scholarly journals Impact of spatial proxies on the representation of bottom-up emission inventories: A satellite-based analysis

2016 ◽  
Author(s):  
Guannan Geng ◽  
Qiang Zhang ◽  
Randall Martin ◽  
Jintai Lin ◽  
Hong Huo ◽  
...  
Keyword(s):  
Population Density ◽  
Rural Areas ◽  
Urban Areas ◽  
Road Transport ◽  
Emission Inventories ◽  
Bottom Up ◽  
Nighttime Light Data ◽  
Nighttime Light ◽  
Current Emission ◽  
The Impact

Abstract. Spatial proxies used in bottom-up emission inventories to derive the spatial distributions of emissions are usually empirical and involve additional levels of uncertainty. Although uncertainties in current emission inventories have been discussed extensively, uncertainties resulting from improper spatial proxies have rarely been evaluated. In this work, we investigate the impact of spatial proxies on the representation of gridded emissions by comparing five gridded NOx emission datasets over China developed from the same magnitude of emissions and different spatial proxies. GEOS-Chem modeled tropospheric NO2 columns simulated from different gridded emission inventories are compared with satellite-based columns. The results show that differences between modeled and satellite-based NO2 columns are sensitive to the spatial proxies used in the gridded emission inventories. The total population density is less suitable for allocating NOx emissions than nighttime light data because population density tends to allocate more emissions to rural areas. Determining the exact locations of large emission sources could significantly strengthen the correlation between modeled and observed NO2 columns. When applying industrial gross domestic product (GDP) values and an updated road network map as proxies for the industrial and on-road transport sectors respectively, modeled NO2 columns could better capture pollution hotspots in urban areas and exhibit best performance of the five cases comparing to satellite-based NO2 columns (slope = 1.01 and R2 = 0.85). This analysis provides a framework for information from satellite observations to inform bottom-up inventory development. In the future, more effort should be devoted to the representation of spatial proxies to improve spatial patterns in bottom-up emission inventories.

scholarly journals Impact of spatial proxies on the representation of bottom-up emission inventories: A satellite-based analysis

2017 ◽  
Vol 17 (6) ◽  
pp. 4131-4145 ◽  
Author(s):  
Guannan Geng ◽  
Qiang Zhang ◽  
Randall V. Martin ◽  
Jintai Lin ◽  
Hong Huo ◽  
...  
Keyword(s):  
Population Density ◽  
Rural Areas ◽  
Urban Areas ◽  
Model Performance ◽  
Road Transport ◽  
Industrial Sector ◽  
Transport Sector ◽  
Emission Inventories ◽  
Bottom Up ◽  
The Impact

Abstract. Spatial proxies used in bottom-up emission inventories to derive the spatial distributions of emissions are usually empirical and involve additional levels of uncertainty. Although uncertainties in current emission inventories have been discussed extensively, uncertainties resulting from improper spatial proxies have rarely been evaluated. In this work, we investigate the impact of spatial proxies on the representation of gridded emissions by comparing six gridded NOx emission datasets over China developed from the same magnitude of emissions and different spatial proxies. GEOS-Chem-modeled tropospheric NO2 vertical columns simulated from different gridded emission inventories are compared with satellite-based columns. The results show that differences between modeled and satellite-based NO2 vertical columns are sensitive to the spatial proxies used in the gridded emission inventories. The total population density is less suitable for allocating NOx emissions than nighttime light data because population density tends to allocate more emissions to rural areas. Determining the exact locations of large emission sources could significantly strengthen the correlation between modeled and observed NO2 vertical columns. Using vehicle population and an updated road network for the on-road transport sector could substantially enhance urban emissions and improve the model performance. When further applying industrial gross domestic product (IGDP) values for the industrial sector, modeled NO2 vertical columns could better capture pollution hotspots in urban areas and exhibit the best performance of the six cases compared to satellite-based NO2 vertical columns (slope  =  1.01 and R2 = 0. 85). This analysis provides a framework for information from satellite observations to inform bottom-up inventory development. In the future, more effort should be devoted to the representation of spatial proxies to improve spatial patterns in bottom-up emission inventories.

