Improving Water Efficiency in the Beverage Industry With the Internet of Things

The food and beverage industry is one of the most water-intensive industries, with water required for various processes (e.g., washing, cooking, cleaning) at almost every stage of the production, as well as being a key constituent in many food and drink products. Therefore, a real-time efficient water management strategy is imperative, and the novel internet of things (IoT)-based technologies can be of significant help in developing it. This chapter presents the architecture of an IoT-based water-monitoring system followed by the demonstration of a case study of a beverage factory wherein the monitoring system helped understand the detailed water usage as well as finding solutions and addressing overconsumption of water during the manufacturing processes. The successful deployment of IoT helped reduce the annual water consumption by 6.7%, monitor water usage in real-time, and improve it.

Investigation on spatial variability and influencing factors of drinking water iodine in Xinjiang, China

Background and objectives Xinjiang is one of the areas in China with extremely severe iodine deficiency. The health of Xinjiang residents has been endangered for a long time. In order to provide reasonable suggestions for scientific iodine supplementation and improve the health and living standards of the people in Xinjiang, it is necessary to understand the spatial distribution of iodine content in drinking water and explore the influencing factors of spatial heterogeneity of water iodine content distribution. Methods The data of iodine in drinking water arrived from the annual water iodine survey in Xinjiang in 2017. The distribution of iodine content in drinking water in Xinjiang is described from three perspectives: sampling points, districts/counties, and townships/streets. ArcGIS was used for spatial auto-correlation analysis, mapping the distribution of iodine content in drinking water and visualizing the distribution of Geographically Weighted Regression (GWR) model parameter. Kriging method is used to predict the iodine content in water at non-sampling points. GWR software was used to build GWR model in order to find the factors affecting the distribution of iodine content in drinking water. Results There are 3293 sampling points in Xinjiang. The iodine content of drinking water ranges from 0 to 128 μg/L, the median is 4.15 μg/L. The iodine content in 78.6% of total sampling points are less than 10 μg/L, and only that in the 3.4% are more than 40 μg/L. Among 1054 towns’ water samples in Xinjiang, 88.9% of the samples’ water iodine content is less than 10 μg/L. Among the 94 studied areas, the median iodine content in drinking water in 87 areas was less than 10 μg/L, those values in 7 areas were between 10–40 μg/L, and the distribution of water iodine content in Xinjiang shows clustered. The GWR model established had found that the effects of soil type and precipitation on the distribution of iodine content in drinking water were statistically significant. Conclusions The iodine content of drinking water in Xinjiang is generally low, but there are also some areas which their drinking water has high iodine content. Soil type and precipitation are the factors affecting the distribution of drinking water iodine content, and are statistically significant (P<0.05).

Variability of thermohaline regime of see water of the Gulf of Mexico in 2005-2017

The Gulf of Mexico is a large, productive, marine and coastal ecosystem providing the coastal residents and neighbouring regions with goods and services. The Gulf of Mexico's water area plays a significant role in shaping the climate across the coastal zone and the thermal state of the region's water also has a major impact on development of atmospheric processes over the Atlantic and Europe. Long-term climate variability throughout the Gulf of Mexico may affect both the strength of the Gulf Stream and heat transfer patterns within the ocean and the economic activity and environmental stability of the entire Northwest Atlantic Region. This work aims at determining the characteristics of variability of temperature regime and salinity of the Gulf of Mexico over recent decades. The study was conducted based on the Gulf of Mexico Regional Climatology (GOM RC) data, version 2, available at the website of the NOAA's National Centers for Environmental Information (NCEI). It analyzes the temperature and salinity values at different depths for the period of 2005-2017. According to the analysis, over 2005-2017 the spatial distribution of the average annual water temperature on the Gulf of Mexico's surface demonstrates its decrease from south to north. Its highest value is observed next to the northwestern coast of Cuba and along the coastal area of the Bay of Campeche, and the lowest temperature is observed at Apalachee Bay located in the northeastern part of the Gulf of Mexico. Though significant horizontal temperature gradients are observed in winter, during the warm period the temperature field is more homogeneous. The minimum average monthly water temperature on the surface is observed in January, the maximum one – in September. The most distinct seasonal changes in temperature are observed in the water of the northern part of the Gulf of Mexico next to the United States' coast. The distribution of average annual salinity of the most of the Gulf of Mexico is homogeneous with the exception of its northern part, especially in the area where the Mississippi River water flows into it, where salinity decreases sharply. Graphs of water temperature and salinity distribution at different depths across different areas of the gulf were constructed in order to determine the water stratification.

