First detection of industrial hydrogen emissions using high-precision mobile measurements in ambient air

doi:10.21203/rs.3.rs-4618373/v1

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First detection of industrial hydrogen emissions using high-precision mobile measurements in ambient air

https://doi.org/10.21203/rs.3.rs-4618373/v1

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Projections towards 2050 of the global hydrogen (H₂) demand indicate an eight-fold increase in present-day hydrogen consumption. Leakage during production, transport, and consumption therefore presents a large potential for increases in the atmospheric hydrogen burden. Although not a greenhouse gas itself, hydrogen has indirect climate effects: through oxidation with the OH radical in the atmosphere the lifetime of methane increases, tropospheric ozone is produced, and the concentration of stratospheric water vapour increases. The Global Warming Potential of H₂ is estimated to be 12.8 times that of CO₂. Available technologies to detect hydrogen emissions have been limited to risk assessments of industrial facilities, while smaller climate-relevant emissions remain undetected. The latter requires measurement capacity at the parts-per-billion level (ppb). We developed and tested a simple and effective method to detect small hydrogen emissions from industrial installations combining active AirCore sampling with ppb-precision analysis by gas chromatography. We applied our methodology at a chemistry park in the Groningen province, the Netherlands, where several hydrogen production and storage facilities are concentrated. From a car and an unmanned aerial vehicle, we detected for the first time small but consistent industrial emissions from leakage and purging across the hydrogen value chain, which include electrolysers, a hydrogen fuelling station, and chemical production plants. Our emission estimates indicate current loss rates between 1-5% of the estimated production and storage in these facilities. This is sufficiently large to urgently flag the need for monitoring and verification of H₂ emissions for the purpose of understanding our climate change trajectory in the 21^st century.

Earth and environmental sciences/Environmental sciences/Environmental impact

Physical sciences/Energy science and technology/Renewable energy/Hydrogen energy

To achieve a zero or low-carbon energy economy, an energy carrier capable of zero emissions of air pollutants and greenhouse gases is needed. Molecular hydrogen (H₂) emerges as a promising contender for this role in this energy transition ^13,31. Initiatives such as the U.S. National Clean Hydrogen Strategy and Roadmap, Germany’s ‘Energiewende’, and the hydrogen roadmap of the Netherlands (‘Nationaal Waterstof Programma’) alongside numerous other programs, underscore countries' ambitions towards a hydrogen value chain ^9,20,24,39. However, due to hydrogen’s pivotal role in the energy transition, the expected increasing release of anthropogenic H₂ emissions into the atmosphere can result in enhanced global warming from indirect effects.

Increased levels of atmospheric H₂ can result in the lengthening of the lifetime of CH₄ and ozone, and higher levels of stratospheric water vapour ^{4,12,13,27,32,38,42,44}. Adding up to a global warming potential of 12.8 ± 5.2 over 100 years and a perturbation lifetime of 1.9 ± 0.5 years in the atmosphere, H₂ surpasses carbon dioxide (CO₂) in terms of greenhouse gas potency ^{12,14,25,40,41}. The current estimates of the loss rate potential (including venting, purging and uncontrolled leakage) of anthropogenic H₂ emissions, solely based on models, range from 1–10% of the total production ^13,35. So far, however, these estimates have not been validated at all by actual measurements, due to the lack of appropriate measurement techniques.

Currently, H₂ detectors utilised in industry are used for safety purposes only. Since the flammability range of H₂ is at 4% volume, handheld detectors with a detection limit starting at 30 µmol mol^− 1 or ppm up to 10% volume are used. However, since the atmospheric background concentration (mole fraction) of molecular hydrogen is ~ 0.5 ppm, anthropogenic H₂ from leakages with no flammability risk but a potential impact on the climate remains undetected. Precise atmospheric H₂ measurements within the scientific world started in 1957 with the introduction of the principle of liquefaction of air ¹¹, followed in the 1970s ³³ with a gas chromatographic (GC) method, designed to analyse molecular hydrogen in atmospheric air based on the reduction of mercuric oxide. In 1994, Wentworth et al. ⁴³ designed the pulsed discharge helium ionisation detector (PDHID), for use in a widespread range of applications outside atmospheric science. In 2009, Novelli et al. ²³ adopted this method on a GC-system to measure molecular hydrogen in the atmosphere. The GC-PDHID technique showed a stable performance with a linear response over the 0-2000 nmol mol^− 1 or ppb range (AGAGE ³⁰, CSIRO ⁸, NOAA ^28,29). The combination of this lab-based-measurement system, and active AirCore sampling on mobile platforms, is the novel sampling technique designed and tested in this study. The active AirCore is a long thin tube that can preserve the profile of the trace gas of interest during sampling, storage and analysis with minimum diffusive mixing ^1,17. The active AirCore was first designed and used for applications focused on CH₄ from the energy (e.g. coal mines) and the agricultural sector (e.g. farms). In our study, the application of the active AirCore sampling technique is broadened to also include the sampling and analysis of atmospheric H₂.

