Current and future emission estimates of exhaust gases and particles from shipping at the largest port in Korea

The emissions of exhaust gases (NO _x , SO₂, VOCs, and CO₂) and particles (e.g., PM) from ships traversing Busan Port in Korea were estimated over three different years (the years 2006, 2008, and 2009). This analysis was performed according to the ship operational modes (“at sea,” “maneuvering,” and “in port”) and ship types based on an activity-based method. The ship emissions for current (base year 2009) and future scenarios (years 2020 and 2050) were also compared. The annual emissions of SO₂, VOCs, PM, and CO₂ were highest (9.6?×?10³, 374, 1.2?×?10³, and 5.6?×?10⁵ ton year^?1, respectively) in 2008. In contrast, the annual NO _x emissions were highest (11.7?×?10³ ton year^?1) in 2006 due mainly to the high NO _x emission factor. The emissions of air pollutants for each ship operational mode differed considerably, with the largest emission observed in “in port” mode. In addition, the largest fraction (approximately 45–67 %) of the emissions of all air pollutants during the study period was emitted from container ships. The future ship emissions of most pollutants (except for SO₂ and PM) in 2020 and 2050 are estimated to be 1.4–1.8 and 4.7–6.1 times higher than those in 2009 (base year), respectively.     

Ship emissions and their externalities for the port of Piraeus – Greece

Air pollution from shipping is currently dominating the international and European agenda on environmental protection. Although port emissions are not significantly contributing to the overall picture of ship-generated emissions, it is important to note that the impact of ship exhaust pollutants has a direct effect on the human population and built environment of many urbanized ports. The passenger (main) port of Piraeus qualifies for a ship emission and externality study by virtue of its dominant presence in the Mediterranean expressed in terms of the most frequent port calls by coastal passenger ships and cruise ships operating in the region, as well as in terms of being a most crowded port city through hosting a sizeable resident and visiting (employers and otherwise) population over a relatively small area.An in-port ship activity-based methodology was applied for manoeuvring and berthing of coastal passenger ships and cruise ships calling at the passenger port of Piraeus, in order to estimate the emission of the main ship exhaust pollutants (NO_X, SO₂ and PM_2.5) over a twelve-month period in 2008–2009. The estimated emissions were analyzed in terms of gas species, seasonality, activity and shipping sector. The application of external cost factors led to the estimation of the emission externalities, in an attempt to evaluate the economic impact of the damage emissions produce mainly upon the human population and the built environment.The results indicate that ship emissions in the passenger port of Piraeus reach 2600 tons annually and their estimated externalities over this period are around 51 million euro. Summer emissions and associated impacts are more profound and coastal passenger shipping, as opposed to cruise shipping, is the dominant contributor of emissions and associated externalities. Overall, in a port city such as Piraeus, the need to introduce stringent control on the emissions produced by passenger ships, beyond that dictated by the current 2005/33/EU Directive is very urgent.     

Time series analysis of ambient air pollution effects on daily mortality

Although the growths of ambient pollutants have been attracting public concern, the characteristic of the associations between air pollutants and mortality remains elusive. Time series analysis with a generalized additive model was performed to estimate the associations between ambient air pollutants and mortality outcomes in Shenzhen City for the period of 2012–2014. The results showed that nitrogen dioxide (NO₂)-induced excess risks (ER) of total non-accidental mortality and cardiovascular mortality were significantly increased (6.05% (95% CI 3.38%, 8.78%); 6.88% (95% CI 2.98%, 10.93%), respectively) in interquartile range (IQR) increase analysis. Also, these associations were strengthened after adjusting for other pollutants. Moreover, similar associations were estimated for sulfur dioxide (SO₂), particulate matter with an aerodynamic diameter of <10 μm (PM₁₀), and total non-accidental mortality. There were significant higher ERs of associations between PM₁₀ and mortality for men than women; while there were significant higher ERs of associations between PM₁₀/NO₂ and mortality for elders (65 or elder) than youngers (64 or younger). Season analyses showed that associations between NO₂ and total non-accidental mortality were more pronounced in hot seasons than in warm seasons. Taken together, NO₂ was positively associated with total non-accidental mortality and cardiovascular mortality in Shenzhen even when the concentrations were below the ambient air quality standard. Policy measures should aim at reducing residents’ exposure to anthropogenic NO₂ emissions.     

