A comparison of energy use, water use and carbon footprint of cassava starch production in Thailand, Vietnam and Colombia

As part of the Net Zero Carbon Water Cycle Program (NZCWCP) for Victoria state in Australia, we have sought to understand the potential to reduce household energy consumption and related Greenhouse Gas (GHG) emissions by influencing water use. Digital metering data disaggregated into 57 million discrete water usage events across 105 households at a resolution of 10 millilitres at 10 second intervals from June 2017 to March 2020, from a previous Yarra Valley Water (Melbourne, Australia) study, was analysed, together with the dynamic relationship between the multiple energy sources (natural gas, grid electricity, solar) used to heat water for showers in each hour of the day. Water-related energy (WRE) use, including water desalination and treatment, pumping, heating, wastewater collection and treatment, comprised 12.6% of Australia’s primary energy use in 2019. Water heating (by natural gas and electricity) comprised the largest component of WRE use for across residential, commercial, and industrial sectors. Furthermore, 69% of Victoria’s total water usage was by residential customers in 2020-2021. WRE GHG emissions were around 3.8% of Victoria’s total GHG emissions in 2018. Showers (~50% of residential WRE), system losses (~27% of residential WRE), and clothes washers (~9% of residential WRE) are the three largest components of WRE consumption. The main objective of this work is the creation of industry-accessible tools to improve knowledge and management options from the understanding of reductions in cost and GHG emissions from household showering WRE use. Potential options considered, to reduce water and energy use, as well as associated GHG emissions and customer utility bills, include (a) behaviour management such as water and energy pricing to change time of use behaviours, and (b) the adoption of efficient shower head improvements. Shower WRE and GHG emissions were found able to be strongly impacted by small changes in daily routines. GHG emissions reduction from showering could be reduced up to 20 (in summer) - 22% (in winter) by shifting demand time of showering or replacing residential showerheads. Extrapolated to state and Australian scales, reductions in water usage could be up to 14 GL (Victoria) and 144 GL (Australia), and reductions in GHG emissions 1,600 ktCO2eq (Victoria) and 17,300 ktCO2eq (Australia). It provides fundamental new information which could inform a suite of new management options to impact water-related energy from showers, and related GHG emissions and customer water and energy cost.

Background: Current scientific literature suggests healthy dietary patterns may have less environmental impact than current consumption patterns, but most of the studies rely on theoretical modeling. The aim of this study was to assess the impact on resources (land, water, and energy) use and greenhouse gas (GHG) emissions of healthy dietary patterns in a sample of Italian adults. Methods: Participants (n = 1806) were recruited through random sampling in the city of Catania, southern Italy. Dietary consumption was assessed through a validated food frequency questionnaire (FFQ); dietary patterns were calculated through dietary scores. The specific environmental footprints of food item production/processing were obtained from various available life-cycle assessments; a sustainability score was created based on the impact of the four environmental components calculated. Results: The contribution of major food groups to the environmental footprint showed that animal products (dairy, egg, meat, and fish) represented more than half of the impact on GHG emissions and energy requirements; meat products were the stronger contributors to GHG emissions and water use, while dairy products to energy use, and cereals to land use. All patterns investigated, with the exception of the Dietary Approach to Stop Hypertension (DASH), were linearly associated with the sustainability score. Among the components, higher adherence to the Mediterranean diet and Alternate Diet Quality Index (AHEI) was associated with lower GHG emissions, dietary quality index-international (DQI-I) with land use, while Nordic diet with land and water use. Conclusions: In conclusion, the adoption of healthy dietary patterns involves less use of natural resources and GHG emissions, representing eco-friendlier options in Italian adults.

Energy-related activities are a major contributor of greenhouse gas (GHG) emissions. A growing body of knowledge clearly depicts the links between human activities and climate change. Over the last century the burning of fossil fuels such as coal and oil and other human activities has released carbon dioxide (CO2) emissions and other heat-trapping GHG emissions into the atmosphere and thus increased the concentration of atmospheric CO2 emissions. The main human activities that emit CO2 emissions are (1) the combustion of fossil fuels to generate electricity, accounting for about 37% of total U.S. CO2 emissions and 31% of total U.S. GHG emissions in 2013, (2) the combustion of fossil fuels such as gasoline and diesel to transport people and goods, accounting for about 31% of total U.S. CO2 emissions and 26% of total U.S. GHG emissions in 2013, and (3) industrial processes such as the production and consumption of minerals and chemicals, accounting for about 15% of total U.S. CO2 emissions and 12% of total ...

