Day 3 · Systems Interventions for a Green Chizhou

01 · The mission

One intervention. One system. One executable proposal.

A proposal passes only if it clears all four bars.

🏛️

Local

Rooted in a real Chizhou / Anhui need, backed by ≥ 2 cited local facts.

在地

🔄

Systemic

Names the feedback loop it shifts and the leverage point it targets.

系统

📅

Executable

An owner, a 12-month pilot, a budget and SMART KPIs.

可执行

🎓

Cross-disciplinary

Uses every discipline at the table — science, engineering, humanities, business.

跨学科

Fully open each group defines its own topic University education Research Policy advice Workforce preparation Upskilling / reskilling Tech innovation & adoption Entrepreneurship ecosystem …or a mix

Choose your arena — the intervention field is fully open; groups may also combine arenas.

Agenda · three hours, three sprints, five pitches

Time	Block	Output
0:00–0:20	Frame — mission & local context	Slides 03–07
0:20–0:45	Toolkit — iceberg · loops · leverage · stakeholders	Slides 08–12
0:45–0:55	Cases & local sparks	Slides 13–14
0:55–1:25	Sprint 1 · Diagnose — iceberg + causal loop	30 min
1:25–1:35	Break	10 min
1:35–2:05	Sprint 2 · Design — leverage point, stakeholders, canvas	30 min
2:05–2:30	Sprint 3 · Deliver — logic model, roadmap, budget, KPIs	25 min
2:30–2:55	Pitches — 5 groups × 5 min	Slide 19
2:55–3:00	Wrap & next steps	Slide 20

02–05 · Context · Pillar 3

The signal is clear — and it names universities

National targets, provincial momentum, city assets: every proposal has to plug into all three.

🇨🇳 National

2030 / 2060

Carbon peak before 2030 · neutrality before 2060

>65% cut in CO₂ per unit GDP by 2030 vs 2005
~25% non-fossil share of primary energy by 2030
~7.3 M renewable-energy jobs in China in 2024 — 44% of the world total (IRENA)
MoE · April 2022 · 教高函〔2022〕3号 — Work Plan for Carbon-Peak & Carbon-Neutrality Talent Training in Higher Education: modern industry colleges & future-technology colleges; dual-carbon industry–education alliances; shortage fields in storage, hydrogen, CCUS, carbon finance, carbon management, carbon markets
≥3 M industrial workers funded for further education & skills upgrading by 2030 (All-China Federation of Trade Unions)

安徽省 Anhui Province

1.79 M

NEV output 2025 — national No. 1 (0.105 M in 2020 → 1.68 M in 2024 → ~15× growth)

By 2025: ≥15.5% non-fossil energy share · energy intensity −14% vs 2020
By 2030: ≥22% non-fossil share · CO₂/GDP −65% vs 2005
Industrial sub-plan: clusters in NEV, PV equipment, robotics; upstream and downstream suppliers encouraged to relocate together
Green demo parks: circular chains built by “horizontal coupling, vertical extension”

池州 Chizhou City

¥122.5 bn

GDP 2025 (+5.3%) · sector ratio 2024 — 8.64 : 42.49 : 48.87

Semiconductors: >¥30 bn cluster, 130+ up- & downstream firms in Chizhou ETDZ
Ecosystem value (GEP) 2024: ¥477.62 bn — catalogue of 3 classes · 116 types · 538 sub-types
Chizhou ETDZ — national low-carbon industrial park pilot; city → province → national green-factory ladder
Shitai · Hongye bamboo — first city-level forest-carbon-ticket zero-carbon factory (260 t tickets offset)
LFP materials 80,000 t/yr · 9 M Mg-alloy plates/yr
Jiuhua Mountain, tea & eco-tourism — 5A site, ~7,300 mu alpine tea, 22 tea co-ops

⚠️

To verify (待核实): Chizhou’s municipal carbon-peak plan (池州市碳达峰实施方案) could not be retrieved — groups citing city targets must confirm them on chizhou.gov.cn first.

Sources: gov.cn white paper; NDRC Action Plan for CO₂ Peaking Before 2030; UNFCCC NDC; moe.gov.cn (2022); IRENA Renewable Energy & Jobs; cnfocus.com; China Daily; ccn.ac.cn; chizhou.gov.cn (2024 bulletin; GEP release 1732730); hongheiku 2025 bulletin; czkfq.investchn.com; forestry.gov.cn; ah.people.com.cn; 12371.cn.

