Underestimation of Thermogenic Methane Emissions in New York City.

Recent studies have shown that methane emissions are underestimated by inventories in many US urban areas. This has important implications for climate change mitigation policy at the city, state, and national levels. Uncertainty in both the spatial distribution and sectoral allocation of urban emissions can limit the ability of policy makers to develop appropriately focused emission reduction strategies.

Methane Emissions Show Recent Decline but Strong Seasonality in Two US Northeastern Cities.

Urban methane emissions estimated using atmospheric observations have been found to exceed estimates derived by using traditional inventory methods in several northeastern US cities. In this work, we leveraged a nearly five-year record of observations from a dense tower network coupled with a newly developed high-resolution emissions map to quantify methane emission rates in Washington, DC, and Baltimore, Maryland. Annual emissions averaged over 2018-2021 were 80.

A multi-city urban atmospheric greenhouse gas measurement data synthesis.

Urban regions emit a large fraction of anthropogenic emissions of greenhouse gases (GHG) such as carbon dioxide (CO) and methane (CH) that contribute to modern-day climate change. As such, a growing number of urban policymakers and stakeholders are adopting emission reduction targets and implementing policies to reach those targets. Over the past two decades research teams have established urban GHG monitoring networks to determine how much, where, and why a particular city emits GHGs, and to track changes in emissions over time.

Relationship between Health-Related Physical Fitness Parameters and Functional Movement Screening Scores Acquired from a Three-Dimensional Markerless Motion Capture System.

The purpose of the present study was to examine the relationship between five algorithm-derived functional movement screening scores (i.e., readiness, explosiveness, functionality, dysfunction, and vulnerability) obtained from an innovative three-dimensional markerless motion capture system (3D-MCS) and some of the key health-related physical fitness parameters such as maximal aerobic capacity (VOmax), body mass index (BMI), body fat percentage (BF%), waist and hip circumferences (WC and HC), and high-density lipoprotein cholesterol (HDL-C).