Exposure of PM2.5 and EC from diesel and gasoline vehicles in communities near the Ports of Los Angeles and Long Beach,California

The Ports of Los Angeles and Long Beach are the entry point for almost half of all cargo containers entering the United States. The use of diesel trucks to move Port-related goods has raised significant public health concerns associated with black carbon and other air pollutants. It is difficult to reliably estimate people's exposure to vehicle-related pollutants due to the narrow impact zone of traffic, usually within 200–300 m downwind of major roadways. Previous studies suffer from the lack of traffic count data on surface streets and the lack of neighborhood-level population data. We examined seasonal and annual average exposures of particulate matter less than 2.5 μm (PM_2.5) and elemental carbon (EC) at a neighborhood scale for communities heavily impacted by diesel trucks near these ports. We assembled a traffic-activity database that distinguishes gasoline and diesel vehicles on both freeways and surface streets, by consolidating information from several sources, including our own field measurements. The CALINE4 model was used to estimate residential exposure of the study population to PM_2.5 and EC. Parcel property data were used to allocate Census block group (BG) population to increase spatial resolution. The annual average PM_2.5 and EC exposure due to local traffic was 3.8 and 0.4 μg m^?3, respectively. On average, surface streets contributed a little more than freeways (55% vs. 45% for EC and 57% and 43% for PM_2.5). Light-duty vehicles contributed significantly more than heavy-duty trucks for PM_2.5 (61% vs. 39%), but slightly less than heavy-duty trucks for EC (49% vs. 51%). Community mean population exposure was similar using parcel, census block, and BG population data, but extreme values and standard deviations varied significantly at different spatial resolutions. The intake fraction for the study population was in the range of 1.0–2.2 × 10^?5 by vehicle type, roadway type, and season.     

Impact of roadside noise barriers on particle size distributions and pollutants concentrations near freeways

Increasing epidemiological evidence has established an association between a host of adverse health effects and exposure to ambient particulate matter (PM) and co-pollutants, especially those emitted from motor vehicles. Although PM and their co-pollutants dispersion profiles near the open freeway have been extensively characterized by means of both experimental measurements and numerical simulations in recent years, such investigations near freeways with roadside barriers have not been well documented in the literature. A few previous studies suggested that the presence of roadside structures, such as noise barriers and vegetation, may impact the decay of pollutant concentrations downwind of the freeway by limiting the initial dispersion of traffic emissions and increasing their vertical mixing due to the upward deflection of airflow. Since the noise barriers are now common roadside features of the freeways, particularly those running through populated urban areas, it is pertinent to investigate the impact of their presence on the particles and co-pollutants concentrations in areas adjacent to busy roadways. This study investigated two highly trafficked freeways (I-710 and I-5) in Southern California, with two sampling sites for each freeway, one with and the other without the roadside noise barriers. Particle size distributions and co-pollutants concentrations were measured in the immediate proximity of freeways and at different distances downwind of the freeways. The results showed the formation of a “concentration deficit” zone in the immediate vicinity of the freeway with the presence of roadside noise barrier, followed by a surge of pollutant concentrations further downwind at 80–100 m away from freeway. The particle and co-pollutants concentrations reach background levels at farther distances of 250–400 m compared to 150–200 m at the sites without roadside noise barriers.     

On-road emission characteristics of heavy-duty diesel vehicles in Shanghai

On-road vehicle tests of nine heavy-duty diesel trucks were conducted using SEMTECH-D, an emissions measuring instrument provided by Sensors, Inc. The total length of roads for the tests was 186 km. Data were obtained for 37,255 effective driving cycles, including 17,216 on arterial roads, 15,444 on residential roads, and 4595 on highways. The impacts of speed and acceleration on fuel consumption and emissions were analyzed. Results show that trucks spend an average of 16.5% of the time in idling mode, 25.5% in acceleration mode, 27.9% in deceleration mode, and only 30.0% at cruise speed. The average emission factors of CO, total hydrocarbons (THC), and NO_x for the selected vehicles are (4.96±2.90), (1.88±1.03) and (6.54±1.90) g km⁻¹, respectively. The vehicle emission rates vary significantly with factors like speed and acceleration. The test results reflect the actual traffic situation and the current emission status of diesel trucks in Shanghai. The measurements show that low-speed conditions with frequent acceleration and deceleration, particularly in congestion conditions, are the main factors that aggravate vehicle emissions and cause high emissions of CO and THC. Alleviating congestion would significantly improve vehicle fuel economy and reduce CO and THC emissions.     

