3.1. Emission Factors
All measurement data can be found in the
Supplementary Materials.
Table 1 displays the calculated emission factors for piglets and growing–finishing pigs. The emission factors for ammonia were 0.31 and 1.85 kg animal
−1 yr
−1 for piglets and finishing pigs, respectively. In general, ammonia emission in confined pig buildings arises from under-floor manure storage [
13]. As the pigs grew, their feed and manure production increased, leading to more ammonia emissions. It was evident that growing–finishing pigs produced higher amounts of TSP and PM compared to piglets. PM often originate from animal-related sources such as feed, faeces, and skin particles [
8]. As pigs progressed through their growth stages, the dust from these sources correspondingly increased, causing the emission factors for TSP and PM to increase.
This study’s ammonia emission factors were benchmarked against existing literature. The Clean Air Policy Support System (CAPSS) of Korea suggested emission factors of 4.4 and 11.4 kg animal
−1 yr
−1 for piglets and growing–finishing pigs, respectively, based on experimental studies conducted in domestic pig farms [
27]. The suggested values included emissions from buildings, compositing facilities, manure treatment facilities, and soil fertilisation. As indicated in
Table 1, the emission factors from pig buildings were 1.9 and 5.2 kg animal
−1 yr
−1. The emission factor for TSP provided by CAPSS was based on US EPA speciate 4.0 data (2006). Meanwhile, the emission factors for PM
10 and PM
2.5 were sourced from the European inventory EMPT/CORINAIR [
28]. Comparing our experimental results with those provided by CAPSS, we observed that the CAPSS emission factors were overestimated for all parameters, except for PM
2.5 in growing–finishing pigs. This discrepancy could stem from CAPSS relying on foreign data. Given the distinct environmental and livestock conditions in Korea versus Europe and the US, differences are expected. Factors like breeding density, pit type, climate, and ventilation can influence emissions, but pinning down their combined effects is not straightforward, as demonstrated by the wide range of emission factors shown in
Table 1. Additionally, the CORINAIR data used by CAPSS were outdated, and recent data [
29] show a decrease in all emission factors. In Korea, advances in livestock facilities have improved breeding environments, which could potentially reduce ammonia and PM.
The emission factors estimated in this study were generally lower than those proposed in Korea and Europe. Specifically, there were significant differences in ammonia and TSP emission factors, while the PM
10 emission factors were similar to those reported in Europe. The measured PM
2.5 values in our study were higher than the European emission factors. However, it is worth noting that some individual studies listed in
Table 1 have also reported similar emission factors to ours. This suggests that emission amounts can significantly vary across swine farms and underscores the importance of long-term measurements across diverse farms to determine representative values.
Notably, the emission factors of this study were derived from daytime measurements. The VERA test protocol suggests segmenting measurements into day and night if daily emission variations exist. However, due to restricted access and limited equipment, night-time measurements were not feasible in our study. The literature suggests that daytime ammonia emission factors are roughly 10% higher for piglets and 7% higher for fattening pigs than night-time values [
30]. Although there are no studies comparing daytime and night-time emission factors for PM, daytime emissions are expected to be higher given their correlation to animal activity [
22].
Table 1.
Emission factors were measured in this study (mean ± standard deviation) and obtained from the literature (kg animal−1 yr−1).
Table 1.
Emission factors were measured in this study (mean ± standard deviation) and obtained from the literature (kg animal−1 yr−1).
