# Satellite-Based Identification of Large Anthropogenic NMVOC Emission Sources

B Franco, L Clarisse, M van Damme, Juliette Hadji-Lazaro, Cathy Clerbaux,

Pierre-François Coheur

► To cite this version:

B Franco, L Clarisse, M van Damme, Juliette Hadji-Lazaro, Cathy Clerbaux, et al. Satellite-Based Identification of Large Anthropogenic NMVOC Emission Sources. Journal of Geophysical Research: Atmospheres, 2024, 129 (22), pp.e2024JD042047. 10.1029/2024jd042047. hal-04788804

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RESEARCH ARTICLE

10.1029/2024JD042047

**Key Points:**

* Oversampled IASI satellite data enable the identification of large anthropogenic point sources of CH₃OH, C₂H₂, and C₃H₆ worldwide

* Identified emitters correspond to petrochemistry, coal exploitation, metallurgy, pharmaceutical manufacturing, and megacities

* Combining IASI NMVOC data with inorganic pollutants SO₂ and NH₃ aids in identifying emission sources

**Correspondence to:**

B. Franco,
bruno.franco@ulb.be

**Citation:**

Franco, B., Clarisse, L., Van Damme, M., Hadji-Lazaro, J., Clerbaux, C., & Coheur, P. (2024). Satellite-based identification of large anthropogenic NMVOC emission sources. *Journal of Geophysical Research: Atmospheres*, 129, e2024JD042047.
https://doi.org/10.1029/2024JD042047

Received 24 JUL 2024
Accepted 4 NOV 2024

© 2024. The Author(s).
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non-commercial and no modifications or
adaptations are made.

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Satellite-Based Identification of Large Anthropogenic
NMVOC Emission Sources

B. Franco¹ ID, L. Clarisse¹, M. Van Damme¹,², J. Hadji-Lazaro³, C. Clerbaux¹,³ ID, and P. Coheur¹

¹Université libre de Bruxelles (ULB), Spectroscopy, Quantum Chemistry and Atmospheric Remote Sensing (SQUARES), BLU-ULB Space Research Center, Brussels, Belgium, ²Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium, ³LATMOS/IPSL, Sorbonne Université, UVSQ, CNRS, Paris, France

**Abstract** Nonmethane volatile organic compounds (NMVOCs) emitted in excess from anthropogenic sources significantly contribute to the formation of harmful pollutants, thereby degrading air quality. While satellite measurements have become valuable tools for tracking anthropogenic emitters, they have primarily targeted inorganic species and methane (CH₄). This study demonstrates the potential of infrared atmospheric sounding interferometers (IASI) to detect anthropogenic NMVOC point sources on a global scale. Using an advanced oversampling technique, we enhance the spatial resolution of IASI measurements to identify emitters of three major NMVOCs: methanol (CH₃OH), acetylene (C₂H₂), and propylene (C₃H₆). These point sources are primarily associated with chemical and petrochemical facilities, coal-burning activities, metallurgy, pharmaceutical manufacturing sites, and megacities. We also highlight the value of combining IASI measurements of NMVOCs with those of the inorganic species, such as sulfur dioxide (SO₂) and ammonia (NH₃), to aid in the identification of anthropogenic point sources.

**Plain Language Summary** Human activities release various gases into the atmosphere, including organic (carbon-based) gases, which contribute to the creation of pollutants that can be harmful to both the environment and public health. While satellite measurements increasingly monitor gas emissions from specific human-related sources, they have predominantly focused on inorganic pollutants, like sulfur dioxide (SO₂), ammonia (NH₃), and methane (CH₄). This study explores the potential of satellite observations from infrared atmospheric sounding interferometers (IASI) to detect human-made sources of organic gases globally. Utilizing a specialized technique to increase the spatial resolution of the satellite data, we pinpoint local emitters of three significant organic species: methanol (CH₃OH), acetylene (C₂H₂), and propylene (C₃H₆). These emitters correspond to chemical and petrochemical plants, coal-burning operations, metal production facilities, pharmaceutical manufacturing sites, and large urban areas. Additionally, combining IASI organic gas data with measurements of SO₂ and NH₃ enhances our ability to detect and identify emission point sources.

# 1. Introduction

Satellite measurements are increasingly used to track anthropogenic emissions of atmospheric pollutants, identifying point sources of nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ammonia (NH₃), and methane (CH₄) (e.g., Beirle et al., 2023; Fioletov et al., 2023; Lauvaux et al., 2022; Van Damme et al., 2018). While global spaceborne studies mainly target these species, nonmethane volatile organic compounds (NMVOCs) from anthropogenic sources raise significant concerns due to their role in forming secondary pollutants like tropospheric ozone (O₃) and particulate matter (Atkinson, 2007; de Gouw et al., 2005; Heald & Kroll, 2020; Volkamer et al., 2006). Elevated NMVOC concentrations in polluted cities and industrialized regions pose air quality challenges, prompting regulatory measures to mitigate emissions. Identifying NMVOC emitters is essential for these efforts. However, due to the limited satellite observations for NMVOCs, investigations into anthropogenic NMVOC emitters have largely been restricted to spaceborne measurements of formaldehyde (HCHO) and glyoxal (CHOCHO) for selected urban sources (e.g., Barkley et al., 2017; Lerot et al., 2021; Zhu et al., 2014; Zuo et al., 2023), or have been constrained by poor spatial coverage by relying on in situ measurements (e.g., Cho et al., 2021; Fried et al., 2020; Parrish et al., 2012; Ryerson et al., 2003; Wert et al., 2003).

Recently, Franco et al. (2022b) leveraged the extensive time series of satellite measurements from the infrared atmospheric sounding interferometer (IASI) to identify over 300 anthropogenic point sources of ethylene (ethene, C₂H₄), a high-yield precursor of HCHO, and tropospheric O₃ (Atkinson, 2007; Fried et al., 2020; Wert
et al., 2003). Here, we build upon this study to track down anthropogenic emitters of methanol (CH₃OH), acetylene (ethyne, C₂H₂), and propylene (propene, C₃H₆). Along with C₂H₄, CH₃OH and C₃H₆ are the major building blocks in the modern chemical industry (Yang, 2015), while C₂H₂ is an important precursor of secondary organic aerosol (Volkamer et al., 2009). After introducing the IASI measurements (Section 2.1) and their spatial averaging (Section 2.2), we provide spectral evidence of the first identification from space of these compounds in the plumes from large industrial facilities (Section 2.3). Subsequently, we report and categorize the detected emitters (Section 3). Finally, we demonstrate the potential of infrared satellite measurements of NMVOCs to complement those of inorganic pollutants (NH₃ and SO₂), thereby enhancing our understanding of anthropogenic emitters (Section 4), before presenting an outlook (Section 5).

## 2. Data and Methods

### 2.1. Satellite Measurements

Deployed on board the polar-orbiting European meteorological satellites (Metop), IASI measures the Earth-atmosphere outgoing radiance across the thermal infrared (645–2,760 cm⁻¹), achieving global coverage twice daily (Clerbaux et al., 2009). Here, we utilize the entire observational time series from IASI/Metop-A (2007–2021), -B (2013–2023), and -C (2019–2023), discarding cloudy scenes and nighttime measurements, which typically exhibit reduced sensitivity due to the lower thermal contrast (Di Gioacchino et al., 2024). The resulting multiyear data set comprises over 1.9 × 10⁹ measurements.

