Climate Change: Analyzing Gender, and Intersectional Approaches

The Challenge

The European Union has the ambitious goal of reducing its greenhouse gas emissions to 20% below 1990 levels by 2020 (European Commission, 2010). The U.S. supports emissions reduction through funding for alternative energy research, but has not legislated limits for total greenhouse gas emissions (Gurgel et al., 2011; Dixon et al., 2010). Both the EU and U.S. also have far-reaching goals for gender equality, but how these two important challenges—climate change and gender equality—might be related is rarely considered (European Commission, 2012; U.S. Equal Employment Opportunity Commission, 2012).

Method: Analyzing Gender, and Intersectional Approaches

Research on the relationship between gender and environmental impact is still in its infancy. Analyzing gender, in this instance, means comparing women’s and men’s behaviors and attitudes in relation to climate change. But researchers must ask: Which women? Which men? and compare groups of women and men based on social factors that also predict climate footprint, such as income, educational background, and geographic location. Viewing women as an undifferentiated group and opposing this to men as an undifferentiated group (simply disaggregating data by sex) misses important factors that influence gendered behaviors. Studies that analyze gender and control for other social factors avoid stereotypes and false correlations.

Gendered Innovations:

1. Understanding the Importance of Analyzing Gender in Relation to Intersecting Factors

Go to Full Case Study

The Challenge
Gendered Innovation 1: Understanding the Importance of Analyzing Gender in Relation to Intersecting Factors
Method: Intersectional Approaches
Sample Study
Transportation
Policy Implications
Conclusions

The Challenge

Strategies for managing global warming fall into two broad categories: mitigation and adaptation. This case study focuses on mitigation in industrialized countries, because these countries are responsible for the “largest share of historical and current global emissions of greenhouse gases” (United Nations, 2002). Mitigation involves strategies to slow anthropogenic climate change, typically by curbing emissions of greenhouse gases through changes in energy supply, transportation, agriculture and urban infrastructure, as well as lifestyle (Barker et al., 2007). The European Institute for Gender Equality (EIGE) states that “there is a lack of awareness of […] the gender aspects of mechanisms to mitigate climate change” as well as “a lack of research to inform debates on these issues” (EIGE, 2012).

Analyzing gender in climate change can support:

• Equality: Environmental legislation, policies, and programs may have different effects on women and men—as well as people of different income levels, ages and geographic locations (Denton, 2002). Gender analysis can contribute to policies that remedy—or at least do not exacerbate—existing social inequalities (EIGE, 2012; see Method: Rethinking Research Priorities and Outcomes).
• Effectiveness: Policies and programs aimed at reducing energy consumption are likely to be more effective if gender analysis ensures that they reach both women and men (Alber, 2011).
• Efficiency: All stakeholders (scientists, policy makers, consumers) should be involved in decision-making to help minimize the economic harm and maximize the ecological benefits of mitigation policies (Mearns et al., 2010; O’Neill et al., 2010).

Gendered Innovation 1: Understanding the Importance of Analyzing Gender in Relation to Intersecting Factors

This case study focuses on methodological approaches to gender analysis in climate change. From the start, gender analysis must avoid stereotypes and essentializing differences between women and men (Lau et al, 2021). Looking at women as an undifferentiated group and opposing this to men as an undifferentiated group (simply disaggregating data by sex) misses important factors influencing behaviors in relations to the environment. These factors include income, age, and geographic location.

