Dune fields of the present day, the Dust Bowl disaster of the 1930s U.S. Great Plains, and contemporary efforts to forecast, simulate, and understand dust storms have a striking, uniform commonality. What these apparently diverse phenomena have in common is that they all result from blowing sand and dust. This review paper unifies these three disparate but related phenomena. Its over-arching goal is to clearly explain these manifestations of windblown sand and dust. First, for contemporary dune fields, we offer reviews of two technical papers that explain the eolian formation and the continuing development of two major dune fields in southeastern California and northwestern Sonora, Mexico: the Algodones Dunes and the Gran Desierto de Altar. Second, historical, geological, meteorological, and socioeconomic aspects of the 1930s Great Plains Dust Bowl are discussed. Third, and last, we return to the present day to summarize two lengthy reports on dust storms and to review two technical papers that concern their forecasting and simulation. The intent of this review is to acquaint the interested reader with how eolian transport of sand and dust affects the formation of present-day dune fields, human agricultural enterprises, and efforts to better forecast and simulate dust storms. Implications: Blowing sand and dust have drastically affected the geological landscape and continue to shape the formation of dune fields today. Nearly a century ago the U.S. Great Plains suffered through the Dust Bowl, yet another consequence of blowing sand and dust brought on by drought and mismanagement of agricultural lands. Today, this phenomenon adversely affects landscapes, transportation, and human respiratory health. A more complete understanding of this phenomenon could (and has) led to more effective mitigation of dust sources, as well as to a more accurate predictive system by which the public can be forewarned.

Abstract In this study, an extreme rainfall event that occurred mainly on October 2, 2018, in the Phoenix metropolitan area, southwestern United States, is simulated with the Weather Research and Forecasting (WRF) model, version 4.0, with multiple microphysics and boundary layer schemes. Paired simulations are conducted by running the model first using a realistic land cover and land‐use dataset (URB run), and second, by replacing the urban land cover with open shrubland cover (called NOURB run). The model simulations are first evaluated against radar Stage IV (hereafter Stage IV) data and multiple radar and multiple sensors (MRMS) rainfall to validate the structure, amplitude, and location (SAL) of the rainfall field for both URB runs and NOURB runs. These evaluation results indicate that the model performance varies considerably depending on the physics schemes employed. Based on SAL values, the average of model simulations captures the main features (values of S, A, and L are less than 0.1) both for URB runs and for NOURB runs. Comparisons of hourly rainfall rates show that modeled rainfall maximums occurred about 1 hr earlier than both Stage IV and MRMS data over the Phoenix metro area, while the maximum rainfall amounts from the model are close to MRMS data but lower than Stage IV data. The differences of rainfall and other meteorological variables between URB runs and NOURB runs are analyzed. The differences of rainfall between URB and NOURB vary depending on the physics scheme employed. Our study also indicates that urbanization‐induced rainfall changes are small within the urban area but are significant at some locations outside of it; an explanation for this pattern needs further investigation. This result implies that using a single physics scheme to address the effects of urbanization on extreme rainfall events may result in inappropriate conclusions.

