**3. Results and Discussion**

The temporal effects of the annual emissions on the current year basis and the cumulative effect of this flow in the atmosphere for both continued emission flow and the eliminated emission flow are given in Figure 9.

In Figure 9, each curve represents the annual pulse emissions. Since the pollutants emitted in previous years are still in the atmosphere and decaying (see Figure 4 for individual emission decay trendlines), these pollutants are added up to emissions of the current year. The accumulation of these pulse emissions is continued until the pollutant has converged to zero concentration.

As can be seen in Figure 9, the flow rate of emission on the current year basis is relatively lower than the amount of the total cumulative emission in the air from the previous years. From this observation, two essential conclusions can be given. First, the importance to account and reduce also "small" amounts of emissions since these "small" amounts add up to a more significant cumulative effect. And second, the interference in the flow of the emissions will have a "visible" affect only a couple of decades later, since it takes time to decay emissions already accumulated in the atmosphere.

The cumulative GHG emissions calculated using the GWP100 values from the IPCC fourth [16] and fifth [15] assessment report and the emissions calculated using the decay function from BCCM show more substantial disparities in a shorter time horizon. At the same time, these disparities reduce in a longer time horizon (see Figure 10).

The use of the latest GWP100 values from IPCC 2013, which include carbon cycle feedback [15], results in emission curves located closer to the curves obtained with BCCM than the use of GWP100 values taken from IPCC 2006 [16]. Especially significant convergence towards numbers obtained by BCCM is evident for CH4 emissions using IPCC 2013 values instead of IPCC 2006 values. As one of the thought-provoking differences between results in IPCC and BCCM methods, the different nature of the line shapes should be stressed out. Since CH4 decay has an evident non-linear nature, the most significant difference in the results is created in the near-term estimates of the CH4 impacts. Similar findings are given in the work by Allen et al. [5], where the most significant misrepresentation of the impacts using GWP is evident in the case of methane and aerosol emissions. In Figure 10, this difference is given between the straight lines of IPCC 2006 and IPCC 2018 results and the non-linear line of BCCM results. Where an almost twofold difference is created in the short-term analysis, this difference cannot also be compensated with overestimated N2O impacts, because N2O results by BCCM follow a linear nature until 2030 relatively tightly.

**Figure 9.** The emission flow rate on the current year basis and the cumulative effect of this flow in the atmosphere for continued emission flow and the elimination of the emission flow: an example of CH4 emissions from enteric fermentation in Latvia, 2005–2100.

**Figure 10.** The comparison of the cumulative GHG emissions calculated using the GWP values from IPCC 2006 and IPCC 2013 and the decay function using the Bern Carbon Cycle Model (BCCM).

These differences in the total cumulative amounts of GHG emissions are due to the use of constant GWP values in the IPCC methodology, while in decay function, the GWP value changes with time; see Figure 11 for GWP values for N2O emissions and Figure 12 for CH4 emissions.

**Figure 11.** Absolute GWP values for N2O emissions given using the BCCM "GWP for N2O" and average GWP values for the first 20 years after pulse emission of N2O named "av.GWP20 for N2O" and has the value of 288.05; for the first 100 years—"av.GWP100 for N2O"; for the first 500 and 1000 years—"av.GWP500 for N2O" and "av.GWP1000 for N2O". GWP value for the first 100 years given in the IPCC 2013, including the carbon cycle feedback, has the value of 298 and is given as "GWP100 for N2O IPCC 2013\*", unitless.

The high sensitivity of the GWP values for the chosen time frame for CH4 and N2O is due to the non-linear nature and different mathematical functions used for approximation of these decay functions. The difference in the average values of GWP for different time horizons can be substantial, and the obtained conclusions can be misleading. When using these averages, a situation is also possible when a longer time horizon diminishes the importance of local and relatively short lifetime emissions, such as CH4. For example, the described situation is evident that in the case of N2O emissions, the time frame of 20 or 100 years does not change the applied GWP values so significantly as they change in the case when CH4 is assessed either in 20 or 100 years (see Figure 12).

Also, the perturbation time of CH4 emissions is approximately ten times less than the perturbation time of N2O emissions. Thus, the use of single metrics for such different behaviour is rather challenging. The difference in the emissions' trendlines, given in Figure 10, between the GWP values from IPCC and the values from BCCM is visually explained in Figures 11 and 12, where GWP100 values used in IPCC2013 for N2O and CH4 emissions graphically are located between different segments. In Figure 11, for N2O emissions, the value of GWP100 from IPCC2013 is 298, including carbon cycle feedbacks. This value of 298 is higher than the mathematical average of GWP20 and GWP100 values for N2O. While for CH4 emissions given in Figure 12, the value of GWP100 from IPCC2013 is 34, including carbon cycle feedbacks. This value of 34 is in between the mathematical average of GWP20 and GWP100 values for CH4. Thus, these selected GWP100 values from IPCC describe different segments of the emission decay period for N2O and CH4 and, therefore, create differences in the obtained results.

