Pub Date : 2021-03-31DOI: 10.4236/AJCC.2021.101005
A. M. Paz-Alberto, E. Camaso, Roann P. Alberto, Daryl A. Juganas, K. M. Mapanao, Carl Dionelle B. Ponce, C. R. Genaro
The Philippines is one of the most hazard prone and vulnerable countries in the world to climate change effects due to its geographical location. Climate change is already happening and affecting many places causing huge problems to coastal ecosystems. Vulnerability and disaster assessment and mapping in coastal areas are essential tasks and undertakings for coastal disaster risk management. The objectives of this study were to assess the climate change vulnerability and disaster risks in the four municipalities (Sta. Cruz, Candelaria, Masinloc and Palauig) of Zambales and to determine the climate change community-based adaptation (CBA) and ecosystem-based adaptation (EBA) strategies. Remote sensing, GIS, secondary data gathering and key informant interview were used to assess vulnerability and disaster risks and mapping in the four municipalities. Survey questionnaire, focus group discussion and key informant interview were utilized in gathering data for the determination of climate change adaptation strategies. Using remote sensing technology, it was revealed that coastline changes have occurred in the shorelines of the four coastal municipalities after a decade. Sea level rise happened in Sta. Cruz and Masinloc, Zambales while there was build-up of soil in the coastline of Candelaria and Palauig, Zambales. Twelve hazard maps, 12 vulnerability maps and 12 disaster risk maps were generated for the three major disasters (flood, landslide, storm surge) in the four coastal municipalities. Based on the flood vulnerability and disaster risk assessment, the municipality of Palauig was found to be the most prone to flooding while the municipality of Candelaria was found to be the most vulnerable to landslide compared to other municipalities. All coastal barangays in the four municipalities were susceptible to storm surge. The four coastal municipalities were conducting community-based adaptation (CBA) and ecosystem-based adaptation (EBA) approaches in order to protect their coastal resources from the damaging impacts of climate change and improve the resilience of their local communities.
{"title":"Climate Change Vulnerability and Disaster Risk Assessment Using Remote Sensing Technology and Adaptation Strategies for Resiliency and Disaster Risk Management in Selected Coastal Municipalities of Zambales, Philippines","authors":"A. M. Paz-Alberto, E. Camaso, Roann P. Alberto, Daryl A. Juganas, K. M. Mapanao, Carl Dionelle B. Ponce, C. R. Genaro","doi":"10.4236/AJCC.2021.101005","DOIUrl":"https://doi.org/10.4236/AJCC.2021.101005","url":null,"abstract":"The Philippines is one of the most hazard prone and vulnerable countries in the world to climate change effects due to its geographical location. Climate change is already happening and affecting many places causing huge problems to coastal ecosystems. Vulnerability and disaster assessment and mapping in coastal areas are essential tasks and undertakings for coastal disaster risk management. The objectives of this study were to assess the climate change vulnerability and disaster risks in the four municipalities (Sta. Cruz, Candelaria, Masinloc and Palauig) of Zambales and to determine the climate change community-based adaptation (CBA) and ecosystem-based adaptation (EBA) strategies. Remote sensing, GIS, secondary data gathering and key informant interview were used to assess vulnerability and disaster risks and mapping in the four municipalities. Survey questionnaire, focus group discussion and key informant interview were utilized in gathering data for the determination of climate change adaptation strategies. Using remote sensing technology, it was revealed that coastline changes have occurred in the shorelines of the four coastal municipalities after a decade. Sea level rise happened in Sta. Cruz and Masinloc, Zambales while there was build-up of soil in the coastline of Candelaria and Palauig, Zambales. Twelve hazard maps, 12 vulnerability maps and 12 disaster risk maps were generated for the three major disasters (flood, landslide, storm surge) in the four coastal municipalities. Based on the flood vulnerability and disaster risk assessment, the municipality of Palauig was found to be the most prone to flooding while the municipality of Candelaria was found to be the most vulnerable to landslide compared to other municipalities. All coastal barangays in the four municipalities were susceptible to storm surge. The four coastal municipalities were conducting community-based adaptation (CBA) and ecosystem-based adaptation (EBA) approaches in order to protect their coastal resources from the damaging impacts of climate change and improve the resilience of their local communities.","PeriodicalId":69702,"journal":{"name":"美国气候变化期刊(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45548726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-31DOI: 10.4236/AJCC.2021.101006
