Intermittent monitoring of environmental standards may induce strategic changes in polluting activities. This paper documents local strategic responses to a cyclical, once-every-six-day air quality monitoring schedule under the federal Clean Air Act. Using satellite data of monitored areas, I show that air quality is significantly worse on unmonitored days. This effect is explained by short-term suppression of pollution on monitored days, especially during high-pollution periods when the city’s noncompliance risk is high. Cities’ use of air quality warnings increases on monitored days, which suggests local governments’ role in coordinating emission reductions. (JEL K32, Q35, Q58, R11)

Regulators often rely on regulated entities to self-monitor compliance, creating strategic incentives for endogenous monitoring. This paper builds a framework to detect whether local governments skip air pollution monitoring when they expect air quality to deteriorate. The core of our method tests whether the timing of monitor shutdowns coincides with the counties’ air quality alerts—public advisories based on local governments’ own pollution forecasts. Applying the method to a monitor in Jersey City, New Jersey, suspected of a deliberate shutdown during the 2013 “Bridgegate” traffic jam, we find a 33% reduction of this monitor's sampling rate on pollution-alert days. Building on large-scale inference tools, we then apply the method to test more than 1,300 monitors across the United States, finding fourteen metropolitan areas with clusters of monitors showing similar strategic behavior. We assess geometric imputation and remote-sensing technologies as potential solutions to deter future strategic monitoring.

We study how air pollution impacts the U.S. labor market by analyzing the effects of drifting wildfire smoke. We link satellite-based smoke plume data with labor market outcomes to estimate that an additional day of smoke exposure reduces quarterly earnings by about 0.1%. Extensive margin responses, including employment reductions and labor force exits, explain 13% of the overall earnings losses. The implied welfare costs from lost earnings due to air pollution exposure is on par with standard valuations of the mortality burden. The findings highlight the importance of labor market channels in air pollution policy responses.

Urban forests are ubiquitous, yet their impacts and values remain largely unknown. We study a massive urban afforestation policy in Beijing that planted 1/3 of a million acres of greenery in less than a decade. We conduct a remote-sensing audit of the program, finding that it contributes to a substantial greening up of the city. This causes significant downwind air quality improvement, reducing average PM2.5 concentration at city population hubs by 4.2%. Rapid vegetation growth unexpectedly led to a 7.4% increase in pollen exposure. Analysis of medical claims data shows that increased aeroallergens triggered emergency room visits, mirroring pollution effects though much less severe. Monetized net health benefits of the program amount to 1.5% of the city’s GDP. Urban forests are only partially capitalized in housing values, with buyers mainly appreciating proximity to green spaces but not the air quality improvements they bring.

In 2013, China launched a landmark program to monitor air quality and disclose real-time data, significantly increasing the public’s access to and awareness of pollution information. The program triggered cascading behavioral changes such as stronger avoidance of outdoor pollution exposure and increased spending on protective products. These behavioral responses mitigated the mortality impact of air pollution. Conservative estimates indicate that the program’s health benefits outweigh the costs by an order of magnitude. The findings highlight the benefits of improving public access to pollution information in developing countries which often experience severe air pollution but lack pollution data collection and dissemination. (JEL D83, D91, I12, O13, P28, Q51, Q53)