Also, longer time horizons, in general, give lower GWP values. Thus, it is always better to select a longer time horizon to have a smaller impact, but does it provide a reasonable picture of these impacts? It can be further discussed, how can the assessment of the impact at the governmen<sup>t</sup> or enterprise-level

reasonably give an interpretation for the values of the possible impacts in 100 or 500 years? And how realistic is it that the cost of these created impacts in 100 or even in the next 20 years will be adequately attributed to the producer or consumer of today? In Figure 10, the total cumulative GHG emissions calculated using GWP values suggested by the IPCC and decay functions are compared until 2030. Usually, the comparison is used to show the created impact. In fact, the effect of the emissions occurring in the last year (2030) and a couple of years before 2030 are not included in the calculations when using the decay function. For the more realistic impacts, see Figure 13a.

**Figure 12.** Absolute GWP values for CH4 emissions given using the BCCM named "GWP for CH4" and average GWP values for the first 20 years after pulse emission of CH4 named "av.GWP20 for CH4" and has the value of 71.16, for the first 100 years—"av.GWP100 for CH4"; for first 500 and 1000 years—"av.GWP500 for CH4" and "av.GWP1000 for CH4". GWP value for the first 100 years given in the IPCC 2013, including carbon cycle feedback, has the value of 34 and is given as "GWP100 for CH4 IPCC 2013\*", unitless.

**Figure 13.** *Cont*.

**Figure 13.** The comparison of the total cumulative GHG emissions calculated using IPCC methodology and decay function before and after year 2030, Latvia (**a**) reference case or business as usual based on Dace et al. [2] (**b**) constant emission after 2020, (**c**) declining emissions by 2% after 2020, (**d**) declining emissions by 10% after 2020.

Assuming that after the year 2030, no more emissions are occurring, Figure 13a shows how the amounts of the emissions released to the atmosphere until 2030 slowly decay. The figure shows that the fraction remaining in the air of various GHG emissions varies by nature. For CH4, the decay is much faster, while N2O has not even halved since its release. Similar findings of the lack of appropriate comparison between short-lived GHGs (in this case, CH4) and long-lived GHGs (N2O) are discussed in work by Boucher et al. [30]. The authors explain that difficulty in using GWP for short-lived GHGs is because the GWP value does not consider that the radiative forcing of these short-lived GHGs has time to relax and reach equilibrium in the analyzed time horizon. Thus, Boucher et al. [30] have introduced the GTP concept that generalizes climate impacts and considers different climate responses for both short and long-lived GHG emissions.

The faster decay of CH4 is usually used as the argumen<sup>t</sup> to reduce the importance of this emission, especially in the agriculture sector, where CH4 emissions have a significant share in the total impact categories; see Figure 14a,b.

**Figure 14.** (**a**) Absolute global temperature change potential (AGTP) and (**b**) global temperature change potential (GTP) calculated for the emissions from agriculture in Latvia.

If the impact on the GTP from CH4 is assessed, it can be seen that CH4 shows a more obvious temperature change e ffect in a shorter run and, in total, contributes to more than half of the temperature change e ffect created by the agriculture in Latvia, as given in Figure 14.

In this case, various di fferent scenarios of the agriculture emission are modelled, such as constant emissions or decreasing emissions; see Figure 15. As can be seen, Figure 13a–c depict related trends very precisely. For example, the total emissions from agriculture in Latvia in the year 2030 between scenarios given in Figure 15a, business as usual or 2% growth of emissions and Figure 15b, constant emissions after the year 2020 calculated based on BCCM will di ffer by 4% only. This example shows how hard it is to reach the emission reductions due to accumulation and long perturbation time of these emissions in the atmosphere. In work by Olivié and Peters [27], the common characteristics and di fferences between GWP and GTP are discussed. Both methods are designed to be simple tools for comparing impacts to climate from several types of GHG emissions. Both methods refer to the pulse emission of some specific GHG in comparison to the pulse emission of the same quantity of reference CO2 emissions, while the di fference is in the used mathematical model—where GWP is based on comparing the changes in radiative forcing overtime, and GTP on global mean temperature changes over time [4].

**Figure 15.** *Cont*.

**Figure 15.** Modelled scenarios for the emissions from agriculture in Latvia, (**a**) reference case or business as usual based on Dace et al. [2], (**b**) constant emission after 2020, (**c**) declining emissions by 2% after 2020, and (**d**) declining emissions by 10% after 2020.

