Weather Reporting System Using IoT: Benefits & Use Cases

case study weather monitoring system

Imagine a world where the weather is no longer an unpredictable force that catches us off guard. This reality is already here, owing to IoT based weather monitoring systems . How do they work, which industries do they serve, and what benefits do they offer?

This article has you covered as we dive into these and even more questions. Learn how IoT technology allows businesses to adapt to changing weather conditions and optimize performance with WebbyLab, an experienced IoT development vendor .

We’ll navigate you through the applications of weather monitoring system using IoT and explain the importance of such ventures. Drawing from our weather reporting expertise in projects like 2Smart Standalone , we’re here to elevate your business operations through the Internet of Things .

 Weather forecasting scenario in the 2Smart Cloud platform.

Weather forecasting scenario in the 2Smart Cloud platform.

The Role of IoT in Weather Reporting Systems

Traditional weather monitoring systems are getting outdated. They’re often prone to errors and inaccurate predictions — and these factors can damage your business. But with IoT in place, these systems transform dramatically. Here’s how.

  • Traditional weather reporting methods, while informative, often suffer from delays in data collection and transfer. IoT, in turn, gathers data from sensors in real time.
  • IoT takes forecasting to the next level when combined with internet-connected weather stations. It can predict the weather accurately and quickly for different geographic locations.
  • IoT-based weather monitoring systems seamlessly integrate data from a multitude of sources. Weather sensors , satellite imagery, weather stations, drones, and even personal devices are just some examples.
  • The Internet of Things brings precision to weather insights. Businesses can collect data from specific places, e.g., by improving crop watering based on soil moisture or changing flight paths to avoid turbulence.

Check how we build custom solutions for clients

Benefits of Weather Reporting System Using IoT

With the Internet of Things, weather monitoring systems have stepped up their game, becoming more accurate, consistent, and quicker in operation. Now, that sounds great, but what does this tech actually offer businesses? Here are the main benefits:

  • Real-time data collection. Thanks to IoT devices and sensors, businesses get weather updates from all sorts of locations right when they need them.
  • Higher accuracy. A weather monitoring system using IoT gathers data from numerous sources, providing a detailed picture of what’s happening with the weather.
  • Wider coverage. Traditional weather monitoring systems usually check conditions at just a few weather stations, leaving out other areas. When IoT technology steps in, businesses can cover more places, even the most distant ones.
  • Predictive analytics. IoT-powered weather reporting systems use historical data and current trends to tell businesses what’s coming. That’s how companies can adjust their operations before any weather-related challenges appear.
  • Reduced response time. Every second counts when the industry is about making fast decisions — aerospace or emergency services. That’s where IoT weather monitoring comes in as a solution , offering real-time insights for rapid response times.
  • Cost-effectiveness. A weather reporting system using IoT allows companies to optimize resource usage and reduce waste. For example, agriculture businesses can leverage weather forecasts to adjust their irrigation and crop protection measures.
  • Increased safety. Industries prone to weather-related risks, like construction or transportation, enjoy the advantages of IoT-based automatic weather stations . These businesses can plan their activities more safely with a minimum of accidents and disruptions.

Benefits of Weather Reporting System Using IoT

Industries That Benefit from Weather Monitoring System Using IoT

Now that you know the main benefits that IoT systems bring to weather monitoring, let’s dive into the industries that reap these advantages. Here are several examples:

Manufacturing

Manufacturing processes are intricately linked to the weather. IoT technology ensures businesses time their production just right, coordinating with the best weather conditions. Whether it’s managing temperature-sensitive materials or adjusting supply chain logistics based on weather forecasts, manufacturing gains efficiency and precision. 

Flying safely and smoothly is the core of aviation, and the weather here is a big player. Thanks to IoT-based weather reporting, airlines and air traffic control get real-time updates on turbulence, lightning, and visibility — all necessary to make flights safer.

Agriculture

Imagine having a trusted partner in farming decisions — that’s what IoT weather insights are all about. When it’s time for planting, watering, or dealing with pests, these become essential. Farmers can get information on rainfall, temperature, and soil moisture with IoT to make smarter choices for their fields.

IoT based weather monitoring systems are handy in the automotive industry. When the weather gets worse and the roads get slippery, the Internet of Things may help. It assists in developing advanced driver assistance systems and fine-tuning cruise control based on visibility, ultimately adapting vehicles for safer driving.

Warehouse Management

Inventory management and logistics greatly depend on the weather. And that’s where IoT weather stations come into play. They help warehouses predict when severe weather might influence their goods and adjust storage conditions accordingly. The same goes for shipping schedules.

The energy sector, whether using renewable or non-renewable sources, is influenced by weather patterns. Using IoT energy management systems, this industry can predict when people will need more or less energy, ultimately optimizing resource allocation and enhancing grid stability.

Weather conditions are crucial for insurance companies. It’s a common instance in the US, where numerous insurance categories exist — from property protection in case of floods and hurricanes to evaluating risks for energy facilities, agriculture, health, and more. With IoT, insurers can assess risks and price their services properly.

Industries That Benefit from Weather Monitoring System Using IoT

Types of Sensors Used for Weather Monitoring

When learning how to develop IoT-based weather reporting system and considering deploying one, the sensors you choose depend on what you’re aiming to explore. There are various gadgets, each with its own particular purpose. Look at how different sensors work for various scenarios:

Boosting Crop Yields

If farmers are diving into smart agriculture, they need information on temperature, humidity, soil moisture, and rainfall. Here are the sensors used in such a case:

  • Temperature sensor
  • Humidity sensor or hygrometer
  • Soil moisture sensor
  • Rain sensor

Increasing Flight Safety

Think about pilots preparing for a smooth flight. They need to know all about wind speed, direction, atmospheric pressure, and even visibility. Check out the sensors suitable for this use case:

  • Barometric sensor
  • Visibility sensor

In a nutshell, the sensors you pick for weather monitoring depend on what you’re diving into.

Reasons to Invest in an IoT-Based Weather Reporting System

Whether in healthcare, agriculture, aviation, transportation, automation , warehouses, or laboratories, the right weather information is your compass. And here are the primary reasons to invest in a weather monitoring system using IoT :

  • Continuous climate monitoring. An IoT-based weather reporting system tracks all environmental changes, whether small or big. It means you always know what’s happening and can prepare for unfavorable weather beforehand.
  • Preventing losses. The IoT platform for weather monitoring serves as your early warning signal. It allows you to minimize damage and secure your business.
  • Avoiding business disruptions. With IoT in place, you don’t have to shut down your business even if the weather gets rough since you’re ready to adapt. You can adjust schedules, reroute logistics, and ensure smooth operations, leveraging predictive analytics and real-time insights.

WebbyLab Experience in Weather Monitoring Using IoT

WebbyLab has a profound background in leveraging the Internet of Things for weather reporting. Here’s our case study on IoT system for weather monitoring :

Leveraging Ready-Made Solutions

We understand that building custom weather stations from scratch might seem the way to go, but we’ve taken a different route. Recognizing the extensive resources and time invested in refining and testing existing solutions, we’ve opted to work with these well-established options. This decision lets us focus on what truly matters — extracting accurate and reliable weather data.

Using Modern Devices

In today’s market, especially in industrial contexts, weather station devices are often designed for large ecosystems. Their software isn’t necessarily tailored to specific clouds or applications. To bridge this gap, we employ separate gateways. These gateways allow us to run our software, connect physically to devices through interfaces like RS-485, RS-232, One Wire, or Ethernet, and process the collected data. Owing to that, we can integrate weather insights into our solutions easily.

Integrating Weather Monitoring into 2Smart Standalone and 2Smart Cloud

Ease of access and usability are critical for us. That’s why integrating weather data into our 2Smart Standalone platform has been a priority. We’ve established integrations with virtual weather platforms like OpenWeather and YahooWeather. With these in place, users can create virtual devices effortlessly and receive real-time weather data for their locations.

The virtual weather stations in the 2Smart Standalone platform.

The virtual weather stations in the 2Smart Standalone platform.

The same goes for our 2Smart Cloud platform , where anyone can set up a weather station and access weather information via our mobile application.

The weather station in the 2Smart Cloud platform.

The weather station in the 2Smart Cloud platform.

Tailoring Weather Insights for Specific Needs

We’ve also tailored weather insights to specific applications. Our smart greenhouse solution, built on the 2Smart Standalone platform , incorporates a unique sensor-based weather forecasting scenario. Users can easily integrate their real-time pressure and wind direction data. Our algorithm then calculates the nearest weather forecast, enhancing precision for greenhouse operations.

