Concerns about potential fetal harm caused by alcohol and drug use have motivated policymakers and public health agencies to dedicate increasing attention and resources to limiting substance use in the context of pregnancy over the past 50 years. Most states now have at least one pregnancy-specific alcohol and drug policy in place. Public health agencies have issued warnings and recommended abstinence before, during, and after pregnancy. Clinical counseling interventions for patients who use alcohol and drugs typically focus exclusively on contraception and the prevention of pregnancy without attention to nuanced pregnancy preferences and reproductive autonomy. This dissertation explores causal inference and multi-level modeling approaches to assess the intended and unintended effects of policies focused on alcohol and drug use in the context of pregnancy, taking into consideration both fetal health and reproductive autonomy. Additionally, it applies a reproductive autonomy framework to questions related to substance use and pregnancy, pushing back against traditional public health frameworks, which are focused on preventing “unintended” pregnancy and neglect to account for individual pregnancy preferences.Chapter 1 assesses whether the oldest and most common type of pregnancy-specific alcohol and drug use policy is associated with changes in birth outcomes. Specifically, we investigated the impacts of Arizona’s alcohol-only and alcohol-plus-drug child abuse and neglect policies on birth outcomes. We used state- level policy information and vital statistics data from 1.5 million singleton births conceived between January 2000 and December 2012 in Arizona and New Mexico and conducted quasi-experimental difference-in-difference approaches to compare pre-to-post policy changes in gestational length and birthweight between the states. Stratified subgroup analyses examined policy associations by race and ethnicity. Contrary to hypotheses, we found apparent population-level improvements in birthweight, and non-significant changes for gestational age, associated with Arizona’s alcohol and drug child abuse and neglect policies relative to New Mexico, where neither policy was implemented. Improvements associated with the policy were specifically among non-Hispanic white and Hispanic/Latinx births. Due to the close timing of the tobacco policies and the CACN policies of interest (particularly when considering lags in policy implementation), it was not possible to distinguish between changes in birth outcomes associated with the tobacco policies and the policies of interest. Given rigorous evidence showing associations between tobacco smoking and adverse birth outcomes and between tobacco control policies and reductions in smoking behavior (including among pregnant people), unexpected improvements in birthweight may be due to co-commencing tobacco policies instead of CACN policies. Chapter 2 evaluates associations between state-level legal recreational cannabis and three outcomes: cannabis use during pregnancy, beliefs about safety of cannabis use during pregnancy, and perceptions of community stigma around cannabis use during pregnancy. We used cross-sectional multi-level survey data collected from 3,571 pregnant or recently pregnant people in 37 states in 2022 and fit generalized linear models and mixed effects ordinal logistic regression models with random effects for state. Findings do not support concerns that legal recreational cannabis is associated with cannabis use during pregnancy or beliefs about safety. Yet, results indicate that legal recreational cannabis may be associated with lower community stigma around cannabis use during pregnancy, which could have implications for pregnant people’s disclosure of use and care-seeking behavior. Chapter 3 investigates relationships between alcohol and drug use, the desire to avoid pregnancy, and incident pregnancy using longitudinal survey data collected from 2,015 individuals with the capacity to become pregnant who were recruited from 23 clinics in 5 Southwestern states from 2019-2023. We used multi-level linear mixed effects regression to explore associations between alcohol, cannabis, or illicit drug use and desire to avoid pregnancy and we used cox proportional hazard models to explore whether there was significant interaction between desire to avoid pregnancy and alcohol, cannabis, or illicit drug use in predicting incident pregnancy. Results indicate that more frequent cannabis use and any illicit drug use, but not heavy alcohol use, were associated with higher desire to avoid pregnancy and that the attainment of pregnancy preferences (or the association between desire to avoid pregnancy and incident pregnancy) differed significantly by heavy alcohol use, but not by cannabis or illicit drug use. Participants who reported heavy alcohol use were less likely to attain their pregnancy preferences over one year relative to those who did not report heavy alcohol use, with those most wanting to avoid pregnancy at significantly increased risk of pregnancy if they reported heavy alcohol use. Among those more open to pregnancy, there was no significant difference in the rate of incident pregnancy by heavy alcohol use.

