『地域政策研究』（高崎経済大学地域政策学会） 第 11 巻

第１号

2008 年７月

57 頁〜 73 頁

Reconciling Local Sustainable Development Benefits andGlobal Greenhouse Gas Mitigation in Asia:
Research Trends and Needs

Toshihiro UCHIDA, Eric ZUSMAN*

Abstract
In recent years, researchers have exhibited a growing interest in co-beneﬁts -- deﬁned as the
local developmental beneﬁts of climate actions. Some of this interest stems from the emerging
awareness that policies with co-beneﬁts may become eligible for future inﬂows of carbon ﬁnance.
Much of this attention relates to studies that estimate that the co-beneﬁts of climate actions could
signiﬁcantly oﬀset the costs of mitigating greenhouse gas emissions. Yet, whereas many studies
have pointed to this potential cost-savings, fewer indications have appeared that this line ofresearch has resonated with policymakers in Asia. The policy impacts of co-beneﬁt studies havethus far been modest in the region. To understand why this is the case, we examine the institutionaland methodological barriers that have made it diﬃcult to integrate co-beneﬁt estimates into
policies. We then identify areas that researchers could pursue to make their studies more policy
relevant.

Key words: Co-beneﬁts; ancillary beneﬁts; cost-beneﬁt analysis────────────────* Names are alphabetical. No senior authorship was assigned. Most of this research was conducted at the Institute for Global
Environmental Strategies where Uchida worked through March 2008. The authors wish to extend their gratitude to Dr. Ancha
Srinivasan for his thoughtful comments on early drafts of this article.

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Toshihiro UCHIDA, Eric ZUSMAN

I Introduction
In recent years, researchers have become increasingly interested in co-beneﬁts -- deﬁned
as the developmental beneﬁts of climate actions.

Some of this attention reﬂects the growing

realization that policies with co-beneﬁts may become eligible for ﬁnancial support from thesuccessor agreement to the Kyoto Protocol (Winkler, et al. 2002). Much of the attention stems
from an emerging consensus that co-beneﬁts could oﬀset the costs of mitigating greenhouse gas(GHG) emissions in developing countries (Chen, et al. 2001; Joh, et al. 2001; Kan, 2004; National
Renewable Energy Laboratory, 2005; EPTRI, 2005; Manila Observatory, 2005; Aunan, et al. 2004;
Wang and Mauzerall, 2006; Aunan, et al. 2006).
This emerging consensus could become particularly important to Asia (Castillo, 2007; Koehn,2008). While Asia contributes a growing proportion of the world's GHGs, the region's developing
countries have expressed concerns that investing in climate actions will divert resourcesfrom poverty alleviation, pollution reduction, and other development priorities. Policies thatsimultaneously address global climate goals and local development needs could allay these cost
concerns. Yet, whereas most studies have demonstrated this potential by quantifying the valueof co-beneﬁts, less attention has been paid to the conditions under which co-beneﬁts are likely tofactor into policy decisions (IGES, 2007).
This is an important oversight. Though the inﬂuence of research on co-beneﬁts seems likely
to expand, thus far several institutional and methodological barriers have limited its impacts in
Asia. The purpose of this paper is therefore to analyze these barriers. Our analysis suggests that,since Asia's local governments are becoming more responsible for implementing measures withco-beneﬁts, alternative quantiﬁcation methods may be needed to complement the data and timeintensive estimation techniques employed in much of the co-beneﬁts literature. Compiling thesemethods in the form of policy guidelines would enhance their usability for local level policymakers.
The remainder of the paper is organized as follows. The following section reviews trends inresearch on co-beneﬁts. Section III discusses institutional and methodological barriers to realizing
co-beneﬁts in Asia. Section IV describes rapid assessment and alternative quantiﬁcation methods
that will be needed to facilitate the entry of co-beneﬁt estimates into policy decisions in Asia.
Section V concludes the paper.

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Reconciling Local Sustainable Development Benefits and Global Greenhouse Gas Mitigation in Asia