Analysis of the air pollution climate at a central urban background site

Measurements of air pollutants from a background site in central London are analysed. These comprise hourly data for CO, NO, NO₂, O₃, SO₂ and PM₁₀ from 1996 to 2008 and particle number count from 2001 to 2008. The data are analysed in terms of long-term trends, annual, weekly and diurnal cycles, and autocorrelation and cross-correlation functions. CO, NO and NO₂ show a typical traffic-associated pattern with two daily peaks and lesser concentrations at the weekend. Particle number count and PM₁₀ show a similar cycle, but with smaller amplitude. Ozone has an annual cycle with a maximum in May, influenced by the spring maximum in background ozone, but the diurnal and weekly cycles are dominated by losses through reaction with nitric oxide. Particle number count shows a minimum corresponding with maximum air temperatures in August, whereas the CO, NO NO₂ and SO₂ show a minimum in June/July. There is a lower particle count to NO_x ratio at the background site compared to a central London kerbside site (Marylebone Road) and a seasonal pattern in particle count to NO_x and PM₁₀ ratios consistent with loss of nanoparticles by evaporation during atmospheric transport. Sulphur dioxide peaks in the morning in summer, but at midday in winter consistent with emissions from elevated sources mixing down from aloft as the diurnal mixed layer deepens. Implications for epidemiological studies of air quality and health are discussed. Sulphur dioxide, carbon monoxide, nitric oxide and nitrogen dioxide show clear downward trends over the measurement period, PM₁₀ declines initially before levels stabilised, and ozone concentrations increased.     

Exposure to hazardous air pollutants along Oba Akran road, Lagos-Nigeria

We measured toxic air pollutants along Oba Akran road in Lagos to evaluate pedestrian exposure. PM₁₀, CO, O₃, NO₂, SO₂, CH₄, noise, wind velocity and temperature were measured simultaneously with portable analyzers. Our results showed that pedestrian exposure to PM₁₀ (with an average of 274.6 μg m⁻³ for all samples) and CO (with an average of 19.27 ppm for all samples) was relatively high. CO is a traffic-related pollutant, so the influence of the local traffic emissions on CO levels is strong. The high concentration of the PM₁₀ measured at the three environments also suggests that the traffic is a major source of ultrafine particles. The overall average concentrations for the 72-day experimental period for SO₂, NO₂ and O₃ are 101.2, 62.5 and 0.32 ppb respectively, all of which are below the US national ambient air quality standards. Strong traffic impacts can be observed from the concentrations of some of these pollutants measured in these three environments. Most clear is a reflection of diesel truck traffic activity rich in black carbon concentrations. The diurnal variation of O₃ and NO₂ also showed that NO₂ was depleted by photochemically formed O₃ during the day and replenished at night as O₃ was destroyed. A multivariate statistical analysis (Principal Component Analysis, Factor Analysis) has been applied to a set of data in order to determine the contribution of different sources. It was found that the main principal components, extracted from the air pollution data, were related to gasoline combustion, oil combustion and ozone interactions.     

PAH air pollution at a Portuguese urban area: carcinogenic risks and sources identification

This study aimed to characterize air pollution and the associated carcinogenic risks of polycyclic aromatic hydrocarbon (PAHs) at an urban site, to identify possible emission sources of PAHs using several statistical methodologies, and to analyze the influence of other air pollutants and meteorological variables on PAH concentrations.The air quality and meteorological data were collected in Oporto, the second largest city of Portugal. Eighteen PAHs (the 16 PAHs considered by United States Environment Protection Agency (USEPA) as priority pollutants, dibenzo[a,l]pyrene, and benzo[j]fluoranthene) were collected daily for 24 h in air (gas phase and in particles) during 40 consecutive days in November and December 2008 by constant low-flow samplers and using polytetrafluoroethylene (PTFE) membrane filters for particulate (PM₁₀ and PM_2.5 bound) PAHs and pre-cleaned polyurethane foam plugs for gaseous compounds. The other monitored air pollutants were SO₂, PM₁₀, NO₂, CO, and O₃; the meteorological variables were temperature, relative humidity, wind speed, total precipitation, and solar radiation. Benzo[a]pyrene reached a mean concentration of 2.02 ng?m^?3, surpassing the EU annual limit value. The target carcinogenic risks were equal than the health-based guideline level set by USEPA (10^?6) at the studied site, with the cancer risks of eight PAHs reaching senior levels of 9.98?×?10^?7 in PM₁₀ and 1.06?×?10^?6 in air. The applied statistical methods, correlation matrix, cluster analysis, and principal component analysis, were in agreement in the grouping of the PAHs. The groups were formed according to their chemical structure (number of rings), phase distribution, and emission sources. PAH diagnostic ratios were also calculated to evaluate the main emission sources. Diesel vehicular emissions were the major source of PAHs at the studied site. Besides that source, emissions from residential heating and oil refinery were identified to contribute to PAH levels at the respective area. Additionally, principal component regression indicated that SO₂, NO₂, PM₁₀, CO, and solar radiation had positive correlation with PAHs concentrations, while O₃, temperature, relative humidity, and wind speed were negatively correlated.     

