution in the Southeast Asia. To study the influence of haze on rainwater chemistry, a short-term investigation was carried out during the occurrence of a severe haze episode from March to April 2014. Rainwater samples were collected after a prolonged drought and analyzed for heavy metals and major ion concentrations using inductively coupled plasma mass spectroscopy (ICP-MS) and ion chromatography (IC), respectively. The chemical composition and morphology of the solid particulates suspended in rainwater were examined using a scanning electron microscope coupled with energy-dispersive X-ray spectroscopy (SEM-EDS). The dataset was further interpreted using enrichment factors (EF), statistical analysis, and a back trajectory (BT) model to find the possible sources of the particulates and pollutants. The results show a drop in rainwater pH from near neutral (pH 6.54) to acidic (
    Matched MeSH terms: Rain/chemistry*
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