Forthcoming articles

International Journal of Environment and Pollution

International Journal of Environment and Pollution (IJEP)

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International Journal of Environment and Pollution (6 papers in press)

Regular Issues

  • Biological denitrification and dephosphorization of a fixed bed reactor packed with long-term carbon release composite under magnetic field   Order a copy of this article
    by Shuchen Tu, Fengzhu Lv, Zilin Meng, Rui Zhang, Yihe Zhang 
    Abstract: A novel multiple-component carbon source mainly with hemp fibre (HF) and biodegradable polybutylene succinate (PBS) was prepared and filled into two fixed bed bioreactors to remove nitrate nitrogen and phosphorus from simulated groundwater. A 121 days monitoring indicates the denitrification and dephosphorisation of bacteria are influenced by temperature. But a magnetic field can decrease the influence. As the operation temperature was 30-36 oC, the average nitrate nitrogen and total phosphorus (TP) removal degree in reactor 1 (without electromagnetic field) was 91.05% and 71.34%, while nitrite remained at low levels (less than 0.2 mg/L). As a magnetic field was introduced, the average nitrogen and phosphorus removals were improved to 93.18% and 78.68%, respectively. Meanwhile, the average effluent concentration of chemical oxygen demand (COD), decreased from 51.2 mgL-1 to 30.8 mgL-1. The morphology and the biofilm attaching amount measurement indicated more bacteria were attached onto the composite and more composite was consumed correspondingly but inhomogeneously. These data show that a magnetic field could improve the growth of bacteria and their attachment onto the composites. The prepared composite is a long-term carbon-release material and the fabricated fixed bed reactors are high performance reactors for NO3-N removal.
    Keywords: denitrification; biofilm; magnetic field; carbon sources; water treatment.

  • Urban emission inventory optimisation using sensor data, an urban air quality model and inversion techniques   Order a copy of this article
    by David Carruthers, Amy Stidworthy, Dan Clarke, Jo Dicks, Rod Jones, Ian Leslie, Olalekan Popoola, Martin Seaton 
    Abstract: An optimisation scheme has been developed that applies a Bayesian inversion technique to a high resolution (street-level) atmospheric dispersion model to modify pollution emission rates based on sensor data. The scheme minimises a cost function using a non-negative least squares solver. For the required covariance matrices assumptions are made regarding the magnitude of the uncertainties in source emissions and measurements and the correlation in uncertainties between different source emissions and different measurement sites. The scheme has been tested in an initial case study in Cambridge, UK, using monitored data from four reference monitors and twenty AQMesh sensor pods for the period, 30 June 2016 30 September 2016. Hourly NOx concentrations from road sources modelled using ADMS-Urban and observed concentrations were processed using the optimisation scheme and the adjusted emissions were re-modelled. The optimisation scheme reduced average road emissions on average by 6.5% compared to the original estimates, changed the diurnal profile of emissions and improved model accuracy at four reference sites.
    Keywords: inversion; optimisation; emissions; ADMS-Urban; sensors.

  • Independent analysis of time-varying hydrogen cyanide gas exposures on rats using toxic load-based modelling   Order a copy of this article
    by Alexander Slawik, James Silva, Kevin Axelrod, Jeffry Urban, Nathan Platt 
    Abstract: The US Defence Threat Reduction Agency (DTRA) sponsored a two-year set of experiments, conducted in 2012 and 2013, that were designed and executed by the US Armys Edgewood Chemical and Biological Center (ECBC) and the Naval Medical Research Unit Dayton (NAMRU-D) to explore time-varying inhalation exposures of hydrogen cyanide gas on rats. Our analysis, detailed in a separate paper, finds that a single set of fitted parameters for the toxic load model (i.e., the toxic load exponent n, probit slope m, and median lethal exposure TL50) cannot accurately model the single exposure experimental data across the experiments full range of time from 2.3 to 30 minutes but can on the longer timescales of 10 to 30 minutes. However, none of the toxic load models that we considered fit the experimental data for the novel, time-varying exposures well, with the Average Concentration and Griffiths-Megson models providing the least inaccurate casualty predictions.
    Keywords: casualty assessment; consequence assessment; Haber’s law; toxic load modelling.

  • Rising environmental awareness in Central Asia: an empirical study from Nursultan, Kazakhstan   Order a copy of this article
    by Ferhat Karaca, John Machell, Ali Turkyilmaz, Dina Kaskina, Kamshat Tussupova 
    Abstract: This paper is the first comprehensive study to assess public environmental awareness on drinking water, household waste management practices, urban air quality, and other environmental issues in Kazakhstan. It aims to assess the findings of an investigation into public environmental awareness within the local society in Nursultan (formerly known as Astana), the capital city of Kazakhstan, and defines major environmental problems, as perceived by the public, using a survey-based research methodology. A series of crossover assessments were carried out to evaluate the level of public awareness on the major environmental issues. Almost a quarter of the respondents stated that they have already begun waste separation, even though there is no penalty system if the waste is not separately collected or recycled. Almost all the respondents agreed that hazardous substances should be treated separately from other waste types. It was also found that the public perception of tap water quality is strongly related to personal experiences, which correspondingly influences the use of tap water as drinking water. As a result of the perceived water quality, bottled water is the preferred alternative drinking water option among the householders. As for peoples perception regarding the major sources of air pollution in their cities, half of respondents, 50%, recognised motor vehicles as the main cause of pollution. Industrial sources, waste disposal, and power plants were considered as other contributors with 35%, 11%, and 11%, respectively.
    Keywords: environmental awareness; waste management; household waste; drinking water; water quality; urban air quality; Kazakhstan.

  • A review on the use of air dispersion models for odour assessment   Order a copy of this article
    by Maurizio Onofrio, Roberta Spataro, Serena Botta 
    Abstract: Only recently, unpleasant odours have become an important environmental issue and a specific legislation is being developed and implemented. The assessment of odour impact involves several different aspects (large number of odorants, human sensitivity, different perception thresholds, etc.) and it is dealt with by the application of different techniques and methods. In this paper, a review about the reliability of air dispersion models applied to odour impact assessment determined by different types of source is presented, based on the analysis of 69 case studies published over the last 10 years. The Gaussian models were the most used techniques (67% of case studies) often accompanied with results validation with experimental data. The analysis of the case studies and related validation processes highlighted the reliability of dispersion models, if some critical issues, such as presence of particular climate conditions, duration of averaging times and position of important receptors, are known and correctly managed.
    Keywords: odour impact; air dispersion model; odour measurement; Gaussian model; impact assessment; CALPUFF; dynamic olfactometry; field inspection; electronic nose; validation of air dispersion model.

Special Issue on: Dioxins, Sources and Effects, Formation and Abatement

  • GC-HRMS analysis for POPs and new POPs with GC-Tof/MS techniques
    by Takumi Takasuga 
    Abstract: .
    Keywords: .