Total life cycle emissions of post-Panamax containerships powered by conventional fuel or natural gas

This study proposes an easy-to-apply method, the Total Life Cycle Emission Model (TLCEM), to calculate the total emissions from shipping and help ship management groups assess the impact on emissions caused by their capital investment or operation decisions. Using TLCEM, we present the total emissions of air pollutants and greenhouse gases (GHGs) during the 25-yr life cycle of 10 post-Panamax containerships under slow steaming conditions. The life cycle consists of steel production, shipbuilding, crude oil extraction and transportation, fuel refining, bunkering, and ship operation. We calculate total emissions from containerships and compare the effect of emission reduction by using various fuels. The results can be used to differentiate the emissions from various processes and to assess the effectiveness of various reduction approaches. Critical pollutants and GHGs emitted from each process are calculated. If the containerships use heavy fuel oil (HFO), emissions of CO₂ total 2.79 million tonnes (Mt), accounting for 95.37% of total emissions, followed by NO_x and SO_x emissions,which account for 2.25% and 1.30%, respectively.The most significant emissions are from the operation of the ship and originate from the main engine (ME).When fuel is switched to 100% natural gas (NG), SO_x, PM₁₀, and CO₂ emissions show remarkable reductions of 98.60%, 99.06%, and 21.70%, respectively. Determining the emission factor of each process is critical for estimating the total emissions. The estimated emission factors were compared with the values adopted by the International Maritime Organization (IMO).The proposed TLCEM may contribute to more accurate estimates of total life cycle emissions from global shipping.

Implications: We propose a total life cycle emissions model for 10 post-Panamax container ships. Using heavy fuel oil, emissions of CO₂ total 2.79 Mt, accounting for approximately 95% of emissions, followed by NO_x and SO_x emissions. Using 100% natural gas, SO_x, PM₁₀, and CO₂ emissions reduce by 98.6%, 99.1%, and 21.7%, respectively. NO_x emissions increase by 1.14% when running a dual fuel engine at low load in natural gas mode.     

Assimilative capacity–based emission load management in a critically polluted industrial cluster

In the present study, a modified approach was adopted to quantify the assimilative capacity (i.e., the maximum emission an area can take without violating the permissible pollutant standards) of a major industrial cluster (Manali, India) and to assess the effectiveness of adopted air pollution control measures at the region. Seasonal analysis of assimilative capacity was carried out corresponding to critical, high, medium, and low pollution levels to know the best and worst conditions for industrial operations. Bottom-up approach was employed to quantify sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and particulate matter (aerodynamic diameter <10 μm; PM₁₀) emissions at a fine spatial resolution of 500 × 500 m² in Manali industrial cluster. AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model), an U.S. Environmental Protection Agency (EPA) regulatory model, was used for estimating assimilative capacity. Results indicated that 22.8 tonnes/day of SO₂, 7.8 tonnes/day of NO₂, and 7.1 tonnes/day of PM₁₀ were emitted from the industries of Manali. The estimated assimilative capacities for SO₂, NO₂, and PM₁₀ were found to be 16.05, 17.36, and 19.78 tonnes/day, respectively. It was observed that the current SO₂ emissions were exceeding the estimated safe load by 6.7 tonnes/day, whereas PM₁₀ and NO₂ were within the safe limits. Seasonal analysis of assimilative capacity showed that post-monsoon had the lowest load-carrying capacity, followed by winter, summer, and monsoon seasons, and the allowable SO₂ emissions during post-monsoon and winter seasons were found to be 35% and 26% lower, respectively, when compared with monsoon season.