06 · Your starting assets

Chizhou University is already in the game

Best proposals scale what exists — they don’t start from zero.

🏫

Applied undergraduate university

Since 2007, led by engineering & management, ~54 undergraduate programmes.

💠

School of Mechanical & Electrical Eng. = School of Semiconductors

A direct institutional link to the city’s flagship cluster.

🌱

“Carbon Neutrality & Green Energy” micro-major

Materials & Environment Engineering — targets carbon-verification, carbon-asset management and new-energy O&M roles.

📊

Digital carbon accounting · national faculty training host (2025)

Business School micro-major + modern industry college. Carbon finance and accounting are named national shortage fields (MoE 2022).

🍵

Tea-themed industry–education integration

Tourism, History & Culture College — scenario-based tea-service modules with hospitality employers.

＋

Also on the bench

Big Data & AI · Geography & Planning · Literature & Media · Foreign Languages · Arts & Education.

Sources: czu.edu.cn (xxjj; jgsz); hxx.czu.edu.cn/6053; jmx.czu.edu.cn/5268; lyxy.czu.edu.cn/10055.

Part two · The systems toolkit

Four tools, used in order

Each one produces an artefact that goes straight onto your proposal canvas. Senge · Meadows · Mendelow · Kellogg Foundation.

Events — REACT · What recent headline, complaint or data point made this issue visible in Chizhou?
Patterns — ANTICIPATE · What has repeated over 3–5 years? Show it with a trend, not an anecdote.
Structures — DESIGN · Which rules, incentives, budgets, curricula or information flows produce that pattern?
Mental models — TRANSFORM · What do students, firms, officials and we as faculty assume that keeps it in place?

Output → one sentence per level on the canvas (canvas box 02).

Source: Senge, The Fifth Discipline (1990); Center for Systems Awareness, Iceberg handout (2020).

Illustrative template — a green-skills reinforcing loop (R1): local green-skilled graduates → firms adopting green tech → demand & co-funding for training → university green programmes → more local green-skilled graduates.

Where is the balancing loop (B) that stalls it? e.g. talent outflow, budget cap, delay in accreditation.

1 · List 5–8 variables that can go up or down (nouns, not actions).
2 · Link them with arrows: + same direction, − opposite.
3 · Label each loop R (reinforcing) or B (balancing).
4 · Mark delays with ‖ — they explain why fixes seem to fail.
5 · Circle the one link your intervention will change.

Sources: The Systems Thinker, “Causal Loop Construction: The Basics”; UNDP Evaluation Methods Center; Cascade Institute CLD Handbook (2024). Template loop is illustrative.

Shallow · parameters & flows — 12 constants, parameters, numbers (e.g. subsidy size) · 11 buffer sizes · 10 structure of stocks & flows.

Middle · feedback & information — 9 lengths of delays · 8 strength of balancing loops · 7 gain of reinforcing loops · 6 structure of information flows (who can see what data).

Deep · rules, goals, paradigms — 5 rules of the system (incentives, assessment, credentials) · 4 power to self-organise · 3 goals of the system · 2 mindset / paradigm · 1 power to transcend paradigms.

🎯

The university’s sweet spot: universities are strongest at 6 · information, 5 · rules (curricula, credentials), 4 · self-organisation (alliances) and 3 · goals. Name your level — and defend it.

Source: D. Meadows, “Leverage Points: Places to Intervene in a System” (1999), donellameadows.org; Abson et al., Ambio (2016).

Manage closely (high power · high interest): university leadership · Chizhou ETDZ management · municipal government / DRC · anchor firms in your target cluster.
Keep satisfied (high power · low interest): provincial DRC / Education Dept · county governments · large anchor firms outside your sector.
Keep informed (low power · high interest): students & faculty · workers & trade unions · SMEs, co-ops, NTU partners.
Monitor (low power · low interest): general public, media · peer universities in Anhui.

Group task: place 8–12 named actors on the grid · for each “manage closely” actor, say what they gain · who could block it, and your mitigation · name the one champion you’ll meet in the next 30 days.

