The Impact of a Building Implosion on Airborne Particulate Matter in an Urban Community

Abstract

In response to community concerns, the air quality impact of imploding a 22-story building in east Baltimore, MD, was studied. Time- and space-resolved concentrations of indoor and outdoor particulate matter (PM) (nominally 0.5–10 µm) were measured using a portable nephelometer at seven and four locations, respectively. PM₁₀ levels varied in time and space; there was no measurable effect observed upwind of the implosion. The downwind peak PM₁₀ levels varied with distance (54,000–589 µg/m³) exceeding pre-implosion levels for sites 100 and 1130 m 3000- and 20-fold, respectively. Estimated outdoor 24-hr integrated mass concentrations varied from 15 to 72 µg/m³. The implosion did not result in the U.S. Environmental Protection Agency (EPA) National Ambient Air Quality Standard (NAAQS) for PM₁₀ being exceeded. X-ray fluorescence analysis indicated that the elemental composition was dominated by crustal elements: calcium (57%), silicon (23%), aluminum (7.6%), and iron (6.1%). Lead was above background but at a low level (0.17 µg/m³). Peak PM₁₀ concentrations were short-lived; most sites returned to background within 15 min. No increase in indoor PM₁₀ was observed even at the most proximate 250 m location. These results demonstrate that a building implosion can have a severe but short-lived impact on community air quality. Effective protection is offered by being indoors or upwind.     

Effects of improved spatial and temporal modeling of on-road vehicle emissions

Numerous emission and air quality modeling studies have suggested the need to accurately characterize the spatial and temporal variations in on-road vehicle emissions. The purpose of this study was to quantify the impact that using detailed traffic activity data has on emission estimates used to model air quality impacts. The on-road vehicle emissions are estimated by multiplying the vehicle miles traveled (VMT) by the fleet-average emission factors determined by road link and hour of day. Changes in the fraction of VMT from heavy-duty diesel vehicles (HDDVs) can have a significant impact on estimated fleet-average emissions because the emission factors for HDDV nitrogen oxides (NOx) and particulate matter (PM) are much higher than those for light-duty gas vehicles (LDGVs). Through detailed road link-level on-road vehicle emission modeling, this work investigated two scenarios for better characterizing mobile source emissions: (1) improved spatial and temporal variation of vehicle type fractions, and (2) use of Motor Vehicle Emission Simulator (MOVES2010) instead of MOBILE6 exhaust emission factors. Emissions were estimated for the Detroit and Atlanta metropolitan areas for summer and winter episodes. The VMT mix scenario demonstrated the importance of better characterizing HDDV activity by time of day, day of week, and road type. More HDDV activity occurs on restricted access road types on weekdays and at nonpeak times, compared to light-duty vehicles, resulting in 5-15% higher NOx and PM emission rates during the weekdays and 15-40% lower rates on weekend days. Use of MOVES2010 exhaust emission factors resulted in increases of more than 50% in NOx and PM for both HDDVs and LDGVs, relative to MOBILE6. Because LDGV PM emissions have been shown to increase with lower temperatures, the most dramatic increase from MOBILE6 to MOVES2010 emission rates occurred for PM2.5 from LDGVs that increased 500% during colder wintertime conditions found in Detroit, the northernmost city modeled.     

Guiding principles for rewilding

There has been much recent interest in the concept of rewilding as a tool for nature conservation, but also confusion over the idea, which has limited its utility. We developed a unifying definition and 10 guiding principles for rewilding through a survey of 59 rewilding experts, a summary of key organizations’ rewilding visions, and workshops involving over 100 participants from around the world. The guiding principles convey that rewilding exits on a continuum of scale, connectivity, and level of human influence and aims to restore ecosystem structure and functions to achieve a self-sustaining autonomous nature. These principles clarify the concept of rewilding and improve its effectiveness as a tool to achieve global conservation targets, including those of the UN Decade on Ecosystem Restoration and post-2020 Global Biodiversity Framework. Finally, we suggest differences in rewilding perspectives lie largely in the extent to which it is seen as achievable and in specific interventions. An understanding of the context of rewilding projects is the key to success, and careful site-specific interpretations will help achieve the aims of rewilding.     

