The quality of air inside buildings, cars and other enclosed spaces is becoming important, but current methods give very variable results when emission tests for volatiles are carried out on polyurethane samples. Scientists at The Dow Chemical Company have developed a process that is designed to minimise the variability
By An Adams*, Esther Quintanilla, Stefan van Bloois and Adrian Birch
From the smell of a new car to the odour of a new bed-in-a-box mattress, polyurethane products are responsible for a number of emissions in the home and in automobiles.
The indoor air quality of cars, trucks and buildings is significantly affected by volatile organic compounds (VOCs), which are emitted from flexible polyurethane used inside these spaces.
However, there is a great deal of uncertainty when it comes to measuring the emissions from polyurethanes, despite many studies that have tried to improve on this uncertainty.
Often, these studies focus on developing and improving the analytical methods used to measure the emission of volatile substances from materials. They frequently neglect the history and pre-treatment of the samples that are being tested.
One of the most widely used tests is the German VDA 278 method, which is regularly specified to measure the level of volatile compounds in samples of polyurethane. Although it is well suited to the evaluation the emission potential of materials, there are often considerable lab-to-lab differences in tests of the same batch of foam.
The method yields two semi-quantitative values. The VOC value represents the total of the high-to-medium volatile substances. These are calculated as toluene equivalents. The test also produces a FOG value. This is the total of substances with low volatility, calculated as hexadecane equivalents.
Although specific instructions on sample handling and storage are provided in the VDA 278 standard, there is no comprehensive report on the impact of these parameters on the reliability of the VOC emission measurements.
Our approach focused on the effects sample storage and preparation had on VDA 278 test results. However, our findings are expected to be relevant for any selected method for the VOC emission measurement, including chamber, bag or headspace methods.
The VDA 278 test relies on common analytical methods based on thermal desorption, gas chromatography and mass spectrometry (TD-GC-MS). These are sound methods, but polyurethane foam is complex.
Table 1. Where variability comes from in VDA278 tests (relative standard deviation RSD, Test 1) | RSD VOC | RSD FOG |
---|---|---|
TD-GC-MS | ||
Optimized in-house RSD | Not Rel | |
In-house, same day repeatability small sample | ||
In-house, same day repeatability large sample | 11% | 12% |
In-house, monthly repeatability large sample | 23% | 11% |
Ring test variation specified in VDA-278 standard, 19 labs | ||
⢠polyester film | 31% | 53% |
⢠polyolefin film | 36% | 52% |
Note: For TD-GC-MS analysis of Tenax tubes the VOC/FOG distinction is not relevant |
Test methods
We carried out two studies. In the first, we tested to see if the level and composition of emissions were stable over a six-month period, and if these were consistent over the surface of a bigger piece of foam (a moulded backrest). In these stability studies, each system was designed to give a representative emission of volatile species from different components in the finished foam such as glycol ethers, volatile tertiary amine catalysts and silicone surfactants. These were not specifically designed to have low emissions. All foams were produced using commercially available materials. The results from this series of tests is shown in Table 1. In the second part, we designed a series of tests to measure the emissions from samples made with one foam formulation. These were taken and stored differently for different periods of time. We evaluated the influence of seven different storage/sampling conditions. Each of these was evaluated at a low concentration (Level 1) and a high concentration (Level 2), in different combinations. By performing a statistical design of experiments, the number of experiments was limited to 32, allowing the importance of all these seven conditions and possible interactions to be evaluated. The details of these factors are shown in Table 2.Table 2.Factors covered in Test 2 | ||
---|---|---|
Factor | Level 1 | Level 2 |
Hours between foaming and packing | 2 | 168 |
Days stored in analytical department | 1 | 14 |
Storage temperature (°C) | 4 | 20 |
Hours between unpacking and analysis | 1 | 168 |
Sample distance from surface (cm) | zero | 2 |
Did sample have skin | Yes | No |
Packaging type | Al foil + PE bag | Open PE bag |
Test results
Different test results obtained on the same foam can be the result of a number of influences. These include sample history â what temperature and relative humidity were the samples were exposed to, and for how long? We will look at these in more detail later. The analytical method, sample characteristics and sample preparation can also affect test results. The VDA 278 method is difficult to calibrate because the test does not name a reference material. The lack of a suitable reference material with a stable and reproducible emission of volatiles complicates standardisation of VOC emission measurements, and can lead to variable test results between laboratories. We decided to use our own calibration process with a standard control solution. This was a methanol base, into which 17 different compounds specified in the VDA test were dissolved. Our results had a relative standard deviation of between 0.3% and 2% when we analysed the control solution. This gave us confidence in the calibration method, the standard Tenax TA tubes used to process the samples, and the TD-GC-MS analytical procedure. Relative standard deviation (RSD) is a measure of how spread out the results of a series of tests are from the average value. A low standard deviation means that the results are generally close to the average, with a few outliers. A high standard deviation means that the results are much more widely spread.Variable samples
The samples used in the VDA 278 test are very small: just 15 mg is used in the TD-GC-MS procedure. We assessed the variability of the test by using nine different pieces of 15 mg from a backrest we had moulded. These produced results with a relative standard deviation of 11% for VOC value, and 13% for FOG. This is significantly higher than the analytical error of our standard control solution. The literature shows that, in some cases, the variability of the VOC emission levels from the sample itself exceeds the analytical uncertainty by an order of magnitude.Table 3. Summary of VOC and FOG data Test 2 | ||
---|---|---|
VOC | FOG | |
Mean | 184 | 640 |
SD | 45 | 171 |
RSD, all 32 samples | 24% | 27% |
RSD repetitions, 2 samples each treatment | ||
Note: units are µg total volatiles/g sample. | ||
SD: Standard Deviation, RSD Relative Standard Deviation |
Table 4.VOC emissions data, differing storage and conditioning times | ||||||
---|---|---|---|---|---|---|
All | Days storage | Days unpacked | ||||
VOC | 1 | 14 | Zero | 7 | ||
Mean | 184 | 224 | 158 | 204 | 165 | |
Stdev | 45 | 45 | 24 | 49 | 31 | |
RSD (%) | 24 | 20 | 15 | 24 | 19 | |
Note: units are µg total volatiles/g sample. | ||||||
SD: Standard Deviation, RSD Relative Standard Deviation |
Table 5.FOG emissions data, differing storage and conditioning times and sample position | ||||||
---|---|---|---|---|---|---|
All | Skin | Days storage | ||||
FOG | No | Yes | 1 | 14 | ||
Mean | 640 | 554 | 777 | 681 | 615 | |
SD | 171 | 85 | 156 | 195 | 155 | |
RSD (%) | 27 | 15 | 20 | 29 | 25 | |
Note: units are µg total volatiles/g sample. | ||||||
SD: Standard Deviation, RSD Relative Standard Deviation |
Table 6. VOC and FOG emissions from surface and bulk samples (no skin) | ||||||
---|---|---|---|---|---|---|
All | All | Surface | Bulk | |||
VOC | FOG | VOC | FOG | VOC | FOG | |
Mean | 178 | 557 | 188 | 646 | 173 | 512 |
SD | 40 | 85 | 58 | 84 | 29 | 37 |
RSD (%) | 22 | 15 | 31 | 13 | 17 | 7 |
Note: units are µg total volatiles/g sample. | ||||||
SD: Standard Deviation, RSD Relative Standard Deviation |