scholarly journals Quantifying the impacts of socio-economic factors on air quality in Chinese cities from 2000 to 2009

2012 ◽  
Vol 167 ◽  
pp. 148-154 ◽  
Author(s):  
Juanjuan Zhao ◽  
Shengbin Chen ◽  
Hua Wang ◽  
Yin Ren ◽  
Ke Du ◽  
...  
Keyword(s):  
Air Quality ◽  
Economic Factors ◽  
Chinese Cities ◽  
Socio Economic Factors

scholarly journals Exploring the Spatial Variation Characteristics and Influencing Factors of PM2.5 Pollution in China: Evidence from 289 Chinese Cities

2019 ◽  
Vol 11 (17) ◽  
pp. 4751 ◽  
Author(s):  
Zhao ◽  
Xu
Keyword(s):  
Spatial Variation ◽  
Environmental Conditions ◽  
Regression Models ◽  
Economic Factors ◽  
Spatial Agglomeration ◽  
Chinese Cities ◽  
Explanatory Variables ◽  
Haze Pollution ◽  
Pm2.5 Concentration ◽  
Socio Economic Factors

Haze pollution has become an urgent environmental problem due to its impact on the environment as well as human health. PM2.5 is one of the core pollutants which cause haze pollution in China. Existing studies have rarely taken a comprehensive view of natural environmental conditions and socio-economic factors to figure out the cause and diffusion mechanism of PM2.5 pollution. This paper selected both natural environmental conditions (precipitation (PRE), wind speed (WIN), and terrain relief (TR)) and socio-economic factors (human activity intensity of land surface (HAILS), the secondary industry's proportion (SEC), and the total particulate matter emissions of motor vehicles (VE)) to analyze the effects on the spatial variation of PM2.5 concentrations. Based on the spatial panel data of 289 cities in China in 2015, we used spatial statistical methods to visually describe the spatial distribution characteristics of PM2.5 pollution; secondly, the spatial agglomeration state of PM2.5 pollution was characterized by Moran’s I; finally, several regression models were used to quantitatively analyze the correlation between PM2.5 pollution and the selected explanatory variables. Results from this paper confirm that in 2015, most cities in China suffered from severe PM2.5 pollution, and only 17.6% of the sample cities were up to standard. The spatial agglomeration characteristics of PM2.5 pollution in China were particularly significant in the Beijing–Tianjin–Hebei region. Results from the global regression models suggest that WIN exerts the most significant effects on decreasing PM2.5 concentration (p < 0.01), while VE is the most critical driver of increasing PM2.5 concentration (p < 0.01). Results from the local regression model show reliable evidence that the relation between PM2.5 concentrations and the explanatory variables varied differently over space. VE is the most critical factor that influences PM2.5 concentrations, which means controlling motor vehicle pollutant emissions is an effective measure to reduce PM2.5 pollution in Chinese cities.

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.

Implication of Socio-economic Factors on Land Use and Forest Cover Changes in and Around Magamba Nature Reserve in Tanzania

2019 ◽  
Vol 5 (1) ◽  
pp. 108-117
Author(s):  
Solomon Jeremiah Sembosi
Keyword(s):  
Land Use ◽  
Forest Cover ◽  
Nature Reserve ◽  
Agricultural Land ◽  
Population Pressure ◽  
Economic Factors ◽  
Rural Settlements ◽  
Mountainous Regions ◽  
Use Of Resources ◽  
Socio Economic Factors

Rural settlements in mountainous regions are a typical process that occurs in many places around the world and have a number of implications on the landscape. Among them is a threat it possesses to the conservation and management of Afromontane ecosystems. This study assessed the socio-economic factors that drive the changes in land use and forest cover and the extent of land use and vegetation cover in and around Magamba Nature Reserve. Focus group discussion, direct field observation and household survey were used to acquire socio-economic information that impacts land use and forest cover. Through the use of Remote Sensing and GIS methods Landsat satellite images of 1995, 2008 and 2015 were employed to identify the extent of the changes in land use and forest cover. The perceived factors for the changes include education level, unemployment, landless/limited, landholding, population pressure, expansion of built-up areas and agricultural land at the expense of other land covers. This study revealed the transformation of natural forest and associated vegetation from one form to another. There was a decrease in natural vegetation from 61.06% in 1995 to 26.02% in 2015 and increase in built-up areas by 6.69% and agricultural areas by 4.70%. This study recommends conservation monitoring and strong law enforcement relating to natural resources so as to promote sustainable use of resources to rescue the diminishing ecosystem services.

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