Papers are currently under preparation describing the inventories presented on this website, and the methods employed for their spatial distribution. Please cite as follows:
Global Anthropogenic Mercury Emission Inventory for 2000: Pacyna, E., J. Pacyna, F. Steenhuisen and S. Wilson. Atmospheric Environment (in prep. 2005)
Spatial Distribution of Global Anthropogenic Mercury Atmospheric Emission Inventories. Wilson, S., F. Steenhuisen, J. Pacyna and E. Pacyna. Atmospheric Environment (in prep. 2005)
Documentation:
| Compilation of Mercury Emission Inventories |
For further information on compilation of the mercury inventories contact Jozef Pacyna, Norwegian Institute for Air Research (NILU)
National anthropogenic mercury emission estimates were compiled at NILU by J. Pacyna and E. Pacyna.
The inventories presented here are for the nominal years 1995 and 2000. For some countries, official emission estimates reported for other years (within 1-2 years of the target nominal year) have been used. In a very few cases where no new emissions estimates were available, 1995 emissions estimates for certain sectors in some countries were also used in 2000.
The 1995 inventory is described in Pacyna & Pacyna (2002) and a paper describing the 2000 inventory is in preparation (Pacyna et al, 2005).
Source Categories
National emission estimates were broken down between the following major source sectors:
Stationary combustion, including
- power plant emissions
- residential heating
Cement production
Non-Ferrous Metallurgy, including
- non-ferrous metal smelting (Cu, Ni, Pb, Zn production)
- gold production
- mercury production
Pig Iron and steel production (and coke production)
Caustic soda production (chlor-alkali industry)
Waste incineration
Other sources
|
Accuracy of the (1995) inventory values was estimated at plus/minus 25% for stationary fossil fuel combustion sources, plus/minus 30% for non-ferrous metal production, iron and steel production and cement production, and a factor of upto 5 for waste disposal sources (Pacyna, et a. 2003).
Datasets used
In preparing the 2000 inventory, the NILU datasets were supplemented by data from other sources as indicated in the following table:
|
Region
|
1995
|
2000
|
| Europe (excluding Russia) |
Pacyna and Pacyna (2002) |
MERCYMS/EMECAP |
| Russia |
Pacyna and Pacyna (2002) |
ACAP (2004b); Pacyna et al (2005) |
| Asia (excluding Russia) |
Pacyna and Pacyna (2002) |
Pacyna et al (2005) |
| North America |
Pacyna et al. (2002) and US EPA NEI (1996)
|
USA: US EPA NEI for HAPs (1999)
Canada: ACAP (2004a); National Pollution Release Inventory (2000)
Other countries: Pacyna et al (2005)
|
| South America |
Pacyna and Pacyna (2002) |
Pacyna et al (2005) |
| Africa |
Pacyna and Pacyna (2002) |
Pacyna et al (2005) |
| Australasia / Oceania |
Pacyna and Pacyna (2002) |
Pacyna et al (2005) |
| Spatial Distribution of Mercury Emission Inventories |
For further information on spatial distribution of the mercury inventories contact Simon Wilson, Arctic Monitoring and Assessment Programme (AMAP) or Frits Steenhuisen, Arctic Centre, University of Groningen (RuG)
Methodology
The methodology employed to spatially distribute the global mercury emission inventories is essentially that described in Pacyna et. al (2003). An updated description of the methodology employed to distribute the 2000 emission inventory is under preparation (Wilson et al, 2005).
The basic approach involves:
(1) Assignment of emissions to point sources where information on this is available:
- Point source emissions can be (accurately) located within the grids based on their (latitude/longitude) coordinates.
- It was possible to associate aproximately 15% of the global annual emissions in 1995 and 2000 with defined point sources. The most complete information on point source emissions is available for Europe, USA (based on National Emissions Inventory for Hazardous Air Pollutants data), Canada (based on National Pollution Release Inventory infomration, mainly for 2000) and Russia (based on ACAP data compilation, mainly for 2000).
(2) Use of population distribution datasets (see below) as a surrogate to spatially distribute 'Distributed source' emissions. These include (a) emissions from diffuse sources, and (b) emissions that are associated with point source but where the location of the point sources is not known.
Country identifiers in emissions datasets and population datasets were recoded (where necessary) to their ISO 3166-1 alpha-3 code. This coding system was used throughout the project to match emissions and population datasets, and to identify counties in product datasets, etc.
Grids
Mercury emissions were distributed into two regular grids covering the entire globe and based on the latitude/longitude coordinate system: the Z05 grid comprising 259200 (720 x 360) grid cells with a cell size of 0.5 x 0.5 degrees, and the (so-called) GEIA grid comprising 64800 (360 x 180) grid cells with a cell size of 1 x 1 degrees.
