Environmental impacts of extensive beef production in Colombia by life cycle assessment: a case study.

The increase in the negative effects of global change promotes the search for alternatives to supply the demand for food worldwide aligned with the Sustainable Development Goals (SDGs) to ensure food security. Animal protein, which is a main source of nutrients in the diet of today's society, especially beef, which is one of the most demanded products nowadays, has been criticized not only for its high water consumption and land occupation for production but also for the emission of greenhouse gases (GHG) from enteric methane generated in the fermentation process within the bovine rumen and deforestation for the adaptation of pastures. This study is mainly motivated by the lack of quantifiable scientific information in Colombia on the environmental impacts of beef production. Therefore, it is intended to estimate some of the impacts of beef production in extensive systems using the life cycle assessment (LCA) method under a particular scenario considering all the production phases (from raw material to fattening, where the cattle are ready to be slaughtered). The study was conducted with data supplied by a farm in Antioquia, Colombia, and the functional unit (FU) was defined as 1 kg of live weight (LW). The scope of this study was gate-to-gate. "The 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories" (IPCC  2006; IPCC 2019) was used to calculate methane and nitrous oxide emissions. LCA modeling was developed with Ecoinvent database v3.8 and the Umberto LCA + software. It was found that the most affected category of damage was ecosystem quality, which represents 77% of the total, followed by human health at 17% and resources at 6%. The category impact of agricultural land occupation is the one that represents the most significant contribution to the ecosystem quality endpoint, with a percentage of 87%, due to the soil's compaction and the loss of the soil's properties. Additionally, the obtained carbon footprint for the system was 28.9 kg of CO2-eq/kg LW.

Leveraging the trend analysis for modeling of the greenhouse gas emissions associated with coal combustion.

In this paper, it is aimed, for the first time, at deriving simple models, leveraging the trend analysis in order to estimate the future greenhouse gas emissions associated with coal combustion. Due to the expectations of becoming the center of global economic development in the future, BRICS-T (Brazil, the Russian Federation, India, China, South Africa, and Turkiye) countries are adopted as cases in the study. Following the models' derivation, their statistical validations and estimating accuracies are also tested through various metrics. In addition, the future greenhouse gas emissions associated with coal combustion are estimated by the derived models. The results demonstrate that the derived models can be successfully used as a tool for estimating the greenhouse gas emissions associated with coal combustions with accuracy ranges from at least 90% to almost 98%. Moreover, the estimating results show that the total amount of greenhouse gas emissions associated with coal combustions in the relevant countries and in the world will increase to 14 BtCO2eq and 19 BtCO2eq by 2035, with an annual growth of 2.39% and 1.71%, respectively. In summary, the current study's findings affirm the usefulness of trend analysis in deriving models to estimate greenhouse gas emissions associated with coal combustion.

Green missing spots: Information entropy on greenhouse gas emission disclosure by Brazilian companies.

This study aims to address a critical gap in the literature by examining the incorporation of uncertainty in measuring carbon emissions using the greenhouse gas (GHG) Protocol methodology across all three scopes. By comprehensively considering the various dimensions of CO2 emissions within the context of organizational activities, our research contributes significantly to the existing body of knowledge. We address challenges such as data quality issues and a high prevalence of missing values by using information entropy, techniques for order preference by similarity to ideal solution (TOPSIS), and an artificial neural network (ANN) to analyze the contextual variables. Our findings, derived from the data sample of 56 companies across 18 sectors and 13 Brazilian states between 2017 and 2019, reveal that Scope 3 emissions exhibit the highest levels of information entropy. Additionally, we highlight the pivotal role of public policies in enhancing the availability of GHG emissions data, which, in turn, positively impacts policy-making practices. By demonstrating the potential for a virtuous cycle between improved information availability and enhanced policy outcomes, our research underscores the importance of addressing uncertainty in carbon emissions measurement for advancing effective climate change mitigation strategies.

The role of microbial communities in biogeochemical cycles and greenhouse gas emissions within tropical soda lakes.

