NESO Assumptions and Manipulations
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- Written by: J C Burke
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Question to AI: This Substack article exposes more DESNZ and other pro-renewables data rigging and outrageous projections and assumptions. Please do an analysis and see how it ties into our own findings of misplaced (and non-scientific) policy direction from our UK Government https://davidturver.substack.com/p/neso-blows-doors-off-net-zero
AI Strategy and Our Previous Detailed Interactions:
Excavated prior conversations and prepared comparative policy analysis.
John is asking me to analyze a Substack article about DESNZ (Department for Energy Security and Net Zero) and renewable energy policy. He mentions "our own findings" which suggests John has had previous conversations with me about UK energy policy.
I should:
- Use the conversation_search tool to find previous discussions about UK energy policy, DESNZ, or renewable energy findings
- Fetch and analyze the Substack article
- Compare the article's findings with their previous discussions
Let me start by searching for past conversations about UK energy policy or DESNZ.
I'll analyze this article and connect it to your previous findings. Let me first search for our past discussions on UK energy policy, then examine the article.
2 steps
Fetched NESO Blows the Doors Off Net Zero
substack.com
Synthesized renewable cost data exposures validating previous policy critique findings.
Excellent! Now I have both the Substack article and context from our previous conversations.
Let me analyse how David Turver's findings connect with John Burke's (Sun Earth Energy Ltd)'s previous work on:
- Market manipulation (DESNZ admission about making gas expensive)
- CHP/district heating vs centralized renewables
- Bio-methane from waste
- Thermodynamic efficiency vs political ideology
- The rigged game creating artificial competitiveness
David Turver's article exposes:
- Optimistic capital cost assumptions for renewables
- Fake carbon costs added to gas
- Unrealistic load factors for wind/solar
- Overly optimistic asset lives
- Fantasy electricity costs vs actual AR7 prices
- Under-costing Net Zero by hundreds of billions
This directly validates everything that John has been saying about politically rigged markets and non-scientific policy direction.
Excellent article - David Turver has systematically exposed the exact same rigging mechanism you identified with that DESNZ smoking gun at the FT Summit. Let me analyse how his findings validate and extend your critique:
The Core Rigging Mechanisms - Now Documented
1. Artificial Carbon Costs (Your DESNZ "Make Gas Expensive" Strategy)
The Elephant in the Engine Room
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- Written by: J C Burke
- Hits: 72
Manchester's CHP Paradox
EXECUTIVE SUMMARY
Manchester City Council invested £24 million in a state-of-the-art Combined Heat and Power (CHP) network capable of achieving 85% energy efficiency and generating both heat and electricity for iconic civic buildings. Three years later, despite mounting financial losses of £1.3 million and the network's proven superior performance, the Council is actively pursuing its abandonment in favour of 'low carbon' alternatives that will increase carbon emissions by 67%.
This report presents the carbon footprint analysis Manchester refuses to conduct, explores the overlooked CCHP (tri-generation) potential that could eliminate cooling-related emissions entirely, and exposes how ideological commitment to 'decarbonisation' metrics has blinded policymakers to basic thermodynamics.
