scholarly journals The Driving Influence of Multi-Dimensional Urbanization on PM2.5 Concentrations in Africa: New Evidence from Multi-Source Remote Sensing Data, 2000–2018

2021 ◽  
Vol 18 (17) ◽  
pp. 9389 ◽  
Author(s):  
Guoen Wei ◽  
Pingjun Sun ◽  
Shengnan Jiang ◽  
Yang Shen ◽  
Binglin Liu ◽  
...  
Keyword(s):  
Spatial Dependence ◽  
Industrial Structure ◽  
Control Strategies ◽  
Spillover Effect ◽  
Remote Sensing Data ◽  
Mitigation Strategies ◽  
Joint Control ◽  
Enhancement Effect ◽  
Rapid Urbanization ◽  
Spatio Temporal

Africa’s PM2.5 pollution has become a security hazard, but the understanding of the varying effects of urbanization on driven mechanisms of PM2.5 concentrations under the rapid urbanization remains largely insufficient. Compared with the direct impact, the spillover effect of urbanization on PM2.5 concentrations in adjacent regions was underestimated. Urbanization is highly multi-dimensional phenomenon and previous studies have rarely distinguished the different driving influence and interactions of multi-dimensional urbanization on PM2.5 concentrations in Africa. This study combined grid and administrative units to explore the spatio-temporal change, spatial dependence patterns, and evolution trend of PM2.5 concentrations and multi-dimensional urbanization in Africa. The differential influence and interaction effects of multi-dimensional urbanization on PM2.5 concentrations under Africa’s rapid urbanization was further analyzed. The results show that the positive spatial dependence of PM2.5 concentrations gradually increased over the study period 2000–2018. The areas with PM2.5 concentrations exceeding 35 μg/m3 increased by 2.2%, and 36.78% of the African continent had an increasing trend in Theil–Sen index. Urbanization was found to be the main driving factor causing PM2.5 concentrations changes, and economic urbanization had a stronger influence on air quality than land urbanization or population urbanization. Compared with the direct effect, the spillover effect of urbanization on PM2.5 concentrations in two adjacent regions was stronger, particularly in terms of economic urbanization. The spatial distribution of PM2.5 concentrations resulted from the interaction of multi-dimensional urbanization. The interaction of urbanization of any two different dimensions exhibited a nonlinear enhancement effect on PM2.5 concentrations. Given the differential impact of multi-dimensional urbanization on PM2.5 concentrations inside and outside the region, this research provides support for the cross-regional joint control strategies of air pollution in Africa. The findings also indicate that PM2.5 pollution control should not only focus on urban economic development strategies but should be an optimized integration of multiple mitigation strategies, such as improving residents’ lifestyles, optimizing land spatial structure, and upgrading the industrial structure.

scholarly journals The Direct and Spillover Effect of Multi-Dimensional Urbanization on PM2.5 Concentrations: A Case Study from the Chengdu-Chongqing Urban Agglomeration in China

2021 ◽  
Vol 18 (20) ◽  
pp. 10609
Author(s):  
Sicheng Wang ◽  
Pingjun Sun ◽  
Feng Sun ◽  
Shengnan Jiang ◽  
Zhaomin Zhang ◽  
...  
Keyword(s):  
Spatial Dependence ◽  
Positive Impact ◽  
Control Strategies ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Urban Agglomeration ◽  
Joint Control ◽  
Economic Adjustment ◽  
Economic Construction ◽  
Economic Development Strategies