II Trends in research on co-beneﬁts
While the term "co-beneﬁts" originated approximately a decade ago, estimating the impactsof public policies has a longer history. During the mid-nineteenth century, the French engineereconomist Jules Dupuit developed the earliest forms of cost-beneﬁt analysis (CBA) to assess theimpacts of local infrastructure projects. Less than a century later, CBA spread yet further when theAmerican Corps of Engineers employed the technique to evaluate federal water projects in the postdepression United States. By the 1980s, CBA was being used to measure the cost-eﬀectiveness of awide range of national and subnational regulatory programs (Pearce, et al. 2006).
The application of CBA to climate policies has a shorter history. This recent interest began
when scholars recognized there were local beneﬁts associated with climate policies that had been
overlooked in earlier studies on "slowing" climate change (Nordhaus, 1991). Morgenstern, forinstance, noted that "these [additional beneﬁts and costs] include health and/or welfare beneﬁts
due to reduction in criteria air pollutants;... beneﬁts of energy savings measures; and, conversely,
potentially low agricultural yields as a result of reduced CO2 fertiliz[ation]" (Morgenstern, 1991).
The recognition of these beneﬁts was signiﬁcant because their inclusion in cost calculations could
alter wait-and-see recommendations counselled in climate-only work.
Their recognition was further signiﬁcant because scholars, realizing that policymakers would
be reluctant to invest in long-term climate policies, could use CBA to estimate the short-term, local
impacts of measures with co-beneﬁts (Markyanda and Rubbelke, 2003). This realization helped
generate a growing body of empirically-driven co-beneﬁt literature. Table 1 contains resultsfrom many of these studies, organizing them in terms of their location, year of publication, typeof co-beneﬁts, and estimated value of beneﬁts normalized per ton of carbon mitigated. The tabledemonstrates that this research has yielded more than 35 estimates from 14 countries.

Table 1: Studies on co-beneﬁts
Location

Year

United States

1991

United States

Air Pollutants

Average Estimated
Value of Co-beneﬁts/
Ton of CO2

Endpoint--

Health$165.00

1993

VOCs

Health$251.00

United States

1993

TSP, PM, SOx, NOx, CO, VOC,
CO2, Pb

Health

$41.00

United States

1993

SO2, NOx, PM

Health$3.00

United States

1993

SO2, NOx, PM, Pb, CO, VOC

Health$33.00− 59 −

Toshihiro UCHIDA, Eric ZUSMAN

United States

1995

SO2, NOx, PM

Health$24.00

United States

1994

Criteria Pollutants

Health

$88.00

United States

1995

Pb, PM, SOx, SO4, O3

Health

$40.00

United States

1998

--

Health

$10.00

United States

1999

SO2, NOx

Health$2.00-$3.00

United States

1999

Criteria Pollutants

Health$8.00-$68.00

United States

1999

--

Health$300.00

Norway1992--

Health$102.00-$146.00

1994

SO2, NOx, CO, VOC, CO2, CH4,
N2O, Particulates

Health, Recreation, Corrosion,
Trafﬁc Noise, Road Maintenance,
and Accidents$246.00

United Kingdom

1992

SO2, NOx, PM

Health

$195.00

United Kingdom

1993

--

Health

$44.00-$201.00----

Health$312.00$153.00

NorwayGermany
Western Europe

2000

SO2, NOx, PM

Human and Animal Health,Materials, Buildings and Other
Infrastructure, Vegetation

European Union

2000

--

Health

$53.00-$79.00

Seoul/Inchon, Korea

2001

PM

Health$10-42.00

Hungary

1998,
2000

TSP, SO2, NOx, CO, VOC,
CO2,CH4,N2O, Particulates

Health, Material and Vegetation
Damage$508.00

Buenos Aires,
Argentina

2002

PM

Health

$56.00-$138.00

Mexico City, Mexico

2003

PM, O3

Health$149.00

Mexico City (BRT),
Mexico2007

TSP, NOx

Health, Time Savings$107.00

Santiago, Chile

1999

Seven Air Pollutants

Health, IQ (from Pb)$251.00-$267.00

2000

SO2, NOx, CO, NMHC, PM, andResuspended Dust

Health

$62.00Santiago, Chile

2006

PM, O3

Health, Agriculture$6.00-$103.00

China

2008

PM

Health

$28.00-$274.00

Santiago, Chile

Beijing, China

2005

SO2, NOx, PM

Health$759.05

Zaozhuang, China

2006

--

Health---1

Shanxi, China

2003

--

Health$120.40

China

2000

SO2, PM

Health

$52.00Shanghai, China

1999

SO2, NOx, PM

Health

$43.65

China

1999

SO2, PM

Health--Manila, Philippines

2005

PM

Health$285.44

Hyderabad, India

2005

PM

Health$873.50

India

2001

PM

Health

$58.00Source: IPCC, 2001; Pearce, 2000; Chen et al. 2001; Gaoli, 2002; Joh et al. 2001; Kan 2004; McKinley, 2003; National
Renewable Energy Laboratory 2005; EPTRI 2005; Manila Observatory 2005, Aunan et al. 2004.

