Market Forces

Barriers to tapping the potential of carbon markets for agriculture

An EDF analysis of carbon credits for rice growers shows great climate and cost-savings potential, but is that enough for farmers to participate?

In 2015, rice became the first crop for which agricultural carbon credits were valid for compliance in the California cap-and-trade system. Unfortunately, as of September 2020, no compliance credits have been generated. A newly released report by EDF explores the reasons why.

In the U.S., agricultural greenhouse gas emissions comprise approximately 10% of the economy-wide total emissions. The share of emissions from agriculture is larger for non-CO2 GHGs, making up approximately 78% of the U.S. total for nitrous oxide and 38% for methane.

Policymakers are eager to find mitigation opportunities in the agriculture sector, best evidenced by the bipartisan Growing Climate Solutions Act, which seeks to enable voluntary credit markets for producers to mitigate climate change.

As both policymakers and producers eye the potential of the agriculture sector to grow climate solutions, it’s worth taking a closer look at both the opportunities and the challenges that must first be addressed to tap this potential.

A case study of carbon credits for rice

EDF’s work on agricultural carbon credits began in earnest in 2007 after receiving the first of several U.S. Department of Agriculture grants to investigate how to bring agricultural emissions reduction credits to market. The objective was to design crediting systems that achieve the dual benefits of reducing GHG emissions while also providing meaningful revenue opportunities to landowners.

An EDF discussion paper summarizes some of the underlying analytics of these efforts for a series of crops and geographies. One specific example from the paper — rice in California — highlights both the carbon- and cost-saving opportunities associated with conservation practices like bailing and drainage, and the challenges associated with agricultural credits as a viable abatement measure.

The opportunity: Lowering costs and emissions

Rice is a GHG-intensive crop. It emits twice the amount of emissions per calorie as wheat, three times that of maize, and accounts for 5-20% of global methane emissions. EDF’s research focused on the nation’s two most intensive rice production regions — California’s Sacramento Valley and Mid-Southern U.S. These regions produce 26% and 72% of the domestic rice supply, respectively.

Our analysis began by using a biogeochemical model, DeNitrification-DeComposition (DNDC), to assess the abatement potential for current (baseline) practices and other lower-GHG alternatives in the California rice region. This led our scientists to discover a fairly large overall mitigation potential of more than 0.6 MMt-CO2e-100/year, or approximately 15%, of overall California rice emissions.

We then developed estimates of abatement costs by practice through cost budgets and consultation with agronomists. Combining this with the GHG modeling yielded the following marginal abatement cost curves (one for each practice).

Marginal Abatement Cost Curves for Rice Practices in California. Abbreviations: N (number of fields); WF (winter flooding of rice paddies); NWF (no winter flooding). WF/NWF practices follow a 60/40% distribution, historically, and play a role in determining the scale of achievable reductions.

These graphs illustrate that for all but one practice there are negative abatement costs with averages ranging from -$29.45/acre to -$0.45/acre, suggesting potential savings for farmers from implementing practice changes. For yields, the DNDC model projected that yields would remain relatively unchanged, aside from dry seeding, for which growers would experience an average 4.5% decrease.

These findings show great promise in terms of GHG abatement potential and cost savings for producers with minimal yield impacts (dry seeding aside). So, why aren’t growers already pursuing these practices? What barriers are getting in the way?

Three key barriers to entry

Our analysis identified a few potential barriers for farmers to generate carbon credits.

  1. Weak price signals

Understanding why growers are passing up potential cost savings from practices that reduce GHG emissions requires a closer look at farm economics. Adam Jaffe offers a useful typology for the various barriers to adoption, some of which I have identified below.

Putting the practice costs and yield impacts together, we can imagine a scenario where we have a carbon market in place and a carbon price of $10/ton (the California spot price at the time this work was carried out). In this instance, we’d find that with an average 0.7 ton/acre reduction, most rice growers would be looking at potential revenue from the market of approximately 0.5% of their overall crop sales revenue (typically $1,500/acre), or 2.6% of their net profit (approximately $250/acre), not including further potential gains from the negative abatement costs of certain practices and locations.

Unfortunately, in context of the overarching farm economics, this makes for a weak incentive.

