Team:Paris Bettencourt/Integrated Practices


  • Assay the state-of-the-art on the use of PERC in Paris.
  • Evaluate the effects of the prohibition of using PERC on a local level.
  • Evaluate the level of awareness on the danger of using PERC.
  • Gather information for the type of product the market is looking for.


  • We interviewed all dry cleaners in Paris face-to-face and gathered >250 testimonies.
  • We analyzed the impact of PERC use in the dry-cleaners in Paris.
  • We identified a negative correlation between PERC use and immigrant population.
  • We identified a problem of lack of information amongst the dry-cleaning community.
  • We discovered the needs of the dry-cleaners and applied them to our product design.
  • We got really fit from walking/biking hundreds of kilometres.


  • Elaboration of a questionaire to asses the impact of PERC use on the dry-cleaning industry in Paris
  • Evaluating of the level of awarenes of the dangers of using PERC
  • Gathering data for our product design
  • Socio-economic analysis of the data


Perchloroethylene (aka tetrachloroethylene or PERC) is the main chemical found in products used for dry cleaning worldwide. It removes stains from all types of fabrics, as it is an excellent solvent for organic materials. It is volatile, highly stable and non-flammable, reasons for which it is so widely used in this industry. The big selling point of this chemical is that it is quite effective and cheap, which means that almost all dry cleaners throughout the globe use it daily. However, PERC is toxic both for humans and the environment. Because of this, in 2022 PERC will be completely banned in France from dry cleaning establishments situated close to residential areas. Similar laws have already been passed in Denmark and the USA.

Impact of PERC on Paris dry cleaners

We conducted face-to-face interviews with all of the dry cleaners in Paris with the aim of understanding how they would deal with the banning of this chemical, as well as assessing their level of awareness of the dangers of PERC. We also aimed to understand the needs of the dry cleaners in order to design a product that would help make their daily lives easier.

Our survey (original questionnaire in French or translated version in English) allowed us to create a better suited product, and also allowed us to assess the level of awareness of the dry cleaners regarding the dangers of using PERC. The city of Paris is divided into 20 neighborhoods, called arrondissements, which differ according to many factors such as per capita income, number of immigrants, etc. This division is very interesting for our study because it allows us to make not only a global analysis of our data, but also a socio-economical one based on the differences in each arrondissement.

250 dry-cleaners and hundreds of kilometres walked later, we got to know which stains are the most difficult to remove and which fabrics are the most problematic.
We also got to know the cleaners' personal experiences with PERC and the impact that the compulsory change would have on their business. We learned that the already existing alternatives to PERC are not considered to be efficient enough.
Most cleaners expressed their concern for their business, being afraid that the new cleaning methods would result in a decrease of the quality of their services. Using the existing alternatives to PERC means that stain removal takes longer than with PERC. It also means that for the most difficult stains they need to use pre-washing products to be able to efficiently get rid of the stains.
We also learned that, among the most difficult stains to remove, red wine is particularly difficult. This type of stain is especially difficult to completely efface from white fabrics, since it has very strong pigments. We therefore decided to focus on developing a pre-washing product for getting rid of the verrry Frrrrench red wine stains.


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Figure 1 Reported PERC use per arrondissement and observed existing correlations. All data obtained from our questionnaire. A. We can observe marked differences in PERC use depending on the arrondissement. In particular, the 12th and 13th arrondissements have the highest percentage of dry cleaners using PERC, and are adjacent to the 20th, which has a much lower percentage of users. B. City-wide, our questionnaire found an almost equivalent number of dry cleaners using PERC. This could possibly be explained by the percentage of immigrants in each neighborhood, as we found a slightly inverse correlation between the percentage of immigrants in an arrondissement and the percentage of dry cleaners using PERC (C). However, we observed no correlation between PERC use and either the percentage of white collar workers (D) or income (E).

PERC use in Paris differs by neighborhood

We first wanted to find out the extent of PERC use in Paris. By visiting every dry cleaning shop in Paris (>250), we were able to determine the percentage of dry cleaners using PERC by neighborhood (or arrondissement), which revealed an uneven distribution of use (figure 1A). Indeed, the 12th and 13th arrondissements have high percentages of PERC use (>80%), and the northern arrondissements, the 17th, 18th, 19th and 20th, have some of the lowest use (<30%) throughout the city. Overall, our data shows that half the dry cleaners in Paris still use PERC as a solvent in their facilities (figure 1B), meaning that when the PERC ban takes full effect in 2022, half of the dry cleaners in Paris will have to invest in updating their shops.
Indeed, we learned through our interviews that many of the dry cleaners that do not use PERC had changed to alternative methods and chemicals in the previous 5 years.