Beyond demonstrating the growing number of co-beneﬁt studies, table 1 underlines two
features of this research that merit attention. The ﬁrst is that the majority of co-beneﬁts come from
improvements in local air quality and related impacts on public health. There are several types ofco-beneﬁts, ranging from shorter commuting times to advances in energy eﬃcient technologies.
Yet most of the literature traces the linkages between hypothetical GHG mitigation scenarios− 60 −

Reconciling Local Sustainable Development Benefits and Global Greenhouse Gas Mitigation in Asia

to the abatement of criteria pollutants to reduced rates of morbidity and premature mortality.2
Cleaner air and better health are the co-beneﬁts that have thus far drawn the most attention fromresearchers (Jochem and Madlener, 2003).
The second notable feature of this research is the growing interest in estimating co-beneﬁts
from developing countries. Prior to 2000, only three out of 19 studies quantiﬁed the value of cobeneﬁts from non-Annex I countries (developing countries that do not have binding reduction
commitments in the Kyoto protocol). Since 2000, 14 out of 17 studies have focused on nonAnnex I countries. This trend arguably reﬂects the recognition that developing countries would
prefer to invest in integrated as opposed to climate-only policies. It is also arguably attributable tothe ﬁnding that, though cross-study co-beneﬁt estimates vary signiﬁcantly, their values tend to begreater in developing than developed countries (IPCC, 2001; IPCC, 2007).
Both the underlying causes and possible consequences of these trends relate to Asia. In termsof causes, the comparatively greater values were likely the product of higher population densities
in developing countries. Higher population densities would increase exposure rates to urban air
pollutants and, therefore, raise the number of beneﬁciaries from policies with co-beneﬁts. The
greater values were also likely the product of initially poorer urban air quality in developing
countries. Initially poorer air quality would increase a measure's marginal impact on pollution and,
therefore, boost the beneﬁts from policies with co-beneﬁts (O'Connor, 2001). Since Asia is home
to many of the world's most densely populated cities and China is home to 20 of 30 of the world's
most polluted cities (World Bank, 2007a), it is clear why these studies would have implications in
the region.
What is less apparent is that these implications could extend from inside to outside Asia. Inside
Asia, many countries have experimented with policies to reduce the social and environmental costsof rapid industrialization, including air pollution, energy eﬃciency, and sustainable transportation
measures. These are precisely the kinds of measures that, if designed and implemented eﬀectively,
could deliver co-beneﬁts. Outside Asia, many of these same policies could qualify for ﬁnancial
support from a post-2012 climate change regime that recognizes non-Annex I parties for pledging
policies that reduce GHG emissions while delivering other development beneﬁts (Winkler, et al.
2002). These are also precisely the kind of institutional reforms that could encourage Asia's
developing countries to incorporate an analysis of co-beneﬁts into policy decisions.
But while some studies have implied the future climate regime may lead to greater
consideration of co-beneﬁts, few studies have addressed a more immediate question: where andwhen would Asia's policymakers use these estimates to strengthen policies? Most of the empiricalresults in table 1 demonstrate the cost-savings from hypothetical mitigation scenarios. But by− 61 −

Toshihiro UCHIDA, Eric ZUSMAN

looking toward the hypothetical future, these studies look past Asia's recent experience with air
pollution, energy eﬃciency, and sustainable transportation measures. This recent history canshed light on the diﬃculties of designing and implementing measures with co-beneﬁts and, more
importantly, where it would be advantageous to integrate an analysis of co-beneﬁts in Asia's future
policy decisions.

III Institutional and methodological barriers(1) Institutional barriers
In both developed and developing countries, policymaking frequently involves bargaining
between agencies with competing administrative portfolios and programmatic objectives. Policy
outputs therefore reﬂect the results of interagency negotiations. But while bureaucratic bargaining
occurs in many countries, its inﬂuence tends to be more pronounced when key agencies lackleverage or have recently begun to challenge the established bureaucratic order. Both descriptions
are consistent with what is happening to climate and environmental agencies in many countries in
Asia. Correspondingly, bureaucratic bargaining has tended to result in policies that fall into one oftwo categories.
The ﬁrst category includes measures that suﬀer from obvious design ﬂaws. To illustrate,
when Thailand's Ministry of Science, Technology, and the Environment (MOSTE) was reforming
the country's air pollution regulations, it granted the Thailand Electricity Generating Authority(TEGA) the responsibility for regulating its own plants (Rock, 2002). The decision diminished thelikelihood that the measure would deliver signiﬁcant health beneﬁts. It also suggested that it would
be diﬃcult to overcome opposition from TEGA, even if MOSTE could demonstrate the cost-savingsof more stringent regulations.
The second category includes measures that contain ambitious but still somewhat ambiguous
goals. To illustrate, when China's National Development Reform Commission (NDRC) and the recently
promoted State Environmental Protection Agency (SEPA) (now the Ministry of Environmental
Protection) successfully inserted a 20% energy eﬃciency improvement target into China's 11th
Five-Year Plan (2006-2010), local governments were delegated the responsibility for devisingconcrete actions to achieve the national goal (Teng and Gu, 2007). The target has thus far proved
diﬃcult to reach, demonstrating again the diﬃculties of maximizing an integrated measure's healthbeneﬁts.
The ﬁrst and second scenarios are in some ways similar; in both cases policies fell short ofreaching their potential. Yet the reasons for these shortfalls diﬀer. In the case of China's energy− 62 −

