Next Article in Journal
The Impact of Agricultural Investments on the Economic Efficiency of Production Factors: An Empirical Study of the Wielkopolska Voivodeship
Previous Article in Journal
Design of a Non-Destructive Seed Counting Instrument for Rapeseed Pods Based on Transmission Imaging
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Review on Photocatalytic Applications for Deodorization in Livestock and Poultry Farms

1
College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China
2
Zhejiang Ecological and Environmental Monitoring Center, Hangzhou 310012, China
3
School of Optical, Mechanical and Electrical Engineering, Zhejiang Agriculture & Forestry University, Hangzhou 311300, China
*
Authors to whom correspondence should be addressed.
Agriculture 2024, 14(12), 2216; https://doi.org/10.3390/agriculture14122216
Submission received: 6 November 2024 / Revised: 24 November 2024 / Accepted: 28 November 2024 / Published: 4 December 2024
(This article belongs to the Section Farm Animal Production)

Abstract

:
Odor emissions from intensive livestock and poultry farming operations pose significant environmental and health concerns. Photocatalysis, an advanced oxidation process (AOP), has shown great promise for mitigating odorous gasses in livestock and poultry farming due to its efficiency, environmental friendliness, and mild operating conditions. This review summarizes the principles and performance of photocatalytic deodorization in livestock and poultry farming and evaluates the advancements in photocatalytic deodorization from lab- to field-scale. Photocatalytic systems demonstrate removal efficiencies of up to 98% for ammonia (NH3), 89.9% for hydrogen sulfide (H2S), 99% for volatile organic compounds (VOCs), and 17.2% for particulate matter (PM). However, reduced efficacy occurs in practical applications due to humidity, dust, and pollutant complexity. Key knowledge gaps, such as insufficient field-scale experiments and limited studies on complex pollutants, hinder further improvements in photocatalytic deodorization. Therefore, this review highlights strategies to enhance photocatalytic systems under farming conditions, including an improved photocatalyst design, reactor optimization, and combined technologies. By bridging the gap between lab-scale studies and field-scale applications, this work provides a foundation for developing sustainable and effective odor control solutions for livestock and poultry farming.

1. Introduction

The growing demand for meat, eggs, and milk has been greatly satisfied with the rapid development of intensive livestock and poultry production. Nevertheless, a significant increase in air pollution issues has also arisen, resulting in not only a reduction in animal performance but also discomfort and diseases [1,2]. Odor emission is one of the major contributors to air pollution worldwide, and animal husbandry is the primary contributor to these odorous emissions [3]. Concentrated animal feeding operations (CAFO) contribute environmental air pollutants such as ammonia (NH3), hydrogen sulfide (H2S), volatile organic compounds (VOCs), and particulate matter (PM) [2,4]. Odorous gasses are substantial constituents of the air pollutants contributed by animal husbandry; they harm the atmosphere, animal productive performance, and human health [5]. Moreover, long-term exposure to a mixture of odorous gasses may cause a risk of different diseases including asthma, atopic dermatitis, neurologic damage, and membrane irritation. In severe cases, some gasses, such as acrolein and formaldehyde, also act as carcinogens [5,6,7].
Therefore, a variety of deodorization technologies have been developed for reducing odorous gasses from livestock and poultry farms, and such technologies can be divided into ‘source-based’ and ‘end-of-pipe’ treatments according to the production stage at which it is implemented [8,9]. The source-based technology aims to reduce odor emission fundamentally and it involves dietary manipulation, in-housing management, manure management, etc. The end-of-pipe technology mitigates the malodor exhaust into the environment, involving physical technologies, chemical technologies, and biotechnologies [3,8,10]. Among all odor control technologies, photocatalysis is presented for odor control in both source-based and end-of-pipe treatments.
As an environmentally friendly advanced oxidation process (AOP), photocatalysis has demonstrated considerable potential in effectively degrading odorous gasses emitted from livestock and poultry farms while minimizing secondary pollution [8,11,12]. The application of photocatalytic deodorization in farm settings has been steadily increasing due to several inherent advantages: (1) high removal efficiency for a wide range of odorous pollutants, (2) cost-effectiveness and environmental friendliness, (3) operation under mild reaction conditions, and (4) the capacity to disinfect various pathogens [11,12,13]. The process is initiated by incident light possessing sufficient energy to induce the separation of photogenerated electron (e)–hole (h+) pairs. These electrons and holes can subsequently react with adsorbed substrates (such as water and pollutants) on the photocatalyst surface. Consequently, odorous compounds are further mineralized into harmless byproducts, including CO2, H2O, and other compounds [12,14,15].
The investigation of using photocatalytic systems for mitigating odorous gasses emitted from livestock and poultry farms has garnered significant research attention to date. Experimental studies, ranging from lab-scale to farm-scale, have demonstrated the feasibility of photocatalytic oxidation as a viable method for reducing or eliminating odorous gasses and pathogens [16,17,18,19]. With the recognition of photocatalysis’ effectiveness in livestock and poultry farms, researchers must pursue the development of photocatalytic systems capable of enhancing photoreactions. This entails identifying more reliable photocatalysts, implementing highly efficient light sources, and optimizing photoreactors to enhance mass and photon transfer [20,21]. Despite the fact that photocatalytic deodorization has tremendous advantages and prospects, a series of limitations and challenges are still hindering its scaling up and capability. The major obstacles associated with photocatalytic deodorization consist of low mass and photon transfer when scaling up, by-products and intermediates, deactivation, and lack of farm-scale experiments [22,23,24,25,26]. Few papers provide a comprehensive overview of the current state of photocatalysis in animal husbandry, and summaries on photocatalytic systems employed in realistic livestock and poultry farms are even fewer. Therefore, the aims of this review are to (1) provide a basic introduction to photocatalytic deodorization for animal farms, (2) summarize recent developments and advances in (synergistic) photocatalytic odor control, varying from lab-scale to farm-scale, and evaluate their performances in diverse experimental conditions, and (3) identify practical challenges and discuss future prospects for further applications of photocatalysis in odor control in animal husbandry.

2. Characteristics of Odorous Gasses from Livestock and Poultry Farms

2.1. Compositions of Odorous Gasses from Animal Feeding

The odor from livestock and poultry is a mixture of gasses which include thousands of compounds, most of which can be divided into four categories: ammonia (NH3), hydrogen sulfide (H2S), volatile organic compounds (VOCs), and particulate matter (PM) [10,27].
NH3 is the most common odor component originating from animal production and is mainly generated from the microbial degradation of N-containing organic compounds, such as animal manure and feces [25]. Long-term exposure to NH3 has been proven to cause diseases and reduce animal welfare [28]. H2S is usually produced by the anaerobic process in the animal digestive tract and manure composting. Inorganic sulfate is also an important source of H2S [29].
Compared with NH3, H2S has lower solubility in water and commonly remains in the manure or slurry in the form of microbubbles until these bubbles grow larger or get stirred and finally burst out into the air, leading to a rapid increase in ambient H2S concentration [29,30].
VOCs comprise a large number of compounds that have an initial boiling point of less than or equal to 250 °C, measured at a standard pressure of 101.3 kPa [31]. As the key component for odor sensation, VOCs from animal production are identified to be the major contributors to odor nuisance, most of which present a low concentration but strong odor [31]. Researchers have conducted experiments to identify VOC components and quantify their concentrations in livestock and poultry farms, showing that volatile fatty acids (VFAs), along with alcohols, are usually the most abundant compounds in swine houses; alcohols also play a dominant role in VOC components in cowsheds; the following five compounds made up close to 70% of total VOCs in a poultry house: acetic acid, 2,3-butanedione, methanol, acetone, and ethanol [32,33,34]. According to previous research, primary odorous VOCs in livestock and poultry farming mainly involve volatile fatty acids (VFAs, e.g., acetic acid, propionic acid, and butyric acid), S-containing VOCs (e.g., methanethiol, dimethyl sulfide, and dimethyl disulfide), amines (e.g., trimethylamine), phenolics (e.g., phenol and p-cresol), and indolics (e.g., indole and skatole) [35,36]. As shown in Table 1, they are believed to be responsible for the odor in swine production, and usually cause a strong olfactory impact even at extremely low levels (ppb or ppm) [37]. VOCs associated with livestock and poultry production are generated from animal exhalation, the degradation of animal manure, slurry fermentation, and feed storage, whereas the fermentation of fresh and stored manure and rotten feed are major pathways of VOCs generation [33,38].
Apart from gas-phase components, particulate matter (PM) is another significant air pollutant for odor, and is related to respiratory diseases and immune damage [39]. It is mainly composed of primary coarse particles that originate from stored feed, manure, bedding, animal skin, feathers, and hair [39]. VOCs and some other odorous gasses can be adsorbed to PM, bringing about malodors to PM [31]. PM can also carry numerous bioaerosols with pathogens such as viruses, bacteria, and fungi [16,39]. Some researchers point out that PM, instead of VOCs, accounts for the majority of odor in livestock and poultry buildings [40]. The types of principal odor compositions in livestock and poultry farms and their concentrations are summarized in Table 1.
Table 1. Concentrations of common odorous substances and PM in the air of livestock and poultry farms.
Table 1. Concentrations of common odorous substances and PM in the air of livestock and poultry farms.
Odor ComponentConcentrationOlfactory ThresholdReferences
Livestock FarmPoultry Farm
NH30.66–61.93 ppmv51.9 ± 40.7 ppmv1.347 ppmv[31,41,42]
H2S43.6–367.3 ppbv2–401 ppbv17.8 ppmv[1,36,43]
VOCsMethanethiol (ME)0.28–1.12 ppbv56 ppbv1.05 ppbv[43,44]
Dimethyl sulfide (DMS)4.9 ppbv4.33 ppbv2.24 ppbv[34,43,44]
Dimethyl disulfide (DMDS)22 ppbv53.63 ppbv12.3 ppbv[34,43,44]
Trimethylamine (TMA)3.0–64.7 ppbv-2.4 ppbv[36,43]
Acetic acid (AA)209.5 ppbv315.28 ppbv0.145 ppmv[31,43,45]
Propionic acid (PA)131570.0355 ppmv[43]
Butyric acid (BA)60 ppbv16.92 ppbv3.89 ppbv[34,43]
Acetaldehyde4 ppbv20.36 ppbv0.186 ppmv[36,43]
Xylene0.9 ppbv1.39 ppbv0.1568 ppmv[34]
Phenol2 ppbv-0.11 ppmv[43]
p-Cresol4.76–57.41 ppbv4221.86 ppbv[37,43]
Indole0.12 ppbv3.6 ppbv0.0316 ppbv[31,34,43]
Skatole7.52 ppbv0.718 ppbv0.562 ppbv[34,43]
PMPM2.539–56 μg/m30.01–4.51 μg/m3-[46,47,48]
PM109.0–74.3 μg/m3415 ± 44–761 ± 60 μg/m3-
TSP191–200 μg/m3234–2090 μg/m3-
As can be seen in Table 1, the concentrations of many air pollutants in livestock and poultry farms are relatively low compared to those in industry or laboratory conditions. But most of them have extremely low olfactory thresholds, leading to malodor issues.

2.2. Current Strategies for Abating Odors in Livestock and Poultry Farms

Technologies have been developed for mitigating odorous gasses in livestock and poultry farms, which can be divided into source-based and end-of-pipe technologies [8,9]. To a broader extent, these air treatment methods can be classified as physical, chemical, and biological technologies [5,10,49]. Generally, physical technologies involve adsorption, masking agents, and diffusion. Odor components are physically adsorbed or masked, causing a decrease in odor perception [10]. Chemical technologies use materials that can react with pollutants for odor treatment, acid and caustic scrubbing, non-thermal plasma, and photocatalysis [24]. Biological methods utilize microorganisms and adsorption to metabolize odorous components into CO2 and H2O [10]. Table 2 lists the abovementioned strategies including their mechanism, target pollutants, merits, and demerits.

3. Fundamentals of Photocatalytic Deodorization Systems

3.1. Basic Principles

It was first reported that water was photodegraded into H2 and O2 in 1972, showing the promising potential of photocatalysis in the degradation of contaminants [55,56]. In the 1980s, photocatalysis was utilized to degrade organic pollutants [20]. To date, a myriad of photocatalysts with many functions for environmental remediation have been successfully invented, and numerous corresponding photocatalytic systems have been designed to intensify the photodegradation process [26,57]. Typically, as illustrated in Figure 1, the consideration of a photocatalytic system involves four parts: photocatalyst, light source, photoreactor, and target reactants [14].
Figure 2 shows the overall principles of air pollutants’ photocatalysis processes, which can be divided into five main steps: (1) air pollutants and other reactants are adsorbed on the photocatalyst surface; (2) incident light that carries abundant energy (higher than band gap) activates the photocatalyst, generating an electron (e)–hole (h+) pair; (3) water and oxygen react with a photogenerated electron and hole that transfer to the surface, producing highly reactive species such as hydroxyl radicals (OH∙) and superoxide radicals (O · 2 ); (4) air pollutants react with these oxidative species and are degraded into small molecules (CO2, H2O, etc.). The structures of pathogens are damaged by photocatalysis; (5) products are desorbed from the interface into the environment [12,22,58].
It should be noted that the above steps can occur simultaneously. In reality, however, a variety of unwanted by-products and intermediates are always formed, part of which is adsorbed on the surface, leading to a reduction in the number of photocatalysis active sites [25]. Furthermore, in livestock and poultry farms, the performance of a photocatalytic system is a combined effect of a series of internal factors and external factors, where the former involves properties such as photocatalysis, light source, photoreactor, pollutant concentration, and the latter involves temperature, humidity, air flow rate and other operating conditions in the farms [59]. Accordingly, these influencing factors should be taken into account when designing a capable photocatalytic system for a certain livestock and poultry farm.

3.2. Photocatalysts for Odor Mitigation

So far, a large number of articles have been published to describe photocatalytic applications in various fields, and a lot of work has been devoted to developing alternative photocatalysts or modifying existing photocatalysts [5,60,61]. In general, photocatalysts for odor mitigation are always semiconductors that have the appropriate bandwidth for redox reactions to occur on the surface. Common photocatalysts for odor mitigation usually comprise the following types according to their degree of investigation: TiO2-based photocatalysts and other metal oxide photocatalysts (MOx), metal sulfides (MSx), Bi-based photocatalysts, and MOFs, as well as their numerous modified derivatives [58,61,62].
TiO2 is the most extensively researched photocatalyst for its efficiency, safety, eco-friendly properties, and low cost [63]. TiO2 semiconductors are used for the heterogeneous photocatalysis of livestock and poultry air pollutants, converting them into harmless or less harmful matters [26]. A large proportion of papers published on the topic of “photocatalytic air treatment in livestock and poultry farms” are concerned with TiO2-based photocatalysts, illustrating a huge field of application for odor mitigation in livestock and poultry farms using TiO2-based photocatalytic systems [13,64].
The forms of TiO2 used practically in livestock and poultry farms include directly painting on the building, coating on the reactor surface, or supporting substrates such as activated carbon, zeolites, aluminum oxide, carbon nanofiber or nanorod, graphene, clay, glass material, and paper [8,64,65,66]. As the absolute concentration of various air pollutants from animal production is commonly low, supporting substrates play a role in adsorbing and condensing target pollutants on their structure such as the surface, abundant holes, and tunnels, thus intensifying photoreactions on the active sites. Jansson et al. [67] compared the performances of pure TiO2, zeolites, and zeolite-supported TiO2 photocatalysts synthesized by the incipient wet impregnation method. Their photocatalytic activity was evaluated in a continuous flat stainless steel reactor under UV irradiation at 6.5 mW/cm2 for the removal of VOCs (formaldehyde and trichloroethylene) in the gas phase. The results show that zeolite/TiO2 hybrid composites possess a higher removal efficiency by adjusting the type and Si/Al ratio of zeolite even if the TiO2 content is as low as 8 wt%. This may be related to the enrichment of the reactant, enhancement of its hydrophobicity by a suitable zeolite, and its tremendous surface area endowed by mineral crystalline [67,68]. However, different supporting materials always have different adsorption affinities to various pollutants, which may restrict the extensive utilization of a single supported photocatalyst when confronting considerably numerous types of pollutants in real-farm applications [66].
In order to inhibit the recombination of photoinduced charge carriers and/or extend the light response range into visible light, modified TiO2 photocatalysts have been researched in the past decades [69]. Doping and coupling are common modifying strategies for preparing more efficient photocatalysts [14,70]. Metal cation-doped TiO2 photocatalysts obtain increasing attention and devotion due to their feasibility of doping and powerful adsorption of visible light. Additionally, superoxide radicals (O2) as a key oxidative component during the photocatalytic process become more inclined to generate in the presence of some transition metal ions, such as Ag+ [71,72].
Several practices of cation-doped photocatalysts have been employed to degrade harmful gasses commonly detected in animal production. Liu et al. [73] prepared a series of M-doped TiO2 photocatalysts (M = Mn, Cu, Ni, Co) by the in situ sol–gel method for H2S degradation. The experimental conditions were set at a constant with an inlet supplying H2S at 150 ppm, a gas flow rate of 1 L/min, and a relative humidity of 50%. It was shown that doped TiO2 photocatalysts present higher efficiency in removing H2S but release even less ozone under vacuum UV (VUV) irradiation. Among the aforementioned materials, Mn-doped TiO2 showed the highest H2S removal efficiency of 89.9% without ozone detected in the outlet gas stream [73]. According to Tobaldi et al.’s [56] research on lanthanide-doped P25-TiO2 photocatalysts under visible light irradiation, modified samples are doped via a solid-state reaction and treated thermally at 900 and 1000 °C. To evaluate the performance of these as-prepared materials, the degradation of isopropanol has been measured by determining the formation of acetone. FT-IR analysis demonstrated that modified samples enhance the generation of oxidative species attached to the surface, which is consistent with the previous literature [14,55]. A La-doped photocatalyst at 900 °C treated with 0.025 mol of La possessed the best photocatalytic activity at 32 ppm/h of acetone formation, whereas the reference sample P25 showed a 25 ppm/h acetone formation [56].
Ag-induced photocatalysts can create a surface plasmon resonance (SPR) effect which extends light adsorption so that it enhances photocatalytic efficiency. Also, Ag acts as an electron trap and captures electrons transferred from the conduction band of TiO2 and converts them into superoxide radicals (O2). Photogenerated holes in the valence band remaining on the TiO2 react with water molecules and help in the formation of hydroxyl radicals (OH∙) [74]. It was found by Liu et al. [75] that methyl mercaptan (CH3SH) could be absorbed, in the dark, onto the Ag-induced catalyst surface in which the S-H and C-S bonds were cleaved and, consequently, Ag-S species (like Ag2S, Ag4S2, AgSH, etc.) were found. Under UV-A irradiation, the above species were oxidized into AgSO3-R and AgSO4 which can also react with CH3SH again, and thus, the reaction cycle proceeds. These types of photocatalysts may provide a new approach to the degradation of S-containing compounds in livestock and poultry farms.
Apart from TiO2 based photocatalysts, zinc oxide (ZnO) is regarded as the second most important semiconductor photocatalyst which is low-cost and easily fabricated into nanomaterials [20]. Researchers have demonstrated its ability to remove VOCs such as benzene, toluene, E-benzene, xylene, acetone, and formaldehyde [55,76]. Meanwhile, ZnO photocatalysts display the potential to disinfect pathogens such as Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). It also prevents the growth of both Gram-positive and Gram-negative bacteria [77,78], exhibiting a relatively high removal efficiency in biosafety. When it comes to farm-scale tests, however, there are few field tests of ZnO photocatalysts for reducing odors in farms, which is ascribed to their comparatively weak stability and tendency for irreversible reactions with NH3 [79].
Tungsten oxide (WO3) photocatalysts have a lower bandgap (2.7 eV) than TiO2 and ZnO (3.2 eV), resulting in its high adsorption efficiency in visible light [26]. Experiments of WO3 treating air pollutants, such as acetaldehyde, trichloroethylene, toluene, isopropanol, NH3, and H2S, have been conducted and presented promising prospects in air treatment [80,81]. However, a WO3 photocatalyst has an insufficient ability to reduce O2 into O2, which weakens its photocatalytic performance [82]. Improvements in its performance have been gained by doping, compositing with other materials, or changing its morphology, which is always applicable to most kinds of photocatalysts [80,82].
Cadmium sulfide (CdS) and zinc sulfide (ZnS) are common metal sulfide photocatalysts that are used in air treatment. Nonetheless, both of them tend to be photocorroded under light conditions. In addition, S2− ions can be easily oxidized by photogenerated holes and oxidants in the atmosphere, causing a decrease in its photocatalytic performance and limitation in its long-term stability [14,83].
Bi-based nanomaterials with unique characteristics have been extensively studied for their prominent advantages. Bi can form SCs with a variety of elements and develop many crystal structures with different energy bands, such as BiX (O, S), BiO jXk (X: Cl, Br, I), and BiXmOn (X: W, P, Mo, V, Fe). Bi-based materials have a unique electronic structure that makes them suitable as visible-light photocatalysts. They can also shift the conduction band upwards when hybridized with the O2p orbital, resulting in a narrow bandgap that enables the utilization of visible light [84].

