German Longitudinal Environmental Study (GLEN)

The German environmental panel GLEN (German Longitudinal Environmental Study) is a Germany-wide mixed-mode panel study for social science research on the environment, climate, and sustainability. Through GLEN, data on environmental attitudes and behavior, environmental inequality, and acceptance of environmental policy measures are collected in up to four self-administered surveys per year. The study is funded by the German Research Foundation (DFG) and is conducted as a long-term project at Heidelberg University, the University of Konstanz, LMU Munich, and the Rhineland-Palatinate Technical University of Kaiserslautern (RPTU). Until May 2025, the University of Leipzig was also involved in the project. This dataset contains data from the first five surveys, which were conducted between November 2024 and January 2026. Recruitment Survey: Importance of various aspects of life (family, friends, leisure, work, education, studies, and religion); life satisfaction; description of place of residence in terms of: good shopping options, reliance on a car, good leisure activities, good healthcare, plenty of nature, good job opportunities; attachment to place of residence; Homeownership; number of people in the household; assessment of one’s own financial situation; frequency of use of various modes of transportation (car, e-bike, bicycle, e-scooter, train/bus in the city and region; train/long-distance bus for longer distances); Internet access at home; personal Internet use in the past week; frequency of various leisure activities in the past four weeks (visiting cafes, pubs, restaurants; going to the movies, concerts, or the theater; watching TV, movies, series, or videos; volunteering; using social media; ordering products online; sports, exercise, physical activity); self-assessment of health status in the past four weeks; perceived pollution and noise levels at place of residence; extent of concerns regarding economic development in Germany, environmental protection, consequences of climate change, wars, crime, public safety, immigration to Germany, other concerns mentioned; extent of environmental concerns regarding: decline in biodiversity, condition of forests, pollution in soil, water, and air, plastic waste and microplastics in nature, soil sealing, and water scarcity; interest in politics; party preference (Sunday question) ; skepticism regarding climate change (evidence of climate change is unreliable, climate change is merely a natural fluctuation, too much fuss about climate change, climate protection is a waste of time, technologies will prevent a catastrophe); satisfaction with democracy in Germany; support for various political measures for environmental and climate protection (ban on new cars with internal combustion engines starting in 2035, permanently free use of public transportation, funded by tax revenue, more wind turbines, including near residential areas, measures against extreme weather events (e.g., flood protection, heat protection), Increase in the CO2 price on fuels, heating oil, and natural gas, with revenue used for climate and environmental policy/full reimbursement to all citizens); approval of the following statements: I find the constant demand to live in an environmentally conscious manner unreasonable; it is fair if the wealthy contribute more to climate protection. Demography: Age (month and year of birth); sex; employment status; education: highest general education qualification; type of vocational training qualifications; type of higher education degree; citizenship; first other citizenship in addition to German citizenship; first other citizenship if no German citizenship, second other citizenship if no German citizenship; country of birth: Germany; other country of birth; region of birth in Germany (West Germany, old federal states including West Berlin, East Germany, new federal states, GDR, former German territories up to 1945; Father’s and mother’s country of birth: Germany. The following were additionally coded: respondent ID; sample; serial number of the interview; survey type; survey participation mode; interview date (day, month, and year of participation); panel consent (initial request); panel consent (follow-up request); email address provided; questionnaire evaluation (interesting, long, difficult); respondent made other comments; flag variables for inconsistencies. Generated variables: gender and year of birth (register data imputed with recruitment data); CASMIN education classification (9 cat., 3 cat.); ISCED A 2011 education classification (8 cat., 3 cat.); migration background; place of residence: RegioStaR4 (differentiated regional statistical region type), federal state; highest general education school leaving certificate (openly recoded); vocational qualification: (as yet) no vocational qualification (openly recoded), in-company vocational training/apprenticeship (openly recoded), school-based vocational training (openly recoded), master craftsman/technician, DHS, vocational academy. (open-coded), University of Applied Sciences/University of Applied Sciences (open-coded), other vocational qualification (open-coded), university degree: Master’s, Diploma, Magister, State Examination (open-coded); Bachelor’s (open-coded), Doctorate (open-coded); weighting factors. Paradata