
Environmental Studies and Forestry
Urban-rural human settlements in China: Objective evaluation and subjective well-being
C. Fang, H. Ma, et al.
This study investigates the transformation of urban-rural settlements in China, revealing a remarkable enhancement in their quality over the last two decades. Conducted by Chuanglin Fang and colleagues, the research presents a compelling look at how satisfaction and well-being fluctuate across different regions and resident types. Join us to learn more about these insightful findings.
~3 min • Beginner • English
Introduction
Rapid socioeconomic development has intensified challenges in human settlements, including pollution, ecological degradation, and inadequate infrastructure. While research has traditionally centered on urban areas, recent work emphasizes integrating rural contexts and considering both objective environmental metrics and residents’ subjective well-being. In China, accelerated industrialization and urbanization have produced pronounced urban–rural disparities, making a comprehensive, integrated assessment urgent for achieving national goals such as urban–rural integration and the UN 2030 Agenda. This study asks how the quality of urban–rural human settlements has evolved over two decades across China, how residents’ subjective satisfaction aligns with objective conditions, and how spatial patterns differ by region and sub-dimension, with the aim to inform sustainable, people-centered settlement improvement.
Literature Review
Human settlements encompass material and non-material environments across urban and rural areas, integrating natural, social, living, and support systems. Foundational theories (Howard’s garden city, Geddes’ notion of area, Doxiadis’ Ekistics) and Chinese scholarship (Wu’s five-component framework) emphasize comprehensive, people-oriented, and environmentally harmonious development. Prior evaluations use multidimensional indices and methods such as entropy weighting, AHP, PCA, and SEM, often referencing frameworks like the UN SDGs. However, gaps remain: limited integration of objective indicators with subjective well-being, separation of urban and rural assessments, and narrow spatial scales focusing on specific cities or regions. Emerging studies incorporate residents’ satisfaction via surveys and fieldwork, revealing divergences between perceived and actual conditions and highlighting the need for integrated, large-scale, urban–rural evaluations that reflect both environmental quality and public satisfaction.
Methodology
Study scope and framework: The study evaluates China’s urban–rural human settlements across 31 provinces, autonomous regions, and municipalities over 2000–2019, using a four-dimension framework: environmental tidiness, environmental health, environmental amenity, and environmental support. Assessments combine objective indicators and subjective well-being.
Objective quality evaluation:
- Indicators (5): (1) Urban sewage treatment rate (%), (2) Harmless treatment rate of urban domestic waste (%), (3) Greening coverage rate in urban built-up areas (%), (4) Rural sanitary toilet penetration rate (%), (5) Rural per capita biomass index (kg; inverse relation to quality).
- Indicator rationale: Sewage and waste treatment gauge urban environmental governance; urban greening reflects livability; rural sanitary toilets indicate basic living conditions; per capita biomass proxies human ecological impact in rural areas (lower is better).
- Weighting: Upper/lower bounds set using national standards, plans, and advanced benchmarks. Indicators normalized into five levels (I–V). Weights derived via AHP supported by entropy using 1006 responses from an indicator-weight questionnaire. Reported weights: C1 0.2302, C2 0.2202, C3 0.1800, C4 0.1995, C5 0.1700.
- Standardization: Membership-degree method with five graded levels I–V mapped to 0–20, 20–40, 40–60, 60–80, 80–100. Positive/negative indicator formulas applied based on s-level intervals to produce standardized scores (x').
- Index calculation: Comprehensive quality index R computed through fuzzy membership and progressive weighted summation of the five standardized indicators using their weights. R graded into I (0–20), II (20–40), III (40–60), IV (60–80), V (80–100).
Subjective well-being evaluation:
- Instrument: Public Satisfaction Questionnaire APP for Quality Evaluation of Urban–Rural Human Settlements in China.
- Sampling: Pilot in Hebei; expert review; nationwide online distribution (July–October 2020); simple random sampling; provincial sample sizes targeted 0.5–1% of population. Valid samples: 551,783 across 31 regions; gender balance (males 270,373; females 281,410); age mainly 18–40 (44% aged 18–30; 46% aged 30–40); 70% with undergraduate/junior college; many in agriculture/forestry/fishery/water conservancy.
- Content: Part 1 resident attributes (gender, age, education, occupation, habitation). Part 2 satisfaction scores (0–100) on four indicators aligned with objective metrics (urban sewage, urban waste treatment, urban greening, rural sanitary toilets); per capita biomass excluded due to low public familiarity.
- Aggregation: Comprehensive satisfaction is the average of the four indicator scores. Satisfaction levels: highly unsatisfied (0–40), unsatisfied (40–60), average (60–75), satisfied (75–85), highly satisfied (85–100). 2020 satisfaction is used as subjective baseline corresponding to 2000–2019 assessments, reflecting cumulative perception.
Data sources:
- Urban sewage treatment: China Urban Construction Statistical Yearbook (2000–2018) and 2019 provincial data.
- Harmless treatment of urban domestic waste: China Statistical Yearbook (2000–2020).
- Urban greening coverage: China City Statistical Yearbook (2000–2005); China Statistical Yearbook (2006–2019).
- Rural sanitary toilet penetration: China Health Statistical Yearbook and China Rural Statistical Yearbook (2000–2019).
- Rural per capita biomass index: Peking University (Shu Tao’s group) dataset for prefecture-level cities (2000–2020).
Key Findings
- National improvement: The comprehensive quality index of urban–rural human settlements rose from 23.48 (2000) to 77.43 (2019), a 231.02% total increase; average annual growth 11.55%. Growth phases: 2000–2007 slow (level II), 2007–2019 faster (transition to level IV).
