Welcome to my website!
I am an Assistant Professor at ASU, with a shared appointment between the School for the Future of Innovation in Society and the School of Sustainability. My research contributes to the following areas: 1) the distributional consequences of environmental policy, 2) analyzing some of the causes of environmental inequality, and 3) heterogeneous responses to environmental risk. My research uses a combination of causal inference methods and remote sensing/pollution transport models.
How to pronounce my name? Dah-nah-eh.
Environmental policies can be ineffective if firms are able to shift production processes from regulated to unregulated sectors. Such incomplete regulation affects the spatial distribution of pollution and can therefore affect who bears the burden of pollution. I study this phenomenon in the context of a policy intended to reduce pollution from mills that process sugarcane in Mexico. In response to the regulation, I show that mills shifted some processing to the fields where sugarcane is grown. Following the policy, sugarcane fields linked to regulated facilities increased fires by 10% which increased PM2.5 exposure by 6%. Pollution increases were unevenly distributed across communities: agricultural fields tend to be located near poorer populations, and therefore the increase in fires increased their pollution burden. My results highlight a previously undiscussed implication of incomplete pollution regulation: its distributional consequences.
Market-based environmental policies are widely adopted on the basis of allocative efficiency. However, there is a growing distributional concern that market forces could increase the pollution exposure gap between disadvantaged and other communities by spatially reallocating pollution. We estimate how this “environmental justice gap" changed following the 2013 introduction of California's carbon market, the world's second largest and the one most subjected to environmental justice critiques. Embedding a pollution transport model within a program evaluation framework, we find that while the EJ gap was widening prior to 2013, it has since fallen by 21-30% across pollutants due to the policy.
This paper quantifies and decomposes recent trends in U.S. PM2.5 disparities from the electricity sector using a high-resolution pollution transport model. Between 2000- 2018, PM2.5 concentrations from electricity fell by 87% for the average individual, more than double the decline rate in overall U.S. ambient PM2.5 concentrations. Across racial/ethnic groups, we detect a dramatic convergence: since 2000, the Black-White PM2.5 disparity from electricity has narrowed by 94% and the Hispanic-White PM2.5 disparity has narrowed by 92%, though these disparities still exist in 2018. A decomposition exercise reveals nearly all of these disparity trends can be attributed to spatially-varying improvements in emissions intensities, with small contributions from scale, compositional, and residential location changes. This suggests local air pollution policies have played a larger role in reducing U.S. racial/ethnic pollution disparities from electricity than recent coal-to-natural gas fuel switching. While we detect similarly large PM2.5 improvements for the average low and high income individual, PM2.5 differences by income are relatively small and have changed little over time.
Emissions trading systems have the potential of increasing air quality given that GHG emissions are often co-produced with local pollutants such as NOx, SOx, and Particulate Matter (PM). Can emissions trading systems exacerbate or alleviate environmental justice concerns in emerging economies? According to the U.S. Environmental Protection Agency, Environmental Justice is achieved when no group is disproportionately affected by an environmental policy or phenomenon. The main objective of this chapter is to estimate the pollution burden faced by marginalized neighbourhoods in Mexico. This is relevant for Mexico given the beginning of the pilot program of the Mexican Emissions Trading System (ETS) and the country’s history of income inequality and poverty. Using linear regression and two-way fixed effects methods, we found that the highest emitters regulated under the ETS are located near poor populations. We estimated a 5 % CO2 emissions-reduction scenario corresponding to national targets and associated NO2 emissions to that scenario. We find that this scenario is consistent with a decrease in the exposure of NO2 pollution for the most marginalized neighbourhoods. This chapter also discusses other potential sources of environmental injustice that could result after the beginning of the ETS and the potential to address them.
Climate change could increase the frequency and duration of droughts that affect Mexico. This is particularly worrisome because many agricultural communities in the country are poor and with limited capacities for adaptation. This study estimated the impact of droughts on rural households’ wellbeing in Mexico, specifically on per-capita earnings, poverty, and children’s school attendance. To do this we focused our empirical analysis on the effects of the 2011 drought; one of the worst droughts that have affected Mexico in the past 70 years. Our results provide clear evidence that droughts have a negative impact on rural households’ wellbeing. Households that experienced a drought had lower per-capita earnings and were almost 5 percentage points more likely to be poor after the drought than their counterparts. Furthermore, droughts reduced male school attendance in almost three percentage points. Our results also provide indirect evidence showing that households that are less familiar with relative water scarcity are the ones that are hit hardest during droughts.
This article investigates whether residents of Mexico City value air quality. Our results suggest that air quality improvement in PM10 is equivalent to a marginal willingness to pay (MWTP) of US$440.31 per property for the period 2006–2013. The corresponding MWTP for PM2.5 is US$880.63, for O3 is US$623.78, and for SO2 is as much as US$2091.50. These estimates are considerably larger in magnitude compared to the few other studies in similar settings. As a percentage of annual household income, these represent 2.44 per cent for PM10, 4.88 per cent for PM2.5, 3.46 per cent for O3 and 11.59 per cent for SO2. Our estimates of land value–pollution elasticities for PM10 (−0.26 and − 0.58) are within range of hedonic estimates for total suspended particulate matter in US cities around the 1970s. The corresponding elasticities range from − 0.55 to − 0.84 for PM2.5, from − 0.06 to − 0.49 for O3 and from − 0.11 to − 0.34 for SO2.
The increment in greenhouse gas emissions and its effect on climate is such that the need for the agricultural sector to adapt seems inevitable. However, given that adaptive measures are limited it is possible that climate change will affect food availability and increase price volatility. This essay presents a synthesis of the evidence of the effects that climate change has on the agricultural sector, with a special emphasis on Latin America. This revision makes it clear that the effects are going to be heterogeneous and that they could very well be costly. Therefore, public policies aimed at reducing greenhouse gas emissions while at the same time promoting adaptive measures to climate change, are essential. The essay concludes with some considerations on future research topics that could contribute to the design of said public policies.
This course is one of the core courses of the Sustainable Energy Ph.D. in the School of Sustainability. This course introduces energy markets, environmental and energy policy, and environmental justice topics from a quantitative perspective. It also provides an introduction to quantitative methods and causal inference methods in R. Finally, it provides tools for energy and environmental policy analysis.
I was an intern in Resources for the Future during the summer of 2018. Margaret Walls and I wrote this blogpost explains the distribution of disaster assistance in the U.S. during the 2017 hurricane season.