Chronic exposure to environment noise is associated with sleep disturbance and cardiovascular diseases. Assessment of population exposed to environmental noise is limited by a lack of routine noise sampling and is critical for controlling exposure and mitigating adverse health effects. Land use regression (LUR) model is newly applied in estimating environmental exposures to noise. Machine-learning approaches offer opportunities to improve the noise estimations from LUR model. In this study, we employed random forests (RF) model to estimate environmental noise levels in five Canadian cities and compared noise estimations between RF and LUR models. A total of 729 measurements and 33 built environment-related variables were used to estimate spatial variation in environmental noise at the global (multi-city) and local (individual city) scales. Leave one out cross-validation suggested that noise estimates derived from the RF global model explained a greater proportion of variation (R2: RF = 0.58, LUR = 0.47) with lower root mean squared errors (RF = 4.44 dB(A), LUR = 4.99 dB(A)). The cross-validation also indicated the RF models had better general performance than the LUR models at the city scale. By applying the global models to estimate noise levels at the postal code level, we found noise levels were higher in Montreal and Longueuil than in other major Canadian cities.

Most of the previous researches estimate influencing factors impact on air quality average without considering the heterogeneity of influential factors on different levels of air quality. In order to detect the different effects of influencing factors on air quality index (AQI) between lower-AQI and higher-AQI cities, this study applies a spatial quantile regression model (SQRM) to investigate heterogeneity of influential factors on AQI, while accounting for spatial autocorrelation of AQI. The results show that heterogeneity effects of windspeed, terrain slope, urbanization sprawl and spatial autocorrelation on AQI are large across the entire AQI spectrum, while heterogeneity effects of precipitation, temperature, relative humidity, terrain fluctuation and urbanization intensity on AQI are not obvious. The spatial positive autocorrelation of AQI in higher-AQI cities is greater than that in lower-AQI cities. Compared with higher-AQI cities, the negative impact of terrain slope on AQI is lager in lower-AQI cities. One unit increase in wind speed contributes AQI to decrease 9.31 to 5.64 then to 5.39 for lower, medium and higher-AQI cities. One unit increase in urbanization sprawl would lead AQI increase 25.6 to 15.6 then to 10.5 for lower, medium and higher-AQI cities. The heterogeneity analysis of meteorological, topographic and socioeconomic factors effects on air quality are of guiding significance for realizing the differentiation of policy measures for air pollution prevention and control.

This study aims to examine the association between short-term exposures to PM₁, PM₂.₅ and PM₁₀ (particulate matter with aerodynamic diameters ≤1 μm, ≤2.5 μm and ≤10 μm, respectively) and hospital admission for ischemic stroke in China. Daily counts of hospital admission for ischemic stroke were collected in 5 hospitals in China during November 2013 to October 2015. Daily concentrations of PM₁, PM₂.₅ and PM₁₀ were collected in 5 cities where the hospitals were located. A time-stratified case-crossover design was used to examine the hospital-specific PM-ischemic stroke association after controlling for potential confounders. Then the effect estimates were pooled using a random-effect meta-analysis. A total of 68,122 hospital admissions for ischemic stroke were identified from 5 hospitals during the study period. The pooled results showed that exposures to PM₁, PM₂.₅ and PM₁₀ were significantly associated with increased hospital admission for ischemic stroke on the current day and previous 1 day. The RRs (relative risk associated with per 10 μg/m³ increase in each pollutant) and 95%CIs (confidence intervals) for the cumulative effects of PM₁, PM₂.₅ and PM₁₀ on ischemic stroke during lag 0–1 days were 1.014 (1.005, 1.0023), 1.007 (1.000, 1.014) and 1.005 (1.001, 1.009), respectively. In total, 3.5%, 3.6% and 4.1% of hospital admissions for ischemic stroke could be attributable to PM₁, PM₂.₅ and PM₁₀, respectively. Exposures to ambient PM₁, PM₂.₅ and PM₁₀ pollution showed acute adverse effects on hospital admission for ischemic stroke. The health effects of PM₁ should be considered by policy-makers.

In order to investigate the impacts of dam-related water impoundment on the spatial-temporal variations and transport of anthropogenic organic pollutants, 15 priority polycyclic aromatic hydrocarbons (PAHs) were analyzed in water samples from the Shuikou Reservoir (SKR) of the Minjiang River. The SKR was formed after the construction of the Shuikou Dam, which is the largest hydropower station in Southeast China. The water samples were collected from the backwater zone of the SKR, in both the wet and dry seasons, corresponding to the drainage and impoundment periods of water flow, respectively. The concentrations of the dissolved PAHs in surface water from the wet season (average of 161 ± 97 ng L⁻¹) were significantly higher (ANOVA, p < 0.01) than those from the dry season (average of 43 ± 21 ng L⁻¹). PAH concentrations in the SKR decreased from upstream (industrialized cities) to downstream (rural towns or counties), indicating high PAH loads caused by intensive urbanization effects. The high proportions of 3-ring PAHs in the wet season were from local sources via surface runoff; while the elevated proportions of 4- to 6- ring PAHs in the dry season reflected atmospheric deposition emerged of these PAHs and/or volatilization of 3-ring PAHs enhanced. Molecular diagnostic ratios of PAH isomers in multimedium and principal component analysis indicated that PAH presence in the SKR was mainly attributed to pyrogenic origin. The isomeric ratios of fluoranthene to fluoranthene plus pyrene in the wet season were homogeneous, implying that there were continuous new inputs along the riverine runoff. However, these ratios showed spatial downward trend in the dry season, indicating continued degradation of PAHs occurred along the transport path during the impoundment period. The input and output fluxes of PAHs in the SKR were 5330 kg yr⁻¹ and 2991 kg yr⁻¹, revealing that the reservoir retained contaminants after impoundment of the hydropower dam.