Frequencies of drought at Ranchi regions, Jharkhand

Studies of water balance have been carried out for Ranchi taking 35 years (1970-2004) of climate data. Ranchi has annual water need of 1754 mm, rainfall of 1460 mm, actual evapotranspiration (AE) of 860 mm, water surplus (WS) of 600 mm and water deficit (WD) of 894 mm. The aridity index values were analyzed to assess the frequency of drought experienced of this region. The study reveals that during the above period, Ranchi has experienced 11 percent of large drought and severe drought, but only 3 per cent disastrous droughts in 35 years. Moderate drought category is observed to be most common with 23 per cent probability. Analyses of periods will contagious drought indicate that during the five year period 1980-84 and 1995-99, moderate, large and severe droughts were experienced.

Hydrological System of the Plitvice Lakes—Trends and Changes in Water Levels, Inflows, and Losses

The Plitvice Lakes National Park is inscribed on UNESCO’s World Heritage List. The lake system is composed of 16 cascading lakes of different sizes separated by tufa barriers, which are the park’s key phenomenon. The lakes are characterized by highly diverse trends of the characteristic hydrological indicators—mean annual water levels, discharges, and tufa barrier growth. The analyses carried out in this paper identified that in the period before the early 1990s, Kozjak Lake had a trend of decreasing discharges, together with a trend of increasing water levels and growing tufa barriers. In contrast to this, in the period after 2001, a trend of increasing discharges was recorded, as well as a trend of decreasing water levels and decreasing tufa barriers. A potential cause of the barriers decreasing in size were the extremely high discharges during the last decade, which resulted in increased erosion of the tufa barriers. Losses of water due to the sinking from the lake system as well as the upper Korana course were confirmed, and it was identified that during the analyzed period the losses had not changed significantly. It was determined that the losses of water from Kozjak Lake occurred during low-water periods; however, they depended not only on the quantity of water flowing through the lakes but also on the hydrological conditions underground. The analyses carried out and the methodological procedures used in the analyzed area of the Plitvice Lakes are useful examples for the performance of analyses at similar lakes in karst formed by tufa deposition processes.

Selection of Water-Saving Plants and Annual Water Consumption Estimation for Garden Green Spaces in Beijing

Currently, the number of urban garden green spaces (GGSs) being constructed in Beijing is increasing, and their high water resource demands contradict the severe water shortage situation in Beijing that is restricting urban construction and economic development. This has created an urgent need to build water-saving GGSs. This study analyzed and compared the daily/annual water consumption of 79 common plants in Beijing, and low-water-consumption (LWC) trees, shrubs and herbs were selected; additionally, the total annual water consumption (TAWC) of all plants in the built-up areas of all 16 districts in Beijing was calculated according to the result of the eighth general survey of landscaping resources in Beijing. The results are as follows: (1) fifteen LWC tree species were selected from among 25 species, and the average daily water consumption (DWC) was <1.09 kg·m−2; (2) nineteen LWC shrubs were selected from among 35 shrubs, and the average DWC was <1.17 kg·m−2; (3) eleven LWC herbs were selected from among 19 herbs, and the AWC was <460.3 kg·m−2; (4) the TAWC of all trees, shrubs and herb plants in the Beijing GGSs was 1.104 × 109, 0.139 × 109, and 0.16 × 109 m3, respectively. Based on the above results, it was estimated that the TAWC of all plants in the built-up areas of all 16 districts in Beijing is approximately 1.403 × 109 m3. These findings provide a better understanding of the water consumption of GGS plants in cities in semiarid and semihumid climates and can be used to help select LWC greening plants that can reduce water consumption when expanding green areas in cities.

