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Rethinking methane from animal agriculture

Abstract

Background

As the global community actively works to keep temperatures from rising beyond 1.5 °C, predicting greenhouse gases (GHGs) by how they warm the planet—and not their carbon dioxide (CO2) equivalence—provides information critical to developing short- and long-term climate solutions. Livestock, and in particular cattle, have been broadly branded as major emitters of methane (CH4) and significant drivers of climate change. Livestock production has been growing to meet the global food demand, however, increasing demand for production does not necessarily result in the proportional increase of CH4 production. The present paper intends to evaluate the actual effects of the CH4 emission from U.S. dairy and beef production on temperature and initiate a rethinking of CH4 associated with animal agriculture to clarify long-standing misunderstandings and uncover the potential role of animal agriculture in fighting climate change.

Methods

Two climate metrics, the standard 100-year Global Warming Potential (GWP100) and the recently proposed Global Warming Potential Star (GWP*), were applied to the CH4 emission from the U.S. cattle industry to assess and compare its climate contribution.

Results

Using GWP*, the projected climate impacts show that CH4 emissions from the U.S. cattle industry have not contributed additional warming since 1986. Calculations show that the California dairy industry will approach climate neutrality in the next ten years if CH4 emissions can be reduced by 1% per year, with the possibility to induce cooling if there are further reductions of emissions.

Conclusions

GWP* should be used in combination with GWP to provide feasible strategies on fighting climate change induced by short-lived climate pollutants (SLCPs). By continuously improving production efficiency and management practices, animal agriculture can be a short-term solution to fight climate warming that the global community can leverage while developing long-term solutions for fossil fuel carbon emissions.

Background

The irreversible impacts of climate change have threatened the sustainability of the earth’s eco-system (O’Gorman 2015; Sahade et al. 2015; Demertzis and Iliadis 2018). The decadal mean temperature has been increasing steadily, resulting in the past decade being the warmest on record (NASA 2020). According to the World Meteorological Organization (WMO), global temperatures during 2015–2019 were on average, 1.1 ± 0.1 °C higher than the pre-industrial level (WMO 2020).

The vital solution to stopping the warming trend is achieving net “zero-emission” of long-lived climate pollutants (LLCPs), primarily carbon dioxide (CO2) and to a lesser degree nitrous oxide (N2O). However, there is growing recognition that minimizing the emissions of SLCPs will quickly, though temporarily, slow the warming of the atmosphere and buy time for the global community to develop solutions to keep temperatures from surpassing the 1.5 °C temperature goal set in the Paris Climate Accord (UNFCCC 2016).

Primary SLCPs include methane (CH4), black carbon, tropospheric ozone, and hydrofluorocarbons (Pierrehumbert 2014; Haines et al. 2017). These pollutants have a relatively shorter existence in the atmosphere, but have high warming potential (Table 1), contributing one-third of the current radiative forcing (RF) from GHGs (Ramanathan and Xu 2010; Shoemaker et al. 2013).

Table 1 Comparison of major SLCPs and CO2

Methane is the second-most abundant GHG and an important contributor to climate warming. Globally, the annual emission of anthropogenic CH4 was 572 (538–593) million metric ton (MMT) per year during 2008–2017, which is an increase of 3.6% from 2000–2010 level’s (Saunois et al. 2016; 2019). With a RF of 0.61 W m−2 (Etminan et al. 2016), CH4 heats the atmosphere 86 and 28 times more efficiently than CO2 over a 20- and 100-year time horizon, respectively.

Methane’s short atmospheric existence

Methane has a short atmospheric lifetime of 12.4 years (Myhre et al. 2013a). About 80–89% of the total atmospheric CH4 is removed by oxidation with tropical hydroxyl radicals (OH), a process referred to as hydroxyl oxidation (Levy 1971; Badr et al. 1992; Kirschke et al. 2013; He et al. 2019). Other sinks include reactions with stratospheric chlorine and oxygen atoms, uptake by soil, and reactions with chlorine atoms in the marine boundary layer (Saunois et al. 2019; Kirschke et al. 2013). Different from CO2, which persists and accumulates in the climate system, CH4 is constantly being removed from the atmosphere. This means that neutral warming will be achieved if the emissions equal the amount being oxidized and destroyed in the air. If emissions exceed the amount being removed, there will be warming. If emissions are less than the amount being removed, then there will be temporary cooling of the atmosphere. According to Cain et al. (2019), with an annual decline rate of 0.3%, a CH4 emission source will not lead to warming in 20 years.

