ORIGINAL RESEARCH
Pollution Characteristics of Polycyclic Aromatic
Hydrocarbons in Unsaturated Zone of the Different
Workshops at a Large Iron and Steel Industrial
Site of Beijing, China
More details
Hide details
1
School of Water Resources and Environment, China University of Geosciences, Beijing 100083, PR China
2
Capital Engineering & Research Incorporation Ltd., Beijing 100053, PR China
Submission date: 2020-01-01
Final revision date: 2020-06-07
Acceptance date: 2020-06-12
Online publication date: 2020-09-16
Publication date: 2020-11-10
Pol. J. Environ. Stud. 2021;30(1):781-792
KEYWORDS
TOPICS
ABSTRACT
The distribution, compositions, sources and ecological risk for polycyclic aromatic hydrocarbons
(PAHs) in industrial fields at a large iron and steel enterprise are discussed. Maximum ΣPAHs
concentrations in soils of different workshops ranged from 17.50 to 11266.80 mg·kg-1. The ΣPAHs
concentrations of the field could classify three categories due to different discharge ways and combustion
condition: >1000 mg·kg-1, 10-1000 mg·kg-1, <10 mg·kg-1. The spatial distribution of BaP concentration in
the coking topsoil was affected by fugitive emissions significantly. Peak values of PAHs occurred in
silt lens in 20-30 m depth indicated that pore size radius and conductivity of unsaturated zone played
a critical role in the vertical distribution. The strong linear correlation between the multiple organic
contaminants indicated that benzene series worked as co-solvents and competitors in unsaturated
zone to promote PAHs migration. Nap and Phe were the most abundant compounds in the coking and
coal stockyard sites, while Fla, BbF, Pyr, Phe and Chry predominated in other workshops affected by
different sources in which coal combustion was the primary source of PAHs. The calculated TEQ of the
coking site was found highest and BaP was the most concerning pollutant of the field since the values
accounted for 57.8-64.4% of total PAHs in the different workshops.
CONFLICT OF INTEREST
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
CITATIONS (5):
1.
Three-dimensional distribution characteristics of multiple pollutants in the soil at a steelworks mega-site based on multi-source information
Yixuan Hou, You Li, Huan Tao, Hongying Cao, Xiaoyong Liao, Xiaodong Liu
Journal of Hazardous Materials
2.
GeoAI-based 3D spatial distribution modeling of PAHs in industrial contaminated soils
Ruicong Zhang, Maogui Hu, Guoxing Ye, Chengdong Xu, Jinfeng Wang
Environmental Pollution
3.
An Adaptive Graph Convolutional Network with Spatial Autocorrelation for Enhancing 3D Soil Pollutant Mapping Precision from Sparse Borehole Data
Huan Tao, Ziyang Li, Shengdong Nie, Hengkai Li, Dan Zhao
Land
4.
Comprehensive prediction of soil benzo[a]pyrene content in Chinese coking enterprises from 2020-2040: an innovative full production cycle approach based on interpretable machine learning
Tienan Ju, Mei Lei, Hu-an Li, Andrew Zi Feng Xing, Guanghui Guo, Shaobin Wang
Journal of Cleaner Production
5.
A Simple Benzothiazole-Based Sensor for Rapid Recognition of Ferric Ion and its Application in Bioimaging and Hybridized Nanofibrous Film
Yaqiong Kong, Zhilong Zhang, Yuanyuan Cai, Zhiwen Zhao, Xiaoyu Zhang, Guoyou Cheng, Xiangzi Li, Duojun Cao
SSRN Electronic Journal