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Construction particulate matter is one of the main environmental impact factors in the construction process. Due to the lack of sufficient awareness and understanding of the potential health effects of particulate matter by project managers and construction workers, the on-site working environment has not been effectively improved for a long time, and construction workers have been exposed to high particulate matter concentration conditions for physical labor for a long time. The construction site is a special operation scene, and the source and diffusion of particulate matter are a complex physical change process, and the degree of damage to the health of construction workers is closely related to the exposure dose. Thus, suitable quantitative and evaluation methods need to be adopted. The current on-site particulate matter concentration control system lacks technical and data support and cannot support the needs of on-site environmental management. In this paper, three construction sites in different stages of construction in Shanghai were selected to measure the mass concentration of open source particulate matter, and on this basis, the emission factors of particulate matter in different operating areas were calculated. At foundation stage, the emission factor of TSP, PM10, PM2.5 are 0.0214 g/m2·h, 0.0067 g/m2·h, 0.0054 g/m2·h; at main structure stage, the emission factor of TSP, PM10, PM2.5 are 0.0136 g/m2·h, 0.0053 g/m2·h, 0.0041 g/m2·h; at installation and decoration stage, the emission factor of TSP, PM10, PM2.5 are 0.0165 g/m2·h, 0.0059 g/m2·h, 0.0043 g/m2·h. Using simulation software to simulate the temporal and spatial distribution of particulate matter concentration at the site of the example project, it is found that workers engaged in pit bottom operation in the foundation stage, steel bar processing in the main structure stage, and plastering, masonry and putty workers in the installation and decoration stage are the people with the highest occupational health risk at the construction site. In this study, DALYs were used as a metric to monetize the health risks of particulate matter to workers in the field. Support scientific decision-making on particulate matter control at construction sites and improve the level of on-site occupational health management.
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BACKGROUND: Epicardial adipose tissue (EAT) is a type of ectopic fat with endocrine and paracrine functions. Aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that responds to environmental stimuli. AhR expression is associated with obesity. In this cross-sectional study, we aimed to determine the relationship between circulating AhR concentrations and EAT. METHODS: A total of 30 men with obesity and 23 age-matched men as healthy controls were enrolled. Plasma AhR concentrations were determined at fasting. The EAT thickness was measured on the free wall of the right ventricle from the basal short-axis plane by magnetic resonance imaging. RESULTS: The participants with obesity had a higher plasma AhR level than the controls (81.0 ± 24.5 vs. 65.1 ± 16.4 pg/mL, P = 0.010). The plasma AhR level was positively correlated with EAT thickness (correlation coefficient = 0.380, P = 0.005). After adjusting for fasting glucose levels, plasma AhR levels were still significantly associated with EAT thickness (95% CI 0.458â5.357, P = 0.021) but not with body mass index (P = 0.168). CONCLUSION: Plasma AhR concentrations were positively correlated with EAT thickness on the free wall of the right ventricle in men. Further investigations are needed to evaluate the causal effects and underlying mechanisms between AhR and EAT.
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The Western Pacific Ocean (the WPO), as one of the busiest shipping areas in the world, holds a complex water traffic network. In 2020, the International Maritime Organization (IMO) low-sulfur fuel regulations were implemented globally, while the COVID-19 outbreak influenced shipping activities together. This study aimed to assess the combined impact of epidemics and low-sulfur fuel policies on ship emissions, as well as their environmental effects on the WPO. The ship emission model based on the Automatic Identification System (AIS) data was applied to analyze the monthly emission variations during 2018-2020. It was found that the epidemic had obvious diverse influences on the coastal ports in the WPO. Overall, shipping emissions declined by 15 %-30 % in the first half of 2020 compared with those in 2019 due to the COVID-19 lockdown, whereas they rebounded in the second half as a result of trade recovery. The pollutants discharged per unit of cargo by ships rose after the large-range lockdown. China's multiphase domestic emission control areas (DECAs) and the IMO global low-sulfur fuel regulation have greatly reduced SO2 emissions from ships and caused them to "bypass and come back" to save fuel costs around emission control areas from 2018 to 2020. Based on satellite data and land-based measurements, it was found that the air quality over sea water and coastal cities has shown a positive response to changes in ship-emitted NOx and SO2. Our results reveal that changes in shipping emissions during typical periods, depending on their niches in the complex port traffic network, call for further efforts for cleaner fuel oils, optimized ECA and ship lane coordination in the future. Shipping related air pollutions during the later economic recovery also needs to be addressed after international scale standing-by events.