For example, a herd of 100 head of cattle will contribute new CH4 to the atmosphere. But if the herd remains constant and reduces their emissions by 0.3% every year over the next 20 years—such as with improved genetics—their CH4 emissions will approximate what is being removed from the atmosphere. As a result, the herd’s warming from CH4 will be neutral. Reductions beyond that, mean that less CH4 is being emitted than removed from the atmosphere, and will induce cooling.

Allen et al. (2017) illustrated the differences between the climate impacts of CH4 versus CO2 in Fig. 1. Entering the atmosphere with steady rising emissions, both CH4 and CO2 warm the climate (Fig. 1, left). While the CH4 warms the climate linearly to its emissions, CO2 warms it at an accelerated rate.

Fig. 1
figure1

(adopted of Allen et al. (2017))

Corresponding climate impacts of a increasing, b constant, and c decreasing carbon dioxide and methane emissions

When emissions are constant, atmospheric CH4 is in a dynamic equilibrium where sources and sinks approximately balanced each other. Therefore, it holds the elevated temperature but adds little additional warming. In contrast, the warming caused by constant CO2 emissions further increases as the gas accumulates in the atmosphere (Fig. 1, middle).

In response to falling emissions, a decrease of current temperature occurs in response to decreasing CH4 emission as the sinks outweigh the emission sources (Fig. 1, right). The warming caused by atmospheric CH4 will drop to near zero in a decade when its emission becomes zero. In contrast, the temperature continues to rise with decreasing CO2 emissions and holds at elevated level as the emissions becomes zero.

Because of its comparatively short atmospheric lifetime, reducing CH4 emissions will not contribute to lowering long-term peak temperature, which is still determined by the stock of atmospheric CO2. However, the near-term benefits of SLCP mitigation on human health, agriculture, ecosystems, and climate have been widely recognized (Allen 2015; Haines et al. 2017).

Metrics for quantifying the climate impacts of methane

Global Warming Potential (GWP)

GWP transfers the climate contribution of different GHGs into a common scale and allows for their climate impacts to be compared. It quantifies the heat-trapping ability of different GHGs based on their RF. By definition (Myhre et al. 2013a), GWP is the time-integrated RF of one pulse emission of GHG related to that of CO2 over a chosen time horizon (Eq. 1).

$${\text{GWP}}_{{\text{i}}} \left( {\text{H}} \right) = \frac{{{\text{AGWP}}_{{\text{i}}} \left( {\text{H}} \right)}}{{{\text{AGWP}}_{{{\text{CO}}_{2} }} \left( {\text{H}} \right)}} = \frac{{\mathop \smallint \nolimits_{0}^{{\text{H}}} {\text{RF}}_{{\text{i}}} \left( {\text{t}} \right){\text{dt}}}}{{\mathop \smallint \nolimits_{0}^{{\text{H}}} {\text{RF}}_{{{\text{CO}}_{2} }} \left( {\text{t}} \right){\text{dt}}}}$$
(1)

where H is the selected time horizon, year; \({RF}_{i}\) and \({RF}_{{CO}_{2}}\) are the global mean RF of the GHG i and CO2, respectively; \({\text{AGWP}}_{\text{i}}\left(\text{H}\right)\) is the Absolute Global Warming Potential for the GHG i.

All GHGs can be converted into equivalent CO2 emission by multiplying the corresponding conversion factor, \({\text{GWP}}_{\text{i}}\left(\text{H}\right)\) (Eq. 2).

$${\text{E}}_{{{\text{CO}}_{2} {\text{-eq}}}} = {\text{E}}_{{{\text{GHG}}_{i} }} \times {\text{GWP}}_{{\text{i}}} \left( {\text{H}} \right)$$
(2)

where \({\text{E}}_{{\text{CO}}_{2-}\text{eq}}\) is CO2-equivalent emission; \({\text{E}}_{{\text{GHG}}_{i}}\) is the emission rate of the GHG i; \({\text{GWP}}_{\text{i}}\left(\text{H}\right)\) is the conversion factor; H is the selected time horizon, year.

Throughout the IPCC assessment reports AR1 to AR5, continuous updates on GWPs have been made to account for various interactions and processes. Commonly used GWP values for CH4 in the IPCC ARs (IPCC 1990, 1995, 2001, 2007, 2013) are listed in Table 2. GWP100, which is calculated based on a selected time horizon of 100 years, is the current universal GHG trading scheme.