The Chengdu-Chongqing urban agglomeration (CUA) faces considerable air quality concerns, although the situation has improved in the past 15 years. The driving effects of population, land and economic urbanization on PM2.5 concentrations in the CUA have largely been overlooked in previous studies. The contributions of natural and socio-economic factors to PM2.5 concentrations have been ignored and the spillover effects of multi-dimensional urbanization on PM2.5 concentrations have been underestimated. This study explores the spatial dependence and trend evolution of PM2.5 concentrations in the CUA at the grid and county level, analyzing the direct and spillover effects of multi-dimensional urbanization on PM2.5 concentrations. The results show that the mean PM2.5 concentrations in CUA dropped to 48.05 μg/m3 at an average annual rate of 4.6% from 2000 to 2015; however, in 2015, there were still 91% of areas exposed to pollution risk (>35 μg/m3). The PM2.5 concentrations in 92.98% of the area have slowly decreased but are rising in some areas, such as Shimian County, Xuyong County and Gulin County. The PM2.5 concentrations in this region presented a spatial dependence pattern of “cold spots in the east and hot spots in the west”. Urbanization was not the only factor contributing to PM2.5 concentrations. Commercial trade, building development and atmospheric pressure were found to have significant contributions. The spillover effect of multi-dimensional urbanization was found to be generally stronger than the direct effects and the positive impact of land urbanization on PM2.5 concentrations was stronger than population and economic urbanization. The findings provide support for urban agglomerations such as CUA that are still being cultivated to carry out cross-city joint control strategies of PM2.5 concentrations, also proving that PM2.5 pollution control should not only focus on urban socio-economic development strategies but should be an integration of work optimization in various areas such as population agglomeration, land expansion, economic construction, natural adaptation and socio-economic adjustment.

The response of surface ozone to current mitigation strategies for reducing air pollution in Chinese megacity clusters

2021 ◽  
Author(s):  
Yijuan Zhang
Keyword(s):  
Air Pollution ◽  
Fine Particles ◽  
Control Strategies ◽  
Action Plan ◽  
Surface Ozone ◽  
River Delta ◽  
Mitigation Strategies ◽  
Chinese Government ◽  
Air Pollution Control ◽  
Rapid Urbanization

<p>China, with rapid urbanization and industrialization, has experienced severe air quality deterioration in recent decades. To release heavy air pollution in China, Chinese government implement the Clean Air Action Plan initiated in 2013. Fine particles (PM<sub>2.5</sub>) concentrations have shown significant declines over the nationwide, which attribute to mitigating anthropogenic emission of primary PM<sub>2.5</sub>, and precursor gases of nitrogen oxides (NOx), sulfur dioxide (SO<sub>2</sub>), and carbon monoxide (CO). However, surface ozone concentrations have unexpectedly increased during the implementation of 2013 to 2019. China has an average trend of 1.9 ppbv a<sup>-1 </sup>in same period, measured by ambient monitoring station of China’s Ministry of Environment and Ecology (China MEE). Notably, surface ozone has faster increased trend in megacity clusters, with 3.3 ppbv a<sup>-1 </sup>in<sup></sup>Beijing-Tianjin-Hebei, 1.6 ppbv a<sup>-1 </sup>in Yangtze River Delta, 1.1 ppbv a<sup>-1 </sup>in Pearl River Delta. At shorter temporal scale, the lockdown during outbreak of COVID-19, in which human activities dramatically decreased with reduction of industry and transport emission, witnessed exceeding 30% increase of maximum daily 8h average (MDA8) O<sub>3</sub>, in major cities (e.g., Shanghai, Hangzhou, Hefei etc.). The investigated results suggested simultaneous controlling concentration of PM2.5 and ozone should coordinate inner physical and chemical processes. In this study, the weather Research and Forecasting with Chemistry was applied to reproduce the following two pathways: (1) The response of surface ozone to modification of photolysis by changed radiation budgets induced by scattering and absorbing aerosols; (2) The further impacts of altered atmospheric oxidizing capacity on surface ozone and aerosols concentrations. This study can provide reasonable advice to air pollution control strategies in Chinese megacity clusters.</p>

Regional characteristics of the gender employment gap: A spatio-temporal approach

2021 ◽  
pp. 103530462110232
Author(s):  
Jorge Chica-Olmo ◽  
Marina Checa-Olivas ◽  
Fernando Lopez-Castellano
Keyword(s):  
Gender Gap ◽  
Spillover Effect ◽  
Jel Codes ◽  
Labour Relations ◽  
Socioeconomic Characteristics ◽  
Regional Characteristics ◽  
Spatial Approach ◽  
Employment Gap ◽  
Diffusion Mechanisms ◽  
Spatio Temporal

