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Although studies have increasingly linked air pollution to specific health outcomes, less well understood is how public perceptions of air quality respond to changing pollutant levels. The growing availability of air pollution measurements and the proliferation of social media provide an opportunity to gauge public discussion of air quality conditions. In this paper, we consider particulate matter (PM) measurements from four Chinese megacities (Beijing, Shanghai, Guangzhou, and Chengdu) together with 112 million posts on Weibo (a popular Chinese microblogging system) from corresponding days in 2011–2013 to identify terms whose frequency was most correlated with PM levels. These correlations are used to construct an Air Discussion Index (ADI) for estimating daily PM based on the content of Weibo posts. In Beijing, the Chinese city with the most PM as measured by U.S. Embassy monitor stations, we found a strong correlation (R = 0.88) between the ADI and measured PM. In other Chinese cities with lower pollution levels, the correlation was weaker. Nonetheless, our results show that social media may be a useful proxy measurement for pollution, particularly when traditional measurement stations are unavailable, censored or misreported. [ABSTRACT FROM AUTHOR]

When assessing the short-term effect of air pollution on health outcomes, it is common practice to consider one pollutant at a time, due to their high correlation. Multi pollutant methods have been recently proposed, mainly consisting of collapsing the different pollutants into air quality indexes or clustering the pollutants and then evaluating the effect of each cluster on the health outcome. A major drawback of such approaches is that it is not possible to evaluate the health impact of each pollutant. In this paper we propose the use of the Bayesian hierarchical framework to deal with multi pollutant concentrations in a two-component model: a pollutant model is specified to estimate the ‘true’ concentration values for each pollutant and then such concentration is linked to the health outcomes in a time-series perspective. Through a simulation study we evaluate the model performance and we apply the modelling framework to investigate the effect of six pollutants on cardiovascular mortality in Greater London in 2011-2012. [ABSTRACT FROM AUTHOR]

This paper presents preliminary results about Turin’s air quality before, during and after the realization of the infrastructure projects for the Turin 2006 XX Winter Olympic Games. We compared the 3-year in-operam (work in progress) period (i.e. 2003–2005, when all infrastructures needed for the organization were built) with the periods before (ante-operam) and after (post-operam): 2000–2002 and 2006–2008, respectively. In particular, we analyzed the concentrations of the primary pollutants (nitrogen dioxide, carbon monoxide and fine particulate matter, PM10) in Turin and Milan. In this way, we could use the measurements from Milan as a control dataset for comparison with the atmospheric pollution conditions in Turin. We found that infrastructural work for the Olympic Games in Turin affected NO2 and PM10 atmospheric concentrations, determining a peak in the average values during the in-operam period (probably due to caterpillar tractor emissions and excavation). This pattern did not emerge from the Milan data, where a decreasing trend can be seen between the ante-operam and the post-operam periods. On the other hand, a negative effect on CO levels was not observed: the decreasing trend, more evident in Turin compared to Milan, can be linked to the expansion during the same period of limited traffic areas created to facilitate the infrastructural work. [ABSTRACT FROM AUTHOR]

Today, China is facing a very serious issue of Air Pollution due to its dreadful impact on the human health as well as the environment. The urban cities in China are the most affected due to their rapid industrial and economic growth. Therefore, it is of extreme importance to come up with new, better and more reliable forecasting models to accurately predict the air quality. This paper selected Beijing, Tianjin and Shijiazhuang as three cities from the Jingjinji Region for the study to come up with a new model of collaborative forecasting using Support Vector Regression (SVR) for Urban Air Quality Index (AQI) prediction in China. The present study is aimed to improve the forecasting results by minimizing the prediction error of present machine learning algorithms by taking into account multiple city multi-dimensional air quality information and weather conditions as input. The results show that there is a decrease in MAPE in case of multiple city multi-dimensional regression when there is a strong interaction and correlation of the air quality characteristic attributes with AQI. Also, the geographical location is found to play a significant role in Beijing, Tianjin and Shijiazhuang AQI prediction. [ABSTRACT FROM AUTHOR]