Implications: The authors present a modified approach for quantitative estimation of assimilative capacity of a critically polluted Indian industrial cluster. The authors developed a geo-coded fine-resolution PM₁₀, NO₂, and SO₂ emission inventory for Manali industrial area and further quantitatively estimated its season-wise assimilative capacities corresponding to various pollution levels. This quantitative representation of assimilative capacity (in terms of emissions), when compared with routine qualitative representation, provides better data for quantifying carrying capacity of an area. This information helps policy makers and regulatory authorities to develop an effective mitigation plan for air pollution abatement.     

The change in O3, SO2 and NO2 concentrations in Lithuania

Due to the dynamic nature of the atmosphere, substantial amounts of gaseous and particulate pollutants are transported to the areas distant from their sources. In order to determine the regional concentration levels of atmospheric pollutants in Lithuania, concentrations of gaseous O₃, SO₂, NO₂ and other pollutants have been measured at the Preila background station (55°20′ N and 21°00′ E, 5 m a.s.l.) since 1981. The long-term concentration data set enabled us to get temporal trends, both on a seasonal and longer time scale, to identify source areas of pollutants and to relate them to the emission data. Based on the data obtained, the different tendencies in the pollutant concentration changes were revealed. Positive trends for ozone (of 2.9% per year during 1983–2000) and a distinct negative trend for both sulphur dioxide (of 3.8% per year during 1981–2000) and nitrogen dioxide (of 3.8% per year during 1983–2000) were found. The air mass back-trajectory analysis was used to assess the source region of air pollutants transported to Lithuania. The pollutant concentration levels were compared with their emission changes in Europe and Lithuania. The general trends in SO₂ as well as in NO₂ concentrations observed are consistent with changes in SO₂ and NO₂ emissions in Europe and Lithuania.     

Air pollutants and health outcomes: Assessment of confounding by influenza

We assessed confounding of associations between short-term effects of air pollution and health outcomes by influenza using Hong Kong mortality and hospitalization data for 1996–2002.Three measures of influenza were defined: (i) intensity: weekly proportion of positive influenza viruses, (ii) epidemic: weekly number of positive influenza viruses ≥4% of the annual number for ≥2 consecutive weeks, and (iii) predominance: an epidemic period with co-circulation of respiratory syncytial virus <2% of the annual positive isolates for ≥2 consecutive weeks. We examined effects of influenza on associations between nitrogen dioxide (NO₂), sulfur dioxide (SO₂), particulate matter with aerodynamic diameter ≤10 μm (PM₁₀) and ozone (O₃) and health outcomes including all natural causes mortality, cardiorespiratory mortality and hospitalization. Generalized additive Poisson regression model with natural cubic splines was fitted to control for time-varying covariates to estimate air pollution health effects. Confounding with influenza was assessed using an absolute difference of >0.1% between unadjusted and adjusted excess risks (ER%).Without adjustment, pollutants were associated with positive ER% for all health outcomes except asthma and stroke hospitalization with SO₂ and stroke hospitalization with O₃. Following adjustment, changes in ER% for all pollutants were <0.1% for all natural causes mortality, but >0.1% for mortality from stroke with NO₂ and SO₂, cardiac or heart disease with NO₂, PM₁₀ and O₃, lower respiratory infections with NO₂ and O₃ and mortality from chronic obstructive pulmonary disease with all pollutants. Changes >0.1% were seen for acute respiratory disease hospitalization with NO₂, SO₂ and O₃ and acute lower respiratory infections hospitalization with PM₁₀. Generally, influenza does not confound the observed associations of air pollutants with all natural causes mortality and cardiovascular hospitalization, but for some pollutants and subgroups of cardiorespiratory mortality and respiratory hospitalization there was evidence to suggest confounding by influenza.     

