Monitoring Waste to Minimize Waste at the University of Massachusetts Amherst

The University of Massachusetts Amherst is committed to sustainability, however, the campus could further reduce its costs and save energy by optimizing the current method of waste removal. The Intergovernmental Panel on Climate Change predicts that by the end of the century, Earth’s average temperature will rise by 11 degrees Fahrenheit unless society takes action to reduce greenhouse gas emissions. According to the EPA, about one-third of carbon emissions in the U.S. come from transportation. Campus garbage bins are collected by carbon-emitting trucks daily, and large truckable waste compactors are collected about three times per week. The amount of harmful carbon emissions released by trucking all of the compactors to their disposal sites totals 9,600 pounds of CO2 (the weight of 12 grand pianos) every week. In this analysis, the current waste removal system is investigated and a method is proposed to save UMass money and energy by reducing the number of waste collections. Initial research focused on how traditional bins could be replaced with solar-powered compactors from Bigbelly Solar Inc. to reduce pickup frequency and generate revenue from separating waste. Findings indicate that solar compactors alone would not have a worthwhile impact on the energy consumption of the UMass campus. Alternatively, a monitoring system that reduces how frequently waste compactors are hauled from campus would have greater impact, saving $1,000 every two weeks, reducing harmful carbon emissions, and using less diesel fuel. Due to the current environmental crisis, UMass should take action to reduce its carbon footprint through this economically favorable system

Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations

We present a user-friendly, cloud-based facility for quantifying methane emissions with 0.25∘ × 0.3125∘ (≈ 25 km × 25 km) resolution by inverse analysis of satellite observations from the TROPOspheric Monitoring Instrument (TROPOMI). The facility is built on an Integrated Methane Inversion optimal estimation workflow (IMI 1.0) and supported for use on the Amazon Web Services (AWS) cloud. It exploits the GEOS-Chem chemical transport model and TROPOMI data already resident on AWS, thus avoiding cumbersome big-data download. Users select a region and period of interest, and the IMI returns an analytical solution for the Bayesian optimal estimate of period-average emissions on the 0.25∘ × 0.3125∘ grid including error statistics, information content, and visualization code for inspection of results. The inversion uses an advanced research-grade algorithm fully documented in the literature. An out-of-the-box inversion with rectilinear grid and default prior emission estimates can be conducted with no significant learning curve. Users can also configure their inversions to infer emissions for irregular regions of interest, swap in their own prior emission inventories, and modify inversion parameters. Inversion ensembles can be generated at minimal additional cost once the Jacobian matrix for the analytical inversion has been constructed. A preview feature allows users to determine the TROPOMI information content for their region and time period of interest before actually performing the inversion. The IMI is heavily documented and is intended to be accessible by researchers and stakeholders with no expertise in inverse modelling or high-performance computing. We demonstrate the IMI's capabilities by applying it to estimate methane emissions from the US oil-producing Permian Basin in May 2018.</p

Complete Genome Sequences of Cluster A Mycobacteriophages BobSwaget, Fred313, KADY, Lokk, MyraDee, Stagni, and StepMih

Seven mycobacteriophages from distinct geographical locations were isolated, using Mycobacterium smegmatis mc2155 as the host, and then purified and sequenced. All of the genomes are related to cluster A mycobacteriophages, BobSwaget and Lokk in subcluster A2; Fred313, KADY, Stagni, and StepMih in subcluster A3; and MyraDee in subcluster A18, the first phage to be assigned to that subcluster

Global tropospheric halogen (Cl, Br, I) chemistry and its impact on oxidants [discussion paper]

We present an updated mechanism for tropospheric halogen (Clĝ€¯+ĝ€¯Brĝ€¯+ĝ€¯I) chemistry in the GEOS-Chem global atmospheric chemical transport model and apply it to investigate halogen radical cycling and implications for tropospheric oxidants. Improved representation of HOBr heterogeneous chemistry and its pH dependence in our simulation leads to less efficient recycling and mobilization of bromine radicals and enables the model to include mechanistic sea salt aerosol debromination without generating excessive BrO. The resulting global mean tropospheric BrO mixing ratio is 0.19ĝ€¯ppt (parts per trillion), lower than previous versions of GEOS-Chem. Model BrO shows variable consistency and biases in comparison to surface and aircraft observations in marine air, which are often near or below the detection limit. The model underestimates the daytime measurements of Cl2 and BrCl from the ATom aircraft campaign over the Pacific and Atlantic, which if correct would imply a very large missing primary source of chlorine radicals. Model IO is highest in the marine boundary layer and uniform in the free troposphere, with a global mean tropospheric mixing ratio of 0.08ĝ€¯ppt, and shows consistency with surface and aircraft observations. The modeled global mean tropospheric concentration of Cl atoms is 630ĝ€¯cm-3, contributing 0.8ĝ€¯% of the global oxidation of methane, 14ĝ€¯% of ethane, 8ĝ€¯% of propane, and 7ĝ€¯% of higher alkanes. Halogen chemistry decreases the global tropospheric burden of ozone by 11ĝ€¯%, NOx by 6ĝ€¯%, and OH by 4ĝ€¯%. Most of the ozone decrease is driven by iodine-catalyzed loss. The resulting GEOS-Chem ozone simulation is unbiased in the Southern Hemisphere but too low in the Northern Hemisphere

Priorities for synthesis research in ecology and environmental science

ACKNOWLEDGMENTS We thank the National Science Foundation grant #1940692 for financial support for this workshop, and the National Center for Ecological Analysis and Synthesis (NCEAS) and its staff for logistical support.Peer reviewedPublisher PD

Priorities for synthesis research in ecology and environmental science

ACKNOWLEDGMENTS We thank the National Science Foundation grant #1940692 for financial support for this workshop, and the National Center for Ecological Analysis and Synthesis (NCEAS) and its staff for logistical support.Peer reviewedPublisher PD

Particles, air quality, policy and health

The diversity of ambient particle size and chemical composition considerably complicates pinpointing the specific causal associations between exposure to particles and adverse human health effects, the contribution of different sources to ambient particles at different locations, and the consequent formulation of policy action to most cost-effectively reduce harm caused by airborne particles. Nevertheless, the coupling of increasingly sophisticated measurements and models of particle composition and epidemiology continue to demonstrate associations between particle components and sources (and at lower concentrations) and a wide range of adverse health outcomes. This article reviews the current approaches to source apportionment of ambient particles and the latest evidence for their health effects, and describes the current metrics, policies and legislation for the protection of public health from ambient particles. A particular focus is placed on particles in the ultrafine fraction. The review concludes with an extended evaluation of emerging challenges and future requirements in methods, metrics and policy for understanding and abating adverse health outcomes from ambient particles