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 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 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.

scholarly journals MOVEIM v1.0: Development of a bottom-up motor vehicular emission inventories for the urban area of Manaus in central Amazon rainforest

2018 ◽  
Author(s):  
Paulo R. Teixeira ◽  
Saulo R. de Freitas ◽  
Francis W. Correia ◽  
Antonio O. Manzi
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Spatial Scales ◽  
Transport Sector ◽  
Emission Inventories ◽  
Monitoring Networks ◽  
Weather Modification ◽  
Vehicular Emission ◽  
Bottom Up ◽  
Quality Models

Abstract. Emissions of gases and particulates in urban areas are associated with a mixture of various sources, both natural and anthropogenic. Understanding and quantifying these emissions is necessary in studies of climate change, local air pollution issues and weather modification. Studies have highlighted that the transport sector is key to closing the world’s emissions gap. Vehicles contribute substantially with the emission of carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx), non-methane hydrocarbon (NMHC), particulate matter (PM), methane (CH4), hydrofluorocarbon (HFC) and nitrous oxide (N2O). Several studies show that vehicle emission inventories are an important approach to providing a baseline estimate of on-road emissions in several scales, mainly in urban areas. This approach is essential to areas with incomplete or non-existent monitoring networks as well as for air quality models. Conversely, the direct downscale of global emission inventories in chemical transport and air quality models may not be able to reproduce the observed evolution of atmospheric pollution processes at finer spatial scales. To address this caveat, we developed a bottom-up vehicular emission inventory along the 258 main traffic routes from Manaus, based on local vehicle fleet data and emission factors (EFs). The results show that the light vehicles are responsible for the largest fraction of the pollutants, contributing 2.6, 0.87, 0.32, 0.03, 456 and 0.8 ton/h of CO, NOx, CH4, PM, CO2 and NMHC, respectively. Including the emissions of motorcycles, buses and trucks, our total estimation of the emissions is 4.1, 1.0, 0.37, 0.07, 63.5 and 2.56 ton/h, respectively. We also noted that light vehicles accounted for about 62.8 %, 84.7 %, 87.9 %, 45.1 %, 71.8 %, and 33.9 % and motorcycles in the order of 32.3 %, 6.5 %, 12.1 %, 6.2 %, 14.8 %, 8.7 %, respectively. Nevertheless, we can highlight the bus emissions which are around 35.7 % and 45.3 % for NMHC and PM. Our results indicate a better distribution over the domain reflecting the influences of standard behavior of traffic distribution per vehicle category. Finally, this inventory provides more detailed information to improving the current understanding of how vehicle emissions contribute to the ambient pollutant concentrations in Manaus and their impacts on regional climate changes. This work will also contribute to improved air quality numerical simulations, provide more accurate scenarios for policymakers and regulatory agencies to develop strategies for controlling the vehicular emissions, and, consequently, mitigate associated impacts on local and regional scales of the Amazon ecosystems.

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 The Impact of Financial and Non-Financial Work Incentives on the Safety Behavior of Heavy Truck Drivers

2021 ◽  
Vol 18 (5) ◽  
pp. 2759
Author(s):  
Sebastjan Škerlič ◽  
Vanja Erčulj
Keyword(s):  
Financial Incentives ◽  
Structural Equation ◽  
Traffic Accidents ◽  
Positive Impact ◽  
Road Transport ◽  
Truck Drivers ◽  
Driving Ability ◽  
Transport Sector ◽  
Safety Behavior ◽  
The Impact

The goal of the research is to determine how compensation affects the safety behavior of truck drivers and consequently the frequency of traffic accidents. For this purpose, a survey was conducted on a sample of 220 truck drivers in international road transport in the EU, where the results of the Structural Equation Model (SEM) show that in the current state of the transport sector, financial and non-financial incentives have a positive impact on the work and safety behavior of drivers. Financial incentives also have an impact on drivers’ increased perception of their driving ability, while moving violations continue to have a major impact on the number of accidents. The proposed improvements enable decision-makers at the highest level to adopt legal solutions to help manage the issues that have been affecting the industry from a work, social and safety point of view for the past several years. The results of the research therefore represent an important guideline for improvements to the legislature as well as in the systematization of truck driver compensation within companies.

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.

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