based on technical information during the survey: Device (computer, tablet, smartphone); time the interview began; time of the last change to the data record; page the participant last edited; last page edited in the questionnaire; time spent on individual pages; proportion of missing responses (weighted by relevance). Starter Survey: Expectations for the new year compared to the previous year; expectations regarding the standard of living in Germany in ten years; expectations regarding technical innovations in ten years (improvements in daily life through artificial intelligence, meeting energy needs through wind and solar energy, self-driving cars, secure energy supply through nuclear fusion, existing nuclear power plants in Germany will go back into operation); opinion on electric cars (more environmentally friendly than other cars, not suitable for everyday use, harmful to the German economy), characterization of place of residence in terms of: good shopping opportunities, plenty of nature, good public transportation infrastructure, safe from flooding (split indicator); social cohesion in the place of residence (people help each other, know each other well, can trust each other, get along well, have little respect for law and order); Frequency of use of various modes of transportation (car, e-bike, bicycle, e-scooter, train/bus in the city and region; train/long-distance bus for longer distances); ownership of the Deutschlandticket in the following months: November 2024, December 2024, January 2025, and February 2025; in none of these months; money spent on New Year’s Eve fireworks; frequency of media consumption (online social networks, television, movies, series, podcasts, daily newspapers, periodicals, magazines); news sources used in the past week (e.g., TV news, 24-hour news channels, radio news, print newspapers, websites/apps, etc.); social networks used in the past week (e.g., YouTube, Facebook, WhatsApp, etc.); frequency of social contact with people in clubs, with coworkers in one’s free time, with friends, and with family members; Important issues for Germany in 2025 mentioned; extent of concerns in various areas (economic development in Germany, environmental protection, consequences of climate change, wars, crime, public safety, immigration to Germany); opinion on politicians in Germany (do they tell the truth, are they corrupt, do they do their job well, are they in politics for their own benefit, are they competent, do they try to do their best for the country); priorities for a new federal government mentioned; support for various policy measures (expansion of bus and rail services, reforestation, ban on or higher taxation of domestic flights, speed limits of 100/120/130 km/h on highways, higher taxes on meat and sausage, legally mandated conversion of heating systems to renewable energy) (split indicators). Vignette experiment on the acceptance of transportation policy measures with different attributes regarding the framework conditions of the measure, the year of the measure, the type of measure, and approval of the measure. Opinion on a ban on the sale of fireworks to private individuals; preferred measures against highly sugary beverages (higher taxes, ban on advertising, call to avoid highly sugary beverages); split indicators and response options; Personality: Optimism (I always see the bright side of things; I always expect good things from the future); interpersonal trust (most people have good intentions, you can’t rely on anyone anymore, in general you can trust people); self-efficacy (in difficult situations I can rely on my abilities, I can handle most problems well on my own, and I can usually solve even strenuous and complicated tasks well). Demography: Age (month and year of birth); sex; The following were additionally coded: Respondent ID; Sample; Survey serial number; Survey type; Survey participation mode; Interview date (day, month, and year of participation); Confirmation of email address; new email address provided; questionnaire evaluation (interesting, long, difficult); respondent provided other comments; incentive: voucher, bank transfer, or donation; account information provided for bank transfer incentive. Generated variables: Sex and year of birth (register data imputed with recruitment data); CASMIN education classification (9 cat., 3 cat., data from the recruitment survey); ISCED A 2011 education classification (8 cat., 3 cat.), data from the recruitment survey); migration background; place of residence: RegioStaR4 (differentiated regional statistical region type), federal state. Paradata based on technical information during the survey: Device (computer, tablet, smartphone); time the interview began; time of the last change to the data record; page the participant last edited; last page edited in the questionnaire; time spent on individual pages; proportion of missing responses (weighted by relevance). Wave 1a 2025: Life satisfaction; frequency of leisure activities in the past month (meeting friends, relaxing, doing nothing, watching TV, movies, series, or videos, sports, fitness, indoor/outdoor exercise, other outdoor activities e.g., walking, gardening); frequency of food consumption (fresh fruit, vegetables, salad, fish, seafood, beef, lamb, other meats, sausage, dairy products, eggs, cheese, sweets, sweet pastries, salty