scholarly journals Source attribution and process analysis for atmospheric mercury in East China simulated by CMAQ-Hg

2015 ◽  
Vol 15 (7) ◽  
pp. 10389-10424 ◽  
Author(s):  
J. Zhu ◽  
T. Wang ◽  
J. Bieser ◽  
V. Matthias
Keyword(s):  
Urban Area ◽  
Urban Areas ◽  
Power Plants ◽  
Process Analysis ◽  
Atmospheric Mercury ◽  
East China ◽  
Mercury Deposition ◽  
Chemical Production ◽  
Horizontal Advection ◽  
The Yrd

Abstract. The contribution from different emission sources and atmospheric processes to gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM), particulate bound mercury (PBM) and mercury deposition in East China were quantified using the Community Multi-scale Air Quality (CMAQ-Hg) modeling system run with nested grid resolution of 27 km. Natural source (NAT) and six categories of anthropogenic mercury sources (ANTH) including cement production (CEM), domestic life (DOM), industrial boilers (IND), metal production (MET), coal-fired power plants (PP) and traffic (TRA) were considered for source apportionment. NAT was responsible for 36.6% of annual averaged GEM concentration which was regard as the most important source for GEM in spite of obvious seasonal variation. Among ANTH, the influence of MET and PP on GEM were most evident especially in winter. ANTH dominated the variations of GOM and PBM concentration with a contribution of 86.7 and 79.1% respectively. Among ANTH, IND was the largest contributor for GOM (57.5%) and PBM (34.4%) so that most mercury deposition came from IND. The effect of mercury emitted from out of China was indicated by > 30% contribution to GEM concentration and wet deposition. The contribution from nine processes consisting of emissions (EMIS), gas-phase chemical production/loss (CHEM), horizontal advection (HADV), vertical advection (ZADV), horizontal advection (HDIF), vertical diffusion (VDIF), dry deposition (DDEP), cloud processes (CLDS) and aerosol processes (AERO) were calculated for processes analysis with their comparison in urban and non-urban regions of Yangtze River Delta (YRD). EMIS and VDIF affected surface GEM and PBM concentration most and tended to compensate each other all the time in both urban and non-urban areas. However, DDEP was the most important removal process for GOM with 7.3 and 2.9 ng m−3 reduced in the surface of urban and non-urban areas respectively in a whole day. Diurnal profile variation of processes revealed the transportation of GOM from urban area to non-urban area and the importance of CHEM/AERO in higher altitudes which caused diffusion of GOM downwards to non-urban area partly. Most of the anthropogenic mercury transported and diffused away from urban area by HADV and VDIF and made gain of mercury in non-urban areas by HADV. Natural emissions only influenced CHEM and AERO more significantly than anthropogenic. Local emission in the YRD contributed 8.5% more to GEM and ~ 30% more to GOM and PBM in urban areas compared to non-urban areas.

scholarly journals Source attribution and process analysis for atmospheric mercury in eastern China simulated by CMAQ-Hg

2015 ◽  
Vol 15 (15) ◽  
pp. 8767-8779 ◽  
Author(s):  
J. Zhu ◽  
T. Wang ◽  
J. Bieser ◽  
V. Matthias
Keyword(s):  
Urban Areas ◽  
Power Plants ◽  
Process Analysis ◽  
Eastern China ◽  
Atmospheric Mercury ◽  
Mercury Deposition ◽  
Chemical Production ◽  
Vertical Diffusion ◽  
Horizontal Advection ◽  
The Yrd

