Monitoring, enforcement, and the choice of environmental policy instruments

How to choose among the dozen policy instruments available to environmental management agencies has been a matter of concern and debate among environmental economists for the entire life of the profession – nearly four decades. The ability, or lack of it, to measure the quantities or observe the actions made "enforceable" by particular policy instruments ought clearly to be central to this choice. However, all too often the monitoring problem has been assumed away. When it is reintroduced in realistic forms, we find, not surprisingly, that some favorite policy instruments, such as pollution charges, are not applicable to some important problems, such as runoff pollution from farms; that marginal subsidies, by changing the burden of proof, may no longer be symmetric with charges; and that the apparent freedom from monitoring requirements of the newly fashionable instrument involving the public provision of information about firms or products is "paid for" by our inability to say anything about its performance on other dimensions that are also of interest. Electronic Publication     

LAND SUBSIDENCE: AN ECONOMIC ANALYSIS1

ABSTRACT. Land subsidence due to groundwater overdraft has been assumed to be one of Arizona's major water related problems. This paper investigates the premise from an economic point of view and concludes that in the case of Arizona the physical fact of land subsidence has little or no economic significance.     

Organic contaminants in the Firth of Clyde following the cessation of sewage sludge dumping

To assess contaminant concentrations in the Firth of Clyde in relation to the former sewage sludge dump site at Garroch Head, and investigate any temporal changes, fish have been sampled annually since 1992 and sediment since 1999. In addition, a further four locations in the Clyde (Holy Loch, Hunterston, Skelmorlie and Irvine Bay) have been sampled for fish and sediment since 1999. Chlorobiphenyls (CBs) were measured in fish samples and polycyclic aromatic hydrocarbons (PAHs) and CBs in sediment. Since sampling was initiated the concentration for the summation operatorICES7 CBs in fish liver has been consistently >500 microg kg(-1) lipid weight at Garroch Head and the other Clyde sites and lower at the reference sites (Pladda, Colonsay, Broad Bay). Although the lowest CB concentrations of the eleven year period in plaice liver from Garroch Head were found in 2002, CB concentrations were found not to have decreased significantly since sewage sludge dumping ceased in 1998. However, a change in CB profile was observed with fish liver collected between 1992 and 1998 from Garroch Head showing a lower proportion of the less chlorinated CBs compared to the 1999-2002 liver samples. Highest CB and PAH concentrations in sediment were found at Garroch Head and Holy Loch with concentrations at these sites being significantly higher than at all other sites.     

Assessing the recovery of lakes in southeastern Canada from the effects of acidic deposition

Reductions in North American sulfur dioxide (SO2) emissions promoted expectations that aquatic ecosystems in southeastern Canada would soon recover from acidification. Only lakes located near smelters that have dramatically reduced emissions approach this expectation. Lakes in the Atlantic provinces, Quebec and Ontario affected only by long-range sources show a general decline in sulfate (SO4(2-)) concentrations, but with a relatively smaller compensating increase in pH or alkalinity. Several factors may contribute to the constrained (or most likely delayed) acidity response: declining base cation concentrations, drought-induced mobilization of SO4(2-), damaged internal alkalinity generation mechanisms, and perhaps increasing nitrate or organic anion levels. Monitoring to detect biological recovery in southeastern Canada is extremely limited, but where it occurs, there is little evidence of recovery outside of the Sudbury/Killarney area. Both the occurrence of Atlantic salmon in Nova Scotia rivers and the breeding success of Common Loons in Ontario lakes are in fact declining although factors beyond acidification also play a role. Chemical and biological models predict that much greater SO2 emission reductions than those presently required by legislation will be needed to promote widespread chemical and latterly, biological recovery. It may be unrealistic to expect that pre-industrial chemical and biological conditions can ever be reestablished in many lakes of southeastern Canada.     

Organic and Inorganic Characterization of Marine Colloids

Abstract

Isolates of the organic matter in the particulate, colloidal and dissolved states were obtained by tangential flow ultrafiltration through 0.40 μm polycarbonate and ～ 1 nm (1000 NMWL?) regenerated cellulose membranes and by solid-liquid reverse phase extraction techniques. the material was analyzed qualitatively by mass spectroscopy, proton nuclear magnetic resonance, Fourier transform infrared spectroscopy, high performance liquid chromatography with fluorescence detection of labelled primary amines and amino acids, and inductively coupled plasma/mass spectroscopy. All three states are characterized by similar organic chemistries. the marine colloidal state in coastal waters off the Californian coast contains primarily carbohydrates, fatty acids, minor amounts of proteinaceous compounds and electropositive elements including aluminium and iron. Aromatic molecules and olefinic functional groups are in low concentration. the colloidal state differs qualitatively from the particulate and dissolved states. Yet all three could be derived, with degradation, from algal or macroalgal surface components.     

