2.4.1 Relationships between sunshine availability and affectivity, stress and well-being

Further to the last comment above, it is interesting initially to test a very simple relationship — positive and negative affectivity scores (with mean averages from 1-5) as a function of the percentage of glass to living room floor area — see Fig.1; where high to low rank order of ratios is: solar tower (41.6%), quasi-solar low-rise (27.9%), solar medium-rise (25%), non­solar medium-rise (19.6%) and non-solar tower (13.7%). It should also be born in mind that the sample size for the solar and non-solar towers was respectively 16 and 12; 9 in the non­solar medium-rise block and 11 in the low-rise quasi-solar scheme; but only 2 in the solar medium-rise case. Therefore, one might reasonably have expected its graphical position to be out of kilter with other case studies, if, indeed, one could justify expectation of any logical correlation. However, this has not proved to be the case. It conforms to a distinct straight-line developing into a steep curve on the positive side, and a generally steeper curve on the negative side. The rate of steepness expresses the diminishing linkage between window size and affectivity. On the positive side, it looks as if this may occur above the 25% mark on the y-axis; while the negative side appears less defined. It may also be noted that a follow-up interview with a smaller sample (7 rather than 11) in the case of the medium-rise non-solar block, with the negative affectivity questions halved from 10 to 5, increased negativity to value of 1.51, rather than 1.25. Although this lies closer to an idealised curve, the smaller number of questions and respondents also give an indication of variability according to sample size. Similarly, with positive affectivity responses bundled down to 3 from10, the score increases to 4.14 from 3.60; in this case suggesting a steadier upward curve. In any event, although the relationships might seem overly simplistic, the results do support a

general trend for increasing positive affectivity with increasing window aperture, as well as a possible corresponding decrease in negative affectivity.

Fig. 1. Positive and negativity as a function of solar aperture to living rooms

The value given to sunlight access, and its added motivational effect, together with private and communal outdoor space is summarized in Table 1. The ratings correspond reasonably well with affectivity, although some responses may reflect what is available and others what would desirably be available. It is certainly evident that respondents with good access to sunlight and access to suitable private outdoor space valued the amenity afforded.

Table 1. Value of sunshine access and private and communal outdoor space

Case study>	solar	non-solar	solar	non-solar	quasi-solar
	high-rise	high-rise	medium-rise	medium-rise	low-rise
1)	4.62 (5)	3.33 (3)	5.0 (5)	3.7 (3)	4.0 (4)
2)	4.56 (5)	3.92 (5)	5.0 (5)	4.8 (5)	3.91 (4)
3)	4.56 (5)	3.92 (5)	5.0 (5)	4.8 (5)	3.91 (5)
4)	2.75 (2)	1.92 (1)	4.5 (5)	4.2 (5)	2.55 (3)

Legend: 1) value of sunlight access; 2) added motivation due to sunshine; 3) value of private outdoor space; 4) value of communal outdoor space. Note: ‘mode’ average in parenthesis

There are less clear tendencies for ‘perceived stress’ relative to solar and non-solar case studies. However, there is a clear-cut difference between the two towers — 1.24 mean score for the solar one compared with 1.88 for non-solar. The mode (most frequent score) for the solar tower was also very clearly 1.0 (signifying no perceived stress), with 13 out of 16 households scoring this way. However, both the solar and non-solar medium rise blocks also scored 1.0; and the quasi-solar reference blocks also scored low at 1.20, with 1.0 again the clear mode.

As anticipated, any relationship between well-being scores and sunshine is not evident, even though the solar tower had the lowest score of 1.57; the others being: 1.94 for the non-solar tower; 2.47 for the solar medium-rise block (small sample); 2.7 for the non-solar, medium — rise block (elderly residents); and 2.01 for the quasi-solar, low-rise blocks (elderly residents).

2.4.2 Relationships between sunshine availability and physical environmental conditions

It is generally accepted that factors such as intensity of occupancy are relevant to environmental outcomes such as indoor temperature and humidity. Social habits such as smoking are also known to influence ventilation regimes [7], but is fairly evenly spread among case studies. Table 2 summarizes the estimates of intensity of occupancy in person — hours per m3 volume.

Table 3 then gives mean, maximum and minimum temperatures and relative humidity (RH) in different seasons for spot readings taken in sets of living rooms and main bedrooms in each

case; while Table 4 gives the equivalent values for CO2 for different seasons, whichever is the greatest. The modest differences between solar and non-solar models in terms of temperature and relative humidity are noteworthy, suggesting that despite significant differences in terms of energy efficiency and energy costs most respondents were able to heat to a reasonable level.