Table 2 GWPs for methane in IPCC assessment reports (ARs)

Global Warming Potential Star (GWP*)

An alternative method denoted as GWP* has been recently proposed to assess the climate effects of SLCPs as a supplementary to GWP (Allen et al. 2017, 2018; Cain 2018). GWP* was first proposed in the form of Eq. 3, which equates the temperature impact of a sustained one-ton-per-year increase in SLCP emission to that of a one-off pulse emission of GWPH × H tons of CO2 (Allen et al. 2018). The recently updated GWP* (Eq. 4) is comprised of a “flow” term (\(r\times \frac{\Delta {E}_{SLCP}}{\Delta t}\times H\)), which characterizes the fast climate response from the atmosphere–ocean surface interface to the changed RF caused by SLCP emission, and a “stock” term (\(s\times {E}_{SLCP}\)), which represents the slower climate response from the deep ocean (Cain et al. 2019).

$${E_{C{O_2} - we}} = ~\frac{{\Delta {E_{SLCP}}}}{{\Delta t}} \times GW{P_i}\left( H \right) \times H$$
(3)
$${E_{C{O_2} - we}} = ~GW{P_i}\left( H \right) \times \left( {r \times \frac{{\Delta {E_{SLCP}}}}{{\Delta t}} \times H + s \times ~{E_{SLCP}}} \right)$$
(4)

where \({\text{E}}_{{\text{CO}}_{2}-\text{we}}\) is CO2-warming equivalent emission; \(\Delta {E}_{SLCP}\) is the change in SLCP emission rate over the time interval \(\Delta t\) (year); \({\text{E}}_{\text{SLCP}}\) is SLCP emission rate; r is the weighting assigned to the climate impacts of the change in SLCP emission rate; s is the weighting assigned to the climate impacts of the current emission (r + s = 1). Equation 3 can be considered a special case of Eq. 4 (r = 1 and s = 0) and can be applied to SLCPs that have only been released in recent years.

The weights r and s are scenario-dependent, and the exact values are estimated by multiple linear regression onto the response to CH4 emissions during 1900–2100 in different scenarios (Cain et al. 2019). Lynch et al. (2020) found that a combination of r = 0.75 and s = 0.25 provide a good estimation of both historical and predicted warming impacts of CH4 with different scenarios. Allen et al. (2018) showed that scaling the change in SLCP emission \(\Delta {E}_{SLCP}\) over a \(\Delta t\) = 20 year provided a good fit for modelled warming. Considering the near to medium effects with all recommended parameters, Eq. 4 can be simplified to Eq. 5:

$${E_{C{O_2} - we}} = ~GW{P_{100}} \times \left( {4 \times {E_{SLCP\left( t \right)}} - 3.75 \times {E_{SLCP\left( {t - 20} \right)}}} \right)$$
(5)

where \({\text{E}}_{\text{SLCP}\left(\text{t}\right)}\) and \({\text{E}}_{\text{SLCP}(\text{t}-20)}\) indicate a current and a 20 years ago SLCP emission, respectively.

It is shown in Eq. 5 that GWP* weighs the climate effects caused by the current CH4 emission (\({\text{E}}_{\text{SLCP}(\text{t})}\)) four times as high as that estimated by GWP. In the meanwhile, it considers most of the CH4 emitted 20 years ago as having been removed (\({\text{E}}_{\text{SLCP}(\text{t}-20)}\)).

Rather than being a brand-new metric, GWP* is a new way of applying GWP to SLCPs like CH4. GWP* does not convert the GHG emissions to an equivalent amount of CO2 (\({\text{E}}_{{\text{CO}}_{2}\text{-eq}}\)), which is always a positive number. Instead, it equates the climate impacts from a one-step permanent change of SLCP emission to that caused by a one-off “pulse” change of CO2 (\({\text{E}}_{{\text{CO}}_{2}-\text{we}}\), CO2-warming equivalent). Therefore, \({\text{E}}_{{\text{CO}}_{2}-\text{we}}\) can be either positive or negative to indicate the “warming” and “cooling” of the temperature compared with 20 years ago, related to an increase and decrease of CO2, respectively. Lynch et al. (2020) compared GWP100 and GWP* in different emission scenarios by using the FaIR v1.3 climate-carbon-cycle model. They demonstrated that GWP* provided a reliable link between CH4 emission and its warming impacts while GWP overestimated the climate impacts when the emissions were constant or decreasing.

Methane from animal agriculture

Methane from livestock production is primarily from enteric fermentation and manure management. Methane from enteric fermentation is a byproduct of digestion of feed materials, chiefly roughage. The majority of CH4 from ruminants is produced in the rumen and is exhaled or belched by the animal. During enteric fermentation in the rumen, methanogenic microorganisms generate CH4 from hydrogen (H2) and CO2 produced by protozoa, bacteria and anaerobic fungi (Martin et al. 2010; Morgavi et al. 2010; Tapio et al. 2017). The amount of CH4 emissions depends on animals (i.e. the type of digestive tract, production stage, age, and weight), feed (i.e. quality, quantity, and composition), and ambient temperature (Shibata and Terada 2010; IPCC 2019). The quantity and quality of feed affect the energy, nitrogen, and minerals available to the microorganisms in the rumen (Shibata and Terada 2010). The protein content in the feed negatively influences CH4 production, and the fiber content positively affects it (Shibata and Terada 2010). Only a small portion of CH4 is produced in the large intestines of ruminants and expelled via flatulence (EPA 1995).