In recent years, the development of the hyperspectral range index (HRI) has played a pivotal role in improving the detection of weak infrared absorbers with IASI (e.g., Clarisse, Clerbaux, et al., 2019; Clarisse, Franco, et al., 2023; Franco, Clarisse, Theys, et al., 2024; Franco et al., 2018). The HRI quantifies the strength of spectral absorption attributed to a trace gas by aggregating the contributions from all spectral bands in which this species is absorbs (Clarisse et al., 2013; Walker et al., 2011). Following the procedure detailed by Franco et al. (2018), we constructed an HRI for each trace gas targeted in this study, using the following wave number ranges: 960–1,080 cm⁻¹ for CH₃OH, 725–735 cm⁻¹ for C₂H₂, and 905–920 cm⁻¹ for C₃H₆. As described by Clarisse, Franco, et al. (2023), the covariance matrix used for setting up the C₂H₂ HRI accounts for long-term changes in carbon dioxide (CO₂), a major interference in the 725–735 cm⁻¹ range. Additionally, we excluded the 10, 1, and 2 smallest eigenvalues of that matrix for CH₃OH, C₂H₂, and C₃H₆, respectively, to avoid artifacts caused by instrument calibration or postprocessing in the IASI time series (Clarisse, Franco, et al., 2023). An HRI value was then calculated for each IASI observation and for each species.

The long-term alignment of the IASI-A, -B, and -C instruments have been evaluated, showing that the instruments are stable and consistent during their overlapping years (Bouillon et al., 2020; Saunders et al., 2021). Moreover, the HRI values for the different NMVOCs over remote regions are consistently close to zero, as expected when there is no detectable trace gas (Clarisse et al., 2013). These assessments provide confidence that no significant systematic differences exist between the IASI instruments in detecting trace gases.

### 2.2. Supersampling

Oversampling techniques have become commonly used to track down emission point sources of atmospheric pollutants (e.g., Sun et al., 2018; Zhu et al., 2014). By combining multiple satellite observations of a given scene, oversampling capitalizes on the partial overlap among the varying measurement footprints to yield information at a higher spatial resolution than the sounder's native resolution. This process produces high-resolution gas distributions that unveil localized geographical features corresponding to pollutant hotspots.

We have applied an augmented version of oversampling developed by Clarisse, Van Damme et al. (2019b), termed hereafter as supersampling, to the IASI HRI data sets. This method integrates two key concepts:

*   **Wind rotation:** This involves rotating each satellite observation around a presumed gas emitter according to the daily horizontal wind direction, aligning all the measurements in the same direction (e.g., Beirle et al., 2011; Valin et al., 2013). The result is a measurement distribution in which the winds blow in a uniform direction, enhancing the representation of the gas emitter and its plume (downwind average) while mitigating contributions from nearby sources. Here, the daily horizontal wind fields are sourced from the European
Center for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis (Hersbach et al., 2020) and collocated with the IASI measurements.

* Super-resolution: Applied to satellite measurements, it consists of repeating the oversampling procedure and correcting the resulting oversampled average at each step until the produced average distribution achieves full consistency with the satellite data (Clarisse, Van Damme et al., 2019b). Wind adjustment preceding each step ensures the homogeneity of the underlying satellite data distribution throughout the process. The wind-adjusted, super-resolved distribution provides a more realistic representation of hotspot strengths and re-solves much finer spatial features, thereby significantly enhancing IASI's detection capabilities.

Wind rotation assumes prior knowledge of the potential gas emitter locations. However, such information is often limited or unavailable, especially for NMVOCs. Therefore, we adopted the method described by Clarisse, Van Damme et al. (2019b), which consists of creating a world map at a hyperfine spatial resolution (0.01° × 0.01°) and treating each grid cell as a presumed emitter. For each grid cell, supersampling is applied to the entire IASI HRI data set, using the grid cell center as the point of wind rotation. From the resultant wind-adjusted, super-resolved distribution, an average HRI value over the downwind area of the presumed emitter is computed and assigned to that grid cell. This process is repeated for each grid cell and for each of the target species independently. Ultimately, we obtained a 2007–2023-averaged 0.01° × 0.01° global distribution for each compound (Figure A1 of Appendix A). The supersampled distribution enables the detection of hotspots that might be challenging or impossible to discern with oversampling alone (Clarisse, Van Damme et al., 2019b; Franco et al., 2022b). The examples of NVMOC hotspots in Figures 1, 4 and 5 are zoom-ins from the global distributions obtained with supersampling.

A significant advantage of using the HRI instead of retrieved gas vertical column densities (VCDs) for supersampling is that it conveys the cumulative information on the target gas present in the satellite spectra and is primarily affected only by instrumental noise (Clarisse et al., 2013; Whitburn et al., 2016). In contrast, VCDs are influenced by additional uncertainties resulting from the HRI-to-VCD conversion, including errors inherited from variables describing the atmosphere and the surface. Due to the weak absorptions of NMVOCs in the thermal infrared, the advantage provided by the HRI is crucial for detecting point sources. As demonstrated by Franco et al. (2022b), utilizing the HRI unveiled C₂H₄ point sources that would have otherwise gone undetected with retrieved VCDs.

The supersampled global distributions of CH₃OH, C₂H₂, and C₃H₆ (Franco, Clarisse, & Coheur, 2024) exhibit variable backgrounds (Figure A1 of Appendix A). Elevated HRI values of CH₃OH and C₂H₂ primarily reflect their regional sources, with substantial contributions from biogenic sources for CH₃OH, Northern Hemisphere biofuel combustion for C₂H₂, and biomass burning for both compounds. The relatively high, homogeneous C₂H₂ background is due to its longer atmospheric lifetime (~2 weeks; Xiao et al., 2007), which enables its long-range transport and mixing in the troposphere. Conversely, the short C₃H₆ lifetime against reactions with the hydroxyl radical (OH) and O₃ (a few hours–1.5 days; Atkinson & Arey, 2003; Seinfeld & Pandis, 2016) results in low background HRI values. Enhancements over deserts are attributed to surface emissivity artifacts (Clarisse, Clerbaux, et al., 2019; Franco et al., 2022b), particularly affecting the C₃H₆ spectral absorption band (Zhou et al., 2011).

Zoom-ins of specific regions in these distributions reveal pronounced local HRI enhancements of 20–40 km geographical extent, corresponding to emission hotspots. Due to varying observational conditions and the presence of false positives (e.g., surface emissivity effects or frequent wildfires), the hotspot identification was based on a careful manual inspection of the data, using two main criteria: a significant local HRI enhancement, clearly differentiating from the surrounding background and the presence of anthropogenic activities (e.g., industrial or urban areas) at the location, as confirmed by visible satellite imagery. It has been demonstrated by Clarisse, Van Damme et al. (2019b) that the gas emitter(s) can be found with supersampling within a distance of 5 km from the local HRI maximum for most point sources. Figure 1 illustrates a typical hotspot for each compound. Close-up views with satellite visible imagery reveal potential emitters, such as chemical plants in the Ningdong Industrial Park (Ningxia, China) for CH₃OH, coal processing plants near Wuhai (Inner Mongolia, China) for C₂H₂, and the Secunda petrochemical complex (South Africa) for C₃H₆ (Figure 1). Each example suggests that the gas enhancements detected with IASI can be traced back to emissions from heavy industrial activities. Interestingly, these sites have also been identified as anthropogenic point sources of C₂H₄ by Franco et al. (2022b), as shown in Figure 1. C₂H₄ industrial emitters have been associated with chemical and petrochemical clusters, iron and steel plants, and various coal-related industries.
<figure><img src="image_3.png" /><figcaption>**Figure 1.** 2007–2023 averaged 0.01° × 0.01° IASI HRI for CH₃OH (a), C₂H₂ (d), and C₃H₆ (g) around hotspot examples, obtained by wind-rotated supersampling. The white squares indicate the location of the source emitter(s) and correspond to the close-up views in (b, e, and h) with satellite visible imagery. (c, f, i) Supersampling of the 2007–2023 averaged IASI C₂H₄ HRI at a 0.01° × 0.01° spatial resolution, at the locations of the CH₃OH, C₂H₂, and C₃H₆ hotspots.</figcaption></figure>