A wide area of air pollutant impact downwind of a freeway during pre-sunrise hours

We have observed a wide area of air pollutant impact downwind of a freeway during pre-sunrise hours in both winter and summer seasons. In contrast, previous studies have shown much sharper air pollutant gradients downwind of freeways, with levels above background concentrations extending only 300 m downwind of roadways during the day and up to 500 m at night. In this study, real-time air pollutant concentrations were measured along a 3600 m transect normal to an elevated freeway 1–2 h before sunrise using an electric vehicle mobile platform equipped with fast-response instruments. In winter pre-sunrise hours, the peak ultrafine particle (UFP) concentration (～95 000 cm^?3) occurred immediately downwind of the freeway. However, downwind UFP concentrations as high as ～40 000 cm^?3 extended at least 1200 m from the freeway, and did not reach background levels (～15 000 cm^?3) until a distance of about 2600 m. UFP concentrations were also elevated over background levels up to 600 m upwind of the freeway. Other pollutants, such as NO and particle-bound polycyclic aromatic hydrocarbons, exhibited similar long-distance downwind concentration gradients. In contrast, air pollutant concentrations measured on the same route after sunrise, in the morning and afternoon, exhibited the typical daytime downwind decrease to background levels within ～300 m as found in earlier studies. Although pre-sunrise traffic volumes on the freeway were much lower than daytime congestion peaks, downwind UFP concentrations were significantly higher during pre-sunrise hours than during the daytime. UFP and NO concentrations were also strongly correlated with traffic counts on the freeway. We associate these elevated pre-sunrise concentrations over a wide area with a nocturnal surface temperature inversion, low wind speeds, and high relative humidity. Observation of such wide air pollutant impact area downwind of a major roadway prior to sunrise has important exposure assessment implications since it demonstrates extensive roadway impacts on residential areas during pre-sunrise hours, when most people are at home.     

Temporal size distribution and concentration of particles near a major highway

Ultrafine particles (UFP, diameter < 100 nm), as reported in recent findings of toxicological and epidemiological studies, could represent health and environmental risks. Motor vehicle emissions usually constitute the most significant source of UFP in an urban environment. Number, surface and mass concentration of particles were determined at increasing distances from the most important Italian road: the “Autostrada del Sole” A1 highway. Particles in the size range from 0.0059 to 20 μm were measured with a Scanning Mobility Particle Sizer (SMPS) and an Aerodynamic Particle Sizer (APS) spectrometers.The A1 highway was selected because it is characterized by two different traffic conditions: a daily and a weekly traffic. During the weekdays the average traffic flow was about 50 vehicles min^?1 with more than 30% of vehicles being heavy-duty (HD) diesel trucks. The weekly traffic component is characterized by an increased traffic up to approximately 100 vehicles min^?1 during Monday mornings and Friday afternoons because of light-duty vehicles, with substantial reduction of the percentage of HD diesel trucks (typically only 10%).The purpose of this study is the characterization of the A1 highway in terms of evolution of particle size distribution (PSD) and total number concentration at different distances from the highway. This analysis is interesting because Italian traffic presents a higher i) percentage of diesel light-duty vehicles and ii) mean traffic speed in respect to US and Australian traffics. Particle number, surface and mass, exponentially decreases as one moves away from the freeway, whereas UFP number concentration measured at 400 m downwind from the freeway is indistinguishable from upwind background concentration.     

Ions in motor vehicle exhaust and their dispersion near busy roads

Measurements in the exhaust plume of a petrol-driven motor car showed that molecular cluster ions of both signs were present in approximately equal amounts. The emission rate increased sharply with engine speed while the charge symmetry remained unchanged. Measurements at the kerbside of nine motorways and five city roads showed that the mean total cluster ion concentration near city roads (603 cm^?3) was about one-half of that near motorways (1211 cm^?3) and about twice as high as that in the urban background (269 cm^?3). Both positive and negative ion concentrations near a motorway showed a significant linear increase with traffic density (R² = 0.3 at p < 0.05) and correlated well with each other in real time (R² = 0.87 at p < 0.01). Heavy duty diesel vehicles comprised the main source of ions near busy roads. Measurements were conducted as a function of downwind distance from two motorways carrying around 120–150 vehicles per minute. Total traffic-related cluster ion concentrations decreased rapidly with distance, falling by one-half from the closest approach of 2 m to 5 m of the kerb. Measured concentrations decreased to background at about 15 m from the kerb when the wind speed was 1.3 m s^?1, this distance being greater at higher wind speed. The number and net charge concentrations of aerosol particles were also measured. Unlike particles that were carried downwind to distances of a few hundred metres, cluster ions emitted by motor vehicles were not present at more than a few tens of metres from the road.     