Lead (Pb) is an important pollutant and it is of significance to explore the Pb distribution, influencing factors and health risk. Pb concentration and mass load per unit area in 385 street dust samples collected from 19 cities in China were determined during 2011-2013. The results show that the Pb concentration are 68.8, 105.4, 41.7, 49.7, 75.6, 81.7, 131.9, 67.5, 109.3, 164.1, 74.8, 66.4, 99.8, 58.4, 114.0, 59.6, 103.7, 55.4 and 80.4 for Beijing, Chengdu, Daqing, Harbin, Jilin, Jinan, Kunming, Lanzhou, Luoyang, Panzhihua, Qingdao, Yinchuan, Guangzhou, Tangshan, Xi’an, Guangyuan, Nanjing, Taiyuan and Tianjin, respectively. The Pb pollution level of urban street dust varies among cities in the range of 1.72–5.56 times higher than soil background values. The allometric function can fit the change in Pb concentration with particle size well. The medium-sized (38–120 μm) particles contributed 60.2%–80.4% to the Pb load and should be highlighted when selecting street dust management techniques. Influenced by the distribution of Pb ore, the Pb concentration of urban street dust in China shows obvious regional differences, with value in the south 112% higher than that in the north. Among all kinds of mining types, metal-related mining activities discharge a large amount of Pb dust in the process of crushing and smelting, thus contributing most to the Pb load. The Pb load was also affected by transportation. The relationship between Pb load and gross domestic product (GDP) was described with the environmental Kuznets curve (EKC) model, which indicated that the Pb emissions of most cities were still increasing. Finally, the human health risk assessment model with adjusted parameters showed that the Pb risk of all cities was below the threshold. Despite all this, given the EKC law of Pb emission, long-term follow-up assessments are needed.

Air quality in the megacity Delhi is affected not only by local emissions but also by pollutants from crop residue burning in the surrounding areas of the city, particularly the rice straw burning in the post monsoon season. As a major burning product, gaseous CO₂, which is rather inert in the polluted atmosphere, provides an alternative solution to characterize the impact of biomass burning from a new perspective that other common tracers such as particulate matters are limited because of their physical and chemical reactiveness. Here, we report conventional ([CO₂], δ¹³C, and δ¹⁸O) and unconventional (Δ¹⁷O) isotope data for CO₂ collected at Connaught Place (CP), a core area in the megacity Delhi, and two surrounding remote regions during a field campaign in October 18–20, 2017. We also measured the isotopic ratios near a rice straw burning site in Taiwan to constrain their end member isotopic compositions. Rice straw burning produces CO₂ with δ¹³C, δ¹⁸O, and Δ¹⁷O values of −29.02 ± 0.65, 19.63 ± 1.16, and 0.05 ± 0.02‰, respectively. The first two isotopic tracers are less distinguishable from those emitted by fossil fuel combustion but the last one is significantly different. We then utilize these end member isotopic ratios, with emphasis on Δ¹⁷O for the reason given above, for partitioning sources that affect the CO₂ level in Delhi. Anthropogenic fraction of CO₂ at CP ranges from 4 to 40%. Further analysis done by employing a three-component (background, rice straw burning, and fuel combustion) mixing model with constraints from the Δ¹⁷O values yields that rice straw burning contributes as much as ∼70% of the total anthropogenic CO₂, which is more than double of the fossil fuel contribution (∼30%), during the study days.

Destructive development of suburban areas in some metropolises has exposed suburban soils to high risk of potentially toxic trace elements (PTEs) enrichment, which also threatens human and ecosystem health. This study investigated the pollution status, sources and spatial patterns of four PTEs (Pb, Cd, Cr and As) in 1805 soil samples collected from the suburbs of Shanghai in 2015. Nineteen potential sources, including: 6 soil property factors, 10 proximity factors and 3 topography factors, were selected to help explain the PTEs aggregation using logistic regression models from global and local perspectives. The statistical results of PTEs concentration revealed that Cd showed the highest pollution risk in local soils, which was followed by As. Soil property was the primary factor affecting the PTEs (except Cr) enrichment, both identified by global models and local models. The local model particularly emphasized the significant correlation between soil property and PTEs in most parts of the outer suburbs and southeastern inner suburbs. Some proximity factors such as distance to district center and water were negatively correlated with Cd pollution and some topography factors such as elevation and slope were closely related to As pollution. It is worth noting that in the coastal areas, especially Chongming Island, there were obvious PTEs depositions in the soil near the estuary. This study helps to identify the sources of anthropogenic contamination and geogenic enrichment of the four PTEs and their spatial patterns, playing an essential role in formulating regional environmental policies for coastal cities.