3.3. Light Sources

Due to a significant increase in the demand for the photocatalytic removal of air pollutants, the interest in higher efficiency and low-cost light sources has grown. Light sources are indispensable in a photocatalytic system; accordingly, a capable light source like UV or visible light exceedingly determines the reaction rate of the photocatalytic process [85]. At present, three types of light sources have been employed as irradiation in terms of the required energy of the photocatalyst, solar light (usually simulated by Xenon lamps), conventional mercury UV lamps, and UV-LEDs [86]. In designing or optimizing a photocatalytic process, factors affecting the reaction rate and removal efficiency caused by light sources should be taken into account, including wavelength, intensity, dispersion of irradiance, etc. [87,88].
Overall, light sources in a photocatalytic deodorization system are expected to involve (1) high radiation homogeneity: the improvement in the distribution of light can substantially increase the efficiency of the photocatalytic process [86]. (2) high irradiance: a higher irradiance usually means more photons incident to the reactant, thus enabling the photocatalytic process within a shorter period [89]. The most widely used light source in deodorization systems is UV light, considering its high energetic production, by which electrons can transfer from VB to CB; it is also reported that a shorter wavelength of radiation (e.g., 185 + 254 nm) could help to generate more oxidative species than a longer one (e.g., 365 nm) [90,91]. When using modified TiO2-based photocatalysts, Bi-based photocatalysts, or other visible light-responsive materials, natural illumination or solar light lamps can provide sufficient energy [23].
In the livestock and poultry industry, UV light sources are the most commonly used radiation. Costa et al. [4] researched the effects of TiO2 painting on the air quality in a weaning unit. In this experiment, ten solar spectrum lamps emited UV light ranging from 315 to 400 nm with a power of 36 W for each lamp. The results of this study show that spraying pig house walls with TiO2 can significantly reduce methane and PM10 concentrations, while NH3 concentrations are not significantly reduced. Such a subtle effect on NH3 removal may be due to the low light intensity and poor irradiance uniformity. Lee et al. [8] employed UV-A as the light source for remediating air pollutants and pathogens in poultry farms while also comparing the performances of conventional UV lamps and UV-LEDs. According to their research, a pilot-scale photoreactor was illuminated by either two fluorescent lamps or a 108-LED array chip during different experiments. The tested gas was collected from a layer house where 200 laying hens were stocked. During the experiment, both light sources presented significant mitigating effects on diethyl disulfide (DEDS) and p-cresol with reduction rates of 26% and 47%, 32% and 49%, respectively. With respect to light sources, experiments on reducing NH3, ozone, dimethyl disulfide (DMDS), diethyl disulfide (DEDS), dimethyl trisulfide (DETS), acetic acid (AA), isopentanoic acid (IA), butanoic acid (BA), isovaleric acid (IA), p-cresol, and skatole demonstrated that UV-A LED shows superior photocatalytic performance over fluorescent lamps [18]. UV-A lights predominantly emit photons with a wavelength range of 315–400 nm. Specifically, UV-A light sources prevail over other lights in on-farm deodorization because of their comparatively high energy, sufficient to excite the separation of e/h+ pairs [92]. Compared to UV-B (280–315 nm) and UV-C (100–280 nm) lights, UV-A demonstrates the least injuries to animal and human cells while UV-B and UV-C can directly cause DNA damage to cells and produce ozone, resulting in their lower safety of application [93]. Given the conditions in livestock and poultry barns, PM concentrations are always much higher, in some cases up to several thousand μg/m3, than when outdoors, [46]. Therefore, a UV-A light source shows the best penetrability through the air and the least proneness to scattering and absorbing because of it having the longest wavelength of the three types of UV lights [94].
From a cost and feasibility perspective, it is worth mentioning that newly emerged UV-LEDs (ultraviolet light-emitting diodes) have been applied in the field of photocatalysis as they present a higher efficiency, smaller size, lower cost, longer lifespan, and more environmental features over traditional mercury lamps [86,95]. More importantly, when comparing external quantum efficiency (EQE) and wall-plug efficiency (WPE) within numerous UV-LEDs, UV-A LEDs reach a peak EQE at nearly 90%, whereas a sharp drop of EQE occurs when the wavelength is shorter than 365 nm, indicating that there still exists significant room for improvement in the application of UV-B and UV-C LEDs [95,96]. Moreover, employing UV-LEDs as the light source may bring about some drawbacks. Since the LED is capsuled in a very small size, the distribution of light irradiance in the photocatalytic system performs less uniformly than in mercury UV lamps, which needs to be overcome by optimizing the arrangement of LED arrays or the geometry of illuminated surfaces [87,89,97]. Therefore, it is recommended that selecting the proper distribution of LEDs as the light source for odor mitigation shows benefits over conventional UV lamps because of the high conversion rates, low costs, and applicable feasibility under animal production conditions.

3.4. Photocatalytic Reactors

The design of photocatalytic reactors plays a key role in the photocatalytic deodorization processes [98], especially when aiming to intensify the contact between photocatalysts and air pollutants, scale up the throughput of air treatment, and boost the photon transfer between light sources and illuminated surfaces [21,99]. The two essential factors in photoreactors are mass transfer and photon transfer [20]. To overcome the limitations of mass transfer and photon transfer, researchers have developed a wide range of photoreactors and established mathematical models to optimize the photocatalytic processes [21]. Up to now, photoreactors have been put into use for strengthening pollutant degradation, mainly involving monolithic photoreactors [100,101], annular photoreactors [102,103], packed-bed photoreactors [104,105,106], fluidized-bed photoreactors [107,108,109,110], their modifications and other photoreactors (shown in Figure 3) [22]. Furthermore, when scaling up a photocatalytic reactor into livestock and poultry farms, the efficiency of photocatalytic processes is sophisticated where various parameters, such as photocatalysts, light intensity, the geometry of photoreactors, air velocity, and humidity, are coupled [54,99]. In such cases, modeling methods help us to better understand the mass transfer and photon transfer processes (see Section 6). Researchers have developed models to deeply investigate the hydrodynamic and photocatalytic performance, and in the meantime, improve performances by adjusting parameters among the photocatalytic system [21,54].
The geometry of photoreactors plays a vital role in mass transfer and photon transfer in photocatalytic processes [111]. As mentioned above, an efficient photoreactor should hold a large surface area to volume ratio for the interaction between catalysts and pollutants, as well as an appropriate geometric shape to ensure that each catalytic surface receives sufficient illumination [111,112]. Nevertheless, there are not many reports that focus on the photoreactor design in the field of animal production; they are mostly devoted to materials development at lab-scale [8,113,114]. A brief introduction to the abovementioned photoreactors is exhibited in Table 3.
Su and Hong [114] developed a photocatalytic livestock biogas packed-bed desulfurizer that consists of acrylic cuboids in series (130 cm height × 20 cm width × 20 cm length, total volume = 52 L) with two ultraviolet light tubes (120 cm length, 40 Watt UV fluorescent blacklight, PULSAR, China) attached to each acrylic cuboid. A mixture of Raschig rings was packed into the two acrylic cuboids where a portion of packing materials was coated with anatase TiO2 powder and concrete on their surface. This reactor was used to remove H2S from the biogas of a dairy cattle farm, obtaining an efficiency of nearly 99% under the flow rate of ≤5 mL/min with a retention time of ≥20 min. According to the study by Lee et al. [116], a mobile laboratory applied in livestock barns was exploited. It is capable of treating up to 1.2 m3/s (4320 m3/h) of air through TiO2-based photocatalysis and an adjustable UV-A dose due to the use of LED lamps. The mobile laboratory (7.2 m × 2.4 m × 2.4 m exterior dimensions) was designed to evaluate the effectiveness of UV photocatalysis by directly connecting to the exhaust gasses emitted from the farm. Under a UV-A dose of 5.81 mJ/cm2 and a treatment time of 57 s, this mobile laboratory can reduce 9% and 34% of NH3 and 1-butanol, respectively. It should be pointed out that in livestock and poultry farms, ventilation rates are as high as several m3∙h−1∙animal−1, especially in hot seasons [41,115,117]. Accordingly, photoreactors should not largely influence ventilation when applied to field-tested odor mitigation.

4. Application of Photocatalytic Air Treatment in Livestock and Poultry Farms

In this section, we summarize the reported study on the photocatalytic decomposition of air pollutants associated with livestock and poultry farms in Table 4, Table 5 and Table 6. As indicated in the tables, there has been a scarcity of previous research in real livestock and poultry farms. Therefore, some lab-scale experiments on the photocatalysis of odorous gasses are discussed here. With substantial variations among the following research conditions, some key characteristics were selected for clarifying their performances and comparing them across different experiments, including the experimental conditions (scale, temperature, and relative humidity), light source, irradiance, illumination dose, reactor type, treatment time, photocatalyst and dose, target air pollutants and their removal rates. Nonetheless, some operating conditions were not mentioned in the literature, which posed a challenge in comparing the performance under different conditions. It is worth mentioning that some parameters were not directly obtained from the literature but needed to be calculated based on other implied conditions. In the following sections, we analyzed the photocatalytic degradation of typical air pollutants (NH3, H2S, VOCs, and PM) in livestock and poultry farms and discussed the brief mechanisms, by-products, and intermediates alongside their photocatalytic degradation. Additionally, we proposed probable methods of intensifying the ability of photocatalytic processes in real livestock and poultry farms based on the photocatalytic properties and farming conditions.

4.1. Degradation of NH3

For a better understanding of the degradation routes of NH3 and developing suitable photochemical methods of NH3 removal, specific explanations of NH3 decomposition have been widely researched. In the gas phase containing abundant moisture, including exhausts, from livestock and poultry farms, the main mechanism of NH3 photocatalysis is shown as follows: NH3 can be oxidized by · O H and · O 2 to form HNO2 and further react to form HNO3 [135] (Equation (1)). HNO3 then reacts with NH3 to produce NH4NO3 which decomposes under light irradiation and forms the major product N2 (Equation (2)). It is necessary to mention that harmful by-products like NOx species can also present in such processes (Equation (3)), so researchers have put their efforts into enhancing N2 selectivity and hinder the generation of unwanted by-products or intermediates [136].
N H 3 + r a d i c a l s H N O 2     H N O 3
H N O 3 + N H 3 N H 4 N O 3   h ν   N 2 + 2 H 2 O + O a d s
N O 3 + h + N O 3   h ν N O x + O 2
As is shown in Table 4, previous studies focused on the degradation of NH3 and demonstrated the removal efficiencies ranging from 5 to 97% at lab-scale and larger scales. Such removal efficiencies are sufficient to rival or even surpass the odor-removing strategies commonly used in pig farms at the present stage involving scrubbers and biological methods [137]. In summary, most studies have employed TiO2 (anatase, P25, etc.) as the photocatalyst, mainly due to its high photocatalytic efficiency and low cost for livestock and poultry farms. In practical production, the primary focus remains on the reliability and long-term stability of photocatalytic systems, even though various elaborately modified photocatalysts have demonstrated their superior performance in the photodegradation of NH3 on certain industrial or laboratory occasions. Such remarkable efficiency has yet to be widely confirmed at a larger scale when compared to TiO2 [138]. It was also reported by Kolinko and Kozlov [139] that in comparison to pure TiO2, noble metal-deposited (Ag, Au, Pd, and Pt) and transition metal oxide-deposited (Fe2O3, CoO, NiO, V2O5, and MoO3) TiO2 either generated more N2O or showed lower reaction rates. N2O lasts for about 150 years in the atmosphere as a greenhouse gas and shows more than 300 times higher potential than CO2.
According to Table 4, the real-farm photocatalytic processes mainly took place in monolithic reactors or tunnel-shaped reactors matching the large ventilation rate of livestock and poultry farms. As discussed in the previous section, a well-designed photoreactor ensures higher mass and photon transfer and the feasibility of determining and controlling operating parameters. Experiments using monolithic reactors showed higher removal efficiency than those using tubular or tunnel reactors [18,122,123]. When applying photocatalysis, the concentration of NH3 from a nursery swine building varied from 0.121 ppm to 0.119 ppm; the reduction was not that satisfactory due to the low residence time (0.018 s) [123]. Some research focused on indoor NH3 photocatalytic degradation and painted photocatalysts on the walls of the barn [28,119]. Such an application configuration inside the barns could continuously control NH3 concentration during the process of emission and the NH3 concentration in the swine barn with photocatalytic painting was measured at 3.76 mg/m3, while that in the control group was 5.41 mg/m3 [28]. It is also beneficial for biosecurity as the TiO2 painting eliminates airborne pathogens [140]. However, such a photocatalytic system brought about challenges in quantifying parameters, and its surface to volume area was much lower than in photoreactors.
An evident trend is that experiments in real livestock and poultry farms usually exhibit lower removal efficiency of NH3 compared to laboratory experiments, which may be caused by the accumulation of PM on the photocatalysts’ surfaces, leading to a decrease in the utilization of radiation, according to the previous study by Lee et al. [116]. Hence, it is recommended that before the photocatalytic process of real farm exhaust, a dust reduction stage should be performed as pre-treatment. It can be seen that, while in a certain experiment, a longer treatment time often acts as an essential parameter, among other experiments, treatment time shows little effect on the removal efficiency of NH3, thus implying a higher removal efficiency [13]. This observation indicates that it is fine to modestly reduce the treatment time to reach a higher gas treatment capacity and lower cost without decreasing NH3 removal efficiency.
Another noteworthy aspect of NH3 photocatalytic degradation is the formation of NOx alongside the complex reaction pathways. NOx species are usually generated due to the inherent reaction mechanism and the incomplete reaction [135]. These species are important greenhouse gasses and are even more toxic to humans and animals than NH3. Their generation cannot be completely avoided; however, it should be inhibited through enhancements in the photocatalytic system, such as applying more efficient photocatalysts and reactors [121,141].

4.2. Degradation of H2S

H2S is another air pollutant in livestock and poultry farms, mainly generated from the anaerobic fermentation of manure. The general pathways of H2S photocatalytic degradation are presented in Equations (4)–(8) [142]. S O 4 2 is the primary product and the intermediate product is SO2. Such products are hard to desorb from the photocatalyst and can occupy reactive sites, leading to the deactivation of photocatalysts and secondary pollution [143].
H 2 S a d s + h + / O H · H 2 S · a d s + H S · a d s
H S · a d s + O 2 H S O O · a d s
H S O O · a d s + O 2 S O 2 , a d s + H O · 2 , a d s
S O 2 , a d s + 1 2 O 2 , a d s + H 2 O a d s     H 2 S O 4 , a d s
H 2 S a d s + 8 O H · a d s S O 4 2 + 2 H + + 4 H 2 O a d s
The effect of photocatalysis on the removal of H2S in pilot-scale and farm-scale was not that outstanding, with the removal efficiency below 50%. According to Table 5, despite the lack of literature on the photocatalytic degradation of H2S in livestock and poultry farms, it can be concluded that the photocatalytic degradation performance of H2S appears weaker than that of NH3 under UV-A irradiation [122]. This is because H2S has weaker Bronsted basicity than NH3, resulting in its poor interaction with hydroxyl groups on the TiO2 surface, thereby leading to its lower affinity for the TiO2 photocatalyst [144]. However, when the wavelength drops below 300 nm, the removal efficiency of H2S becomes much higher due to the synergetic effect of photolysis and photocatalysis [73,123]. When applying a photocatalytic method to the removal of H2S in livestock and poultry farms, the light sources with shorter wavelengths could be applied and the photocatalyst should be regularly regenerated by washing off the sulfate accumulated on the catalyst surface [142].

4.3. Degradation of VOCs

Photocatalysis demonstrates strong degradation efficiency towards various VOCs associated with the odor in livestock and poultry farms, including S-containing compounds, VFAs, trimethylamine, and some aromatic compounds [142]. Compared with conventional methods, it represents excellent removal capability for hydrophobic and recalcitrant air pollutants [145]. At lab-scale, the photocatalysis method can degrade nearly all target pollutants, with removal efficiency ranging from 76.3 to 99% [126,127]. Meanwhile, at pilot-scale and farm-scale, the removal efficiency of photocatalysis for VOCs was reduced to several dozen, and its performance showed a decrease because of the complex conditions in the real farms and mass and photon transfer limitations. The photocatalytic degradation of these VOC pollutants is as efficient as that achieved using biomethods, especially S-containing VOCs, but without the drawback of microbial contamination and increased pressure drops [146].
Additionally, Lee et al. [129] were the first to report a significant change in the overall odor ‘character’ from finishing barn emissions after being treated by UV-A photocatalysis. The treated waste gas smelled like a mix of less-offensive odors, including ‘disinfectant’, ‘minty’, or ‘swimming pool’, with a weaker smell of swine manure in the background, and the total odor concentration was reduced from 412 ± 47 OUE/m3 to 251 ± 4.6 OUE/m3, indicating that photocatalysis could effectively reduce malodor nuisance from both the concentration of VOCs and subjective odor perception.
Substantial differences in the chemical properties of these VOCs in livestock and poultry facilities lead to different photocatalytic degradation mechanisms and pathways [147]. Briefly, S-containing compounds like methanethiol, dimethyl sulfide, dimethyl disulfide, etc., in the gas phase are oxidized into S O 4 2 , CO2, H2O, RSnR, sulfoxide, sulfone, and other hydrocarbons [148]. For odorous VFAs in livestock and poultry farms, like propanoic acid and butyric acid, the major products are CO2 and H2O, as well as short-chain carboxylic acid, alcohol, and aldehyde [149]. Trimethylamine represents the most odorous N-containing organic air pollutant in animal production. In the photocatalytic process, trimethylamine can be degraded into CO2, H2O, N2, NOx, alcohol, and acetone [150]. Aromatic compounds like p-cresol and toluene are degraded to form CO2, H2O, 4-methylcatechol, 4-hydroxybenzoic acid, 4-hydroxybenzyl alcohol, 4-hydroxybenzaldehyde, benzoic acid, hydroquinone, benzyl alcohol, and benzaldehyde [151,152]. The possible photocatalytic pathways of the abovementioned pollutants and their by-products and intermediates are much more abundant than in the raw target pollutants.
However, there is definitely not a single type of VOC but a huge mixture of species in the livestock and poultry farms. The specific removal efficiency of most mixed pollutants will be lower than that of the pollutants alone due to the competition for active sites and the emergence of some substances as intermediates in the pathways of other pollutants (e.g., DMDS is a major odorous gas as well as an intermediate during MT and DMS degradation) [148].
Biard et al. [149] researched the photodegradation properties of propanoic acid and butyric acid alone and their binary gaseous mixture at lab-scale and observed a significant decrease in removal efficiency in comparison to the degradation of the pure compounds. The predominant reason is the competitive adsorption of different species. In addition, they also proved that the degradation of propanoic acid with a poorer affinity for the catalyst is more easily affected by other compounds. In spite of the lower adsorption of propanoic acid, it still demonstrated a better degradation rate due to the fewer by-products formed along its pathway than for butyric acid.
Mutual inhibition of VOCs was also observed in the pilot-scale and industrial-scale research of Assadi et al. [131]. The photocatalytic degradation of isovaleraldehyde alone showed a removal efficiency of 28%, whilst only 20% of isovaleraldehyde was degraded under similar experimental conditions, but the pollutant components were a mixture of isovaleraldehyde, isobutyraldehyde, and 2-methyl butyraldehyde.
However, when the total concentration of VOCs is reduced at the ppb level, the interaction between each component may be low. Héquet et al. [153] showed that the degradation rate of toluene, n-decane, and trichloroethylene in a mixture was not significantly lower at the ppb level, nor were the same intermediates under both individual and mixing experimental conditions. The class of key odorous VOCs in real farms is at extremely low levels, ranging from several to hundreds of ppb, as mentioned before [126]. Nevertheless, few studies have focused on the photocatalytic degradation features of VOCs associated with realistic livestock and poultry farms at the ppb level, not to mention mixtures of these VOCs. Therefore, it is imperative to conduct such research on mixed VOC gas at low concentrations from lab- to farm-scale. This is crucial because VOCs constitute a significant portion of the odor emissions in livestock and poultry farms.

