AMTAtmospheric Measurement TechniquesAMTAtmos. Meas. Tech.1867-8548Copernicus GmbHGöttingen, Germany10.5194/amt-8-2853-2015Methane emission estimates using chamber and tracer release experiments
for a municipal waste water treatment plantYver KwokC. E.camille.yver@lsce.ipsl.frhttps://orcid.org/0000-0002-2181-2863MüllerD.CaldowC.https://orcid.org/0000-0003-3516-8084LebègueB.MønsterJ. G.RellaC. W.ScheutzC.SchmidtM.RamonetM.WarnekeT.BroquetG.CiaisP.Laboratoire des Sciences du Climat et l'Environnement (LSCE/IPSL),
CNRS-CEA-UVSQ, Centre d'Etudes Orme des Merisiers, Gif sur Yvette, FranceInstitute of Environmental Physics, University of Bremen,
Otto-Hahn-Allee 1, 28359 Bremen, GermanyCentre for Atmospheric Chemistry, University of Wollongong,
Wollongong, NSW, 2522, AustraliaDepartment of Environmental Engineering, Technical University of Denmark,
Bygningstorvet – Building 115, 2800 Lyngby, DenmarkPicarro Inc., 3105 Patrick Henry Drive, Santa Clara, CA, USAInstitut für Umweltphysik, University of Heidelberg, Heidelberg, GermanyC. E. Yver Kwok (camille.yver@lsce.ipsl.fr)17July201587285328679December201419March201519June201524June2015This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://amt.copernicus.org/articles/8/2853/2015/amt-8-2853-2015.htmlThe full text article is available as a PDF file from https://amt.copernicus.org/articles/8/2853/2015/amt-8-2853-2015.pdf
This study presents two methods for estimating methane emissions from
a waste water treatment plant (WWTP) along with results from a measurement
campaign at a WWTP in Valence, France. These methods, chamber measurements
and tracer release, rely on Fourier transform infrared spectroscopy
and cavity ring-down spectroscopy instruments. We show that the tracer
release method is suitable for quantifying facility- and some process-scale
emissions, while the chamber measurements provide insight into individual
process emissions. Uncertainties for the two methods are described and
discussed. Applying the methods to CH4 emissions of the WWTP, we confirm
that the open basins are not a major source of CH4 on the WWTP (about
10 % of the total emissions), but that the pretreatment and sludge
treatment are the main emitters. Overall, the waste water treatment plant is representative of an average French WWTP.
Introduction
Human activities cause greenhouse gas (GHG) emissions at a large scale,
changing the atmospheric chemical composition by measurable and consequential
amounts. Anthropogenic GHG emissions such as methane (CH4) now
represent a significant fraction of total greenhouse gas emissions into the
atmosphere. To better understand the anthropogenic sources of GHGs, with the
goal of ultimately reducing these emissions, it is essential to accurately
quantify the emissions at different spatial scales, from the country to the
process scale, and to monitor the possible temporal variabilities. We can sort
estimation methods into two groups depending on the type of measurement used:
the top-down approach based on atmospheric measurements of GHGs at different
scales (global, regional, local) and the bottom-up approach that uses
activity data, emission factors and flux modeling to calculate emissions.
Both approaches can be applied from the global to the process scale depending
on the representativity of the measurements.
Methane is a potent anthropogenic greenhouse gas with a global warming
potential 28 times as strong as that of CO2 on a 100-year
time horizon . Primary sources of anthropogenic methane
emissions are landfills, waste water treatment plants (WWTPs), rice paddies,
ruminants and manure management, oil and gas production and transport
activities. Combining the two approaches by using top-down measurements at
all scales to validate or adjust benchmark bottom-up calculations and
emission factors can help not only improve inventories by a more robust
quantification but also provide valuable information for how to prioritize
emission reduction activities.
(a and b) Aerial view (Google Earth) of the
WWTP. The blue lines show the driving paths during the tracer release
experiment and
the red rectangles show the location of the plumes.
(c) Schematic view of the waste water treatment plant.
(d) Aerial view of the WWTP with methane concentrations shown as red
rectangles measured on 18 September with a northeast wind. The signals showed are above 1850 ppb.
The highest signal near the incinerator is 10 ppm.
In France, methane emissions from waste management (waste water treatment and
landfills) accounted for about 19 % of the total methane emissions
in 2011 following the national inventory from CITEPA ().
Landfills are the largest emitter with 17 %, but waste water
treatment plants still represent a non-negligible part (2 %).
However, these values are estimated with 100 % uncertainty due to
the difficulty in accurately estimating the biological demand of oxygen (BOD),
quantity of CH4 emitted by kg of BOD, fraction of treated incoming
waste water and anoxic/oxic conditions, which are the parameters used by
CITEPA to derive CH4 emissions from WWTP . Several
studies have been conducted in different countries to provide more accurate
estimates of the emissions for WWTPs. and
present estimations based on process modeling,
but some studies such as ,
and calculate
emissions using CH4 measurements with mass budget. Finally, a recent
study by used the tracer release method as described
in this paper to estimate CH4 and N2O emissions from a WWTP.
In these papers, emissions vary from 0.011 to 1.3 kgyr-1 per
population equivalent depending on the WWTP design (e.g., depending on the use
of aerobic or anaerobic processes, presence of a sludge digester) and the
estimation method as the tracer release allows the capturing of leakage emissions
that could be omitted by the other methods. For municipal WWTPs using
activated sludge (aerobic) treatment, emissions still vary from 0.039 to
0.309 kgyr-1 per population equivalent. This range of estimate
shows that the WWTP CH4 emissions depend on the design and the size
of the WWTP. In France, according to the BDERU for 2008 (database for urban
waste water,
http://www.statistiques.developpement-durable.gouv.fr/lessentiel/ar/306/1168/assainissement-traitement-collectif-eaux-usees.html),
there are about 18 600 WWTPs, half of which treat water for a fewer-than-500
population equivalent. However, the 6 % of WWTP with more than
10 000 population equivalent treat 80 % of the waste water. In this
study, we focused on one of these medium-sized WWTPs that employs activated
sludge treatment. We used two methods – chamber measurements and tracer
release method with acetylene – that have been rarely used on WWTPs to
calculate GHG emissions at the process and the plant scale. We aimed not only to estimate