Fine and coarse particulate matter (PM), as measured, for example, in regulatory air pollution monitoring networks, contains biological entities such as fungal spores, pollen, animal dander, leaf wax, and human skin cells, to mention but a few types. Although these bioaerosols come in a wide range of particle size, of 14 common types nine fall into the 0- 10 mu m range and four are in the 0- 2.5 mu m range. These bioaerosols contribute to the concentrations of particulates determined by both filter-based and continuous instruments. This paper reviews bioaerosol research conducted worldwide in the last twenty years. Such studies have been conducted in Toronto, Canada, central Germany, Phoenix, Arizona, Davis, California, Dallas, Texas, and at many other sites worldwide. Notwithstanding the wide variety of climates, ecological systems, and urban and rural environments in which these measurements have been made, a reasonable, first-order estimate of the overall bioaerosol contribution to particles 2.5 microns and smaller (PM2.5) is 16.5% and to particles 10 microns and smaller (PM10) is 16.3%. A percentage contribution of this magnitude from unregulated emissions means that achieving PM standards will require greater reductions in the better understood anthropogenic and natural emissions of geological and combustion particles. In one such case the emission reductions necessary to achieve the standard increase from 25% (with bioaerosols ignored) to 36% (with bioaerosols accounted for). Although to the uninitiated this difference may not appear to be substantial, it can only be considered vast and nearly regulatorily impossible to those policy makers and regulators responsible for enacting emission-reduction regulations. Emissions of airborne biological materials are unregulated. Ignoring this natural component in attempting to achieve national ambient air quality standards for particulates can lead to overly optimistic predictions of attainment. Implications: For those officials still striving to meet federal air quality standards for particulate matter, either PM10 or PM2.5, it would be prudent to acknowledge the presence of unregulated bioaerosols. Ignoring this portion of PM may lead to over-optimistic projections of attainment.

In this study, the Noah-Multiparameterization with Crop land surface model in the Weather Research and Forecasting (WRF) with Chemistry (WRF/Chem) model is modified to include the effects of chronic ozone exposure (COE) on plant conductance and photosynthesis (PCP) found from field experiments. Based on the modified WRF/Chem, the effects of COE on regional hydrometeorology and crop productivity have been investigated over the central United States. Our results indicate that the model in its current configuration can reproduce the rainfall and temperature patterns of the observations and reanalysis data, although it overestimates rainfall. The model underestimates daily maximum 8-hour average ozone concentrations by 4-7 ppb compared with ozone observations from the Clean Air Status and Trend Network. The experimental tests on the effects of COE include setting different thresholds of ambient ozone concentrations ([O-3]) and using linear regressions to quantify PCP against the COE. Compared with the WRF/Chem control run (i.e., without considering the effects of COE), the modified model at different experimental setups consistently improves the simulated estimates of rainfall and temperatures. The simulations in June, July, August, and September of 2009-2014 show that, over crop lands, surface [O-3] decrease latent heat fluxes (LH) by 9 to 11 W/m(2), increase surface air temperatures (T-2) by 0.6 to 0.7 degrees C with the daily maximum temperature increasing up to 1 degrees C, and decrease rainfall by 0.15 to 0.21 mm per day by mostly reducing convective rainfall. Additionally, surface [O-3] decrease crop yields by 18-23%, decrease Gross Primary Productivity (GPP) by 30%-38% in a domain average and up to 50% in some areas, and decrease crop yields by 30-45%, all of which highly depends on the precise experimental setup, especially the [O-3] threshold. The mechanism producing these results is also discussed. Employing this modified WRF/Chem model in any high [O-3] region can more precisely elucidate the interactions of vegetation, meteorology, chemistry/emissions, and crop productivity.

Nine dust storms in south-central Arizona were simulated with the Weather Research and Forecasting with Chemistry model (WRF-Chem) at 2 km resolution. The windblown dust emission algorithm was the Air Force Weather Agency model. In comparison with ground-based PM10 observations, the model unevenly reproduces the dust-storm events. The model adequately estimates the location and timing of the events, but it is unable to precisely replicate the magnitude and timing of the elevated hourly concentrations of particles 10 mu m and smaller ([PM10]).Furthermore, the model underestimated [PM10] in highly agricultural Pinal County because it underestimated surface wind speeds and because the model's erodible fractions of the land surface data were too coarse to effectively resolve the active and abandoned agricultural lands. In contrast, the model overestimated [PM10] in western Arizona along the Colorado River because it generated daytime sea breezes (from the nearby Gulf of California) for which the surface-layer speeds were too strong. In Phoenix, AZ, the model's performance depended on the event, with both under- and overestimations partly due to incorrect representation of urban features. Sensitivity tests indicate that [PM10] highly relies on meteorological forcing. Increasing the fraction of erodible surfaces in the Pinal County agricultural areas improved the simulation of [PM10] in that region. Both 24-hr and 1-hr measured [PM10] were, for the most part, and especially in Pinal County, extremely elevated, with the former exceeding the health standard by as much as 10-fold and the latter exceeding health-based guidelines by as much as 70-fold. Monsoonal thunderstorms not only produce elevated [PM10], but also cause urban flash floods and disrupt water resource deliveries. Given the severity and frequency of these dust storms, and conceding that the modeling system applied in this work did not produce the desired agreement between simulations and observations, additional research in both the windblown dust emissions model and the weather research/physicochemical model is called for.Implications: While many dust storms can be considered to be natural, in semi-arid climates such storms often have an anthropogenic component in their sources of dust. Applying the natural, exceptional events policy to these storms with strong signatures of anthropogenic sources would appear not only to be misguided but also to stifle genuine regulatory efforts at remediation. Those dust storms that have resulted, in part, from passage over abandoned farm land should no longer be considered natural; policymakers and lawmakers need to compel the owners of such land to reduce its potential for windblown dust.