Variability of potential evapotranspiration and moisture conditions in Srikakulam district of Andhra Pradesh

In the present study, evapotranspiration and moisture adequate index for the 37 mandals of the Srikakulam district for the year 2018 has been estimated. The PET values were very high in the summer season of all the mandals than in the other seasons. The normal PET values were lower than that of the actual PET values showing location specific and better estimation characteristics. This estimation of location-specific PET can be helpful for the drought classification and water management planning within the district. Moisture adequate index of all the mandals has indicated that the district as a whole has a humid/temperate climate; but within the district, mandals report different conditions. This makes it a more relevant tool for drought, microclimatic classification and annual water planning for sustainable agriculture.

Improving Water Efficiency in a Municipal Indoor Swimming-Pool Complex: A Case Study

This study aimed to determine the water demand of a municipal swimming pool complex to propose water use efficiency measures. Concomitantly, the possibility of recycling and reusing the water from filter backwashing was evaluated. The pools consumed 25.6% of water, the filter backwashing 24.5%, and the showers 34.7%. Despite the current impossibility of reducing water consumption in pools and filter backwashing, it is feasible to promote more efficient use of water through reducing water consumption by adopting simple water-saving initiatives for showers, taps, and flushing cisterns. These were organized into three distinct scenarios: (a) flushing cistern volume adjustment and the replacement of washbasin and kitchen taps; (b) flushing cistern volume adjustment and shower replacement and (c) flushing cistern volume adjustment, shower, washbasin, and kitchen taps replacement. Under scenarios 1, 2, and 3, the water consumption reduction was 8.0, 13.2, and 20.4%, respectively. The initial investment for scenario 1 was €2290.5, €859.0 for scenario 2 and €3149.5 for scenario 3; the annual water bill reduction was €7115.4, €11,518.1, and €17,655.9, respectively. Therefore, the turnover of the investment was four (scenario 1), one (scenario 2), and three months (scenario 3). The filter washings attained the required standard for irrigation after being subjected to 15 h of sedimentation.

Climate and soil effect on oil palm (Elaeis guineensis Jacq.) yield

Objective: To determine potential and water-limited yields in oil palm producing areas in the State of Tabasco, México. Design/Methodology/Approach: The ERIC III v. 3.2 database (IMTA, 2009) was used to select climatological stations with daily precipitation and maximum and minimum temperature records, going back to more than 20 years. The methodology proposed by the FAO and improved by Fischer et al. (2012) was used to estimate the potential yield. The equation reported by Ruiz-Álvarez et al. (2012) was used to estimate the annual water deficit from the climatic water balance. Results: The average potential yield of oil palm with a high level of inputs varies from 35.8 to 40.6 t ha-1 of fresh fruit bunches. The average water-limited yield can vary from 15.6 to 23.5 t ha-1 in plantations of at least 8 years of age, under rainfed conditions. The reduction in the maximum average attainable yield was the result of 19.2-49.5% soil moisture deficits. Study limitations/Implications: In order to determine their impact on potential and water-limited yields, climate change horizons must be included in future studies; this would enable researchers to establish the future theoretical economic profitability of the crop. Findings/Conclusions: The analysis between the yields indicates that —if the gap between the current yields and water-limited yields is closed— output and percentage would be 6.5-14.4 t ha-1 and 72.8-129% higher than the potential yield.

Leakage analysis of campus water supply system based on MLP neural network

Water supply system is an important part of campus public facilities, and the water supply pipeline will leak, not only increase the cost of water supply, but also cause water waste. This paper collects water consumption data of water meters at all levels in a school’s water supply system, establishes MLP multilayer perceptron neural network model, determines the water leakage rate according to the fluctuation of predicted value and actual value, so as to analyze the leakage situation of each school’s water supply system. When the fluctuation between the actual and predicted water consumption exceeds a certain threshold, water leakage occurs on that day. Through solving the model, the following conclusions are finally drawn: (1) the annual water leakage rate of the school is 10.74%, and the water leakage is 29131.418L. (2) The water leakage rate in the first quarter is the highest, and the water leakage in the second quarter is the highest.(3) The school aquaculture area is the most serious leakage phenomenon, and the maximum water leakage rate of each water meter node is more than 10%.