Land changes and their driving forces in the Southeastern United States

The ecoregions of the Middle Atlantic Coastal Plain, Southeastern Plains, Piedmont, and Blue Ridge provide a continuum of land cover from the Atlantic Ocean to the highest mountains in the East. From 1973 to 2000, each ecoregion had a unique mosaic of land covers and land cover changes. The forests of the Blue Ridge Mountains provided amenity lands. The Piedmont forested area declined, while the developed area increased. The Southeastern Plains became a commercial forest region, and most agricultural lands that changed became forested. Forests in the Middle Atlantic Coastal Plain declined, and development related to recreation and retirement increased. The most important drivers of land conversion were associated with commercial forestry, competition between forest and agriculture, and economic and population growth. These and other drivers were modified by each ecoregion’s unique suitability and land use legacies with the result that the same drivers often produced different land changes in different ecoregions.     

Resolving local-scale emissions for modeling air quality near roadways

A large body of literature published in recent years suggests increased health risk due to exposure of people to air pollution in close proximity to roadways. As a result, there is a need to more accurately represent the spatial concentration gradients near roadways to develop mitigation strategies. In this paper, we present a practical, readily adaptable methodology, using a "bottom-up" approach to develop a detailed highway vehicle emission inventory that includes emissions for individual road links. This methodology also takes advantage of geographic information system (GIS) software to improve the spatial accuracy of the activity information obtained from a Travel Demand Model. In addition, we present an air quality modeling application of this methodology in New Haven, CT. This application uses a hybrid modeling approach, in which a regional grid-based model is used to characterize average local ambient concentrations, and a Gaussian dispersion model is used to provide texture within the modeling domain because of spatial gradients associated with highway vehicle emissions and other local sources. Modeling results show substantial heterogeneity of pollutant concentrations within the modeling domain and strong spatial gradients associated with roadways, particularly for pollutants dominated by direct emissions.     

Impact of three interactive Texas state regulatory programs to decrease ambient air toxic levels

The Federal Clean Air Act (FCAA) framework envisions a federal-state partnership whereby the development of regulations may be at the federal level or state level with federal oversight. The U.S. Environmental Protection Agency (EPA) establishes National Ambient Air Quality Standards to describe “safe” ambient levels of criteria pollutants. For air toxics, the EPA establishes control technology standards for the 187 listed hazardous air pollutants (HAPs) but does not establish ambient standards for HAPs or other air toxics. Thus, states must ensure that ambient concentrations are not at harmful levels. The Texas Clean Air Act authorizes the Texas Commission on Environmental Quality (TCEQ), the Texas state environmental agency, to control air pollution and protect public health and welfare. The TCEQ employs three interactive programs to ensure that concentrations of air toxics do not exceed levels of potential health concern (LOCs): air permitting, ambient air monitoring, and the Air Pollutant Watch List (APWL). Comprehensive air permit reviews involve the application of best available control technology for new and modified equipment and ensure that permits protect public health and welfare. Protectiveness may be demonstrated by a number of means, including a demonstration that the predicted ground-level concentrations for the permitted emissions, evaluated on a case-by-case and chemical-by-chemical basis, do not cause or contribute to a LOC. The TCEQ's ambient air monitoring program is extensive and provides data to help assess the potential for adverse effects from all operational equipment in an area. If air toxics are persistently monitored at a LOC, an APWL area is established. The purpose of the APWL is to reduce ambient air toxic concentrations below LOCs by focusing TCEQ resources and heightening awareness. This paper will discuss examples of decreases in air toxic levels in Houston and Corpus Christi, Texas, resulting from the interactive nature of these programs.

Implications: Texas recognized through the collection of ambient monitoring data that additional measures beyond federal regulations must be taken to ensure that public health is protected. Texas integrates comprehensive air permitting, extensive ambient air monitoring, and the Air Pollutant Watch List (APWL) to protect the public from hazardous air toxics. Texas issues air permits that are protective of public health and also assesses ambient air to verify that concentrations remain below levels of concern in heavily industrialized areas. Texas developed the APWL to improve air quality in those areas where monitoring indicates a potential concern. This paper illustrates how Texas engaged its three interactive programs to successfully address elevated air toxic levels in Houston and Corpus Christi.     

Timekeeping in the honey bee colony: integration of circadian rhythms and division of labor

The daily patterns of task performance in honey bee colonies during behavioral development were studied to determine the role of circadian rhythmicity in age-related division of labor. Although it is well known that foragers exhibit robust circadian patterns of activity in both field and laboratory settings, we report that many in-hive tasks are not allocated according to a daily rhythm but rather are performed 24 h per day. Around-the-clock activity at the colony level is accomplished through the performance of some tasks by individual workers randomly with respect to time of day. Bees are initially arrhythmic with respect to task performance but develop diel rhythmicity, by increasing the occurrence of inactivity at night, prior to becoming foragers. There are genotypic differences for age at onset of rhythmicity and our results suggest that these differences are correlated with genotypic variation in rate of behavioral development: genotypes of bees that progressed through the age polyethism schedule faster also acquired behavioral rhythmicity at an earlier age. The ontogeny of circadian rhythmicity in honey bee workers ensures that essential in-hive behaviors are performed around the clock but also allows the circadian clock to be engaged before the onset of foraging. Received: 6 October 1997 / Accepted after revision: 28 March 1998     

The interplay between incremental,transitional, and transformational adaptation: a case study of Canadian agriculture

Regional Environmental Change - We develop and apply a synthetic framework for understanding potential adaptations to climate change in the Canadian agriculture sector through a case study of...     