Get Weather Insights with WebbyLab

If you’re tired of Mother Nature’s surprises and want to protect your business from weather-related disruptions, consider using an IoT based weather monitoring system . This solution allows for real-time data collection and unparalleled forecasting accuracy, ultimately optimizing your processes.

Ready to feel the difference between traditional weather monitoring and IIoT-based monitoring system ? Contact WebbyLab experts . With our profound experience in IoT projects , we’ll elevate your business with precise weather forecasting solutions.

Learn more about how we engage and what our experts can do for your business

Written by:

Kostiantyn Oliynyk

Kostiantyn Oliynyk

Head of IoT at Webbylab

With a robust academic background in Telecommunication Systems Engineering, I apply my knowledge to lead innovations in the IoT domain. Starting as the first team member in the newly formed IoT department at WebbyLab, I've spearheaded its growth, fostering the expansion into embedded and hardware development alongside our core software projects. My dedication lies in pushing the boundaries of IoT technology, fostering a culture of innovation and excellence that profoundly impacts our clients' operational success.

It uses sensors and devices that gather weather data, connect through messaging protocols , and transmit the information to a central hub or a cloud platform. The collected data is then analyzed to get up-to-date weather insights.

A weather monitoring system using Arduino can observe various parameters: temperature, humidity, air pressure, wind speed, wind direction, rainfall, soil moisture, UV radiation, and more.

Businesses can implement different security measures to protect their IoT weather monitoring systems. Some examples include encryption, robust communication protocols, authentication mechanisms, and adherence to the latest IoT standards .

Users typically get weather information through mobile apps, web interfaces, and dashboards.

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IoT Based Weather Monitoring System For Micro-Climate Forecasting

Jan 1, 2022 | Blog , IoT Based Weather Monitoring System

IoT Based Weather Monitoring System For Micro-Climate Forecasting

Forecasting the weather has come a long way from where it once used to be. Not too long ago, the only way to find out about the day’s weather was through local news channels, radio stations or through aviation weather services. Now, it’s just one click away—all you have to do is check your smartphone.

Environmental monitoring has become incredibly important, given people’s need to be aware of the latest weather conditions wherever they go but more importantly, whatever their profession. Technology is evolving at a dynamic rate, and weather stations need to adapt in order to keep pace with consumer and commercial demand for accuracy. And one of the most important factors that must be considered are microclimates.

What are microclimates?

Weather is not always forecast accurately. One of the biggest drawbacks of the current weather forecasting system is that it is done on a grid. To produce day-to-day forecasts, global model grid lengths range between 9 and 13 km in the smallest sections of the grid all the way up to hundreds of kilometers, leading to inaccurate and inconsistent reports.

These grid systems can not consider microclimates , which are much smaller pockets of land with distinct features that affect temperature, precipitation, and wind.

Some common microclimates include:

  • High-elevation areas
  • Coastal regions
  • Large forests
  • Urban landscapes

To improve weather forecasts in a very specific location, it becomes important to understand and identify microclimate conditions. Whether it’s the topography or construction elements affecting different weather factors, accurately collecting data is essential for microclimates around the world.

So how does a microclimate form? It depends on different topographical features that would affect normal climate and weather patterns. For example, the contrast in topographies can affect airflow, ambient temperature, and cloud formation. The particular soil composition of land can have an effect on its rate of evaporation. Heavy vegetation on a specific area can affect airflow as well as moisture levels; this can be natural or manmade.

Microclimates aren’t limited to differences in nature; unnatural additions to a particular landscape can also create them. Urban centers generate high amounts of heat and smog, which can affect low- and high-level winds. Several acres of parkland in the middle of a city can cause multiple microclimates to emerge in a very small geographic area as well. The same principles apply to agriculture as well; differences in crops, irrigation practices, etc. can affect the microclimate as well.

Due to the very specific characteristics of locations with microclimates, it becomes difficult for a traditional grid-based monitoring system to consider different environmental factors. For example, certain variances can have a significant impact on predicting the path of a hurricane or a snowstorm. For someone who lives in or near such microclimates, the forecast as seen on TV may not be accurate.

In addition, conventional grid-based weather monitoring systems are bulky, expensive, and require constant surveillance . Data is transferred manually, which increases the margin for error and runs up expenses.

Here’s where an IoT-based weather monitoring system steps in.

What is the Internet of Things (IoT)?

So what exactly is the “Internet of Things” (IoT)? Simply put, it is a technology that looks to connect all kinds of devices and sensors to share the data obtained from various locations. Today, IoT devices are used across all industries, processing and analyzing data to coordinate traffic signaling, ensure industrial safety, monitor medical applications, or even regulate the temperature inside a house.

The Internet of Things offers a wide range of connected devices with different protocols in order to achieve complete machine-to-machine interaction. It is viewed as one of the biggest innovations in the data industry. This system connects everything to the internet, with the aim of exchanging data to trigger corresponding actions when needed.

IoT envisions a near-future where regular day-to-day objects will be fitted with microcontrollers and convention stacks that will make the devices ready to talk to each other. It looks to recognize, find, follow, observe, and oversee data across many different gadgets. The end goal of IoT is to make the internet more immersive and helpful.

The technology is an advanced solution for connecting different devices to the internet (in this case, the factors affecting the micro-climate of a region) and connecting them within a network. With the use of sensors and automotive electronic equipment, an advanced system can be developed to keep track of the many different characteristics of the climate, such as temperature, humidity, wind speed and direction, rainfall, and more. The system can then analyze all collated data and generate accurate microclimate forecasts that can be displayed in real-time on a digital screen ( this is part of what we are doing for agriculture here at Benchmark Labs ).

An IoT-based weather monitoring system connected to data centers could also keep track of past information, either on an hourly or a daily basis. The sensor data can be analyzed and plotted in graphs and statistics to further improve forecasting.

What does an IoT-based weather monitoring system entail?

IoT-based weather monitoring technology has been growing very quickly, and it has already bypassed the features and functionalities of conventional systems in many ways. Having been applied in the field of remote monitoring and advanced analytics, the technology is revolutionizing different ventures while offering a range of benefits.

Innovations in weather monitoring have focused on controlling and monitoring different weather conditions. IoT devices help measure the physical parameters of a certain location and upload them in real-time to cloud storage, where the data can be analyzed immediately.

These systems make climate monitoring in difficult geographical terrains possible. The manpower required for accurate microclimate forecasts is significantly reduced, and there is no longer any need to physically go into inhospitable environments just to get accurate measurements. Sensor devices placed in particular locations can do all the work to detect current climate details, such as rainfall, wind speed, humidity, soil moisture, CO2 levels, and other data needed for forecasting.

Going a step further, when one connects the weather station to the internet, IoT can be used much more extensively in predicting and disseminating accurate weather data in a particular location. This information can then be made available anywhere in the world.

Wireless weather monitoring significantly impacts businesses across different industries. Data received from sensors can be collected by microcontrollers and dispatched where it is needed. When leveraging IoT technology, other systems such as home automation, wireless sensor networks, and control systems can work smarter and more efficiently.

Accurate and timely microclimate forecasting using IoT plays a very important role in the field of agriculture, as it can provide farmers and landowners specific weather information that will dictate their daily operations. This technology can also make it possible to safely monitor extreme weather conditions in inhospitable environments.

Here are some of the advantages of using an IoT-based weather monitoring system when it comes to microclimate forecasting:

  • The process is fully automated
  • Does not require human attention
  • Prior alerts of accurate weather conditions
  • Low cost and efforts in the system
  • High accuracy
  • Self-protection
  • A smart way to monitor the environment
  • Efficient & time-saving

What’s next?

Understanding the conditions in a microclimate can help meteorologists and locals alike receive an accurate and specific weather forecast. Given the many factors that affect temperature, precipitation, and wind, accurate data collection and real-time analysis are more critical than ever.

IoT combined with the traditional grid forecast provides an efficient and low-cost solution for continuous monitoring of the environment. These sensor devices and robust systems can easily collect data and create a more accurate picture of a microclimate.

If you would like to learn more about Benchmark Labs from our team and sign up for a trial, go to our sign-up page .

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IoT based weather monitoring system

IoT Based Weather Monitoring System Using Arduino

In this post we are going to construct an IoT based weather monitor system using Arduino which can report us weather status like atmospheric pressure, temperature, humidity, air quality, light intensity etc. of your locality in real time and the data from the sensors are logged to an IoT cloud service called Thingspeak for monitoring and analysis.

We will see:

  • What is IoT based weather monitoring system?
  • Why we need an IoT based weather monitoring system.
  • Types of sensors involved in weather monitoring.
  • Block diagram of IoT based weather monitoring system.
  • Circuit diagram and description.
  • How to setup your Thingspeak account?
  • Program code for Arduino and ESP8266.
  • How to upload data to generic ESP8266?
  • Prototype images.
  • How to operate the circuit?

