A description of four science-based corporate GHG target-setting methods

While large companies routinely announce greenhouse gas emissions targets, few have derived targets based on global climate goals. This changed in 2015 with the creation of the science based targets (SBTs) initiative, which provides guidelines for setting emission targets in line with the temperature goal of the Paris Agreement. SBTs have now been set by more than 500 companies. Methods for setting such targets are not presented in a comparable way in target-setting guidelines and concerns that certain methods may lead to overshoot of the temperature goal have not been investigated. Here, we systematically characterize and compare all seven broadly applicable target-setting methods and quantify the balance between collective corporate SBTs and global allowable emissions for individual methods and different method mixes. We use a simplified global production scenario composed of eight archetypical companies to evaluate target-setting methods across a range of company characteristics and global emission scenarios. The methods vary greatly with respect to emission allocation principles, required company variables and embedded global emission scenarios. Some methods treat companies largely the same, while others differentiate between company types based on geography, economic sector, projected growth rate or baseline emission intensity. The application of individual target-setting methods as well as different mixes of methods tend to result in an imbalance between time-integrated aggregated SBTs and global allowable emissions. The sign and size of this imbalance is in some cases sensitive to the shape of the global emission pathway and the distribution of variables between the company archetypes. We recommend that the SBT initiative (a) use our SBT method characterisation to present methods in a systematic way, (b) consider our emission imbalance analysis in its method recommendations, (c) disclose underlying reasons for its method recommendations, and (d) require transparency from companies on the calculation of established SBTs.

Companies are increasingly setting greenhouse gas (GHG) emission reduction targets to align with the 1.5 °C goal of the Paris Agreement. Currently, companies set these science-based targets (SBTs) for aggregate GHGs expressed in CO2-equivalent emissions. This approach does not specify which gases will be reduced and risk misalignment with ambitious mitigation scenarios in which individual gas emissions are mitigated at different rates. We propose that companies instead set reduction targets for separate baskets of GHGs, defined according to the atmospheric lifetimes and global mitigation potentials of GHGs. We use a sector-level analysis to approximate the average impact of this proposal on company SBTs. We apply a multiregional environmentally extended input output model and a range of 1.5 °C emissions scenarios to compare 1-, 2- and 3-basket approaches for calculating sector-level SBTs for direct (scope 1) and indirect (scope 2 and upstream scope 3) emissions for all major global sectors. The multi-basket approaches lead to higher reduction requirements for scope 1 and 2 emissions than the current single-basket approach for most sectors, because these emission sources are usually dominated by CO2, which is typically mitigated faster than other gases in 1.5 °C scenarios. Exceptions are scope 1 emissions for fossil and biological raw material production and waste management, which are dominated by other GHGs (mainly CH4 and N2O). On the other hand, upstream scope 3 reduction targets at the sector level often become less ambitious with a multi-basket approach, owing mainly to substantial shares of CH4 and, in some cases, non-CO2 long-lived emissions. Our results indicate that a shift to a multi-basket approach would improve the alignment of SBTs with the Paris temperature goal and would require most of the current set of companies with approved SBTs to increase the ambition of their scope 1 and scope 2 targets. More research on the implications of a multi-basket approach on company-level SBTs for all scope 3 activities (downstream, as well as upstream) is needed.

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

Energy-related activities are a major contributor of greenhouse gas (GHG) emissions. A growing body of knowledge clearly depicts the links between human activities and climate change. Over the last century the burning of fossil fuels such as coal and oil and other human activities has released carbon dioxide (CO2) emissions and other heat-trapping GHG emissions into the atmosphere and thus increased the concentration of atmospheric CO2 emissions. The main human activities that emit CO2 emissions are (1) the combustion of fossil fuels to generate electricity, accounting for about 37% of total U.S. CO2 emissions and 31% of total U.S. GHG emissions in 2013, (2) the combustion of fossil fuels such as gasoline and diesel to transport people and goods, accounting for about 31% of total U.S. CO2 emissions and 26% of total U.S. GHG emissions in 2013, and (3) industrial processes such as the production and consumption of minerals and chemicals, accounting for about 15% of total U.S. CO2 emissions and 12% of total ...