K. Mendez, M. A. Adviento-Borbe, A. Lorence, H. Walia
Heat stress studies in rice (Oryza sativa sp.) under extreme weather scenarios generally use constant temperatures to influence the crop responses without relation to actual weather changes. These heat stress studies may have limited implications for future crop yields because elevated temperatures are not based on local temperature fluctuations. This study investigated the night-time air temperature pattern and assessed the status and reliability of available weather station data in four major rice growing states; Arkansas (AR), California (CA), Louisiana (LA) and Texas (TX) using four public weather station databases. Hourly and daily night-time air temperatures from 20:00 to 06:00 were obtained from 1940 to 2018 during the rice growing period. During the 67-year period, a significant increase of 1.12°C and 0.53°C in seasonal night air temperature occurred in CA and AR (P ≤ 0.001) while LA and TX showed minimal to no increase in night air temperature. Across all rice states and years, night air temperature fluctuations ranged between ±0.2°C and ±4°C with the greatest occurred in CA (2.9°C) and AR (4.5°C). Mean night-time air temperature across all states ranged from 22.6°C to 29.5°C with a rate of increase of 0.01°C to 0.02°C per year since 1941. Due to a relatively smaller spatial dataset (from 1941-2018), trend analyses for AR, TX and LA showed modest bias with root mean square errors (RMSE) of 0.5°C to 1.1°C of absolute mean temperature across all locations. Results in this study showed seasonal night-time air temperature change occurred in some major US rice producing states during the last 67-years. This study highlights the need for more weather stations near agricultural farms to reliably derive actual temperature patterns in the rice growing regions.
{"title":"Significant Shift of Ambient Night-Time Air Temperature during Rice Growing Season in Major US Rice States","authors":"K. Mendez, M. A. Adviento-Borbe, A. Lorence, H. Walia","doi":"10.4236/AJCC.2021.101006","DOIUrl":"https://doi.org/10.4236/AJCC.2021.101006","url":null,"abstract":"Heat stress studies in rice (Oryza sativa sp.) under extreme weather scenarios generally use constant temperatures to influence the crop responses without relation to actual weather changes. These heat stress studies may have limited implications for future crop yields because elevated temperatures are not based on local temperature fluctuations. This study investigated the night-time air temperature pattern and assessed the status and reliability of available weather station data in four major rice growing states; Arkansas (AR), California (CA), Louisiana (LA) and Texas (TX) using four public weather station databases. Hourly and daily night-time air temperatures from 20:00 to 06:00 were obtained from 1940 to 2018 during the rice growing period. During the 67-year period, a significant increase of 1.12°C and 0.53°C in seasonal night air temperature occurred in CA and AR (P ≤ 0.001) while LA and TX showed minimal to no increase in night air temperature. Across all rice states and years, night air temperature fluctuations ranged between ±0.2°C and ±4°C with the greatest occurred in CA (2.9°C) and AR (4.5°C). Mean night-time air temperature across all states ranged from 22.6°C to 29.5°C with a rate of increase of 0.01°C to 0.02°C per year since 1941. Due to a relatively smaller spatial dataset (from 1941-2018), trend analyses for AR, TX and LA showed modest bias with root mean square errors (RMSE) of 0.5°C to 1.1°C of absolute mean temperature across all locations. Results in this study showed seasonal night-time air temperature change occurred in some major US rice producing states during the last 67-years. This study highlights the need for more weather stations near agricultural farms to reliably derive actual temperature patterns in the rice growing regions.","PeriodicalId":69702,"journal":{"name":"美国气候变化期刊(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47202267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-10DOI: 10.4236/AJCC.2021.101004
N. Tuan, T. Canh