Methane from livestock manure is a product of anaerobic decomposition of the organic residues in the excreta of animals through a two microorganism mediated processes: “liquification”, where organic substances are converted into organic acids with acetic and propionic acids being the primary products, and “methanogenesis”, where organic acids are broken down into CH4 within a pH range of 6.5–8.0 (Lapp et al. 1975). The anaerobic condition largely determines the production of CH4 during manure storage and handling. Methane emission from manure management is largely dependent on ambient temperature and the composition and management practices of manure, including treatment, storage, and application methods (Petersen et al. 2013).

Methane emissions vary significantly among different animal production systems. Liu et al. (2014) reviewed CH4 emissions data per animal unit (AU) in the literature and reported average emission rates from poultry layer houses (12–13 g d−1 AU−1), swine (24–16 g d−1 AU−1), beef steer (56–118 g d−1 AU−1), beef heifer (161–194 g d−1 AU−1), and dairy cows (281–323 g d−1 AU−1). According to the U.S. EPA GHG inventory (EPA 2020), beef and dairy cattle contribute 72% and 24.7% of the total CH4 from enteric fermentation (7.0 MMT), respectively; and beef and swine contribute 55.9% and 32.4% of the total CH4 from manure management (2.5 MMT), respectively.

By using the life cycle approach, Gerber et al. (2013) reported that global animal agriculture contributes to approximately 7.1 × 103 MMT CO2-eq GHG emissions every year, and livestock CH4 accounts for about 44% of this total amount. Saunois et al. (2019) summarized the outputs from inverse modeling of satellite-based observational data and reported a decadal mean CH4 emission of 111 (106–116) MMT year−1 from global livestock production during 2008–2017. The Food and Agriculture Organization’s (FAO) “bottom-up” inventory indicates that livestock contributed 103.5–109.9 MMT year−1 CH4 globally during the same period (FAO 1997). In the U.S., CH4 emissions from animal agriculture were 9.5 MMT in 2017 (EPA 2020).

Livestock, and in particular cattle, have been broadly branded as major emitters of GHGs and significant drivers of climate change (Steinfeld et al. 2006; Hyner 2015; Abbasi et al. 2016). Dairy and beef cattle account for 65% of global livestock’s CH4 emissions (Gerber et al. 2013). As a result, campaigns advocating for plant-based diets cite solving climate warming as one of the foremost reasons to forego meat (Orde 2016; McMahon 2019). But these opinions fail to distinguish the “flow gas” CH4 from the “stock gas” CO2 and the differences between biogenic and fossil fuel carbon. These arguments also overlook many other benefits of animal agriculture, including providing complete protein and utilizing non-arable land.

By using the examples of the U.S. cattle industry, the present paper intends to initiate a rethinking of CH4 associated with animal agriculture, in respect to its comparatively short atmospheric lifetime, recycling in the biosystem, and the assessment of its climate impacts, with the objectives to clarify long-standing misunderstandings and uncover the potential role of animal agriculture in fighting climate change.

Methods

Calculation of CH4 emission

CH4 emission from U.S. cattle

This paper looks at the CH4 warming impacts of U.S. cattle production (dairy and beef). The CH4 emission data for U.S. cattle production (both dairy and non-dairy) between 1961–2017 were downloaded from the FAOSTAT database (data source: FAO 1997).

CH4 emission from California dairy cows

The population data of dairy cows in California between 1951 and 2017 were obtained from the Milk Pooling Branch and Milk and Dairy Foods Safety Branches of California Department of Food and Agriculture (CDFA 2017). The 2000–2017 enteric CH4 annual emission factors of California dairy cows were from the Greenhouse Gas Inventory of California Air Resources Board (CARB 2019). Yearly CH4 emissions from enteric fermentation were estimated as the product of dairy cow population and the emission factor (Eq. 6).

$$E_{enteric} = {\text{population}} \times {\text{annual emission factor}}$$
(6)

As the emission factors for the years before 2000 were not available from the CARB Greenhouse Gas Inventory, the emissions from the early years were estimated by using the emission factor of the year 2000.

