Difference between revisions of "Team:Paris Bettencourt/Integrated Practices"

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             <li>We discovered the needs of the dry-cleaners and applied them to our product design.
 
             <li>We discovered the needs of the dry-cleaners and applied them to our product design.
 
             <li>We got really fit from walking/biking hundreds of kilometres.
 
             <li>We got really fit from walking/biking hundreds of kilometres.
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<h2 class="red">Introduction</h2>
 
<h2 class="red">Introduction</h2>
 
<p>
 
<p>
Perchloroethylene (aka tetrachloroethylene or PERC) is the main chemical found in products used for dry cleaning worldwide. It acts as a solvent to remove stains from all types of fabrics, since 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 quite cheap, which means that almost all dry cleaners throughout the globe use it daily.  
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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.  
The problem is that PERC is quite toxic, both for humans and the environment. Because of all these reasons, the French government has set up to 2022 the complete banning of PERC from dry cleaning establishments situated close to residential areas. Similar laws had been already passed in Denmark and the USA.  
+
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.  
 
</p>
 
</p>
  
  
<h2 class="red">Impact of PERC in Paris' dry cleaners</h2>
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<h2 class="red">Impact of PERC on Paris dry cleaners</h2>
 
<p>
 
<p>
We interviewed face-to-face all dry cleaners in Paris with the aim of understanding how they would deal with the interdiction of this chemical, as well as assess their level of awareness of the dangers of PERC. We also aimed to understand what were their needs, to try to design a product that would help make their daily life easier. <br><br>
+
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. <br><br>
Our survey (<a href="https://static.igem.org/mediawiki/2016/7/72/Paris_Bettencourt-LEquestionaire.pdf">original questionnaire in French</a> or <a href="https://static.igem.org/mediawiki/2016/4/41/Paris_Bettencourt-THEquestionaire.pdf">translated version in English</a>) allowed us to create a better suiting product, but it also allowed us to assess the level of awareness of the dry cleaners regarding the dangers of using PERC. The interesting thing about Paris is that the city is divided into 20 neighborhoods, the 20 <i>arrondissements</i>. This division is very interesting for our study because it allows us to make not only a statistical analysis of our data, but also a socio-economical one based on the differences in styles of living in each arrondissement.<br><br>
+
Our survey (<a href="https://static.igem.org/mediawiki/2016/7/72/Paris_Bettencourt-LEquestionaire.pdf">original questionnaire in French</a> or <a href="https://static.igem.org/mediawiki/2016/4/41/Paris_Bettencourt-THEquestionaire.pdf">translated version in English</a>) 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.<br><br>
250 dry-cleaners and hundreds of kilometres walked after, we got to know which are the most difficult stains to remove and which are the most problematic fabrics. <br>
+
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. <br>
We also got to know their personal experiences on the use of PERC and the impact that the compulsory change would have on their business. We learnt that the already existing alternatives to PERC are not efficient enough. <br>
+
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. <br>
Most of the dry cleaners expressed their concern over their business, being afraid that the new methodologies would result in a decrease of the quality of their services. Using the existing alternative to PERC means that it takes longer to remove the stains than it used to take when they used 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. <br>
+
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. <br>
We learnt that, among the most difficult stains to remove, red wine is a particularly difficult one to get rid off. This type of stains is especially difficult to remove without a trace on white fabrics, since it has very strong pigments. We therefore decided to focus on developing a pre-washing product for getting rid of the <i>verrry Frrrrench</i> red wine stains. <br>
+
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 <i>verrry Frrrrench</i> red wine stains. <br>
 
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<img src="https://static.igem.org/mediawiki/2016/e/e3/Paris_Bettencourt-HP_PERC.jpg" alt="Quercetin strains degradation" style="width:900px;">
 
<img src="https://static.igem.org/mediawiki/2016/e/e3/Paris_Bettencourt-HP_PERC.jpg" alt="Quercetin strains degradation" style="width:900px;">
 
<p>
 
<p>
<b> Figure 1: Reported PERC use per arrondissement and observed existing correlations.</b> All data obtained from analysis of the answers to the questionnaire. Original set of data not displayed publicly to preserve the anonymity of the dry cleaners.
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<b> Figure 1: Reported PERC use per arrondissement and observed existing correlations.</b> All data obtained from our questionnaire. <b>A.</b> 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>B.</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 (<b>C</b>). However, we observed no correlation between PERC use and either the percentage of white collar workers (<b>D</b>) or income (<b>E</b>).  
 