Abstract. The contribution from different emission sources and atmospheric processes to gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM), particulate bound mercury (PBM) and mercury deposition in eastern China were quantified using the Community Multi-scale Air Quality (CMAQ-Hg) modeling system run with a nested domain. Natural sources (NAT) and six categories of anthropogenic mercury sources (ANTH) including cement production (CEM), domestic life (DOM), industrial boilers (IND), metal production (MET), coal-fired power plants (PP) and traffic (TRA) were considered for source apportionment. NAT were responsible for 36.6 % of annual averaged GEM concentration, which was regarded as the most important source for GEM in spite of obvious seasonal variation. Among ANTH, the influence of MET and PP on GEM were most evident especially in winter. ANTH dominated the variations of GOM and PBM concentrations with contributions of 86.7 and 79.1 %, respectively. Among ANTH, IND were the largest contributor for GOM (57.5 %) and PBM (34.4 %) so that most mercury deposition came from IND. The effect of mercury emitted from out of China was indicated by a > 30 % contribution to GEM concentration and wet deposition. The contributions from nine processes – consisting of emissions (EMIS), gas-phase chemical production/loss (CHEM), horizontal advection (HADV), vertical advection (ZADV), horizontal advection (HDIF), vertical diffusion (VDIF), dry deposition (DDEP), cloud processes (CLDS) and aerosol processes (AERO) – were calculated for process analysis with their comparison in urban and non-urban regions of the Yangtze River delta (YRD). EMIS and VDIF affected surface GEM and PBM concentrations most and tended to compensate each other all the time in both urban and non-urban areas. However, DDEP was the most important removal process for GOM with 7.3 and 2.9 ng m−3 reduced in the surface of urban and non-urban areas, respectively, in 1 day. The diurnal profile variation of processes revealed the transportation of GOM from urban area to non-urban areas and the importance of CHEM/AERO in higher altitudes which partly caused diffusion of GOM downwards to non-urban areas. Most of the anthropogenic mercury was transported and diffused away from urban areas by HADV and VDIF and increased mercury concentrations in non-urban areas by HADV. Natural emissions only influenced CHEM and AERO more significantly than anthropogenic. Local emissions in the YRD contributed 8.5 % more to GEM and ~ 30 % more to GOM and PBM in urban areas compared to non-urban areas.

Gaseous mercury in coastal urban areas

2010 ◽  
Vol 7 (6) ◽  
pp. 537 ◽  
Author(s):  
Anne L. Soerensen ◽  
Henrik Skov ◽  
Matthew S. Johnson ◽  
Marianne Glasius
Keyword(s):  
Urban Areas ◽  
Marine Boundary Layer ◽  
Elemental Mercury ◽  
Atmospheric Mercury ◽  
Mercury Deposition ◽  
Mercury Emissions ◽  
Gaseous Elemental Mercury ◽  
Gaseous Mercury ◽  
Range Transport ◽  
Aquatic Food

Environmental context Mercury is a neurotoxin that bioaccumulates in the aquatic food web. Atmospheric emissions from urban areas close to the coast could cause increased local mercury deposition to the ocean. Our study adds important new data to the current limited knowledge on atmospheric mercury emissions and dynamics in coastal urban areas. Abstract Approximately 50% of primary atmospheric mercury emissions are anthropogenic, resulting from e.g. emission hotspots in urban areas. Emissions from urban areas close to the coast are of interest because they could increase deposition loads to nearby coastal waters as well as contribute to long range transport of mercury. We present results from measurements of gaseous elemental mercury (GEM) and reactive gaseous mercury (RGM) in 15 coastal cities and their surrounding marine boundary layer (MBL). An increase of 15–90% in GEM concentration in coastal urban areas was observed compared with the remote MBL. Strong RGM enhancements were only found in two cities. In urban areas with statistically significant GEM/CO enhancement ratios, slopes between 0.0020 and 0.0087 ng m–3 ppb–1 were observed, which is consistent with other observations of anthropogenic enhancement. The emission ratios were used to estimate GEM emissions from the areas. A closer examination of data from Sydney (Australia), the coast of Chile, and Valparaiso region (Chile) in the southern hemisphere, is presented.

scholarly journals Recent decrease trend of atmospheric mercury concentrations in East China: the influence of anthropogenic emissions

2018 ◽  
Vol 18 (11) ◽  
pp. 8279-8291 ◽  
Author(s):  
Yi Tang ◽  
Shuxiao Wang ◽  
Qingru Wu ◽  
Kaiyun Liu ◽  
Long Wang ◽  
...  
Keyword(s):  
Power Plants ◽  
Source Region ◽  
Elemental Mercury ◽  
Sampling Period ◽  
Atmospheric Mercury ◽  
Cement Clinker ◽  
East China ◽  
Air Pollution Control ◽  
Significance Level ◽  
Chongming Island

