Pursuant to the Paris Agreement,China committed itself to peak its carbon emissions by around 2030 and to increase the non-fossil share ofprimary energy to 20%at the same time.The government has supported the internat...Pursuant to the Paris Agreement,China committed itself to peak its carbon emissions by around 2030 and to increase the non-fossil share ofprimary energy to 20%at the same time.The government has supported the international agreement by setting and strengthening the domesticpolicy targets for an earlier peak and faster reduction,aiming to contain the average global temperature increase to well below 2℃.We developa Kaya Inequality method to assess the time of peak and pace of reduction of China's energy-related CO2emissions based on the national energypolicy targets for 2030.We find that,despite the minor fluctuations,the current plateau essentially represents the peak emissions and should entera phase of steady decline by around 2025,given current trends in energy consumption and decarbonization.Such developments would beconsistent with the strengthened national policy target to achieve 50%of renewable power generation by 2030.However,the basic policy targetsea 20%share of non-fossil energy and 6 Gtce in total energy consumption by 2030ewould be insufficient to peak carbon emissions by around 2030.The synergy and interplay between domestic policy target setting and international climate commitments shed light on the need to elevatenational climate ambitions under the Paris Agreement and beyond.展开更多
In order to quantify the contribution of the mitigation strategies,an extended Kaya identity has been proposed in this paper for decomposing the various factors that influence the CO2 emission.To this end,we provided ...In order to quantify the contribution of the mitigation strategies,an extended Kaya identity has been proposed in this paper for decomposing the various factors that influence the CO2 emission.To this end,we provided a detailed decomposition of the carbon intensity and energy intensity,which enables the quantification of clean energy development and electrification.The logarithmic mean divisia index(LMDI)has been applied to the historical data to quantify the contributions of the various factors affecting the CO2 emissions.Further,the global energy interconnection(GEI)scenario has been introduced for providing a systematic solution to meet the 2℃goal of the Paris Agreement.By combining LMDI with the scenario analysis,the mitigation potential of the various factors for CO2 emission has been analyzed.Results from the historical data indicate that economic development and population growth contribute the most to the increase in CO2 emissions,whereas improvement in the power generation efficiency predominantly helps in emission reduction.A numerical analysis,performed for obtaining the projected future carbon emissions,suggests that clean energy development and electrification are the top two factors that can decrease CO2 emissions,thus showing their great potential for mitigation in the future.Moreover,the carbon capture and storage technology serves as an important supplementary mitigation method.展开更多
In the context of ＂two-wheel drive＂ development mode, China＇s construction land shows significant expansion characteristics. The carbon emission effect of construction land changes is an important factor for the in...In the context of ＂two-wheel drive＂ development mode, China＇s construction land shows significant expansion characteristics. The carbon emission effect of construction land changes is an important factor for the increase of carbon emissions in the atmosphere. In this study, the drivers of carbon emissions in Anhui Province from 1997 to 2011 were quantitatively measured using the improved Kaya identity and Logarithmic Mean Divisia Index. The results show that： economic growth, expansion of construction land and changes in population density have incremental effects on carbon emissions. The average contribution rate of economic growth as the first driver is 266.32 percent. The construction land expansion is an important driving factor with annual mean carbon effect of 6.4057 million tons and annual mean contribution rate of 187.30 percent. But the change in population density has little impact on carbon emission driving. Energy structure changes and energy intensity reduction have inhibitory effects on carbon emissions, of which the annual mean contribution rate is -212.06 percent and -158.115 percent respectively. The targeted policy approaches of carbon emission reduction were put forward based on the decomposition of carbon emission factors, laying a scientific basis to rationally use the land for the Government, which is conducive to build an ecological province for Anhui and achieve the purpose of emission reduction, providing a reference for the research on carbon emission effect of changes in provincial-scale construction land.展开更多
