Published online 5 July 2005
Published in J Environ Qual 34:1260-1269 (2005)
DOI: 10.2134/jeq2003.0348
© 2005 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
TECHNICAL REPORTS
Atmospheric Pollutants and Trace Gases
Agricultural Dust Production in Standard and Conservation Tillage Systems in the San Joaquin Valley
J. B. Baker*,
R. J. Southard and
J. P. Mitchell
Department of Vegetable Crops and Weed Science, University of California, Davis, CA 95616
* Corresponding author (jbbaker{at}ucdavis.edu)
Received for publication September 7, 2004.
 |
ABSTRACT
|
|---|
The negative health effects of repeated dust exposure have been well documented. In California's San Joaquin Valley, agricultural operations may contribute substantially to airborne particulates. We evaluated four management systems to assess impacts on dust production and soil properties for a cotton (Gossypium hirsutum L.)–tomato (Lycopersicon esculentum Mill.) rotation: standard tillage with (STCC) and without (STNO) cover crop, and conservation tillage with (CTCC) and without (CTNO) cover crop. Gravimetric analysis of total dust (TD, <100-µm aerodynamic diameter) and respirable dust (RD, 4-µm aerodynamic diameter) samples collected in the plume generated by field implements showed that dust concentrations for CTNO treatments were about one-third of their STNO counterparts for both cumulative TD and RD measured throughout the two-year rotation, primarily due to fewer in-field operations. The TD and RD production for STNO and STCC was comparable, whereas the CTCC system produced about twice as much TD and RD as CTNO. Energy dispersive spectroscopy (EDS) analyses showed absolute increases of 8 and 39% organic fragments in STCC and CTCC over STNO and CTNO, respectively, while organic fragments in the TD increased by 6% in both cover crop treatments. Soil C content was positively correlated with clay content and increased by an average of 0.12 and 0.07% in the cover crop and non-cover crop treatments, respectively, although soil C for each treatment showed a distinct response to a field texture gradient. While dust emissions show an immediate decrease due to fewer field operations for the conservation tillage treatments, long-term sampling is necessary to determine the effects that increased aggregation through organic matter additions may have on dust production.
Abbreviations: CTCC, conservation tillage with cover crop • CTNO, conservation tillage no cover crop • PM, particulate matter • RD, respirable dust • SOM, soil organic matter • STCC, standard tillage with cover crop • STNO, standard tillage no cover crop • TD, total dust
|
INTRODUCTION
|
|---|
CONSERVATION TILLAGE PRACTICES have seen increased use throughout the United States in recent years, especially in the Midwest where wind and water erosion are often a problem. The percentage of planted land in the United States, managed in conservation tillage, increased from 26% in 1990 to 37% in 2000 (Conservation Technology Information Center, 2002). In California, and especially in the San Joaquin Valley, one of the world's most productive agricultural regions, the acreage under CT practices was as little as 16% of total farm acreage in 2002, compared with 41% in the Midwest (Conservation Technology Information Center, 2002). Implementing CT practices can lead to both economic and production quality benefits, as well as having positive environmental impacts (Ashraf et al., 1999; Reicosky and Lindstrom, 1995).
The Natural Resources Conservation Service (NRCS) defines CT as crop cultural operations that maintain at least 30% cover of the soil surface by plant residue at the time of planting. Conservation tillage can incorporate a range of management practices, from no-till to ridge- and strip-till cultivation to minimum tillage systems that restrict equipment traffic to dedicated zones. Special CT field equipment can often perform the equivalent functions of several standard implements, reducing the necessity for multiple passes through the field. Crops currently grown under CT management in the United States include cotton, corn, grains, tomatoes, and fresh market produce (Conservation Technology Information Center, 2002).
There are many benefits associated with CT management practices. Economic incentives are associated with reduced fuel, labor, and equipment costs due to fewer field passes. Yields are often comparable with those from conventional practices, and profit margins can be increased through reduced operational costs. Reduced tillage can limit loss of CO2 to the atmosphere by preventing exposure and oxidation of soil organic matter (SOM) (Reicosky and Lindstrom, 1995). Soil properties including organic matter content, aggregation, water storage, and infiltration can be improved by implementing conservation tillage practices (Cambardella and Elliott, 1993, 1994; Ashraf et al., 1999). Dust production may in turn be reduced by both limiting the number of passes through a field and by changing key soil properties, such as increasing water-holding capacity and aggregate stability, both due to SOM accumulation. Conservation tillage has been shown to be effective at controlling erosion and dust production in the Columbia Plateau by increasing surface residue and roughness (Stetler and Saxton, 1996). Management practices such as timing tillage operations to optimize soil moisture content (Clausnitzer and Singer, 1996) or modifying equipment (Southard et al., 1997) can also decrease dust emissions.
