On-road motor vehicle emissions and fuel consumption in urban driving conditions

This paper reports on the analysis of on-road vehicle speed, emission, and fuel consumption data collected by four instrumented vehicles. Time-, distance-, and fuel-based average fuel consumption, as well as CO, HC, NOx, and soot emission factors, were derived. The influences of instantaneous vehicle speed on emissions and fuel consumption were studied. It was found that the fuel-based emission factors varied much less than the time- and distance-based emission factors as instantaneous speed changed. The trends are similar to the results obtained from laboratory tests. The low driving speed contributed to a significant portion of the total emissions over a trip. Furthermore, the on-road data were analyzed using the modal approach. The four standard driving modes are acceleration, cruising, deceleration, and idling. It was found that the transient driving modes (i.e., acceleration and deceleration) were more polluting than the steady-speed driving modes (i.e., cruising and idling) in terms of g/km and g/sec. These results indicated that the on-road emission measurement is feasible in deriving vehicle emissions and fuel consumption factors in urban driving conditions.     

Nitrogen balance and groundwater nitrate contamination: comparison among three intensive cropping systems on the North China Plain

The annual nitrogen (N) budget and groundwater nitrate-N concentrations were studied in the field in three major intensive cropping systems in Shandong province, north China. In the greenhouse vegetable systems the annual N inputs from fertilizers, manures and irrigation water were 1358, 1881 and 402 kg N ha(-1) on average, representing 2.5, 37.5 and 83.8 times the corresponding values in wheat (Triticum aestivum L.)-maize (Zea mays L.) rotations and 2.1, 10.4 and 68.2 times the values in apple (Malus pumila Mill.) orchards. The N surplus values were 349, 3327 and 746 kg N ha(-1), with residual soil nitrate-N after harvest amounting to 221-275, 1173 and 613 kg N ha(-1) in the top 90 cm of the soil profile and 213-242, 1032 and 976 kg N ha(-1) at 90-180 cm depth in wheat-maize, greenhouse vegetable and orchard systems, respectively. Nitrate leaching was evident in all three cropping systems and the groundwater in shallow wells (<15 m depth) was heavily contaminated in the greenhouse vegetable production area, where total N inputs were much higher than crop requirements and the excessive fertilizer N inputs were only about 40% of total N inputs.     

Degradation of ethinyl estradiol by nitrifying activated sludge

Degradation of ethinyl estradiol (EE2) by nitrifying activated sludge was studied with micro-organisms grown in a reactor with feedback of sludge fed with only a mineral salts medium containing ammonium as the sole energy source. Ammonium was oxidised by this sludge at a rate of 50 mg NH4+ g(-1) DW h(-1). This activated sludge was also capable of degrading EE2 at a maximum rate of 1 microg g(-1) DW h(-1). Using sludge with an insignificant nitrifying capacity of 1 mg NH4+ g(-1) DW h(-1), no degradation of EE2 was detected. Oxidation of EE2 by nitrifying sludge resulted in the formation of hydrophilic compounds, which were not further identified. Most probably degradation by nitrifying sludge results in a loss of estrogenic activity, as hydroxylated derivatives of EE2 are known to have a substantially lower pharmacological activity than EE2.     

Pilot survey of a broad range of priority pollutants in sediment and fish from the Ebro river basin (NE Spain)

Priority organic pollutants were investigated in sediments and fish collected along the Ebro river basin (NE Spain) to evaluate their occurrence, transport and bioavailability. Sediments were collected in 18 sites and two species of fish were captured in nine sites according to the availability in each area. The sampling sites covered industrial, urban and agricultural areas. Four methods were used to detect 20 organochlorine compounds (OCs), 8 polycyclic aromatic hydrocarbons, 3 organotin compounds, 2 alkylphenols and 40 polybrominated diphenyl ethers (PBDEs) from purified extracts. The contamination pattern was site specific and no downstream increase in concentration of pollutants was observed but rather a generalized low level diffuse pollution. Target compounds were detected in sediments at 0.01 to 2331 microg/kg dry weight, and only OCs and PBDEs were accumulated in benthopelagic fish. Toxicological assessment was performed according to predicted environmental levels and revealed sites where adverse effects could occur.     