4.4. Degradation of PM and Airborne Pathogens

As introduced in the previous section, PM in livestock and poultry farms can absorb and carry odorous compounds, micro-organisms, and their components, which act as odorous gas and pathogen carriers [39]. Photocatalysis can be applied to the abatement of PM and airborne pathogen issues from three aspects, the direct capture of various types of PM [154], the degradation of odorous and toxic compounds carried on PM [155], and the disinfection of airborne pathogens and bioaerosols [156].
Generally, the capture and compound degradation ability of photocatalysis in livestock and poultry farms is much less efficient than the disinfection effect. Most studies have indicated that photocatalysis achieves bacterial disinfection by disrupting the structure of their cell membranes, inflicting irreversible damage on various target sites both inside and outside the cell membranes [157]. Inactivation also takes place toward viruses, distorting the structure of and damage to the encapsulated genome [158]. Lee et al. [16] investigated UV-A photocatalysis for reducing PM and airborne bacteria pathogens. For their PM reduction research, a reactor was connected to a swine manure pit fan, and three types of inlet gas were introduced into the photocatalytic system, waste gas where 96–98% PM was removed, waste gas where 77–86% PM was removed, and unfiltered exhaust from the manure pit fan, respectively. The results showed that UV-A photocatalysis exhibited a low reduction effect on PM concentrations in the swine barn exhaust, whereas the disinfection of pathogens varied significantly from 15 to 95% of CFUs. It was also observed that the lower the total PM concentration in the exhaust, the higher the disinfection efficiency. Zhao et al. [159] designed a pilot-scale UV-PCO scrubber for reducing aerosolized E. faecalis and Infectious Bursal Disease Virus (IBDV) associated with animal farming. They tested the scrubber in a controlled environment at the Animal Health Service and found that E. faecalis was removed to a great extent, even under the irradiation of one single lamp, attaining a removal efficiency of more than 99.7%. In contrast, the efficacy of IBDV elimination was significantly less, with 72.4% of airborne IBDV inactivated. This difference can be attributed to the higher resistance to environmental stress of the virus. In addition, the experimental conditions were similar to those of odorous pollutant removal, suggesting that photocatalysis can remove malodorous gasses in conjunction with airborne pathogens. Researchers have also developed doped and modified photocatalysts that exhibit better disinfection performance due to more oxidative species being generated and the effect of doped ions such as Ag [160]. In addition to end-of-pipe treatment, photocatalytic paint has been proven effective in decomposing PM in barns; 17.2% of PM10 was removed by photocatalytic paint on barn walls in a study by Costa et al. [4].
Despite photocatalysis being deficient in reducing PM concentration, it does show a capability to degrade certain pollutants absorbed in PM. Sohara et al. [155] employed TiO2-supporting quartz fiber filters for degrading polycyclic aromatic hydrocarbons (PAHs). Filters with TiO2 significantly decreased all nine PAH compounds by 37–60% compared to filters without photocatalysts. Moreover, soluble salts existing on PM can inhibit PAH degradation by blocking incident lights and repressing the diffusion of active oxidants.
It is worth noting that, unlike the rapid degradation of gaseous contaminants, photocatalytic PM treatment often requires a much longer duration. This situation is ascribed to the lower solid–solid reaction rate between PM and photocatalysts. Also, the composition of PM includes non-degradable inorganic compounds, consisting of sulfates, nitrates, metal oxides, and carbons, which are unlikely to be decomposed into smaller molecules [161]. Undeniably, PM tends to act as an inhibitor in the photocatalytic process, as discussed before. Hence, it is not desirable to apply a photocatalytic system alone for reducing PM since it would obscure the excellent ability of photocatalysis to handle odor issues.

5. Combined Photocatalytic Deodorization Methods

In Section 4, the individual application of photocatalysis to degrade odorous air pollutants in the livestock and poultry industry was reviewed. Photocatalysis showed remarkable degradation abilities towards NH3, H2S, bioaerosols, and many types VOCs but suffered from constraints such as the weaker degradation efficiency of PM, competition for active sites from mixed components, and deactivation through long-term use. Based on the characteristics of photocatalytic deodorization, it can be concluded that depending solely on photocatalysis may have limited effectiveness in dealing with the multi-component odorous pollutants in livestock and poultry farming [162]. Therefore, attention has been paid to combining different methods to reach higher synergistic performance of biosafety and odor control at lab-scale to farm-scale [120,131]. In general, combined photocatalytic deodorization systems can help to promote the complete mineralization of recalcitrant pollutants, avoid the generation of harmful by-products and intermediates, and prevent the deactivation of the photocatalysts [163,164]. A few studies have also demonstrated the synergistic effect of combined systems on the capability of emission treatment in livestock and poultry farms [52,120], thereby it can be speculated that synergistic photocatalytic deodorization has broad prospects for application.

5.1. Photocatalysis Combined with Non-Thermal Plasma

To improve the performance of photocatalytic systems, novel methods have been developed for synergistic pollutant degradation. Non-thermal plasma (NTP) consists of active species generated by the ionization of neutral gasses at room temperature, including excited atoms, molecules, reactive free radicals, and electrons, which endow NTP with excellent effectiveness upon the decomposition of pollutants [165]. Research showed that a coupled system of non-thermal plasma and photocatalysis demonstrated obvious synergistic performance and decreased by-products within pollutant degradation [162]. According to the position of catalysts, this combined system was divided into two types of catalysis: in-plasma catalysis (IPC), with the photocatalyst placed into the discharge zone, and post-plasma catalysis (PPC), with the photocatalysts placed after the downstream region of plasma discharge (shown in Figure 4) [166]. During the plasma discharge of these two types, some high-energy particles execute a downward transition and emit UV radiation, thus directly activating the photocatalyst. However, this activation effect is believed to be relatively weak. On the other hand, the external electric field can strengthen the generation of highly reactive species. When photocatalysts such as TiO2 particles are in contact with an electrode, micro-discharges could form on the catalyst surface and inside the pores in the discharge region [164,167]. In addition, the plasma-assisted photocatalytic reaction induces gas-phase reaction pathways, leading to increased mineralization of pollutants due to better contact between the reactive particles and pollutants [168,169].
Table 7 summarizes the performance of photocatalysis combined with other methods in the degradation of typical odorous pollutants related to livestock and poultry farms. Most research has been devoted to the IPC type of combined process due to its more powerful synergistic effect than placing the photocatalyst after the discharge area [171].
As shown in Table 7, photocatalysis combined with plasma methods showed better performance than when they were used individually. Assadi, and Saoud et al. [52] conducted many experiments on non-thermal plasma-assisted photocatalytic processes to degrade toxic or odorous air pollutants [130,131,163,172]. As already mentioned, one of the drawbacks of photocatalysis is its deactivation during long-term use, especially when treating S-containing VOCs, which are readily oxidated into non-volatile sulfate compounds. By applying plasma to the regeneration process, the poisoned photocatalyst was fully recovered and the selectivity of CO2 was increased, demonstrating that such a combined method can extend the durability of photocatalytic systems and enable mineralization [163].
Moreover, non-thermal plasma helps to increase photocatalytic performance under conditions of excessively high humidity like in animal farms. Saoud et al. [52] studied the pilot and industrial application of a combined DBD–photocatalysis system for removing pollutants from swine rooms, and the results showed that even in extremely high-humidity environments, the combined method sustained a dramatic degradation efficiency of 95 to 97% for NH3. This synergistic effect could be attributed to the presence of water, which increased the concentration of free radicals. They also found that after being treated by photocatalysis alone or the combined process, the hedonic nature of the odors increased from −2 to −0.5. This enhancement in odor aligns with the study [52] described in previous sections. Additionally, the coupling of plasma and photocatalysis can promote PM decomposition, and this promotion can persist for several months without a significant decrease in removal efficiency [171]
However, excessive moisture in livestock and poultry farms may be detrimental to the degradation of some other pollutants, leading to a reduction in electron density and quenching of the active reactive species, yet ozone and NOx production are reduced [143,164]. Therefore, it is of research value to determine the optimal operating conditions when using the combined methods for a better synergistic effect.
Table 7. Degradation of odorous pollutants by combined photocatalytic methods.
Table 7. Degradation of odorous pollutants by combined photocatalytic methods.
Experimental Conditions
Temp/RH
Experimental ScaleYearReactorTreatment TimePhotocatalyst (Dose)Combined TechnologyPollutantRemoval EfficiencyReference
PhotocatalysisCombined MethodSynergistic Method
20 °C/50%Pilot-scale2014Rectangular planar reactor made of polymethyl methacrylate (PMMA) material with a size of 135 mm × 135 mm × 1 mNRCoated glass fiber tissue (6.5 g/m2)Plasma surface discharge barrier dielectric (SDBD)Trimethylamine~25%, ~20%, and 18% with flow rate of 4, 6, and 10 m3/h, respectively~35%, ~32%, and 28% with flow rate of 4, 6, and 10 m3/h, respectively~74%, ~63%, and 59% with flow rate of 4, 6, and 10 m3/h, respectively[172]
Room temperature/50% Pilot-scale2017NRCoated glass fiber tissue containing colloidal silica and TiO2 (13 g/m2)DBD plasmaBUTY18%28%53%[163]
DMDS28%47%70%
Mixture of BUTY and DMDS19% for BUTY and 5% for DMDS45% for BUTY and 10% for DMDS55% for BUTY and 15% for DMDS
20 °C/5–85%Pilot-scale2023Tubular reactor formed of two concentric Pyrex tubesNRCoated glass fiber tissue containing colloidal silica and TiO2 (13 g/m2)DBD plasmaNH329%37%72%[52]
Propionaldehyde36%42%83%
Industrial-scale NH330–43%26–34%59–96.81%
Ambient temperature/NRPilot-scale2013Rectangular tunnel photoreactor containing pleated photocatalytic mediaNRTiO2 glass fiber tissue (6.5 g/m2)DBD plasmaIsovaleraldehyde~38%~20%~68%[143]
32.4 °C/53%Industrial-scaleTwo similar rectangular tunnel photoreactors connected in seriesNRTiO2 glass fiber tissue (13 g/m2)Isobutyraldehyde/~20%~28%~65%
Isovaleraldehyde~22%~13%~55%
2-methyl butyraldehyde~23%~36%~74%
DMDSNR~37%~24%
20 °C/60%Pilot-scale 2015Tubular reactor formed of two concentric Pyrex tubesNRCoated glass fiber tissue containing colloidal silica and TiO2 (13 g/m2)DBD plasmaTrimethylamine20–35%30–40%59–91%[130]
20 °C/5%Pilot-scale2023Cylindrical reactor with two concentric cylindrical Pyrex glass tubes10.05 sTiO2-loaded glass fiber fabric (NR)Double dielectric barrier discharge (D-DBD) plasmaChlorobenzene18%~30%~75%[167]
20 ± 2 °C/NR Lab-scale2013Tubular reactor with two coaxial quartz tubes0.4–0.8 sTiO2-coated attapulgite at mass ratio of 3:1 (NR)DBD plasmaCS2NR~30–65%~60–70%[171]
100 °C/NR Field-scale2014Coil-shaped reactorsNRTiO2-impregnated Ti-mesh filter (TMiPTM) (NR)DBD plasmaTSPNRNR~98.5%[173]
TVOC97.3–43.8%
30 °C/NR Lab-scale2017Photoreactor: cylindrical reactor constructed of PVC material (pretreatment)
Bio-reactor: acrylic column filled with Raschig rings
6 s (photocatalysis)
20 s (biotrickling)
24 s (combined system)
TiO2 (80% anatase and 20% rutile, NR)Biotrickling filterNH340.9%NR97%[129]
32.0 ± 3.0 °C/68.8 ± 4.4Pilot-scale2012Photoreactor: monolithic reactor
Bio-reactor: rectangular reactor mainly containing a biofiltration bed and a circulating nutrient unit (pretreatment)
7.2 s (photocatalysis)
10.8 s (biotrickling)
18 s (combined system)
Foam nickel coated with P25 (5.19 g/m2)Biotrickling filterEA~75%~90%~99%[174]
Toluene~87%~63%~98%
EB~80%~72%~98%
Xylene~77%~76%~96%
ET~88%~86%~99%
TMB~85%~88%~99%
TVOC85.8–95.1%70.4–89.3%95.8–99.5%
NR/NRPilot-scale2023Photoreactor: photocatalytic scrubber
Bio-reactor: biological scrubber a
4.3 s (both individual and combined systems)25 nm TiO2 (NR)BioscrubberNH389.1%88.3%82.9%[120]
H2S>95%>95%>95%
DMDSNRNR~100%
DMS91.2%~8%~100%
Butyraldehyde,~−10%~15%~90%
Acetaldehyde−51%−18.2%~30%
NR/NRPilot-scale2023Photoreactor: photocatalytic box with a glass roof and stainless steel walls
Bio-reactor: two equal parts of Plexiglas
22–45 s (photocatalysis)
45–90 s (biotrickling)
Foam nickel coated with TiO2 nanoparticles (NR)Biotrickling filterm-xyleneNR~30–75%~60–91%[175]
20–28 °C/~70% Lab-scale2012Photoreactor: annular photoreactor
Bio-reactor: methacrylate biofilter using peat as filter materials
2.7 s (photocatalysis)
44.5 s (biofiltration)
Glass wool-supported TiO2BiofilterToluene6%65%>90%[145]
NR/60%Lab-scale2021Bio-reactor: continuous stirred tank bioreactor27.6 s (photocatalysis)
44.5 s (biological treatment)
TiO2 (<10 g/m2)BiodegradationDichloromethane~65%96.65%99.2%[176]
Note: temperature (Temp), relative humidity (RH), not reported (NR), butyraldehyde, (BUTY), dimethyl disulfide (DMDS), ethyl acetate (EA), ethylbenzene (EB), ethyltoluene (ET), trymethylbenzene (TMB); a there is also one acid scrubber and one caustic scrubber before these two processes (whether individual or combined).

5.2. Photocatalysis Combined with Biomethods

Biological methods have been extensively applied for odor and recalcitrant VOC treatment for several decades [177]. Overall, biological air treatment technology mainly contains biofilters, biotrickling filters, and bioscrubbers [174]. In livestock and poultry farm applications, biological methods prove to be particularly suitable as they can treat exhausts with large volumes and high dust loads in ambient conditions. Moreover, biological methods entail relatively low investment and operational costs, falling between adsorption and advanced oxidation processes, while also releasing minimal harmful by-products and greenhouse gasses [178]. The combined system is usually categorized into three types in the sequence of photocatalysis and biological methods (Figure 5). When biological methods are set downstream, the outlet of the photocatalysis and hydrophobic pollutants such as aromatic hydrocarbons and alkane will be decomposed into water-soluble and biodegradable substances, thus enhancing the mass transfer of the photoreactor. On the other hand, some of the by-products and intermediates can be further degraded by microbial metabolism [179]. Another combination form is to place photocatalysis after biological methods as a post-treatment. This integrated approach addresses recalcitrant pollutants resistant to biological decomposition while concurrently disinfecting microbial aerosol emissions for biosecurity [174,177,180]. By applying a biotrickling filter before photocatalysis, a combined system exhibited remarkable resistance against a shocking load of inlet concentrations and flow rates, whereas only a slight fluctuation in removal efficiency was observed [174]. Unlike plasma-photocatalysis, however, coupling photocatalysis and biomethods into one single reactor is quite a rare occurrence. Though such a combination form can reduce the total volume, the photocatalysis inactivates microorganisms and reduces the synergistic effect [177].
As Table 7 shows, photocatalysis combined with biological methods allows higher performance in treating odorous gasses from livestock and poultry farms. Compared with plasma-assisted photocatalysis, such a combination method shows superior economic feasibility and augments our capability to address substantial exhaust volume and shocking load [124]. Cao et al. [120] developed a combined air-cleaning technology to synergistically reduce air pollutants from livestock houses. In their study, a bioscrubber and photocatalysis were consecutively placed after the acid and caustic scrubbing units. Most odorous gasses, especially hydrophobic VOCs, were removed efficiently due to the synergistic effect, but the odor concentration and bioaerosol were slightly increased in comparison with photocatalysis alone. Hydrophobic and recalcitrant VOCs such as toluene and S-containing compounds can be preliminarily degraded into soluble and biodegradable intermediates like aldehydes, carboxylic acids, and sulfoxides. These substances facilitate rapid mass transfer with the biofilm and serve as carbon sources for microorganisms, thereby enhancing microbial community [145,148]. Combining photocatalysis and biological methods prolongs the lifespan of deodorization. However, the synergistic effect of combined photocatalytic deodorization lacks extensive field testing for further validation and optimization, and bioreactors always bring about extra pressure drops, which may cause insufficient ventilation for animals.

6. Modeling Methods for Scaling up Photocatalytic Systems

When designing a photocatalytic system in livestock and poultry farms, it is advisable to perform experiments at lab-scale to investigate the characteristics of the photocatalyst and pollutant during the photocatalytic process. After that, the obtained data will be used for extrapolating and up-scaling the reactor from the laboratory to a larger size [20,85]. While numerous lab-scale photocatalytic processes for degrading a wide variety of air pollutants have emerged in recent years, these studies did not show high feasibility in commercial or industrial applications let alone in the field of livestock and poultry production. One key limitation that constrains the potential of photocatalysis is the lack of operative intensification and scaling-up methods [181,182]. When designing and scaling up a photocatalytic system, it is crucial to quantitatively research the reduction in air pollutants while accounting for as many influencing factors as possible. The humidity, temperature, light source, gas flow patterns, properties of the photocatalyst, and concentration contribute to the variation in the reaction rate [21,22].

