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Saving the Sahel (Part 1)
| In a recent post, I blogged about the Great Green Wall of China. Today I would like to start a series about another ongoing Program called the Great Green Wall of Africa (more formally the Great Green Wall Initiative). This Program is in the Sahel region of Africa (see map below) and is described well in an article from National Geographic.  Here's a quick summary for that article: In recent years, northern Africa has seen the quality of land significantly due to and poor land management. Land degradation stems from human-related and natural factors, including unsustainable farming practices, , climate change and . Land degradation contributes to the loss of and ; more than 9,000 plants and animal species are considered endangered as a result. Land degradation also poses serious threats to agricultural productivity, , and quality of life. Nowhere is the threat of land degradation more urgent than in the Sahel, where millions of people live on land undergoing , the most extreme form of land degradation. Without action to combat it, desertification will continue to drive people to migrate away from the Sahel. In 2020 alone, more than 2.5 million people in the Sahel region were displaced. The Sahel region, by the way, is a vast semi-arid transitional zone in North-Central Africa, stretching between the Sahara Desert to the north and the tropical savannas to the south. Acting as an ecological and climatic buffer, the word Sahel - ironically - comes from the Arabic sāḥil, (الساحل) meaning "coast" or "shore" (even though it's all about a desert). The Great Green Wall: a brief description The Great Green Wall Initiative is an African-led environmental restoration program launched by the African Union in 2007 to combat desertification, climate change, food insecurity, and poverty across the Sahel region of Africa. Originally envisioned as a continuous “wall” of trees, the initiative has evolved into a broader effort focused on restoring ecosystems, improving sustainable agriculture, and strengthening community resilience. The initiative stretches approximately 8,000 kilometers (5,000 miles) across the width of Africa, from Senegal on the Atlantic coast to Djibouti on the Red Sea, involving more than 20 countries. Its goals include restoring 100 million hectares of degraded land, capturing 250 million tons of carbon, and creating 10 million green jobs across one of the world’s most climate-vulnerable regions. It was designed as a long-term initiative with major targets tied to 2030. But what is it? Project, Program, Portfolio? This is a naming problem we generally have in our discipline. I have seen this as a problem in my own background as a practitioner and continue to see confusion over these terms as I create and teach Project Management (or Program... or Portfolio Management) courses. It's not a project... A project:
The Africa Great Green Wall (GGW) is a fascinating case because it looks very different depending on whether you assess it as:
In the remainder of this post (and continuing with more) I will provide an assessment of how the Program is doing as measured by classic PM measurements (scope, cost, time, risk, success metrics). I think there are learning opportunities simply by seeing how these do (and do not) apply to a large sustainability program. When I teach my PM courses, I try to convey the idea that although the "triple constraint' elements interweave and are interdependent and overlapping, generally the flow is first Scope, then Schedule, and then Cost. In other words we need to know what's in an initiative, and only then can you sequence tasks and milestones, and only then can you really determine costs. Agree or not, I am going to follow that order in my assessment of this sustainability program. The Great Green Wall of Africa - Scope Performance Scope Definition Originally: “A wall of trees across Africa.” Later evolved (I would say massively scope-crept) into:
Status: Massive Scope Expansion The project experienced major scope evolution [scope creep and upscope {consciously-accepted inclusion of new scope}]. Positive side of this growth of scope:
The initiative transitioned from a deliverable-driven program to a (much more ambitious) transformation program. This ambition was well-intentioned, but weakened measurability. In the next post of the series - Schedule and Cost of the Great Green Wall Initiative |
You Can't Get They-ah From Hee-yah