While the energy transition unrolls, further insights into the hydrogen value chain (production, transport, storage, end-use applications) and the potential risks of H₂ leakage are of great importance ^9,19,21,42. Historically, studies like EUROHYDROS ⁴⁴, Harvard Forest (1996–1998 ³, Mace head 1994–1998 ³⁴, focused on the natural hydrogen budget through short-term campaigns. Long-established international networks (AGE-AGAGE, NOAA, more recently ICOS ^29,30) have been measuring atmospheric H₂ in an accurate and systematic way, but their stations are mostly remote. Until now field campaigns specifically focused on regional and local anthropogenic H₂ emission sources originating from the hydrogen value chain have been absent. In Sun et al. (2024) ³⁵ it is rightly pointed out that: “It is important to note that the rates of hydrogen emissions are currently unknown across the value chain. Empirical measurements are needed to improve our understanding of where emissions are coming from and in what quantities.”. Consequently, to bridge the gap between model predictions and reality, our study offers innovative and versatile sampling techniques combined with a state-of-the-art high-precision hydrogen analysis system to provide empirical data from atmospheric H₂ mole fractions originating from industrial activities.

Our study is the first -to our knowledge- that provides such empirical measurements from atmospheric H₂ mole fractions originating from industrial activities. The proof of concept for this study entails detailed measurements of atmospheric H₂ using the active AirCore sampling technique at an industrial site in the province of Groningen (the Netherlands). We first outline our analysis and sampling techniques, after which we discuss the measurement site and necessary a priori information. We then present our observations from two mobile platforms (car and unmanned aerial vehicle (UAV)) before quantifying the emissions from the downwind sources. We use both a mass balance approach and an inverse Gaussian Plume model with multiple source configurations, and we discuss their respective uncertainties. We finish the paper with conclusions and a future outlook for our novel methodology.

2.1 Sampling methods

2.1.1 Active AirCore

The AirCore is an atmospheric sampling system that consists of a thin-wall stainless-steel (S.S.) tubing in the shape of a coil with a passivated inner surface, invented and patented by Pieter Tans ¹⁷. The original design is used to obtain a vertical atmospheric profile by filling itself using the air pressure gradient in the atmosphere. Our “active” AirCore (length 245–285 m, ³/₁₆" OD) collects air samples via the use of a micro-pump (KNF NMP015 KPDC-B 6V) and a mass flow controller (Bronkhorst IQFlow-200C-AAD-11-V-S)^{2, 36}. Using this technique, the AirCore is filled, through a chemical dryer using magnesium perchlorate located at the inlet of the system, with a pressurised and dried profile of the trace gas of interest along a given measurement trajectory ^2,36,37. For our experiments, a similar AirCore as designed and described by Tong et al. (2023) was used, and for more details the reader is referred to this paper. The active AirCore was used on two mobile platforms: driven with a passenger car and flown with a UAV. For the passenger car, we used an active AirCore with a sample volume of ~ 4.1 L. This AirCore is filled to an end-pressure of up to 1.6 bar over the course of about 2 hours of sampling, resulting in up to 38 useful discrete H₂ samples for the GC-PDHID (described in detail in section 2.2). The sampling flow rate was constant and was set to either 45 or 60 ml min^− 1, depending on the desired duration of the sampling. For the active AirCore applied on the UAV the sample volume was 3.7 L, and it was filled with a flow of 200 ml min^− 1 at atmospheric pressure, allowing for up to 21 useful discrete H₂ samples over the course of about 15 minutes of flying time. Prior to each field campaign, both AirCores were filled with synthetic air (UN1956; 20.5 Vol. % O₂, rest N₂), to clean the coil and identify a clear starting point of zero mole fraction H₂ during the analysis.