## 2.3. Spectral Evidence

Despite its high sensitivity, the HRI is prone to false detections when the spectral signature of another trace gas or of surface emissivity overlap and resemble that of the target species. In this section, we provide spectral evidence that CH₃OH, C₂H₂, and C₃H₆ significantly contribute to the HRI enhancements identified as hotspots. To this end, we applied the whitening transformation of spectra introduced by De Longueville et al. (2021) to IASI
<figure><img src="image_4.png" /><figcaption>**Figure 2.** Results of the whitening transformation (in gray) applied to averaged IASI spectra taken over CH₃OH (a), C₂H₂ (b), and C₃H₆ (c) hotspots. Whitened Jacobians for the target species (in red), potential interfering gases (in yellow), and contribution of each spectral channel to the HRI (in blue). Other major spectral residuals correspond to water vapor. Both y-axes are unitless.</figcaption></figure>

observations over detected hotspots. Examples are displayed in Figure 2 for the point sources presented in Figure 1. For each hotspot, we selected a month with favorable observational conditions and averaged all IASI/Metop-A spectra with an HRI value of the target compound greater than 1 for that month throughout the 2007–2020 time series before applying the whitening transformation to these averaged spectra.

The whitening transformation produces a spectrum where all spectral absorptions deviating from the climatological normality are highlighted (gray curves in Figure 2). After applying the whitening to the averaged IASI spectra, we observe in Figure 2 strong spectral residuals that closely match the whitened spectral signature (the
<figure><img src="image_5.png" /><figcaption>**Figure 3.** Global distribution of CH₃OH, C₂H₂, and C₃H₆ point sources detected by IASI and their categorization. In cases where a hotspot falls into multiple categories, only the two main categories are shown on the map.</figcaption></figure>

Jacobian) of the target species in each example (red curves). This provides firm evidence that the elevated HRI values observed over the hotspots correspond to actual enhancements of CH₃OH, C₂H₂, and C₃H₆. Additionally, as shown by Franco et al. (2022b) and Franco, Clarisse, Theys, et al. (2024) for both individual and averaged spectra, element-wise multiplication of the whitened spectrum and target gas's Jacobians quantifies the contribution of each spectral channel to the HRI calculated over the entire spectral range (visualized as blue curves in Figure 2). For the three target species, the spectral channels contributing to the HRI correspond exactly to their main absorption features, while contributions from other channels are negligible. For instance, the spectral residual identified at 908 cm⁻¹ in the C₃H₆ spectral range (Figure 2c), attributed to NH₃, does not contribute as it is nullified by the C₃H₆ Jacobian. This analysis demonstrates that the CH₃OH, C₂H₂, and C₃H₆ hotspots identified with IASI can be unequivocally attributed to industrial point sources.

### 3. Results

We conducted a systematic analysis of the supersampled maps of CH₃OH, C₂H₂, and C₃H₆ to identify gas hotspots worldwide. For each detected hotspot, we used satellite visible imagery and online data regarding the types of companies and industrial activities in the area to determine the likely gas emitter(s). We report in Figure 3 the global distribution of all NMVOC hotspots detected with IASI, categorized by the type of identified emitters. A total of 157 CH₃OH hotspots, 16 C₂H₂ hotspots, and 4 C₃H₆ hotspots were detected (Franco, Clarisse, & Coheur, 2024), with a predominant concentration in the Northern Hemisphere, particularly in East Asia. These hotspots, listed in Tables A1–A3 of Appendix A, correspond to five main types of sectoral emissions: chemical and petrochemical industry, coal-related industry, metallurgy, pharmaceutical industry, and urban areas. In some cases, identifying a distinct emitter was not possible. A single hotspot may also originate from multiple nearby point sources of various types. In these instances, only the two predominant categories are depicted in Figure 3.

It is worth noting that the point sources identified with IASI do not exclusively represent the largest global emitters of these NMVOC compounds. While emission strength is a key factor influencing detection, several other elements come into play. In regions with dense populations and industrial activities, elevated background levels of NMVOCs and the proximity of multiple emitters can obscure individual sources, making distinct hotspot detection more challenging. Furthermore, poor observational conditions—such as weak thermal contrast or frequent cloud cover—can prevent even significant emitters from being detected.
<figure><img src="image_6.png" /><figcaption>**Figure 4.** Visible satellite imagery (a), and 2007–2023 averaged 0.01° × 0.01° IASI HRI of CH₃OH (b) and C₂H₄ (c) obtained by wind-rotated supersampling, over Visakhapatnam, Andhra Pradesh, India. The colored squares indicate the locations of the emission sources, corresponding to the close-up views of the CH₃OH and C₂H₄ point source emitters: the Jawaharlal Nehru Pharma City (d) and the Vizag Steel Plant (e), respectively.</figcaption></figure>

### 3.1. C₃H₆ Point Sources

C₃H₆ has been detected previously with IASI during the exceptional 2009 and 2019/2020 Australian bushfires (Clarisse, R’Honi et al., 2011; De Longueville et al., 2021). With the identification of four C₃H₆ point sources, we present the first detection of anthropogenic C₃H₆ from space (Figure 3). They correspond to Secunda (South Africa), Rabigh (Saudi Arabia), Ningdong base, and Fangshan District (China). The fact that only four large emitters are detected is likely explained by the high reactivity of C₃H₆ in the low troposphere and its weak spectral absorption. These point sources are associated with major petrochemical clusters, which are also sites of C₂H₄ emissions (Franco et al., 2022b).

With a global production of ~120 Mt yr⁻¹, C₃H₆ serves—along with C₂H₄ (~190 Mt yr⁻¹)—as a primary building block for plastics, fibers, and various other chemicals (Zimmermann, 2013; Zimmermann & Walzl, 2009). C₃H₆ is produced industrially through steam cracking of hydrocarbons (ethane, propane, and naphtha) and as a by-product of crude oil refining. Emissions of C₃H₆ can therefore occur from petrochemical facilities during its production and processing, from stack flaring, or through leaks and accidental releases. Substantial amounts have indeed been measured in situ in industrial plumes downwind of petrochemical complexes similar to those identified with IASI (Cho et al., 2021; Fried et al., 2020; Parrish et al., 2012; Ryerson et al., 2003; Wert et al., 2003).

