Cold weather was estimated to account for more than half of weather-related deaths in the U.S. during 2006–2010. Studies have shown that cold-related excessive mortality is especially relevant with decreasing latitude or in regions with mild winter. However, only limited studies have been conducted in the southern U.S. The purpose of our study is to examine impacts of cold weather on mortality in 12 major Texas Metropolitan Areas (MSAs) for the 22-year period, 1990–2011. Our study used a two-stage approach to examine the cold-mortality association. We first applied distributed lag non-linear models (DLNM) to 12 major MSAs to estimate cold effects for each area. A random effects meta-analysis was then used to estimate pooled effects. Age-stratified and cause-specific mortalities were modeled separately for each MSA. Most of the MSAs were associated with an increased risk in mortality ranging from 0.1% to 5.0% with a 1 °C decrease in temperature below the cold thresholds. Higher increased mortality risks were generally observed in MSAs with higher average daily mean temperatures and lower latitudes. Pooled effect estimate was 1.58% (95% Confidence Interval (CI) [0.81, 2.37]) increase in all-cause mortality risk with a 1 °C decrease in temperature. Cold wave effects in Texas were also examined, and several MSAs along the Texas Gulf Coast showed statistically significant cold wave-mortality associations. Effects of cold on all-cause mortality were highest among people over 75 years old (1.86%, 95% CI [1.09, 2.63]). Pooled estimates for cause-specific mortality were strongest in myocardial infarction (4.30%, 95% CI [1.18, 7.51]), followed by respiratory diseases (3.17%, 95% CI [0.26, 6.17]) and ischemic heart diseases (2.54%, 95% CI [1.08, 4.02]). In conclusion, cold weather generally increases mortality risk significantly in Texas, and the cold effects vary with MSAs, age groups, and cause-specific deaths.

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.

Low-cost, light-scattering-based particulate matter (PM) sensors are becoming more widely available and are being increasingly deployed in ambient and indoor environments because of their low cost and ability to provide high spatial and temporal resolution PM information. Researchers have begun to evaluate some of these sensors under laboratory and environmental conditions. In this study, a low-cost, particulate matter sensor (Plantower PMS 1003/3003) used by a community air-quality network is evaluated in a controlled wind-tunnel environment and in the ambient environment during several winter-time, cold-pool events that are associated with high ambient levels of PM. In the wind-tunnel, the PMS sensor performance is compared to two research-grade, light-scattering instruments, and in the ambient tests, the sensor performance is compared to two federal equivalent (one tapered element oscillating microbalance and one beta attenuation monitor) and gravimetric federal reference methods (FEMs/FRMs) as well as one research-grade instrument (GRIMM). The PMS sensor response correlates well with research-grade instruments in the wind-tunnel tests, and its response is linear over the concentration range tested (200–850 μg/m³). In the ambient tests, this PM sensor correlates better with gravimetric methods than previous studies with correlation coefficients of 0.88. However additional measurements under a variety of ambient conditions are needed. Although the PMS sensor correlated as well as the research-grade instrument to the FRM/FEMs in ambient conditions, its response varies with particle properties to a much greater degree than the research-grade instrument. In addition, the PMS sensors overestimate ambient PM concentrations and begin to exhibit a non-linear response when PM2.5 concentrations exceed 40 μg/m³. These results have important implications for communicating results from low-cost sensor networks, and they highlight the importance of using an appropriate correction factor for the target environmental conditions if the user wants to compare the results to FEM/FRMs.

Because people spend most of their time indoors, the characterization of indoor air quality is important for exposure assessment. Unfortunately, indoor air data are scarce, leading to a major data gap in risk assessment. In this study, PM2.5 concentrations in both indoor and outdoor air were simultaneously measured using on-line particulate counters in 13 households in Haidian, Beijing for both heating and non-heating seasons. A bimodal distribution of PM2.5 concentrations suggests rapid transitions between polluted and non-polluted situations. The PM2.5 concentrations in indoor and outdoor air varied synchronously, with the indoor variation lagging. The lag time in the heating season was longer than that in the non-heating season. The particle sizes in indoor air were smaller than those in ambient air in the heating season and vice versa in the non-heating season. PM2.5 concentrations in indoor air were generally lower than those in ambient air except when ambient concentrations dropped sharply to very low levels or there were internal emissions from cooking or other activities. The effectiveness of an air cleaner to reduce indoor PM2.5 concentrations was demonstrated. Non-linear regression models were developed to predict indoor air PM2.5 concentrations based on ambient data with lag time incorporated. The models were applied to estimate the overall population exposure to PM2.5 and the health consequences in Haidian. The health impacts would be significantly overestimated without the indoor exposure being taken into consideration, and this bias would increase as the ambient air quality improved in the future.

