From water to bioethanol: The impact of climate variability on the water footprint

AbstractInforming and engaging citizens to adopt sustainable diets is a key strategy for reducing global environmental impacts of the agricultural and food sectors. In this respect, the first requisite to support citizens and actors of the food sector is to provide them a publicly available, reliable and ready to use synthesis of environmental pressures associated to food commodities. Here we introduce the SU-EATABLE LIFE database, a multilevel database of carbon (CF) and water (WF) footprint values of food commodities, based on a standardized methodology to extract information and assign optimal footprint values and uncertainties to food items, starting from peer-reviewed articles and grey literature. The database and its innovative methodological framework for uncertainty treatment and data quality assurance provides a solid basis for evaluating the impact of dietary shifts on global environmental policies, including climate mitigation through greenhouse gas emission reductions. The database ensures repeatability and further expansion, providing a reliable science-based tool for managers and researcher in the food sector.

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Assessing Impact of Climate Variability in Southwest Coastal Bangladesh Using Livelihood Vulnerability Index

Climate ◽

10.3390/cli9070107 ◽

2021 ◽

Vol 9 (7) ◽

pp. 107

Author(s):

Sabrina Mehzabin ◽

M. Shahjahan Mondal

Keyword(s):

Climate Variability ◽

Linear Regression Analysis ◽

Kendall Test ◽

Vulnerability Index ◽

Precipitation Anomaly ◽

Primary Data ◽

Precipitation Concentration Index ◽

Coastal Bangladesh ◽

Present Decade ◽

The Impact

This study analyzed the variability of rainfall and temperature in southwest coastal Bangladesh and assessed the impact of such variability on local livelihood in the last two decades. The variability analysis involved the use of coefficient of variation (CV), standardized precipitation anomaly (Z), and precipitation concentration index (PCI). Linear regression analysis was conducted to assess the trends, and a Mann–Kendall test was performed to detect the significance of the trends. The impact of climate variability was assessed by using a livelihood vulnerability index (LVI), which consisted of six livelihood components with several sub-components under each component. Primary data to construct the LVIs were collected through a semi-structed questionnaire survey of 132 households in a coastal polder. The survey data were triangulated and supplemented with qualitative data from focused group discussions and key informant interviews. The results showed significant rises in temperature in southwest coastal Bangladesh. Though there were no discernable trends in annual and seasonal rainfalls, the anomalies increased in the dry season. The annual PCI and Z were found to capture the climate variability better than the currently used mean monthly standard deviation. The comparison of the LVIs of the present decade with the past indicated that the livelihood vulnerability, particularly in the water component, had increased in the coastal polder due to the increases in natural hazards and climate variability. The index-based vulnerability analysis conducted in this study can be adapted for livelihood vulnerability assessment in deltaic coastal areas of Asia and Africa.

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A New Integrated Grey Water Footprint Assessment Method

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.671.412 ◽

2015 ◽

Vol 671 ◽

pp. 412-418

Author(s):

Lu Lu Xu ◽

Li Zhu Chen ◽

Hugh Gong ◽

Xue Mei Ding

Keyword(s):

Water Footprint ◽

Ecological Impact ◽

Water Environment ◽

Assessment Method ◽

Water Volume ◽

Accurate Assessment ◽

Ambient Water ◽

Grey Water ◽

The Impact ◽

Comprehensive Indicator

Water footprint is a volumetric indicator of freshwater appropriation. The grey water footprint (GWF) provides a tool to assess the water volume needed to assimilate a pollutant. However, evaluating the impact on water environment cannot rely solely on volumetric consumption of freshwater. It demands accurate assessment criteria to reflect its environmental and ecological effects on ambient water resource. In this paper, a new assessment method is proposed: the effluent toxicity and the Potential Eco-toxic Effects Probe (PEEP) index of aquatic environment are taken into consideration. This method provides a comprehensive indicator for evaluating water footprint, specified in effluents’ ecological impact on ambient water sources.