To attain cleaner air, it is important that authorities make informed decisions when selecting a strategy. Concentrations of particulate matter with an aerodynamic diameter of less than or equal to 2.5 μm (PM 2.5) are high in the Tokyo metropolitan area, even though concentrations of particulate matter with an aerodynamic diameter of less than or equal to 10 μm (PM10) have dropped dramatically since the implementation of the NOx-PM Act. Currently, monitored concentration levels continue to exceed the designated ambient air quality standard set by the Japanese Ministry of the Environment. To our knowledge, no study has investigated a cost-efficient strategy for reducing PM 2.5 concentration levels in the Tokyo metropolitan area. This is the first study to examine a proper control strategy for Japan by developing an integrated model that includes both aerosol and economic models. The simulation results show that prefectures in the Tokyo metropolitan area cannot achieve the standards by relying on their own efforts to reduce PM 2.5. That is, prefectural governments in the Tokyo metropolitan areas need to cooperate with prefectures outside of the area to improve their PM 2.5 concentration levels. Thus, we simulated policies under the assumption that emissions from other sources are reduced to levels such that the PM 2.5 concentration declines by approximately 18 μg/m3. We first simulated an efficient policy, i.e., the implementation of a pollution tax. We found that the total abatement cost to meet the air quality standard using the cost-efficient strategy is approximately 142.7 billion yen. [ABSTRACT FROM AUTHOR]

Air pollution is closely associated with the development of respiratory illness. Behavioral adaptations of people to air pollution may influence its impact, yet this has not been investigated in the literature. Our hypothesis is that people experience and learn the underlying air quality to decide their adaptation, and they have a stronger incentive to behaviorally adapt to the air quality as it deteriorates. We tested our hypothesis on a sample of approximately 25,700 individuals from South Korea from 2002 to 2013 that contained information on daily doctor’s visits due to respiratory disease. We matched individuals to the mean of the past seven-day concentration of the particulate matter of size between 2.5 and 10 micrometers (PM10) in their county of residence. We examined whether people living in counties with greater air pollution suffer less from respiratory disease when the concentration increases. For the analysis, we separated counties into quintiles based on their mean seven-day PM10, and regressed the binary indicator of a daily doctor’s visit with a resulting diagnosis of respiratory disease on the seven-day PM10 concentration of the county of residence interacted with the quintile dummies. The key findings are that a 1-standard-deviation increase in the seven-day PM10 concentration in the two lowest quintiles is associated with an increase of 0.054 percentage points in the likelihood of a doctor’s visit with a resulting diagnosis of respiratory disease, which is about 40% larger than the effect in higher quintiles, and the size of 1-standard-deviation gradually increases from 0.037 percentage points in the third quintile to 0.040 percentage points in the fifth quintile. The smaller increase in the likelihood of respiratory disease in more polluted locations can be explained by the behavioral adaptation to the environment, but the effectiveness of the adaptation seems limited among the highly polluted locations. [ABSTRACT FROM AUTHOR]

This study analyzes the core energy consumption among countries’ specific variables by Environmental Kuznets Curve hypothesis (EKC), for a panel data of 29 (14 developed and 15 developing) countries during the period of 1977–2014. By assessing Generalized Method of Moments (GMM) regressions with first generation tests such as common root, individual Augmented Dickey-Fuller (ADF), and individual root-Fisher-PP which have been computed individually, the results confirm the EKC hypothesis in the case of emissions of solid, liquid, gases, manufacturing industries and also construction. Hence, we computed the cointegration test by Pedroni Kao from Engle-Granger based and Fisher. Since the variables are co-integrated, a panel vector error correction model is estimated in GDP per capita, emission from manufacturing industries, arms import, commercial service export, and coal rent, in order to perform Pairwise Granger Causality test and indicate Vector Error Correction (VEC), with co-integration restrictions. Moreover, the statistical finding from VEC short-run unidirectional causality from GDP per capita growth to manufacturing industries and coal rent, as well as the causal link with manufacturing industries and commercial service export. Additionally, there occurred no causal link among economic growth, arm import and coal rent. [ABSTRACT FROM AUTHOR]

