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[MZZ51-05] Land-use Based Mapping of Lead Exposure Risk around a Former Mining Site in Zambia, using Lizard Biomonitoring Data.
Keywords:lead (Pb), Land-use, biomonitoring
Environmental pollution in urban areas is often thought to be a result of development activities. In these cases, the distribution of pollutants according to the distance from the pollution source is featured. However, even at points relatively far from the pollution source, changes in the surrounding ground surface conditions may increase the exposure opportunities for organisms. In regions in developing countries where environmental pollution has already occurred due to industrial activities before urbanization, land-use changes during city development activities should be paid attention to.
In Kabwe town in the Republic of Zambia, heavy metal pollution has been widespread due to lead and zinc mining activities that operated for nearly 100 years since the beginning of the 20th century, and the pollution continued even beyond the official cessation of industrial activities in 1994. In addition to environmental media such as soil and water, high concentrations of lead have also been detected in the biological media of humans, domestic animals, and wild rodents (Yabe et al. 2015, Nakata et al. 2017, Nakayama et al. 2011).
Mapping and modeling of environmental contaminants to account for differences in land-use are often used to identify sources of contamination. Inverse distance weighted (IDW) interpolation and Kriging interpolation which focus on the distance-dependent similarity between neighboring points (spatial autocorrelation) as described in Tobler's First Law of Geography are widely used in wide-area surveys of soil pollutants such as heavy metals (Hou et al., 2017). The Land-use regression (LUR) model, which uses data from monitoring sites, is also widely used for exposure risk assessment of air pollutants (Beelen et al., 2013).
On the other hand, biomonitoring using organisms as indicators has not yet been systematized in terms of mapping and risk assessment. The followings are the possible reasons: 1) organisms move around, 2) individual differences in exposure and accumulation, and 3) instability in the number of samples and points where they can be captured. We have studied the use of a species of wild lizards (Trachylepis wahlbergii, Scincidae) as a target organism for biomonitoring focusing on land-use. It is assumed that lizards are suitable for biomonitoring because they live in relatively small home ranges, their food is limited to insects, they are widely distributed from residential areas to grasslands and wastelands, and their density per point is relatively high. Our previous study has shown that the relationship between the amount of lead detected in lizards and the distance to the site varies depending on the land-use pattern based on satellite spectrum analysis. The concentrations of lead in the liver of lizards living in areas without vegetation were higher than assumed from the distance (Doya et al., 2020).
Here, we report an evaluation of the validity of land-use classification based on satellite spectrum data, and the possibility of risk simulation/mapping based on data of lead concentrations in lizards.
In Kabwe town in the Republic of Zambia, heavy metal pollution has been widespread due to lead and zinc mining activities that operated for nearly 100 years since the beginning of the 20th century, and the pollution continued even beyond the official cessation of industrial activities in 1994. In addition to environmental media such as soil and water, high concentrations of lead have also been detected in the biological media of humans, domestic animals, and wild rodents (Yabe et al. 2015, Nakata et al. 2017, Nakayama et al. 2011).
Mapping and modeling of environmental contaminants to account for differences in land-use are often used to identify sources of contamination. Inverse distance weighted (IDW) interpolation and Kriging interpolation which focus on the distance-dependent similarity between neighboring points (spatial autocorrelation) as described in Tobler's First Law of Geography are widely used in wide-area surveys of soil pollutants such as heavy metals (Hou et al., 2017). The Land-use regression (LUR) model, which uses data from monitoring sites, is also widely used for exposure risk assessment of air pollutants (Beelen et al., 2013).
On the other hand, biomonitoring using organisms as indicators has not yet been systematized in terms of mapping and risk assessment. The followings are the possible reasons: 1) organisms move around, 2) individual differences in exposure and accumulation, and 3) instability in the number of samples and points where they can be captured. We have studied the use of a species of wild lizards (Trachylepis wahlbergii, Scincidae) as a target organism for biomonitoring focusing on land-use. It is assumed that lizards are suitable for biomonitoring because they live in relatively small home ranges, their food is limited to insects, they are widely distributed from residential areas to grasslands and wastelands, and their density per point is relatively high. Our previous study has shown that the relationship between the amount of lead detected in lizards and the distance to the site varies depending on the land-use pattern based on satellite spectrum analysis. The concentrations of lead in the liver of lizards living in areas without vegetation were higher than assumed from the distance (Doya et al., 2020).
Here, we report an evaluation of the validity of land-use classification based on satellite spectrum data, and the possibility of risk simulation/mapping based on data of lead concentrations in lizards.