Water and energy use and greenhouse gas emissions for nixtamalised maize masa flour production

Indian dairy enterprise is dominated by smallholder dairy farms that contribute 72% of the country's total milk production. These smallholder dairy farms are often considered to emit substantial greenhouse gases (GHG) but are poor in productive performances. Therefore, it is crucial to estimate the carbon footprint (CF) of milk production of the smallholder Indian dairy farms. The primary objectives of the study were (1) Assessing the CF of milk production of smallholder dairy farms through life cycle analysis in south-interior Karnataka, India; (2) Identifying the hotspots of GHG emissions and significant factors influencing the CF of milk production in smallholder dairy production system. The study accounted GHG emissions from different sources and considered multiple functions of the smallholder production system. Estimations were made based on primary data collected from 47 farms and associated secondary data. For estimating the CF of milk production, the emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) on a CO2-equivalent (CO2-eq) basis from feed production, enteric fermentation, manure management, transport and energy usage were allocated to fat- and protein-corrected milk (FPCM) based on mass balance, price (crop byproducts and residues) and feed digestibility. Principal component analysis and stepwise linear regression analysis were performed to identify the major factors influencing the CF. The average total GHG emissions (kg CO2-eq yr-1 farm-1) attributable to milk production based on mass, economic, and digestibility allocations were 8,936, 8,641, and 8,759, respectively. The contributions of CH4, N2O, and CO2 to the total farm GHG emission were 70.6%, 20.5%, and 7.69%, respectively. The major emission hotspots were CH4 emission from enteric fermentation (66.8%) and GHG emission from feed production (23.0%). The average CF of cradle-to-dairy cooperative milk production varied from 1.45 to 1.81 kg CO2-eq kg FPCM-1. The CF of milk production was more than 2-fold greater, when milk yield was below 3,500 kg lactating cow-1 yr-1. The FPCM yield 100 kg body weight-1, dry matter intake, and CH4 emission from manure management were the strongest determinants of the CF and explained 83.4% of the observed variation. The study emphasized the importance of considering multiple functions of a mixed crop-livestock-based dairy production system for estimating CF per unit of product. The results suggest that maintaining high-yielding dairy animals and adopting appropriate feeding strategies for better feed utilization are the possible effective interventions for reducing the CF of milk production.

Smallholder dairy farms face enormous challenges in increasing milk production while mitigating greenhouse gas (GHG) emissions, thereby enhancing climate resilience. The carbon footprint (CF) of smallholder milk production is expected to increase with increasing demand for dairy products under the business-as-usual scenario. This study estimates the carbon footprint of smallholder milk production and examines variation across farms using data from 480 households to identify viable options for mitigating GHG emissions. We applied a cradle to farm-gate life cycle assessment (LCA) approach to examine the effects of farming systems on GHG emission intensities across intensification gradients of smallholder farms (SHF) from four potential dairy districts in the central highlands of Ethiopia. According to our findings, enteric fermentation was the primary source of GHG emissions, and methane(CH4) emissions from enteric fermentation and manure management accounted for the majority of total emissions across farms. The estimated average CF varies depending on farming systems, global warming potential (GWP), and allocation methods used. When GHG emissions were allocated to multiple products using economic allocation and based on IPCC (2007)and IPCC (2014)GWPs, the overall average CF of milk production was 1.91 and 2.35kg CO2e/kg fat and protein-corrected milk (FPCM), respectively. On average, milk accounted for 72% of total greenhouse gas emissions. In terms of farm typology, rural SHF systems produced significantly more CF per kg of milk than urban and peri-urban SHF systems. Variations in milk yield explained more than half of the variation in GHG emissions intensity at the farm level. Feed digestibility and feed efficiency had a negative and significant (P < 0.01) association with CF of SHF. Our findings suggested that improving feed digestibility and feed efficiency by increasing the proportion of concentrate and improved forage as well as chemically upgrading straw and crop residue could provide an opportunity to both increase milk yield and reduce the CF of milk production of SHF in the study area. Supporting SHF to realize strategies contributing to climate-resilient dairy development require interventions at several levels in the dairy value chain.

