Alex Dangel

Hi there!

I am a Postdoctoral Researcher in the Policy Evaluation Lab at the Potsdam Institute for Climate Impact Research.

My research uses field experiments and quasi-experiments to study topics at the intersection of environmental economics, behavioral science, and public health. In particular, I am interested in low-cost environmental sensors and adaptation to environmental health risks.

Previously, I completed my PhD in Economics at Heidelberg University as a member of the Research Center for Environmental Economics. I received a dissertation scholarship from the German Federal Environmental Foundation (DBU).

Working Papers

• This paper studies temporal factors influencing the effectiveness of prosocial appeals used by policy-makers to encourage motorists to voluntarily reduce driving during transitory high pollution episodes. We derive and empirically validate a theoretical framework for repeated multi-day appeals where the desired behavioral response is sensitive to the number of consecutive appeal days and time intervals between appeal events. Our difference-in-differences event study analysis of traffic flows in Stuttgart, Germany shows appeals reduce traffic by about 3% on the first three appeal days, but effectiveness tapers off during prolonged activation. Moreover, appeals reduce traffic by about 5% following a lengthy time interval between appeals and are effective once authorities announce when they will be lifted. Our findings confirm prior North American evidence of limited appeal effectiveness in a novel European setting and highlight the relevance of dynamic temporal factors for voluntary short-term pollution mitigation programs.

In Progress

Now It’s Personal: A Field Experiment on the Demand for Wearable Air Quality Sensors with US Early Adopters (with Timo Goeschl)

• Wearable air quality sensors offer consumers the ability to monitor and respond to personal pollution exposure in real-time, potentially informing behavioral responses to health risks and supplying novel data that can be used to assess population exposure to harmful pollutants. In partnership with a leading manufacturer, we conduct a field experiment in the United States to study demand, use, and impacts of this emerging technology among early adopters. Through a point-of-sale survey and a pricing experiment, we find that mean willingness-to-pay falls short of current market prices, and advantaged groups dominate prospective and actual customer bases. Leveraging natural variation in ambient air quality, we show that demand and user activity increase during unhealthy pollution events. Limited follow-up data suggests that adopters update their beliefs about pollution exposure, substitute public air quality information with private sensor data, and maintain the frequency of defensive behaviors. Our results provide valuable insights for developing pollution monitoring systems and highlight the importance of equitable access to environmental information and adaptation opportunities.

Mind the PM2.5 Gap! Comparing Pollution Exposure Estimates from Wearable Sensors and Ambient Monitors

• Typically, environmental health studies either track personal exposure to harmful pollutants for a small number of individuals or rely on secondary data that insufficiently proxies for true exposure. In this paper, I construct a highly granular, geolocated air pollution dataset at previously unavailable scale by leveraging over 45 million personal PM2.5 (fine particulate matter) exposure readings from a consumer sample of 594 wearable air quality sensor users in the United States. I exploit this novel dataset and natural variation in ambient air quality to assess bias in commonly used PM2.5 secondary data from fixed ambient monitors. On average, personal exposure in my sample is between 7% and 18% less than monitor-based estimates, while median differences correspond to nearly 40% less pollution. Moreover, my analysis shows that this "PM2.5 gap" varies systematically with pollution levels, location, and time. These findings underscore significant heterogeneity in pollution exposure and suggest that previous research relying on monitor data may misstate the relationship between pollution and damages.

The Private Provision of Public Air Quality Information: A Study of Adoption Patterns (with Timo Goeschl)

• Citizens have greatly expanded ground-based air quality data coverage by purchasing and installing stationary air quality sensors (SAQS) to collect and publicly disclose information about air pollution levels in real-time. We study the adoption of this emerging non-regulatory monitoring technology using data through 2022 from one of the two largest SAQS networks globally. Our analysis closely examines adoption determinants and spatiotemporal diffusion patterns in Germany, a global leader in SAQS adoptions. Regression results show that income and green political preferences are two primary adoption determinants. Moreover, SAQS are installed more often near government monitors in Germany, but evidence that monitor non-compliance drives additional adoptions is weak. In line with its unique local public goods properties, we demonstrate that SAQS have local spatial spillovers by employing fixed effects panel models with spatiotemporal neighbor variables. Our findings reveal private air quality data coverage disparities and shed light on the relationship between government and private monitoring.

Recent Presentations

• June 2025: EAERE Summer Conference in Bergen, Norway.
• June 2025: ZEW-Heidelberg-Mannheim Environmental Economics Brownbag Seminar.
• May 2025: Mannheim Conference on Energy and the Environment in Mannheim.
• May 2025: AERE@OSWEET.
• March 2025: CESifo / ifo Junior Workshop on Energy and Climate Economics 2025 in Munich.