Particle composition and size distributions in and around a deep-pit swine operation,Ames, IA

The contribution of emissions from agricultural facilities is rapidly becoming a major concern for local and regional air quality. Characterization of particle properties such as physical size distribution and chemical composition can be valuable in understanding the processes contributing to emissions and ultimate fate of particulate matter from agricultural facilities. A measurement campaign was conducted at an Iowa, deep-pit, three-barn swine finishing facility to characterize near-source ambient particulate matter. Size-specific mass concentrations were determined using minivol samplers, with additional size distribution information obtain using optical particle counters. Particulate composition was determined via ion chromatographic analysis of the collected filters. A thermal-CO₂ elemental/organic carbon analyzer measured particulate carbon. The chemical composition and size distribution of sub-micron particles were determined via real-time aerosol mass spectrometry. Primary particulate was not found to be a major emission from the examined facility, with filter-based impactor samples showing average near-source increases (~15–50 m) in ambient PM₁₀ of 5.8 ± 2.9 μg m⁻³ above background levels. PM_2.5 also showed contribution attributable to the facility (1.7 ± 1.1 μg m⁻³). Optical particle counter analysis of the numerical size distributions showed bimodal distributions for both the upwind and downwind conditions, with maximums around 2.5 μm and below the minimum quantified diameter of 0.3 μm. The distributions showed increased numbers of coarse particles (PM₁₀) during periods when wind transport came from the barns, but the differences were not statistically significant at the 95% confidence level. The PM₁₀ aerosols showed statistically increased concentrations of sulfate, nitrate, ammonium, calcium, organic carbon, and elemental carbon when the samplers were downwind from the pig barns. Organic carbon was the major constituent of the barn-impacted particulate matter in both sub-micron (54%) and coarse size (20%) ranges. The AMS PM₁ chemical speciation showed similar species increases, with the exception of and Ca⁺², the latter not quantified by the AMS.     

Source identification of PM2.5 in an arid Northwest U.S. City by positive matrix factorization

Spokane, WA is prone to frequent particulate pollution episodes due to dust storms, biomass burning, and periods of stagnant meteorological conditions. Spokane is the location of a long-term study examining the association between health effects and chemical or physical constituents of particulate pollution. Positive matrix factorization (PMF) was used to deduce the sources of PM_2.5 (particulate matter ≤2.5 μm in aerodynamic diameter) at a residential site in Spokane from 1995 through 1997. A total of 16 elements in 945 daily PM_2.5 samples were measured. The PMF results indicated that seven sources independently contribute to the observed PM_2.5 mass: vegetative burning (44%), sulfate aerosol (19%), motor vehicle (11%), nitrate aerosol (9%), airborne soil (9%), chlorine-rich source (6%) and metal processing (3%). Conditional probability functions were computed using surface wind data and the PMF deduced mass contributions from each source and were used to identify local point sources. Concurrently measured carbon monoxide and nitrogen oxides were correlated with the PM_2.5 from both motor vehicles and vegetative burning.     

Particulate sulfate levels at a rural site in Israel

Ambient particulate sulfate measurements have been intermittently performed at a rural site in Israel over a period of more than two years. Concurrent measurements of ambient pollutants (SO₂, NO–NO_x, and O₃), as well as meteorological data, were also carried out. The daily data included four particulate sulfate samples representing four successive 6 h accumulating periods. The measured concentrations of sulfate ions ranged from a low 2 g m^-3 observed during the winter season to a high of >50 g m^-3 obtained during the summer. Little correlation was obtained between the sulfate concentration and either O₃ or SO₂, although sulfate and O₃ showed a similar diurnal and annual trend. Based on the data distribution and on a photochemical model, it was concluded that a large part of the particulate sulfate observed at the eastern coast of the Mediterranean Sea must be related to long-range transport from distant sources.     