Reconciling Local Sustainable Development Benefits and Global Greenhouse Gas Mitigation in Asiaeﬃciency targets, the diﬃculties had more to do with the limitations of local governments thanthe limitations on national climate and environmental agencies. This is an important distinction.
It suggests as Asia's national level climate and environmental agencies become more successful
challenging rival agencies, the next step will be taking concrete actions needed to realize cobeneﬁts. It further implies that local governments will become increasing responsible fortaking these next steps. In fact, in countries from India to Indonesia climate issues have moved
up the national policy agenda as implementation responsibilities have been delegated to local
governments.
At least in theory, the devolution of authority is promising. It can serve to strengthen
institutional linkages between local development needs and GHG mitigation targets. But while it hasthese putative advantages, it also presents other practical challenges. One is that local governments
might oppose measures in which beneﬁts are spread nationally but costs are concentrated locally.
Closing a coal-ﬁred power plant, for instance, could save lives across a region but also impose job
losses in a community. Cases with unevenly distributed costs and beneﬁts may require stronger
programs to compensate policy losers, an important area of research that lies outside the purview
of this article.
Another obstacle that is more closely related to the article's main argument is the capacity of
local level agencies to generate and then apply their own co-beneﬁt estimates. These constraints
include the technical and managerial skills of existing employees as well as the attraction,
recruitment and retainment of skilled staﬀ. To highlight a concrete example, a recent World Bank
report recently observed that India's State Pollution Control Boards "are ... characterized by adominant presence of non-technical staﬀ, diﬀerential availability of staﬀ for monitoring polluting
industrial units, and large staﬀ vacancy positions" (World Bank 2007b). A similar description
could apply to China's local environmental protection personnel; there is an average of 21 to 14
personnel focusing on environmental issues at the city and county levels in China respectively (seetable 2).

Table 2: Environmental personnel in China
Level

Number ofOrganizations

Overall Number ofEnvironmental
Monitoring
Employees
Protection Bureaus
Stations

Inspection Average Number of
Personnel
Personnel

National

41

2065

215

108

45

50

Provincial

352

10911

1946

2825

772

31

City

2005

43084

9081

16143

9169

21

County7680

109839

32899

28613

42859

14

Source: 2006 Huanjing Tongji Nianbao (2006 Environmental Statistics Yearbook)− 63 −

Toshihiro UCHIDA, Eric ZUSMAN(2) Methodological barriers
The above review of institutional barriers implies that it is not easy to integrate quantiﬁcation
into the design and implementation of actual policies. To demonstrate why it is challenging, it isuseful to review the major steps needed to complete a CBA, the quantiﬁcation method used in mostof the previous co-beneﬁts studies. These steps include: listing potential impacts of a policy or
project; predicting the quantitative impacts of that policy or project; attaching monetary values tothose impacts; discounting for time to ﬁnd present values; and then adding up and comparing the
beneﬁts and costs (See Table 3) (Boardman, et al. 2005).

Table 3: Major steps needed to conduct a CBA────────────────────────────────────
1. Create a list of potential impacts of a policy/project
2. Predict quantitative impacts
3. Attach monetary values to all impacts
4. Discount for time to ﬁnd present values if the policy/project extends over years
5. Add up the beneﬁts and costs────────────────────────────────────

To illustrate some of the diﬃculty in applying CBA, take the case of a fuel tax (implemented
in China, Philippines, Hong Kong, and Taiwan; and considered in Indonesia). A fuel tax may causechanges in driving behaviour, a shift in purchasing behaviour as well as a shift in production
behaviour toward more fuel-eﬃcient models, all of which can potentially produce health-relatedco-beneﬁts. However, there are many health eﬀects whose cause-and-eﬀect relationships are
not obvious (such as the eﬀects of emission changes on cardiac arrest), and determining what
diseases are impacted by emissions can be complicated for non-specialists (Boardman, et al. 2005).
In addition, the primary changes in driving behaviours and automobile production may havedownstream eﬀects on the production of automobile parts, the medical industry, the insurance
market, among others. Deciding boundaries for analysis (deciding which impacts should be
included for subsequent analysis) presents another challenge for non-specialists, particularly when
the primary behavioural changes have further eﬀects on other actors and cause repercussions inother markets.
Further complicating quantiﬁcation is the need for dependable data and technical knowledge.
In steps 2 and 3, CBA involves predicting quantitative impacts and attaching monetary values
to identiﬁed impacts. These two steps require extensive data sets if costs and beneﬁts are to be
estimated accurately. In the case of analyzing environmental policies and projects, predicting
quantitative impacts necessitates an understanding of how proposed actions (e.g., tightening
emissions standards, introducing cleaner public transportation, or imposing environmental taxes)− 64 −