The Noah-Multiparameterization land surface model in the Weather Research and Forecasting (WRF) with Chemistry (WRF/Chem) is modified to include the effects of chronic ozone exposure (COE) on plant conductance and photosynthesis (PCP) found from field experiments. Based on the modified WRF/Chem, the effects of COE on regional hydroclimate have been investigated over the continental United States. Our results indicate that the model with/without modification in its current configuration can reproduce the rainfall and temperature patterns of the observations and reanalysis data, although it underestimates rainfall in the central Great Plains and overestimates it in the eastern coast states. The experimental tests on the effects of COE include setting different thresholds of ambient ozone concentrations ([O-3]) and using different linear regressions to quantify PCP against the COE. Compared with the WRF/Chem control run (i.e., without considering the effects of COE), the modified model at different experiment setups improves the simulated estimates of rainfall and temperatures in Texas and regions to the immediate north. The simulations in June, July and August of 2007-2012 show that surface [O-3] decrease latent heat fluxes (LH) by 10-27 W m(-2), increase surface air temperatures (T-2) by 0.6 degrees C-2.0 degrees C, decrease rainfall by 0.9-1.4 mm d(-1), and decrease runoff by 0.1-0.17 mm d(-1) in Texas and surrounding areas, all of which highly depends on the precise experiment setup, especially the [ O3] threshold. The mechanism producing these results is that COE decreases the LH and increases sensible heat fluxes, which in turn increases the Bowen ratios and air temperatures. This lowering of the LH also results in the decrease of convective potential and finally decreases convective rainfall. Employing this modifiedWRF/Chem model in any high [ O3] region can improve the understanding of the interactions of vegetation, meteorology, chemistry/emissions, and crop productivity.

In this study, a realistic irrigation method is incorporated into a model called Weather Research and Forecasting with Chemistry (WRF-Chem) to determine the impacts of irrigation on ozone and other pollutants over the Central Valley of California and thereafter throughout the contiguous United States. In comparison with observations, model simulations at current configurations underestimate ozone (O-3) and volatile organic compound (VOC) concentrations, especially during the elevated episode periods. The model results, however, are generally comparable with previous studies and the simulations adequately capture the spatial and temporal variability of these pollutant concentrations. In comparison with observations and model control runs, model simulations with irrigation runs are slightly improved. Our results show that irrigation increases primary pollutant concentrations in the irrigated areas under cloudless conditions, consistent with previous studies. In July and August, 2005, for instance, with clear skies, irrigation increases hourly surface [CO] up to 40 ppb with an irrigated grid average of 16 ppb or 8.3%; [VOC] up to 10 ppb with an irrigated grid average of 4.6 ppb or 21.4%; and [NOx] up to 4 ppb with irrigated grid average of 0.72 ppb or 12.6%, especially near urban areas during daytime. On the other hand, irrigation marginally decreases ground-level ozone concentrations ([O-3]) over irrigated land: it decreases hourly [O-3] by -0.14 ppb or -0.45% and decreases daily 8 h maximum average (DMA8) [O-3] by -0.39 ppb or -0.76%. In contrast, irrigation increases hourly [O-3] up to 5 ppb over the surrounding unirrigated areas of the San Joaquin Valley, during both daytime and nighttime. Furthermore, except for the Pacific Northwest, similar patterns of ozone variation are simulated by the model in other irrigated regions in the continental United States. The explanation is that irrigation results in cooler ground surfaces, which first decreases instability and turbulence, leading to a weakening of the vertical mixing of primary pollutants. Therefore, irrigation increases surface primary pollutant concentrations within the irrigation zone. Irrigation also results in daytime local circulations that enhance horizontal transport of ozone and other pollutants from irrigated to unirrigated areas near the ground surface. Because our results are based on two months in 2005 and on national anthropogenic emission inventories, the magnitude of these ozone changes could vary somewhat year to year; nonetheless, the methods and results from this study can be applied to any heavily polluted and irrigated agricultural area. (C) 2016 Elsevier B.V. All rights reserved.