In this study, a stratified survey sampling was used in order to broaden our knowledge on the management systems of household waste in the town of Kaya/Burkina Faso. Population study consists of households of the town...In this study, a stratified survey sampling was used in order to broaden our knowledge on the management systems of household waste in the town of Kaya/Burkina Faso. Population study consists of households of the town of Kaya. The sample size was fist determined using the sample size calculation formula. Then four (04) strata comprising the town of Kaya sectors that have a Health and Social Promotion Center (HSPC) have been considered. A random household selection method, used inside each stratum and a number of 468 households representative of the town’s population, was surveyed. We have addressed all solid and liquid waste management strategies in those four strata. For each stratum, waste disposal infrastructure, its management in the households and its impacts on the town’s environment and populations’ health were screened. Data collected are presented through descriptive statistics in mean of tables and graphs. Frequently reported diseases in the four HSPCs have been correlated with waste management and disposal methods in the town. Poor handling, evacuation and disposal of waste have numerous negatives impacts on the city’s environment such as proliferation of mosquitoes and flies, bad odors, visual pollution. These negatives impacts on the environment in turn have negatives impacts on the health of the city residents. Malaria appears the most encountered disease followed by Acute Respiratory Infection and Diarrhea. Suggestions aimed at improving waste management and the reduction of its deficiencies impacts on the health of the population has been made.展开更多
An ethnobotanical study was carried out in the sacred forests of Kaya Kauma in Kilifi county and Kaya Tsolokero in Junju location in Kenya between 21st January 2015 to 22nd February 2016. Ethnobotanical data on the kn...An ethnobotanical study was carried out in the sacred forests of Kaya Kauma in Kilifi county and Kaya Tsolokero in Junju location in Kenya between 21st January 2015 to 22nd February 2016. Ethnobotanical data on the knowledge of useful Indigenous Food Plants among the dwelling population in the villages around Kaya Kauma and Kaya Tsolokero were obtained from the using semi-structured questionnaire and interviews of the population in the homesteads around both the forests. The Food Plants included vegetables, fruit or any sort of food if they yield to the society. Results based on a questionnaire survey in 18 villages around Kaya Kauma and 9 villages around Kaya Tsolokero are presented by different stratum of Gender, Age, Tribes, Education level, Relationship to the village, Marital status. Usage of plant as food out of the population interviewed around Kaya Kauma and the total fruit plants mentioned by the villagers dwelling around the forest was 18 belonging to 9 different families. The total vegetable plants which were mentioned by the population around Kaya Kauma were 23 belonging to 12 different families. Other Food Plants mentioned by the community was 36. Out of the population interviewed around Kaya Tsolokero out of the Food Plants mentioned by the community, total fruit plants mentioned by the community was 46 belonging to 19 different families, total vegetable plants mentioned was 20 which belonged to 13 different families and other Food Plants mentioned by the community was 23. Out of the dwelling tribes around Kaya Kanma, Mkauma emerged as the most popular tribe and Mjibana as the most popular tribe around Kaya Tsolokero. The 18 adjoining villages to Kaya Kauma were interviewed for the survey and 9 adjoining villages were interviewed adjacent to Kaya Tsolokero.展开更多
An in-depth study of the energy related carbon emissions has important practical significance for carbon emissions reduction and structural adjustment in Shandong Province and throughout China.Based on the perspective...An in-depth study of the energy related carbon emissions has important practical significance for carbon emissions reduction and structural adjustment in Shandong Province and throughout China.Based on the perspective of industrial structure,the expanded KAYA equation to measure the energy related carbon emissions of the primary industries(Resources and Agriculture)and secondary industries(Manufacturing and Construction)and tertiary industries(Retail and Service)was utilized in Shandong Province from 2011 to 2017.The carbon emissions among industries in Shandong Province were empirically analyzed using the Logarithmic Mean Divisia Index decomposition approach.The results were follows:(1)Under the three industrial dimensions,the energy structure effect and the energy intensity effect have a restraining influence on the carbon emissions of the three industries.(2)The development level effect and the employment scale effect play a pulling role in carbon emissions.(3)From the perspective of the employment structure effect of the primary industry,there is a restraining effect on carbon emissions,while the employment structure effects of the secondary and tertiary industries play a pulling role in carbon emissions,and the employment structure effect of the tertiary industry has a greater pulling effect on carbon emissions than the secondary industry.展开更多