snacks); food management (saving leftovers and eating them later, making spontaneous decisions while shopping, discarding food after the best-by date); frequency of grocery shopping (regional products, organic products, Fair Trade products, low-calorie products, special offers); enjoyment of shopping (clothing and shoes, home furnishings and decor, technical and electronic devices); regarding the past two weeks: emotional well-being (annoyed, lonely, overwhelmed, under pressure, happy, stressed); overall physical health; limitations in daily physical activities; assessment of pain level; fatigue; duration of sleep at night; satisfaction with sleep; impairment due to the following symptoms (anxiety: nervousness, fearfulness, or tension; worries that could not be stopped or controlled; depression: little interest or joy in activities, low mood, melancholy, or hopelessness); frequency of use of various modes of transportation (car, motorcycle, scooter, e-bike, bicycle, e-scooter, train/bus in the city and region; train/long-distance bus for longer distances); frequency of walking; possession of a driver’s license; monthly pass for bus and train for this month (Deutschlandticket or other monthly pass); number of privately used motor vehicles: (car(s); for the three most frequently used cars, the following were asked: vehicle class, fuel type, and kilometers driven in the last 12 months; number of privately used two-wheelers (motorcycle, scooter, moped); for the two most frequently used two-wheelers, the following were asked: Type, fuel, and kilometers driven in the last 12 months; private flights in the last twelve months; number of short-haul, medium-haul, long-haul, and ultra-long-haul flights; vacations: type of vacation in the last 12 months (e.g., city break, relaxation vacation, cruise, etc., no vacation); frequency of short trips, vacations with 4 to 7 overnight stays, and vacations with 8 or more overnight stays; duration of the longest trip in the past 12 months; type of accommodation. Housing: Changes in the landscape of the residential area (solastalgia: grief over what has been lost, annoyance at changes, development generally for the better, little change in recent years); extreme weather events experienced at the place of residence in the last three years (heat, drought, storm, flooding, wildfire, heath fires, none of the above); perceived noise pollution with windows open and closed due to road traffic noise, railway noise, and aircraft noise; type of building for the primary residence; year the house was built; bedroom window facing the street; number of other people in the household; relationship to these other people in the household; number of people in the household under the age of 14; pets, type and number of pets; apartment size (in square meters); number of rooms in the apartment; heating temperature in the living area; primary heating source; supplemental heating; frequency of turning down the heat when leaving the apartment; type of modernization measures carried out in the last 15 years; solar system for electricity or hot water and type of solar system; Home electricity consumption in kWh per year and in euros per month; use of green electricity; additional home/house; household appliances owned (refrigerator, freezer, microwave, dishwasher, washing machine, clothes dryer, portable air conditioner, none of the above); number of desktop PCs, laptops/notebooks, tablets/smartphones, and televisions used. Environmentally conscious behavior in daily life; environmentally conscious behavior dependent vs. independent of others’ behavior; environmentally conscious behavior in one’s personal circle (one’s own expectations of others, others’ expectations, most people behave in an environmentally conscious manner); environmental awareness (concern about future environmental conditions, we are heading toward an environmental catastrophe, limits to growth have been exceeded, environmental problems are exaggerated, politicians are doing too little for environmental protection, we should reduce our standard of living); assessment of one’s own CO2 emissions compared to others in Germany; frequency of waste separation and recycling; trust in institutions; frequency of use of various news sources for political news; protest actions in the last 12 months (e.g., participation in demonstrations, involvement in disruptive actions or citizen initiatives, etc.); topics of the protest actions mentioned; agreement with the goal of climate-friendly transformation in Germany; skepticism toward theories on climate change (evidence for climate change is unreliable, climate change is merely natural fluctuation, too much fuss over climate change, climate protection is a waste of time, unsure whether climate change is occurring, human influence on the climate is exaggerated, too early to address the issue, human activity has little influence on climate change); impact of extreme weather: The government should provide financial support to all those affected; mandatory insurance against storm damage for buildings; support for various political measures in the area of environmental and climate protection (e.g., stricter regulations for the insulation of older residential buildings, a ban on new cars with internal combustion engines starting in 2035, etc.); support for more space