Simultaneous removal of organics, nitrogen and phosphorus was achieved in a bench-scale oxygen-limited membrane bioreactor (OLMBR). Due to the limited dissolved oxygen (~ 0.2 mg/L equilibrium concentration) and the increased sludge concentration associated with the hollow fiber membrane, the OLMBR was endowed with an excellent performance on the removal of multi-pollutants. The optimized removal efficiencies of COD, nitrogen (N), and total phosphorus (TP) were approximately 95.5%, 90.0% and 82.6%, respectively (COD/N/P = 500:10:1, influent loading = 5.0 kg COD·m-3·d-1, 35°C). Mass balance and bacterial community analysis indicated that the removal of organic carbon was mainly achieved by the methane production process (67.6%). Short-cut nitrification-denitrification (SCND) was observed as the primary denitrification process in the OLMBR, in which the concentrated organic compounds served as the electron donors for denitrification. Nitrosomonas was observed to be the predominant ammonium-oxidizing bacteria, while nitrite-oxidizing bacteria were almost absent in the microbial community as revealed by the high-throughput sequencing technique. In addition, Euryarchaeota and Candidatus, which were well associated with the process of denitrifying anaerobic methane oxidation, were also detected. Sludge absorption was the main route for TP removal in the OLMBR, and the production of PH3 gas also accounted for 19.4% of TP removal. This study suggested that the interception effect of hollow fiber membrane provided higher sludge concentration, therefore offering more bacteria for pollutant removal. The OLMBR can be used for simultaneous removal of highly concentrated organics and nutrients in livestock and poultry breeding wastewater. [ABSTRACT FROM AUTHOR]

Delhi has had the distinction of being one of the most polluted cities in the world, especially in the winter months from October—January. These months coincide with the religious festival of Diwali. It is argued that air quality gets worse in the aftermath of Diwali on account of firecrackers that get burned during the festival. We use hourly data on PM 2.5 particulate concentration from 2013 to 2017 to estimate the Diwali effect on air quality in Delhi. We improve on existing work by using the event study technique as well as a difference-in-difference regression framework to estimate the Diwali effect on air quality. The results suggest that Diwali leads to a small, but statistically significant increase in air pollution. The effect is different across locations within Delhi. To our knowledge, this is the first causal estimate of the contribution of Diwali firecracker burning to air pollution. [ABSTRACT FROM AUTHOR]

Public transport passenger demand is inevitably made non-uniform because of spatial and temporal land use planning. This non-uniformity warrants the use of public transport operational strategies to attain operating efficiency. The optimization of these strategies is commonly being done from the operator perspective, and indirectly from the user perspective. However, the environmental perspective of these strategies, in terms of vehicle’s emission, has not been investigated. This study proposed a methodology to analyze the benefits of using transit operational strategies to reduce operating cost and eventually also to reduce undesirable emissions. First, a strategy-based optimization model is established to minimize the number of transit vehicles required. Four candidate operational strategies are considered in this model, including full route operation (FRO), short turn, limited stop, and a combination of limited stop and short turn. Second, the pollutant emissions of transit vehicles are estimated by the MOVES emission model. The developed methodology is applied to a real life case study in Dalian, China. Results show that the use of operational strategies can not only significantly save the number of vehicles by 12.5%, but also reduce emissions of pollutants (i.e., CO2, HC, CO, NOx, PM2.5) by approximately 13%, compared with applying FRO strategy exclusively. In addition, both benefits can be further enhanced through the use of an efficient payment mode (e.g., off-board or contactless card) or improving bus performance in deceleration/acceleration as well as doors opening and closing at a stop. [ABSTRACT FROM AUTHOR]

