scholarly journals Quantitative Assessment of Relationship between Population Exposure to PM2.5 and Socio-Economic Factors at Multiple Spatial Scales over Mainland China

2018 ◽  
Vol 15 (9) ◽  
pp. 2058 ◽  
Author(s):  
Ling Yao ◽  
Changchun Huang ◽  
Wenlong Jing ◽  
Xiafang Yue ◽  
Yuyue Xu
Keyword(s):  
Spatial Scales ◽  
Fine Particulate Matter ◽  
Mainland China ◽  
Mean Value ◽  
Economic Effects ◽  
Population Exposure ◽  
Economic Factors ◽  
Quantile Regression Method ◽  
Grid Level ◽  
Socio Economic Factors

Analyzing the association between fine particulate matter (PM2.5) pollution and socio-economic factors has become a major concern in public health. Since traditional analysis methods (such as correlation analysis and geographically weighted regression) cannot provide a full assessment of this relationship, the quantile regression method was applied to overcome such a limitation at different spatial scales in this study. The results indicated that merely 3% of the population and 2% of the Gross Domestic Product (GDP) occurred under an annually mean value of 35 μg/m3 in mainland China, and the highest population exposure to PM2.5 was located in a lesser-known city named Dazhou in 2014. The analysis results at three spatial scales (grid-level, county-level, and city-level) demonstrated that the grid-level was the optimal spatial scale for analysis of socio-economic effects on exposure due to its tiny uncertainty, and the population exposure to PM2.5 was positively related to GDP. An apparent upward trend of population exposure to PM2.5 emerged at the 80th percentile GDP. For a 10 thousand yuan rise in GDP, population exposure to PM2.5 increases by 1.05 person/km2 at the 80th percentile, and 1.88 person/km2 at the 95th percentile, respectively.

scholarly journals The Socioeconomic Determinants of Crime in Pakistan

2019 ◽  
Vol 2 (3) ◽  
pp. 1-6
Author(s):  
Muhammad Umair
Keyword(s):  
Economic Growth ◽  
Regression Analysis ◽  
World Bank ◽  
Secondary Data ◽  
Economic Effects ◽  
Economic Factors ◽  
Negative Relation ◽  
Socioeconomic Determinants ◽  
Correlation And Regression Analysis ◽  
Socio Economic Factors

Crime is one of the major issues in Pakistan. It not only affects our society but also our economy. The main purpose of this study is showing the effects of socio-Economic factors such as Inflation, Population, income and economic growth to crimes. For this purpose we use secondary data and collected from Pakistan Bureau of Statistics and World Bank over 2006 to 2016. Correlation and regression analysis use to check the socio-economic effects on crimes. Results show negative relation of crime and economic growth. Government strives on economic growth, because it improves, crimes reduce gradually.

scholarly journals Analysis of lockdown perception in the United States during the COVID-19 pandemic

2021 ◽  
Author(s):  
Francesco Vincenzo Surano ◽  
Maurizio Porfiri ◽  
Alessandro Rizzo
Keyword(s):  
United States ◽  
Temporal Analysis ◽  
The United States ◽  
Economic Effects ◽  
Economic Factors ◽  
Political Orientations ◽  
Containment Measures ◽  
Spatio Temporal ◽  
Different Parts ◽  
Socio Economic Factors

AbstractContainment measures have been applied throughout the world to halt the COVID-19 pandemic. In the United States, several forms of lockdown have been adopted in different parts of the country, leading to heterogeneous epidemiological, social, and economic effects. Here, we present a spatio-temporal analysis of a Twitter dataset comprising 1.3 million geo-localized Tweets about lockdown, from January to May 2020. Through sentiment analysis, we classified Tweets as expressing positive or negative emotions about lockdown, demonstrating a change in perception during the course of the pandemic modulated by socio-economic factors. A transfer entropy analysis of the time series of Tweets unveiled that the emotions in different parts of the country did not evolve independently. Rather, they were mediated by spatial interactions, which were also related to socio-ecomomic factors and, arguably, to political orientations. This study constitutes a first, necessary step toward isolating the mechanisms underlying the acceptance of public health interventions from highly resolved online datasets.

scholarly journals SOCIO-ECONOMIC FACTORS AND HILL COUNTRY PRODUCTION AND DEVELOPMENT

1982 ◽  
pp. 241-244
Author(s):  
D.E. Walter
Keyword(s):  
New Zealand ◽  
Guinea Pigs ◽  
Economic Effects ◽  
Research Centre ◽  
Economic Factors ◽  
Hill Country ◽  
The Past ◽  
Association Meeting ◽  
Almost All ◽  
Socio Economic Factors

