Emission of volatile organic compounds (VOCs) is one of the major contributors to air pollution. The main sources of VOCs are petroleum refineries, fuel combustions, chemical industries, decomposition in the biosphere and biomass, pharmaceutical plants, automobile industries, textile manufacturers, solvents processes, cleaning products, printing presses, insulating materials, office supplies, printers etc. The most common VOCs are halogenated compounds, aldehydes, alcohols, ketones, aromatic compounds, and ethers. High concentrations of these VOCs can cause irritations, nausea, dizziness, and headaches. Some VOCs are also carcinogenic for both humans and animals. Therefore, it is crucial to minimize the emission of VOCs. Among the available technologies, the catalytic oxidation of VOCs is the most popular because of its versatility of handling a range of organic emissions under mild operating conditions. Due to that fact, there are numerous research initiatives focused on developing advanced technologies for the catalytic destruction of VOCs. This review discusses recent developments in catalytic systems for the destruction of VOCs. Review also describes various VOCs and their sources of emission, mechanisms of catalytic destruction, the causes of catalyst deactivation, and catalyst regeneration methods.
Urban vegetation affects air quality through influencing pollutant deposition and dispersion. Both processes are described by many existing models and experiments, on-site and in wind tunnels, focussing e.g. on urban street canyons and crossings or vegetation barriers adjacent to traffic sources. There is an urgent need for well-structured experimental data, including detailed empirical descriptions of parameters that are not the explicit focus of the study. This review revealed that design and choice of urban vegetation is crucial when using vegetation as an ecosystem service for air quality improvements. The reduced mixing in trafficked street canyons on adding large trees increases local air pollution levels, while low vegetation close to sources can improve air quality by increasing deposition. Filtration vegetation barriers have to be dense enough to offer large deposition surface area and porous enough to allow penetration, instead of deflection of the air stream above the barrier. The choice between tall or short and dense or sparse vegetation determines the effect on air pollution from different sources and different particle sizes.
Road traffic is one of the main sources of particulate matter in the atmosphere. Despite its importance, there are significant challenges in quantitative evaluation of its contribution to airborne concentrations. This article first reviews the nature of the particle emissions from road vehicles including both exhaust and non-exhaust (abrasion and re-suspension sources). It then briefly reviews the various methods available for quantification of the road traffic contribution. This includes tunnel/roadway measurements, twin site studies, use of vehicle-specific tracers and other methods. Finally, the application of receptor modelling methods is briefly described. Based on the review, it can be concluded that while traffic emissions continue to contribute substantially to primary PM emissions in urban areas, quantitative knowledge of the contribution, especially of non-exhaust emissions to PM concentrations remain inadequate.
A global assessment of precipitation chemistry and deposition has been carried out under the direction of the World Meteorological Organization (WMO) Global Atmosphere Watch (GAW) Scientific Advisory Group for Precipitation Chemistry (SAG-PC). The assessment addressed three questions: (1) what do measurements and model estimates of precipitation chemistry and wet, dry and total deposition of sulfur, nitrogen, sea salt, base cations, organic acids, acidity, and phosphorus show globally and regionally? (2) has the wet deposition of major ions changed since 2000 (and, where information and data are available, since 1990) and (3) what are the major gaps and uncertainties in our knowledge? To that end, regionally-representative measurements for two 3-year-averaging periods, 2000–2002 and 2005–2007, were compiled worldwide. Data from the 2000–2002 averaging period were combined with 2001 ensemble-mean modeling results from 21 global chemical transport models produced in Phase 1 of the Coordinated Model Studies Activities of the Task Force on Hemispheric Transport of Air Pollution (TF HTAP). The measurement data and modeling results were used to generate global and regional maps of major ion concentrations in precipitation and deposition. A major product of the assessment is a database of quality assured ion concentration and wet deposition data gathered from regional and national monitoring networks. The database is available for download from the World Data Centre for Precipitation Chemistry ( ). The assessment concludes that global concentrations and deposition of sulfur and nitrogen are reasonably well characterized with levels generally highest near emission sources and more than an order of magnitude lower in areas largely free of anthropogenic influences. In many parts of the world, wet deposition of reduced nitrogen exceeds that of oxidized nitrogen and is increasing. Sulfur and nitrogen concentrations and deposition in North America and Europe have declined significantly in line with emission reduction policies. Major regions of the world, including South America, the more remote areas of North America, much of Asia, Africa, Oceania, polar regions, and all of the oceans, are inadequately sampled for all of the major ions in wet and dry deposition, and particularly so for phosphorus, organic forms of nitrogen, and weak acids including carbonates and organic acids. Measurement-based inferential estimates of dry deposition are limited to sulfur and some nitrogen in only a few regions of the world and methods are highly uncertain. The assessment concludes with recommendations to address major gaps and uncertainties in global ion concentration and deposition measurements.