Although anthropogenic activities are the primary drivers of increased greenhouse gas (GHG) emissions, it is crucial to acknowledge that wetlands are a significant source of these gases. Brazil's Pantanal, the largest tropical inland wetland, includes numerous lacustrine systems with freshwater and soda lakes. This study focuses on soda lakes to explore potential biogeochemical cycling and the contribution of biogenic GHG emissions from the water column, particularly methane. Both seasonal variations and the eutrophic status of each examined lake significantly influenced GHG emissions. Eutrophic turbid lakes (ET) showed remarkable methane emissions, likely due to cyanobacterial blooms. The decomposition of cyanobacterial cells, along with the influx of organic carbon through photosynthesis, accelerated the degradation of high organic matter content in the water column by the heterotrophic community. This process released byproducts that were subsequently metabolized in the sediment leading to methane production, more pronounced during periods of increased drought. In contrast, oligotrophic turbid lakes (OT) avoided methane emissions due to high sulfate levels in the water, though they did emit CO2 and N2O. Clear vegetated oligotrophic turbid lakes (CVO) also emitted methane, possibly from organic matter input during plant detritus decomposition, albeit at lower levels than ET. Over the years, a concerning trend has emerged in the Nhecolândia subregion of Brazil's Pantanal, where the prevalence of lakes with cyanobacterial blooms is increasing. This indicates the potential for these areas to become significant GHG emitters in the future. The study highlights the critical role of microbial communities in regulating GHG emissions in soda lakes, emphasizing their broader implications for global GHG inventories. Thus, it advocates for sustained research efforts and conservation initiatives in this environmentally critical habitat.

Trends in the contribution of greenhouse gas emissions from food and beverage purchases in Mexico: 1989-2020.

BACKGROUND: Assessing the trends in dietary GHGE considering the social patterning is critical for understanding the role that food systems have played and will play in global emissions in countries of the global south. Our aim is to describe dietary greenhouse gas emissions (GHGE) trends (overall and by food group) using data from household food purchase surveys from 1989 to 2020 in Mexico, overall and by education levels and urbanicity. METHODS: We used cross-sectional data from 16 rounds of Mexico's National Income and Expenditure Survey, a nationally representative survey. The sample size ranged from 11,051 in 1989 to 88,398 in 2020. We estimated the mean total GHGE per adult-equivalent per day (kg CO2-eq/ad-eq/d) for every survey year. Then, we estimated the relative GHGE contribution by food group for each household. These same analyses were conducted stratifying by education and urbanicity. RESULTS: The mean total GHGE increased from 3.70 (95%CI: 3.57, 3.82) to 4.90 (95% CI 4.62, 5.18) kg CO2-eq/ad-eq/d between 1989 and 2014 and stayed stable between 4.63 (95% CI: 4.53, 4.72) and 4.89 (95% CI: 4.81, 4.96) kg CO2-eq/ad-eq/d from 2016 onwards. In 1989, beef (19.89%, 95% CI: 19.18, 20.59), dairy (16.87%, 95% CI: 16.30, 17.42)), corn (9.61%, 95% CI: 9.00, 10.22), legumes (7.03%, 95% CI: 6.59, 7.46), and beverages (6.99%, 95% CI: 6.66, 7.32) had the highest relative contribution to food GHGE; by 2020, beef was the top contributor (17.68%, 95%CI: 17.46, 17.89) followed by fast food (14.17%, 95% CI: 13.90, 14.43), dairy (11.21%, 95%CI: 11.06, 11.36), beverages (10.09%, 95%CI: 9.94, 10.23), and chicken (10.04%, 95%CI: 9.90, 10.17). Households with higher education levels and those in more urbanized areas contributed more to dietary GHGE across the full period. However, households with lower education levels and those in rural areas had the highest increase in these emissions from 1989 to 2020. CONCLUSIONS: Our results provide insights into the food groups in which the 2023 Mexican Dietary Guidelines may require to focus on improving human and planetary health.

Multifunctional Eco-Friendly Adsorbent Cryogels Based on Xylan Derived from Coffee Residues.