Influence of the atmospheric conditions on PM<Subscript>10</Subscript> concentrations in Poznań, Poland

This study investigates atmospheric conditions’ influence on the mean and extreme characteristics of PM₁₀ concentrations in Poznań during the period 2006–2013. A correlation analysis was carried out to identify the most important meteorological variables influencing the seasonal dynamics of PM₁₀ concentrations. The highest absolute correlation values were obtained for planetary boundary layer height (r = ?0.57), thermal (daily minimum air temperature: r = ?0.51), anemological (average daily wind speed: r = ?0.37), and pluvial (precipitation occurrence: r = ?0.36) conditions, however the highest correlations were observed for temporal autocorrelations (1 day lag: r = 0.70). As regulated by law, extreme events were identified on the basis of daily threshold value i.e. 50 μg m^?3. On average, annually there are approximately 71.3 days anywhere in the city when the threshold value is exceeded, 46.6 % of those occur in winter. Additionally, 83.7 % of these cases have been found to be continuous episodes of a few days, with the longest one persisting for 22 days. The analysis of the macro-scale circulation patterns led to the identification of an easy-to-perceive seasonal relations between atmospheric fields that favour the occurrence of high PM₁₀ concentration, as well as synoptic situations contributing to the rapid air quality improvement. The highest PM₁₀ concentrations are a clear reaction to a decrease in air temperature by over 3 °C, with simultaneous lowering of PBL height, mean wind speed (by around 1 m s^?1) and changing dominant wind directions from western to eastern sectors. In most cases, such a situation is related to the expansion of a high pressure system over eastern Europe and weakening of the Icelandic Low. Usually, air quality conditions improve along with an intensification of westerlies associated with the occurrence of low pressure systems over western and central Europe. Opposite relations are distinguishable in summer, when air quality deterioration is related to the inflow of tropical air masses originating over the Sahara desert.     

Characteristics of organic and elemental carbon in PM2.5 samples in Shanghai, China

Shanghai is the largest industrial and commercial city in China, and its air quality has been deteriorating for several decades. However, there are scarce researches on the level and seasonal variation of fine particle (PM_2.5) as well as the carbonaceous fractions when compared with other cities in China and around the world. In the present paper, abundance and seasonal characteristics of PM_2.5, organic carbon (OC) and elemental carbon (EC) were studied at urban and suburban sites in Shanghai during four season-representative months in 2005–2006 year. PM_2.5 samples were collected with high-vol samplers and analyzed for OC and EC using thermal-optical transmittance (TOT) protocol. Results showed that the annual average PM_2.5 concentrations were 90.3–95.5 μg/m³ at both sites, while OC and EC were 14.7–17.4 μg/m³ and 2.8–3.0 μg/m³, respectively, with the OC/EC ratios of 5.0–5.6. The carbonaceous levels ranked by the order of Beijing > Guangzhou > Shanghai > Hong Kong. The carbonaceous aerosol accounted for  30% of the PM_2.5 mass. On seasonal average, the highest OC and EC levels occurred during fall, and they were higher than the values in summer by a factor of 2. Strong correlations (r = 0.79–0.93) between OC and EC were found in the four seasons. Average level of secondary organic carbon (SOC) was 5.7–7.2 μg/m³, accounting for  30% of the total OC. Strong seasonal variation was observed for SOC with the highest value during fall, which was about two times the annual average.     

Influences of meteorological conditions on interannual variations of particulate matter pollution during winter in the Beijing–Tianjin–Hebei area

To investigate the interannual variations of particulate matter (PM) pollution in winter, this paper examines the pollution characteristics of PM with aerodynamic diameters of less than 2.5 and 10 μm (i.e., PM_2.5 and PM₁₀), and their relationship to meteorological conditions over the Beijing municipality, Tianjin municipality, and Hebei Province—an area called Jing–Jin–Ji (JJJ, hereinafter)—in December 2013–16. The meteorological conditions during this period are also analyzed. The regional average concentrations of PM_2.5 (PM₁₀) over the JJJ area during this period were 148.6 (236.4), 100.1 (166.4), 140.5 (204.5), and 141.7 (203.1) μg m^–3, respectively. The high occurrence frequencies of cold air outbreaks, a strong Siberian high, high wind speeds and boundary layer height, and low temperature and relative humidity, were direct meteorological causes of the low PM concentration in December 2014. A combined analysis of PM pollution and meteorological conditions implied that control measures have resulted in an effective improvement in air quality. Using the same emissions inventory in December 2013–16, a modeling analysis showed emissions of PM_2.5 to decrease by 12.7%, 8.6%, and 8.3% in December 2014, 2015, and 2016, respectively, each compared with the previous year, over the JJJ area.     

