Satellite detection of land-use change and effects on regional forest aboveground biomass estimates

We used remote-sensing-driven models to detect land-cover change effects on forest aboveground biomass (AGB) density (Mg.ha(-1), dry weight) and total AGB (Tg) in Minnesota, Wisconsin, and Michigan USA, between the years 1992-2001, and conducted an evaluation of the approach. Inputs included remotely-sensed 1992 reflectance data and land-cover map (University of Maryland) from Advanced Very High Resolution Radiometer (AVHRR) and 2001 products from Moderate Resolution Imaging Spectroradiometer (MODIS) at 1-km resolution for the region; and 30-m resolution land-cover maps from the National Land Cover Data (NLCD) for a subarea to conduct nine simulations to address our questions. Sensitivity analysis showed that (1) AVHRR data tended to underestimate AGB density by 11%, on average, compared to that estimated using MODIS data; (2) regional mean AGB density increased slightly from 124 (1992) to 126 Mg ha(-1) (2001) by 1.6%; (3) a substantial decrease in total forest AGB across the region was detected, from 2,507 (1992) to 1,961 Tg (2001), an annual rate of -2.4%; and (4) in the subarea, while NLCD-based estimates suggested a 26% decrease in total AGB from 1992 to 2001, AVHRR/MODIS-based estimates indicated a 36% increase. The major source of uncertainty in change detection of total forest AGB over large areas was due to area differences from using land-cover maps produced by different sources. Scaling up 30-m land-cover map to 1-km resolution caused a mean difference of 8% (in absolute value) in forest area estimates at the county-level ranging from 0 to 17% within a 95% confidence interval.     

Fertiliser management effects on dissolved inorganic nitrogen in runoff from Australian sugarcane farms

Dissolved inorganic nitrogen (DIN) movement from Australian sugarcane farms is believed to be a major cause of crown-of-thorns starfish outbreaks which have reduced the Great Barrier Reef coral cover by ~21% (1985–2012). We develop a daily model of DIN concentration in runoff based on >200 field monitored runoff events. Runoff DIN concentrations were related to nitrogen fertiliser application rates and decreased after application with time and cumulative rainfall. Runoff after liquid fertiliser applications had higher initial DIN concentrations, though these concentrations diminished more rapidly in comparison to granular fertiliser applications. The model was validated using an independent field dataset and provided reasonable estimates of runoff DIN concentrations based on a number of modelling efficiency score results. The runoff DIN concentration model was combined with a water balance cropping model to investigate temporal aspects of sugarcane fertiliser management. Nitrogen fertiliser application in December (start of wet season) had the highest risk of DIN movement, and this was further exacerbated in years with a climate forecast for ‘wet’ seasonal conditions. The potential utility of a climate forecasting system to predict forthcoming wet months and hence DIN loss risk is demonstrated. Earlier fertiliser application or reducing fertiliser application rates in seasons with a wet climate forecast may markedly reduce runoff DIN loads; however, it is recommended that these findings be tested at a broader scale.     

Dissolution kinetics of sub-millimeter Composition B detonation residues: role of particle size and particle wetting

The dissolution of the 2,4,6-trinitrotoluene (TNT), hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), and octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) from microscale particles (<250 μm) of the explosive formulation Composition B was examined and compared to dissolution from macroscopic particles (>0.5 mm). The dissolution of explosives from detonation soot was also examined. The measured mass transfer coefficients for the microscale particles were one to two orders of magnitude greater than the macroscopic particles. When normalized to particle surface area, mass transfer coefficients of microscale and macroscale particles were similar, indicating that the bulk dissolution processes were similar throughout the examined size range. However, an inverse relationship was observed between the particle diameter and the RDX:TNT mass transfer rate coefficient ratio for dry-attritted particles, which suggests that RDX may be more readily dissolved (relative to TNT) in microscale particles compared to macroscale particles. Aqueous weathering of larger Composition B residues generated particles that possessed mass transfer coefficients that were on the order of 5- to 20-fold higher than dry-attritted particles of all sizes, even when normalized to particle surface area. These aqueous weathered particles also possessed a fourfold lower absolute zeta-potential than dry-attritted particles, which is indicative that they were less hydrophobic (and hence, more wettable) than dry-attritted particles. The increased wettability of these particles provides a plausible explanation for the observed enhanced dissolution. The wetting history and the processes by which particles are produced (e.g., dry physical attrition vs. aqueous weathering) of Composition B residues should be considered when calculating mass transfer rates for fate and transport modeling.     