If we now imagine a new scenario with a carbon price closer to today’s social cost of carbon ($42/ton), we find that the potential revenue from participating in the market rises closer to 2% of crop sales revenue and 11% of net profit. At this price, the incentive appears to be substantially more robust, which tells us that, from a social standpoint and with a strong price signal, the market could be viable. But as it currently stands, conditions are falling short of this potential.

  1. Large transaction costs

Another critical consideration for engaging in any market is transaction costs — for GHG markets in particular, monitoring, reporting and verification (MRV) costs.

Our analysis found transaction costs to be significant on a per-grower basis at approximately $14/acre for an average 1,000-acre California farm. At a market price of $10/ton, transaction costs are double the average expected return from carbon markets of $7/acre, providing a steep disincentive. Even with credits priced at the higher social cost of carbon ($42/ton), transaction costs would still equal nearly 50% of potential revenue, essentially cutting their expected financial gains in half.

Further economic modeling showed the importance of allowing a way to aggregate projects for MRV transations due to the very large third-party fees incurred to verify reductions. However, even if growers use aggregation as a means to cost-share, it will be critical to find ways to use technologies like remote sensing and automated data generation and analysis to streamline this process, realize savings and still guarantee accurate verification.

  1. Changing behavior is an obstacle in itself

Finally, behavioral factors represent a hurdle that cannot be ignored — the hidden additional cost of switching practices. This cost is difficult to quantify precisely, but we know from experience that behavior is hard to shift and farming practice changes typically require planning and close coordination with a number of consultants and business partners.

Understanding this, we performed a survey for corn and almond growers, asking how much participants in a carbon market would need to be paid to reduce fertilizer applications, and thereby decrease nitrous oxide emissions. To isolate the behavioral barriers, we designed the survey to encourage the farmers to assume no additional costs, risks or yield impacts.

Their responses ranged from $18-40/acre, when a representative farmer might only receive $7/acre in returns with a $10/t carbon price. This gap in the valuation likely represents factors such as personal or cultural values and aversion to risk and uncertainty that may be very difficult to overcome using market incentives alone[1].

Managing risk and risk perceptions is a challenge that must be addressed to see widespread uptake of mitigation practices.

Where do we go from here?

The agricultural sector has the potential to play a key role in contributing to national climate goals.

Crediting systems are just one tool to support this, but more research and pilot programs are needed to help overcome the barriers to entry, increase confidence in high-quality and cost-effective credits, and also evaluate and correct for potential inequities and injustices.

EDF is launching a new phase of research dedicated to this work, in addition to developing complementary finance and policy tools that correct for existing disincentives and inequities to create a more just and resilient food system.

With the right combination of tools in the toolbox, we can unleash the power of carbon markets to boost long-term resilience on the farm and beyond.

 

[1] It is important to note that all of the numbers depicted above represent averages, and there are certainly cases for which incentives are large at the individual level, and some growers may have zero or even negative switching costs, so many farmers have ripe potential for carbon market participation.

 

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Costs of climate change are rising: New research shows how local communities could be strained in the near-term

This blog post was co-authored with Nina Donaldson

Much of the existing research on climate change impacts focuses on end-of-century projections across nations, but this misses the very real costs that everyday Americans are already facing daily and will continue to face in the months and years ahead. Case in point today: While most Americans believe that climate change currently affects the U.S., only about a third of the adult population believes that local effects of climate change directly impact their personal lives.

And perceiving that threat on an individual level is a key motivator for pushing meaningful action.

While the impacts of climate change can sometimes feel abstract, the reality is that communities across the country are bearing the burden of climate damages here and now through heat waves, severe thunderstorms, wildfires, and flooding – to name a few – even if they are not making a direct connection themselves between those events and climate change. A new research series by Environmental Defense Fund underscores specifically where and how the potential costs could impact individual counties as soon as the next 20 years.

Behind the research

The Costs of Inaction research series draws on data from multiple sources, including a first-of-its kind study by Hsiang et al. 2017, developed through the Climate Impact Lab, which highlights climate costs and impacts from key sectors. Our research also draws from the Union of Concerned Scientists’ Underwater report and First Street Foundation’s Flood Factor data.

