# Chemical characterization of volatile organic compounds emitted by animal manure

K.M. Haider, C. Focsa, Céline Décuq, B. Esnault, Florence Lafouge, Benjamin

Loubet, D. Petitprez, R. Ciuraru

► To cite this version:

K.M. Haider, C. Focsa, Céline Décuq, B. Esnault, Florence Lafouge, et al.. Chemical characterization of volatile organic compounds emitted by animal manure. Journal of Environmental Management, 2024, 364, pp.121453. 10.1016/j.jenvman.2024.121453. hal-04676540

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Research article

# Chemical characterization of volatile organic compounds emitted by animal manure

K.M. Haider<sup>a, b</sup>, C. Focsa<sup>a</sup>, C. Decuq<sup>b</sup>, B. Esnault<sup>b</sup>, F. Lafouge<sup>b</sup>, B. Loubet<sup>b</sup>, D. Petitprez<sup>c</sup>, R. Ciuraru<sup>b, *</sup>

<figure><img src="image_3.png" /></figure>

## ARTICLE INFO

Handling editor: Lixiao Zhang

**Keywords:**

Volatile organic compounds

Manure emissions

Laboratory chamber experiments

Proton transfer reaction mass spectrometry

Gas chromatography

## ABSTRACT

Animal manure is considered a valuable organic fertilizer due to its important nutrient content enhancing soil fertility and plant growth in agriculture. Besides its beneficial role as fertilizer, animal manure represents a significant source of volatile organic compounds (VOCs), playing a significant role in atmospheric chemistry. Understanding the composition of VOCs from animal manure is crucial for assessing their environmental impact, as they can cause air pollution, odors, and harm to human health and ecosystems. Laboratory studies enhance field measurements by providing a precise inventory of manure emissions, addressing gaps in existing literature. Both approaches complement each other in advancing our understanding of manure emissions. In this context, we conducted an experimental study involving various animal manures (cow, horse, sheep, and goat) taken from a farm in Grignon (near Paris, France). We employed atmospheric simulation chambers within a controlled laboratory environment. The analysis of VOCs involved the combination of Proton Transfer Reaction-Quadrupole ion guide-Time-of-Flight Mass Spectrometry (PTR-QiTOF-MS) and Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS). Using PTR-QiTOF-MS, 368 compounds were detected and quantified within the manure samples. The complementary analysis by TD-GC-MS enhanced our identification of VOCs. Our findings revealed various chemical groups of VOCs, including oxygenated compounds (e.g., ethanol, cresol, acetaldehyde, etc.), nitrogenated compounds (ammonia, trimethylamine, etc.), sulfur compounds (methanethiol, dimethyl sulfide, etc.), aromatic compounds (phenols and indoles), terpenes (isoprene, D-limonene, etc.) and halogenated compounds. Cow manure exhibited the highest VOC emission fluxes, followed by goat, sheep, and horse manures. Notably, oxygenated VOCs were dominant contributors to total VOC emission fluxes in all samples. Statistical analysis highlighted the distinct nature of cow manure emissions, characterized by oxygenated compounds and nitrogenated compounds. In addition, goat manure was isolated from the other samples with high emissions of compounds having both oxygen and nitrogen atoms in their molecular formulas (e.g., CH<sub>3</sub>NO<sub>2</sub>). The experimental dataset obtained in this study provides an inventory reference for both VOCs and their emission fluxes in animal manures. Furthermore, it highlights odorant compounds and VOCs that serve as atmospheric aerosol precursor. Future studies can explore the effectiveness of various manure treatment methods to promote sustainable agriculture practices.

## 1. Introduction

Animal manures are the solid, semisolid, and liquid waste products produced by animal raised to produce milk, eggs, meat, and other agricultural products for human use and consumption. Animals also produce large amounts of animal manure through digestion and metabolism (Williams, 1995). According to the Food and Agriculture

Organization of the United Nations (FAO), the world's total emissions of animal manure were 9.26 × 10<sup>9</sup> t in 2022. The large amounts of animal manure are returned to the field either directly or in the form of manure-based fertilizers (Qian et al., 2016). Today, manure is considered a valuable organic fertilizer due to its important nutrient content, including nitrogen, phosphorous, and potassium, which enhances soil fertility and supports plant growth in agriculture when appropriately

<footnote><sup>a</sup> Univ. Lille, CNRS, UMR 8523 - PhLAM - Physique des Lasers, Atomes et Molécules, Lille, F-59000, France</footnote>

<footnote><sup>b</sup> Université Paris-Saclay, INRAE, AgroParisTech, UMR EcoSys, 91120, Palaiseau, France</footnote>

<footnote><sup>c</sup> Univ.Lille, CNRS, UMR 8522 – PC2A – PhysicoChimie des Processus de Combustion et de l'Atmosphère, Lille, F-59000, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail addresses: kawssar-mujtaba.haider@univ-lille.fr (K.M. Haider), raluca.ciuraru@inrae.fr (R. Ciuraru).</footnote>
handled (Liu et al., 2018; Shober and Maguire, 2018). Besides its beneficial role as fertilizer, animal manure has been viewed as a pollutant and a source of nuisance due to the intensive animal production and diversity in its composition (Williams, 1995).

Environmental pollution caused by animal manure has become a worldwide issue, particularly in regions with high livestock populations, but insufficient land for proper manure management. Spreading animal manure on land releases a variety of complex pollutants, including dust, bacteria, mold, endotoxins, greenhouse gases (GHG), ammonia, and particulate matter (PM), all of which can impact air quality both locally and regionally (Woodbury et al., 2014). Methane and nitrogen oxides (NOx) are primary byproducts of manure breakdown, with methane significantly contributing to GHG accumulation in the troposphere (Chadwick et al., 2011). Additionally, livestock is a substantial source of carbon dioxide (CO2) (Hempel et al., 2016) and NH3 (Schmithausen et al., 2018; Yao et al., 2018). According to Zhang et al. (2017), global manure nitrogen production is projected to rise due to increasing livestock populations, greatly affecting the GHG balance in terrestrial ecosystems. In Europe, agriculture accounts for over 81% of global ammonia emissions, with animal manure being the primary source (Wyer et al., 2022). Ammonia emissions from farming activities have become a public concern due to their health impacts and their role in acidifying natural environments and forming atmospheric aerosols (Atkinson, 2000; Kammer et al., 2020).

Anaerobic digestion systems have been widely used for treating livestock manure due to their advantages in being able to process large volumes of raw materials, their simplicity, and generation of renewable energy (Delfino et al., 2003). Moreover, the anaerobic digestion of animal manure prior to its utilization as fertilizer has beneficial effects. This process results in digestate with increased concentrations of mineralized nutrients that are readily available for plant uptake compared to untreated manure (Orzi et al., 2018). Moreover, digestion results in a significant odor reduction, as reviewed by Insam et al. (2015). However, the substantial volume of biogas digestate produced during biogas is typically stored before its land application, which makes it a significant source of pollutant gases (Giannadaki et al., 2018; Salazar Gómez et al., 2016). The significance of GHG (i.e., methane and nitrous oxide), ammonia, and hydrogen sulfide emissions from livestock has been well recognized and studied (Cai et al., 2006; Filipy et al., 2006; Wang et al., 2017, 2018). Manure nutrient contents and emissions are affected by the type of housing, timing of manure removal, storage conditions and storage duration and manure management systems (Higgins et al., 2003). For instance, a new study has demonstrated that composting dairy manure with biochar significantly reduces methane emissions by 58% and mitigates air pollutants such as hydrogen sulfide (H2S), volatile organic compounds (VOCs), and nitrogen oxides (NOx) by approximately 67%, 61%, and 70%, respectively. The findings of this study suggest that biochar composting not only aids in meeting climate goals but also has the potential to enhance air quality and mitigate health risks in rural areas. However, future research is needed to quantify these effects (Harrison et al., 2024).

Recently, there has been a significant concern about the odorous gases emitted from manure, driven by the growing number of animal farms (Woodbury et al., 2014). The odorant emissions consist of a complex mixture of VOCs and H2S, which adversely affect air quality and pose health risks (Woodbury et al., 2014; Ciganek and Neca, 2008; Feilberg et al., 2010). The primary source of odorant VOC emissions is attributed to the incomplete anaerobic fermentation of the wastes by bacteria (Mackie et al., 1998). High concentrations of VOCs can lead to undesirable reactions and even toxicity in individuals if they surpass a certain threshold (Cunha et al., 2016). Additionally, VOCs serve as essential precursors in atmospheric photochemistry, with certain compounds significantly contributing to the formation and production of atmospheric pollutants such as ozone and secondary organic aerosols (SOA) (Toro et al., 2006; Ciuraru et al., 2021; Zheng et al., 2009; Ziemann and Atkinson, 2012). Most research on VOCs primarily focuses on

areas such as petrochemical processes, solvent and paint utilization, fuel combustion, waste management, and other industries or fields (Zheng et al., 2009; Guo et al., 2017; Klimont et al., 2002; Wei et al., 2008). Studies investigating VOC emissions from animal husbandry mainly focus on farm buildings and the management of manure (Cai et al., 2006; Blunden et al., 2005; Ni et al., 2012; Shaw et al., 2007; Trabue et al., 2010). A recent study sought to assess the influence of animal diet on VOC emissions and the odor generated from swine manure (Choi et al., 2024). In this work, three types of feed were evaluated, focusing on complex odor, ammonia, sulfur-based odors, and VOCs. Results showed that low-calorie pellet-type feed led to a decrease in complex odor and ammonia levels over time, with a shift in odorous substances from ammonia and sulfur compounds to VOCs. This demonstrated the impact of feed operations on odor and VOC emissions from swine manure (Choi et al., 2024).

Various technologies have been developed and implemented to improve the efficiency of VOC sampling and measurement. For a thorough evaluation of VOCs, it is advisable to utilize a combination of online techniques, such as PTR-MS, and offline methods, like GC-MS (Ni et al., 2012). This combination enables the quantitative and qualitative analysis to be carried out in a much less time-consuming way that in the case of using one analytical technique. The GC-MS and PTR-MS methods complement each other for two main reasons. Firstly, PTR-MS lacks the capability to separate chemical compounds as effectively as GC-MS. Additionally, PTR-MS predominantly identifies analytes based on the protonated molecule mass, often without complete fragmentation, leading to unclear chemical structure determination. Hence, preliminary tests often require GC-MS to ensure correct compound identification. It is advisable to use PTR-MS alongside GC-MS for quantitative analysis during research (Majchrzak et al., 2018).

