Predicted Support for Climate Mitigation Policies by Group 

These predicted probabilities come from the Yale Climate Change in the American Mind survey between 2008 and 2023 (n=33,265) controlling for age, gender, education, and income.

This image shows predicted support for climate mitigation policies when interacting with ideology and party. In general, we would expect respondents to become more opposed to climate mitigation policies the more conservative they are. Yet, this relationship varies substantially by party and across racial groups.

First, there is no overlap between Democrats and Republicans in supporting climate mitigation policies for white voters, but there is a fair amount of overlap in every other racial category. Republicans are less supportive than Democrats on average, but there is a fair amount of overlap for non-white voters compared to white voters. Democrats are the most supportive, and the racial groups differ mainly in how high or low the lines start, but they all display the same broad pattern of declining support with more conservative ideology. Those in the "other" category either choose "independent", "no party" or refused to answer, and have the lowest predicted support for climate mitigation policies. However, the more conservative their ideology, the more likely they are to support regulations, contrary to their peers in the two major parties.

Ideology is a strong predictor for support of climate mitigation policies for all racial groups, with the notable exception of Black Democrats, where support remains relatively low in comparison to other Democratic constituents. Ideology is a strong predictor of support for climate mitigation policies among Republicans compared to other parties, indicated by a steeper slope on average. However, Variance within Republican ideology as a predictor is also relatively higher compared to Democrats and those in the other category.

The upshot is that conventional thinking on partisan sorting on climate mitigation policies among the public is strongest among white respondents. Ideology and party affiliation remain salient for non-white voters but there is far more overlap between parties and across ideologies. These patterns should inform an analysis of potential coalition building for climate mitigation policies in the electorate.

Climate-Related Lobbying Over Time

This visualization tracks two measures of climate-related lobbying directed at Congress and federal agencies from 2008 to 2020. Using data from LobbyView, which documents lobbying activities reported under the Lobbying Disclosure Act of 1995, I analyze efforts by publicly traded companies through both the frequency of lobbying instances and estimated total expenditures. The data spans from the first quarter of fiscal year 2008 through the second quarter of fiscal year 2020.

Campaign Contributions to Each Political Party by Industry

This figure shows industry contributions to members of Congress by industry. This figure is based on contributions from PACs and individuals giving $200 or more from the oil and gas, utility, mining, waste management, and coal industries. All donations took place during the two years preceding each election year. The Federal Election Commission released figures for the most recent cycle on Monday, March 20, 2023.

Communities Facing Pollution Burden Compared to Designated Energy Communities under 48C Tax Credits

The upper figure shows the spatial distribution of pollution, and the census tracts that exceed thresholds for critical pollution metrics are marked in red, and other census tracts are in purple. Data comes from the Climate and Economic Justice Screening Tool (https://screeningtool.geoplatform.gov/en/methodology). The lower figure shows qualifying census tracts (red) for the Energy Project Tax Credit, known as the 48C tax credit. This IRA allocated$4 billion to projects that expand clean energy manufacturing, recycling, and critical mineral refining for projects that reduce greenhouse gas emissions at industrial facilities. In 2009, the first-ever round of 48C credits allocated$2.3 billion to nearly 200 clean energy manufacturing projects across 43 states.

Illegal Unreported and Unregulated Fishing

Illegal fishing, commonly known as Illegal Unreported and Unregulated (IUU) fishing, is a pervasive issue in global fisheries and international waters. It is estimated to account for approximately $23.5 billion in annual value, representing nearly a quarter of the total landed value of all fisheries worldwide (Agnew et al., 2009; Pauly et al., 2016). IUU fishing is linked to significant environmental degradation, including declines in fish populations, ecosystem damage, revenue loss, and food insecurity (Pascoe et al., 2008). Additionally, it is associated with transnational criminal activities, such as labor and human rights abuses, as well as various forms of drug, weapons, and human and wildlife trafficking (Kittinger et al., 2017). Despite being a major environmental challenge, IUU fishing has received limited attention from social science scholars, with most research focusing on environmental criminology.

This is a visualization I made as part of a working paper examining how conditions of scarcity affect illegal, unregulated, and unreported (IUU) fishing activity in varied institutional environments. This paper leverages the exogenous timing and geography of marine heatwaves (MHWs) to study the effects of climate-induced scarcity shocks on 1) illegal industrial-scale fishing behavior and 2) test whether institutional features mediate or exacerbate trends in IUU fishing. The sparse literature on IUU fishing indicates that weak state capacity contributes to IUU fishing but does not specify how different measures of state capacity, such as the ability to control territory and capacity for taxation, influence illicit behavior. Furthermore, this paper investigates how measures of levels of corporatism influence IUU fishing practices. By combining new data from Global Fishing Watch with anomalous sea surface temperature data, I investigate how different features of 1) states, 2) markets, and 3) ecological realities shape this IUU fishing under conditions of scarcity.

DC Heat Exposure and Sensitivity Index

This is mapping tool is designed to show the social and economic factors correlated with heat sensitivity and exposure. HSEI Data was gathered from Open Data DC and contains variables related to socioeconomic, health, and environmental metrics for DC's 206 census tracts.

DC Cooling Center Data When the temperature or heat index in the District reaches 95 degrees, the District Government, through the Department of Human Services (DHS) and the Homeland Security and Emergency Management Agency (HSEMA), will implement the Heat Emergency Plan and activate cooling centers for residents to seek relief. We provide locations, names of centers, phone numbers, and hours of cooling centers.

DC Tree Data DDOT's Urban Forestry Division (UFD) is the primary steward of Washington DC's ~170,000 public trees and has a mission of keeping this resource healthy, safe, & growing! Trees provide many benefits to the populations, such as improving air and water quality and creating habitat for local fauna. Importantly, trees are also critical for keeping the city cooler.

Data Sources:

  1. HSEI Data: Open Data DC

  2. DC Cooling Center Data: Open Data DC

  3. DC Tree Data: Open Data DC

Contact: kv2717a@american.edu