Ten ways remote sensing can contribute to conservation

In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners’ use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain‐referral survey. We then used a workshop‐based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real‐time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing‐derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to monitor and evaluate the effectiveness of conservation efforts? How does the expansion and intensification of agriculture and aquaculture alter ecosystems and the services they provide? How can remote sensing be used to determine the degree to which ecosystems are being disturbed or degraded and the effects of these changes on species and ecosystem functions?     

Processing and Morphology Impacts on Mechanical Properties of Fungal Based Biopolymer Composites

Fungal based biopolymer matrix composites with lignocellulosic agricultural waste as the filler are a viable alternative for some applications of synthetic polymers. This research provides insight into the impact of the processing method and composition of agriwaste/fungal biopolymer composites on structure and mechanical properties. The impact of nutrition during inoculation and after a homogenization step on the three-point bend flexural modulus and strength was determined. Increasing supplemental nutrition at inoculation had little effect on the overall composite strength or modulus; however, increasing carbohydrate loading after a homogenization step increased flexural stress at yield and bulk flexural modulus. The contiguity of the network formed was notably higher in the latter scenario, suggesting that the increase in modulus and strength of the final composite after homogenization was the result of contiguous hyphal network formation, which improves the integrity of the matrix and the ability to transfer load to the filler particles.     

Critical review of the building downwash algorithms in AERMOD

The only documentation on the building downwash algorithm in AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model), referred to as PRIME (Plume Rise Model Enhancements), is found in the 2000 A&WMA journal article by Schulman, Strimaitis and Scire. Recent field and wind tunnel studies have shown that AERMOD can overpredict concentrations by factors of 2 to 8 for certain building configurations. While a wind tunnel equivalent building dimension study (EBD) can be conducted to approximately correct the overprediction bias, past field and wind tunnel studies indicate that there are notable flaws in the PRIME building downwash theory. A detailed review of the theory supported by CFD (Computational Fluid Dynamics) and wind tunnel simulations of flow over simple rectangular buildings revealed the following serious theoretical flaws: enhanced turbulence in the building wake starting at the wrong longitudinal location; constant enhanced turbulence extending up to the wake height; constant initial enhanced turbulence in the building wake (does not vary with roughness or stability); discontinuities in the streamline calculations; and no method to account for streamlined or porous structures.

Implications: This paper documents theoretical and other problems in PRIME along with CFD simulations and wind tunnel observations that support these findings. Although AERMOD/PRIME may provide accurate and unbiased estimates (within a factor of 2) for some building configurations, a major review and update is needed so that accurate estimates can be obtained for other building configurations where significant overpredictions or underpredictions are common due to downwash effects. This will ensure that regulatory evaluations subject to dispersion modeling requirements can be based on an accurate model. Thus, it is imperative that the downwash theory in PRIME is corrected to improve model performance and ensure that the model better represents reality.     

Evaluation of airborne particulate matter and metals data in personal,indoor and outdoor environments using ED-XRF and ICP-MS and co-located duplicate samples

Factors and sources affecting measurement uncertainty associated with monitoring metals in airborne particulate matter (PM) were investigated as part of the Windsor, Ontario Exposure Assessment Study (WOEAS). The assessment was made using co-located duplicate samples and a comparison of two analytical approaches: ED-XRF and ICP-MS. Sampling variability was estimated using relative percent difference (RPD) of co-located duplicate samples. The comparison of ICP-MS and ED-XRF results yields very good correlations (R² ≥ 0.7) for elements present at concentrations that pass both ICP-MS and ED-XRF detection limits (e.g. Fe, Mn, Zn, Pb and Cu). PM concentration ranges (median, sample number) of 24-h indoor PM₁₀ and personal PM₁₀ filters, and outdoor PM_2.5 filters were determined to be 2.2–40.7 (11.0, n = 48) μg m^?3, 8.0–48.3 (11.9, n = 48) μg m^?3, and 17.1–42.3 (21.6, n = 18) μg m^?3, respectively. The gravimetric analytical results reveal that the variations in PM mass measurements for same-day sampling are insignificant compared to temporal or spatial variations: 92%, 100% and 96% of indoor, outdoor and personal duplicate samples, respectively, pass the quality criteria (RPD ≤ 20%). Uncertainties associated with ED-XRF elemental measurements of S, Ca, Mn, Fe and Zn for 24-h filter samples are low: 78%–100% of the duplicate samples passed the quality criteria. In the case of 24-h filter samples using ICP-MS, more elements passed the quality criteria due to the lower detection limits. These were: Li, Na, K, Ca, Si, Al, V, Fe, Mn, Co, Cu, Mo, Ag, Zn, Pb, As, Mg, Sb, Sn, Sr, Th, Ti, Tl, and U. Low air concentrations of metals (near or below instrumental detection limits) and/or inadvertent introduction of metal contamination are the main causes for excluding elements based on the pass/fail criteria. Uncertainty associated with elemental measurements must be assessed on an element-by-element basis.