scholarly journals Evaluation of modeling NO<sub>2</sub> concentrations driven by satellite-derived and bottom-up emission inventories using in situ measurements over China

2018 ◽  
Vol 18 (6) ◽  
pp. 4171-4186 ◽  
Author(s):  
Fei Liu ◽  
Ronald J. van der A ◽  
Henk Eskes ◽  
Jieying Ding ◽  
Bas Mijling
Keyword(s):  
Spatial Correlation ◽  
Rural Areas ◽  
Urban Areas ◽  
Transport Model ◽  
Chemical Transport ◽  
In Situ Measurements ◽  
Nox Emissions ◽  
Emission Inventories ◽  
Bottom Up

Abstract. Chemical transport models together with emission inventories are widely used to simulate NO2 concentrations over China, but validation of the simulations with in situ measurements has been extremely limited. Here we use ground measurements obtained from the air quality monitoring network recently developed by the Ministry of Environmental Protection of China to validate modeling surface NO2 concentrations from the CHIMERE regional chemical transport model driven by the satellite-derived DECSO and the bottom-up MIX emission inventories. We applied a correction factor to the observations to account for the interferences of other oxidized nitrogen compounds (NOz), based on the modeled ratio of NO2 to NOz. The model accurately reproduces the spatial variability in NO2 from in situ measurements, with a spatial correlation coefficient of over 0.7 for simulations based on both inventories. A negative and positive bias is found for the simulation with the DECSO (slope  =  0.74 and 0.64 for the daily mean and daytime only) and the MIX (slope  =  1.3 and 1.1) inventories, respectively, suggesting an underestimation and overestimation of NOx emissions from corresponding inventories. The bias between observed and modeled concentrations is reduced, with the slope dropping from 1.3 to 1.0 when the spatial distribution of NOx emissions in the DECSO inventory is applied as the spatial proxy for the MIX inventory, which suggests an improvement of the distribution of emissions between urban and suburban or rural areas in the DECSO inventory compared to that used in the bottom-up inventory. A rough estimate indicates that the observed concentrations, from sites predominantly placed in the populated urban areas, may be 10–40 % higher than the corresponding model grid cell mean. This reduces the estimate of the negative bias of the DECSO-based simulation to the range of −30 to 0 % on average and more firmly establishes that the MIX inventory is biased high over major cities. The performance of the model is comparable over seasons, with a slightly worse spatial correlation in summer due to the difficulties in resolving the more active NOx photochemistry and larger concentration gradients in summer by the model. In addition, the model well captures the daytime diurnal cycle but shows more significant disagreement between simulations and measurements during nighttime, which likely produces a positive model bias of about 15 % in the daily mean concentrations. This is most likely related to the uncertainty in vertical mixing in the model at night.

scholarly journals Evaluation of modelling NO<sub>2</sub> concentrations driven by satellite-derived and bottom-up emission inventories using in-situ measurements over China

2017 ◽  
Author(s):  
Fei Liu ◽  
Ronald J. van der A ◽  
Henk Eskes ◽  
Jieying Ding ◽  
Bas Mijling
Keyword(s):  
Spatial Correlation ◽  
Rural Areas ◽  
Urban Areas ◽  
Transport Model ◽  
Chemical Transport ◽  
In Situ Measurements ◽  
Nox Emissions ◽  
Emission Inventories ◽  
Bottom Up