Agricultural and animal farming practices contribute significantly to greenhouse gas (GHG) emissions such as NH3, CH4, CO2, and NOx, causing local environmental concerns involving health risks and water/air pollution. A growing need to capture these pollutants is leading to the development of new strategies, including the use of solid adsorbents. However, commonly used adsorbent materials often pose toxicity and negative long-term environmental effects. This study aimed to develop responsive eco-friendly cryogels using xylan extracted from coffee parchment, a typical residue from coffee production. The crosslinking in cryogels was accomplished by "freeze-thawing" and subsequent freeze-drying. Cryogels were characterized in terms of morphology by using scanning electron microscopy, porosity, and density by the liquid saturation method and also moisture adsorption and ammonia adsorption capacity. The analysis showed that the porosity in the cryogels remained around 0.62-0.42, while the apparent densities varied from 0.14 g/cm3 to 0.25 g/cm3. The moisture adsorption capacity was the highest at the highest relative humidity level (80%), reaching 0.25-0.43 g of water per gram of sample; the amount of water adsorbed increased when the xylan content in the cryogel increased up to 10% w/v, which was consistent with the hygroscopic nature of xylan. The ammonia adsorption process was modeled accurately by a pseudo-second-order equation, where the maximum adsorption capacity in equilibrium reached 0.047 mg NH3/g when xylan reached 10% w/v in cryogels, indicating a chemisorption process. The cryogels under investigation hold promise for ammonia adsorption applications and GHG separation, offering a sustainable alternative for gas-capturing processes.

Microbial communities present in Sargassum spp. leachates from the Mexican Caribbean which are involved in their degradation in the environment, a tool to tackle the problem.

The Sargassum phenomenon is currently affecting the Caribbean in several ways; one of them is the increase of greenhouse gases due to the decomposition process of this macroalgae; these processes also produce large amounts of pollutant leachates, in which several microbial communities are involved. To understand these processes, we conducted a 150-day study on the Sargassum spp environmental degradation under outdoor conditions, during which leachates were collected at 0, 30, 90, and 150 days. Subsequently, a metagenomic study of the microorganisms found in the leachates was carried out, in which changes in the microbial community were observed over time. The results showed that anaerobic bacterial genera such as Thermofilum and Methanopyrus were predominant at the beginning of this study (0 and 30 days), degrading sugars of sulfur polymers such as fucoidan, but throughout the experiment, the microbial communities were changed also, with the genera Fischerella and Dolichospermum being the most predominant at days 90 and 150, respectively. A principal component analysis (PCA) indicated, with 94% variance, that genera were positively correlated at 30 and 90 days, but not with initial populations, indicating changes in community structure due to sargassum degradation were present. Finally, at 150 days, the leachate volume decreased by almost 50% and there was a higher abundance of the genera Desulfobacter and Dolichospemum. This is the first work carried out to understand the degradation of Sargassum spp, which will serve, together with other works, to understand and provide a solution to this serious environmental problem in the Caribbean.

Understanding the Relations between Soil Biochemical Properties and N2O Emissions in a Long-Term Integrated Crop-Livestock System.

Edaphoclimatic conditions influence nitrous oxide (N2O) emissions from agricultural systems where soil biochemical properties play a key role. This study addressed cumulative N2O emissions and their relations with soil biochemical properties in a long-term experiment (26 years) with integrated crop-livestock farming systems fertilized with two P and K rates. The farming systems consisted of continuous crops fertilized with half of the recommended P and K rates (CCF1), continuous crops at the recommended P and K rates (CCF2), an integrated crop-livestock system with half of the recommended P and K rates (ICLF1), and an integrated crop-livestock at the recommended P and K rates (ICLF2). The ICLF2 may have promoted the greatest entry of carbon into the soil and positively influenced the soil's biochemical properties. Total carbon (TC) was highest in ICLF2 in both growing seasons. The particulate and mineral-associated fractions in 2016 and 2017, respectively, and the microbial biomass fraction in the two growing seasons were also very high. Acid phosphatase and arylsulfatase in ICLF1 and ICLF2 were highest in 2016. The soil properties correlated with cumulative N2O emissions were TC, total nitrogen (TN), particulate nitrogen (PN), available nitrogen (AN), mineral-associated organic carbon (MAC), and microbial biomass carbon (MBC). The results indicated that ICLF2 induces an accumulation of more stable organic matter (OM) fractions that are unavailable to the microbiota in the short term and result in lower N2O emissions.