In this study, the impacts of Mexican and southwestern U.S. agricultural and urban irrigation on North American monsoon (NAM) rainfall and other hydrometeorological fields are investigated using the Weather Research and Forecasting (WRF) Model by implementing an irrigation scheme into the WRF land surface model. Taking the 2000-12 monsoon seasons as examples, multiple WRF simulations with irrigation are conducted by designing different crops' maximum allowable water depletions (SWm). In comparison with gridded rainfall observations in urban and rural area, the WRF simulations with/without irrigation generally capture the observations very well, but with underestimation along the western slope of the Sierra Madre Occidental (SMO) and overestimation over southern Mexico. The simulations of WRF with irrigation are slightly improved over those without irrigation, compared with rainfall and sounding observations. Sensitivity studies reveal that the impact of irrigation on rainfall varies with location and NAM rainfall variability. Irrigation increases rainfall in eastern Arizona western New Mexico and in northwestern Mexico because of the irrigation-induced increases of convective available potential energy (CAPE) and precipitable water. Overall, irrigation decreases rainfall in western Arizona, along the western slope of the SMO, and in central Mexico because of irrigation-induced increases of convective inhibition (CIN), decreases of CAPE, and/or large-scale water vapor divergence.

AbstractPhysical mechanisms of incongruency between observations and Weather Research and Forecasting (WRF) Model predictions are examined. Limitations of evaluation are constrained by (i) parameterizations of model physics, (ii) parameterizations of input data, (iii) model resolution, and (iv) flux observation resolution. Observations from a new 22.1-m flux tower situated within a residential neighborhood in Phoenix, Arizona, are utilized to evaluate the ability of the urbanized WRF to resolve finescale surface energy balance (SEB) when using the urban classes derived from the 30-m-resolution National Land Cover Database. Modeled SEB response to a large seasonal variation of net radiation forcing was tested during synoptically quiescent periods of high pressure in winter 2011 and premonsoon summer 2012. Results are presented from simulations employing five nested domains down to 333-m horizontal resolution. A comparative analysis of model cases testing parameterization of physical processes was done usin...