Using a dispersion model to estimate emission rates of particulate matter from paved roads

From January 1996 to June 1997, we carried out a series of measurements to estimate emissions of PM₁₀ from paved roads in Riverside County, California. The program involved the measurement of upwind and downwind vertical profiles of PM₁₀, in addition to meteorological variables such as wind speed and vertical turbulent intensity. This information was analyzed using a new dispersion model that incorporates current understanding of micrometeorology and dispersion. The emission rate was inferred by fitting model predictions to measurements. The inferred emission factors ranged from 0.2 g VKT^-1 for freeways to about 3 g VKT^-1 for city roads. The uncertainty in these factors is estimated to be approximately a factor of two since the contributions of paved road PM₁₀ emissions to ambient concentrations were comparable to the uncertainty in the mean value of the measurement. At this stage, our best estimate of emission factor lies between 0.1 and 10 g VKT^-1; there is some indication that it is about 0.1 g VKT^-1 for heavily traveled freeways, and is an order of magnitude higher for older city roads. We found that measured silt loadings were poor predictors of emission factors.The measured emission factors imply that paved road emissions may contribute about 30% to the total PM₁₀ emissions from a high traffic area such as Los Angeles. This suggests that it is necessary to develop methods that are more reliable than the upwind–downwind concentration difference technique.     

Air pollutant concentrations near three Texas roadways,Part I: Ultrafine particles

Vehicular emitted air pollutant concentrations were studied near three types of roadways in Austin, Texas: (1) State Highway 71 (SH-71), a heavily traveled arterial highway dominated by passenger vehicles; (2) Interstate 35 (I-35), a limited access highway north of Austin in Georgetown; and (3) Farm to Market Road 973 (FM-973), a heavily traveled surface roadway dominated by truck traffic. Air pollutants examined include carbon monoxide (CO), oxides of nitrogen (NO_x), and carbonyl species in the gas-phase. In the particle phase, ultrafine particle (UFP) concentrations (diameter < 100 nm), fine particulate matter (PM_2.5, diameter < 2.5 μm) mass and carbon content and several particle-bound organics were examined. All roadways had an upwind stationary sampling location, one or two fixed downwind sample locations and a mobile monitoring platform that characterized pollutant concentrations fall-off with increased distance from the roadways. Data reported in this paper focus on UFP while other pollutants and near-roadway chemical processes are examined in a companion paper. Traffic volume, especially heavy-duty traffic, wind speed, and proximity to the road were found to be the most important factors determining UFP concentrations near the roadways. Since wind directions were not consistent during the sampling periods, distances along wind trajectories from the roadway to the sampling points were used to study the decay characteristics of UFPs. Under perpendicular wind conditions, for all studied roadway types, particle number concentrations increased dramatically moving from the upwind side to the downwind side. The elevated particle number concentrations decay exponentially with increasing distances from the roadway with sharp concentration gradients observed within 100–150 m, similar to previously reported studies. A single exponential decay curve was found to fit the data collected from all three roadways very well under perpendicular wind conditions. No consistent pattern was observed for UFPs under parallel wind conditions. However, regardless of wind conditions, particle concentrations returned to background levels within a few hundred meters of the roadway. Within measured UFP size ranges, smaller particles (6–25 nm) decayed faster than larger ones (100–300 nm). Similar decay rates were observed among UFP number, surface, and volume.     

