Determination of emission factors from a landfill through an inverse methodology: Experimental determination of ambient air concentrations and use of numerical modelling

The application of numeric modelling for determining the impact of landfills needs for reliable emission source data. In this study, a methodology for the characterization of the emission profiles of the different sources present in landfills for emission factors determination, applying an indirect methodology, is presented. Ambient air concentrations of volatile organic compounds (VOCs), hydrogen sulphide (H2S) and ammonia (NH3) were determined in three potentially emission sources in Can Mata landfill (Hostalets de Pierola, Catalonia, Spain): dumping areas, pre-closed zone and leachate reservoir as well as in biogas, for the determination of emission factors. Multi-sorbent bed and Tenax TA tubes were used for a wide range of VOCs sampling, and analysis was conducted through TD-GC/MS. H2S and NH3 were sampled and analysed using Radiello passive samplers. The highest total VOC (TVOC) concentrations were found in dumping areas (0.7-3.5 mg m-3), followed by leachate reservoir (0.3-0.6 mg m-3) and pre-closed area (77-165 μg m-3). On the other hand, the highest H2S and NH3 concentrations were found in leachate reservoir, presenting values of 0.8-1.1 mg m-3 and 1.7-1.8 mg m-3, respectively. With the application of odour thresholds to the concentrations obtained, the most critical compounds regarding odour annoyances were determined. The highest odour units (O.U.) were found in leachate reservoir due to H2S concentrations, whereas VOCs contributed mainly to O.U. in the dumping areas. The obtained ambient air concentrations were used for the indirect determination of the emission factors through numerical modelling using a Eulerian dispersion model. The emission factors obtained for the landfill for TVOC, H2S and NH3 were in the range of 0.44-10.9 g s-1, 0.16-1.02 g s-1 and 0.23-1.82 g s-1, respectively, depending on the emission source. Reliable emission factors are crucial to obtain landfill impact maps, which are essential for the correct management of these facilities.

Air quality impacts of landfill fires: A case study from the Brahmapuram Municipal Solid Waste Treatment Plant in Kochi, India

The occurrence of waste fires in unscientifically managed landfill sites has become a pressing environmental issue in the urban centers of developing economies. In the present work, an investigation was carried out to evaluate the air quality implications of three major fire events that occurred at the Brahmapuram Municipal Solid Waste Treatment Plant (BMSWTP) in Kochi, India. Initially, Landsat-based surface temperature monitoring was conducted to identify the thermal hotspots within the landfill. The emissions of different pollutants during waste fires were quantified and compared between satellite-based ex-situ and field-based in-situ methods. The dispersion patterns of PM2.5 particles released during the fires were visualised using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) particle dispersion model. The Landfill Gas Emissions Model (LandGEM) was employed to quantify the greenhouse gases (GHGs) released during waste storage, which was then compared with the GHGs emissions during waste fires. In-situ emission estimates showed that the combustion of waste at BMSWTP led to the release of 909.3 MT of PM10, 938.8 MT of PM2.5, 5832.9 MT of CO, 43.6 MT of SOx, 284.2 MT of NOx, 138,941.9 MT of CO2, 426.8 MT of CH4, and 2665.1 MT of VOC. However, a noticeable disparity was observed between the in-situ and ex-situ emission estimates, wherein the latter underestimated the actual emissions. Most of the emitted PM2.5 particles propagated oceanward under the influence of prevailing winds, covering the densely populated areas of Kochi municipal corporation. The amount of CH4 and CO2 emitted during the waste fires was on par with the emissions from 159 days of waste storage for CH4 and 51.8 years of waste storage for CO2, with a cumulative global warming potential of 147.9 Gg CO2-e.

Atmospheric microplastic deposition in a coastal city of India: The influence of a landfill source on monsoon winds

Coastal zones experience various wind events that may influence the characteristics, distribution, and dynamics of atmospheric microplastic pollutants. In the present study, we investigated the characteristics of the bulk atmospheric microplastic deposition in Kochi, Kerala, India, during three distinct seasons: Northeast Monsoon (NEM), Summer (SMR), and Southwest monsoon (SWM). Seasonally, the highest microplastic fallout rate was recorded for the NEM (37.29 particles m-2d-1), followed by SMR (15.17 particles m-2 d-1) and the SWM (11.57 particles m-2d-1). The microplastic abundance was not correlated to the amount of rainfall. Further, the wind rose and HYSPLIT trajectory analysis illustrated the arrival of northeast monsoon winds to the city via the region in and around the municipal landfill, which could be a major source of airborne microplastic to the sampling stations, and the forward trajectories from the landfill site extended into the Arabia Sea, providing evidence on the potential atmospheric transport and subsequent deposition of microplastics into the ocean. With respect to the qualitative characteristics, blue-coloured and fibrous microplastics dominated the samples with a considerable number of particles belonging to the size range of 200-500 μm. The practice of drying synthetic clothes under natural sunlight may have substantially contributed to the increased prevalence of airborne microfibers. The higher numbers of polyethylene (PE) and polypropylene (PP) in the bulk microplastic deposition reinforce the concept of low-density polymers being more susceptible to deflation by the wind. Overall, the work signifies the role of monsoon winds in transporting microplastics from an unscientifically managed municipal landfill site and also highlights the importance of reducing the quantity of plastic waste ending up at the landfill to reduce the emission of microplastics proportionately.

