Category Archives: Changement climatique/Climate change

Solar photovoltaic panels and rebound effect (of electric consumption)

An excellent article describing the interdisciplinary approach of rebound effects in German solar photovoltaic user households (prosumer) has been recently published (Galvin et al. 2022). Authors highlight the most important steps of their interdisciplinary process: an engagement to dialogue between various background researchers, to design “from the beginning” an interdisciplinary method and findings analysis strategies, to identify the detailed role of each researcher teams, and to develop a shared vocabulary.

This paper presents an overview of method, findings, and common analysis/interpretation of 3 studies (see Fig 1). This research team explored the potential rebound effect in term of electricity consumption in prosumers.

Qualitative interviews of rural prosumers (N= 19)

Three frameworks emerged form thematic analyses: a “geo-sociotechnical” domain (association between technology, self-regulation and sun), interaction between ‘positive and negative’ rebound effects, and financial/psychological explanations. An “income effect” also was identified in early photovoltaic adopters (i.e., 2000’s). Indeed, extra electricity was purchased around 0.5 euro/kWh, and household ‘benefits’ may have been associated with more travels,.. Here, it was not necessary a rebound effect in term of electricity consumption. A ‘price effect’ was observed (i.e., the kWh price was lower in more recent adopters), so it was less interesting to purchase its own electricity. A moral licensing effect was reported among participants.

National online cross-sectional questionnaire (N= 1291 vs 297 (non)prosumer).

Prosumers were younger, lived in a larger house, had higher incomes, had more frequently a heat pump, and high level of environmental concerns. Researchers would quantify a possible rebound effect occurring after households install a photovoltaic system. To identify possible correlated of rebound effects, they also collected data about attitudes, economic incentives, and behaviors. No significant differences was observed for electric consumption between (non)prosumers (even if I don’t clearly understand their statistical approach).

Data analysis of co2online dataset

This no profit organization have a data-set of people self-reporting their electricity consumption (1992-2018). 79 households reported their consumption before and after their photovoltaic system installation. A rebound effect of 9.6% was found. Authors highlighted a possible limit, a possible self-monitoring effect on electricity consumption. In other words, this rebound effect may be underestimated.

rebound effect

As expected in an interdisciplinary research project, all findings were collectively discussed. The team decided to ‘re-run’ their analyses to investigate the effect of feed-in tariff (major change in 2011 from 0.5 euro/kWh to 0.09 euro/kWh, see Fig 3) and regulations changes (i.e., allowed self-consumption) on their previous results.

A significant difference was found between (non)prosumers in 2011 sub-sample, prosumers consumed more electricity (18%, c-à-d 675.57kWh/y) than control participants. A rebound effect of 14% was observed. Analyses based on co2online data-set suggested a possible rebound effect of 33% in post-2011 installers. It is important to note that ‘income effect’ was reported in interview only in pre-2011 users. Again, the level of self-reported environment concerns (questionnaire measure) was not related to electricity consumption. It contrasts with findings from some interviews. Furthermore, authors suggested that this important rebound effect in post-2011 prosumers could be problematic because it decrease the renewable electricity going into the grid.

By extrapolating the findings and conclusions, this investigation may be a good illustration of interdependence between decision to buy a solar photovoltaic mostly based on (economic and ‘rational’ psychological factors), the system rules moving (e.g., kWh price), technical and power improvements of photovoltaic systems, and strengthened personal ecological values (for better of for worst). This figure synthesizes this idea.

  • Galvin, Ray, Johannes Schuler, Ayse Tugba Atasoy, Hendrik Schmitz, Matthias Pfaff, and Jan Kegel. 2022. “A Health Research Interdisciplinary Approach for Energy Studies: Confirming Substantial Rebound Effects Among Solar Photovoltaic Households in Germany.” Energy Research & Social Science 86 (April): 102429. https://doi.org/10.1016/j.erss.2021.102429.

Gendered inequalities, health and climate change

In climate change perspectives, three inequalities have been well-documented: inequalities between (1) and within countries (2), and inequalities between generations (3). However, the gendered inequalities are and will be exacerbated by climate change consequences (4). An open-access chapter presents the most important issues of this question (4). Authors add a health perspective combined with climate change gendered inequalities.

A set of key points:

  • Deaths related to natural disasters are higher among women. Their motor skills are generally lower than men (e.g., running, swimming, climbing). Also, they have a poor access to climate-related information.
  • Women may be more “biologically vulnerable” during heat waves. High temperatures also are associated with complications in pregnancy and poor neonatal outcomes.
  • Women are more exposed to indoor pollution (from fuel-wood stoves) and have higher burden to outdoor air pollution.
  • Women are the worst affected by food insecurity because they are (most of time) responsible for cooking, feeding caring…. and they eat less.
  • During dry seasons, women spend time and energy to collect water. It increases their risk of heat illness

You can find an interactive map displaying 130 studies that investigate how men and women are affected by climate change here .

You

  • 1. Guivarch C, Taconet N. Global inequalities and climate change. In: The Routledge Handbook of the Political Economy of the Environment. Routledge; 2021.
  • 2. United Nations Environment Programme. The emissions gap report 2020. 2020.
  • 3. Thiery W, Lange S, Rogelj J, Schleussner C-F, Gudmundsson L, Seneviratne SI, et al. Intergenerational inequities in exposure to climate extremes. Science [Internet]. 8 oct 2021 [cité 27 déc 2021]; Disponible sur: http://www.science.org/doi/abs/10.1126/science.abi7339
  • 4. Kommu V, Alexander D, Lingam L. Gendered vulnerabilities and health inequities. In: Climate Change and the Health Sector [Internet]. 1re éd. London: Routledge India; 2021. p. 90‑7.

