Determining Reduced-Emission Goals Needed to Achieve Air Quality Goals— A Hypothetical Case

Air management steps involved in determining reduced-emission goals include determining the effects of various pollutant concentrations on man, animals, plants, and property; deciding which effects to prevent; selecting ambient air quality goals that will prevent these effects; measuring and evaluating pollutant concentrations from sources and in the ambient atmosphere; calculating over-all source reductions needed to achieve selected ambient air quality goals; and finally, determining reduced-emission goals for the various source types. Examples are cited of the various decisions and actions involved in determining a set of reduced-emission goals for stationary and mobile combustion sources.     

An Air Quality Data Analysis System for Interrelating Effects,Standards, and Needed Source Reductions: Part 3. Vegetation Injury

Acute leaf injury data are analyzed for 19 plant species exposed to ozone or sulfur dioxide. The data can be depicted by a new leaf injury mathematical model with two characteristics: (1) a constant percentage of leaf surface is injured by an air pollutant concentration that is inversely proportional to exposure duration raised to an exponent; (2) for a given exposure duration, the percent leaf injury as a function of pollutant concentration tends to fit a lognormal frequency distribution. Leaf injury as a function of laboratory exposure duration is modeled and compared with ambient air pollutant concentration measurements for various averaging times to determine which exposure durations are probably most important for setting ambient air quality standards to prevent or reduce visible leaf injury. The 8 hour average appears to be most important for most of the plants investigated for most sites, 1 hr concentrations are important for most plants at a few sites, and 3 hr S0₂ concentrations are important for some plants, especially those exposed to isolated point sources of the pollutant. The 1, 3, and 8 hr threshold injury concentrations are listed for each of the 19 plant species studied. To prevent or reduce acute leaf injury, fixed, nonoverlapping ambient air quality measurements and standards are recommended for averaging times of 1, 3, and 8hr.     

An Air Quality Data Analysis System for Interrelating Effects,Standards, and Needed Source Reductions: Part 8. An Effective Mean O3 Crop Reduction Mathematical Model

A plant injury mathematical model, applied previously to acute and chronic leaf injury data, is used here to model National Crop Loss Assessment Network (NCLAN) data for 15 cultivars and to calculate species parameters from the cultivar analyses. Percent crop yield reduction is estimated as a function of a new parameter, the effective mean O₃ concentration: m_e = [(Σ c_h ^?1/v)/n]^?v, where c_h is the hourly average ambient O₃ concentration for each daytime hour (defined here as 9:00 A.M.–4:00 P.M., always standard time) of data available at an air sampling site for summer (defined here as June 1–August 31), n is the total number of such available hours, and v is an exposure time-concentration parameter, calculated here to be approximately –0.376. Crop yield reduction for soybean is calculated here as z = 0.478 In (tm_e ^2-66) – 0.42, where z is the Gaussian transform of percent crop reduction, t is the hours of exposure (525 h is used here; 7 h/day for 75 days), and In indicates that the natural logarithm is taken of the quantity within parentheses. Crop yield reductions for seven plant species are estimated with similar equations for each of the 1824 site-years of 1981–1983 hourly O₃ concentration data available in the National Aerometric Data Bank (NADB). County-average effective mean O₃ concentrations are indicated by shading on a U.S. map. State-average O₃ parameters and estimated percent crop yield reductions are tabulated. The National Ambient Air Quality Standard (NAAQS) for O₃ specifies that, on the average, the second highest daily maximum 1-h average O₃ concentration in a year shall not exceed 0.12 ppm. For years 1981-1983,71% of the NADB sites recorded annual second highest daily maximum 1-h average O3 concentrations below 0.125 ppm (for summer daytime hours). Ambient O₃ concentrations reduced the total U.S. crop yield an estimated 5% for years 1981–1983. (Summer, daytime, and all acronyms are always used herein as defined above.)     