A quantitative study was used in the study of the tendency to change drought indicators in Vietnam through the Ninh Thuan province case study. The research data are temperature and precipitation data of 11 stations from 1986 to 2016 inside and outside Ninh Thuan province. To do the research, the author uses a non-parametric analysis method and the drought index calculation method. Specifically, with the non-parametric method, the author uses the analysis, Mann-Kendall (MK) and Theil-Sen (Sen’s slope), and to analyze drought, the author uses the Standardized Precipitation Index (SPI) and the Moisture Index (MI). Two Softwares calculated in this study are ProUCL 5.1 and MAKENSEN 1.0 by the US Environmental Protection Agency and Finnish Meteorological Institute. The calculation results show that meteorological drought will decrease in the future with areas such as Phan Rang, Song Pha, Quan The, Ba Thap tend to increase very clearly, while Tam My and Nhi Ha tend to increase very clearly short. With the agricultural drought, the average MI results increased 0.013 per year, of which Song Pha station tended to increase the highest with 0.03 per year and lower with Nhi Ha with 0.001 per year. The forecast results also show that by the end of the 21st century, the SPI tends to decrease with SPI 1 being −0.68, SPI 3 being −0.40, SPI 6 being −0.25, SPI 12 is 0.42. Along with that is the forecast that the MI index will increase 0.013 per year to 2035, the MI index is 0.93, in 2050 it is 1.13, in 2075 it will be 1.46, and by 2100 it is 1.79. Research results will be used in policymaking, environmental resources management agencies, and researchers to develop and study solutions to adapt and mitigate drought in the context of variable climate change.
{"title":"Analysis of Trends in Drought with the Non-Parametric Approach in Vietnam: A Case Study in Ninh Thuan Province","authors":"N. Tuan, T. Canh","doi":"10.4236/AJCC.2021.101004","DOIUrl":"https://doi.org/10.4236/AJCC.2021.101004","url":null,"abstract":"A quantitative study was used in the study of the tendency to change drought indicators in Vietnam through the Ninh Thuan province case study. The research data are temperature and precipitation data of 11 stations from 1986 to 2016 inside and outside Ninh Thuan province. To do the research, the author uses a non-parametric analysis method and the drought index calculation method. Specifically, with the non-parametric method, the author uses the analysis, Mann-Kendall (MK) and Theil-Sen (Sen’s slope), and to analyze drought, the author uses the Standardized Precipitation Index (SPI) and the Moisture Index (MI). Two Softwares calculated in this study are ProUCL 5.1 and MAKENSEN 1.0 by the US Environmental Protection Agency and Finnish Meteorological Institute. The calculation results show that meteorological drought will decrease in the future with areas such as Phan Rang, Song Pha, Quan The, Ba Thap tend to increase very clearly, while Tam My and Nhi Ha tend to increase very clearly short. With the agricultural drought, the average MI results increased 0.013 per year, of which Song Pha station tended to increase the highest with 0.03 per year and lower with Nhi Ha with 0.001 per year. The forecast results also show that by the end of the 21st century, the SPI tends to decrease with SPI 1 being −0.68, SPI 3 being −0.40, SPI 6 being −0.25, SPI 12 is 0.42. Along with that is the forecast that the MI index will increase 0.013 per year to 2035, the MI index is 0.93, in 2050 it is 1.13, in 2075 it will be 1.46, and by 2100 it is 1.79. Research results will be used in policymaking, environmental resources management agencies, and researchers to develop and study solutions to adapt and mitigate drought in the context of variable climate change.","PeriodicalId":69702,"journal":{"name":"美国气候变化期刊(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42238852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-10DOI: 10.4236/AJCC.2021.101002
Felix Ndukson Buba, Samam Obaguo, O. Ogah, F. O. Ajayi
The frequency and consequences of extreme flood events have increased in recent times, having huge impact on the socio-economic well-being of nations with the most significant impact being felt at the community level. Flooding is the most common environmental hazard in Nigeria, particularly Lokoja, with the frequency, intensity, and extent likely to increase due to the effects of global warming leading to climate change such as sea level rise, more intensive precipitation levels, and higher river discharges. While destructive impacts of flood events continue to increase, flood managers in Nigeria have continued to implement a top-down approach towards mitigating these impacts, without involving affected communities in planning and implementation of mitigation strategies. This study therefore employed a participatory approach to determine the causes and impact of flooding in the study area. Participatory research tools such as key informant interviews, focus group discussions, and questionnaire surveys using the purposive sampling method were deployed to elicit data on the perception of the communities about the causes and impact of flood events. Descriptive statistical analysis was performed to elucidate the major causes and areas of impact while qualitative analysis was carried out to corroborate the results and to make for a robust outcome. The Chi Square Test analysis was performed to empirically establish a relationship between the impacts and flooding. Results show that major causes of flooding are the release of water from dams (83% in Adankolo, 97% in Gadumo, and 100% in Ganaja), overflow of rivers, and heavy rainfall while flooding affects economic concerns, property and basic amenities. The Chi Square Test analysis determined empirically that a relationship exists between several areas of impact and flood occurrence. The research concludes that participatory flood research approach can provide flood managers and decision makers a bottom-up approach for effective and robust flood mitigation strategies.