Harbour of Ravenna: The contribution of harbour traffic to air quality

Ravenna is one of the main Italian ports and has assumed a leadership position in Italy for some products and markets. The commercial harbour and the adjacent industrial area are very important for the economic system of Ravenna but, at the same time, they are highly critical areas.In particular, on average 8000 ships per year pass through the harbour of Ravenna, influencing air quality in harbour environment.The paper originates from a study about the contribution of different sources of air pollution in Ravenna and its aim is to evaluate the maritime traffic contribution to the air quality in the port area and to determine the suitability of an urban air quality model to support the air quality management in Ravenna. NO_x and PM are selected as modelled pollutants.The study is made up of two parts. The first deals with the evaluation of annual emission of PM₁₀ and NO_x coming from ships through a standard European methodology while in the second we simulated the diffusion of these pollutants in the whole area. In order to evaluate the capability of the model to treat maritime traffic emissions, we compared hour-by-hour simulated concentrations with data collected by a fixed monitoring station located near the Candiano Canal.NO_x concentrations obtained by short- and long-term simulations show a good match with the values measured by the fixed monitoring station, located in the centre of harbour area, and these results are also supported by FA2 performance index.Instead the omission of the secondary particulate and the contribution of other sources of particulate matter in the port area are probably the most important causes of the PM₁₀ underestimation.The worse results obtained according to the performance indexes indicate the need to consider the formation and transport of secondary particulate matter in order to obtain more reliable predictions.     

Influence of ship emissions on air quality and input of contaminants in southern Alaska National Parks and Wilderness Areas during the 2006 tourist season

The impact of ship emissions on air quality in Alaska National Parks and Wilderness Areas was investigated using the Weather Research and Forecasting model inline coupled with chemistry (WRF/Chem). The visibility and deposition of atmospheric contaminants was analyzed for the length of the 2006 tourist season. WRF/Chem reproduced the meteorological situation well. It seems to have captured the temporal behavior of aerosol concentrations when compared with the few data available. Air quality follows certain predetermined patterns associated with local meteorological conditions and ship emissions. Ship emissions have maximum impacts in Prince William Sound where topography and decaying lows trap pollutants. Along sea-lanes and adjacent coastal areas, NO_x, SO₂, O₃, PAN, HNO₃, and PM_2.5 increase up to 650 pptv, 325 pptv, 900 pptv, 18 pptv, 10 pptv, and 100 ng m^?3. Some of these increases are significant (95% confidence). Enhanced particulate matter concentrations from ship emissions reduce visibility up to 30% in Prince William Sound and 5–25% along sea-lanes.     

Characteristics and origins of air pollutants in Wuhan,China, based on observations and hybrid receptor models

To identify the characteristics of air pollutants and factors attributing to the formation of haze in Wuhan, this study analyzed the hourly observations of air pollutants (PM_2.5, PM₁₀, NO₂, SO₂, O₃, and CO) from March 1, 2013, to February 28, 2014, and used hybrid receptor models for a case study. The results showed that the annual average concentrations for PM_2.5, PM₁₀, NO₂, SO₂, O₃, and CO during the whole period were 89.6 μg m^?3, 134.9 μg m^?3, 54.9 μg m^?3, 32.4 μg m^?3, 62.3 μg m^?3, and 1.1 mg m^?3, respectively. The monthly variations revealed that the peak values of PM_2.5, PM₁₀, NO₂, SO₂, and CO occurred in December because of increased local emissions and severe weather conditions, while the lowest values occurred in July mainly due to larger precipitation. The maximum O₃ concentrations occurred in warm seasons from May to August, which may be partly due to the high temperature and solar radiation. Diurnal analysis showed that hourly PM_2.5, PM₁₀, NO₂, and CO concentrations had two ascending stages accompanying by the two traffic peaks. However, the O₃ concentration variations were different with the highest concentration in the afternoon. A case study utilizing hybrid receptor models showed the significant impact of regional transport on the haze formation in Wuhan and revealed that the mainly potential polluted sources were located in the north and south of Wuhan, such as Baoding and Handan in Hebei province, and Changsha in Hunan province. Implications: Wuhan city requires a 5% reduction of the annual mean of PM_2.5 concentration by the end of 2017. In order to accomplish this goal, Wuhan has adopted some measures to improve its air quality. This work has determined the main pollution sources that affect the formation of haze in Wuhan by transport. We showed that apart from the local emissions, north and south of Wuhan were the potential sources contributing to the high PM_2.5 concentrations in Wuhan, such as Baoding and Handan in Hebei province, Zhumadian and Jiaozuo in Henan province, and Changsha and Zhuzhou in Hunan province.     

