In the past N.-H. Lin has collaborated on articles with B.-J. Tsuang. One of their most recent publications is In-cloud scavenging and deposition of sulfates and nitrates: Case studies and parameterization. Which was published in journal Atmospheric Environment. Part A. General Topics.

More information about N.-H. Lin research including statistics on their citations can be found on their Copernicus Academic profile page.

N.-H. Lin's Articles: (2)

In-cloud scavenging and deposition of sulfates and nitrates: Case studies and parameterization

AbstractScavenging of sulfates and nitrates—two most common ions leading the cloudwater acidity—was investigated during field studies atop a site in Mt. Mitchell (35°44′05″N, 82°17′15″W) State Park where the highest peak (2038 m MSL) of the eastern U.S. is located. Experiments were conducted during the growing seasons (15 May–30 September) of 1986 and 1987 using an instrumented meteorological tower (16.5 m tall) and a passive cloudwater collector. A cloud episode that occurred on 12 October 1987, was also comprehensively investigated. Clouds were frequently observed in which the Fraser fir and red spruce stands stayed immersed 28% and 41% of the time during the 1986 and 1987 seasons, respectively. Rate of cloudwater deposition on the forest canopy was determined using an inferential cloud deposition model. It was found by analysing nine short duration (lasting 8 h or less) and 16 long duration cloud events that the ionic concentration (SO42− and NO3−) is inversely proportional to the rate (Ic) of cloudwater deposition (in mm h−1) and can be expressed by the following relationship: [SO42−] = aIc−b or [NO3−] = aIc−b. Theoretical arguments leading to these relationships are presented. The b values for predicting NO32− concentration are found in the range of 0.14–1.24 (mean = 0.48) for short duration and 0.062–0.63 (mean = 0.27) for long duration cloud events, respectively. The corresponding b values for predicting NO3− concentrations are 0.19–1.16 (mean = 0.49) and 0.072–0.59 (mean = 0.27), respectively. When the b parameter was between 0.2 and 0.6, the correlation coefficients between measured and predicted ionic concentrations were found to exceed 0.7. The parameter a is shown to represent the maximum ionic flux for a given cloud event. The ratio of the a parameter for SO42− to NO3− varied between 1.75 and 6.95, indicating that the SO42− contributes to the total ionic concentration substantially more than the NO3− leading to the conclusion that the cloudwater acidity is primarily due to the presence of sulfuric acid which has been demonstrated to cause foliar injury and growth retardation in red spruce trees. The above parameterization is similar to the one that is frequently used to relate ionic concentration in precipitation to the rainfall rate. In order to understand physico-chemical processes leading to the proposed parameterization schemes, meteorological and chemical variables are comprehensively analysed for one short duration and two long duration cloud events. The concentrations of principal ions (SO42−, NO3−, H+ and NH4+) during the short duration cloud events were found to be much higher than those during the long duration ones, especially at colder temperatures. Such short cloud events have a potential of causing foliar narcosis in red spruce stands because of unusually acidic cloudwater to which these stands stay exposed intermittently during each growing season.

Quantification on the source/receptor relationship of primary pollutants and secondary aerosols by a Gaussian plume trajectory model: Part III—Asian dust-storm periods

AbstractCharacteristics of pollutants at heights in the top of the Planetary Boundary Layer (PBL) are collected and used in a local-scale model. A subsidence mechanism is developed to quantify the concentration fraction from the top PBL to simulate PM concentration during Asian dust-storm (ADS) periods. The results show that using the data measured at a mountain station, which is very vulnerable to ADS, as the top boundary conditions for the air quality model can capture all the PM2.5 episodes due to local sources and ADS events, at a low-altitude urban station. The correlation coefficient (r2) of daily PM2.5−10 concentration has increased from 0.17 to 0.62 by incorporating the subsidence mechanism, and that of PM2.5 increases as well. The model results of nitrate, sulfate and ammonium aerosol in fine radii can be compared with observations. According to our analysis, five out of eight PM2.5 or PM10 episode days occurred on ADS days in the past 4 years (1999–2002). During ADS episodes in 2000, 12% of PM2.5 and 53% of PM2.5−10 were from ADS dust. In addition, two dry deposition algorithms are evaluated; the algorithm of Seinfeld and Pandis (Atmospheric Chemistry and Physics from Air Pollution to Climate Change, Wiley, New York, 1998, 1057pp.) is suggested in this case study.

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