{"title":"A Participatory Assessment of the Impact of Flooding in Some Communities in Lokoja, Kogi State, Nigeria","authors":"Felix Ndukson Buba, Samam Obaguo, O. Ogah, F. O. Ajayi","doi":"10.4236/AJCC.2021.101002","DOIUrl":"https://doi.org/10.4236/AJCC.2021.101002","url":null,"abstract":"The frequency and consequences of extreme flood events have increased in recent times, having huge impact on the socio-economic well-being of nations with the most significant impact being felt at the community level. Flooding is the most common environmental hazard in Nigeria, particularly Lokoja, with the frequency, intensity, and extent likely to increase due to the effects of global warming leading to climate change such as sea level rise, more intensive precipitation levels, and higher river discharges. While destructive impacts of flood events continue to increase, flood managers in Nigeria have continued to implement a top-down approach towards mitigating these impacts, without involving affected communities in planning and implementation of mitigation strategies. This study therefore employed a participatory approach to determine the causes and impact of flooding in the study area. Participatory research tools such as key informant interviews, focus group discussions, and questionnaire surveys using the purposive sampling method were deployed to elicit data on the perception of the communities about the causes and impact of flood events. Descriptive statistical analysis was performed to elucidate the major causes and areas of impact while qualitative analysis was carried out to corroborate the results and to make for a robust outcome. The Chi Square Test analysis was performed to empirically establish a relationship between the impacts and flooding. Results show that major causes of flooding are the release of water from dams (83% in Adankolo, 97% in Gadumo, and 100% in Ganaja), overflow of rivers, and heavy rainfall while flooding affects economic concerns, property and basic amenities. The Chi Square Test analysis determined empirically that a relationship exists between several areas of impact and flood occurrence. The research concludes that participatory flood research approach can provide flood managers and decision makers a bottom-up approach for effective and robust flood mitigation strategies.","PeriodicalId":69702,"journal":{"name":"美国气候变化期刊(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44563179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-10DOI: 10.4236/AJCC.2021.101001
C. Firebaugh, T. Zolnikov, Frances Furio, G. Ng
There is increasing evidence that climate change, like other natural disasters has the potential for significant human health impacts, including mental health. Fear as a psychological construct concerning climate change is not well understood. An online cross-sectional survey was conducted, targeting a demographically representative sample of Americans (n = 546) in terms of ethnicity, age, and gender. Survey questions included demographic information and global questions regarding self-rated anxiety and fear of climate change. Ordinal logistic models were created to determine which demographic factors were most predictive of climate change fear in the US population. Over half of the study sample (50.9%) indicated being moderately or very afraid of climate change. In the end, only three factors remained significant (p < 0.001) in the model; self-reported level of anxiety, political affiliation, and identifying and Hispanic/Latino. Climate change fear is still not understood, especially in terms of its impact on the mental health of the population in general, though prolonged fear can be an antecedent to other mental health disorders. This study had demonstrated that fear of climate change impacts over half of the U.S population. Level of fear differs significantly by demographic. This study has provided evidence that climate change fear impacts a significant proportion of the US population, prompting a need to investigate the potential acute and long-term impacts of this fear on the human psyche. The harms and benefits of the fear response to climate change should be explored as well as potential responses to fear due to climate change.
