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An approach to predict population exposure to ambient air PM2.5 concentrations and its dependence on population activity for the megacity London
2020
Singh, Vikas | Sokhi, Ranjeet S. | Kukkonen, Jaakko
A comprehensive modelling approach has been developed to predict population exposure to the ambient air PM₂.₅ concentrations in different microenvironments in London. The modelling approach integrates air pollution dispersion and exposure assessment, including treatment of the locations and time activity of the population in three microenvironments, namely, residential, work and transport, based on national demographic information. The approach also includes differences between urban centre and suburban areas of London by taking account of the population movements and the infiltration of PM₂.₅ from outdoor to indoor. The approach is tested comprehensively by modelling ambient air concentrations of PM₂.₅ at street scale for the year 2008, including both regional and urban contributions. Model analysis of the exposure in the three microenvironments shows that most of the total exposure, 85%, occurred at home and work microenvironments and 15% in the transport microenvironment. However, the annual population weighted mean (PWM) concentrations of PM₂.₅ for London in transport microenvironments were almost twice as high (corresponding to 13–20 μg/m³) as those for home and work environments (7–12 μg/m³). Analysis has shown that the PWM PM₂.₅ concentrations in central London were almost 20% higher than in the surrounding suburban areas. Moreover, the population exposure in the central London per unit area was almost three times higher than that in suburban regions. The exposure resulting from all activities, including outdoor to indoor infiltration, was about 20% higher, when compared with the corresponding value obtained assuming inside home exposure for all times. The exposure assessment methodology used in this study predicted approximately over one quarter (−28%) lower population exposure, compared with using simply outdoor concentrations at residential locations. An important implication of this study is that for estimating population exposure, one needs to consider the population movements, and the infiltration of pollution from outdoors to indoors.
Afficher plus [+] Moins [-]Spatiotemporal dynamics and impacts of socioeconomic and natural conditions on PM2.5 in the Yangtze River Economic Belt
2020
Liu, Xiao-Jie | Xia, Si-You | Yang, Yu | Wu, Jing-fen | Zhou, Yan-Nan | Ren, Ya-Wen
The determination of the spatiotemporal patterns and driving factors of PM₂.₅ is of great interest to the atmospheric and climate science community, who aim to understand and better control the atmospheric linkage indicators. However, most previous studies have been conducted on pollution-sensitive cities, and there is a lack of large-scale and long-term systematic analyses. In this study, we investigated the spatiotemporal evolution of PM₂.₅ and its influencing factors by using an exploratory spatiotemporal data analysis (ESTDA) technique and spatial econometric model based on remote sensing imagery inversion data of the Yangtze River Economic Belt (YREB), China, between 2000 and 2016. The results showed that 1) the annual value of PM₂.₅ was in the range of 23.49–37.67 μg/m³ with an inverted U-shaped change trend, and the PM₂.₅ distribution presented distinct spatial heterogeneity; 2) there was a strong local spatial dependence and dynamic PM₂.₅ growth process, and the spatial agglomeration of PM₂.₅ exhibited higher path-dependence and spatial locking characteristics; and 3) the endogenous interaction effect of PM₂.₅ was significant, where each 1% increase in the neighbouring PM₂.₅ levels caused the local PM₂.₅ to increase by at least 0.4%. Natural and anthropogenic factors directly and indirectly influenced the PM₂.₅ levels. Our results provide spatial decision references for coordinated trans-regional air pollution governance as well as support for further studies which can inform sustainable development strategies in the YREB.
Afficher plus [+] Moins [-]Comparison of land use regression and random forests models on estimating noise levels in five Canadian cities
2020
Liu, Ying | Goudreau, Sophie | Oiamo, Tor | Rainham, Daniel | Hatzopoulou, Marianne | Chen, Hong | Davies, Hugh | Tremblay, Mathieu | Johnson, James | Bockstael, Annelies | Leroux, Tony | Smargiassi, Audrey
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.
Afficher plus [+] Moins [-]Heterogeneity of influential factors across the entire air quality spectrum in Chinese cities: A spatial quantile regression analysis
2020
Han, Xiaodan | Fang, Wei | Li, Huajiao | Wang, Yao | Shi, Jianglan
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.
Afficher plus [+] Moins [-]Short-term effect of PM1 on hospital admission for ischemic stroke: A multi-city case-crossover study in China
2020
Chen, Lijun | Zhang, Yongming | Zhang, Wenyi | Chen, Gongbo | Lü, Peng | Guo, Yuming | Li, Shanshan
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.
Afficher plus [+] Moins [-]Spatial-temporal distribution and transport flux of polycyclic aromatic hydrocarbons in a large hydropower reservoir of Southeast China: Implication for impoundment impacts
2020
Wu, Yuling | Wang, Xinhong | Ya, Miaolei | Li, Yongyu | Liu, Yihao | Chen, Hanzhe
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.
Afficher plus [+] Moins [-]Lead distribution in urban street dust and the relationship with mining, gross domestic product GDP and transportation and health risk assessment
2020
Chang, Xuan | Li, Ying-Xia
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.
Afficher plus [+] Moins [-]A new perspective of probing the level of pollution in the megacity Delhi affected by crop residue burning using the triple oxygen isotope technique in atmospheric CO2
2020
Laskar, Amzad H. | Maurya, Abhayanand S. | Singh, Vishvendra | Gurjar, Bhola R. | Liang, Mao-Chang
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.
Afficher plus [+] Moins [-]Identifying the sources and spatial patterns of potentially toxic trace elements (PTEs) in Shanghai suburb soils using global and local regression models
2020
Liu, Yue | Fei, Xufeng | Zhang, Zhonghao | Li, Yansheng | Tang, Junzhe | Xiao, Rui
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.
Afficher plus [+] Moins [-]Determination of dry deposition velocity of polycyclic aromatic hydrocarbons under the sub-tropical climate and its implication for regional cycling
2020
Dotel, Jagdish | Gong, Ping | Wang, Xiaoping | Pokhrel, Balram | Wang, Chuanfei | Nawab, Javed
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.
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