Characteristics of rural domestic sewage discharge and their driving mechanisms: evidence from the Northern Region, China

Highlights

● First to apply spatial autocorrelation analysis to rural domestic sewage discharge.

● In peri-urban areas, rural sewage discharge tends to exhibit high-high clustering.

● Social development is the most influential factor of rural sewage discharge level.

● Urbanization rate, education, and population age structure are influencing factors.

● The county level rural domestic sewage data set has been scientifically established.

Abstract

The traits of rural domestic sewage emission are unclear, negatively affecting rural domestic sewage treatment and sewage management. This study used data from the Second National Pollution Source Census Bulletin to establish a data set. The spatial distribution characteristics and main factors influencing rural sewage discharge in the Northern Region were studied using spatial autocorrelation analysis and structural equations. The findings demonstrated that (1) a significant Spearman correlation between drainage water volume (DWV), chemical oxygen demand (COD), ammonia nitrogen (NH₃-N), total nitrogen (TN), and total phosphorus (TP) and that the correlation coefficients between DWV and COD, NH₃–N, TN and TP were 0.87**, 1.0**, 0.99**, 0.99**, respectively; (2) rural sewage discharge showed spatial autocorrelation, and rural domestic sewage discharge in the districts and counties with an administration was significantly higher than in the surrounding areas; and (3) social development was the main driver rural domestic sewage changes (path coefficient was 0.407**), and the main factors influencing rural domestic sewage discharge were the urbanization rate, years of education, and population age structure. This study obtained the spatial variation law and clarified the main influencing factors of rural domestic sewage to provide data support and a theoretical basis for subsequent rural sewage collection and treatment. Use of the Inner Mongolia Autonomous Region in northern China as a typical case, provides a theoretical foundation for scientific decision-making on rural domestic sewage treatment at the national and regional levels and offers new perspectives for managing pollutants.

Graphical abstract

Keywords

Rural domestic sewage / Emission characteristics / Spatial autocorrelation analysis / Influencing factors

References

[1] Aberilla J M, Gallego-Schmid A, Stamford L, Azapagic A. (2020). Environmental assessment of domestic water supply options for remote communities. Water Research, 175: 115687

[2] Chen Y C. (2020). System dynamics evaluation of household water use behavior and associated greenhouse gas emissions and environmental costs: a case study of Taipei City. Journal of Water Process Engineering, 37: 101409

[3] Cheniti H, Cheniti M, Brahamia K. (2021). Use of GIS and Moran’s I to support residential solid waste recycling in the city of Annaba, Algeria. Environmental Science and Pollution Research International, 28(26): 34027–34041

[4] Deng G Y, Li L, Song Y N. (2016). Provincial water use efficiency measurement and factor analysis in China: based on SBM-DEA model. Ecological Indicators, 69: 12–18

[5] Department of Ecology and Environment of Inner Mongolia Autonomous Region(2022). Progress of comprehensive environmental improvement in rural and pastoral areas of the entire region, 2021. Available online at the website of sthjt.nmg.gov.cn (accessed May 10, 2023)

[6] Dikbas F. (2018). A new two-dimensional rank correlation coefficient. Water Resources Management, 32: 1539–1553

[7] Duan N, Xiong J M, Feng Q, Wang L H, Yang F, Ding H. (2023). Special rural sewage treatment plan in Jiangxia district, Wuhan City, China. Sustainability, 15(3): 1764

[8] Elith J, Leathwick J R. (2009). Species distribution models: ecological explanation and prediction across space and time. Annual Review of Ecology Evolution and Systematics, 40: 677–697

[9] Gao Y X, Yu J H, Song Y Z, Zhu G W, Paerl H W, Qin B Q. (2019). Spatial and temporal distribution characteristics of different forms of inorganic nitrogen in three types of rivers around Lake Taihu, China. Environmental Science and Pollution Research, 26: 6898–6910

[10] Hou F, Zhang T, Peng Y Z, Cao X X, Pang H T, Shao Y Q, Lu X C, Yuan J, Chen X, Zhang J. (2022). Partial anammox achieved in full scale biofilm process for typical domestic wastewater treatment. Frontiers of Environmental Science & Engineering, 16(3): 33