Method: Intersectional Approaches

---

---

Stereotype	Factors to Consider
Men have larger “climate footprints” than women.	Consider the following methodological factors when analyzing automobile-related emissions. 1. Gender behaviors vs. income? Men do not necessarily have a higher marginal propensity to emit (MPE) than women—that is, men do not necessarily emit more greenhouse gases (GHGs) per unit of earned income. For example, in New Zealand, where data are available, women drive on average 8,000 km/year and men 12,000 km/year (New Zealand Ministry of Transport, 2011). But median incomes are NZD 19,100 for women and 31,500 for men (Statistics New Zealand, 2012). Using a linear model, women drive 0.42 km per NZD of income, whereas men drive 0.38 km per NZD. Therefore, if one considers a woman and man earning the same amount of money (for example, NZD 25,000), a woman would be expected to drive farther than a man: 10,500 km vs. 9,500 km. This disparity is not universal: For example, in Sweden, estimates suggest that men drive farther than women both in an absolute sense and relative to their incomes (Johansson-Stenman, 2001). 2. Distance vs. fuel efficiency? Women and men may, on average, drive cars of differing fuel efficiency, fuel types, and so on. Some studies report that women consider fuel efficiency more than do men when evaluating vehicles (Achtnicht, 2012). Other studies find “no statistically significant effects” related to age, gender, or education (Popp et al., 2009). 3. Distance vs. driving conditions? Women and men might, on average, drive under differing conditions (city vs. highway, low vs. high traffic congestion, etc.). Such conditions influence fuel efficiency and complicate the process of converting distance driven into fuel consumed (Barth et al., 2008).
Women care more about the environment than men, and therefore produce lower emissions.	Consider the following methodological factors: 1. Differences in attitudes are important, but often small. For example, in a EU-wide study, 69% of women and 67% of men stated that climate change was “a very serious problem.” Women (50%) and men (51%) are similarly likely to consider climate change to be among “the most serious problems currently facing the world as a whole” (Eurobarometer, 2009). 2. Income may intersect with gender as a predictor of climate concern (Franzen et al., 2010). 3. Education level and political affiliation may intersect with gender as a predictor of climate attitudes. In the U.S., where data are available, education and political affiliation interact: among self-identified Democrats, climate concern rises with increasing education; among self-identified Republicans, it declines with education (Hamilton, 2011).
Men have more knowledge than women about technical topics, including climate change.	Consider the following methodological issues: 1. Survey design: Survey instruments may affect judgments about women’s and men’s climate change knowledge. Surveys indicate that women are more likely to report “false positives” (incorrectly believe that a given factor does cause climate change) whereas men are more likely to report “false negatives” (incorrectly believe that a factor does not cause climate change) (O’Connor et al., 1998). 2. Self-reported vs. actual knowledge: In self-report studies, men may assert a greater level of climate knowledge than women (Eurobarometer, 2009). In tests of actual knowledge, results differ with some studies showing no significant difference (McCright, 2010; Sundblad et al., 2007).

View General Method

Sample Study

The chart below shows differences in energy use between single women and single men in multiple income categories (see source for definitions of income categories; Räty et al., 2009). Single persons were selected to avoid methodological challenges in attributing energy use to a specific individual within a multi-individual household. These data are:

• 1. Sex-disaggregated, allowing comparisons between women and men.
• 2. Income-disaggregated, allowing comparisons between people of different socioeconomic statuses.
• 3. Disaggregated by specific forms of energy consumption.

Data supporting this type of analysis are rare (EIGE, 2012). In lieu of comprehensive data, figures from Germany are presented. Methodological challenges in interpreting available data include:

• 1. Data do not directly reflect climate impact, as different forms of energy use have different climate impacts per megajoule (MJ) delivered (Granovskii et al., 2007).
• 2. Data are not necessarily representative of all Germans, as energy use patterns differ between single- and multi-person households (Brounen et al., 2012).
• 3. Data are likely to be non-representative of Europe as a whole, given that energy use—particularly for transport—differs between European countries (European Environment Agency, 2011).
• 4. Data do not reflect indirect climate impacts, which are significant for many energy sources. For example, transportation data consider only the direct release of GHGs from combustion engines—not the indirect release of GHGs associated with oil drilling, petroleum refining, fuel transportation, pipeline construction, and other production activities. (Charpentier et al., 2009).
• 5. Data do not necessarily reflect energy usage or climate impact incurred outside Germany itself (Davis et al., 2010; Mahesh et al., 2010).
• 6. Data do not reflect climate impact incurred through mechanisms other than GHG emission, including: a) deforestation, which reduces absorbance rates of CO₂ in the biosphere (Watson et al., 2000); and b) changes in terrestrial or atmospheric albedo (Piekle et al., 2002).

In Germany, single men consume on average 147,000 MJ/year, 37% more than single women’s 108,000 MJ/year (not shown in graph above) (Räty et al., 2009). The majority of this difference disappears when data are corrected for income. For example, in the lowest income category, single men consume only 1% more energy than single women (119,601 MJ vs. 118,368 MJ). In the highest income category, single men consume 2% more energy than single women (292,221 MJ vs. 285,234 MJ). Highest-income women consume 141% more energy than lowest-income women; for men, the figure is 144%. Income is therefore an important factor to analyze when looking at women's and men’s energy consumption.