Using the combination of online and offline methods, VOC emissions from intensive pig production have been investigated. However, the range of identified compounds was restricted, mainly attributed to the use of quadrupole PTR-MS (Feilberg et al., 2010). A comprehensive list of VOCs has been suggested in a few studies (Ciganek and Neca, 2008; Schiffman et al., 2001; Yuan et al., 2017); though research on VOC emission fluxes and factors from animal manure samples under controlled laboratory conditions is still limited. The identified VOCs belong to six major chemical groups: volatile fatty acids, volatile amines, indoles, phenols, and sulfur compounds (Woodbury et al., 2014, 2022; Feilberg et al., 2010, 2011). The dominant odorous sulfide compounds such as dimethyl sulfide, dimethyl disulfide, dimethyl trisulfide, methyl sulfide, etc., were reported in Shaw et al. and Tanlong et al. (Shaw et al., 2007; Tanlong et al., 2017) studies. Most of the reported studies have focused on pig, dairy, or poultry farming, leaving a notable gap in our understanding of VOC emissions from other types of livestock. Ni et al. (2012) reviewed 100 studies on VOC emissions at swine facilities, while only three studies have examined VOC emissions from sheep farming (Kammer et al., 2020; Yuan et al., 2017; Ngwabie et al., 2007). Studies on ambient VOCs in livestock facilities have revealed that oxygenated hydrocarbons are the predominant VOCs (Blunden et al., 2005; Shaw et al., 2007; Trabue et al., 2010). Trabue et al. (2010) identified acetic acid, 2,3-butanedione, methanol, acetone, and ethanol as the top five VOC components, constituting 70% of the total VOCs (TVOCs) on poultry farms. Blunden et al. (2005) observed that the oxygenated hydrocarbons, i.e., ethanol, methanol, acetaldehyde, and acetone, accounted for 37%–73% of the TVOCs observed in pig houses. Shaw et al. (2007) found that methanol, acetaldehyde, acetone, propylaldehyde, and dimethyl sulfide are the dominant VOC compounds for dairy. Therefore, the most common VOCs in the air of livestock and poultry farms are alcohols (i.e., methanol, ethanol, etc.), ketones (i.e., acetone, 2,3-butanedione, etc.), and aldehydes (i.e., acetaldehyde, etc.).

More than 400 VOCs were characterized in a field campaign using a combination of online and offline mass spectrometric techniques (Kammer et al., 2020). This campaign was conducted at the same farm where we collected our samples, located in Grignon, France,
approximately 35 km west of Paris. The findings indicated that more VOCs were emitted from the dairy stable compared with the sheep pens, with the highest emissions being oxygenated compounds and hydrocarbons. The authors identified specific emission tracers for each type of pen and used correlation analysis to pinpoint the sources of VOC emissions (Kammer et al., 2020). This study estimated the emission rates of ammonia and VOCs using a CO₂ mass balance model, marking the first evaluation of the emission rates for most of the identified VOCs. The dataset obtained in this study enhances emissions inventories for agricultural activities (Kammer et al., 2020).

Thorough laboratory investigations are essential for examining emission fluxes under controlled conditions and acquiring qualitative and quantitative data on VOC emissions from animal manure. Detailed chemical analysis is required to evaluate appropriate odor reduction technologies and to explore the atmospheric reactivity of VOCs. In recent years, significant progress has been achieved in understanding VOC emissions from livestock production. However, there remains a significant gap in research concerning VOC emissions from organic waste products of livestock origin such as animal manure. The need for laboratory studies in complement to field measurements, as conducted by Kammer et al. (2020), enables a precise inventory of manure emissions and is emphasized by the limited existing literature in this domain. Laboratory studies and field measurements thus play complementary roles in advancing our understanding of manure emissions.

In this study, we conducted an experimental investigation involving various animal manure samples, including those from cows, horses, sheep, and goats. Our objective was to compile a comprehensive inventory of the VOCs emitted by these samples. The laboratory study aimed to examine, identify, and quantify the VOCs released by the different manure types. To achieve this, we employed atmospheric simulation chambers within a controlled laboratory environment. The analysis of VOCs involved the combination of online techniques, specifically Proton Transfer Reaction-Quadrupole ion guide-Time-of-Flight Mass Spectrometry (PTR-QiTOF-MS), as well as offline methods, including Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS), to explore the chemical composition of the emitted VOCs.

## 2. Materials and methods

Four animal manure samples (horse, cow, sheep, and goat manures) collected from a farm situated in Grignon, France (35 km west of Paris, 48°50′28.89″ N, 1°56′56.03″ E, altitude: 131 m above sea level) were analyzed (refer to Supporting Materials: Detailed Contextual Information on Farm and Animal Characteristics). The samples were stored at 4 °C before the experiments. The experimental setup used in this study is described in Haider et al. (2022) and represented in Fig. S1. The experiments were conducted in temperature-controlled chambers made of poly(methyl methacrylate) with Teflon walls. In this work, we used the two chambers of volume 0.03 m³ and 0.18 m³. Each sample underwent three replicates. Two of the experiments were conducted in a 0.18 m³ chamber, with 1 kg of sample evenly distributed over a 0.32 m² surface area. The third experiment took place in a 0.03 m³ chamber, with 500 g of sample spread over a 0.14 m² surface area. The sample thickness was maintained at 3–4 mm. The experiments were performed using the same protocol detailed in Haider et al. (2022). The emitted VOCs were analyzed in real-time using PTR-QiTOF-MS and were simultaneously captured onto Tenax TA cartridges at a flow rate of 0.5 L per minute for 60–90 min. Subsequently, offline analyses were conducted using TD-GC-MS. In parallel to these experiments, blank tests were performed without samples to verify and avoid chamber contamination. The concentrations of SO₂ (measured with model 43C, Thermo Environmental Instruments), NH₃ (measured with Picarro G2103), and the relative humidity (RH) were monitored, and the findings are outlined in Table S1.

In this study, we used standard drift tube conditions (4 mbar and 80 °C) employing a drift voltage of 1000 V, resulting in an E/N value of

132 Td to operate the PTR-QiTOF-MS measurements. The raw data obtained from PTR-QiTOF-MS were processed using the methodology outlined in Haider et al. (2022). peak list with a signal-to-noise ratio (S/N) > 3.0 was generated using the mMass software (Strohalm et al., 2010). The mass-to-charge range selected for analysis was between m/z 31 and 400. Signals attributed to instrumental background or water clusters, such as m/z 37.03, m/z 38.03, m/z 39.03, and m/z 55.03, were excluded from the analysis. The PTR viewer 3.2.12 software (Ionicon analytik GmbH) was used to identify the chemical molecular formula that corresponds to each protonated molecular ion in the peak lists, following the procedure outlined in Haider et al. (2022). Subsequently, the averaged mass spectra were used to compute the average mass concentration and emission flux of the emitted compounds (Haider et al., 2022).

The emitted VOCs were collected on Tenax TA cartridges for approximately 60–90 min at a pumping flow of 0.5 L per minute, regulated by a mass flow controller (Bronkhorst). Before the experiment, the tubes were pre-conditioned by heating at 280 °C under a helium flow of 60 mL min⁻¹ for 6 h. Following sampling, the cartridges were stored in the dark at 4 °C until their analysis. After sampling, the cartridges were stored in darkness at 4 °C until analysis. Subsequently, the extraction step was processed using a thermo-desorption unit (Thermal Desorption Unit, TDU, Gerstel) where the tubes were desorbed from 50 °C to 280 °C at a rate of 60 °C min⁻¹ and then held at 280 °C for 6 min. VOCs were cryo-focused in the Programmable Temperature Vaporization (PTV) at 5 °C using a Tenax liner. The separation of VOCs was performed using an Agilent 7890B gas chromatograph equipped with a capillary column of 60 m length, 0.25 mm internal diameter, and 1 µm film thickness. The oven temperature was initially set at 40 °C for 5 min and then increased to 60 °C at a rate of 11 °C min⁻¹. Helium was utilized as the carrier gas. VOC detection was conducted using an Agilent 5977A mass spectrometric detector. The electron impact (EI) mode was set at +70 eV, and monitoring was performed from m/z 20 to 470. The ion source and quadrupole analyzer temperatures were set at 230 °C and 150 °C, respectively. TD-GC-MS data were processed using Mass-Hunter (B.April 07, 5560) software from Agilent Technologies Inc. Unknown Analysis (B.06.00) module was used to carry on the automatic peak detection and mass spectrum deconvolution. Each compound was identified by deconvoluted peaks, and the mass spectrum of the deconvoluted compounds was reconstructed and compared to the NIST (National Institute of Standards and Technology, 2011) mass spectra database for identification. The minimum required match factor between the observed and reference mass spectra was 70%. Each compound was then manually verified to confirm the proposed formula.

Double bond equivalent (DBE) analysis was performed on the hydrocarbons emitted from all samples in this work, following the methodology detailed in (Haider et al., 2022). Principal component analysis (PCA) was used to compare the PTR-QiTOF mass spectra. Statistical analysis of the emitted VOCs was undertaken to identify the chemical compounds that differentiate between the samples. PCA was performed with a matrix containing the integrated peak areas (i.e. variables) against the mass spectra (i.e. observations) using Python (Haider et al., 2022).

## 3. Results

### 3.1. Detection of VOCs by PTR-QiTOF-MS

A dataset comprising gas-phase emissions over time was acquired for each type of manure using PTR-QiTOF-MS. An example of the PTR-QiTOF mass spectrum for each sample is depicted in Fig. S2. The majority of the detected peaks (>90%) were attributed to appropriate molecular formulas, with an average mass uncertainty of assignments ranging between 13 and 29 ppm. Only a few peaks remained unassigned, as detailed in Table S2. As an example, the peak list associated with cow manure comprised 255 mass peaks. Out of these, 233 peaks were
successfully assigned. The assigned ionic peaks were attributed to either a VOC (224 VOCs) or its ¹³C isotopic peak (9 peaks). For cow manure, only 22 mass peaks were not assigned to a molecular formula and were categorized as unknown compounds. The identification of certain detected ions using PTR-QiTOF-MS relied on TD-GC-MS measurements conducted for each sample, along with existing knowledge on emissions from manure samples and livestock production available in the literature. The respective total number of assigned VOCs in cow, horse, goat, and sheep manures were **224, 233, 254**, and **257**. Further data analysis, including chemical classification, quantification, and statistical analysis, exclusively considered these assigned VOCs. For a comprehensive list of these assigned VOCs in each sample, refer to https://doi.org/10.57745/PGB2SY.

In this work, **368** compounds were detected and quantified in all samples using PTR-QiTOF-MS, with **115** compounds commonly found in all samples (refer to https://doi.org/10.57745/PGB2SY). From PTR-MS analysis, sheep manure exhibited the highest number of VOCs among all samples, with a total of 257, followed by a goat (254), horse (233), and cow manure (224).

The VOCs detected by PTR-QiTOF-MS were classified into distinct chemical groups: hydrocarbons (HC), nitrogenated compounds (N-compounds), oxygenated compounds (O-compounds), halogenated compounds (containing at least one halogen atom), sulfur compounds (S-compounds), and others (containing different heteroatoms in their molecular formula). The number of compounds assigned to each chemical group is illustrated in Fig. 1. The distribution of these chemical families of VOCs varied among the analyzed samples. Oxygenated compounds (OVOCs) emerged as the dominant class in all samples, with sheep manure exhibiting the maximum number of emitted OVOCs (90), followed by goat, horse, and cow manure, respectively. The number of assigned HC was relatively consistent across all samples. Goat manure showed the highest number of N-compounds, while cow manure exhibited the maximum number of S-compounds. A few halogenated compounds were also found, accounting for less than 1% of the assigned molecular formulas.