From these studies, we extract locally relevant data for several U.S. states projected to experience severe impacts, such as in Florida and Arizona. We examine an array of climate change impacts, including loss of property tax revenue from flooding, increased heat-related deaths, higher electricity costs, and declining crop yields. These represent only some of the detrimental effects that many already experience today and that we can expect to see worsen over the next 20 years and beyond.

International challenge, local costs

For example, Floridians already pay 13% more than the national average for electricity, but without ambitious action on climate, they can expect to see increases of more than 5% annually, paying up to an additional $122 on their electricity bills every year over the next 20 years. This will be especially straining on low-income households, which already spend roughly 10% of their income on electricity costs – three times the proportion of what the average household typically spends on electricity costs.

Arizonians will also face similar annual increases in their electricity bills to keep their homes cool as more extreme heat days occur. Exposure to extreme heat can be deadly, causing heat stroke, dehydration, and other serious issues. With two of the fastest-warming cities in the nation, Arizonians face an increasing threat, particularly in urban areas where dark pavement, buildings, and other structures that absorb heat make temperatures even hotter. In Maricopa County, home to Phoenix, a 64% increase in heat-related deaths could occur every single year over the next 20 years. This puts our children, elderly, and sick at great risk as well as those who lack access to air conditioning.

Mapping the costs

As part of this research series, EDF also created new interactive maps of Florida and Arizona that highlight the near-term costs of climate inaction, which allow the user to explore additional costs at the county level for these two states. These costs include estimated heat-related mortality (additional deaths per 100,000 people), electricity expenditure increases (estimated using a version of the EIA’s National Energy Modeling System (NEMS) both for businesses and individual households), and losses in crop yields and property tax revenue. All estimates assume a high emissions scenario in which fossil fuel-intensive economic growth continues and no ambitious climate action is pursued. These interactive maps are designed to allow local policymakers, advocates, and stakeholders to explore the impacts in their county.

EDF also commissioned an in-depth report from RTI International, a Raleigh-based research institute, to use these data to show how climate change impacts will impose significant costs on North Carolina’s residents and its economy. The report showcases the projected costs that eight major sectors of the state’s economy may face within the next 20 to 30 years if measures to curb climate-warming pollution are not taken.

EDF’s research series makes clear that the costs of climate inaction are being felt in our lifetimes and will only grow exponentially worse over time. It’s crucial we enact ambitious climate policy to mitigate the most severe impacts. To explore how climate change will impact your local community, visit the Cost of Inaction Research series.

 

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Why the value of reducing health risks in China is rising

This post is a collaboration with Yana Jin

Since 2013, the Chinese government has changed its approach to regulating pollution, including providing the public greater access to information about their own exposure. This increased visibility into pollution exposure can affect citizens’ perceptions of how pollution affects their own health, and their desire to avoid these negative health outcomes. Understanding this shift in perception can tell us not only about what’s happening in China today, but also how developing countries may react to greater information about pollution.

Yana Jin, EDF’s new High-Meadows Economics Fellow, recently published a study in the Journal of Environmental Economics and Management, in which she and coauthors estimate Chinese citizens’ willingness to pay (WTP) to reduce mortality and morbidity risk associated with air pollution exposure. Specifically, the authors estimate a Value of a Statistical Life (VSL) and a Value of a Statistical Illness (VSI) of RMB 5.54 million ($1.58 million) and RMB 0.82 million ($0.23 million), which are higher than earlier estimates in China.

EDF’s Beia Spiller recently chatted with Yana about her paper and discussed the importance of the findings for policy making.

Beia: What does Value of a Statistical Life (or Value of a Statistical Illness) imply? Why do we need to put a value on human health?

Yana: The Value of a Statistical Life, VSL (or Value of a Statistical Illness, VSI) describes how much individuals are willing to pay to reduce the risk of premature death (or illnesses). Obviously, there is no market value for human health; VSL and VSI provide policymakers a common metric for valuing improvements in health outcomes.

Beia: How can VSL and VSI be used in policy making? What is the implication for environmental policy?

Yana: VSL and VSI provide a basis for conducting regulatory impact analyses and benefit cost analyses. For most environmental policies, the co-benefits of improved health outcomes dominate the total regulatory benefits (or the social cost of inactions). For example, in 2020 the total annual benefit of the Clean Air Act in the United States was estimated to be $2 trillion (in 2006 prices), more than 30 times the law’s total compliance costs; 90% of these benefits are due to reductions in mortality and morbidity attributable to ambient air pollution. This conclusion is based on an analysis using US-specific VSL and VSI estimates as part of the key parameters.