Abstract. Measurements of gaseous elemental mercury (GEM), other air pollutants, including SO2, NOx, O3, PM2.5, and CO, and meteorological conditions were carried out at Chongming Island in East China from 1 March 2014 to 31 December 2016. During the sampling period, GEM concentrations significantly decreased from 2.68 ± 1.07 ng m−3 in 2014 (March to December) to 1.60 ± 0.56 ng m−3 in 2016 (March to December). Monthly mean GEM concentration showed a significant decrease, at a rate of -0.60±0.08 ng m−3 yr−1 (R2=0.64, p < 0.01 significance level). Combining the analysis of the potential source contribution function (PSCF), principle component analysis (PCA), and the emission inventory, we found that the Yangtze River Delta (YRD) region was the dominant source region of GEM in Chongming Island and the main source industries included coal-fired power plants, coal-fired industrial boilers, and cement clinker production. We further quantified the effect of emission change on the air Hg concentration variations at Chongming Island through a coupled method of trajectory clusters and air Hg concentrations. It was found that the reduction of domestic emissions was the main driver of GEM decline in Chongming Island, accounting for 70 % of the total decline. The results indicated that air pollution control policies targeting SO2, NOx, and particulate matter reductions had significant co-benefits on GEM.

scholarly journals Global deposition of speciated atmospheric mercury to terrestrial surfaces: an overview

2019 ◽  
Author(s):  
Lei Zhang ◽  
Peisheng Zhou ◽  
Shuzhen Cao ◽  
Yu Zhao
Keyword(s):  
Dry Deposition ◽  
Urban Areas ◽  
Wet Deposition ◽  
Current Knowledge ◽  
Elemental Mercury ◽  
Atmospheric Mercury ◽  
Future Research ◽  
Observation System ◽  
Mercury Deposition ◽  
Gaseous Elemental Mercury

Abstract. One of the most important processes in the global mercury biogeochemical cycling is the deposition of atmospheric mercury, including gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM), and particulate-bound mercury (PBM), to terrestrial surfaces. In this paper, methods for the observation of wet, dry, litterfall, throughfall, and cloud/fog deposition and models for mercury dry deposition are reviewed. Surrogate surface methods with cation exchange membranes are widely used for GOM dry deposition measurements, while observation methods for GEM dry deposition are more diverse. The methodology for Hg wet deposition is more mature, but the influence of cloud/fog scavenging is easy to neglect. Dry deposition models for speciated mercury have high uncertainties owing to the presence of sensitive parameters related to GOM chemical forms. Observation networks for mercury wet deposition have been developed worldwide, with the Global Mercury Observation System (GMOS) covering the northern hemisphere, the tropics, and the southern hemisphere. Wet deposition implies the spatial distribution of atmospheric mercury pollution, while GOM dry deposition depends highly on the elevation. Litterfall Hg deposition is crucial to forests. Urban areas have high wet deposition and PBM dry deposition because of high reactive mercury levels. Grasslands and forests have significant GOM and GEM dry deposition, respectively. Evergreen broadleaf forests bear high litterfall Hg deposition. Future research needs have been proposed based on the current knowledge of global mercury deposition to terrestrial surfaces.

Modeling Atmospheric Mercury Deposition in the Vicinity of Power Plants

2006 ◽  
Vol 56 (6) ◽  
pp. 743-751 ◽  
Author(s):  
Christian Seigneur ◽  
Kristen Lohman ◽  
Krish Vijayaraghavan ◽  
John Jansen ◽  
Leonard Levin
Keyword(s):  
Power Plants ◽  
Atmospheric Mercury ◽  
Mercury Deposition

The Status of Livelihood Vulnerability and Its CopingCapacities of Urban Squatters in Kathmandu Metropolitan City, Nepal