- Indicator trends: All indicators increased notably. By 2019, the standardized score for urban sewage treatment averaged 86.96 (avg annual growth 26.70%). Urban domestic waste harmless treatment improved steadily (avg annual growth 22.23%). Urban greening and rural sanitary toilet penetration increased with fluctuations. Rural per capita biomass index score rose from 34.42 (2000) to 76.73 (2019), implying reduced ecological pressure from human activity in rural areas.
- Spatial patterns (objective): Clear gradient decreasing from southeastern coastal to northwestern inland regions. In 2019, all provinces except Tibet reached medium-high (60–80) or high (80–100) levels; provinces with low levels in 2009 (20–40) decreased from 10 to 0 by 2019. Eastern provinces led with strong infrastructure and governance; northwest and northeast lagged due to harsher natural conditions and aging infrastructure but showed rapid recent improvements.
- Subjective satisfaction: National average satisfaction in 2020 was 80.09 (“Satisfied”). Twelve regions exceeded the national average. Highest: Beijing (88.64), Shandong (87.29), Guizhou (86.83), Guangxi (86.74), all “highly satisfied”. Lowest included Shanxi, Inner Mongolia, Chongqing, Anhui, Liaoning (around “average”). No clear east–west decline in subjective satisfaction.
- Determinants of satisfaction: Men reported higher satisfaction than women; younger respondents (<18) more often “satisfied/highly satisfied”, while those >70 more often “average/unsatisfied”. Higher-education (master’s+) responses were more polarized. Unemployed and manufacturing workers had higher dissatisfaction. Urban and rural satisfaction were similar (rural 65.13% “highly satisfied” vs. urban 63.25%), reflecting rural improvement initiatives.
- Objective–subjective relationship: Overall positive correlation. Regions categorized into H–H, H–L, L–H, L–L based on medians. H–H included Beijing, Jiangsu, Zhejiang, Shandong; L–L included Xinjiang, Gansu, Qinghai, Henan, Heilongjiang, Chongqing, Shanxi, Yunnan, Tibet. Notable divergences: higher subjective than objective in Guizhou, Hubei, Sichuan, Ningxia; opposite in Shanghai, Jiangxi, Guangdong, Hunan.
- Sub-dimension consistency: Stronger consistency between objective and subjective assessments for urban greening and rural sanitary toilets (most regions H–H or L–L). Weaker consistency for urban sewage and waste treatment; e.g., Inner Mongolia, Anhui, Liaoning had above-average objective sewage performance but lower satisfaction. Average satisfaction for rural sanitary toilets was relatively low at 76.43, indicating remaining infrastructure gaps.
Discussion
The findings indicate that while objective environmental quality has broadly improved, regional disparities persist, shaped by economic development, infrastructure capacity, and natural conditions. The overall positive correlation between objective quality and public satisfaction suggests that environmental improvements are generally perceived by residents, particularly for features closely tied to daily life (urban greening, rural toilets). However, divergences in sewage and waste treatment evaluations highlight perception gaps likely driven by service reliability, visibility, and local expectations.
Regional categorization underscores policy needs: H–H regions (e.g., Beijing, Jiangsu, Zhejiang, Shandong) can focus on refined management and smart-city upgrades; L–L regions (e.g., Xinjiang, Gansu, Qinghai, Henan, Heilongjiang, Chongqing, Shanxi, Yunnan, Tibet) require foundational investments in sanitation, drainage, and waste systems. Regions with higher satisfaction than objective scores (e.g., Guizhou, Hubei, Sichuan, Ningxia) may benefit from recent visible improvements or adjusted expectations, whereas the opposite pattern (e.g., Shanghai, Jiangxi, Guangdong, Hunan) suggests heightened public expectations outpacing objective gains.
Heterogeneous resident attributes influence satisfaction, implying that participatory planning and targeted communication are essential. Tailoring interventions to local contexts—water and greening in arid northwest, infrastructure in southwest mountainous areas, and urban renewal in northeast—can better align objective improvements with perceived well-being.
Conclusion
This study proposes and applies a comprehensive, large-scale framework integrating objective indicators and subjective well-being to evaluate China’s urban–rural human settlements (2000–2019). Key contributions include: (1) documenting substantial nationwide improvements with spatial patterns of higher quality in the East/South and lower in the West/North, though disparities have narrowed; (2) establishing that national satisfaction is at a “Satisfied” level (80.09) without a clear east–west gradient, and highlighting the role of resident attributes in shaping perceptions with similar satisfaction between urban and rural residents; (3) demonstrating a positive overall relationship between objective quality and satisfaction, with stronger alignment in urban greening and rural sanitary toilets than in sewage and waste treatment, and classifying regions into H–H, H–L, L–H, and L–L types to guide policy.
Future research should refine and expand the indicator system to capture broader environmental and social dimensions, conduct long-term follow-up to track evolving perceptions and outcomes, and further integrate public participation mechanisms to ensure that improvements meet diverse local needs and sustain residents’ well-being.
Limitations
The indicator system, constrained by national-scale data availability, does not fully capture the comprehensive conditions and nuanced needs of residents. The subjective evaluation relies on 2020 perceptions applied to 2000–2019 conditions, assuming cumulative perception stability. Some indicators (e.g., rural per capita biomass) were excluded from subjective assessment due to low public familiarity, limiting comparability across all dimensions. Regional heterogeneity in resources, environments, and development stages may affect both objective metrics and subjective expectations, influencing alignment between the two.
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