United States Household Carbon Footprints: Quantifying the relationship between household-level income inequality and greenhouse gas emissions (1996-2015)

As long as humanity has existed, we have altered our environment to provide goods, services, and (more recently) wealth to people. Over the last several centuries, the scope and pace of this transformation has accelerated with the onset of technological innovation, social and economic reorganization, and an ensuing population boom. Today, humanity’s demands on nature have become the dominant force shaping the critical earth systems upon which all life depends. From local land-use change to the global climate many of these anthropogenic pressures pose an existential threat to nature and the dependent social systems that rely on them. Yet, extreme economic and social inequality within and across human societies leads to significant inequality in who reaps the benefits of these transformations, who reaps the harms, and who makes the decisions on that benefit-harm distribution. Here I quantify, at high granularity and over a 20-year period (1996-2015), the GHG emissions footprints of United States households, based on the flow of income, goods and services these emissions enable. I compare the scale and distributions of household-level GHG emissions across different social groups and responsibility frameworks and provide policy insights related to those findings

Lights, Camera...Citizen Science: Assessing the Effectiveness of Smartphone-Based Video Training in Invasive Plant Indentification

The rapid growth and increasing popularity of smartphone technology is putting sophisticated data-collection tools in the hands of more and more citizens. This has exciting implications for the expanding field of citizen science. With smartphonebased applications (apps), it is now increasingly practical to remotely acquire high quality citizen-submitted data at a fraction of the cost of a traditional study. Yet, one impediment to citizen science projects is the question of how to train participants. The traditional ‘‘in-person’’ training model, while effective, can be cost prohibitive as the spatial scale of a project increases. To explore possible solutions, we analyze three training models: 1) in-person, 2) app-based video, and 3) app-based text/images in the context of invasive plant identification in Massachusetts. Encouragingly, we find that participants who received video training were as successful at invasive plant identification as those trained in-person, while those receiving just text/images were less successful. This finding has implications for a variety of citizen science projects that need alternative methods to effectively train participants when in-person training is impractical

The Indestructible Insect: Velvet Ants from Across the United States Avoid Predation by Representatives from All Major Tetrapod Clades

Velvet ants are a group of parasitic wasps that are well known for a suite of defensive adaptations including bright coloration and a formidable sting. While these adaptations are presumed to function in antipredator defense, observations between potential predators and this group are lacking. We conducted a series of experiments to determine the risk of velvet ants to a host of potential predators including amphibians, reptiles, birds, and small mammals. Velvet ants from across the United States were tested with predator’s representative of the velvet ants native range. All interactions between lizards, free-ranging birds, and a mole resulted in the velvet ants survival, and ultimate avoidance by the predator. Two shrews did injure a velvet ant, but this occurred only after multiple failed attacks. The only predator to successfully consume a velvet ant was a single American toad (Anaxyrus americanus). These results indicate that the suite of defenses possessed by velvet ants, including aposematic coloration, stridulations, a chemical alarm signal, a hard exoskeleton, and powerful sting are effective defenses against potential predators. Female velvet ants appear to be nearly impervious to predation by many species whose diet is heavily derived of invertebrate prey

The Science Performance of JWST as Characterized in Commissioning

This paper characterizes the actual science performance of the James Webb Space Telescope (JWST), as determined from the six month commissioning period. We summarize the performance of the spacecraft, telescope, science instruments, and ground system, with an emphasis on differences from pre-launch expectations. Commissioning has made clear that JWST is fully capable of achieving the discoveries for which it was built. Moreover, almost across the board, the science performance of JWST is better than expected; in most cases, JWST will go deeper faster than expected. The telescope and instrument suite have demonstrated the sensitivity, stability, image quality, and spectral range that are necessary to transform our understanding of the cosmos through observations spanning from near-earth asteroids to the most distant galaxies.Comment: 5th version as accepted to PASP; 31 pages, 18 figures; https://iopscience.iop.org/article/10.1088/1538-3873/acb29

Patterns in Trash: Factors that Drive Municipal Solid Waste Recycling

Municipal recycling is driven by a variety of factors. Yet how these factors change over time is not well understood. I analyze a suite of contextual and program variable in multiple time periods, spanning 16 years, in the Commonwealth of Massachusetts. Based on the models run, I reach the surprising conclusion that most program variables have an insignificant effect on recycling rates. These findings can inform municipal officials and waste managers as they seek new ways to increase municipal recycling participation

Author response to: Clean Cut (adaptive, multimodal surgical infection prevention programme) for low-resource settings: a prospective quality improvement study

response to commentar

Data supporting S2 Fig (producer).

