Managing Forests for Biodiversity Conservation and Climate Change Mitigation.

We include biodiversity impacts in forest management decision making by incorporating the countryside species area relationship model into the partial equilibrium model GLOBIOM-Forest. We tested three forest management intensities (low, medium, and high) and limited biodiversity loss via an additional constraint on regional species loss. We analyzed two scenarios for climate change mitigation. RCP1.9, the higher mitigation scenario, has more biodiversity loss than the reference RCP7.0, suggesting a trade-off between climate change mitigation, with increased bioenergy use, and biodiversity conservation in forests. This trade-off can be alleviated with biodiversity-conscious forest management by (1) shifting biomass production destined to bioenergy from forests to energy crops, (2) increasing areas under unmanaged secondary forest, (3) reducing forest management intensity, and (4) reallocating biomass production between and within regions. With these mechanisms, it is possible to reduce potential global biodiversity loss by 10% with minor changes in economic outcomes. The global aggregated reduction in biodiversity impacts does not imply that biodiversity impacts are reduced in each ecoregion. We exemplify how to connect an ecologic and an economic model to identify trade-offs, challenges, and possibilities for improved decisions. We acknowledge the limitations of this approach, especially of measuring and projecting biodiversity loss.

Scientific and Regulatory Policy Committee Points to Consider for Medical Device Implant Site Evaluation in Nonclinical Studies.

Nonclinical implantation studies are a common and often critical step for medical device safety assessment in the bench-to-market pathway. Nonclinical implanted medical devices or drug-device combination products require complex macroscopic and microscopic pathology evaluations due to the physical presence of the device itself and unique tissue responses to device materials. The Medical Device Implant Site Evaluation working group of the Society of Toxicologic Pathology's (STP) Scientific and Regulatory Policy Committee (SRPC) was tasked with reviewing scientific, technical, and regulatory considerations for these studies. Implant site evaluations require highly specialized methods and analytical schemes that should be designed on a case-by-case basis to address specific study objectives. Existing STP best practice recommendations can serve as a framework when performing nonclinical studies under Good Laboratory Practices and help mitigate limitations in standards and guidances for implant evaluations (e.g., those from the International Organization for Standardization [ISO], ASTM International). This article integrates standards referenced by sponsors and regulatory bodies with practical pathology evaluation methods for implantable medical devices and combination products. The goal is to ensure the maximum accuracy and scientific relevance of pathology data acquired during a medical device or combination drug-device implantation study.

Relation of blood lead levels and lead in gasoline: an updated systematic review.

BACKGROUND: Millions of tons of lead were added to gasoline worldwide beginning in 1922, and leaded gasoline has been a major source of population lead exposure. In 1960s, lead began to be removed from automotive gasoline. Removal was completed in 2021. OBJECTIVES: To determine whether removal of lead from automotive gasoline is associated with declines in population mean blood lead levels (BPb). METHODS: We examined published studies that reported population blood leaded levels for two or more years, and we calculated average concentrations of lead in gasoline corresponding to the years and locations of the blood lead level measurements. RESULTS: Removal of lead from gasoline is associated with declines in BPb in all countries examined. In some countries, BPb continues to fall after lead has been eliminated from gasoline. Following elimination of lead from gasoline, BPb less than 1 µg/dL have been observed in several European and North American countries, and BPb less than 3 µg/dL have been documented in several studies from South America. DISCUSSION: There remain many countries for which no multi-year studies of populations BPb have been identified, including all of Central America, high population countries including Pakistan and Indonesia, and major lead producers including Australia and Russia. CONCLUSION: Removal of lead from gasoline has been a public health success. Elimination of lead from gasoline has enabled many countries to achieve population mean BPb levels of 1 µg/dL or lower. These actions have saved lives, increased children's intelligence and created great economic benefit in countries worldwide.

Combined Heat and Power May Conflict with Decarbonization Goals-Air Emissions of Natural Gas Combined Cycle Power versus Combined Heat and Power Systems for Commercial Buildings.