2.1.2 Flasks samples

As a complementary method to validate the AirCore H₂ measurements, vacuumized and dried 2.4 L glass flasks (with two Louwers Hapert Viton sealed valves) were filled at atmospheric pressure in pairs along the measurement trajectory to collect discrete dry air samples, by applying a magnesium perchlorate dryer tube on the flask inlet. All mole fraction analyses of the glass flasks were conducted by both the GC-PDHID for H₂ and a cavity ringdown spectrometer (CRDS) system (Picarro Inc. CA, model G2401) for mole fractions of CO₂, CH₄, and CO, the latter to get additional information on the potential emission sources co-located with H₂ (described in more detail in the Supplementary information section 1 and 2: Methods & Materials and Results & Discussion) ^5,22.

2.2 Analysis methods

2.2.1 GC-PDHID system

For the detection of molecular H₂ in the atmosphere we use an Agilent 8890 Gas Chromatograph (GC) equipped with a pulsed discharge helium ionisation detector (PDHID, Agilent) designed after Novelli et al. (2009). In addition, our GC-system was fitted with a separate analysis line for N₂O and SF₆ equipped with a micro electron capture detector (µECD, Agilent) of which more details are given in the Supplementary information. For the purpose of this paper, we will focus here on the PDHID analysis used for the detection of H₂. First, sample air is flushed over a 2 ml sample loop for H₂ (and 5 ml for N₂O/SF₆) at a rate of 52 ± 2 ml min^− 1 for 1.37 minutes. As such, the average sample size used for one measurement is 137 ± 5 ml which includes the overshoot of the pressure controller and the dead volume of the tubing and valves (using ¹⁄₁₆” OD and ⅛” OD S.S. Swagelok) between the sample carrier (flask or AirCore) and the loops (2 ml & 5 ml). Secondly, for 30 s the sample loop is equilibrated from 1.5 bar filling pressure to ambient pressure (the exhaust of the loop is equipped with a 1 m x ¹⁄₁₆” OD coil to prevent back-diffusion of lab air). Then, the sample is injected onto the first packed pre-column (Agilent S.S. packed column, 4.5 m x ⅛” OD x 2 mm, Hayesep-DB, 100–120 mesh) where H₂ is separated from the air matrix. Right after elution of the H₂ onto the second analytical column (Agilent S.S. packed column, 4.5 m x ⅛” OD x 2 mm, Hayesep-DB, 80–100 mesh), the pre-column is set into backflush mode to prevent oxygen and other contaminants from reaching the analytical column and detector. At 5.3 ± 0.3 minutes the H₂ peak reaches the detector, and it shows a 19.5 ± 1 seconds wide chromatogram. The total measurement time for one sample is 7 minutes. Potential drift is corrected by measuring a reference tank every 3 samples. Our GC-PDHID measures H₂ with a precision < 2 ppb and it is calibrated against a suite of in-house made dry whole-air working standards which themselves are calibrated against 3 primary standards linked to the international NOAA-H2-X1996 hydrogen scale (maintained by the Max Planck Institute for Biogeochemistry (MPI-BGC) Jena, Germany) ^15,16. The absolute accuracy of the primary standards is < 1 ppb. For more details about our GC-setup and measurement procedure, we refer to the Supplementary information (section 1: Methods & Materials).

AirCore analysis on the GC-PDHID

During analysis, the inlet of the active AirCore is connected to a push gas, while the outlet is connected to the sample inlet of the GC. As a push gas, the same H₂-free synthetic air as for the prefilling (at 1 bar over-pressure) was used, clearly marking the start and end of the atmospheric sampling sequence.

The GC-system uses an electronic pressure controller to regulate the flow. Typically, the push gas is set to the same pressure as the AirCore sample being around 1.6 bar absolute to minimise smearing of the sample. However, in our system, a slight overpressure of 0.4 hPa is required to push the sample through our sample loop. Potential drift is corrected for by utilising a bracketing method, wherein up to 3 samples are bracketed by a known low and high standard for calibration. It should be noted that measurement uncertainty cannot be minimised by repetition or duplication, since by the very nature of the AirCore sampling technique, it is considered a series of unique samples.

