ArticleEnvironmental science and pollution research international2021
Pollution characteristics and human health risk assessments of toxic metals and particle pollutants via soil and air using geoinformation in urbanized city of Pakistan.
Article in Environmental science and pollution research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Analysis of PMEnvironmental toxicology · 2025Article
- Climate change and its environmental and health effects from 2015 to 2022: A scoping review.Heliyon · 2025Review
- Exploring the relationship between air quality and health shocks to the elderly: A retrospective cross-sectional study in China.Frontiers in public health · 2023Article
- Article
Corrections and comments
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Authors and funding
11 authors.
Funding
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Abstract
Toxic metals and particle pollutants in urbanized cities have significantly increased over the past few decades mainly due to rapid urbanization and unplanned infrastructure. This research aimed at estimating the concentration of toxic metals and particle pollutants and the associated risks to public health across different land-use settings including commercial area (CA), urban area (UA), residential area (RA), and industrial area (IA). A total of 47 samples for both soil and air were collected from different land-use settings of Faisalabad city in Pakistan. Mean concentrations of toxic metals such as Mn, Zn, Pb, Ni, Cr, Co, and Cd in all land-use settings were 92.68, 4.06, 1.34, 0.16, 0.07, 0.03, and 0.02 mg kg
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.