Literature | Piglets | Growing–Finishing Pigs |
---|
Ammonia | TSP | PM10 | PM2.5 | Ammonia | TSP | PM10 | PM2.5 |
---|
This study | 0.31 ± 0.21 | 0.04 ± 0.03 | 0.03 ± 0.03 | 0.01 ± 0.01 | 1.85 ± 1.26 | 0.22 ± 0.19 | 0.16 ± 0.17 | 0.09 ± 0.10 |
Korean CAPSS [27] | 1.9 | 0.54 | 0.18 | 0.029 | 5.2 | 1.26 | 0.42 | 0.069 |
EMPT/EEA [29] | | 0.27 | 0.05 | 0.002 | 3.7 1, 2.8 2 | 1.05 | 0.14 | 0.01 |
Literature review [31] | | | 0.56–0.73 * | | | | 0.75–1.46 * | 0.008 |
Literature review [23] | | | | | 1.6–4.8 | | 0.30–3.47 * | |
Belgian pig farms [23] | | | | | 2.20 | | 0.10 | 0.008 |
Irish pig units [19] | 0.40–1.09 | | | | 2.52–4.34 | | | |
Experimental units [26] | | | | | 2.38–2.53 | | | |
Chinese pig farms [32,33] | 0.038–0.118 | | | | | 0.39 | 0.18 | 0.044 |
3.2. Seasonal Variation in Emission Factors
The emission calculations for PM and ammonia were a product of the facility’s ventilation rate and the emission concentration. These emissions were highly influenced by climate and seasonal variations [
8,
20,
32,
34,
35,
36,
37]. In mechanically ventilated buildings, high ventilation rates were maintained to alleviate the heat stress of animals in summer, which in turn reduced the concentration of indoor concentrations of PM and ammonia. Conversely, during winter, minimised ventilation rates were maintained to conserve thermal energy, resulting in elevated indoor concentrations. Although our current emission factors were calculated assuming a year-long uniformity, understanding the seasonal fluctuations in emissions is crucial for effective livestock management and local environmental conservation. In this study, the data collected during the entire experimental period were divided into four seasons: spring (March–May), summer (June–August), autumn (September–November), and winter (December–February). The emission factors were then calculated for each season.
The seasonal emission factors for ammonia, as delineated in
Table 2, were as follows: 0.381, 0.299, 0.288, and 0.117 kg animal
−1 yr
−1 for piglets and 2.974, 1.017, 2.203, and 1.978 kg animal
−1 yr
−1 for growing–finishing pigs, corresponding to the spring, summer, autumn, and winter seasons, respectively. Interestingly, ammonia emissions were higher during the transitional seasons of spring and autumn, with a larger range of fluctuation, which could be attributed to significant changes in ventilation rate due to large daily temperature variations during the seasonal transition (
Figure 3). Conversely, during the summer, the change in emission factors was relatively small, as daily temperature changes were less pronounced, with ventilation fans operating at their maximum or minimum ventilation capacities throughout the season. This pattern is expected to reflect similarly during the winter months. A comparison between summer and winter emissions revealed that summer ammonia emissions in piglet pens were approximately three times that of winter emissions, corroborating with the findings of Feng et al. [
33]. However, the observed emission factors for growing–finishing pigs were unusual, as they were higher in winter than in summer. While ammonia generation typically increases at higher temperatures, resulting in increased emissions during summer [
38], our study found that the facility’s indoor temperature was consistently maintained at 26 °C or above throughout the year. This could have offset the seasonal temperature effect on ammonia emissions. The facility’s liquid manure pit recirculation system might also have played a role. This system separated the solid fraction of manure for collection and recirculated the liquid fraction through aerobic treatment, which effectively decreased nitrogen levels, potentially reducing ammonia gas generation compared to conventional swine housing methods [
39]. Another possible reason is the gas-to-particle conversion of ammonia gas to ammonium. This conversion is more prevalent in high-humidity environments [
40,
41,
42]. Given that approximately 60% of Korea’s annual rainfall occurs during the summer, leading to heightened humidity, it is plausible that extended manure storage in growing–finishing pig facilities during these conditions might encourage this ammonia-gas-to-ammonium conversion. This could explain the lower-than-anticipated ammonia emissions in summer. Moreover, the significantly increased PM
2.5 emissions observed in summer could align with this hypothesis.