for bike lanes as well as more space for green areas in cities; support for the aforementioned measures, even if this means less space for cars. Demography: Employment status or current occupation; specific occupation; economic sector/industry of current occupation; assessment of one’s own economic situation; net household income (grouped); height in cm; weight in kg; current relationship status; marital status; age (month and year of birth). The following were additionally coded: Respondent ID; sample; serial number of the survey; survey type; survey participation mode; interview date (day, month, and year of participation); Flag variables for inconsistencies and implausible values; new address provided; invite via email in the future; email address provided; questionnaire evaluation (interesting, long, difficult); respondent made other comments; incentive: voucher, bank transfer, or donation; account information provided for bank transfer incentive. Generated variables: sex and year of birth (register data imputed with recruitment data); CASMIN education classification (9 cat., 3 cat., data from the recruitment survey); ISCED A 2011 education classification (8 cat., 3 cat.), (data from the recruitment survey); migration background (data from the recruitment survey); body mass index (BMI); occupation, activity according to ISCO08 and KldB2010; place of residence: RegioStaR4 (differentiated regional statistical region type), federal state; weighting factors. Paradata based on technical information during the survey: Device (computer, tablet, smartphone); time the interview began; time of the last change to the data set; page the participant last edited; last page edited in the questionnaire; time spent on individual pages; proportion of missing answers (weighted by relevance). Interwave 2025a: Importance of quality of life in the place of residence regarding neighborhood, short distances, internet connection, plenty of space, and recreational opportunities; leisure activities in the past four weeks (meeting friends, relaxing, doing nothing, watching TV, movies, series, or videos, sports, fitness, indoor/outdoor exercise, other outdoor activities e.g., walking, gardening); Employment; characteristics of employment (physically demanding, often exhausted, interesting work, primarily outdoors in the summer); skepticism toward theories on climate change (e.g., the evidence for climate change is unreliable, climate change is a natural fluctuation in Earth’s temperature, etc.); Internet: Internet usage activities in the past four weeks; attitude toward Internet usage (prefer meeting people online rather than in person, would be lonely without the Internet, often spend too much time online); trust in people on the Internet; perception of temperature at place of residence in summer 2025; feeling of physical strain due to temperatures in summer 2025; sleep problems due to temperatures in summer 2025; problems experienced by family/friends due to temperatures in the summer of 2025; perception of extreme weather events (often think about extreme weather events, feel worried when thinking about extreme weather). Vignette experiment on CO2 pricing with different questions (fairness of individual CO2 pricing, reduction of CO2 emissions through CO2 pricing, support for the presented CO2 pricing), split indicator: CO2 pricing vs. cultural offerings. Self-assessment of awareness regarding current CO2 pricing regulations; effectiveness of a CO2 price increase in reducing CO2 emissions; estimate of the proportion of people in Germany who support a CO2 price increase; preferred use of government revenue from the CO2 price. Leisure activities and cultural offerings: Attitudes toward leisure time (I have too little free time to do everything I want, it is important to use my free time wisely, etc.); attendance at leisure events in the past four weeks (e.g., movie theaters, art exhibitions, classical music concerts, etc.); opinion on public funding for various cultural offerings (classical music concerts, concerts by local or lesser-known artists, art exhibitions, production of German films, adult education centers, swimming pools); groups of people who should be eligible for discounts on cultural events; belief in personal control (I am in control of my own life; if I try hard, I will succeed; my life is largely determined by others; my plans are often thwarted by fate); interest in the following survey topics: health and well-being, daily life, nature and the environment, politics, climate change, leisure and recreation. The following were additionally coded: respondent ID; sample; survey serial number; survey type; survey participation mode; interview date (day, month, and year of participation); new address provided; questionnaire evaluation (interesting, long, difficult); respondent made other comments; incentive: voucher, bank transfer, or donation; account information provided for bank transfer incentive. Generated variables: gender and year of birth (register data imputed with recruitment data); CASMIN education classification (9 cat., 3 cat., data from the recruitment survey); ISCED A 2011 education classification (8 cat., 3 cat.), data from the recruitment survey); migration background (data from the recruitment survey); Occupation, activity according to ISCO08 and KldB2010; Place of