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Despite decades of literature and practice with community-engaged research along with advancements in the recognition of environmental injustices, the application of equity-/justice-based and collaborative approaches between government agencies and community-based organizations has been limited. The toxic legacies of environmental racism, redlining, displacement, and segregation combined with the accelerating human-caused climate crisis warrant an increased need for consultation and collaboration between frontline communities and power brokers to markedly improve quality of life and health outcomes in environmental justice neighborhoods. This paper describes the processes and progress to date from a community-led collaboration between local community-based organizations and the Enforcement Division of the California Air Resources Board to assess and address air pollution in South Stockton, particularly from heavy-duty diesel trucks. South Stockton is one of the most polluted neighborhoods in California’s San Joaquin Valley, one of the most disparate and polluted regions in the United States. Some of the most significant components integrated into this project thus far include taking an equity-, justice-, and youth-oriented approach to community development that intentionally emphasizes a historical understanding of root causes of social and environmental injustices and provides pathways to workforce development. Including these elements has been essential in building the trust necessary to transform disparate power relations between the state and environmental justice communities, and to put multiple ways of knowing into conversation with each other to co-learn and co-power solutions to air pollution in South Stockton.

This paper considers the diverse public good characteristics of COVID-19 activities along with their strategic implications. The underlying aggregator technologies, which relate individual contributions to the amount consumed, affect the prognosis for the supply of COVID-related activities. Weakest-link activities assume a particularly pivotal role in curbing the spread of COVID-19. For instance, the propagation of COVID-19 through new strains is disproportionately influenced by those countries with the smallest vaccination rates or least isolation actions. Diverse income distribution among at-risk countries raises the need to “shore up” weakest-link countries’ provision to lift global supply. Generally, shoring-up actions result in a Prisoner’s Dilemma with unfavorable collective action prospects. As the number of countries requiring shoring up increases, the less favorable is the prospect for addressing provision shortfalls. Also, as the number of capable countries to do the shoring up increases, the prospect for successful action diminishes. The paper also examines the strategic implications of other aggregators—e.g., best shot and better shot—associated with COVID-inhibiting actions. To address best-shot anti-COVID actions, countries must pool or coordinate actions to meet a threshold. A host of institutions—e.g., the World Health Organization or public-private partnerships—can facilitate shoring-up weakest-link activities or coordinating best-shot actions.

As a waterborne pathogen of increasing concern, techniques for cost-effective and rapid characterization of Legionella are vital. This study examines the development of a Matrix Assisted Laser Desorption/Ionization-Time of Flight Mass Spectrometry (MALDI-TOF-MS) analysis methodology for this microbe. First, optimal sample preparation methods for the analysis of environmental Legionella isolates via MALDI-TOF-MS were determined. These methods were then implemented to perform strain-level characterization of environmental Legionella isolates from central Arizona. Results demonstrate that a MALDI-TOF-MS method involving BCYE agar-based culturing and protein extraction-based sample preparation yield high-quality mass spectra. Twenty-eight environmental Legionella isolates originating from two separate drinking water distribution systems were analyzed. Multiple species were detected, and strain-level characterization was achieved, with 12 unique strains distinguished. In addition, isolates of L. pneumophila, the most common species observed in the study, were correctly assigned to specific sampling sites. These results demonstrate the potential for this technique to be applied for sub-species characterization of Legionella with significant benefits over established methodologies.

For 1990–2019, this study presents two-step GMM estimates of EU members’ demands for defense spending based on alternative spatial-weight matrices. In particular, EU spatial connectivity is tied to EU membership status, members’ contiguity, contiguity and power projection, inverse distance, and arms trade. At a Nash equilibrium, our EU demand equations are derived explicitly from a spatially based game-theoretical model of alliances. Myriad spatial linkages among EU members provide a robust free-riding finding, which differs from the spatial and non-spatial literature on EU defense spending. Even though the EU applies common trade policies and allows for unrestricted labor movement among members, members’ defense responses adhered to those of a defense alliance. Moreover, EU defense spending exhibits positive responses to GDP and transnational terrorist attacks, and a negative response to population. During the sample period, EU members did not view Russia as a military threat.