Environmental Impact and Remediation of Residual Lead and Arsenic Pesticides in Soil
Bibliographic record
Abstract
Chemical control of insects is considered one of the most beneficial developments of civilization (Klassen & Schwartz, 1983). As long ago as 1000 B.C., sulfur compounds were used to control insects in Asia Minor (National Academy of Science, 1969). However, the extensive use of chemicals to control pests has developed only in the last 150 years. The first example of large-scale effective chemical control of an insect pest occurred in 1867, with the use of Paris green (copper acetoarsenate) to control Colorado potato beetle, Leptinotarsa deecemlineata (Say). Paris green was later used to control codling moth, Laspeyresia pomonella (Linnaeus), on fruit trees (Klassen & Schwartz, 1983). Due to its effectiveness in controlling gypsy moth, Porthetria dispar (Linnaeus), lead arsenate replaced Paris green in New England in 1892. Lead arsenate was later used to control codling moth in apple, plum, and peach orchards (Klassen and Schwartz, 1983; Peryea, 1998a). This chapter will focus on the inorganic pesticide lead arsenate (PbHAsO4) and its effects on the environment. Both lead (Pb) and arsenic (As) have been used to produce a large number of chemical and manufactured products. Some of these products have been used in agriculture as defoliants, insecticides, and fungicides to control pests in apple, plum, and peach orchards, turf, vegetable crops, and on cattle. From the late 1800s to about 1947, lead arsenate was the most commonly used insecticide for control of codling moth in deciduous tree fruit orchards in countries throughout the world, including the USA, Australia, Canada, New Zealand, England, and France, because of its low cost, high efficiency, and low phytotoxicity (Focus, 2006; Peryea and Kammereck, 1997 and Shepard, 1951). The wide use of lead arsenate significantly increased its annual production during the early 1900s. Worldwide, lead arsenate production increased from 2,268 metric tons in 1908 to more than 41,000 metric tons in 1944. Even though the total amount of lead arsenate used on orchards is not known, this pesticide was applied frequently and at high application rates. Annual application rates as high as 215 kg Pb ha-1 and 80 kg As ha-1 were recommended for apple orchards (Peryea and Creger, 1994). Such high application rates helped minimize the development of resistant insects, a problem that farmers were facing with other insecticides. Moreover, the fact that lead arsenate has multiple sites of action made it unlikely that insect resistance could be achieved with single mutations (Georghiou, 1983). Lead arsenate was used as an insecticide until the introduction of the organochlorine dichlorodiphenyltrichloroethane (DDT) in the 1940s (Peryea 1998a; Wolz et al., 2003). However, lead arsenate continued to be used in some locations into the 1970s and was not officially banned until 1988 (Focus, 2006).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".