Abstract. In this study, WRF-Chem is utilized at high resolution (1.333 km grid spacing for the innermost domain) to investigate impacts of southern California anthropogenic emissions (SoCal) on Phoenix ground-level ozone concentrations ([O3]) for a pair of recent exceedance episodes. First, WRF-Chem control simulations, based on the US Environmental Protection Agency (EPA) 2005 National Emissions Inventories (NEI05), are conducted to evaluate model performance. Compared with surface observations of hourly ozone, CO, NOX, and wind fields, the control simulations reproduce observed variability well. Simulated [O3] are comparable with the previous studies in this region. Next, the relative contribution of SoCal and Arizona local anthropogenic emissions (AZ) to ozone exceedances within the Phoenix metropolitan area is investigated via a trio of sensitivity simulations: (1) SoCal emissions are excluded, with all other emissions as in Control; (2) AZ emissions are excluded with all other emissions as in Control; and (3) SoCal and AZ emissions are excluded (i.e., all anthropogenic emissions are eliminated) to account only for Biogenic emissions and lateral boundary inflow (BILB). Based on the USEPA NEI05, results for the selected events indicate the impacts of AZ emissions are dominant on daily maximum 8 h average (DMA8) [O3] in Phoenix. SoCal contributions to DMA8 [O3] for the Phoenix metropolitan area range from a few ppbv to over 30 ppbv (10–30 % relative to Control experiments). [O3] from SoCal and AZ emissions exhibit the expected diurnal characteristics that are determined by physical and photochemical processes, while BILB contributions to DMA8 [O3] in Phoenix also play a key role. Finally, ozone transport processes and pathways within the lower troposphere are investigated. During daytime, pollutants (mainly ozone) near the Southern California coasts are pumped into the planetary boundary-layer over the Southern California desert through the mountain chimney and pass channel effects, aiding eastward transport along the desert air basins in southern California and finally, northeastward along the lower Gila River basin in Arizona, thereby affecting Phoenix air quality during subsequent days. This study indicates that local emission controls in Phoenix need to be augmented with regional emission reductions to attain the federal ozone standard, especially if a more stringent standard is adopted in the future.

The effects of urbanization on ozone levels have been widely investigated over cities primarily located in temperate and/or humid regions. In this study, nested WRF-Chem simulations with a finest grid resolution of 1 km are conducted to investigate ozone concentrations [O-3] due to urbanization within cities in arid/semi-arid environments. First, a method based on a shape preserving Monotonic Cubic Interpolation (MCI) is developed and used to downscale anthropogenic emissions from the 4 km resolution 2005 National Emissions Inventory (NEI05) to the finest model resolution of 1 km. Using the rapidly expanding Phoenix metropolitan region as the area of focus, we demonstrate the proposed MCI method achieves ozone simulation results with appreciably improved correspondence to observations relative to the default interpolation method of the WRF-Chem system. Next, two additional sets of experiments are conducted, with the recommended MCI approach, to examine impacts of urbanization on ozone production: (1) the urban land cover is included (i.e., urbanization experiments) and, (2) the urban land cover is replaced with the region's native shrubland. Impacts due to the presence of the built environment on [O-3] are highly heterogeneous across the metropolitan area. Increased near surface [O-3] due to urbanization of 10-20 ppb is predominantly a nighttime phenomenon while simulated impacts during daytime are negligible. Urbanization narrows the daily [O-3] range (by virtue of increasing nighttime minima), an impact largely due to the region's urban heat island. Our results demonstrate the importance of the MCI method for accurate representation of the diurnal profile of ozone, and highlight its utility for high-resolution air quality simulations for urban areas.

Phoenix, Arizona, has been an ozone nonattainment area for the past several years and it remains so. Mitigation strategies call for improved modeling methodologies as well as understanding of ozone formation and destruction mechanisms during seasons of high ozone events. To this end, the efficacy of lateral boundary conditions (LBCs) based on satellite measurements (adjusted-LBCs) was investigated, vis-à-vis the default-LBCs, for improving the predictions of Models-3/CMAQ photochemical air quality modeling system. The model evaluations were conducted using hourly ground-level ozone and NO(2) concentrations as well as tropospheric NO(2) columns and ozone concentrations in the middle to upper troposphere, with the 'design' periods being June and July of 2006. Both included high ozone episodes, but the June (pre-monsoon) period was characterized by local thermal circulation whereas the July (monsoon) period by synoptic influence. Overall, improved simulations were noted for adjusted-LBC runs for ozone concentrations both at the ground-level and in the middle to upper troposphere, based on EPA-recommended model performance metrics. The probability of detection (POD) of ozone exceedances (>75ppb, 8-h averages) for the entire domain increased from 20.8% for the default-LBC run to 33.7% for the adjusted-LBC run. A process analysis of modeling results revealed that ozone within PBL during bulk of the pre-monsoon season is contributed by local photochemistry and vertical advection, while the contributions of horizontal and vertical advections are comparable in the monsoon season. The process analysis with adjusted-LBC runs confirms the contributions of vertical advection to episodic high ozone days, and hence elucidates the importance of improving predictability of upper levels with improved LBCs.