This study compares the environmental impacts of a centralized natural gas combined cycle (NGCC) and a distributed natural gas-fired combined heat and power (CHP) energy system in the United States. We develop an energy-balance model in which each energy system supplies the electric, heating, and cooling demands of 16 commercial building types in 16 climate zones of the United States. We assume a best-case scenario where all the CHP's heat and power are allocated toward building demands to ensure robust results. We quantify the greenhouse gas (GHG) emissions, conventional air pollutants (CAPs), and natural gas (NG) consumption. In most cases, the decentralized CHP system increases GHG emissions, decreases CAP emissions, and decreases NG consumption relative to the centralized NGCC system. Only fuel-cell CHPs were able to simultaneously reduce GHG, CAP, and NG consumption relative to the NGCC-based system. The results suggest that despite their energy efficiency benefits, standard distributed CHP-based systems typically do not have enough benefits compared to an NGCC-based system to justify a reorganization of existing infrastructure systems. Because fuel-cell CHPs can also use hydrogen as a fuel source, they are compatible with decarbonized energy systems and may aid in the transition toward a cleaner energy economy.

A mid-century ecological forecast with partitioned uncertainty predicts increases in loblolly pine forest productivity.

Ecological forecasting of forest productivity involves integrating observations into a process-based model and propagating the dominant components of uncertainty to generate probability distributions for future states and fluxes. Here, we develop a forecast for the biomass change in loblolly pine (Pinus taeda) forests of the southeastern United States and evaluate the relative contribution of different forms of uncertainty to the total forecast uncertainty. Specifically, we assimilated observations of carbon and flux stocks and fluxes from sites across the region, including global change experiments, into a forest ecosystem model to calibrate the parameter distributions and estimate the process uncertainty (i.e., model structure uncertainty revealed in the residuals of the calibration). Using this calibration, we forecasted the change in biomass within each 12-digit Hydrologic (H12) unit across the native range of loblolly pine between 2010 and 2055 under the Representative Concentration Pathway 8.5 scenario. Averaged across the region, productivity is predicted to increase by a mean of 31% between 2010 and 2055 with an average forecast 95% quantile interval of ±15 percentage units. The largest increases were predicted in cooler locations, corresponding to the largest projected changes in temperature. The forecasted mean change varied considerably among the H12 units (3-80% productivity increase), but only units in the warmest and driest extents of the loblolly pine range had forecast distributions with probabilities of a decline in productivity that exceeded 5%. By isolating the individual components of the forecast uncertainty, we found that ecosystem model process uncertainty made the largest individual contribution. Ecosystem model parameter and climate model uncertainty had similar contributions to the overall forecast uncertainty, but with differing spatial patterns across the study region. The probabilistic framework developed here could be modified to include additional sources of uncertainty, including changes due to fire, insects, and pests: processes that would result in lower productivity changes than forecasted here. Overall, this study presents an ecological forecast at the ecosystem management scale so that land managers can explicitly account for uncertainty in decision analysis. Furthermore, it highlights that future work should focus on quantifying, propagating, and reducing ecosystem model process uncertainty.

New approach for optimal electricity planning and dispatching with hourly time-scale air quality and health considerations.

Integrating accurate air quality modeling with decision making is hampered by complex atmospheric physics and chemistry and its coupling with atmospheric transport. Existing approaches to model the physics and chemistry accurately lead to significant computational burdens in computing the response of atmospheric concentrations to changes in emissions profiles. By integrating a reduced form of a fully coupled atmospheric model within a unit commitment optimization model, we allow, for the first time to our knowledge, a fully dynamical approach toward electricity planning that accurately and rapidly minimizes both cost and health impacts. The reduced-form model captures the response of spatially resolved air pollutant concentrations to changes in electricity-generating plant emissions on an hourly basis with accuracy comparable to a comprehensive air quality model. The integrated model allows for the inclusion of human health impacts into cost-based decisions for power plant operation. We use the new capability in a case study of the state of Georgia over the years of 2004-2011, and show that a shift in utilization among existing power plants during selected hourly periods could have provided a health cost savings of $175.9 million dollars for an additional electricity generation cost of $83.6 million in 2007 US dollars (USD2007). The case study illustrates how air pollutant health impacts can be cost-effectively minimized by intelligently modulating power plant operations over multihour periods, without implementing additional emissions control technologies.

Longitudinal effects of prenatal exposure to air pollutants on self-regulatory capacities and social competence.