Reducing agricultural dust production has both environmental and human health implications. Numerous studies have linked negative health effects to repeated exposure to small airborne particulate matter (particulate matter < 10-µm aerodynamic diameter [PM10] and particulate matter < 2.5-µm aerodynamic diameter [PM2.5]) (Pope, 1991; Schwartz et al., 1993). Diseases linked to dust inhalation include asthma, pulmonary fibrosis, and lung cancer (Doelman et al., 1990; Ross et al., 1993; Guthrie, 1995). Allergic responses such as asthma are generally associated with organic dust exposure. Nonallergic responses, such as bronchitis and chronic obstructive airways disease, are generally linked to inorganic dust exposure from agricultural sources (Schenker, 2000). In 2002, only 1 of the 58 California counties was in compliance with state air quality standards for PM10 (California Air Resources Board, 2003). In the San Joaquin Valley, a prominent agricultural region, many of the airborne particulates may be associated with agricultural practices including tilling, disking, and cultivating. These practices have recently (as of January 2004) become subject to air pollution standards by the California Air Resources Board (2004).
We compared the quantity and composition of dust produced from four different treatments: standard tillage with (STCC) and without (STNO) cover crop, and conservation tillage with (CTCC) and without (CTNO) cover crop. These studies constituted a portion of a larger project whose goals were to compare conservation and standard tillage in terms of farm productivity and profits, soil water storage and crop water availability, pest and crop management requirements, dust production, and soil quality indicators.
|
MATERIALS AND METHODS
|
|---|
The field study site (Fig. 1)
was located at the University of California's West Side Research and Extension Center (WSREC) in Five Points, CA (36°20'29'' N, 120°7'14'' W). An 85- by 365-m field in a map unit of Panoche clay loam (fine-loamy, mixed, superactive, thermic Typic Haplocambids) (Arroues, 2000) was dedicated to the project, and a uniform barley (Hordeum vulgare L.) crop was grown over the entire field before the commencement of field treatments. The field was divided into two halves; a tomato–cotton rotation was used in one half, and a cotton–tomato rotation was pursued in the other half. Management treatments of standard tillage without cover crop (STNO), standard tillage with cover crop (STCC), conservation tillage without cover crop (CTNO), and conservation tillage with cover crop (CTCC) were replicated four times on each half of the field (Fig. 1). The cover crop was a mixture of triticale (Triticosecale), rye (Secale cereale L.), and vetch (Vicia sativa L.). The standard tillage operations attempted to follow as closely as possible common local practices, including fall bed preparations such as disking, chiseling, bed listing, and power incorporating, used by farmers in the vicinity of the field station. Farms in the area are typically large-acreage family farms with an average size of about 3200 ha (Mitchell et al., 2001). Common crops include cotton and tomatoes during the summer, and lettuce and garlic during the winter. Conservation tillage operations were planned to minimize soil disturbances and to create dedicated traffic lines to reduce soil compaction. Conservation tillage beds created at the start of the project were left intact after each growing season, as opposed to ST beds, which were destroyed and reformed each year.
View larger version (21K):
[in this window]
[in a new window]
|
Fig. 1. Location of West Side Research and Extension Center (WSREC) and field layout of treatment plots with position, in meters, to the center of each plot from the south end of the field. STNO, standard tillage no cover crop; STCC, standard tillage with cover crop; CTNO, conservation tillage no cover crop; CTCC, conservation tillage with cover crop.