Long-term relationships of beef and dairy cattle and greenhouse gas emissions: Application of co-integrated panel models for Latin America.

The cattle sector plays a pivotal role in the economies of numerous Latin American and Caribbean countries. However, it also exerts a significant impact on environmental degradation, including substantial contributions to greenhouse gas emissions (accounting for 23.5 % of global livestock emissions) and deforestation (70 % attributed to livestock in South America). This article aims to investigate the complex, long-term, and short-term relationships between population growth, pastureland expansion, deforestation, and the cattle sector in 15 countries across the region, focusing on their effects on greenhouse gas emissions as well as beef and dairy production. Utilizing data from FAOSTAT spanning the period from 1990 to 2019, a cointegrated panel model was developed using the Pooled Mean Group technique, resulting in the estimation of six models. The aggregate-level results for the region reveal the presence of relatively stable long-term relationships. This implies that over time, the influence of population growth, pastureland expansion, and deforestation on greenhouse gas emissions from cattle production tends to diminish in significance. This long-term behavior may be particularly pronounced in countries with more developed cattle sectors, where efforts to mitigate the environmental impacts of cattle production, such as promoting improved forage technologies, silvo-pastoral systems, grazing management practices, and the implementation of policies, regulatory frameworks, and incentives, have gained traction. These progressive countries can serve as regional benchmarks, and the lessons they have learned hold valuable insights for the sustainable intensification of cattle production in countries with less-developed cattle sectors.

Factors Affecting Enteric Emission Methane and Predictive Models for Dairy Cows.

Enteric methane emission is the main source of greenhouse gas contribution from dairy cattle. Therefore, it is essential to evaluate drivers and develop more accurate predictive models for such emissions. In this study, we built a large and intercontinental experimental dataset to: (1) explain the effect of enteric methane emission yield (g methane/kg diet intake) and feed conversion (kg diet intake/kg milk yield) on enteric methane emission intensity (g methane/kg milk yield); (2) develop six models for predicting enteric methane emissions (g/cow/day) using animal, diet, and dry matter intake as inputs; and to (3) compare these 6 models with 43 models from the literature. Feed conversion contributed more to enteric methane emission (EME) intensity than EME yield. Increasing the milk yield reduced EME intensity, due more to feed conversion enhancement rather than EME yield. Our models predicted methane emissions better than most external models, with the exception of only two other models which had similar adequacy. Improved productivity of dairy cows reduces emission intensity by enhancing feed conversion. Improvement in feed conversion should be prioritized for reducing methane emissions in dairy cattle systems.

Life Cycle Greenhouse Gas Emissions of Brazilian Sugar Cane Ethanol Evaluated with the GREET Model Using Data Submitted to RenovaBio.

Brazil is the second-largest ethanol producer in the world, primarily using sugar cane as feedstock. To foster biofuel production, the Brazilian government implemented a national biofuel policy, known as RenovaBio, in which greenhouse gas (GHG) emission reduction credits are provided to biofuel producers based on the carbon intensities (CI) of the fuels they produce. In this study, we configured the GREET model to evaluate life cycle GHG emissions of Brazilian sugar cane ethanol, using data from 67 individual sugar cane mills submitted to RenovaBio in 2019/2020. The average CI per megajoule of sugar cane ethanol produced in Brazil for use in the U.S. was estimated to be 35.2 g of CO2 equivalent, a 62% reduction from U.S. petroleum gasoline blendstock without considering the impacts of land use change. The three major GHG sources were on-field N2O emissions (24.3%), sugar cane farming energy use (24.2%), and sugar cane ethanol transport (19.3%). With the probability density functions for key input parameters derived from individual mill data, we performed stochastic simulations with the GREET model to estimate the variations in sugar cane ethanol CI and confirmed that despite the larger variations in sugar cane ethanol CI, the fuel provided a robust GHG reduction benefit compared to gasoline blendstock.