AirCore sample storage time, sample resolution and positioning

The accuracy and precision of the active AirCore samples are dependent on the storage time following the completion of the field campaign. An AirCore sample is typically measured in the lab directly after a field experiment, to keep the storage time, and thus the smearing effects by molecular diffusion, as short as possible. Extensive laboratory storage tests were done to evaluate the profile loss, i.e. the storability of molecular hydrogen in an active AirCore and determine the necessary maximum time for which an accurate retrieval can be guaranteed. Further details regarding these experiments are available in the Supplementary information (section 1: Methods & Materials). Across all sampling days, the median storage time, calculated from the ending of the sampling time, was for the car AirCore 0.75 h while for the UAV it was 1.41 h, before we started our analysis.

Given the continuous air sampling in the AirCore but discrete analyses on the GC, a relation needs to be established between the H₂ mole fractions and the path driven or flown. The spatial distribution is primarily influenced by sample size, sampling flow and mobility. With a constant sampling flow, each discrete sample linearly corresponds to a specific time duration and range of GPS coordinates. Smaller sample sizes increase the resolution of the trace gas profile and decrease the spatial distribution. Considering the spatial distribution, the samples are categorised into stationary and mobile, depending on whether the mobile platform (passenger car or UAV) was stationary or in motion. The analysis of the stationary samples is straightforward, the GPS-coordinates directly pinpoint the representative location. The mobile samples require additional interpretation and assumptions. As the mobile platform (passenger car or UAV) moves during sampling, each discrete sample corresponds to a range of GPS-coordinates. Given the filling mode of the sample loop (see 2.2.1), the actual sampled air of the discrete sample corresponds to the final segment of the loop flush. The assigned location is deducted to be at 83 $\pm$ 10% of the discrete sample’s transect, based on the loss during equilibration and the flushing time, a more extensive explanation is given in the Supplementary information (section 1: Methods & Materials).

Flasks analysis

The flasks filled in the field were measured on the GC-PDHID for H₂ and on the CRDS system for CO₂, CO and CH₄ with well-established methods in our lab ²², more details in the Supplementary information (section 1: Methods & Materials).

2.2.3 Measurement platforms

2.2.3.1 Passenger car

For sampling from a passenger car, the sampler is installed on the backseat next to the operator. The inlet of the AirCore is positioned outside of the car's rear window (Fig. 1) with the filter facing backwards and downwards to protect the inlet from potential rainfall and impact from insects. The measurement starts when the AirCore is set to sampling mode and the pump flow is set to either 45 or 60 ml min^− 1. A detailed description of the car AirCore is provided in the Supplementary information (section 1: Methods & Materials). The ambient air is dried at the inlet of the AirCore with magnesium perchlorate. The active AirCore in the passenger car is equipped with a GPS tracker and a logger for timestamp, pump pressure, coil pressure, volume sampled, and volume collected in the coil. After the field campaign is completed, typically 2 hours duration from start sampling, the AirCore is transported immediately back to the laboratory for analysis.

2.2.3.2 Unmanned Aerial Vehicle (UAV)

The UAV or drone has a carrier capacity of 8 kg, sufficient for our AirCore system with a payload capacity of 6 kg. Considering the sample volume and flow rate, the maximum flight duration is 15 minutes. Although the UAV can ascend vertically up to 500 m, flight restrictions limited the vertical profile to an altitude of maximally 140 m. The UAV AirCore system has a similar sampling method as the passenger car, only simplified, with a manual pump switch and without parameter registration. GPS tracking, flight speed, altitude, and other technical parameters are recorded by the UAV. Figure 2 shows a simple schematic of the aerial AirCore setup, for more details we refer to the Supplementary information (section 1: Methods & Materials).