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

Globally, agriculture is directly responsible for 14% of annual greenhouse gas(GHG) emissions and induces an additional 17% through land use change, mostlyin developing countries (Vermeulen et al 2012). Agricultural intensification andexpansion in these regions is expected to catalyze the most significant relativeincreases in agricultural GHG emissions over the next decade (Smith et al 2008,Tilman et al 2011). Farms in the developing countries of sub-Saharan Africa andAsia are predominately managed by smallholders, with 80% of land holdingssmaller than ten hectares (FAO 2012). One can therefore posit that smallholderfarming significantly impacts the GHG balance of these regions today and willcontinue to do so in the near future.However, our understanding of the effect smallholder farming has on theEarth’s climate system is remarkably limited. Data quantifying existing andreduced GHG emissions and removals of smallholder production systems areavailable for only a handful of crops, livestock, and agroecosystems (Herrero et al2008, Verchot et al 2008, Palm et al 2010). For example, fewer than fifteenstudies of nitrous oxide emissions from soils have taken place in sub-SaharanAfrica, leaving the rate of emissions virtually undocumented. Due to a scarcity ofdata on GHG sources and sinks, most developing countries currently quantifyagricultural emissions and reductions using IPCC Tier 1 emissions factors.However, current Tier 1 emissions factors are either calibrated to data primarilyderived from developed countries, where agricultural production conditions aredissimilar to that in which the majority of smallholders operate, or from data thatare sparse or of mixed quality in developing countries (IPCC 2006). For the mostpart, there are insufficient emissions data characterizing smallholder agricultureto evaluate the level of accuracy or inaccuracy of current emissions estimates.Consequentially, there is no reliable information on the agricultural GHG budgetsfor developing economies. This dearth of information constrains the capacity totransition to low-carbon agricultural development, opportunities for smallholdersto capitalize on carbon markets, and the negotiating position of developingcountries in global climate policy discourse.Concerns over the poor state of information, in terms of data availability andrepresentation, have fueled appeals for new approaches to quantifying GHGemissions and removals from smallholder agriculture, for both existing conditionsand mitigation interventions (Berry and Ryan 2013, Olander et al 2013).Considering the dependence of quantification approaches on data and the currentdata deficit for smallholder systems, it is clear that in situ measurements must bea core part of initial and future strategies to improve GHG inventories and

Taking Stock of Strategies on Climate Change and the Way Forward: A Strategic Climate Change Framework for Australia

This paper investigates the effects that science-based targets (SBTs) have on corporate greenhouse gas (GHG) emissions. Using a difference-in-differences methodology, we assess whether companies that commit to a net zero goal show a decrease in GHG emissions compared to similar companies that declare such goals later. Our results provide limited evidence that organizations with SBT reduce emissions, particularly for Scope 1 and Scope 2 emissions, as the findings lack strong statistical significance. We also examine whether the pace of emission reductions increases as companies approach their target year. Our results indicate that efforts to reduce emissions increase before the announcement, but may stabilize thereafter. These results highlight the challenges of accurately assessing the tangible impact of voluntary corporate commitments on climate goals and underscore the need for comprehensive and clear reporting to prevent misleading claims and promote confidence in climate finance.

BackgroundPolicies to mitigate climate change by reducing greenhouse gas (GHG) emissions can yield public health benefits by also reducing emissions of hazardous co-pollutants, such as air toxics and particulate matter. Socioeconomically disadvantaged communities are typically disproportionately exposed to air pollutants, and therefore climate policy could also potentially reduce these environmental inequities. We sought to explore potential social disparities in GHG and co-pollutant emissions under an existing carbon trading program—the dominant approach to GHG regulation in the US and globally.Methods and findingsWe examined the relationship between multiple measures of neighborhood disadvantage and the location of GHG and co-pollutant emissions from facilities regulated under California’s cap-and-trade program—the world’s fourth largest operational carbon trading program. We examined temporal patterns in annual average emissions of GHGs, particulate matter (PM2.5), nitrogen oxides, sulfur oxides, volatile organic compounds, and air toxics before (January 1, 2011–December 31, 2012) and after (January 1, 2013–December 31, 2015) the initiation of carbon trading. We found that facilities regulated under California’s cap-and-trade program are disproportionately located in economically disadvantaged neighborhoods with higher proportions of residents of color, and that the quantities of co-pollutant emissions from these facilities were correlated with GHG emissions through time. Moreover, the majority (52%) of regulated facilities reported higher annual average local (in-state) GHG emissions since the initiation of trading. Neighborhoods that experienced increases in annual average GHG and co-pollutant emissions from regulated facilities nearby after trading began had higher proportions of people of color and poor, less educated, and linguistically isolated residents, compared to neighborhoods that experienced decreases in GHGs. These study results reflect preliminary emissions and social equity patterns of the first 3 years of California’s cap-and-trade program for which data are available. Due to data limitations, this analysis did not assess the emissions and equity implications of GHG reductions from transportation-related emission sources. Future emission patterns may shift, due to changes in industrial production decisions and policy initiatives that further incentivize local GHG and co-pollutant reductions in disadvantaged communities.ConclusionsTo our knowledge, this is the first study to examine social disparities in GHG and co-pollutant emissions under an existing carbon trading program. Our results indicate that, thus far, California’s cap-and-trade program has not yielded improvements in environmental equity with respect to health-damaging co-pollutant emissions. This could change, however, as the cap on GHG emissions is gradually lowered in the future. The incorporation of additional policy and regulatory elements that incentivize more local emission reductions in disadvantaged communities could enhance the local air quality and environmental equity benefits of California’s climate change mitigation efforts.