{"title":"Population Levels of Climate Change Fear in the United States","authors":"C. Firebaugh, T. Zolnikov, Frances Furio, G. Ng","doi":"10.4236/AJCC.2021.101001","DOIUrl":"https://doi.org/10.4236/AJCC.2021.101001","url":null,"abstract":"There is increasing evidence that climate change, like other natural disasters has the potential for significant human health impacts, including mental health. Fear as a psychological construct concerning climate change is not well understood. An online cross-sectional survey was conducted, targeting a demographically representative sample of Americans (n = 546) in terms of ethnicity, age, and gender. Survey questions included demographic information and global questions regarding self-rated anxiety and fear of climate change. Ordinal logistic models were created to determine which demographic factors were most predictive of climate change fear in the US population. Over half of the study sample (50.9%) indicated being moderately or very afraid of climate change. In the end, only three factors remained significant (p < 0.001) in the model; self-reported level of anxiety, political affiliation, and identifying and Hispanic/Latino. Climate change fear is still not understood, especially in terms of its impact on the mental health of the population in general, though prolonged fear can be an antecedent to other mental health disorders. This study had demonstrated that fear of climate change impacts over half of the U.S population. Level of fear differs significantly by demographic. This study has provided evidence that climate change fear impacts a significant proportion of the US population, prompting a need to investigate the potential acute and long-term impacts of this fear on the human psyche. The harms and benefits of the fear response to climate change should be explored as well as potential responses to fear due to climate change.","PeriodicalId":69702,"journal":{"name":"美国气候变化期刊(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42486660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-10DOI: 10.4236/AJCC.2021.101003
Rahel Solomon, B. Simane, B. Zaitchik
The challenge of meeting the ever-increasing food demand for the growing population will be further exacerbated by climate change in Ethiopia. This paper presents the simulated economy-wide impacts of climate change on the agriculture sector of Ethiopia using a dynamic computable general equilibrium (CGE) model. The study simulated the scenarios of agricultural productivity change induced by climate change up to the year 2050. At national level, the simulation results suggest that crop production will be adversely affected during the coming four decades and the severity will increase over the time period. Production of teff, maize and sorghum will decline by 25.4, 21.8 and 25.2 percent, respectively by 2050 compared to the base period. Climate change will also cause losses of 31.1 percent agricultural GDP at factor cost by 2050. Climate change affects more the income and consumption of poor rural households than urban rural non-farming households. The reduction in agricultural production will not be evenly distributed across agro ecological zones, and will not all be negative. Among rural residents, climate change impacts tend to hurt the income of the poor more in drought prone regions. Income from labor, land and livestock in moisture sufficient highland cereal-based will decline by 5.1, 8.8 and 15.2 percent in 2050. This study indicated that since climate change is an inevitable phenomenon, the country should start mainstreaming adaptation measures to sustain the overall performance of the economy.