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Contaminantes Atmosféricos , Contaminación del Aire , COVID-19 , Epidemias , Aceites Combustibles , Humanos , Contaminantes Atmosféricos/análisis , Navíos , COVID-19/epidemiología , Control de Enfermedades Transmisibles , Contaminación del Aire/análisis , Azufre , Emisiones de Vehículos/análisis , Material Particulado/análisisRESUMEN
Clean air policies have achieved remarkable air quality improvement in China for the last decade. However, as more importance was attached to climate issues and further improvement of air quality, policies with greenhouse gas (GHG) reduction potential were supposed to play a significant role. Here, we designed a conventional legislation pathway scenario (CLP) and an enhanced greenhouse gas reduction scenario (EGR), to estimate the co-effects of policies effective in GHG reduction on air pollutant control and air quality improvement in the Yangtze River Delta (YRD) region from 2014 to 2020, adopting a measure-specific evaluation method and an integrated WRF-CAMx model simulation. Results showed that: 1) With the implementation of enhanced measures with GHG reduction potential, emissions of SO2, NOx, PM2.5, PM10, VOCs and NH3 decreased by 16.4 %, 21.6 %, 18.6 %, 16.5 %, 23.9 % and 15.4 % in EGR scenario respectively, compared with CLP scenario. And the annual mean simulated concentrations of PM2.5, SO2 and NO2 of the YRD decreased by 11.2 %, 15.4 % and 20.6 %, respectively. 2) The average 8-h maxima (MDA8) concentration of O3 presented a slightly increasing trend under the impacts of measures with GHG reduction potential, which might be on account of the unbalanced control of NOx and VOCs, the two major precursors of O3. 3) Based on the source apportionment analysis, major partition of total ozone in the four receptors in YRD was from regional transportation, rather than local formation. And the major sectors contributing to ozone were industry and transportation sector. This study quantitatively assessed the co-benefits of GHG-control-effective policies and specific measures on air quality improvement, which would help to provide implications for future policy-making to achieve air pollution and climate change co-control.
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Contaminantes Atmosféricos , Contaminación del Aire , Gases de Efecto Invernadero , Ozono , Compuestos Orgánicos Volátiles , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Contaminación del Aire/prevención & control , China , Monitoreo del Ambiente , Gases de Efecto Invernadero/análisis , Dióxido de Nitrógeno/análisis , Ozono/análisis , Material Particulado/análisis , Políticas , Compuestos Orgánicos Volátiles/análisisRESUMEN
A better understanding of river capacity for contaminants (i.e., water environmental capacity, WEC) is essential for the reasonable utilization of water resources, providing government's with guidance about sewage discharge management, and allocating investments for pollutant reduction. This paper applied a new framework integrating a modified hydro-environmental model, Soil and Water Assessment Tool (SWAT) model, and load-duration curve (LDC) method for the dynamic estimation of the NH3-N WEC of the data-scarce Luanhe River basin in China. The impact mechanisms of hydrological and temperature conditions on WEC are discussed. We found that 77% of the WEC was concentrated in 40% hydrological guarantee flow rates. While the increasing flow velocity promoted the pollutant decay rate, it shortened its traveling time in streams, eventually reducing the river WEC. The results suggest that the integrated framework combined the merits of the traditional LDC method and the mechanism model. Thus, the integrated framework dynamically presents the WEC's spatiotemporal distribution under different hydrological regimes with fewer data. It can also be applied in multi-segment rivers to help managers identify hot spots for fragile water environmental regions and periods at the basin scale.
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Contaminantes Ambientales , Contaminantes Químicos del Agua , China , Monitoreo del Ambiente/métodos , Ríos , Agua , Contaminantes Químicos del Agua/análisisRESUMEN
Heat-induced labor loss is a major economic cost related to climate change. Here, we use hourly heat stress data modeled with a regional climate model to investigate the heat-induced labor loss in 231 Chinese cities. Results indicate that future urban heat stress is projected to cause an increase in labor losses exceeding 0.20% of the total account gross domestic product (GDP) per year by the 2050s relative to the 2010s. In this process, certain lower-paid sectors could be disproportionately impacted. The implementation of various urban adaptation strategies could offset 10% of the additional economic loss per year and help reduce the inequality-related impact on lower-paid sectors. So future urban warming can not only damage cities as a whole but can also contribute to income inequality. The implication of adaptation strategies should be considered in regard to not only cooling requirements but also environmental justice.
