Environmental Impact of Increased Adherence to SENC Food Based Dietary Guidelines in the Average Dietary Patterns in Spain

Objectives To analyze estimated changes in greenhouse gas (GHG) emission, cropland use and freshwater use of greater adherence to recommendations in Food-Based Dietary Guidelines (FBDG) issued by the Spanish Society of Community Nutrition (SENC) in average dietary patterns in Spain. Methods The data analyzed was drawn from the ENPE study (n = 6800), a cross-sectional study conducted on a random population sample of Spanish population (2015). Dietary intake data was collected by means of a validated 210-item quantitative food frequency questionnaire. A score of adherence to recommendations in SENC FBDG (DG score) was computed (DG score range 0 to 16). Based on food group intake and adherence to each quantitative recommendation, we estimated food group consumption for a 20% increase in adherence to FBDGs. We calculated the potential environmental impact for those estimates, considering data available on crop specific environmental footprints for greenhouse gas emissions, cropland use and freshwater use. Results SENC FBDGs were formulated in tune with current food, cultural, gastronomic, and economic context. Changes in usual diets that people could comfortably afford in the short and medium term were suggested. Mean adherence DG score in this sample was 7.43 ± 1.94 (median = 7). Dietary changes required for increased adherence DG score included decreased consumption of red and processed meats as well as sugary foods and beverages. In addition, higher consumption of whole grains, fish, eggs, legumes, fruit, vegetables and nuts. Such dietary changes were estimated to contribute to 24% reduction in GHG emissions, but 16% increase in cropland use and 25% in freshwater use. Conclusions FBDG are useful tools for preventive actions and health promotion, helpful for guidance in health, education, and community settings. Despite limited evidence, increased adherence to SENC FBDGs can contribute to reduce GHG emissions. Analysis of impact on a variety of indicators of sustainability, comprehensive food system view and consumer involvement are needed to gain adherence to FBDGs and additional impact on sustainability. Funding Sources Non-for-profit Eroski Foundation funded the ENPE study field work in collaboration with SPRIM. Funders had no role in data analysis, selection or interpretation of results. The authors declare no competing interests.

A scalable and spatiotemporally resolved agricultural life cycle assessment of California almonds

Purpose California’s Central Valley produces more than 75% of global commercial almond supply, making the life cycle performance of almond production in California of global interest. This article describes the life cycle assessment of California almond production using a Scalable, Process-based, Agronomically Responsive Cropping System Life Cycle Assessment (SPARCS-LCA) model that includes crop responses to orchard management and modeling of California’s water supply and biomass energy infrastructure. Methods A spatially and temporally resolved LCA model was developed to reflect the regional climate, resource, and agronomic conditions across California’s Central Valley by hydrologic subregion (San Joaquin Valley, Sacramento Valley, and Tulare Lake regions). The model couples a LCA framework with region-specific data, including water supply infrastructure and economics, crop productivity response models, and dynamic co-product markets, to characterize the environmental performance of California almonds. Previous LCAs of California almond found that irrigation and management of co-products were most influential in determining life cycle CO2eq emissions and energy intensity of California almond production, and both have experienced extensive changes since previous studies due to drought and changing regulatory conditions, making them a focus of sensitivity and scenario analysis. Results and discussion Results using economic allocation show that 1 kg of hulled, brown-skin almond kernel at post-harvest facility gate causes 1.92 kg CO2eq (GWP100), 50.9 MJ energy use, and 4820 L freshwater use, with regional ranges of 2.0–2.69 kg CO2eq, 42.7–59.4 MJ, and 4540–5150 L, respectively. With a substitution approach for co-product allocation, 1 kg almond kernel results in 1.23 kg CO2eq, 18.05 MJ energy use, and 4804 L freshwater use, with regional ranges of 0.51–1.95 kg CO2eq, 3.68–36.5 MJ, and 4521–5140 L, respectively. Almond freshwater use is comparable with other nut crops in California and globally. Results showed significant variability across subregions. While the San Joaquin Valley performed best in most impact categories, the Tulare Lake region produced the lowest eutrophication impacts. Conclusion While CO2eq and energy intensity of almond production increased over previous estimates, so too did credits to the system for displacement of dairy feed. These changes result from a more comprehensive model scope and improved assumptions, as well as drought-related increases in groundwater depth and associated energy demand, and decreased utilization of biomass residues for energy recovery due to closure of bioenergy plants in California. The variation among different impact categories between subregions and over time highlight the need for spatially and temporally resolved agricultural LCA.

Relationship of the Significance of Freshwater Use to Health Protocols During the Covid-19 Pandemic in Bantul Village, Yogyakarta

The Covid-19 pandemic has an impact on the use of freshwater. Freshwater has an essential role in preventing the spread of Covid-19 related to the implementation of health protocols also Clean and Healthy Living Behavior. The important factors that influence water use are socioeconomic conditions, including income level, type of work, and education level. The spread of Covid-19 significantly occurs in urban areas. Bantul village is the center of government, economy and one of the planned areas of urban settlements in Bantul Regency. Bantul village is also a hinterland of the Yogyakarta agglomeration area. This study was conducted to determine the influence of socio-economic conditions on the significance of changes in water use during the Covid-19 pandemic to implement health protocols in Bantul village. The data was obtained through interviews with 99 respondents based on random sampling techniques. This research was conducted with quantitative methods and descriptive analysis techniques. The result shows an increase in freshwater use during the pandemic, particularly washing hands and taking a shower. The highest increase in freshwater use is in Kurahan Hamlet. While in Grujugan Hamlet, there has been no increase. The increase in freshwater use indicates the suitable implementation of health protocols.