Reconciling Local Sustainable Development Benefits and Global Greenhouse Gas Mitigation in Asia

will change ambient environmental quality as well as the behaviour of consumers, ﬁrms, and otherrelevant agents. This may involve the development and use of environmental simulation models,
which, in turn, requires technical knowledge as well as extensive inputs from environmental
monitoring data.3 For example, the Integrated Environmental Strategies (IES) program of the UnitedStates Environmental Protection Agency (US EPA), which applied the standard CBA to estimate cobeneﬁts in several cities in Asia, proceeded with the steps in table 4 to obtain co-beneﬁt estimates(US EPA, 2005). As is evident from these steps, the IES employs a combination of several technicalmodels, making the procedure fairly complicated and data intensive.

Table 4: Key steps in applying the IES model
1. Projection of energy use by the LEAP model
2. Estimation of emission factors by fuel types
3. Projection of stationary, mobile and fugitive emissions from each grid (1km x 1km)
4. Projection of ambient concentrations of major pollutants using Industrial Sources Complex (ISC)
5. Estimation of human health eﬀects
6. Attaching monetary values on the health eﬀects

A related issue is the need to acquire market prices and economic data to establish monetary
values on predicted impacts. The data required for these purposes are typically less dependable
in developing countries in Asia "since even rudimentary environmental databases are lacking
throughout the region and systems of national accounts and other standard measures of economic
performance and social well-being exclude the costs and beneﬁts associated with the use ofenvironmental services" (ADB, 2001).
In sum, the troubles associated with deﬁning the impacts of policies, securing reliable
data, using technical models, and related technical diﬃculties make applying the standard
CBA problematic in developing countries. The next section discusses attempts to resolve thesemethodological diﬃculties.

IV Rapid assessment methods(1) Simplifying CBA
The previous sections point to an important tension. On one hand, there is reason to believethat co-beneﬁts might be greater in developing Asia than other regions, and policies withthese beneﬁts might be attractive to regional policymakers. On the other, there are signiﬁcantinstitutional and methodological barriers to designing, implementing, and estimating the eﬀects of− 65 −

Toshihiro UCHIDA, Eric ZUSMAN

these policies. Initial attempts have been made to reconcile this tension by introducing alternatives
to the standard CBA. In this section, we discuss rapid assessment methods, a simpliﬁed version of
the standard CBA, that may be more amenable to policymakers in developing countries in Asia.
Rapid assessment methods refer to a collection of methods that reduces data, budget, and timerequirements. Rapid assessment methods are based on CBA, but modify part of the quantiﬁcation
procedures used in the standard CBA. One of the rapid assessment methods that can simplify thestandard CBA is the emissions-based unit value approach. The emissions-based unit value approach
derives how a unit reduction of emissions of a certain pollutant translates into beneﬁts measured inmonetary terms. A table summarizing the relationship between changes in emissions and estimatedbeneﬁts is constructed ﬁrst by making appropriate adjustments to the estimates in previous CBA
studies. Table 5 is an example of such a table for the case of health beneﬁts of reduced emissions
from coal-ﬁred power plants in New York (Rowe et al., 1994; ADB, 1996). For example, previous
studies suggest that a ton of emission reductions of PM10 would bring a total of US$3,000-$5,000of health beneﬁts, of which 60% ($1,800-$3,000) accrued in the form of a reduction in premature
mortality, 20% in the form of a reduction in adult chronic morbidity, and so on. Similarly, a tonof emission reductions of SO2 would bring a total of US$750-$1,300 of health beneﬁts, of which$375-$650 was attributed to a reduction in premature mortality. Once such a table is constructed,
it can be applied to estimate health co-beneﬁts of other similar studies by further adjusting topopulation density, level of income, and other relevant location-speciﬁc factors.

Table 5: Estimated health beneﬁts for coal-ﬁred power plants (US$/ton)
PollutantPrematuremortality

Adult chronic
morbidity

Acutemorbidity

Material
damages

Reducedvisibility

Total value(US dollars)

PM10

60%

20%

10%

5%

5%

$3,000$5,000

SO2

50%

15%

10%

20%

5%

$750$1,300

Source: Rowe, et al. 1994; ADB, 1996.