Spatial PM2.5 mobile source impacts using a calibrated indicator method

Motor vehicles are major sources of fine particulate matter (PM_2.5), and the PM_2.5 from mobile vehicles is associated with adverse health effects. Traditional methods for estimating source impacts that employ receptor models are limited by the availability of observational data. To better estimate temporally and spatially resolved mobile source impacts on PM_2.5, we developed an approach based on a method that uses elemental carbon (EC), carbon monoxide (CO), and nitrogen oxide (NO_x) measurements as an indicator of mobile source impacts. We extended the original integrated mobile source indicator (IMSI) method in three aspects. First, we generated spatially resolved indicators using 24-hr average concentrations of EC, CO, and NO_x estimated at 4 km resolution by applying a method developed to fuse chemical transport model (Community Multiscale Air Quality Model [CMAQ]) simulations and observations. Second, we used spatially resolved emissions instead of county-level emissions in the IMSI formulation. Third, we spatially calibrated the unitless indicators to annually-averaged mobile source impacts estimated by the receptor model Chemical Mass Balance (CMB). Daily total mobile source impacts on PM_2.5, as well as separate gasoline and diesel vehicle impacts, were estimated at 12 km resolution from 2002 to 2008 and 4 km resolution from 2008 to 2010 for Georgia. The total mobile and separate vehicle source impacts compared well with daily CMB results, with high temporal correlation (e.g., R ranges from 0.59 to 0.88 for total mobile sources with 4 km resolution at nine locations). The total mobile source impacts had higher correlation and lower error than the separate gasoline and diesel sources when compared with observation-based CMB estimates. Overall, the enhanced approach provides spatially resolved mobile source impacts that are similar to observation-based estimates and can be used to improve assessment of health effects.

Implications: An approach is developed based on an integrated mobile source indicator method to estimate spatiotemporal PM_2.5 mobile source impacts. The approach employs three air pollutant concentration fields that are readily simulated at 4 and 12 km resolutions, and is calibrated using PM_2.5 source apportionment modeling results to generate daily mobile source impacts in the state of Georgia. The estimated source impacts can be used in investigations of traffic pollution and health.     

Reductive dehalogenation: A subsurface bioremediation process

Introduction and large-scale production of synthetic halogenated organic chemicals over the last fifty years has resulted in a group of contaminants that tend to persist in the environment and resist both biotic and abiotic degradation. The low solubility of these types of contaminants, along with their toxicity and tendency to accumulate in food chains, make them particularly relevant targets for remediation activities. Among the mechanisms that result in dehalogenation of some classes of organic contaminants are stimulation of metabolic sequences through introduction of electron donor and acceptor combinations; addition of nutrients to meet the needs of dehalogenating microorganisms; possible use of engineered microorganisms; and use of enzyme systems capable of catalyzing reductive dehalogenation. The current state of research and development in the area of reductive dehalogenation is discussed along with possible technological application of relevant processes and mechanisms to remediation of soil and groundwater contaminated with chlorinated organics. In addition, an overview of research needs is suggested, which might be of interest for development of in-situ systems to reduce the mass of halogenated organic contaminants in soil and groundwater.     

Integrated Assessment Modeling of Atmospheric Pollutants in the Southern Appalachian Mountains. Part I: Hourly and Seasonal Ozone

Abstract

Recently, a comprehensive air quality modeling system was developed as part of the Southern Appalachians Mountains Initiative (SAMI) with the ability to simulate meteorology, emissions, ozone, size- and composition-resolved particulate matter, and pollutant deposition fluxes. As part of SAMI, the RAMS/EMS-95/URM-1ATM modeling system was used to evaluate potential emission control strategies to reduce atmospheric pollutant levels at Class I areas located in the Southern Appalachians Mountains. This article discusses the details of the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. The daily mean normalized bias and error for 1-hr and 8-hr ozone were within U.S. Environment Protection Agency guidance criteria for urban-scale modeling. The model typically showed a systematic overestimation for low ozone levels and an underestimation for high levels. Because SAMI was primarily interested in simulating the growing season ozone levels in Class I areas, daily and seasonal cumulative ozone exposure, as characterized by the W126 index, were also evaluated. The daily ozone W126 performance was not as good as the hourly ozone performance; however, the seasonal ozone W126 scaled up from daily values was within 17% of the observations at two typical Class I areas of the SAMI region. The overall ozone performance of the model was deemed acceptable for the purposes of SAMI’s assessment.     

Emission Strength Validation Using Four-Dimensional Data Assimilation: Application to Primary Aerosol and Precursors to Ozone and Secondary Aerosol

ABSTRACT

Three-dimensional air quality models (AQMs) represent the most powerful tool to follow the dynamics of air pollutants at urban and regional scales. Current AQMs can account for the complex interactions between gas-phase chemistry, aerosol growth, cloud and scavenging processes, and transport. However, errors in model applications still exist due in part to limitations in the models themselves and in part to uncertainties in model inputs. Four-dimensional data assimilation (FDDA) can be used as a top-down tool to validate several of the model inputs, including emissions inventories, based on ambient measurements. Previously, this FDDA technique was used to estimate adjustments in the strength and composition of emissions of gas-phase primary species and O₃ precursors.

In this paper, we present an extension to the FDDA technique to incorporate the analysis of particulate matter (PM) and its precursors. The FDDA approach consists of an iterative optimization procedure in which an AQM is coupled to an inverse model, and adjusting the emissions minimizes the difference between ambient measurements