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<p>With rapid urban construction, economic development, and population growth, groundwater quality has become an important factor limiting the sustainable development of Chengdu. In particular, nitrate and nitrite accumulation in the human body may cause adverse health effects. Because the sources and transformation processes of inorganic nitrogen in groundwater are complex, accurately identifying its origin is essential for the effective and sustainable management of groundwater resources. In this study, hydrochemical analysis, a self-organizing neural network (SOM), principal component analysis (PCA), the absolute principal component score–multiple linear regression (APCS-MLR) model, and positive matrix factorization (PMF) were combined to quantitatively distinguish the influences of natural and anthropogenic factors on groundwater quality. The results showed that mean nitrogen concentrations measured 2.59&#xa0;mg L⁻1 (NO₃⁻-N; 2.44% exceeding GB/T 14848–2017 Class III limits), 0.1&#xa0;mg L⁻1 (NH₄⁺-N; 6.1% exceedance), and 0.02&#xa0;mg L⁻1 (NO₂⁻-N). SOM clustering revealed that most samples in clusters 1–3 were strongly influenced by geological background, indicating a significant natural control on groundwater chemistry. PCA-APCS-MLR results further revealed several major sources, including evaporite dissolution (31.63%), reduction (13.02%), domestic pollution (9.17%), silicate dissolution (32.15%), and unidentified sources (14.03%), with natural sources contributing a total of 76.81%. Domestic pollution was the dominant contributor to NO₃⁻–N (38.85%), whereas reduction processes mainly controlled NH₄⁺–N (49.72%). PMF analysis also identified multiple influencing factors, including water–rock interaction (32.28%), domestic pollution (11.51%), reduction (16.01%), waste leachate (20.68%), and soil dissolution (19.52%). Natural sources accounted for 67.81% of the overall impact, while anthropogenic activities still exerted a considerable influence (32.19%). Overall, natural factors were identified as major sources influencing hydrochemical components. Domestic pollution was the major contributor to NO₃⁻–N, whereas NH₄⁺–N was predominantly derived from natural processes associated with water–rock interaction and reduction. This combined approach more accurately reflects the hydrogeochemical conditions of the basin and provides a scientific basis for groundwater protection and environmental management.</p>

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Source apportionment of inorganic nitrogen in shallow groundwater in the Chengdu plain area based on multiple quantitative and qualitative methods

  • 期刊论文

  • 发表日期：

    2025年12月22日

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  • Liu Hao,
  • Liu Yong,
  • Sun Hongzhi,
  • Huang Huan,
  • Liu Yanming

摘要

With rapid urban construction, economic development, and population growth, groundwater quality has become an important factor limiting the sustainable development of Chengdu. In particular, nitrate and nitrite accumulation in the human body may cause adverse health effects. Because the sources and transformation processes of inorganic nitrogen in groundwater are complex, accurately identifying its origin is essential for the effective and sustainable management of groundwater resources. In this study, hydrochemical analysis, a self-organizing neural network (SOM), principal component analysis (PCA), the absolute principal component score–multiple linear regression (APCS-MLR) model, and positive matrix factorization (PMF) were combined to quantitatively distinguish the influences of natural and anthropogenic factors on groundwater quality. The results showed that mean nitrogen concentrations measured 2.59 mg L⁻1 (NO₃⁻-N; 2.44% exceeding GB/T 14848–2017 Class III limits), 0.1 mg L⁻1 (NH₄⁺-N; 6.1% exceedance), and 0.02 mg L⁻1 (NO₂⁻-N). SOM clustering revealed that most samples in clusters 1–3 were strongly influenced by geological background, indicating a significant natural control on groundwater chemistry. PCA-APCS-MLR results further revealed several major sources, including evaporite dissolution (31.63%), reduction (13.02%), domestic pollution (9.17%), silicate dissolution (32.15%), and unidentified sources (14.03%), with natural sources contributing a total of 76.81%. Domestic pollution was the dominant contributor to NO₃⁻–N (38.85%), whereas reduction processes mainly controlled NH₄⁺–N (49.72%). PMF analysis also identified multiple influencing factors, including water–rock interaction (32.28%), domestic pollution (11.51%), reduction (16.01%), waste leachate (20.68%), and soil dissolution (19.52%). Natural sources accounted for 67.81% of the overall impact, while anthropogenic activities still exerted a considerable influence (32.19%). Overall, natural factors were identified as major sources influencing hydrochemical components. Domestic pollution was the major contributor to NO₃⁻–N, whereas NH₄⁺–N was predominantly derived from natural processes associated with water–rock interaction and reduction. This combined approach more accurately reflects the hydrogeochemical conditions of the basin and provides a scientific basis for groundwater protection and environmental management.