the total emissions of the site but also to investigate individual
processes and evaluate the missing elements between these two measurement
scales. Another goal was to estimate the uncertainties for each method to
provide a more robust emission estimation and be able to compare our results
with other studies or inventories. An intensive measurement campaign was thus
conducted at one of the WWTP of Valence, France, from 17 to
21 September 2012.
First, we present the details of the site under study, followed by the
different emission estimation methods, measurement techniques and instruments
employed during the experimental campaign. Finally, we present and discuss
the results obtained for CH4 from the process scale up to the site
scale. All the emission estimates hereafter refer directly to CH4,
i.e., the notation kg of CH4day-1 or kg of
CH4yr-1 per population equivalent is replaced by
kg day-1 or kg yr-1 per population equivalent.
Description of the site
The WWTP is located in the southwest of the city of Valence, around
50 m east from the Rhône river, which flows in a north–south
direction (see Fig. ). Valence is located in the southeastern part
of France, 500 km southeast of Paris, 100 km south of Lyon
and 70 km southwest of Grenoble. The station is managed by Veolia
France and treats the water for 150 000 inhabitant equivalents, which
represents about 2800 m3h-1 with an exiting BOD of
35 kgm-3 (http://www.valenceagglo.fr/stations-depuration).
The water follows a several step treatment (see Fig. ). After being
filtered for solids, the water is filtered for sand particles (down to
200 microns in diameter) by sedimentation, and oil is removed by injection of
air bubbles. The water is then distributed to three aeration basins
(12 000 m3 each) via a dispatcher basin. In the aeration basins,
air is periodically injected to help aerobic bacteria to digest the organic
matter. The water and the sludge are sent to a degassing/dispatcher basin and
then separated by sedimentation inside three clarification basins
(6000 m3 each). The sludge from the different steps is collected
and dried before being incinerated. The cleaned water from the overspill of
the clarification basins is discharged into the Rhône river. During the
campaign, one of the aeration basins was being cleaned, so only two were in
use.
We anticipated the potential for methane release during all steps of the
process. In the aeration basins, periods of aeration with aerobic reaction
alternate with rests when anaerobic reactions can occur. Methane formed
during these resting phases is then transported to the surface when aeration
restarts and provokes a mixing of water. In the degassing basin, water is
mixed and dissolved methane can be released. In the clarification basin, as
there is a slow mixing, some degassing could still be expected, with bacteria
from the active sludge still producing methane. Finally, the sludge may still
contain methane that could be emitted during centrifugation, storage and
incineration. In addition, methane dissolved in the incoming water from the
city will be released at the plant, starting from the first exposure to the
atmosphere, and certainly during the aeration process. Figure d
shows a qualitative image of the methane measured with the mobile instrument
described in Sect. around the site on 18 September with
a southwest wind. We indeed see higher CH4 concentrations on the site
than outside with peaks for the degassing basin, the water pretreatment and
the sludge incinerator.
Emission estimation methodsChamber measurements on the basins
Depending on the basin areas under investigation, two different modes of
chamber measurements were employed: (a) accumulation closed-chamber
measurements and (b) flow-through open-chamber
measurements. The former mode was employed on the clarification basin
(18 September) and on the aeration basin (19 September) outside of the
aerated area of the basin, which had rather calm surfaces, and the latter on
the aerated part of the aeration basin, where air is injected in the basin,
resulting in a large air flux and turbulent surface (see
Figs. and ).
Accumulation (closed-chamber) measurements
The chamber was closed against ambient air and the mass flux F is
calculated from the linear increase of the measured gas mole fraction in the
chamber with time (see Fig. a):
F=ΔCΔtpVMAbasinRTA,
where ΔCΔt is the fitted linear increase of the gas
mole fraction in the chamber with time (mol mol-1s-1), p is
the pressure in the floating chamber (Pa), T the temperature (K), R the
universal gas constant (8.314 m3PaK-1mol-1), V
represents the volume of the chamber (m3), A the water surface area
enclosed by the chamber (m2), Abasin the area of the basin
(m2) and M the molar mass of methane (g mol-1). Fluxes were
converted to the unit g day-1. The chamber had a small vent hole
(ca. 10 mm in diameter). When the chamber was first placed on the
water, it was vented to the atmosphere to allow the chamber pressure equalize
to atmospheric pressure. After about 20 s, the vent was closed.
Ambient pressure was recorded at the weather station.
Schematic of the two basins that were measured with the
floating chamber. (a) Clarification basin: the yellow arrow shows the
direction in which the arm rotates. The red dots and symbols refer to the location
of the chamber during runs 1, 2, 3 (symbol i), 4, 5, 7 (symbol ii) and 6, 8, 9 (symbol iii).
(b) Aeration basin: the red rectangle denotes the aeration area, the arrow the water flow.
As for the errors, five main sources of uncertainty were considered. First,
the error associated with the linear fit was taken into account and
calculated as the coefficient of variation (CV). Secondly, the uncertainty
associated with the volume of the chamber was considered. This uncertainty
arises both from the initial measurement of the total volume of the chamber
and the uncertainty associated with the water level in the chamber.
Because of the conic shape of the chamber, the uncertainty of the water level
also affected the uncertainty of the water surface area enclosed by the
chamber. Here it was assumed that the water level varied by 1 cm.
The uncertainties associated with the pressure and temperature sensors were
also considered in terms of the confidence interval provided by the
manufacturer. The overall uncertainty was calculated for each run using
propagation of uncertainties .
Schematic showing different modes of chamber deployment. (a)
Conventional floating chamber used on a calm surface (accumulation closed-chamber measurements).
The schematic concentration vs. time points out how the gas accumulates in the chamber over time
(in case of a positive net flux from water to air). This increase is linearly approximated and from the slope,
the flux is calculated. (b) Flow-through open chamber: the excess air escapes and the
concentration measured in the chamber relates directly to the concentration in the emitted air.