2.3 Measurement site

2.3.1 Site description

Located on the northeast side of Groningen (the Netherlands), the chemistry park Delfzijl (53.3105 N, 6.9752 E) (Fig. 3) offers an ideal site for the field campaigns outlined for this study. With the Wadden Sea located north of the park and rural areas extending at least 18 km southward (SLD: Straight-line distance), minimum external influences on the atmospheric H₂ mole fractions are ensured. The chemistry park is a confined piece of land surrounded by a rural environment with large-scale and fully operational chemical processes in which molecular hydrogen is either produced, transported, stored or consumed within the park. With predominantly north-westerly winds, the emissions from the park itself are easily distinguishable downwind of the park, while easterly winds allow for observing background conditions from the surrounding agricultural area. The closest potential polluter outside of the park, is the seaport Eemshaven, 17 km SLD away to the North-West, hosting coal-and gas-fired power plants but so-far no known H₂ emitting processes. Its emissions are potentially only visible (co-emitted with CO₂ and CO) with strong north-western winds. In the WSW at 28 km SLD a potential H₂ emitter is the urban area of the city of Groningen, with e.g. a H₂ fuelling station and H₂ buses. The optimal accessibility to the chemistry park, without the need for permits or registration for all mobile platforms, facilitates the field campaigns. Furthermore, the cooperation with the industry stakeholders strengthens the eventual emission estimates and loss rate predictions, because of the specifications given on the processes and production rates (through personal communication).

Considering the sampling equipment, the proximity of Delfzijl to our laboratory ensured the profile accuracy by maintaining a minimum storage time. Even though the primary processes in the chemistry park in Delfzijl are not entirely representative of the complete hydrogen value chain, it is crucial to identify potential H₂ leakages or emissions from real facilities, before a widespread implementation is completed.

2.3.2 Industrial hydrogen production and emission estimates

For our purpose, the chemistry park Delfzijl houses four relevant industries, based on a priori information about production and emission processes, to ensure confidentiality the industries in question will be referred to by an arbitrary numbering. At industry N1 (Industry N1 consists of two processes), NaOH, Cl and H₂ are produced from brine via the process of electrolysis (1a). The surplus H₂ is transported over the park to a nearby power plant for combustion (1b) and to industry F3 for direct usage at a hydrogen fuelling station. Any remaining H₂ is directly vented. At industry E2 hydrogen peroxide is produced, for which in-house H₂ is produced from steam-methane reformation.

For industries N1 and E2, hydrogen emissions from purging and venting on sampling days are known (personal communication). Since no emission data for F3 are available, a loss rate estimation of 0.5% (~ 0.24% high-pressure storage, ~ 0.25% compressor leakage) is used from the known storage present ⁹. Industry R4 encompasses all remaining factories/companies for which no a priori information is available regarding H₂ production, consumption, purging or venting. The daily production is calculated using the average annual production rate for industry N1 and industry E2. Combined with the H₂ consumption of industry F3, the estimated production and emission rates per day are summarised in Table 1, where only for day 1 the H₂ emissions differ from the rest of the measurement days. A detailed description of the daily production and emission estimates per category is provided in the Supplementary information (section 1: Methods & Materials).

Table 1

Production and emission estimates, as provided via personal communication.
Date (dd-mm-yy)	Production per day (10⁷ g)	Emission per day (10³ g)
04-08-23	2.05 ± 0.33	7.3 ± 0.7 (*10²)
06-09-23 to 20-12-23	2.05 ± 0.33	8.3 ± 0.8

2.4 Emission estimate methods and uncertainties

2.4.1 Mass Balance approach

We apply a Mass Balance approach to estimate the amount of H₂ emitted in g s^− 1 by the Delfzijl chemistry park industries, by using the enhancement of atmospheric H₂ in an assumedly homogenous distributed 2D plane downwind of the park ^1,7,18,26,36. We use the following simple Mass Balance equation to derive the H₂ flux (Q in g s^− 1) across the transect within the downwind plane of the chemistry park:

$$Q = C\cdot \frac{u\cdot cos\left(\theta \right)\cdot \varDelta A\cdot {M}_{H2}\cdot P}{R\cdot T}$$

In the Mass Balance Eq. (1), C is the enhancement of the H₂ mole fraction [mol H₂/mol air] over background values. The average wind speed is denoted by ū [m s^− 1], and the area of a vertical grid box perpendicular to the wind direction is given by ΔA [m²]. To account for uncertainty in the mean wind direction, a deviation to the wind angle (assumed perpendicular to the grid box) is represented by θ [degrees]. Finally, the molar mass of H₂ is given by M_H2, P is the air pressure [Pa], R is the universal gas constant [m³⋅Pa⋅K^− 1⋅mol^− 1] and T is the mean atmospheric temperature [K]. We assume a standard atmospheric air pressure of 101325 Pa and an air temperature of 288.15 K. We run the Mass Balance in a Monte Carlo approach (N = 500 simulations) to account for parameter uncertainties. The determination and uncertainties for the parameters used in the Mass Balance approach are discussed in more detail in the Supplementary information (section 1: Methods & Materials).