Current policies to reduce greenhouse gas (GHG) emissions and increase adaptation and mitigation funding are insufficient to limit global temperature rise to 1.5°C. It is clear that further action is needed to avoid the worst impacts of climate change and achieve a just climate future. Here, we offer a new perspective on emissions responsibility and climate finance by conducting an environmentally extended input output analysis that links 30 years (1990–2019) of United States (U.S.) household-level income data to the emissions generated in creating that income. To do this we draw on over 2.8 billion inter-sectoral transfers from the Eora MRIO database to calculate both supplier- and producer-based GHG emissions intensities and connect these with detailed income and demographic data for over 5 million U.S. individuals in the IPUMS Current Population Survey. We find significant and growing emissions inequality that cuts across economic and racial lines. In 2019, fully 40% of total U.S. emissions were associated with income flows to the highest earning 10% of households. Among the highest earning 1% of households (whose income is linked to 15–17% of national emissions) investment holdings account for 38–43% of their emissions. Even when allowing for a considerable range of investment strategies, passive income accruing to this group is a major factor shaping the U.S. emissions distribution. Results suggest an alternative income or shareholder-based carbon tax, focused on investments, may have equity advantages over traditional consumer-facing cap-and-trade or carbon tax options and be a useful policy tool to encourage decarbonization while raising revenue for climate finance.</div

Data supporting S10 & S11 Figs (producer).

Current policies to reduce greenhouse gas (GHG) emissions and increase adaptation and mitigation funding are insufficient to limit global temperature rise to 1.5°C. It is clear that further action is needed to avoid the worst impacts of climate change and achieve a just climate future. Here, we offer a new perspective on emissions responsibility and climate finance by conducting an environmentally extended input output analysis that links 30 years (1990–2019) of United States (U.S.) household-level income data to the emissions generated in creating that income. To do this we draw on over 2.8 billion inter-sectoral transfers from the Eora MRIO database to calculate both supplier- and producer-based GHG emissions intensities and connect these with detailed income and demographic data for over 5 million U.S. individuals in the IPUMS Current Population Survey. We find significant and growing emissions inequality that cuts across economic and racial lines. In 2019, fully 40% of total U.S. emissions were associated with income flows to the highest earning 10% of households. Among the highest earning 1% of households (whose income is linked to 15–17% of national emissions) investment holdings account for 38–43% of their emissions. Even when allowing for a considerable range of investment strategies, passive income accruing to this group is a major factor shaping the U.S. emissions distribution. Results suggest an alternative income or shareholder-based carbon tax, focused on investments, may have equity advantages over traditional consumer-facing cap-and-trade or carbon tax options and be a useful policy tool to encourage decarbonization while raising revenue for climate finance.</div

Annual mean CO₂e intensity of supplier-based wages and other income sources (1990–2019).

Wages and employer healthcare contributions are industry specific CO2e multipliers and are presented by income group. The other income categories use weighted national average multipliers (shaded blue area). (Producer-based results are presented in S2 Fig).</p

Mean household t CO₂e emissions (2019) per income group under the pre-tax supplier framework.

The width of each income group, on the x-axis, corresponds with each group’s share of national emissions. Color indicates income category. Black error bars are bootstrapped 95% confidence intervals for total t CO2e from all three sources. Similarly, gray error bars are bootstrapped 95% confidence intervals on the total t CO2e given an assumed ±20% error in carbon intensity per dollar. (Producer-based results are presented in S8 Fig).</p