Carbon dioxide emissions represent the primary driver behind the accelerated global warming problem. While mitigating these emissions from key sectors may necessitate a protracted timeframe, several promising technologies offer the potential for short-term advancements in full or partial decarbonization efforts. In pursuit of establishing a sustainable and reliable zero-carbon energy system, the deployment of energy storage systems integrated with clean and renewable resources becomes imperative. Solar and wind technologies are ubiquitously available across numerous nations and have attained a level of maturity conducive to widespread deployment on a grid scale. The combination of solar and wind energy with energy storage serves to expedite the decarbonization of electricity generation processes. Notably, the industrial and transportation sectors are difficult to be decarbonized, requiring decades to decarbonize due to the imperative of either developing novel technologies or optimizing existing ones to boost efficiency and cost-effectiveness. Giving priority to decarbonizing processes or sectors that can be mitigated relatively easily accelerates the broader decarbonization of more complex counterparts, thereby promoting a comprehensive approach to carbon mitigation strategies.The electricity generation is an important first step in decarbonizing the rest of sectors. In this dissertation, I investigated the challenges and the potential solutions for decarbonizing the electricity generation using clean and renewable sources of energy. Furthermore, I explored the possibility of decarbonizing some of the industrial processes using solar thermal technology. Eventually, I proposed the possible opportunity for Direct Air Carbon Capture (DACC) for indirect decarbonization of other hard-to-be-decarbonized processes/sectors like steel and cement industry and aviation sector. To achieve 100% renewable electricity grid, all the carbon emitting resources are replaced by a renewable resources like solar and wind for all the years from 2015 to 2020. The real historical demand and generation data are used. We explored various 100% renewable electricity grid scenarios by using different mixes between the available renewable resources (solar, onshore wind, offshore wind, and geothermal) with different overbuild capacities. Our findings indicate that while summer currently poses the greatest challenge, a solar-dominant grid shifts this challenge to the winter, contingent upon solar and storage capacities. To reduce the storage size and decrease the severity of the winter challenge, we investigated the potential of winter-dominant onshore wind and the usage of a clean dispatchable source of energy like the Allam cycle sequentially. We found that the storage size can be reduced by 30%-40% and we can generate about 37% of the total annual electricity consumption using the available winter-dominant onshore wind. Further analysis of the energy storage indicates that part of it is used frequently every day to supply the electricity demand during the nights (diurnal storage) and another big part of it is used to compensate the limited solar generation during the winter (seasonal storage). The rest of the energy storage is used to cover the cloudy days across the year (cross-day storage). Decarbonizing the industrial sector will add to the current electricity demand. Thus, we investigated the possibility of decarbonizing some of the industrial processes using solar thermal technology that does not rely on the electricity grid. We presented a comprehensive assessment of the performance of a novel solar thermal system, the Non-tracking Asymmetric Shadeless (NASH) concentrator, highlighting its efficiency and energy generation capabilities. A steady-state model developed for the system offers valuable insights into its operational dynamics and performance trends. Other industrial processes and sectors are hard to decarbonize, (e.g. the steel industry, the cement industry, and the aviation sector). It may take decades to decarbonize these processes/sectors. We proposed that we use Direct Air Carbon Capture (DACC) to capture the carbon emissions from these processes/sector. The DACC will be powered by the surplus electricity generated by a 100% renewable electricity grid. By combining empirical data analysis with theoretical modeling, this dissertation contributes to advancing our understanding of the challenges and the potential solutions for decarbonizing electricity generation, offering crucial insights for policymakers and stakeholders navigating the transition to sustainable and reliable clean energy systems.