Thus, here we refer to the concentration reached in one time interval.
Flow-through (open-chamber) measurements
The chamber was modified for flow-through measurements with five small holes
(ca. 10 mm in diameter) present in the top of the chamber to allow
excess injected air to escape. During aeration times, the air in the chamber
was replaced within a few minutes. Hence, the gas concentration in the
chamber represented the concentration in the aeration air emitted from the
basin once several mixing times in the chamber volume had occurred.
Therefore, the mass flux of the emitted gas could be calculated by the amount
of injected air, the gas concentration in the injected air and its
integration over time (see Fig. b):
F=∑t(Cchamber-Cbackground)MVmdVAerationdtAaeration,
where Cchamber is the gas mole fraction measured in the chamber
(mol mol-1), Cbackground is the background gas mole
fraction in the injected air,
dVaerationdt is the volume of air
injected inside the basin per time (m3h-1), M is the molar
mass of CH4 (g mol-1), Vm is the molar
volume of ideal gases (m3mol-1) and Aaeration is
the surface area of the aeration area in the aeration basin. The volume of
air injected in the aeration basins was monitored with an Endress + Hauser
AT70 flowmeter. The uncertainty given by the manufacturers is 2 %.
The air injected into the aeration basin was ambient air. Note that
multiplication with Aaeration contains the assumption that air is
injected homogeneously in the basin. As the air is released from
approximately evenly spaced diffusors at the bottom of the basin, we think
that this assumption is warranted. The uncertainty was then calculated with
error propagation, taking into account both the uncertainty of the injected
air volume (2 %), the uncertainty of the background CH4
concentration and the error of the CH4 measurement.
Instruments used during the campaign and their specifications.
InstrumentIntegration time used in the studySpeciesUncertainty for species of interestFTIR LSCE1 min/30 minCO2, CH4, N2O, CO and δ13C<0.1% (CH4)FTIR Bremen5 minCO2, CH4, N2O, CO and δ13C<0.1% (CH4)CRDS1 s/1 minCH4,CO2, C2H2, H2O<0.1% (CH4), <5% (C2H2)Weather station1 minWind speed, wind direction, temperature, relative humidity and atmospheric pressure3 %, 3∘, 0.3 ∘C, 3, 0.05 %Tracer release method
The tracer release method consists of releasing a tracer gas (here
C2H2) at a known rate from a location which is collocated with the
unknown emission of a trace gas to be determined, here CH4. This
method has often been used in previous studies to determine CH4 from
landfills and more recently WWTPs .
Concentrations of the tracer as well as the gas of interest are measured
using a mobile instrument downwind in the co-propagating plumes. The ratio of
the area of the two plume signals is proportional to the emission rate. Thus,
knowing the emission rate of the released gas and the concentrations of both
gases, we could calculate the emission rate of the gases of interest:
FCH4=FC2H2ACH4AC2H2MCH4MC2H2,
where FCH4 are the emissions of CH4 (kg h-1),
FC2H2 are the known emissions of C2H2
(kg h-1), ACH4AC2H2 is the ratio of
the areas under the signals of CH4 and C2H2 once the
background subtracted and MCH4MC2H2 is the
ratio of the molar masses of CH4 and C2H2. For stationary
experiments, Eq. () was modified such that the slope of the
CH4 vs. C2H2 linear regression was used to calculate the
unknown flux instead of the area under the signals. Indeed, in this case, as
there was no crossing of the plumes, there is no area under the signals to
integrate but instead a mixed signal varying with the wind direction.
In this method, the uncertainties arise then from the concentration
measurements, the tracer flux and the collocation of the plumes. CH4
and C2H2 concentration errors are less than 0.1 and 5 %,
respectively, for 1 s average. Once the gas cylinder is installed and
regulated, the flow of the tracer gas is steady and well known, and this error
depends on the precision, the reproducibility (given by the manufacturer) and
the reading error. The precision is defined by the maximum value that the
flowmeter can read and is here below 2 % on 1507 Lh-1. The reproducibility on the read flow is
0.5 % and the reading error is estimated as a quarter the size of
the float, i.e., 1 mm. Thus the maximum total uncertainty on the
C2H2 flow is 0.5 kgday-1 with the precision being the
major factor.
The main uncertainties come from the imperfect collocation of the plumes and
from the analysis of the plumes, especially the background determination for
CH4 and the calculation of the areas, as the signal/noise ratio is
not very high in this study. Indeed, even while driving several hundreds of
meters out of the plumes, in the “WWTP-free” air, the background for
CH4 was still highly variable from one crossing to the other. To
address this issue, the background for each CH4 plume was calculated
using a linear regression between the first and last point of the peak
instead of removing an average background value for the whole event. Once
this background was subtracted, the ratio of the areas was calculated.
C2H2 background values were almost 0, so no background was
subtracted. We used 1 s averaged data. Indeed, the more data points
are used, the better the resolution of the signal is, allowing for a
finer area estimation, which is the observation we are looking to extract. The
autocorrelation of the errors on the 1 s data is taken into account in the
global error which is the aggregation of the different errors. To estimate
the non-collocation error, we ran one experiment with the C2H2
cylinder at a different location; however, due to the small amplitudes of the
signal as well as the CH4 high noise, these data could not be used
quantitatively. To reduce this error as much as possible, we drove far
enough away as was convenient with the existing roads (500 m to
1 km away) to consider the two signals collocated. The goal is also
to position the cylinder such as it is neither downwind nor upwind of the
CH4 source to minimize dispersion discrepancies. We also discuss this
assumption qualitatively in Sect. .