There is growing evidence supporting the notion that exposure to air pollution can contribute to cognitive and psychiatric disorders, including depression and suicide. Given the relationship between exposure to acute stressors and substance abuse, the present study assessed the association between exposure to ambient air pollution and emergency department (ED) visits for alcohol and drug abuse. ED visit data selected according to International Classification of Disease (ICD-9) coding 303 (alcohol dependence syndromes) and 305 (non-dependent abuse of drugs) were collected in five hospitals in Edmonton, Canada. A time-stratified case crossover design was used. Conditional logistic regression was applied to calculate odds ratios (OR) and 95% confidence intervals (95% CI). Season, temperature, and relative humidity were adjusted for using natural splines. Results are reported for an increase in pollutant concentrations equivalent to one interquartile range (IQR). Statistically significant positive associations with substance abuse were observed for CO, NO2 and particulate matter with an aerodynamic diameter less than 10 μm (PM10) and 2.5 μm (PM2.5). The strongest results were obtained in the cold period (October–March) for 1-day lagged CO (OR = 1.03, 95% CI: 1.01, 1.05, IQR = 0.4 ppm) and NO2 (OR = 1.04, 95% CI: 1.01, 1.07, IQR = 12.8 ppb); ORs were also significant for CO and NO2 with lags of 2 to 6 days and 2 to 7 days, respectively. The study suggests that, even at low levels, increases in ambient CO, NO2, and PMs are associated with increased hospital admissions for substance abuse, possibly as a result of impacts of air quality on mental health or depression. [ABSTRACT FROM AUTHOR]

This study examines the Environmental Kuznets Curve hypothesis (EKC), considering the primary energy consumption among other country-specific variables, for a panel of the EU-28 countries during the period 1990–2014. By estimating pooled OLS regressions with Driscoll-Kraay standard errors in order to account for cross-sectional dependence, the results confirm the EKC hypothesis in the case of emissions of sulfur oxides and emissions of non-methane volatile organic compounds. In addition to pooled estimations, the output of fixed-effects regressions with Driscoll-Kraay standard errors support the EKC hypothesis for greenhouse gas emissions, greenhouse gas emissions intensity of energy consumption, emissions of nitrogen oxides, emissions of non-methane volatile organic compounds and emissions of ammonia. Additionally, the empirical findings from panel vector error correction model reveal a short-run unidirectional causality from GDP per capita growth to greenhouse gas emissions, as well as a bidirectional causal link between primary energy consumption and greenhouse gas emissions. Furthermore, since there occurred no causal link between economic growth and primary energy consumption, the neo-classical view was confirmed, namely the neutrality hypothesis. [ABSTRACT FROM AUTHOR]

The Beijing-Tianjin-Hebei area faces a severe fine particulate matter (PM2.5) problem. To date, considerable progress has been made toward understanding the PM2.5 problem, including spatial-temporal characterization, driving factors, and health effects. However, little research has been done on the dynamic interactions and relationships between PM2.5 concentrations in different cities in this area. To address the research gap, this study discovered a phenomenon of time-lagged intercity correlations of PM2.5 time series and proposed a visualization framework based on this phenomenon to visualize the interaction in PM2.5 concentrations between cities. The visualizations produced using the framework show that there are significant time-lagged correlations between the PM2.5 time series in different cities in this area. The visualizations also show that the correlations are more significant in colder months and between cities that are closer, and that there are seasonal changes in the temporal order of the correlated PM2.5 time series. Further analysis suggests that the time-lagged intercity correlations of PM2.5 time series are most likely due to synoptic meteorological variations. We argue that the visualizations demonstrate the interactions of air pollution between cities in the Beijing-Tianjin-Hebei area and the significant effect of synoptic meteorological conditions on PM2.5 pollution. The visualization framework could help determine the pathway of regional transportation of air pollution and may also be useful in delineating the area of interaction of PM2.5 pollution for impact analysis. [ABSTRACT FROM AUTHOR]

Currently, Haze is one of the greatest environmental problems with serious impacts on human health in China, especially in capital region (Beijing-Tianjin-Hebei region). To alleviate this problem, the Chinese government introduced a National Air Pollution Control Action Plan (NAPCAP) with air pollutants reduction targets by 2017. However, there is doubt whether these targets can be achieved once the plan is implemented. In this work, the effectiveness of NAPCAP is analyzed by developing models of the statistical relationship between PM2.5 concentrations and air pollutant emissions (SO2, NOx, smoke and dust), while taking into account wind and neighboring transfer impacts. The model can also identify ways of calculating the intended emission levels in the Beijing–Tianjin–Hebei area. The results indicate that haze concentration control targets will not be attained by following the NAPCAP, and that the amount of progress needed to meet the targets is unrealistic. A more appropriate approach to reducing air emissions is proposed, which addresses joint regional efforts. [ABSTRACT FROM AUTHOR]