If co-beneﬁts of a fuel tax are to be estimated, it may not be appropriate to directly apply table
5 since it was constructed for emissions reductions from coal-ﬁred power plants. This actually
illustrates the need to construct a table for each of the major policies with potential co-beneﬁts,
including fuel eﬃciency standards, renewable energy targets, clean technology development
initiatives, among others. Constructing such tables would greatly enhance the usability of rapid
assessment methods to policymakers.
Other types of co-beneﬁts can also be estimated using rapid assessment methods. Consider
estimating the beneﬁts of reduced number of deaths in traﬃc accidents (people may drive less
− 66 −

Reconciling Local Sustainable Development Benefits and Global Greenhouse Gas Mitigation in Asiaor shift to public transportation due to higher fuel prices, which may reduce traﬃc accidents). To
estimate the value of lives saved, the standard CBA may employ contingent valuation method anduse local people's willingness to pay (WTP) values. Rapid assessment methods can alternatively rely
on beneﬁt transfer: beneﬁt transfer literally transfers estimates of previous studies to the current
study with appropriate adjustments, thereby reducing time, budget, and the technical burden of
conducting on-the-ground estimations. Past studies that estimated the value of lives saved undersimilar conditions can be found through online databases.4 Since WTP values vary according tofactors such as income, total number of people aﬀected, areas aﬀected, average exposure time tothe air, and weather conditions, the values can be adjusted according to these attributes in order totransfer the estimates to the current study.
To oﬀer another example, consider estimating the beneﬁts of time saved due to reduced
congestion. Another rapid assessment method, a cost-based approach, can be employed. Since CBA
evaluates policies from social perspectives, social costs and beneﬁts, rather than market costs andbeneﬁts, should be used in principle. In practice, however, market costs and beneﬁts are mucheasier to calculate, and the diﬀerences between the social and market values can be reasonably
small under appropriate conditions. By applying a cost-based approach, the beneﬁt of time saved
can be estimated based on hourly salary and changes in commuting time rather than willingness
to pay estimates, which necessitates conducting surveys that are time consuming, costly andtechnically more complicated.
As shown above, there are several rapid assessment methods that can replace part of thestandard CBA, but they are not prepared in the form that non-specialists can apply without
diﬃculty. For example, applying the emissions-based unit value approach to estimate health cobeneﬁts of a fuel tax would be diﬃcult unless a table is prepared that describes the relationshipbetween emissions and ﬁnal estimates (a table like Table 5). Similarly, to estimate other co-beneﬁts
of a fuel tax, rapid assessment methods need to be developed and presented in suﬃciently simple
formats. In sum, there is a need for developing and compiling simpler estimation methods for eachof the major policies with signiﬁcant co-beneﬁts.
Rapid assessment methods are not without weaknesses. In principle, there is a trade-oﬀ
between their usability and objectivity; the ease of use tends to be improved only at the expenseof objectivity. We believe, however, that improving the usability of the standard CBA with rapid
assessment methods will be beneﬁcial to practitioners. In the next sections, we brieﬂy discuss twoalternative methods that are potentially more user friendly, a checklist approach and multi-criteria
analysis (MCA).

− 67 −

Toshihiro UCHIDA, Eric ZUSMAN(2) A checklist approach
In table 3, we presented the major steps needed to carry out CBA. A checklist approach
simpliﬁes step 1 by preparing a checklist consisting of major co-beneﬁts, thereby overcoming
the diﬃculties associated with deﬁning the impacts of policies. In addition, step 2, predicting
quantitative impacts, is usually much simpler than the standard CBA. Furthermore, a checklist
approach vastly simpliﬁes steps 3 and 4. That is, it does not explicitly monetize impacts and it
typically excludes time dimensions from analyses.5
A representative example in the ﬁeld of co-beneﬁts is the CDM Gold Standard. The Gold
Standard employs a checklist approach as a basis for quantifying developmental co-beneﬁts of GHG
mitigation projects. A set of developmental co-beneﬁt indicators (checklist) is used to determine if aproject satisﬁes sustainability requirements for Gold Standard certiﬁcation.

Table 6: A checklist used in the CDM Gold Standard
1. Local/regional/global environment‒ Water quality and quantity‒ Air quality (emissions other than GHGs)‒ Other pollutants (e.g. toxic chemicals, ozone, etc.)‒ Soil quality and quantity‒ Biodiversity
2. Social sustainability and development‒ Employment quality‒ Livelihood of the poor ‒ poverty alleviation, distributional equity, access to essential services‒ Access to energy services‒ Human and institutional capacity
3. Economic and technological development‒ Employment (number)‒ Balance of payments‒ Technological self reliance
Sources: Gold Standard, 2006

Table 6 is a checklist used by the CDM Gold Standard. The Gold Standard checklist has threemajor components: environment, social development, and economic development. Under eachcomponent, there are several indicators such as water quality and quantity, access to energy
services, and technological self-reliance. A project is assessed against each indicator, whichcorresponds to step 2 (predicting quantitative impacts) of the standard CBA. A project receives
scores ranging from -2 (major negative impact) to +2 (major positive impact) under each indicator.
Sophisticated models can be used to assess scores, but simpliﬁed procedures are more typical.
After step 2, a total score is calculated without monetizing each impact. A project fails to satisfy
the sustainability requirements if a project has scores of -2, a non-positive total score, or a negative− 68 −