Patan Pragya ◽  
2019 ◽  
Vol 5 (1) ◽  
pp. 19-32
Author(s):  
Chhabi Ram Baral
Keyword(s):  
Data Collection ◽  
Urban Area ◽  
Urban Areas ◽  
Quantitative Methods ◽  
Urban Poverty ◽  
Rural Poverty ◽  
Poor People ◽  
Qualitative And Quantitative ◽  
Qualitative And Quantitative Methods ◽  
The Status

Urban poverty is one of multidimensional issue in Nepal. Increasing immigration from the outer parts of Kathmandu due to rural poverty, unemployment and weak security of the lives and the properties are core causes pushing people into urban areas. In this context how squatter urban area people sustain their livelihoods is major concern. The objectives of the study are to find out livelihood assets and capacities squatters coping with their livelihood vulnerability in adverse situation. Both qualitative and quantitative methods are applied for data collection. It is found that squatters social security is weak, victimized by severe health problems earning is not regular with lack of physical facilities and overall livelihood is critical. This study helps to understand what the changes that have occurred in livelihood patterns and how poor people survive in urban area.

scholarly journals The Wood Quality of Small-Leaved Lime (Tilia cordata Mill.) Trees in an Urban Area: A Pilot Study

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 420
Author(s):  
Benas Šilinskas ◽  
Aistė Povilaitienė ◽  
Gintautas Urbaitis ◽  
Marius Aleinikovas ◽  
Iveta Varnagirytė-Kabašinskienė
Keyword(s):  
Urban Area ◽  
Urban Areas ◽  
Wood Quality ◽  
Wood Products ◽  
Urban Trees ◽  
Measuring System ◽  
Forest Site ◽  
Tilia Cordata ◽  
Mean Values ◽  
Wood Development

This study performed a pilot evaluation of the wood quality—defined by a single parameter: dynamic modulus of elasticity (MOEdyn, N mm−2)—of small-leaved lime (Tilia cordata Mill.) trees in urban areas. A search of the literature revealed few studies which examined the specifics of tree wood development in urban areas. Little is known about the potential of wood from urban trees wood of their suitability for the timber industry. In this study, an acoustic velocity measuring system was used for wood quality assessment of small-leaved lime trees. The MOEdyn parameter was evaluated for small-leaved lime trees growing in two urban locations (along the streets, and in an urban park), with an additional sample of forest sites taken as the control. MOEdyn was also assessed for small-leaved lime trees visually assigned to different health classes. The obtained mean values of MOEdyn of 90–120-year old small-leaved lime trees in urban areas ranged between 2492.2 and 2715.8 N mm−2. For younger trees, the values of MOEdyn were lower in the urban areas than in the forest site. Otherwise, the results of the study showed that the small-leaved lime wood samples were of relatively good quality, even if the tree was classified as moderately damaged (which could cause a potential risk to the community). Two alternatives for urban tree management can be envisaged: (1) old trees could be left to grow to maintain the sustainability of an urban area until their natural death, or (2) the wood from selected moderately damaged trees could be used to create wood products, ensuring long-term carbon retention.

scholarly journals Semantic segmentation of PolSAR image data using advanced deep learning model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rajat Garg ◽  
Anil Kumar ◽  
Nikunj Bansal ◽  
Manish Prateek ◽  
Shashi Kumar
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Deep Learning ◽  
Urban Area ◽  
Urban Areas ◽  
Learning Algorithms ◽  
Semantic Segmentation ◽  
Learning Model ◽  
Machine Learning Algorithms ◽  
Deep Learning Model