Total CH4 emissions from California dairies were the sum of CH4 from enteric fermentation and manure management. Methane emissions from manure management were estimated as below (Eq. 7).

$$E_{manure} = {\text{Population}} \times \mathop \sum \limits_{i = 0}^{all} \left( {{\text{Emission factor for MMP}}_{i} \times {\text{Proportion of MMP}}_{i} } \right)$$
(7)

The Manure Management Practices (MMPi) include anaerobic digester, anaerobic lagoon, dairy spread, deep pit, liquid slurry, pasture, and solid storage. The CH4 emission factor for each MMPi and the yearly proportion of each MMPi in California manure management system, as listed in Table 3, were obtained from the CARB Greenhouse Gas Inventory (CARB 2019).

Table 3 Emission factors used for calculating methane emission from California dairy cows

Calculation of CO2-equivalent

The CO2-equivalents of annual total CH4 emissions from U.S. cattle production were obtained by multiplying the GWP100 of CH4 (Eq. 2)

$${\text{E}}_{{{\text{CO}}_{2} {\text{-eq }}}} = {\text{E}}_{{CH_{4} }} \times {\text{GWP}}_{{{\text{CH}}_{4} }} \left( {100} \right)$$

where \({\text{E}}_{{CH}_{4}}\) is the annual total CH4 emission and \({\text{GWP}}_{{\text{CH}}_{4}}\left(100\right)\) is 28.

Calculation of CO2-warming equivalent

The CO2-warming equivalents of annual total CH4 emissions from U.S. cattle production were obtained using the GWP* method (Eq. 5).

$$E_{{CO_{2} {\text{-}} we}} = {\text{GWP}}_{{{\text{CH}}_{4} }} \left( {100} \right) \times \left( {4 \times E_{{CH_{4} \left( t \right)}} - 3.75 \times E_{{CH_{4} \left( {t - 20} \right)}} } \right)$$

where \({E}_{{CH}_{4}\left(t\right)}\) and \({E}_{{CH}_{4}\left(t-20\right)}\) indicate a current and a 20 years ago CH4 emission, respectively.

As Eq. 5 was derived by setting a \(\Delta t\) of 20-year, the first 20-year CH4 emission data (1961–1980) were used as reference (\({E}_{{CH}_{4}\left(t-20\right)}\) in Eq. 5) to obtain the \({E}_{{CO}_{2}-we}\) during 1981–2000.

Results

Cattle production in the U.S.

From 1961 to 2017, the U.S. dairy cattle population has decreased by 46% (FAO 1997). At a similar time, the population of beef cattle peaked at 1.2 × 108 head in 1975, before declining. In 2017, the beef cattle population was 8.4 × 107 head—a reduction of 30% from 1975 (Fig. 2).

Fig. 2
figure2

U.S. non-dairy (i.e., beef) and dairy cattle population between 1961 and 2017. Hollow columns represent non-dairy cow population; solid columns represent dairy cow population; dashed lines represent total methane emission

Total CH4 emission from U.S. cattle production, including emissions from both enteric fermentation and manure management, was 7.4 MMT in 1961 and 6.2 MMT in 2017, with a peak emission of 8.5 MMT in 1975 (FAO 1997). The CH4 emission from U.S. cattle was 27% less in 2017 than the 1975 level.

Shown in Fig. 3, CH4 from U.S. cattle was contributing negative CO2-we to the climate each year since 1986, except for the period of 2008–2012. Between 1986 and 2017, the decrease in average annual CO2-we from U.S. cattle CH4 emission is equivalent to decreased warming from 50 MMT atmospheric CO2 (Fig. 3, top), which is approximately 1% of the emission from nationwide fossil fuel combustion (EPA 2020). However, the GWP results suggested that the CH4 emissions from U.S. cattle production led to a “net carbon” (CO2-eq) gain of 165–196 MMT annually during the same period.

Fig. 3
figure3

Climate impacts of the methane from U.S. non-dairy (i.e., beef) and dairy cattle production. Solid line represents GWP results and dashed line represents GWP* results

For the cumulative climate impacts assessed by GWP, it was aggregating all the past impacts throughout 1981–2017 without acknowledging decreases in warming during those years. It only showed positive warming from a decreasing herd, even though less cattle resulted in less CH4, and thus less warming. As a result, it did not accurately calculate the warming caused by CH4 from the U.S. cattle herd during that period (Fig. 3, bottom). Conversely, the GWP* fluctuated between 55 and 200 MMT CO2-we in the 1980s, and since 1990, it has become increasingly negative in response to factoring in the reduced emissions of the gradually decreasing herd.

Dairy production in California

California leads the United States in agriculture production and is the largest producer of milk and dairy products (USDA 2020). To further investigate how the development of the U.S. livestock industry affects climate change, and how GWP versus GWP* provide different indications to mitigation priorities, we focused on California dairies, applying the two metrics to their CH4 emissions.

