PM2.5 concentrations in a typical residential apartment in Beijing and immediately outside of the building were measured simultaneously during heating and non-heating periods. The objective was to quantitatively explore the relationship between indoor and outdoor PM2.5 concentrations. A statistical method for predicting indoor PM2.5 concentrations was proposed. Ambient PM2.5 concentrations were strongly affected by meteorological conditions, especially wind directions. A bimodal distribution was identified during the heating season due to the frequent and rapid transition between severe pollution events and clean days. Indoor PM2.5 concentrations were significantly correlated with outdoor PM2.5 concentrations but with 1–2 h delay, and the differences can be explained by ambient meteorological features, such as temperature, humidity, and wind direction. These results indicate the potential to incorporate indoor exposure features to the regional air quality model framework and to more accurately estimate the epidemiological relationship between human mortality and air pollution exposure.

Epidemiological investigations regarding temperature influence on human health have focused on mortality rather than morbidity. In addition, most information comes from developed countries despite the increasing evidence that climate change will have devastating impacts on disadvantaged populations living in developing countries. In the present study, we assessed the impact of daily temperature range on upper and lower respiratory infections in Cordoba, Argentina, and explored the effect modification of socio-economic factors and influence of airborne particles We found that temperature range is a strong risk factor for admissions due to both upper and lower respiratory infections, particularly in elderly individuals, and that these effects are more pronounced in sub-populations with low education level or in poor living conditions. These results indicate that socio-economic factors are strong modifiers of the association between temperature variability and respiratory morbidity, thus they should be considered in risk assessments.

This study presents a novel system for online, field measurement of copper (Cu) in ambient coarse (2.5–10 μm) particulate matter (PM). This new system utilizes two virtual impactors combined with a modified liquid impinger (BioSampler) to collect coarse PM directly as concentrated slurry samples. The total and water-soluble Cu concentrations are subsequently measured by a copper Ion Selective Electrode (ISE). Laboratory evaluation results indicated excellent collection efficiency (over 85%) for particles in the coarse PM size ranges. In the field evaluations, very good agreements for both total and water-soluble Cu concentrations were obtained between online ISE-based monitor measurements and those analyzed by means of inductively coupled plasma mass spectrometry (ICP-MS). Moreover, the field tests indicated that the Cu monitor could achieve near-continuous operation for at least 6 consecutive days (a time resolution of 2–4 h) without obvious shortcomings.

Many reports of trees' impacts on urban air quality neglect pattern and process at the landscape scale. Here, we describe brief campaigns to quantify the effect of trees on the dispersion of airborne particulates using high time resolution measurements along short transects away from roads. Campaigns near major highways in Queens, NY showed frequent, stochastic spikes in PM2.5. The polydisperse PM2.5 class poorly represented the behavior of discrete classes. A transect across a lawn with trees had fewer spikes in PM2.5 concentration but decreased more gradually than a transect crossing a treeless lawn. This coincided with decreased Turbulence Kinetic Energy downwind of trees, indicating recirculation, longer residence times and decreased dispersion. Simply planting trees can increase local pollution concentrations, which is a special concern if the intent is to protect vulnerable populations. Emphasizing deposition to leaf surfaces obscures the dominant impact of aerodynamics on local concentration.

A source-oriented CMAQ was applied to determine source sector/region contributions to primary particulate matter (PPM) in China. Four months were simulated with emissions grouped to eight regions and six sectors. Predicted elemental carbon (EC), primary organic carbon (POC), and PPM concentrations and source contributions agree with measurements and have significant spatiotemporal variations. Residential is a major contributor to spring/winter EC (50–80%), POC (60%–90%), and PPM (30–70%). For summer/fall, industrial contributes 30–50% for EC/POC and 40–60% for PPM. Transportation is more important for EC (20–30%) than POC/PPM (<5%). Open burning is important in summer/fall of Guangzhou and Chongqing. Dust contributes to 1/3–1/2 in spring/fall of Beijing, Xi'an and Chongqing. Based on sector–region combination, local residential/transportation and residential/industrial from Heibei are major contributors to spring PPM in Beijing. In summer/fall, local industrial is the largest. In winter, residential/industrial from local and Hebei account for >90% in Beijing.