We highlight the Räty et al. study because it is one of the few to consider gender behaviors in relation to other social factors. Looking at single women and men, however, does not take into consideration asymmetries in family relations: Women more often than men care for dependents (children and the elderly). An ideal study would compare women and men, controlling for all other relevant factors, including age, socioeconomic status, education, partnering status, household configuration (number of children and other dependents), geographic location (including density of settlement), and types of available transport. Occupation, age, geographic location, and household composition have all been shown to correlate with transport-related emissions in the United Kingdom (Brand et al., 2008). Future studies of gender in relation to climate change might consider these as other important intersecting factors.

Transportation

Within any given income group (see chart above), energy consumption differences between women and men are most pronounced in transportation. In the lowest income category, men expend 160% more energy on transport than women (21,372 MJ vs. 8,220 MJ). In the highest income category, men expend 48% more energy (75,624 MJ vs. 50,964 MJ). These differences shrink as income increases, but they do not disappear. They are significant because transportation is a major source of GHG emissions—see below:

Policy Implications

Integrated public and private transportation systems will be an important part of the solutions (see Rethinking Research Priorities and Outcomes). The International Energy Agency (IEA), United States Energy Information Administration, and World Business Council on Sustainable Development (WBCSD) all project worldwide transport energy consumption to increase 2% per year in the coming decades. As "almost all of this new [transport] consumption is expected to be in petroleum fuels […] CO₂ emissions will essentially grow in lockstep with energy consumption" (Ribeiro et al., 2007)—see below.

Individual Consumer Choice

Individuals can do their part to reduce emissions. They can choose to walk, bicycle, or take public transportation when possible. They can choose smaller, more energy-efficient cars. They can carpool, or travel shorter distances for leisure. But user choice goes only so far. Urban planning and design are central to minimizing the need for transportation, to maximizing efficient public transportation, and to mitigating gender inequality (for designing cities to enhance gender equality, see Case Study: Housing and Neighborhood Design). Examples of projects include:

Cycling Promotion Projects: State and local governments are working to promote cycling as a form of transportation in order to reduce GHG emissions and promote health (Andersen et al., 2012; Bauman et al., 2008). For example, the Danish government is studying cycling through its “Bikeability: Cities for Zero Emission Travel and Public Health” project. The project supports research into how demographics, bicycle infrastructure, and overall city design influence cycling (Bikeability, 2012). Analyzing gender may be important to planning new cycling infrastructure—considering women’s and men’s travel patterns and behaviors may enhance cycle route planning.

Other factors, however, may intersect with gender. These include:

• • Geographic locations: Available data suggest that women’s and men’s cycling behaviors differ substantially by location. In Denmark, for example, women are more than twice as likely as men to report commuting to work or school by cycling—36% versus 17% (Madsen, 2010). In the UK, women are only slightly more likely than men to report commuter cycling (Foster et al., 2011). In the U.S. and Australia, men are about three times as likely as women to report commuting by cycling (Garrard et al., 2012; Garrard et al., 2008).
• • Age: In Washington State, cycling was observed to be most common among adults age 25-45, declining at both lower and higher ages (Moudon et al., 2005).
• • Body Mass Index: In a study of 13 countries, cycling was observed to be correlated to healthy weights (Bassett et al., 2008).
• • Income: In Flanders, Belgium, low median income was associated with higher rates of commute cycling (Vandenbulcke et al., 2011).

Large-scale comprehensive studies provide limited information on the interaction between gender and other factors—more research is needed to increase understanding (Pucher et al., 2011).

Gender Budgeting in the Canton of Basel-Stadt, Switzerland: The Statistical Office of the Canton of Basel-Stadt collects sex-disaggregated data to inform transportation policy. Other variables are also considered—for example, the office has examined how both women’s and men’s transit expenditures change with age. The office also estimates how public funds spent on transport infrastructure benefit women and men (Office for Gender Equality of the Canton of Basel-Stadt, 2008).

Conclusions

Researchers are beginning to study climate change mitigation from a gender perspective. Efforts to analyze factors that intersect with gender—including income, age, travel patterns, geographic location, and environmental attitudes—contribute to a better understanding of climate impacts and responses to mitigation measures. This understanding may improve the effectiveness of mitigation strategies by ensuring buy-in from all energy users. It may also support efficiency and equality by achieving mitigation at the lowest possible social and economic cost, and by ensuring that costs are shared in equitable ways.