Estimating Future NO2 Levels in the Greater Los Angeles Area by Source–Type Contribution

Two indicator pollutants, carbon monoxide (CO) for mobile source influence and sulfur dioxide (SO₂) for stationary source influence, were used to estimate source-type contributions to ambient NO₂ levels in a base year and to predict NO₂ concentrations in a future year. For a specific source-receptor pair, the so-called influence coefficient of each of three source categories (mobile sources, power plants, and other stationary sources) was determined empirically from concurrent measurements of CO and SO₂ concentrations at the receptor site and CO and SO₂ emissions from each source category in the source area. Those coefficients, which are considered time invariant, were used in conjunction with the base year and future year NO _x emission values to estimate source-type contribution to ambient NO₂ levels at seven study sites selected from the Greater Los Angeles area for both the base year period, 1974 through 1976, and the future goal year of 1987 in which the air quality standards for NO₂ are to be attained. The estimated NO₂ air quality at the seven sites is found to meet the national annual standard of 5 pphm and over 99.9% of total hours, the California 1-hr NO₂ standard of 25 pphm in 1987. The estimated power plant contributions to ambient NO₂ levels are found to be considerably smaller than those to total NO _x emissions in the area. Providing that reasonably complete air quality and emissions data are available, the present analysis method may prove to be a useful tool in evaluating source contributions to both short-term peak and long-term average NO₂ concentrations for use in control strategy development.     

Major air pollutants in Bursa,Turkey: their levels,temporal changes,interactions, and sources

Bursa is one of the largest cities of Turkey and it hosts 17 organized industrial zones. Parallel to the increase in population, rapidly growing energy consumption, and increased numbers of transport vehicles have impacts on the air quality of the city. In this study, regularly calibrated automatic samplers were employed to get the levels of air pollution in Bursa. The concentrations of CH₄ and N-CH₄ as well as the major air pollutants including PM₁₀, PM_2.5, NO, NO₂, NO_x, SO₂, CO, and O₃, were determined for 2016 and 2017 calendar years. Their levels were 1641.62?±?718.25, 33.11?±?5.45, 42.10?±?10.09, 26.41?±?9.01, 19.47?±?16.51, 46.73?±?16.56, 66.23?±?32.265, 7.60?±?3.43, 659.397?±?192.73, and 51.92?±?25.63 µg/m³ for 2016, respectively. Except for O₃, seasonal concentrations were higher in winter and autumn for both years. O₃, CO, and SO₂ had never exceeded the limit values specified in the regulations yet PM₁₀, PM_2.5, and NO₂ had violated the limits in some days. The ratios of CO/NO_x, SO₂/NO_x, and PM_2.5/PM₁₀ were examined to characterize the emission sources. Generally, domestic and industrial emissions were dominated in the fall and winter seasons, yet traffic emissions were effective in spring and summer seasons. As a result of the correlation process between O_x and NO_x, it was concluded that the most important source of O_x concentrations in winter was NO_x and O₃ was in summer.     

Spatial and seasonal variations of atmospheric BTEX,sulfur dioxide,nitrogen dioxide,and ozone concentrations in Istanbul,and health risk assessment of BTEX

Volatile organic compounds (VOCs) such as benzene, toluene, ethylbenzene, and xylene (BTEX) along with inorganic gases such as sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and ozone (O₃) levels were found in the atmosphere of the Kemerburgaz region where environmental issues became a major concern due to nearby incineration plant and waste disposal facility in Istanbul. Ten sampling locations were selected considering possible sources in the study area. The sampling areas were classified as suburban, industrial, rural, and background regions. Sampling campaigns were carried out for four-week periods from March 2011 to August 2012 in all locations. Elevated concentrations of BTEX around roads and the industrial locations indicated that vehicle exhaust and industrial activities were the main sources of these pollutants in the region. Concentrations of NO₂ were also high around roads. A much more uniform distribution was observed for SO₂ during sampling periods. However higher levels were observed at suburban locations due to the use of coal for local heating especially during winter. Ozone concentrations were low at the industrial locations and roadsides, but high in suburban and rural locations downwind from the sources. The results of these organic and inorganic gases meet the national limit values. Furthermore, a lifetime risk assessment methodology was used to evaluate the potential adverse health effects of BTEX. The mean cancer risk level for benzene was estimated to be 7.71E-07 that is lower than assigned acceptable risk level of 1.0E-04. Toluene, ethylbenzene, and xylenes were lower than the specified level of 1.0 with respect to mean non-carcinogenic risks. The findings reveal that determined BTEX emissions do not pose a health threat to residents in the studied region.     