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South Africa’s increasing climate variability and its effect on food production

Outlook on Agriculture ◽

10.1177/00307270211004970 ◽

2021 ◽

pp. 003072702110049

Author(s):

Mashudu Tshikovhi ◽

Roscoe Bertrum van Wyk

Keyword(s):

South Africa ◽

Climate Variability ◽

Food Production ◽

Fixed Effects ◽

Crop Yields ◽

Negative Impact ◽

Secondary Data ◽

Mean Annual Temperature ◽

Fixed Effects Panel Regression ◽

The Impact

This study examines the impact of increasing climate variability on food production in South Africa, focusing on maize and wheat yields. A two-way fixed effects panel regression model was used to assess the climate variability impacts, analysing secondary data for the period 2000 to 2019 for nine provinces in South Africa. The study found that increasing climate variability has a negative impact on maize and wheat production in South Africa. Specifically, the results indicated a negative correlation between mean annual temperature with both maize and wheat yields. A decrease in precipitation affected maize yields negatively, while the impact on wheat yields was positive, although insignificant. This analysis, therefore, depicted that crop yields generally increase with more annual precipitation and decrease with higher temperatures. The study recommends that funding initiatives to educate farmers on increasing climate variability and its effects on farming activities in South Africa should be prioritised.

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Ranking the Impact of Climate Variability on UK Retail Sectors: A Path to Resilience

SSRN Electronic Journal ◽

10.2139/ssrn.2675965 ◽

2015 ◽

Cited By ~ 1

Author(s):

Jean-Louis Bertrand ◽

Miia Parnaudeau

Keyword(s):

Climate Variability ◽

The Impact

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Equitable Allocation of Blue and Green Water Footprints Based on Land-Use Types: A Case Study of the Yangtze River Economic Belt

Sustainability ◽

10.3390/su10103556 ◽

2018 ◽

Vol 10 (10) ◽

pp. 3556 ◽

Cited By ~ 5

Author(s):

Gang Liu ◽

Lu Shi ◽

Kevin Li

Keyword(s):

Land Use ◽

Water Resources ◽

Agricultural Land ◽

Optimal Allocation ◽

Water Footprint ◽

Agricultural Water ◽

Land Area ◽

Lexicographic Optimization ◽

The Impact

This paper develops a lexicographic optimization model to allocate agricultural and non-agricultural water footprints by using the land area as the influencing factor. An index known as the water-footprint-land density (WFLD) index is then put forward to assess the impact and equity of the resulting allocation scheme. Subsequently, the proposed model is applied to a case study allocating water resources for the 11 provinces and municipalities in the Yangtze River Economic Belt (YREB). The objective is to achieve equitable spatial allocation of water resources from a water footprint perspective. Based on the statistical data in 2013, this approach starts with a proper accounting for water footprints in the 11 YREB provinces. We then determined an optimal allocation of water footprints by using the proposed lexicographic optimization approach from a land area angle. Lastly, we analyzed how different types of land uses contribute to allocation equity and we discuss policy changes to implement the optimal allocation schemes in the YREB. Analytical results show that: (1) the optimized agricultural and non-agricultural water footprints decrease from the current levels for each province across the YREB, but this decrease shows a heterogeneous pattern; (2) the WFLD of 11 YREB provinces all decline after optimization with the largest decline in Shanghai and the smallest decline in Sichuan; and (3) the impact of agricultural land on the allocation of agricultural water footprints is mainly reflected in the land use structure of three land types including arable land, forest land, and grassland. The different land use structures in the upstream, midstream, and downstream regions lead to the spatial heterogeneity of the optimized agricultural water footprints in the three YREB segments; (4) In addition to the non-agricultural land area, different regional industrial structures are the main reason for the spatial heterogeneity of the optimized non-agricultural water footprints. Our water-footprint-based optimal water resources allocation scheme helps alleviate the water resources shortage pressure and achieve coordinated and balanced development in the YREB.

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Modeling the impact of climate variability on Black Sea anchovy recruitment and production

Fisheries Oceanography ◽

10.1111/fog.12080 ◽

2014 ◽

Vol 23 (5) ◽

pp. 436-457 ◽

Cited By ~ 6

Author(s):

Ceren Güraslan ◽

Bettina A. Fach ◽

Temel Oguz

Keyword(s):

Climate Variability ◽

Black Sea ◽

The Impact

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Tree-ring-based spring precipitation reconstruction in the Sikhote-Alin' Mountain range

Climate of the Past ◽

10.5194/cp-17-951-2021 ◽

2021 ◽

Vol 17 (2) ◽

pp. 951-967

Author(s):

Olga Ukhvatkina ◽

Alexander Omelko ◽

Dmitriy Kislov ◽

Alexander Zhmerenetsky ◽

Tatyana Epifanova ◽

...