6.1. Kinetic Modeling

The heterogeneous photocatalytic reaction includes two continuous steps: the absorption of the reactant (pollutants, water, etc.) on the catalyst surface and initialization of the oxidization reactions [183]). Hence, the overall reaction rate is largely affected by the absorption process. Up to now, many researchers have proposed a kinetic model to explain the factors affecting the reaction rate. Among those kinetic models, the Langmuir–Hinshelwood model (L-H model) and its variations are the most widely used due to their high interpretability of many photocatalytic reactions [85,109]. As Equation (9) indicates, r is the reaction rate, k is the first-order reaction rate constant, K is the absorption–desorption equilibrium constant, and C represents the reactant concentration on the catalyst surface [21]. In practice, these two parameters are often obtained from curve-fitting 1 k vs. 1 C at different pollutant concentrations [184].
r = k K C 1 + K C
Sopyan fabricated two types of TiO2 thin film made of anatase and rutile TiO2, respectively, and performed experiments on their kinetic parameters. The study employed Equation (10) as a kinetic model to determine k and K in the photocatalytic experiments using linear least-squares analysis. The results indicated that the anatase phase TiO2 photocatalyst had about eight-times larger k than the rutile TiO2 in the degradation of NH3. In the degradation of acetaldehyde, anatase also showed a 5- and 1.5-times larger rate constant (r) than rutile. The data were consistent with the sequence of molecular polarity, NH3 > CH3CHO > H2S, which led to different affinity to TiO2 [144]. Xu et al. [109] improved this simple kinetic model in the form of Equation (2). During their research, the acetaldehyde gas varied between 200 ppm, 500 ppm, and 1000 ppm with an illumination of 2000 lux, and photocatalysis took place in a fluidized-bed reactor at a temperature of 20 °C and humidity of 20%. The regression results using Equation (10) as the kinetic model demonstrated that the model with m = 1 and n = 2 made the most accurate prediction (error rate equal to 0.02), whereas the simple L-H model (i.e., m = n = 1) also showed a satisfactory result (error rate equal to 0.05).
r = k K C m 1 + K C n
In the actual photocatalytic process of degrading pollutants from livestock and poultry farms, the reaction products and pathways always comprise multiple species and approaches due to the complex composition of gasses and intrinsic properties of photocatalytic reactions [135]. When the substance absorbed on the catalyst surface is not unique, the competitive relationship between different reactants (origin reactants, intermediates, and by-products) must be taken into account [21]. Therefore, the L-H model can be rewritten as Equation (3).
r = k K C p 1 + 1 j K i C i
r = k K C p 1 + K p C p + K w C w
where j refers to the count of reactants and Cp refers to the target pollutant concentration on the surface. For example, water vapor is a compound that commonly competes for active sites, so the kinetic model can be modified according to Equation (4). Where Kp is the equilibrium constant of the pollutant, Kw is the equilibrium constant of water vapor, and Kw is the equilibrium constant of the pollutant [21]. If incorporating both the effect of irradiation and competitive compounds, the reaction kinetic model can be written as Equation (5).
r = I λ n k K C p 1 + 1 j K i C i
where I refers to the light irradiance, λ refers to the light wavelength, and n is representative of the electron transfer coefficient. The exponent n mainly depends on the catalyst irradiation and wavelength [20,185]. More specifically, when the incident illumination is low, n is close to 1, implying an approximately linear relationship between irradiance and n. As the light intensity increases, however, n decreases sharply below 0.5 and even 0 at very high photon flux values, which may be ascribed to the limited active sites on catalysts or the prominence of the recombination of electrons and holes [20,21,138]. In the study of Salvadó-Estivill et al. [186], the exponent n in Equation (5) was first-order on the light irradiance from 6.2 to 28.1 W/m2. They conducted a trichloroethylene (TCE) photocatalytic experiment in a plate reactor with a 75 mm × 100 mm glass plate coated with the photocatalyst. This reactor was illuminated by five fluorescent lamps (Philips TL 8W/08 F8T5/BLB, 0.0155 m bulb diameter, 0.26 m bulb length, and 1.2 W UV-A output). As the inlet concentration of TCE increased from 25.1 to 40.5 μM, the reaction rate remained linear with light intensity (n = 1). The authors of [185] conducted experiments on the photocatalytic degradation of dimethyl sulfide (DMS) in a flowthrough planar film reactor under varied LED illuminations. The inlet concentration of DMS was controlled at 3 ppmv, and the resident time was 15 s. The relationships between light intensity and reaction rate are shown in Table 8.
Therefore, the intrinsic parameters of the photocatalytic process should be studied extensively, that is, the intrinsic parameters are usually inferred from inherent mechanisms during photocatalysis and contain properties of catalysts or reactions independent of mass or transfer limitations, which are unrelated to other parameters such as the light intensity and geometry of photoreactors [187]. It is beneficial for researchers to obtain values decoupled from certain reactor designs and consequently replicate kinetic models in scaled-up systems, such as in commercial applications and field testing [20]. Salvadores et al. [188] investigated the degradation of acetaldehyde in a self-designed continuous flat photoreactor where the coated acrylic pieces were placed between the reactor walls and irradiated with seven fluorescent visible radiation lamps. Three different paints varying in TiO2 quantity (12, 14, and 18% w/w) were synthesized to assess their degradation. An intrinsic kinetic model of acetaldehyde and intermediate formaldehyde was proposed as a function of the Local Superficial Rate of Photon Adsorption (LSRPA). They validated the model by performing experiments under different conditions, and the results indicated that the RMSE between the model predictions and experimental outlet concentrations for the three photocatalytic paints and different experimental conditions was 5.74% for acetaldehyde and 9.97% for formaldehyde. Moreover, intrinsic kinetic and adsorption constants have been studied for the photodegradation of common VOCs, including acetone, acetaldehyde, toluene, and isopropanol [21]. Although the intrinsic kinetic parameters are crucial for the photocatalytic system when scaled up, there still exists a demand for future studies on intrinsic parameters in the deodorization of livestock and poultry farms.

6.2. Irradiation Transport Modeling

As is illustrated in the previous sections, light intensity exhibits a huge contribution to the photocatalytic reaction rates, and the light uniformity on the illuminated surface becomes essential as well. Therefore, modeling the radiation field can be useful for investigating and optimizing light distribution. It is believed that along the travel through a medium, a bundle of light rays undergoes absorption, out-scattering, and in-scattering [20]. Accurate modeling of the radiation field within the photoreactor necessitates solving the radiative transfer equation (RTE) within the appropriate coordinate framework. The rigorous modeling of the radiation field in the photoreactor requires the radiative transfer equation (RTE) solution in the appropriate coordinate system [20,189].
d I λ s , Ω d s = κ a , λ I λ s , Ω σ s , λ I λ s , Ω + σ s , λ 4 π 0 4 π p ( Ω Ω ) I λ ( s , Ω ) d Ω
where the first term on the right-hand side represents the absorbed radiation, the second term represents the out-scattering of radiation, and the third term represents the energy increase resulting from the in-scattering of radiation. The parameters κ a , λ and σ s , λ refer to the wavelength-dependent absorption and scattering coefficients of the medium. p ( Ω Ω ) is the phase function, which characterizes the directional distribution of scattered radiation as it transitions from direction Ω to Ω . From the RTE, we can calculate its intensity and its wavelength within the whole reactor.
For different photoreactors and photocatalytic materials, Equation (6) is usually simplified to reduce the complexity. In some photocatalytic systems, catalysts are painted or coated on the reactor walls, becoming aggregated and immobilized on the walls [17,19,105]. In such cases, the scattering appears negligible compared to the absorption when the catalyst particles are close together [190]. Hence, RTE is reduced to the Beer–Lambert Law (Equation (7)) or the integral form (Equations (15) and (16)) [187,191]:
d I λ ( s , Ω ) d s = κ a , λ I λ s , Ω
I = I 0 e μ x
where I is the light intensity through the catalyst layer, μ is the attenuation coefficient that is determined by the photocatalyst, and x is the thickness of the photocatalyst layer. Equation (8) indicates the exponential decrease in the light traveling through a photocatalytic material [190]. Specifically, photocatalytic and optic interplay often occur on the thin film of monolithic reactors, annular reactors, and plug-flow reactors. However, in the case of slurry reactors, the interplay between reactors and lights becomes volumetric. In such cases, the incident intensity at any point from all directions can be expressed as Equation (9). The local volumetric rate of photon absorption (LVRPA) is further calculated and it is proportional to the reaction rate according to Equations (17) and (18) [20,192].
E = 0 4 π I λ ( s , Ω ) d Ω
L V R P A = κ a , λ 0 4 π I λ ( s , Ω ) d Ω = κ a , λ E
As the RTE is a transcendental equation, it is hard to obtain exact solutions using algebraic methods. Therefore, the P1 model, discrete ordinate (DO) method, finite volume (FV) method, and Monte Carlo (MC) method, and their integration with commercial CFD software, such as COMSOL Multiphysics® (version 5.3a) and ANSYS Fluent® CFX-14.0, have been employed to solve RTE questions [192,193,194]. Aside from these isolated methods, researchers have combined the MC method and conventional geometric optics and further proposed the ray-tracing simulation technique for determining the path of each single ray. By applying ray-tracing software or a ray-tracing algorithm to reactor design, researchers can simulate, evaluate, and improve the performance of photoreactors [194,195,196].

6.3. Computational Fluid Dynamics Modeling

In the direction of gaseous deodorization from livestock and poultry farms, computational fluid dynamics (CFD) modeling is extensively regarded as an effective tool for calculating hydrodynamics and mass transfer patterns, enabling researchers to couple parameters present in the photocatalytic processes [189]. As the photoreactor scaling-up process requires about a focus on a series of coupled parameters under livestock and poultry farm circumstances, CFD modeling can effectively predict the performance of photocatalytic systems, including their mass transfer efficiency, radiation uniformity, and removal efficiency [104]. The temperature in livestock and poultry farms is typically room temperature, indicating that the gas flow can be seen as a Newtonian incompressible fluid with constant physical properties, and the exhaust from farms is always regarded as laminar [20]. The classical Navier–Stokes (N–S) equations (Equations (19)–(21)) can be introduced to calculate the mass balance of exhaust-containing pollutants [21].
ρ t + ( ρ v ) = 0
( ρ v ) t + ρ v v = p + μ 2 v + ρ g
C i t = v C i + D i C i + r i C i
where ρ is the density, v is the velocity vector, p is the pressure, μ is the dynamic viscosity, ρ g is the gravitational force, C i is the concentration of the air pollutant i, D i is the diffusion coefficient of substance I, and r i C i is the generation or reduction rate of substance i.
For the practical application of the CFD model to photocatalytic systems, researchers first model the geometry of photoreactors into mesh elements and establish the gas flow patterns [197]. After that, the radiation model should be correctly developed according to the radiation characteristics of the light source, where the exact luminous characteristics are often determined from experiments. Reaction kinetics, including adsorption–desorption and photocatalytic reaction kinetic parameters, are subsequently established, as in the case of the L-H model and its modified forms. With all the coupled parameters and boundary conditions ready, computers will simulate the reaction process and conclude if the performance is satisfactory [198,199].

7. Future Prospects

The application of photocatalysis has shown promising effects on the improvement in air quality due to its numerous advantages. Photocatalysis is recognized as a sustainable method of effectively dealing with odor issues, and great progress has been made in elucidating its mechanism and light effects and creating modified photocatalysts for better performance.
At present, however, the application of photocatalytic processes in livestock and poultry farms still faces many challenges. Practical farming conditions often involve high humidity, high dust concentrations, diverse pollutant compounds, and other environmental interferences, requiring photocatalysts to possess high stability and adaptability [200]. Moreover, due to the lack of research in this field, the current low efficiency of photocatalytic reactors limits their deodorization performance in practical applications. Further, limited farm-scale photocatalytic experiments have been conducted, making it challenging to ensure that photocatalysis maintains its high performance under practical conditions. Additionally, the formation of by-products is unavoidable in photocatalytic processes due to their inherent characteristics, and some by-products or intermediates may still exhibit malodor or toxicity.
Based on the aforementioned analysis, researchers are urged to adopt comprehensive strategies to improve the current conditions. Firstly, the development of photocatalysts tailored for practical farming environments with high performance, achieved through various modified methods, is paramount [201]. Such modifications serve dual purposes: they optimize light energy utilization across both the visible and UV spectra, thereby broadening the range of light responses and increasing the reduction rate, while also conferring enhanced stability and efficiency in real-world applications. Secondly, leveraging energy-efficient light sources can enhance cost-effectiveness. With the continual decrease in the costs and improvement in the luminous efficiency of UV-LEDs, they are anticipated to supplant conventional UV lamps, offering superior activation of photocatalysts with reduced energy consumption [202].
In terms of photoreactor design, concerted efforts should be directed towards developing reactors that enhance both mass and photon transfer. Monolithic reactors, distinguished by their substantial surface-to-volume ratio, exceptionally high exhaust throughput, and minimal interference with production facility ventilation, are particularly well suited for photocatalytic applications in livestock and poultry farms. Furthermore, under sophisticated farming conditions, a standalone photocatalytic system may appear somewhat insufficient. One efficient way of overcoming this is combining different methods, like non-thermal plasma and biological methods, with photocatalysis. The synergistic effects can mitigate the intrinsic drawbacks of photocatalysis, such as limited PM degradation capability and the formation of harmful by-products, and achieve higher performance than the sum of individual methods [164,177]. Finally, to bridge the gap between lab-scale tests and farm-scale applications, modeling methods should be widely applied to understand components’ behavior within photocatalytic systems in indoor air treatment. Taking all of these parameters into account, computational tools are likely to become fundamental for designing and scaling up photoreactors [21].

8. Conclusions

This review provides an overview of photocatalysis applied in the deodorization process in livestock and poultry farms with research from lab-scale to farm-scale. In this review, the increasingly prominent odor issues in livestock and poultry farming are introduced. Odors in livestock and poultry farms contain a mixture of various intricate odor compounds, where the odorous gasses produced are characterized by a large volume, a low absolute concentration, and a complex composition. Photocatalytic deodorization, recognized as an AOP, offers significant advantages, including high removal efficiencies, environmental sustainability, and operational flexibility under mild conditions. Photocatalytic systems have demonstrated remarkable capability, achieving removal efficiencies of up to 98% for NH3, 89.9% for H2S, and 99% for VOCs, which underscores the potential of photocatalysis as a superior alternative to odor control technologies.
A photocatalytic deodorization system consists of photocatalysts, light sources, and reactors, and relies on their effective coordination. Semiconductors such as TiO2 are the most studied photocatalysts, and in this paper, other photocatalytic materials and methods of enhancing them are also discussed. To drive photocatalytic reactions more effectively, UV-LEDs are considered to be a future solution for providing abundant radiation and use less energy than conventional UV lamps. Some visible light-driven photocatalysts could effectively reduce the costs of illumination sources. From an application standpoint, however, both photocatalysts and light sources need to be arranged within the appropriate reactors for better mass transfer and photon transfer. Monolithic reactors, annular reactors, packed-bed reactors, and fluidized-bed reactors were discussed in this paper, and monolithic reactors are believed to be the most suitable configurations for treating exhausts with large flow rates in real farms.
However, the removal efficiency in practical applications is lower when treating real exhausts that contain numerous compounds and high humidity. For example, photocatalysis cannot effectively decrease PM concentration and even deactivates under dusty conditions. Thus, the combination of photocatalysis and other deodorization methods is of vital importance for synergistically removing odorous pollutants. Non-thermal plasma can introduce gas-phase reaction routes, reduce the formation of by-products, and help regenerate photocatalysts even with low treatment time. Biological methods are effective in degrading hydrophilic VOCs and PM through absorption and microbial activity. In addition, the combined system can better resist huge concentration fluctuations (shocking loads) in livestock and poultry farms. Future studies on farm-scale applications should utilize modeling methods and computational tools to better understand the kinetics, light distribution, and fluid patterns. Bridging the gap between lab/pilot-scale and large/farm-scale experiments is still a challenging issue relying on various parameters. Photocatalytic deodorization in livestock and poultry farms is still in its early stages, necessitating researchers to dedicate efforts towards exploring and developing efficient and cost-effective technologies and processes.

