Comparing estimates of fugitive landfill methane emissions using inverse plume modeling obtained with Surface Emission Monitoring (SEM), Drone Emission Monitoring (DEM), and Downwind Plume Emission Monitoring (DWPEM)

Figures & data

Table 1. Hand-generated configuration of the 18 sources created to test the optimization-based methane emission estimation approach.

Source number	x position (m)	y position (m)	Emission rate Q (g/s)
1	387	785	9.2
2	485	870	7.6
3	210	510	5.8
4	585	801	11.3
5	563	594	8.4
6	308	412	5.9
7	407	383	12.7
8	478	534	4.6
9	450	782	6.7
10	392	305	8.3
11	650	700	8.2
12	315	581	10.9
13	420	200	6.2
14	150	417	8.7
15	422	608	4.5
16	567	303	6.5
17	340	300	4.7
18	487	409	7.8

Figure 1. Source and receptor positions for the hand-generated SEM.

Figure 2. Source and receptor positions for the hand-generated drone emission monitoring (DEM).

Figure 3. Source and receptor positions for the hand-generated downwind plume monitoring (DWPEM). The figure shows the limits of the studied landfill and the model-predicted methane concentrations for the receptors.

Figure 4. Field study SEM measurements performed in the two-days sampling campaign with their corresponding methane concentrations in ppmv. Red circular markers indicate the position of the emission sources predicted using the GA-based method.

Figure 5. Field study DEM measurements performed in day 1 of the sampling campaign with their corresponding methane concentrations in ppmv. Red circular markers indicate the position of the emission sources predicted using the GA-based method.

Table 2. Meteorological parameter values for the field campaign.

	Day 1 (April 10, 2018)	Day 2 (April 11, 2018)
Measurements	SEM + DWPME	SEM + DEM
Sky	Cloudy	Sunny
Temperature (°C)	20.0	20.5
Wind direction	NNE	WSW
Wind speed (m/s)	4.0	0.9
Stability class	C	A

Table 3. Whole-site methane emission predictions for varying number of estimated sources using SEM and DEM for the hand-generated case-study. The estimation error is displayed for each case.

	Number of estimated sources
	17	18	19
SEM-based methane emission [g/s] (error)	141 (2.2%)	145 (5%)	138 (0%)
DEM-based methane emission [g/s] (error)	139 (0.7%)	142 (2.9%)	143 (3.6%)

Figure 6. Predicted source positions using the DEM dataset compared with the predefined source locations in the hand-generated case study. Results obtained using the SEM dataset are also displayed.

Figure 7. Predicted source emission rates using the SEM and the DEM datasets compared with the predefined emission rates in the hand-generated case study.

Table 4. Emission estimates and prediction errors using DEM dataset with variable stability class, wind direction and speed. The reference values are indicated in bold for each case.

	Parameter value and resulting emission rate in the landfill
Stability Class	A	B	C	D	-
Emission rate (g/s)	199.8	142	134.9	105.6
Estimation error	(44.8%)	(2.9%)	(2.2%)	(23.5%)
Wind direction	NNW	N	NNE	NE	ENE
Emission rate (g/s)	131.5	123.4	142	131.4	130.8
Estimation error	(4.7%)	(10.6%)	(2.9%)	(4.8%)	(5.2%)
Wind speed (m/s)	1	2	2.68	3	4
Emission rate (g/s)	87.7	140.2	142	163.7	199.5
Estimation error	(36.4%)	(1.6%)	(2.9%)	(18.6%)	(44.6)

Table 5. Whole site emission predictions using DEM with variable wind speed ranging between 1.18 m/s and 4.18 m/s. Emission estimates are displayed for the minimum, the average and the maximum wind speed values.

	Assumed wind speed (m/s)
	1.18	2.68	4.18
Predicted landfill emission [g/s]	113	149	211

Table 6. SEM and DEM based estimated methane emission sources for the field study.

Parameter	SEM-based results	DEM-based results
Mean (g/s)	17	14
Minimum (g/s)	4.84	6.15
Maximum (g/s)	20.0	20.0
Total Flux (g/s)	350	287
Count/Number of Sources	21	20

Table 7. Total estimated emissions based on DWPEM for the field study. The wind direction for each plume is indicated. Results of the optimization-based method are compared with the results obtained using the method proposed by (Fredenslund et al. 2018).

	Estimated methane flux (g/s)
Plume and wind direction	Optimization-based estimation	Inverse plume modeling (Fredenslund et al. 2018)
Plume 1- (36.7°)	264	201
Plume 2- (38.7°)	214	240
Plume 3- (24.6°)	216	262
Plume 4- (44.1°)	190	176
Plume 5- (47.4°)	255	253
Average value	228	226

Fredenslund, A. M., J. Mønster, P. Kjeldsen, and C. Scheutz. 2018. Development and implementation of a screening method to categorise the greenhouse gas mitigation potential of 91 landfills. Waste Manage.87:915–23.

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