The grids are defined as follows:
Z05 (0.5 x 0.5 degree) grid definition:
259200 (720 x 360) cells
Z05 Cellcode = (j*1000) + i
j = row number starting at 1 for 90S to 89.5S latitude, to 360 for 89.5N to 90N latitude
i = column number starting at 1 for 180W to 179.5W longitude, to 720 for 179.5E to 180E longitude.
(coordinates represent the center of the gridcell)
The latitude and longitude of the center of a gridcell is given by:
latitude = ((j-181)/2) + 0.25
longitude = ((i-361)/2) + 0.25
GEIA (1 x 1 degree ) grid definition
64800 (360 x 180) gridcells
GEIA Cellcode = (j*1000) + i
j = row number starting at 1 for 90S to 89S latitude, to 180 for 89N to 90N latitude
i = column number starting at 1 for 180W to 179W longitude, to 360 for 179E to 180E longitude.
(coordinates represent the center of the gridcell)
The latitude and longitude of the center of the grid is given by:
latitude = (j-91) + 0.5
longitude = (i-181) + 0.5
Speciation (source split factors)
Total mercury emissions (HgT) were split into three main 'species' groups: elemental mercury (Hg0), divalent mercury (Hg2), and particulate mercury (HgP) using a set of defined split factors.
For most emissions, the split factors used were as follows:
|
Species
|
Coal combustion
|
Oil combustion
|
Cement production
|
Non-ferrous metal production
|
Pig Iron & Steel
|
Caustic soda
|
Waste incineration
|
Other
|
|
Power plants
|
Residential heat
|
Cu-Ni-Pb-Zn
|
Au
|
Hg
|
|
Hg0
|
0.5
|
0.5
|
0.5
|
0.8
|
0.8
|
0.8
|
0.8
|
0.8
|
0.7
|
0.2
|
0.8
|
|
Hg2
|
0.4
|
0.4
|
0.4
|
0.15
|
0.15
|
0.15
|
0.2
|
0.15
|
0.3
|
0.6
|
0.15
|
|
HgP
|
0.1
|
0.1
|
0.1
|
0.05
|
0.05
|
0.05
|
0
|
0.05
|
0
|
0.2
|
0.05
|
Exceptions were:
USA emissions, where split factors were assigned according to MACT codes as specified in the received datasets.
Emissions from some countries for certain source sectors, where the split factors were adjusted to reflect available technology, etc
Emission height levels
(Geometric) emission height levels were similarly assigned, based on the source sectors concerned or in the case of USA point sources, stack height reported in the received datasets.
Population datasets
Population distribution is widely used as a surrogate parameter for the spatial distribution of emissions from anthropogenic sources when the exact location of the emissions is not known - based on the logic that emissions derived from human activities are co-located with areas of highest population density.
The datasets required for this process are values for the proportion of a countries total population in a given gridcell - this value being used as a multiplier for the total emissions from 'distributed sources' (for a given source category) from that country.
To date, most work on spatial distribution of global (and regional) emissions inventories has employed a (1990) population distribution dataset available from GEIA (Li, 1996). This dataset has a resolution of 1 x 1 degree and is based on 1990 global population distribution.
In order to (a) improve the spatial resolution of the distribution on 'distributed source' emissions, and (b) use contemporary population distribution with respect to the emissions datasets, new population datasets were constructed as follows:
Data on global population distribution in 1995 and 2000 (Gridded Population of the World (GPW v3)) were obtained from the CIESIN (2004). These datasets have a spatial resolution of 2.5 arc-minutes.
To assess the absolute number of people living each 0.5 degree cell, an intersect was made by overlaying the 0.5 degree grid and a GPW v3 country dataset for the year concerned. Cells that contained land area from more than one country were split into respective sub-cells (polygons).
The image below shows the 0.5 x 0.5 degree grid superimposed on the CIESIN GPW population distribution dataset. Cell boundaries and national borders define the gridded population 'polygons'. In the area where France, Belgium and Luxembourg border each other, one grid cell has been split into three polygons.
(Click figure to see a larger version)
A zonal statistics procedure was used to calculate the total population within each grid cell or (in cases or two or more countries occupying part of a given cell) sub-cell (polygon)). During this procedure, a small loss in the population totals occurs due to the fact that the country data and GPW raster cannot be completely spatially matched. To overcome this problem, working values for country total populations were calculated by summing the population values of all polygons assigned to that country. Based on these working totals and the absolute population numbers within each polygon, the proportion of a contries population in that cell was calculated.
The 1995 and 2000 population datasets used in this work are available in both 1 x 1 degree and 0.5 x 0.5 degree grids.
Following use of the proportion of population in a cell as a multiplier for national emission values, emissions within each cell were aggregated to combine the emissions in cells shared by more than one country.