Nowadays, several dispersion models are available to simulate the transport processes of air pollutants and toxic substances including radionuclides in the atmosphere. Reliability of atmospheric transport models has been demonstrated in several recent cases from local to global scale; however, very few actual emission data are available to evaluate model results in real-life cases. In this study, the atmospheric dispersion of 131I emitted to the atmosphere during an industrial process was simulated with different models, namely the WRF-Chem Eulerian online coupled model and the HYSPLIT and the RAPTOR Lagrangian models. Although only limited data of 131I detections has been available, the accuracy of modeled plume direction could be evaluated in complex late autumn weather situations. For the studied cases, the general reliability of models has been demonstrated. However, serious uncertainties arise related to low level inversions, above all in case of an emission event on 4 November 2011, when an important wind shear caused a significant difference between simulated and real transport directions. Results underline the importance of prudent interpretation of dispersion model results and the identification of weather conditions with a potential to cause large model errors. [ABSTRACT FROM AUTHOR]

Urban environmental measurements and observational statistics should reflect the properties generated over an adjacent area of adequate length where homogeneity is usually assumed. The determination of this characteristic source area that gives sufficient representation of the horizontal coverage of a sensing instrument or the fetch of transported quantities is of critical importance to guide the design and implementation of urban landscape planning strategies. In this study, we aim to unify two different methods for estimating source areas, viz. the statistical correlation method commonly used by geographers for landscape fragmentation and the mechanistic footprint model by meteorologists for atmospheric measurements. Good agreement was found in the intercomparison of the estimate of source areas by the two methods, based on 2-m air temperature measurement collected using a network of weather stations. The results can be extended to shed new lights on urban planning strategies, such as the use of urban vegetation for heat mitigation. In general, a sizable patch of landscape is required in order to play an effective role in regulating the local environment, proportional to the height at which stakeholders’ interest is mainly concerned. [ABSTRACT FROM AUTHOR]

Background and purpose: The data concerning the association between environmental pollution and epilepsy attacks are limited. The aim of this study was to explore the association between acute air pollution exposure and epilepsy attack. Methods: A hospital record-based study was carried out in Xi’an, a heavily-polluted metropolis in China. Daily baseline data were obtained. Time-series Poisson regression models were applied to analyze the association between air pollution and epilepsy. Results: A 10 μg/m3 increase of NO2, SO2, and O3 concentrations corresponded to 3.17% (95%Cl: 1.41%, 4.93%), 3.55% (95%Cl: 1.93%, 5.18%), and -0.84% (95%Cl: -1.58%, 0.09%) increase in outpatient-visits for epilepsy on the concurrent days, which were significantly influenced by sex and age. The effects of NO2 and SO2 would be stronger when adjusted for PM2.5. As for O3, a -1.14% (95%Cl: -1.90%, -0.39%) decrease was evidenced when adjusted for NO2. The lag models showed that the most significant effects were evidenced on concurrent days. Conclusions: We discovered previously undocumented relationships between short-term air pollution exposure and epilepsy: while NO2 and SO2 were positively associated with outpatient-visits of epilepsy, O3 might be associated with reduced risk. [ABSTRACT FROM AUTHOR]

Background and Purpose: Increasing ozone concentrations have been known to damage human health and ecosystems. Although ozone tends to display diurnal variation, most studies have reported only on the association between daily ozone concentrations and ischemic stroke occurrence on the same day, or with a 1-day lag. We investigated the effect of the diurnal variation of ozone on ischemic stroke occurrence during the same day. Methods: We included a consecutive series of 1,734 patients from January 1, 2008, to December 31, 2014, at a single tertiary hospital in Seoul, South Korea. We evaluated differences between temperature and pollutants at the time of stroke onset for each time interval and averaged those parameters across the 7-year study period. Results: During the interval from 13:00 to 16:59, we found a positive association between ischemic stroke occurrence and ozone concentration relative to other time periods. Upper median ozone levels from 13:00 to 16:59 were positively correlated with ischemic stroke (odds ratio, 1.550; 95% confidence intervals, 1.220 to 1.970; P = <0.001) when compared with lower median levels. Conclusions: The results show diurnal patterns of ischemic stroke occurrence based on upper and lower median ozone levels for a 24-hour period, which extends understanding of the association between stroke occurrence and environmental influences. [ABSTRACT FROM AUTHOR]