Estimating within-city variability in air pollution concentrations is important. Land use regression (LUR) models are able to explain such small-scale within-city variations. Transparency in LUR model development methods is important to facilitate comparison of methods between different studies. We therefore developed LUR models in a standardized way in 36 study areas in Europe for the ESCAPE (European Study of Cohorts for Air Pollution Effects) project. Nitrogen dioxide (NO ) and nitrogen oxides (NO ) were measured with Ogawa passive samplers at 40 or 80 sites in each of the 36 study areas. The spatial variation in each area was explained by LUR modelling. Centrally and locally available Geographic Information System (GIS) variables were used as potential predictors. A leave-one out cross-validation procedure was used to evaluate the model performance. There was substantial contrast in annual average NO and NO concentrations within the study areas. The model explained variances ( ) of the LUR models ranged from 55% to 92% (median 82%) for NO and from 49% to 91% (median 78%) for NO . For most areas the cross-validation was less than 10% lower than the model . Small-scale traffic and population/household density were the most common predictors. The magnitude of the explained variance depended on the contrast in measured concentrations as well as availability of GIS predictors, especially traffic intensity data were important. In an additional evaluation, models in which local traffic intensity was not offered had 10% lower compared to models in the same areas in which these variables were offered. Within the ESCAPE project it was possible to develop LUR models that explained a large fraction of the spatial variance in measured annual average NO and NO concentrations. These LUR models are being used to estimate outdoor concentrations at the home addresses of participants in over 30 cohort studies. ► LUR models were developed in 36 study areas in Europe using a standardized approach. ► NO models explained a large fraction of concentration variability (median 82%). ► Local traffic intensity data were important predictors for LUR model development.
For reducing health impacts from air pollution, it is important to know the sources contributing to human exposure. This study systematically reviewed and analysed available source apportionment studies on particulate matter (of diameter of 10 and 2.5 microns, PM and PM ) performed in cities to estimate typical shares of the sources of pollution by country and by region. A database with city source apportionment records, estimated with the use of receptor models, was also developed and available at the website of the World Health Organization. Systematic Scopus and Google searches were performed to retrieve city studies of source apportionment for particulate matter. Six source categories were defined. Country and regional averages of source apportionment were estimated based on city population weighting. A total of 419 source apportionment records from studies conducted in cities of 51 countries were used to calculate regional averages of sources of ambient particulate matter. Based on the available information, globally 25% of urban ambient air pollution from PM is contributed by traffic, 15% by industrial activities, 20% by domestic fuel burning, 22% from unspecified sources of human origin, and 18% from natural dust and salt. The available source apportionment records exhibit, however, important heterogeneities in assessed source categories and incompleteness in certain countries/regions. Traffic is one important contributor to ambient PM in cities. To reduce air pollution in cities and the substantial disease burden it causes, solutions to sustainably reduce ambient PM from traffic, industrial activities and biomass burning should urgently be sought. However, further efforts are required to improve data availability and evaluation, and possibly to combine with other types of information in view of increasing usefulness for policy making.