[11] Huang Y, Li P, Li H, Zhang B, He Y. (2021). To centralize or to decentralize? A systematic framework for optimizing rural wastewater treatment planning. Journal of Environmental Management, 300: 113673

[12] Ju H Q, Chen J, Xu J W, Zhang H X. (2022). How do non-agricultural employment and regional selection affect farmers’ domestic sewage discharge behavior? Empirical evidence from rural China. International Journal of Environmental Research and Public Health, 19(17): 10694

[13] Latrach L, Ouazzani N, Hejjaj A, Mahi M, Masunaga T, Mandi L. (2018). Two-stage vertical flow multi-soil-layering (MSL) technology for efficient removal of coliforms and human pathogens from domestic wastewater in rural areas under arid climate. International Journal of Hygiene and Environmental Health, 221(1): 64–80

[14] Liu S H, Zhang X, Zhou Y F, Yao S B. (2021a). Spatiotemporal evolution and influencing factors of carbon sink dynamics at county scale: a case study of Shaanxi Province, China. International Journal of Environmental Research and Public Health, 18(24): 13081

[15] Liu X C, Zhang M D, Zhou W Y, Zhang J, Deng S H. (2020). A path analysis for chemical oxygen demand and ammonia nitrogen discharge from industrial sewage in China. Water Resources, 47(6): 1012–1019

[16] LiuYDuJ DingBLiu YLiuWXiaAHuoR RanQHaoY CuiX, . (2021b) Water resource conservation promotes synergy between economy and environment in China’s northern drylands. Frontiers of Environmental Science & Engineering, 16(3): 28

[17] Malakar K, Lu C H. (2021). Measuring sustainability as distance to ideal position of economy, society and environment: application to China’s provincial water resources (2004-17). Journal of Environmental Management, 292: 112742

[18] Massoud M A, Tarhini A, Nasr J A. (2009). Decentralized approaches to wastewater treatment and management: applicability in developing countries. Journal of Environmental Management, 90(1): 652–659

[19] Ministry of Housing and Urban-Rural Development of the People’s Republic of China (2021) The Statistical Yearbook of Urban and Rural Construction. 2021. vailable online at the website of mohurd.gov.cn (accessed May 3, 2023)

[20] Monti F, Stewart D, Surendra A, Alecu I, Nguyen-Tran T, Bennett S A L, Cuperlovic-Culf M. (2023). Signed Distance Correlation (SiDCo): an online implementation of distance correlation and partial distance correlation for data-driven network analysis. Bioinformatics, 39: btad210

[21] Mühlbach G, Reimers L. (1987). Linear extrapolation by rational functions, exponentials and logarithmic functions. Journal of Computational and Applied Mathematics, 17(3): 329–344

[22] Okadera T, Watanabe M, Xu K Q. (2006). Analysis of water demand and water pollutant discharge using a regional input-output table: an application to the City of Chongqing, upstream of the Three Gorges Dam in China. Ecological Economics, 58: 221–237

[23] Rong Y, Zhang Y, Sun Z, Liu Z, Jin X, Jin P. (2023). Characteristics of rural sewage discharge and a case study on optimal operation of rural sewage treatment plant in Shaanxi, China. Chemical Engineering Journal, 453: 139853

[24] Sun H, Tian Y, Li L, Meng Y, Huang X, Zhan W, Zhou X, Cai G. (2022). Anthropogenic pollution discharges, hotspot pollutants and targeted strategies for urban and rural areas in the context of population migration: numerical modeling of the Minjiang River basin. Environment International, 169: 114912

[25] Thomas F M, Vesk P A, Hauser C E. (2018). A field ecologist’s adventures in the virtual world: using simulations to design data collection for complex models. Ecological Applications, 28: 2130–2141

[26] Treiblmaier H, Bentler P M, Mair P. (2011). Formative constructs implemented via common factors. Structural Equation Modeling, 18(1): 1–17

[27] Usami S. (2021). On the differences between general Cross-Lagged Panel Model and Random-Intercept Cross-Lagged Panel Model: interpretation of Cross-Lagged parameters and model choice. Structural Equation Modeling, 28(3): 331–344