What is an IoT based weather monitoring system?

It is a system that involves in acquiring weather and environment data using advanced electronic sensors and sending them to a web server via internet for real time weather monitoring and storage of data for future analysis and study.  

Why we need an IoT based weather monitoring system?

  • Ease of monitoring your local weather conditions in real time from anywhere in the world.
  • For storing weather and environment data for short and long term for studying weather pattern changes and to understand how human induced climate change affected your local weather.
  • Easy deployment of the setup for monitoring local atmospheric conditions and microclimates for weather forecasting and prediction.

Types of sensors involved in weather monitoring:

We can find wide spectrum of electronic sensors involved in weather monitoring system depending on the kind of application.

For example:

Farmers need to know the temperature, relative humidity, soil moisture, rain fall etc. to enhance their crop production and the following type of sensors are utilized to obtain the data:

  • Temperature sensor.
  • Humidity / hygrometer sensor.
  • Soil moisture sensor.
  • Rain sensor etc.

For an airplane pilot he/she needs to know wind speed, wind direction, atmospheric pressure, precipitation, visibility etc. before they takeoff and they use the following sensors:

  • Barometric sensor – for measuring atmospheric pressure.
  • Anemometer – for measuring wind speed.
  • Rain sensor.
  • Visibility sensor – for measuring visibility during snow, rain, storm etc.

In conclusion, the sensors used for monitoring weather depends on the type application we going to deploy for.

Block diagram of IoT based weather monitoring system:

Block diagram - IoT based weather monitoring system

We are going to develop the weather monitoring system using the above illustrated blocks. The brain of the project is an Arduino board and the surrounding blocks are digital and analog sensors for acquiring local weather and environment data.

A generic ESP8266 is used for interfacing the circuit setup with internet via 2.4 GHz Wi-Fi band. The ESP8266 sends the sensor data to a cloud server where the data gets updated in real time and also gets stored for future analysis. We are utilizing a 16 x 2 LCD display to showcase the sensor data, so that we can observe real-time data locally.

Full circuit diagram for IoT based weather monitoring system:

IoT basIoT based weather monitoring system using Arduinod weather moniotring system using Arduino

The above circuit consists of the following modules:

  • 5V / 3.3V Power supply regulator.
  • Arduino Uno.
  • 16 x 2 display with I2C adapter module.
  • DHT11 temperature & humidity sensor.
  • MQ-135 sensor air quality sensor.
  • BMP180 – Barometric sensor.
  • Light depend resistor (LDR).
  • Generic ESP8266 Wi-Fi module.

Now, let’s explore what each of the module does and how it is interfaced with other modules.

Power supply 5V and 3.3V:

Power supply 5V/3.3V

The above illustrated module takes 9V to 12V DC supply from a wall adapter and converts to 5V and 3.3V for providing power to Arduino board and sensors.

There are multiple 5V and 3.3V supply outputs in this module and you need to connect 5V supply to 5V sensor modules and 3.3V supply to 3.3V sensor modules. Mismatching will lead to malfunction of the respective modules / sensors.   

A button is provided on the module to turn ON/OFF the 5V / 3.3V output. A green LED indicates that the module is powered ON. There is also a USB power output but we won’t be using it for this project.

16 x 2 LCD display:

I2C LCD display

We are utilizing a 16 x 2 LCD display to showcase sensor data locally and it can display 16 alphanumeric characters in 2 rows.

An I2C display module is used in this project to reduce the number of wires that connect from microcontroller to LCD display to four; otherwise we need to connect 16 wires.

I2C display module operates on I2C bus and has the following four pins:

  • SDA – Serial data.
  • SCL – Serial clock.
  • GND – ground.

The Vcc pin connects to 5V of the power supply module and GND connects to GND of the supply, the SDA connects to A4 of Arduino and SCL connects to A5.

The I2C module has backlight control, by removing the jumper we can turn off the backlight and vice-versa. You can adjust the display contrast by rotating the potentiometer (blue color on the module) using a small screw driver.

DHT11 temperature and humidity module:

DHT11 Sensor

DHT11 is a digital sensor responsible for collecting temperature and humidity data from your surroundings. It has three terminals namely:

Vcc connects to 5V supply, GND connects to GND and data pin connects to A0 of Arduino.

Note: The pin diagram for DHT11 module could differ from manufacture to manufacture and it is recommended to take a good look at your module to see which pins are Vcc, GND and Data before you apply power to the circuit.

BMP180 barometric sensor:

BMP180 barometric sensor

The above illustrated module is a barometric sensor which is capable of measuring atmospheric data; it can give out data like, atmospheric pressure at ground level, atmospheric pressure at sea level and altitude.

We will be only extracting atmospheric pressure data at ground and sea level to display it on the LCD, but we will be sending only the atmospheric pressure data at ground level to Thingspeak server, which is the relevant data for your locality.

It has the following pins:

  • Vcc – 3.3V.

Care must be taken while connecting the supply to this module as it operates on 3.3V DC and 5V will kill the module. It operates on I2C bus, same as I2C display adapter module.

MQ-135 air quality sensor module:

case study weather monitoring system

MQ-135 is an analog air quality sensor which takes air samples from your surroundings and gives out an analog voltage at its output terminal. MQ-135 can detect the following gases:

  • Smoke, CO2 etc.

The operating voltage of MQ-135 is 5V and consumes around 160mA, the sensor has built-in heater for heating the sensor for its normal operation and if the sensor is exposed to strong wind we may get incorrect readings. The sensor takes typically around 3 to 5 minutes to reach optimum temperature depending on surrounding air flow.

The sensor has good sensitivity to detect the above mentioned gases, but the disadvantage is it cannot differentiate which gas or gases have been detected.

Generic ESP8266 module:

Genric ESP8266

The above illustrated module is called generic ESP8266 which is responsible for connecting the weather monitoring system to internet. This module is inserted on a breakout board adapter so that ESP8266 can be interfaced on a breadboard.

Pin diagram of ESP8266:

Pin Diagram of ESP8266

ESP8266 is not a just another ordinary module, it has a full-fledged 32-bit microcontroller which requires a program code to function. We will be using a programmer to upload the code to this ESP8266 module which we will see in the later part of this article. It operates on 3.3V and communicates on serial interface with Arduino.

Light depend resistor – LDR:

Photoresistor

LDR is responsible for collecting data about the intensity of light at your surroundings and it is a passive analog sensor.

The LDR is essentially a resistor that is sensitive to the light, when higher intensity light falls on the photosensitive surface its resistance drops and when less light is received its resistance increases.

In other words, the resistance is inversely proportional to the intensity of the light on the photosensitive surface of LDR. 

This concludes all the modules and sensors used in the circuit setup.

Program code for Arduino:              

I2C LCD library : Click here

DHT library : Click here

BMP180 library : Click here

Program code for Generic ESP8266

Download Thingspeak Library : Click here

Insert your Wi-Fi credentials here the code:

Insert your Thingspeak credentials here:

How to upload code to generic ESP8266 module:

  • You need to download ESP8266 board package.
  • You need an ESP8266 programmer board.

1) How to download ESP8266 board package?

  • Copy this link:  http://arduino.esp8266.com/stable/package_esp8266com_index.json
  • Now open Arduino IDE and click on  File > Preferences .
  • A window will open like this:

Preferences

  • Paste the URL on the box and click “OK”.
  • Now go to  Tools > Board > Boards Manager.

 A window will popup:

boards manager

  • Type “ESP8266” on the box as shown and you will get installation option, select the  latest version  and click install.
  • Now the IDE will download the necessary packages and this could take more than 5 minute to complete.
  • Now go to  Tools > Board > ESP8266 boards > select “Generic ESP8266”.
  • Now, copy the given ESP8266 program code and paste it on to Arduino IDE software.
  • Now press compile button (Green tick button). The compilation of code may take more than couple of minutes so be patient. If the compilation failed please check whether have you selected the “Generic ESP8266 Module” in the board option or not.
  • After successful compilation of code, now it’s time to upload the code to ESP8266.

2) USB ESP8266 Programmer:

ESP8266 Programmer

The above illustrated USB device is used for programming the generic ESP8266 module.

Please note that two pins on the programmer must be shorted before you upload the code, otherwise you will get errors while uploading.

Now insert the ESP8266 on the programmer and plug it to your PC’s USB port, like this and click upload:

ESP8266 Programmer

Once you successfully uploaded the code, you will the below info on your IDE:

case study weather monitoring system

Now, you may insert the ESP8266 on your main circuit setup.

How to setup your Thingspeak account for receiving data?

