Little is known about pollution in urban snow and how aerosol and gaseous air pollutants interact with the urban snowpack. Here we investigate interactions of exhaust pollution with snow at low ambient temperature using fresh snow in a temperature-controlled chamber. A gasoline-powered engine from a modern light duty vehicle generated the exhaust and was operated in homogeneous and stratified engine regimes. We determined that, within a timescale of 30 min, snow takes up from the exhaust a large mass of organic pollutants and aerosol particles, which were observed by electron microscopy, mass spectrometry and aerosol sizers. Specifically, the concentration of total organic carbon in the exposed snow increased from 0.948 ± 0.009 to 1.828 ± 0.001 mg/L (homogeneous engine regime) and from 0.275 ± 0.005 to 0.514 ± 0.008 mg/L (stratified engine regime). The concentrations of benzene, toluene and 13 out of 16 measured polycyclic aromatic hydrocarbons (PAHs), particularly naphthalene, benz[a]anthracene, chrysene and benzo[a]pyrene in snow increased upon exposure from near the detection limit to 0.529 ± 0.058, 1.840 ± 0.200, 0.176 ± 0.020, 0.020 ± 0.005, 0.025 ± 0.005 and 0.028 ± 0.005 ng/kg, respectively, for the homogeneous regime. After contact with snow, 50–400 nm particles were present with higher relative abundance compared to the smaller nanoparticles (<50 nm), for the homogeneous regime. The lowering of temperature from 25 ± 1 °C to (−8) – (−10) ± 1 °C decreased the median mode diameter of the exhaust aerosol particles from 69 nm to 57 nm (p < 0.1) and addition of snow to 51 nm (p < 0.1) for the stratified regime, but increased it from 20 nm to 27 nm (p < 0.1) for the homogeneous regime. Future studies should focus on cycling of exhaust-derived pollutants between the atmosphere and cryosphere. The role of the effects we discovered should be evaluated as part of assessment of pollutant loads and exposures in regions with a defined winter season.

Air quality is closely related to quality of life. Air pollution forecasting plays a vital role in air pollution warnings and controlling. However, it is difficult to attain accurate forecasts for air pollution indexes because the original data are non-stationary and chaotic. The existing forecasting methods, such as multiple linear models, autoregressive integrated moving average (ARIMA) and support vector regression (SVR), cannot fully capture the information from series of pollution indexes. Therefore, new effective techniques need to be proposed to forecast air pollution indexes. The main purpose of this research is to develop effective forecasting models for regional air quality indexes (AQI) to address the problems above and enhance forecasting accuracy. Therefore, two hybrid models (EMD-SVR-Hybrid and EMD-IMFs-Hybrid) are proposed to forecast AQI data. The main steps of the EMD-SVR-Hybrid model are as follows: the data preprocessing technique EMD (empirical mode decomposition) is utilized to sift the original AQI data to obtain one group of smoother IMFs (intrinsic mode functions) and a noise series, where the IMFs contain the important information (level, fluctuations and others) from the original AQI series. LS-SVR is applied to forecast the sum of the IMFs, and then, S-ARIMA (seasonal ARIMA) is employed to forecast the residual sequence of LS-SVR. In addition, EMD-IMFs-Hybrid first separately forecasts the IMFs via statistical models and sums the forecasting results of the IMFs as EMD-IMFs. Then, S-ARIMA is employed to forecast the residuals of EMD-IMFs. To certify the proposed hybrid model, AQI data from June 2014 to August 2015 collected from Xingtai in China are utilized as a test case to investigate the empirical research. In terms of some of the forecasting assessment measures, the AQI forecasting results of Xingtai show that the two proposed hybrid models are superior to ARIMA, SVR, GRNN, EMD-GRNN, Wavelet-GRNN and Wavelet-SVR. Therefore, the proposed hybrid models can be used as effective and simple tools for air pollution forecasting and warning as well as for management.

This study examined effects of short-term urban air pollution exposures on inflammation, thrombosis, and autonomic imbalance in subjects at risk for cardiovascular disease (CVD). We enrolled 61 patients with multiple CVD risk factors and measured high sensitive C-reactive protein (hs-CRP), fibrinogen, D-dimer, and heart rate variability (HRV) indices. Two health examinations for each participant were performed during December 2002 through September 2003. Changes in inflammation and thrombotic markers and HRV indices with exposures to PM2.5, organic carbon (OC), elemental carbon (EC), sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO) at 1- to 3-day lags were analyzed using mixed models. The results showed inflammatory and thrombotic markers increased with 1- to 3-day lagged PM2.5 components and gaseous pollutants exposures. hs-CRP maximally increased 0.19 [95% confidence interval (CI): 0.07–0.31] and 0.15 (95% CI: 0.05–0.24) mg/L for an interquartile range (IQR) of 1-day lagged SO2 (2.3 ppb) and CO (0.5 ppm), respectively. D-dimer maximally increased 1.05 (95% CI: 0.13–1.75), 0.72 (95% CI: 0.09–1.21), 0.92 (95% CI: 0.13–1.50), and 0.90 (95% CI: 0.07–1.61) mg/dL for an IQR of 1-day lagged OC (3.9 μg/m3), EC (2.0 μg/m3), SO2, and NO2 (13.4 ppb), respectively. The HRV indices, including low frequency, very low frequency, and the ratio of low frequency to high frequency decreased 19.8 (95% CI: 4.4–32.7), 12.9 (95% CI: 0.8–23.4), and 17.6 (95% CI: 5.4–28.2)% for an IQR of 1-day lagged PM2.5 (20.2 μg/m3), respectively. Our findings demonstrated PM2.5 components and gaseous pollutants exert prolonged inflammatory and thrombotic reactions, while PM2.5 exert an immediate autonomic imbalance.

In the last few years, ship emissions have attracted growing attention in the scientific community. The main reason is the constant increase of marine emissions over the last twenty years due to the intensification of port traffic. Thus, this study aimed to evaluate ship emissions (PM10, PM2.5, NOx, SO2, CO, CO2, N2O CH4, NMVOC, and HC) through the activity-based methodology in four of the main ports of Portugal (Leixões, Setúbal, Sines and Viana do Castelo) during 2013 and 2014. The analysis was performed according to ship types (bulk carrier, container, general cargo, passenger, Ro-Ro cargo, tanker and others) and operational modes (manoeuvring, hotelling and during cruising). Results indicated that tankers were the largest emitters in two of the four analysed ports. Regarding cruising emissions, container ships were the largest emitters. . CO2, NOx and SO2 estimated emissions represented more than 95% of the cruising and in-port emissions. Results were also compared with the total national emissions reported by the Portuguese Environment Agency, and if the in-port emissions estimated in the present study would have been taken into account to these totals, emissions of NOx and SO2 would increase 15% and 24% in 2013 and 16% and 28% in 2014. Summing up ships seem to be an important source of air pollution, mainly regarding NOx and SO2.

Data on fine particulate matter (PM2.5) in China were first announced in 2013. The primary objective of this study was to evaluate the acute effects of PM2.5 on asthma morbidity in Beijing, China. A total of 978,658 asthma hospital visits consisting of 928,607 outpatient visits, 40,063 emergency room visits and 9988 hospital admissions from January 1, 2010, to June 30, 2012, were identified from the Beijing Medical Claim Data for Employees. A generalized additive Poisson model was applied to explore the association between PM2.5 and health service use. The mean daily PM2.5 concentration was 99.5 μg/m3 with a range from 7.2 μg/m3 to 492.8 μg/m3. Ambient PM2.5 concentration was significantly associated with increased use of asthma-related health services. Every 10 μg/m3 increase in PM2.5 concentration on the same day was significantly associated with a 0.67% (95% CI, 0.53%–0.81%), 0.65% (95% CI, 0.51%–0.80%), and 0.49% (95% CI, 0.35%–0.64%) increase in total hospital visits, outpatient visits and emergency room visits, respectively. The exposure–response association between PM2.5 concentration and hospital visits for asthma exacerbations was approximately linear. In conclusion, this study found that short-term elevations in PM2.5 concentration may increase the risk of asthma exacerbations. Our findings contribute to the limited scientific literature concerning the acute effects of PM2.5 on asthma morbidity outcomes in developing countries.

This manuscript evaluates spatial and temporal variations of source contributions to ambient fine particulate matter (PM2.5) in Israeli, Jordanian, and Palestinian cities. Twenty-four hour integrated PM2.5 samples were collected every six days over a 1-year period (January to December 2007) in four cities in Israel (West Jerusalem, Eilat, Tel Aviv, and Haifa), four cities in Jordan (Amman, Aqaba, Rahma, and Zarka), and three cities in Palestine (Nablus, East Jerusalem, and Hebron). The PM2.5 samples were analyzed for major chemical components, including organic carbon and elemental carbon, ions, and metals, and the results were used in a positive matrix factorization (PMF) model to estimate source contributions to PM2.5 mass. Nine sources, including secondary sulfate, secondary nitrate, mobile, industrial lead sources, dust, construction dust, biomass burning, fuel oil combustion and sea salt, were identified across the sampling sites. Secondary sulfate was the dominant source, contributing 35% of the total PM2.5 mass, and it showed relatively homogeneous temporal trends of daily source contribution in the study area. Mobile sources were found to be the second greatest contributor to PM2.5 mass in the large metropolitan cities, such as Tel Aviv, Hebron, and West and East Jerusalem. Other sources (i.e. industrial lead sources, construction dust, and fuel oil combustion) were closely related to local emissions within individual cities. This study demonstrates how international cooperation can facilitate air pollution studies that address regional air pollution issues and the incremental differences across cities in a common airshed. It also provides a model to study air pollution in regions with limited air quality monitoring capacity that have persistent and emerging air quality problems, such as Africa, South Asia and Central America.