BACKGROUND: We evaluated the influence of prenatal exposure to widespread urban air pollutants on the development of self-regulation and social competence in a longitudinal prospective cohort of children born to nonsmoking minority women in New York City. METHODS: Air pollutant exposure was estimated categorically by level of polycyclic aromatic hydrocarbon (PAH)-DNA adducts in maternal blood collected at delivery, providing a biomarker of maternal exposure to PAH over a 2- to 3-month period. Deficient emotional self-regulation (DESR) was defined as moderate elevations on three specific scales of the child behavior checklist (anxious/depressed, aggressive behavior, and attention problems). We used generalized estimating equations to assess the influence of prenatal exposure to PAH on DESR in children at 3-5, 7, 9, and 11 years of age, adjusted for gender and race/ethnicity. Next, we assessed the association of prenatal exposure to PAH with social competence, as measured by the social responsiveness scale (SRS), the association of impaired self-regulation with social competence, and whether impairment in self-regulation mediated the association of prenatal exposure to PAH with social competence. RESULTS: We detected a significant interaction (at p = .05) of exposure with time, in which the developmental trajectory of self-regulatory capacity was delayed in the exposed children. Multiple linear regression revealed a positive association between presence of PAH-DNA adducts and problems with social competence (p < .04), level of dysregulation and problems with social competence (p < .0001), and evidence that self-regulation mediates the association of prenatal exposure to PAH with social competence (p < .0007). CONCLUSIONS: These data suggest that prenatal exposure to PAH produces long-lasting effects on self-regulatory capacities across early and middle childhood, and that these deficits point to emerging social problems with real-world consequences for high-risk adolescent behaviors in this minority urban cohort.

Habitat suitability of biocrust communities in a cold desert ecosystem.

Drylands are unique among terrestrial ecosystems in that they have a significant proportion of primary production facilitated by non-vascular plants such as colonial cyanobacteria, moss, and lichens, i.e., biocrusts, which occur on and in the surface soil. Biocrusts inhabit all continents, including Antarctica, an increasingly dynamic continent on the precipice of change. Here, we describe in-situ field surveying and sampling, remote sensing, and modeling approaches to assess the habitat suitability of biocrusts in the Lake Fryxell basin of Taylor Valley, Antarctica, which is the main site of the McMurdo Dry Valleys Long-Term Ecological Research Program. Soils suitable for the development of biocrusts are typically wetter, less alkaline, and less saline compared to unvegetated soils. Using random forest models, we show that gravimetric water content, electrical conductivity, and snow frequency are the top predictors of biocrust presence and biomass. Areas most suitable for the growth of dense biocrusts are soils associated with seasonal snow patches. Using geospatial data to extrapolate our habitat suitability model to the whole basin predicts that biocrusts are present in 2.7 × 105 m2 and contain 11-72 Mg of aboveground carbon, based on the 90% probability of occurrence. Our study illustrates the synergistic effect of combining field and remote sensing data for understanding the distribution and biomass of biocrusts, a foundational community in the carbon balance of this region. Extreme weather events and changing climate conditions in this region, especially those influencing snow accumulation and persistence, could have significant effects on the future distribution and abundance of biocrusts and therefore soil organic carbon storage in the McMurdo Dry Valleys.

Electric urban delivery trucks: energy use, greenhouse gas emissions, and cost-effectiveness.

We compare electric and diesel urban delivery trucks in terms of life-cycle energy consumption, greenhouse gas (GHG) emissions, and total cost of ownership (TCO). The relative benefits of electric trucks depend heavily on vehicle efficiency associated with drive cycle, diesel fuel price, travel demand, electric drive battery replacement and price, electricity generation and transmission efficiency, electric truck recharging infrastructure, and purchase price. For a drive cycle with frequent stops and low average speed such as the New York City Cycle (NYCC), electric trucks emit 42-61% less GHGs and consume 32-54% less energy than diesel trucks, depending upon vehicle efficiency cases. Over an array of possible conditions, the median TCO of electric trucks is 22% less than that of diesel trucks on the NYCC. For a drive cycle with less frequent stops and high average speed such as the City-Suburban Heavy Vehicle Cycle (CSHVC), electric trucks emit 19-43% less GHGs and consume 5-34% less energy, but cost 1% more than diesel counterparts. Considering current and projected U.S. regional electricity generation mixes, for the baseline case, the energy use and GHG emissions ratios of electric to diesel trucks range from 48 to 82% and 25 to 89%, respectively.

Coordinated EV adoption: double-digit reductions in emissions and fuel use for $40/vehicle-year.