Reconciling Local Sustainable Development Benefits and Global Greenhouse Gas Mitigation in Asia

subtotal score for any of the three components (Gold Standard, 2006).
As this example illustrates, a checklist approach is simpler than the standard CBA, and can
reduce the diﬃculties associated with deﬁning the impacts of policies, securing reliable data,
and using technical models. However, it tends to be less objective since quantitative impacts areassessed using simpliﬁed procedures, where simpliﬁcation is achieved typically by subjective
assumptions, human judgment, and approximation.
(3) Multi-criteria analysis (MCA)
Multi-criteria analysis (MCA) is a tool that applies a transparent and scientiﬁc method todecision-making problems in the face of complex, and often conﬂicting, multiple criteria. Simply
stated, MCA is a more rigorous version of a checklist approach in that it uses statistical procedures.
Like a checklist approach, MCA does not monetize impacts. However, a major diﬀerence is MCA
attaches a weight to each indicator through expert or stakeholder consultations and statisticalapplications. Instead of a simple summation, a weighted summation is used to calculate thetotal score of a project, and a decision is made according to the ranks of total scores of projects.
The values of weights can be interpreted as reﬂecting social values associated with each factor.
Therefore, depending on the social and developmental needs, diﬀerent countries or communities
can have diﬀerent values for weights.
MCA has several strengths. For instance, decision-making may involve multiple criteria forsocial, economic, environmental factors. Some of these criteria cannot be easily condensed intoa monetary value, particularly when ethical and moral principles are involved.6 MCA supports
decision-making without translating every feasible variable into a single (monetary) measure. An
additional strength is that MCA can reasonably incorporate both quantitative and qualitative data,
because scores can be given to even qualitative data through, for example, expert judgments (achecklist approach can also handle both quantitative and qualitative data).
Yet, MCA is not without weaknesses. For instance, absolute values of total scores may be
diﬃcult to interpret. In a CBA, a net beneﬁt indicates a social value of a policy as measured by amonetary unit, but only relative scores have meaning in the case of MCA. An additional weakness isthat MCA is comparatively more sophisticated and requires expert or stakeholder consultations andstatistical applications. Finally, as with many of the techniques discussed in this section, although
MCA applies statistical procedures, the subjectivity of experts may be an unavoidable drawback.
(4) Comparisons of CBA, MCA, and a checklist approach
As discussed above, there is typically a trade-oﬀ between objectivity and usability in theseapproaches. CBA attempts to monetize all impacts and thus facilitates comparisons in a relatively
objective manner. MCA applies statistical methods to support decision making without translating− 69 −

Toshihiro UCHIDA, Eric ZUSMAN

every impact into a single monetary value, albeit with a degree of subjectivity. A checklist is simple
to conduct, but can be subjective.
The strengths and weaknesses of these methods are summarized in table 7. A greater numberof plus signs indicate the method has desirable properties in terms of each criterion. In general,
CBA is objective, but requires technical expertise, data, and time. A checklist approach, on theother hand, requires less data, time and technical expertise, but is less objective and could present
diﬃculties when it comes to comparisons of policies. MCA tends to fall between CBA and achecklist approach.

Table 7: Comparisons of CBA, MCA, and a checklist approach
Criteria

CBA

MCA

Checklist approach

Data requirement+
Data intensive++
Relatively less dataintensive, qualitative data
can be incorporated+++
Less data intensive, qualitative
data can be incorporated

Time requirement+
Time consuming, but there are
rapid assessment methods++
Relatively time consuming+++Less time consuming

Needs of technicalexpertise+Technically demanding, butthere are rapid assessment
methods++
Relatively technicallydemanding+++Less technically demanding

Objectivity of estimates+++
Objective,
Estimates are measured inmonetary values++
Relatively subjective,
Absolute values of total
scores carry no meaningby themselves+
Subjective

Ease of comparisonsacross policies

+++
Easy

++
Relatively easy,
Total scores can be used
to rank policies+
Diﬃcult,
Total scores cannot be directlycompared across policies

Note: A greater number of plus signs indicates the method has desirable properties in terms of the criterion

The table presents only general picture. For example, rapid assessment methods can be
employed to improve the usability of the standard CBA at the expense of objectivity. There isclearly no method that is desirable along all criteria. While the appropriate method will depend on
the objective of a study, for many of the reasons raised in this paper it might make more sense toerr on the side of usability in developing countries in Asia.