{"title":"The Impact of Climate Change on Agriculture Production in Ethiopia: Application of a Dynamic Computable General Equilibrium Model","authors":"Rahel Solomon, B. Simane, B. Zaitchik","doi":"10.4236/AJCC.2021.101003","DOIUrl":"https://doi.org/10.4236/AJCC.2021.101003","url":null,"abstract":"The challenge of meeting the ever-increasing food demand for the growing population will be further exacerbated by climate change in Ethiopia. This paper presents the simulated economy-wide impacts of climate change on the agriculture sector of Ethiopia using a dynamic computable general equilibrium (CGE) model. The study simulated the scenarios of agricultural productivity change induced by climate change up to the year 2050. At national level, the simulation results suggest that crop production will be adversely affected during the coming four decades and the severity will increase over the time period. Production of teff, maize and sorghum will decline by 25.4, 21.8 and 25.2 percent, respectively by 2050 compared to the base period. Climate change will also cause losses of 31.1 percent agricultural GDP at factor cost by 2050. Climate change affects more the income and consumption of poor rural households than urban rural non-farming households. The reduction in agricultural production will not be evenly distributed across agro ecological zones, and will not all be negative. Among rural residents, climate change impacts tend to hurt the income of the poor more in drought prone regions. Income from labor, land and livestock in moisture sufficient highland cereal-based will decline by 5.1, 8.8 and 15.2 percent in 2050. This study indicated that since climate change is an inevitable phenomenon, the country should start mainstreaming adaptation measures to sustain the overall performance of the economy.","PeriodicalId":69702,"journal":{"name":"美国气候变化期刊(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47517689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.4236/ajcc.2021.104022
Nikunj Jaitawat, V. Saraswat, Nirmala Singh Rathore
In this research paper we have evaluated the relation between surface Ozone (O3), Sun Spot Number (SSN) and Carbon Monoxide (CO) over an American station “Tutuila” for the long period of 35 years (1980-2015). It was analyzed that CO and O3 show an increasing trend over the maximum months of the year, whereas SSN shows decreasing trend throughout the year. We have concluded that, for O3 the increasing trend is found to be maximum in the month of December, whereas surprisingly just a month before it i.e., in November, the value was negative. We also analyze here the CO data for the same period. It is observed that the CO increases from January to June. Its increment is found to be minimum in January month and maximum in the month of April. After it, the CO shows the decay trend from July to September, and then again increases from October to December months. NO2 data of 11 years is also studied here and concluded that, the variation observed in March month is very small and is positive. In the same way, a positive trend is observed for NO2 data in June month, but in rest all the months the value is negative.
{"title":"Study of Surface Ozone over an American Station for a Period of 3.5 Decade","authors":"Nikunj Jaitawat, V. Saraswat, Nirmala Singh Rathore","doi":"10.4236/ajcc.2021.104022","DOIUrl":"https://doi.org/10.4236/ajcc.2021.104022","url":null,"abstract":"In this research paper we have evaluated the relation between surface Ozone (O3), Sun Spot Number (SSN) and Carbon Monoxide (CO) over an American station “Tutuila” for the long period of 35 years (1980-2015). It was analyzed that CO and O3 show an increasing trend over the maximum months of the year, whereas SSN shows decreasing trend throughout the year. We have concluded that, for O3 the increasing trend is found to be maximum in the month of December, whereas surprisingly just a month before it i.e., in November, the value was negative. We also analyze here the CO data for the same period. It is observed that the CO increases from January to June. Its increment is found to be minimum in January month and maximum in the month of April. After it, the CO shows the decay trend from July to September, and then again increases from October to December months. NO2 data of 11 years is also studied here and concluded that, the variation observed in March month is very small and is positive. In the same way, a positive trend is observed for NO2 data in June month, but in rest all the months the value is negative.","PeriodicalId":69702,"journal":{"name":"美国气候变化期刊(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70503361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.4236/ajcc.2021.104028