Spatial and temporal variations in traffic-related particulate matter at New York City high schools

Relatively little is known about exposures to traffic-related particulate matter at schools located in dense urban areas. The purpose of this study was to examine the influences of diesel traffic proximity and intensity on ambient concentrations of fine particulate matter (PM_2.5) and black carbon (BC), an indicator of diesel exhaust particles, at New York City (NYC) high schools. Outdoor PM_2.5 and BC were monitored continuously for 4–6 weeks at each of 3 NYC schools and 1 suburban school located 40 km upwind of the city. Traffic count data were obtained using an automated traffic counter or video camera. BC concentrations were 2–3 fold higher at urban schools compared with the suburban school, and among the 3 urban schools, BC concentrations were higher at schools located adjacent to highways. PM_2.5 concentrations were significantly higher at urban schools than at the suburban school, but concentrations did not vary significantly among urban schools. Both hourly average counts of trucks and buses and meteorological factors such as wind direction, wind speed, and humidity were significantly associated with hourly average ambient BC and PM_2.5 concentrations in multivariate regression models. An increase of 443 trucks/buses per hour was associated with a 0.62 μg/m³ increase in hourly average BC at an NYC school located adjacent to a major interstate highway. Car traffic counts were not associated with BC. The results suggest that local diesel vehicle traffic may be important sources of airborne fine particles in dense urban areas and consequently may contribute to local variations in PM_2.5 concentrations. In urban areas with higher levels of diesel traffic, local, neighborhood-scale monitoring of pollutants such as BC, which compared to PM_2.5, is a more specific indicator of diesel exhaust particles, may more accurately represent population exposures.     

Road fugitive dust emission characteristics in Beijing during Olympics Game 2008 in Beijing,China

Eighty road dust-fall (DF) monitoring sites and 14 background monitoring sites were established in the Beijing metropolitan area, and monitoring was conducted from January 2006 to December 2008. The dust-fall attributable to roads (ΔDF) showed a clear decline from 2006 to 2008. Dust-fall levels decreased across different road types from freeway > major arterial roads > minor arterial roads > collector roads > background sites. The ΔDF showed declines of 65%, 55%, 65% and 84% respectively for freeways, major arterial, minor arterial and collector roads from August 2007 to August 2008, and declines of 77%, 76%, 82% and 82% between August 2006 and August 2008. The ΔDF declined by 80%, 79%, 82% and 69% for freeways, major arterial, minor arterial and collector roads respectively between September 2007 and September 2008, and declined by 84%, 88%, 80% and 81% between September 2006 and September 2008.Eighty samples were collected in August 2007 and August 2008 and analyzed for silt loading. PM₁₀ emission factors and emission strengths were calculated using the AP-42 model. The silt loading reduced by 77%, 35%, 61%, 59% and 75% for freeways, major arterial, minor arterial, collector and local roads respectively. The PM₁₀ emission factors were reduced by 57%, 15%, 36%, 51% and 61% and the PM₁₀ emission strength declined by 70%, 40%, 55%, 65% and 72% for freeways, major arterial, minor arterial, collector and local roads respectively between August 2007 and August 2008. The decline is consistent with the reduction in road dust-fall.     

Use of n-fold cross-validation to evaluate three methods to calculate heavy truck annual average daily traffic and vehicle miles traveled

Reliable estimates of heavy-truck volumes in the United States are important in a number of transportation applications including pavement design and management, traffic safety, and traffic operations. Additionally, because heavy vehicles emit pollutants at much higher rates than passenger vehicles, reliable volume estimates are critical to computing accurate inventories of on-road emissions. Accurate baseline inventories are also necessary to forecast future scenarios. The research presented in this paper evaluated three different methods commonly used by transportation agencies to estimate annual average daily traffic (AADT), which is used to determine vehicle miles traveled (VMT). Traffic data from continuous count stations provided by the Iowa Department of Transportation were used to estimate AADT for single-unit and multiunit trucks for rural freeways and rural primary highways using the three methods. The first method developed general expansion factors, which apply to all vehicles. AADT, representing all vehicles, was estimated for short-term counts and was multiplied by statewide average truck volumes for the corresponding roadway type to obtain AADT for each truck category. The second method also developed general expansion factors and AADT estimates. Truck AADT for the second method was calculated by multiplying the general AADT by truck volumes from the short-term counts. The third method developed expansion factors specific to each truck group. AADT estimates for each truck group were estimated from short-term counts using corresponding expansion factors. Accuracy of the three methods was determined by comparing actual AADT from count station data to estimates from the three methods. Accuracy of the three methods was compared using n-fold cross-validation. Mean squared error of prediction was used to estimate the difference between estimated and actual AADT. Prediction error was lowest for the method that developed separate expansion factors for trucks. Implications for emissions estimation using the different methods are also discussed.     