General Observations
The total global anthropogenic emission inventory estimates for 1995 and 2000 from the data compiled by Pacyna et al (2005) are 2317 and 2188 metric tonnes, respectively. Accuracy of the (1995) anthropogenic emission inventory values was estimated at plus/minus 25% for stationary fossil fuel combustion sources, plus/minus 30% for non-ferrous metal production, iron and steel production and cement production, and a factor of upto 5 for waste disposal sources (Pacyna, et a. 2003). After the various calculations required to prepare the spatially distributed inventories, corresponding totals for 1995 and 2000 were within 1% of these values.
The anthropogenic emission estimates can be compared with estimates of global mercury emissions to the air from natural sources which are of the order of 2000 metric tonnes per year.
Updating of the 1995 spatially-distributed emission inventory
In addition to the preparation of a new spatially-distributed inventory for 2000, the previously published 1995 inventory (Pacyna et al. 2003) has been updated. The updated version differs from the previously published version in several important respects:
- Errors noted with respect to some point source locations in the original spatially-distributed 1995 emission inventory have been corrected.
- Double counting of some emissions from some countries (as both point source and distributed emissions) have been corrected.
- The (new) 1995 population dataset was used to distribute non-point source emissions (the previous version used the GEIA 1990 1 x 1 degree resolution population dataset).
These factors all affect the resulting distributied inventory to some extent.
Comparison of the 1995 and 2000 emission inventories
Because of differences in the emission datasets used to construct teh 1995 and 2000 inventories, and also the different population datasets, it is not appropriate to directly compare the gridded 1995 and 2000 inventories on a cell-by-cell basis. Examples of mapping artifacts associated with the data and procedures used can be seen by visual comparison of Map 1 (2000 emissions) and Map 2 (1995 emissions). For example, in Canada, more point source emissions were documented in 2000 than in 1995. Thus, whereas the emissions in 1995 are largely mapped to population distribution, emissions are more 'concentrated' in individual cells in 2000. A similar picture is seen in Russia.
The way in which population data are spatially distributed in the GPW datasets produces another 'suspect artifact' in the spatially-distributed datasets. The presence of at least some population counts in almost all (land-based) grid cells means that some part of the (distributed source) emissions are always mapped to these cells, even if the population density is very low. To 'visually adjust' for this artifact, a cut-off value has been used when producing maps of the gridded emission distributions, to 'mask' cells where very low emissions have been assigned due to presentce of some few individuals.
Differences between the 1995 and 2000 inventories as percentage difference in national emission totals is presented in map form in Map 3.
ACAP, 2004a. Arctic Mercury Release Inventory. Arctic Council Action Plan to Eliminate Pollution from the Arctic (ACAP). Danish Environmental Protection Agency. Copenhagen.
ACAP, 2004b. Assessment of Mercury Releases from the Russian Federation. Arctic Council Action Plan to Eliminate Pollution from teh Arctic (ACAP). Danish Environmental Protection Agency. Copenhagen.
Canadian National Pollution Release Inventory: http://www.npri-inrp.com
CIESIN, 2004. Center for International Earth Science Information Network (CIESIN), Columbia University; and Centro Internacional de Agricultura Tropical (CIAT) 2004. Gridded Population of the World (GPW), Version 3. Beta. Palisades, NY: CIESIN, Columbia University.
http://sedac.ciesin.columbia.edu/gpw
http://beta.sedac.ciesin.columbia.edu/gpw/index.jsp
ISO 3166-1 alpha-3 codes: http://www.posc.org/technical/reference/country.htm#CodeTable
Li, Y. F., 1996, “Global Population Distribution Database”, Report to the United Nations Environment Programme under UNEP Sub-Project Number FP/1205-95-12, Canadian Global Emissions Inventory Centre, Atmospheric Environment Service, Environment Canada, 4905 Dufferin St., Downsview, Ontario, M3H 5T4, Canada.
http://www.geiacenter.org/presentData/pop.html
MERCYMS: http://www.cs.iia.cnr.it/MERCYMS/project.htm
Pacyna, J. and E. Pacyna (2002). Global emissions of mercury from anthropogenic sources in 1995. Water, Air and Soil Pollution 137, 149-165.
Pacyna, E., J. Pacyna, F. Steenhuisen and S. Wilson (2005). Global emissions of mercury from anthropogenic sources in 1995. Atmospheric Environment (in prep).
Pacyna, J., E. Pacyna, F. Steenhuisen and S. Wilson (2003). Mapping 1995 global anthropogenic emissions of mercury. Atmospheric Environment 37 Supp. No. 1 S-109-S117.
US EPA http://www.epa.gov/air/data/neidb.html
Wilson, S., F. Steenhuisen, J. Pacyna and E. Pacyna (2005). Mapping global anthropogenic emissions of mercury. Atmospheric Environment (in prep).