Heat island and oasis effects of vegetative canopies: Micro-meteorological field-measurements

Dry-bulb temperature, dew-point, wind speed, and wind direction were measured in and around an isolated vegetative canopy in Davis CA from 12 to 25 October 1986. These meteorological variables were measured 1.5 m above ground along a transect of 7 weather stations set up across the canopy and the upwind/downwind open fields. These variables were averaged every 15 minutes for a period of two weeks so we could analyze their diurnal cycles as well as their spatial variability. The results indicate significant nocturnal heat islands and daytime oases within the vegetation stand, especially in clear weather. Inside the canopy within 5 m of its upwind edge, daytime temperature fell by as much as 4.5 °C, whereas the nighttime temperature rose by 1 °C. Deeper into the canopy and downwind, the daytime drop in temperature reached 6 °C, and the nighttime increase reached 2 °C. Wind speed was reduced by ~ 2 ms^–1 in mild conditions and by as much as 6.7 ms^–1 during cyclonic weather when open-field wind speed was in the neighborhood of 8 ms^–1. Data from this project were used to construct correlations between temperature and wind speed within the canopy and their corresponding ambient, open-field values.With 10 Figures     

Using the OSPM Model on Pollutant Dispersion in an Urban Street Canyon

An observational campaign was conducted in the street canyon of Zhujiang Road in Nanjing city in 2007.Hourly mean concentrations of PM10 were measured at street and roof levels.The Operational Street Pollution Model(OSPM)street canyon dispersion model was used to calculate the street concentrations and the results were compared with the measurements.The results show that there is good agreement between measured and predicted concentrations.The correlation coecient R2 values(R2 is a measure of the correlation of the predicted and measured time series of concentrations)are 0.5319,0.8044,and 0.6630 for the scatter plots of PM10 corresponding to light wind speed conditions,higher wind speed conditions,and all wind speed conditions,respectively.PM10 concentrations tend to be smaller for the higher wind speed cases and decrease rapidly with increasing wind speed.The presentations of measured and modelled concentration dependence on wind direction show fairly good agreement.PM10 concentrations measured on the windward side are relatively smaller,compared with the corresponding results for the leeward side.This study demonstrates that it is possible to use the OSPM to model PM10 dispersion rules for an urban street canyon.     

Turbulent exchange above a pine forest,I: Fluxes and gradients

Measurements of gradients of wind, temperature and humidity and of the corresponding turbulent fluxes have been carried out over a sparse pine forest at Jädra»s in Sweden. In order to ascertain that correct gradient estimates were obtained, two independent measuring systems were employed: one system with sensors at 10 fixed levels on a 51 m tower and another with reversing sensors for temperature and humidity, covering the height interval 23 to 32 m. Turbulent fluxes were measured at three levels simultaneously. Data from three field campaigns: in June 1985, June 1987 and September 1987 have been analyzed. The momentum flux is found on the average to be virtually constant from tree top level, at 20 to 50 m. The average fluxes of sensible and latent heat are not so well behaved. The ratio of the non-dimensional gradients of wind and temperature to their corresponding values under ideal conditions (low vegetation) are both found to be small immediately above the canopy (about 0.3 for temperature and 0.4 for wind). With increasing height, the ratios increase, but the values vary substantially with wind direction. The ratios are not found to vary systematically with stability (unstable stratification only studied). The ratio of the non-dimensional humidity gradient to the corresponding non-dimensional potential temperature gradient (equivalent to k _h /k _w ) is found to be unity for (z – d)/L _v less than about –0.1 and about 1.4 for near neutral stratification, but the scatter of the data is very large.     

PM10 Observed at a Meteorological Station in Beijing: Historical Trend and Implications