Air quality in Yanbu,Saudi Arabia

Yanbu, on the Red Sea, is an affluent Saudi Arabian industrial city of modest size. Substantial effort has been spent to balance environmental quality, especially air pollution, and industrial development. We have analyzed six years of observations of criteria pollutants O₃, SO₂, particles (PM_2.5 and PM₁₀) and the known ozone precursors—volatile organic compounds (VOCs) and nitrogen oxides (NO_x). The results suggest frequent VOC-limited conditions in which ozone concentrations increase with decreasing NO_x and with increasing VOCs when NO_x is plentiful. For the remaining circumstances ozone has a complex non-linear relationship with the VOCs. The interactions between these factors at Yanbu cause measurable impacts on air pollution including the weekend effect in which ozone concentrations stay the same or even increase despite significantly lower emissions of the precursors on the weekends. Air pollution was lower during the Eids (al-Fitr and al-Adha), Ramadan and the Hajj periods. During Ramadan, there were substantial night time emissions as the cycle everyday living is almost reversed between night and day. The exceedances of air pollution standards were evaluated using criteria from the U.S. Environmental Protection Agency (EPA), World Health Organization (WHO), the Saudi Presidency of Meteorology and Environment (PME) and the Royal Commission Environmental Regulations (RCER). The latter are stricter standards set just for Yanbu and Jubail. For the fine particles (PM_2.5), an analysis of the winds showed a major impact from desert dust. This effect had to be taken into account but still left many occasions when standards were exceeded. Fewer exceedances were found for SO₂, and fewer still for ozone. The paper presents a comprehensive view of air quality at this isolated desert urban environment.

Implications: Frequent VOC-limited conditions are found at Yanbu in Saudi Arabia that increase ozone pollution if NO_x is are reduced. In this desert environment, increased nightlife produces the highest levels of VOCs and NO_x at night rather than the day. The effects increase during Ramadan. Fine particles peak twice a day—the morning peak is caused by traffic and increases with decreasing wind, potentially representing health concerns, but the larger afternoon peak is caused by the wind, and it increases with increasing wind speeds. These features suggest that exposure to pollutants must be redefined for such an environment.     

A general method for evaluating the effects of air pollutants on lung cancer prevalence

ABSTRACT

It is widely accepted that some air pollutants are related to lung cancer prevalence. An effective method is proposed to quantitatively evaluate the effects of air pollutants and the interactions between them. The method consisted of three parts: data decomposition, comparable data generation and relationship inference. Firstly, very limited monitoring data published by Geographic Information System were applied to calculate the inhalable air pollution of relatively massive patient samples. Then the investigated area was partitioned into a number of districts, and the comparable data containing air pollutant concentrations and lung cancer prevalence in all districts were generated. Finally, the relationships between pollutants and lung cancer prevalence were concluded by an information fusion tool: Choquet integral. As an example, the proposed method was applied in the investigation of air pollution in Tianjin, China. Overall, SO₂, O₃ and PM_2.5 were the top three factors for lung cancer. And there was obvious positive interaction between O₃ and PM_2.5 and negative interaction among SO₂, O₃ and PM₁₀. The effect of SO₂ on men was larger than on women. O₃ and SO₂ were the most important factors for the adenocarcinoma and squamous cell carcinoma, respectively. The effect of SO₂ or NO₂ on squamous cell carcinoma is obviously larger than that on adenocarcinoma, while the effect of O₃ or PM_2.5 on adenocarcinoma is obviously larger than that on squamous cell carcinoma. The results provide important suggestions for management of pollutants and improvement of environmental quality. The proposed method without any parameter is general and easily realized, and it sets the foundation for further researches in other cities/countries.