Two of the four identified C₃H₆ point sources are also characterized by coal mining and processing activities, like at Secunda (Figure 1). In regions where oil and gas reserves are limited or too expensive to exploit, coal-to-olefins (CTO) and methanol-to-olefins (MTO) conversion technologies have emerged as substitutes to the conventional production pathways (Amghizar et al., 2017; Zimmermann, 2013; Zimmermann & Walzl, 2009). In the CTO
<figure><img src="image_7.png" /><figcaption>**Figure 5.** Visible satellite imagery (a), and 2007–2023 averaged 0.01° × 0.01° IASI HRI of C₂H₂ (b) and C₂H₄ (c) obtained by wind-rotated supersampling, over Baotou, Inner Mongolia, China. The colored squares indicate the locations of the emission sources, corresponding to the close-up views of the C₂H₂ and C₂H₄ point source emitters (d–e).</figcaption></figure>

process, coal is gasified to produce synthesis gas (syngas), a mixture of carbon monoxide and hydrogen, which serves as feedstock for the production of fuels and chemicals, including light olefins (C₂H₄ and C₃H₆), CH₃OH, and NH₃. In the MTO route, CH₃OH itself is converted by dehydration into light olefins. In point sources where coal is used as raw material, C₃H₆ released from the incomplete heating and burning of coal adds to the emissions from chemical facilities.

## 3.2. CH₃OH Point Sources

While available spaceborne observations of CH₃OH primarily relate to its biogenic sources (e.g., Cady-Pereira et al., 2012; Franco et al., 2018; Wells et al., 2012), here we identify anthropogenic CH₃OH emissions by detecting 157 global point sources from space, with most located in Asia, the Middle East, and eastern North America (Figure 3). Although CH₃OH can be produced from atmospheric gas precursors (Bates et al., 2021; Jacob et al., 2005; Millet et al., 2008; Müller et al., 2016), this secondary formation primarily affects the CH₃OH background and is assumed to have little impact on the local enhancements detected by IASI over point sources.

Global industrial production of CH₃OH amounts to 90–100 Mt yr⁻¹, positioning it—after C₂H₄ and C₃H₆—as the third most abundantly produced organic compound (Ott et al., 2012; Yang, 2015). CH₃OH is generally obtained by catalytic conversion of syngas, and roughly 85% of synthetized CH₃OH is utilized directly in the chemical industry as feedstock or solvent (Ott et al., 2012). It is therefore no surprise that half of the CH₃OH point sources are associated with chemical and petrochemical facilities (e.g., in the Middle East). The industrial synthesis of CH₃OH is increasingly used as a substitute for petroleum products, particularly via the CTO/MTO pathways
(Zimmermann, 2013; Zimmermann & Walzl, 2009), which explains why many of the CH₃OH point sources associated with chemical facilities are also characterized by coal refining (Figure 3).

Some CH₃OH hotspots are found over areas hosting a cluster of pharmaceutical companies, laboratories, and manufacturing facilities, known as pharma cities, especially in India (Figure 3). A typical example is the CH₃OH point source associated with the Jawaharlal Nehru Pharma City, west of Visakhapatnam, India (Figure 4). CH₃OH serves indeed as a solvent and starting material for the synthesis of various medicines and pharmaceutical intermediates (Ott et al., 2012). Among the current satellite products, CH₃OH is the only species that allows pinpointing specifically to this industrial sector. The area of this CH₃OH point source is also the site of a significant, eastward-shifted C₂H₄ enhancement (Figure 4c), attributed to emissions from an integrated steel plant (Franco et al., 2022b).

The remaining CH₃OH point sources are associated with megacities such as Tianjin, Jakarta, and Lagos (Figure 3). Elevated concentrations of CH₃OH have been measured in dense urban environments (e.g., de Gouw et al., 2018; Simpson et al., 2020) due to its use in the fuel and energy sector. Incomplete combustion, for example, from vehicle exhaust and domestic heating, can also release CH₃OH. As explained by Franco et al. (2022b), urban point sources are generally more difficult to detect from space because the associated emissions are more diffuse than for industrial sources. Furthermore, urban and industrial CH₃OH emissions cannot be distinguished when heavy industries are located in urban areas. For instance, the cities Rio de Janeiro, Sao Paulo, and Curitiba (Brazil), which emerge as local emitters, host petrochemical hubs.

### 3.3. C₂H₂ Point Sources

Spaceborne measurements of C₂H₂ indicate a significant influence from biomass burning regions and a notable latitudinal gradient due to prevalent anthropogenic sources in the Northern Hemisphere (Bernath et al., 2020; Duflot et al., 2015). Given its longer lifetime of ~2 weeks (Xiao et al., 2007), the supersampled IASI C₂H₂ distribution exhibits a higher HRI background compared to CH₃OH (4–7 days; Bates et al., 2021; Khan et al., 2014; Müller et al., 2016), C₃H₆, and C₂H₄ (both with lifetimes ranging from a few hours to 1.5 days; Atkinson & Arey, 2003; Seinfeld & Pandis, 2016), resulting in weaker and more diffuse C₂H₂ hotspots that are challenging to detect. We have, however, identified 16 C₂H₂ point sources, all of which are associated with a heavy industry (Figure 3).

Before the emergence of the cheaper, more competitive light olefins, C₂H₂ was a key building block in industrial organic chemistry due to its capacity to be converted into valuable products with high yields (Pässler et al., 2011). Although its industrial production—primarily through steam cracking of hydrocarbons—has steadily declined, C₂H₂ remains utilized in the chemical industry, particularly for synthesizing vinyl compounds, as well as in metal processing. China currently stands as the largest producer of C₂H₂ and consumes ~80% of the global production (Pässler et al., 2011). Noteworthy, all the C₂H₂ points sources identified with IASI are in China (Figure 3), predominantly concentrated in the northern central provinces (e.g., Inner Mongolia, Ningxia, and Shanxi).

The C₂H₂ point sources are characterized by chemical industries, coal-related activities, and metallurgy. Similar to C₃H₆ and CH₃OH, C₂H₂ emissions from chemical facilities can occur through gas flaring and fugitive releases. As a by-product of pyrolytic reactions, C₂H₂ is also emitted from the incomplete combustion of hydrocarbons, from the incomplete gasification of coal during the production of syngas, and from coal undergoing high-temperature pyrolysis to produce coke in the iron and steel industry (Pässler et al., 2011). The majority of these point sources are common to both C₂H₂ and C₂H₄ (Franco et al., 2022b), such as Baotou, Inner Mongolia, which gathers coal mining and processing activities, coal-fired power plants, steel plants, and chemical industries (Figure 5).

### 4. Case Study

Identifying point sources is often challenging due to the presence of various potential emitters at the same location, especially in regions where information is sparse or difficult to obtain. Combining organic and inorganic tracers to study anthropogenic emissions can provide more insights into largest gas emitters and help identify the most polluted areas for further dedicated measurements. As a case study, we analyze the supersampled distributions of C₂H₂, C₂H₄, C₃H₆, and CH₃OH, as well as those of SO₂ HRI and NH₃ VCDs from IASI (Clarisse, Van Damme et al., 2019b; Van Damme et al., 2018), depicted as contour plots in Figure 6, over an industrial valley in the Inner Mongolia and Ningxia provinces (China).
<figure><img src="image_8.png" /><figcaption>**Figure 6.** Clustered point sources of atmospheric pollutants detected by IASI in an industrial valley in central China. Hotspots are outlined by colored contour lines representing C₂H₄ HRI = 0.4, C₂H₂ HRI = 1.2, CH₃OH HRI = 1.5, C₃H₆ HRI = 0.3, SO₂ HRI = 2.5, and NH₃ column = 1.5 × 10¹⁶ molec cm⁻², obtained from the supersampled distribution of each species. Insets present zoom-ins of potential emitters.</figcaption></figure>

Although there is a much longer history of measuring anthropogenic SO₂ emissions using ultraviolet-visible satellite sounders (e.g., Fioletov et al., 2013; Fioletov et al., 2023; Liu et al., 2018; McLinden et al., 2016; Theys et al., 2021) compared to infrared instruments (e.g., Clarisse, Fromm, et al., 2011), and despite the lower sensitivity of thermal infrared measurements to SO₂ in the lowermost atmospheric layers due to the weak thermal contrast between the surface and the boundary layer, we make use of IASI SO₂ data to maintain consistency in spatial resolution, footprint, overpass time, and vertical sensitivity with the NMVOCs and NH₃ measurements. Note that in Figure 6, results for NH₃ are expressed in VCDs.