This study also evaluated the seasonal emission factors of TSP, PM
10, and PM
2.5 in both piglet and finishing pig pens. For piglets, the seasonal TSP emission factors across spring, summer, fall, and winter were 0.044, 0.048, 0.039, and 0.009 kg animal
−1 yr
−1, respectively. For finishing pigs, the values were 0.249, 0.282, 0.137, and 0.247 kg animal
−1 yr
−1 in the same order. PM
10 emissions or piglets were 0.029, 0.048, 0.018, and 0.006 kg animal
−1 yr
−1 while, for finishing pigs, they were 0.133, 0.214, 0.077, and 0.154 kg animal
−1 yr
−1 in the same order. PM
2.5 emissions for piglets were 0.011, 0.022, 0.007, and 0.002 kg animal
−1 yr
−1 and, for growing–finishing pigs, they were 0.054, 0.193, 0.045, and 0.052 kg animal
−1 yr
−1. In contrast to ammonia emissions, PM emission factors peaked during summer, which was in agreement with the findings of Van Ransbeeck’s research [
23]. The variability was also most pronounced in summer. While winter emissions were lower in piglet pens, the fattening pig pens exhibited emissions similar to or even higher than the transitional seasons, showcasing a distinct pattern compared to ammonia emission factors.
The study determined that seasonal variations in PM and ammonia emissions were relatively small in the piglet facilities. In contrast, these variations were more pronounced in the growing–finishing pig facilities. Notably, the indoor concentrations in the growing–finishing pig facilities, skyrocketed during winter, primarily due to the reduced ventilation. This led to a significant increase in emission concentrations—about three to six times higher than in the autumn season. Therefore, even with the reduced ventilation rates, the emission factors remained elevated during winter.
3.3. Correlation Analysis
The ventilation rate and emission concentration are pivotal in calculating emission factors. These metrics are influenced by various factors, including external meteorological conditions, indoor climatic conditions, animal growth conditions, and farm operations and management. In this study, Pearson’s correlation coefficient was used to assess the interrelationship between these variables, as detailed in
Table 3,
Table 4,
Table 5 and
Table 6.
From the correlation analysis, a clear positive correlation was observed between the number of animals, their average age, and the ventilation rate. As pigs matured and gained weight, their breeding density also increased. This subsequently led to an increase in the total ventilation rate within the facility, aiming to maintain the required ventilation rate per pig, aligning with findings from prior research [
8,
43].
A pronounced positive correlation was identified between the ventilation rate and air temperatures both inside and outside the barn, with coefficients ranging from 0.488 to 0.498. This could be attributed to the consistent internal temperatures maintained in both piglet and finishing pig facilities, achieved by modulating the ventilation in relation to the external temperature. Moreover, there was a weak negative correlation between ammonia emission concentration and ventilation rate (−0.340). A more distinct negative correlation was noted between ammonia emission concentration and the external air temperature (−0.656) and inside the barn (−0.674), consistent with the findings of Van Ransbeeck et al. [
23].
The emission factor of ammonia demonstrated a strong positive correlation with both the number of animals (0.679) and their average age (0.613). As pigs age, the quantity of faeces they produce increases. Consequently, with an increasing number of animals, the total amount of faeces generated in the pit also increases, resulting in a proportional increase in the amount of ammonia generated. The emission factor of ammonia exhibited a strong positive correlation (0.574) with emission concentration but a very weak positive correlation (0.222 with a
p-value of 0.174) with ventilation, indicating a stronger association with emission concentration compared to ventilation, both of which were factors involved in the calculation of the emission factor. Notably, the ammonia emission factor demonstrated a significant negative correlation (−0.514) with indoor relative humidity. Philippe’s review paper corroborated these observations, suggesting that while indoor relative humidity might not directly influence ammonia emissions, factors like indoor temperature or ventilation might impact it. This, in turn, might introduce secondary effects driven by various complex factors, leading to a correlation with ammonia emission [
38]. Supporting this study, our study revealed that the ammonia emission factor in summer is significantly lower than in other seasons. Considering Korea’s climate, summers tend to have high relative humidity, while relative humidity drops during the winter and transition seasons. Thus, it is plausible to deduce that reduced humidity correlates with increased ammonia emissions, with the seasonal differences further solidifying the relationship between ammonia emissions and relative humidity.
