« Chevrolet debuts Sail Hatchback, MPV Concept at New Delhi Auto Expo; first products from JV with SAIC | Main | Rasmussen survey finds concern over global warming among likely US voters at highest level in 2.5 years; 30% say very serious »
Peking University team develops method for modeling historical global black carbon emissions from motor vehicles with reduced uncertainty
7 January 2012
|Geographical distributions of global BC emissions from motor vehicles in 1976 (A) and 2006 (B). Country-based mean values are shown for 1976 and 1° × 1° resolution was used for 2006. Credit: ACS, Wang et al. Click to enlarge.|
Researchers at Peking University have developed a new methodology to model black carbon (BC) emissions from diesel and gasoline motor vehicles. In a study published in the ACS journal Environmental Science & Technology, they found that for global BC emission calculations, 87% and 64% of the variation found in results from earlier studies can be eliminated for diesel and gasoline vehicles by using the new model. (The team’s review of the literature found 385 BC emissions factors for motor vehicles—excluding motorcycles and super-emitters—varying over 4 orders of magnitude.)
In addition to a reduction in uncertainty, their new model can be used to develop a global on-road vehicle BC emission inventory with spatial and temporal resolution, the researchers suggest.
Black carbon is a key short-lived climate change forcer (earlier post) and motor vehicles are important sources of BC in the environment. An earlier global BC emission inventory by Bond et al. put annual emissions of BC from 50 anthropogenic sources at 4,669 Gg in 1996, of which 917 Gg (19.6%) were from motor vehicles. A subsequent emission inventory for Asia estimated total BC emissions from on-road vehicles in this region alone to be 294 and 446 Gg in 2001 and 2006, respectively.
It was predicted that global BC emissions from motor vehicles might reach 1,025−1,754 Gg by 2050 under different UN IPCC (Intergovernmental Panel on Climate Change) scenarios, overriding residential, industry, and power sectors to become the largest anthropogenic source, the Peking University authors note.
Researchers have often estimated BC emissions based on the amount of fuel consumed and emission factors (EFBC, defined as the amount of BC emitted per mass of fuel consumed) of various activities.
EFBC for motor vehicles measured by various laboratories vary in orders of magnitude due to many factors including vehicle type, fuel composition, vehicle model year, marketing country, operation mode, ambient temperature, analytical method, and so on, leading to high uncertainty in emission inventory development. The uncertainty could be reduced significantly by applying different EFBC for diesel and gasoline vehicles and for separating developed and developing countries.
The objectives of this study were to identify the key factors affecting EFBC for motor vehicles based on a thorough literature review and to develop a quantitative relationship between EFBC and these factors. If such a model can be established, the EFBC for various countries in different years where no measurement was available could be better estimated. Subsequently, spatial and temporal variations of global BC emission can be characterized with reduced uncertainty. There is also a potential of applying the quantitative approach developed in this study to other pollutants.—Wang et al.
|Relationship between the predicted and measured logEF BC for diesel (A) and gasoline (B) vehicles. Developed (open circles) and developing (solid triangles) countries are marked differently. Credit: ACS, Wang et al. Click to enlarge.|
The Peking University team found that EFBC for motor vehicles of a given year in a particular country can be predicted using gross domestic product per capita (GDPc), temperature, and the year a country’s GDPc reached US$3,000 (Y3000). GDPc represents technical progress in terms of emission control, while Y3000 suggests the technical transfer from developed to developing countries.
Using their model, the team calculated EFBC for and annual BC emissions from on-road vehicles from 1960 to 2006 for 221 countries/ territories worldwide.
Based on their model, they found:
In 1976, the major emission source regions were West Europe and North America, and the top 3 countries for vehicle BC emissions were the United States (330 Gg/y), Japan (54.6 Gg/y), and Canada (47.2 Gg/y).
After 30 years, the spatial distribution pattern completely shifted, and the ASIA and ALM countries became the dominant source regions. Vehicle BC emission increased 6.8 times in China, which became the highest source country (219 Gg/y), followed by India (85.3 Gg/y), and Brazil (63.1 Gg/y).
Emissions in the United States, Japan, and Canada decreased by 91%, 77%, and 90%, respectively, over the 30 years’ period.
Globally, annual BC emissions have increased from 474 Gg in 1960 to 1294 Gg in 1978, decreased to 918 Gg in 1994, and started to increase again afterward...Although satisfactory models were developed, the future prediction was not conducted primarily because technical advances have not been kept in steady step, and new emerging technologies may lead to fast decreases in EFs over a short period in the future, leading to large uncertainties in EFBC prediction. A typical example is the recently introduced diesel particulate filters, the effect of which cannot be captured in the model.—Wang et al.
Rong Wang, Shu Tao, Huizhong Shen, Xilong Wang, Bengang Li, Guofeng Shen, Bin Wang, Wei Li, Xiaopeng Liu, Ye Huang, Yanyan Zhang, Yan Lu, and Huiling Ouyang (2012) Global Emission of Black Carbon from Motor Vehicles from 1960 to 2006. Environmental Science & Technology doi: 10.1021/es2032218
Bond, T. C.; Streets, D. G.; Yarber, K. F.; Nelson, S. M.; Woo, J. H.; Klimont, Z. (2004) A technology-based global inventory of black and organic carbon emissions from combustion. J. Geophys. Res., [Atmos.] 109, D14203 doi: 10.1029/2003JD003697
TrackBack URL for this entry:
Listed below are links to weblogs that reference Peking University team develops method for modeling historical global black carbon emissions from motor vehicles with reduced uncertainty: