Use of Models and Facility-Level Data in Greenhouse Gas Inventories

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Use of Models and Facility-Level Data in Greenhouse Gas Inventories them are rapidly degradable waste combine with the appropriate moisture content and temperature under tropical condition in this region. Methane emission rates and gas analysis Methane emission rates from the landfill surface in this study were measured using the chamber technique which consists of trapping the gas as it leaves the soil surface, either by allowing the gas to build up in a closed enclosure (closed or static chamber technique) (Perera et al., 1999). Static chambers are the most frequently used technique for the measurement of gas fluxes from soils. The chamber technique is low cost, and simple to operate, but extremely labor and time intensive (Bogner et al., 1997). The chambers used in this study were constructed with φ 0.40 m PVC pipe (covering an area of 0.126 m 2 ), 0.25 m. in height and with a PVC cap at the top of the chamber. To protect against air intrusion, the chambers were sealed to the ground by placing wet soil around the outside. Methane samples were collected in 10-mL vacuum tubes from a chamber after 1, 2, 3, and 4 minutes using 60-mL plastic syringes fitted with plastic valves. The samples were analyzed using a gas chromatograph equipped with a flame ionization detector (GC- FID). The methane flux was determined from concentration data (C in ppmv) plotted versus elapsed time (t in minutes). The data generally fit a linear relationship, in which case dC / dt is the slope of the fitted line. The methane flux, F (g/m 2 /d), was then calculated as follows in Equation 1 (Rolston, 1986; Hegde et al., 2003): V dC F = ( ) (1) A dt Where V is chamber volume and A is the area covered by the chamber. The slope of the line, dC / dt , was determined by the differential result between CH 4 concentration and elapsed time. In order to conduct the flux chamber measurements, numerous samples were collected across the landfill or dumpsite surfaces on a regular grid pattern at 30 – 40m intervals. Precipitation was absent and barometric pressure and ambient wind speed, factors which known to affect emissions, were relatively constant during investigations. Geospatial distribution Due to the large areal extent of landfill surfaces and the heterogeneous nature of landfill gas fluxes, a large number of chamber samples must be collected (Mosher et al., 1999). However, proper interpolation methodology must be applied for geospatial analysis of field data. This technique offers the potential of calculating whole site emission estimates from point measurements, which could lead to improving the estimation of landfill methane emission (Spokas et al., 2003). Geospatial distributions of the methane emissions in this study were estimated by Kriging method. Kriging refers to the process of using the spatial dependency to predict the value of a property at unknown locations from the relationship observed at the sampling location. The weight for the Kriging analysis was decided by semivariogram (Spokas et al., 2003). The Surfer software (Golden Software, Inc.) was used to analyze the geospatial distribution in this study. The Kriging model was applied to map the results, and the volumetric value of the contour map was estimated by volume and area integration algorithms in Surfer. Table 1 Characteristics of study sites Site Landfill Open Year Site Age from 2006 (yrs) Area (m 2 ) Disposal method Average tipping (tonnes per day) Pattaya (MD1) 2002 4 53,618 Deep landfill 240 Mabtapud (MD2) 2001 5 29,280 Deep landfill 58 Cha-Am (MS1) 2000 6 47,680 Shallow landfill 26 Laemchabang (MD3) 1999 7 71,200 Deep landfill 152 Hua-Hin (MD4) 1996 10 44,160 Deep landfill 46 Samut Prakan (UD1) 1999 7 25,600 Deep dumpsite 80 Nakhon Pathom (UD2) 1997 9 48,781 Deep dumpsite 180 Nonthaburi (UD3) 1982 24 67,367 Deep dumpsite 800 Rayong (US1) 2001 5 35,200 Shallow dumpsite 69 IPCC Expert Meeting Report 56 TFI
Use of Models and Facility-Level Data in Greenhouse Gas Inventories Methane emission inventory In order to compare methane emissions between field investigations and model estimation, the IPCC Waste Model was used in this study. In the model, CH 4 emissions from landfills for a single year are estimated using the following equation; ⎡ ⎤ CH 4 Emissions = ⎢∑ CH 4 generated x, T − RT ⎥ × (1 − OX T ) (2) ⎣ x ⎦ Where CH 4 Emissions = CH 4 emitted in year T, Gg, T = inventory year, x = waste category or type/material, R T = recovered CH 4 in year T, Gg, and OX T = oxidation factor in year T, (fraction). The OX reflects the amount of CH 4 from solid waste disposal site (SWDS) that is oxidized in the soil or other material covering the waste. The amount CH 4 generated from decomposable material in year T (=CH 4 generated T) is estimated using the first order decay (FOD) of the mass of decomposable organic carbon (= DDOCm, Gg) in each waste category or type/material as follows; CH 4 generatedT = DDOCm decompT × F ×16 /12 (3) Where DDOCm decomp T = DDOCm decomposed in year T, Gg, F = fraction of CH 4 by volume in generated landfill gas (fraction) and 16/12 = molecular weight ratio between methane and carbon (ratio). DDOCm decomp DDOCma T T −k T − × ( − e ) −k ( DDOCma e ) = DDOCma 1 1 (4) = DDOCmd + 1 (5) T T − × Where DDOCma T = DDOCm accumulated in the solid waste disposal site at the end of year T, Gg, DDOCma T-1 = DDOCm accumulated in the SWDS at the end of year T-1, Gg, DDOCmd T = DDOCm deposited into the SWDS in year T, Gg, k = reaction constant (k = ln(2)/t 1/2), yr -1 , and t 1/2 = half-life time, yr. DDOCm = W × DOC × DOC f × MCF (6) Where W = mass of waste deposited, Gg, DOC = degradable organic carbon in the year of deposition, (fraction, Gg- C/Gg-waste), DOC f = fraction of DOC that can decompose, (fraction), and MCF = CH 4 correction factor for aerobic decomposition in the year of deposition, (fraction). Parameter evaluation The emission results that were obtained from field investigations have been modeled with the FOD model (IPCC Waste Model). To find the optimal set of gas generation parameters, the approach by Oonk et al. (1994) was used. This entails the minimization of the difference between the calculated gas generation rates and the actual rates to determine the optimal set of gas generation parameters using error function for statistical analysis. The error equation used is shown as Equation 7. E = n ∑ i= 1 2 ( Qc − Qob) (7) Where E is error function, Qc is calculated generation, Qob is observed generation and n = number of waste disposal sites. By following this approach, MCF, the main parameter, was first optimized. The MCF is the fraction of waste which degrades anaerobically in landfills. The value of this parameter depends on the landfill operation, shape or the specific surface of landfills, the existence and the air permeability of the top cover, the water content or the level of leachate in landfills. In the IPCC Guidelines, default value for the MCF is classified in four categories for simplification. In this study, MCF was evaluated by using error function analysis with IPCC Waste Model and information of study sites including waste composition, waste in place history, and operation practice. In order to optimize MCF, other parameters were fixed with IPCC default values for tropical climate region except oxidation factor (OX). The default half-life values for food waste, paper, wood and textiles were 2, 10, 20 and 10 years, respectively. The default delay time was 6 months. The IPCC Expert Meeting Report 57 TFI
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Use of Models and Facility-Level Data in Greenhouse Gas Inventories

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