Based on the 12-hour PM2.5 samples collected in an urban site of Beijing, sixteen PM2.5-bound Polycyclic Aromatic Hydrocarbons (PAHs) were measured to investigate the characteristics and potential source regions of particulate PAHs in Beijing. The study period included the summer period in July–August 2014, the APEC source control period during the Asia-Pacific Economic Cooperation (APEC) meeting in the first half of November 2014, and the heating period in the second half of November 2014. Compared to PM2.5, sum of 16 PM2.5-bound PAHs exhibited more significant seasonal variation with the winter concentration largely exceeding the summer concentration. Temperature appeared to be the most crucial meteorological factor during the summer and heating periods, while PM2.5-bound PAHs showed stronger correlation with relative humidity and wind speed during the APEC source control period. Residential heating significantly increased the concentrations of higher-ring-number (≥4) PAHs measured in PM2.5 fraction. Potential source contribution function (PSCF) and concentration weighted trajectory (CWT) analysis as well as the (3 + 4) ring/(5 + 6) ring PAH ratio analysis revealed the seasonal difference in the potential source area of PM2.5-bound PAHs in Beijing. Southern Hebei was the most likely potential source area in the cold season. Using black carbon (BC) and carbon monoxide (CO) as the PAH tracers, regional residential, transportation and industry emissions all contributed to the PAH pollution in Beijing.

Mining activities have contaminated many riverine floodplains with arsenic (As). When floodplain soils become anoxic under water-saturated conditions, As can be released from the solid phase. Several microbially-driven As solubilization processes and numerous influential factors were recognized in the past. However, the interplay and relative importance of soil properties and the influence of environmental factors such as temperature remain poorly understood, especially considering the (co)variation of soil properties in a floodplain. We conducted anoxic microcosm experiments at 10, 17.5, and 25 °C using 65 representative soils from the mining-impacted Ogosta River floodplain in Bulgaria. To investigate the processes of As solubilization and its quantitative variation we followed the As and Fe redox dynamics in the solid and the dissolved phase and monitored a range of other solution parameters including pH, Eh, dissolved organic C, and dissolved Mn. We related soil properties to dissolved As observed after 20 days of microcosm incubation to identify key soil properties for As solubilization. Our results evidenced reductive dissolution of As-bearing Fe(III)-oxyhydroxides as the main cause for high solubilization. The availability of nutrients, most likely organic C as the source of energy for microorganisms, was found to limit this process. Following the vertical nutrient gradient common in vegetated soil, we observed several hundred μM dissolved As after 1–2 weeks for some topsoils (0–20 cm), while for subsoils (20–40 cm) with comparable total As levels only minor solubilization was observed. While high Mn contents were found to inhibit As solubilization, the opposite applied for higher temperature (Q10 2.3–6.1 for range 10–25 °C). Our results suggest that flooding of nutrient-rich surface layers might be more problematic than water-saturation of nutrient-poor subsoil layers, especially in summer floodings when soil temperature is higher than in winter or spring.

The arrival and discharge of seven antibiotics were monitored at two trickling filter sewage treatment plants of 6000 and 11,000 population equivalents (PE) and two activated sludge plants of 33,000 and 162,000 PE in Southern England. The investigation consisted of 24 h composite samples taken on two separate days every summer from 2012 to 2015 and in the winter of 2015 (January) from influent and effluent. The average influent concentrations generally matched predictions based on England-wide prescription data for trimethoprim, sulfamethoxazole, azithromycin, oxytetracycline and levofloxacin (within 3-fold), but were 3–10 times less for clarithromycin, whilst tetracycline influent concentrations were 5–17 times greater than expected. Over the four years, effluent concentrations at a single sewage plant varied by up to 16-fold for clarithromycin, 10-fold for levofloxacin and sulfamethoxazole, 7-fold for oxytetracycline, 6-fold for tetracycline, 4-fold for azithromycin and 3-fold for trimethoprim. The study attempted to identify the principal reasons for this variation in effluent concentration. By measuring carbamazepine and using it as a conservative indicator of transport through the treatment process, it was found that flow and hence concentration could alter by up to 5-fold. Measuring influent and effluent concentrations allowed assessments to be made of removal efficiency. In the two activated sludge plants, antibiotic removal rates were similar for the tested antibiotics but could vary by several-fold at the trickling filter plants. However, for clarithromycin and levofloxacin the variations in effluent concentration were above that which could be explained by either flow and/or removal alone so here year on year changes in consumption are likely to have played a role.

