Adjustment costs from environmental change

The paper is concerned with the case whereby the distribution of a firm's productivity shocks changes without the knowledge of the firm. Over time the firm learns about the nature and extent of the change in the distribution of the shock and adjusts, incurring adjustment costs in the process. The long-run loss in profits (±) due to the shift in the distribution we term the equilibrium response. The transitory loss in profits, incurred while the firm is learning about the distribution shift, is termed the adjustment cost. The theory is then applied to the problem of measuring adjustment costs in the face of imperfectly observed climate change in agriculture. The empirical part of the paper involves estimating a restricted profit function for agricultural land in a five-state region of the Midwest US as a function of prices, land characteristics, actual weather realizations and expected weather. We then simulate the effect of an unobserved climate shock, where learning about the climate shock is by observing the weather and updating prior knowledge using Bayes Rule. We find adjustment costs to climate change are 1.4% of annual land rents.     

Globally regional life cycle analysis of automotive lithium-ion nickel manganese cobalt batteries

Electric vehicles based on lithium-ion batteries (LIB) have seen rapid growth over the past decade as they are viewed as a cleaner alternative to conventional fossil-fuel burning vehicles, especially for local pollutant (nitrogen oxides [NO_x], sulfur oxides [SO_x], and particulate matter with diameters less than 2.5 and 10 μm [PM_2.5 and PM₁₀]) and CO₂ emissions. However, LIBs are known to have their own energy and environmental challenges. This study focuses on LIBs made of lithium nickel manganese cobalt oxide (NMC), since they currently dominate the United States (US) and global automotive markets and will continue to do so into the foreseeable future. The effects of globalized production of NMC, especially LiNi_1/3Mn_1/3Co_1/3O₂ (NMC111), are examined, considering the potential regional variability at several important stages of production. This study explores regional effects of alumina reduction and nickel refining, along with the production of NMC cathode, battery cells, and battery management systems. Of primary concern is how production of these battery materials and components in different parts of the world may impact the battery’s life cycle pollutant emissions and total energy and water consumption. Since energy sources for heat and electricity generation are subject to great regional variation, we anticipated significant variability in the energy and emissions associated with LIB production. We configured Argonne National Laboratory’s Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET®) model as the basis for this study with key input data from several world regions. In particular, the study examined LIB production in the US, China, Japan, South Korea, and Europe, with details of supply chains and the electrical grid in these regions. Results indicate that 27-kWh automotive NMC111 LIBs produced via a European-dominant supply chain generate 65 kg CO₂e/kWh, while those produced via a Chinese-dominant supply chain generate 100 kg CO₂e/kWh. Further, there are significant regional differences for local pollutants associated with LIB, especially SO_x emissions related to nickel production. We find that no single regional supply chain outperforms all others in every evaluation metric, but the data indicate that supply chains powered by renewable electricity provide the greatest emission reduction potential.

     

Geoadditive regression modeling of stream biological condition

Indices of biotic integrity have become an established tool to quantify the condition of small non-tidal streams and their watersheds. To investigate the effects of watershed characteristics on stream biological condition, we present a new technique for regressing IBIs on watershed-specific explanatory variables. Since IBIs are typically evaluated on an ordinal scale, our method is based on the proportional odds model for ordinal outcomes. To avoid overfitting, we do not use classical maximum likelihood estimation but a component-wise functional gradient boosting approach. Because component-wise gradient boosting has an intrinsic mechanism for variable selection and model choice, determinants of biotic integrity can be identified. In addition, the method offers a relatively simple way to account for spatial correlation in ecological data. An analysis of the Maryland Biological Streams Survey shows that nonlinear effects of predictor variables on stream condition can be quantified while, in addition, accurate predictions of biological condition at unsurveyed locations are obtained.     

Concentration and Recovery of Viruses from Water: A Comprehensive Review

Enteric viruses are a cause of waterborne disease worldwide, and low numbers in drinking water can present a significant risk of infection. Because the numbers are often quite low, large volumes (100–1,000 L) of water are usually processed. The VIRADEL method using microporous filters is most commonly used today for this purpose. Negatively charged filters require the addition of multivalent salts and acidification of the water sample to effect virus adsorption, which can make large-volume sampling difficult. Positively charged filters require no preconditioning of samples, and are able to concentrate viruses from water over a greater pH range than electronegative filters. The most widely used electropositive filter is the Virosorb 1MDS; however, the Environmental Protection Agency has added the positively charged NanoCeram filters to their proposed Method 1615. Ultrafilters concentrate viruses based on size exclusion rather than electrokinetics, but are impractical for field sampling or processing of turbid water. Elution (recovery) of viruses from filters following concentration is performed with organic (e.g., beef extract) or inorganic solutions (e.g., sodium polyphosphates). Eluates are then reconcentrated to decrease the sample volume to enhance detection methods (e.g., cell culture infectivity assays and molecular detection techniques). While the majority of available filters have demonstrated high virus retention efficiencies, the methods to elute and reconcentrate viruses have met with varying degrees of success due to the biological variability of viruses present in water.     

Using decision science to evaluate global biodiversity indices

Global biodiversity indices are used to measure environmental change and progress toward conservation goals, yet few indices have been evaluated comprehensively for their capacity to detect trends of interest, such as declines in threatened species or ecosystem function. Using a structured approach based on decision science, we qualitatively evaluated 9 indices commonly used to track biodiversity at global and regional scales against 5 criteria relating to objectives, design, behavior, incorporation of uncertainty, and constraints (e.g., costs and data availability). Evaluation was based on reference literature for indices available at the time of assessment. We identified 4 key gaps in indices assessed: pathways to achieving goals (means objectives) were not always clear or relevant to desired outcomes (fundamental objectives); index testing and understanding of expected behavior was often lacking; uncertainty was seldom acknowledged or accounted for; and costs of implementation were seldom considered. These gaps may render indices inadequate in certain decision-making contexts and are problematic for indices linked with biodiversity targets and sustainability goals. Ensuring that index objectives are clear and their design is underpinned by a model of relevant processes are crucial in addressing the gaps identified by our assessment. Uptake and productive use of indices will be improved if index performance is tested rigorously and assumptions and uncertainties are clearly communicated to end users. This will increase index accuracy and value in tracking biodiversity change and supporting national and global policy decisions, such as the post-2020 global biodiversity framework of the Convention on Biological Diversity.     

Tagging Diesel and Residential Oil Furnace Emissions in Roanoke,Virginia, with Enriched Isotopes of Samarium

Stable isotopic tracers were used in Roanoke, Virginia, to tag particulate emissions from diesel trucks and residential oil furnaces, two sources of soot and PAHs which cannot be differentiated on the basis of known constituents. Approximately 1.6 g of enriched ¹⁴⁹Sm were used to tag 264 m³ of diesel fuel burned by the city bus and truck fleets; 0.39 g of ¹⁵⁰Sm were used to tag 106 m³ of residential heating oil. Picogram amounts of the tracers were determined simultaneously by thermal-ionization mass spectrometry in fine particles collected within the city at signal-to-noise ratios as large as 6000. These results demonstrate the feasibility of tracing particles from multiple combustion sources with stable, separated isotopes.