Placements are typical starting points — re-map for your own case. Source: Mendelow power–interest grid, via Mind Tools “Stakeholder Analysis” and NN/g “Stakeholder Analysis for UX Projects”.

11 · Case gallery

Eight models you can borrow from

Ask of every case: what did they change — a rule, an information flow, a goal?

🔬

Tsinghua · Institute for Carbon Neutrality

China · research. Est. Sept 2021: innovation centre, think tank, talent base and international platform in one.

🤝

UNEP–Tongji Institute (IESD)

China · partnership. A UN partnership since 2002, pairing degree programmes with applied policy research.

🎓

Carbon-Neutrality Future Tech Colleges

China · education. China University of Petroleum · Beijing University of Technology — integrated bachelor–master–PhD tracks, e.g. a 2024 energy-storage cohort.

🏙️

AUST · Low-Carbon & Carbon-Finance Lab

Anhui · peer. A nearby peer scaling carbon finance through the MoE 2024 batch.

🌏

SJTU · China-UK Low Carbon College

Sino-foreign. A multi-disciplinary low-carbon college with the University of Edinburgh.

🍃

NTU EcoCampus

Singapore · campus. Target of −35% energy, water and waste by 2020, using digital-twin retrofits — the campus as a living lab.

🇪🇺

Pact for Skills · Renewables

EU · reskilling. Industry, training providers and regions jointly commit to up- and reskilling.

🌉

Community-college clean-energy bridges

US · workforce. E.g. Richland’s 8-week bridge programme, and EV technician training at Olive-Harvey College.

Sources: tsinghua.edu.cn; unep-iesd.tongji.edu.cn; cup.edu.cn; bjut.edu.cn; sciencenet.cn; sustain.org; iesve.com; ec.europa.eu Pact for Skills; richland.edu; knkx.org.

💠

Semiconductor industrial college

Anchor: >¥30 bn cluster, 130+ firms; the School of Mechanical & Electrical Eng. is also the School of Semiconductors.

Leverage 5 · rules

🌳

GEP & forest-carbon-ticket lab

Anchor: ¥477.62 bn GEP catalogue, and the first city-level carbon-ticket zero-carbon factory (Shitai).

Leverage 6 · information

🏭

ETDZ zero-carbon park partner

Anchor: a national low-carbon industrial park pilot with a 3-tier green-factory ladder. The university acts as verifier and talent hub.

Leverage 6 · information

🔋

Battery-materials upskilling

Anchor: an 80,000 t LFP-materials project, Mg-alloy plate capacity, and the existing carbon-neutrality micro-major.

Leverage 4 · self-organisation

🚗

NEV supply-chain bridge programme

Anchor: Anhui is No. 1 in NEVs (1.79 M in 2025); local lines make 5 M rail and NEV parts per year.

Leverage 9 · delays

🍵

Low-carbon Jiuhua tea & tourism

Anchor: ~7,300 mu of alpine tea, 22 co-ops and 九华黄精 GI; builds on the existing tea-hospitality modules.

Leverage 3 · goals

🎋

Bamboo circular-economy lab

Anchor: Hongye bamboo-straw value chain; EMF circular-design pedagogy.

Leverage 10 · stocks & flows

✊

Chizhou Green Skills Pact

Anchor: ACFTU’s ≥3 M worker reskilling target; EU Pact for Skills model; micro-credentials co-funded by firms.

Leverage 4 · self-organisation

Sources: see slides 04–07 — chizhou.gov.cn, czkfq.investchn.com, forestry.gov.cn, ah.people.com.cn, 12371.cn, english.news.cn.

13 · One-page proposal canvas

Twelve boxes. Three sprints. One page.

Group __ · Title ______________ — fill 01–03 in Sprint 1, 04–08 in Sprint 2, 09–12 in Sprint 3.

01

Problem & evidence

Which local problem? Include ≥ 2 cited facts.

02

System diagnosis

Iceberg (4 lines) plus the key R/B loop.

03

Leverage point

Meadows level # and why it beats a shallower fix.

04

The intervention

What exactly will the university do? One sentence plus 3 components.

05

Beneficiaries

Who benefits, how many, and where?

