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IES China National Assessment Case Study

Background on the IES-China National Assessment

The IES Program engages developing countries to help build capacity and support for integrated planning to reduce emissions of both global greenhouse gases (GHGs) and local air pollutants. The program promotes the analysis of and local support for implementing policy measures that result in multiple environmental, public health, and economic “co-benefits.” The IES-China Program began in 1999 with a statement of intent between China's State Environmental Protection Administration (SEPA, now the Ministry of Environmental Protection) and the U.S. Environmental Protection Agency (EPA), in conjunction with the U.S.-China Forum on Environment and Development. The program's first analysis was conducted in 1999 and examined the co-benefits of clean energy and transport strategies in Shanghai. A similar study was completed in Beijing in 2006, with a focus on air pollution targets for the 2008 Olympics. More information on these two studies can be found at www.epa.gov/ies/china/shanghai.htm and www.epa.gov/ies/china/beijing.htm.

This fact sheet summarizes the third IES-China analysis, an assessment of the multiple benefits of clean energy and transportation policies at a national level. Tsinguhua University's Department of Environmental Science and Engineering led the energy and atmospheric modeling work of the IES-China National Assessment, and Peking University's Health Science Center led the air pollution health effects work. Other collaborating parties included EPA, SEPA, and the National Renewable Energy Laboratory (NREL).

Methods and Objectives of the IES-China National Assessment

The IES-China National Assessment examined the air quality and public health impacts of clean energy and transport sector strategies in China. The project utilized the Long-Range Energy Alternative Planning (LEAP) model to project energy utilization. The following emissions were examined over a 30-year period: carbon dioxide (CO2), nitrogen oxides (NOx), sulfur dioxide (SO2), xnon-methane volatile organic compounds (NMVOCs), black carbon (BC), organic carbon (OC), and ammonia (NH3).

The study examined three scenarios: a base case assuming business as usual (BAU), a climate change policy (CCP) scenario, and a pollution control policy (PCP) scenario. These scenarios are outlined in Table 1. Analysts used the projected emissions for each scenario and time period (2001, 2005, 2010, 2020, and 2030) as inputs for the air quality model—Models-3/Community Multiscale Air Quality (CMAQ)—to better understand the impact on concentration levels for NOx, SO2, and particulate matter (PM) in future years.

The changes in concentration levels of PM2.5 for each scenario and study year were entered into EPA's Environmental Benefits Mapping and Analysis Program (BenMAP) to calculate the expected impact on health endpoints (morbidity and mortality) for the entire population of China. This model was also used to calculate the economic value of the changes in mortality and morbidity. The study was the first application of BenMAP on a national scale in China.

Table 1: National Assessment Policies

Policy Scenarios Key Assumptions
Business sources in urban households.(BAU)
  • Electricity and gas fuel are the dominant energy as Usual
  • Energy Conservation Law and related laws are implemented.
  • For mobile sources, Euro III standards are implemented in 2008, Euro IV in 2012, and more strict standards in 2018 and 2025.
  • “Two controlled zones” policies are successfully implemented: new power plants must install flue gas desulfurization (FGD) equipment after 2000, and NOx control technologies begin to be widely used in 2015.
Climate Change Policies(CCP) In addition to BAU:
  • Energy intensity in the industrial sector decreases more rapidly.
  • Energy conservation standards for buildings improve significantly, and dispersed heating supplies are replaced by more centralized ones.
  • More energy-saving appliances are used in the residential sector.
  • Automobile fuel economy increases more rapidly.
  • Efficiency of electricity plants and heat boilers increases.
Pollution Control Policies (PCP) In addition to BAU:
  • Replacement of small power plants with larger ones is accelerated, and FGD and NOx control technologies begin to be widely used after 2012.
  • Efficiency of SO2 and NOx control in the industrial sector is significantly improved.
  • PM control is more focused, and more electrostatic precipitators and baghouse filters are installed.
  • For mobile sources, EURO III standards are implemented in 2008, EURO IV in 2010, and more strict standards in 2015 and 2020.

Findings

Table 2 lists projected levels of GHG emissions and local/regional pollutants in 2030 under the three scenarios: BAU, CCP, and PCP.

Table 2: Projected Levels of GHG Emissions and Local Pollutants in 2030 (kTons per year)

GHG/Pollutant BAU CCP % Reduction from BAU PCP % Reduction from BAU
CO2 1,889 1,560 17.4% 1,523 19.4%
SO2 28,085 23,382 16.7% 16,067 42.8%
NOx 17,470 15,094 13.6% 12,596 27.9%
BC 691 514 25.6% 424 38.6%
OC 1,582 1,301 17.7% 1,166 26.3%
NMVOC 16,945 15,198 10.3% 12,512 26.2%

These IES results indicate that CCP policies are most effective when the goal is to reduce GHG emissions and local/regional pollutants at the same time. PCP policies are most effective in reducing local/regional pollutants, but they offer few additional benefits in terms of GHG abatement compared to CCP.

The results of the valuation of health effects show that PCP has more PM2.5-related economic benefits than CCP alone. In 2030, the expected value of avoided morbidity and mortality from Scenario 1 is $3.49 per capita in 2005 dollars. The value of avoided morbidity and mortality under Scenario 2 in 2030 is estimated at $11.76 per capita in 2005 dollars.

Recommendations

Based on the findings of the IES National Assessment, the IES-China team recommended the following policies to China's policymakers to address both GHG and air pollution goals:

For More Information

Please contact Jack Fitzgerald (fitzgerald.jack@epa.gov).


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