Penetration and Duration of Oxidant Air Pollution in the South Coast Air Basin of California

On June 18, 19, and 20, 1970, two aircraft, a rawinsonde, two pibal stations, and four ground stations provided simultaneous samples of total oxidant, temperature, and winds up to 8000 ft in an area extending from Santa Monica, Calif., east to Redlands and north across the San Bernardino Mountains. It was shown that photochemical oxidant formed in the marine layer is vented up the slopes and over the crest of the San Bernardino Mountains during the day. Layers of high oxidant concentrations were detected above the inversion base, suggesting that some pollution is vented up the slopes and subsequently advected back to the south. The diurnal changes in the temperature inversion also contribute to the high concentration found above the inversion base. These processes result in multi-layers of pollution. The study suggests that oxidant air pollution is transported up to 80 mi to forested mountains, where severe damage to conifer species has been documented.     

Estimating Long-Term Ground Level Concentrations of SO2 from Short-Term Peak Data

Maximum concentrations of sulfur dioxide vary approximately inversely as the square root of the averaging time for periods up to a year, a much longer time period than those reported in previously published studies. This finding is based on analyses of SO₂ and tracer gas concentrations measured in the vicinities of a test stack, a petrochemical complex, and eight power plants. Therefore, for a given set of emission conditions, long-term concentrations of SO₂ and other conservative pollutants emitted by well-defined sources can be rapidly estimated from maximum short-term concentrations, and vice versa. The scatter in the data corresponds to an estimation error of about a factor of three for averaging time conversions of one day to one year. This is approximately the same error associated with conventional calculations. Therefore, the use of averaging time conversions is justified as a rapid screening technique to estimate compliance with ambient air quality standards.     

Characterization of On-Road Vehicle NO Emissions by a TILDAS Remote Sensor

ABSTRACT

A tunable infrared laser differential absorption spectrometer (TILDAS) was used to remotely sense the nitric oxide (NO) emissions from 1,473 on-road vehicles. The real-world measurement precision of this instrument in the limit of low NO concentration is 5 ppm of the vehicle exhaust, which corresponds to a 3o detection limit of 15 ppm. Our analysis of the distribution of negative concentration measurements produced during this experiment supports this claim, showing that the instrumental noise for this set of measurements was at most 8 ppm in the limit of low NO concentration. The high sensitivity of this instrument allowed us to measure the NO emissions of even the cleanest vehicles. The measured vehicle fleet NO emissions closely fit a gamma distribution with 10% of the fleet contributing about 50% of the total fleet emissions. Newer vehicles had lower NO emissions than older ones, but high NO emitters were found in every vehicle age cohort. On a vehicle-by-vehicle basis, NO emissions correlated very weakly with vehicle velocity, acceleration, power per unit mass, carbon monoxide (CO) emissions, and hydrocarbon (HC) emissions. High NO emitting vehicles could not be identified by remote sensing of CO or HC emissions and vice versa. When we compared the NO emissions for 117 vehicles measured more than one time, about half of the high NO emitters were found to be very consistent, while the other half varied significantly.     

Clean Air Corridors: A Geographic and

Meteorological factors, pollutant emissions, and geographic regions related to transport of low optical extinction coefficient air to Grand Canyon National Park were examined. Back trajectories were generated by two models, the Atmospheric Transport and Dispersion Model (ATAD) and an approach using the Nested Grid Model output for a Lagrangian particle transport model (NGM/ CAPITA). Meteorological information along the trajectories was analyzed for its relationship to visibility at the Grand Canyon. Case studies considered days with anomalously clean air from the southwest and dirty air from the northwest. Clean air was most frequently from the north and northwest, rarely from the south. Low emissions, high ventilation and washout by precipitation was associated with clean air. All clean days with transport from the Los Angeles area had upper-level low pressure over the region with high ventilation and usually abundant precipitation. The dirtiest days with transport from the northwest were affected by forest fires.     