Climate change & physical activity behaviours : A challenge for health psychology

In November, I gave a talk for the European Health Psychology Society SIG Equity, Global Health and Sustainability. Slides are available here.

In conclusion, I presented an updated definition of health behaviors : “actions and patterns of actions within a context that enable human choices that result in reduced or net zero carbon, energy, water, and ecological footprint and (in)directly result in equitable improvement, restoration, and maintenance of health for humans and nonhuman health for current and future generations” (1).

I also presented a set of priorities for health psychology community:

  • To systematically present climate change consequences in courses
  • A responsibility of ‘senior researchers’ to reshape their research questions in CC perspectives
  • To develop collaborations with environmental/climate  psychology) researchers
  • To accelerate implementation of effective interventions to cope with CC/health issues
  • To prioritize social change >>> technology based solutions
    To develop multilevel interventions with multi- or interdisciplinary perspectives
  • To reorganize our research practices (carbon footprint of congress)

Finally, I shared the link to download our info-graphics (open access).

Chevance G, Fresán U, Hekler E, Edmondson D, Lloyd S j, Ballester J, et al. Thinking health-related behaviors in a climate change context: A narrative review [Internet]. OSF Preprints; 2021 [cited 2021 May 19]. Available from: https://osf.io/pb8vc/

Complex associations between air pollution, insomnia symptoms and physical activity

In a preprint co-authored with G. Chevance et al. (1), we examined the associations between climate change consequences and health behaviors. We identified a set of (bi)directional associations between natural hazards, rising sea level, greenhouse gas emission, temperature increase and the following behaviors : alcohol consumption, cigarette smoking, water consumption, preventive behaviors, sleep, food related behaviors and physical activity (PA) domains. We synthesized these associations with this figure.

This system map offers a “meta” and simplified perspective of previous studied associations. However, we did not include the potential associations between health behaviors. Indeed, these associations are not well identified and may be different in function of the time scale (i.e., daily associations vs long term association), study participant characteristics and assessment tools (see e.g., see the following reviews for PA sleep associations at short and long term (2,3)).
A recent cross-sectional study investigated the associations of long-term exposure to ambient air pollution with insomnia symptoms in a large Chinese sample. Furthermore, the authors examined whether PA domains had a potential “buffering effect”.
In the perspective of our review, it’s particularly relevant because we could improve the subsection about sleep, PA domains, and air pollution (4). Also, China is one of the most polluted countries in the world.

Strengths of this study:

  • -residents >3 years in their current residence
  • relative good measure of insomnia symptoms
  • good control of indoor air pollution and environmental factors (e.g., temperature)

I synthesized Xu et al. findings with the following slides (4). A buffering effect of physical activity was found for leisure PA and moderate PA “doses”. High levels of total and occupational PA accentuated the air pollution – insomnia association. In brief, the potential positive role of PA varied in term of domain, dose and air pollution measures.

 

 

This study is a good illustration of health behaviors associations complexity. In a climate change perspective (i.e., higher level of air pollution in cities around the world in next decades), physical activity promotion and insomnia prevention/treatment strategies should be revised.

  • 1. Chevance G, Fresán U, Hekler E, Edmondson D, Lloyd S j, Ballester J, et al. Thinking health-related behaviors in a climate change context: A narrative review [Internet]. OSF Preprints; 2021 [cited 2021 May 19]. Available from: https://osf.io/pb8vc/
  • 2. Kredlow MA, Capozzoli MC, Hearon BA, Calkins AW, Otto MW. The effects of physical activity on sleep: a meta-analytic review. J Behav Med. 2015 Jun;38(3):427–49.
  • 3. Atoui S, Chevance G, Romain A-J, Kingsbury C, Lachance J-P, Bernard P. Daily associations between sleep and physical activity: A systematic review and meta-analysis. Sleep Medicine Reviews. 2021 Jun;57:101426.
  • 4. Xu J, Zhou J, Luo P, Mao D, Xu W, Nima Q, et al. Associations of long-term exposure to ambient air pollution and physical activity with insomnia in Chinese adults. Science of The Total Environment. 2021 Oct;792:148197.

 

For the climate, please stop to support the FC Bayern Munich ! 

What is the related travel annual carbon footprint of German Football Bundesliga fans ?

Two German researchers collected the following self-reported data about age, sex, level of education, income, environmental values, club membership, favorite team and travel behavior in relation home and away matches (for 2018/19 season) via an online questionnaire (1). They included 539 fans and >50% of respondents were a member of their favorite club.

  • The average seasonal carbon footprint / fan was 311 kg CO2 eq (almost 3% of annual carbon footprint for a German)
  • Highest carbon footprints were found for FC Bayern Munich & RB Leipzig (i.e., 673.8 and 387kg CO2 eq )
  • Private car was the most used frequent mode of transport

The following factors were associated with higher carbon footprint: club membership, fan of Bayern or Leipzig. It’s important to note that income and environmental values were not significantly associated.

This study is a first approach of carbon footprint sport fans. The relative low carbon footprint associated with travels is relatively specific (i.e., geographical scale but also train and public transport availability). It should be very different, if same data were collected in NHL or NBA fans.

1. Loewen C, Wicker P. Travelling to Bundesliga matches: the carbon footprint of football fans. Journal of Sport & Tourism. 2021 May 27;0(0):1–20.