|
|
Dust samples were collected during every field operation with portable battery-powered vacuum pumps manufactured by Gilian (Wayne, NJ). One pump per sample (except for disking 19 and 20 Oct. 2000, which had two pumps per sample) was placed at a constant location on each field implement in the plume of dust generated by the implement. Pumps were calibrated with a flow meter before and after sampling to ensure uniform pump flow and operating conditions. Total dust (TD, <100-µm aerodynamic diameter) and respirable dust (RD) samples were collected during tillage from each plot on preweighed PTFE (polytetrafluoroethylene; Teflon) membrane filters at a flow rate of 2.2 L min–1. The RD samples were obtained using a cyclone (BGI Incorporated, Waltham, MA) in which the particles smaller than 4 µm were kept suspended while the larger particles settled out and were not sampled (Fig. 2)
. The samplers were attached to each field implement about 0.4 m above the ground surface, with the exception of the cotton harvester samples, which were placed at approximately 2 m above the ground. Sampling duration was noted for each measurement so that the concentration of dust measured could be calculated, thus allowing dust production from the tillage systems and different operations to be compared. Our results reflect in-the-field dust concentrations and cannot be used directly to indicate PM concentrations relative to USEPA air quality standards (USEPA, 2002). Soil samples for field water content were taken at each dust sampling occasion from a depth of 0 to 15 cm near the center of each treatment plot. Gravimetric water content (
g) was determined after oven-drying at 105°C. Weather data (temperature, precipitation, wind speed and direction, and relative humidity) were obtained from the California Irrigation Management Information System's (CIMIS) Five Points station, located at WSREC, for each sampling date.
View larger version (140K):
[in this window]
[in a new window]
|
Fig. 2. Battery-operated Gilian personal sampling pumps. The pump on the left contains a Teflon filter in a filter holder cassette for collecting total dust; the pump on the right contains a filter holder cassette with a cyclone attached for sampling respirable dust.
|
|
The PTFE filters were weighed on a Cahn (Paramount, CA) electrobalance in a climate-monitored room. X-ray diffraction (XRD) patterns of dust samples were obtained on an Inel (Artenay, France) diffractometer with a position sensitive detector after sonicating the PTFE filters in 2-propanol and transferring the dust to a silver membrane filter. Soil samples for particle size analysis and carbon content were collected each fall and spring from the center of each treatment plot at two depths, 0 to 15 cm and 15 to 30 cm. Particle size distribution was measured by the pipette method (Jackson, 1975) on each 0- to 15-cm soil sample. Aliquots of the <2- and <10-µm fractions were obtained from each sample, which were then subjected to treatments of K and heating to 350 and 550°C, and Mg and Mg plus glycerol. Patterns of XRD for the <2- and <10-µm fractions of the soil were obtained on a Diano (Medford, MA) 8000 diffractometer using Cu K
radiation. Dust elemental analysis was obtained on a FEI XL30-SFEG high-resolution scanning electron microscope with an EDAX (Hillsboro, OR) Phoenix energy dispersive X-ray spectroscopy (EDS) system, capable of analyzing for elements of atomic number 6 (C) and greater. Particle counts were obtained from the EDAX software by automated comparison and manual verification of particle EDS spectra to a mineral library generated by Rebecca Domingo-Neumann at UC Davis (unpublished data, 2002–2003). Total C analyses of soil samples were performed on a Carlo-Erba (Milan, Italy) 1500 C/N analyzer.
An analysis of covariance (ANCOVA) model in SAS statistical software (SAS Institute, 2004) using standard least squares regression was used to predict TD and RD concentrations from six factors: tillage treatment (STNO, STCC, CTNO, or CTCC), operation (e.g., disk, chisel, plant cover crop), crop rotation (cotton or tomato), soil moisture, clay content, and a tillage-by-operation interaction. All data were log-transformed to correct for a non-normal distribution, then back-transformed after analysis to obtain an adjusted mean and 95% confidence limits. Comparisons of adjusted dust measurements were made using a Student's t test.
|
RESULTS AND DISCUSSION
|
|---|
The results of the ANCOVA model fit for the total dust size fraction indicated that each factor, except for moisture and clay content, was significant at the 0.05 confidence level (Table 1). Although not significant at the 0.05 confidence level, moisture and clay content still appeared to explain some of the model variation in dust concentration, but were overwhelmed by the other factors in the model. For respirable dust, each factor, except for clay content and the tillage-by-operation interaction, was significant at the 0.05 confidence level. The model fit was highly significant for both TD and RD; the null hypothesis that dust concentration was independent of the model factors was rejected in both cases.
