Industrial Zoning as a Means of Controlling Area Source Air Pollution

The simple ATDL urban dispersion model Is based on the formula Xo(g/m³) = CO(g/m²s)/U(m/s). The diurnal variation of the stability factor C, which can be thought of as the width of the urban area divided by the vertical dispersion of the pollution cloud, has not before been satisfactorily estimated. Using observed diurnal variations of CO concentrations and traffic frequencies reported by DeMarrais of the EPA for many stations in the states of Maryland, New Jersey, and Colorado, and using wind data from these states, hourly values of C - XoU/Q were calculated. The ratio of C to the daily average C is found to equal about 2.5 at 4 a.m., drops to about 0.5 by 8 a.m., and remains at 0.5 until about 6 p.m.., when it starts to climb slowly again. Application of this new stability factor to independent CO data from Los Angeles yields correlations between measured and predicted concentrations of about 0.7.     

A novel cell division factor from tobacco 2B-13 cells that induced cell division in auxin-starved tobacco BY-2 cells

Effects of auxin as plant hormones are widespread; in fact in almost all aspects of plant growth and development auxin plays a pivotal role. Although auxin is required for propagating cell division in plant cells, its effect upon cell division is least understood. If auxin is depleted from the culture medium, cultured cells cease to divide. It has been demonstrated in this context that the addition of auxin to auxin-starved nondividing tobacco BY-2 cells induced semisynchronous cell division. On the other hand, there are some cell lines, named habituated cells, that can grow without auxin. The cause and reason for the habituated cells have not been clarified. A habituated cell line named 2B-13 is derived from the tobacco BY-2 cell line, which has been most intensively studied among plant cell lines. When we tried to find the difference between two cell lines of BY-2 and 2B-13 cells, we found that the addition of culture filtrated from the auxin-habituated 2B-13 cells induced semisynchronous cell division in auxin-starved BY-2 cells. The cell division factor (CDF) that is responsible for inducing cell division in auxin-starved BY-2 cells was purified to near-homogeneity by sequential passage through a hydroxyapatite column, a ConA Sepharose column and a Sephadex gel filtration column. The resulting purified fraction appeared as a single band of high molecular weight on sodium dodecyl sulfate-polyacrylamide gel electrophoresis gels by silver staining and was able to induce cell division in auxin-starved BY-2 cells. Identification of the protein by MALD-TOF-MS/MS revealed that it is structurally related to P-glycoprotein from Gossypioides kirkii, which belongs to ATP-binding cassette (ABC)-transporters. The significance of CDF as a possible ABC-transporter is discussed in relationship to auxin–autotrophic growth and auxin-signaling pathway.     

Environmental monitoring of fluoride emissions using precipitation, dust, plant and soil samples

A pollution gradient was observed in precipitation, plants and soils sampled at different locations around a fluoride producing chemical plant in Germany. In all samples the influence of emissions was discernible up to a distance of 500 m from the plant. However, fluoride concentrations in plant bioindicators (leaves of birch and black berry) and in bulk precipitation showed a more pronounced relationship with the distance from the source than fluoride concentrations in soil. Vegetables sampled in the vicinity of the plant also had elevated concentrations of fluoride, but only the consumption of larger quantities of this material would lead to exceedances of recommended daily F-intake. The present study did not indicate the existence of low phytotoxicity thresholds for fluoride in the plant species used in the study. Even at very high fluoride concentrations in leaf tissue (963 ppm) plants did not show injury due to HF. Dust sampling downwind of the chemical plant confirmed that particulate fluoride was of minor importance in the study area.     

Safety assessment of automated vehicles: how to determine whether we have collected enough field data?

Abstract

Objective: The amount of collected field data from naturalistic driving studies is quickly increasing. The data are used for, among others, developing automated driving technologies (such as crash avoidance systems), studying driver interaction with such technologies, and gaining insights into the variety of scenarios in real-world traffic. Because data collection is time consuming and requires high investments and resources, questions like “Do we have enough data?,” “How much more information can we gain when obtaining more data?,” and “How far are we from obtaining completeness?” are highly relevant. In fact, deducing safety claims based on collected data—for example, through testing scenarios based on collected data—requires knowledge about the degree of completeness of the data used. We propose a method for quantifying the completeness of the so-called activities in a data set. This enables us to partly answer the aforementioned questions.