基金This project is supported by National Natural ScienceFoundation of China Innovative Research Groups Program‘Research on Chinese Public Policy Theory and GovernanceMechanism’(71721002)The Clean DevelopmentMechanism Funding Program‘Study on the Possibility ofChina's Early Emission Peak in the Context of Global Low-Carbon Development’(2013081)。
文摘Pursuant to the Paris Agreement,China committed itself to peak its carbon emissions by around 2030 and to increase the non-fossil share ofprimary energy to 20%at the same time.The government has supported the international agreement by setting and strengthening the domesticpolicy targets for an earlier peak and faster reduction,aiming to contain the average global temperature increase to well below 2℃.We developa Kaya Inequality method to assess the time of peak and pace of reduction of China's energy-related CO2emissions based on the national energypolicy targets for 2030.We find that,despite the minor fluctuations,the current plateau essentially represents the peak emissions and should entera phase of steady decline by around 2025,given current trends in energy consumption and decarbonization.Such developments would beconsistent with the strengthened national policy target to achieve 50%of renewable power generation by 2030.However,the basic policy targetsea 20%share of non-fossil energy and 6 Gtce in total energy consumption by 2030ewould be insufficient to peak carbon emissions by around 2030.The synergy and interplay between domestic policy target setting and international climate commitments shed light on the need to elevatenational climate ambitions under the Paris Agreement and beyond.
基金This work was supported by the Science and Technology Foundation of GEIGC(101662227)National Key Research and Development Program of China(2018 YFB0905000).
文摘In order to quantify the contribution of the mitigation strategies,an extended Kaya identity has been proposed in this paper for decomposing the various factors that influence the CO2 emission.To this end,we provided a detailed decomposition of the carbon intensity and energy intensity,which enables the quantification of clean energy development and electrification.The logarithmic mean divisia index(LMDI)has been applied to the historical data to quantify the contributions of the various factors affecting the CO2 emissions.Further,the global energy interconnection(GEI)scenario has been introduced for providing a systematic solution to meet the 2℃goal of the Paris Agreement.By combining LMDI with the scenario analysis,the mitigation potential of the various factors for CO2 emission has been analyzed.Results from the historical data indicate that economic development and population growth contribute the most to the increase in CO2 emissions,whereas improvement in the power generation efficiency predominantly helps in emission reduction.A numerical analysis,performed for obtaining the projected future carbon emissions,suggests that clean energy development and electrification are the top two factors that can decrease CO2 emissions,thus showing their great potential for mitigation in the future.Moreover,the carbon capture and storage technology serves as an important supplementary mitigation method.
基金the Key Research Fund of Anhui Provincial Education Department (No.2010sk502zd)the National Natural Science Foundation of China (No.41071337)
文摘In the context of ＂two-wheel drive＂ development mode, China＇s construction land shows significant expansion characteristics. The carbon emission effect of construction land changes is an important factor for the increase of carbon emissions in the atmosphere. In this study, the drivers of carbon emissions in Anhui Province from 1997 to 2011 were quantitatively measured using the improved Kaya identity and Logarithmic Mean Divisia Index. The results show that： economic growth, expansion of construction land and changes in population density have incremental effects on carbon emissions. The average contribution rate of economic growth as the first driver is 266.32 percent. The construction land expansion is an important driving factor with annual mean carbon effect of 6.4057 million tons and annual mean contribution rate of 187.30 percent. But the change in population density has little impact on carbon emission driving. Energy structure changes and energy intensity reduction have inhibitory effects on carbon emissions, of which the annual mean contribution rate is -212.06 percent and -158.115 percent respectively. The targeted policy approaches of carbon emission reduction were put forward based on the decomposition of carbon emission factors, laying a scientific basis to rationally use the land for the Government, which is conducive to build an ecological province for Anhui and achieve the purpose of emission reduction, providing a reference for the research on carbon emission effect of changes in provincial-scale construction land.