From 1950 to 1970, the California dairy industry was contracting by farm but not animal numbers: The number of farms decreased by 75% (from 19428 to 4473) while the total herd in the state remained stable, between 7.5 × 105 and 8.5 × 105 head (CDFA 2017).

Between 1970 and 2008, the California dairy industry boosted its production and the total herd doubled from 8.5 × 105 to 1.9 × 106 head (Fig. 4). The special concentration continued with the number of farms decreasing from 4473 in 1970 to 1852 in 2008. During this time, from 1970 to 2008, the warming impact of California dairies increased using both GWP and GWP*. But GWP* showed warming increasing three times quicker than the traditional method, GWP. Noticeably, the state implemented its first climate policy, California Global Warming Solutions Act, in 2006 and set its goal for a sustainable development outlook.

Fig. 4
figure4

California dairy cow population and milk production between 1950 and 2017. Columns represent the dairy cow population in California and the dashed lines represent the milk production

Between 2008 and 2016, the number of California dairy cows has been decreasing by about 1% annually, and GWP* and GWP characterize climate contributions of California dairies drastically different. GWP* calculations show warming peaking in 2008, and then rapidly decreasing to 50% of its peak value in 2017, while the GWP results hit a plateau in 2008 and held at elevated levels from then on (Fig. 5, top).

Fig. 5
figure5

Climate impacts of methane from California dairy production. Grey and black solid lines represent GWP and GWP* of the methane emissions from California dairy cows, respectively; grey and black dotted lines represent the GWP and GWP* results, respectively, when the herd is constant; grey and black dashed lines represent the GWP and GWP* results, respectively, when the herd decreases 1% every year; grey and black dash-dotted lines represent the GWP and GWP* results, respectively, when the methane emissions meet California’s mitigation target

Because the GWP* results showed that climate warming effects of animal agriculture could be significantly reduced by lowering emissions slightly, we continued our study with a 20-year projection, starting from 2018, in three assumed scenarios. The first scenario simulates when the California dairy industry continues current production practices and the emissions of CH4 remain constant with the 2017 level. The second scenario simulates the emissions of CH4 continue to decrease by 1% per year to approximate the results of the 1% annual decrease in population between 2008 and 2016. The third scenario simulates the emission of CH4 meets the target mitigation goal of California to reduce 40% of CH4 emissions from livestock by 2030 (below 2013 level).

If CH4 emissions from the California dairy industry remain constant every year, GWP* suggests that annual warming will decrease to less than 20% of the 2008 peak level in ten years and stabilize around 13% of the peak level in twenty years (Fig. 5, top).

If CH4 emissions continue to decrease by 1% every year, GWP* calculations indicate that the dairy industry will no longer contribute additional warming after ten years of reduction.

If CH4 emissions follow California’s ambitious mitigation goal established in Senate Bill 1383, which calls for a 40% reduction of 2013 emission by 2030, the CH4 from the dairy industry will be contributing negative GWP* after five years of reduction (Fig. 5, top). Assuming the reduction has started in 2018, the annual reduction is equivalent to removing the warming caused by 9 and 25 MMT CO2 every year during the 2020s and the 2030s, respectively. The projection indicates that it is an efficient short-term solution. In contrast, the GWP results continued to show the warming contribution by the dairy industry every year in all three projected scenarios (Fig. 5, bottom).

Discussion

Recycled carbon in animal agriculture

To fully understand livestock’s contributions to the climate, it must be understood that CH4 emissions from biogenic- versus fossil sources do not equally correspond to warming. This is because biogenic CH4 is not new carbon in the atmosphere. It is a constituent of the natural biogenic carbon cycle, which has been an essential part of life since it began.

In the natural biogenic carbon cycle, plants assimilate CO2 from the atmosphere during photosynthesis and store it as carbohydrates (e.g., cellulose or starch). Ruminant animals consume the plants and convert some of the carbon contained in plant carbohydrates into CH4, which is then exhaled or belched out into the atmosphere. The CH4 remains in the atmosphere for about 12 years, before it is converted back into CO2 through hydroxyl oxidation (Levy 1971; Badr et al. 1992). Therefore, biogenic carbon is “recycled carbon” and not new and additional to our atmosphere, though the warming effects during its atmospheric presence should still be recognized. Biogenic carbon is markedly different from fossil fuel carbon, the latter which was stored underground for millions of years, and then added to the atmosphere. The combustion of fossil fuel frees this carbon at a speed much faster than it can be removed, resulting in “net additional carbon” added to the atmosphere. Therefore, the carbon in biogenic and fossil CH4 are different in respect to their originations and atmospheric behaviors. Biogenic carbon keeps recycling among bio-system and the atmosphere, while the carbon from fossil fuel is a “net” addition to the atmosphere.