Author Contributions

D.H.: conceptualization, formal analysis, methodology, writing—original draft; Q.S.: writing—review and editing, investigation, formal analysis; X.Y.: data curation, supervision; X.Z.: data curation; X.W.: data curation; K.W.: data curation, review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Zhejiang Provincial Department of Agriculture and Rural Affairs, grant number 2023SNJF55; the Key R&D Projects of Zhejiang Province (2022C02015); Zhejiang Provincial Department of Agriculture and Rural Affairs, grant number 2023ZDXT12; and Zhejiang Provincial Department of Agriculture and Rural Affairs, grant number 2024SNJF041.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Hamon, L.; Andrès, Y.; Dumont, E. Aerial Pollutants in Swine Buildings: A Review of Their Characterization and Methods to Reduce Them. Environ. Sci. Technol. 2012, 46, 12287–12301. [Google Scholar] [CrossRef] [PubMed]
  2. Guo, L.; Zhao, B.; Jia, Y.; He, F.; Chen, W. Mitigation Strategies of Air Pollutants for Mechanical Ventilated Livestock and Poultry Housing—A Review. Atmosphere 2022, 13, 452. [Google Scholar] [CrossRef]
  3. Cao, T.; Zheng, Y.; Dong, H. Control of Odor Emissions from Livestock Farms: A Review. Environ. Res. 2023, 225, 115545. [Google Scholar] [CrossRef] [PubMed]
  4. Costa, A.; Chiarello, G.L.; Selli, E.; Guarino, M. Effects of TiO2 Based Photocatalytic Paint on Concentrations and Emissions of Pollutants and on Animal Performance in a Swine Weaning Unit. J. Environ. Manag. 2012, 96, 86–90. [Google Scholar] [CrossRef] [PubMed]
  5. Talaiekhozani, A.; Rezania, S.; Kim, K.-H.; Sanaye, R.; Amani, A.M. Recent Advances in Photocatalytic Removal of Organic and Inorganic Pollutants in Air. J. Clean. Prod. 2021, 278, 123895. [Google Scholar] [CrossRef]
  6. Trabue, S.; Scoggin, K.; Tyndall, J.; Sauer, T.; Hernandez-Ramirez, G.; Pfeiffer, R.; Hatfield, J. Odorous Compounds Sources and Transport from a Swine Deep-Pit Finishing Operation: A Case Study. J. Environ. Manag. 2019, 233, 12–23. [Google Scholar] [CrossRef]
  7. Piccardo, M.T.; Geretto, M.; Pulliero, A.; Izzotti, A. Odor Emissions: A Public Health Concern for Health Risk Perception. Environ. Res. 2022, 204, 112121. [Google Scholar] [CrossRef]
  8. Lee, M.; Koziel, J.A.; Li, P.; Jenks, W.S. Mitigation of Air Pollutants by UV-A Photocatalysis in Livestock and Poultry Farming: A Mini-Review. Catalysts 2022, 12, 782. [Google Scholar] [CrossRef]
  9. Wi, J.; Lee, S.; Kim, E.; Lee, M.; Koziel, J.; Ahn, H. Evaluation of Semi-Continuous Pit Manure Recharge System Performance on Mitigation of Ammonia and Hydrogen Sulfide Emissions from a Swine Finishing Barn. Atmosphere 2019, 10, 170. [Google Scholar] [CrossRef]
  10. Wang, Y.-C.; Han, M.-F.; Jia, T.-P.; Hu, X.-R.; Zhu, H.-Q.; Tong, Z.; Lin, Y.-T.; Wang, C.; Liu, D.-Z.; Peng, Y.-Z.; et al. Emissions, Measurement, and Control of Odor in Livestock Farms: A Review. Sci. Total Environ. 2021, 776, 145735. [Google Scholar] [CrossRef]
  11. Pu, S.; Long, D.; Liu, Z.; Yang, F.; Zhu, J. Preparation of RGO-P25 Nanocomposites for the Photocatalytic Degradation of Ammonia in Livestock Farms. Catalysts 2018, 8, 189. [Google Scholar] [CrossRef]
  12. Wang, H.; Li, X.; Zhao, X.; Li, C.; Song, X.; Zhang, P.; Huo, P.; Li, X. A Review on Heterogeneous Photocatalysis for Environmental Remediation: From Semiconductors to Modification Strategies. Chin. J. Catal. 2022, 43, 178–214. [Google Scholar] [CrossRef]
  13. Konkol, D.; Popiela, E.; Skrzypczak, D.; Izydorczyk, G.; Mikula, K.; Moustakas, K.; Opaliński, S.; Korczyński, M.; Witek-Krowiak, A.; Chojnacka, K. Recent Innovations in Various Methods of Harmful Gases Conversion and Its Mechanism in Poultry Farms. Environ. Res. 2022, 214, 113825. [Google Scholar] [CrossRef] [PubMed]
  14. Ren, H.; Koshy, P.; Chen, W.-F.; Qi, S.; Sorrell, C.C. Photocatalytic Materials and Technologies for Air Purification. J. Hazard. Mater. 2017, 325, 340–366. [Google Scholar] [CrossRef] [PubMed]
  15. Zhu, S.; Wang, D. Photocatalysis: Basic Principles, Diverse Forms of Implementations and Emerging Scientific Opportunities. Adv. Energy Mater. 2017, 7, 1700841. [Google Scholar] [CrossRef]
  16. Lee, M.; Koziel, J.A.; Macedo, N.; Li, P.; Chen, B.; Jenks, W.S.; Zimmerman, J.; Paris, R.V. Mitigation of Particulate Matter and Airborne Pathogens in Swine Barn Emissions with Filtration and UV-A Photocatalysis. Catalysts 2021, 11, 1302. [Google Scholar] [CrossRef]
  17. Lee, M.; Koziel, J.A.; Murphy, W.; Jenks, W.; Chen, B.; Li, P.; Banik, C. Field-Scale Testing of Mobile Laboratory for Mitigation of Gaseous Emissions from the Swine Farm with UV-A Photocatalysis. In Proceedings of the 2021 ASABE Annual International Virtual Meeting, Online, 12–16 July 2021; American Society of Agricultural and Biological Engineers: St. Joseph, MI, USA, 2021. [Google Scholar]
  18. Lee, M.; Li, P.; Koziel, J.A.; Ahn, H.; Wi, J.; Chen, B.; Meiirkhanuly, Z.; Banik, C.; Jenks, W.S. Pilot-Scale Testing of UV-A Light Treatment for Mitigation of NH3, H2S, GHGs, VOCs, Odor, and O3 Inside the Poultry Barn. Front. Chem. 2020, 8, 613. [Google Scholar] [CrossRef]
  19. Lei, D.; Xie, X.; Xiang, Y.; Huang, X.; Xiao, F.; Cao, J.; Li, G.; Leung, D.Y.C.; Huang, H. An Efficient Process for Aromatic VOCs Degradation: Combination of VUV Photolysis and Photocatalytic Oxidation in a Wet Scrubber. Chemosphere 2022, 309, 136656. [Google Scholar] [CrossRef]
  20. Boyjoo, Y.; Sun, H.; Liu, J.; Pareek, V.K.; Wang, S. A Review on Photocatalysis for Air Treatment: From Catalyst Development to Reactor Design. Chem. Eng. J. 2017, 310, 537–559. [Google Scholar] [CrossRef]
  21. Oliveira de Brito Lira, J.; Riella, H.G.; Padoin, N.; Soares, C. An Overview of Photoreactors and Computational Modeling for the Intensification of Photocatalytic Processes in the Gas-Phase: State-of-Art. J. Environ. Chem. Eng. 2021, 9, 105068. [Google Scholar] [CrossRef]
  22. Escobedo, S.; de Lasa, H. Photocatalysis for Air Treatment Processes: Current Technologies and Future Applications for the Removal of Organic Pollutants and Viruses. Catalysts 2020, 10, 966. [Google Scholar] [CrossRef]
  23. Weon, S.; He, F.; Choi, W. Status and Challenges in Photocatalytic Nanotechnology for Cleaning Air Polluted with Volatile Organic Compounds: Visible Light Utilization and Catalyst Deactivation. Environ. Sci.-Nano 2019, 6, 3185–3214. [Google Scholar] [CrossRef]
  24. Zhong, L.; Haghighat, F. Photocatalytic Air Cleaners and Materials Technologies—Abilities and Limitations. Build. Environ. 2015, 91, 191–203. [Google Scholar] [CrossRef]
  25. Li, Y.-W.; Ma, W.-L. Photocatalytic Oxidation Technology for Indoor Air Pollutants Elimination: A Review. Chemosphere 2021, 280, 130667. [Google Scholar] [CrossRef]
  26. Ahmad, R.; Ahmad, Z.; Khan, A.U.; Mastoi, N.R.; Aslam, M.; Kim, J. Photocatalytic Systems as an Advanced Environmental Remediation: Recent Developments, Limitations and New Avenues for Applications. J. Environ. Chem. Eng. 2016, 4, 4143–4164. [Google Scholar] [CrossRef]
  27. Mackie, R.I.; Stroot, P.G.; Varel, V.H. Biochemical Identification and Biological Origin of Key Odor Components in Livestock Waste. J. Anim. Sci. 1998, 76, 1331. [Google Scholar] [CrossRef]
  28. Guarino, M.; Costa, A.; Porro, M. Photocatalytic TiO2 Coating—To Reduce Ammonia and Greenhouse Gases Concentration and Emission from Animal Husbandries. Bioresour. Technol. 2008, 99, 2650–2658. [Google Scholar] [CrossRef]
  29. Blunden, J.; Aneja, V.P.; Westerman, P.W. Measurement and Analysis of Ammonia and Hydrogen Sulfide Emissions from a Mechanically Ventilated Swine Confinement Building in North Carolina. Atmos. Environ. 2008, 42, 3315–3331. [Google Scholar] [CrossRef]
  30. Ni, J.-Q. Factors Affecting Toxic Hydrogen Sulfide Concentrations on Swine Farms—Sulfur Source, Release Mechanism, and Ventilation. J. Clean. Prod. 2021, 322, 129126. [Google Scholar] [CrossRef]
  31. Ni, J.-Q.; Robarge, W.P.; Xiao, C.; Heber, A.J. Volatile Organic Compounds at Swine Facilities: A Critical Review. Chemosphere 2012, 89, 769–788. [Google Scholar] [CrossRef]
  32. Ngwabie, N.M.; Schade, G.W.; Custer, T.G.; Linke, S.; Hinz, T. Abundances and Flux Estimates of Volatile Organic Compounds from a Dairy Cowshed in Germany. J. Environ. Qual. 2008, 37, 565–573. [Google Scholar] [CrossRef] [PubMed]
  33. Yuan, B.; Coggon, M.M.; Koss, A.R.; Warneke, C.; Eilerman, S.; Peischl, J.; Aikin, K.C.; Ryerson, T.B.; de Gouw, J.A. Emissions of Volatile Organic Compounds (VOCs) from Concentrated Animal Feeding Operations (CAFOs): Chemical Compositions and Separation of Sources. Atmos. Chem. Phys. 2017, 17, 4945–4956. [Google Scholar] [CrossRef]
  34. Trabue, S.; Scoggin, K.; Li, H.; Burns, R.; Xin, H.; Hatfield, J. Speciation of Volatile Organic Compounds from Poultry Production. Atmos. Environ. 2010, 44, 3538–3546. [Google Scholar] [CrossRef]
  35. Van Huffel, K.; Hansen, M.J.; Feilberg, A.; Liu, D.; Van Langenhove, H. Level and Distribution of Odorous Compounds in Pig Exhaust Air from Combined Room and Pit Ventilation. Agric. Ecosyst. Environ. 2016, 218, 209–219. [Google Scholar] [CrossRef]
  36. Seo, S.-C.; Lee, W.-J.; Kim, D.-Y.; Kim, K.-Y. Temporal Distribution Characteristics of Odorous Compounds in Swine Houses of South Korea. Air Qual. Atmos. Health 2023, 16, 2003–2017. [Google Scholar] [CrossRef]
  37. Yang, X.; Zhu, W.; Koziel, J.A.; Cai, L.; Jenks, W.S.; Laor, Y.; Leeuwen, J.H.V.; Hoff, S.J. Improved Quantification of Livestock Associated Odorous Volatile Organic Compounds in a Standard Flow-through System Using Solid-Phase Microextraction and Gas Chromatography–Mass Spectrometry. J. Chromatogr. A 2015, 1414, 31–40. [Google Scholar] [CrossRef]
  38. Nie, E.; Zheng, G.; Ma, C. Characterization of Odorous Pollution and Health Risk Assessment of Volatile Organic Compound Emissions in Swine Facilities. Atmos. Environ. 2020, 223, 117233. [Google Scholar] [CrossRef]
  39. Cambra-López, M.; Aarnink, A.J.A.; Zhao, Y.; Calvet, S.; Torres, A.G. Airborne Particulate Matter from Livestock Production Systems: A Review of an Air Pollution Problem. Environ. Pollut. 2010, 158, 1–17. [Google Scholar] [CrossRef]
  40. Yang, X.; Lorjaroenphon, Y.; Cadwallader, K.R.; Wang, X.; Zhang, Y.; Lee, J. Analysis of Particle-Borne Odorants Emitted from Concentrated Animal Feeding Operations. Sci. Total Environ. 2014, 490, 322–333. [Google Scholar] [CrossRef]
  41. Chai, L.; Ni, J.-Q.; Diehl, C.A.; Kilic, I.; Heber, A.J.; Chen, Y.; Cortus, E.L.; Bogan, B.W.; Lim, T.T.; Ramirez-Dorronsoro, J.-C.; et al. Ventilation Rates in Large Commercial Layer Hen Houses with Two-Year Continuous Monitoring. Br. Poult. Sci. 2012, 53, 19–31. [Google Scholar] [CrossRef]
  42. Wolkoff, P. Indoor Air Pollutants in Office Environments: Assessment of Comfort, Health, and Performance. J. Hyg. Environ. Health 2013, 216, 371–394. [Google Scholar] [CrossRef] [PubMed]
  43. Schiffman, S.S.; Bennett, J.L.; Raymer, J.H. Quantification of Odors and Odorants from Swine Operations in North Carolina. Agric. For. Meteorol. 2001, 108, 213–240. [Google Scholar] [CrossRef]
  44. Feilberg, A.; Liu, D.; Adamsen, A.P.S.; Hansen, M.J.; Jonassen, K.E.N. Odorant Emissions from Intensive Pig Production Measured by Online Proton-Transfer-Reaction Mass Spectrometry. Environ. Sci. Technol. 2010, 44, 5894–5900. [Google Scholar] [CrossRef] [PubMed]
  45. Almaie, S.; Vatanpour, V.; Rasoulifard, M.H.; Koyuncu, I. Volatile Organic Compounds (VOCs) Removal by Photocatalysts: A Review. Chemosphere 2022, 306, 135655. [Google Scholar] [CrossRef] [PubMed]
  46. Dai, C.; Huang, S.; Zhou, Y.; Xu, B.; Peng, H.; Qin, P.; Wu, G. Concentrations and Emissions of Particulate Matter and Ammonia from Extensive Livestock Farm in South China. Environ. Sci. Pollut. Res. 2019, 26, 1871–1879. [Google Scholar] [CrossRef]
  47. Ni, J.-Q.; Chai, L.; Chen, L.; Bogan, B.W.; Wang, K.; Cortus, E.L.; Heber, A.J.; Lim, T.-T.; Diehl, C.A. Characteristics of Ammonia, Hydrogen Sulfide, Carbon Dioxide, and Particulate Matter Concentrations in High-Rise and Manure-Belt Layer Hen Houses. Atmos. Environ. 2012, 57, 165–174. [Google Scholar] [CrossRef]
  48. Yao, Q.; Yang, Z.; Li, H.; Buser, M.D.; Wanjura, J.D.; Downey, P.M.; Zhang, C.; Craige, C.; Torrents, A.; McConnell, L.L.; et al. Assessment of Particulate Matter and Ammonia Emission Concentrations and Respective Plume Profiles from a Commercial Poultry House. Environ. Pollut. 2018, 238, 10–16. [Google Scholar] [CrossRef]
  49. Van der Heyden, C.; Demeyer, P.; Volcke, E.I.P. Mitigating Emissions from Pig and Poultry Housing Facilities through Air Scrubbers and Biofilters: State-of-the-Art and Perspectives. Biosyst. Eng. 2015, 134, 74–93. [Google Scholar] [CrossRef]
  50. Hwang, O.; Lee, S.-R.; Cho, S.; Ro, K.S.; Spiehs, M.; Woodbury, B.; Silva, P.J.; Han, D.-W.; Choi, H.; Kim, K.-Y.; et al. Efficacy of Different Biochars in Removing Odorous Volatile Organic Compounds (VOCs) Emitted from Swine Manure. ACS Sustain. Chem. Eng. 2018, 6, 14239–14247. [Google Scholar] [CrossRef]
  51. Jafari, M.J.; Matin, A.H.; Rahmati, A.; Azari, M.R.; Omidi, L.; Hosseini, S.S.; Panahi, D. Experimental Optimization of a Spray Tower for Ammonia Removal. Atmos. Pollut. Res. 2018, 9, 783–790. [Google Scholar] [CrossRef]
  52. Saoud, W.A.; Belkessa, N.; Azzaz, A.A.; Rochas, V.; Mezino, V.; Presset, M.-A.; Lechevin, S.; Genouel, A.; Rouxel, S.; Monsimert, D.; et al. Pilot Scale Investigation of DBD-Plasma Photocatalysis for Industrial Application in Livestock Building Air: Elimination of Chemical Pollutants and Odors. Chem. Eng. J. 2023, 468, 143710. [Google Scholar] [CrossRef]
  53. Xia, D.; Li, Z.; Xie, Y.; Zhang, X. Kinetic Simulations of Volatile Organic Compounds Decomposition by Non-Thermal Plasma Treatment. Water Air Soil. Poll. 2016, 227, 463. [Google Scholar] [CrossRef]
  54. Zhang, Y.; Wang, Y.; Xie, R.; Huang, H.; Leung, M.K.H.; Li, J.; Leung, D.Y.C. Photocatalytic Oxidation for Volatile Organic Compounds Elimination: From Fundamental Research to Practical Applications. Environ. Sci. Technol. 2022, 56, 16582–16601. [Google Scholar] [CrossRef]
  55. Mazhar, S.I.; Shafi, H.Z.; Shah, A.; Asma, M.; Gul, S.; Raffi, M. Synthesis of Surface Modified Hydrophobic PTFE-ZnO Electrospun Nanofibrous Mats for Removal of Volatile Organic Compounds (VOCs) from Air. J. Polym. Res. 2020, 27, 222. [Google Scholar] [CrossRef]
  56. Tobaldi, D.M.; Pullar, R.C.; Škapin, A.S.; Seabra, M.P.; Labrincha, J.A. Visible Light Activated Photocatalytic Behaviour of Rare Earth Modified Commercial TiO2. Mater. Res. Bull. 2014, 50, 183–190. [Google Scholar] [CrossRef]
  57. Humayun, M.; Wang, C.; Luo, W. Recent Progress in the Synthesis and Applications of Composite Photocatalysts: A Critical Review. Small Methods 2022, 6, 2101395. [Google Scholar] [CrossRef]
  58. Truong, P.L.; Kidanemariam, A.; Park, J. A Critical Innovation of Photocatalytic Degradation for Toxic Chemicals and Pathogens in Air. J. Ind. Eng. Chem. 2021, 100, 19–39. [Google Scholar] [CrossRef]
  59. Fermoso, J.; Sánchez, B.; Suarez, S. Air Purification Applications Using Photocatalysis. In Nanostructured Photocatalysts; Elsevier: Amsterdam, The Netherlands, 2020; pp. 99–128. ISBN 978-0-12-817836-2. [Google Scholar]
  60. Chen, J.; Qiu, F.; Xu, W.; Cao, S.; Zhu, H. Recent Progress in Enhancing Photocatalytic Efficiency of TiO2-Based Materials. Appl. Catal. A-Gen. 2015, 495, 131–140. [Google Scholar] [CrossRef]
  61. Zhang, F.; Wang, X.; Liu, H.; Liu, C.; Wan, Y.; Long, Y.; Cai, Z. Recent Advances and Applications of Semiconductor Photocatalytic Technology. Appl. Sci. 2019, 9, 2489. [Google Scholar] [CrossRef]
  62. Priya, A.K.; Suresh, R.; Kumar, P.S.; Rajendran, S.; Vo, D.-V.N.; Soto-Moscoso, M. A Review on Recent Advancements in Photocatalytic Remediation for Harmful Inorganic and Organic Gases. Chemosphere 2021, 284, 131344. [Google Scholar] [CrossRef]