Extra attention is needed for VSI. Unlike premature mortality, which already receives lots of empirical attention, WTP for morbidity risk reductions is poorly understood in developing and developed countries. Solid VSI estimates can overcome the shortcomings of current alternative proxies in policymaking, such as the medical cost of illness and work day losses, which often undervalue the true social cost of non-fatal illnesses.

Beia: As you mention, estimates of the Value of a Statistical Life in the US (approx. $8-10 million) already exist. Why is it important from a policy perspective for this sort of analysis to be conducted for the Chinese population separately?

Yana: There is no one-size-fits-all VSL. Various factors influence VSL, including income and risk context of the affected population. Given that 92% of all pollution-related mortalities occur in developing countries, trying to draw conclusions for these populations from valuations in developed countries will involve substantial uncertainty.

Because the VSL is affected by both underlying air pollution levels and income, the VSLs will be different across China and the US. Furthermore, there are likely significant differences in the two populations’ understanding and awareness of the significance of air pollution’s impacts on health. For these reasons, we need studies based on the Chinese population and their specific setting to understand how they value risk reductions associated with improvements in air quality.

Beia: You find a much (almost 10x) smaller VSL in China than what has been estimated in the US. Does this mean that the Chinese morally value improvements in health less than populations in the US?

Yana: Not at all. Because the Chinese population currently has a much lower income than those in the US, their smaller household budgets constrain them from allocating the same amount of money to improvements in health. Though the difference in VSLs across countries seems huge right now, the VSL is highly elastic to per-capita income. This implies that as Chinese populations become richer, one can expect to see a sharp increase in Chinese VSL. Indeed, the VSL in the current study is already more than 10 times higher than early studies in the 1990s-2000s reported in China.

Beia: You test whether people have different willingness to pay to avoid specific illnesses (heart disease, stroke, or obstructive pulmonary disease) due to air pollution exposure, but find no significant differences across illness. Why is this an important policy question, and what would have been the implication for environmental policy had the opposite been true?

Yana: Whether the values across illnesses are different is of high policy relevance. For example, the risk of heart disease and stroke during extreme haze episodes is disproportionately higher than for other illnesses. If their associated VSI and VSL are also higher, this would imply that short-term policies that aim to curtail pollution spikes could be exceedingly beneficial, even though the transient effects do not reduce other more chronic, cumulative, long-term risks, which would only be affected by a steady decrease in annual average air pollution.

However, we find that the estimates are the same across illnesses. Therefore, policymakers can focus on the risk levels, and do not need to set illness-specific resource allocation priorities from the economic valuation perspective when managing air quality.

Beia: How could your VSL and VSI findings be used now?

Yana: Since 2013, the Chinese central government implemented its Air Pollution Prevention and Control Action Plan, investing 1.84 trillion RMB to improve air quality. This led to a significant drop in air pollution levels over the years in historically polluted Northern China, thereby generating marked health improvements. Our updated VSL and VSI can help to quantify and compare the observed health benefits with the costs of the policy that enabled these air quality improvements.

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Four reasons why China’s 2060 net-zero goal is so important

A shift in ambition, narrative, global cooperation and likely support for mitigation in least-developed countries

Shanghai Bund skyline landmark ,Ecological energy renewable solar panel plant

The announcement by President Xi Jinping at the UN General Assembly last month makes me optimistic.

First, on its own, achievement of this goal will contribute to a reduction in expected future temperature by 0.2 to 0.3 degrees

Second, having a clear and ambitious end goal will shift the narrative within China from incremental slowing of emissions growth and reductions in some sectors to a focus on how emissions can be eliminated entirely (or close to it).

A vision of transformation toward a low-emissions China will complement the vision of a “Beautiful China.” Pollution control efforts are highly complementary with climate mitigation actions – e.g. moving to renewable energy from fossil fuels, restoring ecosystems – and can dramatically improve the wellbeing of the Chinese people. A clear and attractive vision can mobilize a wider community to seek and implement the multitude of small and large changes needed. It will increase confidence in the future of China’s new national ETS, the strengthening of which will almost inevitably need to be part of China’s strategy. That confidence will make the ETS more effective by generating realistic prices and greater certainty for investors.