Adoption of electric vehicles (EVs) would affect the costs and sources of electricity and the United States efficiency requirements for conventional vehicles (CVs). We model EV adoption scenarios in each of six regions of the Eastern Interconnection, containing 70% of the United States population. We develop electricity system optimization models at the multidecade, day-ahead, and hour-ahead time scales, incorporating spatial wind energy modeling, endogenous modeling of CV efficiencies, projections for EV efficiencies, and projected CV and EV costs. We find two means to reduce total consumer expenditure (TCE): (i) controlling charge timing and (ii) unlinking the fuel economy regulations for CVs from EVs. Although EVs provide minimal direct GHG reductions, controlled charging provides load flexibility, lowering the cost of renewable electricity. Without EVs, a 33% renewable electricity standard (RES) would cost $193/vehicle-year more than the reference case (10% RES). Combining a 33% RES, EVs with controlled charging and unlinking would reduce combined electric- and vehicle-sector CO2 emissions by 27% and reduce gasoline consumption by 59% for $40/vehicle-year more than the reference case. Coordinating EV adoption with adoption of controlled charging, unlinked fuel economy regulations, and renewable electricity standards would provide low-cost reductions in emissions and fuel usage.

Pan-European monitoring of susceptibility to human-use antimicrobial agents in enteric bacteria isolated from healthy food-producing animals.

OBJECTIVES: To determine the antimicrobial susceptibility of Escherichia coli, Salmonella, Campylobacter and Enterococcus from cattle, pigs and chickens across the European Union (EU) using uniform methodology. METHODS: Intestinal samples (1624) were taken at slaughter across five EU countries. Bacteria were isolated in national laboratories, whilst MICs were determined in a central laboratory for key antimicrobials used in human medicine. Clinical resistance was based on CLSI breakpoints and decreased susceptibility based on European Food Safety Authority (EFSA)/EUCAST epidemiological cut-off values. RESULTS: Isolation rates were high for E. coli (n=1540), low for Salmonella (n=201) and intermediate for Campylobacter (n=940) and Enterococcus (n=786). For E. coli and Salmonella, clinical resistance to newer compounds (cefepime, cefotaxime and ciprofloxacin) was absent or low, but decreased susceptibility was apparent, particularly in chicken strains. Resistance to older compounds (except gentamicin) was variable and higher. Colistin resistance was absent for E. coli, but apparent for Salmonella. For Campylobacter jejuni, ciprofloxacin resistance was markedly prevalent for chickens, whereas clinical resistance and decreased susceptibility to erythromycin was absent or very low. For Campylobacter coli, resistance was notably higher. None of the Enterococcus faecium strains was resistant to linezolid, but some were resistant to ampicillin or vancomycin. Resistance to quinupristin/dalfopristin was frequent. CONCLUSIONS: Resistance patterns varied widely depending on bacterial species, antibiotics, hosts and region. Resistance varied among countries, particularly for older antimicrobials, but clinical resistance to newer antibiotics used to treat foodborne disease in humans was generally very low. In the absence of resistance to newer compounds in E. coli and Salmonella, the apparent decreased susceptibility should be monitored.

Incorporating New Technologies in EEIO Models.

We propose a methodology to add new technologies into Environmentally Extended Input-Output (EEIO) models based on a Supply and Use framework. The methodology provides for adding new industries (new technologies) and a new commodity under the assumption that the new commodity will partially substitute for a functionally-similar existing commodity of the baseline economy. The level of substitution is controlled by a percentage (%) as a variable of the model. In the Use table, a percentage of the current use of the existing commodity is transferred to the new commodity. The Supply or Make table is modified assuming that the new industries are the only ones producing the new commodity. We illustrate the method for the USEEIO model, for the addition of second generation biofuels, including naphtha, jet fuel and diesel fuel. The new industries' inputs, outputs and value-added components needed to produce the new commodity are drawn from process-based life cycle inventories (LCIs). Process-based LCI inputs and outputs per physical functional unit are transformed to prices and assigned to commodities and environmental flow categories for the EEIO model. This methodology is designed to evaluate the environmental impacts of substituting products in the current US economy with bio-versions, produced by new technologies, that are intended to reduce negative environmental impacts. However, it can be applied for any new commodity for which the substitution assumption is reasonable.

Bone mass and microarchitecture in CKD patients with fracture.

Patients with predialysis chronic kidney disease (CKD) have increased risk for fracture, but the structural mechanisms underlying this increased skeletal fragility are unknown. We measured areal bone mineral density (aBMD) by dual-energy x-ray absorptiometry at the spine, hip, and radius, and we measured volumetric BMD (vBMD), geometry, and microarchitecture by high-resolution peripheral quantitative computed tomography (HR-pQCT) at the radius and tibia in patients with CKD: 32 with fracture and 59 without fracture. Patients with fracture had lower aBMD at the spine, total hip, femoral neck, and the ultradistal radius, the last having the strongest association with fracture. By HR-pQCT of the radius, patients with fracture had lower cortical area and thickness, total and trabecular vBMD, and trabecular number and greater trabecular separation and network heterogeneity. At the tibia, patients with fracture had significantly lower cortical area, thickness, and total and cortical density. Total vBMD at both radius and tibia most strongly associated with fracture. By receiver operator characteristic curve analysis, patients with longer duration of CKD had area under the curve of >0.75 for aBMD at both hip sites and the ultradistal radius, vBMD and geometry at the radius and tibia, and microarchitecture at the tibia. In summary, patients with predialysis CKD and fractures have lower aBMD by dual-energy x-ray absorptiometry and lower vBMD, thinner cortices, and trabecular loss by HR-pQCT. These density and structural differences may underlie the increased susceptibility to fracture among patients with CKD.

