Transforming Brick Manufacturing in Bangladesh to Promote Clean Air and Better Health

Last registered on September 27, 2022


Trial Information

General Information

Transforming Brick Manufacturing in Bangladesh to Promote Clean Air and Better Health
Initial registration date
September 26, 2022

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
September 27, 2022, 11:59 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.


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Primary Investigator

Stanford University

Other Primary Investigator(s)

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Across South Asia, the brick manufacturing industry is dominated by inefficient, coal-burning kilns. Brick kilns are one of the largest emitters in the region. In Bangladesh, kilns contribute 17% of the country’s annual CO2 emissions and 11% of PM2.5. The pollution released by these kilns worsens local air quality, health and agricultural productivity, and global climate. Reducing these emissions could generate large social benefits. A properly constructed and operated zigzag kiln can reduce black carbon by 41%, CO2 by 21%, and PM2.5 by 80% – and strikingly, also increase kiln profitability. Yet the vast majority are incorrectly constructed and operated. Our preliminary work found that lack of knowledge regarding proper construction and operation and inattention to worker incentives undermine kiln operation. We propose a randomized intervention among kiln owners in Bangladesh that relaxes these barriers to improve kiln performance, reduce air pollution, and lower greenhouse gas emissions.
External Link(s)

Registration Citation

Luby, Stephen. 2022. "Transforming Brick Manufacturing in Bangladesh to Promote Clean Air and Better Health." AEA RCT Registry. September 27.
Sponsors & Partners



Experimental Details


A properly constructed and operated zig zag kiln can reduce black carbon by 41%, CO2 by 21%, and PM2.5 by 80%. However, most conversions to zig zag kilns in Bangladesh have been poorly implemented. Consequently, the new zig zag kiln appear to be just as polluting as the older style they replaced. Our study of kiln owners suggests a puzzle: a correctly built and operated zig zag kiln can increase kiln profits, yet these gains are not realized by owners with poorly constructed and operated kilns. Our preliminary work suggests two primary barriers to effective implementation: 1) lack of knowledge of the specific interventions and their true economic return and 2) inattention to the incentives of workers whose cooperation is crucial to running an efficient kiln.
We will address these barriers through a randomized intervention that provides:
1) extensive information, training, and technical support on low-cost improvements
2) information and encouragement to kiln owners to adopt strategies that incentivize workers to adopt the new practices.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Primary outcomes will include carbon monoxide/carbon dioxide ratio (a measure of combustion efficiency measured by placing a sensor into the flu gas), specific energy consumption (the energy used in MJ for firing 1 kg of brick) and proportion of Class 1 bricks produced. We will track coal usage and sample coal to test for carbon content, and then apply the IPCC’s methodology to estimate tons of CO2 abated due to the intervention by converting specific energy consumption to CO2. Secondary outcomes include additional measures of brick production and earnings, as well as measures of working conditions and whether any type of worker incentives were adopted.
Primary Outcomes (explanation)
The CO/CO2 ratio is a measure of complete combustion – the more complete the combustion, the more carbon gets converted into CO2 and the lower the ratio. It is measured by collecting data with a flue gas analyzer. Previous work done in India, indicates that in better functioning zigzag kilns (using coal as the main fuel), the CO/CO2 ratio is ≤ 0.025. The CO/CO2 ratio is an objective measure, though it provides only a cross sectional assessment of the combustion efficiency at the time of measurement, rather than an averaged performance for the whole season.

Specific energy consumption (SEC) is a scientific measure of energy performance that takes into account variation in gross calorific values (GCV) of fuels and fired brick weight; a lower SEC indicates higher efficiency. It is calculated by multiplying the tons of coal consumed by the gross calorific value (in MJ/kg) and dividing by the total production of bricks (in kg), thus the resulting units of specific energy consumption are in MJ/kg-fired brick.