Effect of different cleaning procedures on water use and bacterial levels in weaner pig pens

Pork is one of the most globally eaten meats and the pig production chain contributes significantly to the water footprint of livestock production. However, very little knowledge is available about the on-farm factors that influence freshwater use in the pig production chain. An experiment was conducted to quantify the effect of three different washing treatments on freshwater use, bacterial levels [(total bacterial counts; TBC), Enterobacteriaceae and Staphylococcus] and cleaning time in washing of pens for weaning pigs. Three weaner rooms were selected with each room having 10 pens and a capacity to hold up to 14 pigs each. Pigs were weaned and kept in the pens for 7 weeks. Finally, the pens were cleaned before the next batch of pigs moved in. The washing treatments used were power washing and disinfection (WASH); presoaking followed by power washing and disinfection (SOAK), and presoaking followed by detergent, power washing and disinfection (SOAK + DETER). A water meter was used to collect water use data and swab samples were taken to determine the bacterial levels. The results showed that there was no overall effect of washing treatments on water use. However, there was an effect of treatment on the washing time (p<0.01) with SOAK and SOAK+DETER reducing the washing time per pen by 2.3 minutes (14%) and 4.2 minutes (27%) compared to WASH. Nonetheless, there was an effect of sampling time (before or after washing) (p<0.001) on the levels of TBC and Staphylococcus, but no effect was seen on Enterobacteriaceae levels. Thus, the washing treatments used in this study had no effect on the water use of the pork production chain. Although there was no difference in both water use and bacterial load, from a producer perspective, presoaking and detergent use can save time and labour costs, so this would be the preferred option.

The characterization of the cow-calf, stocker and feedlot cattle industry water footprint to assess the impact of livestock water use sustainability

Perception of freshwater use varies between nations and has led to concerns of how to evaluate water use for sustainable food production. The water footprint of beef cattle (WFB) is an important metric to determine current levels of freshwater use and to set sustainability goals. However, current WFB publications provide broad WF values with inconsistent units preventing direct comparison of WFB models. The water footprint assessment (WFA) methodologies use static physio-enviro-managerial equations, rather than dynamic, which limits their ability to estimate cattle water use. This study aimed to advance current WFA methods for WFB estimation by formulating the WFA into a system dynamics methodology to adequately characterize the major phases of the beef cattle industry and provide a tool to identify high-leverage solutions for complex water use systems. Texas is one of the largest cattle producing areas in the United States, a significant water user. This geolocation is an ideal template for WFB estimation in other regions due to its diverse geography, management-cultures, climate and natural resources. The Texas Beef Water Footprint model comprised seven submodels (cattle population, growth, nutrition, forage, WFB, supply chain and regional water use; 1432 state variables). Calibration of our model replicated initial WFB values from an independent study by Chapagain and Hoekstra in 2003 (CH2003). This CH2003 v. Texas production scenarios evaluated model parameters and assumptions and estimated a 41–66% WFB variability. The current model provides an insightful tool to improve complex, unsustainable and inefficient water use systems.

Impact of Cruise Activity on Freshwater Use in the Port of Palma (Mallorca, Spain)

Lack of knowledge about freshwater use in ports of tourist destinations hinders accurate assessment of water availability and water planning. In this study, freshwater use in the Port of Palma (Spain) is analyzed by sector (commercial, mixed, navy and recreational) for the period 2007–2018. This study shows the dynamics of consumption and evaluates the effects of increased cruise tourism from 2007 to 2018 in the port. Water data supplied by the Port Authority of the Balearic Islands for each sector, together with water volumes recharged by ships, allow a detailed analysis of the water used by merchants and cruise lines. Results reveal a significant increase in freshwater withdrawals by cruise ships in the Port of Palma in the last ten years, closely related to the boom of cruise activity. Water use and recharge by cruise ships increased in both the high and low tourist seasons. Homeport cruises have a significant effect on the increase of freshwater withdrawals, as each homeport cruise ship recharged a mean volume of 628 m3 per mooring. This paper proposes a water withdrawal indicator of liters loaded per passenger at the port. Given the current lack of restriction on the number of cruise ships per day docking in the Port of Palma, cruise activity may well become a threat to water availability during drought episodes and another environmental cost to add to the already questioned cruise tourism activity of the island.

Automatic Mapping of Center Pivot Irrigation Systems from Satellite Images Using Deep Learning

The availability of freshwater is becoming a global concern. Because agricultural consumption has been increasing steadily, the mapping of irrigated areas is key for supporting the monitoring of land use and better management of available water resources. In this paper, we propose a method to automatically detect and map center pivot irrigation systems using U-Net, an image segmentation convolutional neural network architecture, applied to a constellation of PlanetScope images from the Cerrado biome of Brazil. Our objective is to provide a fast and accurate alternative to map center pivot irrigation systems with very high spatial and temporal resolution imagery. We implemented a modified U-Net architecture using the TensorFlow library and trained it on the Google cloud platform with a dataset built from more than 42,000 very high spatial resolution PlanetScope images acquired between August 2017 and November 2018. The U-Net implementation achieved a precision of 99% and a recall of 88% to detect and map center pivot irrigation systems in our study area. This method, proposed to detect and map center pivot irrigation systems, has the potential to be scaled to larger areas and improve the monitoring of freshwater use by agricultural activities.