 In a recent post, I talk about the paradox of AI - how it promises to be a savior of sorts in many ways (see my last post about how it is aiding with floating solar projects), but also is an energy hog and causes much in the way of problems in terms of water use, carbon production, and disruption to the local area. I want to go back to the 'dark side' of AI, MAINE-ly the area of local disruption - and as you may have guessed, I will focus on Maine, USA. Let me set this up with a bit of culture. Maine - the most northeast of the New England states in the USA, has its own culture (really several cultures). There's a thread of very sarcastic, practical, pointed comedy in this culture. Indeed, there was a humorist duo made up of Marshall Dodge and Bob Bryan, who told (or retold) stories set in that dry, literalism culture of traditional "downeast" Maine. These were published/recorded and broadcast in the 1950s and the 1960s. Here's one story: A fellow driving through Maine stops and asks an old Mainer sitting on the porch: “Can you tell me how to get to Portland?” The Mainer thinks for a while and says: “Nope… you can’t get there from here.”* The traveler looks puzzled and says: “Well then… where does this road go?” The Mainer says: "Don't go nowhere - it just sits there". So with this in mind, let's look at the news - the controversy and legislation regarding AI Data Centers in Maine. According to this article, published on 17-April-2026, Maine lawmakers passed a statewide freeze on large data centers this week, the first of its kind in the country. If Gov. Janet Mills signs the bill into law, it would impose a moratorium on building data centers that use more than 20 megawatts of power in the state for a year and a half. During those 18 months, a council of government officials, experts and other stakeholders will be tasked with developing guidelines and recommendations for building future data centers, according to The Hill. However, Governor Janet Mills did not sign the bill. She vetoed it on April 24, 2026. The bill (LD 307) would have created the nation’s first statewide moratorium on large AI/data-center projects in Maine, temporarily blocking new facilities using more than 20 megawatts of power while the state studied impacts on electricity costs, water use, and the grid. The Governor said she actually supported the idea of a temporary pause in general, but objected because the Legislature refused to exempt a major proposed redevelopment project in Jay, Maine, at the former Androscoggin paper mill site. According to her statement:
The Maine debate captures the AI Sustainability Paradox perfectly. While AI systems may help humanity:
...and in general be a sustainability "hero"... To train and run large AI models, society is rapidly building hyperscale data centers that:
That’s the paradox: AI may help solve climate and efficiency problems globally while simultaneously intensifying environmental and social pressures locally. The Maine case is especially interesting because it forces a collision between two different scales of thinking: 1. The Global Scale Argument Supporters of AI infrastructure say: • the economic future depends on AI, • the energy transition itself may require AI, • and states that reject infrastructure risk missing major investment waves. From this perspective, a data center is seen almost like a railroad, hydroelectric dam, or semiconductor fab — foundational infrastructure for the next era of civilization. 2. The Local Scale Argument Opponents or skeptics ask: • Why should one town absorb the environmental burden? • Will electricity prices rise for residents? • Will water systems be stressed? • Are the promised jobs permanent or mostly temporary? • Who benefits — local citizens or distant tech firms? • What happens to community identity and land use? This is a classic “externalities” debate: • the benefits are diffuse and global, • while the costs are immediate and local. The irony is profound: AI may help reduce worldwide waste and carbon emissions through optimization, but the infrastructure needed to do that may itself require enormous resource consumption. There’s also a deeper systems-thinking lesson here that aligns strongly with portfolio and program management concepts that I discuss here on People, Planet, Profits, and Projects, as well in my courses: AI resembles a portfolio-level optimization problem - thinking of projects as INVESTMENTS At the project level, a single data center may appear environmentally costly. But at the systems level, AI-enabled efficiencies could theoretically produce net-positive outcomes. The challenge is that: • local stakeholders - like the Mainer sitting on his porch and radiating sarcasm all day - experience the project costs directly, but global society may receive the portfolio benefits later. That is going to naturally involve friction between that local and global scale - and will pit Joe Mainer against (at least what are seen as) corporate oligarchs. The Maine story also reflects a broader transition in how society thinks about technology. For decades, digital technologies were treated as “clean” because they lacked smokestacks and assembly lines. AI is revealing that advanced computation - at least the way it is headed now - has very tangible ecological consequences. And there’s yet another paradox layered underneath: the more AI succeeds, the more 'computing power' society demands, which increases infrastructure expansion, which increases energy demand, which requires even more optimization - an AI "power spiral" of sorts. That’s why some analysts now argue that the future of AI is inseparable from: • energy policy, • nuclear power, • water management, • transmission infrastructure, • and regional economic planning. In other words, AI is no longer just a software story. It is becoming an industrial-policy story as you see in this Maine example. The Maine governor’s response actually reflects an attempt to balance this paradox: • rejecting a total moratorium, • while acknowledging the need for oversight and study. That middle position implicitly recognizes that the issue is not simply “AI good” or “AI bad.” The real challenge is governance: How do we capture AI’s transformative benefits without imposing disproportionate environmental or social costs on specific communities? That may become one of the defining program-management and public-policy questions of the next decade. And I hope that we can get there from here. *this is pronounced, "ya can't get they-ah from hee-yah" |
