Heavy metal pollution in indoor dust of residential, commercial, and industrial areas: a review of evolutionary trends

Abstract

Heavy metals (HMs) in indoor dust are among the most toxic micropollutants and have attracted mainly the attention of researchers in the last three decades concerning the environmental and human health perspectives. Hence, a thorough literature-based bibliometric analysis was inevitably needed to identify the research trend for the prevalence of HMs in indoor environments and their toxicological aspects. Accordingly, exploring publications on the Web of Science Core Collection database to identify the articles published on HM pollution in indoor dust environments revealed several peculiar findings. The review article indicates that the majority of studies conducted in this field are monitoring-based, utilizing “HMs (n = 79) ,” “contaminations (n = 49) ,” “lead (n = 49),” and “health” as primary keywords in the published articles. Among the countries, China emerged as the most active investigator in this area, followed by the USA, Middle East, Turkey, Korea, and India. Additionally, China has established collaborations with ~150 and >90 countries, respectively, solidifying its leading position in publications. Studies on HM pollution in indoor dust have evolved from initial exposure analyses in the 1990s to encompass bioavailability, bioaccessibility, exposure, risk assessment, speciation, and source apportionment assessments. Metal pollution in residential and commercial areas (schools/offices) primarily originates from in-house sources and vehicle emissions, while industrial areas, driven by anthropogenic activities (e-waste recycling/mining), face metal pollution from different sources. The analysis underscores that studies predominantly focus on risk assessment of significant metals, their bioaccessibility/bioavailability, and source apportionments. This study’s exploration of HMs in indoor dust provides explicit content and trends, offering valuable insights for researchers delving into this field. It not only suggests remedial measures but also contributes to the development of forecasting models.