More than twenty papers have been delivered at this 1981 New Zealand Grassland Association meeting and almost all have dealt with two aspects of farming - how to grow more feed for livestock and how to convert this feed into production. All of the participants and speakers here must at some stage, whether in the research centre or in the field, have wondered how much of this information was going to hit where it counted. Would it end up being preached to the converted again, played with by the farmer 'guinea pigs', scoffed at by many as more impractical academic garbage? Just how much impact on farming production and development will your findings and recommendations have? Could it be, like a seagull on top of a lighthouse, your earnest calls will be largely drowned out by the forces of the elements? 'fhere is no shortage of cynics in our community, and plenty under the label of farmers:But the mere fact of having a discussion on socio-economic effects on hill country production and development confirms growing awareness over the past few years that other factors than farming technology may be inhibiting growth on these farms.

Vicious Cycle of Economic Growth, Pm2.5 and COVID-19 Case of G7 Countries

2020 ◽  
Author(s):  
Rıdvan Karacan
Keyword(s):  
Economic Growth ◽  
Air Pollution ◽  
Particulate Matter ◽  
Fossil Fuels ◽  
Fine Particulate Matter ◽  
Panel Cointegration ◽  
Air Pollutant ◽  
Population Exposure ◽  
Causality Analysis ◽  
G7 Countries

<p>Today, production is carried out depending on fossil fuels. Fossil fuels pollute the air as they contain high levels of carbon. Many studies have been carried out on the economic costs of air pollution. However, in the present study, unlike the former ones, economic growth's relationship with the COVID-19 virus in addition to air pollution was examined. The COVID-19 virus, which was initially reported in Wuhan, China in December 2019 and affected the whole world, has caused many cases and deaths. Researchers have been going on studying how the virus is transmitted. Some of these studies suggest that the number of virus-related cases increases in regions with a high level of air pollution. Based on this fact, it is thought that air pollution will increase the number of COVID-19 cases in G7 Countries where industrial production is widespread. Therefore, the negative aspects of economic growth, which currently depends on fossil fuels, is tried to be revealed. The research was carried out for the period between 2000-2019. Panel cointegration test and panel causality analysis were used for the empirical analysis. Particulate matter known as PM2.5[1] was used as an indicator of air pollution. Consequently, a positive long-term relationship has been identified between PM2.5 and economic growth. This relationship also affects the number of COVID-19 cases.</p><p><br></p><p><br></p><p>[1] "Fine particulate matter (PM2.5) is an air pollutant that poses the greatest risk to health globally, affecting more people than any other pollutant (WHO, 2018). Chronic exposure to PM2.5 considerably increases the risk of respiratory and cardiovascular diseases in particular (WHO, 2018). For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator" (OECD.Stat).</p>

DINAMIKA KELOMPOK TANI ANUGERAH MOLLO DI DESA NETPALA KECAMATAN MOLLO UTARA KABUPATEN TIMOR TENGAH SELATAN

2020 ◽  
Vol 21 (1) ◽  
pp. 71-80
Author(s):  
Tanggu Dedo Yeremias ◽  
Ernantje Hendrik ◽  
Ignatius Sinu
Keyword(s):  
Formal Education ◽  
Secondary Data ◽  
Nonparametric Test ◽  
Primary Data ◽  
Economic Factors ◽  
Dynamic Level ◽  
South Central ◽  
Group Members ◽  
Relationship Of ◽  
Socio Economic Factors

ABSTRACT This research has been carried out in the Anugerah Mollo Farmer Group, in Netpala Village, North Mollo District, South Central Timor Regency, starting in March - April 2019. This study aims to determine: (1) The dynamic level of the Anugerah Mollo Farmer Group in Netpala Village, North Mollo District, South Central Timor Regency, (2) Relationship between Socio-economic factors of farmer group members and the level of dynamics of the Anugerah Mollo Farmer Group in Netpala Village, North Mollo District, South Central Timor Regency. Determination of the location of the study carried out intentionally (purposive sampling) The type of data collected is primary data obtained from direct interviews with respondents guided by the questionnaire, while secondary data is obtained from the relevant agencies. To find out the first purpose of the data analyzed using a Likert scale, to find out the second purpose of the data analyzed using the Sperman Rank statistical Nonparametric test. The results of this study indicate that: (1) The level of dynamism of the Anugerah Mollo Farmer Group in Netpala Village, North Mollo District, South Central Timor Regency, is in the very dynamic category of 84%, (2) The relationship of socio-economic factors is only one of the five variables that are significantly related namely land area with a coefficient of rs 0.278 and t = 1.782 count greater than t table 1.699 (p> 0.05), while other social factors such as age, formal education, number of family dependents, and experience of farming show no significant relationship with the level of dynamism of Anugerah Mollo Farmers Group in Netpala Village.

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