Cumulative dust concentrations for each of the treatments were calculated by summing the nonadjusted mean values of all operations contributing to a particular treatment over a complete cotton–tomato rotation. Total dust concentrations were 2716 µg L–1 for STNO, 2637 µg L–1 for STCC, 921 µg L–1 for CTNO, and 1643 µg L–1 for CTCC. Cumulative respirable dust concentrations were 450 µg L–1 for STNO, 422 µg L–1 for STCC, 159 µg L–1 for CTNO, and 314 µg L–1 for CTCC. Statistical analyses could not be performed for these data because in taking the mean for each operation performed in a particular treatment, the sample number was effectively reduced to one. Each treatment had variations in the number of component operations and in the number of measurements contributing to an operation, so data could not be directly compared, and the adjusted means generated by the ANCOVA model were necessary to compare among treatment and operation. Nonetheless, it seems reasonable that the general trends indicated by the cumulative dust numbers (STNO and STCC produced comparable dust, CTNO produced about one-third and CTCC produced about two-thirds the dust of STNO and STCC for both TD and RD) were still valid since dust was measured for every operation performed.
Dust concentrations, in the field, for the four treatments (STNO, STCC, CTNO, and CTCC) are summarized in Table 2 (total dust) and Table 3 (respirable dust). All treatments received one complete cotton–tomato rotation. Dust concentrations depended on the type of operation and environmental conditions. Wind speed was relatively constant, with speeds of 1.8 m s–1 or less on all sampling dates, as measured at the Five Points CIMIS weather station. Wind direction was generally from the northwest. Since the samplers were placed directly in the dust plume generated by the implement, and samples were collected for the entire duration of the operation on the plot, the low measured wind speeds should have had little effect on variations in the amount of dust collected among treatments and sampling days. We did not measure atmospheric instability and did not attempt to relate our measurements to ambient air quality standards for locations downwind of the field. The relative values of the measurements are useful for comparison purposes among treatments or operations, and should not be greatly affected by variations in atmospheric stability among sampling dates since the samples were collected directly in the dust plume generated by the implement. Soil moisture content ranged from 0.01 to 0.22 g H2O g–1 soil, and varied with season, time to last irrigation, clay content, and treatment. Each moisture measurement was associated with a specific dust measurement and sampling date and was accounted for in the ANCOVA model.
Tillage System Effects (Standard vs. Conventional Tillage)
The CT treatments produced much less dust compared with ST treatments due to a decreased number of field operations. The CTNO treatment used the fewest field operations and produced the least dust. For cumulative dust production over the two-year rotation, CTNO produced about one-third the TD and RD of STNO; CTCC produced about two-thirds the TD and three-fourths the RD of STCC. The major reductions in dust production for the CT treatments originated from limited preplanting bed preparation operations (no bed preparation for CTNO), elimination of the two dustiest operations (disking and power incorporating), and limited in-season cultivation. Harvest and planting operations together produced similar dust concentrations for all treatments except CTNO, which produced about half as much dust. The major difference between CTNO and CTCC was in bed preparation, which involved planting and chopping the cover crop for CTCC. When comparing operations that were common to all four treatments, two of the operations, cultivating tomatoes and transplanting tomatoes, yielded increased total dust concentrations for the CT treatments. These operations disturb the soil surface, and the increase compared with ST may be due to the large amount of surface residue (not incorporated) in the CT treatments. In these instances, organic matter may constitute a large fraction of the dust mass (Table 4). Another operation common to all treatments, the cotton harvest, which did not disturb the soil surface, produced comparable dust concentrations for all treatments.
View this table:
[in this window]
[in a new window]
|
Table 4. Percent organic fragments in dust determined by scanning electron microscope (SEM) energy-dispersive analysis by X-rays (EDAX).
|
|
Cover Crop Effects (No Cover Crop vs. Cover Crop)
Both total and respirable dust concentrations for STCC and STNO were similar, even though there were more field operations for STCC. Incorporation of the cover crop in STCC may aid in stabilizing soil structure by the addition of SOM. Conservation tillage with cover crop produced twice as much dust as CTNO. Much of this can be accounted for in the fall cover crop planting and management operations, but many of the operations common to both CTNO and CTCC produced more respirable dust in CTCC. This may be due to the increased organic component of the dust for CTCC (Table 4).
