scholarly journals Fuel choices in urban Indian households

2007 ◽  
Vol 12 (6) ◽  
pp. 757-774 ◽  
Author(s):  
MEHDI FARSI ◽  
MASSIMO FILIPPINI ◽  
SHONALI PACHAURI

ABSTRACTThis paper applies an ordered discrete choice framework to model fuel choices and patterns of cooking fuel use in urban Indian households. The choices considered are for three main cooking fuels: firewood, kerosene, and LPG (liquid petroleum gas). The models, estimated using a large microeconomic dataset, show a reasonably good performance in the prediction of households’ primary and secondary fuel choices. This suggests that ordered models can be used to analyze multiple fuel use patterns in the Indian context. The results show that lack of sufficient income is one of the main factors that retard households from using cleaner fuels, which usually also require the purchase of relatively expensive equipments. The results also indicate that households are sensitive to LPG prices. In addition to income and price, several socio-demographic factors such as education and sex of the head of the household are also found to be important in determining household fuel choice.

2021 ◽  
pp. 101262
Author(s):  
Mriduchhanda Chattopadhyay ◽  
Toshi H. Arimura ◽  
Hajime Katayama ◽  
Mari Sakudo ◽  
Hide-Fumi Yokoo

Forests ◽  
2018 ◽  
Vol 9 (7) ◽  
pp. 429 ◽  
Author(s):  
Zar Win ◽  
Nobuya Mizoue ◽  
Tetsuji Ota ◽  
Tsuyoshi Kajisa ◽  
Shigejiro Yoshida

There is concern over the environmental impact of charcoal use for cooking in urban areas; however, studies have mainly been limited to Africa and South Asia. This investigation aimed to evaluate woodfuel consumption rates and patterns in an urban area in Yedashe Township, Myanmar and compared them with results from a rural area in the same township. From interviews with 66 urban households, it was evident that firewood and charcoal consumption rates in the urban area were about one-third and one-fourth, respectively, of those in the rural area. These low consumption rates were because of multiple-fuel use (mainly woodfuel and electricity) in the urban area in contrast to single-fuel use in the rural area. We estimated the forest area required to meet woodfuel demand of the whole township to be 3738 ha; that could decrease by almost 40% (1592 ha) if the single-fuel use in the rural area switched to the multiple-fuel methods used in the urban area. This study confirms that urbanization with an “energy stack” in multiple-fuel use, rather than an “energy ladder” from firewood to charcoal, could largely reduce the environmental impact on forests.


2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
M. Shupler ◽  
J. Mwitari ◽  
A. Gohole ◽  
R. Anderson de Cuevas ◽  
E. Puzzolo ◽  
...  

2018 ◽  
Author(s):  
Ping Yan ◽  
Hua Peng ◽  
Luobin Yan ◽  
Shaoyun Zhang ◽  
Aimin Chen

Soil pH is the main factor affecting soil nutrient availability and chemical substances in soil. It is of great significance to study the spatial variability of soil pH for soil nutrient management and soil pollution prediction. In order to explore the causes of spatial variability of soil pH in redbed areas, the Nanxiong Basin in south China was selected as an example, and soil pH was measured in the topsoil by nested sampling (0–20 cm depth). The spatial variability characteristics of the soil pH were analysed by geostatistics and classical statistical methods, and the main factors influencing the spatial variability of soil pH are discussed. The results showed that the coefficient of variation in the redbed areas of Nanxiong Basin was 17.18%, indicating moderate variability. The geostatistics analysis showed that the spherical model is the optimal theoretical model for explaining the soil pH’s variability, which is influenced by both structural and random factors. The spatial distribution and pattern analysis showed that soil pH content in the northeast and southwest is relatively high, and is lower in the northwest. These results indicate that topographic factors and land use patterns are the main factors.


2020 ◽  
Vol 48 ◽  
pp. 904-922
Author(s):  
Manaswinee Kar ◽  
Suprava Jena ◽  
Abhishek Chakraborty ◽  
Prasanta Kumar Bhuyan

Sign in / Sign up

Export Citation Format

Share Document