In order to explain these in PERC use, we also analyzed the socio-economic characteristics of the neighborhoods. Interestingly, we observed a negative correlation between the percentage of immigrants in a neighborhood with the use of PERC (figure 1C).

In contrast, neither the percentage of professional "white-collar" workers nor the per capita income of the arrondissements correlated with PERC use (figure 1C-D).

Quercetin strains degradation

Figure 2 Awareness of PERC risks and public opinions on GMO use. Most respondents to our questionnaire felt that there was no risk associated with PERC use. B. The perception of the health risks of PERC use is related to the perceived difficulty of changing from PERC to an alternative. C-E. The perception of risk associated with using GMO alternatives to PERC also varied depending on the perceived health risks of PERC use.

Openness to PERC alternatives is related to perceived risk of PERC use

Next, we wanted to gauge awareness of the dangers of using PERC in the dry cleaning community. We found that the majority of dry cleaners have either no or light to moderate awareness of the risks of working with PERC (figure 2A). Moreover, many dry cleaners that felt that there was no risk were suspicious of the French government for banning the chemical.

In addition, dry cleaners who were more aware of PERC risks were also inclined to view the change to PERC alternatives as easier (figure 2B). This includes perception to alternatives based on GMO technology, as we mapped openness to GMOs throughout the city (figure 2C), and found that overall, dry cleaners are not concerned about GMOs (figure 2D). Finally, those who were not concerned about the use of PERC were also less concerned about the use of GMO alternatives (figure 2E).

Quercetin strains degradation

Figure 3 Types of stains observed and the difficulty of cleaning certain fabrics. A. Word cloud representing the most commonly observed stains by dry cleaners according to our questionnaire. Fat and wine stains were the most prevalent. B. Wine stains are considered to be very difficult to clean. C. All of the fabrics that we studied in our enzyme project (silk, linen, wool, and cotton) were considered difficult to clean.

Learning from tradition to innovate

We felt that understanding the needs of the dry cleaning industry was important in order to design a product that addresses problems that were most commonly faced in real life conditions.

Based on questionnaire responses, the most commonly observed stains are fat, wine, ink, and blood (figure 3A). Wine stains in particular are very challenging to remove, with the vast majority of respondents ranking them as “hard” (figure 3B). We also learned that dry cleaners who had already changed from PERC to new alternatives now have to use a pre-washing treatment for demanding stains such as wine. In contrast, PERC alone was sufficient to clean these stains before, indicating a need for a more efficient product for difficult stains.

Finally, we observed that silk is by far the most difficult fabric to clean (figure 3D). Indeed, the fragility of silk means that pre-washing treatments cannot be applied for very long without damaging the fabric, giving us more evidence for the need for more efficient stain treatments.

Producing a product with real-world applications

Lastly, based on the results of our questionnaire, we decided to focus on creating an enzymatic pre-washing product for wine stains. In order to increase the efficiency of this product compared to normal enzymatic treatments, we carried out a screen to find protein domains that would bind to the fabric to be treated. By fusing these Protein Binding Domains to enzymes, we wished to increase the efficiency of stain removing enzymes. This could be particularly effective for cleaning silk, as it would reduce the amount of pre-washing treatment needed, therefore reducing the damage incurred by washing.


The Human Practices were designed by the entire team with the help of our advisors. Face-to-face interviews were carried out by Alicia, Allison, Antoine V. and Sébastien (due to the fact that speaking French was necessary to perform them) and the data analysed by Alicia. We are not publishing our original data in order to protect the privacy of the questionnaire respondants. A big thank you to our advisors Jake and Jason for helping us analyse the results.


  • The list of the dry cleaners existing in Paris was obtained in the Yellow Pages (Pages Jaunes)
  • The statistics for each Arrondissement were obtained in the Mairie de Paris and in the Institut National de la Statistique et des Etudes Economiques