Research

As governments and corporations worldwide strive for carbon neutrality, nature-based climate solutions (NbCS) have been increasingly utilized in carbon offset markets. Focusing on the most common nature-based offset generating projects, the improved forest management (IFM) projects, this paper presents the first empirical analysis to a) identify factors influencing their decisions to enter either regulated or voluntary carbon offset markets, and b) evaluate the efficiency of both markets in achieving credible carbon offsetting from these projects. Using a novel spatial dataset describing 34 IFM projects in the regulated California carbon offset market, and 28 in the voluntary carbon offset market across 20 US states, we estimate projects' stocks and fluxes of forest carbon using the U.S. Forest Service's Forest Inventory and Analysis (FIA) field surveys collected between 1999-2021. Comparing with control forestland with similar biomass carbon storage capacities constructed with covariate pre-matching, we find that the differences in initial credit issuance drive the market entry choices. The regulated market offers over 80% initial carbon credit issuance, which attracted projects with increasing and higher initial carbon stocks relative to their controls prior to entering the market. The voluntary market's gradual credit issuance scheme instead motivates participation from projects with decreasing and lower biomass relative to controls before their market entrance. Employing a forest simulation model to approximate representative projects on the two markets, we suggest that IFM projects in both markets submit more aggressive baseline harvesting scenarios than their actual pre-market management plans measured by FIA, in order to achieve more offset credits from carrying carbon stocks above these baselines. As a result, the current carbon markets likely have inefficiencies in overcrediting forest projects. We would recommend standardizing baseline protocols and enhancing the monitoring of historical forest management activities, in order to improve the reliability of the current carbon offset crediting system.

In light of escalating wildfire occurrences exacerbated by climate change, smoke related air pollution has become increasingly the concerns for public health and economic growth. This study analyze the impacts of short-term smoke forecasts issued by NOAA (National Oceanic and Atmospheric Administration) in California during 2015-2020, which exposes increasingly prolonged smoke hazards to densely populated areas. Utilizing the variations in realized and day-ahead forecast of smoke-related fine particular matters, I identify changes in residential electricity and water consumption under different levels of realized and forecast smoke exposures. Light smoke exposures lead to increased electricity and decreased water consumption, implying adaptations of indoor air filtering and avoidance of using polluted water. Heavy smoke exposures likely drive evacuations and large-scale cleaning afterwards, which are shown with the significant decrease in residential electricity and increase in water consumption. Accurate smoke forecasts complement these adaptations, in regular years (2015-2019) decrease electricity consumption and encourage evacuations, and in COVID stay-at-home year (2020) increase electricity consumption and encourage indoor air filtering. Further evidenced by economic and health outcome changes under quality smoke forecasts, including lowered unemployment rates and weakly reduced mortalities, these behavioral adjustments underscore the social benefits of adaptations by electricity and water consumption with high-quality smoke-related air quality predictions.