These distributions reveal a significant cluster of gas hotspots, delineated with a constant HRI (or VCD) threshold specific to each compound in Figure 6: C₂H₄ HRI = 0.4, C₂H₂ HRI = 1.2, CH₃OH HRI = 1.5, C₃H₆ HRI = 0.3, SO₂ HRI = 2.5, and NH₃ column = 1.5 × 10¹⁶ molec cm⁻². These thresholds were selected to clearly visualize the gas hotspots in this case study and vary by species and region depending on local background gas concentrations and observational conditions, particularly thermal contrast. The gas hotspots are concentrated around five locations (labeled A–E), each corresponding to the point source of at least two different species and hosting a high density of industrial facilities. Coal-related activities are particularly prevalent in the region, as coal has been the primary feedstock supporting industrial and economic development in central China (Crelling et al., 2010; Li et al., 2019; Tong et al., 2018).

Location B exhibits significant enhancements in all species (except C₃H₆), indicating that large gas releases can occur from the many coal mines, coke plants, and coal-fired power plants in the area. CH₃OH enhancement in the
absence of large cities suggests additional emissions from chemical plants, contributing to the C₂H₂ and C₂H₄ hotspots. Conversely, CH₃OH and C₂H₄ enhancements at locations C–D may primarily be attributed to the urban agglomeration, while C₂H₂ and SO₂ hotspots would indicate emissions from coal refining facilities, power plants, and steel factories. A large chemical complex could be responsible for CH₃OH, C₂H₄, and C₃H₆ fluxes at location E. In particular, the C₃H₆ point source, confirmed through spectral analysis, corresponds to an olefin plant. Two other spots with C₃H₆ HRI above the defined threshold are observed in the region, but those are false detections due to spectral emissivity anomalies from rocks and sands. Metallurgy activities, likely smelters, are also present and can release SO₂ at location E. Conversely, the northernmost location A exhibits C₂H₂ and C₂H₄ hotspots only, likely due to the coal sector. In contrast to other species, NH₃ shows substantial enhancement covering a large part of the area, attributable to agriculture and husbandry activities throughout the valley. Chemical industries also contribute at locations B and E due to the presence of fertilizer plants (Clarisse, Van Damme et al., 2019b; Van Damme et al., 2018).

**5. Outlook**

This study demonstrates the feasibility of detecting anthropogenic emission point sources of small (NM)VOCs using infrared satellite data. It represents a significant step toward future endeavors, which might include inferring top-down emission fluxes from identified point sources. This would be of particular interest as top-down estimates derived from time-resolved airborne observations are tailored to specific sites, whereas satellite data sets provide the means to infer emissions from global point sources using a single sounder. Additionally, spaceborne fluxes of inorganic species have already shown that current bottom-up emission inventories often misrepresent these point sources and their emission rates (e.g., Beirle et al., 2023; Fioletov et al., 2023; Van Damme et al., 2018). Similarly, inferring top-down fluxes of NMVOCs will be essential for improving our understanding and representation of anthropogenic emissions.

The weak spectral absorption of NMVOCs, leading to high uncertainties in retrieved VCDs, currently hinders this task. However, our study serves as a proof of concept in light of forthcoming infrared satellite sounders, including the polar-orbiting IASI-New Generation (IASI-NG) and the geostationary Infrared Sounder on board Meteosat Third Generation (MTG-IRS). With enhanced instrumental performance compared to IASI, or with extensive spatial coverage and up to 30-min revisit times, these future sounders are anticipated to detect a greater number of anthropogenic emitters and provide the potential for top-down quantification of their emission rates.

**Appendix A: Supplementary Materials**
<figure><img src="image_9.png" /><figcaption>**Figure A1.** 2007–2023 averaged 0.01° × 0.01° global distribution of CH₃OH (a), C₂H₂ (b), and C₃H₆ (c) HRI, obtained by wind-rotated supersampling of the IASI data. The C₃H₆ HRI enhancements observed over deserts (e.g., Sahara and Australia) are due to surface emissivity anomalies.</figcaption></figure>
<table><caption>**Table A1**
A Catalog of CH₃OH Point Sources, With Identified Potential Emitters</caption><thead><tr><th></th><th>Name</th><th>Country</th><th>Lat</th><th>Lon</th><th>Ch</th><th>Co</th><th>Me</th><th>Ur</th><th>Ph</th><th>Un</th></tr></thead><tbody><tr><td>1</td><td>Curitiba</td><td>Brazil</td><td>-25.516</td><td>-49.348</td><td>x</td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>2</td><td>Rio de Janeiro</td><td>Brazil</td><td>-22.719</td><td>-43.408</td><td>x</td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>3</td><td>Sao Paulo</td><td>Brazil</td><td>-23.527</td><td>-46.652</td><td>x</td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>4</td><td>Kamloops</td><td>Canada</td><td>50.693</td><td>-120.407</td><td></td><td></td><td></td><td></td><td></td><td>x</td></tr><tr><td>5</td><td>Medicine Hat</td><td>Canada</td><td>50.080</td><td>-110.664</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>6</td><td>Montreal</td><td>Canada</td><td>45.547</td><td>-73.677</td><td>x</td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>7</td><td>Toronto</td><td>Canada</td><td>43.755</td><td>-79.399</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>8</td><td>Winnipeg</td><td>Canada</td><td>49.841</td><td>-97.107</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>9</td><td>Santiago</td><td>Chile</td><td>-33.473</td><td>-70.762</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>10</td><td>Anshan</td><td>China</td><td>41.152</td><td>122.912</td><td></td><td></td><td>x</td><td>x</td><td></td><td></td></tr><tr><td>11</td><td>Anyang</td><td>China</td><td>36.106</td><td>114.214</td><td></td><td></td><td>x</td><td></td><td></td><td></td></tr><tr><td>12</td><td>Baise</td><td>China</td><td>23.739</td><td>106.871</td><td></td><td>x</td><td></td><td></td><td></td><td>x</td></tr><tr><td>13</td><td>Baoding</td><td>China</td><td>38.834</td><td>115.462</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>14</td><td>Baotou</td><td>China</td><td>40.614</td><td>109.690</td><td>x</td><td></td><td>x</td><td></td><td></td><td></td></tr><tr><td>15</td><td>Beijing</td><td>China</td><td>39.845</td><td>116.421</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>16</td><td>Cangzhou</td><td>China</td><td>38.388</td><td>116.815</td><td>x</td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>17</td><td>Changsha</td><td>China</td><td>28.190</td><td>113.058</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>18</td><td>Changshou District</td><td>China</td><td>29.776</td><td>107.008</td><td>x</td><td></td><td>x</td><td></td><td></td><td></td></tr><tr><td>19</td><td>Changzhou</td><td>China</td><td>31.697</td><td>120.168</td><td></td><td></td><td>x</td><td>x</td><td></td><td></td></tr><tr><td>20</td><td>Chengdu</td><td>China</td><td>30.742</td><td>104.068</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>21</td><td>Chongqing</td><td>China</td><td>29.572</td><td>106.533</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>22</td><td>Dalad Banner</td><td>China</td><td>40.321</td><td>110.060</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>23</td><td>Dezhou</td><td>China</td><td>37.468</td><td>116.278</td><td>x</td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>24</td><td>Dongguan</td><td>China</td><td>22.932</td><td>113.805</td><td>x</td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>25</td><td>Gaomi City</td><td>China</td><td>36.334</td><td>119.858</td><td></td><td></td><td></td><td></td><td></td><td>x</td></tr><tr><td>26</td><td>Guangzhou/Foshan</td><td>China</td><td>23.120</td><td>113.122</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>27</td><td>Hainan District</td><td>China</td><td>39.370</td><td>106.856</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>28</td><td>Hamusi Golmud</td><td>China</td><td>36.729</td><td>95.202</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>29</td><td>Harbin</td><td>China</td><td>45.681</td><td>126.580</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>30</td><td>Hefei</td><td>China</td><td>31.825</td><td>117.339</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>31</td><td>Heze</td><td>China</td><td>35.241</td><td>115.455</td><td>x</td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>32</td><td>Hohhot</td><td>China</td><td>40.701</td><td>111.510</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>33</td><td>Huixian</td><td>China</td><td>35.432</td><td>113.771</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>34</td><td>Hulunbuir City</td><td>China</td><td>49.344</td><td>119.661</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>35</td><td>Jiaocheng County</td><td>China</td><td>37.526</td><td>112.190</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>36</td><td>Jincheng</td><td>China</td><td>35.701</td><td>112.813</td><td>x</td><td></td><td>x</td><td></td><td></td><td></td></tr><tr><td>37</td><td>Jinhua</td><td>China</td><td>29.057</td><td>119.558</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>38</td><td>Jinjie Park</td><td>China</td><td>38.707</td><td>110.173</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>39</td><td>Jungar Qi</td><td>China</td><td>40.040</td><td>111.270</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>40</td><td>Kaifeng</td><td>China</td><td>34.744</td><td>114.411</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>41</td><td>Kaiyuan</td><td>China</td><td>23.730</td><td>103.195</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>42</td><td>Kuytun/Dushanzi</td><td>China</td><td>44.352</td><td>84.873</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>43</td><td>Lanzhou</td><td>China</td><td>36.089</td><td>103.770</td><td>x</td><td></td><td></td><td>x</td><td></td><td></td></tr></tbody></table>
<caption>Table A1</caption>