A framework for future-oriented environmental impact assessment of companies considering Science-Based Targets

BackgroundSocietal pressures exist to reduce greenhouse gas (GHG) emissions from farm animals, especially in beef cattle. Both total GHG and GHG emissions per unit of product decrease as productivity increases. Limitations of previous studies on GHG emissions are that they generally describe feed intake inadequately, assess the consequences of selection on particular traits only, or examine consequences for only part of the production chain. Here, we examine GHG emissions for the whole production chain, with the estimated cost of carbon included as an extra cost on traits in the breeding objective of the production system.MethodsWe examined an example beef production system where economic merit was measured from weaning to slaughter. The estimated cost of the carbon dioxide equivalent (CO2-e) associated with feed intake change is included in the economic values calculated for the breeding objective traits and comes in addition to the cost of the feed associated with trait change. GHG emission effects on the production system are accumulated over the breeding objective traits, and the reduction in GHG emissions is evaluated, for different carbon prices, both for the individual animal and the production system.ResultsMultiple-trait selection in beef cattle can reduce total GHG and GHG emissions per unit of product while increasing economic performance if the cost of feed in the breeding objective is high. When carbon price was $10, $20, $30 and $40/ton CO2-e, selection decreased total GHG emissions by 1.1, 1.6, 2.1 and 2.6% per generation, respectively. When the cost of feed for the breeding objective was low, selection reduced total GHG emissions only if carbon price was high (~ $80/ton CO2-e). Ignoring the costs of GHG emissions when feed cost was low substantially increased emissions (e.g. 4.4% per generation or ~ 8.8% in 10 years).ConclusionsThe ability to reduce GHG emissions in beef cattle depends on the cost of feed in the breeding objective of the production system. Multiple-trait selection will reduce emissions, while improving economic performance, if the cost of feed in the breeding objective is high. If it is low, greater growth will be favoured, leading to an increase in GHG emissions that may be undesirable.

Science-based targets (SBTs) are receiving increased attention in the corporate business world. They support the achievement of an overall Net Zero ambition, in line with the latest climate science and a 1.5°C future. Setting such targets offers a clearly defined pathway for businesses to reduce their carbon emissions, which can add credibility to their overall strategy and objectives. This chapter introduces the concept of SBTs and outlines their benefits. It then provides an overview of how these might be developed by following certain steps using the process outlined by the Science-Based Targets initiative (SBTi). It also highlights why this could be the right approach for carbon reduction target setting in any organisation. The apparel and footwear sector is selected as an example to outline the process and to explore sector-specific guidance. The streamlined route for setting SBTs in small and medium-sized enterprises (SMEs) is also discussed. Good practice in science-based target setting from an SME already involved in this approach will be shared through a case study as inspiration for others, and Further Resources are suggested to assist organisations.