Instruments and setup
During this 1-week campaign, two Fourier transform infrared (FTIR) analyzers measuring CO2,
CH4, N2O, CO and δ13C in CO2 (Ecotech and
University of Wollogong, Australia), one cavity ring-down spectroscopy (CRDS) instrument (custom prototype,
Picarro Inc., Santa Clara) measuring CH4, CO2 and H2O
or C2H2, CH4 and H2O and a weather station were
installed to measure GHG concentrations and/or estimate CH4 emissions
(see Fig. and Table ). Here, we focused only on
CH4 and C2H2 concentrations even though the instruments
measured more species. One of the FTIR analyzers was used to measure samples
from the basins with the chamber technique described above and the second
mostly sampled air at the same location as the weather station but performed
some measurements above the basins as well. These ambient air measurement
gave a general picture of the conditions during the campaign and the
concentration variability. The CRDS instrument, used for the tracer release
method, was installed in a car along with a real-time GPS device and was thus
mobile except for a one-night-long comparison with the FTIR. The instrumental
techniques and the setup of the instruments during the campaign are detailed
hereafter.
FTIR analyzers
An FTIR analyzer records a spectrum over a broad IR range
(1800–5000 cm-1), thereby offering the possibility of measuring
a large number of species simultaneously. Spectra are stored and can be
analyzed at a later date with a different method to get data with a higher
accuracy or study new species. In the FTIR, the infrared signal passes first
through a Michelson interferometer, then this modulated beam traverses the
sample cell. The resulting time-modulated signal is then converted into an
infrared spectrum through Fourier transform. The FTIR analyzer operated by
the LSCE is a commercially available Ecotech instrument. The instrument
operated by the Bremen University was built at the University of Wollongong,
Australia. Both instruments are functionally identical. A detailed
description is found in and
. Briefly, each of the two instruments consists of
a commercially available FTIR interferometer (IRcube, Bruker Optics, Germany)
with a 1 cm-1 resolution coupled with a 3.5 L multi-pass
cell with a 24 m optical path length (PA-24, InfraredAnalysis,
Anaheim, USA). The cell and the interferometer are put together on an optical
bench inside a temperature-controlled chamber. An in situ PT100 platinum
resistance thermometer and a pressure sensor (HPM-760s, Teledyne
Hastings, USA) are installed on the multi-pass cell. Nitrogen (grade 4.5) is
used to purge the interferometer housing as well as the transfer optics
between the cell and the interferometer. A drying system composed of
a 24 in counter-flow Nafion dryer (Permapure, Toms River, NJ, USA) followed
by a chemical dryer (Mg(ClO4)2) was located upstream from the
cell.
During the campaign, both instruments were installed in small shelters
without air conditioning. The first one, operated by LSCE, was installed to
sample ambient air above the whole station for the majority of the time.
During the last day, air was sampled above different basins. For this
instrument, the pressure of the cell is controlled using a mass flow sensor
mounted at the outlet of the cell, and the flow is controlled by another mass
flow controller installed upstream from the drying system. Four calibration
gases and a control gas were used regularly during the 5 days of the
campaign for calibration (once a day, 45 min for each calibration
gas) and quality control (every 3–4 h). During these 5 days, the
temperature inside the shelter sometimes exceeded 30 ∘C. In
order to keep the performances unchanged, the FTIR and the cell were kept at
32 ∘C instead of the typical 30 ∘C. However,
the temperature variations in the shelter were leading to cell temperature
fluctuations, and therefore the reproducibility error was higher than in the
laboratory (0.01 vs. 0.005 %, respectively). The main sampling inlet
was installed on top of a building located between the clarification and the
aeration basins at about 7 ma.g.l. Ambient air measurements took
place from 17 September 17:00 to 20 September 2012 14:00 and then from
20 September 18:30 to 21 September 2012 05:00. During the afternoon of
20 September, measurements above the clarification, the aeration and the
degassing basins were taken with the LSCE FTIR analyzer sampling inlet
50 cm above the basins to compare with the ambient sampling.
The second FTIR was operated by the Bremen University and was used to analyze
samples from a floating chamber operated on the clarification and the
aeration basins. Due to the complexity of moving the shelter or deploying
longer lines, no other places, such as the pretreatment area, could be measured
with the chamber. The chamber consisted of a large upside-down flower pot
surrounded by a tractor tire inner tube, which served as a floating device.
The edge of the flower pot was filled with water, so that the chamber was
sealed with respect to the water surface. The edge extended 3 cm into
the water. A 12 V computer fan inside the chamber ensured mixing of
the air in the chamber. The volume of the chamber was 0.10 m3, and
the surface area of the water in the chamber was 0.28 m2. The
chamber was connected to the FTIR in situ analyzer using PFA sampling lines
and air from the chamber was circulated in a closed loop through the analyzer
with a flow rate of 0.06 m3h-1. The data were calibrated using
a suite of secondary standards measured once during the campaign with methane
concentrations ranging from 1.8 to 40 ppm.
On the clarification basin, chamber placements aimed to capture spatial flux
variations and covered three approximate positions as indicated in
Fig. a. The clarification basin possessed a rotating
arm, or mixer, that was used to gently stir the basin and encourage the
drainage of benthic sludge towards and out of a central hole at the bottom of
the basin. Whilst the mixer was on, the floating chamber was tethered to the
rotating arm and moved very slowly with the arm. Consequently, whilst
sampling, the chambers moved about one-half to one full rotation around the
basin. The movement-induced turbulence was assumed to have a negligible
effect on the flux, as the arm rotated at a slow rate, covering one rotation
of 360∘ in approximately 30 min. Fluxes were calculated
from the accumulation of methane in the chamber over time (closed chamber),
as described above. On the aeration basin, two floating chamber measurements
were conducted outside the aeration area. Focus was laid on measurements in
the area where the aeration took place. Due to the high air flux in the
aeration area, closed-chamber measurements were not suitable. Instead, we
modified the setup and operated the chamber as open chamber over night
(19–20 September), as detailed previously.