Method: In this article, the (traffic) data are interpreted as a sequence of different so-called scenarios that can be grouped into a finite set of scenario classes. The building blocks of scenarios are the activities. For every activity, there exists a parameterization that encodes all information in the data of each recorded activity. For each type of activity, we estimate a probability density function (pdf) of the associated parameters. Our proposed method quantifies the degree of completeness of a data set using the estimated pdfs.

Results: To illustrate the proposed method, 2 different case studies are presented. First, a case study with an artificial data set, of which the underlying pdfs are known, is carried out to illustrate that the proposed method correctly quantifies the completeness of the activities. Next, a case study with real-world data is performed to quantify the degree of completeness of the acquired data for which the true pdfs are unknown.

Conclusion: The presented case studies illustrate that the proposed method is able to quantify the degree of completeness of a small set of field data and can be used to deduce whether sufficient data have been collected for the purpose of the field study. Future work will focus on applying the proposed method to larger data sets. The proposed method will be used to evaluate the level of completeness of the data collection on Singaporean roads, aimed at defining relevant test cases for the autonomous vehicle road approval procedure that is being developed in Singapore.     

Resource protection for waterbirds in Chesapeake bay

Many living resources in the Chesapeake Bay estuary have deteriorated over the past 50 years. As a result, many governmental committees, task forces, and management plans have been established. Most of the recommendations for implementing a bay cleanup focus on reducing sediments and nutrient flow into the watershed. We emphasize that habitat requirements other than water quality are necessary for the recovery of much of the bay's avian wildlife, and we use a waterbird example as illustration. Some of these needs are: (1) protection of fast-eroding islands, or creation of new ones by dredge deposition to improve nesting habitat for American black ducks(Anas rubripes), great blue herons(Ardea herodias), and other associated wading birds; (2) conservation of remaining brackish marshes, especially near riparian areas, for feeding black ducks, wading birds, and wood ducks(Aix sponsa); (3) establishment of sanctuaries in open-water, littoral zones to protect feeding and/or roosting areas for diving ducks such as canvasbacks(Aythya valisineria) and redheads(Aythya americana), and for bald eagles(Haliaeetus leucocephalus); and (4) limitation of disturbance by boaters around nesting islands and open-water feeding areas. Land (or water) protection measures for waterbirds need to include units at several different spatial scales, ranging from “points” (e.g., a colony site) to large-area resources (e.g., a marsh or tributary for feeding). Planning to conserve large areas of both land and water can be achieved following a biosphere reserve model. Existing interagency committees in the Chesapeake Bay Program could be more effective in developing such a model for wildlife and fisheries resources.     

Tropical fruit trees as bioindicators of industrial air pollution in southeast Brazil

Psidium guajava L., Psidium cattleyanum Sabine and Mangifera indica L. were tested under field conditions as possible tropical bioindicators of industrial air pollution. The study was performed around the industrial complex of Cubat?o, SE Brazil, which comprises 23 industries, including fertilizer, cement, chemical, petrochemical, and steel plants, with 110 production units and 260 emission sources of pollutants. Saplings were exposed to environmental conditions during four periods of 16 weeks each (September 1994-September 1995), at four different sites in the coastal mountains near the industrial complex: the Valley of Pil?es River (VP), the reference area; the Valley of Mogi River (VM), with high contamination of particulate matter, fluorides (F), sulfur (S) and nitrogen (N) compounds; Caminho do Mar (CM1, CM2), mainly affected by organic pollutants, S and N compounds, and secondary pollutants; and Paranapiacaba (PP), affected by secondary pollutants, such as ozone. M. indica did not adapt to the climatic conditions at the exposure sites. In the two Psidium species, the presence of visible symptoms, root/shoot ratio, foliar contents of F, S and N, amounts of ascorbate (AA) and water-soluble thiols (-SH), as well as peroxidase activity (POD) were determined. P. guajava showed higher foliar accumulation of F, S and N, more pronounced alterations of biochemical indicators, and less visible leaf injury than P. cattleyanum. P. guajava may be used as an accumulative indicator in tropical climates, while further studies will be needed before P. cattleyanum might be applied as a sensitive species in biomonitoring programs.