Inhalable particles (PM10), with aerodynamic equivalent diameters that are generally 10 micrometers or smaller, are basic pollutants in many areas, especially in northern China, and thus the pollution from PM10 inhalable particulate matter is a growing concern for public health. Independent long-term observations are necessary to evaluate the efficacy of PM10 reduction actions. Variations in the PM10 concentration from 2006 to 2017 at an observation station (NJ) in Beijing were recorded and analyzed. The average value ±1 standard deviation of daily mean PM10 concentrations was 138.8 ±96.1 μg m-3 for 1307 days (accounting for 34.7% of the total days), showing PM10 concentration exceeding the National Ambient Air Quality Standard (NAAQS) 24-h average of 150 μg m-3. Particulate concentration depended upon various meteorological conditions as also observed in this work: at low wind speed (<4 m s-1), the concentrations of PM10 revealed a downward trend with -19 μg m-3 per unit of wind speed, but when wind speed rose (>4 m s-1), the values increased by 49 μg m-3 per unit of wind speed. In Beijing, air masses from northwest China, especially from the Gobi Desert and other desert areas, had net contributions to long-range transport of natural dust, enhancing the PM10 concentrations by up to 29%. Overall, PM10 mass concentration showed a significant downward trend with -8.0 μg/m3/yr from 2006 to 2017. Although with higher fluctuations in recorded data, similar downward trends derived from the ) in 2017 still exceeded the NAAQS standard. The results showed that there is still a long way to go to reduce PM10 in Beijing.     

A numerical investigation of wind speed effects on lake-effect storms

Observations of lake-effect storms that occur over the Great Lakes region during late autumn and winter indicate a high sensitivity to ambient wind speed and direction. In this paper, a two-dimensional version of the Penn State University/National Center for Atmospheric Research (PSU/NCAR) model is used to investigate the wind speed effects on lake-effect snowstorms that occur over the Great Lakes region.Theoretical initial conditions for stability, relative humidity, wind velocity, and lake/land temperature distribution are specified. Nine different experiments are performed using wind speeds ofU=0, 2, 4,..., 16 m s^–1. The perturbation wind, temperature, and moisture fields for each experiment after 36 h of simulation are compared.It is determined that moderate (4–6 m s^–1) wind speeds result in maximum precipitation (snowfall) on the lee shore of the model lake. Weak wind speeds (0U<4 m s^–1) yield significantly higher snowfall amounts over the lake along with a spatially concentrated and intense response. Strong wind speeds (6<U16 m s^–1), yield very little, if any, significant snowfall, although significant increases in cloudiness, temperature, and perturbation wind speed occur hundreds of kilometers downwind from the lake.     

A determination of the CH4, NO x and CO2 emissions from the Prudhoe Bay,Alaska oil development

In this paper we quantify the CH₄, CO₂ and NO _x emissions during routine operations at a major oil and gas production facility, Prudhoe Bay, Alaska, using the concentrations of combustion by products measured at the NOAA-CMDL observatory at Barrow, Alaska and fuel consumption data from Prudhoe Bay. During the 1989 and 1990 measurement campaigns, 10 periods (called events) were unambiguously identified where surface winds carry the Prudhoe Bay emissions to Barrow (approximately 300 km). The events ranged in duration from 8–48 h and bring ambient air masses containing substantially elevated concentrations of CH₄, CO₂ and NO _y to Barrow. Using the slope of the observed CH₄ vs CO₂ concentrations during the events and the CO₂ emissions based on reported fuel consumption data, we calculate annual CH₄ emissions of (24+/–8)×10³ metric tons from the facility. In a similar manner, the annual NO _x emissions are calculated to be (12+/–4)×10³ metric tons, which is in agreement with an independently determined value. The calculated CH₄ emissions represent the amount released during routine operations including leakage. However this quantity would not include CH₄ released during non-routine operations, such as from venting or gas flaring.     

Size distributions of ambient air particles and enrichment factor analyses of metallic elements at Taichung Harbor near the Taiwan Strait

This work attempts to characterize metallic elements associated with atmospheric particulate matter on a dry deposition plate, a TE-PUF high-volume air sampler and a universal air sampler. Dry deposition fluxes of particulates and concentrations of total suspended particulate, fine (PM_2.5) and coarse (PM_2.5–10) particulate matters were collected at Taichung harbor sampling sites from August 2004 to January 2005. Chemical analyses of metallic elements were made using a flame atomic absorption spectrophotometer coupled with hollow cathode lamps. Concentrations of metal elements in the forms of coarse particles and fine particles as well as the coarse/fine particulate ratios were presented. Statistical methods such as correlation analysis, principal component analysis and enrichment factor analysis were performed to compare the chemical components and identify possible emission sources at the sampling sites. Metallic elements of Cu, Zn, Pb, Cr, Ni and Mg had higher EF_crust ratios in winter and spring than in summer and autumn. Diurnal and nocturnal variations of metallic element concentrations in fine and coarse particles were also discussed.     