Continued

<table><thead><tr><th></th><th>Name</th><th>Country</th><th>Lat</th><th>Lon</th><th>Ch</th><th>Co</th><th>Me</th><th>Ur</th><th>Ph</th><th>Un</th></tr></thead><tbody><tr><td>44</td><td>Leshan</td><td>China</td><td>29.459</td><td>103.784</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>45</td><td>Linyi</td><td>China</td><td>35.155</td><td>118.204</td><td></td><td></td><td></td><td></td><td></td><td>x</td></tr><tr><td>46</td><td>Linyi</td><td>China</td><td>35.086</td><td>110.749</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>47</td><td>Liuzhou</td><td>China</td><td>24.358</td><td>109.375</td><td></td><td>x</td><td>x</td><td>x</td><td></td><td></td></tr><tr><td>48</td><td>Longkou</td><td>China</td><td>37.637</td><td>120.448</td><td></td><td></td><td></td><td></td><td></td><td>x</td></tr><tr><td>49</td><td>Miaotan Village</td><td>China</td><td>38.058</td><td>108.990</td><td></td><td></td><td></td><td></td><td></td><td>x</td></tr><tr><td>50</td><td>Nankang</td><td>China</td><td>25.714</td><td>114.790</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>51</td><td>Ningdong base</td><td>China</td><td>38.197</td><td>106.586</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>52</td><td>Qitaihe</td><td>China</td><td>45.771</td><td>130.799</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>53</td><td>Quanzhou</td><td>China</td><td>24.851</td><td>118.528</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>54</td><td>Renqiu</td><td>China</td><td>38.702</td><td>116.106</td><td>x</td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>55</td><td>Shanghai</td><td>China</td><td>31.162</td><td>121.506</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>56</td><td>Shantou</td><td>China</td><td>23.472</td><td>116.713</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>57</td><td>Shaoxing</td><td>China</td><td>30.087</td><td>120.500</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>58</td><td>Shenyang</td><td>China</td><td>41.821</td><td>123.341</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>59</td><td>Shijiazhuang</td><td>China</td><td>37.978</td><td>114.619</td><td>x</td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>60</td><td>Shizuishan</td><td>China</td><td>38.929</td><td>106.437</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>61</td><td>Tengzhou</td><td>China</td><td>34.971</td><td>117.211</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>62</td><td>Tianjin</td><td>China</td><td>39.115</td><td>117.124</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>63</td><td>Urumqi</td><td>China</td><td>44.032</td><td>87.702</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>64</td><td>Wenzhou</td><td>China</td><td>27.876</td><td>120.758</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>65</td><td>Wujiang District</td><td>China</td><td>30.873</td><td>120.654</td><td></td><td></td><td></td><td></td><td></td><td>x</td></tr><tr><td>66</td><td>Wuyang County</td><td>China</td><td>33.427</td><td>113.624</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>67</td><td>Xiamen</td><td>China</td><td>24.597</td><td>118.121</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>68</td><td>Xi'An</td><td>China</td><td>34.295</td><td>108.837</td><td>x</td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>69</td><td>Xiaoyi</td><td>China</td><td>37.098</td><td>111.797</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>70</td><td>Xifeng County</td><td>China</td><td>27.164</td><td>106.719</td><td></td><td></td><td></td><td></td><td></td><td>x</td></tr><tr><td>71</td><td>Xingping</td><td>China</td><td>34.292</td><td>108.481</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>72</td><td>Xinxiang</td><td>China</td><td>35.215</td><td>113.785</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>73</td><td>Xuzhou</td><td>China</td><td>34.258</td><td>117.223</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>74</td><td>Yichang</td><td>China</td><td>30.509</td><td>111.468</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>75</td><td>Yinchuan</td><td>China</td><td>38.457</td><td>106.060</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>76</td><td>Yingcheng</td><td>China</td><td>30.950</td><td>113.612</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>77</td><td>Yulin</td><td>China</td><td>38.120</td><td>109.556</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>78</td><td>Zhangjiagang</td><td>China</td><td>31.828</td><td>120.448</td><td>x</td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>79</td><td>Zhangzhou</td><td>China</td><td>24.540</td><td>117.685</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>80</td><td>Zhengzhou</td><td>China</td><td>34.734</td><td>113.583</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>81</td><td>Zhongwei</td><td>China</td><td>37.627</td><td>105.205</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>82</td><td>Zhumadian</td><td>China</td><td>32.973</td><td>114.008</td><td>x</td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>83</td><td>Zibo</td><td>China</td><td>36.722</td><td>118.025</td><td></td><td></td><td></td><td></td><td></td><td>x</td></tr><tr><td>84</td><td>Bogota</td><td>Colombia</td><td>4.614</td><td>-74.140</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>85</td><td>Ain Sokhna</td><td>Egypt</td><td>29.670</td><td>32.281</td><td>x</td><td></td><td>x</td><td></td><td></td><td></td></tr><tr><td>86</td><td>Cairo</td><td>Egypt</td><td>30.107</td><td>31.233</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr></tbody></table>
<caption>Table A1</caption>