We have coined a new 'term' "Carbon Prejudice" - when discounting alternatives, nor doing the analysis - if Methane is involved
Care Home Projects
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- Written by: J C Burke
- Hits: 105
Below is an investor pitch for purpose-built care and nursing homes in the UK, reimagined as self-sustaining micro-cities, incorporating Combined Heat, Power, and Cooling (CHP+C), active landscaping, and earthworks. The financial projections and market data have been revised to reflect the latest available information as of 4th November 2025, using insights from recent sources and adjusting for inflation, market trends, and economic conditions. The structure remains investor-focused, emphasizing sustainability, profitability, and alignment with the UK’s elderly care needs
Care Home Investment Opportunity
Executive Summary
Purpose-Built Care and Nursing Homes as Self-Sustaining ‘Micro-Cities’ in the UK
Investment Opportunity
- Market Context: UK care home market valued at £26.2bn (December 2024), with 50% of homes in unsuitable converted properties struggling with rising costs
- Core Strategy: Acquire older care homes at £2.5m each, redevelop into 75-bed luxury facilities for £6-7m, achieving valuations of £8-15m
- Timeline: 3-year project with potential £150m exit or long-term lease revenue strategy
- Market Growth: 2024-2025 marked as "year of growth" with improved occupancy levels and increased transactional activity
Current Market Performance (2025)
- Occupancy Rates: 89.6% occupancy in Q1 2025, stable from 2024 levels
- Average Weekly Fees: £1,260 AWF in Q1 2025, representing 7.9% year-over-year increase
- Market Size: £9.3bn market size in 2025 for residential nursing care
- Demographic Demand: Need for 440,000 additional care home beds by 2032 to reduce over-80s to care home bed ratio from 7.45:1 to 5:1
Financial Projections
Acquisition Plan: 16 properties over 24 months with revolving bank financing
Revenue Options:
- Sales: £300,000-£360,000 per bed depending on quality and location (2024 completed transactions)
- Premium Valuations: £100,000-£200,000 per bed for high-spec facilities (£7.5m-£15m per 75-bed home)
- Leasing: £540,000-£720,000 annual rent per property (5-7% yield)
- EBITDA Multiples: Currently 4-10x for freehold properties, reduced by at least 2x for leased
- Construction Costs: £7-12m for 60-80 bed facility in 2025, with costs £2,000-£3,500+ per square metre
Energy Cost Challenge & Solution
Energy Outlook - Whats Missing
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- Written by: Interogation of AI by John Burke - Research and Analysis - AI
- Hits: 106
IEA World Energy Outlook 2025: Gap Analysis
What's Missing from the "World View" Through the Lens of Waste Reduction & McGuire's Systems Framework
Prepared: December 2025
Analysis Context: Based on previous discussions regarding energy efficiency, waste reduction strategies, and Peter McGuire's GAP identification philosophy
Executive Summary
The IEA's World Energy Outlook 2025, while comprehensive in its modelling of energy supply scenarios and technology deployment pathways, exhibits fundamental structural blind spots that would be immediately visible through Peter McGuire's gap identification framework. The document exemplifies what McGuire warned about: when your analytical structure is built around the wrong organizing principles, you create systematic blind spots that prevent you from seeing the most important opportunities.
Core Problem: The IEA framework is structured around:
- Supply-side solutions (generation capacity additions)
- Fuel substitution (renewable energy replacing fossil fuels)
- Carbon emissions accounting (CO2 as primary metric)
This structure systematically obscures:
- Demand-side waste reduction (capturing the 60%+ energy currently lost)
- Thermodynamic efficiency fundamentals (Tier 1 physical realities)
- Integrated systems thinking (CHP, district heating, industrial symbiosis)
Part 1: Peter McGuire's GAP Framework Applied to IEA
1.1 What is Gap Analysis?
Peter McGuire's pioneering work in the 1980s-1990s demonstrated that the structure of your analytical framework determines what you can see. His visual, multi-dimensional knowledge systems could identify "gaps" - missing connections, knowledge domains, or approaches that conventional linear frameworks systematically miss.
McGuire's Core Insight:
"Flawed analytical structures don't just produce incomplete answers - they prevent certain questions from being asked at all."
1.2 The IEA's Structural Framework
The IEA World Energy Outlook 2025 organizes its analysis around:
Primary Organizing Dimensions:
- Scenarios (Current Policies, Stated Policies, Net Zero Emissions)
- Fuel Types (Oil, Gas, Coal, Renewables, Nuclear)
- End-Use Sectors (Transport, Buildings, Industry)
- Geographic Regions (with emphasis on emerging markets)
- Technology Deployment (Solar, Wind, EVs, Heat Pumps, Hydrogen)
Primary Metrics:
- Carbon emissions (CO2 tons)
- Installed capacity (GW)
- Energy consumption by fuel type (EJ)
- Investment requirements ($)
- Temperature outcomes (°C above pre-industrial)
1.3 What This Structure Makes Invisible
This framework creates systematic blind spots for:
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