2.4.2 Inverse Gaussian dispersion model approach

As a control and substantiation to the Mass Balance approach, we derive emission rates using the inverse Gaussian approach. For this, we used a standard point source Gaussian dispersion model (Eq. 2) in combination with the three-dimensional mole fraction data from the active AirCore measurements.

$$C(x,y,z) = \frac{Q}{2\pi {\sigma }_{y}{\left(x\right)\sigma }_{z}\left(x\right)ū}exp(-\frac{(y-{y}_{s}{)}^{2}}{2{{\sigma }_{y}}^{2}\left(x\right)})\left[exp\right(\frac{(z-{z}_{s}{)}^{2}}{2{{\sigma }_{z}}^{2}\left(x\right)})+exp(\frac{(z+{z}_{s}{)}^{2}}{2{{\sigma }_{z}}^{2}\left(x\right)}\left)\right]$$

In the Gaussian dispersion model, C(x, y, z) are the enhanced H₂ mole fractions [mol H₂ mol air^− 1] inside the plume at specific coordinates (x, y, z in metres) downwind from a source in the Delfzijl chemistry park. Q is the emission rate given in [g s^− 1] and ū is the wind speed along the plume direction in [m s^− 1]. The stability parameters 𝜎_𝑦 and 𝜎_𝑧 with units [m] (Eq. 3) describe horizontal and vertical mixing, they depend on atmospheric stability and can be calculated using the Pasquill Gifford parameters found in the Supplementary information (section 1: Methods & Materials). The last exponential term in the equation represents the reflection of plumes from the surface ⁶.

$${\sigma }_{y} = \frac{r\cdot x}{(1+\frac{x}{a}{)}^{P}} {\sigma }_{z} = \frac{s\cdot x}{(1+\frac{x}{a}{)}^{q}}$$

We identify 5 point sources for H₂ in the Delfzijl chemistry park that can be linked to activities involving significant production, storage or usage of H₂ (see section 2.3.2). Point source locations (surface coordinates and emission height) are chosen based on process type and personal communication. Similar to the Mass Balance approach, a Monte Carlo approach is run 500 times to ensure not only local minima are found and parameter ranges are significantly explored. For more detailed explanations of the determination of uncertainties and parameters, see the Supplementary information (Section 1: Methods & Materials).

2.5 Field experiments

A total of 7 sampling transects on 7 separate days have been made with the active AirCore system aboard the passenger car. For 3 out of 7 transects driven on 4th Augustus, 11th September and 6th December, in the afternoon between 14h:00m and 16h:00m local time (UTC + 1), the wind direction spanned West to North (270–350 degrees), as shown in Fig. 4. The UAV flights included four transects that lasted between 10h:30m to 13h:13m minutes carried out on 5th, 12th, 17th October and the 6th December of 2023 in the afternoon between 14h:00m and 16h:00m local time, of which two were flown successfully downwind and one upwind of the chemistry park. The height of the vertical profiles spans from 0 m (ground level) to ~ 140 m in altitude. Both the passenger car and UAV flight details are summarised in the Supplementary information (section 1: Methods & Materials).

3.1 Active AirCore passenger car results

We measured strong enhancements of H₂ mole fractions with values up to 1346 ± 2 ppb downwind of the chemistry park, relative to 530 ± 11 ppb upwind. We summarise this data in Fig. 5 with a 3D visualisation of individual samples’ enhancement over the background, displayed along the north-west angle of incidence, corresponding to the wind direction. Out of 53 downwind samples analysed, 35 (66%) had > 100 ppb enhancements, a number that is much larger than the typical seasonal changes, trends, and enhancements found at long-term monitoring sites that are situated away from local sources ²⁹. With no atmospheric chemical pathway to produce this hydrogen in-situ, this unequivocally points towards substantial emissions of H₂ in the Delfzijl park.