Recovery of Critical Metals from Aqueous Sources.

Critical metals, identified from supply, demand, imports, and market factors, include rare earth elements (REE), platinum group metals, precious metals, and other valuable metals such as lithium, cobalt, nickel, and uranium. Extraction of metals from U.S. saline aqueous, emphasizing saline, sources is explored as an alternative to hardrock ore mining. Potential aqueous sources include seawater, desalination brines, oil-and-gas produced waters, geothermal aquifers, and acid mine drainage, among others. A feasibility assessment reveals opportunities for recovery of lithium, strontium, magnesium, and several REE from select sources, in quantities significant for U.S. manufacturing and for reduction of U.S. reliance on international supply chains. This is a conservative assessment given that water quality data are lacking for a significant number of critical metals in certain sources. The technology landscape for extraction and recovery of critical metals from aqueous sources is explored, identifying relevant processes along with knowledge gaps. Our analysis indicates that aqueous mining would result in much lower environmental impacts on water, air, and land than ore mining. Preliminary assessments of the economics and energy consumption of recovery show potential for recovery of critical metals.

Life cycle energy and greenhouse gas emissions for an ethanol production process based on blue-green algae.

Ethanol can be produced via an intracellular photosynthetic process in cyanobacteria (blue-green algae), excreted through the cell walls, collected from closed photobioreactors as a dilute ethanol-in-water solution, and purified to fuel grade ethanol. This sequence forms the basis for a biofuel production process that is currently being examined for its commercial potential. In this paper, we calculate the life cycle energy and greenhouse gas emissions for three different system scenarios for this proposed ethanol production process, using process simulations and thermodynamic calculations. The energy required for ethanol separation increases rapidly for low initial concentrations of ethanol, and, unlike other biofuel systems, there is little waste biomass available to provide process heat and electricity to offset those energy requirements. The ethanol purification process is a major consumer of energy and a significant contributor to the carbon footprint. With a lead scenario based on a natural-gas-fueled combined heat and power system to provide process electricity and extra heat and conservative assumptions around the ethanol separation process, the net life cycle energy consumption, excluding photosynthesis, ranges from 0.55 MJ/MJ(EtOH) down to 0.20 MJ/ MJ(EtOH), and the net life cycle greenhouse gas emissions range from 29.8 g CO2e/MJ(EtOH) down to 12.3 g CO2e/MJ(EtOH) for initial ethanol concentrations from 0.5 wt % to 5 wt %. In comparison to gasoline, these predicted values represent 67% and 87% reductions in the carbon footprint for this ethanol fuel on a energy equivalent basis. Energy consumption and greenhouse gas emissions can be further reduced via employment of higher efficiency heat exchangers in ethanol purification and/ or with use of solar thermal for some of the process heat.

Similarities in Recalcitrant Structures of Industrial Non-Kraft and Kraft Lignin.

This work compares the structure of industrially isolated lignin samples from kraft pulping and three alternative processes: butanol organosolv, supercritical water hydrolysis, and sulfur dioxide/ethanol/water fractionation. Kraft processes are known to produce highly condensed lignin, with reduced potential for catalytic depolymerization, whereas the alternative processes have been hypothesized to impact the lignin less. The structural properties most relevant to catalytic depolymerization are characterized by elemental analysis, quantitative 13 C and 2 D HQSC NMR spectroscopy, gel permeation chromatography, and thermogravimetric analysis. Quantification of the ß-O-4 ether bond content shows partial depolymerization, with all samples having less than 12 bonds per 100 aromatic units. This results in theoretical monomer yields of less than 5 %, strongly suggesting the alternative fractionation processes generate highly condensed lignin structures that are no more suitable for catalytic depolymerization than kraft lignin. However, the different thermal degradation profiles suggest there are physicochemical differences that could be leveraged in other valorization strategies.