Brick production and quality are quantified by summing the total number of bricks fired during completed batches and multiplying by the proportion of bricks that fall into the following classes: class-1, class-1.5, class-2, class-3, and breakages. Class-1 represents the highest quality of bricks and command the highest price. To produce Class-1 bricks, kilns need to operate with consistent temperature throughout the firing zone. Thus, the share of class-1 bricks is an indicator both of higher profit and energy efficiency which would generate fewer emissions.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We hypothesize that by addressing the most important barriers to improved kiln operation, we can improve efficiency of kiln operation and reduce air pollution and GHG emitted in the short term. A growing body of economics literature addresses poor management in low-income countries; however the evidence remains mixed on the best strategies to improve management and why owners do not themselves invest in these profit-enhancing strategies. Entrepreneurship and business management trainings targeted toward microfinance beneficiaries have not increased longer-term profit or income, perhaps because they were not sufficiently intensive, whereas an intensive but costly management consulting intervention among Indian textile firms substantially increased productivity. Perhaps most closely related to our setting, a cost-saving technology delivered to soccer ball factories in Pakistan initially failed due to misaligned incentives between owners and workers.

Drawing on this evidence and our team’s experience in India and Bangladesh, we will deliver a randomized intervention that provides intensive training and technical support, information and encouragement to kiln owners to incentivize workers to adopt the new practices, and testimonials from pilot kiln owners who adopted these practices and saw increases in profits. We will have two experimental arms: 1) technical knowledge and training (technical arm) and 2) technical knowledge and training + worker incentives (incentive arm). Kilns assigned to both arms will receive information, training, and encouragement to adopt a suite of technical and operational improvements including improved firing practices, improved brick setting, increased insulation, and good bookkeeping. Trainings will highlight the financial benefits of these improvements and include live participation from owners who adopted them during our pilot, to directly address owners’ uncertainty of economic returns. This will be delivered in the form of an initial “classroom” training, a series of on-kiln trainings targeting specific operational components, and technical support available throughout the firing season. Kilns in the incentive arm will receive the technical training plus additional information and recommendations to encourage use of targeted worker incentives. The recommendations, which include a mix of financial and non-financial mechanisms, are informed by the economics literature, the experience of Indian kiln owners, results from our pilot, and testimonials from owners who participated in our pilot study.
Experimental Design Details
Not available
Randomization Method
randomization done in office by a computer
Randomization Unit
firm level (brick kiln)
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Not applicable
Sample size: planned number of observations
300 brick kilns + 1800 workers
Sample size (or number of clusters) by treatment arms
100 kilns per arm (control, technical, incentive); 600 workers per arm (with 6 workers from each kiln across different job categories).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Our randomized controlled trial has two experimental arms: a technical arm that receives intensive training and technical support on improved kiln operation and an incentive arm that receives information and nudges on how to incentive workers to correctly adopt the practices in addition to the intensive technical training. Our proposed intervention, when successfully adopted, increases the energy efficiency of kiln operation and increases profit for kiln owners (from reduced spending on coal and greater production of higher quality bricks). In our pilot, 60% of kilns assigned to either treatment arm adopted the two most important technical intervention components. Using data from our pilot study in Jashore, Bangladesh completed during the 2021-2022 brick firing season, we conduct power calculations for three outcomes that reflect energy efficiency and improved kiln operation: percent of class-1 bricks produced, CO/CO2 ratio, and specific energy consumption. Although the pilot study was too small to estimate these outcomes with precision, the point estimates do provide some empirically based suggestion on potential effect size. Approach Based on our pilot results, we have estimated effect sizes for the “intention-to-treat” (ITT) effect of each experimental arm, as well as a “treatment-on-the-treated” (TOT) effect that accounts for imperfect compliance with the intervention (both from kilns assigned to the treatment arm that did not take-up the intervention