SD Model Simulation for Resource-Based City Sustainable Development

What Are Resource-Based Cities?

• Definition: Urban centers dependent on natural resource extraction (e.g., coal, oil, minerals) for economic growth. Their industrial structures are often dominated by resource-intensive sectors .
• Challenges:
  1. Resource depletion: Over-reliance on finite resources leads to economic instability.
  2. Environmental damage: Pollution and habitat destruction from mining and processing .
  3. Social inequity: Job losses and reduced quality of life during industry downturns .

System Dynamics (SD) Models Explained

SD models simulate how variables like industrial output, pollution levels, and policy interventions interact over time. For example:

• Lvliang City Case Study: An SD model revealed that increasing environmental investment by 15% reduced carbon emissions by 20% without harming economic growth .
• Core Components:
  1. Feedback loops (e.g., pollution reducing tourism revenue).
  2. Time delays (e.g., lag between policy implementation and visible results).

Recent Discoveries and Case Studies

Industrial Restructuring in Huainan

Huainan, a coal-dependent city, shifted from a “two-three-one” (secondary-tertiary-primary) to a “three-two-one” industrial structure by investing in green technologies and services. This reduced coal reliance and improved air quality .

Digital Economy’s Role in Shaanxi

The digital economy boosted industrial upgrading in Shaanxi’s resource-based cities by enhancing innovation and energy efficiency. Policies like “civilized city” initiatives improved green total factor productivity by 12% .

Benxi’s Transformation

Benxi, a steel-producing city, reduced sulfur dioxide emissions by 40% through stricter environmental regulations and diversification into eco-tourism .

Data-Driven Insights

Table 1: Challenges Faced by Resource-Based Cities

Challenge	Example Cities	Impact
Resource depletion	Panjin (oil)	30% decline in oil reserves (2005–2015)
Pollution	Lvliang (coal)	25% increase in PM2.5 levels (2009–2019)
Social instability	Huainan (coal)	15% unemployment during coal crises

Table 2: SD Model Outcomes for Lvliang City

Policy Intervention	Economic Growth	Carbon Emissions	Energy Use
15% environmental investment	+3.5% GDP	-20%	-12%
Tech innovation subsidies	+5.1% GDP	-15%	-18%

Table 3: Success Factors in City Transformations

City	Strategy	Outcome
Benxi	Eco-tourism development	40% SO2 reduction
Huainan	Green industrial parks	30% coal dependency drop
Shaanxi	Digital economy policies	12% productivity gain

Strategies for Sustainable Development

Industrial Diversification:

• Develop non-resource sectors like tourism, tech, and services.
• Example: Huainan’s shift to a “three-two-one” industrial structure .

Policy Synergy:

• Combine environmental regulations with economic incentives (e.g., tax breaks for green tech).
• High-tech zones (HTZs) boosted innovation in 114 Chinese cities .

Community Engagement:

• Retrain workers for new industries and strengthen social safety nets .

Conclusion: Pathways to a Balanced Future

SD models are not just theoretical tools—they are lifelines for resource-based cities. By simulating scenarios like industrial shifts or pollution controls, cities can avoid costly mistakes and prioritize inclusive growth. China’s case studies demonstrate that sustainability is achievable through innovation, policy coherence, and community resilience. As the world urbanizes, these lessons will shape the future of cities everywhere.