The remediation of contaminated sites necessitates robust and objective sustainability assessment frameworks to guide decision-making, yet prevailing methods often rely on qualitative or semi-quantitative metrics susceptible to subjectivity. This study establishes a comprehensive, fully quantitative evaluation system integrating environmental, economic, and social dimensions, comprising 13 objective indicators derived from Life Cycle Assessment (LCA), economic documentation, and publicly accessible social data—including nighttime light intensity, Point of Interest (POI) data, and social media sentiment analysis. The system employs the Analytic Hierarchy Process (AHP) for weight assignment, ensuring methodological rigor and expert consensus. Validated through three case studies of remediated contaminated sites in Shandong Province, China, the framework reveals distinct sustainability profiles: Site 1 achieved the highest composite score (0.1030), demonstrating balanced performance across all dimensions, whereas Sites 2 and 3 yielded negative scores (−0.2490 and −0.1069, respectively), reflecting trade-offs between remediation efficiency, secondary environmental impacts, and socio-economic outcomes. The key findings underscore the dominance of environmental health indicators—notably Disability-Adjusted Life Years (DALYs)—in overall weighting and highlight the critical influence of remediation technology selection on lifecycle impacts. The study validates the utility of a quantitative, multi-criteria approach in identifying optimal remediation strategies, facilitating cross-project comparability, and supporting the transition from cost-centric remediation toward value-driven, sustainable redevelopment.

Groundwater is the main source of drinking, irrigation, and ecological water in the Baiyangdian Lake Basin (BLB), but growing human activity has raised concerns about its quality. This study assesses major ion geochemistry and multi-receptor environmental risks across the BLB using 1113 groundwater samples (983 shallow, 130 deep). Risks to drinking water supply, agricultural irrigation, and wetland health are evaluated within a single framework, and Positive Matrix Factorization (PMF) is used for quantitative source apportionment. Shallow groundwater shows markedly higher dissolved solids and nitrate than deep groundwater, with 20.7% of shallow samples exceeding the WHO nitrate guideline. Multi-receptor assessment finds that 41.2% of shallow wells pose risk to at least one endpoint and 12.5% to two or more simultaneously. PMF identifies three sources—geogenic weathering, agricultural nitrate, and wastewater discharge—with nitrate as the largest single contributor to water quality impairment. The findings point to an urgent need for targeted agricultural non-point source control and provide a basis for nested, multi-scale groundwater management in the BLB and similar intensively exploited alluvial aquifers.