Abstract. Chemical transport models together with emission inventories are widely used to simulate NO2 concentrations over China, but validation of the simulations with in situ measurements has been extremely limited. Here we use ground measurements obtained from the air quality monitoring network recently developed by the Ministry of Environmental Protection of China to validate modelling surface NO2 concentrations from the CHIMERE regional chemical-transport model driven by the satellite-derived DECSO and the bottom-up MIX emission inventories. We applied a correction factor to the observations to account for the interferences of other oxidized nitrogen compounds (NOz), based on the modelled ratio of NO2 to NOz. The model accurately reproduces the spatial variability of NO2 from in-situ measurements, with a spatial correlation coefficient of over 0.7 for simulations based on both inventories. A negative and positive bias is found for the simulation with the DECSO (slope = 0.74/0.64 for the daily-mean/daytime only) and the MIX (slope = 1.3/1.1) inventory respectively, suggesting an underestimation and overestimation of NOx emissions from corresponding inventories. The bias between observed and modelled concentrations is reduced with the slope dropping from 1.3 to 1.0 when the spatial distribution of NOx emissions in the DECSO inventory is applied as the spatial proxy for the MIX inventory, which suggests an improvement of the distribution of emissions between urban and suburban/rural areas in the DECSO inventory compared to that used in the bottom-up inventory. A rough estimate indicates that the observed concentrations, from sites predominantly placed in the populated urban areas, may be 10–40 % higher than the corresponding model grid-cell mean. This reduces the estimate of the negative bias of the DECSO based simulation to the range of −30 % to 0 % on average, and establishes more firmly that the MIX inventory is biased high over major cities. The performance of the model is comparable over seasons, with a slightly worse spatial correlation in summer, due to the difficulties in resolving the more active NOx photochemistry and larger concentration gradients in summer by the model. In addition, the model well captures the daytime diurnal cycle, but shows more significant disagreement between simulations and measurements during night time, which likely produces a positive model bias of about 15 % in the daily mean concentrations. This is most likely related to the uncertainty in vertical mixing in the model at night.

Impact of Elected Women Representatives of Panchayati Raj in Physical and Financial and Business Assets Development of Rural Women: A Study among the Rural Women’s of Tiruvannamalai District, Tamil Nadu[1]

2017 ◽  
Vol 4 (24) ◽  
Author(s):  
Kalaichelvi Sivaraman ◽  
Rengasamy Stalin
Keyword(s):  
Rural Women ◽  
Rural Areas ◽  
Urban Areas ◽  
Direct Democracy ◽  
Tamil Nadu ◽  
Local Level ◽  
Rural And Urban Areas ◽  
The Government ◽  
The Impact ◽  
Panchayati Raj

This research paper is the part of Research Project entitled “Impact of Elected Women Representatives in the Life and Livelihood of the Women in Rural Areas: With Special Reference to Tiruvannamalai District, Tamil Nadu” funded by University of Madras under UGC-UPE Scheme.The 73rd and 74th amendments of the Constitution of India were made by the government to strengthen the position of women and to create a local-level legal foundation for direct democracy for women in both rural and urban areas. The representation for women in local bodies through reservation policies amendment in Constitution of India has stimulated the political participation of women in rural areas. However, when it’s comes to the argument of whether the women reservation in Panchayati Raj helps or benefits to the life and livelihood development of women as a group? The answer is hypothetical because the studies related to the impact of women representatives of Panchayati Raj in the life and livelihood development of women was very less. Therefore, to fill the gap in existing literature, the present study was conducted among the rural women of Tiruvannamalai district to assess the impact of elected women representatives in the physical and financial and business development of the women in rural areas. The findings revealed that during the last five years because of the women representation in their village Panjayati Raj, the Physical Asset of the rural women were increased or developed moderately (55.8%) and Highly (23.4%) and the Financial and Business Asset of the rural women were increased or developed moderately (60.4%) and Highly (18.7%).

scholarly journals Effectiveness of Government Policies in Controlling COVID-19 in India

2020 ◽  
pp. 002073142098374
Author(s):  
Ashutosh Pandey ◽  
Nitin Kishore Saxena
Keyword(s):  
Population Density ◽  
Rural Areas ◽  
Rural Population ◽  
Urban Areas ◽  
Urban Population ◽  
Demographic Factors ◽  
Poverty Rate ◽  
Government Policies ◽  
Cumulative Number ◽  
Population Number