  • To send sensor data to Thingspeak, you need a Thingspeak account and you can sign-up here .
  • Create a new channel and do the following to your Thingspeak channel:

Thingspeak channel settings

  • Scroll down and press save.
  • Please take note of your channel ID and you need to copy and insert the ID to the ESP8266 code.
  • Now go to API key tab and you will see “write API” and “read API” keys. Write API key is a secret code for writing data to your Thingspeak channel.

case study weather monitoring system

  • You need copy and paste the write API key to the ESP8266 code.

Prototype images of IoT based weather monitoring system:

IoT based weather monitoring system

How to operate the IoT based weather monitoring system:

  • Make sure that you have connected all the wirings properly and all the modules are connected.
  • Plug a 9V to 12V DC adapter to the power supply module’s DC socket and press the ON switch.
  • You will see sensor data on the LCD cycling between sensors as shown below:

DHT11 temperature and humidity:

case study weather monitoring system

BMP180 atmospheric pressure at ground and sea level (unit is Pa):

case study weather monitoring system

MQ-135 Air quality sensor:

case study weather monitoring system

LDR sensor – intensity of the light:

Lower percentage indicates low light intensity and higher the percentage indicates higher light intensity.

case study weather monitoring system

Please note that air quality and light intensity values are between 0 and 100% and no unit. Also please note that MQ-135 sensor needs to heat up for its proper functioning, so initially while the sensor is heating up it will throw incorrect values and incorrect quality status like toxic or poor.

Data on Thingspeak:

  • DHT11 sensor:

case study weather monitoring system

BMP180 and LDR:

case study weather monitoring system

MQ-135 sensor:

case study weather monitoring system

Note: Initially zero value will get updated on all the 5 fields on Thingspeak and after that real time data starts updating. 

If you have any questions regarding this project, feel free to ask us in the comment, you will get a guaranteed reply from us.

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My nick name is blogthor , I am a professional electronics engineer specialized in Embedded System. I am a experienced programmer and electronics hardware developer. I am the founder of this website , I am also a hobbyist, DIYer and a constant learner. I love to solve your technical queries via comment section.

81 thoughts on “ IoT Based Weather Monitoring System Using Arduino ”

I want the email please sir to communicate with you regarding this project is necessary.

Yes, you can ask you questions here…

Do we need usb cable for data to be transferred to thingspeak , or will it be updated through wifi

Hi, it will be updated through Wi-Fi.

Hlo sir, I am getting error while i try to upload the code.

Hi, Please add all the libraries as mentioned in the post

value_1 = ((value[1] – 0x30) * 10 + (value[2] – 0x30)); value_2 = ((value[3] – 0x30) * 10 + (value[4] – 0x30)); value_3 = ((value[5] – 0x30) * 10000 + (value[6] – 0x30) * 1000 + (value[7] – 0x30) * 100 + (value[8] – 0x30) * 10 + (value[9] – 0x30)); value_4 = ((value[10] – 0x30) * 10 + (value[11] – 0x30)); value_5 = ((value[12] – 0x30) * 10 + (value[13] – 0x30));

Can u please explain the above code?

Hi, The input data from arduino to ESP8266 is received as stream of individual number, here we are grouping the numbers of a sensor using array, so that a sensor data is combined correctly before sending it via internet. For Example, LDR data is sent to ESP8266 as 1 0 0 for 100%. The above block of code combines individual digits to 100 before sending to cloud. The received individual digits by ESP8266 will be their ASCII values, so to convert them to proper integer (before combining) we are subtracting the received individual data with 0x30 hex value. Regards

Thanks a lot:-) Can u please say which value corresponds to which sensor… And how is array length 15?

Hi, Value 1 & 2 are DHT11, Value 3 is BMP180, Value 4 is LDR, Value 5 is MQ-135. Regards

Hello, Could anyone please tell me what is the programming language used for programming here? Thankyou

C language.

Thankyou so much for you’re previous reply. I had another doubt like how the power supply given to the entire circuit?

Hi, The circuit requires 3.3V and 5V, in our circuit setup we used a power supply that accepts 9V in and 3.3V & 5V out. Regards

I am getting DHT 11 SENSOR ERROR others are working what may be the issue. Sometimes it shows the temperature and Humidity but majority of the time it shows as DHT 11 SENSOR ERROR

Hi, There must be loose connections on one or more wires of the sensor.

I am using Nodemcu instead of ESP8266 is there any changes in the code I need to make. Please Share. I am getting output in LCD the problem is I am not getting serial output from Arduino and Node MCU as well as thingspeak. Please help.

Hi, We need to make the project from starch if we want to use NodeMCU.

We got the method and all other things about this project but i have to make it with model so can u suggest some example for what mode can i make for iot based weather monitor ???

Hi, You can use any plastic junk box as enclosure for the project and make some vent hole so that there will be proper air circulation for the sensors. Regards

Please check your VCC and GND connections. Check DHT11 sensor out cable connection.

Can we add gsm module in this project.

Hi, Yes you can, also we need to do some additional programming depending your requirements.

Hi. Thanks for the code and setup. But when uploading my code to esp8266 board, I am recieving following error message: esptool.FatalError: Failed to connect to ESP8266: Timed out waiting for packet header

Can you please tell me its meaning and how to solve it?

Hi, Are you using the illustrated programmer kit? If so you need to short the two terminals as shown in one of the images. Usually, it takes only one attempt to program the ESP8266. Regards

What are the advantages over other projects of the same theme?

Hi, This circuit is well tested one and we have integrated a lot of relevant sensors. Regards

Thingspeak shows only zero values

Initially it will show zeros just for one cycle then, it will update actual values. If you can see values on your LCD check Tx and Rx connections between Arduino and ESP8266 for Tx and Rx. Don’t alter any delay in the code.

If arduino nano is used, does the programming code change?

Yes, you can use arduino nano.

1.Sir, after how much time it will show the data, meaning after how long we can see the weather.

2. Sir how we check the practical data with actual data.

Hi, The data will appear after 1 to 2 mins on Thingspeak, initially it will update zeros and then sensor data starts updating. I did not understand your 2nd question. Regards

Hey buddy it’s showing dht11 sensor error

Hi, Please find its correct Vcc, GND and output Pin. These are differs from manufacture to manufacture.

Sir, can we see the results in mobile?

Hi, Yes, you can by logging into your Thingspeak account on your browser.

Is there any alternate method to upload code for wifi module.

Yes, there is check this article and scroll down to the section where I explained how to upload it.

MQ 135 is showing constant data and it is not varying while connecting to arduino what is the i am not understanding

can you please tell what is the constant value? It is a wiring issue on your setup.

I am able to get the output on the serial monitor in the Arduino IDE but unable to get the output on the things speak app.i have uploaded the code on the esp8266 also but unable to get on the things speak app.please help me

Assuming you have correctly put your SSID, password and write API key on ESP8266 code, then the only thing is to check your wiring and more importantly check Vcc and GND voltage at ESP8266’s terminal, it should be more than 3.0V only then it can upload the data.

It is showing 16 and good throughout the run time

Hi, it is a wiring fault please double check your wiring connection.

I have uploaded the esp8266 code in the esp8266 and it successfully uploaded .I have connected the circuit as mentioned above but unable to get the data on the things speak app.i have uploaded the correct wifi credentials and thingspeak credentials.But unable to get the data on the things speak app.It is also not showing zero also.i am unable to solve the issue .please can you tell me whether I have to do any extra things.please help me

Check the voltage at Vcc and GND terminal of ESP8266 it should be above 3.0V and lower than 3.3V.

sir i need your help with this project my name is kiran and i choose this project as a mini project in my college so disclosing your contact info here is unsafe so iam going to post my mail id here so that you can contact me [PROTECTED]

Hi, You can ask you queries here and I will try to address it here.

Sir, this might be a dumb question but can you use a powerbank to power the board aka the power regulator?

You you can, but still you need to provide 3.3V from a regulator.

I see, can you explain the part of uploading the code to arduino cuz I got confused between uploading the esp8266 code first and arduino code later? Thanks for the reply btw 🙂

Hi, You need to remove the microcontroller from the arduino board so that ESP8266 can be programmed, later you can reinstall the microcontroller to the board and upload the code designated to arduino. You can also upload the code for arduino first, but to make things easy for newbies I mention that.

I see, thanks again for the help 🙂

Can I get the ppt of this project? Because it will use for my study to do my project.kindly send me sir.

Sorry, we did not document a PPT for this project.

I need help, already done uploading the code and everything but the lcd just flashing on and off without displaying anything and in thingspeak nothing showing up 🙁

You wiring to LCD is not proper and also check the voltage that is going to LCD.