Floating an idea into reality: the other side of the AI Project Paradox
 In my last post, I explored the growing concerns around artificial intelligence—energy consumption, carbon footprint, data privacy, and even the “noise” it introduces into our systems. These concerns are real, and in some cases, they’re driving moratoriums on new data center construction. But that’s only one side of the story. This post explores the other side of the paradox: AI as a positive force—not as a drain on resources, but as a multiplier of sustainable outcomes. And one of the most compelling examples is floating solar. A Pilot in Colorado Just outside Denver, in Golden, Colorado, a modest project is quietly pointing toward the future. Developed by Noria Energy, the Aurea Solar Project sits atop the Fairmount Reservoir. At roughly 50 kW, it’s small by utility-scale standards—but its significance goes far beyond its size. This is the first floating solar array in the United States to incorporate tracking technology. Instead of remaining fixed, the panels rotate on the water to follow the sun, increasing energy production by an estimated 10–20%. But what makes this project especially compelling is not just the technology—it’s the system it supports. The energy generated helps power a local water utility, directly linking renewable energy production with water infrastructure systems. At the same time, the panels reduce evaporation from the reservoir—an important benefit in the water-constrained American West. This is not just a solar project. It’s an integrated energy–water system. You’ll soon find out why the heck I keep highlighting the word SYSTEM. A real one in NJ Because (as you know if your follow this blog) I like to feature moving pictures (aka videos), have a look at this video to see a real floating solar project. Back to the Paradox: Where AI Enters the Picture At first glance, you might not see AI at work here. But like with most things today… it’s THERE. Today, the system tracks the sun mechanically. Tomorrow, AI will: -Optimize panel orientation in real time based on weather and cloud cover -Predict energy output and dynamically adjust operations -Balance what are normally competing objectives—maximizing energy generation while minimizing water loss -Anticipate maintenance needs before failures occur Across renewable energy and smart infrastructure projects, AI-driven optimization has been shown to:
Let’s take a look at these from the viewpoint of this blog: People, Planet, Profits, and Projects People The Aurea project supports a water utility serving tens of thousands of residents and promotes workforce development. Planet Floating solar reduces land use and water evaporation, while AI enhances efficiency and sustainability. Profits The system approach and clever, reasoned, thoughtful application of AI makes this system more efficient and profitable. Projects This pilot project involves multiple stakeholders and uncertainty—an ideal environment for AI-enabled decision-making, taking decision to action, thoughtfully, and based on real-time information. And now…as promised…the systems piece…. From Static Infrastructure to Intelligent Systems The Colorado project is becoming a proving ground for intelligent, adaptive infrastructure systems. This is also a powerful example of systems thinking in action—what the Systems Thinking & Systems Intelligence (STSI) community highlights as the need to see relationships, not just components. We are working within a system of systems—energy, water, environment, and community—all interconnected. STSI Insight: “The performance of a system is driven not by its parts alone, but by the quality of the relationships among those parts.” Learn more about this at stsi.pro. Reframing the AI Conversation AI stands properly accused of being an energy hog, a privacy stealer, and other nasty stuff. On the other side of the paradox, however, AI can generate clean energy, conserve water, improve resilience, and support communities. The key is where and how we apply it, how we guardrail it, how we thoughtfully work with it. Closing Thought AI, when aligned with purpose, becomes a force for integrating systems, and systems of systems—connecting people, planet, and projects in powerful new ways. |
The Environment of the Built Environment: an AI Paradox