Soil Carbon Stocks and Greenhouse Gas Mitigation of Agriculture in the Brazilian Cerrado-A Review.

New agricultural practices and land-use intensification in the Cerrado biome have affected the soil carbon stocks. A major part of the native vegetation of the Brazilian Cerrado, a tropical savanna-like ecoregion, has been replaced by crops, which has caused changes in the soil carbon (C) stocks. To ensure the sustainability of this intensified agricultural production, actions have been taken to increase soil C stocks and mitigate greenhouse gas emissions. In the last two decades, new agricultural practices have been adopted in the Cerrado region, and their impact on C stocks needs to be better understood. This subject has been addressed in a systematic review of the existing data in the literature, consisting of 63 articles from the Scopus database. Our review showed that the replacement of Cerrado vegetation by crop species decreased the original soil C stocks (depth 0-30 cm) by 73%, with a peak loss of 61.14 Mg ha-1. However, when analyzing the 0-100 cm layer, 52.4% of the C stock data were higher under cultivated areas than in native Cerrado soils, with a peak gain of 93.6 Mg ha-1. The agricultural practices implemented in the Brazilian Cerrado make low-carbon agriculture in this biome possible.

A COMPRENHESIVE ECO-EFFICIENCY ANALYSIS OF WASTEWATER TREATMENT PLANTS: ESTIMATION OF OPTIMAL OPERATIONAL COSTS AND GREENHOUSE GAS EMISSIONS.

The transition to a neutral carbon and sustainable urban water cycle requires improving eco-efficiency in wastewater treatment processes. To support decision-making based on eco-efficiency evaluations, reliable estimations are fundamental. In this study, the eco-efficiency of a sample of 109 WWTPs was evaluated using efficiency analysis tree method. It combines machine learning and linear programming techniques and therefore, overcomes overfitting limitations of non-parametric methods used by past research on this topic. Results from the case study revealed that optimal costs and greenhouse gas emissions depend on the quantity of organic matter and suspended solids removed from wastewater. The estimated average eco-efficiency is 0.373 which involves that the assessed WWTPs could save 0.32 €/m3 and 0.11 kg of CO2 equivalent/m3. Moreover, only 4 out of 109 WWTPs are identified as eco-efficient which implies that the majority of the evaluated facilities can achieve substantial savings in operational costs and greenhouse gas emissions.

Key drivers of the textile and clothing industry decarbonisation within the EU-27.

The European Union has identified the Textile and Clothing industry as one of the essential objectives towards carbon neutrality in 2050 in line with the "European Green Deal". There are no previous research papers focused on analysing the drivers and inhibitors of the past greenhouse gas emission changes of the textile and clothing industry in Europe. This paper aims to analyse the determinants of the changes in these emissions, and the disassociation level between emissions and economic growth, throughout the 27 Member States of the European Union, from 2008 to 2018. A Logarithmic Mean Divisia Index that explains the key drivers of the changes in greenhouse gas emissions of European Union Textile and Cloth industry and a Decoupling Index have been applied. The results generally conclude that the intensity and carbonisation effects are key factors that contribute to reducing greenhouse gas emissions. The lower relative weight of the textile and clothing industry throughout the EU-27 was noteworthy, and favours lower emissions, partially counteracted by the activity effect. Also, most Member States have been decoupling the industry's emissions from economic growth. Our policy recommendation shows that if further reductions in greenhouse gas emissions are to be achieved, energy efficiency improvements and cleaner use of energy sources would offset the potential increase in emissions of this industry as a result of a relative increase in its gross value added.

Assessing the carbon footprint of a Colombian University Campus using the UNE-ISO 14064-1 and WRI/WBCSD GHG Protocol Corporate Standard.