Evaluation of ecological disturbance and intrinsic bioremediation potential of pulp mill-contaminated lake sediment using key enzymes as probes

A rapid protocol was developed to measure 10 different enzymic activities from a large number of 1-cm-sliced freshly collected lake sediments. Layers heavily polluted by organic halogens (4900 mg Cl kg(-1)) revealed severe depression of phosphatase, sulfatase, leucine-aminopeptidase, chitinase, acetate esterase and butyrate esterase activities as compared to layers above and below the most polluted zone. alpha-Glucosidase, beta-glucosidase, beta-xylosidase and palmitate esterase were less affected. Methane oxidation potential was dramatically depressed in the polluted strata whereas tetrachloromethane dehalogenating activity was observed in the polluted sediment only. The sediment layers formed after the chlorine discharges into the lake had diminished to 1/10, and showed restoration of the activities close to those observed in non-recipient sediment, in spite of the persisting presence of >1000 mg of organic chlorine (kg dry wt)(-1). We conclude that certain enzymic activities involved in breakdown or oxidation of organic matter in the sediments are useful probes for assessing the degree of ecological damage and its potential for restoration in recipient lakes of industrial discharges.     

Removal of nitrogen and phosphate from wastewater by addition of bittern

Removal of nitrogen and phosphate through crystallization of struvite (MgNH(4)PO(4).6H(2)O) has gained increasing interest. Since wastewaters tend to be low in magnesium relative to ammonia and phosphates, addition of this mineral is usually required to effect the struvite crystallization process. The present study evaluated the feasibility of using bittern, a byproduct of salt manufacture, as a low-cost source of magnesium ions. High reaction rates were observed; the extent of nitrogen and phosphorus removals did not change beyond 10 min. Phosphorus removals from pure solutions with bittern added were equivalent to those obtained with MgCl(2) or seawater. Nitrogen removals with bittern were somewhat lower than with the alternate Mg(2+) sources, however. Application of bittern to biologically treated wastewater from a swine farm achieved high phosphate removal, but ammonia removals were limited by imbalance in the nitrogen:phosphorus ratio.     

Diflubenzuron residue and persistence on an oak forest after aerial application

Abstract

A twenty hectare forest block in central Pennsylvania was aerially sprayed with diflubenzuron (Dimilin 25W®) at the dose of 33.23g A.I./ha in 9.4 litres/ha. Leaf samples were collected from the upper and lower canopies of 27 oaks and understory within this block on the day of spray, May 29, 1991. Canopy leaves were also collected on May 31, June 10, July 29 and September 26, 1991.

Recovery of diflubenzuron residues on fortified canopy‐leaf and litter‐leaf samples using analytical techniques employed in this study averaged 87.4% (SE = 7.5%) and 66.2% (SE = 8.2%), respectively.

On the day of spray, diflubenzuron residues on the upper canopy, lower canopy and understory averaged 81.18, 39.65 and 8.35 ng/cm², respectively. Diflubenzuron residues on canopy‐leaf samples collected 2, 12, 61 and 120 days post‐spray averaged 14.83 (SE = 10.19), 16.75 (SE = 9.95), 12.84 (SE = 8.25) and 11.20 (SE = 7.52) ng/cm², respectively. Diflubenzuron residues on litter‐leaf samples collected after leaf senescence ‐ 169 and 323 days post spray contained measurable amounts of diflubenzuron in 51 and 59% of the samples, respectively. Of the samples with measurable amounts of diflubenzuron, residues averaged 1.36 (SE = 2.44) and 0.65 ng/cm² (SE = 0.73) respectively.     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.