</p>
 
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</div>
  
<h3>On the use of PERC in Paris</h3>
+
<h3>PERC use in Paris differs by neighborhood</h3>
 
<p>
 
<p>
The first question we wanted to answer with our questionnaire was the one of how widely spread was the use of PERC in Paris. Our data shows that half the dry cleaners in Paris still use PERC as a solvent in their dry-cleaning facilities (figure 1B), which means that <b>in the followup to 2022, time when the chemical will be prohibited in France, half of the dry-cleaners of Paris will have to make the investment of updating their facilities</b>.<br>
+
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.<br>
Although we do not have numbers for it because we did not originally include the question in our questionnaire, we found out that many of the dry cleaners that do not use PERC had changed to the alternatives in the previous 5 years.<br><br>
+
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.<br>
Looking at figure 1A, we can see that the distribution of the use of PERC in Paris is not homogeneous, with some arrondissements using it much more than others. <b>The 12th and 13th arrondissements were the ones in which the use of PERC was still more prominent, and the north arrondissements, the 17th, 18th, 19th and 20th were the ones in which PERC was most seldom used</b>.<br><br>
+
<br>
We analysed the <b>socio-economic characteristics</b> of those arrondissements, trying to find some correlation that would help us explain the differences on the use of the chemical.<br>
+
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). <br><br>
We initially expected that on the "richest" arrondissements the use of alternatives would be more frequent. We based this hypothesis on the thought that businesses that were located in expensive arrondissements would be able to support the monetary effort of changing their infrastructures easier than those located in poorer arrondissements. Nonetheless, <b>a correlation between the mean income and the use of PERC was not found</b>. We hypothesised that this might be due to the fact that the French Government has made the effort to support monetaryly the dry cleaners that change their infrastructures to be able to use the alternatives, and thanks to this help, the economical differences between arrondissements have been diluted. <br><br>
+
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).  
We also expected to see a correlation between the awareness of the population that inhabited the arrondissement and the use of PERC. We hypothesised that those arrondissements in which their inhabitants had easier access to high education would be more sensibilised to the dangers of using the chemical, and would therefore pressure their local dry-cleaners to change to the alternatives. Nonetheless, once again, our original premise was completely wrong, since <b>no correlation between white workers and use of PERC was found</b>. <br>
+
The one correlation that we were able to find was that existing between the use of PERC and the percentage of immigrant population. Those with a <b>higher percentage of immigrant population displayed the lowest values of PERC use</b>. Once we observed this correlation we realised that we had been looking at the data with the wrong perspective all along.<br>
+
Paris is traditionally a city with a high percentage of immigrant population, and the different populations are well distributed throughout the 20 arrondissements. Nonetheless, the immigrant population is higher in the north districts, which are also the poorer ones. Something that could explain the correlation observed between immigrant population and PERC use is that the people that live in the 17th, 18th, 19th and 20th might both live and work in dry cleaners in these arrondissements. Therefore, a stronger concern would exist on those dry cleaners, since the effects on health of using PERC would be more strongly felt by those both living and working close to PERC-using facilities.<br>
+
A second explanation could also be that the French Government helps more those who need it the most, and would therefore have begun helping the dry cleaners in those arrondissements first.<br>
+
A third explanation could also be that the 17th, 18th, 19th and 20th arrondissements have seen an increase in population in the last decades. The new population living there could have started new business, choosing to use the alternatives directly, whereas in the older arrondissements like the 1st and the 6th, with long-stablished dry-cleaning facilities, the change would be slower.  
+
 
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<img src="https://static.igem.org/mediawiki/2016/5/54/Paris_Bettencourt-HP_RISKS.jpg" alt="Quercetin strains degradation" style="width:900px;">
 
<img src="https://static.igem.org/mediawiki/2016/5/54/Paris_Bettencourt-HP_RISKS.jpg" alt="Quercetin strains degradation" style="width:900px;">
 