Higher education institutions (HEIs) transfer skills and knowledge between industries, the government, and the public, playing a vital role at educating future leaders in creating a globally sustainable system. Therein, evaluating greenhouse gas emissions from an educational institute is the first step towards the proposed reduction targets at the local, national, and international levels. In this research, we report the first approximate carbon footprint calculation of emissions corresponding to scope 1, scope 2, and scope 3 emissions for the main urban campuses of Universidad Nacional de Colombia, Medellín, using the UNE-ISO 14064-1 and WRI/WBCSD GHG Protocol Corporate standard. The carbon footprint in 2019 was approximately 7250.52 tons CO2 eq, and 0.432 tons CO2 eq per person. Scope 1 emissions accounted for about 2.84% of the carbon footprint, while scope 2 and 3 emissions each contributed nearly 14% and 83%, respectively. The largest sources of greenhouse gas emissions were the transportation process (58.51%), the wastewater process (17.01%), followed by electricity consumption (14.03%), and the e-mails that are sent (6.51%). It is suggested some proposals and strategies for mitigating and reducing emissions. Colombian HEIs exhibit the lowest ton of CO2 eq. per person compared to the other HEIs. Several reasons explain this behavior across the document such as geographic location (climate and topography), cultural factors (consumption patterns and types of transportation), population size, typology (public or private), gross domestic product (GDP) of each country, and methodology implemented. Results cannot be extrapolated to the Colombian case for the differences in the local conditions; therefore, it is not possible to get solid conclusions on the CF behavior in the Colombian HEIs. In this research, we provide for the first time a carbon footprint calculation where the sociological, political, and geographic conditions not extrapolated representing a valuable contribution to the HEI's of the country. This research can be a benchmark in the carbon footprint calculation and a methodological contribution to HEIs in the country.

The individual and combined impact of environmental taxes in Chile - A flexible computable general equilibrium analysis.

Many studies simulate carbon taxes with computable general equilibrium (CGE) models, but there is scarce evidence about how other environmental taxes implemented simultaneously reinforce or lessen the impacts. This study aims to determine the individual and combined effect of taxes on CO2 and other local air pollutants (SO2, NOX, and PM) currently applied in Chile. A flexible CGE model is used to sensitize the results, allowing two nested production structures to be compared. Both nested production structures include a high disaggregation of the energy sector that considers different fossil fuels and renewable energies. The results show that environmental taxes reduce between 5.4% and 6.9% of net CO2 equivalent emissions in the most realistic scenarios. In addition, the carbon tax explains 84%-85% of the drop in net CO2 equivalent emissions, 81%-82% of the reduction in fossil energy consumption, 76%-78% of the decline in GDP, and generates co-benefits by reducing local air pollutants. The tax on PM emissions is the second more relevant to reduce net CO2 equivalent emissions, while taxes on SO2 and NOX emissions have marginal effects. By comparing the impacts of both structures to previous studies based on microdata, it is concluded that the KL-EM provides the best results.

Greenhouse Gas Emissions Associated With the Mexican Diet: Identifying Social Groups With the Largest Carbon Footprint.

Background: Most studies of the climate footprint of diets have been conducted in countries in the global north, but the majority of the world population lives in global south countries. We estimated total dietary greenhouse gas emissions (GHGE) in Mexico, examined the contribution of major food and beverage groups, and assessed variation across social groups. Methods: We linked individual-level dietary data from the Mexican National Health and Nutrition Survey 2018 to the SHARP Indicators Database, containing GHGE estimates for 182 primary food and beverages. Results: Mean dietary GHGE was 3.9 kg of carbon dioxide equivalent per person per day. Dietary GHGE is highest among those in young adulthood and middle age versus adolescents and older adults, and among males, those with higher educational attainment, higher socioeconomic status, that do not speak an indigenous language, and that live in urban areas. Conclusion: The Mexican diet has a much lower carbon footprint than diets in other Latin American countries for which such estimates are available. In contrast to patterns observed in Argentina and Brazil, dietary GHGE was lowest in those in lower socioeconomic and educational strata and in rural areas. A better understanding of the differences in diet sustainability between and within countries will be needed for developing global and local strategies that meet the environmental sustainability goals.

The health, environmental, and economic dimensions of future dietary transitions in Argentina.

