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Technology Measuring the Effectiveness of Clean Cooking Solutions

Did you know that burning fuel for cooking contributes significantly to the climate crisis? Roughly one third of the world’s population relies on dangerous and polluting biomass stoves and fires to cook their daily meals, sending 120 megatons of climate pollutants into the atmosphere each year, according to the Clean Cooking Alliance. Additionally, 4 million people die every year from inhaling the smoke from cooking, and these same vulnerable populations are set to be the first to face the worst impacts of climate change. We know that these households must be provided with clean energy and clean cookstoves, but because change must take place inside individual homes, it is difficult to know if these clean cookstoves are having their intended impact. A clean, modern-fuel stove may be distributed or purchased by a household, but how do we know if a clean cookstove is utilized by a household for daily cooking? How do we know if it meets all of a family’s cooking needs? Access is not enough if we can’t understand what is actually happening inside homes.

Family with cookstove

At the Autodesk Foundation, we believe that the success of our grants and impact investments depends on our ability to use impact evidence to inform our decisions. There are many different frameworks and methodologies to evaluate impact. Traditional impact measurements and management (IMM) methods, such as theory of change, self-reported key performance indicators (KPIs), and third-party auditing have helped us identify indicators like the number of individuals reached or number of innovations deployed. However, they fall short in telling us if those individuals actually used the innovation and whether they changed their behavior to sustain using them. This is exactly where investing in enabling technology, such as sensors and Internet of Things (IoT) technologies, in combination with qualitative methods can help us understand the depth of impact. Sensor technology as an impact measurement and management (IMM) mechanism can help establish accountability, inform decision making, and generate objective evidence of success. Sensors can play a critical role in providing high quality data on the performance and adoption of cleaner cooking solutions.

A clean, modern-fuel stove may be distributed or purchased by a household, but how do we know if a clean cookstove is utilized by a household for daily cooking? How do we know if it meets all of a family’s cooking needs?

Nexleaf Analytics has spent more than ten years experimenting with different applications of sensor technology to answer these questions. By applying temperature sensors and remote monitoring systems, a simple, efficient, wood-fuel cookstove can be made “smart,” and send data on actual stove usage to cloud-based systems where impact can be measured and monitored. Modern energy (gas and electricity) allows for added opportunities for this kind of IoT-based monitoring, using metering and network connectivity.

User with EPC and Sensor

​​An EPC alongside a traditional charcoal stove in a home in Mwanza, Tanzania. Use of the charcoal stove is monitored by the Nexleaf temperature sensor (pictured top left) and the EPC is monitored by a Smartmeter. Photo credit: A2EI.

Combining quantitative and qualitative data usage patterns

In a recent pilot study, a combination of direct quantitative data and qualitative data were used for IMM to understand electric cooking usage patterns. Nexleaf Analytics and the Access to Energy Institute (A2EI) utilized both temperature sensors and smart meters to capture how long and how frequently households used both new electric pressure cooker (EPC) and traditional charcoal stoves. Logs of foods cooked were also taken by the households through the MECS Cooking Diaries methodology. Through continuous monitoring of cooking activity, the study revealed that 1) EPC use greatly increased alongside electricity price reduction, and 2) households continued to use charcoal stoves alongside their electric cookers.

Cookstove Use Data Chart

Data from smart meters shows the number of cooking events on electric pressure cookers (EPCs). Data show 3 distinct phases of use: initial high use during the “honeymoon” period when the EPCs were new, a subsequent drop off in use, and then a dramatic increase in use after a new low tariff rate was introduced. The cooking patterns show a strong connection between use and price, valuable data for those planning schemes to increase use of electric cooking over charcoal. Photo credit: A2EI

Days of cooking on electric, traditional, and “stacked” combination of stoves

Days of cooking on electric, traditional, and “stacked” combination of stoves

Smart meters and temperature sensors reveal how many days different stove types were in use. Households continue to use their traditional stoves on many days by themselves, and when they cook with electricity they continue to “stack”- the practice of using multiple stoves in a household – with their traditional stove. Energy transitions take time and stove stacking is expected: understanding how long and often traditional stoves remain in use informs what unmet needs remain for households.

Understanding how stoves are actually being used not only directly measures impact, but also paves the way for understanding the end-user experience and the information needed to reduce barriers to a successful clean energy transition. That end-user experience was evaluated using a direct end-user survey component by 60 Decibels. 60 Decibels developed Lean Data while at non-profit impact investor Acumen. It is an approach to impact measurement that focuses on speed, repeatability, and comparability through the use of phone surveys to gather quantitative and qualitative data. Used in combination with the objective measurement of cooking, these qualitative insights bring the “why” to the “how much.”

Sensor technology as an impact measurement and management (IMM) mechanism can help establish accountability, inform decision making, and generate objective evidence of success.

Overwhelmingly, users surveyed named time-savings as a motivating factor for EPC use, both among those who chose to purchase their EPC at the end of the pilot and among those who didn’t. With the clean energy transition so reliant on individual household behavior and technology adoption, understanding these customer motivations is critically important for long-term success of initiatives.

Source: 60 Decibels, phone interviews of 91 PowerGen EPC pilot users in June 2021 in Tanzania.

The insights from the pilot demonstrate how technology and Lean Data approaches can be combined to enhance IMM and provide a comprehensive picture of impact at the end-user level. The purpose of this pilot was to understand the impact and viability of electric cooking appliances at a small scale to inform larger projects. From here, clean cooking and household energy efforts can develop the pricing schemes and other conditions for impact at a larger scale, eventually achieving the climate and health outcomes we need.

Ultimate goal – using impact data to drive policy decisions

This is a crucial time for IMM. We need to get creative about using every tool in our toolkit to understand the actual impact climate interventions have by gathering meaningful data and drawing actionable insights. Timely, data-driven feedback mechanisms are critical for funders and governments to ensure environmental, health, and energy initiatives are delivering on their promise. For the communities directly impacted by these programs, continuous assessment and analysis provides an opportunity to provide feedback that informs how the initiatives move forward.

Ishita Jain is the Impact Insights & Analysis Manager at the Autodesk Foundation responsible for measuring the social & environmental impact of the Foundation’s work and establishing best practices around impact measurement and management. Ishita earned a Masters in Design for Social Innovation from the School of Visual Arts in ... Read more
Megan Bomba is the Senior Program Manager for Clean Cooking at Nexleaf Analytics. Megan manages the operations, planning, and coordination required to achieve Nexleaf’s goals of bringing more robust data to the clean cooking sector in order to understand the most efficient path to a successful clean energy transition. Megan ... Read more
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