Changed vegetation composition in coniferous forests near to motorways in Southern Germany: the effects of traffic-born pollution

To estimate the effect of traffic emissions on the vegetation composition of coniferous forests near to motorways, three transects of 520 m length were studied by analysing vegetation composition, soil parameters and deposition data in the Munich-area, Southern Germany. The detected patterns suggest that motorways have an impact on the vegetation composition in the neighbourhood of roads. Depending on the wind direction, the influences of the motorways reaches up to 230 m on downwind side and up to 80 m on upwind side. The vegetation is mainly affected by the deposition of nitrogen deriving from fuel combustion and by basic substances added to road salt. By monitoring vegetation changes near to motorways, it is possible to estimate the areas where harmful alterations of the ecosystem can be expected.     

Use of n-Fold Cross-Validation to Evaluate Three Methods to Calculate Heavy Truck Annual Average Daily Traffic and Vehicle Miles Traveled

Abstract

Reliable estimates of heavy-truck volumes in the United States are important in a number of transportation applications including pavement design and management, traffic safety, and traffic operations. Additionally, because heavy vehicles emit pollutants at much higher rates than passenger vehicles, reliable volume estimates are critical to computing accurate inventories of on-road emissions. Accurate baseline inventories are also necessary to forecast future scenarios. The research presented in this paper evaluated three different methods commonly used by transportation agencies to estimate annual average daily traffic (AADT), which is used to determine vehicle miles traveled (VMT). Traffic data from continuous count stations provided by the Iowa Department of Transportation were used to estimate AADT for single-unit and multiunit trucks for rural freeways and rural primary highways using the three methods. The first method developed general expansion factors, which apply to all vehicles. AADT, representing all vehicles, was estimated for short-term counts and was multiplied by statewide average truck volumes for the corresponding roadway type to obtain AADT for each truck category. The second method also developed general expansion factors and AADT estimates. Truck AADT for the second method was calculated by multiplying the general AADT by truck volumes from the short-term counts. The third method developed expansion factors specific to each truck group. AADT estimates for each truck group were estimated from short-term counts using corresponding expansion factors. Accuracy of the three methods was determined by comparing actual AADT from count station data to estimates from the three methods. Accuracy of the three methods was compared using n-fold cross-validation. Mean squared error of prediction was used to estimate the difference between estimated and actual AADT. Prediction error was lowest for the method that developed separate expansion factors for trucks. Implications for emissions estimation using the different methods are also discussed.     

Using pollution roses to assess sulfur dioxide impacts in a township downwind of a petrochemical complex

This study used pollution roses to assess sulfur dioxide (SO₂) pollution in a township downwind of a large petrochemical complex based on data collected from a single air quality monitoring station. The pollution roses summarized hourly SO₂ concentrations at the Taishi air quality monitoring station, located approximately 7.8–13.0 km south of the No. 6 Naphtha Cracking Complex in Taiwan, according to 36 sectors of wind direction during the preoperational period (1995–1999) and two postoperational periods (2000–2004 and 2005–2009). The 99th percentile of hourly SO₂ concentrations 350? downwind from the complex increased from 28.9 ppb in the preoperational period to 86.2–324.2 ppb in the two postoperational periods. Downwind SO₂ concentrations were particularly high during 2005–2009 at wind speeds of 6–8 m/sec. Hourly SO₂ levels exceeded the U.S. Environmental Protection Agency (EPA) health-based standard of 75 ppb only in the postoperational periods, with 65 exceedances from 0–10? and 330–350? downwind directions during 2001–2009. This study concluded that pollution roses based on a single monitoring station can be used to investigate source contributions to air pollution surrounding industrial complexes, and that it is useful to combine such directional methods with analyses of how pollution varies between different wind speeds, times of day, and periods of industrial development.

Implications: The pollution roses summarize SO₂ concentrations by wind direction and to investigate source contribution to air quality. Percentile statistics can catch pollution episodes occurring in a very short time at specific wind directions and speeds. The downwind areas have already exceeded regulated 1-hr SO₂ standard since the operation of the complex.     