There is a substantial body of research that recognises the importance of analysing regional characteristics in employment and labour relations that occur in a given geographical context. However, this phenomenon has been scarcely studied from a spatial approach. This article uses a spatio-temporal panel data model to examine the spatial interactions between the gender employment gap and, some labour and socioeconomic characteristics of 727 municipalities of Andalusia, Spain, for the period 2012–2016. The results show that due to spatial diffusion mechanisms, a spatial spillover effect occurs in both the gender gap in employment and in some of the labour and socioeconomic characteristics considered. These findings may be extended to other geographic areas and can be of use for the implementation of regional policies aimed at narrowing the gender employment gap. JEL Codes: R10, J16, E24

scholarly journals A Spatio-Temporal Local Association Query Algorithm for Multi-Source Remote Sensing Big Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2333
Author(s):  
Lilu Zhu ◽  
Xiaolu Su ◽  
Yanfeng Hu ◽  
Xianqing Tai ◽  
Kun Fu
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Temporal Correlation ◽  
Local Association ◽  
Sensing Data ◽  
Multi Scale ◽  
Correlation Networks ◽  
Efficient Integration ◽  
Spatio Temporal ◽  
Query Algorithm

It is extremely important to extract valuable information and achieve efficient integration of remote sensing data. The multi-source and heterogeneous nature of remote sensing data leads to the increasing complexity of these relationships, and means that the processing mode based on data ontology cannot meet requirements any more. On the other hand, the multi-dimensional features of remote sensing data bring more difficulties in data query and analysis, especially for datasets with a lot of noise. Therefore, data quality has become the bottleneck of data value discovery, and a single batch query is not enough to support the optimal combination of global data resources. In this paper, we propose a spatio-temporal local association query algorithm for remote sensing data (STLAQ). Firstly, we design a spatio-temporal data model and a bottom-up spatio-temporal correlation network. Then, we use the method of partition-based clustering and the method of spectral clustering to measure the correlation between spatio-temporal correlation networks. Finally, we construct a spatio-temporal index to provide joint query capabilities. We carry out local association query efficiency experiments to verify the feasibility of STLAQ on multi-scale datasets. The results show that the STLAQ weakens the barriers between remote sensing data, and improves their application value effectively.

scholarly journals Comparison of spatio-temporal transmission characteristics of COVID-19 and its mitigation strategies in China and the US

2020 ◽  
Vol 30 (12) ◽  
pp. 1963-1984
Author(s):  
Zhiming Feng ◽  
Chiwei Xiao ◽  
Peng Li ◽  
Zhen You ◽  
Xu Yin ◽  
...  
Keyword(s):  
Mitigation Strategies ◽  
Transmission Characteristics ◽  
The Us ◽  
Spatio Temporal

Combining static and dynamic environmental factors at various scales to predict shallow landsliding in South Tyrol, Italy – The Proslide project

2021 ◽  
Author(s):  
Robin Kohrs ◽  
 Lotte de Vugt ◽  
Thomas Zieher ◽  
Alice Crespi ◽  
Mattia Rossi ◽  
...  
Keyword(s):  
Regional Scale ◽  
Remote Sensing Data ◽  
Predisposing Factors ◽  
Physical Models ◽  
Data Driven ◽  
Catchment Scale ◽  
Heterogeneous Model ◽  
South Tyrol ◽  
Daily Precipitation Data ◽  
Spatio Temporal