## 3.2. Identification of VOCs by TD-GC-MS

An example of a gas chromatogram got from TD-GC-MS analysis of all manure samples is illustrated in Fig. S3. The list of identified compounds (417) in all samples is given in https://doi.org/10.57745/PGB2SY. Using offline measurements, the identification of VOCs was based on the deconvolution step, and then the spectra were compared to the NIST spectra database. The total number of compounds identified in cow, horse, goat, and sheep manures were 307, 290, 300, and 304, respectively.

Through a combination of online and offline measurements, compounds exclusively emitted by a particular sample represent its emission tracers. The list of emission tracers for each sample identified by either

PTR-Qi-TOF-MS or TD-GC-MS or both is presented in https://doi.org/10.57745/PGB2SY. The number of emission tracers for cow, sheep, horse, and goat was 79, 64, 55, and 35, respectively.

Compounds identified in each sample using TD-GC-MS were categorized based on their chemical group, Fig. 2. The chemical groups of compounds obtained using the PTR-Qi-TOF-MS technique exhibited similar patterns in the TD-GC-MS analysis. OVOCs predominated among the identified compounds in all samples, including alcohols, ketones, aldehydes, carboxylic acids, esters, etc. Moreover, a comparable number of HC were identified in horse, goat, and sheep manures, with the lowest observed in cow manure.

## 3.3. Comparison of online and offline results

The gas phase was analyzed using both PTR-QiTOF-MS and TD-GC-MS. The TD-GC-MS data primarily aided in assigning ions detected in PTR-QiTOF-MS to specific compounds and provided additional chemical identification of the VOCs. This combination enables both quantitative and qualitative analysis of manure VOC composition. In this work, PTR-MS provides real-time analysis of VOC emissions from manure samples without sample preparation. It also offers high sensitivity but limited separation capability, in contrast to GC-MS, which separates complex mixtures based on volatility and offers high specificity and compound identification.

The comparison of online and offline techniques resulted in a comprehensive list of 631 molecular formulas, as detailed in https://doi.org/10.57745/PGB2SY. Kammer et al. (2020) conducted a field measurement study at the same farm in Grignon from which our samples originated. Consequently, it is noteworthy to compare the field measurements conducted by Kammer et al. (2020) with the laboratory measurements from our study, and this comparative analysis is presented in https://doi.org/10.57745/PGB2SY. The number of detected molecules in both techniques is given in Table 1. For example, 70 out of the 224 assigned molecular formulas for cow manure emissions were also identified through TD-GC-MS analysis. Overall, 26% of the VOCs detected by PTR-MS were also identified by GC-MS. This underlines the consistency of the identification process, considering that these measurement techniques are independent. Our findings are noteworthy when compared to a similar study conducted for field measurements (13% overlap) by Kammer et al. (2020).

The TD-GC-MS method proves valuable in identifying isomeric compounds, contributing to a greater number of identified compounds compared to the assigned molecular formulas. Therefore, certain molecular formulas assigned with the PTR-QiTOF-MS corresponded to multiple compounds. For instance, the protonated ion corresponding to *m/z* 127.112 was assigned to the emission of C₈H₁₄OH⁺ using PTR-QiTOF-MS, while the TD-GC-MS analysis revealed the identification of 4 isomers for the C₈H₁₄O formula (6-methyl-5-hepten-2-one, 2,2,5-trimethyl-cyclopentanone, 2-methyl-cycloheptanone and 3-methyl-3-

<figure><img src="image_4.png" /><figcaption>**Fig. 1.** The number of compounds assigned for each chemical group in each sample using PTR-QiTOF-MS, along with the total number of assigned VOCs, is provided in parentheses.</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Fig. 2. The distribution of compounds identified via TD-GC-MS across chemical groups, along with the total number of identified compounds in parentheses.</figcaption></figure>

<caption>**Table 1**</caption>

Comparison between PTR-QiTOF-MS and TD-GC-MS techniques showing the number of common formulas detected by both techniques.

<table><thead><tr><th rowspan="2">Sample</th><th colspan="2">PTR-QiTOF-MS</th><th colspan="2">TD-GC-MS</th><th rowspan="2">PTR-QiTOF-MS vs. TD-GC-MS</th></tr><tr><th># of detected mass peaks</th><th># of assigned molecular formulas (VOCs)</th><th># of identified molecular formulas</th><th># of identified compounds (VOCs)</th></tr></thead><tbody><tr><td>Cow</td><td>255</td><td>224</td><td>214</td><td>307</td><td>70</td></tr><tr><td>Horse</td><td>243</td><td>233</td><td>212</td><td>290</td><td>64</td></tr><tr><td>Goat</td><td>274</td><td>254</td><td>200</td><td>300</td><td>65</td></tr><tr><td>Sheep</td><td>276</td><td>257</td><td>224</td><td>304</td><td>66</td></tr></tbody></table>

hepten-2-one). Thus, there were more compounds in TD-GC-MS than the number of molecular formulas assigned with the PTR-QiTOF-MS.

### 3.4. VOC emission characteristics

The average mean mass concentration of the assigned VOCs was determined based on their mixing ratio obtained from the three PTR-QiTOF-MS measurements and considering the molecular weight of the compound (refer to https://doi.org/10.57745/PGB2SY). The total mass concentration of each chemical group was computed by summing the concentrations of individual compounds within each group. The diverse

chemical groups exhibited varying contributions to the overall concentration, as illustrated in Fig. 3. Across all samples, oxygenated OVOCs consistently presented the highest mass concentration. The second most abundant group in all samples comprised compounds with different heteroatoms in the molecular formula (other compounds). Comparable concentrations of HC and N-compounds were observed in each sample.

The total emission flux of all assigned VOCs was calculated. Notably, cow manure demonstrated the highest VOC emission fluxes at 66 ± 26 µg m⁻² min⁻¹, followed by goat, sheep, and horse manures with 32 ± 5, 31 ± 11, and 25 ± 5 µg m⁻² min⁻¹, respectively. Table 2 provides insights into the total emission flux of each chemical group, derived from averaging the emission fluxes of the three PTR-QiTOF measurements. Cow manure exhibited elevated emissions of HC, O-compounds, N-compounds, and other compounds (with distinct heteroatoms) compared to the other samples. Lower emissions of sulfur and halogenated compounds were observed across all samples.

The assigned OVOCs were further categorized based on the number of oxygen atoms in the molecular formula. Approximately half of the assigned OVOCs in horse, sheep, and goat manures contained a single oxygen atom with the molecular formula CₓHᵧO; however, they constituted 77% in cow manure. The percentage contribution of each OVOC class was calculated and is displayed in Fig. S4. Cow manure exhibited a distinct distribution of OVOCs by their number of oxygen atoms compared to the other three samples. Compounds containing one oxygen atom with the molecular formula CₓHᵧO showed the maximum emission flux from cow manure, while their contribution to OVOCs in the other three samples was comparable. Compounds with two oxygen atoms and the molecular formula CₓHᵧO₂ showed a comparable

<figure><img src="image_6.png" /><figcaption>Fig. 3. Mass concentration of each chemical group in each sample. The error bars displayed in the figure represent the standard deviation of the average mass concentration obtained from the three replicates of each sample.</figcaption></figure>
<caption>**Table 2**</caption>

Total emission fluxes for each chemical group identified in manure samples, with the standard deviation of the average emission flux obtained from the three replicates of each sample displayed alongside.

<table><thead><tr><th rowspan="2">Manure type</th><th colspan="6">Total emission flux of each chemical group (µg m<sup>-2</sup> min<sup>-1</sup>)</th></tr><tr><th>HC</th><th>O-compounds</th><th>N-compounds</th><th>S-compounds</th><th>Other compounds</th><th>Halogenated compounds</th></tr></thead><tbody><tr><td>Cow</td><td>10 ± 2</td><td>36 ± 19</td><td>7.21 ± 1.84</td><td>0.86 ± 0.12</td><td>12.59 ± 2.18</td><td>0.28 ± 0.05</td></tr><tr><td>Horse</td><td>4.29 ± 0.21</td><td>11 ± 3</td><td>2.80 ± 0.47</td><td>0.86 ± 0.12</td><td>6.30 ± 1.09</td><td>0.34 ± 0.05</td></tr><tr><td>Sheep</td><td>4.62 ± 1.63</td><td>12 ± 5</td><td>2.93 ± 1.06</td><td>0.86 ± 0.12</td><td>9.51 ± 3.21</td><td>0.21 ± 0.07</td></tr><tr><td>Goat</td><td>4.92 ± 0.66</td><td>13 ± 2</td><td>4.41 ± 0.63</td><td>0.33 ± 0.14</td><td>8.64 ± 1.36</td><td>0.28 ± 0.05</td></tr></tbody></table>

contribution to OVOC emission fluxes in horse, sheep, and goat manures. A minimal contribution from compounds containing more than two oxygen atoms was observed.

# 4. Discussion

The detected VOCs were classified into six chemical groups (1) HC, (2) Oxygenated, (3) Nitrogenated, (4) Sulfur (5) Halogenated, and (6) Other compounds. In the following sections, results are discussed based on the chemical family of VOCs, with a particular focus on compounds considered as characteristic emissions from manure and important for understanding atmospheric chemistry. The results under discussion were compared with relevant literature cited in Table S3 of the Supplementary Materials.

## 4.1. Hydrocarbons

A total of 85 HC were detected using online and/or offline methods in animal manure samples, and DBE analysis was performed on these 85 HC. For each HC, the DBE value was calculated, and the plot DBE versus the number of carbon atoms is provided in Table S4 and Fig. S5. Among the 88 HC, 27 compounds were detected using PTR-QiTOF-MS, 34 compounds by TD-GC-MS, and 27 compounds were detected using both techniques. Using DBE analysis, HC was categorized into different subclasses with the same DBE value but different alkylation degrees (compounds situated in the same straight line in Fig. S5). The DBE values

obtained ranged from 0 to 10. HC with a DBE of 0 were identified as linear alkanes by TD-GC-MS, including 3-methyl hexane (C₇H₁₆), 3-methyl pentane (C₆H₁₄), 6-methyl tridecane (C₁₄H₃₀), hexadecane (C₁₆H₃₄), pentadecane (C₁₅H₃₂), etc. Notably, these compounds were not detected via PTR-QiTOF-MS, likely due to their lower proton affinity (PA) compared to water.

Compounds with a DBE of 1 were identified as either alkenes or cycloalkanes, such as 10-methyl-3-undecene (C₁₂H₂₄) and 1,5-dimethyl cyclooctane (C₁₀H₂₀), which were detected using TD-GC-MS. Other compounds with a DBE of 2 were categorized as alkynes, cycloalkenes, or dienes such as 1,3-octadiene (C₈H₁₄). Cycloalkynes or polyenes with a DBE of 3, such as 6-butyl-1,4-cycloheptadiene (C₁₁H₁₈) and 3-ethylidene cyclohexene (C₈H₁₂), were also found. The majority of the detected HC in this study were aromatics with DBE ≥4. Additionally, 4 compounds identified as terpenes were emitted from all manure samples, and detected using both online and offline analysis techniques. Furthermore, 8 polycyclic aromatic hydrocarbons, including naphthalene, 1,7-dimethylnaphthalene, 1,6,7-trimethylnaphthalene, fluorene, and anthracene, were detected in this study by PTR-QiTOF-MS and/or GC-MS.

