Sewer systems are an important part of the urban water cycle, because they protect public health and natural aquatic environments from contamination. However, adapting our sewer systems to future challenges requires a better understanding of important transport and transformation processes, such as emission of greenhouse gases or unwanted infiltration of clean groundwater. In this short communication, we propose that monitoring of gases with mass spectrometric methods can deliver a better insight into biochemical transformation and exchange processes than what is currently possible with conventional wastewater analytics. The results from three case studies provide insight into the dynamics of GHG, such as CH 4 and CO 2, and use Helium as a tracer to assess both groundwater infiltration and sewer airflow patterns. In the future, this can be used to design novel experiments, e.g. by simultaneously analyzing inert and active gas species, or actively injecting tracer gases into the ground- and wastewater. Future work should investigate better filtration or indirect sampling methods to sample gas from sewage, such as specially-tailored flux chambers. For network-wide analyses, boundary conditions regarding sewer ventilation, as well as sources and sinks of gases need to be better understood. Keywords: noble gases, sewer, portable mass spectrometer, tracer system, wastewater pollution, infiltration, sewer gas exchange, sewer transport and transformation ∗Corresponding Author. Email address: joerg.rieckermann@eawag.ch (J¨ org Rieckermann) Preprint submitted to Elsevier July 28, 2023 1. Introduction 1 Sewers are important because they protect public health and natural aquatic environ- 2 ments from contamination by safely conveying polluted wastewater to treatment plants. 3 Although sewers are expected to last about 75 to 150 years, it is often much less in reality 4 as current maintenance is insufficient given reduced public expenditure. The resulting sewer 5 deterioration causes problems such as sewer collapse, blockages from infamous “fatbergs”, 6 sulfide corrosion, odor problems, and unwanted intrusion of clean ground- and stormwater, 7 so-called “infiltration and inflow” (Ellis et al., 2010; Staufer et al., 2012; Vollertsen et al., 8 2008). 9 With rapid urbanization and climate change, these problems will become worse. Hence 10 there is an urgent need to adapt the sewer systems that were designed and built by previous 11 generations, to a future with more diverse needs than just hydraulic capacity. As an exam- 12 ple, the integrated assessment of sewers and wastewater treatment plants is no longer only 13 based on flows and pollutant loads, but already takes into account Greenhouse Gas (GHG) 14 emissions and the potential to recover energy and other resources from the wastewater sys- 15 tem (Figueroa et al., 2021; Yadav et al., 2021; Saagi et al., 2022; Di Capua et al., 2022). 16 This requires a more detailed understanding of transport and transformation processes of 17 the compounds in the sewers than before. 18 Transport and transformation processes in sewers are usually highly dynamic, espe- 19 cially during wet weather, and pollutant concentrations often change within a few minutes 20 (Huisman et al., 2004; Rieckermann et al., 2005). Unfortunately, conventional sewer mea- 21 surements of water levels and velocities only provide limited insights on transformation pro- 22 cesses. Therefore, tracer systems, which we define as the combination of tracer substance 23 and monitoring system, are increasingly used to study in-sewer processes. For example, nat- 24 ural tracers such as sulfate (SO 4), chemical oxygen demand (COD), the artificial sweetener 25 acesulfame, caffeine, and stable isotopes of water were used to separate the hydrographs of 26 combined sewage into groundwater (stormwater) and foul sewage (Heiderscheidt et al., 2022; 27 Houhou et al., 2010; Kracht et al., 2008; Zhao et al., 2020). In a similar fashion, gaseous 28 2 tracers such as sulfur hexafluoride (SF 6), carbon monoxide (CO) or oxygen (O 2) were uti- 29 lized to study the horizontal gas transport and ventilation in sewers (Huisman et al., 2004; 30 Madsen et al., 2006; Parker and Ryan, 2001). However, most of the current tracer systems 31 rely on grab sampling followed by a labor-intensive and time-consuming lab-based analysis. 32 Moreover, tracer systems which can be used to observe in-sewer processes with the required 33 temporal resolution of a few minutes are largely lacking. 