Cover crop treatments significantly increased the proportion of organic fragments in the dust (Table 4, Fig. 3)
. Inorganic constituents were a mixture of mostly layer silicates (Fig. 4) with some feldspar and quartz. Both cover crop treatments had relative increases in organic fragments of about 6% over corresponding non-cover crop treatments in the TD. In the RD fraction, STCC showed an 11% absolute increase in organic fragments compared with STNO, while CTCC showed a 44% absolute increase over CTNO. The cover crop was incorporated into the soil in the STCC treatment, but it was left as surface residue in the CTCC treatment. This may account for the difference in increases in organic fragments between NO and CC treatments for the ST and CT systems. Conservation tillage with cover crop had the highest percentage of organic fragments of all treatments in both TD and RD, with 20 and 49% organic particles in the TD and RD, respectively. Figures 3a and 3b show examples of respirable dust back-scattered electron (BSE) images and particle identifications from the STNO and CTCC treatments, with accompanying spectra for a layer silicate (Fig. 4a) and an organic fragment (Fig. 4b) from the CTCC sample. Although the health implications of an increased organic constituent in the dust are not clear, the increased organic matter may lead to an increased allergenic response in agricultural workers (Schenker, 2000).
View larger version (145K):
[in this window]
[in a new window]
|
Fig. 3. Back-scattered electron (BSE) images of respirable dust (RD) from tomato cultivation. The light-colored background is the silver membrane filter used to mount the dust for analysis. (a) Standard tillage no cover crop (STNO) treatment. 1, Organic fragment; 2, silver filter; 3, layer silicate; 4, layer silicate; 5, silver filter; 6, silver filter; 7, layer silicate; 8, Na plagioclase; 9, layer silicate; 10, quartz; 11, layer silicate. (b) Conservation tillage with cover crop (CTCC) treatment. 1, Na plagioclase; 2, organic fragment; 3, layer silicate; 4, layer silicate; 5, organic fragment; 6, layer silicate; 7, organic fragment.
|
|
View larger version (22K):
[in this window]
[in a new window]
|
Fig. 4. Energy-dispersive analysis by X-rays (EDAX) spectra of respirable dust (RD) particles from Fig. 3b. (a) Layer silicate particle corresponding to Particle Number 3. (b) Organic fragment corresponding to Particle Number 2.
|
|
Mineralogy
X-ray diffraction data (not shown) indicated similar mineralogy across the field, consistent with the source of mixed alluvium, mostly from the central Coast Ranges. Diffractograms of TD and RD (not shown) also indicated similar mineralogy to the source soil, analogous to the results obtained by Clausnitzer and Singer (1999), who demonstrated that the mineralogy of the RD fraction collected in the field was virtually identical to the <10-µm fraction of the source soil, and that no significant sorting of the particles occurred while suspended.
Soil Carbon and Texture Effects
Soil particle size analysis showed a distinct texture gradient, plotted as the percent clay-sized particles, from south to north across the field (Fig. 5)
. Textures varied from clay loam (32% clay, 33% silt, 35% sand) at the south end (13 m) to sandy clay loam (23% clay, 23% silt, 54% sand) at the north end (360 m). Although the soil is mapped as Panoche clay loam, our data indicated a variation from the named soil phase within the field and demonstrate the natural variability inherent in soils at this level of mapping. The texture gradient across the field complicated our interpretation of the soil properties–dust production relationship somewhat, since soil texture is a major factor determining many soil properties. Porosity, water-holding capacity, aggregation, organic matter content, and the proportion of particles that are of "dust" size (<100 µm for TD and 4 µm for RD) are all related to particle size distribution. Research by Carvacho et al. (2001) indicates that clay content (<2-µm diameter), rather than sand or silt content, provides the best indicator of the potential of the soil to produce PM10 dust in the San Joaquin Valley. Nonetheless, the textural gradient does not affect our interpretation of the cumulative dust production from the tillage systems since all combinations of treatments occurred across the field during the crop rotation. Additionally, the ANCOVA analysis showed that texture had relatively less effect than operation or treatment on dust production.