[28] Wang C, Feng B, Wang P, Guo W, Li X, Gao H, Zhang B, Chen J. (2022). Revealing factors influencing spatial variation in the quantity and quality of rural domestic sewage discharge across China. Process Safety and Environmental Protection, 162: 200–210

[29] Wang R J, Wang Q B, Dong L S, Zhang J F. (2021). Cleaner agricultural production in drinking-water source areas for the control of non-point source pollution in China. Journal of Environmental Management, 285: 112096

[30] Wei H R, Zhang Y, Xiu P S, Zhang H F, Zhu S K. (2022). Index-based analysis of industrial structure and environmental efficiency based on sewage discharge assessment in China. Alexandria Engineering Journal, 61: 493–500

[31] Wei K L, Wang W L, Fahad S. (2023). Spatial and temporal characteristics of rural livability and its influencing factors: implications for the development of rural revitalization strategy. Environmental Science and Pollution Research, 30: 49162–49179

[32] Wu X H, Yue B, Huang Q F, Wang Q, Li Z L, Wang Y T, Yu J Y. (2018). Investigation of the physical and chemical characteristics of rural solid waste in China and its spatiotemporal distributions. Environmental Science and Pollution Research International, 25(18): 17330–17342

[33] Wu Z N, Jiang M M, Wang H L, Di D Y, Guo X. (2022). Management implications of spatial-temporal variations of net anthropogenic nitrogen inputs (NANI) in the Yellow River Basin. Environmental Science and Pollution Research International, 29(35): 52317–52335

[34] Xu Y, Li H Y, Li Y, Zheng X Q, Zhang C X, Gao Y, Chen P Z, Li Q, Tan L. (2022). Systematically assess the advancing and limiting factors of using the multi-soil-layering system for treating rural sewage in China: from the economic, social, and environmental perspectives. Journal of Environmental Management, 312: 114912

[35] Yan Y, Zhang Y J, Fan B, Yang M, Cai L, Fu X, Liu X, Hou J W. (2011). Estimation and spatial analysis of water pollution loads from towns in China. International Journal of Sustainable Development and World Ecology, 18(3): 219–225

[36] Yao J, Fan M, Xiao Y T, Liang X Y, Cai C, Wang Y Z. (2023). Spatial-temporal characteristics of corrected total phosphorus pollution loads from agricultural non-point sources in Tuojiang River watershed, Sichuan Province of southwestern China. Environmental Science and Pollution Research International, 30(14): 42192–42213

[37] Yao T, Wei Y G, Zhang J H, Wang Y N, Yu Y J, Huang W Y. (2022). What influences the urban sewage discharge in China? The effect of diversified factors on the urban sewage discharge in different regions of China. Environment, Development and Sustainability, 24(5): 6099–6135

[38] Yin X W, Feng Q, Zheng X J, Zhu M, Wu X, Guo Y, Wu M, Li Y. (2021). Spatio-temporal dynamics and eco-hydrological controls of water and salt migration within and among different land uses in an oasis-desert system. Science of the Total Environment, 772: 145572

[39] Zhang X H, Cao J, Li J R, Deng S H, Zhang Y Z, Wu J. (2015). Influence of sewage treatment on China’s energy consumption and economy and its performances. Renewable & Sustainable Energy Reviews, 49: 1009–1018

[40] Zhang Y, Bi P, Hiller J E. (2010). Climate variations and Salmonella infection in Australian subtropical and tropical regions. Science of the Total Environment, 408: 524–530

[41] Zhao H X, Cui J X, Wang S F, Lindley S. (2018). Customizing the coefficients of urban domestic pollutant discharge and their driving mechanisms: evidence from the Taihu Basin, China. Journal of Environmental Management, 213: 247–254

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 51838013), the project of Inner Mongolia “Prairie Talents” Engineering Innovation Entrepreneurship Talent Team, and the Innovation Team of the Inner Mongolia academy of Science and Technology (No. CXTD2023-01-016).

Conflict of Interests

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

RIGHTS & PERMISSIONS

2024 Higher Education Press