Sir, I’m getting dht11 error on lcd and I didn’t get anything in thingspeak. I have checked my wiring and replaced them with new components but the results stays the same

Hi, Your issue with DT11 is pin configuration of the sensor, connect the sensor properly, its +Ve, GND and output. Even if any one of the wire is mismatched you will error. Regards

how data is analysed in thinkspeak ?

Hi, you can download the data from your Thingspeak account in various formats and you may analyze it visually or with a software.

What kind of simulation you using for the circuit?

No simulation was used for this project.

CAN YOU SEND THE CODE FOR STM 32 BECAUSE I’M doing it in STM 32 (BLUE PILL), SO PLEASE CAN YOU SEND IT WILL BE A GREAT HELP

Hi, We will try to publish one in future 🙂

I am using Nodemcu instead of ESP8266 is there any changes in the code I need to make. Please Share I need it

Yes, you need to make a lot of change to the code! You may need to develop from scratch.

How do I add rain sensor to it ?

Hi, you can add a rain sensor on any of the digital pins (if your rain sensor’s output is digital). Configure the pin as digital input, create a new function for the rain sensor, put your values to send_data() function. You need to understand the code before you can start changes in your project. Regards

The ESP8266 is sending all values as 0. I have checked the RX and TX wires. They are connected properly.

Any modification from your side done in the code? only a few time it should update zero at max after that it should update the values.

i got dht 11 sensor error, my all wiring is totally ok, please help about the error

Hi, either you sensor is damaged or still your wiring to DHT11 is incorrect.

I am getting nan at the output terminal:

Hi, The serial terminal was not configured in the first place in this project 🙂

Sir the data is not showing in thingspeak website

Hi, Please give us more info about your circuit setup, is it updating on LCD display etc.

Hi sir I am facing an issue with the uploading of the arduino code it always says “programmer is not responding” what to do now ??

Are you using the programmer module?

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NCESC - 2018 (Volume 6 - Issue 13)

Internet of things (iot) based weather monitoring system.

case study weather monitoring system

  • Article Download / Views: 36,019
  • Total Downloads : 13
  • Authors : Girija C, Harshalatha H, Andreanna Grace Shires, Pushpalatha H P
  • Paper ID : IJERTCONV6IS13149
  • Volume & Issue : NCESC – 2018 (Volume 6 – Issue 13)
  • Published (First Online): 24-04-2018
  • ISSN (Online) : 2278-0181
  • Publisher Name : IJERT

Creative Commons License

Department of Electronics and Communication, NIEIT, Mysuru

Andreanna Grace Shires

Harshalatha H

Pushpalatha H P

Abstract- The system proposed in this paper is an advanced solution for monitoring the weather conditions at a particular place and make the information visible anywhere in the world. The technology behind this is Internet of Things (IoT), which is an advanced and efficient solution for connecting the things to the internet and to connect the entire world of things in a network. Here things might be whatever like electronic gadgets, sensors and automotive electronic equipment. The system deals with monitoring and controlling the environmental conditions like temperature, relative humidity and CO level with sensors and sends the information to the web page and then plot the sensor data as graphical statistics. The data updated from the implemented system can be accessible in the internet from anywhere in the world.

Keywords- Internet of Things (IoT) Embedded Computing System; Arduino Software, ESP8266, Smart Environment.

. INTRODUCTION

The internet of Things (IoT) is viewedas an innovation and financial wave in the worldwide data industry after the Internet. The IoT is a wise system which associates all things to the Internet with the end goal of trading data and conveying through the data detecting gadgets as per concurred conventions. It accomplishes the objective of keen recognizing, finding, following, observing, and overseeing things . It is an augmentation and extension of Internet-based system, which grows the correspondence from human and human to human and things or things and things. In the IoT worldview, many articles encompassing us will be associated into systems in some shape . It is a current correspondence paradigm that envisions a near future, in which the objects of regular day to day existence will be outfitted with microcontrollers, handsets for computerized correspondence, and reasonable convention stacks that will make them ready to speak with each other and with the clients, turning into a vital piece of the Internet. The IoT idea,consequently, goes for making the Internet much more immersive and unavoidable.Moreover, by empowering simple get to and association with a wide assortment of gadgets, for example, for example, home apparatuses, reconnaissance cameras, checking sensors, actuators, showcases, vehicles, et cetera, the IoT will encourage the advancement of various applications that make utilization of the possibly gigantic sum and assortment of information created by such questions give new

administrations to subjects, organizations, and open organizations. Present innovations in technology mainly focus on controlling and monitoring of different activities. These are increasingly emerging to reach the human needs. Most of this technology is focused on efficient monitoring and controlling different activities. An efficient environmental monitoring system is required to monitor and assess the conditions in case of exceeding the prescribed level of parameters (e.g., noise, CO and radiation levels). When the objects like environment equipped with sensor devices, microcontroller and various software applications becomes a self-protecting and self- monitoring environment and it is also called as smart environment. In such environment when some event occurs the alarm or LED alerts automatically. The effects due to the environmental changes on animals, plants and human beings can be monitored and controlled by smart environmental monitoring system. By using embedded intelligence into the environment makes the environment interactive with other objectives, this is one of the application that smart environment targets. Human needs demands different types of monitoring systems these are depends on the type of data gathered by the sensor devices.Event Detection based and Spatial Process Estimation are the two categories to which applications are classified. Initially the sensor devices are deployed in environment to detect the parameters (e.g., Temperature, Humidity and CO etc.)while the data acquisition, computation and controlling action (e.g., the variations in the temperature and CO levels with respect to the specified levels).

Sensor devices are placed at different locations to collect the data to predict the behaviour of a particular area of interest. The main aim of the this paper is to design and implement an efficient monitoring system through which the required parameters are monitored remotely using internet and the data gathered from the sensors are stored in the cloud and to project the estimated trend on the web browser. A solution for monitoring the temperature, humidity and CO levels i.e., any parameter value crossing its threshold value ranges, for example CO levels in air in a particular area exceeding the normal levels etc., in the environment using wireless embedded computing system is proposed in this paper. The solution also provides an intelligent remote monitoring for a particular area of interest. In this paper we also present a trending results of collected or sensed data with respect to the normal or specified ranges of particular parameters. The

embedded system is an integration of sensor devices, wireless communication which enables the user to remotely access the various parameters and store the data in cloud.

SYSTEM ARCHITECTURE

The implemented system consists of a microcontroller (ESP8266) as a main processing unit for the entire system and all the sensor and devices can be connected with the microcontroller. The sensors can be operated by the microcontroller to retrieve the data from them and it processes the analysis with the sensor data and updates it to the internet through Wi-Fi module connected with it.

A.BLOCK DIAGRAM

Fig. 1 Block Diagram of the Project

B.WI-FI MODULE

Fig 2.ESP8266

Here we used ESP8266 Wi-Fi module which is having TCP/IP protocol stack integrated on chip. So that it can provide any microcontroller to get connected with Wi-Fi network. ESP8266 is a preprogrammed SOC and any microcontroller has to communicate with it through UART interface.. It works with a supply voltage of 3.3v. The module is configured with AT commands and the microcontroller should be programmed to send the AT commands in a required sequence to configure the module in client mode. The module can be used in both client and server modes.

The system consists of temperature and humidity sensor(DHT

11) and CO sensor(MQ 6). These 2 sensors will measure the primary environmental factors temperature, humidity and the

CO levels. All this sensors will gives the analog voltage representing one particular weather factor. The microcontroller will converts this analog voltage into digital data.

D.TEMPERATURE SENSOR AND HUMIDITY SENSOR

The DHT11 is an essential, ultra minimal effort computerized temperature and humidity sensor.

Fig. 3 Temperature and Humidity Sensor DHT 11

It utilizes a capacitive humidity sensor and a thermistor to gauge the surrounding air, and releases a digital data on the data pin (no analog information pins required). The main genuine drawback of this sensor is you can just get new information from it once every 2 seconds, so when utilizing our library, sensor readings can be up to 2 seconds old. Itworks on 3 to 5V power supply. Good for 20- 80% humidity readings with 5% accuracy and for 0-50°C temperature readings ±2°C accuracy

E.CARBON MONOXIDE (CO) SENSOR

Carbon Monoxide (CO) sensor, suitable for sensing CO concentrations in the air.

Fig. 4 Carbon Monoxide (CO) sensor MQ 6

Carbon monoxide sensor, suitable for sensing CO concentration in air. The MQ-6 can sense CO-gas concentration somewhere in the range of 20 to 2000ppm. This sensor has a high affectability and quick reaction time. The sensor's yield is aanalog resistance. The drive circuit is exceptionally straightforward; you should simply control the heater curl with 5V, include a load resistance, and associate the output to an ADC. The standard reference strategy for the estimation of carbon monoxide concentration in air depends on the ingestion of infrared radiation by the gas in a no dispersive photometer. This technique is reasonable for stable establishments at fixed site monitoring stations. All the more as of late, convenient carbon monoxide analyzers with data- logging have turned out to be accessible for individual presentation observing. These estimations depend on the electrochemical responses between carbon monoxide and de- ionized water, which are detected by exceptionally planned sensors. These days the determination, strength and affectability of the electrochemical analyzers are inside the details of the reference technique and, together with the data-

logging systems, they fit into a little rucksack or even a pocket.