Implications: For total lung cancer prevalence, male and female lung cancer prevalence, and adenocarcinoma and squamous cell carcinoma prevalence, the proposed method not only quantify the effect of single pollutant (SO₂, NO₂, CO, O₃, PM_2.5, and PM₁₀) but also reveals the correlations between different pollutants such as positive interaction or negative interaction. The proposed method without any geographic predictor and parameter is much easier to realize, and it sets the foundation for further research in other cities/countries. The study results provide important suggestions for the targeted management of different pollutants and the improvement of human lung health.     

Understanding of regional air pollution over China using CMAQ,part I performance evaluation and seasonal variation

The U.S. EPA Models-3 Community Multiscale Air Quality (CMAQ) modeling system with the process analysis tool is applied to China to study the seasonal variations and formation mechanisms of major air pollutants. Simulations show distinct seasonal variations, with higher surface concentrations of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and particulate matter with aerodynamic diameter less than or equal to 10 μm (PM₁₀), column mass of carbon monoxide (CO) and NO₂, and aerosol optical depth (AOD) in winter and fall than other seasons, and higher 1-h O₃ and troposphere ozone residual (TOR) in spring and summer than other seasons. Higher concentrations of most species occur over the eastern China, where the air pollutant emissions are the highest in China. Compared with surface observations, the simulated SO₂, NO₂, and PM₁₀ concentrations are underpredicted throughout the year with NMBs of up to ?51.8%, ?32.0%, and ?54.2%, respectively. Such large discrepancies can be attributed to the uncertainties in emissions, simulated meteorology, and deviation of observations based on air pollution index. Max. 1-h O₃ concentrations in Jan. and Jul. at 36-km are overpredicted with NMBs of 12.0% and 19.3% and agree well in Apr. and Oct. Simulated column variables can capture the high concentrations over the eastern China and low values in the central and western China. Underpredictions occur over the northeastern China for column CO in Apr., TOR in Jul., and AODs in both Apr. and Jul.; and overpredictions occur over the eastern China for column CO in Oct., NO₂ in Jan. and Oct., and AODs in Jan. and Oct. The simulations at 12-km show a finer structure in simulated concentrations than that at 36-km over higher polluted areas, but do not always give better performance than 36-km. Surface concentrations are more sensitive to grid resolution than column variables except for column NO₂, with higher sensitivity over mountain and coastal areas than other regions.     

A Statistical Assessment of Saturation and Mobile Sampling Strategies to Estimate Long-Term Average Concentrations across Urban Areast

Abstract

The objectives of this study were: (1) to quantify the errors associated with saturation air quality monitoring in estimating the long-term (i.e., annual and 5 yr) mean at a given site from four 2-week measurements, once per season; and (2) to develop a sampling strategy to guide the deployment of mobile air quality facilities for characterizing intraurban gradients of air pollutants, that is, to determine how often a given location should be visited to obtain relatively accurate estimates of the mean air pollutant concentrations. Computer simulations were conducted by randomly sampling ambient monitoring data collected in six Canadian cities at a variety of settings (e.g., population-based sites, near-roadway sites). The 5-yr (1998–2002) dataset consisted of hourly measurements of nitric oxide (NO), nitrogen dioxide (NO₂), oxides of nitrogen (NO_x), sulfur dioxide (SO₂), coarse particulate matter (PM₁₀), fine particulate matter (PM_2.5)_, and CO. The strategy of randomly selecting one 2-week measurement per season to determine the annual or long-term average concentration yields estimates within 30% of the true value 95% of the time for NO₂, PM₁₀ and NO_x. Larger errors, up to 50%, are expected for NO, SO₂, PM_2.5, and CO. Combining concentrations from 85 random 1-hr visits per season provides annual and 5-yr average estimates within 30% of the true value with good confidence. Overall, the magnitude of error in the estimates was strongly correlated with the variability of the pollutant. A better estimation can be expected for pollutants known to be less temporally variable and/or over geographic areas where concentrations are less variable. By using multiple sites located in different settings, the relationships determined for estimation error versus number of measurement periods used to determine long-term average are expected to realistically portray the true distribution. Thus, the results should be a good indication of the potential errors one could expect in a variety of different cities, particularly in more northern latitudes.