Atmospheric dry deposition is a major pathway for removal of polycyclic aromatic hydrocarbons (PAHs) from the atmosphere. Despite its significance in the atmospheric environment, measurements of the dry deposition velocity (VDD) and deposition fluxes (FDD) of PAHs are relatively limited. In this study, a passive dry deposition (PAS-DD) collector was co-deployed with passive air sampler polyurethane foam (PAS-PUF) from November 2015 to November 2016 in two major cities (Kathmandu and Pokhara), Nepal, to investigate the VDD and FDD of PAHs. The VDD of PAHs ranged from 0.25 to 0.5 cm s⁻¹ and the annual average was recorded as 0.37 ± 0.08 cm s⁻¹. On the basis of measured VDD, the FDD of ∑15PAHs in Kathmandu and Pokhara were estimated as 66 and 5 kg yr⁻¹ respectively. According to the measured VDD of Kathmandu and Pokhara in this study, and the previously published VDD data of Toronto, Canada, where the same PAS-DD collector was used, a significant multi-linear correlation (r² = 0.79, p < 0.05) was found between VDD of higher molecular weight (HMW with MW ≥ 228.3 and ≥ 4 rings) PAHs and meteorological parameters (precipitation and wind speed) and vapor pressure of PAHs. To the best of our knowledge, this enabled the development of an empirical model that can exhibit the combined effects of meteorological conditions on the VDD of HMW PAHs. The model was used to estimate the VDD values for major cities in the Indo-Gangetic Plain (IGP) region and the maximum estimated proportion of HMW PAHs deposited by dry deposition reached up to 60% of total emissions. Although PAH emissions in the IGP region pose global risks, the results of this study highlight the considerable risk for local IGP residents, due to the large dry deposition proportion of HMW PAHs.

Antibiotic resistance surveillance data is lacking in many parts of the world, limiting effective therapy and management of resistance development. Analysis of urban wastewater, which contains bacteria from thousands of individuals, opens up possibilities to generate informative surveillance data in a standardized and resource-efficient way. Here, we evaluate the relationship between antibiotic resistance prevalence in E. coli from wastewater and clinical samples by studying countries with different resistance situations as assessed by traditional clinical surveillance. Composite, influent wastewater samples were collected over 24 h from treatment plants serving major cities in ten European countries. Using a broth screening method, resistance to six antibiotic classes was analyzed for 2507 E. coli isolates (n = 247–252 per country). Resistance prevalence in wastewater E. coli was compared to that in clinical E. coli reported by the European Antibiotic Resistance Surveillance Network. Resistance prevalence was lower in wastewater than clinical E. coli but followed similar geographic trends. Significant relationships were found for resistance to aminopenicillins (R² = 0.72, p = 0.0019) and fluoroquinolones (R² = 0.62, p = 0.0072), but not for aminoglycosides (R² = 0.13, p = 0.31) and third-generation cephalosporins (R² = 0.00, p = 0.99) where regression analyses were based on considerably fewer resistant isolates. When all four antibiotic classes were taken into account, the relationship was strong (R² = 0.85, p < 0.0001). Carbapenem resistance was rare in both wastewater and clinical isolates. Wastewater monitoring shows promise as method for generating surveillance data reflecting the clinical prevalence of antibiotic resistant bacteria. Such data may become especially valuable in regions where clinical surveillance is currently limited.

Air pollution is one of the most important branches of environmental science as it affects human health, climate and ecosystems. Emissions of air pollutants from transport (vehicles and ships) in port cities strongly affect air quality at local scales, warranting for a combination of theoretical and experimental studies to identify pollution hotspots. The purpose of this paper is to provide a methodology for developing a hybrid emission inventory from transport sector for two port cities located respectively on the Northern Aegean islands of Chios and Lesvos. Emission inventories were constructed for the year 2014 based on top-down and bottom-up approaches. Official data from local authorities and survey results were used for the calculation of emissions. Traffic emissions were spatially allocated to the road network based on population data and hourly traffic counts, and distributed over time (on an hourly basis) with the use of local temporal coefficients.Regarding carbon monoxide road emissions, the highest quantities are mainly emitted by Passenger Cars (43%,32% in Chios and Lesvos respectively) while for PM₁₀ emissions, trucks have the largest share (66% in Chios and 86% in Lesvos). The pollutants that are emitted in greater quantities from the ships at the ports of Mytilene and Chios are NOₓ, followed by SO₂ and CO. Most of the ship emissions in the ports occur by the ships at berth, as they remain berthed for hours whereas maneuvering lasts 15–20 min. As for the daily contribution of the two transport sources to the pollution profile of Mytilene, road emissions are higher for almost all pollutants. However, the contribution of ship emissions is not negligible, especially during the touristic period when marine traffic increases and emissions close to the port area become more important than those from road transport.