Third, it changes the climate cooperation ‘game’, significantly.

Economists think of climate cooperation as a game because each player’s (in this case country’s) decisions depends on what they think other players/countries will do – like chess, or rugby. China’s latest ‘move’ responds to others’ earlier moves and anticipates and will influence later ones. Global cooperation on climate change is hard, because of temptations to free-ride. We can use game theory to explore ways to improve humanity’s odds of a good outcome. We know that humans can sometimes cooperate when it’s a repeated ‘game’ – we get many chances to try to cooperate, observe others, reward or sanction and then try again.

And it’s not a binary outcome where we either win or lose.  Any level of cooperation is better than nothing. It might be optimal to aim for no more than 1.5 degrees above pre-industrial temperatures but even if we don’t achieve that, 2 degrees would be better than 2.5 degrees.

Cooperation is easier when some players take leadership, and that’s what China has done. They are not the first emerging economy to set a net-zero target (Bhutan, Chile, Costa Rica, Fiji, the Marshall Islands and South Africa are examples of others), but China’s size makes its announcement a game changer in several ways. The Chinese have shifted the focal point for emerging country contributions to a more ambitious level.

In addition, the rewards to other countries from helping to encourage and sustain China’s efforts rise – if they act in ways that lead China to draw back from this commitment there is more to lose. The costs of mitigation will fall as China learns and shares its new knowledge and technology. Finally, there is less risk that efforts to lower emissions in one country will lead to movement of high emitting-activity to China thereby having no global impact.

Fourth, it means that China, a really large player, will now need to engage even more seriously in helping less developed countries accelerate their mitigation.

Reaching net-zero will be much easier for the Chinese if they can buy high-quality internationally transferable mitigation outcomes (new United Nations Paris Agreement language for international credits). Their engagement in this market could firm up the rules and, critically, mobilize the skills and financial and technical resources that the poorer countries who could credibly sell such credits will need to embark on their own transformational emission reductions journeys.

As China mitigates more aggressively domestically it will develop technology and know-how that it can also export, as it has already on a smaller scale. Some exports will be particularly useful for countries where lower-cost Chinese technology, such as electric buses or cars might be more attractive than expensive European or North American ones. China’s Belt and Road Initiative offers a critical mechanism that can be turned to this purpose. If China can help poor countries develop strong mitigation policies, through strong South-South cooperation, they could transform global cooperation further and strengthen markets for this technology. This would make me even more optimistic.

 

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How innovative policies can help clean the transportation sector

As climate week gets underway, policymakers should prioritize ways to reduce emissions from one of the biggest contributors to greenhouse gases: the transportation sector. A diverse group of stakeholders recently came together to discuss opportunities to do just that.

Transportation accounts for nearly one third of all greenhouse gas emissions in the U.S. and a substantial share of local pollution in urban areas. Not only do these emissions greatly contribute to climate change, they can cause significant health concerns, from respiratory and cardiovascular illnesses, to premature mortality. Furthermore, communities of color and low-income communities have suffered much more from the health and well-being impacts of transportation-related air pollution than non-disadvantaged communities. Thus, it is both a social and environmental imperative to clean our transportation system.

However, cleaning our transportation system is not a trivial task—the effects of pollution vary widely in space and across different communities; the impacts of pollution are felt locally, regionally and globally; and multiple challenges across many different sectors of our economy to achieving this goal still exist. We will need a coordinated, multi-sector approach, with major investments and targeted policies.

To discuss these solutions and explore opportunities, Resources for the Future, Environmental Defense Fund, and Duke University’s Nicholas Institute hosted a two-day virtual workshop in July 2020. We invited individuals from all over the country, and from different sectors, including local governments, non-governmental organizations, stakeholder and community groups, industry, and academics, in an effort to increase communication across sectors, explore diverse policy solutions, and hear from different points of view.

Though we heard diverse approaches and assumptions from the different speakers and participants, we all agreed on the following: Cleaning our transportation system is a necessary and urgent action, and we can leverage this transformation to achieve even more improvements in social outcomes, above and beyond those caused by the transportation sector.

