TASK 2.5.5 NATURAL EXPOSURE TESTING IN CALIFORNIA
Bibliographic record
Abstract
Airborne particulate matter that settles on a roof can either reflect or absorb incoming solar radiation, dependent on the chemical content and size of the particles. These light scattering and absorption processes occur within a few microns of the surface, and can affect the solar reflectance of the roof. Wilkes et al. (2000) tested 24 different roof coatings on a low-slope test stand and observed about a 25% decrease in the solar reflectance of white-coated and aluminum-coated surfaces as the time of exposure increased; however, the decrease leveled off after 2 years. SPRI Inc. and its affiliates studied the effect of climatic exposure on the surface properties of white thermoplastic single-ply membranes and determined that membranes lose from 30 to 50% of their reflectance over 3 years (Miller et al. 2002). The CMRC and its affiliates AISI, NamZAC, MBMA, MCA and NCCA exposed unpainted and painted metal roofing on both steep- and low-slope test roofs and found that after 3 years, the painted polyvinylidene fluoride (PVDF) metal roofs lost less than 5% of their original reflectance (Miller et al. 2004). The results of the three different weathering studies are very interesting in terms of their solar reflectance after 3 years of exposure. The white thermoplastic membrane and white ceramic coating with white topcoat had original reflectance measures that were about 20 percentage points higher than the painted metal; however, after 3-years of field exposure the solar reflectance of the painted metal exceeds that of the thermoplastic membrane and equals that of the coating. The long-term loss of reflectance appears driven by the ability of the particulate matter to cling to the roof and resist being washed off by wind and or rain. Miller et al. (2002) discovered that aerosol deposition introduced biomass of complex microbial consortia onto the test roofs and the combination of contaminants and biomass accelerated the loss of solar reflectance for the thermoplastic membranes and the roof coatings. Airborne contaminants and biomass were also detected on the painted metal roofs; however, the loss of solar reflectance was less than 5% for the painted metal roofs. The chemistry of the PVDF paint resin system uses similar organic film bonding to that responsible for Teflon , making it extremely chemical resistant and dirt shedding. Miller and Rudolph (2003) found the PVDF painted metals maintained solar reflectance even after 30 years of climatic exposure. Therefore the reduction of roof reflectance is closely related to the composition of the roof and to the chemical profile of the contaminants soiling the roof. Contaminants collected from samples of roof products exposed at seven California weathering sites were analyzed for elements and carbons to characterize the chemical profile of the particles soiling each roof sample and to identify those elements that degrade or enhance solar reflectance. The losses in solar reflectance varied from site to site and also varied at a give site based on the color of the coupon. The least drop in reflectance was observed in the alpine climate of McArthur while the largest drop occurred in sites near urban development. Light color samples were soiled after just one year of exposure. The darker color coupons did not show the same seasonal variations in solar reflectance as observed for the lighter colors. However, after an additional year of exposure the samples at all sites regained most of their solar reflectance due to rain and/or wind washing. The loss of reflectance appears cyclical with the onset of seasons having more rainfall. Solar reflectance of the cool pigmented coupons always exceeded that of the conventional pigmented coupons. Climatic soiling did not cause the cool pigmented roof coupons to lose any more solar reflectance than their conventional pigmented counterparts. The effect of roof slope appears to have more of an effect on lighter color roofs whose solar reflectance exceeds at least 0.5 and visually shows the accumulation of airborne contaminants. The thermal emittance remained invariant with time and location and was therefore not affected by climatic soiling. A thin-film deposition model was developed based on first principles, which simulates light interaction with a soiled substrate. This model was used in combination with the measured data to determine the solar absorptance and reflectance of particulate matter at each of the sites calculated using least squares fitting routines. Principal Component Analysis was used to determine the most important combinations of chemicals correlated with changes in solar absorption. Linear regression helped extract an approximate correlation using chromium, iron and elemental carbon concentrations. It appears that chromium ranks first, iron ranks second, and elemental carbon ranks third in importance to soil absorptance in the data
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.030 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".