Regarding the PM emission factors, TSP, PM10, and PM2.5 showed a positive correlation with the number of animals and their average age. This is because PM in pig houses often originates from various sources, including animal activities, faeces, feed dust, and hair. These data suggest that as the size and age of the pig increase, the likelihood of fine dust emission also increases.
Among the factors affecting the TSP emission factor, the average age had the highest correlation coefficient (0.581), followed by the number of animals (0.547), relative humidity inside the barn (−0.529), and ventilation rate (0.476). For PM
10, the order of strong correlation coefficients was ventilation rate (0.638), number of animals (0.488), and average age (0.473). For PM
2.5, it was ventilation rate (0.735), average age (0.526), and number of animals (0.465). The PM emission factors were influenced by both indoor relative humidity and indoor air temperature. However, TSP emission factors were more significantly influenced by indoor relative humidity. This is attributed to the fact that when humidity levels are high, dust absorbs more moisture, causing it to aggregate and settle on surfaces such as floors and equipment [
44]. Conversely, the emission factors of smaller particles like PM
10 and PM
2.5 were similarly affected by both indoor air temperature and relative humidity.
Compared to ammonia, the ventilation rate had a greater impact on PM emission factors than on emission concentrations. The correlation coefficients between ventilation rate and emission factors were 0.476 for TSP, 0.638 for PM10, and 0.735 for PM2.5. Notably, as particle size decreased, the positive correlation coefficient between ventilation rate and emission factor gradually increased. This happens because fine particles are more influenced by airflow and can move more freely along the streamline formed by the exhaust fan in the facility.
A prior study by Aarnink and Ellen [
43] reported that dust generated inside livestock facilities can either remain airborne or adhere to facility interiors and animals. Airborne dust can also re-deposit. The movement of animals mainly causes this airborne dust. Dust that becomes dislodged and airborne is then affected by the airflow in the facility formed by ventilation. Ventilation primarily affects the sedimentation rate of dust, with larger particles settling faster and smaller particles being more easily transported by air currents. Therefore, there is a stronger correlation between the ventilation rate and the generation of smaller PM.
Besides the emission factor, the emission concentration of PM was significantly affected by temperatures. The outdoor temperature had correlation coefficients of −0.635, −0.687, and −0.468 for TSP, PM
10, and PM
2.5, respectively, greatly affecting emission concentration. Indoor temperature also showed significant correlations, with coefficients of −0.539, −0.503, and −0.411, respectively. Both outdoor and indoor temperatures majorly impact the ventilation operation in pig farms. As temperatures increase, ventilation frequency and volume also increase, leading to reduced emission concentrations. However, no significant relationship was observed directly between emission concentration and ventilation rate. Meanwhile, as shown in
Table 3, with the ventilation rate showing positive correlations of 0.488 and 0.498 with the outdoor and indoor temperatures, respectively, it can be inferred that increasing temperatures leads to an increase in ventilation rates, which indirectly reduces emission concentrations.
Table 7 provides a comparative analysis of the monthly MSY values from May 2020 to October 2021, as reported by the farmer, against the average monthly emission concentrations and emission factors during the same period. The analysis revealed a distinct positive correlation between MSY and emission concentrations for several emission substances. For instance, there was a notable correlation between MSY and the concentrations of TSP and PM
10 for piglets and ammonia for growing–finishing pigs. However, drawing a direct connection between the emission concentration (which can be viewed as the indoor concentration) and MSY proved elusive. A higher MSY suggests a greater number of pigs ready for the market. Given that the number of pigs on the farm directly correlates with emission concentration, this seems to explain the observed relationship between MSY and emission concentration.
When MSY was compared with the emission factor, it was challenging to establish a clear correlation between ammonia and PM. It was thus concluded that the MSY, which represents the productivity of the farm, and the emission factors of ammonia and PM were not statistically significant. Prior research also supports this conclusion, suggesting that MSY is more influenced by qualitative factors such as the impact of diseases, education levels of farm owners, worker proficiency, and regular farm consultation rather than by quantitative factors such as the concentrations of ammonia or PM in farms [
45,
46].