Observation of wind shear during evening transition and an estimation of submicron aerosol concentrations in Beijing using a Doppler wind lidar

The wind speed and direction measured over six months by a Doppler wind lidar (Windcube-8) were compared with wind cup anemometers mounted on the 325-m Beijing meteorological tower (BMT). Five mountain–plain wind cases characterized by wind direction shear were selected based on the high-frequency (1.1 s) wind profile of the Windcube-8 and analyzed with 1-h mesoscale surface weather charts. Also analyzed was the relationship between in-situ PM₁ (aerodynamic diameter ≤ 1 μm) concentrations measured at 260 m on BMT and the carrier-to-noise ratio (CNR) of the co-located Windcube-8. The results showed that the 10-min averaged wind speed and direction were highly correlated (R = 0.96–0.99) at three matched levels (80, 140, and 200 m). The evening transition duration was 1–3 h, with an average wind speed of 1 m s^–1 at 80 m above the ground. In addition, there was a zero horizontal-wind-speed zone along the wind direction shear line, and in one case, the wind speed was characterized by a Kelvin–Helmholtz gravity wave. The variability of the PM₁ concentrations was captured by the CNR of the Windcube-8 in a fair weather period without the long-range transport of dust.     

Meteorological results of MONSOON-88 expedition (pre-monsoon period)

Mean atmospheric circulation, moisture budget and net heat exchange were studied during a pre-monsoon period (18th March to 3rd May, 1988), making use of the data collected on board Akademik Korolev in the central equatorial and southern Arabian Sea region. The net heat exchange (R _n ) is found to be about 20 W m^–2 for a small area (0–4° N; 55–60° E), 50% less than the dimatological value. The mean value of net radiation (140 W m^–2) is less than the climatological value, which was due to higher cloud amount. The higher SST enhanced both the latent and sensible heat fluxes.The mean atmospheric circulation obtained from the upper air data is quite convincing. The mean exchange coefficient (C _e ) estimated from the moisture budget is about 1.0 × 10^–3 for a wind speed of 4 m s^–1. This value is slightly lower than that obtained by the usual methods.National Institute of Oceanography, RC, 52-Kirlampudi layout, Visakhapatnam — 530 023.India Meteorological Department, Gauhati.     

Near-source particulate emissions and plume dynamics from agricultural field operations

Particulate matter emissions generated by agricultural field preparation and harvesting operations were measured remotely via aerosol lidar and sampled simultaneously with a variety of aerosol point samplers in order to quantify dust plume space and time dynamics and particulate mass and number concentrations. Data for two cotton operations (disking, harvesting) in a flood-irrigated field in New Mexico are presented. Dust plume dynamics varied with boundary layer meteorological conditions, especially atmospheric stability, with plume maximum height significantly lower under stable conditions. Plume tracking indicated little change in plume area with height under unstable conditions and plume movement depended on wind speed and direction. Particle mass distributions indicate approximately 50% of the measured PM₁₀ mass was PM_2.5, significantly higher than previously reported values, possibly due to the near-source nature of the samples collected here. Variability in plume movement matched the variability in short-term wind fluctuations and this variability helps explain why models that utilize long-term averages perform poorly when trying to capture plume dynamics for nonsteady sources such as tractor operations.     

Atmospheric ionic species in PM2.5 and PM1 aerosols in the ambient air of eastern central India

This study elucidates the characteristics of ambient PM_2.5 (fine) and PM₁ (submicron) samples collected between July 2009 and June 2010 in Raipur, India, in terms of water soluble ions, i.e. Na⁺, NH ₄ ⁺ , K⁺, Mg²⁺, Ca²⁺, Cl^?, NO ₃ ^? and SO ₄ ^2? . The total number of PM_2.5 and PM₁ samples collected with eight stage cascade impactor was 120. Annual mean concentrations of PM_2.5 and PM₁ were 150.9?±?78.6 μg/m³ and 72.5?±?39.0 μg/m³, respectively. The higher particulate matter (PM) mass concentrations during the winter season are essentially due to the increase of biomass burning and temperature inversion. Out of above 8 ions, the most abundant ions were SO ₄ ^2? , NO ₃ ^? and NH ₄ ⁺ for both PM_2.5 and PM₁ aerosols; their average concentrations were 7.86?±?5.86 μg/m³, 3.12?±?2.63 μg/m³ and 1.94?±?1.28 μg/m³ for PM_2.5, and 5.61?±?3.79 μg/m³, 1.81?±?1.21 μg/m³ and 1.26?±?0.88 μg/m³ for PM₁, respectively. The major secondary species SO ₄ ^2? , NO ₃ ^? and NH ₄ ⁺ accounted for 5.81%, 1.88% and 1.40% of the total mass of PM_2.5 and 11.10%, 2.68%, and 2.48% of the total mass of PM₁, respectively. The source identification was conducted for the ionic species in PM_2.5 and PM₁ aerosols. The results are discussed by the way of correlations and principal component analysis. Spearman correlation indicated that Cl^? and K⁺ in PM_2.5 and PM₁ can be originated from similar type of sources. Principal component analysis reveals that there are two major sources (anthropogenic and natural such as soil derived particles) for PM_2.5 and PM₁ fractions.     