The purpose of this study is to find the demographic factors associated with the spread of COVID-19 and to suggest a measure for identifying the effectiveness of government policies in controlling COVID-19. The study hypothesizes that the cumulative number of confirmed COVID-19 patients depends on the urban population, rural population, number of persons older than 50, population density, and poverty rate. A log-linear model is used to test the stated hypothesis, with the cumulative number of confirmed COVID-19 patients up to period [Formula: see text] as a dependent variable and demographic factors as an independent variable. The policy effectiveness indicator is calculated by taking the difference of the COVID rank of the [Formula: see text]th state based on the predicted model and the actual COVID rank of the [Formula: see text]th state[Formula: see text]Our study finds that the urban population significantly impacts the spread of COVID-19. On the other hand, demographic factors such as rural population, density, and age structure do not impact the spread of COVID-19 significantly. Thus, people residing in urban areas face a significant threat of COVID-19 as compared to people in rural areas.

scholarly journals A Comparative Analysis of the Government and NGOs in Delivering Quality Services for the Rural People of Pakistan: Community Perspectives

2020 ◽  
Vol 30 (1-2) ◽  
pp. 203-225
Author(s):  
Mohsin Khan ◽  
Jetnor Kasmi ◽  
Abdul Saboor ◽  
Iftikhar Ali
Keyword(s):  
Drinking Water ◽  
Service Delivery ◽  
Rural Areas ◽  
Public Health Education ◽  
Road Transport ◽  
Extension Services ◽  
Rural People ◽  
Basic Services ◽  
The Government ◽  
The Impact

Often the government and the non-governmental organisations (NGOs) are criticised for their poor performances in delivering services particularly in rural areas. However, there has been limited research on the assessment of their relative performances in service delivery as well as on the perceptions of people on the quality of such service delivery. This study examines the relative performances of NGOs and the governmental development interventions that provide basic services including public health, education, drinking water and sanitation. The study explains the impact of agricultural extension services and infrastructure such as access to roads and markets on the rural people and measures the satisfaction level of the rural community. For this purpose, 225 households (HHs) in 8 villages of Phalia Tehsil, district Mandi Bahauddin, Punjab, Pakistan were first surveyed in 2010 and then in 2014 using a structured questionnaire. The findings reveal different satisfaction levels of HHs, with most of them expressing less satisfaction on government service delivery compared with NGOs. They reveal satisfaction over the performance of NGOs in health, drinking water supplies and agriculture extension services. Further, the study shows an increasing satisfaction of people on access to road, transport, agri-market and price of agri-commodities by the government.

scholarly journals Delineating the Urban Areas of a Cross-Boundary City with Open-Access Data: Guangzhou–Foshan, South China

2021 ◽  
Vol 13 (5) ◽  
pp. 2930
Author(s):  
Pengfei Ban ◽  
Wei Zhan ◽  
Qifeng Yuan ◽  
Xiaojian Li
Keyword(s):  
Urban Area ◽  
Urban Areas ◽  
City Size ◽  
Border City ◽  
Point Of Interest ◽  
Nighttime Light Data ◽  
Profile Line ◽  
Point Analysis ◽  
Nighttime Light ◽  
Single Data

Cities defined mainly from the administrative aspect can create impact and problems especially in the case of China. However, only a few researchers from China have attempted to identify urban areas from the morphology dimension. In addition, previous studies have been mostly based on the national and regional scales or a single prefecture city and have completely ignored cross-boundary cities. Defining urban areas on the basis of a single data type also has limitations. To address these problems, this study integrates point of interest and nighttime light data, applies the breaking point analysis method to determine the physical geographic scope of the Guangzhou–Foshan cross-border city, and then compares this city with Beijing and Shanghai. Results show that Guangzhou–Foshan comprises one core urban area and six suburban counties, among which the core urban area extends across the administrative boundaries of Guangzhou and Foshan. The urban area and average urban radius of Guangzhou–Foshan are larger than those of Beijing and Shanghai, and this finding contradicts the city size measurements based on the administrative division system of China and those published on traditional official statistical yearbooks. In terms of urban density value, Shanghai has the steepest profile followed by Guangzhou–Foshan and Beijing, and the profile line of Guangzhou–Foshan has a bimodal shape.