06

Stakeholders & champion

“Manage closely” actors, blockers, and a named champion.

07

Disciplines at work

What do science, engineering, humanities and business each contribute?

08

Policy fit

Which national, Anhui or Chizhou policy does it serve?

09

Logic model

Inputs → activities → outputs → outcomes → impact.

10

12-month roadmap

4 quarterly milestones and one owner each.

11

Budget & funding

Main cost lines and who co-funds.

12

KPIs & risks

3 SMART KPIs · top 2 risks and mitigations.

14–15 · Theory of change · roadmap · budget · KPIs

Executable means dated, owned, costed, measured

“If we do this, then that changes — because…” Every arrow hides an assumption; test your two riskiest first in the pilot.

1

Inputs

People · money · assets.

2

Activities

What we do.

3

Outputs

What we deliver (countable).

4

Outcomes

What changes (1–3 yrs).

5

Impact

System-level shift.

Illustrative example · Semiconductor industrial college — numbers are placeholders, not targets

1

Inputs — 6 faculty + 4 firm engineers · shared cleanroom-lite lab · co-funding from ETDZ firms.

2

Activities — co-design 3 modules on green packaging & energy efficiency · semester-long placements.

3

Outputs — [N] students certified · [N] firm energy audits · 1 micro-credential.

4

Outcomes — higher local hiring of graduates · measured kWh savings in partner firms.

5

Impact — the cluster grows greener with local talent: loop R1 turns on.

“Because…” — write your assumptions. e.g. “firms will co-fund if graduates cut their onboarding time.” Test your two riskiest assumptions first in the pilot.

Q1

Mobilise · months 1–3

Sign MoU with the champion, form the team, collect baseline data.

Q2

Pilot · months 4–6

Run the first cohort, module or audit, and test the two riskiest assumptions.

Q3

Iterate · months 7–9

Hold a mid-point review and adjust the design; add a second partner.

Q4

Scale decision · months 10–12

Report KPIs, apply for provincial or MoE funding, and decide go / adapt / stop.

Budget template

People (faculty time, RAs) — ¥ ____
Equipment & lab — ¥ ____
Training delivery & materials — ¥ ____
Outreach & evaluation — ¥ ____

Co-funders: university · firms · city / ETDZ · province / MoE.

SMART KPIs

S · M · A · R · T — specific, measurable, achievable, relevant, time-bound. Sentence templates; your group sets the numbers.

Output — “40 technicians complete the micro-credential by Month 9.”
Outcome — “3 partner firms cut measured kWh/unit by 5% by Month 12.”
System — “Co-funding ratio from firms ≥ 30% of year-2 budget.”

Sources: W.K. Kellogg Foundation, Logic Model Development Guide; BetterEvaluation; La Piana, “Theory of Change or a Logic Model?”. Evaluation lens: OECD DAC criteria (oecd.org/dac/results-evaluation). The example is illustrative.

16 · Group sprints & roles

Six people. Six roles. Three timed sprints.

Sprint 1 · 30 min · Diagnose

5

Agree the problem (5 min)

10

Iceberg, four levels (10 min)

15

Draw the causal loop (15 min)

→ Canvas 01–03

Sprint 2 · 30 min · Design

5

Choose the leverage point (5 min)

10

Define the intervention (10 min)

15

Stakeholder grid and policy fit (15 min)

→ Canvas 04–08

Sprint 3 · 25 min · Deliver

10

Logic model (10 min)

10

Roadmap and budget (10 min)

5

KPIs, risks and pitch rehearsal (5 min)

→ Canvas 09–12

⏱️

Facilitator

Keeps time; makes sure every voice is heard.

🗺️

Systems mapper

Draws the iceberg and loop on the wall.

🔍

Evidence lead

Checks every fact has a source.

💰

Budget & KPI lead

Owns canvas boxes 10–12.

🗣️

Stakeholder voice

Plays the firm, the official or the student, and pushes back.

🎤

Pitcher

Presents the 5-minute pitch.

⚖️

Rule: mix disciplines in every role pair — no role is held by the discipline it “belongs” to.

17 · Pitch format & rubric

Five minutes to pitch. Scored out of 25.

3 + 2 format — 3 minutes of presentation, 2 minutes of Q&A from a “critical friend” group.