34 35 In this short communication, we present a new set of tracer systems to study sewer 36 transport and transformation processes with a portable mass spectrometer. We used it to 37 perform the very first continuous and simultaneous high-resolution on-site measurements 38 of noble gases and greenhouse gases in sewers and demonstrate the potential in three case 39 studies: i) online monitoring of biochemical gases to assess dynamics and GHG emissions, ii) 40 using noble gases to monitor groundwater-sewer interactions and iii) monitor sewer airflow 41 patterns. In addition, we critically discuss opportunities to use portable gas monitoring to 42 better understand in-sewer processes, identify current limitations and suggest future research 43 to overcome them. 44 2. Materials and Methods 45 2.1. Online measurements of gases in sewers with a portable mass spectrometer 46 We used a portable mass spectrometer (miniRUEDI, Gasometrix Switzerland; Brennwald 47 et al. (2016)) to quantify the partial pressures of the gas tracers: helium (He), argon (Ar), 48 krypton (Kr), carbon dioxide (CO 2), methane (CH 4), in the sewer headspace. The 6-port 49 inlet of miniRUEDI is capable of continuously sampling up to six gas sources alternately. 50 In the following case studies, the port selector switched between the sewer atmosphere 51 and standard gases. The signals of the gases in the sewer headspace were calibrated by 52 comparing peak heights with the standards and then converted to partial pressures and 53 volumetric percentages (ppm). For He, Ar, and Kr, atmospheric air was used as a standard 54 for the calibration, whereas for CO 2and CH 4a standard gas mixture of 1% CO 2and 1% 55 CH4in N 2was used (Brennwald et al., 2016; M¨ achler et al., 2012). 56 3 In this study, the gases were sampled from the headspace of the sewer system with PVC 57 tubes ( ϕ6 mm or 8 mm, Festo) and peristaltic pumps (PD 5001, Heidolph). The gases from 58 the headspace were pumped to the miniRUEDI, which was located at the ground level. The 59 purging time of the sampling systems depends on the length of the tubes, ranging from 1 60 to 2 min in this study. The overall temporal resolution for the analysis of one sample (from 61 one single port) was around 5 to 8 minutes including the purging time before switching the 62 port. In comparison to grab sampling, even with automatic samplers, this makes it possible 63 to better capture the dynamics of the gas tracers and associated processes. 64 wastewaterGroundwaterapprox. airtightpipe with ventilation Figure 1: Scheme of miniRUEDI online measurements. The portable mass spectrometer miniRUEDI was fixed in a 80 cm ×52 cm ×32 cm hard-shell suitcase with wheels. The overall weight was around 32 kg. The gases from the sewer pipe headspace and the headspace of the sump pump tank were sampled with the PVC tubing and peristaltic pumps. Their signals were then analyzed by the miniRUEDI. 2.2. Study site 65 The study catchment is located in the municipality of D¨ ubendorf, close to the Swiss 66 Federal Institute of Aquatic Science and Technology (Eawag). D¨ ubendorf consists of a 67 mixture of infrastructure without a dominant type of industry. The wastewater composition 68 is mainly residential, with some industrial contributions. Experiments were conducted in 69 one of the gravity-driven trunk sewers that collects and conveys the combined wastewater 70 4 from the town through the domain of Eawag. It has a circular profile with a diameter of 71 1000 mm, an average depth around 2.8 m, and a slope of 1.6 ‰. Long-term monitoring data 72 from an area-velocity meter (OCM pro CF, NIVUS, Germany) showed average dry weather 73 flow rates between 50 L/s and 115 L/s. The groundwater infiltration flow rate, estimated by 74 the night-time minimum method (De B´ en´ edittis and Bertrand-Krajewski, 2005), is about 45 75 to 50 L/s. Although the nigh-time minimum methods makes simplifying assumptions and 76 neglects dynamics (Kracht et al., 2007), the range is typical for combined sewer systems. 77 In our study, we sampled this location at two points, one with natural ventilation and 78 one without (Figure 1). The main monitoring point is inside a manhole of the trunk sewer 79 (47.404770, 8.611741). This was readily accessible as an underground cable canal connecting 80 the manhole to the experimental hall of Eawag, where most of our wastewater research is 81 performed. A second monitoring point was located inside the tank of a sump pump station 82 (labeled as ”pstank”), which is used to continuously extract wastewater from the trunk 83 sewer to the experimental hall. The tank is 6 m deep, with a residence time of ca. 30 min. 84 In contrast to the trunk sewer, it is virtually air tight. Thus, it can be assumed that in the 85 sump pump tank the equilibrium state of the studied gases between bulk wastewater and 86 corresponding headspace has been established. The concentration of the gases dissolved in 87 the bulk wastewater can therefore be calculated by Henry’s law and the partial pressures of 88 the gases in the headspace. 