As mentioned in section 3.4, emission fluxes of the assigned HC detected by PTR-QiTOF-MS were calculated. The highest emission flux of HC was observed in cow manure at 10 ± 2 µg m⁻² min⁻¹ (Table 2). The left panel of Fig. 4 depicts the bar graph representation of HC subclasses identified using DBE analysis. HC detected using PTR-QiTOF-MS falls into four categories: aliphatic (linear alkenes or alkynes), aromatic (benzene and its derivatives), alicyclic (cycloalkanes,

<figure><img src="image_7.png" /><figcaption>**Fig. 4.** Left panel: Classification of HC detected by PTR-QiTOF-MS in each sample using the DBE method. The total emission flux of each sub-class is illustrated. Right panel: Emission flux of (a) BTEX and (b) terpene compounds emitted from manure samples. The error bars depicted in the figure represent the standard deviation of the average emission flux obtained from the three replicates of each sample.</figcaption></figure>
cycloalkenes, or cycloalkynes), and terpenes. The total emission flux for each category is displayed, with aromatic compounds exhibiting the maximum emissions in all samples. Compounds with DBE = 3 were predominant in cow manure (2.8 ± 0.6 µg m⁻² min⁻¹). Similarly, terpenes showed the highest emissions from cow manure (1.71 ± 0.36 µg m⁻² min⁻¹), while being lower in the other three samples.

The fluxes of BTEX (Benzene, Toluene, Ethylbenzene, Xylenes) and terpene compounds emitted from the four samples are shown in the right panel of Fig. 4 (a). Benzene ($C_6H_6$, m/z 79.05), toluene ($C_7H_8$, m/z 93.07), ethylbenzene, and xylene ($C_8H_{10}$, m/z 107.09) were emitted from all samples and detected using both PTR-QiTOF-MS and TD-GC-MS. Goat manure exhibited the highest emissions of benzene, while sheep manure had the greatest emissions of toluene. Ethylbenzene and xylene showed the highest emissions in cow manure, with equal emissions from the other three samples. BTEX compounds have been previously reported within farm buildings (Ciganek and Neca, 2008). Kammer et al. (2020) reported emissions of markers of anthropogenic combustion tracers, such as BTEX, trimethyl benzene, propyl benzene, and NOₓ from dairy stable and sheep pens. The authors found no correlation between NOₓ and BTEX, suggesting that BTEX compounds originated from the sheep pens. In our laboratory chamber experiments, the emissions of BTEX compounds are considered low compared to those reported by Kammer et al. (2020), who conducted field experiments. It was assumed that anthropogenic sources, such as farming activities inside the farm buildings, are the primary contributors to BTEX compounds (Kammer et al., 2020).

Ions corresponding to m/z 69.07, 137.12, 205.19, and 273.26 were assigned as $C_5H_8H^+$ (isoprene), $C_{10}H_{16}H^+$ (monoterpenes, D-limonene, and 3-carene), $C_{15}H_{24}H^+$ (sesquiterpenes) and $C_{20}H_{32}H^+$ (diterpenes) (Fig. 4, b). TD-GC-MS analysis revealed different isomers of sesquiterpenes in each type of sample. Sesquiterpenes ranked as the 2nd highest emitted compounds from sheep and goat manure, while they were the 6th and 10th most emitted compounds in cow and horse manures, respectively. Terpenes are usually attributed to biogenic emissions (Kumar et al., 2013; Sánchez-Monedero et al., 2018; Eitzer, 1995). Terpene emissions dominated the total concentrations of emitted VOCs (about 50% of the total amount of VOCs) in a composting pile at different stages of the process (Sánchez-Monedero et al., 2018). Terpene emissions were lower than 1 µg m⁻² min⁻¹ in our samples, similar to what was obtained by Kammer et al. (2020) in the farm. Our samples showed the highest emissions from cow manure, followed by goat, horse, and sheep manure. Terpenes, natural compounds released from the feedstock, were emitted from yard waste compost (Eitzer, 1995). Additionally, Büyüksönmez & Evans (Büyüksönmez and Evans, 2013) emphasized terpenes as the most significant compounds emitted from the tested feedstock. In our study, terpenes contributed 2.6%, 2.5%, 1%, and 2.8% to the total flux of VOCs in cow, horse, sheep, and goat manures, respectively. This contribution notably contrasts with terpenes' contribution to the total VOC flux emitted from green waste compost piles of varying ages (10%) (Kumar et al., 2013). It is essential to note that our analyzed manure samples were mixed with straw. This difference in terpene contribution is attributed to the type of emitter, as straw is not considered a strong terpene emitter, as demonstrated by Beck et al. (2007).

## 4.2. Oxygenated compounds

In this work, the predominant class of VOCs identified in the four samples was OVOCs, with the maximum observed 36 ± 19 µg m⁻² min⁻¹ in cow manure. The emission fluxes of OVOCs in horse, sheep, and goat manures were comparable, measuring 11 ± 3, 12 ± 5, and 13 ± 2 µg m⁻² min⁻¹, respectively. In this work, the detected OVOCs contained from one to four oxygen atoms, suggesting that the emitted OVOCs were not highly oxidized. The majority of the assigned OVOCs detected by PTR-QiTOF-MS were identified through TD-GC-MS analysis. Cow manure notably displayed various characteristic groups of OVOCs,

including alcohols, carboxylic acids, carbonyls (ketones and aldehydes), ethers, and esters. This observation is consistent with previous studies that have highlighted the prevalence of OVOCs, such as methanol, ethanol, acetic acid, and acetone in dairy cattle emissions (Ngwabie et al., 2007; Sun et al., 2008). Yuan et al. (2017) also reported the significant contribution of oxygenated compounds, including alcohols and carbonyls, to the total concentration of emitted VOCs from different concentrated animal feeding operation sites. Furthermore, Zhang et al. (2019) showed the dominance of OVOCs, such as ethanol, acetone, and 2-butanone, in VOC emissions from swine manure biogas digestate storage. Ngwabie et al. (2007) identified methanol, acetaldehyde, acetone, and isopropanol in sheep houses, with ethanol dominating the emissions.

Compounds assigned as $C_xH_yO$ contributed to 89%, 62%, 55%, and 56% of the total emission flux of OVOCs in cow, horse, sheep, and goat manure, respectively. Cow manure showed the highest emission flux at 31.80 ± 18.59 µg m⁻² min⁻¹ of $C_xH_yO$, primarily attributed to the high emissions of three compounds: $C_3H_6O$ (m/z 59.04), $C_4H_8O$ (m/z 73.06), and $C_7H_8O$ (m/z 109.07). These compounds were identified using TD-GC-MS as: $C_3H_6O$ (acetone), $C_4H_8O$ (butanal and 2-butanone), and $C_7H_8O$ (anisole, p-cresol, and benzyl alcohols) contributing alone to 58% of the total $C_xH_yO$ emissions flux. $C_7H_8O$ was identified as 4-methylphenol in sheep houses (Ngwabie et al., 2007). Butanal and butanone were classified as the 2nd most emitted VOCs from cow manure. $C_4H_8O$ has been identified in dwelling houses and stables of dairy and cattle farms (Beck et al., 2007), with animal exhalation being considered the main emission source of this compound (Kammer et al., 2020).

The highest emissions of acetone were observed from cow manure (1st most emitted), followed by horse, goat, and sheep manures. Acetone, butanal, and butanone were consistently emitted from all samples. In contrast to the findings of Kammer et al. (2020), who reported acetone and trimethylamine as the most emitted VOCs after ethanol and methanol in sheep pens, our study observed a different order of emissions in sheep manure. This difference can be attributed to various factors, including (i) differences in measurement conditions; whether conducted in field or laboratory conditions, (ii) concentration calculation and PTR calibration, and (iii) diverse sources of emitted VOCs, where some emissions are correlated to respiration (acetone), agricultural practices, as well as animal and excreta emissions (Kammer et al., 2020; Ngwabie et al., 2007).

Methanol ($CH_4O$, m/z 33.03) was present in all samples except cow manure, emerging as the most abundant VOC in horse and goat manures (2.13 ± 0.26 and 2.61 ± 0.38 µg m⁻² min⁻¹, respectively). Our findings nearly doubled those reported by Liu et al. (2018) (1.2 µg m⁻² min⁻¹), following pig manure land application. Acetaldehyde ($C_2H_4O$, m/z 45.03) was detected in all samples, ranking as the most emitted compound from sheep manure. It exhibited similar emission fluxes at 0.8 ± 0.5 µg m⁻² min⁻¹ in horse and sheep manures, whereas in cow manure, it was lower at 0.3 ± 0.2 µg m⁻² min⁻¹. Goat manure displayed the lowest emission flux of acetaldehyde at 0.063 ± 0.006 µg m⁻² min⁻¹. These findings align with some previous studies (Filipy et al., 2006; Ngwabie et al., 2007; Sun et al., 2008), although acetaldehyde emissions from pig manure land application were notably higher (16.7 µg m⁻² min⁻¹) (Liu et al., 2018). Ethanol ($C_2H_6O$, m/z 47.05) showed very low emission flux (<0.01 µg m⁻² min⁻¹) across all samples. Additionally, an oxygenated ion corresponding to m/z 87.08 assigned as $C_5H_{10}OH^+$, was detected in all samples using PTR-QiTOF-MS. Various compounds for $C_5H_{10}O$ were identified using TD-GC-MS such as 3-methyl-2-butanone, 3-methyl butanal, pentanal, 2-pentanone, and 3-pentanone, previously reported in lactating cows in open stalls, cattle farms, and intensive pig production (Filipy et al., 2006; Beck et al., 2007; Feilberg et al., 2015).

Compounds assigned as $C_xH_yO_2$ showed comparable contributions to the total emission flux of OVOCs in horse, sheep, and goat manures (33%, 36%, and 39%, respectively), while the lowest contribution was observed in cow manure (8%). Compounds with the formula $C_xH_yO_2$ were determined to be carboxylic acids, esters, or ethers through TD-GC-MS.
MS analysis. CH₂O₂ (m/z 47.02), identified as formic acid in the literature (Feilberg et al., 2015), was detected in all samples at an identical emission flux of 0.02 µg m⁻² min⁻¹. Acetic acid (protonated ion C₂H₄O₂H⁺, m/z 61.03) was emitted from all samples, with the highest emission flux observed in cow manure at 0.0989 ± 0.0548 µg m⁻² min⁻¹. This emission level is notably low compared to its emission from swine manure slurry (3–24 µg m⁻² min⁻¹) (Parker et al., 2013). Acetic acid has been proposed as a cowshed emission tracer by Feilberg et al. (2015) and Rabaud et al. (2003). It was also reported as the third most concentrated VOC in the dairy stable, sheep pens, and outdoors, according to Kammer et al. (2020). Moreover, acetic acid exhibited high fluxes from lactating cow waste, as reported by Shaw et al. (2007). C₃H₆O₂ (m/z 75.04), identified as propanoic acid and 1-hydroxy-2-propanone through TD-GC-MS analysis, was emitted from all samples, with the highest emission flux observed in cow manure (0.07 ± 0.06 µg m⁻² min⁻¹). Propanoic acid has been recognized as a characteristic compound of emissions from cow and sheep pens (Ngwabie et al., 2007). Liu et al. (2018) reported a substantial emission flux of propanoic acid (1012 µg m⁻² min⁻¹) during the 37-h application of pig manure slurry, while demonstrating lower emissions (~9 µg m⁻² min⁻¹) after swine manure slurry application (Parker et al., 2013). Furthermore, propanoic acid was also detected in swine slurry emissions, with an average emission flux of 2.6 µg m⁻² min⁻¹ during 4 weeks of swine slurry application (Parker et al., 2013). Benzoic acid (protonated ion C₇H₆O₂H⁺, m/z 123.05) was emitted from all samples except cow manure. This compound results from the metabolic degradation of an amino acid, phenylalanine (Mackie et al., 1998).