In the case of a stable herd with decreasing CH4 emission, the availability of cattle emitted carbon is reduced in the atmosphere. Yet, the biogenic carbon cycle will still require carbon as the herd’s feed demand will remain unchanged. Atmospheric carbon—from biogenic or fossil sources—will be incorporated into the cycle, eating into the abundance of CO2 that has accumulated in the atmosphere. If the CH4 emission from a herd decreases due to improved technologies and farm management, the biogenic carbon cycle can continuously absorb the airborne net carbon in the air, serving as a temporary “sink” to reduce the current atmospheric carbon burden, providing a short-term solution to climate warming.

Quantification of methane’s climate effects

Limitations with applying GWP to biogenic methane

Albeit the wide international application of GWP100 as a quantitative basis for GHG trading, there is no shortage of discussion on its limitations, especially its applicability to SLCPs like CH4 (Harvey 1993; Manne and Richels 2001; Alvareza et al. 2012).

First, though GWP does account for the different lifetime of GHGs, the physical interpretation of a SLCP’s GWP becomes increasingly ambiguous as the selected time horizon extends. When the integration in Eq. 1 proceeds over the 100-year horizon, the numerator approaches a constant quickly because the emitted CH4 will be oxidized in about a decade, but in the meantime, the denominator keeps increasing. Therefore, the magnitudes of GWPs are strongly dependent on the selection of the target time horizon for assessment (Manne and Richels 2001).

Second, GWP does not accurately reflect the actual climate impacts of CH4. Defined as the ratio of time integrals of RF, GWP can only be positive and always indicates a “warming” effect on the climate. It cannot reflect the potential “cooling” caused by a decline of the CH4 emission (Fig. 1, right). Therefore, using GWP as the quantification tool overestimates the climate impacts caused by constant or decreasing emissions of SLCPs, and therefore could overlook opportunities for climate mitigation.

GWP* for evaluating the climate effects of SLCPs

GWP* is designed to characterize the short-lived nature of SLCPs. Cain et al. (2019) and Lynch et al. (2020) explained the application of GWP* with different emission scenarios and demonstrated that GWP* was able to accurately assess the “cooling” of the temperature compared with 20 years ago when the sinks of CH4 outweigh the emissions, while GWP still ended up with “warming” effects under the same scenario.

Also, GWP* can be directly linked to the temperature change by using a transient climate response to cumulative carbon emissions (TCRE) coefficient. But this method tends to underestimate the temperature response and is less accurate compared to more comprehensive methods (Lynch et al. 2020).

However, the practical application of GWP* will inevitably encounter challenges. Developers still need to provide different SLCP-specific parameter sets for GWP*, which may complicate its application. More case studies are necessary to further comprehension of the new GWP*, as well as the conceptional differences between \({\text{E}}_{{\text{CO}}_{2}\text{-eq}}\) and \({\text{E}}_{{\text{CO}}_{2}-\text{we}}\). Future investigations are needed regarding how to incorporate the climate information provided by GWP* into carbon footprint studies and GHG mitigation policies (Schleussner et al. 2019).

The climate impacts of U.S. cattle production when considering GWP*

According to the long-term projection of the International Farm Comparison Network (IFCN), the worldwide milk demand will increase by 35% by the end of 2030 as both the global human population and dairy consumption per capita increases by 16% (Wyrzykowski et al. 2018). However, increasing demand for production does not necessarily result in the proportional increase of CH4 production.

Methane emission from U.S. cattle was decreasing and contributing negative CO2-we to the climate each year since 1986, except for the period of 2008–2012, indicating decreasing of the temperature rather than “warming”. As a result of a decreasing CH4 emission, the biogenic carbon cycle consumed more carbon than it emitted and offset “net carbon” in the atmosphere, contributing to a “cooling” of the temperature compared to 20 years ago.

According to Cain et al. (2019), it will not add additional warming to the climate in twenty years when the CH4 emission is reduced by 0.3% every year. The 20-year projections in our study indicates that the dairy industry in California can effectively help limit warming in ten years with an annual CH4 reduction of 1%, which is achievable by further utilizing production efficiencies and optimizing waste management. It is an example of a short-term solution to climate warming that the global community can leverage while developing long-term solutions.