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Aclimatación , Regulación de la Temperatura Corporal , Cambio Climático , Modelos Climáticos , Frío , Femenino , Humanos , EmbarazoRESUMEN
In this cross-sectional study, enrollment included 818 female adults undergoing bone mineral density (BMD) assessment during the health examination. Subjects with osteoporosis had the lowest circulating platelet concentrations. The circulating platelet concentration was positively correlated with BMD. A high platelet concentration had independently low odds of osteoporosis. PURPOSE: Platelets play an important role in bone metabolism. However, the association between circulating platelet counts and bone mineral density (BMD) has been inconsistently reported. We aimed to investigate the relationship between platelet counts and osteoporosis in Chinese women. METHODS: In this cross-sectional study, a total of 818 female adults who underwent BMD assessment during the health examination were enrolled. Blood cell counts and biochemistry data were recorded. RESULTS: Subjects with osteoporosis had the lowest platelet counts (238 ± 59 × 109/L) compared with subjects with osteopenia (256 ± 64 × 109/L) and a normal BMD (269 ± 76 × 109/L, P < 0.001). The circulating platelet concentration was positively correlated with the BMD of the lumbar spine (r = 0.195, P < 0.001), left hip (r = 0.145, P < 0.001), and right hip (r = 0.149, P < 0.001). According to the receiver operating characteristic curve, the cutoff platelet concentration for differentiating osteoporosis was 260 × 109/L. A high platelet concentration had significantly low odds of osteoporosis after adjusting for other covariates (odds ratio = 0.574, 95% confidence interval: 0.346â0.953, P = 0.032). CONCLUSION: The circulating platelet concentration was significantly correlated with BMD in Chinese women.
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Enfermedades Óseas Metabólicas , Osteoporosis , Absorciometría de Fotón , Adulto , Plaquetas , Densidad Ósea , Enfermedades Óseas Metabólicas/epidemiología , Estudios Transversales , Femenino , Humanos , Vértebras Lumbares/diagnóstico por imagenRESUMEN
The implementation of pollutant emission control has made initial achievements in the plant power, iron, and steel industries in China. To further improve air quality, it is of great significance to carry out research on zero-impact emissions of the petrochemical industry. Based on the existing concept and practice of zero emissions, this study proposes the concept of zero-impact emissions, taking emission concentration as the constraint. A typical petrochemical enterprise (namely Enterprise A) in Shanghai Chemical Industry Park as the research object, and used the CALPUFF model to simulate the target pollutant emissions (i.e. sulfur dioxide (SO2), nitrogen oxide (NOx), particulate matter (PM), and volatile organic compounds (VOCs)). The current emission standard, spatial distributions, and emission heights of chimneys in Enterprise A was considered as the baseline emission scenario and taking the zero-impact emission as a target for simulation. The results show that the current emission standards of NOx and VOCs (benzene) exceeded the zero-impact emission limits, and needed to be reduced by 22% and 87.5%, respectively. Moreover, the areas that exceeded the zero-impact concentration limits were located northwest of the chimneys and Hangzhou Bay. In terms of seasonal effects, the wind conditions in spring were more adverse for the enterprise to achieve zero-impact emissions. Based on the simulation, the zero-impact emission limits of SO2, NOx, PM, and VOCs (benzene) for Enterprise A were 50 mg/m3, 78 mg/m3, 10 mg/m3, and 0.32 mg/m3, respectively.Implications: Through case study, this paper solves the environmental management issue which is of universal significance for chemical industry park. The concept of zero-impact emissions and the determination method of zero-impact concentration limits proposed in this study could be used as references for related research on cutting emissions. Although the conclusion of this study about the emission limits is not suitable for other enterprises to apply directly, the calculation method of zero-impact emission limit can be used by other enterprises. Furthermore, the zero-impact emission limits on park scale can be determined after comprehensive evaluation based on the calculation results of multiple enterprises.