Our study identified volatile fatty acids (VFAs), including heptanoic acid (C₇H₁₄O₂), hexanoic acid (C₆H₁₂O₂), isobutyric acid (C₄H₈O₂), and isovaleric acid (C₅H₁₀O₂). Woodbury et al. (2022) reported that these VFAs make significant contributions to the total odor activity value. Hexanoic and heptanoic acid were detected in all samples except cow manure. Whereas isobutyric acid and isovaleric acid were emitted from all manure samples. In addition to VFAs, three phenolic compounds (C₇H₈O, C₆H₆O, and C₈H₁₀O) were found in this work. C₇H₈O, identified as cresol or 3-methylphenol, was detected in all samples except sheep manure using PTR-QiTOF-MS. However, TD-GC-MS analysis of sheep manure did detect this compound. In cow manure, C₇H₈O, the third most emitted VOC from this sample, showed the highest emission flux at 1.39 ± 1.35 µg m⁻² min⁻¹. An ion corresponding to m/z 95.08 was assigned to C₆H₆O and identified in all samples with different fluxes. Cow manure showed the highest emission flux of phenol at 0.525 ± 0.189 µg m⁻² min⁻¹, while horse and sheep manures exhibited the same emission flux of this compound (0.02 ± 0.01 µg m⁻² min⁻¹). Goat manure showed the lowest emission flux of phenol (0.127 ± 0.009 µg m⁻² min⁻¹). Phenol emissions following the surface application or injection of swine manure slurry into the soil were reported at fluxes of 4.02 and 0.86 µg m⁻² min⁻¹, respectively by Parker et al. (2013). Phenol and cresol emissions exhibited a strong correlation due to their emission source. Cresol is generated during the microbial degradation of tyrosine (amino acid) and is associated with the production of phenol (Mackie et al., 1998). This relationship can explain the relatively high emissions observed in our samples. Another phenolic compound, detected at m/z 123.08, was assigned to the protonated form of C₈H₁₀O. It is identified in cow and sheep manures as 4-ethylphenol at emission fluxes 0.12 ± 0.02 and 0.039 ± 0.016 µg m⁻² min⁻¹, respectively. TD-GC-MS identified two compounds corresponding to C₈H₁₀O, 1-methoxy-4-methyl-benzene and 3-ethylphenol. This compound constituted only a few percent of emissions from concentrated animal feeding operations (Yuan et al., 2017).

### 4.3. Nitrogenated compounds

Several nitrogenated compounds were identified in animal manure samples. Based on emission flux calculations, cow manure exhibited the highest emission flux of nitrogenated compounds at 7.21 ± 1.87 µg m⁻²

min⁻¹, followed by goat, sheep, and horse manures (Table 2). NH₃ is by far the most abundant gaseous compound measured in the emissions from the manure application (Williams, 1995). NH₃ is a crucial end-product resulting from the biological and chemical breakdown of manure protein, uric acid, and urea decomposition (Mackie et al., 1998). Its volatilization into the atmosphere is influenced by soil pH, temperature, and moisture. This process contributes to the deposition of sulfate and nitrate, thereby causing acid rain and soil acidification (Atkinson, 2000).

The quantitative analysis of NH₃ using the H₃O⁺ ionization mode in PTR-QiTOF-MS is challenging due to its interaction with the surfaces of various materials and the high water solubility of NH₃, which promotes the back reactions of NH₄⁺ to NH₃ (Norman et al., 2009). An alternative approach for NH₃ measurement using PTR-MS has been proposed by (Norman et al., 2007). This method relies on the chemical ionization of NH₃ with oxygen (O₂) as the source gas, producing O₂⁺ as an ionizing reagent, in contrast to the H₃O⁺ method (Norman et al., 2007). This approach was not applied in our work and the H₃O⁺ was used as an ionizing reagent. Furthermore, our study aimed to characterize the VOC emissions from manure samples. The proton transfer approach of the instrument was suitable for measuring most of the VOCs of interest. In this study, NH₃ was measured separately using the Picarro instrument. The results indicated the highest concentration of NH₃ in sheep manure (18.3 ppm), followed by goat, cow, and horse manure at 10.2 ppm, 7.09 ppm, and 6.35 ppm, respectively (Fig. S6).

The ion m/z 46.06 was assigned to the protonated form C₂H₇NH⁺ of dimethylamine (DMA) (Kammer et al., 2020). This compound was found in all samples except horse manure. Additionally, a multipeak at the nominal mass m/z 60 was observed. The first ion signal (m/z 60.05) corresponded to ¹³C isotope of protonated acetone (C₃H₆OH⁺, m/z 59.04) and the second signal (m/z 60.08) assigned to C₃H₉NH⁺. Feilberg et al. (2015) applied a correction of the signal of C₃H₉NH⁺ to the ¹³C isotopomer of acetone, due to the use of the PTR-MS with a quadrupole mass analyzer, which has a lower resolution than the instrument employed in our study (~2600). C₃H₉N identified as trimethylamine (TMA) in (Beck et al., 2007; Feilberg et al., 2015), was detected only by PTR-MS and not by TD-GC-MS in our study. Kammer et al. (2020) reported that trimethylamine was the most emitted compound from sheep pen and was considered as an emission tracer of sheep pen emissions. Feilberg et al. (2015) explained that TMA elutes from a specific GC column in the first few runs. The highest emission flux of TMA was observed from cow manure at 0.3 ± 0.2 µg m⁻² min⁻¹, followed by sheep, goat, and horse manures at 0.043 ± 0.017, 0.018 ± 0.007, and 0.008 ± 0.002 µg m⁻² min⁻¹. Liu et al. (2018) also detected TMA after land application of pig slurry, with an emission flux of 8.9 µg m⁻² min⁻¹. However, this emission was relatively higher compared to our samples, possibly attributed to differences in analysis conditions and manure types. Sintermann et al. (2014) showed that dairy excreta (urine + feces) serve as the primary source of NH₃, DMA, and TMA in dairy farming. TMA, classified as a volatile aliphatic amine species, is released from agricultural activities and is the predominant gas-phase aliphatic amine (compared to methylamine and DMA) at agricultural sites (Sintermann et al., 2014). Both gas-phase DMA and TMA play a role in nucleation, showing high potential efficiency for secondary particle formation. They can also condense onto existing aerosol particles (Sintermann et al., 2014; Lee et al., 2019).

Two aromatic nitrogenated compounds, C₈H₇NH⁺ (m/z 118.06) and C₉H₉NH⁺ (m/z 132.08), were detected by PTR-MS in all samples (Fig. 5, a). Analysis of TD-GC-MS data revealed that C₈H₇N corresponded to indole in all samples. C₉H₉N was identified as 4-methylindole in cow, horse, and goat manure, while it was identified as 6-methylindole by GC-MS in sheep manure. 6-methylindole can be considered as an emission tracer of this manure. The emission flux of indole was relatively consistent in all samples (~0.96 ± 0.01 µg m⁻² min⁻¹). 4-methylindole exhibited the highest emission flux in cow manure at 1.3 ± 0.4 µg m⁻² min⁻¹, followed by sheep and horse manures at 0.11 ± 0.03 and 0.098
<figure><img src="image_8.png" /><figcaption>Fig. 5. (a) Emission flux of indoles and (b) sulfur compounds detected by PTR-QiTOF-MS analysis in animal manure samples.</figcaption></figure>

± 0.017 µg m⁻² min⁻¹, respectively. Notably, 4-methylindole ranked as the 4th most emitted compound from cow manure. Indole (C₈H₇N) was emitted at an emission flux of 2.3 µg m⁻² min⁻¹ after the land application of pig slurry (Liu et al., 2018). This emission flux was comparatively lower, at 0.564 and 0.035 µg m⁻² min⁻¹, after surface application or injection of swine slurry into the soil, respectively (Parker et al., 2013).

Several indoles have been extensively reported in the literature and recognized as odorant compounds released from livestock production and after land application of different animal manure types (Liu et al., 2018; Feilberg et al., 2010, 2011; Ni et al., 2012; Woodbury et al., 2022; Parker et al., 2013). Indole and skatole are the principal end-products of tryptophan metabolism (Mackie et al., 1998). These compounds, along with phenols, possess high odor activity and contribute significantly to odor nuisance (Kammer et al., 2020; Feilberg et al., 2010, 2011). Moreover, indole and skatole (3-methyl indole) were reported as the main aromatic compounds, contributing 14.7% and 8.84%, respectively, to odor activity values from the land application of beef cattle manure (Woodbury et al., 2022). A recent study also demonstrated new particle formation from skatole ozonolysis in the presence of SO₂, both emitted by sludge samples (Ciuraru et al., 2021). The authors suggested skatole could be an additional VOC source with a potentially significant impact on atmospheric particle formation during the sludge spreading periods (Ciuraru et al., 2021).

### 4.4. Sulfur compounds

A total of 11 sulfur compounds were identified in manure samples using PTR-QiTOF-MS. The emission of sulfur compounds from the analyzed manure samples was relatively low. The total emission flux of these compounds was equal in cow, horse, and sheep manures, while a lower flux was observed in goat manure (Table 2). The emission flux of each sulfur compound detected by PTR-QiTOF-MS analysis of manure samples is illustrated in Fig. 5 (b). Sulfur compounds are important components of essential amino acids such as methionine, cysteine, homocysteine, and taurine, which originate from the proteins consumed by livestock (Higgins et al., 2006; Zhu et al., 2016).

Two sulfur compounds, detected at *m/z* 49.01 and 63.02 as CH₄SH⁺ and C₂H₆SH⁺ ions, respectively, were found in the emissions of all samples. CH₄S was identified as methanethiol through TD-GC-MS showing the lowest emission flux of 0.047 ± 0.023 µg m⁻² min⁻¹ in

cow manure. This value was higher compared to the emissions from pig manure (0.02 µg m⁻² min⁻¹) reported by Liu et al. (2018). C₂H₆S was identified as dimethyl sulfide (DMS) (Beck et al., 2007; Feilberg et al., 2015), with goat manure showed the highest emission flux at 0.22 ± 0.12 µg m⁻² min⁻¹. This exceeded the value reported by Liu et al. (2018) in swine slurry application (0.06 µg m⁻² min⁻¹). A compound detected at *m/z* 94.99, assigned to the protonated form of C₂H₆S₂, was found in the PTR-MS mass spectra of horse manure emissions at a very low flux (0.06 ± 0.01 µg m⁻² min⁻¹). TD-GC-MS confirmed the presence of C₂H₆S₂ in the emissions of all samples, identified as dimethyl disulfide (DMDS). Parker et al. (2013) reported higher emission flux of DMDS following pig slurry surface application or injection into soil (0.086 and 0.037 µg m⁻² min⁻¹, respectively). The high photochemical reactivity of DMDS may contribute to its limited detection by PTR-MS in cow, sheep, and goat manures, as a significant portion could be lost before the sample introduction into the chamber.