Approaches of California dairy industry to climate neutrality

The projections demonstrate that portions of animal agriculture are already part of a climate solution in some regions. With genetic optimization, better nutrition and animal care, and farm management improvements, less emissions are generated today while still meeting the increased demand for dairy products. For example, the advancements in genetic evaluation and artificial insemination in the late 1960s increased the availability of the high-yielding dairy cows for producers, which promoted the annual yield of milk by 55% since 1980 (Shook 2006; Bauman and Capper 2010). The introduction of a total mixed ration in the 1970s and the diet formulation program enabled feeding a nutritionally well-balanced diet to ensure the performance and productivity of dairy cows (Kolver and Muller 1998; Bauman and Capper 2010). From 1950 to 2016, the dairy industry in California has tripled its milk production efficiency from 3.3 × 103 to 10.6 × 103 kg per cow, while the CH4 emitted per unit milk production (kg CH4/ kg milk) decreased from 0.102 to 0.035.

Continued progress of farm management practices significantly reduce GHGs and other gas pollutants from dairy farms (Boadi et al. 2004; Newbold and Rode 2006). For example, anaerobic digesters have gained growing popularity due to their capacity to reduce GHGs and recover energy. As of March 2020, there were a total of 127 anaerobic digesters on dairy farms throughout California, and 108 of them were granted by the Dairy Digester Research and Development Program (DDRDP) between 2015 and 2019 (CDFA 2020). In conjunction, a total of 106 dairies were funded to install alternative manure management practices (AMMPs), including separators, weeping walls, scrapers, alternative manure treatment and storage, etc. According to CDFA, these measures will provide an annual reduction of 2.2 × 106 tons CO2-eq GHGs, which equals 25% of the manure CH4 emissions in the state’s 2013 inventory, over the next five years (CDFA 2019).

California dairy farms are also taking additional steps to mitigate their total GHGs emissions via various measures, such as the adoption of solar energy and electrified farm practices. According to the life cycle assessment of Naranjo et al. (2020), California dairies emitted 1.12 to 1.16 kg CO2-eq GHG emissions to produce 1 kg energy-and protein-corrected milk (ECM) in 2014, which is a reduction of 45–46.9% compared to its 1964 level.

Conclusions

Methane is a short-lived climate pollutant  and it is fundamentally incorrect to assess the climate contribution of the “flow gas” CH4 in the same way as the “stock gas” CO2. The widely used metric GWP overestimates the CH4 induced “warming” and fails to reflect the relative “cooling” when the emission is decreasing. Therefore, applying GWP to biogenic CH4 from animal agriculture may result in misguided mitigation strategies and targets.

GWP* should be used in combination with GWP to provide feasible strategies on fighting SLCPs-induced climate change. The GWP* results in the present study showed that U.S. cattle production did not contribute additional climate warming between 1986 and 2017. It also suggest that California dairy farms are on the path to climate neutrality. By continuously improving production efficiency and management practices, animal agriculture can be a short-term solution to fight climate warming that the global community can leverage while developing long-term solutions for fossil fuel carbon emissions.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on request.

Abbreviations

AGWP:

Absolute Global Warming Potential

AMMPs:

Alternative manure management practices

ARs:

IPCC assessment reports

AU:

Animal unit

CARB:

California Air Resources Board

CDFA:

California Department of Food and Agriculture

DDRDP:

Dairy Digester Research and Development Program

\({\text{E}}_{{\text{CO}}_{2}\text{-eq}}\) :

CO2-equivalent emission

\({\text{E}}_{{\text{CO}}_{2}-\text{we}}\) :

CO2-warming equivalent emission

ECM:

Energy- and protein-corrected milk

EPA:

Environmental Protection Agency

FAO:

Food and Agriculture Organization of the United Nations

GHG:

Greenhouse gas

GWP100 :

100-Year global warming potential

GWP*:

Global warming potential star

Gt:

Gigaton (109 tons)

IFCN:

International Farm Comparison Network

IPCC:

Intergovernmental Panel on Climate Change

LLCP:

Long-lived climate pollutant

MMT:

Million metric ton (106 tons)

MMP:

Manure Management Practices

RF:

Radiative forcing

SLCP:

Short-lived climate pollutant

TCRE:

Transient climate response to cumulative carbon emissions

UNFCCC:

United Nations Framework Convention on Climate Change

USDA:

United States Department of Agriculture

WMO:

World Meteorological Organization

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SL analyzed the data and wrote the manuscript. JP provided critical comments and assisted in revising the manuscript. FM guided this study and proposed the core viewpoints of this manuscript. All authors read and approved the final manuscript.

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Liu, S., Proudman, J. & Mitloehner, F.M. Rethinking methane from animal agriculture. CABI Agric Biosci 2, 22 (2021). https://doi.org/10.1186/s43170-021-00041-y

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Keywords

  • Methane
  • Short-lived climate pollutant
  • Greenhouse gas
  • Livestock
  • Cattle
  • Global warming potential
  • GWP*