The aim of the study was to determine the effects of stormwater and snowmelt runoff on the ELISA EQ PCDD/PCDF and triclosan concentrations in the small urban Sokołówka River (Central Poland). The obtained results demonstrate the decisive influence of hydrological conditions occurring in the river itself and its catchment on the quoted PCDD/PCDF ELISA EQ concentrations. The lowest PCDD/PCDF values of 87, 60 and 67 ng EQ L-1 in stormwater, the river and its reservoirs, respectively, were associated with the highest river flow of 0.02 m3 s-1 and high precipitation (11.2 mm) occurred five days before sampling. In turn, the highest values of 353, 567 and 343 ng EQ L-1 in stormwater, the river and its reservoirs, respectively, were observed during periods of intensive snow melting (stormwater samples) and spring rainfall preceded by a rainless phase (river and reservoir samples) followed by low and moderate river flows of 0.01 and 0.005 m3 s-1. An analogous situation was observed for triclosan, with higher ELISA EQ concentrations (444 to 499 ng EQ L-1) noted during moderate river flow and precipitation, and the lowest (232 to 288 ng EQ L-1) observed during high river flow and high precipitation preceded by violent storms. Stormwater was also found to influence PCDD/PCDF EQ concentrations of the river and reservoirs, however only during high and moderate flow, and no such effect was observed for triclosan. The study clearly demonstrates that to mitigate the high peaks of the studied pollutants associated with river hydrology, the increased in-site stormwater infiltration and purification, the development of buffering zones along river course and the systematic maintenance of reservoirs to avoid the accumulation of the studied micropollutants and their subsequent release after heavy rainfall are required. [ABSTRACT FROM AUTHOR]

The composition and relative abundance of airborne pollen in urban areas of Australia and New Zealand are strongly influenced by geographical location, climate and land use. There is mounting evidence that the diversity and quality of airborne pollen is substantially modified by climate change and land-use yet there are insufficient data to project the future nature of these changes. Our study highlights the need for long-term aerobiological monitoring in Australian and New Zealand urban areas in a systematic, standardised, and sustained way, and provides a framework for targeting the most clinically significant taxa in terms of abundance, allergenic effects and public health burden. [ABSTRACT FROM AUTHOR]

We describe spatial patterns in environmental injustice and inequality for residential outdoor nitrogen dioxide (NO2) concentrations in the contiguous United States. Our approach employs Census demographic data and a recently published high-resolution dataset of outdoor NO2 concentrations. Nationally, population-weighted mean NO2 concentrations are 4.6 ppb (38%, p<0.01) higher for nonwhites than for whites. The environmental health implications of that concentration disparity are compelling. For example, we estimate that reducing nonwhites’ NO2 concentrations to levels experienced by whites would reduce Ischemic Heart Disease (IHD) mortality by ∼7,000 deaths per year, which is equivalent to 16 million people increasing their physical activity level from inactive (0 hours/week of physical activity) to sufficiently active (>2.5 hours/week of physical activity). Inequality for NO2 concentration is greater than inequality for income (Atkinson Index: 0.11 versus 0.08). Low-income nonwhite young children and elderly people are disproportionately exposed to residential outdoor NO2. Our findings establish a national context for previous work that has documented air pollution environmental injustice and inequality within individual US metropolitan areas and regions. Results given here can aid policy-makers in identifying locations with high environmental injustice and inequality. For example, states with both high injustice and high inequality (top quintile) for outdoor residential NO2 include New York, Michigan, and Wisconsin. [ABSTRACT FROM AUTHOR]