IMPACT OF DIGITAL MARKETING: THE PRESENT SCENARIO IN TELANGANA STATE – AN EMPERICAL STUDY

2021 ◽  
Vol 8 (65) ◽  
pp. 15164-15172
Author(s):  
S. Pratap ◽  
Aziz Fatima
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Digital Marketing ◽  
Rural And Remote ◽  
Remote Areas ◽  
Wide Range ◽  
Rural And Remote Areas ◽  
Telangana State ◽  
The Impact ◽  
Made In

In present scenario of COVID-19, the effect of pandemic on Digital Marketing is visible not only in urban areas but also in rural areas. Customers are searching for various products and services through Google by which they can purchase wide range of products and services to fill their needs and desires at relatively low price. The freedom to select numerous products is available by browsing various websites. Hence this study focuses on Impact of digital marketing particularly in the selected rural areas of Telangana state. This state been formed recently but in the IT sector it is receiving much attention throughout the globe, as many MNC’s are establishing their operations in this state. Therefore, an attempt has been made in this study to find out how the Impact of digital marketing is trickling down in the rural and remote areas of newly formed Telangana state. Hence this study focuses the impact of digital marketing in the selected areas of Telangana state.

Impact of adenotonsillectomy on the quality of life of patients operated on at the Hospital de Clínicas, Paraguay

2021 ◽  
pp. 1-7
Author(s):  
Carlos Mena Canata ◽  
Rebeca Noemí Ruiz Vallejos
Keyword(s):  
Quality Of Life ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Rural Areas ◽  
Urban Areas ◽  
Obstructive Sleep ◽  
Significant Difference ◽  
Before And After ◽  
The Impact

The objective of this study is to determine the impact of adenotonsillectomy on the quality of life of postoperative patients.The study is observational, cross-sectional, and retrospective. The files of all postoperative adenotonsillectomy patients in Otorhinolaryngology Service, Hospital de Clínicas, San Lorenzo Paraguay. The Obstructive sleep apnea – 18 questionnaire (OSA 18) was applied, asking patients about symptoms before and after surgery. An effective sample of 143 postoperative patients was obtained. The average age was 6.05 ± 2.08 years, 55.10% (81) were male and 44.89% (66) were female, 65.30% (96) were from urban areas and 34.69% (51) from the rural areas. The t test was performed for means of two paired samples, comparing the results of the Obstructive sleep apnea – 18 questionnaire surveys before and after surgery which presented a significant difference (p <0.05) with a tendency to improve the quality of life after surgery. It has been shown that there is a significant difference, a considerable improvement in the quality of life of patients after adenotonsillectomy.

scholarly journals Modeling Charging Infrastructure Requirements to Achieve a Holistic E-Mobility Integration in Regional Energy Systems

2021 ◽  
Author(s):  
Dominik Husarek ◽  
Simon Paulus ◽  
Michael Metzger ◽  
Vjekoslav Salapic ◽  
Stefan Niessen
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Mobility Model ◽  
Residential Areas ◽  
Charging Infrastructure ◽  
Charging System ◽  
Charging Station ◽  
Grid Operators ◽  
Regional Energy Systems ◽  
The Impact

Since E-Mobility is on the rise worldwide, large Charging Infrastructure (CI) networks are required to satisfy the upcoming Charging Demand (CD). Understanding this CD with its spatial and temporal uncertainties is important for grid operators to quantify the grid impact of Electric Vehicle integration and for Charging Station (CS) operators to assess long-term CI investments. Hence, we introduce an Agent-based E-Mobility Model assessing regional CI systems with their multi-directional interactions between CSs and vehicles. A Global Sensitivity Analysis (GSA) is applied to quantify the impact of 11 technical levers on 17 relevant charging system outputs. The GSA evaluates the E-Mobility integration in terms of grid impact, economic viability of CSs and Service Quality of the deployed Charging Infrastructure (SQCI). Based on this impact assessment we derive general guidelines for E-Mobility integration into regional systems. We found, inter alia, that CI policies should aim at allocating CSs across different types of locations to utilize cross-locational effects such as CSs at public locations affecting the charging peak in residential areas by up to 18%. Additionally, while improving the highway charging network is an effective lever to increase the SQCI in urban areas, public charging is an even stronger lever in rural areas.

Sign in / Sign up

Export Citation Format

Share Document