Evaluation of Wind Fields Used in Grand Canyon Visibility Transport Commission Analyses

ABSTRACT

The Grand Canyon Visibility Transport Commission (GCVTC) was established by the U.S. Congress to assess the potential impacts of projected growth on atmospheric visibility at Grand Canyon National Park and to make recommendations to the U.S. Environmental Protection Agency on what measures could be taken to avoid such adverse impacts. A critical input to the assessment tool used by the commission was three-dimensional model-derived wind fields used to transport the emissions. This paper describes the evaluation of the wind fields used at various stages in the assessment. Wind fields evaluated included those obtained from the Colorado State University Regional Atmospheric Modeling System (RAMS), the National Meteorological Center's Nested Grid Model (NGM), and the National Oceanic and Atmospheric Administration's Atmospheric Transport and Dispersion (ATAD) trajectory model. The model-derived wind fields were evaluated at multiple vertical levels at several locations in the southwestern United States by determining differences between model predicted winds and winds that were measured using radiosonde and radar wind profiler data. Model-derived winds were also evaluated by determining the percent of time that they were within acceptable differences from measured winds.

All models had difficulties, generally meeting the acceptable criteria for less than 50% of the predictions. The RAMS model had a persistent bias toward southwesterly winds at the expense of other directions, especially failing to represent channeling by north-south mountain ranges in the lower levels. The NGM model exhibited a substantial bias in the summer months by extending northwesterly winds in the eastern Pacific Ocean well inland, in contrast to the observed southwesterlies at inland locations. The simpler ATAD trajectory model performed somewhat better than the other models, probably because of its use of more upper air sites. The results of the evaluation indicated that these wind fields could not be used to reliably predict source-receptor impacts on a particular day; thus, seasonally averaged impacts were used in the GCVTC assessment.     

Comparison of Ambient PM Risk with Risks Estimated from PM Components of Smoking and Occupational Exposures

ABSTRACT

Air pollution studies are based on individual-level health response data and group-level exposure data. Therefore, exposure misclassification occurs, and the results may be biased to an unknown magnitude and direction. Testing the validity of such associations requires a study design using individual-level data for both exposure and response. One can test the plausibility of group-level PM risk estimates by comparing them to individual-level estimates of risk from constituents of ambient air. The twofold purpose of this review is to consider the internal consistency of risks estimated from the three major PM cohort studies and to determine individual-level mortality risks associated with ambient concentrations of tobacco smoke and occupational exposures and compare them with risks associated with ambient PM.

The paper demonstrates the risks are not consistent within and between the PM cohort studies. Higher ambient concentration risks (ACRs) from the ambient PM cohort studies are not coherent with ACRs derived from individual-level smoking and occupational risks for total, cardiopulmonary, and lung cancer mortality. Individual-level studies suggest increased risk of mortality cannot be measured with reliability at concentrations found in ambient air.     

A Comparison of Nonlinear Regression and Neural Network Models for Ground-Level Ozone Forecasting

ABSTRACT

A hybrid nonlinear regression (NLR) model and a neural network (NN) model, each designed to forecast next-day maximum 1-hr average ground-level O₃ concentrations in Louisville, KY, were compared for two O₃ seasons—1998 and 1999. The model predictions were compared for the forecast mode, using forecasted meteorological data as input, and for the hindcast mode, using observed meteorological data as input. The two models performed nearly the same in the forecast mode. For the two seasons combined, the mean absolute forecast error was 12.5 ppb for the NLR model and 12.3 ppb for the NN model. The detection rate of 120 ppb threshold exceedances was 42% for each model in the forecast mode. In the hindcast mode, the NLR model performed marginally better than the NN