89 In addition to the gas measurements and the flow data in the sewer, we collected comple- 90 mentary monitoring data on precipitation, air pressure, air temperature, etc. at the study 91 site from the official MeteoSwiss weather station at Zurich-Kloten (47.478387, 8.530160, ca. 92 10 km away) and from the station ”D¨ ubendorf-Empa” of the Swiss National Air Pollution 93 Monitoring Network (NABEL) (47.40299, 8.61341, ca. 0.5 km away). These data sets are 94 important as reference measurements to calibrate the miniRUEDI to local ambient air and 95 to interpret the results. Further complementary data have been collected, such as atmo- 96 spheric gases concentrations (case study 1 and 2) and dissolved noble gases concentrations 97 in the local groundwater (case study 2). The raw and processed data are openly available 98 5 at the The Eawag Research Data Institutional collection (ERIC1) for further analysis. 99 3. Results and discussion 100 In the following, we present the results from three case studies, which demonstrate the 101 usefulness of gas tracers and mass spectrometric analysis in studying in-sewer processes. 102 Case study 1 investigated the gases related to biochemical reactions in the sewers. Case 103 study 2 used helium as a groundwater tracer to assess groundwater infiltration, arguably 104 making rather rough assumptions. In case study 3, we artificially injected helium as a tracer 105 to measure the air transport and ventilation in a short reach of the trunk sewer. 106 3.1. Case 1: online monitoring of biochemical gases 107 CO2and CH 4are key gas species related to biochemical reactions and GHG emission. 108 They were hence selected as gas tracers, and their concentrations in the pipe headspace 109 and the sump pump tank headspace were monitored and quantified as described in section 110 2.1. Each sampling point was connected to one inlet port of the miniRUEDI. The device 111 measured the gases from these two points semi-simultaneously by continuously switching 112 between the two inlet ports every 6 to 7 min. 113 An example of online monitoring results of gas concentrations are shown in Figure 2. 114 The CO 2concentration in the sump pump headspace was about 2000 ppm, while the CH 4 115 concentration was about 750 ppm. The concentrations of these two gases in the sewer pipe 116 headspace were about a third to a fourth lower (750 ppm and 200 ppm, respectively), most 117 probably due to ventilation losses and dilution. The measured CH 4concentrations were close 118 to the lowest bound of the values reported in other studies (Liu et al., 2015a,b). However, 119 due to the nature of our study, this data may not be representative for the whole study 120 site, as the monitoring campaign was not designed to capture the seasonality or spatial 121 distribution in the catchment. 122 1Please see: https://doi.org/10.25678/0006JS. 6 5001000150020002500CO2 (ppm) 2022-03-17 2022-03-19 2022-03-21 2022-03-23 2022-03-25 2022-03-27 2022-03-29 Time0200400600800CH4 (ppm) sewer headspace pstank headspace atmospheric levelFigure 2: shows the concentrations of CO 2and CH 4in the ambient atmosphere, in the pipe headspace (connected to the ambient atmosphere) and the headspace of the sump pump tank (not ventilated). The open circles show the original data points while the lines show the results of a LOESS smoothing. The atmospheric concentrations were derived from typical fractions of the gas species in the atmospheric air. It can be seen that the concentrations in the headspace of the sump pump tank were higher than those in the pipe headspace, because the gases produced by biological activities were accumulated. The CH 4 concentrations are in the lower range compared to literature values (Liu et al., 2015a,b) The online measurement of CO 2and CH 4with high temporal resolution better cap- 123 tures the dynamics of the gases compared to traditional grab sampling and offline analysis. 124 Such datasets enable various advanced data analysis when coupled with conventional flow 125 measurement. For example, an exploratory data analysis using these datasets and linear 126 regression suggested a slightly positive correlation between the sewer temperature and the 127 CO2concentrations in the pipe headspace (0.0896, normalized). The novel data and result- 128 ing analysis therefore provide new insights into relevant processes, such as pollutant loading 129 and GHG emissions. Thus, they can play a role in assessing mitigation strategies. However, 130 up till now only the information regarding gas concentrations can be acquired. Gas flux, 131 as a more critical indicator in many sewer system studies, can only be accessed if more in- 132 7 formation and knowledge about sewer air transport and ventilation is available (see section 133 3.4). 