  63. Che, J.; Bae, N.; Noh, J.; Kim, T.; Yoo, P.J.; Shin, T.J.; Park, J. Poly(3-Hexylthiophene) Nanoparticles Prepared via a Film Shattering Process and Hybridization with TiO2 for Visible-Light Active Photocatalysis. Macromol. Res. 2019, 27, 427–434. [Google Scholar] [CrossRef]
  64. Lee, M.; Koziel, J.A.; Murphy, W.; Jenks, W.S.; Chen, B.; Li, P.; Banik, C. Evaluation of TiO2 Based Photocatalytic Treatment of Odor and Gaseous Emissions from Swine Manure with UV-A and UV-C. Animals 2021, 11, 1289. [Google Scholar] [CrossRef] [PubMed]
  65. Grčić, I.; Marčec, J.; Radetić, L.; Radovan, A.-M.; Melnjak, I.; Jajčinović, I.; Brnardić, I. Ammonia and Methane Oxidation on TiO2 Supported on Glass Fiber Mesh under Artificial Solar Irradiation. Environ. Sci. Pollut. Res. 2021, 28, 18354–18367. [Google Scholar] [CrossRef] [PubMed]
  66. Lyu, J.; Zhu, L.; Burda, C. Considerations to Improve Adsorption and Photocatalysis of Low Concentration Air Pollutants on TiO2. Catal. Today 2014, 225, 24–33. [Google Scholar] [CrossRef]
  67. Jansson, I.; Suárez, S.; Garcia-Garcia, F.J.; Sánchez, B. Zeolite–TiO2 Hybrid Composites for Pollutant Degradation in Gas Phase. Appl. Catal. B-Environ. 2015, 178, 100–107. [Google Scholar] [CrossRef]
  68. Liu, C.; Zhang, R.; Wei, S.; Wang, J.; Liu, Y.; Li, M.; Liu, R. Selective Removal of H2S from Biogas Using a Regenerable Hybrid TiO2/Zeolite Composite. Fuel 2015, 157, 183–190. [Google Scholar] [CrossRef]
  69. Park, H.; Park, Y.; Kim, W.; Choi, W. Surface Modification of TiO2 Photocatalyst for Environmental Applications. J. Photochem. Photobiol. C Photochem. Rev. 2013, 15, 1–20. [Google Scholar] [CrossRef]
  70. Khaki, M.R.D.; Shafeeyan, M.S.; Raman, A.A.A.; Daud, W.M.A.W. Application of Doped Photocatalysts for Organic Pollutant Degradation—A Review. J. Environ. Manag. 2017, 198, 78–94. [Google Scholar] [CrossRef]
  71. Kumar, S.G.; Devi, L.G. Review on Modified TiO2 Photocatalysis under UV/Visible Light: Selected Results and Related Mechanisms on Interfacial Charge Carrier Transfer Dynamics. J. Phys. Chem. A 2011, 115, 13211–13241. [Google Scholar] [CrossRef]
  72. Mao, H.; Fei, Z.; Bian, C.; Yu, L.; Chen, S.; Qian, Y. Facile Synthesis of High-Performance Photocatalysts Based on Ag/TiO2 Composites. Ceram. Int. 2019, 45, 12586–12589. [Google Scholar] [CrossRef]
  73. Liu, G.; Ji, J.; Hu, P.; Lin, S.; Huang, H. Efficient Degradation of H2S over Transition Metal Modified TiO2 under VUV Irradiation: Performance and Mechanism. Appl. Surf. Sci. 2018, 433, 329–335. [Google Scholar] [CrossRef]
  74. Chakhtouna, H.; Benzeid, H.; Zari, N.; Qaiss, A.E.K.; Bouhfid, R. Recent Progress on Ag/TiO2 Photocatalysts: Photocatalytic and Bactericidal Behaviors. Environ. Sci. Pollut. Res. 2021, 28, 44638–44666. [Google Scholar] [CrossRef] [PubMed]
  75. Liu, T.; Li, X.; Li, F. AgNO3-Induced Photocatalytic Degradation of Odorous Methyl Mercaptan in Gaseous Phase: Mechanism of Chemisorption and Photocatalytic Reaction. Environ. Sci. Technol. 2008, 42, 4540–4545. [Google Scholar] [CrossRef] [PubMed]
  76. Shojaei, A.; Ghafourian, H.; Yadegarian, L.; Lari, K.; Sadatipour, M.T. Removal of Volatile Organic Compounds (VOCs) from Waste Air Stream Using Ozone Assisted Zinc Oxide (ZnO) Nanoparticles Coated on Zeolite. J. Environ. Health Sci. 2021, 19, 771–780. [Google Scholar] [CrossRef] [PubMed]
  77. Karthik, S.; Siva, P.; Balu, K.S.; Suriyaprabha, R.; Rajendran, V.; Maaza, M. Acalypha Indica–Mediated Green Synthesis of ZnO Nanostructures under Differential Thermal Treatment: Effect on Textile Coating, Hydrophobicity, UV Resistance, and Antibacterial Activity. Adv. Powder Technol. 2017, 28, 3184–3194. [Google Scholar] [CrossRef]
  78. Shalahuddin Al Ja’farawy, M.; Kusumandari; Purwanto, A.; Widiyandari, H. Carbon Quantum Dots Supported Zinc Oxide (ZnO/CQDs) Efficient Photocatalyst for Organic Pollutant Degradation—A Systematic Review. Environ. Nanotechnol. Monit. Manag. 2022, 18, 100681. [Google Scholar] [CrossRef]
  79. Venkata Laxma Reddy, P.; Kim, K.-H.; Kim, Y.-H. A Review of Photocatalytic Treatment for Various Air Pollutants. Asian J. Atmos. Environ. 2011, 5, 181–188. [Google Scholar] [CrossRef]
  80. Kim, Y.; Irie, H.; Hashimoto, K. A Visible Light-Sensitive Tungsten Carbide/Tungsten Trioxde Composite Photocatalyst. Appl. Phys. Lett. 2008, 92, 182107. [Google Scholar] [CrossRef]
  81. Wang, X.; Sun, M.; Murugananthan, M.; Zhang, Y.; Zhang, L. Electrochemically Self-Doped WO3/TiO2 Nanotubes for Photocatalytic Degradation of Volatile Organic Compounds. Appl. Catal. B-Environ. 2020, 260, 118205. [Google Scholar] [CrossRef]
  82. Jansson, I.; Yoshiiri, K.; Hori, H.; García-García, F.J.; Rojas, S.; Sánchez, B.; Ohtani, B.; Suárez, S. Visible Light Responsive Zeolite/WO3–Pt Hybrid Photocatalysts for Degradation of Pollutants in Air. Appl. Catal. A-Gen. 2016, 521, 208–219. [Google Scholar] [CrossRef]
  83. Ning, X.; Lu, G. Photocorrosion Inhibition of CdS-Based Catalysts for Photocatalytic Overall Water Splitting. Nanoscale 2020, 12, 1213–1223. [Google Scholar] [CrossRef] [PubMed]
  84. Cui, Y.; Li, M.; Zhu, N.; Cheng, Y.; Lam, S.S.; Chen, J.; Gao, Y.; Zhao, J. Bi-Based Visible Light-Driven Nano-Photocatalyst: The Design, Synthesis, and Its Application in Pollutant Governance and Energy Development. Nano Today 2022, 43, 101432. [Google Scholar] [CrossRef]
  85. Zhao, J.; Yang, X. Photocatalytic Oxidation for Indoor Air Purification: A Literature Review. Build. Environ. 2003, 38, 645–654. [Google Scholar] [CrossRef]
  86. Martín-Sómer, M.; Pablos, C.; Van Grieken, R.; Marugán, J. Influence of Light Distribution on the Performance of Photocatalytic Reactors: LED vs Mercury Lamps. Appl. Catal. B-Environ. 2017, 215, 1–7. [Google Scholar] [CrossRef]
  87. da Costa Filho, B.M.; Vilar, V.J.P. Strategies for the Intensification of Photocatalytic Oxidation Processes towards Air Streams Decontamination: A Review. Chem. Eng. J. 2020, 391, 123531. [Google Scholar] [CrossRef]
  88. Jo, W.-K.; Tayade, R.J. New Generation Energy-Efficient Light Source for Photocatalysis: LEDs for Environmental Applications. Ind. Eng. Chem. Res. 2014, 53, 2073–2084. [Google Scholar] [CrossRef]
  89. Walsh, D.J.; Schneider, T.N.; Olsen, B.D.; Jensen, K.F. Design and Simulation of a Uniform Irradiance Photochemical Platform. React. Chem. Eng. 2023, 8, 416–423. [Google Scholar] [CrossRef]
  90. Shayegan, Z.; Lee, C.-S.; Haghighat, F. TiO2 Photocatalyst for Removal of Volatile Organic Compounds in Gas Phase—A Review. Chem. Eng. J. 2018, 334, 2408–2439. [Google Scholar] [CrossRef]
  91. Zhang, F.; Wang, M.; Zhu, X.; Hong, B.; Wang, W.; Qi, Z.; Xie, W.; Ding, J.; Bao, J.; Sun, S.; et al. Effect of Surface Modification with H2S and NH3 on TiO2 for Adsorption and Photocatalytic Degradation of Gaseous Toluene. Appl. Catal. B-Environ. 2015, 170–171, 215–224. [Google Scholar] [CrossRef]
  92. Wang, C.; Bai, H.; Yi, N.; Kang, X. Multi-Dimensional Optimization for a Novel Photocatalytic Reactor Incorporating the Decolorization of Azo Dye and Thermal Management of Ultraviolet Light-Emitting Diode Arrays. Energ. Convers. Man-X 2023, 17, 100344. [Google Scholar] [CrossRef]
  93. McMillan, T.J.; Leatherman, E.; Ridley, A.; Shorrocks, J.; Tobi, S.E.; Whiteside, J.R. Cellular Effects of Long Wavelength UV Light (UVA) in Mammalian Cells. J. Pharm. Pharmacol. 2010, 60, 969–976. [Google Scholar] [CrossRef] [PubMed]
  94. Bertagna Silva, D.; Buttiglieri, G.; Babić, S. State-of-the-Art and Current Challenges for TiO2/UV-LED Photocatalytic Degradation of Emerging Organic Micropollutants. Environ. Sci. Pollut. Res. 2021, 28, 103–120. [Google Scholar] [CrossRef] [PubMed]
  95. Rasoulifard, M.H.; Fazli, M.; Eskandarian, M.R. Performance of the Light-Emitting-Diodes in a Continuous Photoreactor for Degradation of Direct Red 23 Using UV-LED/S2O82−Process. J. Ind. Eng. Chem. 2015, 24, 121–126. [Google Scholar] [CrossRef]
  96. Kneissl, M.; Seong, T.-Y.; Han, J.; Amano, H. The Emergence and Prospects of Deep-Ultraviolet Light-Emitting Diode Technologies. Nat. Photonics 2019, 13, 233–244. [Google Scholar] [CrossRef]
  97. Roibu, A.; Morthala, R.B.; Leblebici, M.E.; Koziej, D.; Van Gerven, T.; Kuhn, S. Design and Characterization of Visible-Light LED Sources for Microstructured Photoreactors. React. Chem. Eng. 2018, 3, 849–865. [Google Scholar] [CrossRef]
  98. Yusuf, A.; Garlisi, C.; Palmisano, G. Overview on Microfluidic Reactors in Photocatalysis: Applications of Graphene Derivatives. Catal. Today 2018, 315, 79–92. [Google Scholar] [CrossRef]
  99. Alalm, M.G.; Djellabi, R.; Meroni, D.; Pirola, C.; Bianchi, C.L.; Boffito, D.C. Toward Scaling-Up Photocatalytic Process for Multiphase Environmental Applications. Catalysts 2021, 11, 562. [Google Scholar] [CrossRef]
  100. Avila, P.; Bahamonde, A.; Blanco, J.; Sánchez, B.; Cardona, A.I.; Romero, M. Gas-Phase Photo-Assisted Mineralization of Volatile Organic Compounds by Monolithic Titania Catalysts. Appl. Catal. B-Environ. 1998, 17, 75–88. [Google Scholar] [CrossRef]
  101. Jacobs, M.; Meir, G.; Hakki, A.; Thomassen, L.C.J.; Kuhn, S.; Leblebici, M.E. Scaling up Multiphase Photochemical Reactions Using Translucent Monoliths. Chem. Eng. Process 2022, 181, 109138. [Google Scholar] [CrossRef]
  102. Bouzaza, A.; Vallet, C.; Laplanche, A. Photocatalytic Degradation of Some VOCs in the Gas Phase Using an Annular Flow Reactor. J. Photochem. Photobiol. A Chem. 2006, 177, 212–217. [Google Scholar] [CrossRef]
  103. Vincent, G.; Marquaire, P.M.; Zahraa, O. Abatement of Volatile Organic Compounds Using an Annular Photocatalytic Reactor: Study of Gaseous Acetone. J. Photochem. Photobiol. A Chem. 2008, 197, 177–189. [Google Scholar] [CrossRef]
  104. Tong, K.; Yang, L.; Du, X.; Yang, Y. Review of Modeling and Simulation Strategies for Unstructured Packing Bed Photoreactors with CFD Method. Renew. Sustain. Energy Rev. 2020, 131, 109986. [Google Scholar] [CrossRef]
  105. Watanabe, S.; Ma, X.; Song, C. Adsorptive Desulfurization of Jet Fuels over TiO2-CeO2 Mixed Oxides: Role of Surface Ti and Ce Cations. Catal. Today 2021, 371, 265–275. [Google Scholar] [CrossRef]
  106. Zou, L.; Luo, Y.; Hooper, M.; Hu, E. Removal of VOCs by Photocatalysis Process Using Adsorption Enhanced TiO2–SiO2 Catalyst. Chem. Eng. Process. 2006, 45, 959–964. [Google Scholar] [CrossRef]
  107. Alvarado, A.C.; Predicala, B.Z. Control of Gas and Odor Levels in Swine Facilities Using Filters with Zinc Oxide Nanoparticles. Trans. ASABE 2017, 60, 943–956. [Google Scholar] [CrossRef]
  108. Assadi, H.; Armaghan, F.; Taheri, R.A. Photocatalytic Oxidation of Ketone Group Volatile Organic Compounds in an Intensified Fluidized Bed Reactor Using Nano-TiO2/UV Process: An Experimental and Modeling Study. Chem. Eng. Process. 2021, 161, 108312. [Google Scholar] [CrossRef]
  109. Xu, P.; Ding, C.; Li, Z.; Yu, R.; Cui, H.; Gao, S. Photocatalytic Degradation of Air Pollutant by Modified Nano Titanium Oxide (TiO2)in a Fluidized Bed Photoreactor: Optimizing and Kinetic Modeling. Chemosphere 2023, 319, 137995. [Google Scholar] [CrossRef]
  110. Zhang, M.; An, T.; Fu, J.; Sheng, G.; Wang, X.; Hu, X.; Ding, X. Photocatalytic Degradation of Mixed Gaseous Carbonyl Compounds at Low Level on Adsorptive TiO2/SiO2 Photocatalyst Using a Fluidized Bed Reactor. Chemosphere 2006, 64, 423–431. [Google Scholar] [CrossRef]
  111. Sharma, S.; Kumar, R.; Raizada, P.; Ahamad, T.; Alshehri, S.M.; Nguyen, V.-H.; Thakur, S.; Nguyen, C.C.; Kim, S.Y.; Le, Q.V.; et al. An Overview on Recent Progress in Photocatalytic Air Purification: Metal-Based and Metal-Free Photocatalysis. Environ. Res. 2022, 214, 113995. [Google Scholar] [CrossRef]
  112. Van Gerven, T.; Mul, G.; Moulijn, J.; Stankiewicz, A. A Review of Intensification of Photocatalytic Processes. Chem. Eng. Process. 2007, 46, 781–789. [Google Scholar] [CrossRef]
  113. Matter, F.; Niederberger, M. The Importance of the Macroscopic Geometry in Gas-Phase Photocatalysis. Adv. Sci. 2022, 9, 2105363. [Google Scholar] [CrossRef] [PubMed]
  114. Su, J.-J.; Hong, Y.-Y. Removal of Hydrogen Sulfide Using a Photocatalytic Livestock Biogas Desulfurizer. Renew. Energy 2020, 149, 181–188. [Google Scholar] [CrossRef]
  115. Mosleh, S.; Ghaedi, M. Photocatalytic Reactors: Technological Status, Opportunities, and Challenges for Development and Industrial Upscaling. In Interface Science and Technology; Elsevier: Amsterdam, The Netherlands, 2021; Volume 32, pp. 761–790. ISBN 978-0-12-818806-4. [Google Scholar]
  116. Lee, M.; Koziel, J.A.; Murphy, W.; Jenks, W.S.; Fonken, B.; Storjohann, R.; Chen, B.; Li, P.; Banik, C.; Wahe, L.; et al. Design and Testing of Mobile Laboratory for Mitigation of Gaseous Emissions from Livestock Agriculture with Photocatalysis. Int. J. Environ. Res. Public Health 2021, 18, 1523. [Google Scholar] [CrossRef] [PubMed]
  117. Calvet, S.; Cambra-López, M.; Blanes-Vidal, V.; Estellés, F.; Torres, A.G. Ventilation Rates in Mechanically-Ventilated Commercial Poultry Buildings in Southern Europe: Measurement System Development and Uncertainty Analysis. Biosyst. Eng. 2010, 106, 423–432. [Google Scholar] [CrossRef]
  118. Pu, S.; Wang, H.; Zhu, J.; Li, L.; Long, D.; Jian, Y.; Zeng, Y. Heterostructure Cu2O/(001)TiO2 Effected on Photocatalytic Degradation of Ammonia of Livestock Houses. Catalysts 2019, 9, 267. [Google Scholar] [CrossRef]
  119. Chen, Q.; Cai, J.; Hua, W.; Li, K.; Zhang, X.; Xiao, L.; Zhang, W.; Ni, Y.; Zhang, J. Effect of a New Tungsten Trioxide-Based Bactericide on the Environment of Piggeries and Piglet Health. Environ. Technol. Innov. 2022, 28, 102628. [Google Scholar] [CrossRef]
  120. Cao, T.; Zheng, Y.; Dong, H.; Wang, S.; Zhang, Y.; Cong, Q. A New Air Cleaning Technology to Synergistically Reduce Odor and Bioaerosol Emissions from Livestock Houses. Agric. Ecosyst. Environ. 2023, 342, 108221. [Google Scholar] [CrossRef]
  121. Wu, H.; Ma, J.; Li, Y.; Zhang, C.; He, H. Photocatalytic Oxidation of Gaseous Ammonia over Fluorinated TiO2 with Exposed (001) Facets. Appl. Catal. B-Environ. 2014, 152–153, 82–87. [Google Scholar] [CrossRef]
  122. Lee, M.; Wi, J.; Koziel, J.A.; Ahn, H.; Li, P.; Chen, B.; Meiirkhanuly, Z.; Banik, C.; Jenks, W. Effects of UV-A Light Treatment on Ammonia, Hydrogen Sulfide, Greenhouse Gases, and Ozone in Simulated Poultry Barn Conditions. Atmosphere 2020, 11, 283. [Google Scholar] [CrossRef]
  123. Liu, Z.; Murphy, P.; Maghirang, R. Mitigation of Air Emissions from Swine Buildings through the Photocatalytic Technology Using UV/TiO2. In Proceedings of the 2015 ASABE International Meeting, New Orleans, LA, USA, 26–29 July 2015; American Society of Agricultural and Biological Engineers: St. Joseph, MI, USA, 2015. [Google Scholar]
  124. Wu, L.-C.; Kuo, C.-L.; Chung, Y.-C. Removal of High Concentrations of NH3 by a Combined Photoreactor and Biotrickling Filter System. J. Environ. Sci. Health Part A 2011, 46, 1675–1682. [Google Scholar] [CrossRef]
  125. Maxime, G.; Aymen Amine, A.; Abdelkrim, B.; Dominique, W. Removal of Gas-Phase Ammonia and Hydrogen Sulfide Using Photocatalysis, Nonthermal Plasma, and Combined Plasma and Photocatalysis at Pilot Scale. Environ. Sci. Pollut. Res. 2014, 21, 13127–13137. [Google Scholar] [CrossRef] [PubMed]
  126. Yao, H.; Feilberg, A. Characterisation of Photocatalytic Degradation of Odorous Compounds Associated with Livestock Facilities by Means of PTR-MS. Chem. Eng. J. 2015, 277, 341–351. [Google Scholar] [CrossRef]
  127. Zhu, W.; Koziel, J.; Maurer, D. Mitigation of Livestock Odors Using Black Light and a New Titanium Dioxide-Based Catalyst: Proof-of-Concept. Atmosphere 2017, 8, 103. [Google Scholar] [CrossRef]
  128. Maurer, D.L.; Koziel, J.A. On-Farm Pilot-Scale Testing of Black Ultraviolet Light and Photocatalytic Coating for Mitigation of Odor, Odorous VOCs, and Greenhouse Gases. Chemosphere 2019, 221, 778–784. [Google Scholar] [CrossRef]
  129. Lee, M.; Koziel, J.A.; Murphy, W.; Jenks, W.S.; Chen, B.; Li, P.; Banik, C. Mitigation of Odor and Gaseous Emissions from Swine Barn with UV-A and UV-C Photocatalysis. Atmosphere 2021, 12, 585. [Google Scholar] [CrossRef]