AbstractUrban area mapping is an important application of remote sensing which aims at both estimation and change in land cover under the urban area. A major challenge being faced while analyzing Synthetic Aperture Radar (SAR) based remote sensing data is that there is a lot of similarity between highly vegetated urban areas and oriented urban targets with that of actual vegetation. This similarity between some urban areas and vegetation leads to misclassification of the urban area into forest cover. The present work is a precursor study for the dual-frequency L and S-band NASA-ISRO Synthetic Aperture Radar (NISAR) mission and aims at minimizing the misclassification of such highly vegetated and oriented urban targets into vegetation class with the help of deep learning. In this study, three machine learning algorithms Random Forest (RF), K-Nearest Neighbour (KNN), and Support Vector Machine (SVM) have been implemented along with a deep learning model DeepLabv3+ for semantic segmentation of Polarimetric SAR (PolSAR) data. It is a general perception that a large dataset is required for the successful implementation of any deep learning model but in the field of SAR based remote sensing, a major issue is the unavailability of a large benchmark labeled dataset for the implementation of deep learning algorithms from scratch. In current work, it has been shown that a pre-trained deep learning model DeepLabv3+ outperforms the machine learning algorithms for land use and land cover (LULC) classification task even with a small dataset using transfer learning. The highest pixel accuracy of 87.78% and overall pixel accuracy of 85.65% have been achieved with DeepLabv3+ and Random Forest performs best among the machine learning algorithms with overall pixel accuracy of 77.91% while SVM and KNN trail with an overall accuracy of 77.01% and 76.47% respectively. The highest precision of 0.9228 is recorded for the urban class for semantic segmentation task with DeepLabv3+ while machine learning algorithms SVM and RF gave comparable results with a precision of 0.8977 and 0.8958 respectively.

scholarly journals Cost-efficient factors in local public spending: Detecting relationships between local environments, population size and urban area category

2021 ◽  
pp. 239980832110038
Author(s):  
Hiroki Baba ◽  
Yasushi Asami
Keyword(s):  
Population Size ◽  
Urban Area ◽  
Urban Areas ◽  
Local Governments ◽  
Statistical Significance ◽  
Population Decline ◽  
Public Spending ◽  
Local Environment ◽  
Environment Factors ◽  
Major Factors

This study examines regional differences in local environment factors to better understand the sustainability of local governments indexed by per capita public spending. Under the condition of heterogeneous population size, we examine how factor characteristics differ depending on the spatial context represented by the urban area category. By employing a Cobb–Douglas cost function with congestion effects on public service provision, the estimated factors enable us to articulate major factors and differences in cost-efficiency between urban area categories. We found that statistical significance and even the signatures of local environment factors differ depending on the urban employment area category. Regarding factors such as the ratios of employees in secondary and tertiary industries, these did not tend to be statistically significant in small-sized urban areas, while small-sized cities in large-sized urban areas were likely to gain confidence intervals. Moreover, we did not observe any statistical significance for the ratio of elderly people due to the balance of spending between national and local governments. These findings could contribute to sustainable management of cities in the advent of population decline.

scholarly journals Key Performance Indicators for an Energy Community Based on Sustainable Technologies

2021 ◽  
Vol 13 (16) ◽  
pp. 8789
Author(s):  
Giovanni Bianco ◽  
Barbara Bonvini ◽  
Stefano Bracco ◽  
Federico Delfino ◽  
Paola Laiolo ◽  
...  
Keyword(s):  
Performance Indicators ◽  
Urban Areas ◽  
High Performance ◽  
Power Plants ◽  
New Technologies ◽  
Storage Systems ◽  
Clean Energy ◽  
Key Performance Indicators ◽  
Energy Performance ◽  
Green Energy

As reported in the “Clean energy for all Europeans package” set by the EU, a sustainable transition from fossil fuels towards cleaner energy is necessary to improve the quality of life of citizens and the livability in cities. The exploitation of renewable sources, the improvement of energy performance in buildings and the need for cutting-edge national energy and climate plans represent important and urgent topics to be faced in order to implement the sustainability concept in urban areas. In addition, the spread of polygeneration microgrids and the recent development of energy communities enable a massive installation of renewable power plants, high-performance small-size cogeneration units, and electrical storage systems; moreover, properly designed local energy production systems make it possible to optimize the exploitation of green energy sources and reduce both energy supply costs and emissions. In the present paper, a set of key performance indicators is introduced in order to evaluate and compare different energy communities both from a technical and environmental point of view. The proposed methodology was used in order to assess and compare two sites characterized by the presence of sustainable energy infrastructures: the Savona Campus of the University of Genoa in Italy, where a polygeneration microgrid has been in operation since 2014 and new technologies will be installed in the near future, and the SPEED2030 District, an urban area near the Campus where renewable energy power plants (solar and wind), cogeneration units fed by hydrogen and storage systems are planned to be installed.

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