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Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Contaminación del Aire/prevención & control , Industria Química , China , Monitoreo del Ambiente , Material Particulado/análisisRESUMEN
In spite of the state-of-the-art performances of machine learning in the PM2.5 estimation, the high-value PM2.5 underestimation and non-random aerosol optical depth (AOD) missing are still huge obstacles. By incorporating wavelet decomposition (WD) into the extreme gradient boosting (XGBoost), a hybrid XGBoost-WD model was established to obtain the full-coverage PM2.5 estimation at 3-km spatial resolution in the Yangtze River Delta Urban Agglomeration (YRDUA). In this study, 3-km-resolution meteorological fields simulated by WRF along with AOD derived from Moderate Resolution Imaging Spectroradiometer (MODIS) were served as explanatory variables. Model MW and Model NW were developed using XGBoost-WD for the areas with and without AOD respectively to obtain a full-coverage PM2.5 mapping in the YRDUA. The XGBoost-WD model showed good performances in estimating PM2.5 with R2 of 0.80 in the Model MW and 0.87 in the Model NW. Moreover, the K-value of Model MW increased from 0.77 to 0.79 and that of Model NM increased from 0.81 to 0.86 compared with the model without the step of WD, indicating an improvement on the problem of PM2.5 underestimation. Due to a better ability of capturing abrupt changes in the PM2.5 concentrations, the spatial evolution of PM2.5 during a typical pollution event could be mapped more accurately. Finally, the analysis of variable importance showed that the three most important variables in the estimation of the low-frequency coefficients of PM2.5 (PM2.5_A4) were temperature at 2 m (T2), day of year (DOY) and longitude (LON), while that in the high-frequency coefficients of PM2.5 (PM2.5_D) were CO, AOD and NO2. This study not only provided an effective solution to the PM2.5 underestimation and AOD missing problems in the PM2.5 estimation, but also proposed a new method to further refine the sophisticated correlations between PM2.5 and some spatiotemporal variables.
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Contaminantes Atmosféricos , Contaminación del Aire , Aerosoles/análisis , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , China , Monitoreo del Ambiente , Material Particulado/análisis , RíosRESUMEN
To study the impact of vessel pollution on the atmospheric environment of the surrounding area, we present a numerical simulation method based on regional emissions inventories. The general spatial resolution is ≥1 km and the temporal resolution is ≥1 h; parameters which are suitable for the study of larger space-time scales. In this paper, the WRF/CALMET/CALPUFF model and Automatic Identification System (AIS) data are employed to develop a single-vessel atmospheric pollution diffusion model. The goal of this research uses existing meteorological models and diffusion models to provide a simulation technology method for studying the diffusion of SO2 from a single ship. We take the outgoing phase of ocean-going container vessels in Yantian Port as an example. It can be used to set the position of sensitive receptors near the port area. Simulations are implemented with CALPUFF and the results are compared with data derived from on-site monitoring instrument. The CALPUFF modelling domain covers an area of 925 km2 with a grid spacing of 500 m. The simulation results demonstrated agreement with the measured data. The ground concentration contribution value ranged from 10 to 102 µg/m3, while the affected area was about 4-26 km2 and the high-value area of the ground concentration contribution was distributed within 1-2 km from the ship track. Emissions generated by the vessels represent a considerable contribution to SO2 pollution around the harbor areas.
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Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , China , Monitoreo del Ambiente , Humanos , Material Particulado/análisisRESUMEN
This study, for the first time, estimates the climate impacts of adopting green roofs and cool roofs on the seasonal urban climate of 16 cities that comprise the Yangtze River Delta metropolitan. We use a suite of regional climate simulation to compare the local climate impacts of the implementation of different roof strategies in summer and winter. The results indicate that in summer, the 2 m surface temperature reduced significantly when these two roof strategies are adopted, with peak reductions of 0.74 and 1.19 K for green roofs and cool roofs, respectively. The cooling impact of cool roofs is more effective than that of green roofs under the scenarios assumed in this study. Besides, rooted in the different mechanisms influencing urban heat flux, significant indirect effects were also observed: adopting cool roofs leads to a decreased precipitation in summer and an apparent reduction in wintertime temperatures in the urban area. Although cool roofs can be an effective way to reduce high temperatures during the summer, green roofs have fewer adverse impacts on other climate conditions. These results underline the need for comprehensive climate change policies that incorporate place-based solutions and extend beyond the nearly exclusive focus on summertime cooling.