134 3.2. Case 2: continuous monitoring of noble gases to assess groundwater infiltration 135 In the second case study, we measured noble gases in the sewer pipe headspace and sump 136 pump tank headspace for the first time. Because groundwater is usually enriched with noble 137 gases above atmospheric solubility equilibrium (Kipfer et al., 2002),the noble gases can be 138 used to estimate the magnitude and the dynamics of infiltration into sewers. Generally, the 139 sampling and the gas analysis procedure are the same as shown in section 2.1. 140 A prior investigation showed that the concentrations of the dissolved noble gases in 141 the local groundwater were higher than those in the atmosphere-saturated water by up to 142 20% (Popp et al., 2020).Without groundwater infiltration, the headspace concentrations of 143 noble gases in the “pipe” would be the same as atmospheric values. However, the observed 144 concentrations in the monitoring points were slightly above the atmospheric concentrations. 145 Although the observed average increase of 0.73% was small compared to the analytical 146 precision of the miniRUEDI ( <5%), this might still indicate the presence of groundwater, 147 as it is the main source of noble gases in the sewers apart from atmospheric air. However, 148 the observed dynamics of the noble gases were not synchronized with the sewer flow rate 149 (see below). 150 Suggested by Kracht et al. (2007), a simplified mass balance equation of infiltration 151 ratio based on end-member mixing analysis was used to estimate the ratio of groundwater 152 infiltration, which was converted into absolute values by multiplying with the flow data. 153 For the sake of the argument, since direct liquid-phase sampling methods are lacking, we 154 made the rather rough assumption that equilibrium was established between the foul sewage 155 from the households and the atmospheric air. We also assumed that the bulk wastewater 156 in the sump pump tank and the corresponding headspace were in equilibrium, given the 157 virtually airtight conditions of the well. The dissolved noble gases in the foul sewage and 158 the bulk wastewater were then derived based on Henry’s law using atmospheric data and 159 on-site measurement data from the miniRUEDI. Another simplifying assumption was that 160 8 10% of the noble gases input was lost from the sewer system due to ventilation. The details 161 on the assumptions and calculations can be found in Zhu (2022). 162 The concentration profiles of dissolved helium, as an example of noble gases, and the 163 groundwater infiltration flow rate were calculated as shown in Figure 3. In general, the 164 estimated infiltration flow rate ranged from 25 L/s to 80 L/s (infiltration ratio 40% to 80%), 165 which is similar to the estimate obtained with the night-time minimum method (Figure 166 3). In comparison, values from literature and previous research on other catchments range 167 from 15% to 80% infiltration, making our values close to the higher bound (Kracht et al., 168 2007; Zhao et al., 2020). Interestingly, the daily fluctuations suggested by our observations 169 corresponded to the observations using stable isotopes of water as tracers and a fast grab 170 sampling method (Kracht et al., 2007). 171 In general, the on-site continuous monitoring of noble gases as tracers allowed explor- 172 ing the groundwater infiltration dynamics down to the minute scale. Such measurements 173 could give unprecedented insights into the short-term dynamics of groundwater-wastewater 174 interactions and greatly improve asset management strategies. It should be noted that, 175 due to the lack of direct liquid-phase sampling methods, the mass balance relied on rough 176 assumptions regarding ventilation conditions and gas exchange in the sewers, which could 177 lead to a systematic bias. Further, the spatial distribution of groundwater infiltration in 178 the drainage catchment was not considered. The routing of infiltrated groundwater could 179 have a great impact on the dynamics and kinetics of gases in the sewer and hence affect the 180 quantification of groundwater infiltration even more. 181 9 0.800.850.900.951.00Helium concentration (g/m3)1e5 Groundwater Wastewater (gas lost factor:10%) Foul Sewage (atmospheric air saturated water) 020406080100Inflitration ratio (%) Helium tracer method Night-minimum method 03-18 03-19 03-20 03-21 03-22 03-23 03-24 03-25 03-26 03-27 03-28 Time0255075100125150Flowrate (L/s)Night-minimum method T otal Flowrate Helium tracer methodFigure 3: (Top) Time series of helium concentrations in the wastewater, groundwater and the foul sewage at the study site, (middle) the temporal dynamics of the estimated infiltration ratio, and (bottom) the resulting hydrograph separation. In the upper figure, the open circles describe the raw monitoring data in the sump pump tank, while the blue line shows the smoothed results of LOESS. The foul sewage was assumed to be in equilibrium with the atmospheric air. The dotted line showed the dissolved helium in the local groundwater. The line located in-between the two end-members suggests the existence of groundwater in the wastewater. In the middle and bottom plots, the results of infiltration ratio and associated hydrograph decomposition suggest that the estimates of the helium tracer method are in a similar range as those computed with the conventional night-time minimum method. Although the absolute infiltration values are based on rough assumptions, the observed daily fluctuation of mixing ratios are rather robust. 3.3. Case 3: estimation of sewer air transport using helium as tracer 182 We measured the sewer headspace air velocity from a travel time experiment with helium. 183 Specifically, we injected 9 L as a dirac input at a manhole 170 m upstream of the pipe 184 monitoring location, assuming complete mixing over the entire headspace cross section. At 185 the pipe, the helium signals were sampled and recorded as described in section 2.1. For a 186 simplicity estimation of the travel time, we took the time difference between the injection and 187 the first concentration peak (Figure 4) instead of fitting an advection-dispersion transport 188 10 model. The resulting air velocity was 0.064 m/s and the flow rate 39.6 L/s, with a ratio 189 of air velocity to water velocity of 9.1%. Both the air velocity and the velocity ratio are 190 comparably low (Madsen et al., 2006; Parker and Ryan, 2001). 191 Interestingly, the observations did not show a smooth breakthrough curve, suggesting 192 that air flow conditions were complex due to various structures. However, the results clearly 193 demonstrate the potential for further research regarding sewer ventilation and air transport. 194 For example, given a sewer reach with complete geometry information, one can use the 195 mentioned tracer systems to quantify ventilation rates (i.e., the turnover of sewer air) via 196 mass balances. 197 In practice, we found it challenging to dose a large volume of tracer gas as a dirac pulse 198 from the surface through a closed manhole cover. Our final solution was to use a large 199 balloon filled with Helium, which was attached to the tube of an air compressor with a nail 200 placed inside. The compressed air pushed out the nail and popped the balloon, creating an 201 instantaneous tracer pulse. 202 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 Time56789Helium (ppm) sewer headspace atmospheric level Injection time (10:15) Figure 4: Time series of the helium tracer in the pipe headspace after a dirac input at time 10:15, in a manhole 170 m upstream. The first peak showed at around 11:00. The following small peaks might be caused by effects such as back-flow introduced by the various structures in the sewer. From this experiment, the average sewer air transport velocity was estimated to 0.064 m/s. 3.4. Opportunities and Challenges 203 Continuous monitoring of gases in sewers using portable mass spectrometers, like the 204 miniRUEDI, was investigated in three case studies. These studies demonstrated its poten- 205 tials for advancing research in various areas, including biological transformations, pollutant 206 11 dynamics, groundwater infiltration, and sewer ventilation. 207 In our view, one of the biggest potential benefits is to measure several gases simulta- 208 neously with one single portable device like miniRUEDI. Combining information on bio- 209 chemically relevant gases and inert gas tracers could possibly construct new approaches for 210 non-contact based pollution monitoring. Also, together with pumps for autonomous dosing 211 of multiple tracers, the in-situ measurements of gas tracers at a high temporal resolution 212 allows us to assess important sewer process parameters relevant for sewer modeling and 213 support subsequent maintenance decisions. For instance, by injecting multiple inert tracers 214 with different Henry’s constants, their travel time and concentrations can serve as valuable 215 inputs for calibration of sewer air transport models, which is helpful for predicting odor 216 emission, corrosion, and heat transfer. Such methodology could also be used to design more 217 complex experiments, similar to the QUEST-C tracer method (Rieckermann et al., 2007). 