 If you’ve been following this blog, or in general have a mature view of project management, you know that sustainability in projects is all about thinking past the end of the project and considering the project’s product in service – and the impacts of that ‘product’ as it operates in the steady state. Also, if you have been following, well, anything, you know that AI is in just about every news story, and if it isn’t it may even be writing that news story. One news story that caught my attention in light of the relationship between sustainability and AI is this article posted about the great state of Maine. It opens, “Maine lawmakers passed a statewide freeze on large data centers this week, the first of its kind in the country. If Gov. Janet Mills signs the bill into law, it would impose a moratorium on building data centers that use more than 20 megawatts of power in the state for a year and a half.” And it’s not just Maine.According to The Hill, “The new Maine ban is part of a larger trend of state legislatures considering bills to impose new restrictions on data centers as the public and experts express concerns about the negative economic and environmental effects of these projects.” There are many concerns about AI. Privacy, control, jobs, consumption, pollution all are front of mind. I came across this amazing interview between Claude and Bernie Sanders. Whether you are a fan of Bernie Sanders or not – whether you are a fan of AI or not, have a listen to this conversation. It’s mostly about privacy but Sanders and other politicians in the US are wanting a moratorium on data center construction, and it’s not just the US. Here’s a report that says that up to half of the world’s data centers may be delayed. But I digress. Let’s get back to that conversation between Claude and Bernie. I was astounded by the ‘frank’ attitude Claude had in ‘admitting’ what is happening with respect to some of these concerns – even though there was one point where there was a giant ‘pregnant pause’ before it answers. See if you can catch that moment. This post is meant to be thought-provoking. Many of you may be working on ‘the built environment’ – construction, water systems, even transportation and telecom, which fit in that category. Are you thinking about what impacts the project’s PRODUCT has in the long term? Are you considering ALL of the stakeholders involved – not just the people working on the project, or the sponsors, or the immediate customers, but those who will be affected (in any way) by the result of the project in its steady state.There are cases near my home where a data center construction project has become controversial not because of power consumption or classic ‘pollution’ or water (the usual suspects) but also literal physical noise based on the diesel generators involved in supporting the center.See the story from Boston’s WBUR here. If this interests you, have a look at this report which concluded that a Virginia data center was projected to contribute up to $99 million in health damages to local residents each year. Please do not get me wrong here. I am not opposed to the development and deployment of AI. As I have posted recently, there are tremendously promising(and proven) contributions that AI can make in the world of reducing carbon emissions and improving social conditions for humans. This is a both/and situation. Or, rather it can be a both/and situation – having the benefits of AI while limiting its downsides – if the proper guardrails are set up, and, importantly, if you as project managers step up as project leaders and raise these concerns early on, and engage with the appropriate stakeholders early on. What are your thoughts here?I am interested in hearing from project managers in the built environment area, especially those involved in data center projects. What do you think? |
Is plastic on your mind?
 Microplastics have been on my mind lately. I mean that quite literally. A recent study from Duke University shows that human brains now contain a teaspoon of microplastics (7 grams). Other respected studies reveal significant increases of microplastics in the bones and other parts of the body. Unlike my recent series on the Great Green Wall, where a major government (China) took on a big problem with huge scope and billions of yuan in funding, this story, based mostly on this article from the Smithsonian Magazine, is about one high school student’s approach to solving (or at least remediating) the microplastics problem, starting locally, but thinking globally. So, innovative, systems thinking doesn’t always come from billion-dollar portfolios—it can start as a single project, in a high school science fair in Virginia. Rather than providing all of the detail here, I think it’s best just to watch this short video about the prevalence of microplastics. So, how did Virginia high school student Mia Heller react to the problem, after reading the local newspaper’s coverage about microplastics in her town’s water supply? Well, she got to work on a science project that sought to find an inexpensive and easy way to remove microplastics. Here she is explaining the system to you: What are the lessons learned from such an inspiring high school project for us – practitioners of project management in the larger sense? It’s about empowering young people to express their ideas, providing support and encouragement. It’s about active science education and the support we may be able to lend as project managers. It’s about the fact that great projects often start not with a top executive proposing a grandiose solution, but rather with a question from someone at an entry-level position. In summary: 1. Innovation is not hierarchical
So:
https://isef.net/project/enev053-self-recycling-system-for-microplastic-removal |