Factor analysis of submicron particle size distributions near a major United States-Canada trade bridge

A factor analytic model has been applied to resolve and apportion particles based on submicron particle size distributions downwind of a United States-Canada bridge in Buffalo, NY. The sites chosen for this study were located at gradually increasing distances downwind of the bridge complex. Seven independent factors were resolved, including four factors that were common to all of the five sites considered. The common factors were generally characterized by the existence of two or more number and surface area modes. The seven factors resolved were identified as follows: fresh tail-pipe diesel exhaust, local/street diesel traffic, aged/evolved diesel particles, spark-ignition gasoline emissions, background urban emissions, heavy-duty diesel agglomerates, and secondary/transported material. Submicron (<0.5 microm) and ultrafine (<0.1 microm) particle emissions downwind of the bridge were dominated by commercial diesel truck emissions. Thus, this study obtained size distinction between fresh versus aged vehicle exhaust and spark-ignition versus diesel emissions based on the measured high time-resolution particle number concentrations. Because this study mainly used particles <300 nm in diameter, some sources that would usually exhibit number modes >100 nm were not resolved. Also, the resolved profiles suggested that the major number mode for fresh tailpipe diesel exhaust might exist below the detection limit of the spectrometer used. The average particle number contributions from the resolved factors were highest closest to the bridge.     

Particle volatility in the vicinity of a freeway with heavy-duty diesel traffic

During February–March 2006, a major field sampling campaign was conducted adjacent to the Interstate 710 (I-710) freeway in Los Angeles, CA. I-710 has high traffic volumes (ca. 11,000 vehicles h⁻¹) and a high percentage (17–18%) of heavy-duty diesel vehicle (HDDV) traffic. The volatility of ambient particles of 20, 40, 80 and 120 nm in diameter was investigated using a Tandem Differential Mobility Analyzer (TDMA) at two locations—close to the freeway (10 m) and approximately 150 m downwind. The smallest particles (20 nm) are largely volatile at both locations. Larger particles, e.g., ⩾40 nm) showed evidence of external mixing, with the non-volatile fraction increasing with particle size. Particle volatility increased with decreasing ambient temperature. The HDDVs contribute to relatively larger non-volatile particle number and volume fractions and greater external mixing than earlier observations at a pure light-duty gasoline vehicle freeway [Kuhn et al., 2005c. Atmospheric Environment 39, 7154–7166]. Finally, the fraction of externally mixed soot particles decreased as the downwind distance increased from the I-710, due to atmospheric processes such as vapor adsorption and condensation as well as particle coagulation.     

Evaluating Speed Differences between Passenger Vehicles and Heavy Trucks for Transportation-Related Emissions Modeling

Abstract

Heavy-duty trucks make up only 3% of the on-road vehicle fleet, yet they account for >7% of vehicle miles traveled in the United States. They also contribute a significant proportion of regulated ambient emissions. Heavy vehicles emit emissions at different rates than passenger vehicles. They may also behave differently on‐road, yet may be treated similarly to passenger vehicles in emissions modeling. Input variables to the MOBILE software, such as average vehicle speed, are typically specified the same for heavy trucks as for passenger vehicles. Although not frequently considered in modeling emissions, speed differences between passenger vehicles and heavy trucks may influence emissions, because emission rates are correlated to average speed. Differences were evaluated by collecting average and spot speeds for heavy trucks and passenger vehicles on arterials and spot speeds on freeways in Des Moines, IA, and Minneapolis/St. Paul, MN. Speeds were compared by study site. Space mean speeds for heavy trucks were lower than passenger vehicle speeds for all of the arterials with differences ranging from 0.8 to 19 mph. Spot speeds for heavy trucks were also lower at all of the arterial and freeway locations with differences ranging from 0.8 to 6.1 mph. The impact that differences in on‐road speeds had on emissions was also evaluated using MOBILE version 6.2. Misspecification of average truck speed is the most significant at lower and higher speed ranges.     

Environmental factors affecting the frequency of road traffic accidents: a case study of sub-urban area of Pakistan

Road traffic accidents (RTAs) are among the life-threatening issues facing rural as well as sub-/urban communities. Several factors contribute to RTAs ranging from human to technical and natural/environmental impacts. Anthropogenic air pollution and corresponding environmental factors also increase the probability of RTAs. Current study reports the relationship of the weather conditions to RTAs. The study establishes the relevancy of different weather conditions like rainfall, temperature, fog, and wind storm with the incidences of RTAs in rural and urban settings of Vehari, Punjab—Pakistan. The results of the study showed that rainfall, severe coldness, fog, and heat conditions were directly related with the occurrence of RTAs. The percentage of RTAs which occurred due to fog, rainfall, temperature, and other weather-related factors was 34, 25, 21, and 20%, respectively. The age of the driver significantly correlated (R²?=?0.60) with RTAs; the drivers in the age group 40–60 years caused the least RTAs during their drive. Since the smaller vehicles were involved in maximum RTAs, it relates negatively (R²?=?0.82) to vehicles power. Among different vehicles motor bikes were involved in most (42%) of the reported RTAs. Therefore, during severe weather conditions, vehicles with smaller size and young drivers must be dealt with carefully while interacting (crossing, overtaking, and maneuvering) on the roads regardless of rural or urban conditions. Factors including civic sense, traffic education, vehicle size, drivers’ maturity, road conditions, and environmental impacts may be considered while designing traffic rules and traffic aware campaigns specific for developing countries such as Pakistan.