Kupang city is growth rapidly and located in a strategic position between Australia and Timor Leste. A sharp increase of GHG emission along with environmental pollution, contamination of water, air and improper waste disposal practices as its consequence to the global environment. The city's government ambition to evaluate impact of economic activity on greenhouse gases (GHG) emission contribution. This paper outlined pollutant sectors that contribute substantially to GHG emission in Kupang along with its structure, and count an estimated amount of emission coefficients for 27 economy sectors. More in-depth explanation about indirect coefficient pollutant emission which beneficial not only for calculation of the emission amount but more as inventory data for LCA. The paper is investigated review the trends of some priority sectors, then introduction of indirect coefficients of pollutant sectors, and showed the Pollutant Emission Structure for Kupang. After that, an estimated amount of Kupang GHG emission under BAU is also counted and confirmed. The paper only considers GHG emission issues while air pollutant emission only be provided as inventory data but will not be used as exogenous data for this paper. In the final part a brief explanation and implications of GHG emission policy in Kupang are identified. A detailed of input-output data for individual process are provided includes all groups of processes or industry sectors relevant to economy activities in Kupang City. A time period for Global Warming Potential (GWP) 20 year and 100 years are used to forecasted amounts share of total GHG emission in Kupang and Indonesia by 2020 compared to 2010. As results first, the GHG emission and air pollutant coefficients for 27 sectors in Kupang based on method is presented in NIES which use to count the GHG emission. These also become an Inventory data for researchers of regional science in Indonesia, however, geography and socioeconomic conditions in every region is different, so that some criteria will be applied. Second, found total GHG emission in Kupang is $1.0164\mathrm{x} 10^{-3}$ Gt or around 0.047% compared to total GHG emission by 2010 and 0.034% compared to total GHG emission by 2020 in Indonesia. The study suggests to government consider a proper method in decide a reliable environmental policy and technical measures to reach GHG emission targets by 2020. Third, total share of CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> e in Indonesia emitted from Kupang for GWP 20 years and 100 years respectively were came out as follow.

BackgroundThe typical Western diet is associated with high levels of greenhouse gas (GHG) emissions and with obesity and other diet-related diseases. This study aims to determine the impact of adjustments to the current diet at specific moments of food consumption, to lower GHG emissions and improve diet quality.MethodsFood consumption in the Netherlands was assessed by two non-consecutive 24-h recalls for adults aged 19–69 years (n = 2102). GHG emission of food consumption was evaluated with the use of life cycle assessments. The population was stratified by gender and according to tertiles of dietary GHG emission. Scenarios were developed to lower GHG emissions of people in the highest tertile of dietary GHG emission; 1) reducing red and processed meat consumed during dinner by 50% and 75%, 2) replacing 50% and 100% of alcoholic and soft drinks (including fruit and vegetable juice and mineral water) by tap water, 3) replacing cheese consumed in between meals by plant-based alternatives and 4) two combinations of these scenarios. Effects on GHG emission as well as nutrient content of the diet were assessed.ResultsThe mean habitual daily dietary GHG emission in the highest tertile of dietary GHG emission was 6.7 kg CO2-equivalents for men and 5.1 kg CO2-equivalents for women. The scenarios with reduced meat consumption and/or replacement of all alcoholic and soft drinks were most successful in reducing dietary GHG emissions (ranging from − 15% to − 34%) and also reduced saturated fatty acid intake and/or sugar intake. Both types of scenarios lead to reduced energy and iron intakes. Protein intake remained adequate.ConclusionsReducing the consumption of red and processed meat during dinner and of soft and alcoholic drinks throughout the day leads to significantly lower dietary GHG emissions of people in the Netherlands in the highest tertile of dietary GHG emissions, while also having health benefits. For subgroups of the population not meeting energy or iron requirements as a result of these dietary changes, low GHG emission and nutritious replacement foods might be needed in order to meet energy and iron requirements.

Livestock production is under growing public and scientific scrutiny for its greenhouse gas (GHG) emissions. This article contains a preliminary assessment of the inclusion of upstream life-cycle GHG emissions in concentrated feeds design, using the most common nonlinear programming optimization algorithms to determine feed composition. First, GHG emissions are included as costs in a single criteria optimization problem. The unit price of GHG emissions was obtained using a genetic algorithm. Second, GHG emissions are included as a target function to minimize in a multi criteria optimization problem using goal attainment programming. Results obtained after both optimization methods were applied to two case studies, namely fattening pigs and rabbit feeds. Changing ingredients in concentrated feed blends has a marginal effect on GHG emissions due to mandatory nutritional constraints. If the optimization is unconstrained, the maximum possible decrease in GHG emissions is 27.5% for the pigs feed, accompanied by increasing costs and a decrease in feed nutritional quality. To maintain nutritional integrity, the maximum possible reduction in GHG emissions is 7.5%. Considering cost as an optimization variable in the problem, the maximum decreases are even lower. It is possible to decrease emissions by 71% for the rabbits feed, but the cost of the reduction is higher than the opportunity cost for farmers to reduce GHG emissions using other strategies. These results are qualitatively robust but critically depend on feed ingredients GHG emissions and cost data.