Elsevier

Biosystems Engineering

Volume 193, May 2020, Pages 126-137
Biosystems Engineering

Review
Meta-analysis of greenhouse gas and ammonia emissions from dairy manure composting

https://doi.org/10.1016/j.biosystemseng.2020.02.015Get rights and content

Highlights

  • Silo composts perform better in reducing GHG emissions than static, turning, windrow.

  • Lower initial TC and TN minimises emissions better than adjusting environmental conditions.

  • Applying compost biofilters is most effective to reduce NH3 emissions during composting.

  • Adding sawdust or straw could significantly reduce CH4 and N2O emissions during composting.

In order to minimise nutrient losses, comprehensive overviews of the magnitude of gaseous emissions from manure composting processes and the factors that influence these losses are urgently needed. This study presents a meta-analysis of greenhouse gases (GHGs) and ammonia (NH3) emissions from four main dairy manure composting methods (static, turning, windrow and silo) based on 41 scientific articles (153 treatments). Gaseous emissions and secondary variables such as average composting temperature, initial moisture content, initial total carbon (TC) and initial total nitrogen (TN) content from each compost treatment were extracted and normalised to enable inter-study comparison. Six mitigation measures for composting were selected and mitigation efficiency (Em) of each measure on different gas emissions were calculated. Gaseous emissions from different composting methods showed large differences. Turning composting resulted in larger carbon and nitrogen losses compared to other composting methods. Although silo composting significantly promoted NH3 emission, it reduced GHG losses by 82.84% compared with turning composting. Principal component analysis showed that the initial TC and TN content of the composted material were crucial in mediating gaseous emissions. Low TC and TN content can simultaneously reduce CH4, CO2 and N2O emissions. Applying compost biofilters was the most effective way to reduce NH3 emission with ME value of −97%. Adding sawdust or straw could reduce CH4 and N2O emissions by 66.3% and 44.0% respectively. Gaseous emissions from dairy manure composting varied a lot and were affected by physical characteristics of composted material and management practices of composting.

Introduction

Manure composting technology has become the most popular form of manure management (Bernal et al., 2009, Onwosi et al., 2017), since it not only can reduce the volume of the accumulated faeces from intensive and specialised animal production but also produces a slow-release end-product, rich in humus, which could be used for crop fertilisation. However, manure composting also emits greenhouse gases such as N2O, CO2, CH4 and NH3 into the atmosphere, which could contribute to global warming, acidification of soil and formation of particulate matters in the air (NH3). It has been reported that gaseous emissions from the manure composting process may account for 46% and 67% of the initial N and C content of the original manure, respectively (Shah, Oenema, & Lantinga, 2012). Most of the total N mass in the initial material can be lost by NH3 emission throughout the composting process (Martins and Dewes, 1992, Parkinson et al., 2004, Sommer, 2001). Nitrous oxide emission accounted for about 0.1%~5% of total N losses (Sommer, 2001, Tamura and Osada, 2006, Maeda et al., 2013a, Mulbry and Ahn, 2014), but it could cause more environmental concerns as N2O has 265 times the global warming potential of CO2 (IPCC, 2013). Carbon dioxide production was the principal pathway for C losses, and CH4 emission may represent less than 10% (Hao et al., 2004, Mulbry and Ahn, 2014). These released gases are the major contributors to global warming (IPCC, 2013). Therefore, accurate estimation of gaseous emissions from dairy manure composting has great importance in mitigating nutrient losses and alleviating environmental pollution. Currently, the calculation of GHG emissions from composting is based on default values recommended by the IPCC, with the values of 0.44–2.41 g [CH4] kg−1 [VS] and 6–100 g [N2O–N] kg−1 [TN] (IPCC, 2006). Nevertheless, these recommended values have been questioned because of large biases, with most of the GHG emission factors from literature of dairy manure composting (Biala et al., 2016, Fillingham et al., 2017, Sommer, 2001). For example, Sommer (2001) reported that 0.09 g [CH4–C] kg−1 [DM] and 2.00 g [N2O–N] kg−1 [TN] were lost during the composting. Biala et al. (2016) believed gaseous emissions from composting were 0.004 g [CH4–C] kg−1 [DM] and 0.01 g [N2O–N] kg−1 [TN], and Fillingham et al. (2017) reported gaseous emissions from composting as 0.85 g [CH4–C] kg−1 [DM] and 10.40 g [N2O–N] kg [TN]. Even though much work in the literature has evaluated GHG and NH3 emissions during composting processes on dairy farms, it is challenging to integrate and compare these results due to differences in composting methods (e.g., static, turning, windrow, silo) and functional units (e.g., emissions per kg fresh manure or per kg manure dry matter or other constituents). A systematic analysis can review and integrate quantitative results from publications, hence refining the emission factors with additional information about composting conditions. Previous systematic analyses of GHG and NH3 emissions from dairy farms have mainly focused on anaerobic digestion processes (Ahn et al., 2011, Miranda et al., 2016, Miranda et al., 2015, Sajeev et al., 2018) and the whole manure management chain (Hou et al., 2015, Wang et al., 2018). A systematic analysis focused on gaseous emissions from dairy manure composting is still lacking.

This work addressed this by systematically reviewing and numerically combining studies of GHG and NH3 emissions from dairy manure composting. We reviewed studies that analysed potential factors affecting gaseous emissions from the dairy manure composting process and the effects of mitigation measures during composting on CH4, CO2, N2O, and NH3 emissions. The specific objectives of this study were to:

  • (1)

    compare differences in GHG and NH3 emissions from different composting methods;

  • (2)

    identify key environmental and chemical explanatory variables that might affect GHG emissions from dairy manure composting process;

  • (3)

    analyse the impacts of mitigation measures on GHG and NH3 emissions at the composting stage.

Section snippets

Data sources and extraction

In order to include as many publications about dairy manure composting as possible, a systematic literature search and selection from bibliographic databases were performed. Keywords and logical connectors represented in Fig. 1 were used for searching scientific articles. The keywords aimed to identify papers focusing on the cattle husbandry sector, composting technologies and the emission indicators. Articles published before December 2018 were collected from Web of Science (WOS, //apps.webofknowledge.com/

Gases emissions from different composting methods

Gaseous emissions from different composting methods are shown in Fig. 3. Basic statistics (including mean, median, range and 95% IQR) of emission factors of CH4, CO2, N2O and NH3 can be found in Table S6 in Supporting Data. A total of 65 treatments relating to CH4 emission were reported in the database. Turning and windrow composting showed the highest median values of CH4 EFs, followed by static composting, while silo composting had the lowest CH4 emission (Fig. 3A). The high emissions for

Conclusions

The emissions of GHG and NH3 from four common composting methods (static, turning, windrow and silo composts) were compared. Turning composting would cause the highest gas emissions compared to other composting methods, whereas silo composts had the best performance in reducing GHG emissions though they significantly promoted N losses through NH3 emission. The EFs from data synthesis in this study can refine and supplement the EFs of IPCC recommended values for dairy manure composting and

Declaration of Competing Interest

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

Acknowledgements

This work was supported by The National Key Research and Development Program of China (grant number 2018YFD0800100); Innovation Team of Tianjin Cattle Research System (grant number ITTCRS2017006).

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