These emissions are not incidental but systematic (Fig. 6), as we find them across all sampling days and also under different wind directions and atmospheric conditions. Compared to the samples collected upwind of the park, the downwind data shows consistent enhanced atmospheric H₂ mole fractions, averaging 30 up to 280 ppb each day. Furthermore, due to an inhomogeneous release of anthropogenic H₂ emissions from the chemistry park, there is high variability (± 92 ppb) in the enhancement of individual samples collected on the same day. In contrast, the upwind sampled data remains consistently close to the atmospheric background mole fraction of H₂ (530 ± 10 ppb). Moreover, the very low variability of the upwind data emphasises the stability of the atmospheric background mole fraction as well as that of our sampling and analysis system, as expected when no nearby sources have influenced the samples.

3.2 Active AirCore UAV results

UAV-based sampling confirms the existence of substantial H₂ sources in the Delfzijl industrial park, although downwind measured mole fraction enhancements at the UAV flight level were lower (40–100 ppb of H₂) than we measured at the surface. However, the small variability (± 5 ppb) within daily flights relative to those in Fig. 6 makes these signals very robust indicators of enhanced H₂. Figure 7 summarises this by comparing two downwind-sampling days with one where we sampled upwind vertical profiles. The vertical profiles show that H₂ for all measurement days was relatively well mixed over the vertical plane, and the average enhancements over the background exceed the vertical H₂ gradients and variability. Local wind-shear effects near the surface could possibly have impacted data points below 20 metres in both downwind profiles; such near surface effects would also contribute to the higher variability found for our car samples.

3.3 Flasks sampling results

Our flask-derived data confirms the variability in enhanced H₂ mole fractions found at the chemistry park in Delfzijl. The H₂ mole fraction measured from the car and in the flasks for similar GPS-coordinates show for upwind locations a clear background signal while over the span of the park enhanced H₂ mole fractions up to 950 ppb were found, see the Supplementary information for more details (section 2: Results & Discussion).

Next to this, our flask-derived data gives insight into co-located GHG emissions associated with atmospheric H₂ for three categories at the park: chemical processes from industry, microbial processes from biomass, and puff emissions from a hydrogen fuelling station. From Fig. 8, it is evident that general chemical processes from industry exhibit no clear co-location with CO and CH₄. Furthermore, the most enhanced atmospheric H₂ mole fractions, with no co-located GHGs, originate from the hydrogen fuelling station situated at the start of the park. Only at the rear of the park, near the biomass waste incinerator, a clear co-location between atmospheric H₂ and microbial processes was found based on observations of CO and CH₄.

3.4 Emission estimates

We calculate loss rates (Fig. 9) between 0.2 and 4.6% for H₂-related activities at the chemistry park Delfzijl, relative to estimated daily production. On a day-to-day basis we find variations in emission rates originating from measured mole fractions and/or meteorological conditions, with median values ranging from 0.9–5.0 g s^− 1 (Mass Balance approach) to 0.1–2.8 g s^− 1 (inverse Gaussian). This range partly shows the significant impact of the environmental conditions on the model’s outcome, but especially the variability in the observed H₂ mole fraction enhancements originating from the park contributes strongly to the quoted range. The variation in the enhanced H₂ mole fraction suggests consistent but not uniform emissions over time, leading to diverse emission estimates. Furthermore, the relative homogeneity of the flown UAV profiles substantiates the continuous wide spread of emissions. On the days when both a car and UAV enhancements were sampled and measured, the emission estimates are highly similar. This similarity in the determined leak rate by the UAV flight and the car data enhances the robustness of the outcome.

We find that, on average, the inverse Mass Balance approach produces median emission rates 2.6 times as high as those by the inverse Gaussian approach for all days. We expect this is due to the presence of high mole fraction samples near sources in the passenger car dataset, which in the Mass Balance approach causes an overestimation of emissions due to an unrealistically large grid box area given the proximity to the source and the resulting short mixing time. Contrarily, the Inverse Gaussian approach can explain these high mole fraction samples using relatively low emission rates given the proximity to the source.