practices and from control kilns that sought to learn the intervention practices) by using random assignment to both arms as an instrument for adoption. These results for each of the three outcomes are summarized in Table 1 below. We first calculate the minimum detectable effect size (MDES) assuming both arms have equal effect sizes, a significance level of 0.05 and power of 0.9. Then, because there is suggestive evidence from our pilot that the incentive arm encouraged better adherence to the improved operating practices and resulted in better outcomes, we also calculate our statistical power for detecting differences between the incentive and technical arms. These scenarios indicate that with a sample size of 100 kilns per experimental arm (300 total kilns), we are powered for all three outcomes with 90% power in most cases. For class-1 bricks the incentive arm performed much better, producing 7.12 percentage points more class-1 bricks than the control group and we would be powered to detect an effect size of this magnitude with only 25 kilns per arm. The effect size for the technical arm was much smaller (2.1 percentage points higher than the control group) and with 100 kilns per arm we would not be powered to detect such a small difference. However, 2.1 percentage points is an extremely conservative estimate for a potential effect size. The minimum detectable effect size for 100 kilns per arm at 90% power is 3.56 percentage points. This is half the magnitude of the incentive arm and still relatively conservative, particularly when considering the TOT estimate of 9.22 percentage points among adopters. For the CO/CO2 ratio, with 100 kilns per arm we almost are powered for the more conservative ITT effect attained by the incentive arm but more than sufficiently powered to detect the larger effect size attained by the technical arm. With 100 kilns per arm at 90% power, we are powered to detect an effect size of -0.0064 in the CO/CO2 ratio, while we would need only 65 kilns per arm to detect an effect as large as -0.008, which is what the technical arm attained in the pilot. Somewhat surprisingly, the measured CO/CO2 ratio in the pilot was lower in the technical arm than in the incentive arm. This may simply reflect that the CO/CO2 ratio is a cross sectional measure that we captured based on data from a few hours in each kiln and so may not accurately reflect the performance over the whole season. Indeed, the first CO/CO2 ratio was measured before the incentive arm was even rolled out. Nevertheless, the calculations suggest that we will have sufficient power to be able to detect changes in CO/CO2 ratio with the interventions. Similar to percent of Class-1 bricks, our pilot results suggest kilns assigned to the incentive arm had a much lower specific energy consumption (SEC). While we will not be powered to detect effect sizes as small as what the pilot found in the technical arm, we are powered to detect effect sizes smaller than what the technical arm attained. With 100 kilns per arm at 90% power, we are powered to detect an effect size of -0.065 in SEC, while we would need 70 kilns per arm to detect an effect as large as -0.083, which is the ITT effect for the incentive arm compared to the control group. Practical Considerations We have focused on the threshold of 100 kilns per arm due to practical and logistical considerations of implementing such a complex intervention with fidelity. Since brick kilns initiate firing within about three weeks of each other, we face an outsized requirement for trained implementers to support the intervention in the few weeks leading up to kiln firing and the initial weeks of the season. Based on our pilot experience, we are confident that with the planned staff we can implement the intervention in 100 kilns per arm. Increasing the study size to > 100 kilns per arm would not only generate more expenses than we could cover but would impact the fidelity of the implementation. A poorly implemented technical intervention among 200 kilns per experimental arm would be unlikely to generate effect sizes of similar magnitude to the pilot if a small percentage of kilns adopts the intervention. Conclusion Balancing the practical and logistical considerations of the RCT with the power calculations, we are confident that we will be able to implement a well-executed trial among 300 kilns (with 100 kilns per arm). Our pilot achieved 60% uptake of the two most important components of the technical intervention. We used outcomes associated with this level of uptake for these power calculations. We anticipate that by implementing lessons learned in the pilot we will achieve a higher uptake in the full trial, which will further improve power. Even with conservative assumptions a 300-kiln study will be powered to detect effect sizes that are well within the bounds of what we observed in our pilot study and would be powered to detect a difference between treatment arms in Class-1 brick production with 80% power.

Institutional Review Boards (IRBs)

IRB Name
icddr,b Ethical Review Committee
IRB Approval Date
IRB Approval Number
Analysis Plan

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