Statistically significant correlations between increase of asthma attacks in children and elevated concentrations of particulate matter of diameter 10 microns and less (PM10) were determined for metropolitan Phoenix, Arizona. Interpolated concentrations from a five-site network provided spatial distribution of PM10 that was mapped onto census tracts with population health records. The case-crossover statistical method was applied to determine the relationship between PM10 concentration and asthma attacks. For children ages 5–17, a significant relationship was discovered between the two, while children ages 0–4 exhibited virtually no relationship. The risk of adverse health effects was expressed as a function of the change from the 25th to 75th percentiles of mean level PM10 (36 μg m−3). This increase in concentration was associated with a 12.6% (95% CI: 5.8%, 19.4%) increase in the log odds of asthma attacks among children ages 5–17. Neither gender nor other demographic variables were significant. The results are being used to develop an asthma early warning system for the study area.

Deterministic photochemical air quality models are commonly used for regulatory management and planning of urban airsheds. These models are complex, computer intensive, and hence are prohibitively expensive for routine air quality predictions. Stochastic methods are becoming increasingly popular as an alternative, which relegate decision making to artificial intelligence based on Neural Networks that are made of artificial neurons or 'nodes' capable of 'learning through training' via historic data. A Neural Network was used to predict particulate matter concentration at a regulatory monitoring site in Phoenix, Arizona; its development, efficacy as a predictive tool and performance vis-à-vis a commonly used regulatory photochemical model are described in this paper. It is concluded that Neural Networks are much easier, quicker and economical to implement without compromising the accuracy of predictions. Neural Networks can be used to develop rapid air quality warning systems based on a network of automated monitoring stations.

The Phoenix metropolitan area is currently designated as 'serious' with regard to violation of the U.S. National Ambient Air Quality Standards (NAAQS) for particulate matter of aerodynamic diameter less than 10μm (PM10). Most of the severe PM10 violations have been attributed to regional natural exceptional events or local exceptional (episodic) events associated with windblown dust emanating from area sources such as construction and agricultural sites, vacant lots and alluvial channels. During such events, the pollution concentration spikes for a short period of time, thus raising the 24-hour average of PM10 anomalously. This may lead to the excess of PM10 concentration above the currently set 24-averaged standards, 150μg/m, determined in the interest of protecting public health (primary standard) and the environment (secondary). For PM10, both standards are the same. Even if the NAAQS are not exceeded during such an event, severe health repercussions can occur due to pulsed PM10 events. For example, thunderstorm-induced asthma epidemics that swamp hospital emergency rooms within 20 minutes of the onset of a storm have been attributed to suspension of micron-sized starch granules that originate in pollen (Venables et al. 1997). Unlike for industrial and transportation-networks associated sources, it is difficult to predict and control PM pollution arising from natural episodic events. In general, deterministic models have been used for such predictions, but unavailability of the up-to-date pollution inventories, the complexity of models and the fact that air pollution prediction models, such as CMAQ, do not have sound dust entrainment module have been the bane in developing operational forecasting tools based on deterministic models (Choi et al. 2006; Choi & Fernando 2007).