S. Akther, Md. Mahfuzul Islam, M. Hossain, Z. Parveen
Mangrove soils are well known for their high capacity of storing organic carbon (SOC) in various pools; however, a relatively small change in SOC pools could cause significant impacts on greenhouse gas concentrations. Thus, for an in-depth understanding of SOC distribution and stock to predict the role of Sundarbans mangrove in mitigating global warming and greenhouse effects, different extraction methods were employed to fractionate the SOC of Sundarbans soils into cold-water (CWSC) and hot-water (HWSC) soluble, moderately labile (MLF), microbial biomass carbon (MBC), and resistant fractions (RF) using a newly developed modified-method. A significant variation in total SOC (p < 0.001), SOC stock (p < 0.001) and soil bulk density (p < 0.05) at the Sundarbans mangrove forest were observed. In most soils, bulk density increased from the surface to 100 cm depth. The total SOC concentrations were higher in most surface soils and ranged from 1.21% ± 0.02% to 8.19% ± 0.09%. However, C in lower layers may be more resistant than that of upper soils because of differences in compositions, sources and environmental conditions. SOC was predominately associated with the resistant fraction (81% - 97%), followed by MLF (2% higher SOC stock in the soil profile and its primary association in resistant fractions suggested that Sundarbans mangrove soil is sequestering carbon and thereby serving as a significant carbon sink in Bangladesh.
{"title":"Fractionation of Organic Carbon and Stock Measurement in the Sundarbans Mangrove Soils of Bangladesh","authors":"S. Akther, Md. Mahfuzul Islam, M. Hossain, Z. Parveen","doi":"10.4236/ajcc.2021.104028","DOIUrl":"https://doi.org/10.4236/ajcc.2021.104028","url":null,"abstract":"Mangrove soils are well known for their high capacity of storing organic carbon (SOC) in various pools; however, a relatively small change in SOC pools could cause significant impacts on greenhouse gas concentrations. Thus, for an in-depth understanding of SOC distribution and stock to predict the role of Sundarbans mangrove in mitigating global warming and greenhouse effects, different extraction methods were employed to fractionate the SOC of Sundarbans soils into cold-water (CWSC) and hot-water (HWSC) soluble, moderately labile (MLF), microbial biomass carbon (MBC), and resistant fractions (RF) using a newly developed modified-method. A significant variation in total SOC (p < 0.001), SOC stock (p < 0.001) and soil bulk density (p < 0.05) at the Sundarbans mangrove forest were observed. In most soils, bulk density increased from the surface to 100 cm depth. The total SOC concentrations were higher in most surface soils and ranged from 1.21% ± 0.02% to 8.19% ± 0.09%. However, C in lower layers may be more resistant than that of upper soils because of differences in compositions, sources and environmental conditions. SOC was predominately associated with the resistant fraction (81% - 97%), followed by MLF (2% higher SOC stock in the soil profile and its primary association in resistant fractions suggested that Sundarbans mangrove soil is sequestering carbon and thereby serving as a significant carbon sink in Bangladesh.","PeriodicalId":69702,"journal":{"name":"美国气候变化期刊(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70503505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.4236/ajcc.2021.103012
Yasminath Judith Follone Avaligbé, F. Chabi, C. Gnanglè, O. D. Bello, I. Yabi, L. Ahoton, A. Saidou
{"title":"Modelling the Current and Future Spatial Distribution Area of Shea Tree (Vittelaria paradoxa C. F. Gaertn) in the Context of Climate Change in Benin","authors":"Yasminath Judith Follone Avaligbé, F. Chabi, C. Gnanglè, O. D. Bello, I. Yabi, L. Ahoton, A. Saidou","doi":"10.4236/ajcc.2021.103012","DOIUrl":"https://doi.org/10.4236/ajcc.2021.103012","url":null,"abstract":"","PeriodicalId":69702,"journal":{"name":"美国气候变化期刊(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70503270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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