CRDS analyzer
For the mobile tracer release measurement, we used an
acetylene/methane/carbon dioxide/water vapor analyzer based on cavity ring-down spectroscopy, an optical technology in which direct measurement of
infrared absorption loss in a sample cell is used to quantify the
mole fraction of the gas. This instrument (S/N DFADS2006, Picarro, Inc.,
Santa Clara, CA) is a custom analyzer based upon a standard
C2H2/CH4/H2O model (G2203, Picarro, Inc., Santa Clara, CA) to
which a high precision CO2 measurement was added . The
inherent stability of the CRDS instrument allows it, when properly
calibrated to traceable reference standards, to deliver accurate measurements
that need very infrequent calibration relative to other CO2 and
CH4 instrumentation. The overall measurement interval is just below
1 s (i.e., one to two measurements registered during 1 s).
There are two modes of operation for this analyzer: a C2H2/CH4/H2O
mode and a CO2/CH4/H2O mode. The spectroscopy of CO2,
CH4 and H2O is identical to the algorithms that are used in
several standard models from the same manufacturer (e.g., models G1301,
G2301, G2401); the performance of these instruments for atmospheric
measurements of CO2, CH4 and H2O has been described
in detail elsewhere . The basic
performance reported in these papers should be highly representative of the
performance of this analyzer. For the C2H2/CH4 mode, the
performances are described in details in .
A series of laboratory tests was performed in order to establish the basic
performance of the analyzer, consisting of continuous measurements on
prepared gas mixtures. The uncertainty calculated from these tests is
summarized in Table . The CH4 measurements were calibrated
in the field using the same calibration gases as the LSCE FTIR. The
C2H2 measurement was not calibrated directly with a standard gas but
using another instrument. For our purpose, the instrument was installed in
the back of a car and was powered by the car battery. It was connected to
a GPS mounted on the car roof and to internet via a 3G router. This allowed
us to visualize in real time the location and intensity of the concentrations we
were measuring and to ensure we are totally crossing the emission plumes. The
air inlet is fixed on the GPS and its length is about 1 m long.
The scope of this campaign was to test the tracer release method to estimate
the whole site emissions using mobile measurements. Three releases were
performed in that manner. However, when the wind conditions were favorable,
one stationary experiment, focusing on a single element of the site, was also
performed. The typical transects for the mobile measurements as well as the
location of the stationary experiment are indicated on Fig. . Mobile
measurements occurred on 17 and 18 September while fixed measurements with
the inlet next to the LSCE FTIR inlet were performed during the night of
19–20 September. During the first three releases, a 0.05 m3
cylinder of C2H2 was situated next to the degassing basin. The flow
is controlled with a glass tube flowmeter (Sho-Rate from Brooks) with
a precision better than 5 % and a reproducibility of 0.5 %.
During the first release episode, the wind was coming from the south. Using
the nearby bridge above the Rhône (about 500 m away), we
transected the plumes about 10 times. The plumes were located on the bridge
and we drove before and after for at least the same distance as the length of
the bridge to ensure that we were back on background levels. The flow on the
flowmeter was fixed at 40 mm which translates to
10.3 kgday-1. Later that day, a stationary experiment was
performed to measure the emissions from the degassing basin with the car
parked about 65 m away from it and the flowmeter was adjusted to
a flow of 10.6 kgday-1. The C2H2 gas cylinder was
situated on the eastern edge of the degassing basin, about 7 m east
of the center of the 5 m radius basin. On 19 September, the wind was
stronger and coming from the north. The instruments were driven along the
roads south of the station about 400 m away to cross the plumes. As
for the previous day, we ensured that the plumes were fully crossed. The flow
on the flowmeter was adjusted to 105 mm to compensate for the
stronger dispersion which translates to 27.8 kgday-1. Finally,
a last experiment with the C2H2 cylinder close to the clarification
basin to the station was conducted.
Weather station
A weather station (WXT520, Vaisala) was installed next to the FTIR and radon
analyzer inlets. Wind speed, wind direction, temperature, relative humidity
and atmospheric pressure were measured every second and averaged every
minute.
Results
In this section, we present first the weather conditions and the
concentration measurements that allowed us to get a general picture of the
site and to estimate our instruments comparability. Then, we show the results
from the two methods to estimate CH4 emissions.
Continuous ambient air measurements
The CH4 concentrations from the LSCE FTIR analyzer, the wind speed,
the wind direction and the temperature measured during the whole campaign
(except the sampling above the basins) are shown in Fig. . Using the
wind direction, we plotted the wind rose for the whole campaign. It can be
seen from the wind rose and the time series that the wind varied between two
major directions during the campaign: south-southwest (SSW) and northeast.
During the first day, the wind was variable but came mainly from the SSW
direction. On 17 September, the wind direction was the same and steadier. On
19 and 20 September, the wind direction was again more variable with
northeast being the main direction. Temperatures followed a typical daily
pattern and varied between 10 and 24 ∘C.
Upper panel: CH4 concentrations from the LSCE FTIR analyzer at Valence and
from the suburban station of Gif-sur-Yvette, wind speed, wind direction and temperature during the campaign.
Lower panel: wind roses of the wind speed (m s-1) and CH4 concentration (ppb) during the campaign.
CH4 concentrations varied between 1900 and 3000 ppb. The gaps in the data
correspond to calibration periods and sampling above the basins. The highest
concentrations were observed on the first and last days matching stable air mass
(almost no wind speed and quick changes in wind directions). We compared these data
to a suburban site, Gif-sur-Yvette (about 50 km southwest of Paris),
plotted in grey in the upper panel. We see that the concentrations measured there
did not present peaks like measured at the WWTP. This supports the hypothesis of very
local emissions from the plant elevating the measured concentrations up to 1000 ppb
above what is observed in suburban area sites that are not located on a local source spot.
On the concentration wind rose, we observed no preferential direction of higher concentrations.
Note that for the direction with few data and low wind speed, we observed high
concentrations that can be expected from a slower dispersion.
Instrument comparison
During the last night (20 to 21 September), the CRDS and the FTIR analyzers
inlet lines were placed next to each other to sample the same air. The
comparison of the two is shown in Fig. . Contrary to the FTIR
analyzer, which was calibrated regularly during the entire campaign, the CRDS
analyzer was calibrated only once before the in situ measurements. However,
a good agreement was observed between the two instruments with a mean
difference of 2.4 ± 3.9 ppb (SD). The WMO recommendation for
laboratory intercomparison is <2ppb in background air .