Abstract. Forest fires in North and Central America have been frequent and extensive over the past few years. Though much research has addressed the effects of forest fires in tropical South America and Africa on regional and global-scale oxidants, the same is not true for North America. Here we show that one of the days during an intensive field campaign conducted over Phoenix, Arizona, in 1998 was substantially influenced by transport from forest fires in central and southern Mexico. We combined data collected from aircraft platforms, surface stations, and satellite with model results to establish that the origin of the air sampled over Phoenix on 20 May 1998, was from forest fires in Mexico. We also investigated the effect of the smoke layer on photolysis rates and hence photochemistry over a five-day travel period from the source region to Phoenix. The results show that a smoke layer could reduce photolysis rates of key tropospheric constituents significantly and decrease the oxidant formation rates during the first few days of the plume history. The ultimate effect of the smoke layer on the evolution of oxidants in the plume was, however, shown to be minimal.

High (episodic) particulate matter (PM) events over the sister cities of Douglas (AZ) and Agua Prieta (Sonora), located in the US–Mexico border, were simulated using the 3D Eulerian air quality model, MODELS-3/CMAQ. The best available input information was used for the simulations, with pollution inventory specified on a fine grid. In spite of inherent uncertainties associated with the emission inventory as well as the chemistry and meteorology of the air quality simulation tool, model evaluations showed acceptable PM predictions, while demonstrating the need for including the interaction between meteorology and emissions in an interactive mode in the model, a capability currently unavailable in MODELS-3/CMAQ when dealing with PM. Sensitivity studies on boundary influence indicate an insignificant regional (advection) contribution of PM to the study area. The contribution of secondary particles to the occurrence of high PM events was trivial. High PM episodes in the study area, therefore, are purely local events that largely depend on local meteorological conditions. The major PM emission sources were identified as vehicular activities on unpaved/paved roads and wind-blown dust. The results will be of immediate utility in devising PM mitigation strategies for the study area, which is one of the US EPA-designated non-attainment areas with respect to PM.

In May and June of 1998, an extensive measurement campaign was fielded in the city of Phoenix and its environs. Measurements were made at ground sites and aboard the Department of Energy's G-1 research aircraft in an effort to understand the production of O3 in this area. Diurnal variations in O3 differed at the upwind Palo Verde, downtown Phoenix Super Site, and downwind Usery Pass surface stations. Air masses entering the metropolitan area had O3 concentrations greater than 40ppbv. Maximum O3 concentrations near 100ppbv were observed downtown at 14:00 local standard time; similar concentrations occurred much later in the day at the downwind site. One aircraft case study on 5 June, 1998 is presented to illustrate ozone production in the region. Calculated ozone production rate and efficiency varied from 1 to 7ppbvh−1, and 1–3molecules of O3 per molecule of NOz, respectively, for this flight. Hydrocarbon apportionment, based upon ground site and aircraft measurements, establishes that biogenic species are not significant contributors to O3 production in the Phoenix area. Therefore, carbon monoxide becomes a major contributor to OH reactivity as the more reactive anthropogenic hydrocarbons become depleted. The relatively low ozone production observed in this study is attributed to a low rate of radical production in the dry atmosphere.

An extensive VOC data set was gathered as part of a photochemical oxidant field campaign conducted in the Phoenix air basin in the late spring of 1998. Sampling was done at the surface and by aircraft at midboundary layer height; in regions with emission sources and downwind in the urban plume. VOC concentration ratios were used to calculate photochemical age, defined as the time integrated exposure of an air mass to OH radical. Based on the VOC ratios of 15 compounds (with OH reactivity varying between acetylene and p, m‐xylene), we present estimates for photochemical age and dilution factors for several regions within the air basin. Geographic trends are in agreement with the expectation that pollutants are transported in a generally eastward direction so that older and more dilute mixtures occur to the east of the city. Photochemical ages determined from aircraft samples agree with those determined at a downwind surface site. The bias in photochemical age that occurs because fresh pollutants are added to an aged mixture has been quantified by using a particle trajectory model. A combination of trajectory results (actual age of the pollutants in an air mass) and photochemical age yields an estimate of the average OH concentration experienced by the air parcel. OH obtained in this way is somewhat lower, but has the same trends as OH concentrations calculated using a photochemical box model that is constrained with observed concentrations coincident with the VOC samples.