Major US electric utility climate pledges have the potential to collectively reduce power sector emissions by one-third

Life cycle assessment of various alternative management strategies in the swine industry was performed to evaluate their impact on greenhouse gas (GHG) emissions, cumulative energy use, and cumulative water use. The management strategies included the use of immunocastration (IC), production without ractopamine (NoRAC), production without antimicrobials used for either growth promotion (NoAGP) or disease prevention (NoPREV), production of entire males (boars) (EM), and use of gestation pens (PENS). A common baseline scenario representing standard management practices in the swine industry was created against which all alternative management practices were compared pairwise. The study scope was from cradle-to-farm gate with a functional unit of 1 kg live weight at the farm gate. The baseline and each alternative management scenario was simulated in Pig Production Environmental Footprint Calculator (PPEC) model by varying key variables to populate life cycle inventory inputs for SimaPro V7.3 (Pre' Consultant, the Netherlands), a life cycle assessment modeling program. Increase in GHG emissions, energy use, and water use were observed for NoAGP (1.56, 1.75, and 1.03%, respectively), NoPREV (17.32, 18.40, and 15.58%, respectively), and NoRAC (6.52, 4.87, and 7.52%, respectively) scenarios. For EM scenario, GHG emissions and energy use increased by 2.09 and 3.75%, respectively but water use decreased by 2.29%. Lower GHG emissions, energy use, and water use were observed for PENS (0.97, 1.50, and 0.97%, respectively) and IC (2.39, 2.57, and 2.96%, respectively) scenarios. These changes in the impact categories were statistically significant (P < 0.05) for all scenarios except for changes to GHG emissions for EM and changes to water consumption for PENS and NoAGP. However, the uncertainty analysis showed that the tails of distribution for baseline and alternative management scenario pair overlapped. The impact of management practices on sustainability metrics resulted from differences in pig performance parameters, manure production, feed consumption, etc. between various management practices and the baseline scenario. Due to uncertainties in input parameters, the results should be interpreted as general trends which specifically highlight trade-offs that may result from shifts in production practices. The study identified some of the hot spots in pig production and can be useful in determining best management practices to make swine production more environmentally sustainable.

Change in carbon footprint of canola production in the Canadian Prairies from 1986 to 2006

Agriculture significantly impacts the global environment, contributing to greenhouse gas (GHG) emissions, air and water pollution, and biodiversity loss. As the global population grows and demands higher agricultural output, these environmental impacts are expected to intensify. Among global contributors, China, with its vast population and prominent agricultural sector, plays a leading role in GHG emissions. Understanding and mitigating these impacts in China is crucial for addressing broader global environmental challenges. To address these key issues, we conducted a study on the dynamic impact of agricultural key variables (agricultural land, fertilizer consumption, energy use for agriculture, agricultural value-added, forest land, livestock, fisheries, and crop production) on GHG emissions by utilizing the data from 1990 to 2020, and employed linear and non-linear linear autoregressive distributed lag (ARDL and NARDL) models. In the study, co-integration analysis confirms the long-run relationship between variables, and the long-term findings from the ARDL model reveal important insights, increased agricultural land use, fertilizer consumption, agricultural energy use, crop production, livestock production, and fishery production increases GHG emissions in China and GHG emissions can be reduced by increasing forest land in the long term. Furthermore, with the asymmetric NARDL regression applied to three key variables, the positive shock analysis results confirm that agricultural land use (AGL+), fertilizer consumption (FC+), and agricultural energy use (EUA+) can significantly contribute to long-term GHG emissions. However, adverse shocks to (AGL−), (FC−), and (EUA−) could significantly compress GHG emissions. These findings offer valuable implications for Chinese authorities’ focus on expanding forest land, using more renewable energy, and minimizing the usage of chemicals in agriculture. These measures can help to mitigate emissions while promoting sustainable agricultural practices.