  130. Assadi, A.A.; Bouzaza, A.; Lemasle, M.; Wolbert, D. Acceleration of Trimethylamine Removal Process Under Synergistic Effect of Photocatalytic Oxidation and Surface Discharge Plasma Reactor. Can. J. Chem. Eng. 2015, 93, 1239–1246. [Google Scholar] [CrossRef]
  131. Assadi, A.A.; Bouzaza, A.; Soutrel, I.; Petit, P.; Medimagh, K.; Wolbert, D. A Study of Pollution Removal in Exhaust Gases from Animal Quartering Centers by Combining Photocatalysis with Surface Discharge Plasma: From Pilot to Industrial Scale. Chem. Eng. Process 2017, 111, 1–6. [Google Scholar] [CrossRef]
  132. Li, X.Z.; Hou, M.F.; Li, F.B.; Chua, H. Photocatalytic Oxidation of Methyl Mercaptan in Foul Gas for Odor Control. Ind. Eng. Chem. Res. 2006, 45, 487–494. [Google Scholar] [CrossRef]
  133. Yang, X.; Koziel, J.A.; Cutler, T.; van Leeuwen, H.; Zhang, S.; Hoff, S.J.; Jenks, W.; Zimmerman, J. Treatment of Livestock Odor and Pathogens with Ultraviolet Light. In Proceedings of the 2008 ASABE Annual International Meeting, Providence, RI, USA, 29 June–2 July 2008; American Society of Agricultural and Biological Engineers: St. Joseph, MI, USA, 2008. [Google Scholar]
  134. Yang, X.; Koziel, J.A.; Laor, Y.; Zhu, W.; van Leeuwen, J.H.; Jenks, W.S.; Hoff, S.J.; Zimmerman, J.; Zhang, S.; Ravid, U.; et al. VOC Removal from Manure Gaseous Emissions with UV Photolysis and UV-TiO2 Photocatalysis. Catalysts 2020, 10, 607. [Google Scholar] [CrossRef]
  135. Vikrant, K.; Kim, K.-H.; Dong, F.; Giannakoudakis, D.A. Photocatalytic Platforms for Removal of Ammonia from Gaseous and Aqueous Matrixes: Status and Challenges. ACS Catal. 2020, 10, 8683–8716. [Google Scholar] [CrossRef]
  136. Shu, Y.; Ji, J.; Zhou, M.; Liang, S.; Xie, Q.; Li, S.; Liu, B.; Deng, J.; Cao, J.; Liu, S.; et al. Selective Photocatalytic Oxidation of Gaseous Ammonia at Ppb Level over Pt and F Modified TiO2. Appl. Catal. B-Environ. 2022, 300, 120688. [Google Scholar] [CrossRef]
  137. Abdi, M.; Alinezhad, E.; Akbari Sene, R.; Haghighi, M.; Keshizadeh, H.; Naddafi, K. Evaluation of a Pilot-Scale Scrubber for the Mitigation of NH3 Emissions from Laboratory Animal House in the Presence of Different Oxidants. J. Environ. Chem. Eng. 2020, 8, 103708. [Google Scholar] [CrossRef]
  138. Sundar, K.P.; Kanmani, S. Progression of Photocatalytic Reactors and It’s Comparison: A Review. Chem. Eng. Res. Des. 2020, 154, 135–150. [Google Scholar] [CrossRef]
  139. Kolinko, P.A.; Kozlov, D.V. Products Distribution during the Gas Phase Photocatalytic Oxidation of Ammonia over the Various Titania Based Photocatalysts. Appl. Catal. B-Environ. 2009, 90, 126–131. [Google Scholar] [CrossRef]
  140. Dell’Edera, M.; Lo Porto, C.; De Pasquale, I.; Petronella, F.; Curri, M.L.; Agostiano, A.; Comparelli, R. Photocatalytic TiO2-Based Coatings for Environmental Applications. Catal. Today 2021, 380, 62–83. [Google Scholar] [CrossRef]
  141. Schreck, M.; Niederberger, M. Photocatalytic Gas Phase Reactions. Chem. Mater. 2019, 31, 597–618. [Google Scholar] [CrossRef]
  142. Alonso-Tellez, A.; Robert, D.; Keller, N.; Keller, V. A Parametric Study of the UV-A Photocatalytic Oxidation of H2S over TiO2. Appl. Catal. B Environ. 2012, 115–116, 209–218. [Google Scholar] [CrossRef]
  143. Yu, Y.; Zhang, T.; Zheng, L.; Yu, J. Photocatalytic Degradation of Hydrogen Sulfide Using TiO2 Film under Microwave Electrodeless Discharge Lamp Irradiation. Chem. Eng. J. 2013, 225, 9–15. [Google Scholar] [CrossRef]
  144. Sopyan, I. Kinetic Analysis on Photocatalytic Degradation of Gaseous Acetaldehyde, Ammonia and Hydrogen Sulfide on Nanosized Porous TiO2 Films. Sci. Technol. Adv. Mater. 2007, 8, 33–39. [Google Scholar] [CrossRef]
  145. Palau, J.; Penya-Roja, J.M.; Gabaldón, C.; Álvarez-Hornos, F.J.; Martínez-Soria, V. Effect of Pre-treatments Based on UV Photocatalysis and Photo-oxidation on Toluene Biofiltration Performance. J. Chem. Tech. Biotech. 2012, 87, 65–72. [Google Scholar] [CrossRef]
  146. Mudliar, S.; Giri, B.; Padoley, K.; Satpute, D.; Dixit, R.; Bhatt, P.; Pandey, R.; Juwarkar, A.; Vaidya, A. Bioreactors for Treatment of VOCs and Odours—A Review. J. Environ. Manag. 2010, 91, 1039–1054. [Google Scholar] [CrossRef] [PubMed]
  147. Augugliaro, V.; Bellardita, M.; Loddo, V.; Palmisano, G.; Palmisano, L.; Yurdakal, S. Overview on Oxidation Mechanisms of Organic Compounds by TiO2 in Heterogeneous Photocatalysis. J. Photoch Photobio C 2012, 13, 224–245. [Google Scholar] [CrossRef]
  148. Vorontsov, A.V. Photocatalytic Transformations of Organic Sulfur Compounds and H2S. Russ. Chem. Rev. 2008, 77, 909–926. [Google Scholar] [CrossRef]
  149. Biard, P.-F.; Bouzaza, A.; Wolbert, D. Photocatalytic Degradation of Two Volatile Fatty Acids in Monocomponent and Multicomponent Systems: Comparison between Batch and Annular Photoreactors. Appl. Catal. B-Environ. 2007, 74, 187–196. [Google Scholar] [CrossRef]
  150. Assadi, A.A.; Bouzaza, A.; Wolbert, D. Photocatalytic Oxidation of Trimethylamine and Isovaleraldehyde in an Annular Reactor: Influence of the Mass Transfer and the Relative Humidity. J. Photochem. Photobiol. A Chem. 2012, 236, 61–69. [Google Scholar] [CrossRef]
  151. Ardizzone, S.; Bianchi, C.L.; Cappelletti, G.; Naldoni, A.; Pirola, C. Photocatalytic Degradation of Toluene in the Gas Phase: Relationship between Surface Species and Catalyst Features. Environ. Sci. Technol. 2008, 42, 6671–6676. [Google Scholar] [CrossRef]
  152. Khunphonoi, R.; Grisdanurak, N. Mechanism Pathway and Kinetics of P-Cresol Photocatalytic Degradation over Titania Nanorods under UV–Visible Irradiation. Chem. Eng. J. 2016, 296, 420–427. [Google Scholar] [CrossRef]
  153. Héquet, V.; Raillard, C.; Debono, O.; Thévenet, F.; Locoge, N.; Le Coq, L. Photocatalytic Oxidation of VOCs at Ppb Level Using a Closed-Loop Reactor: The Mixture Effect. Appl. Catal. B-Environ. 2018, 226, 473–486. [Google Scholar] [CrossRef]
  154. Chen, K.-N.; Sari, F.N.I.; Ting, J.-M. Multifunctional TiO2/Polyacrylonitrile Nanofibers for High Efficiency PM2.5 Capture, UV Filter, and Anti-Bacteria Activity. Appl. Surf. Sci. 2019, 493, 157–164. [Google Scholar] [CrossRef]
  155. Sohara, K.; Yamauchi, K.; Sun, X.; Misawa, K.; Sekine, Y. Photocatalytic Degradation of Polycyclic Aromatic Hydrocarbons in Fine Particulate Matter (PM2.5) Collected on TiO2-Supporting Quartz Fibre Filters. Catalysts 2021, 11, 400. [Google Scholar] [CrossRef]
  156. Bono, N.; Ponti, F.; Punta, C.; Candiani, G. Effect of UV Irradiation and TiO2-Photocatalysis on Airborne Bacteria and Viruses: An Overview. Materials 2021, 14, 1075. [Google Scholar] [CrossRef] [PubMed]
  157. Dalrymple, O.K.; Stefanakos, E.; Trotz, M.A.; Goswami, D.Y. A Review of the Mechanisms and Modeling of Photocatalytic Disinfection. Appl. Catal. B-Environ. 2010, 98, 27–38. [Google Scholar] [CrossRef]
  158. De Pasquale, I.; Lo Porto, C.; Dell’Edera, M.; Curri, M.L.; Comparelli, R. TiO2-Based Nanomaterials Assisted Photocatalytic Treatment for Virus Inactivation: Perspectives and Applications. Curr. Opin. Chem. Eng. 2021, 34, 100716. [Google Scholar] [CrossRef]
  159. Zhao, Y.; Aarnink, A.J.A.; Xin, H. Inactivation of Airborne Enterococcus Faecalis and Infectious Bursal Disease Virus Using a Pilot-Scale Ultraviolet Photocatalytic Oxidation Scrubber. J. Air Waste Manag. 2014, 64, 38–46. [Google Scholar] [CrossRef]
  160. Habibi-Yangjeh, A.; Asadzadeh-Khaneghah, S.; Feizpoor, S.; Rouhi, A. Review on Heterogeneous Photocatalytic Disinfection of Waterborne, Airborne, and Foodborne Viruses: Can We Win against Pathogenic Viruses? J. Colloid Interface Sci. 2020, 580, 503–514. [Google Scholar] [CrossRef]
  161. Misawa, K.; Sekine, Y.; Kusukubo, Y.; Sohara, K. Photocatalytic Degradation of Atmospheric Fine Particulate Matter (PM2.5) Collected on TiO2 Supporting Quartz Fibre Filter. Environ. Technol. 2020, 41, 1266–1274. [Google Scholar] [CrossRef]
  162. Liu, G.; Xiao, M.; Zhang, X.; Gal, C.; Chen, X.; Liu, L.; Pan, S.; Wu, J.; Tang, L.; Clements-Croome, D. A Review of Air Filtration Technologies for Sustainable and Healthy Building Ventilation. Sustain. Cities Soc. 2017, 32, 375–396. [Google Scholar] [CrossRef]
  163. Abou Saoud, W.; Assadi, A.A.; Guiza, M.; Bouzaza, A.; Aboussaoud, W.; Ouederni, A.; Soutrel, I.; Wolbert, D.; Rtimi, S. Study of Synergetic Effect, Catalytic Poisoning and Regeneration Using Dielectric Barrier Discharge and Photocatalysis in a Continuous Reactor: Abatement of Pollutants in Air Mixture System. Appl. Catal. B-Environ. 2017, 213, 53–61. [Google Scholar] [CrossRef]
  164. Khezami, L.; Nguyen-Tri, P.; Saoud, W.A.; Bouzaza, A.; El Jery, A.; Duc Nguyen, D.; Gupta, V.K.; Assadi, A.A. Recent Progress in Air Treatment with Combined Photocatalytic/Plasma Processes: A Review. J. Environ. Manag. 2021, 299, 113588. [Google Scholar] [CrossRef]
  165. Zhou, J.; Wei, T.; An, X. Combining Non-Thermal Plasma Technology with Photocatalysis: A Critical Review. Phys. Chem. Chem. Phys. 2023, 25, 1538–1545. [Google Scholar] [CrossRef]
  166. Li, Y.; Zhang, R.; Du, L.; Zhang, Q.; Wang, W. Synergistic Effect and Mechanism of Non-Thermal Plasma Catalysis System in Volatile Organic Compounds Removal: A Review. Catal. Sci. Technol. 2016, 6, 73–80. [Google Scholar] [CrossRef]
  167. Kone, N.A.; Belkessa, N.; Serhane, Y.; Coulibaly, S.L.; Kamagate, M.; Mouni, L.; Loganathan, S.; Coulibaly, L.; Bouzaza, A.; Amrane, A.; et al. Chlorobenzene Mineralization Using Plasma/Photocatalysis Hybrid Reactor: Exploiting the Synergistic Effect. Catalysts 2023, 13, 431. [Google Scholar] [CrossRef]
  168. Belkessa, N.; Bouzaza, A.; Assadi, A.A. Understanding of the Synergy Effect of DBD Plasma Discharge Combined to Photocatalysis in the Case of Ethylbenzene Removal: Interaction between Plasma Reactive Species and Catalyst. J. Environ. Chem. Eng. 2023, 11, 110640. [Google Scholar] [CrossRef]
  169. Rafique, M.S.; Tahir, M.B.; Rafique, M.; Shakil, M. Photocatalytic Nanomaterials for Air Purification and Self-Cleaning. In Nanotechnology and Photocatalysis for Environmental Applications; Elsevier: Amsterdam, The Netherlands, 2020; pp. 203–219. ISBN 978-0-12-821192-2. [Google Scholar]
  170. Zhang, Y.; Zhu, Y.; Tao, S.; Zhang, Z.; Chen, M.; Jiang, Z.; Shangguan, W. Plasma-Coupled Catalysis in VOCs Removal and CO2 Conversion: Efficiency Enhancement and Synergistic Mechanism. Catal. Commun. 2022, 172, 106535. [Google Scholar] [CrossRef]
  171. Zhu, C.; Wang, X.; Huang, Q.; Huang, L.; Xie, J.; Qing, C.; Chen, T. Removal of Gaseous Carbon Bisulfide Using Dielectric Barrier Discharge Plasmas Combined with TiO2 Coated Attapulgite Catalyst. Chem. Eng. J. 2013, 225, 567–573. [Google Scholar] [CrossRef]
  172. Assadi, A.A.; Palau, J.; Bouzaza, A.; Penya-Roja, J.; Martinez-Soriac, V.; Wolbert, D. Abatement of 3-Methylbutanal and Trimethylamine with Combined Plasma and Photocatalysis in a Continuous Planar Reactor. J. Photochem. Photobiol. A Chem. 2014, 282, 1–8. [Google Scholar] [CrossRef]
  173. Ochiai, T.; Ichihashi, E.; Nishida, N.; Machida, T.; Uchida, Y.; Hayashi, Y.; Morito, Y.; Fujishima, A. Field Performance Test of an Air-Cleaner with Photocatalysis-Plasma Synergistic Reactors for Practical and Long-Term Use. Molecules 2014, 19, 17424–17434. [Google Scholar] [CrossRef]
  174. He, Z.; Li, J.; Chen, J.; Chen, Z.; Li, G.; Sun, G.; An, T. Treatment of Organic Waste Gas in a Paint Plant by Combined Technique of Biotrickling Filtration with Photocatalytic Oxidation. Chem. Eng. J. 2012, 200–202, 645–653. [Google Scholar] [CrossRef]
  175. Du, Q.; Zhong, Z.; Zhang, T.; Xu, Y.; Zhang, G.; Wu, S.; Xu, J. Synergistic Degradation Performance of UV/TiO2 Photocatalysis and Biotrickling Filtration Inoculated with Aspergillus sp. S1 for Gaseous m-xylene. J. Chem. Technol. Biotechnol. 2023, 98, 498–505. [Google Scholar] [CrossRef]
  176. Almomani, F.; Rene, E.R.; Veiga, M.C.; Bhosale, R.R.; Kennes, C. Treatment of Waste Gas Contaminated with Dichloromethane Using Photocatalytic Oxidation, Biodegradation and Their Combinations. J. Hazard. Mater. 2021, 405, 123735. [Google Scholar] [CrossRef]
  177. Han, M.-F.; Hu, X.-R.; Wang, Y.-C.; Tong, Z.; Wang, C.; Cheng, Z.-W.; Feng, K.; Qu, M.-M.; Chen, J.-M.; Deng, J.-G.; et al. Comparison of Separated and Combined Photodegradation and Biofiltration Technology for the Treatment of Volatile Organic Compounds: A Critical Review. Crit. Rev. Environ. Sci. Technol. 2022, 52, 1325–1355. [Google Scholar] [CrossRef]
  178. Dobslaw, D.; Ortlinghaus, O. Biological Waste Air and Waste Gas Treatment: Overview, Challenges, Operational Efficiency, and Current Trends. Sustainability 2020, 12, 8577. [Google Scholar] [CrossRef]
  179. Rene, E.R.; Veiga, M.C.; Kennes, C. Combined Biological and Physicochemical Waste-Gas Cleaning Techniques. J. Environ. Sci. Health Part A 2012, 47, 920–939. [Google Scholar] [CrossRef] [PubMed]
  180. Hu, X.-R.; Han, M.-F.; Wang, C.; Yang, N.-Y.; Wang, Y.-C.; Duan, E.-H.; Hsi, H.-C.; Deng, J.-G. A Short Review of Bioaerosol Emissions from Gas Bioreactors: Health Threats, Influencing Factors and Control Technologies. Chemosphere 2020, 253, 126737. [Google Scholar] [CrossRef]
  181. Sacco, O.; Vaiano, V.; Sannino, D. Main Parameters Influencing the Design of Photocatalytic Reactors for Wastewater Treatment: A Mini Review. J. Chem. Technol. Biotechnol. 2020, 95, 2608–2618. [Google Scholar] [CrossRef]
  182. Santoro, D.; Crapulli, F.; Turolla, A.; Antonelli, M. Detailed Modeling of Oxalic Acid Degradation by UV-TiO2 Nanoparticles: Importance of Light Scattering and Photoreactor Scale-Up. Water Res. 2017, 121, 361–373. [Google Scholar] [CrossRef]
  183. Sun, P.; Zhang, J.; Liu, W.; Wang, Q.; Cao, W. Modification to L-H Kinetics Model and Its Application in the Investigation on Photodegradation of Gaseous Benzene by Nitrogen-Doped TiO2. Catalysts 2018, 8, 326. [Google Scholar] [CrossRef]
  184. Shie, J.-L.; Lee, C.-H.; Chiou, C.-S.; Chang, C.-T.; Chang, C.-C.; Chang, C.-Y. Photodegradation Kinetics of Formaldehyde Using Light Sources of UVA, UVC and UVLED in the Presence of Composed Silver Titanium Oxide Photocatalyst. J. Hazard. Mater. 2008, 155, 164–172. [Google Scholar] [CrossRef]
  185. Wang, Z.; Liu, J.; Dai, Y.; Dong, W.; Zhang, S.; Chen, J. Dimethyl Sulfide Photocatalytic Degradation in a Light-Emitting-Diode Continuous Reactor: Kinetic and Mechanistic Study. Ind. Eng. Chem. Res. 2011, 50, 7977–7984. [Google Scholar] [CrossRef]
  186. Salvadó-Estivill, I.; Hargreaves, D.M.; Li Puma, G. Evaluation of the Intrinsic Photocatalytic Oxidation Kinetics of Indoor Air Pollutants. Environ. Sci. Technol. 2007, 41, 2028–2035. [Google Scholar] [CrossRef]
  187. Visan, A.; Van Ommen, J.R.; Kreutzer, M.T.; Lammertink, R.G.H. Photocatalytic Reactor Design: Guidelines for Kinetic Investigation. Ind. Eng. Chem. Res. 2019, 58, 5349–5357. [Google Scholar] [CrossRef]
  188. Salvadores, F.; Alfano, O.M.; Ballari, M.M. Kinetic Study of Air Treatment by Photocatalytic Paints under Indoor Radiation Source: Influence of Ambient Conditions and Photocatalyst Content. Appl. Catal. B-Environ. 2020, 268, 118694. [Google Scholar] [CrossRef]
  189. Tong, K.; Yang, L.; Du, X. Modelling of TiO2-Based Packing Bed Photocatalytic Reactor with Raschig Rings for Phenol Degradation by Coupled CFD and DEM. Chem. Eng. J. 2020, 400, 125988. [Google Scholar] [CrossRef]
  190. Malayeri, M.; Haghighat, F.; Lee, C.-S. Modeling of Volatile Organic Compounds Degradation by Photocatalytic Oxidation Reactor in Indoor Air: A Review. Build. Environ. 2019, 154, 309–323. [Google Scholar] [CrossRef]
  191. Boyjoo, Y.; Ang, M.; Pareek, V. Some Aspects of Photocatalytic Reactor Modeling Using Computational Fluid Dynamics. Chem. Eng. Sci. 2013, 101, 764–784. [Google Scholar] [CrossRef]
  192. Meng, X.; Yun, N.; Zhang, Z. Recent Advances in Computational Photocatalysis: A Review. Can. J. Chem. Eng. 2019, 97, 1982–1998. [Google Scholar] [CrossRef]