The most significant difference between GWP and GTP is that GTP is an end-point metrics, while GWP is a cumulative measure of climate change. Thus, the value of radiative forcing is of grea<sup>t</sup> importance in the analysis of GTP, and more weight is given to climate effects of radiative forcing that come later in the perturbation time of the analyzed pollutants. Thus, for the emissions with a shorter perturbation time, there will be a more significant difference between the results of GWP and GTP results. This theory implies that the GWP assessment gives an overestimation of the short-lived pollutants for the mitigation of climate change. In work by Boucher and Reddy [30], the difference between black carbon emissions for 100 years perspective in the case of using GTP gave seven times smaller impact than the corresponding GWP assessment. These findings are also in agreemen<sup>t</sup> with the work of Shine et al. [4]. Also, the choice of the time horizon to evaluate the impacts of the emissions is of significant importance. By far, the most common practice is to use a 100-year time horizon, since it is used in the Kyoto Protocol [27], but there is no scientific justification in using this particular time horizon. The larger the time horizon is chosen, the fewer effects can be attributed to short-lived pollutants [30]. On the other hand, sustainability cannot be achieved if only long-lived pollutants are accounted and restricted, while short-lived continue to degrade local ecosystems. Therefore, here, both short-term and long-term impacts on sustainability should be assessed and balanced.

Moreover, the choice of the time horizon of 20 years or 100 years or some other time horizon is still not scientifically justified by any concrete evidence [30]. Thus, the obtained results are also sensitive to the assumed time horizon and can lead to contradicting conclusions.

Our findings are also in agreemen<sup>t</sup> with work published by Shimako [7] and Shimako et al. [8]. The authors of the research studied the same total amount of emissions but taken with two di fferent emission timing profiles. One emission profile was constant through the simulation, another emission profile peaked in the beginning and then was zero for 4/5 of the simulation. Due to this di fference in the emission profiles, the temporal e ffects of these two emission profiles also di ffer. In contrast, the total amount of emissions at the end of the simulation was the same for both profiles. In case GWP would be multiplied by the total amount of emissions, the obtained results would be the same for both profiles. This phenomenon is also evident in our findings—the cumulative emissions have di fferent impact profiles when the same amount of total emissions is considered using temporal impacts.

Since the short-lived GHG emissions a ffect local environments in more apparent patterns, such as e ffects on air quality, human health, and local ecosystems, in work by Rypdal et al. [33], it was proposed to regulate short-lived emission in regional policy contexts. The influence of the emissions on local metrics is reviewed in detail in work by Rypdal et al. [34] and by Levasseur et al. [6].

Work by Olivié and Peters [27] also explains that in coupled systems, the temperature changes will also a ffect the ocean in two ways. Firstly, the absorption of CO2 directly by the ocean will increase if the temperature will rise. Secondly, ocean circulation patterns will be changing, due to direct e ffects from increased respiration and photosynthesis or indirectly by changes in precipitation. Also, the authors discuss how various changes in these coupled systems might influence the numerical values used in IRF. Nevertheless, we would like to stress that, in this work, the precise numerical values were not of such high importance as the depiction of overall dynamics and di fferent results that can be obtained using two di fferent methodological approaches.

Also, work by Jardine et al. [35] shows that various feedbacks exist when CH4 emissions are analyzed. For example, the global atmospheric lifetime of CH4 is defined by the amount of atmospheric concentration of CH4 (CH4 burden) divided by the amount of annual removal of CH4 from the atmosphere (CH4 sink). Thus, increasing the concentration of CH4 in the atmosphere will lead to longer global atmospheric lifetimes. In work by Holmes [36], the strength of chemical feedback for CH4 was analyzed using meteorological, chemical, and emissions factors. The research shows that this feedback depends weakly (likely in the 10% range) on temperature, insolation, water vapour, and emissions of NO. While perturbation time of CH4 might rise as high as 40% and more, this means that close accounting of the balance in CH4 is needed in order to have valid assumptions about the time when "constant" values cannot be treated as constants anymore.

To sum up, we believe that both types of emission accounting (the constant GWP values for a 100-year time horizon (GWP100) and the time dynamic GWP values for a 100-year time horizon obtained by using the BCCM) are valuable to use; each has its strength and weaknesses. Thus, we propose to also look on the temporal impacts of emissions, since it might help in designing more precisely targeted policy measures appropriate for the chosen mitigation priorities.

As given in the report by Jardine et al. [35], CH4 emissions decay about ten times faster than N2O, but from the other point of view, policy measures targeting CH4 reduction will also show the e ffect on the reduction of climate change ten times faster than measures targeting N2O. Also, the report by the United Nations Environment Programme and the World Meteorological Organization [37] shows that the adoption of policies targeting short-lived GHGs would allow reaching climate change mitigation targets with higher confidence. The report also shows that CO2 reduction measures alone would exceed the set temperature thresholds anyway already in the near term. In contrast, only CH4 reduction measures would keep the temperature below the threshold in the near term while exceeding the limit later because of the e ffect of other GHGs. As the opposing argumen<sup>t</sup> for stricter control of long-term pollutants is the fact that any technological solution and policy measure will be implemented only for the finite time. Usually, the selected time horizon is much shorter than the consequences of the pollution associated with these technologies.