residence: RegioStaR4 (differentiated regional statistical region type), federal state; Weighting factor. Paradata based on technical information during the survey: Device (computer, tablet, smartphone); time the interview began; time of the last change to the data record; page the participant last edited; last page edited in the questionnaire; time spent on individual pages; proportion of missing responses (weighted by relevance). Wave 1b 2025: Importance of life domains (family, friends, leisure, work, education, studies, religion); life satisfaction; attachment to place of residence; length of residence; green view from apartment windows; garden, balcony, or rooftop terrace, none of the above; frequency of use of various modes of transportation for errands and leisure; monthly pass for bus and train for this month (Deutschlandtickelt or other monthly pass); secondhand items purchased in the last 12 months (clothing, shoes, furniture, household appliances, electronic devices, other items, none of the above); secondhand items sold or given away; frequency of repairs to household appliances and electronic devices (repairing them oneself, having them repaired); life goals (achieving excellence, experiencing community and mutual care, avoiding conflicts, being happy, being rich, avoiding risks and uncertainties, being free and independent, having an exciting daily life, maintaining traditions and customs, advocating for tolerance and diversity); materialism (admire people with expensive homes, cars, or clothing; admire those who forgo a luxurious lifestyle); self-assessment of risk-taking; subjective social status; memberships in selected clubs and organizations; active or passive membership; employment status or current occupation; new school diploma obtained in the last 12 months; type of new school diploma; new vocational training certificate obtained; type of new vocational training certificate; type of university degree obtained; monthly net income; changed jobs in the last six months; occupational status; specific occupational status: employees and workers; civil servants: career group; self-employed: number of employees; farmers: area farmed; weekly working hours; number of working days per week; number of days working from home per week; ability to work from home; distance to work/school/university/training; mobility: type and frequency of transportation used for the commute to work/school/university/training. Housing, Partnership, and Family: Number of other people in the household; relationship status; duration of current relationship; living with partner; children; age and sex of up to three children; living with the child; gender of partner; partner’s highest level of general education; partner’s employment status or current occupation; partner’s occupation and industry; whether partner owns a car; whether partner follows a vegetarian or vegan diet; whether partner is concerned about the environment; division of labor within the partnership in various areas (cooking, preparing meals, grocery shopping, taking out the trash, recycling, fixing things); frequency of disagreements in the following areas: financial matters, leisure activities, environmentally conscious behavior in daily life, decisions about everyday purchases, politics, and diet. Children and parenting: Parenting goals (healthy diet, being lovable, being liked, being able to fit into groups, accepting rules, obeying, sense of responsibility, environmentally conscious behavior); for the oldest child, the following were asked: Health status; frequency of outdoor leisure time; attends school/daycare; travels to school/daycare alone or with parents; usual mode of transportation to school/daycare; distance from home to school/daycare; frequency of various discussion topics (everyday problems, nutrition, health behaviors, environmental and climate protection, politics); whether opinions on these topics tend to be similar or different; specific topics related to environmental and climate protection where differing opinions were mentioned; whether the oldest child is concerned about the environment and the consequences of climate change; Importance of the child receiving the following: new toys on a regular basis, brand-name clothing, electronic games/toys, toys and clothing free of harmful substances, preference for used over new toys and clothing; the child’s freedom to decide on clothing purchases, which cell phone (or whether to have one at all), and the mode of transportation used for the commute to school. Health: Illnesses or ailments in the past twelve months; limitations in daily life due to health status; smoking status: Number of cigarettes, pipes, cigars, or cigarillos smoked per day, as well as e-cigarettes or vapes per day and the amount of e-liquid used per day; people who smoke in the home; concerns about economic development in Germany, environmental protection, the consequences of climate change, wars, crime, public safety, immigration to Germany, and other concerns mentioned; environmental concerns (decline in biodiversity, condition of forests, pollution in soil, water, and air, plastic waste and microplastics in nature, soil sealing, water scarcity). Politics: Party preference (current poll); satisfaction with democracy in Germany; opinion on the topic of taxes vs. social benefits; opinion