The most common mass spectrometry approach analyzing contamination of the environment deals with targeted analysis, i.e. detection and quantification of the selected (priority) pollutants. However non-targeted analysis is becoming more often the method of choice for environmental chemists. It involves implementation of modern analytical instrumentation allowing for comprehensive detection and identification of the wide variety of compounds of the environmental interest present in the sample, such as pharmaceuticals and their metabolites, musks, nanomaterials, perfluorinated compounds, hormones, disinfection by-products, flame retardants, personal care products, and many others emerging contaminants. The paper presents the results of detection and identification of previously unreported organic compounds in snow samples collected in Moscow in March 2016. The snow analysis allows evaluation of long-term air pollution in the winter period. Gas chromatography coupled to a high resolution time-of-flight mass spectrometer has enabled us with capability to detect and identify such novel analytes as iodinated compounds, polychlorinated anisoles and even Ni-containing organic complex, which are unexpected in environmental samples. Some considerations concerning the possible sources of origin of these compounds in the environment are discussed.

Over 700 million people in Sub-Saharan Africa depend on solid biomass fuel and use simple cookstoves in poorly ventilated kitchens, which results in high indoor concentrations of household air pollutants. Switching from biomass to biogas as a cooking fuel can reduce airborne emissions of fine particulate matter (PM2.5) and carbon monoxide (CO), but households often only partially convert to biogas, continuing to use solid biomass fuels for part of their daily cooking needs. There is little evidence of the benefits of partial switching to biogas. This study monitored real-time PM2.5 and CO concentrations in 35 households in Cameroon and Uganda where biogas and firewood (or charcoal) were used. The 24 h mean PM2.5 concentrations in households that used: (1) firewood and charcoal; (2) both firewood (mean 54% cooking time) and biogas (mean 46% cooking time); and (3) only biogas, were 449 μg m⁻³, 173 μg m⁻³ and 18 μg m⁻³ respectively. The corresponding 24 h mean CO concentrations were 14.2 ppm, 2.7 ppm and 0.5 ppm. Concentrations of both PM2.5 and CO were high and exceeded the World Health Organisation guidelines when firewood and charcoal were used. Partially switching to biogas reduced CO exposure to below the World Health Organisation guidelines, but PM2.5 concentrations were only below the 24 h recommended limits when households fully converted to biogas fuel. These results indicate that partial switching from solid fuels to biogas is not sufficient and continues to produce concentrations of household air pollution that are likely to harm the health of those exposed. Programmes introducing biogas should aim to ensure that household energy needs can be fully achieved using biogas with no requirement to continue using solid fuels.

Exposure to particulate matter with diameter ≤10 μm (PM10) entails well documented adverse effects on human health. In the last decade, concentration of PM10 in Lombardy (10 million inhabitants), Italy, has been gradually decreasing. We evaluated how the mortality burden due to PM10 varied in that same period.We focused on 13 areas of the Region in 2003–2014: 11 cities with more than 50,000 inhabitants, 1 smaller alpine town and 1 agricultural province. For each area, we collected PM10 annual average concentrations and natural mortality data, and we used the posterior area-specific effects from a previous Bayesian meta-analysis to estimate the short-term impact of PM10 on mortality, in terms of deaths attributable (AD) to annual average exposures exceeding the WHO threshold of 20 μg/m3.PM10 annual average values showed a non-homogenous decreasing trend in the investigated time period in most of the areas. Overall, the population-weighted exposure levels decreased, except for a peak in 2011, but never met the WHO threshold. In 2003–2006, PM10 levels were responsible, on average, for 343.0 annual AD from natural causes that decreased to 253.5 in 2007–2010 and to 208.3 in 2011–2014. Overall we estimated that PM10 was responsible for about 1% of all natural deaths (min-max range: 0.86%–1.42%); the impact was heterogeneous among areas.By collecting routinely available data for the most populated areas in Lombardy, we returned a picture of air pollution and health trends in the last decade. Notwithstanding the observed reduction in PM10 between 2003 and 2014 and the resulting decline in the number of AD, the impact is still relevant. Hence, appropriate policies for emission reduction could have a further beneficial effect on population health. Studies based on routine data and local effect estimates are recommended to properly inform the policy-making process.