Characterization of ambient volatile organic compounds at a landfill site in Guangzhou, South China

Zou, Songbing; Lee, Shuncheng; Chan, Cheuk-Yin; Ho, Kin Fai; Wang, Xinming; Чан, Лю; Zhang, Z.X

doi:10.1016/s0045-6535(03)00004-3

Cited by 149 publications

(106 citation statements)

References 15 publications

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“…In recent decades, advanced statistical and calculation methods have been developed to classify large data clusters into meaningful range, extract useful information, identify relationships among corresponding data, and evaluate the results. Although many methods such as projection pursuit technique and neural networks have been developed, multivariate statistical techniques have enabled better and easier assessment for interpretation of complicated data sets in water quality studies [5]. Similarly, another study stated that multivariate statistical techniques are useful for reducing large data obtained from physicochemical water quality studies [6].…”

Section: Application Of Multivariate Statistical Methodsmentioning

confidence: 99%

“…The locations of sampling points were as described in Table 1. In total, 196 samples were collected and analysed for BOD 5 , COD, ammonia-N, kjeldahl-N, oil-grease, fecal and total coliform, TSS, TDS, nitrite, nitrate, total and ortho phosphate, surfactants, chloride, F ig. 1.…”

Section: Study Area and Samplingmentioning

confidence: 99%

“…Among the applied methods for linkage and distance combination, the best results for variable relation were obtained using Ward's method and Euclidian distance. According to analysis, parameters were roughly classifi ed into two major groups: Cluster 1 ranged from Cl to ammonia-N and Cluster 2 from Zn to BOD 5 …”

Section: Hierarchical Cluster Analysismentioning

confidence: 99%

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Application of Multivariate Statistical Methods for Water Quality Assessment of Karasu-Sarmisakli Creeks and Kizilirmak River in Kayseri, Turkey

Özdemir¹

2016

Pol. J. Environ. Stud.

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Monitoring water quality of rivers has particular ecological, economic, and environmental importance for a region. However, long-term monitoring of a river network requires a large amount of analysis with high work load and cost. In this study, multivariate analysis was performed to decrease the number of parameters and sampling points for monitoring water quality in the Kızılırmak River and its southern ranches of Karasu and Sarmısaklı creeks. On the study area, water quality parameters were collected from seven sampling points for 2004-07 and 2010-14. Multivariate statistical analysis was performed by hierarchical cluster analysis and principal component analysis for the evaluation of parameter variations and dataset interpretation. The dataset was divided into periods A and B to evaluate the effects of seasonal changes on sampling points and parameters.

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Section: Application Of Multivariate Statistical Methodsmentioning

confidence: 99%

Section: Study Area and Samplingmentioning

confidence: 99%

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Application of Multivariate Statistical Methods for Water Quality Assessment of Karasu-Sarmisakli Creeks and Kizilirmak River in Kayseri, Turkey

Özdemir¹

2016

Pol. J. Environ. Stud.

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“…Zou et al [20], Kim et al [28], Ying et al [29], Gallego et al [30]). This can be attributed to management conditions at the composting site and waste type, as composting sites are likely to have lower BTEX rates (Durmusoglu et al [3], Zou et al [20] ) in Italy for a 0.5-6 km radius around a landfill during winter. Again, different management practices at the landfill site may play a role as well as the presence of other pollutant sources within the sampling area (Davoli et al [14]).…”

Section: Resultsmentioning

confidence: 99%

The Influence of Btex Landfill Gas Emissions: A Case Study of Residents in Roodepoort, Gauteng, South Africa

Roffe¹,

Moolla²,

Grab³

2017

WIT Transactions on Ecology and the Environment

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Landfills produce pollutants that negatively impact humans and the environment. In developing countries such as South Africa, landfilling is the most common form of solid waste management. People living in close proximity to landfills are particularly at risk to harmful pollutants such as volatile organic compounds (VOCs). Although VOCs only constitute ~1% of landfill gas (LFG) emissions, they are of concern as the risk associated with these pollutants is high. Of particular concern within the VOCs, is the BTEX group (viz. benzene, toluene, ethyl benzene and xylenes). These pollutants are wind dispersed to surrounding residential areas, exposing residents to hazardous gases. BTEX LFG emissions were quantified and spatially mapped using Radiello Passive Samplers (analysed by a GC with built-in FID) in residential areas around a landfill in Roodepoort, South Africa. The BTEX levels ranged from 8.83 to 39.62 µg.m -3 . The effect of the slow south to south-westerly wind speeds of ~2.44 m.s -1 , the valley terrain, and the location of the landfill resulted in a BTEX 'hotspot' north and east of the landfill site. Combined with the passive sampling strategy, a study on residents perceptions revealed that residents were concerned with this 'hotspot' area and linked it to the landfill site. They were furthermore concerned with the landfill's associated pollution and odours. It was concluded that residents living closer to the landfill were at higher risk to BTEX, especially during the winter season. Future work should include sampling at the landfill site, specifically over different time frames to include seasonality, and possibly using different sampling methods.

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“…The trace components in landfill gas are mainly produced during microbial decomposition of organic materials deposited in the landfill or by vaporization of low boiling point liquids contained in the waste [4]. Non-methane organic compounds (NMOCs) constitute a numerous group of trace compounds, reaching up to 1% of gas volume [5,6]. Volatile organic compounds (VOCs) comprise important group of the NMOCs in landfill gas.…”

Section: Introductionmentioning

confidence: 99%

Microbial removal of selected volatile organic compounds from the model landfill gas

Zdeb

Lebiocka

2016

Ecological Chemistry and Engineering S

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Landfills of municipal waste are an important source of BTEXs in the atmosphere. Biodegrability of these compounds implies that biological methods, such as oxidation in landfill covers, may be an effective way to mitigate emission of these gases. The aim of the study was to evaluate the efficiency of BTEXs removal from landfill gas by biofiltration method and to analyze the influence of methane on BTEXs oxidation rate. The experiments were carried out at laboratory scale continuous flow system (microcosms) and in batch tests. A mixture of municipal waste compost and expanded clay pellets (1:1 of volume) was used as a filter bed material. The model landfill gas (50% vol. of CH4 and 50% vol. of CO2) purged through the microcosms was enriched with toluene (series 1) and all the BTEXs (series 2). The results of 7-month continuous flow experiment showed that removal efficiency of BTEXs in experimental columns ranged from 91 to 100% when the individual trace gases loading rates in model gas were in the range of 0.1-0.2 g m -2 d -1 . The rate of toluene removal, which followed the first order kinetics, depended on the presence of methane in treated gas. About 2-fold higher values of rate constant and 2.5-fold higher values of initial toluene removal rates were observed when no methane was present in the headspaces inside the vials used in the batch tests.

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Characterization of ambient volatile organic compounds at a landfill site in Guangzhou, South China

Cited by 149 publications

References 15 publications

Application of Multivariate Statistical Methods for Water Quality Assessment of Karasu-Sarmisakli Creeks and Kizilirmak River in Kayseri, Turkey

Application of Multivariate Statistical Methods for Water Quality Assessment of Karasu-Sarmisakli Creeks and Kizilirmak River in Kayseri, Turkey

The Influence of Btex Landfill Gas Emissions: A Case Study of Residents in Roodepoort, Gauteng, South Africa

Microbial removal of selected volatile organic compounds from the model landfill gas

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