ESTIMATING INSECTICIDE APPLICATION FREQUENCIES: A COMPARISON OF GEOMETRIC AND OTHER COUNT DATA MODELS

The number of insecticide applications made by an apple grower to control an insect infestation is modeled as a geometric random variable. Insecticide efficacy, rate per application, month of treatment, and method of application all have significant impacts on the expected number of applications. The number of applications to control a given insect population is dependent on the probability of achieving successful control with a given application. Results suggest that northeastern growers have the highest and mid-Atlantic growers the lowest probability of controlling an infestation with a given application. Results also indicate that scales require the least and moths the most number of applications. Growers are not responsive to per unit insecticide prices, but respond negatively to insecticide toxicity, supporting findings from previous pesticide demand analyses.Apples, Count data, Geometric, Insect control, Pesticides, Crop Production/Industries,

INFORMATION QUALITY, TECHNOLOGY DEPRECIATION, AND BT COTTON ADOPTION IN THE SOUTHEAST

In 1996, Bt cotton became one of the first genetically engineered crops to be available commercially. This study focuses on the various sources and quality of information about Bt cotton profitability available to farmers in the Southeast and assesses the relative importance of such information in the farmers' adoption decisions. A model of the individual decision to adopt is developed to incorporate two recent theories of the role of information quality (the "effective information" hypothesis and the "popularity" hypothesis) as well as the effect of current technology depreciation. The data show some support for all three factors as determinants of adoption.Crop Production/Industries,

Health-Related Benefits of Attaining the 8-Hr Ozone Standard

During the 2000–2002 time period, between 36 and 56% of ozone monitors each year in the United States failed to meet the current ozone standard of 80 ppb for the fourth highest maximum 8-hr ozone concentration. We estimated the health benefits of attaining the ozone standard at these monitors using the U.S. Environmental Protection Agency’s Environmental Benefits Mapping and Analysis Program. We used health impact functions based on published epidemiologic studies, and valuation functions derived from the economics literature. The estimated health benefits for 2000 and 2001 are similar in magnitude, whereas the results for 2002 are roughly twice that of each of the prior 2 years. The simple average of health impacts across the 3 years includes reductions of 800 premature deaths, 4,500 hospital and emergency department admissions, 900,000 school absences, and > 1 million minor restricted activity days. The simple average of benefits (including premature mortality) across the 3 years is $5.7 billion [90$4.9 billion (90% CI, 0.5–14.0) for the proportional rollback simulation method. Results are sensitive to the form of the standard and to assumptions about background ozone levels. If the form of the standard is based on the first highest maximum 8-hr concentration, impacts are increased by a factor of 2–3. Increasing the assumed hourly background from zero to 40 ppb reduced impacts by 30 and 60% for the proportional and quadratic attainment simulation methods, respectively

The influence of location, source, and emission type in estimates of the human health benefits of reducing a ton of air pollution

The benefit per ton ($/ton) of reducing PM2.5 varies by the location of the emission reduction, the type of source emitting the precursor, and the specific precursor controlled. This paper examines how each of these factors influences the magnitude of the$/ton estimate. We employ a reduced-form air quality model to predict changes in ambient PM2.5 resulting from an array of emission control scenarios affecting 12 different combinations of sources emitting carbonaceous particles, NOx, SOx, NH3, and volatile organic compounds. We perform this modeling for each of nine urban areas and one nationwide area. Upon modeling the air quality change, we then divide the total monetized health benefits by the PM2.5 precursor emission reductions to generate $/ton metrics. The resulting$/ton estimates exhibit the greatest variability across certain precursors and sources such as area source SOx, point source SOx, and mobile source NH3. Certain $/ton estimates, including mobile source NOx, exhibit significant variability across urban areas. Reductions in carbonaceous particles generate the largest$/ton across all locations

Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: an analysis of data from the Global Burden of Diseases Study 2015