Particulate matter (PM) is a complex, heterogeneous mixture that changes in time and space. It encompasses many different chemical components and physical characteristics, many of which have been cited as potential contributors to toxicity. Each component has multiple sources, and each source generates multiple components. Identifying and quantifying the influences of specific components or source-related mixtures on measures of health-related impacts, especially when particles interact with other co-pollutants, therefore represents one of the most challenging areas of environmental health research. Current knowledge does not allow precise quantification or definitive ranking of the health effects of PM emissions from different sources or of individual PM components and indeed, associations may be the result of multiple components acting on different physiological mechanisms. Some results do suggest a degree of differential toxicity, namely more consistent associations with traffic-related PM emissions, fine and ultrafine particles, specific metals and elemental carbon and a range of serious health effects, including increased morbidity and mortality from cardiovascular and respiratory conditions. A carefully targeted programme of contemporary toxicological and epidemiological research, incorporating more refined approaches (e.g. greater speciation data, more refined modelling techniques, accurate exposure assessment and better definition of individual susceptibility) and optimal collaboration amongst multidisciplinary teams, is now needed to advance our understanding of the relative toxicity of particles from various sources, especially the components and reactions products of traffic. This will facilitate targeted abatement policies, more effective pollution control measures and ultimately, a reduction in the burden of disease attributable to ambient PM pollution. ► Identifying toxic component(s) of particulate matter is a major challenge. ► Evidence suggesting differential toxicity of components and sources are discussed. ► Targeted and contemporary studies are needed to further understand relative toxicity of particles. ► Goals of refined research are abatement policies, pollution control measures and improved health.
Measurements at appropriate spatial and temporal scales are essential for understanding and monitoring spatially heterogeneous environments with complex and highly variable emission sources, such as in urban areas. However, the costs and complexity of conventional air quality measurement methods means that measurement networks are generally extremely sparse. In this paper we show that miniature, low-cost electrochemical gas sensors, traditionally used for sensing at parts-per-million (ppm) mixing ratios can, when suitably configured and operated, be used for parts-per-billion (ppb) level studies for gases relevant to urban air quality. Sensor nodes, in this case consisting of multiple individual electrochemical sensors, can be low-cost and highly portable, thus allowing the deployment of scalable high-density air quality sensor networks at fine spatial and temporal scales, and in both static and mobile configurations. In this paper we provide evidence for the performance of electrochemical sensors at the parts-per-billion level, and then outline results obtained from deployments of networks of sensor nodes in both an autonomous, high-density, static network in the wider Cambridge (UK) area, and as mobile networks for quantification of personal exposure. Examples are presented of measurements obtained with both highly portable devices held by pedestrians and cyclists, and static devices attached to street furniture. The widely varying mixing ratios reported by this study confirm that the urban environment cannot be fully characterised using sparse, static networks, and that measurement networks with higher resolution (both spatially and temporally) are required to quantify air quality at the scales which are present in the urban environment. We conclude that the instruments described here, and the low-cost/high-density measurement philosophy which underpins it, have the potential to provide a far more complete assessment of the high-granularity air quality structure generally observed in the urban environment, and could ultimately be used for quantification of human exposure as well as for monitoring and legislative purposes. ► Suitably configured electrochemical sensors can be used for air quality studies. ► Evidence of performance of electrochemical sensors at parts-per-billion levels. ► Sensors are sensitive, low noise, highly linear and generally highly selective. ► Measurement density (space and time) unachievable using current methods. ► Show low-cost air quality sensor networks are now feasible for widespread use.
The North China Plain (NCP) and the Yangtze River Delta (YRD) in China have been experiencing severe particulate matter (PM) pollution problems associated with the rapid economic growth and the accelerated urbanization. In this study, hourly mass concentrations of PM and PM during June 1st–August 31st, 2013 were collected in 13 cities located in or adjacent to the NCP region and 20 cities located in the YRD region. The overall average PM and PM concentrations were 77.0 μg/m and 136.2 μg/m in the NCP region, respectively, and 42.8 μg/m and 74.9 μg/m in the YRD region, respectively. The frequencies of occurrence of concentrations exceeding the China's Ambient Air Quality Standard (AAQS) (BG3095-12) Grade I standards were 83% for PM and 93% for PM in the NCP region, and 51% for PM and 66% for PM in the YRD region. Strong temporal correlation for both PM and PM between cities within 250 km was frequently observed. PM was found to be negatively associated with wind speed. On the PM episode days (when the 24 h PM concentration is greater than 75 μg/m ), average PM concentrations were 2–4 times greater compared to the non-episode days. The PM to PM ratio increased from 0.50 (0.57) on the non-episode days to 0.64 (0.64) on the episode days in the NCP (YRD) region. No distinct weekday/weekend difference was observed for PM , PM , and other gaseous pollutants (CO, SO , NO , and O ) in all cities. The results presented in this paper will serve as an important basis for future regional air quality modeling and source apportionment studies.
