Dong Ying, He Xin-Lin, Zhang Ya-Ning, Wu Xi-Jun, Liu Jing, Zhang Fu-Chu, Zhao Jian
College of Water Conservancy & Architectural Engineering, Shihezi University, Shihezi 832003, China.
School of Civil Engineering, Yulin University, Yulin 719000, China.
Huan Jing Ke Xue. 2025 Jul 8;46(7):4285-4295. doi: 10.13227/j.hjkx.202406188.
Taking Kuye River， a typical river in the Yulin National Energy and Chemical Base as the research object， 16 polycyclic aromatic hydrocarbons （PAHs） concentrations were measured from 59 water samples collected in the dry and wet seasons. The seasonal distribution characteristics of PAHs were analyzed， and the positive definite matrix factorization model （PMF） was used to analyze the PAHs pollution sources. By combining PMF and the human health risk assessment model （HHR）， the PMF-HHR risk source quantitative analysis coupling model was established， and the contribution of various pollution sources to population health risk was calculated. The results showed that 10 and 16 PAHs were detected in the dry and wet seasons， respectively. The concentration of ∑PAHs in the dry season was higher than that in the wet season， and the ranges of ∑PAHs in the dry season were 54.36-369.94 ng·L， with an average value of 185.11 ng·L， and low ring （2-3 ring） PAHs was the dominant compound， accounting for 89.55% of ∑PAHs on average. During the wet season， the ranges of ∑PAHs were 50.06-278.16 ng·L， with an average value of 128.22 ng·L， mainly middle-low ring （2-4 ring） PAHs， of which the average proportion of low ring （2-3 ring） was 33.22%， and that of the middle ring （4 ring） was 51.41%. PAHs in the Kuye River analyzed by the PMF model mainly came from coking and petroleum emissions （37.39%）， coal combustion （34.78%）， traffic emission （14.40%）， and fuel-wood combustion （13.44%）. The coking and petroleum source and coal combustion source were the main factors affecting the PAHs concentration in the study area. The non-carcinogenic risk of PAHs in the study area could be ignored， but the carcinogenic risk exceeded the significant threshold by 2-5 times. The average contribution rate of pollution sources to carcinogenic risk by the PMF-HHR model was as follows： traffic emissions （36.75%） > coking and petroleum emissions （30.15%） > coal combustion （17.17%） > fuel-wood combustion （15.93%）. Traffic emission sources and BaP were priority control sources and monomer for PAHs carcinogenic risk in the Kuye River. The contribution of the same pollution source to the PAHs concentration and health risk was different. Quantitative analysis PAHs pollution source risk was the key to pollution mitigation and risk control in energy and chemical industry area. It is suggested that the risk source quantitative analysis model should be applied to environmental risk management to reduce human health risk more effectively.
以榆林国家能源化工基地典型河流窟野河为研究对象，测定了枯水期和丰水期采集的59个水样中16种多环芳烃（PAHs）的浓度。分析了PAHs的季节分布特征，并采用正定矩阵因子分解模型（PMF）分析PAHs污染源。通过将PMF与人体健康风险评估模型（HHR）相结合，建立了PMF-HHR风险源定量分析耦合模型，计算了各污染源对人群健康风险的贡献。结果表明，枯水期和丰水期分别检测到10种和16种PAHs。枯水期∑PAHs浓度高于丰水期，枯水期∑PAHs浓度范围为54.36～369.94 ng·L，平均值为185.11 ng·L，低环（2～3环）PAHs为优势化合物，平均占∑PAHs的89.55%。丰水期∑PAHs浓度范围为50.06～278.16 ng·L，平均值为128.22 ng·L，主要为中低环（2～4环）PAHs，其中低环（2～3环）平均占33.22%，中环（4环）平均占51.41%。利用PMF模型分析得出窟野河PAHs主要来源于焦化和石油排放（37.39%）、煤炭燃烧（34.78%）、交通排放（14.40%）和薪柴燃烧（13.44%）。焦化和石油源以及煤炭燃烧源是影响研究区域PAHs浓度的主要因素。研究区域PAHs的非致癌风险可忽略不计，但致癌风险超过显著阈值2～5倍。PMF-HHR模型计算的污染源对致癌风险的平均贡献率依次为：交通排放（36.75%）＞焦化和石油排放（30.15%）＞煤炭燃烧（17.17%）＞薪柴燃烧（15.93%）。交通排放源和苯并[a]芘是窟野河PAHs致癌风险的优先控制源和单体。同一污染源对PAHs浓度和健康风险的贡献不同。定量分析PAHs污染源风险是能源化工园区污染减排和风险控制的关键。建议将风险源定量分析模型应用于环境风险管理，以更有效地降低人体健康风险。