Characterization and source identification of trace elements in PM2.5 from Mira Loma, Southern California

Concentrations of thirty-five trace elements in ambient fine particulate matter (PM_2.5) were measured from September 2001 to January 2002 in Mira Loma, a semi-urban area in southern California. The most abundant species were found to be sulfur (S; 23% of the total trace element concentration), followed by Si, Fe, Ca, and Al (soil-related elements; 51% of the total). In general, total trace element concentrations were found to be significantly higher for the drier months of September and October, compared to December and January. Factor analysis, enrichment factor (EF) analysis, and ratio analysis (Al/Zn) revealed a significant contribution of soil-related sources to the ambient trace elements for PM_2.5 in the study area. Other important contributors to the trace elements in ambient PM_2.5 in Mira Loma included motor vehicle-related emissions (brake pads, lubricant oils, gasoline, and diesel combustion), secondary sulfates, sea salts, and biomass burning. The influence of sea salts on the study area was identified using a backward trajectory analysis.     

不同降水强度对PM2.5的清除作用及影响因素

云和降水过程是大气污染物的重要清除途径,但由于降水过程和大气污染颗粒物本身的复杂性,目前降水过程对大气污染物的清除机制及影响因素有待深入研究。该文利用2014年3月—2016年7月在北京地区连续观测的PM_2.5和降水数据,研究了不同降水强度对PM_2.5的清除率,以及雨滴谱、风速和降水持续时间对PM_2.5清除率的影响。研究表明:降水强度越大,对PM_2.5清除效率越高。小雨、中雨和大雨对PM_2.5清除率平均值分别为5.1%,38.5%和50.6%。小雨不但对PM_2.5的清除率最低,而且对PM_2.5的清除效果也存在很大差异,约50%的小雨个例中PM_2.5质量浓度出现减小情况,而另外50%的小雨个例中,PM_2.5质量浓度出现增加情况。在持续时间长或地面风速增大的情况下,小雨也表现出较高的清除率。在中雨和大雨情况下,PM_2.5质量浓度均出现明显减小情况。但降水持续时间和风速对中雨和大雨的清除率影响较小,这是由于中雨和大雨一般在较短时间内即可清除大部分PM_2.5,因此,对降水的持续时间和风速大小不敏感。     

Etude experimentale d'une relation entre le coefficient de frottement et le facteur de rafales en regime de vent faible et au-dessus d'une surface d'eau

