Progress in Emission Inventories of
Pearl River Delta Region
Junyu (Allen) Zheng, Ph.D
South China University of Technology
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Context: Emission Inventory
 Air pollutant emission inventories are
fundamental information for:
 emission trend characterization
 emission budgeting for regulatory and
compliance purposes
 assessment of pollution control strategies
 predication of ambient pollutant concentrations
and health effect
 emission trading
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History in Emission Inventories in PRD
The first EI of PRD for 1997
2002 The second EI of PRD for 2001
2003 Developing the EI manual of PRD
jointly by GDEMC and HKEPD
2005~2007: Developing and reviewing
the EI of 2003 using the EI manual
2008: GDEPD and HKEPD publicly released
the 2003-based EIs in the PRD
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Source: Prof. Liuju Zhong

Limitations in PRD Emission Inventories
 Lack of localized emission factors
 Difficulties in activity data collection
 High uncertainty
 less work in the spatial, temporal allocation
and chemical speciation
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Newest Available Emission Inventories in PR
D
 Base Year: 2006
 Pollutants: SO2, VOC, NOX, PM10, PM2.5, CO
 Source Categories
 Power plants
 Industrials sources
 Mobile sources
 VOC products sources
 Biogenic sources
 Other sources
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Spatial Distribution of SO2 Emissions
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Spatial Distribution of NOx Emissions
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Spatial Distribution of PM10 Emissions
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Spatial Distribution of VOC Emissions
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Key Findings in PRD Emission Inventories
 About 51.4% of SO2 from power plants, 39.9%
from industrial sources, and 8.8% from other
categories
 41.6 % of NOx emissions were contributed by
power plants, 46% from mobile sources, and
12.4% from others.
The industrial, mobile and power plant sources
are major contributors for PM10 and PM2.5
emissions, accounting for 52.6%, 22.3%, and
22.8% for the total PM10 emissions and 40.8%,
36.2%, and 20.4% for the PM2.5, respectively
 Mobile source is the largest contributor
responsible for the 39.9%, and biogenic and VOC
product-related sources accounting for 24.5% and10
23.6% of the total VOC emissions in the region

Key Findings in PRD Emission Inventories
 There is relatively low uncertainty in SO2 emission
estimates
 Medium to high uncertainty for the NOx emissions, high
uncertainty for the NOx emissions are mainly from on-road
and non-road mobile source categories.
 High uncertainties exist in the VOC, PM2.5, PM10 and
CO emissions due to lack of key representative emission
factors and large uncertainty in activity data. On-road
mobile, VOC product-related and biogenic sources are key
contributors to the high uncertainty in VOC emissions
 Industrial and on-road mobile sources are main
uncertainty sources for leading to high uncertainty in
PM10 and PM 2.5 emission estimates.
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Future PRD Inventory Improvement
 Enhancement of local emission factor
development and proper classification and
collection of activity data.
 Improving estimates of emissions from mobile
sources will greatly increase the accuracy of NOx,
VOC, CO,PM10 and PM 2.5 emission estimates in
the PRD region.
 The industrial sources, especially for nonmetallic
mineral products industry, should be prioritized for
improving the estimates for PM2.5 and PM10
emissions.
 Enhancement of collection of activity data for the
VOC-related product sources will be helpful for
improving VOC emission estimates. 12

Future PRD Inventory Improvement
 More work are needed for improving
temporal and spatial allocations
 An open data sharing policy among
different parties will be another important
way to improve the PRD regional emission
inventory.
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