Panel I: Effectiveness and Behavioral Responses to Carbon Pricing and Vehicle Regulations under Existing Policies  

The first panel of the day discussed the effectiveness of carbon pricing and vehicle regulations on cleaning the transportation system, given existing policies and the nature of our “business as usual” future.

One of the main takeaways: though carbon and gasoline taxes can and have had an impact on reducing gasoline consumption, these taxes won’t be enough to achieve the major structural changes needed for the sector.

Other policies, such as vehicle efficiency standards and scrappage programs (like cash-for-clunkers), can help ensure older vehicles are replaced with better, more efficient (or even electric) alternatives, and can also work in conjunction with gasoline and carbon taxes to help achieve a cleaner transportation system. However, these programs may cause some unintended consequences if not pursued cautiously or developed jointly with policies that increase access to alternative modes of transportation.

Panel II: Distributional Effects of Transportation Policy

The workshop’s second panel focused on how to structure transportation policies to reduce the inequalities that transport-related pollution creates among different communities. The speakers highlighted the many different types of inequalities created by unjust and problematic housing and transportation policies, magnified by disadvantaged communities’ greater exposure to pollution, and how the transformation of the system can be leveraged to improve these distributional outcomes.

To be able to achieve these improvements, several steps must be taken, including:

  • Use data and modeling to identify disadvantaged communities most affected by transportation pollution;
  • Actively engage with community and environmental justice groups from the beginning when setting policy in order to identify their most pressing issues and concerns and ensure they have a seat at the table;
  • Conduct research to identify the most beneficial policies and actions for these communities and address their concerns;
  • Work to avoid unintended consequences of transportation policy that may harm disadvantaged communities in our quest to green the transportation system.

Panel III: Investments on Carbon Revenue: Efficacy and Impacts Across Groups

Our third panel explored the many avenues for investments of revenue raised from policies such as a carbon tax. There exist almost infinite options for investments- in both the private and public sectors, to individuals or corporations, for education and behavior modification, to infrastructure and technology, and so much more. Identifying the investment that provides the largest bang for buck is a challenge worth pursuing in order to maximize the benefits of our clean transportation transformation.

One of the difficulties is understanding the distributional impacts of investments. It is important to identify who will benefit the most from these investments, and whether there are important spillovers such as job creation. When the benefits of an investment are diffuse or long term, this can create a political challenge in its implementation. Furthermore, understanding the policy context around the investment is key: non-transportation-related policies such as zoning or housing regulations can affect the benefits of any investment in this space. For example, changing zoning rules could improve access to alternative modes of transportation, making investments in electric vehicle charging stations and public transit more effective at shifting driving away from private, fossil-fueled vehicles.

Panel IV: Changing the Rules: State and Local Policies and Potential Interactions with Carbon Pricing

The final panel of the day discussed how non-carbon pricing policies at the state and local level may interact with existing carbon policies, such as the Regional Greenhouse Gas Initiative (RGGI, a regional cap and trade program covering GHG emissions from 10 states in the northeast). Though cap and trade or carbon pricing sends a price signal to reduce carbon emissions, it alone may not be enough to achieve the large transformation required.

Alternative policies, such as the low carbon fuel standard, congestion pricing, or even policies outside of the transportation sector can help to bring about even greater reductions of transportation emissions, especially when combined with carbon pricing policies.

Electricity sector policies are an especially important one to get right. As our transportation system becomes less reliant on gasoline and more reliant on electricity for fueling, we need to ensure that the electric sector is clean (and carbon pricing can play an important role in achieving this outcome), while also implementing policies to reduce the costs that charging vehicles can place on the system.

A Vision for a Clean Transportation Future

This workshop made a strong case for urgent action—the emissions associated with transportation are too large and affect too many vulnerable communities to allow the status quo to continue unabated. Many different types of policies can be implemented, and even in the face of political challenges – particularly at the federal level – cities and states across the country are already taking action.

The speakers envisioned a future where transportation is clean; where all individuals across the country, regardless of where they live, have mobility access and alternatives in their modes of travel; where investments are made with an eye towards maximizing the public benefit and ensuring those most disadvantaged are uplifted; and where all communities have a voice in shaping the path of this clean transformation. This clean future exists; now it is up to us to shape policies in order to achieve it.