Continuous measurements of PM2.5, PM10 and CO were conducted at an urban site of Udaipur in India from April 2011 to March 2012. The annual mean concentrations of PM2.5, PM10 and CO were 42 ± 17 μg m−3, 114 ± 31 μg m−3 and 343 ± 136 ppbv, respectively. Concentrations of both particulate and CO showed high values during winter/pre-monsoon (dry) period and lowest in the monsoon season (wet). Local anthropogenic emission and long-range transport from open biomass burning sources along with favourable synoptic meteorology led to elevated levels of pollutants in the dry season. However, higher values of PM10/PM2.5 ratio during pre-monsoon season were caused by the episodes of dust storm. In the monsoon season, flow of cleaner air, rainfall and negligible emissions from biomass burning resulted in the lowest levels of pollutants. The concentrations of PM2.5, PM10 and CO showed highest values during morning and evening rush hours, while lowest in the afternoon hours. In winter season, reductions of PM2.5, CO and PM10 during weekends were highest of 15%, 13% and 9%, respectively. In each season, the highest PM2.5/PM10 ratio coincided with the highest concentrations of pollutants (CO and NOX) indicating predominant emissions from anthropogenic sources. Exceptionally high concentrations of PM10 during the episode of dust storm were due to transport from the Arabian Peninsula and Thar Desert. Up to ∼32% enhancements of PM10 were observed during strong dust storms. Relatively low levels of O3 and NOx during the storm periods indicate the role of heterogeneous removal.

To investigate the spatial and temporal behaviors of particulate matter in Lanzhou, Jinchang and Jiayuguan during 2014, the hourly concentrations of PM2.5 and PM10 were collected from the Ministry of Environmental Protection (MEP) in this study. The analysis indicated that the mean annual PM10 (PM2.5) concentrations during 2014 were 115 ± 52 μg/m3 (57 ± 28 μg/m3), 104 ± 75 μg/m3 (38 ± 22 μg/m3) and 114 ± 72 μg/m3 (32 ± 17 μg/m3) in Lanzhou, Jinchang and Jiayuguan, respectively, all of which exceeded the Chinese national ambient air quality II standards for PM. Higher values for both PM fractions were generally observed in spring and winter, and lower concentrations were found in summer and autumn. Besides, the trend of seasonal variation of particulate matter (PM) in each city monitoring site is consistent with the average of the corresponding cities. Anthropogenic activities along with the boundary layer height and wind scale contributed to diurnal variations in PM that varied bimodally (Lanzhou and Jinchang) or unimodally (Jiayuguan). With the arrival of dust events, the PM10 concentrations changed dramatically, and the PM10 concentrations during dust storm events were, respectively, 19, 43 and 17 times higher than the levels before dust events in Lanzhou, Jinchang and Jiayuguan. The ratios (PM2.5/PM10) were lowest, while the correlations were highest, indicating that dust events contributed more coarse than fine particles, and the sources of PM are similar during dust storms. The relationships between local meteorological parameters and PM concentrations suggest a clear association between the highest PM concentrations, with T ≤ 7 °C, and strong winds (3–4 scale). However, the effect of relative humidity is complicated, with more PM10 and PM2.5 exceedances being registered with a relative humidity of less than 40% and 40–60% in Lanzhou, while higher exceedances in Jinchang appeared at a relative humidity of 80–100%.

An Aerodyne quadrupole aerosol mass spectrometry (Q-AMS) was utilized to measure the size-resolved chemical composition of non-refractory submicron particles (NR-PM1) from October 27 to December 3, 2014 at an urban site in Lanzhou, northwest China. The average NR-PM1 mass concentration was 37.3 μg m−3 (ranging from 2.9 to 128.2 μg m−3) under an AMS collection efficiency of unity and was composed of organics (48.4%), sulfate (17.8%), nitrate (14.6%), ammonium (13.7%), and chloride (5.7%). Positive matrix factorization (PMF) with the multi-linear engine (ME-2) solver identified six organic aerosol (OA) factors, including hydrocarbon-like OA (HOA), coal combustion OA (CCOA), cooking-related OA (COA), biomass burning OA (BBOA) and two oxygenated OA (OOA1 and OOA2), which accounted for 8.5%, 20.2%, 18.6%, 12.4%, 17.8% and 22.5% of the total organics mass on average, respectively. Primary emissions were the major sources of fine particulate matter (PM) and played an important role in causing high chemically resolved PM pollution during wintertime in Lanzhou. Back trajectory analysis indicated that the long-range regional transport air mass from the westerly was the key factor that led to severe submicron aerosol pollution during wintertime in Lanzhou.