Methanethiol, DMS, and DMDS are potential odorous compounds with low human odor detection thresholds (Filipy et al., 2006; Schiffman et al., 2001), raising concerns about odor issues at farm buildings. Additionally, five sulfur compounds assigned as C₄H₄SH⁺, C₅H₆SH⁺, C₅H₈SH⁺, C₆H₁₂SH⁺, and C₇H₁₀SH⁺ ions were exclusively observed in cow manure, serving as potential emission tracers. CS₂ (*m/z* 76.95) was detected only in goat manure using PTR-MS, while TD-GC-MS identified it as carbon disulfide in the gas phase emissions of sheep manure. Notably, carbon disulfide, DMS, and DMDS were found to be dominant VOCs in both indoor and outdoor parts of animal farms (Ciganek and Neca, 2008).

In this work, hydrogen sulfide (H₂S) was not detected by the PTR-QiTOF-MS system. This compound has a relatively low proton affinity (691 kJ mol⁻¹) compared to water (705 kJ mol⁻¹), making its measurement challenging using PTR-MS. Additionally, the humidity-dependent backward reaction of protonated H₂S further complicates its accurate measurement (Hansen et al., 2012). Feilberg et al. (2010) proposed a correction method for measuring H₂S by PTR-MS, however we did not apply this method in our work. Thus, emissions of H₂S from our manure samples were not excluded, as it was detected in sheep manure by TD-GC-MS. H₂S is a major sulfur compound emitted from livestock production. Feilberg et al. (2015) demonstrated that agriculture, particularly in countries with intensive livestock production like Denmark, constitutes a significant sulfur source. The absence of H₂S detection by TD-GC-MS analysis of cow, horse, and goat manure emissions can be attributed to its oxidation upon contact with air (Feilberg
et al., 2015) occurring before sample introduction into the chamber. The microbial oxidation of H₂S at the manure-air surface has been observed to occur within a few seconds, significantly faster than typical chemical oxidation (Kühl and Jørgensen, 1992). Due to this rapid oxidation and loss of H₂S, its emission from the manure samples under this study cannot be ruled out.

### 4.5. Emissions of halogenated and other compounds

Table 3 presents the list of the ten halogenated compounds identified in manure samples along with their molecular formulas, molecular weight, and chemical identification achieved through TD-GC-MS analysis. Halogenated compounds showed nearly identical emission fluxes in all samples (Table 2). These compounds can be generated from various sources, including substances like food additives, chemical cleaning agents, and coatings (Duan et al., 2014). Other potential contributors to halogenated compounds include industrial solvents, paint removers, refrigerants, soaps, paints, and varnish (Orzi et al., 2018). Furthermore, the emissions of halogenated compounds are contributed from both degradable (e.g., chlorofluorocarbons and trichloroethylene) and non-biodegradable (e.g., perfluorinated compounds) compounds (Liu et al., 2018). The presence of halogenated compounds demands special attention due to the potential high toxicological risk they may pose to workers and local inhabitants (Scheutz et al., 2008).

### 4.6. Sample comparison

The gas phase emissions from all samples, measured by PTR-QiTOF-MS were compared using PCA. This approach aimed to classify the samples and unveil the similarities and differences among them. It is worth noting that for this comparison only the assigned VOCs (224, 233, 254, and 257 in cow, horse, sheep, and goat manures, respectively) were considered. The analysis revealed that the majority of the variance within the dataset could be explained by only a few principal components (PC), compared to the hundreds of initial variables. Specifically, the first two principal components (PC1 and PC2) accounted for approximately 89% of the variance and were enough to discriminate between the four manure types. The score plot depicting PC1 and PC2 is presented in Fig. 6.

PC1 explained around 82% of the total dataset variability in the dataset, allowing it to distinguish between the samples independently. The score plot indicated that cow manure was distinctly isolated from other manures and separated by PC1. On the other hand, PC2 played a role in distinguishing between horse and sheep manure from goat manure. The influence of mass peaks on each PC was inferred through

<caption>**Table 3**</caption>

List of halogenated compounds detected by TD-GC-MS and PTR-QiTOF-MS techniques.

<table><thead><tr><th>Molecular formula</th><th>Molecular weight</th><th>Chemical identification</th><th>Samples</th></tr></thead><tbody><tr><td>C<sub>2</sub>H<sub>3</sub>F<sup>a</sup></td><td>46.022</td><td>Flouroethene</td><td>horse and sheep</td></tr><tr><td>C<sub>2</sub>H<sub>5</sub>F<sup>a</sup></td><td>48.038</td><td>Flouroethane</td><td>goat</td></tr><tr><td>C<sub>6</sub>H<sub>5</sub>Cl<sup>a</sup></td><td>112.008</td><td>Chlorobenzene</td><td>cow, horse, goat</td></tr><tr><td>C<sub>7</sub>H<sub>7</sub>Cl<sup>a</sup></td><td>126.024</td><td>Benzyl chloride</td><td>sheep</td></tr><tr><td>C<sub>2</sub>H<sub>3</sub>Cl<sub>3</sub><sup>a</sup></td><td>131.930</td><td>1,1,1-trichloroethane</td><td>cow, horse, sheep, goat</td></tr><tr><td>C<sub>8</sub>H<sub>17</sub>Cl<sup>a</sup></td><td>148.102</td><td>2-chlorooctane</td><td>goat</td></tr><tr><td>C<sub>14</sub>Cl<sub>4</sub><sup>a</sup></td><td>151.875</td><td>Carbon tetrachloride</td><td>horse, sheep, goat</td></tr><tr><td>C<sub>7</sub>H<sub>13</sub>Br<sup>a</sup></td><td>176.020</td><td>1-bromo-4-methyl-cyclohexane</td><td>sheep</td></tr><tr><td>C<sub>7</sub>H<sub>6</sub>OCl<sub>2</sub><sup>b</sup></td><td>176.989</td><td>—</td><td>horse, goat</td></tr><tr><td>C<sub>7</sub>H<sub>5</sub>OCl<sub>3</sub><sup>b</sup></td><td>210.951</td><td>—</td><td>cow, horse, sheep</td></tr></tbody></table>

their loadings. Consequently, the significance of each component could be illustrated from its corresponding loadings plot, as depicted in Fig. 6.

The positive value of PC1 (Fig. 6) primarily resulted from the contribution of oxygenated compounds C<sub>x</sub>H<sub>y</sub>O (e.g., alcohols, phenols, ketones, and aldehydes) and nitrogenated compounds “C<sub>x</sub>H<sub>y</sub>N” (e.g., trimethyl amine and C<sub>9</sub>H<sub>9</sub>N). PC1 showed a high negative contribution from two sulfur compounds (methanethiol and DMS). PC2, accounting for only 7% of the variance, demonstrated a significant contribution from compounds containing oxygen and nitrogen atoms with molecular formulas C<sub>a</sub>H<sub>b</sub>O<sub>c</sub>N<sub>d</sub> such as C<sub>2</sub>H<sub>5</sub>NO, C<sub>2</sub>H<sub>6</sub>NO, C<sub>3</sub>H<sub>8</sub>NO, etc.

The separation observed using PCA was primarily associated with the contribution of oxygenated compounds with one O atom (e.g., acetone, 2-butanone, butanal, p-cresol, anisole, 4-isopropylcyclohexanone, acetophenone, formaldehyde, phenol, etc.). In addition, nitrogenated compounds showed a significant contribution in cow manure compared to other samples. Compounds such as dimethylamine, trimethylamine, indole, and 4-methyl indole were highly emitted from this sample (Fig. 6, b). Horse and sheep manures appeared chemically similar in gas-phase emissions and were separated from goat manure primarily due to the influence of PC2. Goat manure received a high contribution from nitrogen- and oxygen-containing compounds, such as CH<sub>3</sub>NO<sub>2</sub>, C<sub>2</sub>H<sub>4</sub>NO, C<sub>2</sub>H<sub>3</sub>NO<sub>2</sub>, and C<sub>3</sub>H<sub>3</sub>NO (Fig. 6, c).

The variation in VOC emission characteristics in the studied animal manure samples can be attributed to different factors. Variations in animal feed composition influences the types and concentrations of organic compounds present in manure, affecting the subsequent decomposition process and VOC production. This variation may impact manure odor, ammonia, and VOC emissions, as recently demonstrated by Choi et al. (2024). Additionally, differences in microbial communities, pH levels, moisture content, and environmental conditions further contribute to the diversity of VOC emissions observed (Köninger et al., 2021). Each type of animal manure contains unique chemical compounds and microbial populations, resulting in distinct VOC profiles during decomposition. Future studies can be conducted to deeply understand the impact of these factors on VOC emission concentrations and profiles for different animal manure types.

## 5. Conclusions, recommendations, and further research

### 5.1. Findings

In conclusion, this laboratory-based study utilized atmospheric simulation chambers combined with advanced analytical techniques, PTR-QiTOF-MS and TD-GC-MS, to conduct an in-depth analysis of gas phase emissions from four animal manure samples. Using PTR-QiTOF-MS, we were able to identify and quantify 368 compounds. The TD-GC-MS data were mainly used for the assignment of *m/z* ions detected in PTR-QiTOF-MS to specific compounds and to provide additional chemical identification of the VOCs. The integration of both techniques demonstrated efficacy in characterizing VOC emissions from animal manure. The identified VOCs were classified into different chemical families, including oxygenated, nitrogenated, sulfur, aromatic, terpenes, and halogenated compounds. The emission fluxes were calculated, revealing that cow manure exhibited the highest VOC emission fluxes of 66 ± 26 µg m⁻² min⁻¹, followed by goat, sheep, and horse manures with 32 ± 5, 31 ± 11, and 25 ± 5 µg m⁻² min⁻¹, respectively. Notably, OVOCs emerged as the dominant compounds across all samples, contributing significantly to total VOC emission fluxes. Statistical analysis further highlighted the distinct nature of cow manure emissions, characterized by oxygenated (e.g., acetone, butanal, 2-butanone, p-cresol, anisole, 4-isopropylcyclohexanone, formaldehyde, phenol, acetophenone, etc.) and nitrogenated compounds (e.g., dimethylamine, trimethylamine, indole and 4-methyl indole). In addition, goat manure showed isolation from the other three samples, as it was characterized by high emissions of compounds having both oxygen and nitrogen atoms in the molecular formula (e.g., CH<sub>3</sub>NO<sub>2</sub>, C<sub>2</sub>H<sub>4</sub>NO, C<sub>2</sub>H<sub>3</sub>NO<sub>2</sub>, etc.).