We can then reasonably expect that if we had calibrated the CRDS instrument
more often, we would have reached the recommended goal even for polluted air masses.
Indeed, more frequent calibrations would have helped to compensate the
temperature and atmospheric pressure influences on the measurements. However,
the best solution would be to have the instruments in insulated shelters.
Moreover, in the case of the tracer release, no calibration is needed as the
instrument is linear in the range of measured concentrations and we use
differences to the background to infer the fluxes.
Fluxes measured during chamber measurements on the clarification basin.
a The fluxes were calculated by a linear fit because diffusive flux could be
assumed.b The observed concentration increase was not linear. The numbers are based
on a linear fit of the steepest increase over a 10 min period. The fluxes calculated represent an upper limit.
Comparison of CH4 concentrations from the LSCE FTIR and CRDS analyzers during the night of 20 September.
Floating chamber experiments conducted on the clarification basin when the mixer was off (a–d) and on (e–h), respectively.
Process-scale measurements and fluxesClarification basin
During the floating chamber deployment (accumulation mode), the CH4
concentration increased in the chamber over time. A total of eight chamber
runs were made on the clarification basin. Where possible (see discussion
below), the increase was approximated by linear least-square fitting and the
fluxes were calculated. Only four out of eight floating chamber measurements on the
clarification basin exhibited an approximately linear increase (chamber runs
2 (from minute 7 on), 3, 4, 7; see Fig. b–d and f). The emissions calculated from these measurements averaged
3.8 mg min-1 (for the individual values see Table ). The
standard deviation, calculated to assess the spread of the individual
measurements, was 2.6 mg min-1. It is reasonable that upscaling to the
whole basin introduced uncertainty when not all locations on the basin were
covered by our measurements. The uncertainty in volume and area contributed
to the squared total error by 52 and 48 %, respectively, for all four
diffusive flux measurements. The uncertainties associated with CV, pressure
and temperature were negligible. Based on our four measurements, we consider
the obtained average of 3.8 mg min-1 or 5.4 g day-1 to give the order
of magnitude of the diffusive exchange flux, which represents the lower limit
of the total emissions from the clarification basin. For the other four
measurements (see Fig. a, e, g and h), the increase
cannot be linearly approximated. Due to the very sudden increase of the
methane concentration in the chamber, we think that erratic methane emissions
caused this nonlinearity, i.e., ebullition. Since such events might occur
more frequently close to the rotating arm and the number of measurements is
too small for estimating the frequency of such events, it is difficult to
estimate the basin methane flux generated by erratic events.
However, we can state that the highest average flux for these measurements
over a 10 min period was 169 mg min-1 (chamber run 5,
Fig. e).
Measurements in the aeration area of the basin. Upper panel: methane concentration
vs. time. Lower panel: respective volume of injected air during the same time period.
Overall it can be stated that the fluxes of methane were higher when the
mixer was on and the arm rotated. The rotating arm extended down through the
water column and caused increased turbulence at the water–air interface,
throughout the water column and within the methane-rich sediments. The
increased turbulence combined with resultant release of methane from the
sediments could very likely explain the elevated flux and the high
variability of the fluxes whilst the mixer was on. Runs 1 and 5 both show
a high CH4 flux that differs remarkably from the other chamber runs.
These runs were the first measurements conducted after the mixer was turned
off (run 1) and on (run 5). The switching of the mixer on and off may have
momentarily increased ebullition, resulting in the nonlinear and rapid
increase of the concentration in the chamber (see Fig. a and e). Repeated measurements at different locations in the basin and under
different conditions (mixer on/off) could further reveal the actual pattern
of the fluxes from the clarification basin.
Considering the lower limit (diffusive flux) of the observed fluxes, we can
state that the emissions from the clarification basin due to diffusive
emissions are about 5.4 ± 3.0 gday-1. In addition to the
diffusive emissions, we observed erratic methane emissions, most likely due
to bubbles, which would explain the very sudden increase to very high methane
concentrations. Within the short time of measurements on the basin (1 day),
it was not possible to do a systematic study of the methane emissions due to
these erratic events. Therefore, here we can only provide an approximate
estimate for erratic fluxes from the basin. We choose this approximate
estimate in a way that it expresses the maximum erratic flux that we can
consider possible according to our measurements. For this, we took the
highest of the four erratic fluxes we measured and assumed that this flux,
measured over 10 min, occurred for 24 h over the entire area of the
basin. In that case, the emissions would sum up to 243 g day-1.
Aeration basin
The fluxes from outside of the aeration area and their uncertainties were
derived in the same way as for the diffusive emissions from the clarification
basin. We calculated a mean flux of 36 ± 2 gday-1
(38 ± 2 and 34 ± 2 gday-1). This is more than 6
times higher than the diffusive flux measured on the clarification basin. We
have no measurement for non-linear fluxes on the aeration basin, therefore,
the value given here (36 gday-1) is a conservative estimate
including the diffusive flux only and would represent the lower limit of the
total flux (diffusive + erratic) from this area. The fluxes are very different where the aeration takes
place. There, the floating chamber was
operated in flow-through mode over night. Figure shows the
CH4 mixing ratios in the chamber (upper panel) and the amount of
injected air (lower panel). It can be seen that when the aeration starts,
the methane concentration rises up to a maximum and already decreases before
the aeration stops. We think that during the phases when no air and thus no
oxygen is injected, there is a buildup of methane in the basin. Once the
aeration starts, the methane is emitted from the basin with the aeration air.
The night measurements cover approximately 13 h and are therefore
believed to offer a reasonably good temporal coverage for upscaling. We
calculated the CH4 emissions with Eq. (), with
a background concentration of 1973 ppb, which is the average ambient
CH4 measured with the LSCE FTIR during the night from 19 to
20 September. Accordingly, 553 ± 17 gday-1 was emitted from
the aeration basin (with the uncertainty of the background CH4
concentration, taken as the largest deviation from the mean, equal to
2.5 %).
