Acknowledgments
This work was made possible by financial support from Environment Canada and the United Nations Environment
Programme, under UNEP Sub-Project Number FP/1205-95-12.
I am grateful to Dr. Ashbindu Singh of the Global Resources Information
Database, United Nations Environment Programme for his constant
encouragement, to Dr. Alexey G. Ryaboshapko, Institute of Global
Climate and Ecology, Moscow, Russia for providing population data
of former Soviet Union. Dr. Ann McMillan, former Chief, and Dr.
S. Venkatesh, Acting Chief of the Modelling & Integration
Research Division, Atmospheric Environment Service, Environment
Canada, have both strongly supported this project during difficult
times. I would like to thank Mr. Jeff Turner for his work in processing
population data and Ms. Tina Shapiro for editing this report.
Thanks also go to my Global Emissions Inventory Activities (GEIA)
working group colleagues for their constant supports and valuable
suggestions. They are Dr. Trevor Scholtz of ORTECH, Canada, Dr.
Robert J. Andres of the University of Alaska Fairbanks, Dr. Thomas
E. Graedel of the AT&T Bell Laboratories, Dr. Carmen M. Benkovitz
of the Brookhaven National Laboratory, Dr. Gregg Marland of the
Oak Ridge National Laboratory, United States, Dr. Jos G. J. Olivier
of the National Institute of Public Health and Environmental Protection
(RIVM), the Netherlands, Dr. Leonor Tarrason of the Norwegian
Meteorological Institute, and Dr. Jozef M. Pacyna of the Norwegian
institute for Air Research, Norway. Fruitful discussions with
Dr. Jennifer Logan of the Harvard University are also highly appreciated.
Introduction
With the push towards sustainable development, there has been a growing demand
for complete and accurate population data. Agenda 21 of the Rio conference, for
example, stressed the need to formulate integrated national policies for environment
and development which take into account demographic trends and factors. Population
databases are forming the backbone of many important studies modelling
the complex interactions between population growth and environmental
degradation, predicting the effects of global climate change on
humans, and assessing the risks of various hazards such as floods,
air pollution and radiation. Detailed information on population
size, growth and distribution (along with many other environmental
parameters) is of fundamental importance to such efforts.
This project has provided a population database depicting the worldwide distribution of
population in a 1X1 latitude/longitude grid system. The database is unique, firstly, in that
it makes use of the most recent data available (1990). Secondly, it offers true apportionment
for each grid cell that is, if a cell contains populations from two different countries,
each is assigned a percentage of the grid cell area, rather than artificially assigning the
whole cell to one or the other country (this is especially important for European countries).
Thirdly, the database gives the percentage of a country's total population accounted for in each cell.
So if a country's total in a given year around 1990 (1989 or 1991, for example) is known,
then population in each cell can be calculated by using the percentage given in the database
with the assumption that the growth rate in each cell of the country is the same. And lastly,
this dataset is easy to be updated for each country as new national population figures become available.
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