<footnote>a Compound detected by TD-GC-MS.</footnote>

<footnote>b Compound detected by PTR-QiTOF-MS.</footnote>
<figure><img src="image_9.png" /><figcaption>**Fig. 6.** (a) Score plot of PC2 vs. PC1 for animal manure samples, with the percentage contribution of each PC to the total variance indicated in parenthesis. Points of the same color represent data recorded for the same sample. The loading plots for (b) PC1 and (c) PC2 derived from the PTR mass spectra of animal manure samples. The protonated molecules (VOCH⁺) that contribute to the positive and negative values of each PC are shown, with hydrocarbons (light red), oxygenated compounds (dark grey), nitrogenated compounds (green), sulfur compounds (blue), and nitrogen- and oxygen-containing compounds (pink) displayed.</figcaption></figure>

Statistical analysis revealed similarities between the VOC emissions of horse and sheep manures.

## 5.2. Research limitations

The detailed VOC inventory and emission flux calculations derived from our work can be used for environmental policies and regulations, setting standards for manure management practices to mitigate emissions impact on air quality and public health. While laboratory studies provide controlled environments for analysis, they may not fully replicate real-world conditions. Factors such as temperature, humidity, and microbial activity in natural environments could influence VOC emissions. VOCs emitted from manure can have significant environmental implications, including air quality degradation and contributions to atmospheric chemistry. Understanding how temperature and humidity influence emission composition allows for better predictions of the environmental impact of manure VOC emissions under different climate conditions. By understanding odor perception and the factors affecting VOC emissions, agricultural managers can effectively manage odor emissions from manure, thus promoting sustainable and responsible agricultural practices.

## 5.3. Recommendations and further research

The laboratory setup employed in our study for identifying and quantifying VOCs can support future field measurements, providing an important understanding of the composition and concentration of VOCs in manure emissions. These field validation studies are needed to confirm our laboratory findings and assess their applicability to real-world agricultural areas. Future studies can explore the effectiveness

of various manure treatment methods, contributing to the development of sustainable agriculture practices. In addition, future research should prioritize studies to assess temporal variations in emissions across different seasons and environmental conditions. Investigating the impact of various manure management practices on emissions and conducting odor perception studies to understand the olfactory impact on nearby communities are essential. Comparative studies among different types of animal manure and global assessments of VOC emissions are also recommended to quantify their contribution to air quality and climate change. These research efforts will contribute to the development of effective mitigation strategies and sustainable agricultural practices.

### CRediT authorship contribution statement

K.M. Haider: Writing – review & editing, Writing – original draft, Methodology, Data curation, Conceptualization, Writing – review & editing, Writing – original draft, Methodology, Data curation, Conceptualization. C. Focsa: Writing – review & editing, Validation, Supervision, Conceptualization, Writing – review & editing, Validation, Supervision, Conceptualization. C. Decuq: Writing – review & editing, Methodology, Writing – review & editing, Methodology. B. Esnault: Methodology, Methodology. F. Lafouge: Lafouge, Writing – review & editing, Methodology. B. Loubet: Loubet, Writing – review & editing. D. Petitprez: petitprez, Writing – review & editing, Supervision. R. Ciuraru: Writing – review & editing, Supervision, Project administration, Funding acquisition, Conceptualization.
Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability

Data available as Supplementary in attach and data used in this article are publicly available on Recherche Data Gouv multidisciplinary repository (https://doi.org/10.57745/PGB2SY)

Acknowledgements

This work was supported by the French national programme LEFE/ INSU (ENGRAIS) no 1762C0001, the INRAE Agroecosystems depart- ment, and the French National Research Agency through the ANR-21- CE01-0019-01 SOFORA project. This work also benefited from the support of the ANAEE-FR services 592 (ANR project n°11-INBS-0001) and of the Labex CaPPA (Chemical and Physical Properties of the At- mosphere) funded by the French National Research Agency (ANR) through the PIA (Programme d'Investissement d'Avenir) under contract ANR-11-LABX-0005-01 and by the Regional Council Hauts-de-France and the European Funds for Regional Economic Development (FEDER). The authors thank Michel Burban for the sample collection.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.
org/10.1016/j.jenvman.2024.121453.

References

Atkinson, R., 2000. Atmospheric chemistry of VOCs and NOx. Atmos. Environ. 34
(12-14), 2063-2101. https://doi.org/10.1016/S1352-2310(99)00460-4.

Beck, J.P., Heutelbeck, A., Dunkelberg, H., 2007. Volatile organic compounds in
dwelling houses and stables of dairy and cattle farms in Northern Germany. Sci.
Total Environ. 372 (2-3), 440-454. https://doi.org/10.1016/j.
scitotenv.2006.10.009.

Blunden, J., Aneja, V.P., Lonneman, W.A., 2005. Characterization of non-methane volatile organic compounds at swine facilities in eastern North Carolina. Atmos. Environ. 39 (36), 6707-6718. https://doi.org/10.1016/j.atmosenv.2005.03.053.

Büyüsönmez, F., Evans, J., 2013. Biogenic emissions from green waste and comparison to the emissions resulting from composting Part II: volatile organic compounds (VOCs). Compost Sci. Util. 15, 191-199. https://doi.org/10.1080/
1065657X.2007.10702332.

Cai, L., Koziel, J.A., Lo, Y.-C., Hoff, S.J., 2006. Characterization of volatile organic compounds and odorants associated with swine barn particulate matter using solid-phase microextraction and gas chromatography-mass spectrometry-olfactometry. J. Chromatogr. A 1102 (1-2), 60-72. https://doi.org/10.1016/j.
chroma.2005.10.040.

Chadwick, D., et al., 2011. Manure management: implications for greenhouse gas emissions. Anim. Feed Sci. Technol. 166-167, 514-531. https://doi.org/10.1016/j.
anifeedsci.2011.04.036.

Choi, W., Lee, W., Kim, K., 2024. Odor generation pattern of swine manure according to the processing form of feed. J. Anim. Sci. Technol. 66 (1), 219-231. https://doi.org/
10.5187/jast.2023.e48.

Ciganek, M., Neca, J., 2008. Chemical characterization of volatile organic compounds on animal farms. Vet. Med. (Praha) 53 (12), 641-651. https://doi.org/10.17221/1969-
VETMED.

Ciuraru, R., et al., 2021. New particle formation from agricultural recycling of organic waste products. Npj Clim. Atmospheric Sci. 4 (1) https://doi.org/10.1038/s41612-
021-00160-3. Art. no. 1.

Cunha, C.S., et al., 2016. Greenhouse gases inventory and carbon balance of two dairy systems obtained from two methane-estimation methods. Sci. Total Environ. 571, 744-754. https://doi.org/10.1016/j.scitotenv.2016.07.046.

Delfino, R.J., Gong, H., Linn, W.S., Pellizzari, E.D., Hu, Y., 2003. Asthma symptoms in Hispanic children and daily ambient exposures to toxic and criteria air pollutants. Environ. Health Perspect. 111 (4), 647-656. https://doi.org/10.1289/ehp.5992.

Duan, Z., Lu, W., Li, D., Wang, H., 2014. Temporal variation of trace compound emission on the working surface of a landfill in Beijing, China. Atmos. Environ. 88, 230-238. https://doi.org/10.1016/j.atmosenv.2014.01.051.

Eitzer, B.D., 1995. Emissions of volatile organic chemicals from municipal solid waste composting facilities. Environ. Sci. Technol. 29 (4), 896-902. https://doi.org/
10.1021/es00004a009.

Feilberg, A., Liu, D., Adamsen, A.P.S., Hansen, M.J., Jonassen, K.E.N., 2010. Odorant emissions from intensive pig production measured by online proton-transfer-reaction mass spectrometry. Environ. Sci. Technol. 44 (15), 5894-5900. https://doi.org/
10.1021/es100483s.

Feilberg, A., Hansen, M.N., Lindholst, S., 2011. Chemical evaluation of odor reduction by soil injection of animal manure. J. Environ. Qual. 40 (5), 1674-1682. https://doi.
org/10.2134/jeq2010.0499.

Feilberg, A., Bildsoe, P., Nyord, T., 2015. Application of PTR-MS for measuring odorant emissions from soil application of manure slurry. Sens. Switz. 15 (1), 1148-1167. https://doi.org/10.3390/s150101148.

Filippy, J., Rumburg, B., Mount, G., Westberg, H., Lamb, B., 2006. Identification and quantification of volatile organic compounds from a dairy. Atmos. Environ. 40 (8), 1480-1494. https://doi.org/10.1016/j.atmosenv.2005.10.048.

Giannadaki, D., Giannakis, E., Pozzer, A., Lelieveld, J., 2018. Estimating health and economic benefits of reductions in air pollution from agriculture. Sci. Total Environ. 622-623, 1304-1316. https://doi.org/10.1016/j.scitotenv.2017.12.064.

Guo, H., et al., 2017. Tropospheric volatile organic compounds in China. Sci. Total Environ. 574, 1021-1043. https://doi.org/10.1016/j.scitotenv.2016.09.116.

Haider, K.M., et al., 2022. Chemical identification and quantification of volatile organic compounds emitted by sewage sludge. Sci. Total Environ. 838, 155948 https://doi.
org/10.1016/j.scitotenv.2022.155948.

Hansen, M.J., Liu, D., Guldberg, L.B., Feilberg, A., 2012. Application of proton-transfer-reaction mass spectrometry to the assessment of odorant removal in a biological air cleaner for pig production. J. Agric. Food Chem. 60 (10), 2599-2606. https://doi.
org/10.1021/jf300182c.

Harrison, B.P., Moo, Z., Perez-Agredano, E., Gao, S., Zhang, X., Ryals, R., 2024. Biochar-composting substantially reduces methane and air pollutant emissions from dairy manure. Environ. Res. Lett. 19 (1), 014081 https://doi.org/10.1088/1748-9326/
ad1ad2.

Hempel, S., et al., 2016. Non-linear temperature dependency of ammonia and methane emissions from a naturally ventilated dairy barn. Biosyst. Eng. 145, 10-21. https://
doi.org/10.1016/j.biosystemseng.2016.02.006.

Higgins, M.J., Yarosz, B.D.P., Chen, Y.-C., Mass, N.A., 2003. Mechanisms of Volatile Sulfur Compound and Odor Production in Digested Biosolids. Residuals Biosolids.

Higgins, M.J., et al., 2006. Cycling of volatile organic sulfur compounds in anaerobically digested biosolids and its implications for odors. Water Environ. Res. 78 (3), 243-252. https://doi.org/10.2175/106143005X90065.

Insam, H., Gómez-Brandón, M., Ascher, J., 2015. Manure-based biogas fermentation residues - friend or foe of soil fertility? Soil Biol. Biochem. 84, 1-14. https://doi.org/
10.1016/j.soilbio.2015.02.006.

Kammer, J., et al., 2020. Characterization of particulate and gaseous pollutants from a French dairy and sheep farm. Sci. Total Environ. 712, 135598 https://doi.org/
10.1016/j.scitotenv.2019.135598.