Continued

<table><thead><tr><th></th><th>Name</th><th>Country</th><th>Lat</th><th>Lon</th><th>Ch</th><th>Co</th><th>Me</th><th>Ur</th><th>Ph</th><th>Un</th></tr></thead><tbody><tr><td>87</td><td>Mansoura</td><td>Egypt</td><td>31.063</td><td>31.373</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>88</td><td>Malabo</td><td>Equ. Guinea</td><td>3.780</td><td>8.712</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>89</td><td>Bremen Harbor</td><td>Germany</td><td>53.103</td><td>8.758</td><td></td><td></td><td>x</td><td>x</td><td></td><td></td></tr><tr><td>90</td><td>Ankleshwar</td><td>India</td><td>21.598</td><td>73.015</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>91</td><td>Avashi</td><td>India</td><td>17.620</td><td>73.463</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>92</td><td>Birwadi</td><td>India</td><td>18.131</td><td>73.500</td><td>x</td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>93</td><td>Jawaharlal Nehru</td><td>India</td><td>17.659</td><td>83.079</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>94</td><td>Khopoli</td><td>India</td><td>18.827</td><td>73.241</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>95</td><td>Kistaipally</td><td>India</td><td>17.577</td><td>78.355</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>96</td><td>Taloja</td><td>India</td><td>19.134</td><td>73.195</td><td>x</td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>97</td><td>Bontang</td><td>Indonesia</td><td>0.147</td><td>117.468</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>98</td><td>Jakarta</td><td>Indonesia</td><td>-6.239</td><td>106.948</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>99</td><td>Medan</td><td>Indonesia</td><td>3.617</td><td>98.642</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>100</td><td>Palembang</td><td>Indonesia</td><td>-2.964</td><td>104.780</td><td>x</td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>101</td><td>Surabaya</td><td>Indonesia</td><td>-7.275</td><td>112.679</td><td>x</td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>102</td><td>Asalouyeh</td><td>Iran</td><td>27.560</td><td>52.542</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>103</td><td>Bojnurd</td><td>Iran</td><td>37.546</td><td>57.509</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>104</td><td>Mamaqan</td><td>Iran</td><td>37.877</td><td>45.928</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>105</td><td>Marvdatsh</td><td>Iran</td><td>29.846</td><td>52.725</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>106</td><td>Tabriz</td><td>Iran</td><td>38.061</td><td>46.221</td><td>x</td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>107</td><td>Tehran</td><td>Iran</td><td>35.639</td><td>51.350</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>108</td><td>Urmia</td><td>Iran</td><td>37.376</td><td>45.245</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>109</td><td>Asahikawa</td><td>Japan</td><td>43.760</td><td>142.368</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>110</td><td>Hirosaki</td><td>Japan</td><td>40.639</td><td>140.475</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>111</td><td>Nagoya</td><td>Japan</td><td>35.244</td><td>136.864</td><td>x</td><td></td><td>x</td><td>x</td><td></td><td></td></tr><tr><td>112</td><td>Osaka</td><td>Japan</td><td>34.551</td><td>135.452</td><td>x</td><td></td><td>x</td><td>x</td><td></td><td></td></tr><tr><td>113</td><td>Sapporo</td><td>Japan</td><td>43.105</td><td>141.313</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>114</td><td>Tokyo/Yokohama</td><td>Japan</td><td>35.760</td><td>139.788</td><td>x</td><td></td><td>x</td><td>x</td><td></td><td></td></tr><tr><td>115</td><td>Kuala Lumpur</td><td>Malaysia</td><td>3.074</td><td>101.478</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>116</td><td>Kuching</td><td>Malaysia</td><td>1.548</td><td>110.388</td><td></td><td></td><td></td><td></td><td></td><td>x</td></tr><tr><td>117</td><td>Ciudad Juarez</td><td>Mexico</td><td>31.662</td><td>-106.394</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>118</td><td>Mexico City</td><td>Mexico</td><td>19.459</td><td>-99.105</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>119</td><td>Monterrey</td><td>Mexico</td><td>25.760</td><td>-100.289</td><td></td><td></td><td>x</td><td>x</td><td></td><td></td></tr><tr><td>120</td><td>Torreon</td><td>Mexico</td><td>25.672</td><td>-103.456</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>121</td><td>Benin City</td><td>Nigeria</td><td>6.292</td><td>5.620</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>122</td><td>Ibadan</td><td>Nigeria</td><td>7.397</td><td>3.939</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>123</td><td>Lagos</td><td>Nigeria</td><td>6.559</td><td>3.295</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>124</td><td>Port Harcourt</td><td>Nigeria</td><td>4.772</td><td>7.039</td><td>x</td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>125</td><td>Sohar Port</td><td>Oman</td><td>24.451</td><td>56.610</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>126</td><td>Karachi</td><td>Pakistan</td><td>24.869</td><td>67.310</td><td>x</td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>127</td><td>Manila</td><td>Philippines</td><td>14.619</td><td>121.081</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>128</td><td>Krasnoyarsk</td><td>Russia</td><td>56.064</td><td>92.954</td><td></td><td></td><td></td><td></td><td></td><td>x</td></tr><tr><td>129</td><td>Novomoskovsk</td><td>Russia</td><td>54.063</td><td>38.188</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<caption>Table A1</caption>