Conversion factors

1 ppm= 1.145 mg/m3

1 mg/mg = 0.873 ppm

THING SPEAK

According to its developers, Thing Speak is an open source Internet of Things (IOT) application and API to store and retrieve data from things using the HTTP protocol over the Internet or via a Local Area Network. Thing Speak enables the creation of sensor logging applications, location tracking applications, and a social network of things with status updates".

Thing Speak has integrated support from the numerical computing software MATLAB from MathWorks allowing Thing Speak users to analyze and visualize uploaded data using Matlab without requiring the purchase of a Matlab license from Mathworks.

Fig. 5 Circuit Diagram of the system

SIMULATION RESULTS

After sensing the data from different sensor devices, which are placed in particular area of interest. The sensed data will be automatically sent to the web server, when a proper connection is established with sever device.The web server page which will allow us to monitor and control the system. The web page gives the information about the temperature, humidity and the CO level variations in that particular region, where the embedded monitoring system is placed. The sensed data will be stored in cloud (Google Spread Sheets). The data stored in cloud can be used for the analysis of the parameter and continuous monitoring purpose. The temperature and humidity levels and CO levels in air at regular time intervals. All the above information will be stored in the cloud, so that we can provide trending of temperature and humidity levels and CO levels in a particular area at any point of time.

Fig.6(a) Simulation of Temperature v/s Time

Fig.6(b) Simulation of Humidity v/s Time

Fig.6(c) Simulation of Smoke content v/s Time

By keeping the embedded devices in the environment for monitoring enables self protection (i.e., smart environment) to the environment. To implement this need to deploy the sensor devices in the environment for collecting the data and analysis. By deploying sensor devices in the environment, we can bring the environment into real life i.e. it can interact with other objects through the network. Then the collected data and analysis results will be available to the end user through the Wi-Fi. The smart way to monitor environment and an efficient, low cost embedded system is presented with different models in this paper. In the proposed architecture functions of different modules were discussed. The temperature, humidity and CO value can be monitored with Internet of Things (IoT) concept experimentally tested for monitoring three parameters. It also sent the sensor parameters to the cloud (Google Spread Sheets). This data will be helpful

for future analysis and it can be easily shared to other end users. This model can be further expanded to monitor the developing cities and industrial zones for weather monitoring. To protect the public health from pollution, this model provides an efficient and low cost solution for continuous monitoring of environment.

FUTURE SCOPE

An alarm can be added to the circuit to notify the user in case of excess smoke conditions i.e. Smoke alarm.

An SMS can be sent to clients notifying them with the temperature/humidity/smoke parameters.

E. Welbourne, L. Battle, G. Cole, K. Gould, K. Rector, S. Raymer et al., Building the internet of things using RFID: The RFID experience, IEEE internet comput., vol. 13, no. 3, pp.48- 55, May- Jun. 2009.

Shifeng Fang; Li Da Xu; Yunqiang Zhu; JiaerhengAhati; Huan Pei; Jianwu Yan; Zhihui Liu., An integrated system for regional environmental monitoring and management based on internet of things, IEEE Transactions on Industrial Informatics,vol.10, no. 2,pp.1596-1605, May-Jun. 2014.

J. A. Stankovic, Research directions for the Internet ofThings,

IEEE Internet ThingsJ., vol. 1, no. 1, pp. 39, Feb. 2014

Shanzhi Chen; HuiXu; Dake Liu; Bo Hu; Hucheng Wang.

L. Atzori, A. Iera, and G. Morabito, The internet of things: A survey, Comput. Netw., vol. 54, no. 15, pp. 27872805, 2010

P. Bellavista, G. Cardone, A. Corradi, and L. Foschini,Convergence of MANET and WSN in IoT urban scenarios,IEEE Sens. J., vol. 13, no. 10, pp. 35583567, Oct. 2013.

BulipeSrinivasRao , Prof. Dr. K. SrinivasaRao , Mr. N. Ome, Internet of Things (IOT) Based Weather Monitoring system, IJARCCE Journal,vol. 5, no. 9, sept. 2016.

B. Vongsagon, J. Ekchamanonta, K.Bumrungkhet, and S.Kittipiyakul, XBee wireless sensor networks for temperature monitoring, Retrieved 7/11/15 World WideWeb http://citeseerx.i st.psu.edu/viewdoc/download?doi=10.1.1.4 76.9630&rep

=rep1&type=pdf

Nashwa El-Bendary, Mohamed Mostafa M. Fouad, Rabie A. Ramadan, Soumya Banerjee and Aboul Ella Hassanien, Smart Environmental Monitoring Using Wireless Sensor Networks,K15146_C025.indd, 2013

Grzegorz Lehmann, Andreas Rieger, Marco Blumendorf, SahinAlbayrakDAI, A 3-Layer Architecture for Smart Environment Models/A model-based approach/LaborTechnische University Berlin, Germany 978-1-4244-5328-3/10 © IEEE,2010.

CharalamposDoukas, Building Internet of Things with the ESP8266, CreateSpace Publications, 2012

Shifeng Fang et al., "An Integrated System for Regional Environmental Monitoring and Management Based on Internet of Things," , IEEE Transactions on Industrial Informatics , vol.10, no.2, pp.1596-1605, May 2014.

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Case Study of Constructing Weather Monitoring System in Difficult Environment

  • Graduate School of Media Design

Research output : Chapter in Book/Report/Conference proceeding › Conference contribution

A high density real time weather monitoring system helps us to reduce the damage of disaster. We can utilize this data not only disaster but also agriculture, education material and so on. To install automatic weather stations (AWSs) to the real field, we have to consider a high temperature, dust, heavy rain, power outage, cost, etc. In India. In this paper, we describe how to install low cost weather monitoring system to appalling environment and make it stable through our 19 AWSs installation challenge experience in Hyderabad city, India.

Publication series

  • Disaster mitigation
  • Sensor network
  • Weather monitoring

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

  • 10.1109/UIC-ATC-ScalCom.2014.59

Other files and links

  • Link to publication in Scopus
  • Link to the citations in Scopus

Fingerprint

  • Disasters Engineering & Materials Science 100%
  • Monitoring Engineering & Materials Science 60%
  • Agriculture Engineering & Materials Science 58%
  • Rain Engineering & Materials Science 58%
  • Dust Engineering & Materials Science 54%
  • Outages Engineering & Materials Science 49%
  • Education Engineering & Materials Science 45%
  • Costs Engineering & Materials Science 40%

T1 - Case Study of Constructing Weather Monitoring System in Difficult Environment

AU - Yamanouchi, Masato

AU - Ochiai, Hideya

AU - Reddy, Y. K.

AU - Esaki, Hiroshi

AU - Sunahara, Hideki

N1 - Publisher Copyright: © 2014 IEEE.

N2 - A high density real time weather monitoring system helps us to reduce the damage of disaster. We can utilize this data not only disaster but also agriculture, education material and so on. To install automatic weather stations (AWSs) to the real field, we have to consider a high temperature, dust, heavy rain, power outage, cost, etc. In India. In this paper, we describe how to install low cost weather monitoring system to appalling environment and make it stable through our 19 AWSs installation challenge experience in Hyderabad city, India.

AB - A high density real time weather monitoring system helps us to reduce the damage of disaster. We can utilize this data not only disaster but also agriculture, education material and so on. To install automatic weather stations (AWSs) to the real field, we have to consider a high temperature, dust, heavy rain, power outage, cost, etc. In India. In this paper, we describe how to install low cost weather monitoring system to appalling environment and make it stable through our 19 AWSs installation challenge experience in Hyderabad city, India.

KW - Disaster mitigation

KW - Sensor network

KW - Weather monitoring

UR - http://www.scopus.com/inward/record.url?scp=84949550177&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84949550177&partnerID=8YFLogxK

U2 - 10.1109/UIC-ATC-ScalCom.2014.59

DO - 10.1109/UIC-ATC-ScalCom.2014.59

M3 - Conference contribution

AN - SCOPUS:84949550177

T3 - Proceedings - 2014 IEEE International Conference on Ubiquitous Intelligence and Computing, 2014 IEEE International Conference on Autonomic and Trusted Computing, 2014 IEEE International Conference on Scalable Computing and Communications and Associated Symposia/Workshops, UIC-ATC-ScalCom 2014

BT - Proceedings - 2014 IEEE International Conference on Ubiquitous Intelligence and Computing, 2014 IEEE International Conference on Autonomic and Trusted Computing, 2014 IEEE International Conference on Scalable Computing and Communications and Associated Symposia/Workshops, UIC-ATC-ScalCom 2014

A2 - Zheng, Yu

A2 - Thulasiraman, Parimala

A2 - Apduhan, Bernady O.