We developed a measurement method for low-level in-situ (semi)-continuous (industrial) H₂ emissions using an active AirCore sampler and a GC-PDHID analysis system. During a number of field experiments significantly enhanced atmospheric H₂ mole fractions were detected at the industrial chemistry park in Delfzijl (Groningen province, the Netherlands), ranging from downwind mole fractions of 580 ppb up to 1500 ppb. The consistency in the enhanced atmospheric H₂ mole fraction during every experiment indicated a continuity in H₂ emissions from the chemistry park. In addition to the AirCore samples, we analysed grab samples from flasks collected during the field experiments. These flasks were intercompared on H₂ with the AirCore data (at similar GPS-coordinates), and besides H₂, analysed on mole fractions of CO₂, CH₄, and CO to gather additional information on co-located processes. From the flask data, the enhanced H₂ mole fractions found at the chemistry park could be divided into three sections: microbial production, chemical production and H₂ purge emissions. The flask results indicated that most of the enhanced H₂ mole fractions were substantiating the AirCore data and did not correlate with enhanced mole fractions of CO_2, CO and CH₄ except for CH₄ and CO emissions in the proximity of a biomass waste incinerator at the park. The UAV-based AirCore downwind vertical profiles were relatively well mixed showing some plume variability in H₂ mole fraction along the 140 m altitude. The background upwind profile showed a nearly constant continuous background signal throughout the profile. Our first empirically determined emission estimates showed percentages (0.2–5%) well within the range of model predictions. Our results represent a stepping stone in the development of an easy-to-use and highly accurate sampling technique to detect and quantify in situ H₂ emissions from leakage, purging and storage, pivotal for the development of the energy transition.

With the data obtained from this study, we hope to inform industry and policy makers to not oversee the environmental impact of current small H₂ emissions, considering the plans for significant upscaling of sectors along the hydrogen value chain. For future work, data gathered with our sampling and analysis method has the potential to substantiate model emission estimates across the hydrogen value chain. Further work will focus on increasing the number of transects for the further expansion of data sets, not only for the chemical industry but also focused on other parts of the hydrogen value chain.

Acknowledgements

We are grateful for the technical support of Marc O. Bleeker.

Author contributions

W.P. and H.A.J.M. initiated the study. I.M.W. and H.A.S. contributed to the study concept and design. Material preparation and all experiments were conducted by I.M.W., H.A.S. and S.M.A.C.. Data analysis was done by I.M.W. and H.A.S. The system setup was supported by B.A.M.K.. The model development was done by F.T.S. and W.P.. The draft of the manuscript was written by I.M.W. with support of H.A.S. and F.T.S.. All authors read, commented, and approved the final manuscript.

Data availability

All data and analysis software used in this manuscript is accessible from an open access data archive under ‘https://github.com/IrisMWestra/Atmospheric-hydrogen-Delfzijl-.git’. For more information correspondence should be addressed to I.M.W.

Funding

The project has received financial support from the Nationaal Programma Groningen and the European Union via the subsidy ‘Waterstof Werkt: Train and Learn Hub ’ and by the Gas & Hydrogen Partnerships Shell Nederland.

Competing interests

The authors declare no competing interests.

Additional information

Correspondence and requests for materials should be addressed to I.M.W..

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First detection of industrial hydrogen emissions using high-precision mobile measurements in ambient air

Status:

Version 1

Abstract

Figures

1. Introduction

2. Methods

2.1 Sampling methods

2.1.1 Active AirCore

2.1.2 Flasks samples

2.2 Analysis methods

2.2.1 GC-PDHID system

2.2.3 Measurement platforms

2.2.3.1 Passenger car

2.2.3.2 Unmanned Aerial Vehicle (UAV)

2.3 Measurement site

2.3.1 Site description

2.3.2 Industrial hydrogen production and emission estimates

2.4 Emission estimate methods and uncertainties

2.4.1 Mass Balance approach

2.4.2 Inverse Gaussian dispersion model approach

2.5 Field experiments

3. Results & discussion

3.1 Active AirCore passenger car results

3.2 Active AirCore UAV results

3.3 Flasks sampling results

3.4 Emission estimates

4. Conclusions & Outlook

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1