We observed trends in total soil C percentage with the field texture gradient at 0 to 15 cm for all sampling dates. Soil C contents were higher at the south end of the field, which had higher clay percentages. This trend was observed for pooled data over all the treatments (not shown), but was more pronounced when the treatments were separated (Fig. 6)
. From November 1999 to November 2001, soil C content increased for both cover crop treatments, but the slope of the trend lines changed. Statistical analyses (JMP statistical software; SAS Institute, 2004) illustrate that year and clay content were significant predictors of carbon content at the 0.05 confidence level (Table 5). Although not significant at the 0.05 level, p values for the comparison of the slopes of the 1999 and 2001 trendlines indicated that the slopes for the STCC, CTNO, and CTCC treatments were changing with time. In fall 1999 (baseline sampling), each treatment showed a fairly uniform distribution of soil C across the field. In fall 2001, STCC showed the smallest difference in percent C across the field, perhaps because the incorporation of large amounts of cover crop material resulted in a higher overall C content, which masked the effects of clay content. In the CT treatments for fall 2001, the slopes of the trend lines were steeper, indicating a greater disparity among percent C across the field. The decreased disturbances for CT compared with ST may have accentuated the effects of the clay content's influence on percent C since organic matter was left as surface residue and not incorporated. Increased C in the STNO treatment was attributed to crop residues incorporated after harvest and greater biomass production in cotton and tomato crops than in the previous fallow cycle; the slope of the trend line did not change. Increased soil C in the cover crop treatments was reflected in the increased percentage of organic fragments from EDAX particle counts of the dust samples from these treatments (Table 4). Leaving the cover crop as surface residue versus incorporation into the soil may have had an effect on the percentage of organic fragments in the dust; incorporation of residue may stabilize and protect particulate organic matter and lead to increased aggregate stability (Baker, 2004).
View larger version (24K):
[in this window]
[in a new window]
|
Fig. 6. Soil carbon vs. clay content, 0- to 15-cm sampling depth. November 1999 data are baseline samples before applying treatments. (a) Standard tillage no cover crop (STNO). (b) Standard tillage with cover crop (STCC). (c) Conservation tillage no cover crop (CTNO). (d) Conservation tillage with cover crop (CTCC).
|
|
View this table:
[in this window]
[in a new window]
|
Table 5. Statistical analyses for Fig. 6, Soil carbon versus clay content, 0- to 15-cm sampling depth. The year-by-clay content interaction is equivalent to the slope of the trendlines in Fig. 6.
|
|
In summary, both total and respirable dust concentrations, in the field, were significantly reduced in the conservation tillage treatments compared with standard tillage, mainly due to fewer in-field operations. There was an increased organic constituent in the respirable dust in the cover crop treatments. The potential health effect of increased organic matter in the dust is not known, although there may be the potential for increased allergic responses in agricultural workers (Schenker, 2000). Thus, some benefits of reduced dust by the CT approach may be offset somewhat by an increased organic fraction in the dust from the CC treatment. We did not measure PM10 or PM2.5 at locations upwind or downwind from our field sites, so the effects of the CT systems on ambient air quality in relation to USEPA air quality standards are not completely clear. Nonetheless, it is reasonable to assume that reduced dust in the field would translate to reduced ambient dust if CT practices were adopted widely. At this point, it is clear that the reduced dust is due largely to a reduction in the number of field operations. Continued data collection is necessary to determine the effects of changes in dynamic soil properties, such as soil aggregation and SOM content, on dust production.
|
ACKNOWLEDGMENTS
|
|---|
Many thanks to Rebecca Domingo-Neumann, dust guru of the pedology laboratory at UC Davis, for invaluable assistance with the SEM and dust XRD analyses; and to Jaime Solorio, Ed Scott, and the rest of the staff at WSREC for their untiring efforts in the field.
|
REFERENCES
|
|---|
- Arroues, K. 2000. Classification and correlation of the soils of Fresno County, western part. USDA-NRCS, Washington, DC (in press).
- Ashraf, M., C.H. Pearson, D.G. Westfall, and R. Sharp. 1999. Effect of conservation tillage on crop yields, soil erosion, and soil properties under furrow irrigation in western Colorado. Am. J. Alternative Agric. 14:85–92.
- Baker, J.B. 2004. Agricultural dust production and dynamic soil properties in standard and conservation tillage systems in the San Joaquin Valley, California. M.S. thesis. Univ. of California, Davis.
- California Air Resources Board. 2003. State area designations map: Particulate matter (PM10) [Online]. Available at www.arb.ca.gov/desig/adm/s_pm10.htm (verified 30 Mar. 2005). CARB, Sacramento.
- California Air Resources Board. 2004. California air pollution control laws [Online]. Available at www.arb.ca.gov/bluebook/bb04/caair/caair.htm (verified 30 Mar. 2005). CARB, Sacramento.
