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Particulate matter < or =10 microm (PM10) emissions due to wind erosion can vary dramatically with changing surface conditions. Crust formation, mechanical disturbance, soil texture, moisture, and chemical content of the soil can affect the amount of dust emitted during a wind event. A refined method of quantifying windblown dust emissions was applied at Mono Lake, CA, to account for changing surface conditions. This method used a combination of real-time sand flux monitoring, ambient PM10 monitoring, and dispersion modeling to estimate dust emissions and their downwind impact. The method identified periods with high emissions and periods when the surface was stable (no sand flux), even though winds may have been high. A network of 25 Cox sand catchers (CSCs) was used to measure the mass of saltating particles to estimate sand flux rates across a 2-km2 area. Two electronic sensors (Sensits) were used to time-resolve the CSC sand mass to estimate hourly sand flux rates, and a perimeter tapered element oscillating microbalance (TEOM) monitor measured hourly PM10 concentrations. Hourly sand flux rates were related by dispersion modeling to hourly PM10 concentrations to back-calculate the ratio of vertical PM10 flux to horizontal sand flux (K-factors). Geometric mean K-factor values (K(f)) were found to change seasonally, ranging from 1.3 x 10(-5) to 5.1 x 10(-5) for sand flux measured at 15 cm above the surface (q15). Hourly PM10 emissions, F, were calculated by applying seasonal K-factors to sand flux measurements (F = K(f) x q15). The maximum hourly PM10 emission rate from the study area was 76 g/m2 x hr (10-m wind speed = 23.5 m/sec). Maximum daily PM10 emissions were estimated at 450 g/m2 x day, and annual emissions at 1095 g/m2 x yr. Hourly PM10 emissions were used by the U.S. Environmental Protection Agency (EPA) guideline AERMOD dispersion model to estimate downwind ambient impacts. Model predictions compared well with monitor concentrations, with hourly PM10 ranging from 16 to over 60,000 microg/m3 (slope = 0.89, R2 = 0.77).  相似文献   
2.
ABSTRACT

Particulate matter ≤10 μm (PM10) emissions due to wind erosion can vary dramatically with changing surface conditions. Crust formation, mechanical disturbance, soil texture, moisture, and chemical content of the soil can affect the amount of dust emitted during a wind event. A refined method of quantifying windblown dust emissions was applied at Mono Lake, CA, to account for changing surface conditions. This method used a combination of real-time sand flux monitoring, ambient PM10 monitoring, and dispersion modeling to estimate dust emissions and their downwind impact. The method identified periods with high emissions and periods when the surface was stable (no sand flux), even though winds may have been high. A network of 25 Cox sand catchers (CSCs) was used to measure the mass of saltating particles to estimate sand flux rates across a 2-km2 area. Two electronic sensors (Sensits) were used to time-resolve the CSC sand mass to estimate hourly sand flux rates, and a perimeter tapered element oscillating microbalance (TEOM) monitor measured hourly PM10 concentrations. Hourly sand flux rates were related by dispersion modeling to hourly PM10 concentrations to back-calculate the ratio of vertical PM10 flux to horizontal sand flux (K-factors). Geometric mean K-factor values (K f) were found to change seasonally, ranging from 1.3 × 10?5 to 5.1 × 10?5 for sand flux measured at 15 cm above the surface (q 15). Hourly PM10 emissions, F, were calculated by applying seasonal K-factors to sand flux measurements (F?=?K f ×?q 15). The maximum hourly PM10 emission rate from the study area was 76 g/m2·hr (10-m wind speed?=?23.5 m/sec). Maximum daily PM10 emissions were estimated at 450 g/m2·day, and annual emissions at 1095 g/m2·yr. Hourly PM10 emissions were used by the U.S. Environmental Protection Agency (EPA) guideline AERMOD dispersion model to estimate downwind ambient impacts. Model predictions compared well with monitor concentrations, with hourly PM10 ranging from 16 to over 60,000 μg/m3 (slope?=?0.89, R 2?=?0.77).

IMPLICATIONS Under a U.S. Environmental Protection Agency (EPA)-approved plan, the method described in this paper has been used since 2000 at Owens Lake, CA, to identify and successfully mitigate dust from over 100 km2 of the dry lakebed. It continues to be used to monitor dust control compliance at Owens Lake. Scaled-down versions of the Owens Lake network can be implemented in other areas in a manner similar to the Mono Lake study. Once K-factors are established, low-cost CSC samplers (about $35 U.S.) may be used for periodic monitoring (e.g., daily, weekly, or monthly) to estimate PM10 emissions or to evaluate dust control compliance.  相似文献   
3.
An inkjet printing process has been suggested for producing nylon 6 in an additive manufacturing approach and this paper reports on the jettability of molten reactive materials made by caprolactam with activator and catalyst to study the feasibility of the approach in an inkjet system. The materials physical properties which are important for jetting were characterized and then the melt supply behaviour in the system was studied and finally jetting trials were monitored to investigate the effect of parameter settings on the stability of the jet array. It was found that the surface tension and viscosity of all materials were within the suitable range. However, with the catalyst mixtures, microcrystals of the undissolved salt of the catalyst complex were found to influence the melt supply behaviour considerably. The mixtures had a narrower range of parameters where stability occurred compared with caprolactam. Monitoring the jet stability recommended a suitable range of jetting parameters for the deposition stage of researching the new approach. A higher level of instability was observed with the catalyst mixture especially when jetting with multiple nozzles due to the microcrystals.  相似文献   
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