In the paper a novel hybrid model combining air mass trajectory analysis and wavelet transformation to improve the artificial neural network (ANN) forecast accuracy of daily average concentrations of PM two days in advance is presented. The model was developed from 13 different air pollution monitoring stations in Beijing, Tianjin, and Hebei province (Jing-Jin-Ji area). The air mass trajectory was used to recognize distinct corridors for transport of “dirty” air and “clean” air to selected stations. With each corridor, a triangular station net was constructed based on air mass trajectories and the distances between neighboring sites. Wind speed and direction were also considered as parameters in calculating this trajectory based air pollution indicator value. Moreover, the original time series of PM concentration was decomposed by wavelet transformation into a few sub-series with lower variability. The prediction strategy applied to each of them and then summed up the individual prediction results. Daily meteorological forecast variables as well as the respective pollutant predictors were used as input to a multi-layer perceptron (MLP) type of back-propagation neural network. The experimental verification of the proposed model was conducted over a period of more than one year (between September 2013 and October 2014). It is found that the trajectory based geographic model and wavelet transformation can be effective tools to improve the PM forecasting accuracy. The root mean squared error (RMSE) of the hybrid model can be reduced, on the average, by up to 40 percent. Particularly, the high PM days are almost anticipated by using wavelet decomposition and the detection rate (DR) for a given alert threshold of hybrid model can reach 90% on average. This approach shows the potential to be applied in other countries’ air quality forecasting systems.
This paper presents the 2005 global inventory of anthropogenic emissions to the atmosphere component of the work that was prepared by UNEP and AMAP as a contribution to the UNEP report ( ). It describes the methodology applied to compile emissions data on the two main components of the inventory – the ‘by-product’ emissions and the ‘intentional use’ emissions – and to geospatially distribute these emissions estimates to produce a gridded dataset for use by modelers, and the results of this work. It also presents some initial results of work to develop (simplified) scenario emissions inventories for 2020 that can be used to investigate the possible implications of actions to reduce mercury emissions at the global scale.
Intensifying the proportion of urban green infrastructure has been considered as one of the remedies for air pollution levels in cities, yet the impact of numerous vegetation types deployed in different built environments has to be fully synthesised and quantified. This review examined published literature on neighbourhood air quality modifications by green interventions. Studies were evaluated that discussed personal exposure to local sources of air pollution under the presence of vegetation in open road and built-up street canyon environments. Further, we critically evaluated the available literature to provide a better understanding of the interactions between vegetation and surrounding built-up environments and ascertain means of reducing local air pollution exposure using green infrastructure. The net effects of vegetation in each built-up environment are also summarised and possible recommendations for the future design of green infrastructure are proposed. In a street canyon environment, high-level vegetation canopies (trees) led to a deterioration in air quality, while low-level green infrastructure (hedges) improved air quality conditions. For open road conditions, wide, low porosity and tall vegetation leads to downwind pollutant reductions while gaps and high porosity vegetation could lead to no improvement or even deteriorated air quality. The review considers that generic recommendations can be provided for vegetation barriers in open road conditions. Green walls and roofs on building envelopes can also be used as effective air pollution abatement measures. The critical evaluation of the fundamental concepts and the amalgamation of key technical features of past studies by this review could assist urban planners to design and implement green infrastructures in the built environment.
A review was conducted of the published literature on source apportionment of ambient particulate matter (PM) in Europe using receptor models (RMs). Consistent records were identified for source contribution estimates of PM mass concentrations for 272 records and of organic carbon (OC) in PM for 60 records. Over the period 2000–2012, a shift was observed in the use of RMs from principal component analysis, enrichment factors, and classical factor analysis to Positive Matrix Factorization while Chemical Mass Balance is still topical. Following a meta-analysis of the published results, six major source categories for PM were defined that comprise almost all individual sources apportioned in Europe: atmospheric formation of secondary inorganic aerosol (SIA), traffic, re-suspension of crustal/mineral dust, biomass burning, (industrial) point sources, and sea/road salt. For the OC fraction, the three main source categories were: atmospheric formation of secondary organic aerosol, biomass burning, and fossil fuel combustion. The geographical and seasonal variations of these sources are mapped and discussed. A special analysis of PM concentrations that exceed the current European air quality limits indicated SIA and traffic as the most important source categories to target for abatement throughout the year together with biomass burning during the cold season. ► Receptor models evolve towards tools with refined uncertainty treatment. ► Positive Matrix Factorization and Chemical Mass Balance are the most used models. ► Gas-to-particle conversion is the main PM mass and particulate organic carbon source. ► To abate exceedances, secondary inorganic and traffic are the main sources to target. ► More long term speciated PM datasets would foster source identification studies.
