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Abstract
Air pollution, with ozone-generating processes being of primary importance,
coupled with the ever-diminishing natural resources in general and land
resources in particular, are among the most significant ecological impacts of the
modern-age
transportation
network.
The
transportation
network
and
corresponding traffic flow constitute a system which is the most elementary part
of a country's infrastructure and a prerequisite for its economic growth. The
necessity to protect and preserve our ecosystem, linked to the ongoing need for
robust and functional traffic infrastructures, calls for the development and
implementation of a modeling system targeting the various factors involved in
the transportation-to-ozone formation linkage. The daily dynamics of rush hour
traffic emissions to inland air pollution in general and airborne ozone
measurements in particular was studied using a newly devised interdisciplinary
modeling system. For the purpose of this study, the following models were
selected: a transportation model (EMME/2) coupled to the emission-factor
model (EFM), the regional atmospheric modeling system (RAMS) and a transport
and diffusion model (TDM). The photochemical module was addressed through
multiple-regression analysis, which found a correlation between ozone mixing
ratios, NOy levels and air temperature (Olszyna et al., 1994, 1997) in
photochemically aged air masses typical of the region under study (Peleg et al.,
1994). Explicitly, the modeling system’s construction and execution tracked the
following path: (i) Execution of a dynamic atmospheric model (RAMS), to obtain
the atmospheric windfiled parameters at a predefined resolution; (ii) Combining
the output data from (i) with the coupled traffic flow-emission factor models, as
input to the transport and diffusion model (TDM), to obtain a traffic-derived
time-dependent spatial distribution of the air pollution particles; (iii) Finally,
executing a photochemical model on output data from (i) and (ii) to obtain the
transportation-originating emission pollution-oriented ozone dispersion. The
photochemical module was addressed through a multiple-regression analysis,
which found a correlation between ozone-mixing ratios, NOy levels and air
temperature in photochemically aged air masses typical of the region under
study. Part II [Ranmar et al., 2001] decribes the modeling flow algorithm, its
components and its calibration with an airborne-measured ozone episode
detected over central Israel.
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The impact of the Tel Aviv metropolitan area as well as the Gaza Strip, as
pivotal coastal transportation sources for inland air pollution in general and
ozone formation in particular, was addressed in part III [Ranmar et al .,2001].
The modeling results elucidated a spatial and temporal overlap between the
ozone precursors and ozone production. The model simulations indicated east
to southeasterly dispersion of the pollution cloud. The results agreed well with
both spatial and temporal summertime ozone levels as recorded by aircraft over
central Israel, as well as with ground-based monitoring stations. The surface
observations indicated that ozone levels exhibit a distinct inland scale
dependency: peaking at later hours and on average reaching higher levels as we
progress inland. These results correspond well with the dynamics of the inlandpenetrating plume where an increase in ozone concentrations is attributed to
ongoing photochemical transformations while traversing inland. Synoptic
analysis identified the conditions prevailing when elevated air pollution, and
especially high ozone levels, exist over central Israel during the early, mid and
late summer. The analysis showed that this season features a shallow mixed
layer and weak zonal flow, which lead to poor ventilation rates and inhibit
efficient dispersion of this secondary pollutant. These poor ventilation rates
result in the slow transport of ozone precursors originating from urban
pollution
plumes
along
the
Mediterranean
coastline,
enabling
their
photochemical transformation under intense solar radiation during their travel
from the coast inland in central Israel. Thus, these findings establish a scenario
in which the physical process of inland movement of pollutants in general, and
ozone precursors in particular, is established. The Tel Aviv metropolitan area
and possibly the Gaza Strip region emit transportation pollutants into the
troposphere on a daily basis, initiating their subsequent photochemical
transformation as they are transported downwind. Model simulations showed
that about 60% of the detected inland ozone concentration is nourished by
traffic emissions during the morning rush hours from the Tel Aviv metropolitan
area. The work presented here demonstrates the ability of interdisciplinary
modeling systems to collectively operate as a prediction tool/tracing device,
capable of successfully predicting ozone pollution hotspots.