<p>
 
<p>
<b> Figure 2: Awareness of the population on the risks of using PERC.</b> All data obtained from analysis of the answers to the questionnaire. Original set of data not displayed publicly to preserve the anonymity of the dry cleaners.
+
<b> Figure 2: Awareness of PERC risks and public opinions on GMO use. <b>A.</b> Most respondents to our questionnaire felt that there was no risk associated with PERC use. <b>B.</b> The perception of the health risks of PERC use is related to the perceived difficulty of changing from PERC to an alternative. <b>C-E.</b> The perception of risk associated with using GMO alternatives to PERC also varied depending on the perceived health risks of PERC use.</p>
 
</p>
 
</p>
 
</div>
 
</div>
  
<h3>On the awareness of Parisian dry-cleaners</h3>
+
<h3>Openness to PERC alternatives is related to perceived risk of PERC use</h3>
 
<p>
 
<p>
The second question we wanted to answer with our questionnaire was the one of how aware are the dry-cleaners of the risks of working with PERC. Looking at figure 2A, we can see that the majority of dry-cleaners have no perception, or light to moderate perception of the risk of working with PERC. This shows that <b>the information is not reaching the dry-cleaning industry effectively</b>. Moreover, many dry-cleaners answered that they believed there to be no risks of working with PERC, and felt suspicious for the reasons why the French government was taking these measurements. These results are very interesting and show that <b>there needs to be a more effective communication between the authorities and the dry-cleaning industry</b>, and that there has to be a channel for discussion between them, in order for the industry to regain confidence. <br>
+
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 (<b>figure 2A</b>). Moreover, many dry cleaners that felt that there was no risk were suspicious of the French government for banning the chemical.<br>
Our questionnaire also suggests that, as can be seen in figure 2B, dry-cleaners in which the workers were concerned about the health problems associated with PERC found the transition to new alternatives easier, showing that obviously the concern for health overcomes the economical struggle.<br><br>  
+
<br>
Lastly, we evaluated the concern of Parisian dry-cleaners on the use of enzymes that were produced in GMO. The overall picture is that in the entirety of Paris, there were <b>not many dry cleaners that were preoccupied with the prospect of using GMO enzymes</b>. Our data also shows that amongst the people that reported to have light or no concern on the effect of PERC on human health the percentage of people concerned about the use of GMOs on laundry was lower than that of those that were worried about it.
+
In addition, dry cleaners who were more aware of PERC risks were also inclined to view the change to PERC alternatives as easier (<b>figure 2B</b>). This includes perception to alternatives based on GMO technology, as we mapped openness to GMOs throughout the city (<b>figure 2C</b>), and found that overall, dry cleaners are not concerned about GMOs (<b>figure 2D</b>). Finally, those who were not concerned about the use of PERC were also less concerned about the use of GMO alternatives (<b>figure 2E</b>).
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<img src="https://static.igem.org/mediawiki/2016/b/b2/Paris_Bettencourt-HP_STAINS.jpg" alt="Quercetin strains degradation" style="width:900px;">
 
<img src="https://static.igem.org/mediawiki/2016/b/b2/Paris_Bettencourt-HP_STAINS.jpg" alt="Quercetin strains degradation" style="width:900px;">
 
<p>
 
<p>
<b> Figure 3: Most difficult stains and fabrics.</b> All data obtained from analysis of the answers to the questionnaire. Original set of data not displayed publicly to preserve the anonymity of the dry cleaners.
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<b> Figure 3: Types of stains observed and the difficulty of cleaning certain fabrics. A.</b> Word cloud representing the most commonly observed stains by dry cleaners according to our questionnaire. Fat and wine stains were the most prevalent. <b>B.</b> Wine stains are considered to be very difficult to clean. <b>C.</b> All of the fabrics we to studied in our enzyme project (silk, linen, wool, and cotton) were considered difficult to clean.
 
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<h3>Learning from tradition to innovate</h3>
 