     

Demolition of high-rise public housing increases particulate matter air pollution in communities of high-risk asthmatics

Public housing developments across the United States are being demolished, potentially increasing local concentrations of particulate matter (PM) in communities with high burdens of severe asthma. Little is known about the impact of demolition on local air quality. At three public housing developments in Chicago, IL, PM with an aerodynamic diameter < 10 microm (PM10) and < 2.5 microm were measured before and during high-rise demolition. Additionally, size-selective sampling and real-time monitoring were concurrently performed upwind and downwind of one demolition site. The concentration of particulates attributable to demolition was estimated after accounting for background urban air pollution. Particle microscopy was performed on a small number of samples. Substantial increases of PM10 occurred during demolition, with the magnitude of that increase varying based on sampler distance, wind direction, and averaging time. During structural demolition, local concentrations of PM10 42 m downwind of a demolition site increased 4- to 9-fold above upwind concentrations (6-hr averaging time). After adjusting for background PM10, the presence of dusty conditions was associated with a 74% increase in PM10 100 m downwind of demolition sites (24-hr averaging times). During structural demolition, short-term peaks in real-time PM10 (30-sec averaging time) occasionally exceeded 500 microg/m(3). The median particle size downwind of a demolition site (17.3 microm) was significantly larger than background (3 microm). Specific activities are associated with realtime particulate measures. Microscopy did not identify asbestos or high concentrations of mold spores. In conclusion, individuals living near sites of public housing demolition are at risk for exposure to high particulate concentrations. This increase is characterized by relatively large particles and high short-term peaks in PM concentration.     

Air pollutant concentrations near three Texas roadways, part II: Chemical characterization and transformation of pollutants

Spatial gradients of vehicular emitted air pollutants were measured in the vicinity of three roadways in the Austin, Texas area: (1) State Highway 71 (SH-71), a heavily traveled arterial highway dominated by passenger vehicles; (2) Interstate 35 (I-35), a limited access highway north of Austin in Georgetown; and (3) Farm to Market Road 973 (FM-973), a heavily traveled surface roadway with significant truck traffic. A mobile monitoring platform was used to characterize the gradients of CO and NO_x concentrations with increased distance from each roadway, while concentrations of carbonyls in the gas-phase and fine particulate matter mass and composition were measured at stationary sites upwind and at one (I-35 and FM-973) or two (SH-71) downwind sites. Regardless of roadway type or wind direction, concentrations of carbon monoxide (CO), nitric oxide (NO), and oxides of nitrogen (NO_x) returned to background levels within a few hundred meters of the roadway. Under perpendicular wind conditions, CO, NO and NO_x concentrations decreased exponentially with increasing distance perpendicular to the roadways. The decay rate for NO was more than a factor of two greater than for CO, and it comprised a larger fraction of NO_x closer to the roadways than further downwind suggesting the potential significance of near roadway chemical processing as well as atmospheric dilution. Concentrations of most carbonyl species decreased with distance downwind of SH-71. However, concentrations of acetaldehyde and acrolein increased farther downwind of SH-71, suggesting chemical generation from the oxidation of primary vehicular emissions. The behavior of particle-bound organic species was complex and further investigation of the size-segregated chemical composition of particulate matter (PM) at increasing downwind distances from roadways is warranted. Fine particulate matter (PM_2.5) mass concentrations, polycyclic aromatic hydrocarbons (PAHs), hopanes, and elemental carbon (EC) concentrations generally exhibited concentrations that decreased with distance downwind of SH-71. Concentrations of organic carbon (OC) increased from upwind concentrations immediately downwind of SH-71 and continued to increase further downwind from the roadway. This behavior may have primarily resulted from condensation of semi-volatile organic species emitted from vehicle sources with transport downwind of the roadway.