V Conclusion
In this paper, we have demonstrated that, despite a growing literature on co-beneﬁts, there
exist signiﬁcant institutional and methodological hurdles to realizing the local impacts of climate− 70 −

Reconciling Local Sustainable Development Benefits and Global Greenhouse Gas Mitigation in Asia

policies. We have further argued that, at least in the near term, simpler estimation techniques may
be needed to complement the standard CBA. CBA has a long history, but its recent application has
tended to be in places where there is a full understanding of the scope of policy impacts, adequate
data, and suﬃcient human and material resources to integrate estimates into policies. Many ofthese conditions are absent in Asia.
In view of their absence, we believe that future research needs to look more closely at the typesof policies to which the standard CBA or rapid assessment methods can be applied in estimatingco-beneﬁts. It would also be useful to investigate the trade-oﬀs of quantifying co-beneﬁts without
monetization, and the types of policies to which a checklist approach and MCA could be eﬀectively
applied. But most importantly, it is necessary to develop and compile simpler methods for major
policies with signiﬁcant co-beneﬁts, perhaps in the form of policy guidelines. We believe this would
greatly enhance usability for policymakers by reducing time, technical diﬃculty, data requirements,
and dependence on technical models.
In moving in this direction, we further believe that it is important that co-beneﬁt researchers
focus their eﬀorts in locations where there are insuﬃcient resources but signiﬁcant co-beneﬁts.
If one of the primary objectives of these studies is to strengthen the linkages between local
developmental and international climate objectives, then it makes sense to work with local
policymakers to ﬁnd out what techniques works for local policymakers (Morgenstern, 2002).7 Ina similar vein, it may be advisable to focus on non-health impacts of integrated policies (such as
reduced traﬃc congestion) that may be more tangible and politically attractive than the healthimpacts estimated in most studies (IGES, 2007; See Aunan et al., 2000 for impacts on crop yields
for instance).
We recognize that our argument runs counter to the wisdom that simplifying techniques
and adapting them to local circumstances could create confusion. Indeed, writing at a time when
initial wave of co-beneﬁt studies were published, Krupnick et al. (2000) warned that the "methods
should be consistent and estimates should not." We accept this wisdom but worry about its policy
implications. For in the same piece, Krupnick et al. also warned about the applications of co-beneﬁt
approaches in developing countries. Now that we have had some time to examine those prospects,
we conclude that it might be worthwhile to weigh the trade-oﬀs between methodological rigor
and policy relevance, especially in places where co-beneﬁts might be sizable but the capacity toestimate them is not.
（内田
（エリック

俊博・高崎経済大学地域政策学部専任講師）

ザスマン・財団法人地球環境戦略研究機関研究員）− 71 −

Toshihiro UCHIDA, Eric ZUSMAN────────────
1

The Zaozhuang study does not look speciﬁcally at CO2.

2

There are a wide variety of co-beneﬁts, though most studies focus on improvements in local air quality (reduced PM 10, PM2.5,

ground level ozone leading to reduced morbidity and mortality rates) and related improvements in local public health. Other
co-beneﬁts include reduced harm from transregional air pollutants (acid rain and sand storms); reduced congestion; reduced
industrial sprawl; reduced traﬃc accidents; increased employment opportunities in potential growth industries; reduced oil
dependence; increased foreign exchange credits; increased foreign investment; greater technology transfer; and improved
eﬃciencies in industrial processes.
3

For instance, in Jakarta equipment for monitoring ambient air quality was recently shut down, raising concerns about theaccuracy of the data reported for the city.
4

See, for example, the United States Environmental Protection Agency's (EPA) Envalue at http://www.epa.nsw.gov.au/

envalue/Default.asp?ordertype=MEDIUM and Canada's EVRI at http://www.environment.nsw.gov.au/education/evri.htm.
5

Co-beneﬁts could be realized in the near term, minimizing problems with discount rates and intergenerational equity that

otherwise prove diﬃcult in estimating climate costs and beneﬁts.
6
For example, Hammitt and Zhou (2006) applied contingent valuation to China to estimate willingness to pay (WTP) to
reduce risks of mortality. The value of statistical life (a reference value of a human life saved) in China derived from the study
was in the range of US$4,000 - US$17,000, substantially less than the United States Environmental Protection Agency's (EPA)
recommended value of US$6.1 million in 1999 dollars (US EPA, 2000). The fact that the value of statistical life estimate in
China is far less than that in the United States does not mean life saved in two countries can be treated diﬀerently. A direct
application of these results may raise tough moral questions.
7

Morgenstern et al, 2002, for instance, make the case for working from the bottom up, noting that in the case of Taiyuan,
China "incremental changes to ongoing policies with demonstrated local beneﬁts may be an extremely eﬀective way of starting
down the long road of carbon mitigation, especially in developing countries."
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