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Cambio Climático , Frío , Ciudades , Conservación de los Recursos Naturales , Estaciones del Año , TemperaturaRESUMEN
This work studied the impacts of ship emissions at a high temporal resolution on the real-time concentrations of PM2.5, NO2, and SO2 in urban harbors and coastal sea areas, taking the Yangtze River Delta (YRD) as an example. The WRF-Chem model with 3 nested grids and ship emissions derived from an automatic identification system (AIS) were combined to simulate the air quality. The AIS data showed significant temporal fluctuations in ship emissions, with hourly mean fluxes of approximately 1082.41 ± 444.41 and 593.55 ± 404.95 g/h/km2 near ports and in the channel waters of the YRD, respectively. The monthly mean contributions of shipping emissions reached 80.72% (2.15 ppbv) and 81.79% (8.79 ppbv) to ambient SO2 and NO2 in Ningbo Port, and 10.61% (6.96 µg/m3) to PM2.5 in Shanghai Port, respectively, regions with dense ship traffic. The relative differences in the PM2.5, SO2, and NO2 concentrations modeled using monthly and hourly ship emissions accounted for -10-15%, -10-30%, and - 5-30%, respectively. Compared with cruise- and land-based measurements, the simulations using hourly emissions were in much better agreement with the observations than those using monthly emissions and appropriately captured some air pollutant concentration peaks. Simulations during shipping-related periods with hourly ship emissions improved the normalized mean bias (NMBs) from -43.03%, 301.49%, and 223.02% to -27.28%, 90.45%, and 167.52%, respectively, for PM2.5, SO2, and NO2, highlighting the importance of using ship emissions with a fine temporal resolution. Our study showed that ignoring hourly fluctuations in ship emissions during air quality modeling leads to considerable uncertainties, especially in coastal urban areas and harbors with high ship activities. These results imply that data with a high temporal resolution, such as hourly ship emissions, are necessary to understand the realistic impacts of shipping traffic and to implement more precise control policies to improve coastal air quality.
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PM2.5 pollution has been one of the main environmental issues of concern for the Yangtze River Delta Urban Agglomeration (YRDUA) during the recent decade. In this paper, allied with big data and wavelet analysis, spatiotemporal variations of PM2.5 and its influencing factors (air pollutants and meteorological factors) are studied based on hourly concentrations of PM2.5 from 2015 to 2018 in the YRDUA. Results showed that PM2.5 presented a step-shaped decline from northwest to southeast in space and significant multi-scale temporal variations in time. On the macroscopic level, PM2.5 concentrations decreased from 2015 to 2018, showing a U-shaped pattern within a year. On the microscopic level, it had a four-stage annual variation (January to March, April to June, July to September, October to December) and the mutation events mainly occurred in winter. There were two dominant periods of PM2.5, an annual cycle on the time scale of 250-480 d and a semi-annual cycle on the time scale of 130-220 d. In addition, PM2.5 showed time scale-dependent correlations with air pollutants and meteorological factors. Among air pollutants, the correlation between PM2.5 and CO was the most consistent, and the correlation between PM2.5 and SO2/NO2 improved with the increase of time scale, while the correlation between PM2.5 and O3 was positive at shorter time scales but negative at broader time scales. Among meteorological factors, the correlations between PM2.5 and wind speed, precipitation, temperature, air pressure and relative humidity were mainly reflected at broader time scales. These findings would be helpful to improve the accuracy of prediction model and provide references for the ongoing joint prevention and control.
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China has been in the implementation phase of Domestic Ship Emission Control Areas (DECAs) regulation to reduce emissions of air pollutants from ships near populated areas since 2016. The Yangtze River Delta (YRD) is one of the busiest port clusters in the world, accounting for 11% of global seaborne cargo throughput, so future improvements in shipping emission controls may still be important in this region. To assess the impact of future ship emissions on air quality of coastal areas, this study evaluates emissions reductions and air quality in 2030 for three scenarios (business as usual, stricter regulations, and aspirational policies) representing increasing levels of control compared with a base year of 2015. We projected ship emissions in the region using a bottom-up approach developed in this study and based on the historical ship automatic identification system (AIS) activity data. We then predicted air quality across the YRD region in 2030 using the Community Multiscale Air Quality (CMAQ) model. The annual average contributions of ship emissions to ambient PM2.5 would decrease by 70.9%, 80.4%, and 86.2% relative to 2015 under the three scenarios, with the largest reductions of more than 4.1 µg/m3 near Shanghai Port under the aspirational scenario. Reductions in ship emissions generally led to lower levels of PM2.5, particularly in most of the coastal cities in the YRD. Compared with a business-as-usual approach the aspirational scenario reduced SO2, NOx and PM2.5 concentrations from shipping by 71.8%, 61.1% and 52.5%, respectively. It was also more effective than the stricter regulation scenario, suggesting that the requirement to use 0.1% sulfur fuel within a 100Nm DECA would have additional benefits to ambient PM2.5 concentrations beyond 12Nm DECA area. This study provides evidence to inform deliberations on the potential air quality benefits of future control policies for ship emissions in China.