In usual aerodynamic bulk formulas, the drag coefficient C _d has been best estimated in the 5 to 16 m s^–1 range of mean wind velocity; a value of 1.3 × 10^–3 is often considered for operational use. However, in the 0 to 5 m s^–1 range of mean wind velocity, corresponding to meteorological conditions of very light wind, experimental results have not resulted in any convincing agreement between various authors (Hicks et al., 1974; Wu, 1969; Kondo and Fujinawa, 1972; Mitsuta, 1973; Brocks and Krugermeyer, 1970).In the present paper, the drag coefficient is experimentally determined in conditions of very light wind and limited fetch (about 250 m). Due to this limited fetch, we have to be cautious in the extrapolation of our results to other sites. Nevertheless, some of experimental results are worth describing, considering the paucity of data in light wind conditions.Mean value and standard deviation (respectively 1.84 × 10^–3 and 1.24 × 10^–3) are obtained from 70 runs of 10-min duration. Mean wind velocities observed at 2 m above water surface are found to lie between 1.2 and 3.6 m s^–1. Whereas this mean value is in fair agreement with C _{d 10} = 1.3 × 10^–3, usually given for the 5 to 16 m s^–1 range (Kraus, 1972), the above value for the standard deviation seems too large to be left without further analysis.A more exhaustive analysis of the 70 values obtained for C _d shows that it depends on a parameter characteristic of longitudinal fluctuations of the wind velocity. A similar idea was put forward earlier by Kraus (1972). Relations between the drag coefficient and wind fluctuations may be tentatively given by: % MathType!MTEF!2!1!+-% feaafiart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaam4qamaaBa% aaleaacaWGKbGaaGOmaaqabaGccqGH9aqpdaqadaqaaiabgkHiTiaa% igdacaGGUaGaaGimaiaaiEdacqGHRaWkcaaIXaGaaGinaiaac6caca% aIZaGaaGinamaalaaabaGaeq4Wdm3aaSbaaSqaaiaadwhacaGGNaaa% beaaaOqaaaaaaiaawIcacaGLPaaaruqqYLwySbacfaGaa8hEaiaa-b% cacaaIXaGaaGimamaaCaaaleqabaGaeyOeI0IaaG4maaaakiaabcca% caqGGaGaaeiiaiaabccacaqGXaGaaeOlaiaabAdacaqGGaGaaeyBai% aabccacaqGZbWaaWbaaSqabeaacaqGTaGaaeymaaaakiabgsMiJkqa% dwhagaqeamaaBaaaleaacaaIYaaabeaakiabgsMiJkaaiodacaGGUa% GaaGOnaiaab2gacaqGGaGaae4CamaaCaaaleqabaGaaeylaiaabgda% aaaaaa!634E!\[C_{d2} = \left( { - 1.07 + 14.34\frac{{\sigma _{u'} }}{{}}} \right)x 10^{ - 3} {\text{ 1}}{\text{.6 m s}}^{{\text{ - 1}}} \leqslant \bar u_2 \leqslant 3.6{\text{m s}}^{{\text{ - 1}}} \] and % MathType!MTEF!2!1!+-% feaafiart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaam4qamaaBa% aaleaacaWGKbGaaGOmaaqabaGccqGH9aqpdaqadaqaaiabgkHiTiaa% iodacaGGUaGaaGioaiaaiAdacqGHRaWkcaaIZaGaaiOlaiaaiodaca% aI2aGaam4raaGaayjkaiaawMcaaerbbjxAHXgaiuaacaWF4bGaa8hi% aiaaigdacaaIWaWaaWbaaSqabeaacqGHsislcaaIZaaaaOGaaeilaa% aa!4B42!\[C_{d2} = \left( { - 3.86 + 3.36G} \right)x 10^{ - 3} {\text{,}}\] where _u/\-u ₂ and G, respectively, represent the standard deviation of u normalized with \-u ₂ and the longitudinal gust factor quoted in Smith (1974).We have established a relationship between these fluctuation parameters and the stability as given by a bulk layer Richardson number (between 0 and 2 m). These relations are given by: % MathType!MTEF!2!1!+-% feaafiart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaSaaaeaacq% aHdpWCdaWgaaWcbaGaamyDaiaacEcaaeqaaaGcbaGabmyDayaaraWa% aSbaaSqaaiaaikdaaeqaaaaakiabg2da9iaaicdacaGGUaGaaGymai% aaikdacqGHRaWkcaaIZaGaaiOlaiaaiIdacaaI1aGaaeiiaiaabkfa% caqGPbWaaSbaaSqaaiaabcdacaqGTaGaaeOmaaqabaaaaa!4802!\[\frac{{\sigma _{u'} }}{{\bar u_2 }} = 0.12 + 3.85{\text{ Ri}}_{{\text{0 - 2}}} \] and G=1.35+14.56 Ri_0–2. The increase in gustiness with stability is in qualitative agreement with Goptarev (1957)'s experimental results.In spite of the high-level correlation between C _d and _u/\-u ₂(G) on the one hand and between _u/\-u ₂(G) and Ri_0–2on the other hand, we found a poor relationship between C _d and Ri_0–2. It is worth noting too that the trend observed here for C _d to increase with stability is in complete disagreement with the usual theoretical expectation for C _d to decrease with increasing layer stability above water.

---

---

E.R.A. du C.N.R.S. n 259.