Table 2. Mean occupant intensity estimates (person-hrs/m3) Case study> solar non-solar solar non-solar quasi-solar high-rise high-rise medium-rise medium-rise low-rise living room 0.75 0.90 0.15 1.33 0.60 kitchen 1.65 2.05 0.60 2.30 1.00 main bedroom 1.12 1.38 0.60 1.62 0.67 Table 3. Mean Temperatures (oC), RH (%) Case study> solar non-solar solar non-solar quasi-solar high-rise high-rise medium-rise medium-rise low-rise Winter Temp. RH Temp. RH Temp. RH Temp. RH Temp. RH liv. mean 21.8 32.7 21.1 37.1 22.1 49.8 19.0 38.0 liv. min. 20.0 28.0 19.0 31.0 21.3 44.0 18.8 36.8 liv. max. 23.0 39.0 22.0 45.0 22.9 55.6 19.2 40.1 Spring Temp. RH Temp. RH Temp. RH Temp. RH Temp. RH liv. mean 21.6 38.4 20.7 23.8 19.3 44.5 19.6 34.8 liv. min. 19.5 33.4 17.8 14.0 15.5 34.9 19.3 34.1 liv. max. 24.3 51.1 23.5 43.8 21.5 52.5 19.9 35.5 Winter Temp. RH Temp. RH Temp. RH Temp. RH Temp. RH bed. mean 21.3 31.5 20.9 36.6 22.1 49.8 bed. min. 19.0 28.0 19.0 31.0 21.3 44.0 bed. max. 23.0 38.0 22.0 41.0 22.9 55.6 Spring Temp. RH Temp. RH Temp. RH Temp. RH Temp. RH bed. mean 22.5 35.0 21.5 28.5 18.6 41.8 bed. min. 20.2 31.1 18.5 18.8 14.6 32.2 bed. max. 26.1 40.9 24.8 41.7 21.7 49.1

Table 4. Mean CO2 (ppm: acceptable range 600-825; tolerable max.1,000) Case study> solar non-solar solar non-solar quasi-solar high-rise high-rise medium-rise medium-rise low-rise liv. mean 852 Dec 05 1,066 Dec 05 945 Oct 06 1,196 Mar 06 815 liv. min. 600 730 760 740 590 liv. max. 1,370 1,670 1,130 1,830 1,200 bed. mean 776 Mar 06 1,019 Mar 06 915 Oct 06 1,033 Mar 06 bed. min. 630.0 620 720 770 bed. max. 970.0 1,380 1,110 1,710

Data in Table 4 indicate that the solar tower enjoys better air quality than the non-solar tower; and that the solar medium-rise block enjoys better air quality than the non-solar medium-rise block. There is also similarity comparing the values for the non-solar tower and the non-solar medium-rise block. Here only the minimum values fall within the range normally regarded as acceptable; the maxima are well above the threshold taken as the tolerable maximum; and the mean values are somewhat above this threshold. In the solar tower only three of sixteen flats came above this limit in their living rooms in the case of winter readings. In the case of the solar medium-rise block, the sample was too small to pass a similar comment — one of the two tenants came above the 1,000 ppm limit. This appears noteworthy given the presence of

the MVHR system. However, it was revealed during the interview that the occupant avoided using the MVHR due to a phobia about insects entering via the ducts. It is also worth noting that the CO2 readings for the quasi-solar low-rise were similar to those of the tower block. Given the respective similarities between the solar tower sample and the quasi-solar low-rise sample with respect to positive affectivity (4.42 cf. 4.67) and perceived stress (1.24 cf.1.20 with 1.0 the mode in each case), taken together with general level of energy efficiency (see

2.1 and 2.3 above) and solar access (Fig. 1), it is reasonable to posit that this may engender a fairly relaxed attitude to opening windows.

It is also of interest to note that the average temperature regimes in the solar and non-solar towers appear quite similar, as does RH; while comparing respective medium rise blocks, both RH and temperature are somewhat higher in the solar case. Durational readings, Table 5, provide a more in-depth picture of temperature and humidity, although the sample is limited.