Moving from trends to benchmarks by using regression tree analysis to find inbreeding thresholds in a critically endangered bird

Understanding how inbreeding affects endangered species in conservation breeding programs is essential for their recovery. The Hawaiian Crow (‘Alalā) (Corvus hawaiiensis) is one of the world's most endangered birds. It went extinct in the wild in 2002, and, until recent release efforts starting in 2016, nearly all of the population remained under human care for conservation breeding. Using pedigree inbreeding coefficients (F), we evaluated the effects of inbreeding on Hawaiian Crow offspring survival and reproductive success. We used regression tree analysis to identify the level of inbreeding (i.e., inbreeding threshold) that explains a substantial decrease in ‘Alalā offspring survival to recruitment. Similar to a previous study of inbreeding in ‘Alalā, we found that inbreeding had a negative impact on offspring survival but that parental (vs. artificial) egg incubation improved offspring survival to recruitment. Furthermore, we found that inbreeding did not substantially affect offspring reproductive success, based on the assumption that offspring that survive to adulthood breed with distantly related mates. Our novel application of regression tree analysis showed that offspring with inbreeding levels exceeding F = 0.098 were 69% less likely to survive to recruitment than more outbred offspring, providing a specific threshold value for ongoing population management. Our results emphasize the importance of assessing inbreeding depression across all life history stages, confirm the importance of prioritizing parental over artificial egg incubation in avian conservation breeding programs, and demonstrate the utility of regression tree analysis as a tool for identifying inbreeding thresholds, if present, in any pedigree-managed population.     

The effects of parametric uncertainties in simulations of a reactive plume using a Lagrangian stochastic model

A combined Lagrangian stochastic model with micro-mixing and chemical sub-models is used to investigate a reactive plume of nitrogen oxides (NO_x) released into a turbulent grid flow doped with ozone (O₃). Sensitivities to the model input parameters are explored for different source NO_x scenarios. The wind tunnel experiments of Brown and Bilger (1996) provide the simulation conditions for the first case study where photolysis reactions are not included and the main uncertainties occur in parameters defining the turbulence scales, source size and reaction rate of NO with O₃. Using nominal values of the parameters from previous studies, the model gives a good representation of the radial profile of the conserved mean scalar ${\overline{\Gamma }}_{{\text{NO}}_{\text{x}}}$ although slightly over predicts peak mean NO₂ concentrations ${\overline{\Gamma }}_{{\text{NO}}_{\text{2}}}$ compared to the experiments. The high dimensional model representation (HDMR) method is used to investigate the effects of uncertainties in model inputs on the simulation of chemical species concentrations. For this scenario, the Lagrangian velocity structure function coefficient has the largest impact on simulated ${\overline{\Gamma }}_{{\text{NO}}_{\text{x}}}$ profiles. Photolysis reactions are then included in a chemical scheme consisting of eight reactions between species NO, O, O₃ and NO₂. Independent and interactive effects of 22 input parameters are studied for two source NO_x scenarios using HDMR, including turbulence parameters, temperature dependant rate parameters, photolysis rates, temperature, fraction of NO in total NO_x at the source and background ozone concentration [O₃]. For this reactive case, the variance in the predicted mean plume centre ${\overline{\Gamma }}_{{\text{O}}_{\text{3}}}$ is caused by parameters describing both physical (mixing time-scale coefficient) and chemical processes (activation energy for the reaction O₃+NO). The variance in predicted plume centre ${\overline{\Gamma }}_{{\text{NO}}_{\text{2}}}$ and root mean square NO₂ concentration ${\gamma }_{{\text{NO}}_{\text{2}}}^{\prime }$, is strongly influenced by the fraction of NO in the source NO_x, and to a lesser extent the mixing time-scale coefficient. Adjusting the latter gives improved agreement with the Brown and Bilger experiment. Some weak parameter interactions are observed.     

Cancer risk assessment of selected hazardous air pollutants in Seattle

The risk estimates calculated from the conventional risk assessment method usually are compound specific and provide limited information for source-specific air quality control. We used a risk apportionment approach, which is a combination of receptor modeling and risk assessment, to estimate source-specific lifetime excess cancer risks of selected hazardous air pollutants. We analyzed the speciated PM(2.5) and VOCs data collected at the Beacon Hill in Seattle, WA between 2000 and 2004 with the Multilinear Engine to first quantify source contributions to the mixture of hazardous air pollutants (HAPs) in terms of mass concentrations. The cancer risk from exposure to each source was then calculated as the sum of all available species' cancer risks in the source feature. We also adopted the bootstrapping technique for the uncertainty analysis. The results showed that the overall cancer risk was 6.09 x 10(-5), with the background (1.61 x 10(-5)), diesel (9.82 x 10(-6)) and wood burning (9.45 x 10(-6)) sources being the primary risk sources. The PM(2.5) mass concentration contributed 20% of the total risk. The 5th percentile of the risk estimates of all sources other than marine and soil were higher than 110(-6). It was also found that the diesel and wood burning sources presented similar cancer risks although the diesel exhaust contributed less to the PM(2.5) mass concentration than the wood burning. This highlights the additional value from such a risk apportionment approach that could be utilized for prioritizing control strategies to reduce the highest population health risks from exposure to HAPs.     

Taking a ‘Big Data’ approach to data quality in a citizen science project

Data from well-designed experiments provide the strongest evidence of causation in biodiversity studies. However, for many species the collection of these data is not scalable to the spatial and temporal extents required to understand patterns at the population level. Only data collected from citizen science projects can gather sufficient quantities of data, but data collected from volunteers are inherently noisy and heterogeneous. Here we describe a ‘Big Data’ approach to improve the data quality in eBird, a global citizen science project that gathers bird observations. First, eBird’s data submission design ensures that all data meet high standards of completeness and accuracy. Second, we take a ‘sensor calibration’ approach to measure individual variation in eBird participant’s ability to detect and identify birds. Third, we use species distribution models to fill in data gaps. Finally, we provide examples of novel analyses exploring population-level patterns in bird distributions.     

Visions for the North Sea: The Societal Dilemma Behind Specifying Good Environmental Status

We augment discussions about the Good Environmental Status of the North Sea by developing two extreme visions and assessing their societal benefits. One vision (‘Then’) assumes restoration of benthic functioning; we contend that trawling had already degraded the southern North Sea a century ago. Available information is used to speculate about benthic functioning in a relatively undisturbed southern North Sea. The second vision (‘Now’) draws on recent benthic functioning. The supply of five ecosystem services, supported by benthic functioning, is discussed. ‘Then’ offers confidence in the sustainable supply of diverse services but restoration of past function is uncertain and likely to be paired with costs, notably trawling restraints. ‘Now’ delivers known and valued services but sustained delivery is threatened by, for example, climate change. We do not advocate either vision. Our purpose is to stimulate debate about what society wants, and might receive, from the future southern North Sea.

Electronic supplementary material

The online version of this article (doi:10.1007/s13280-014-0536-5) contains supplementary material, which is available to authorized users.     

Toward enhanced subsurface intervention methods using chaotic advection

Many intervention activities in the terrestrial subsurface involve the need to recover/emplace distributions of scalar quantities (e.g. dissolved phase concentrations or heat) from/in volumes of saturated porous media. These scalars can be targeted by pump-and-treat methods or by amendment technologies. Application examples include in-situ leaching for metals, recovery of dissolved contaminant plumes, or utilizing heat energy in geothermal reservoirs. While conventional pumping methods work reasonably well, costs associated with maintaining pumping schedules are high and improvements in efficiency would be welcome. In this paper we discuss how transient switching of the pressure at different wells can intimately control subsurface flow, generating a range of "programmed" flows with various beneficial characteristics. Some programs produce chaotic flows which accelerate mixing, while others create encapsulating flows which can isolate fluid zones for lengthy periods. In a simplified model of an aquifer subject to balanced pumping, chaotic flow topologies have been predicted theoretically and verified experimentally using Hele-Shaw cells. Here, a survey of the key characteristics of chaotic advection is presented. Mathematical methods are used to show how these characteristics may translate into practical situations involving regional flows and heterogeneity. The results are robust to perturbations, and withstand significant aquifer heterogeneity. It is proposed that chaotic advection may form the basis of new efficient technologies for groundwater interventions.     

Identifying crop vulnerability to groundwater abstraction: modelling and expert knowledge in a GIS

Water use is expected to increase and climate change scenarios indicate the need for more frequent water abstraction. Abstracting groundwater may have a detrimental effect on soil moisture availability for crop growth and yields. This work presents an elegant and robust method for identifying zones of crop vulnerability to abstraction. Archive groundwater level datasets were used to generate a composite groundwater surface that was subtracted from a digital terrain model. The result was the depth from surface to groundwater and identified areas underlain by shallow groundwater. Knowledge from an expert agronomist was used to define classes of risk in terms of their depth below ground level. Combining information on the permeability of geological drift types further refined the assessment of the risk of crop growth vulnerability. The nature of the mapped output is one that is easy to communicate to the intended farming audience because of the general familiarity of mapped information. Such Geographic Information System (GIS)-based products can play a significant role in the characterisation of catchments under the EU Water Framework Directive especially in the process of public liaison that is fundamental to the setting of priorities for management change. The creation of a baseline allows the impact of future increased water abstraction rates to be modelled and the vulnerability maps are in a format that can be readily understood by the various stakeholders. This methodology can readily be extended to encompass additional data layers and for a range of groundwater vulnerability issues including water resources, ecological impacts, nitrate and phosphorus.