Real-time air concentrations and turbulent fluxes of volatile organic compounds (VOCs) over historic closed landfills to assess their potential environmental impact

For the first time, emission/deposition fluxes of volatile organic compounds (VOCs) and H₂S from a historic closed landfill site in Southern Italy were determined by Eddy Covariance (EC) using Proton Transfer Reaction Time-of-Flight Mass Spectrometry (PTR-TOF-MS). This was done in two field campaigns of one week performed in July and October 2016, where fluxes of CO₂ and CH₄ were also measured. Many compounds not previously identified in the biogas were detected by PTR-TOF-MS, but only in July some of them produced positive fluxes exceeding the flux limit of detection. Methanol was the most emitted compound with an average flux of 44.20 ± 4.28 μg m^-2 h^-1, followed by toluene with a mean flux of 18.97 ± 2.47 μg m^-2 h^-1. Toluene fluxes were 10 times higher than those of benzene, fitting rather well with values previously measured in the biogas. VOCs emission fluxes of monoterpenes and highly reactive arenes did not reflect, however, the biogas composition. This, combined with tiny emissions of VOC oxidation products, suggests that landfill emissions underwent some photochemical degradation before being dispersed in the atmospheric boundary layer (ABL). Deposition fluxes of some VOCs emitted from the sea was also observed in July. No relevant VOC fluxes were instead measured in October, suggesting that temperature was the variable controlling most landfill emission. Albeit small, summer landfill emissions from the investigated site can have an impact on the population living nearby, because they contain or still generate compounds that causing nuisance.

Quantification and control of gaseous emissions from solid waste landfill surfaces

Landfilling is the most common option for solid waste disposal worldwide. Landfill sites can emit significant quantities of greenhouse gases (GHGs; e.g., methane, carbon dioxide, and nitrous oxide) and release toxic and odorous compounds (e.g., sulfides). Due to the complex composition and characteristics of landfill surface gas emissions, the quantification and control of landfill emissions are challenging. This review attempts to comprehensively understand landfill emission quantification and control options by primarily focusing on GHGs and odor compounds. Landfill emission quantification was highlighted by combining different emissions monitoring approaches to improve the quality of landfill emission data. Also, landfill emission control requires a specific approach that targets emission compounds or a systematic approach that reduces overall emissions by combining different control methods since the diverse factors dominate the emissions of various compounds and their transformation. This integrated knowledge of emission quantification and control options for GHGs and odor compounds is beneficial for establishing field monitoring campaigns and incorporating mitigation strategies to quantify and control multiple landfill emissions.

Locating and quantifying multiple landfills methane emissions using aircraft data

A mass balance approach to quantify methane (CH4) emission of four co-located landfills by means of airborne measurements and dispersion modelling was proposed and assessed. By flying grids at different heights above the landfills, atmospheric CH4 densities and wind components were measured along the edges and inside the study atmospheric volume, in order to calculate mass flows in the along- and across-wind directions. A steady-state Gaussian dispersion model was applied to build the concentration fields associated to unit emission from each landfill, while the contribution of each one to the total emission was assessed using a General Linear Model approach, minimizing the difference between measured and modeled mass flows. Results showed that wind spatial and temporal variability is the main factor controlling the accuracy of the method, as a good agreement between measured and modeled mass flows was mainly found for flights made in steady wind conditions. CH4 emissions of the entire area ranged from 213.5 ± 33.5 to 317.9 ± 90.4 g s-1 with a mean value of 252.5 ± 54.2 g s-1. Contributions from individual sources varied from 17.5 to 40.1 g m-2 day-1 indicating a substantial heterogeneity of the different landfills, which differed in age and waste composition. The proposed method was validated against tower eddy covariance flux measurements made at one of the landfills, revealing an overall agreement within 20%.

Composition and emission of VOC from biogas produced by illegally managed waste landfills in Giugliano (Campania, Italy) and potential impact on the local population

The composition in Volatile Organic Compounds (VOC) of the biogas produced by seven landfills of Giugliano (Naples, Campania, Italy) was determined and VOC emission rates assessed to verify if these compounds represent a potential threat to the population living nearby. VOC composition in the biogas could not be predicted, as heterogeneous waste was dumped from the late 1980s to the early 2000s and then underwent biological degradation. No data are available on the amount and composition of VOC in the biogas before the landfills closure as no operational biogas collection system was present. In this study, VOC composition was determined by gas chromatography-mass spectrometry (GC-MS), after collecting samples from collection pipes and from soil fractures in cover soil or capping. Individual VOC were quantified and data compared with those collected at two landfills in Latium, when they were still in operation. Relevant differences were observed, mainly due to waste aging, but no specific VOC revealing toxic waste dumping was found, although the concurrent presence of certain compounds suggested that dumping of industrial wastes might have occurred. The average VOC emission was assessed and a dispersion model was run to find out if the emitted plume could affect the health of population. The results suggested that fugitive emissions did not represent a serious danger, since the concentrations simulated at the neighboring cities were below the threshold limits for acute and chronic diseases. However, VOC plume could cause annoyance at night when the steady state conditions of the atmosphere enhance pollutants accumulation in the lower layers. In addition, some of the emitted VOC, such as alkylbenzenes and monoterpenes, can contribute to tropospheric ozone formation.

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed. This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables. The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills. Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.