Table 5. Temperatures (oC), RH (%) and mixing ratio (g/kg) ranges: Living Rm. Case study> solar non-solar solar non-solar quasi-solar high-rise high-rise medium-rise medium-rise low-rise temp. ‘mode’ 19.5-20.5 19.5-23.5 20.5-24.5 18.5-22.7 21.5-25.0 temp. min/max 18.0-26.5 18.7-24.7 20.0-29.0 15.5-23.5 20.5-26.5 RH ‘mode’ 30-52% 30-52% 33-50% 35-50% 32-52% RH min/max 28-70% 28-60% 30-35% 30-85% 32-55% MR %>7 g/kg 13.5%(5.7%) 97.6%(98%) 12.1 %(13.9%) 99.7%(99.7%) 15.0%(22.1%) MR %>10 g/kg.0%(0%) 0%(22.6%) 0%(0%) 16.3%(18.1%) ©X О ©x о Notes: i) Frequency of Mixing Ratio (MR) %s > 7 and 10 g/kg in parenthesis are for bedrooms; ii) ‘Mode’ in this table signifies the majority range of values, not a recurring single value

The last two rows in Table 5 are of particular significance. Although RH seems to be mainly within a reasonable range, the percentage frequency of mixing ratio of dry to moist air (MR) values above the threshold of 7 g/kg is worryingly high in the non-solar cases; especially given that there are still significant percentages above 10 g/kg. The threshold or benchmark value is used because this is the level above which it has been found that the dust mite population will readily grow [8]. The lower levels of frequency in this regard for the solar cases correspond with the better air quality. Further, it is relevant that the higher levels of ‘intensity of occupation’ (Table 2) in the non-solar cases correspond with the poorer air quality (Table 4) and higher frequency of humidity (mixing ratio) above ‘growing threshold’ for dust mites (Table 5). Table 6 summarizes presence of dampness due to condensation and/or presence of mould. Again, the non-solar housing is manifestly at a disadvantage compared with the solar, or even quasi-solar counterparts.

Table 6. Instances of presence of damp/mould Case study> solar non-solar solar non-solar quasi-solar high-rise high-rise medium-rise medium-rise low-rise windows 1 ex 16 (6%) 5 ex 12 (42%) 1 ex 2 (50%) 5 ex 7 (71%) 1 ex 11 (9%) walls 0 5 ex 12 (42%) 0 1 ex 7 (14%) 0 clothes 0 1ex 12 (8%) 0 0 0

It is also likely that the ones with relatively high incidence of condensation and/or mould will have expressed their dissatisfaction via negative affectivity and/or perceived stress. Links to poor health or well-being are also a possibility, especially relative to the responses to questions concerning nasal ailments (33% for the non-solar tower cf. 12.5% for the solar tower).

3. Conclusions

Firstly, the analysis does support an apparent association between sunlight/energy-efficiency attributes and perceived stress and positive affectivity, particularly the latter where a logical connection could be anticipated due to questions being directed at positive emotions. For the converse reason, an association between sunlight and negative affectivity is less convincing. Causality relating to health/wellbeing is also so diverse that it was unlikely to yield any tangible association with access to sunlight. Having said that, the solar tower does have the lowest incidence of ailments. The responses relating to how much residents valued sunshine and were additionally motivated by its presence, as well as private outdoor space in the form of ‘sun-traps’, add further weight to this conclusion, aligning with the positive affectivity scores. Secondly, there is evidence of a relationship between availability of sunlight in homes and some physical environmental indicators: a) CO2, expressing air quality; b) humidity, when expressed as a percentage frequency above particular mixing ratio thresholds which in turn denote the likelihood of dust mite propagation and hence risk of asthma. The greater the solar access, the better was the air quality, and the lower were the levels of mixing ratio (MR) or vapour pressure.

Furthermore, the presence of damp or mould was greater in the non-solar case studies. Although, one might have expected such incidence to relate to general energy-efficiency and the ability to heat dwellings, there were no examples of unsuitably low temperatures during any of the periods used for monitoring (mainly winter and spring, but also some in autumn). Instead, the explanation appears to be that the more energy-efficient, and also more sunlit, homes encourage residents to be more relaxed in relation to ventilation — i. e. more inclined to open windows. It is also apparent that they are able to do this without unduly compromising economy — the solar case studies are also the cheapest to heat. It also seems likely that thermal capacity is relevant in playing a part in allowing intermittent opening of windows, without any undue energy penalty.

The evidence presented is such that the basic hypothesis appears to merit further detailed investigation. Environmental architects and engineers have for too long only been evaluating passive solar design in terms of potential energy saving rather than psychosocial benefits, that are in turn linked to wider ‘quality of life’ environmental and sustainability indicators.

References

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[7] Ho H M, (1995). User-performance sensitivity of small sunspaces in a Scottish housing context, PhD Thesis, Mackintosh School of Architecture, University of Glasgow, UK

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