Effect of climate change on air quality

Air quality is strongly dependent on weather and is therefore sensitive to climate change. Recent studies have provided estimates of this climate effect through correlations of air quality with meteorological variables, perturbation analyses in chemical transport models (CTMs), and CTM simulations driven by general circulation model (GCM) simulations of 21st-century climate change. We review these different approaches and their results. The future climate is expected to be more stagnant, due to a weaker global circulation and a decreasing frequency of mid-latitude cyclones. The observed correlation between surface ozone and temperature in polluted regions points to a detrimental effect of warming. Coupled GCM–CTM studies find that climate change alone will increase summertime surface ozone in polluted regions by 1–10 ppb over the coming decades, with the largest effects in urban areas and during pollution episodes. This climate penalty means that stronger emission controls will be needed to meet a given air quality standard. Higher water vapor in the future climate is expected to decrease the ozone background, so that pollution and background ozone have opposite sensitivities to climate change. The effect of climate change on particulate matter (PM) is more complicated and uncertain than for ozone. Precipitation frequency and mixing depth are important driving factors but projections for these variables are often unreliable. GCM–CTM studies find that climate change will affect PM concentrations in polluted environments by ±0.1–1 μg m^?3 over the coming decades. Wildfires fueled by climate change could become an increasingly important PM source. Major issues that should be addressed in future research include the ability of GCMs to simulate regional air pollution meteorology and its sensitivity to climate change, the response of natural emissions to climate change, and the atmospheric chemistry of isoprene. Research needs to be undertaken on the effect of climate change on mercury, particularly in view of the potential for a large increase in mercury soil emissions driven by increased respiration in boreal ecosystems.     

Impact of underestimating the effects of cold temperature on motor vehicle start emissions of air toxics in the United States

Analyses of U.S. Environmental Protection Agency (EPA) certification data, California Air Resources Board surveillance testing data, and EPA research testing data indicated that EPA's MOBILE6.2 emission factor model substantially underestimates emissions of gaseous air toxics occurring during vehicle starts at cold temperatures for light-duty vehicles and trucks meeting EPA Tier 1 and later standards. An unofficial version of the MOBILE6.2 model was created to account for these underestimates. When this unofficial version of the model was used to project emissions into the future, emissions increased by almost 100% by calendar year 2030, and estimated modeled ambient air toxics concentrations increased by 6-84%, depending on the pollutant. To address these elevated emissions, EPA recently finalized standards requiring reductions of emissions when engines start at cold temperatures.     

46,XX/46,XY chromosome complement in amniotic fluid cell culture followed by the birth of a normal female child

Experience indicates that the most likely explanation for a mixture of 46,XX/46,XY cells in an amniotic fluid sample is that of maternal cell contamination and that a normal male child is to be expected at birth. We report the birth of a normal female child following prenatal diagnosis of such a mixture. Extensive postnatal studies failed to reveal an XY cell line. The possible sources of the XY cell line are discussed, as are the various techniques that were applied in an effort to discover it's origin. Cross-contamination of samples could be ruled out and there was no evidence of an unsuspected twin pregnancy. It is clear from this case that not all 46,XX/46,XY results obtained in amniotic fluid can be assumed to represent maternal cell contamination and some effort should be made to eliminate other potential sources for such a mixture.     

SIMULATING NITROGEN LOSSES FROM AGRICULTURAL LAND: IMPLICATIONS FOR WATER QUALITY AND PROTECTION POLICY1

ABSTRACT: EPIC, a soil erosion/plant growth simulation model, is used to simulate nitrogen losses for 120 randomly selected and previously surveyed cropland sites. Simulated nitrogen losses occur through volatilization, surface water and soil runoff, subsurface lateral flow, and leaching. Physical and crop management variables explain a moderate but significant proportion of the variation in nitrogen losses. Site slope and tillage have offsetting effects on surface and ground water losses. Nitrogen applications in excess of agronomic recommendations and manure obtained off the farm and applied to the sites are significant contributors to nitrogen losses. Farm characteristics such as production of confined livestock, total manure nitrogen available, and farm income per cropland acre explain a relatively large portion of the variability in manure nitrogen applied to survey sites. The results help to identify farm characteristics that can be used to target nutrient management programs. Simulation modeling provides a useful tool for investigating variables which contribute to agricultural nitrogen losses.