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Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , China , Ciudades , Monitoreo del Ambiente , Material Particulado/análisis , Ríos , Navíos , Emisiones de Vehículos/análisisRESUMEN
Rapid urbanisation has altered the vulnerability of urban areas to heat wave disasters. There is an urgent need to identify the factors underlying the effect of heat waves on human health and the areas that are most vulnerable to heat waves. In this study, we plan to integrate indices associated with heat wave vulnerability based on meteorological observation data, remote sensing data and point of interest (POI) data; analyse the influence of urbanisation on the urban vulnerability environment; and explore the relationship between the vulnerability environment and heat-wave-related mortality. Finally, we attempt to map the spatial distribution of high heat-wave-related mortality risk based on the results of heat wave vulnerability study and artificial society. The results reveal that 1) there are differences in the influence of urbanisation on heat wave exposure, sensitivity and adaptability; 2) the exposure and sensitivity level effects on the lower limit of health impacts and the adaptability level effects on the upper limit of the health impact from heat wave in a given study area; and 3) areas vulnerable to the effects of heat waves are not confined to the city centre, which implies that residents living in suburban areas are also vulnerable to heat waves. Finally, this study not only explores the factors contributing to the impacts of heat waves but also describes the spatial distribution of the risk of disaster-associated mortality, thereby providing direct scientific guidance that can be used by cities to address heat wave disasters in the future.
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Macrodatos , Tiempo (Meteorología) , Ciudades , Desastres , Calor , Rayos Infrarrojos , UrbanizaciónRESUMEN
Characteristics of the spatial and temporal distribution of air pollutants may reveal the cause of air pollution, especially for large regions where the anthropogenic pollutant emission is concentrated. This study addresses this issue by focusing on Shandong province, which has the highest air pollutant emissions in China. First, the spatial and temporal variation characteristics of the observed concentrations of conventional pollutants are analyzed in detail. The most prominent indicator of the problem (PM2.5), was selected as the key analytical object. On the spatial scale, the Multivariate Moran model was used to identify factors affecting the spatial distribution of PM2.5. On the time scale, wavelet analysis was used to explore the fluctuation characteristics of PM2.5 at different time periods. Results show that there are significant regional differences in pollutant concentration within Shandong province. The concentration of particulate matter and gaseous pollutants in western and northern Shandong is significantly higher than eastern Shandong. The average concentrations of PM2.5, PM10, SO2 and NO2 were highest in winter and lowest in summer, whereas concentration of O3 peaked in summer. For PM2.5, the annual mean concentration has a significant spatial correlation with SO2 emission, GDP per capita, population density and energy consumption per unit of GDP; in addition, the correlation between different regions and various indices is different. On the time scale, the fluctuation energy of PM2.5 concentrated in Dezhou and Liaocheng is the strongest on December 18 and 19, 2015. The inversion temperature has a strong influence on the daily variation of PM2.5 concentration. The formation and evolution of atmospheric pollution, therefore, can be explored by combining the temporal and spatial distribution of pollutants, providing a comprehensive analytical method for atmospheric pollution in different regions.