Diets link human health with environmental sustainability, offering promising pressure points to enhance the sustainability of food systems. We investigated the health, environmental, and economic dimensions of the current diet in Argentina and the possible effects of six dietary change scenarios on nutrient adequacy, dietary quality, food expenditure, and six environmental impact categories (i.e., GHG emissions, total land occupation, cropland use, fossil energy use, freshwater consumption, and the emission of eutrophying pollutants). Current dietary patterns are unhealthy, unsustainable, and relatively expensive, and all things being equal, an increase in income levels would not alter the health dimension, but increase environmental impacts by 33-38%, and costs by 38%. Compared to the prevailing diet, the six healthier diet alternatives could improve health with an expenditure between + 27% (National Dietary Guidelines) to -5% (vegan diet) of the current diet. These dietary changes could result in trade-offs between different environmental impacts. Plant-based diets showed the lowest overall environmental impact, with GHG emissions and land occupation reduced by up to 79% and 88%, respectively, without significant changes in cropland demand. However, fossil energy use and freshwater consumption could increase by up to 101% and 220%, respectively. The emission of eutrophying pollutants could increase by up to 54% for all healthy diet scenarios, except for the vegan one (18% decrease). We conclude that the health and environmental crisis that Argentina (and other developing countries) currently face could be mitigated by adopting healthy diets (particularly plant-based), bringing in the process benefits to both people and nature. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11625-021-01087-7.

The Environmental Profile of Ecuadorian Export Banana: A Life Cycle Assessment.

Ecuador is one of the largest banana exporters in the world. This sector generates wealth and employment in the country. Life cycle method tools support finding critical points and improvement measures in systems. In this study, the Ecuadorian banana is evaluated through life cycle assessment (LCA), including agriculture, packaging, transfer to the Port of Guayaquil, and transport to a foreign port. OpenLCA software was used, applying the Recipe Midpoint (H) V1.13 impact evaluation method and using primary data collected from a local producer and secondary data from Ecoinvent 3.6 databases, Agribalyse 3.0.1, and the literature. Functional units were established at three levels: "1 ton of Banana at-the-farm-gate"; "1 ton of Banana at-the-packaging-stage-gate"; and "1 ton of Banana at-the-port-of-destination". The impact categories evaluated are climate change (GWP100), fossil depletion (FDP), freshwater eutrophication (FEP), marine eutrophication (MEP), ozone layer depletion (ODPinf), particulate matter formation (PMFP), formation of photochemical oxidants (POFP), and terrestrial acidification (TAP100). The carbon footprint (GWP100) of "Banana at-the-farm-gate", "Banana at-the-packaging-stage-gate", and "Banana at-the-foreign-port" ranged from 194 to 220, 342 to 352, and 615.41 to 625.44 kg CO2-Eq/Ton banana, respectively. Hotspots of the system are the fertilizer field emissions, cardboard packaging, rachis disposal, and maritime transport. Improvement measures should focus on reducing the amount of fertilizers and developing circular alternatives for residual biomass valorization.

Estimation of greenhouse gases shadow price in the English and Welsh water industry.

Moving to a more sustainable and low-carbon footprint urban water cycle is essential in the light of climate change. In this paper, we estimate the implicit cost of reducing greenhouse gas (GHG) emissions for several English and Welsh water companies from 2013 to 2019. Using econometric techniques, we compute the shadow prices of direct and indirect CO2 emissions associated with the provision of drinking water. This methodological approach also allows us to investigate the impact of a set of environmental variables on the costs of water companies and therefore on the costs of reducing GHG emissions. We then compute the returns to scale, technical change, and technical efficiency of the water companies. The empirical results show the following: (1) the average shadow price of CO2 across years was 0.114 £/kgCO2, which means that the English and Welsh water industry needs to spend an extra £0.114 in operating expenditure to prevent the emission of one kilogramme of CO2; (2) the cost of reducing GHG emissions is very variable among water companies and across years; (3) water taken from boreholes and average pumping head increases cost requirements and therefore the inefficiency of water companies; and (4) the water industry may lower its production costs and thus the costs of reducing GHG emissions by improving its daily operations and adopting new technologies. From a policy perspective, this study evidences that in the English and Welsh water industry, a market-based approach may be more suitable to reduce GHG emissions than a carbon tax policy.