文摘In this study, a stratified survey sampling was used in order to broaden our knowledge on the management systems of household waste in the town of Kaya/Burkina Faso. Population study consists of households of the town of Kaya. The sample size was fist determined using the sample size calculation formula. Then four (04) strata comprising the town of Kaya sectors that have a Health and Social Promotion Center (HSPC) have been considered. A random household selection method, used inside each stratum and a number of 468 households representative of the town’s population, was surveyed. We have addressed all solid and liquid waste management strategies in those four strata. For each stratum, waste disposal infrastructure, its management in the households and its impacts on the town’s environment and populations’ health were screened. Data collected are presented through descriptive statistics in mean of tables and graphs. Frequently reported diseases in the four HSPCs have been correlated with waste management and disposal methods in the town. Poor handling, evacuation and disposal of waste have numerous negatives impacts on the city’s environment such as proliferation of mosquitoes and flies, bad odors, visual pollution. These negatives impacts on the environment in turn have negatives impacts on the health of the city residents. Malaria appears the most encountered disease followed by Acute Respiratory Infection and Diarrhea. Suggestions aimed at improving waste management and the reduction of its deficiencies impacts on the health of the population has been made.
文摘An ethnobotanical study was carried out in the sacred forests of Kaya Kauma in Kilifi county and Kaya Tsolokero in Junju location in Kenya between 21st January 2015 to 22nd February 2016. Ethnobotanical data on the knowledge of useful Indigenous Food Plants among the dwelling population in the villages around Kaya Kauma and Kaya Tsolokero were obtained from the using semi-structured questionnaire and interviews of the population in the homesteads around both the forests. The Food Plants included vegetables, fruit or any sort of food if they yield to the society. Results based on a questionnaire survey in 18 villages around Kaya Kauma and 9 villages around Kaya Tsolokero are presented by different stratum of Gender, Age, Tribes, Education level, Relationship to the village, Marital status. Usage of plant as food out of the population interviewed around Kaya Kauma and the total fruit plants mentioned by the villagers dwelling around the forest was 18 belonging to 9 different families. The total vegetable plants which were mentioned by the population around Kaya Kauma were 23 belonging to 12 different families. Other Food Plants mentioned by the community was 36. Out of the population interviewed around Kaya Tsolokero out of the Food Plants mentioned by the community, total fruit plants mentioned by the community was 46 belonging to 19 different families, total vegetable plants mentioned was 20 which belonged to 13 different families and other Food Plants mentioned by the community was 23. Out of the dwelling tribes around Kaya Kanma, Mkauma emerged as the most popular tribe and Mjibana as the most popular tribe around Kaya Tsolokero. The 18 adjoining villages to Kaya Kauma were interviewed for the survey and 9 adjoining villages were interviewed adjacent to Kaya Tsolokero.
基金supported by the National Natural Science Foundation of China under Grants 71804089 and 71771138Humanities and Social Sciences Youth Foundation of Ministry of Education of China under Grants 18YJCZH034 and 19YJC790128+2 种基金Jiangsu Post-doctoral Research Funding Plan(2018K195C)Natural Science Foundation of Shandong Province,China under Grant ZR2018LG003Social Science Planning Project Foundation of Shandong Province,China under Grant 16CGLJ09.
文摘An in-depth study of the energy related carbon emissions has important practical significance for carbon emissions reduction and structural adjustment in Shandong Province and throughout China.Based on the perspective of industrial structure,the expanded KAYA equation to measure the energy related carbon emissions of the primary industries(Resources and Agriculture)and secondary industries(Manufacturing and Construction)and tertiary industries(Retail and Service)was utilized in Shandong Province from 2011 to 2017.The carbon emissions among industries in Shandong Province were empirically analyzed using the Logarithmic Mean Divisia Index decomposition approach.The results were follows:(1)Under the three industrial dimensions,the energy structure effect and the energy intensity effect have a restraining influence on the carbon emissions of the three industries.(2)The development level effect and the employment scale effect play a pulling role in carbon emissions.(3)From the perspective of the employment structure effect of the primary industry,there is a restraining effect on carbon emissions,while the employment structure effects of the secondary and tertiary industries play a pulling role in carbon emissions,and the employment structure effect of the tertiary industry has a greater pulling effect on carbon emissions than the secondary industry.