An Air Quality Data Analysis System for Interrelating Effects,Standards, and Needed Source Reductions: Part 10. Potential Ambient O3 Standards to Limit Soybean Crop Reduction

Soybean percent crop reduction was estimated as a function of ambient O₃ concentrations for each of 80 agricultural sites in the National Aerometric Data Bank (NADB) for each available year of data for years 1981-1985. Fourteen O₃ concentration statistics were calculated for each of the resulting 320 site-years of data. The two statistics that correlated best with estimated crop reduction were an effective mean O₃ concentration (1 percent of variance unexplained) and an arithmetic mean O₃ concentration (4 percent unexplained). The worst correlation of the 14 was for the statistic used in the present O₃ National Ambient Air Quality Standard (NAAQS), the second highest daily maximum 1-h O₃ concentration (42 percent unexplained). The number of site-years for estimated percent soybean yield reductions was plotted versus increasing O₃ concentrations for each of the 14 O₃ statistics. A maximum crop reduction line was drawn on each plot. These lines were used to estimate (and list) potential ambient O₃ standards for each of the 14 statistics that would limit soybean crop reduction at agricultural. NADB sites to 5, 10, 15, or 20 percent.     

Real-life efficiency of urine source separation

Urine source separation (NoMix technology) is a promising innovation in wastewater management. To improve and further develop NoMix technology, it has been implemented in four Swiss households and at our research institute (Eawag). We conducted measurements during one year on frequency of toilet usage (in households 5.2/person/day for weekdays, and 6.3/person/day for weekends), flushing behavior (30–85% small flushes), and recovered urine. We calculate the amount of urine effectively recovered per voiding in NoMix toilets (138 ml/flush in households; 309 ml/flush in women's toilets at Eawag), and waterfree urinals (225 ml/usage). We estimate urine recovery in the households to be maximally 70–75% of the expected quantity, leaving room for technical and behavioral improvements. Based on sampling of N and P concentrations, we suspect nitrogen losses in the extended urine piping system. For households and workplaces, the daily and weekly flushing pattern is recorded. Our results are in accordance with literature data from a shorter period but with more people. These results represent a good dimensioning basis for future urine source separation applications. An example of extrapolation to an entire watershed is presented. The flushing pattern corresponds well with the typical nitrogen loading of a treatment plant.     

Bepflanzung einer Tankstelle mit Weiden

In Axelved, Denmark, an abandoned gas filling station serves as a test field for phytoremediation. Laboratory studies accompany the project. The toxicity of fresh and weathered gasoline and diesel to willow and poplar trees was studied by use of a tree transpiration toxicity test. The correlation between diesel content in soil and decrease in willow tree transpiration (Salix viminalis x schwerinii) was highly significant (r ²=0.81, n=19). the EC₅₀ (50% inhibition of transpiration) for the sum of hydrocarbons (HC) was determined to be 3910 mg/kg (95% confidence interval from 2900 to 5270 mg/kg). The EC₁₀ was 810 mg/kg (95% confidence interval 396 to 1660 mg/kg). The results were verified with artificially mixed diesel and gasolinecontaminated soils and two willow and one poplar species (S. viminalis, S. alba andPopulus nigra). The degradation of radiolabeledm-xylene was studied with and without willows. The compound was readily degraded. Willow trees accelerated the elimination, but mainly due to the volatilization ofm-xylene. Model studies provided the result that biodegradation in soil is the fastest elimination process at the site, but it is limited by the availability of electron acceptors. The pollutants are almost persistent in the groundwater, but in aerated soil, 10000 mg/kg hydrocarbons at 1 m depth are degraded within 13 years. The main effect of willows on the pollutants’ persistence is that willows transpire water, lower the groundwater level and aerate the soil, hereby speeding up biodegradation.     

Nutrient and Sediment Production,Watershed Characteristics,and Land Use in the Tahoe Basin,California‐Nevada1

Abstract: In efforts to control the degradation of water quality in Lake Tahoe, public agencies have monitored surface water discharge and concentrations of nitrogen, phosphorus, and suspended sediment in two separate sampling programs. The first program focuses on 20 watersheds varying in size from 162 to 14,000 ha, with continuous stream gaging and periodic sampling; the second focuses on small urbanized catchments, with automated sampling during runoff events. Using data from both programs, we addressed the questions (1) what are the fluxes and concentrations of nitrogen and phosphorus entering the lake from surface runoff; (2) how do the fluxes and concentrations vary in space and time; and (3) how are they related to land use and watershed characteristics? To answer these questions, we calculated discharge‐weighted average concentrations and annual fluxes and used multiple regression to relate those variable to a suite of GIS‐derived explanatory variables. The final selected regression models explain 47‐62% of the variance in constituent concentrations in the stormwater monitoring catchments, and 45‐72% of the variance in mean annual yields in the larger watersheds. The results emphasize the importance of impervious surface and residential density as factors in water quality degradation, and well‐developed soil as a factor in water quality maintenance.