Environmental Risks to Human Health: New indicators

As presented in Linking Environment and Health, the World Resources Institute (WRI) has developed new environmental health indicators that describe environmental risks to human health in both developing and developed countries. The indicators rank countries according to potential environmental threats to human health. Set out below is a description of the methods used to compile the maps shown in Linking Environment and Health. Developing countries For developing countries, the indicator aggregates measures of environmental risks to human health from three categories: air, water, and nutrition. Each category includes three variables described below. In some cases, selected variables for the indicator were simply added, averaged, and ranked from lowest to highest. In other cases, the variables were constructed using several data sets that were combined in a way to represent potential exposure to an environmental health threat. Air quality The air portion of the indicator for developing countries includes three variables representing potential exposure to poor quality air:exposure to polluted indoor air, exposure to polluted ambient air, and exposure to air polluted with lead from gasoline. Each of these three variables was estimated using the best available data. For example, exposure to polluted indoor air was calculated using the amount of residential coal and biomass fuel consumed per household in each country. WRI divided the total amount of residential coal and biomass fuel consumed per country by the total number of households within that country. When the amount of residential coal and biomass fuel burned per country was not available from the International Energy Agency, WRI used data from the United Nations (Energy Yearbook) on total traditional fuel consumed. WRI subtracted the amount of bagasse produced by each country from the total biomass fuel consumed, assuming that the remainder was used exclusively for residential use. (Bagasse is a residue left after sugar is extracted from sugar cane and is often used as a fuel in the sugar milling industry.) This indicator of exposure to indoor air pollution does not account for confounding factors that can reduce exposure to biomass fuel used indoors such as cooking methods, stove and heater design, house and kitchen design, and ventilation systems. Potential exposure to polluted ambient air was calculated using the number of cities with air concentration levels of pollutants exceeding World Health Organization (WHO) guidelines (for several gases and particles) and the population of those cities. Pollutants considered include total suspended particulates (TSP), black smoke (BS), particulate matter (PM-10), sulfur dioxide (SO2), and nitrogen dioxide (NO2). The final estimate, representing potential exposure to polluted outdoor air, shows the population living in cities with air quality data exceeding WHO guidelines as a percentage of the total population of all cities for which WRI had both air quality and population data. (The city’s entire population was considered at risk if any pollutants listed previously exceeded WHO guidelines, using the most recently reported air quality data.) Data shortcomings complicate the task of estimating potential exposure to polluted air. Consistent and reliable data on air quality for most cities of the world are lacking. In constructing these indicators, bear in mind that the urban population in some countries is represented with data from only one city and that many countries do not have any cities with air quality data and thus could not be included in the indicator. Ambient air quality, however, is important to consider when examining human health and the environment. Even though the data are not comprehensive, they are important to include as one measure of comparing relative environmental health threats among countries. Exposure to air polluted with lead from gasoline is derived using three variables: the market share of leaded gasoline used in a country, the total amount of gasoline consumed, and the maximum lead content of the gasoline. The leaded gas emission level obtained from multiplying these variables was then weighted with the urban population density to arrive at the final lead exposure measure. The market share of leaded gasoline and the maximum leadconcentration of the gasoline are rapidly changing in many countries of the world. Generally, countries are moving away from using leaded gasoline with high concentrations of lead to either gasoline with lower concentrations of lead or to all lead-free gasoline. Exceptions do occur, however. Between 1995 and 1997, Bulgaria increased its use of leaded gasoline from 87 to 95 percent (1). To estimate population density of urban areas, WRI combined a database that determines the builtup areas in countries from satellite images of city lights at night with data on urban population from the U.N. Population Division. The Nighttime Lights of the World database is a 1 kilometer by 1 kilometer resolution map derived from nighttime imagery from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) of the United States. This database contains the locations of stable lights, including frequently observed light sources such as gas flares at oil drilling sites. Time series analysis is used to exclude temporary light sources such as fires and lightning. Although the lights database provides the best available source for data on builtup areas for countries of the world, it may underestimate the builtup area for countries with densely populated but low-lit areas, such as squatter settlements. This type of underestimation could have the effect of showing an inflated value for exposure to leaded gasoline (the leaded gas would be emitted over a smaller, more densely populated area). However, WRI used the database because it is the best source of information for calculating a relative estimate of urban populations potentially exposed to leaded gas emissions. Water quality The water portion of the indicator for developing countries includes three variables: two represent potential exposure to poor quality water (i.e., percentage of the population without access to safe water and without adequate sanitation), and one represents exposure to insect-borne diseases (i.e., the percentage of the population with malaria). Data regarding access to safe water and adequate sanitation are problematic (as is often pointed out by UNICEF, the agency that publishes these data). Definitions of these situations may vary within and among countries over time; they may be based on descriptive reports of water sources or installed sewage systems, rather than on quantitative measures regarding water quality or distance to the facility for the population served. In addition, although WHO provides recommended values for distance to water supply and sanitation and for quantities available, countries revise these standards. For example, Brazil reports that only toilets on a sewage system are considered an adequate means of excreta disposal. Conversely, many sub-Saharan African countries report access to any kind of pit latrine as access to an adequate means of excreta disposal. References and notes 1. Magda Lovei, The World Bank, Washington, D.C., January 1998 (personal communication).