Methane maxima reached during the night chamber measurement vs.
time without aeration. Blue are measurements; red is the linear fit.
It can further be seen from Fig. that the methane
concentration maxima are lower during the late night than in the evening. In
fact, an overall decrease of the maxima can be observed, along with shorter
periods of non-aeration. Figure indicates a linear
correlation between the length of the non-aeration period and the methane
maximum that is observed during the subsequent chamber measurement
(correlation coefficient R=0.86). This supports our hypothesis that methane
production occurs during non-aeration times, which is, in turn, responsible
for the high methane emitted in the subsequent aeration phase.
CH4 concentrations measured by the LSCE FTIR analyzer over the different basins.
Degassing basin
It was not possible to measure the small degassing basin that feeds the
clarification basins using the floating chamber method due to the obstructed
access to this basin. However, measurements above the clarification, aeration
and degassing basins were performed with the LSCE FTIR analyzer sampling
inlet 50 cm above the basins (see Fig. ). For the
aeration and the clarification basins, the concentrations at the time of
measurement were close to the concentrations measured for the whole station.
For the degassing basin, elevated concentrations of CH4 are measured
up to 4300 ppb.The mobile CRDS CH4/C2H2 instrument was also
used to quantify the emissions from this source. On 18 September, with winds
originating from the SSW, driving both immediately upwind and downwind of
this basin (within 10 m) and the nearby clarification basin, a clear
and distinct plume from this basin was identified. No significant emissions
were observed from any of the clarification basins consistent with the
floating chamber measurements. The measurement vehicle was parked at
a distance about 9 times greater than the separation of the C2H2 and
CH4 sources. We expect the plumes should be reasonably mixed at this
distance, especially given the strong afternoon turbulent mixing of the
atmosphere when these measurements were made (see Fig. ). Under
these well-mixed conditions, the static plume correlation method can be
employed to estimate the emissions of CH4. About half an hour of
CH4 and C2H2 measurements were made at this location, with
the wind wafting the plumes back and forth across the measurement location.
The winds came reliably from the SSW during this time, meaning that the
measurements were not polluted by methane from the aeration basins or
incineration building. The time series of C2H2 and CH4 are
shown in Fig. b. The signals are clearly correlated. We plotted
methane as function of C2H2 and fitted the resulting distribution
with a linear function. The fit has a slope of
0.244 ppbCH4ppb-1C2H2, with an
R2 of 0.62. Given the release rate of 10.6 kgday-1 for
C2H2, we found that the methane emissions from the degassing basin
were 1.13 ± 0.5 kgday-1. Given the wind direction, this
emission number could include emissions from one or more of the clarification
basins. However, whilst the floating chamber measurements showed that maximum
emissions from the clarification basins were comparable (0.8 kgday-1), on
average they were about one-quarter of this amount. As this figure includes
erratic fluxes, for which a conservative upper limit was given, the true
fluxes are likely to be much lower. For example, if only diffusive emissions
were included, then the flux would be smaller than 0.025 kg d-1 per
basin. This compares to 1.135 kg d-1 from the degassing basin.
Conclusively, the emissions from the clarification basin contribute only very
little to the emissions from aquatic surfaces in the WWTP.
Plant scale
Figure a and c present measurements from CH4 and
C2H2 during the two successful tracer release episodes using dynamic
measurements. We see that the acetylene baseline is very close to 0
and stable, while the CH4 baseline varies between the releases and
during them. The elevation of the signal above the background is on average
15–20 ppb for CH4 and between 2 and 16 ppb for
C2H2 which is 5 to 20 times lower than for the static measurements
reflecting the distance to the sources compared to the static measurements.
The ratio for each numbered peak was calculated and the results and their
uncertainties are summed up in Table . We observe a large
variability (approximately 35 %) between the plumes but with
a consistent average between the two mobile release episodes. The average
value over the 2 days is 34.2 ± 11.6 kgday-1 or
83 ± 28 gyr-1 per inhabitant. The errors here represent
the SD of the measurements and therefore also include the emission
variability.
CH4 emissions (kg day-1) for the whole station using the tracer release method.
North wind South wind TransectCH4 emissions (kg day-1)TransectCH4 emissions119.1±0.5128.7±0.5221.0±0.5249.6±0.5348.1±0.5330.0±0.5442.1±0.5425.0±0.5547.3±0.5518.6±0.5635.9±0.5647.0±0.5746.3±0.5731.2±0.5822.9±0.58Average35.3±12.5Average32.9±11.35DiscussionUncertainties
In this paper, we used two methods to estimate emissions with associated
uncertainties. These uncertainties and the parameters they arise from are
summarized in Table 4. Depending on the methods, the uncertainties range
from 5 to 60 %. However, in most cases there are several parameters
that can be determined more accurately to reduce these uncertainties. In
Table 4 the parameters in bold are the parameters with the higher
uncertainty.
In the case of the closed chamber, the water area enclosed by the chamber and
the air volume in the chamber are the parameters associated with the
strongest uncertainties. They eventually depend on the uncertainty of the
water level. Consequently, a more accurate measurement of the water level in
the chamber and a minimization of its variation should be aimed at if
lowering of the total uncertainty is desired . The error associated with the
water surface area can be fully eliminated by choosing a box over a conic
chamber. With a box, the variation of the water level would not affect the
surface area across which the exchange takes place.
Concentrations of CH4 and C2H2 during the three
tracer release episodes. Episode (a): estimation of the whole plant
emission on 18 September with a south wind; the C2H2 cylinder is located in A
(see Fig. 1). Episode (b): estimation of the degassing basin
emissions on 18 September with a south wind; the C2H2 cylinder is located in
A. Episode (c): estimation of the whole plant emissions on
19 September with a north wind; the C2H2 cylinder is located in A. The numbers
indicate the signals (peaks) that are used to calculate the CH4 emissions.
For the open-chamber measurements, the uncertainty comes mostly from the
injected air flow measurement and is related to the WWTP equipment (in this
case the measurement uncertainty is 2 %).