218 which dosed two distinct tracers at different locations to assess wastewater leakage between 219 the locations. In addition, in-situ measurements of gas tracers would also facilitate novel 220 active tracer techniques. For example, it might become possible to inject noble gases into the 221 groundwater and monitor them in the nearby sewer networks to assess the spatial variability 222 of sewer-groundwater interactions. 223 However, as with every novel method, there are still substantial limitations. Firstly, we 224 experienced that it is still challenging to sample gases directly from the liquid wastewater, 225 which has much more particles than, for example, grondwater. The gas-equilibrium mem- 226 brane inlet system developed for clean ground and surface waters (M¨ achler et al., 2012) would 227 rapidly clog when applied in wastewater. For the proposed applications, only sampling the 228 sewer atmosphere means that the mass balance of the tracers is always incomplete and that 229 it can only be closed applying several rough assumptions on gas exchange and ventilation 230 patterns. We see two possible solutions to this: first, a gas-tight clogging-free pre-filtration 231 system coupled with a gas-equilibrium membrane inlet module could be developed. This 232 probably requires some automation, including back-washing with filtrate to operate reliably 233 under changing conditions. Second, one could develop a floating flux chamber as in Gruber 234 et al. (2020) and Attermeyer et al. (2021), to facilitate the development of an equilibrium 235 12 state. 236 Moreover, unknown boundary conditions, such as ventilation conditions and gas exchange 237 with the atmosphere, make it difficult to interpret measurement data, and to extend the 238 findings to the assessment of an entire drainage system with respects to topics like large-scale 239 GHG emissions. We hope that more experience with mass-spectrometric gas monitoring will 240 help to close this gap. 241 4. Conclusions 242 Adapting our sewer systems to future challenges from urbanization and climate change 243 requires better experimental methods to improve understanding of transport and transfor- 244 mations in sewers. The results of our study suggest that the continuous monitoring of gases 245 with mass spectrometric methods can deliver better insights into in-sewer processes than 246 what is possible with current wastewater analytics. Specifically, online monitoring of gases 247 related to bio-chemical transformations can provide insights into pollutants and their con- 248 version processes. The noble gases also seem very promising as environmental tracers for 249 sewer-groundwater interactions. 250 In our view, the most promising direction is probably the simultaneous analysis of inert 251 and active gas species, which might provide new insights into the biological activities such as 252 oxygen turnover in the sewers. In the future, this might give new insights into pollutant dy- 253 namics. Also, the possibility of using multiple noble gases simultaneously as artificial tracers, 254 has not yet been explored in wastewater systems. Currently, one of the strongest limitations 255 is that a gas-tight clogging-free pre-filtration system coupled with a gas-equilibrium mem- 256 brane inlet module to monitor dissolved gases is missing. Also, it is challenging to interpret 257 the data regarding system-wide processes, such as groundwater infiltration, which still re- 258 quires rather rough assumptions. Therefore, future research should concentrate on better 259 understanding the unknown boundary conditions regarding sewer ventilation and sources 260 and sinks of gases. 261 13 Acknowledgement 262 The authors would like to thank Prof. Dr. Max Maurer for valuable feedback regarding 263 wastewater processes and using mass spectrometric monitoring of sewer gases as a novel 264 tracer system. Special thanks go to Simon Bloem (Eawag), who not only helped with 265 carrying out the field work in the drainage system, but also provided critical reality checks 266 of each and every new idea and saved us a lot of time and resources. Further thanks go to 267 Christian Ebi, Macro Kipf, and Richard Frankhauser (all Eawag), who provided experiment 268 space and devices, technical support, and routine data from the study site. 269