Ground-level ozone has become a problem of major concern in many
metropolitan areas in Israel experiencing recurring high ozone concentrations
during the summertime “photochemical smog season”. In a study aimed at
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complementing the airborne ozone pollution modeling (part II and III), statistical
data analyses of urban and rural surface ozone were performed (part IV). The
statistical analyses were based upon data collected between June 1 and September
30 for the years 1999 and 2000 from the national air pollution-monitoring network.
They targeted the the following objectives: (i) performing preliminary data analyses
in order to extract site, month and day-of-week dependencies of ground-level ozone.
This study was executed for five cities representing densely populated and
industrial areas (Tel aviv and Jerusalem), moderately populated (Be’er Sheva and
Modiin) and rural, less populated regions (Ariel);
prediction
models
based
on
multiple
linear
(ii) developing statistical ozone
regression
methods,
using
meteorological and chemical variables. The mathematical models were set to
address the daily 1-h max, 8-h averages and daily 1-h averaged ozone
concentration dynamics and were developed for four locations in Israel (Tel Aviv,
Ariel, Modiin and Jerusalem).
Realization of (i)
was achived by obtaining preliminary characteristics of
the ground-level ozone profiles of the aforementioned regions in Israel under
different time regimes. The various instances of quantitative ozone phenomena were
based upon different time intervals (monthly, daily, 1-h maxima and 8-h (10:00 h –
17:00 h) ozone averages). The presented results reveal a rather site-specific, and to
a lesser extent month-specific ozone average concentration spectrum. Additionally,
two distinct regimes are suggested, one concerning the time-space dependency of
the trans-boundary inland-transported pollution from Tel Aviv to Modiin to
Jerusalem (discussed in part III), and the other concerning isolated, “self-sustained”
ozone producers, represented by Be’er Sheva and Ariel. Analyses of day-of-week
dependency revealed two transportation emission-ozone formation regimes. The
first corresponds to the more highly populated urbanized areas (Tel Aviv, Jerusalem
and Be’er Sheva) where the weekend decrease (Friday and Saturday) in traffic
emissions results in a slight increase in ozone levels. Such a weekday-to-weekend
dependency reflects the transition from a VOC-limited regime to a NOx-limited
regime found in populated industrial urban areas. The opposite results are
encountered in Ariel, in which the low local weekend NO x emissions by traffic flow
inhibit the formation of ozone. Sunday, the first working day in Israel, is found to
exhibit on average higher ozone concentrations than mid-week days, even though
traffic activities are on par with these days. A possible mechanism for the
asymmetrical day-of-week increase in ozone levels is the downward mixing of the
ozone reservoir at the inversion base, replenished by the relatively high weekend
i
concentrations. Objective (ii)
was accomplished by utilizing multiple linear
regression prediction models for the 1-h max and 8-h average ozone levels were
based on 19 explanatory meteorological and chemical variables. The most
significant explanatory (highest R2) variables, obtained through stepwise regression
and correlation analyses, were site-specific. For 1-h peak ozone levels at the four
sites, RMSE model error ranged from 5.7 ppbv to 10.8 ppbv, while the R2 values (R2
 0.6) were site-independent. For the 8-h average the RMSE model error ranged
from 4.8 ppbv to 6.7 ppbv, the R2 values from 0.58 to 0.69. The daily 1-h average
ozone prediction model aimed at capturing the dynamics of daily ozone evolution
incorporated a different set of variables including a polynomial in time as its
predictors. The model’s statistical attributes (R2 and model RMSE, respectively)
were: Tel Aviv (0.78, 7.4 ppbv), Ariel (0.66, 8.8 ppbv), Modiin (0.76, 8.4 ppbv), and
Jerusalem (0.64, 10.9 ppbv). In general, the predicted daily 1-h peaks, 8-h averages
and daily 1-h averages tracked the observed values at the four stations and
generally,
the
models
captured
the
daily
variation
reasonably
well,
but
underestimated high concentrations of observed ozone. This occurred particularly
on days following days of low observed values and in the case of daily 1-h averages,
when a secondary late afternoon-to-late evening peak was established. While the
prediction models did not reach the anticipated predictive levels, they provide the
first statistical procedures addressing decision-grade forecast levels in Israel.