A pan-European survey of antimicrobial susceptibility towards human-use antimicrobial drugs among zoonotic and commensal enteric bacteria isolated from healthy food-producing animals.

OBJECTIVES: The aim of the study was to study antimicrobial susceptibility in Escherichia coli, Salmonella, Campylobacter and Enterococcus recovered from chickens, pigs and cattle using uniform methodology. METHODS: Intestinal samples were taken at slaughter in five EU countries per host and bacteria isolated in national laboratories. MICs were determined in a central laboratory of key antimicrobials used in human medicine. Clinical resistance was based on CLSI breakpoints and decreased susceptibility on EFSA epidemiological cut-off values. RESULTS: Isolation rates from a total of 1500 samples were high for E. coli (n=1465), low for Salmonella (n=205) and intermediate for Campylobacter (n=785) and Enterococcus (n=718). Resistance prevalence varied among antibiotics, bacteria, hosts and countries. For E. coli and Salmonella, clinical resistance to newer compounds (cefepime, cefotaxime, ciprofloxacin) was absent or low, but a decreased susceptibility was apparent, particularly in chickens. Clinical resistance to older compounds (except colistin and gentamicin) was variable and higher. For Campylobacter jejuni from chickens, ciprofloxacin resistance was markedly higher than in isolates from cattle. Clinical resistance to erythromycin was absent for both hosts; decreased susceptibility very low. Similar trends were determined for Campylobacter coli, but C. jejuni was less resistant. None of the enterococcal strains was resistant to linezolid, but a few displayed resistance to ampicillin or vancomycin. Resistance prevalence to quinupristin/dalfopristin was clearly higher. CONCLUSIONS: Antimicrobial resistance among enteric organisms in food animals varied among countries, particularly for older antimicrobials, but clinical resistance to essential compounds used to treat disease in humans was generally zero or low. In the absence of clinical resistance to newer compounds in E. coli and Salmonella, the apparent decreased susceptibility should be monitored carefully.

Future Lyme disease risk in the south-eastern United States based on projected land cover.

Lyme disease is the most significant vector-borne disease in the United States, and its southward advance over several decades has been quantified. Previous research has examined the potential role of climate change on the disease's expansion, but no studies have considered the role of future land cover upon its distribution. This research examines Lyme disease risk in the south-eastern U.S. based on projected land cover developed under four Intergovernmental Panel on Climate Change Scenarios: A1B, A2, B1, and B2. Land cover types and edge indices significantly associated with Lyme disease in Virginia were incorporated into a spatial Poisson regression model to quantify potential land cover suitability for Lyme disease in the south-eastern U.S. under each scenario. Our results indicate an intensification of potential land cover suitability for Lyme disease under the A scenarios and a decrease of potential land cover suitability under the B scenarios. The decrease under the B scenarios is a critical result, indicating that Lyme disease risk can be decreased by making different land cover choices. Additionally, health officials can focus efforts in projected high incidence areas.

Relation of chlorine, copper and sulphur to dioxin emission factors.

Dioxin emission factors for different combustion categories range over five orders of magnitude. Both chlorine (Cl(2)) and transition metals, including copper (Cu) have been suggested to promote the formation of dioxin in incinerators, and sulphur (S) has been suggested to inhibit dioxin formation. We show that dioxin (PCDD and PCDF) emission factors from 17 different combustion categories are approximately linearly correlated with the average copper or chlorine content of the combusted material, and inverse linearly correlated with the average sulphur content of the material. Copper and chlorine are correlated and, thus cannot be distinguished. The analysis suggests that the wide range of dioxin emission factors could be explained by the content of sulphur and transition metals or chlorine in combusted materials.

Use of self-monitoring tools in a clinic sample of adults with type 2 diabetes.

Self-monitoring is an effective strategy for chronic disease management; many readily available mobile applications allow tracking of diabetes-related health behaviors but their use has not yet been integrated into routine clinical care. How patients engage with these applications in the real world is not well understood. The specific aim of this study is to survey adults with type 2 diabetes (T2D) regarding self-monitoring behaviors, including mobile application use. In 2015, we surveyed an adult diabetes clinic population (n = 96) regarding self-monitoring behaviors: diet, physical activity, weight, and blood glucose. Self-monitoring with any method ranged from 20-90 %. About half of the participants owned smartphones; few had mobile applications. The most common app-tracked behavior was physical activity, then weight and diet. Despite numerous available mobile health-tracking applications, few T2D adults from our sample used them, though many reported self-monitoring with other methods.