<p>Shallow landslides in alpine environments can constitute a serious threat to the exposed elements. The spatio-temporal occurrence of such slope movements is controlled by a combination of predisposing factors (e.g. topography), preparatory factors (e.g. wet periods, snow melting) and landslide triggers (e.g. heavy precipitation events).  </p><p>For large study areas, landslide assessments frequently focus either on the static predisposing factors to estimate landslide susceptibility using data-driven procedures, or exclusively on the triggering events to derive empirical rainfall thresholds. For smaller areas, dynamic physical models can reasonably be parameterized to simultaneously account for static and dynamic landslide controls.  </p><p>The recently accepted Proslide project aims to develop and test methods with the potential to improve the predictability of landslides for the Italian province of South Tyrol. It is envisaged to account for a variety of innovative input data at multiple spatio-temporal scales. In this context, we seek to exploit remote sensing data for the spatio-temporal description of landslide controlling factors (e.g. precipitation RADAR; satellite soil moisture) and to develop models that allow an integration of heterogeneous model inputs using both, data-driven approaches (regional scale) and physically-based models (catchment scale). This contribution presents the core ideas and methodical framework behind the Proslide project and its very first results (e.g. relationships between landslide observations and gridded daily precipitation data at regional scale). </p>

Application of GIS technology in public health: successes and challenges

Parasitology ◽  
2016 ◽  
Vol 143 (4) ◽  
pp. 401-415 ◽  
Author(s):  
STEPHANIE M. FLETCHER-LARTEY ◽  
GRAZIELLA CAPRARELLI
Keyword(s):  
Public Health ◽  
Control Strategies ◽  
Health Sector ◽  
Remote Sensing Data ◽  
Environmental Data ◽  
Data Availability ◽  
Parasitic Diseases ◽  
Gis Technology ◽  
The Public ◽  
Application Of Gis

SUMMARYThe uptake and acceptance of Geographic Information Systems (GIS) technology has increased since the early 1990s and public health applications are rapidly expanding. In this paper, we summarize the common uses of GIS technology in the public health sector, emphasizing applications related to mapping and understanding of parasitic diseases. We also present some of the success stories, and discuss the challenges that still prevent a full scope application of GIS technology in the public health context. Geographical analysis has allowed researchers to interlink health, population and environmental data, thus enabling them to evaluate and quantify relationships between health-related variables and environmental risk factors at different geographical scales. The ability to access, share and utilize satellite and remote-sensing data has made possible even wider understanding of disease processes and of their links to the environment, an important consideration in the study of parasitic diseases. For example, disease prevention and control strategies resulting from investigations conducted in a GIS environment have been applied in many areas, particularly in Africa. However, there remain several challenges to a more widespread use of GIS technology, such as: limited access to GIS infrastructure, inadequate technical and analytical skills, and uneven data availability. Opportunities exist for international collaboration to address these limitations through knowledge sharing and governance.

scholarly journals Control Strategies for the Transition From Multijoint to Single-Joint Arm Movements Studied Using a Simple Mechanical Constraint

2000 ◽  
Vol 83 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Robert A. Scheidt ◽  
W. Zev Rymer
Keyword(s):  
Control Strategies ◽  
Human Subjects ◽  
Dynamic Performance ◽  
Activity Patterns ◽  
Adaptive Controller ◽  
Emg Activity ◽  
Joint Control ◽  
Primary Role ◽  
Joint Task ◽  
Normal Human

Changes were studied in neuromotor control that were evoked by constraining the motion of the elbow joint during planar, supported movements of the dominant arm in eight normal human subjects. Electromyograph (EMG) recordings from shoulder and arm muscles were used to determine whether the normal multijoint muscle activity patterns associated with reaching to a visual target were modified when the movement was reduced to a single-joint task, by pinning the elbow to a particular location in the planar work space. Three blocks of 150 movements each were used in the experiments. Subjects were presented with the unconstrained task in the first and third blocks with an intervening block of constrained trials. Kinematic, dynamic, and EMG measures of performance were compared across blocks. The imposition of the pin constraint caused predictable changes in kinematic performance, in that near-linear motions of the hand became curved. This was followed by changes in limb dynamic performance at the elbow. However, changes in EMG activity at the shoulder lagged the kinematic changes substantially (by about 15 trials). The gradual character of the changes in EMG timing does not support a primary role for segmental reflex action in mediating the transition between multijoint and single-joint control strategies. Furthermore, the scope and magnitude of these changes argues against the notion that human motor performance is driven by the optimization of muscle- or joint-related criteria alone. The findings are best described as reflecting the actions of a feedforward adaptive controller that has properties that are modified progressively according to the environmental state.

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