The ESCAPE study (European Study of Cohorts for Air Pollution Effects) investigates relationships between long-term exposure to outdoor air pollution and health using cohort studies across Europe. This paper analyses the spatial variation of PM , PM absorbance, PM and PM concentrations between and within 20 study areas across Europe. We measured NO , NO , PM , PM absorbance and PM between October 2008 and April 2011 using standardized methods. PM was determined as the difference between PM and PM . In each of the twenty study areas, we selected twenty PM monitoring sites to represent the variability in important air quality predictors, including population density, traffic intensity and altitude. Each site was monitored over three 14-day periods spread over a year, using Harvard impactors. Results for each site were averaged after correcting for temporal variation using data obtained from a reference site, which was operated year-round. Substantial concentration differences were observed between and within study areas. Concentrations for all components were higher in Southern Europe than in Western and Northern Europe, but the pattern differed per component with the highest average PM concentrations found in Turin and the highest PM in Heraklion. Street/urban background concentration ratios for PM (mean ratio 1.42) were as large as for PM absorbance (mean ratio 1.38) and higher than those for PM (1.14) and PM (1.23), documenting the importance of non-tailpipe emissions. Correlations between components varied between areas, but were generally high between NO and PM absorbance (average = 0.80). Correlations between PM and PM were lower (average = 0.39). Despite high correlations, concentration ratios between components varied, e.g. the NO /PM ratio varied between 0.67 and 3.06. In conclusion, substantial variability was found in spatial patterns of PM , PM absorbance, PM and PM . The highly standardized measurement of particle concentrations across Europe will contribute to a consistent assessment of health effects across Europe. ► We used one method to measure PM , PM absorbance & PM in 20 European areas. ► We studied contrasts of these metrics and PM within andbetweenall 20 areas.► Concentrationswerehigher in Southern than in Western and Northern European areas.► Within-area contrasts varied by area andwerelarger for PM absorbance & PM . ► Concentration ratios of particle metrics and NO varied significantly across areas.
Amines are emitted by a wide range of sources and are ubiquitous atmospheric organic bases. Approximately 150 amines and about 30 amino acids have been identified in the atmosphere. We review the present knowledge of atmospherically relevant amines with respect to their sources, fluxes, and dynamics including gas-phase reactions, gas-to-particle conversion and deposition. The health effects of aliphatic and aromatic amines are briefly summarized as well as the atmospheric occurrence and reactivity of amino acids and urea. ► 154 amines, 32 amino acids and urea have been identified in the atmosphere. ► Sources, fluxes, and dynamics of atmospheric amines and amino acids are reviewed. ► Health effects of aliphatic and aromatic amines are briefly summarized.
The bioaccessibility and human health risks of As and heavy metals (Cu, Pb, Zn, Ni, Co, Cr, Cd and Mn) in total suspended particulates (TSP) and fine particulate matter (PM2.5) in Nanjing, China were investigated. The average mass concentration ratios of PM2.5 to TSP were 0.61 for Gulou sampling site and 0.50 for Pukou sampling site, respectively. Zn, Pb, Mn and Cu were the most abundant elements among the studied metal(loid)s in both TSP and PM2.5. The results of a simple bioaccessibility extraction test of the studied metal(loid)s varied among elements, with Cd, Zn, Mn, Pb and As showing the higher bioaccessibility. The carcinogenic risks of As, Cd, Co, Cr and Ni in both TSP and PM2.5 via dermal contact and inhalation exposure were within the acceptable level (<1 × 10 ) for both children and adults, but there was potential carcinogenic risk posed by Pb via ingestion to children and adults. The hazard index values for all of the studied elements suggested no non-carcinogenic health risks via ingestion and dermal contact, but a potential non-carcinogenic health risk via inhalation to adults. Values of hazard quotient and hazard index indicated the non-carcinogenic risks from the studied metal(loid)s to children via ingestion, dermal contact and inhalation pathways in Nanjing given the present air quality. ► Bioaccessibility of metal(loid)s in aerosols (TSP and PM2.5) were analyzed using SBET. ► Zn, Pb, Mn and Cu were the most abundant contaminants in both TSP and PM2.5. ► Pb, As and Co in TSP/PM2.5 were the main exposure contaminants for children. ► Main risks for adults resulted from inhalation exposure of TSP and PM2.5. ► Health risk from metal(loid)s in PM2.5 is higher than that in TSP.