Simple SummaryA spring calving herd (~350 beef cows) over two production cycles was used to compare the whole-farm greenhouse gas (GHG) emissions among calf-fed vs. yearling-fed production systems, with and without growth implants. Farm GHG emissions initially included enteric CH4, manure CH4 and N2O, cropping N2O, and energy use CO2. The carbon footprint ranged from 19.9–22.5 kg CO2e per kg carcass weight. Including soil organic carbon loss from annual cropping and carbon sequestration from perennial pastures and haylands further reduced the carbon footprint by 11–16%. The carbon footprint of beef was reduced by growth promotants (4.9–5.1%) and by calf-fed beef production (6.3–7.5%).A spring calving herd consisting of about 350 beef cows, 14–16 breeding bulls, 60 replacement heifers and 112 steers were used to compare the whole-farm GHG emissions among calf-fed vs. yearling-fed production systems with and without growth implants. Carbon footprint ranged from 11.63 to 13.22 kg CO2e per kg live weight (19.87–22.52 kg CO2e per kg carcass weight). Enteric CH4 was the largest source of GHG emissions (53–54%), followed by manure N2O (20–22%), cropping N2O (11%), energy use CO2 (9–9.5%), and manure CH4 (4–6%). Beef cow accounted for 77% and 58% of the GHG emissions in the calf-fed and yearling-fed. Feeders accounted for the second highest GHG emissions (15% calf-fed; 35–36% yearling-fed). Implants reduced the carbon footprint by 4.9–5.1% compared with hormone-free. Calf-fed reduced the carbon footprint by 6.3–7.5% compared with yearling-fed. When expressed as kg CO2e per kg carcass weight per year the carbon footprint of calf-fed production was 73.9–76.1% lower than yearling-fed production, and calf-fed implanted was 85% lower than hormone-free yearling-fed. Reducing GHG emissions from beef production may be accomplished by improving the feed efficiency of the cow herd, decreasing the days on low quality feeds, and reducing the age at harvest of youthful cattle.

Due to the growing demand for livestock products both within the country and in foreign markets, there is a need to boost the production of maize-based animal feed in Thailand. However, greenhouse gas (GHG) emissions and the potential for reducing these emissions through the production of various types of animal feed remain ambiguous. Thus, this study is aimed at estimating GHG emissions from broiler, layer, and swine feed production in Thailand and identifying economic advantages of alternative methods to mitigate those emissions. Field surveys were carried out to quantify the input and output of energy and materials in 10 commercial feed mills so as to determine greenhouse gas emissions using proper emission factors. The scope of this study is based on the cradle-to-gate approach. The functional unit used for greenhouse gas evaluation was kg CO2-eq/t of feed. Total greenhouse gas emissions from broiler, layer, and swine feed production were found to be 650 ± 20, 706 ± 20, and 466 ± 20 kg CO2-eq/t of feed, respectively. Layer feed production created the highest greenhouse gas emissions, 1.09 and 1.52 times that of broiler and swine feed production, respectively. This is because layer feed required intensive fish meal (FM) as protein sources for improving egg quality. In broiler and swine feed production, the most significant emissions are attributed to the use of maize grain (MG) and soybean meal (SBM) as sources of carbohydrate and protein in those feeds. However, animal feed production operation at the existing condition still emits CO2 to the atmosphere as CO2 fixation efficiencies of 69.3, 67.5, and 75.9% for broiler, layer, and swine feed, respectively. From the sustainable resource consumption scenarios in broiler, layer, and swine feed production, approximately 39.6, 49.6, and 43.3% reduced carbon emissions could be achieved by using MG rotated with SB in the maize plantation phase and substituting FM, wheat grain and fossil fuel needed in the manufacturing process with SBM, locally-produced tapioca chips and biomass energy. Consequently, the potential cost savings of such replacements were determined to be 54.0, 62.5, and 29.7 USD/t of feed, respectively.

Environmental data and facts in the semiconductor manufacturing industry: An unexpected high water and energy consumption situation

Changes in the life cycle environmental footprint of egg production in Canada from 1962 to 2012

Increasing energy and protein use efficiency improves opportunities to decrease land use, water use, and greenhouse gas emissions from dairy production