Klimont, Z., Streets, D.G., Gupta, S., Cofala, J., Lixin, F., Ichikawa, Y., 2002. Anthropogenic emissions of non-methane volatile organic compounds in China. Atmos. Environ. 36 (8), 1309-1322. https://doi.org/10.1016/S1352-2310(01) 00529-5.

Köninger, J., Lugato, E., Panagos, P., Kochupillai, M., Orgiazzi, A., Briones, M., 2021. Manure management and soil biodiversity: towards more sustainable food systems in the EU. Agric. Syst. 194, 103251 https://doi.org/10.1016/j.agsy.2021.103251.

Kühl, M., Jørgensen, B.B., 1992. Microsensor measurements of sulfate reduction and sulfate oxidation in compact microbial communities of aerobic biofilms. Appl. Environ. Microbiol. 58 (4), 1164-1174. https://doi.org/10.1128/aem.58.4.1164-
1174.1992.

Kumar, R.R., Park, B.J., Cho, J.Y., 2013. Application and environmental risks of livestock manure. J. Korean Soc. Appl. Biol. Chem. 56 (5), 497-503. https://doi.org/10.1007/
s13765-013-3184-8.

Lee, S.-H., et al., 2019. New particle formation in the atmosphere: from molecular clusters to global climate. J. Geophys. Res. Atmospheres 124 (13), 7098-7146. https://doi.org/10.1029/2018JD029356.

Liu, D., Nyord, T., Rong, L., Feilberg, A., 2018. Real-time quantification of emissions of volatile organic compounds from land spreading of pig slurry measured by PTR-MS and wind tunnels. Sci. Total Environ. 639, 1079-1087. https://doi.org/10.1016/j.
scitotenv.2018.05.149.

Mackie, R.I., Stroot, P.G., Varel, V.H., 1998. Biochemical identification and biological origin of key odor components in livestock waste. J. Anim. Sci. 76, 1331-1342.

Majchrzak, T., Wojnowski, W., Lubinska-Szczygel, M., Różańska, A., Namieśnik, J., Dymerski, T., 2018. PTR-MS and GC-MS as complementary techniques for analysis of volatiles: a tutorial review. Anal. Chim. Acta 1035, 1-13. https://doi.org/10.1016/j.
aca.2018.06.056.

Ngwabie, N.M., Schade, G.W., Custer, T.G., Linke, S., Hinz, T., 2007. Volatile organic compound emission and other trace gases from selected animal buildings. Landbauforsch. Volkenrode 57 (3), 273-284.

Ni, J.Q., Robarge, W.P., Xiao, C., Heber, A.J., 2012. Volatile organic compounds at swine facilities: a critical review. Chemosphere 89 (7), 769-788. https://doi.org/10.1016/
j.chemosphere.2012.04.061.

Norman, M., Hansel, A., Wisthaler, A., 2007. O2+ as reagent ion in the PTR-MS instrument: detection of gas-phase ammonia. Int. J. Mass Spectrom. 265 (2), 382-387. https://doi.org/10.1016/j.ijms.2007.06.010.

Norman, M., et al., 2009. Intercomparison of ammonia measurement techniques at an intensively managed grassland site (Oensingen, Switzerland). Atmos. Chem. Phys. 9 (8), 2635-2645. https://doi.org/10.5194/acp-9-2635-2009.

Orzi, V., Riva, C., Scaglia, B., D'Imporzano, G., Tambone, F., Adani, F., 2018. Anaerobic digestion coupled with digestate injection reduced odour emissions from soil during manure distribution. Sci. Total Environ. 621, 168-176. https://doi.org/10.1016/j.
scitotenv.2017.11.249.
Parker, D.B., et al., 2013. Odorous VOC emission following land application of swine manure slurry. Atmos. Environ. 66, 91–100. https://doi.org/10.1016/j.atmosenv.2012.01.001.

Qian, M., et al., 2016. Occurrence of trace elements and antibiotics in manure-based fertilizers from the Zhejiang Province of China. Sci. Total Environ. 559, 174–181. https://doi.org/10.1016/j.scitotenv.2016.03.123.

Rabaud, N.E., Ebeler, S.E., Ashbaugh, L.L., Flocchini, R.G., 2003. Characterization and quantification of odorous and non-odorous volatile organic compounds near a commercial dairy in California. Atmos. Environ. 37 (7), 933–940. https://doi.org/10.1016/S1352-2310(02)00970-6.

Salazar Gómez, J.I., Lohmann, H., Krassowski, J., 2016. Determination of volatile organic compounds from biowaste and co-fermentation biogas plants by single-sorbent adsorption. Chemosphere 153, 48–57. https://doi.org/10.1016/j.chemosphere.2016.02.128.

Sánchez-Monedero, M.A., Fernández-Hernández, A., Higashikawa, F.S., Cayuela, M.L., 2018. Relationships between emitted volatile organic compounds and their concentration in the pile during municipal solid waste composting. Waste Manag. 79, 179–187. https://doi.org/10.1016/j.wasman.2018.07.041.

Scheutz, C., et al., 2008. Atmospheric emissions and attenuation of non-methane organic compounds in cover soils at a French landfill. Waste Manag. 28 (10), 1892–1908. https://doi.org/10.1016/j.wasman.2007.09.010.

Schiffman, S.S., Bennett, J.L., Raymer, J.H., 2001. Quantification of odors and odorants from swine operations in North Carolina. Agric. For. Meteorol. 108 (3), 213–240. https://doi.org/10.1016/S0168-1923(01)00239-8.

Schmithausen, A., et al., 2018. Quantification of methane and ammonia emissions in a naturally ventilated barn by using defined criteria to calculate emission rates. Animals 8 (5), 75. https://doi.org/10.3390/ani8050075.

Shaw, S.L., et al., 2007. Volatile organic compound emissions from dairy cows and their waste as measured by proton-transfer-reaction mass spectrometry. Environ. Sci. Technol. 41 (4), 1310–1316. https://doi.org/10.1021/es061475e.

Shober, A.L., Maguire, R.O., 2018. Manure management. In: Reference Module in Earth Systems and Environmental Sciences. Elsevier. https://doi.org/10.1016/B978-0-12-409548-9.09115-6.

Sintermann, J., et al., 2014. Trimethylamine emissions in animal husbandry. Biogeosciences 11 (18), 5073–5085. https://doi.org/10.5194/bg-11-5073-2014.

Strohalm, M., Kavan, D., Novák, P., Volný, M., Havlíček, V., 2010. MMass 3: a cross-platform software environment for precise analysis of mass spectrometric data. Anal. Chem. 82 (11), 4648–4651. https://doi.org/10.1021/ac100818g.

Sun, H., et al., 2008. Alcohol, volatile fatty acid, phenol, and methane emissions from dairy cows and fresh manure. J. Environ. Qual. 37 (2), 615–622. https://doi.org/10.2134/jeq2007.0357.

Tanlong, Z., Bin, S., Hongmin, D., Xiuping, T., Tongshuai, L., Yue, W., 2017. Emission characteristics of volatile organic compounds during pilot swine manure composting. Trans. Chin. Soc. Agric. Eng. Trans. CSAE 33 (6), 192–198. https://doi.org/10.11975/j.issn.1002-6819.2017.06.025.

Toro, M.V., Cremades, L.V., Calbó, J., 2006. Relationship between VOC and NOx emissions and chemical production of tropospheric ozone in the Aburrá Valley (Colombia). Chemosphere 65 (5), 881–888. https://doi.org/10.1016/j.chemosphere.2006.03.013.

Trabue, S., Scoggin, K., Li, H., Burns, R., Xin, H., Hatfield, J., 2010. Speciation of volatile organic compounds from poultry production. Atmos. Environ. 44 (29), 3538–3546. https://doi.org/10.1016/j.atmosenv.2010.06.009.

Wang, Y., et al., 2017. Mitigating greenhouse gas and ammonia emissions from swine manure management: a system analysis. Environ. Sci. Technol. 51 (8), 4503–4511. https://doi.org/10.1021/acs.est.6b06430.

Wang, Y., et al., 2018. Mitigating greenhouse gas and ammonia emissions from beef cattle feedlot production: a system meta-analysis. Environ. Sci. Technol. 52 (19), 11232–11242. https://doi.org/10.1021/acs.est.8b02475.

Wei, W., Wang, S., Chatani, S., Klimont, Z., Cofala, J., Hao, J., 2008. Emission and speciation of non-methane volatile organic compounds from anthropogenic sources in China. Atmos. Environ. 42 (20), 4976–4988. https://doi.org/10.1016/j.atmosenv.2008.02.044.

Williams, P.E.V., 1995. Animal production and European pollution problems. Anim. Feed Sci. Technol. 53 (2), 135–144. https://doi.org/10.1016/0377-8401(95)02017-T.

Woodbury, B.L., Gilley, J.E., Parker, D.B., Marx, D.B., Miller, D.N., Eigenberg, R.A., 2014. Emission of volatile organic compounds after land application of cattle manure. J. Environ. Qual. 43 (4), 1207–1218. https://doi.org/10.2134/jeq2013.05.0185.

Woodbury, B.L., Gilley, J.E., Parker, D.B., Marx, D.B., 2022. Emission of volatile organic compounds from land-applied beef cattle manure as affected by application method, diet, and soil water condition. J. ASABE 65 (1), 123–133. https://doi.org/10.13031/ja.14587.

Wyer, K.E., Kelleghan, D.B., Blanes-Vidal, V., Schauberger, G., Curran, T.P., 2022. Ammonia emissions from agriculture and their contribution to fine particulate matter: a review of implications for human health. J. Environ. Manag. 323, 116285 https://doi.org/10.1016/j.jenvman.2022.116285.

Yao, L., et al., 2018. Atmospheric new particle formation from sulfuric acid and amines in a Chinese megacity. Science 361 (6399), 278–281. https://doi.org/10.1126/science.aao4839.

Yuan, B., et al., 2017. Emissions of volatile organic compounds (VOCs) from concentrated animal feeding operations (CAFOs): chemical compositions and separation of sources 4945–4956. https://doi.org/10.5194/acp-17-4945-2017.

Zhang, B., Tian, H., Lu, C., Dangal, S.R.S., Yang, J., Pan, S., 2017. Global manure nitrogen production and application in cropland during 1860 – 2014 : a 5 arcmin gridded global dataset for Earth system modeling 667–678.

Zhang, Y., Zhu, Z., Zheng, Y., Chen, Y., Yin, F., 2019. Characterization of Volatile Organic Compound (VOC) Emissions from Swine Manure Biogas Digestate Storage¹.

Zheng, J., et al., 2009. Speciated VOC emission inventory and spatial patterns of ozone formation potential in the pearl river delta, China. Environ. Sci. Technol. 43 (22), 8580–8586. https://doi.org/10.1021/es901688e.

Zhu, Y., Zheng, G., Gao, D., Chen, T., Wu, F., 2016. Odor composition analysis and odor indicator selection during sewage sludge composting. J. Air Waste Manag. Assoc. 66 (9), 930–940. https://doi.org/10.1080/10962247.2016.1188865.

Ziemann, P.J., Atkinson, R., 2012. Kinetics, products, and mechanisms of secondary organic aerosol formation. Chem. Soc. Rev. 41 (19), 6582–6605. https://doi.org/10.1039/C2CS35122F.