  193. Jiang, S.; Li, F.; Xie, F. Nonrelativistic Limit of the Compressible Navier--Stokes--Fourier--P1 Approximation Model Arising in Radiation Hydrodynamics. Siam J. Math. Anal. 2015, 47, 3726–3746. [Google Scholar] [CrossRef]
  194. Mueses, M.A.; Machuca-Martinez, F.; Hernández-Ramirez, A.; Li Puma, G. Effective Radiation Field Model to Scattering—Absorption Applied in Heterogeneous Photocatalytic Reactors. Chem. Eng. J. 2015, 279, 442–451. [Google Scholar] [CrossRef]
  195. Claes, T.; Dilissen, A.; Leblebici, M.E.; Van Gerven, T. Translucent Packed Bed Structures for High Throughput Photocatalytic Reactors. Chem. Eng. J. 2019, 361, 725–735. [Google Scholar] [CrossRef]
  196. De Oliveira, G.X.; Kuhn, S.; Riella, H.G.; Soares, C.; Padoin, N. Combining Computational Fluid Dynamics, Photon Fate Simulation and Machine Learning to Optimize Continuous-Flow Photocatalytic Systems. React. Chem. Eng. 2023, 8, 2119–2133. [Google Scholar] [CrossRef]
  197. Peralta Muniz Moreira, R.; Li Puma, G. Multiphysics Computational Fluid-Dynamics (CFD) Modeling of Annular Photocatalytic Reactors by the Discrete Ordinates Method (DOM) and the Six-Flux Model (SFM) and Evaluation of the Contaminant Intrinsic Kinetics Constants. Catal. Today 2021, 361, 77–84. [Google Scholar] [CrossRef]
  198. Van Walsem, J.; Verbruggen, S.W.; Modde, B.; Lenaerts, S.; Denys, S. CFD Investigation of a Multi-Tube Photocatalytic Reactor in Non-Steady-State Conditions. Chem. Eng. J. 2016, 304, 808–816. [Google Scholar] [CrossRef]
  199. Wang, Z.; Liu, J.; Dai, Y.; Dong, W.; Zhang, S.; Chen, J. CFD Modeling of a UV-LED Photocatalytic Odor Abatement Process in a Continuous Reactor. J. Hazard. Mater. 2012, 215–216, 25–31. [Google Scholar] [CrossRef] [PubMed]
  200. Kuspanov, Z.; Bakbolat, B.; Baimenov, A.; Issadykov, A.; Yeleuov, M.; Daulbayev, C. Photocatalysts for a Sustainable Future: Innovations in Large-Scale Environmental and Energy Applications. Sci. Total Environ. 2023, 885, 163914. [Google Scholar] [CrossRef]
  201. Hu, G.; Yang, J.; Duan, X.; Farnood, R.; Yang, C.; Yang, J.; Liu, W.; Liu, Q. Recent Developments and Challenges in Zeolite-Based Composite Photocatalysts for Environmental Applications. Chem. Eng. J. 2021, 417, 129209. [Google Scholar] [CrossRef]
  202. Amano, H.; Collazo, R.; Santi, C.D.; Einfeldt, S.; Funato, M.; Glaab, J.; Hagedorn, S.; Hirano, A.; Hirayama, H.; Ishii, R.; et al. The 2020 UV Emitter Roadmap. J. Phys. D Appl. Phys. 2020, 53, 503001. [Google Scholar] [CrossRef]
Figure 1. General structure of a photocatalytic system.
Figure 1. General structure of a photocatalytic system.
Agriculture 14 02216 g001
Figure 2. Principle mechanism of photocatalytic degradation of pollutants.
Figure 2. Principle mechanism of photocatalytic degradation of pollutants.
Agriculture 14 02216 g002
Figure 3. Schematics of some types of photoreactors: (a) monolithic reactor, (b) annular reactor, (c) packed-bed reactor, (d) fluidized-bed reactor.
Figure 3. Schematics of some types of photoreactors: (a) monolithic reactor, (b) annular reactor, (c) packed-bed reactor, (d) fluidized-bed reactor.
Agriculture 14 02216 g003
Figure 4. Schematics of two main types of plasma-photocatalysis systems: (a) IPC, reproduced from [52]; (b) PPC, reproduced from [170].
Figure 4. Schematics of two main types of plasma-photocatalysis systems: (a) IPC, reproduced from [52]; (b) PPC, reproduced from [170].
Agriculture 14 02216 g004
Figure 5. Schematic representation of three types of photocatalytic–biological methods: (a) biological method is set downstream of photocatalysis, (b) biological method is set upstream of photocatalysis, (c) biological method and photocatalysis are integrated. Reproduced from [177].
Figure 5. Schematic representation of three types of photocatalytic–biological methods: (a) biological method is set downstream of photocatalysis, (b) biological method is set upstream of photocatalysis, (c) biological method and photocatalysis are integrated. Reproduced from [177].
Agriculture 14 02216 g005
Table 2. Merits and demerits of different types of odor treatment methods.
Table 2. Merits and demerits of different types of odor treatment methods.
Mitigating StrategiesMitigation CategoryTarget PollutantsMeritDemeritReference
Adsorption and MaskingSource-based/End-of-pipeNH3, H2S, VOCsEasy to operate
Readily available raw materials
Effective in adsorbing various odor compounds
High regeneration costs, difficult to handle waste
Limited capacity for high flow or low gas concentration exhaust
[50]
Wet scrubberEnd-of-pipeNH3, H2S, VOCs, PMLarge exhaust treatment flow
Efficient for NH3, and other hydrophilic substances
Difficult to degrade hydrophobic VOCs
High water consumption and wastewater generation
[3,51]
Non-thermal plasmaEnd-of-pipeVOCs, PMStrong removal effect on VOCs in livestock and poultry farms
Significantly reduce PM and airborne aerosol concentrations
Formation of harmful by-products and intermediates
High electric consumption
[52,53]
Biological methodsEnd-of-pipeNH3, VOCs, PMLow energy consumption and no secondary pollutionHard to control moisture and pH
High pressure drop
Deterioration of the filter bed during long-term operation
[10]
PhotocatalysisSource-based/End-of-pipeNH3, H2S, VOCsSafe and non-toxic
High removal efficiency
Operate under mild ambient conditions
Dust in livestock and poultry farms can reduce photocatalytic efficiency
Potential generation of toxic by-products and intermediates
[54]
Table 3. A brief introduction to photoreactors.
Table 3. A brief introduction to photoreactors.
PhotoreactorAdvantagesDisadvantagesReference
Monolithic reactorHigh throughput and low pressure drop
Large surface to volume ratio
High photon flux utilization
Low light efficiency with significant gradient through monolithic materials[111,115]
Annular reactorAdvantageous for determining reaction kinetic parameters
High irradiance uniformity with a central light source
Easy to quantify reactor configuration parameters
Low gas throughput
Low surface to volume ratio
[20,111]
Packed-bed reactorSimple structure, easy operation, and low cost
High surface to volume ratio
Good recycling and high stability
High pressure drop
Easy to form channel flow resulting in low contact between catalysts and pollutants
[111,115]
Fluidized-bed reactorHigh throughput and low pressure drop
Good contact of catalyst-light and catalyst-reactants
Catalyst loss
Hard to control
[20,110]
Table 4. Summary of photocatalytic methods for NH3 removal.
Table 4. Summary of photocatalytic methods for NH3 removal.
Experimental Conditions
Temp/RH
Experimental ScaleYearLight SourceIrradiance (mW/cm2)UV Dose (mJ/cm2)Reactor or Reaction PlaceTreatment TimePhotocatalyst (Dose)Pollutant/REReference
18.9–27.30 °C/53.6%Farm-scale in farrowing rooms2008UV-A (315–400 nm)0–0.144NRThe whole farrowing barnNRTiO2 (70 g/m2)NH3/30.50%[28]
15 °C/75%Lab-scale2018UV-A (365 nm)NRsNRTubular photocatalytic reactorNRRGO-P25(NR)NH3/97.39%[11]
18 °C/NRLab-scale2019Xeon lightNRNRTubular photocatalytic reactorNRPolyester fiber supported TiO2 (0.18 g)NH3/90%[118]
22–28 °C/55–63%Pilot-scale2020UV-A-LED (365 nm)0–4.850–824.5Rectangular tunnel photoreactor170 sTiO2 (10 μg/cm2)NH3/8.7%[18]
22–28 °C/55–63%Pilot-scaleUV-A-fluorescent light (365 nm)0–0.440–74.8170 sTiO2 (10 μg/cm2)NH3/5.2%
NR/50%Lab-scale2021UV-A + UV-B2.45 (UV-A)
1.35 (UV-B)
NRAnnular reactor, mini-photocatalytic wind tunnel, photocatalytic wind tunnelNRGlass fiber cloth supported TiO2
(1.7 ± 0.1 μg/cm2)
NH3/43%, 50% (for mini-photocatalytic wind tunnel and photocatalytic wind tunnel, respectively)[65]
11 ± 3 °C/34 ± 6%Pilot-scale2021UV-A-LED (367 nm)0.413.90Photocatalytic mobile laboratory (serpentine tunnel reactor)9.5 sTiO2 (10 μg/cm2)NH3/9%[116]
0.105.8157 sTiO2 (10 μg/cm2)NH3/11%
NR/NRPilot-scale2022UV-A (315–400 nm)NANAThe whole piglets barnNAWO3 (NR)NH3/30.5%[119]
NR/NRPilot-scale2023UV-C (185–254 nm)NRNRPhotocatalytic scrubberNR25 nm-TiO2 (NR)NH3/89.1%[120]
NR/NRLab-scale2014UV-A (365 nm)0.46NRBlack-colored boxNRF-TiO2 (4.2 mg/cm2)NH3/35%[121]
25 ± 3 °C/12%Lab-scale2020UV-A-LED (365 nm)4.85970Annular reactor200 sTiO2 (10 μg/cm2)NH3/18.7%[122]
NR/NRLab-scale2015UV-C (185–254 nm)2.28.8Multi-stage honeycomb photocatalytic reactor4 sP25 (182 m2/m3)NH3/53%[123]
NR/NRFarm-scale in nursery swine buildingUV-C (185–254 nm)2.20.03960.018 sP25 (182 m2/m3)NH3/10%
30 °C/NRLab-scale2011UV-A (365 nm)11.6 aNRAnnular PVC photoreactor with aluminum foil10 sTiO2 (3.3 mg/cm2)NH3/47%[124]
12 sTiO2 (3.3 mg/cm2)NH3/54%
20 °C/60%Lab-scale2023UV lamp (wavelength not reported)NRNRAnnular formed of two concentric Pyrex tubes<4.76 s aTiO2 Glass Fiber Tissue (13 g/m2)NH3/29%[52]
23.6 °C/86%Pilot-scaleNH3/30–43%
NR/8.65, 25.9, 43.2, 69.2% bPilot-scale2014UV-A (355 nm)4.26.552–16.338Rectangular tunnel reactor1.56–3.89 s cGlass fiber tissue
(6.5 g/m2)
NH3/~4.6–32%[125]
Note: Temperature (Temp), relative humidity (RH), removal efficiency (RE), not reported (NR); a calculated from indirect information in paper; b relative humidity was calculated assuming an experimental temperature of 25 °C and 1 atm; c calculated from reactor volume area and gas flow rate.
Table 5. Summary of photocatalytic methods for H2S removal.
Table 5. Summary of photocatalytic methods for H2S removal.
Experimental Conditions
Temp/RH
Experimental ScaleYearLight SourceIrradiance (mW/cm2)UV Dose (mJ/cm2)Reactor or Reaction PlaceTreatment TimePhotocatalyst (Dose)Pollutant/REReference
NR/NRPilot-scale2021UV-A (365 nm)NRNRPhotocatalytic mobile laboratory (serpentine tunnel reactor)NRTiO2 (10 μg/cm2)H2S/40%[17]
25 ± 3 °C/12%Lab-scale2020UV-A-LED (365 nm)4.85970Annular reactor200 sTiO2 (10 μg/cm2)H2S/~3%[122]
20.1 ± 1.4 °C/51.4 ± 2.0%Lab-scale2015UV-A (368 nm)2.32–55.90.6–1.3Honeycomb monolith photocatalytic reactor0.23 sTiO2 (NR)H2S/14%[126]
NR/NRLab-scale2015UV-C (185–254 nm)2.28.8Multi-stage honeycomb photocatalytic reactor4 sP25 (182 m2/m3)H2S/49%[123]
NR/NRFarm-scale in nursery swine buildingUV-C (185–254 nm)2.20.03960.018 sP25 (182 m2/m3)H2S/24%
Lab-scale (150 ppm H2S gas)Lab-scale2018VUV lamp (<200 nm)NRNRTubular quartz photoreactor loaded with catalystsNRM-TiO2 (M = Mn, Cu, Ni, Co) (1 g)H2S/89.9% for Mn-TiO2[73]
Note: Temperature (Temp), relative humidity (RH), removal efficiency (RE), not reported (NR).
Table 6. Summary of photocatalytic methods for VOCs removal.
Table 6. Summary of photocatalytic methods for VOCs removal.
Experimental Conditions
Temp/RH
Experimental ScaleYearLight SourceIrradiance (mW/cm2)UV Dose (mJ/cm2)ReactorTreatment TimePhotocatalyst (Dose)Pollutant/REReference
20.1 ± 1.4 °C/51.4 ± 2.0%Lab-scale2015UV-A (368 nm)2.32–5.590.6–1.3Honeycomb monolith photocatalytic reactor0.23 sTiO2 (NR)MT/87%
DMS/96%
DMDS/91%
1-Butanol/95%
AA/89%
PA/98%
BA/98%
VA/99%
[126]
40 °C/40%Lab-scale2017UV-A (365 nm)0.06112.2Glass plates200 sTiO2 (10 μg/cm2)DMDS/40.4%
DEDS/81.0%
DMTS/76.3%
BA/86.9%
Guaiacol/100%
p-cresol/93.8%
[127]
21.8–26.0 °C/46–84%Pilot-scale2019UV-A (365 nm)0–0.040–1.89Rectangular tunnel photoreactor47.2 sTiO2 (10 μg/cm2)p-cresol/22.0%
DMDS/23.6% a
DMTS/41.1% a
BA/6.8% a
iso-VA/5.6% a
Phenol/10.9% a
Indole/47.5% a
[128]
22–28 °C/55–63%Pilot-scale2020UV-A-LED (365 nm)0–0.440–74.8Rectangular tunnel photoreactor170 sTiO2 (10 μg/cm2)DEDS/42%
BA/62%
p-cresol/49%
Skatole/35%
[18]
NR/NRPilot-scale2021UV-A (365 nm)0.415.3Photocatalytic mobile laboratory (serpentine tunnel reactor)9.51 sTiO2 (10 μg/cm2)DMDS/62%
iso-BA/44%
BA/32%
p-cresol/40%
Indole/66%
Skatole/49%
[17]
28.5 ± 2.3 °C/66 ± 4.3%Pilot-scale2021UV-A (367 nm)0.415.3Photocatalytic mobile laboratory (serpentine tunnel reactor)12.9 sTiO2 (10 μg/cm2)DMDS/62%
IA/44%
BA/32%
p-cresol/40%
Skatole/49%
[129]
UV-C (254 nm)3.7 × 10−41.6 × 10−34.32 siso-BA/10.3% a
UV-C (222 nm)5.9 × 10−42.55 × 10−34.32 siso-BA/11.8% a
BA/1.6% a
Indole/26.5% a
UV-C (185 + 254 nm)1 × 10−53 × 10−53 siso-BA/33.6% a
p-cresol/49.6% a
Skatole/16.5% a
22 ± 5 °C/40%Pilot-scale2020UV-A (365 nm)0.413.9Annular reactor9.51 sTiO2 (10 μg/cm2)AA/48.6%
BA/52.6%
p-cresol/66.5%
Indole/32.3%
[122]
16 ± 1 °C/40%Pilot-scaleUV-C (185 + 254 nm)10484.8 sTiO2 (10 μg/cm2)p-cresol/47.1%
Indole/54.2%
11 ± 3 °C/34 ± 6 °CPilot-scale2021UV-A-LED (367 nm)0.415.8Photocatalytic mobile laboratory (serpentine tunnel reactor)14.1 sTiO2 (10 μg/cm2)1-Butanol/41%[116]
20 °C/60%Lab-scale2023UV lamp (wavelength not reported)2.0<9.52Annular formed of two concentric Pyrex tubes<4.76 s bTiO2 Glass Fiber Tissue (13 g/m2)PA/37%[52]
20 °C/60%Lab-scale2015UV-A (360 nm)2.0NRAnnular reactorNRTiO2 Glass Fiber Tissue (6.5 g/m2)TMA/19–68%[130]
Ambient temperature/NRPilot-scale2017UV-A (wavelength not reported)NRNRRectangular tunnel photoreactor containing the pleated photocatalytic mediaNRTiO2 Glass Fiber Tissue (6.5 g/m2)Isovaleraldehyde/~38%[131]
32.4 °C/56%Industrial-scaleUV-A (wavelength not reported)NRNRTwo similar rectangular tunnel photoreactor connected in seriesNRTiO2 Glass Fiber Tissue (13 g/m2)Isobutyraldehyde/~20%
Isovaleraldehyde/~22%
2-methyl butyraldehyde/~23%
(NR/43%)Pilot-scale2006UV-A (365 nm)1.28NRCubic photoreactor made from Pyrex glass with an effect volume of 33.4 L (inner surface was coated with Teflon film to avoid adsorption)NRNH4+-TiO2 (3.93 mg/cm2)MT/86%[132]
25 °C/NRPilot-scale2008UV-C (185 + 254 nm)1.555.5Tubular photoreactor made from PTFE with quartz windows on its top for UV transmission37 sP25 (NR)MT/85.8%
ET/76.6%
DMS/77.4%
BM/87.6%
AA/58.8%
PA/64.7%
BA/61.2%
iso-VA/55.4%
p-cresol/73.4%
[133]
33–35 °C/NRPilot-scale2020UV-A (340–400 nm, peak at 365 nm)~28~50Quartz tubular photoreactor surrounded by UV lamps1.8 sAnatase-TiO2 (NR)DMDS/~50%
DMTS/~99%
Decane/~20–50%
[134]
~28~169.46.1 sDMDS/80–100%
DMTS/~99%
p-cresol/~99%
Decane/~90%
4.826.4–30.245.5–6.3 sDMDS/~90%
DMTS/~90%
Decane/2%
10.859.4–68.045.5–6.3 sDMDS/80–100%
DMTS/~99%
p-cresoll/~95%
Decane/30–60%
28.8158.4–181.445.5–6.3 sDMDS/80–100%
DMTS/~99%
p-cresol/~99%
Decane/~80–95%
Note: Temperature (Temp), relative humidity (RH), removal efficiency (RE), not reported (NR), methanethiol (MT), dimethyl sulfide (DMS), dimethyl disulfide (DMDS), dimethyl trisulfide (DMTS), isovaleric acid (iso-VA), acetic acid (AA), propionic acid (PA), butyric acid (BA), valeric acid (VA), isovaleric acid (iso-BA), trimethylamine (TMA), diethyl disulfide (DEDS), isobutyric acid (iso-BA), ethyl mercaptan (ET), butyl mercaptan (BM); a reduction is not significant; b calculated from indirect information in paper.
Table 8. The relationships between light intensity, reaction rate, and n in Equation (5) according to [185].
Table 8. The relationships between light intensity, reaction rate, and n in Equation (5) according to [185].
Wavelength (nm)Fitting Range I (mW∙cm−2)kK (mol m−2 s)n
3570–1.03.51 × 10−80.78
1.0–2.53.47 × 10−80.16
3750–1.03.02 × 10−80.69
1.0–2.53.00 × 10−80.20
3850–2.51.16 × 10−80.75
4020–2.54.12 × 10−80.86
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Han, D.; Sun, Q.; Yan, X.; Zhang, X.; Wang, X.; Wang, K. Review on Photocatalytic Applications for Deodorization in Livestock and Poultry Farms. Agriculture 2024, 14, 2216. https://doi.org/10.3390/agriculture14122216

AMA Style

Han D, Sun Q, Yan X, Zhang X, Wang X, Wang K. Review on Photocatalytic Applications for Deodorization in Livestock and Poultry Farms. Agriculture. 2024; 14(12):2216. https://doi.org/10.3390/agriculture14122216

Chicago/Turabian Style

Han, Dongxuan, Qinqin Sun, Xiaojie Yan, Ximing Zhang, Xiaoshuai Wang, and Kaiying Wang. 2024. "Review on Photocatalytic Applications for Deodorization in Livestock and Poultry Farms" Agriculture 14, no. 12: 2216. https://doi.org/10.3390/agriculture14122216

APA Style

Han, D., Sun, Q., Yan, X., Zhang, X., Wang, X., & Wang, K. (2024). Review on Photocatalytic Applications for Deodorization in Livestock and Poultry Farms. Agriculture, 14(12), 2216. https://doi.org/10.3390/agriculture14122216

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop