Forecasting Air Pollution Potential: A Synoptic Climatological Approach

ABSTRACT

This paper describes the development and application of an air pollution potential (APP) forecast model based on a synoptic climatological approach in a heavily industrialized area in Durban, South Africa. The aim of the forecasting procedure, based on a system of orange, red, and all-clear alerts, was to give industry advance warning of periods of poor atmospheric dispersion so that it could take action to reduce emissions. The key meteorological parameter in accurately identifying the commencement of an APP episode was found to be negative surface pressure tendency. Wind direction was the most useful parameter in estimating the end point of an APP episode. The model was very successful in identifying periods of elevated SO₂, but there is a need for further refinement in forecasting the end point of an episode.     

An Environmental Decision-Making Tool for Evaluating Ground-Level Ozone-Related Health Effects

Abstract

A computer model called the Ozone Risk Assessment Model (ORAM) was developed to evaluate the health effects caused by ground-level ozone (O₃) exposure. ORAM was coupled with the U.S. Environmental Protection Agency’s (EPA) Third-Generation Community Multiscale Air Quality model (Models-3/CMAQ), the state-of-the-art air quality model that predicts O₃ concentration and allows the examination of various scenarios in which emission rates of O₃ precursors (basically, oxides of nitrogen [NO_x] and volatile organic compounds) are varied. The principal analyses in ORAM are exposure model performance evaluation, health-effects calculations (expected number of respiratory hospital admissions), economic valuation, and sensitivity and uncertainty analysis through a Monte Carlo simulation. As a demonstration of the system, ORAM was applied to the eastern Tennessee region, and the entire O₃ season was simulated for a base case (typical emissions) and three different emission scenarios. The results indicated that a synergism occurs when reductions in NO_x emissions from mobile and point sources were applied simultaneously. A 12.9% reduction in asthma hospital admissions is expected when both mobile and point source NO_x emissions are reduced (50 and 70%, respectively) versus a 5.8% reduction caused by mobile source and a 3.5% reduction caused by point sources when these emission sources are reduced individually.     

Particulate Emissions from Construction Activities

Abstract

Although it has long been recognized that road and building construction activity constitutes an important source of particulate matter (PM) emissions throughout the United States, until recently only limited research has been directed to its characterization. This paper presents the results of PM₁₀ and PM_2.5 (particles ≤10 μm and ≤2.5 μm in aerodynamic diameter, respectively) emission factor development from the onsite testing of component operations at actual construction sites during the period 1998 –2001. Much of the testing effort was directed at earthmoving operations with scrapers, because earthmoving is the most important contributor of PM emissions across the construction industry. Other sources tested were truck loading and dumping of crushed rock and mud and dirt carryout from construction site access points onto adjacent public paved roads. Also tested were the effects of watering for control of scraper travel routes and the use of paved and graveled aprons at construction site access points for reducing mud and dirt carryout. The PM₁₀ emissions from earthmoving were found to be up to an order of magnitude greater than predicted by AP-42 emission factors drawn from other industries. As expected, the observed PM_2.5:PM₁₀ emission factor ratios reflected the relative importance of the vehicle exhaust and the resuspended dust components of each type of construction activity. An unexpected finding was that PM_2.5 emissions from mud and dirt carryout were much less than anticipated. Finally, the control efficiency of watering of scraper travel routes was found to closely follow a bilinear moisture model.     

Parts-per-trillion LC-MS(Q) analysis of herbicides and transformation products in surface water

The goal of this study was to develop a robust method of analyzing surface water samples for S-triazine herbicides, chloroacetanilide herbicides, and their transformation products (TPs) using solid-phase extraction (SPE) followed by liquid chromatograph-mass spectrometry (LC-MS) with electrospray ionization (ESI) by in-source collision-induced dissociation (ISCID) capability of an orthogonal electrospray ionization probe on a single quadrupole LC-MS system. The method developed here met the goals of the study and yielded estimated method detection limits (EMDLs) averaging 0.3 ± 0.1 ng L(-1) for S-triazines and their TPs and 0.7 ± 0.4 ng L(-1) for chloroacetanilides and TPs. Spiked filtered river water yielded SPE recoveries ranging from 94.2 % ± 4.8 % for S-triazines and TPs after eliminating three compounds with less that 65 % recovery from analysis and 95.9 % ± 19 % for chloroacetanilides and their TPs. The method was field-tested with filtered water samples collected from four sites over a four-month period. Detectible values of S-triazines and TPs ranged from 0.3 to 1540 ng L(-1) with a mean of 79.3 and a median of 19.4 ng L(-1). Detectible values for chloroacetanilides and TPs ranged from 0.31 to 3780 ng L(-1) with a mean of 252 and a median of 25.6 ng L(-1). An additional goal was to determine if the method was useful for microbial degradation studies using native bacterial communities. The bacteria transformed atrazine (2-chloro-4-ethylamino-6-isopropylamino-S-triazine) solely into 2-hydroxy atrazine (2-hydroxy-4-ethylamino-6-isopropylamino-S-triazine) with concentrations of 78.4, 63.3 and 32.5 ng L(-1) after 12 days of incubation compared with 6.3 and 7.1 ng L(-1) for control dark and control sunlight respectively.     

Modeling transit bus fuel consumption on the basis of cycle properties

A method exists to predict heavy-duty vehicle fuel economy and emissions over an "unseen" cycle or during unseen on-road activity on the basis of fuel consumption and emissions data from measured chassis dynamometer test cycles and properties (statistical parameters) of those cycles. No regression is required for the method, which relies solely on the linear association of vehicle performance with cycle properties. This method has been advanced and examined using previously published heavy-duty truck data gathered using the West Virginia University heavy-duty chassis dynamometer with the trucks exercised over limited test cycles. In this study, data were available from a Washington Metropolitan Area Transit Authority emission testing program conducted in 2006. Chassis dynamometer data from two conventional diesel buses, two compressed natural gas buses, and one hybrid diesel bus were evaluated using an expanded driving cycle set of 16 or 17 different driving cycles. Cycle properties and vehicle fuel consumption measurements from three baseline cycles were selected to generate a linear model and then to predict unseen fuel consumption over the remaining 13 or 14 cycles. Average velocity, average positive acceleration, and number of stops per distance were found to be the desired cycle properties for use in the model. The methodology allowed for the prediction of fuel consumption with an average error of 8.5% from vehicles operating on a diverse set of chassis dynamometer cycles on the basis of relatively few experimental measurements. It was found that the data used for prediction should be acquired from a set that must include an idle cycle along with a relatively slow transient cycle and a relatively high speed cycle. The method was also applied to oxides of nitrogen prediction and was found to have less predictive capability than for fuel consumption with an average error of 20.4%.     

Drought,water access,and urban agriculture: a case study from Silicon Valley

In California, the growing popularity of urban agriculture (UA) has unfolded against a backdrop of historic drought. While UA is often celebrated as an urban sustainability strategy, it must be able to persist during drought if it is to perform these functions. Using Santa Clara County – the geographic core of Silicon Valley – as a case study, we use interviews and surveys to explore the implications of drought for UA. We show how developing an understanding of water access for UA during a drought requires examining the social and institutional context of water management and use. In metropolitan California, the highly decentralised water supply system combined with the diverse institutional arrangements that support UA create an uneven landscape of water access. Consequently, the pressure to change water-consuming practices – that is, the stress that institutional drought responses place on different water users – is geographically and socially differentiated. Among UA water users, responses to drought have also varied, in part because the possibilities for change are constrained by the sociotechnical arrangements of UA sites and the different purposes of UA.     

Designing and Implementing a Network for Sensing Water Quality and Hydrology across Mountain to Urban Transitions

Water resources are increasingly impacted by growing human populations, land use, and climate changes, and complex interactions among biophysical processes. In an effort to better understand these factors in semiarid northern Utah, United States, we created a real‐time observatory consisting of sensors deployed at aquatic and terrestrial stations to monitor water quality, water inputs, and outputs along mountain to urban gradients. The Gradients Along Mountain to Urban Transitions (GAMUT) monitoring network spans three watersheds with similar climates and streams fed by mountain winter‐derived precipitation, but that differ in urbanization level, land use, and biophysical characteristics. The aquatic monitoring stations in the GAMUT network include sensors to measure chemical (dissolved oxygen, specific conductance, pH, nitrate, and dissolved organic matter), physical (stage, temperature, and turbidity), and biological components (chlorophyll‐a and phycocyanin). We present the logistics of designing, implementing, and maintaining the network; quality assurance and control of numerous, large datasets; and data acquisition, dissemination, and visualization. Data from GAMUT reveal spatial differences in water quality due to urbanization and built infrastructure; capture rapid temporal changes in water quality due to anthropogenic activity; and identify changes in biological structure, each of which are demonstrated via case study datasets.     

Think globally,act locally: neighbourhood pollution and the future of the earth

Each year governments and industry around the globe spend billions of dollars in search of treatments and cures for diseases that shorten lives, which often means gadgets, implants, radiation and pills. These “cures”, do not get to the root of the problem. Perhaps it is time for us to adjust our thinking to be more proactive instead of reactive in public health. Perhaps we need to consider confronting environmental pollution of air, soil and water at a local level. As the Physicians for Social Responsibility point out, we should be “preventing what we cannot cure”. One such preventive measure is ensuring that our communities, including our poor inner-city neighbourhoods, enjoy a clean environment. We challenge local and national policy-makers to respond to the global call and to take action to address environmental toxins; to take local action to ameliorate the pollution of the air, water and soil in so many of our nation’s neighbourhoods. A person’s neighbourhood, and the proximity of dangerous environmental contaminants within it, is a powerful predictor of how long s/he will live. While situations like the poisoning of the water in Flint, Michigan have gotten some attention, they are generally treated as the exception rather than a reflection of real environmental hazards that exist in the west. Moreover we wonder why more endemic issues of neighbourhood environmental contamination that shorten human lives are not a priority for local action or that it is not linked to disproportionate production of greenhouse gases that cause climate change/warming/chaos.     

Population dynamics and the economics of invasive species management: the greenhouse whitefly in California-grown strawberries

In agriculture, relatively few efficacious control measures may be available for an invasive pest. In the case of a new insect pest, insecticide use decisions are affected by regulations associated with its registration, insect population dynamics, and seasonal market price cycles. We assess the costs and benefits of environmental regulations designed to regulate insecticide applications on an invasive species. We construct a bioeconomic model, based on detailed scientific data, of management decisions for a specific invasion: greenhouse whiteflies in California-grown strawberries. The empirical model integrates whitefly population dynamics, the effect of whitefly feeding on strawberry yields, and weekly strawberry price. We use the model to assess the optimality of alternative treatment programs on a simulated greenhouse whitefly population. Our results show that regulations may lead growers to "under-spray" when placed in an economic context, and provide some general lessons about the design of optimal invasive species control policies.     

Balancing Conservation and Economic Sustainability: The Future of the Amazon Timber Industry

Logging has been a much maligned feature of frontier development in the Amazon. Most discussions ignore the fact that logging can be part of a renewable, environmentally benign, and broadly equitable economic activity in these remote places. We estimate there to be some 4.5 ± 1.35 billion m³ of commercial timber volume in the Brazilian Amazon today, of which 1.2 billion m³ is currently profitable to harvest, with a total potential stumpage value of $15.4 billion. A successful forest sector in the Brazilian Amazon will integrate timber harvesting on private lands and on unprotected and unsettled government lands with timber concessions on public lands. If a legal, productive, timber industry can be established outside of protected areas, it will deliver environmental benefits in synergy with those provided by the region’s network of protected areas, the latter of which we estimate to have an opportunity cost from lost timber revenues of $2.3 billion over 30 years. Indeed, on all land accessible to harvesting, the timber industry could produce an average of more than 16 million m³ per year over a 30-year harvest cycle—entirely outside of current protected areas—providing $4.8 billion in returns to landowners and generating $1.8 billion in sawnwood sales tax revenue. This level of harvest could be profitably complemented with an additional 10% from logging concessions on National Forests. This advance, however, should be realized only through widespread adoption of reduced impact logging techniques.