Assessing Urban River Pollution Mitigation in Chongqing's Liangping District

Thesis Abstract

Urban river systems in rapidly expanding cities face intensified pollution pressures from industrial, domestic, and agricultural sources, with Chongqing’s Liangping District exhibiting concurrent rapid urbanization, agricultural runoff, and wastewater mismanagement that threaten ecological integrity and community health. This study investigates the effectiveness of pollution mitigation efforts in Liangping’s urban river network, addressing the gap between policy intentions and on-the-ground outcomes in a complex morpho- socio-technical setting. The aim is to evaluate current mitigation interventions, quantify pollution loads, and identify drivers of success and failure to inform targeted improvements. Specific objectives are to (i) quantify spatial and temporal trends of key pollutants (ammonium-nitrogen, total phosphorus, biochemical oxygen demand, and Escherichia coli) in five representative river segments over a 24-month period; (ii) assess the performance of existing interventions—urban green buffers, constructed wetlands, septic-tank upgrades, and informal waste disposal controls—using a quasi-experimental design; (iii) analyze stakeholder perceptions and institutional arrangements influencing implementation using a mixed-methods approach; (iv) model the relationship between mitigation measures, urbanization pressure, and water quality using multiple regression and time-series analyses; and (v) provide evidence-based recommendations for optimizing the Liangping District river pollution mitigation framework. The study adopts a mixed-methods research design grounded in a social-ecological perspective to capture biophysical and governance dimensions. The population comprises river segments within Liangping District, municipal agencies (water resources, environmental protection, urban planning), and local communities. A stratified random sample will select 5 river segments along the Liangping urban corridor, with 60 water quality monitoring events conducted quarterly across a 2-year period, yielding 300 datapoints for each pollutant. In addition, 40 key informants from municipal agencies and 120 household/facility surveys will be collected. Water samples will be analyzed in accredited laboratories following national standard methods for nutrient, organic pollution, and microbial indicators. Survey instruments will be designed to capture perceptions of pollution risk, legitimacy of interventions, compliance behavior, and perceived effectiveness. Data analysis will integrate quantitative and qualitative techniques. Descriptive statistics will summarize pollutant concentrations and trend patterns. Interrupted time-series analysis and difference-in-differences estimation will evaluate the impact of mitigation interventions, controlling for seasonal variability and rainfall. Multiple linear regression will identify predictors of water quality improvements, including intensity of interventions, urban density, and proximity to discharge sources. Geospatial analysis will map pollutant hotspots and intervention footprints. For qualitative data, thematic analysis will be applied to interview transcripts and open-ended survey responses to extract drivers of success, barriers to implementation, and recommendations from stakeholders. Theoretical framing will draw on the Institutional Theory of Pollution Control and the Environmental Kuznets Curve concept to interpret governance dynamics and pollution trajectories, complemented by the Theory of Planned Behavior to understand community compliance with waste management practices. Expected findings anticipate that integrated interventions—combining green infrastructure with upgraded wastewater management—will produce measurable reductions in nutrient loads and microbial indicators, particularly in segments with higher enforcement and community engagement. However, heterogeneity is expected, with weaker outcomes near informal settlements and areas lacking maintenance funding. The study will contribute to knowledge by providing a context-specific assessment of urban river pollution mitigation in a fast-developing Chinese district, illustrating how governance capacity, funding stability, and local participation interact with technical measures to determine outcomes. The practical implications include a clear attribution of intervention effectiveness, a prioritized set of action items for Liangping District authorities (e.g., scaling green buffers, improving operation and maintenance of constructed wetlands, and formalizing waste disposal), and a decision-support framework for adaptive management under variable rainfall. The main conclusion will articulate that an integrated, adaptive management approach—underpinned by robust maintenance regimes, transparent monitoring, and community co-management—offers the most reliable pathway to sustained river quality improvements in Liangping. Recommendations will emphasize (i) expanding and sustaining green infrastructure coupled with active wastewater upgrades; (ii) establishing a centralized data platform for monitoring with public access; (iii) formalizing stakeholder roles through binding municipal regulations; and (iv) implementing community-based education and incentive schemes to reduce improper waste disposal and enhance compliance.