A2 - Nakamoto, Yukikazu

A2 - Ning, Huansheng

A2 - Sun, Yuqing

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 11th IEEE International Conference on Ubiquitous Intelligence and Computing and 11th IEEE International Conference on Autonomic and Trusted Computing and 14th IEEE International Conference on Scalable Computing and Communications and Associated Symposia/Workshops, UIC-ATC-ScalCom 2014

Y2 - 9 December 2014 through 12 December 2014

case study weather monitoring system

Villanova 20-Year Study Shows Rain Gardens Can Control Storm Runoff

Villanova University researchers have been monitoring a university rain garden for 20 years and can now show that rain gardens are good at soaking up storm water runoff and preventing pollution from entering waterways, writes Zoe Read for WHYY .

Storms wash pollution off streets and buildings and sewage overflows because of outdated sewer systems in the Philadelphia region that accept storm water and raw sewage.

When the systems overflow, the runoff and sewage end up in rivers and streams.

Rain gardens could be part of a solution.

“Overall, what we ended up seeing is that the system can manage a lot of the water that’s coming in off the watershed. And we’ve seen that it’s been able to consistently do that over time,” said researcher Bridget Wadzuk , associate director of the Villanova Center for Resilient Water Systems .

Rain gardens collect storm water and use plants and soil that can soak up water and pollutants from buildings and roads.

Villanova used U.S. EPA and Pennsylvania Department of Environmental Protection funding for its lengthy rain garden monitoring.

The rain gardens work best when they are well maintained and feature a diverse range of plants.

Read more about what else Villanova discovered about rain gardens at WHYY.

Villanova 20-Year Study Shows Rain Gardens Can Control Storm Runoff

  • International

The latest on the massive solar storm

By Angela Fritz, Elise Hammond and Chris Lau, CNN

Biden administration closely tracking potential for geomagnetic storm impacts

From CNN's Betsy Klein

Joe Biden delivers remarks at Gateway Technical College in Sturtevant, Wisconsin, on May 8.

The Biden administration is monitoring the possibility of impacts from the solar storm this weekend, according to a White House official.

The official said an interagency effort is underway with participation from the Department of Energy, the National Oceanic and Atmospheric Administration and the Cybersecurity and Infrastructure Security Agency, among others. 

“NOAA’s Space Weather Prediction Center has notified operators of infrastructure systems of potential risks so they can take any needed mitigation measures,” the official said, and “The Cybersecurity and Infrastructure Security Agency as well as other sector risk management agencies are working closely with infrastructure operators to ensure necessary precautions are taken.”

The US Secret Service presidential protection division is also coordinating with the White House and local jurisdictions, US Secret Service communications chief Anthony Guglielmi said.

“This ensures maximum interoperability and is important when visiting remote locations or in instances with extreme environmental events, like solar flares and major storms,” he said.

Incredible photos of northern lights over the UK on social media

Increased solar activity will cause northern lights to be visible in places they are rarely seen.

From CNN's Ashley Strickland

Jacob Anderson shared this image of the lights seen in Edinburgh, Scotland.

A series of solar flares and coronal mass ejections from the sun have the potential to create dazzling auroras that may be seen as far south as Alabama and Northern California as early as Friday and continuing into the weekend, according to the National Oceanic and Atmospheric Administration’s  Space Weather Prediction Center .

Increased solar activity causes auroras that dance around Earth’s poles , known as the northern lights, or aurora borealis, and southern lights, or aurora australis. When the energized particles from coronal mass ejections reach Earth’s magnetic field, they interact with gases in the atmosphere to create different-colored light in the sky.

Geomagnetic storms driven by the sun in recent months have caused auroras to be visible in places where they are rarely seen, including as far south as New Mexico, Missouri, North Carolina and California in the United States as well as the southeast of England and other parts of the United Kingdom.

Depending on the location, the auroras may not always be visible overhead, but keep an eye on the horizon, experts say, because they may create a colorful display there as well.

Even if auroras aren’t visible in the sky, experts at the center recommend taking images of the sky with your phone because the images may capture what you can’t see with the naked eye.

Prepare for space weather as you would prepare for an extended power outage, officials say

From CNN's Brian Fung

To prepare for the incoming geomagnetic storm this week, the US government is advising people to take the same steps they would take in response to an extended power outage.

For example, for a space weather event, the government recommends keeping extra batteries or a hand-powered charger available for small electronic devices.

Officials say you may want to disconnect electric appliances to protect them from power surges and limit your electricity usage during a solar weather event. You may also want to keep your car’s gas tank at least half-full so that you do not need to visit a gas station, which needs electricity to operate the pumps.

Regarding cell phones, many wireless carrier providers already maintain backup power generators and mobile cellular towers that they can deploy in the event of a natural disaster or other major incident.

Redundancy and resiliency are watchwords of all critical infrastructure providers, so even if the power grid did fail, consumers might have to worry more about how to keep their phones charged rather than whether they could stay online.

There's an increased chance of northern lights visibility in northern United Kingdom, scientists say

From CNN's Mitchell McCluskey

There is an increased chance of visibility for the northern lights, or aurora borealis, particularly across Scotland, Northern Ireland and parts of northern England and Wales due to the solar storm this weekend, the United Kingdom’s Meteorological Office says.

There is a chance of visibility even further south, but the Met Office advises using long exposure on camera to capture the lights.  

"Multiple coronal mass ejections from the sun are expected to reach Earth in the coming days bringing the potential for aurora visibility over the UK, particularly on Friday night,” said Krista Hammond, Met Office space weather manager.  “Aurora visibility may persist through Saturday night, but as it stands this is likely to be less widespread than on Friday night with northern parts of the UK most likely to continue to have the best viewing potential,” Hammond said. 

The Met Office said that they will continue to monitor the conditions of the sun.

Incoming geomagnetic storm could impact communications and GPS systems

A geomagnetic storm caused by solar flare activity could trigger numerous effects for life on Earth this weekend, according to the National Oceanic and Atmospheric Administration.

This kind of solar activity involves the release of energy from the sun that travels through space and eventually reaches Earth.

When that radiation hits the magnetic sphere surrounding the planet, it causes fluctuations in  the ionosphere , a layer of the upper atmosphere. Those changes can directly affect satellites and other spacecraft in orbit, altering their orientation or  potentially knocking out  their electronics.

Here’s what that could mean:

  • Communications: Changes to the ionosphere can block or degrade radio transmissions trying to pass through the atmosphere to reach satellites. Since GPS satellites depend on signals penetrating the ionosphere, the geomagnetic disturbance scientists are expecting could affect critical technology used by planes, ocean-going vessels, and in the agriculture and oil and gas industries. It could also affect  shortwave radio transmissions  used by ships and aircraft, emergency management agencies and the military.
  • Your cellphone: Consumer wireless networks rely on different radio frequencies than the high-frequency band, so it appears unlikely that the storm will directly affect cellular service. The GPS features on your phone also typically use a mix of pure GPS and cellular tower-based location tracking, so even if GPS signals are disrupted, phone users may still be able to maintain a rough location fix.
  • Power grid: Severe space weather can jeopardize power grids, according to NOAA, whose  alert  this week said to expect “possible widespread voltage control problems” and that “some protective systems may mistakenly trip out key assets from the power grid.”
  • On the International Space Station: NASA’s Space Radiation Analysis Group is dedicated to monitoring conditions for astronauts aboard the ISS. If there appears to be an increased radiation risk, the astronauts can move to parts of the station that are more well-shielded.

CNN's Ashley Strickland contributed reporting to this post.

Scientists issue severe geomagnetic storm watch for the first time in nearly 20 years

From CNN's Brian Fung and Ashley Strickland

People visit St Mary's lighthouse to see the aurora borealis, in Whitley Bay, England, on May 10.

The US government issued its first severe  geomagnetic storm watch  in nearly 20 years, advising the public of “at least five earth-directed coronal mass ejections” and sunspots that could arrive as early as Friday and continue through the weekend, according to scientists.

A severe geomagnetic storm, or G4, is the second-highest grade in the US government’s  classification system .

The Space Weather Prediction Center has been tracking multiple strong flares emitting from a large cluster of sunspots on the solar surface since Wednesday. The cluster is 16 times the diameter of Earth. Radiation from this activity will begin to hit Earth’s magnetic field on Friday and last through the weekend, the National Oceanic and Atmospheric Administration said.