Pollutant emissions need to be accurately estimated to ensure that air quality plans are designed and implemented appropriately. (EFs) are empirical functional relations between pollutant emissions and the activity that causes them. In this review article, the techniques used to measure road vehicle emissions are examined in relation to the development of EFs found in used to produce emission inventories. The emission measurement techniques covered include those most widely used for road vehicle emissions data collection, namely chassis and engine dynamometer measurements, remote sensing, road tunnel studies and portable emission measurements systems (PEMS). The main advantages and disadvantages of each method with regards to emissions modelling are presented. A review of the ways in which EFs may be derived from test data is also performed, with a clear distinction between data obtained under controlled conditions (engine and chassis dynamometer measurements using standard driving cycles) and measurements under real-world operation. ► The accuracy of road emission models is directly linked to the quality of their emission factors. ► Road vehicles have a large natural variability in their emission profiles. ► Emission factors may have different resolution according to their intended use. ► Emission modellers should combine laboratory data with real-world measurements.
Air quality is strongly dependent on weather and is therefore sensitive to climate change. Recent studies have provided estimates of this climate effect through correlations of air quality with meteorological variables, perturbation analyses in chemical transport models (CTMs), and CTM simulations driven by general circulation model (GCM) simulations of 21st-century climate change. We review these different approaches and their results. The future climate is expected to be more stagnant, due to a weaker global circulation and a decreasing frequency of mid-latitude cyclones. The observed correlation between surface ozone and temperature in polluted regions points to a detrimental effect of warming. Coupled GCM–CTM studies find that climate change alone will increase summertime surface ozone in polluted regions by 1–10 ppb over the coming decades, with the largest effects in urban areas and during pollution episodes. This climate penalty means that stronger emission controls will be needed to meet a given air quality standard. Higher water vapor in the future climate is expected to decrease the ozone background, so that pollution and background ozone have opposite sensitivities to climate change. The effect of climate change on particulate matter (PM) is more complicated and uncertain than for ozone. Precipitation frequency and mixing depth are important driving factors but projections for these variables are often unreliable. GCM–CTM studies find that climate change will affect PM concentrations in polluted environments by ±0.1–1 μg m over the coming decades. Wildfires fueled by climate change could become an increasingly important PM source. Major issues that should be addressed in future research include the ability of GCMs to simulate regional air pollution meteorology and its sensitivity to climate change, the response of natural emissions to climate change, and the atmospheric chemistry of isoprene. Research needs to be undertaken on the effect of climate change on mercury, particularly in view of the potential for a large increase in mercury soil emissions driven by increased respiration in boreal ecosystems.
Due to its rapidly expanding economic and industrial developments, China is currently considered to be the engine of the world's economic growth. China's economic growth has been accompanied by an expansion of the urban area population and the emergence of a number of mega cities since the 1990. This expansion has resulted in tremendous increases in energy consumption, emissions of air pollutants and the number of poor air quality days in mega cities and their immediate vicinities. Air pollution has become one of the top environmental concerns in China. Currently, Beijing, Shanghai, and the Pearl River Delta region including Guangzhou, Shenzhen and Hong Kong, and their immediate vicinities are the most economically vibrant regions in China. They accounted for about 20% of the total GDP in China in 2005. These are also areas where many air pollution studies have been conducted, especially over the last 6 years. Based on these previous studies, this review presents the current state of understanding of the air pollution problems in China's mega cities and identifies the immediate challenges to understanding and controlling air pollution in these densely populated areas.