<h3>Learning from tradition to innovate</h3>
 
<p>
 
<p>
As explained before, we developed our questionnaire with two things in mind; first, to evaluate the impact of PERC on the dry-cleaning industry, and second, to <b>get to know the industry's needs in order to produce a product that could really be useful in real life conditions</b>. In order to do so, we got to know what were the needs and struggles that the dry-cleaners go through on a daily base. We learnt from what it is traditionally done in order to innovate. <br><br>
+
We felt that understanding the needs of the dry cleaning industry was important in order to design a product that address problems that were most commonly faced in real life conditions. <br>
First, we got to know that the <b>most common stains</b> that drive people to take their clothes to the dry cleaners are <b>fat, wine, ink and blood</b> (figure 3A). <br>
+
<br>
We also learnt that <b>red wine stains are particularly challenging to remove</b>, with the great majority of dry-cleaners answering that they were hard to remove. Interestingly, we learnt those dry cleaners that had already made the change from PERC to new alternatives had now to use a <b>pre-washing treatment for demanding stains, such as red wine</b>. This did not happen before with PERC, that was enough to clean the stains on its own.<br>
+
Based on questionnaire responses, the most commonly observed stains are fat, wine, ink, and blood (<b>figure 3A</b>). Wine stains in particular are very challenging to remove, with the vast majority of respondents ranking them as “hard” (<b>figure 3B</b>). 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.<br>
Lastly, we got to know that the <b>hardest fabric to clean stains from</b> is, without a doubt, </b>silk. This is mainly due to the fragile nature of the fabric. The fragile nature of silk means that the pre-washing chemicals cannot act for a long time without damaging the fabric, highlighting the need for efficient stain-treatments.<br><br>
+
<br>
We, therefore, decided to <b>focus on creating an enzymatic pre-washing product for wine stains</b>. In order to make the product very efficient, we decided to </b>fuse our enzymes to Fabric Binding Domains</b>, taking special attention to silk binding domains, since it was the most difficult fabric to clean stains from. By concentrating the enzymatic activity on the fabric we make the process more efficient, hence <b>protecting the fragile nature of this fabric</b>.
+
Finally, we observed that silk is by far the most difficult fabric to clean (<b>figure 3D</b>). 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.
 
</p>
 
</p>
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</div>
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<h2 class="red">Reflections on the data</h2>
 +
<h3>PERC use by arrondissement</h3>
 +
Upon taking these results together, we realized that we had been looking at the data with the wrong perspective. Paris is traditionally a city with a high immigrant population that is well distributed throughout the 20 arrondissements. Nonetheless, the immigrant population is higher in the north districts, which are also the poorer ones. Something that could explain the correlation observed between immigrant population and PERC use is that the people that live in the 17th, 18th, 19th and 20th might both live and work in dry cleaners there. Therefore, the health effects of PERC use would be more strongly felt by those both living and working close to PERC-using facilities. A second explanation could also be that the French Government gives assistance according to need, and would therefore have begun helping the dry cleaners in those arrondissements first. A third explanation could also be that the 17th, 18th, 19th and 20th arrondissements have seen a increase in population in the last decades. The new population living there could have started new business, choosing to use the alternatives directly, whereas dry cleaners in the older arrondissements have been established longer, and therefore less likely to have changed equipment.</p>
 +
</div>
 +
<h3>Producing a product with real-world applications</h3>
 +
 +
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.
 +
</p>
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</div>
 
 
 
<h2 class="red">Attributions</h3>
 
<h2 class="red">Attributions</h3>
 
<p>
 
<p>
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. A big thank you to our advisors Jake and Jason for helping us analyse the results.
+
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.
 
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Revision as of 13:00, 19 October 2016



Applied human practices: a study on the use and impact of PERC in Paris

Goals

  • 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.

Results

  • 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.

Introduction

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.

Results

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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).

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Figure 2: Awareness of PERC risks and public opinions on GMO use. A. 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).

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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 we to 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 address 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.

Reflections on the data

PERC use by arrondissement

Upon taking these results together, we realized that we had been looking at the data with the wrong perspective. Paris is traditionally a city with a high immigrant population that is well distributed throughout the 20 arrondissements. Nonetheless, the immigrant population is higher in the north districts, which are also the poorer ones. Something that could explain the correlation observed between immigrant population and PERC use is that the people that live in the 17th, 18th, 19th and 20th might both live and work in dry cleaners there. Therefore, the health effects of PERC use would be more strongly felt by those both living and working close to PERC-using facilities. A second explanation could also be that the French Government gives assistance according to need, and would therefore have begun helping the dry cleaners in those arrondissements first. A third explanation could also be that the 17th, 18th, 19th and 20th arrondissements have seen a increase in population in the last decades. The new population living there could have started new business, choosing to use the alternatives directly, whereas dry cleaners in the older arrondissements have been established longer, and therefore less likely to have changed equipment.

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.

Attributions

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.

References

  • 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