Continued

<table><thead><tr><th></th><th>Name</th><th>Country</th><th>Lat</th><th>Lon</th><th>Ch</th><th>Co</th><th>Me</th><th>Ur</th><th>Ph</th><th>Un</th></tr></thead><tbody><tr><td>130</td><td>Salavat</td><td>Russia</td><td>53.382</td><td>55.838</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>131</td><td>St-Petersburg</td><td>Russia</td><td>59.855</td><td>30.399</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>132</td><td>Tolyatti</td><td>Russia</td><td>53.553</td><td>49.596</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>133</td><td>Al Jubail</td><td>Saudi Arabia</td><td>27.057</td><td>49.552</td><td>x</td><td></td><td>x</td><td></td><td></td><td></td></tr><tr><td>134</td><td>Jeddah</td><td>Saudi Arabia</td><td>21.429</td><td>39.215</td><td></td><td></td><td></td><td></td><td></td><td>x</td></tr><tr><td>135</td><td>Riyadh</td><td>Saudi Arabia</td><td>24.593</td><td>46.794</td><td></td><td></td><td></td><td>x</td><td></td><td></td></tr><tr><td>136</td><td>Secunda</td><td>South Africa</td><td>-26.571</td><td>29.164</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>137</td><td>Daegu</td><td>South Korea</td><td>35.876</td><td>128.526</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>138</td><td>Gunsan/Jeonju</td><td>South Korea</td><td>35.899</td><td>126.896</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>139</td><td>Incheon</td><td>South Korea</td><td>37.462</td><td>126.714</td><td>x</td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>140</td><td>Kaohsiung City</td><td>Taiwan</td><td>22.582</td><td>120.470</td><td>x</td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>141</td><td>Taichung City</td><td>Taiwan</td><td>24.129</td><td>120.610</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>142</td><td>Taipei</td><td>Taiwan</td><td>25.017</td><td>121.430</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>143</td><td>Ho Chi Minh City</td><td>Thailand</td><td>10.883</td><td>106.676</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>144</td><td>Augusta</td><td>USA</td><td>33.457</td><td>-81.980</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>145</td><td>Baltimore</td><td>USA</td><td>39.300</td><td>-76.554</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>146</td><td>Boston</td><td>USA</td><td>42.371</td><td>-71.148</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>147</td><td>Columbus</td><td>USA</td><td>39.963</td><td>-83.007</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>148</td><td>Detroit</td><td>USA</td><td>42.334</td><td>-83.296</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>149</td><td>Kingsport</td><td>USA</td><td>36.491</td><td>-82.491</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>150</td><td>New York</td><td>USA</td><td>40.734</td><td>-73.973</td><td>x</td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>151</td><td>Norfolk</td><td>USA</td><td>36.805</td><td>-76.240</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>152</td><td>Philadelphia</td><td>USA</td><td>39.926</td><td>-75.168</td><td>x</td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>153</td><td>Pittsburgh</td><td>USA</td><td>40.415</td><td>-79.919</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>154</td><td>Fergana</td><td>Uzbekistan</td><td>40.440</td><td>71.847</td><td>x</td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>155</td><td>Navoi</td><td>Uzbekistan</td><td>40.077</td><td>65.322</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>156</td><td>Tashkent</td><td>Uzbekistan</td><td>41.288</td><td>69.235</td><td></td><td></td><td></td><td></td><td>x</td><td></td></tr><tr><td>157</td><td>Barcelona</td><td>Venezuela</td><td>10.075</td><td>-64.772</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

Note. The categories are abbreviated as Ch for the chemical and petrochemical industry, Co for the coal-related industry, Me for metallurgy, Ur for urban, Ph for the pharmaceutical industry, and Un for undetermined.
<table><caption>**Table A2**
A Catalog of C₂H₂ Point Sources, With Identified Potential Emitters</caption><thead><tr><th></th><th>Name</th><th>Country</th><th>Lat</th><th>Lon</th><th>Ch</th><th>Co</th><th>Me</th><th>Ur</th><th>Ph</th><th>Un</th></tr></thead><tbody><tr><td>1</td><td>Baotou</td><td>China</td><td>40.612</td><td>109.735</td><td>x</td><td>x</td><td>x</td><td></td><td></td><td></td></tr><tr><td>2</td><td>Changzhi</td><td>China</td><td>36.467</td><td>113.008</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>3</td><td>Dalad Banner</td><td>China</td><td>40.359</td><td>109.972</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>4</td><td>Datong County</td><td>China</td><td>36.871</td><td>101.747</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>5</td><td>Hohhot</td><td>China</td><td>40.737</td><td>111.428</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>6</td><td>Huangzhong District</td><td>China</td><td>36.492</td><td>101.535</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>7</td><td>Jinjie Park</td><td>China</td><td>38.703</td><td>110.186</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>8</td><td>Mengxi Park</td><td>China</td><td>39.912</td><td>106.800</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>9</td><td>Shihezi</td><td>China</td><td>44.361</td><td>86.032</td><td>x</td><td>x</td><td>x</td><td></td><td></td><td></td></tr><tr><td>10</td><td>Shizuishan</td><td>China</td><td>38.940</td><td>106.429</td><td>x</td><td>x</td><td>x</td><td></td><td></td><td></td></tr><tr><td>11</td><td>Urumqi</td><td>China</td><td>44.008</td><td>87.737</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>12</td><td>Wuhai</td><td>China</td><td>39.372</td><td>106.726</td><td>x</td><td>x</td><td>x</td><td></td><td></td><td></td></tr><tr><td>13</td><td>Xiliangcun</td><td>China</td><td>41.040</td><td>112.125</td><td></td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>14</td><td>Xining</td><td>China</td><td>36.639</td><td>101.692</td><td>x</td><td></td><td>x</td><td></td><td></td><td></td></tr><tr><td>15</td><td>Yushe County</td><td>China</td><td>37.015</td><td>112.899</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>16</td><td>Zhangjiakou</td><td>China</td><td>40.747</td><td>114.923</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr></tbody></table>

*Note.* The categories are abbreviated as Ch for the chemical and petrochemical industry, Co for the coal-related industry, Me for metallurgy, Ur for urban, Ph for the pharmaceutical industry, and Un for undetermined.

<table><caption>**Table A3**
A Catalog of C₃H₆ Point Sources, With Identified Potential Emitters</caption><thead><tr><th></th><th>Name</th><th>Country</th><th>Lat</th><th>Lon</th><th>Ch</th><th>Co</th><th>Me</th><th>Ur</th><th>Ph</th><th>Un</th></tr></thead><tbody><tr><td>1</td><td>Fangshan District</td><td>China</td><td>39.732</td><td>115.905</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>2</td><td>Ningdong base</td><td>China</td><td>38.181</td><td>106.621</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr><tr><td>3</td><td>Rabigh</td><td>Saudi Arabia</td><td>22.701</td><td>39.019</td><td>x</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>4</td><td>Secunda</td><td>South Africa</td><td>-26.564</td><td>29.168</td><td>x</td><td>x</td><td></td><td></td><td></td><td></td></tr></tbody></table>

*Note.* The categories are abbreviated as Ch for the chemical and petrochemical industry, Co for the coal-related industry, Me for metallurgy, Ur for urban, Ph for the pharmaceutical industry, and Un for undetermined.

## Data Availability Statement

The supersampled IASI distributions of CH₃OH, C₂H₂, C₃H₆, and SO₂ generated and analyzed in this study (Franco, Clarisse, & Coheur, 2024) have been deposited in the Zenodo database (https://doi.org/10.5281/zenodo.12723194). The supersampled IASI C₂H₄ HRI data set (Franco et al., 2022a) is available from the Zenodo database (https://doi.org/10.5281/zenodo.7085725). The IASI NH₃ VCD product can be obtained from the AERIS data infrastructure: IASI/Metop-A (https://doi.org/10.25326/12; Clarisse, Van Damme et al., 2023a), IASI/Metop-B (https://doi.org/10.25326/13; Clarisse, Van Damme et al., 2023b), and IASI/Metop-C (https://doi.org/10.25326/500; Clarisse, Van Damme et al., 2023c). The codes of the oversampling, wind rotation, and supersampling used in this work (Clarisse, Van Damme et al., 2019a) are available at https://squares.ulb.be/NH3-IASI.html.
Acknowledgments

This research has been supported by the World Emission project (https://www.world-emission.com/) funded by the European Space Agency (contract No. 4000137291/22/I-EF). Activities at ULB have also been supported by the HIRS Prodex arrangement (ESA-BELSPO) and the Spheres project funded under the Actions de Recherche Concertées (ARC) from the French Community (Belgium). L.C. is research associate supported by the F.R.S.-FNRS. The French scientists are grateful to CNES and Centre National de la Recherche Scientifique (CNRS) for financial support. The authors thank Raphaëlle De Cruyenaere for the preliminary analysis of the IASI data in the framework of her master's thesis.

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