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In this study, the authors endeavored to develop an effective framework for improving local urban air quality on meso-micro scales in cities in China that are experiencing rapid urbanization. Within this framework, the integrated Weather Research and Forecasting (WRF)/CALPUFF modeling system was applied to simulate the concentration distributions of typical pollutants (particulate matter with an aerodynamic diameter <10 µm [PM10], sulfur dioxide [SO2], and nitrogen oxides [NOx]) in the urban area of Benxi. Statistical analyses were performed to verify the credibility of this simulation, including the meteorological fields and concentration fields. The sources were then categorized using two different classification methods (the district-based and type-based methods), and the contributions to the pollutant concentrations from each source category were computed to provide a basis for appropriate control measures. The statistical indexes showed that CALMET had sufficient ability to predict the meteorological conditions, such as the wind fields and temperatures, which provided meteorological data for the subsequent CALPUFF run. The simulated concentrations from CALPUFF showed considerable agreement with the observed values but were generally underestimated. The spatial-temporal concentration pattern revealed that the maximum concentrations tended to appear in the urban centers and during the winter. In terms of their contributions to pollutant concentrations, the districts of Xihu, Pingshan, and Mingshan all affected the urban air quality to different degrees. According to the type-based classification, which categorized the pollution sources as belonging to the Bengang Group, large point sources, small point sources, and area sources, the source apportionment showed that the Bengang Group, the large point sources, and the area sources had considerable impacts on urban air quality. Finally, combined with the industrial characteristics, detailed control measures were proposed with which local policy makers could improve the urban air quality in Benxi. In summary, the results of this study showed that this framework has credibility for effectively improving urban air quality, based on the source apportionment of atmospheric pollutants. IMPLICATIONS: The authors endeavored to build up an effective framework based on the integrated WRF/CALPUFF to improve the air quality in many cities on meso-micro scales in China. Via this framework, the integrated modeling tool is accurately used to study the characteristics of meteorological fields, concentration fields, and source apportionments of pollutants in target area. The impacts of classified sources on air quality together with the industrial characteristics can provide more effective control measures for improving air quality. Through the case study, the technical framework developed in this study, particularly the source apportionment, could provide important data and technical support for policy makers to assess air pollution on the scale of a city in China or even the world.
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Contaminantes Atmosféricos/química , Monitoreo del Ambiente/métodos , Modelos Teóricos , Tiempo (Meteorología) , Contaminación del Aire/análisis , China , Ciudades , Óxidos de Nitrógeno/análisis , Material Particulado/análisis , Estaciones del Año , Dióxido de Azufre/análisisRESUMEN
The Yangtze River Delta (YRD) port cluster is one of five major port clusters in China and is home to Shanghai port, the largest port worldwide. In this study, an automatic identification system-based model was built to estimate the ship exhaust emissions in the YRD and the East China Sea within 400 km of the coastline. In 2010, the total emissions of SO2, NOX, and PM2.5 were 3.8 × 10(5) tonnes/yr, 7.1 × 10(5) tonnes/yr, and 5.1 × 10(4) tonnes/yr, respectively. More than 60% and 85% of the ship emissions occurred within 100 km and 200 km of the coastline, respectively. Ship emissions also showed distinct seasonal variability. The emission of SO2 and NOX by ships in hot spots, such as ports and vessel traffic hubs was much higher than that on land, with maximum SO2 and NOX intensities from ships that were 36 times and 17 times greater, respectively, than the maximal land-based emissions. The potential impact of ship emissions at six hot spots on the surrounding atmospheric environment was estimated with the HYSPLIT model. Our study demonstrated that ship emissions have an important impact on both the entire YRD region and on greater East China.
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Contaminantes Atmosféricos/análisis , Modelos Teóricos , Navíos/estadística & datos numéricos , Emisiones de Vehículos/análisis , China , Ríos , Estaciones del AñoRESUMEN
This paper reports on a study which explored the possible relationship between road traffic noisescape and urban form in Hong Kong. A total of 212 residential complexes from 11 contrasting urban forms were sampled, and their noise levels assessed both at dwelling and neighbourhood scales by noise mapping. Its findings indicate that residential complexes with different urban forms have significantly different noisescape attributes. There is a strong correlation between the noise characteristics and morphological indicators at the dwelling scale. A less obstreperous noisescape is associated with urban forms with lower road and building densities, and with building arrangements which provide self-noise screening. These findings suggest that urban form is an influential determinant of the noisescape in the urban environment, and they point to the need to rethink the conventional approach to managing the urban acoustic environment.
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Ciudades , Monitoreo del Ambiente , Ruido del Transporte , Hong Kong , ViviendaRESUMEN
The CCD multi-band data of HJ-1A has great potential in inland water quality monitoring, but the precision of atmospheric correction is a premise and necessary procedure for its application. In this paper, a method based on dark pixel for water-leaving radiance retrieving is proposed. Beside the Rayleigh scattering, the aerosol scattering is important to atmospheric correction, the water quality of inland lakes always are case II water and the value of water leaving radiance is not zero. So the synchronous MODIS shortwave infrared data was used to obtain the aerosol parameters, and in virtue of the characteristic that aerosol scattering is relative stabilized in 560 nm, the water-leaving radiance for each visible and near infrared band were retrieved and normalized, accordingly the remotely sensed reflectance of water was computed. The results show that the atmospheric correction method based on the imagery itself is more effective for the retrieval of water parameters for HJ-1A CCD data.