Keyword(s):

Climate Variability ◽

Tree Ring ◽

Southern Oscillation ◽

Russian Far East ◽

Pinus Koraiensis ◽

Mountain Range ◽

Korean Pine ◽

Sikhote Alin ◽

The Impact ◽

Standard Tree

Abstract. Climate reconstructions provide important insight into past climate variability and help us to understand the large-scale climate drivers and impact of climate change. However, our knowledge about long-term year-to-year climate variability is still limited due to the lack of high-resolution reconstructions. Here, we present the first precipitation reconstructions based on tree rings from Pinus koraiensis (Korean pine) from three sites placed along a latitudinal (330 km) gradient in the Sikhote-Alin' mountains in the Russian Far East. The tree-ring width chronologies were built using standard tree-ring procedures. We reconstructed the April–June precipitation for the southern Sikhote-Alin' (SSA), March–June precipitation for the central Sikhote-Alin' (CSA) and March–July precipitation for the northwestern Sikhote-Alin' (NSA) over the years 1602 to 2013, 1804 to 2009 and 1858 to 2013, respectively. We found that an important limiting factor for Korean pine growth was precipitation within the period when the air current coming from the continent during the cold period is replaced with the impact of the wet ocean air current. We identified that common wet years for SSA, CSA and NSA occurred in 1805, 1853, 1877, 1903, 1906, 1927, 1983 and 2009 and common dry years occurred in 1821, 1869, 1919, 1949 and 2003. Our reconstructions have 3-, 15- and 60-year periods, which suggests the influence of the El Niño–Southern Oscillation and Pacific Decadal Oscillation on the region's climate and relevant processes. Despite the impact of various global processes, the main contribution to precipitation formation in the study area is still made by the Pacific Ocean, which determines their amount and periodicity.

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Exploring the Impact of Climate Variability on Malaria Transmission Using a Dynamic Mosquito-Human Malaria Model

The Open Infectious Diseases Journal ◽

10.2174/1874279301810010088 ◽

2018 ◽

Vol 10 (1) ◽

pp. 88-100 ◽

Cited By ~ 5

Author(s):

Gbenga J. Abiodun ◽

Peter J. Witbooi ◽

Kazeem O. Okosun ◽

Rajendra Maharaj

Keyword(s):

Climate Variability ◽

Malaria Transmission ◽

Malaria Incidence ◽

Principal Component ◽

Wavelet Coherence ◽

Human Malaria ◽

Kwazulu Natal ◽

The Impact ◽

Wavelet Coherence Analysis ◽

Malaria Model

Introduction: The reasons for malaria resurgence mostly in Africa are yet to be well understood. Although the causes are often linked to regional climate change, it is important to understand the impact of climate variability on the dynamics of the disease. However, this is almost impossible without adequate long-term malaria data over the study areas. Methods: In this study, we develop a climate-based mosquito-human malaria model to study malaria dynamics in the human population over KwaZulu-Natal, one of the epidemic provinces in South Africa, from 1970-2005. We compare the model output with available observed monthly malaria cases over the province from September 1999 to December 2003. We further use the model outputs to explore the relationship between the climate variables (rainfall and temperature) and malaria incidence over the province using principal component analysis, wavelet power spectrum and wavelet coherence analysis. The model produces a reasonable fit with the observed data and in particular, it captures all the spikes in malaria prevalence. Results: Our results highlight the importance of climate factors on malaria transmission and show the seasonality of malaria epidemics over the province. Results from the principal component analyses further suggest that, there are two principal factors associated with climates variables and the model outputs. One of the factors indicate high loadings on Susceptible, Exposed and Infected human, while the other is more correlated with Susceptible and Recovered humans. However, both factors reveal the inverse correlation between Susceptible-Infected and Susceptible-Recovered humans respectively. Through the spectrum analysis, we notice a strong annual cycle of malaria incidence over the province and ascertain a dominant of one year periodicity. Consequently, our findings indicate that an average of 0 to 120-day lag is generally noted over the study period, but the 120-day lag is more associated with temperature than rainfall. This is consistence with other results obtained from our analyses that malaria transmission is more tightly coupled with temperature than with rainfall in KwaZulu-Natal province.

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