Few studies have evaluated the effects of ambient air pollution and temperature in triggering out-of-hospital coronary deaths (OHCDs) in China. We evaluated the associations of air pollution and temperature with daily OHCDs in Shanghai, China from 2006 to 2011. We applied an over-dispersed generalized additive model and a distributed lag nonlinear model to analyze the effects of air pollution and temperature, respectively. A 10 μg/m3 increase in the present-day PM10, PM2.5, SO2, NO2 and CO were associated with increases in OHCD mortality of 0.49%, 0.68%, 0.88%, 1.60% and 0.08%, respectively. A 1 °C decrease below the minimum-mortality temperature corresponded to a 3.81% increase in OHCD mortality on lags days 0–21, and a 1 °C increase above minimum-mortality temperature corresponded to a 4.61% increase over lag days 0–3. No effects were found for in-hospital coronary deaths. This analysis suggests that air pollution, low temperature and high temperature may increase the risk of OHCDs.

Identifying particulate matter (PM) emitted from industrial processes into the atmosphere is an important issue in environmental research. This paper presents a passive sampling method using simple artificial samplers that maintains the advantage of bio-monitoring, but overcomes some of its disadvantages. The samplers were tested in a heavily polluted area (Linfen, China) and compared to results from leaf samples. Spatial variations of magnetic susceptibility from artificial passive samplers and leaf samples show very similar patterns. Scanning electron microscopy suggests that the collected PM are mostly in the range of 2–25 μm; frequent occurrence of spherical shape indicates industrial combustion dominates PM emission. Magnetic properties around power plants show different features than other plants. This sampling method provides a suitable and economic tool for semi-quantifying temporal and spatial distribution of air quality; they can be installed in a regular grid and calibrate the weight of PM.

Moxibustion is a traditional Chinese medicine therapy that burns moxa floss which produces a substantial amount of PM10 into the environment, thus spawning safety concerns about health impacts of the smoke. We compared the oxidative capacity and elemental composition of moxibustion-derived and ambient PM10 in summer and winter to provide a source-, spatial- and temporal-comparison of PM10 biological responses. The PM10 oxidative capacity was 2.04 and 1.45 fold lower, and dose-dependent slope gradient was 2.36 and 1.76 fold lower in moxibustion environment than indoor or outdoor. Oxidative damage was highly correlated with iron, cesium, aluminum and cobalt in indoor, but moxibustion environment displayed low associations. The total elemental concentration was also lower in moxibustion environment than indoor (2.28 fold) or outdoor (2.79 fold). The source-to-dose modeling and slope gradient analysis in this study can be used as a model for future source-, spatial- and temporal-related moxibustion safety evaluation studies.

During the last few years, the induction of toxicological mechanisms by atmospheric ultrafine particles (UFP) has become one of the most studied topics in toxicology and a subject of huge debates. Fine particles (FP) and UFP collected at urban and rural sites in Lebanon were studied for their chemical composition and toxicological effects. UFP were found more enriched in trace elements, secondary inorganic ions, total carbon and organic compounds than FP. For toxicological analysis, BEAS-2B cells were exposed for 24, 48 and 72 h to increasing concentrations of FP, water-UFP suspension (UFPw) and UFP organic extract (UFPorg). Our findings showed that UFP caused earlier alterations of mitochondrial metabolism and membrane integrity from the lowest concentrations. Moreover, a significant induction of CYP1A1, CYP1B1 and AhRR genes expression was showed after cells exposure to UFPorg and to a lesser extent to UFPw and FP samples.

This study investigated particulate matter (PM) loading rates and concentrations in ambient air from naturally ventilated dairy barns and also the influences of pertinent meteorological factors, traffic, and animal activities on mass loading rates and mass concentrations. Generally, relationships between PM2.5 concentration and these parameters were significantly poorer than those between the PM loading rate and the same parameters. Although ambient air PM2.5 loading rates correlated well with PM2.5 emission rates, ambient air PM2.5 concentrations correlated poorly with PM2.5 concentrations in the barns. A comprehensive assessment of PM2.5 pollution in ambient air, therefore, requires both mass concentrations and mass loading rates. Emissions of PM2.5 correlated strongly and positively with wind speed, temperature, and solar radiation (R2 = 0.84 to 0.99) and strongly but negatively with relative humidity (R2 = 0.93). Animal activity exhibited only moderate effect on PM2.5 emissions, while traffic activity did not significantly affect PM2.5 emissions.