For the tracer release method, the largest uncertainties come from the
collocation assumption of the signals and the baseline estimates. These
uncertainties can be reduced by lengthening the period of “clean” air
measurement between each plume crossing and by ensuring that the signals are
correlated. Moreover, controlled release exercises as done by
can help quantify the non-collocation error.
In our study, when the acetylene cylinder was located near the degassing
basin, the two signals were slightly shifted in time (not shown) depending
on the direction we were driving. This shows that this location was not
optimal for sampling the methane emissions from the station when still close to
it (about 500 m). Judging by the horizontal displacement of the
plumes with respect to each other, and the direction of the wind, there was
another methane source west of the degassing basin. When the cylinder was
moved to the clarification basin, we observed an opposite horizontal
displacement, which indicates that the cylinder was now located west to the
axis of the methane plume propagating in the direction of the wind. It seems
then that the optimal location would have been near the LSCE FTIR sampling
lines. This means a displacement of about 50 m, which translates into
an underestimation of 10–15 % on the flux
. This would translate into an average flux of
about 38.9 kgday-1, which lies within our uncertainty estimate
(11.6 kgday-1).
Summary of the uncertainties resulting from the different methods
(in percent). The parameters with the higher uncertainty are in bold.
Closed chamberOpen chamberTracer releaseUncertainties6–60315Parametersmixing ratio, chamber surface area and volume, pressure, temperature, linear fitmixing ratio, air flowmixing ratios, acetylene flux, correlation, baseline estimates
Summary of the results from the process to the site scale.
The given uncertainties were determined in different ways. Refer to the main
text for details.
In summary, there is potential to reduce the uncertainty of each method,
which should be considered when aiming for more robust WWTP emission
estimates. Moreover, longer measurement campaigns over different times of the
year would also allow us to catch the variability of the emissions of the site.
Finally, if aiming for a general estimates, several WWTPs have to be
investigated.
First insights into the Valence WWTP methane emissions
The results from the chamber and the tracer release measurements are
summarized in Table . If we add the maximum contribution from
the different basins, the emissions are approximately 3.1 kgday-1,
i.e., 8 % of the total emissions observed from the facility using the
tracer dilution method. We confirm then that the main source of emissions
from the plant is not these basins but is located elsewhere, as shown in
Fig. d.
In other studies presented in , the emissions
from municipal waste water treatment plants using activated sludge treatment,
such as the Valence plant, varied from 39 to 306 gyr-1 per
inhabitant. The higher limit was found for a plant using a sludge digester
producing biogas. This unit was found to emit three-quarters of the total
emissions of the plant, leaving approximately 77 gyr-1 per
inhabitant emitted by the other processes. The Valence plant estimate agrees
with this last value (83 gyr-1 per inhabitant).
We can also compare this estimate with inventories estimates. The European
Database for Global Atmospheric Research (EDGAR,
, which provides gridded maps, and
the CITEPA, which is responsible for the French inventory, use the IPCC
methodology to estimate CH4 emission factors from WWTPs (see Eq. ).
EF=BOD×365.Bo×∑x(WSx.MCFx),
where Bo is the maximum CH4 production capacity, WSx is the percentage of a
certain process used in the WWTP and MCFx is the conversion rate of this
process. According to the hypothesis, the conversion rate for a WWTP like Valence (aerobic
treatment) should be at the maximum 0.1 with a maximum of 0.4 if not well
managed (IPCC chapter 6 table 6.3,
http://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/5_Volume5/V5_6_Ch6_Wastewater.pdf).
The Bo is usually estimated to be 0.6 kgCH4 kg-1BOD. CITEPA estimates
for France an average emission factor of 74 g yr-1 per inhabitant, which
is very close to the Valence estimate. Using the data from the WWTP, we can
calculate the conversion rate and compare it to the awaited value. Here, we
find a conversion rate of 0.07, which is in the expected range. From these
first measurements, it seems then that the Valence WWTP is an average French
WWTP in terms of CH4 emissions.
Conclusions
We measured CH4 at one of the waste water treatment plants in the
city of Valence, France. Two instruments – FTIR and CRDS – combined
with different methods – floating chamber and tracer release – were
used. They allowed us to span several scales from the individual process to the
site.
The duration of the campaign, 4 days only, was too short to accurately
quantify the emissions and sample the site variability. However, we have
shown that these methods are suitable to evaluate emissions at these
different scales and that they complement each other. The estimated
uncertainty for any of the methods is under 60 % and could in most
cases be reduced by more experiments (e.g., controlled release for the tracer
release method) or by a more precise measurement of the experiment apparatus
(e.g., the area of the chamber in contact with the water). From a qualitative
point of view, the emissions from the waste water plant are representative of
an average French WWTP. The estimates on three structures from the plant, the
aeration, clarification and degassing basins, show that even though these are the
largest open structures on site, they are not the main emitters of methane on
the plant. Concentration measurements seem to indicate that the incinerator
building and the pretreatment could be the main sources. Finally, these
estimates are in the same range of values as found in the literature.
This study demonstrates the use of new techniques, FTIR and CRDS analyzers,
to estimate small-scale emissions and help improve emission factors for
bottom-up inventories. Longer periods of measurements are, however, necessary
to be able to sample statistically significant numbers of events and get more
accurate emission estimates.
Acknowledgements
We thank Veolia Eau and especially Julien Malandain, head of the waste water
treatment network from Drôme-Ardèche, and all the staff including Sandy
Chabanel, Cédric Comte, Yvan Blache and Nicolas Drut in the stations of
Valence and Romans-sur-Isere for their technical help, great
involvement and interest in the measurement campaign. We also thank the city
of Valence for supporting this project. Thank you to Benoit Wastine and
Cyrille Vuillemin from LSCE for their help in organizing the campaign. This
campaign was funded through the BridGES project (supported by the Versailles
Saint-Quentin-en-Yvelines University, the French Alternative Energies and
Atomic Energy Commission (CEA), the French National Center for Scientific
Research (CNRS) and Thales Alenia Space and Veolia Water).
Edited by: D. Feist
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