on immigration policies for foreigners; authoritarianism (leaving important decisions to leaders, established practices should not be questioned, making troublemakers feel unwelcome); acceptance of protests for and against environmental and climate issues (demonstrations, blockades, or occupations, property damage); media and online services used for political news in the past week; news avoidance; likelihood of extreme weather events in the place of residence over the next three years (extreme heat, extreme drought, storms, flooding, forest or heath fires); perception of being well warned about extreme weather; assessment of the ability to protect oneself from extreme heat in daily life; behavior at home during heat waves (e.g., exterior sun protection, fans, or portable air conditioners, etc.); assessment of public heat protection measures in the place of residence; expected impacts of climate protection on the German economy; support for the following climate protection measures: supporting climate-friendly behavior, making climate-damaging behavior more expensive, prohibiting climate-damaging behavior by law); preference regarding German climate policy (measures against the causes vs. against the effects of climate change); funding for climate policy in Germany: too much, too little, or just right; approval of Germany’s climate policy relative to other countries (Germany should not play a leading role, Germany should support poorer countries in environmental and climate protection, opinion on climate justice at the international level (affected countries should have more influence, rich countries should pay more than poorer countries); assessment of various measures for environmental and climate protection (permanent free use of public transportation, financed by tax revenue, more wind turbines even near residential areas, increasing the CO2 price on fuels, heating oil, and natural gas and using the revenue for climate and environmental policy, increasing the CO2 price and fully refunding all citizens, mileage-based tolls for all roads, 30 km/h speed limit in built-up areas); Perception of relative deprivation (I never get what I’m actually entitled to; others always get all the benefits); agreement with statements on justice (those who perform better at work should also earn more; society should take special care of the weak and those in need; there should be no major differences in income and wealth; those at the top of society should have better living conditions); agreement with statements on climate justice in Germany (the rich should pay more for climate protection than the poor; those most affected by climate change should have a greater say in climate protection); groups more severely affected by the consequences of climate change (tend to be poorer rather than richer people, women rather than men, foreigners rather than Germans, older rather than younger people); car ownership; energy poverty (I have to dress warmly at home because of heating costs; I can barely afford the high monthly electricity bills; I have enough money to replace a broken washing machine; I sometimes can’t afford to fill up my car with gas; I sometimes don’t have enough money to get my car repaired). The following were additionally coded: Respondent ID; Sample; sequential survey number; survey type; survey participation mode; interview date (day, month, and year of participation); new address provided; invite via email in the future; email address; questionnaire evaluation (interesting, long, difficult); respondent made other comments; incentive: gift card, bank transfer, or donation; account information provided for bank transfer incentive; Illness in the last 12 months: at least one additional illness mentioned; update on highest general education qualification, vocational qualification, and university degree. Generated variables: sex and year of birth (register data imputed with recruitment data); CASMIN education classification (9 cat., 3 cat.); ISCED A 2011 education classification (8 cat., 3 cat.); migration background (data from the recruitment survey); occupation and activity according to ISCO08 and according to KldB2010 (from Wave 1a); occupation and activity of the partner according to ISCO08 (from Wave 1a) and according to KldB2010 (from Wave 1a); place of residence: RegioStaR4 (differentiated regional statistical region type), federal state; weighting factor. Metadata based on technical information during the survey: device (computer, tablet, smartphone); time the interview began; time of the last change to the data record; page the participant last edited; last page edited in the questionnaire; time spent on individual pages; proportion of missing responses (weighted by relevance). Gross-datasets for all waves: Respondent ID; survey indicator, invitation mode, mode of the first, second, or third reminder; date of the first invitation; date of the first, second, or third reminder; survey start and end dates (CAWI); year of birth and sex from registry data; Case included in the SUF for the current wave; not included in all waves: Experiment 1 invitation indicator: illustrated figure in the initial survey; Experiment 2 invitation indicator: 10% exclusion in the 2025a interwave survey; disposition status for the recruitment survey; disposition status since the 2025 initial survey.