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How Climate Economics supports the Paris agreement temperature targets

New research building on Nobel Prize winner Nordhaus’ past contributions shows reaching UN climate targets is a good investment for the planet

Two years ago William Nordhaus was awarded the Nobel Prize in Economic Sciences for his pioneering work on “integrated assessment modeling” (IAM) and his Dynamic Integrated model of Climate and the Economy (DICE)—a framework designed to analyze the interplay between the economy and climate change, and used to assess economically optimal CO2 emission pathways and the social cost of carbon (SCC). Now a new paper published in Nature Climate Change demonstrates that a 1.5 to 2 degree target in line with the UN Paris agreement is economically optimal when the DICE model is updated to reflect newer research and latest expert assessment.

As I described in a blog about Nordhaus’ Nobel Prize two years ago, there were several ways new research could strengthen the results from Nordhaus’ DICE model and other IAMs. In this new paper, Martin C. Hänsel and co-authors (including Daniel Johansson, Christian Azar and EDF Senior Contributing Economist Thomas Sterner) made a number of such modifications to the baseline assumptions to update the results coming out of Nordhaus’ DICE model.

Two of their key updates relates to the economic assumptions/inputs to the model:

  • Updating the damage function (the assumed relationship between climatic changes and economic damages) to reflect a recent meta-analysis of climate damage estimates; and
  • Updating how equity between present and future generations is taken into account in DICE by revising the parameters determining the social discount rate. The choice of discount rate has a large impact on the results coming out of IAMs, since it determines the weight given to the climate damages affecting future generations.  This has spurred a long-standing debateespecially since the value of at least one of the parameters typically discussed is based on value judgments. Hänsel et al therefore chose to update the values of the parameters determining the social discount rate according to a recent survey of expert opinions.

The authors also made a number of additional updates to reflect new research in climate science and thereby improve the assumptions determining the relationship between greenhouse gas (GHG) emissions and temperature change (which include assumptions with respect to the global carbon cycle and the energy balance model translating radiative forcing to temperature impacts).

The authors also considered the impact of:

  • NETs (negative emissions technologies) such as afforestation, Biomass Energy with Carbon Capture and Storage (BECCS), and direct air capture. By providing the additional option of negative emissions after 2050, NETs further reduce the optimal equilibrium temperature, but also leads to a lower SCC in 2020 since the availability of NETs makes it optimal to postpone some emission reductions. However, it’s important to note that the potential magnitude of NETs available and on what timeline is debated and, for some strategies, still to be demonstrated.
  • Emission pathways with higher abatement of non-CO2 GHG emissions (which are not determined inside the DICE model) and make even lower equilibrium temperatures attainable. This illustrates the value of also addressing short term climate forcers such as methane emissions.

Both these latter updates contribute to a reduction in the economically optimal equilibrium temperature in DICE (i.e., the long run global average temperature which would provide the theoretically optimal balance between the social cost of climate damages and the costs of emission reductions).

The combined results of all these updates – reflecting recent findings in the climate economics and climate science literature – to the baseline assumptions in DICE are:

  • The SCC in 2020 is twice as high with all the other updates but with Nordhaus’ baseline assumptions for the social discount rate left unchanged. This is well in line with the strong consensus that SCCs at the levels produced with the baseline assumptions in DICE ($39 per tonne) significantly underestimate the true social costs of carbon dioxide emissions.
  • Optimal climate policy according to this updated DICE model keeps equilibrium temperature below 2 °C in 2100 in three quarters of all model runs.

Despite these key updates to the DICE framework, there are still—as the authors also point out—additional enhancements that can be made to improve this type of climate economic analysis, which weighs the costs and benefits of climate action. Such enhancements include consideration of risk and uncertainty and the representation of so-called “tipping points” as well as taking into account that the value of environmental assets relative to other goods and services may increase as they suffer a larger share of the costly damages from climate change.

Overall, these new findings show that the temperature targets in the Paris agreement (where countries committed to limiting the global temperature rise to well below 2 °C and to actively pursue a 1.5 °C target) are also supported by climate economic analysis and that reaching the UN climate targets is a good investment for the planet.

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