- Cambardella, C.A., and E.T. Elliott. 1993. Carbon and nitrogen distribution in aggregates from cultivated and native grassland soils. Soil Sci. Soc. Am. J. 57:1071–1076.[Abstract/Free Full Text]
- Cambardella, C.A., and E.T. Elliott. 1994. Carbon and nitrogen dynamics of soil organic matter fractions from cultivated grassland soils. Soil Sci. Soc. Am. J. 58:123–130.[Abstract/Free Full Text]
- Carvacho, O.F., L.L. Ashbaugh, M.S. Brown, and R.G. Flocchini. 2001. Relationship between San Joaquin Valley soil texture and PM10 emission potential using the UC Davis Dust Resuspension Test Chamber. Trans. ASAE 44:1603–1608.
- Clausnitzer, H., and M.J. Singer. 1996. Respirable-dust production from agricultural operations in the Sacramento Valley, California. J. Environ. Qual. 25:877–884.[Abstract/Free Full Text]
- Clausnitzer, H., and M.J. Singer. 1999. Mineralogy of agricultural source soil and respirable dust in California. J. Environ. Qual. 28:1619–1629.[Abstract/Free Full Text]
- Conservation Technology Information Center. 2002. 2002 National crop residue management survey: A survey of tillage system use by crops and acres planted. CTIC, West Lafayette, IN.
- Doelman, C.J.A., R. Leurs, W.C. Oosterom, and A. Bast. 1990. Mineral dust exposure and free radical-mediated lung damage. Exp. Lung Res. 16:41–55.[ISI][Medline]
- Guthrie, G.D. 1995. Eat, breathe, and be wary: Mineralogy in environmental health. Rev. Geophys. (Suppl.) 33:117–121.[CrossRef]
- Jackson, M.L. 1975. Soil chemical analysis—Advanced course. 2nd ed. Published by the author, Madison, WI.
- Mitchell, J.P., P.B. Goodell, R. Krebill-Prather, T.S. Prather, K.J. Hembree, D.S. Munk, D.M. May, R.L. Coviello, T.K. Hartz, and G.S. Pettygrove. 2001. Innovative agricultural extension partnerships in California's central San Joaquin Valley. J. Extension 39(6). Also available online at www.joe.org/joe/2001december/rb7.html (verified 30 Mar. 2005).
- Pope, C.A. 1991. Respiratory hospital admissions associated with PM-10 pollution in Utah, Salt Lake, and Cache Valleys. Arch. Environ. Health 46:90–97.[ISI][Medline]
- Reicosky, D.C., and M.J. Lindstrom. 1995. Impact of fall tillage on short-term carbon dioxide flux. p. 177–187. In R. Lal, J. Kimble, E. Levine, and B.A. Stewart (ed.) Soils and global change. CRC Lewis Publ., Boca Raton, FL.
- Ross, M., P. Nolan, A.M. Langer, and W.C. Cooper. 1993. Health effects of mineral dusts other than asbestos. In G.D. Guthrie and B.T. Mossman (ed.) Health effects of mineral dusts. Mineralogical Soc. of Am., Washington, DC.
- SAS Institute. 2004. SAS software. Version 8.2. SAS Inst., Cary, NC.
- Schenker, M. 2000. Exposures and health effects from inorganic agricultural dusts. Environ. Health Perspect. 108:661–664.
- Schwartz, J., D. Slater, T.V. Larson, W.E. Pierson, and J.Q. Koenig. 1993. Particulate air pollution and hospital emergency room visits for asthma in Seattle. Am. Rev. Respir. Dis. 147:826–831.[ISI][Medline]
- Southard, R.J., R.J. Lawson, H.E. Studer, and M. Brown. 1997. Modified almond harvester reduces orchard dust. Calif. Agric. 51:10–13.
- Stetler, L.D., and K.E. Saxton. 1996. Wind erosion and PM(10) emissions from agricultural fields on the Columbia Plateau. Earth Surf. Processes Landforms 21:673–685.[CrossRef]
- United States Environmental Protection Agency. 2002. Ozone and particulate matter standards [Online]. Available at www.epa.gov/airlinks/airlinks4.html (verified 30 Mar. 2005). USEPA, Washington, DC.
This article has been cited by other articles:
|
|
|
|
 
J. J. Veenstra, W. R. Horwath, and J. P. Mitchell
Tillage and Cover Cropping Effects on Aggregate-Protected Carbon in Cotton and Tomato
Soil Sci. Soc. Am. J.,
March 12, 2007;
71(2):
362 - 371.
[Abstract]
[Full Text]
[PDF]
|
|
|
TOP
ABSTRACT
INTRODUCTION