Background Exposure to ambient air pollution increases morbidity and mortality, and is a leading contributor to global disease burden. We explored spatial and temporal trends in mortality and burden of disease attributable to ambient air pollution from 1990 to 2015 at global, regional, and country levels. Methods We estimated global population-weighted mean concentrations of particle mass with aerodynamic diameter less than 2·5 μm (PM2·5) and ozone at an approximate 11 km × 11 km resolution with satellite-based estimates, chemical transport models, and ground-level measurements. Using integrated exposure–response functions for each cause of death, we estimated the relative risk of mortality from ischaemic heart disease, cerebrovascular disease, chronic obstructive pulmonary disease, lung cancer, and lower respiratory infections from epidemiological studies using non-linear exposure–response functions spanning the global range of exposure. Findings Ambient PM2·5 was the fifth-ranking mortality risk factor in 2015. Exposure to PM2·5 caused 4·2 million (95% uncertainty interval [UI] 3·7 million to 4·8 million) deaths and 103·1 million (90·8 million 115·1 million) disability-adjusted life-years (DALYs) in 2015, representing 7·6% of total global deaths and 4·2% of global DALYs, 59% of these in east and south Asia. Deaths attributable to ambient PM2·5 increased from 3·5 million (95% UI 3·0 million to 4·0 million) in 1990 to 4·2 million (3·7 million to 4·8 million) in 2015. Exposure to ozone caused an additional 254 000 (95% UI 97 000–422 000) deaths and a loss of 4·1 million (1·6 million to 6·8 million) DALYs from chronic obstructive pulmonary disease in 2015. Interpretation Ambient air pollution contributed substantially to the global burden of disease in 2015, which increased over the past 25 years, due to population ageing, changes in non-communicable disease rates, and increasing air pollution in low-income and middle-income countries. Modest reductions in burden will occur in the most polluted countries unless PM2·5 values are decreased substantially, but there is potential for substantial health benefits from exposure reduction

Bioactive Hydrogel Substrates: Probing Leukocyte Receptor–Ligand Interactions in Parallel Plate Flow Chamber Studies

The binding of activated integrins on the surface of leukocytes facilitates the adhesion of leukocytes to vascular endothelium during inflammation. Interactions between selectins and their ligands mediate rolling, and are believed to play an important role in leukocyte adhesion, though the minimal recognition motif required for physiologic interactions is not known. We have developed a novel system using poly(ethylene glycol) (PEG) hydrogels modified with either integrin-binding peptide sequences or the selectin ligand sialyl Lewis X (SLe(X)) within a parallel plate flow chamber to examine the dynamics of leukocyte adhesion to specific ligands. The adhesive peptide sequences arginine–glycine–aspartic acid–serine (RGDS) and leucine–aspartic acid–valine (LDV) as well as sialyl Lewis X were bound to the surface of photopolymerized PEG diacrylate hydrogels. Leukocytes perfused over these gels in a parallel plate flow chamber at physiological shear rates demonstrate both rolling and firm adhesion, depending on the identity and concentration of ligand bound to the hydrogel substrate. This new system provides a unique polymer-based model for the study of interactions between leukocytes and endothelium as well as a platform to develop improved scaffolds for cardiovascular tissue engineering

Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter.

Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations

Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (similar to 25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available

A Comparative Risk Assessment Of Burden Of Disease And Injury Attributable To 67 Risk Factors And Risk Factor Clusters In 21 Regions, 1990–2010: A Systematic Analysis For The Global Burden Of Disease Study 2010

Background Quantification of the disease burden caused by different risks informs prevention by providing an account of health loss different to that provided by a disease-by-disease analysis. No complete revision of global disease burden caused by risk factors has been done since a comparative risk assessment in 2000, and no previous analysis has assessed changes in burden attributable to risk factors over time

Biodiversity recovery of Neotropical secondary forests

Old-growth tropical forests harbor an immense diversity of tree species but are rapidly being cleared, while secondary forests that regrow on abandoned agricultural lands increase in extent. We assess how tree species richness and composition recover during secondary succession across gradients in environmental conditions and anthropogenic disturbance in an unprecedented multisite analysis for the Neotropics. Secondary forests recover remarkably fast in species richness but slowly in species composition. Secondary forests take a median time of five decades to recover the species richness of old-growth forest (80% recovery after 20 years) based on rarefaction analysis. Full recovery of species composition takes centuries (only 34% recovery after 20 years). A dual strategy that maintains both old-growth forests and species-rich secondary forests is therefore crucial for biodiversity conservation in human-modified tropical landscapes. Copyright © 2019 The Authors, some rights reserved