These five coronal mass ejections, or large clouds of ionized gas called plasma, are magnetic fields that erupt from the sun’s outer atmosphere, releasing from the sun in the direction of Earth.

Because the coronal mass ejections carry their own magnetic field, they can overwhelm power lines and induce electrical currents, said Rob Steenburgh, space scientist at the Space Weather Prediction Center.

Officials say this solar storm is "an unusual event" — but it isn't the first instance of space weather

US scientists warn about possible communication outages or interference to GPS systems as at least five coronal mass ejections from the sun head toward Earth Friday and into this weekend.

The Space Weather Prediction Center referred to this as “an unusual event.” There have been three geomagnetic storms since December 2019, but all of them have been considered weak, according to the center.

So far, researchers have observed only three severe geomagnetic storms during the current solar cycle, which began in December 2019, according to the center.

Previously, a G5, or extreme geomagnetic storm, occurred in October 2003, resulting in power outages in Sweden and damaged power transformers in South Africa, according to the center. This current storm has been classified as a G4, the second-highest grade.

Other historical instances of space weather: In 1989, a space weather event led to a  massive blackout in Quebec, Canada  for more than nine hours after geomagnetic fluctuations damaged transformers and other important equipment.

In October, an extreme geomagnetic storm stronger than the one predicted for this weekend led to power outages in Sweden and damaged power transformers in South Africa, the SWPC said.

The largest known geomagnetic storm in history, known as the Carrington Event of 1859, caused telegraph stations to spark and catch fire.

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Panchayats to have climate monitoring system soon

Biju paravath, 11 may 2024, 02:39 pm ist.

case study weather monitoring system

Representational Image | Photo : AP

Thiruvananthapuram: In order to collect data for a study on climate change and its adverse effects on the agricultural sector, the Centre has directed the State to install rain gauges and climate monitoring systems in all panchayats.

The weather monitoring system will have a provision to send warnings to mobile phones in case of emergencies.

The Centre has also entrusted the States to choose and designate certain private companies as accredited agencies for the purpose.

A tender will be invited from private firms for the contract. The measures for the same should be completed by August. Although the private firms will be the accredited agencies, the government will have the proprietorship of the data.

Both the Centre and the State can make use of the data. The costs will be shared between the Centre and the State. In the initial year, 90 percent of the expenses will be covered by the Centre (10 percent State), followed by 80 percent in the subsequent year (20 percent State), and 60 percent (40 percent State) in the year after. Beyond this, expenses will be equally divided between the Centre and the State.

The insurance for the agricultural crops has been revised in accordance with the climate change. At present, the insurance companies access the data from private firms. The cost for the same has been included in the premium. If the data is provided by the Government then the expense could be reduced.

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Decreasing the energy demand in public buildings using nature-based solutions: case studies from Novi Sad (Republic of Serbia) and Osijek (Republic of Croatia)

  • Stevan Savić 1 ,
  • Hrvoje Krstić 2 ,
  • Ivan Šećerov 1 &
  • Jelena Dunjić 1  

Energy, Sustainability and Society volume  14 , Article number:  23 ( 2024 ) Cite this article

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Nature-based solutions (NBS) in urban areas offer an opportunity to improve environmental conditions and to reduce CO 2 emissions towards establishing climate-neutral cities in the next few decades. Furthermore, the implementation of NBSs—vertical or horizontal green infrastructures on public facilities—could in particular improve both climate, including outdoor thermal conditions on a micro-scale (especially during the summer season) and the energy demand of buildings as well as save heating energy during the winter period.

On both selected buildings, extensive green roofs were implemented as an NBS intervention. The analysed data were obtained using the monitoring systems (from 2019 to 2022) installed on two public buildings in Novi Sad (Republic of Serbia) and Osijek (Republic of Croatia), with a focus on climate/bioclimate characteristics and thermal transmission capacities. Four automatic weather stations (AWS) were used for microclimate monitoring, along with the heat flow meter (HFM) method, to measure the alterations in the thermal transmittance ( U value) of a flat concrete roof before and after energy refurbishment and the installation of a green roof. The outcomes of this study show that the air temperatures ( Ta ) and globe temperatures ( Tg ) near the green roof are lower by 0–3 °C for Ta and by 0–16.5 °C for Tg than the values captured by the AWSs at other locations. An even more interesting fact is that the green roof has a constant cooling potential during tropical nights, and based upon this research, the cooling value is around 2 °C for Tg (the Ta value is not distinct). The thermal transmittance results show that more savings can be achieved by applying a green roof with an 8 cm thick substrate: U values decreased by 50–69%, as measured by two different heat flux sensors.

Conclusions

Nature-based solutions, such as the implementation of an extensive green roof, have positive effects on diverse aspects of urban environments and building energy savings, which are particularly evident in extreme seasons, both summer and winter. Applying the proposed monitoring and assessment system could help local communities in their efforts to reduce carbon-based emissions. This paper provides a good example of the implementation of NBSs on a local- and a micro-scale.

Current and previous events in the modern world, such as the recent COVID-19 pandemic, had a significant socioeconomic impact within the European Union (EU) [ 1 ]. Unfortunately, the pandemic was not the only event in past years that caused a shift in our lives—with an increased dependence of energy, and after the outbreak of the “Ukraine war”, the EU has got another battle to fight [ 2 ]. While wars, embargoes, sanctions and other geopolitical hostilities can disrupt fossil fuel supplies, renewable energy costs are now resilient to such events, unlike those of fossil fuels [ 3 ]. As the atmosphere continues to warm every year, resulting in climate change, the European Commission invests 30% of the budget in climate-related programmes, projects, and initiatives [ 4 ]. The principles and policies of sustainable development have been recognized since the 1970s. While the focus on sustainable development offers real opportunities to developed countries, developing countries, facing many problems, are generally more oriented toward economic development, which is not always aligned with sustainability principles [ 5 ]. The green transition, transition toward economically sustainable growth and economy, which is based on low-carbon solutions, is unfortunately a long-term process [ 6 ]. The EU has proposed The European Green Deal, a plan to decarbonise its economy by 2050 and fight climate change, but some Members States remain sceptical of this policy [ 7 , 8 ].

While working hard to reduce fossil fuel consumption and make the environment more desirable to live in, the EU tends to fight against one of the legacies of previous times with an equal passion, making the reduction of energy demand in buildings through the adoption of energy efficiency policies one its key pillars [ 9 ]. Studies demonstrate that European residential buildings account for up to 40% of energy consumption and up to 36% of CO 2 emissions [ 10 ], offering solutions regarding the prioritisation of energy efficiency intervention in such buildings [ 11 ]. Energy efficiency in public buildings is not a problem limited to the EU. It is widespread all over the world. The UN Sustainable Development Goals (Agenda 2030) prove that the problem is global [ 12 ].

According to Eurostat, the gross primary energy consumption in the Republic of Croatia in 2021 was 9.61 Terawatt hours (TWh) and the final energy consumption was 8.1 TWh [ 13 ]. For the Republic of Croatia over the past 15 years, the balance in primary energy supply of oil and oil products accounted for 50%, while the share of natural gas was 25.6% [ 4 ]; renewable energy sources accounted for 31.33% of Croatia’s energy mix, with 53.47% of the total electricity production coming from renewables, primarily large hydropower plants [ 3 ]. The Republic of Croatia imports about 54.54% of the total energy consumed annually [ 13 ]: 74.48% of natural gas, 78.34% of oil and petroleum products, and 100% of its solid fossil fuel needs. The Republic of Croatia also co-owns the Krško nuclear plant in Slovenia, which is included in its energy mix as imported electricity [ 13 ]. In 2020, the Croatian government adopted a new Energy Strategy until 2030, with an outlook through 2050 [ 14 ]. The Strategy tends to improve energy independence, to increase energy efficiency, reduce dependence on non-renewable sources, and increase production from renewable resources. The Strategy predicts that renewable energy resources as a share of the total energy consumption will grow to 36.4% in 2030 and to 65.6% in 2050. Buildings are complex energy systems and the largest individual energy consumers; the European buildings sector is responsible for about 40% of the total primary energy consumption [ 15 , 16 ]. Furthermore, the stock of residential buildings constructed before the 1970s, which have a low performance regarding energy saving, makes up for more than three-fourths of the total existing residential buildings in the European Union [ 17 ]. The situation is the same in the Republic of Croatia, where approximately 70% of the total existing buildings are constructed before 1980 [ 18 ]. The Croatian national nZEB plan was adopted in 2015. The minimum threshold for the primary energy ranges between 50 kWh/m2a and 80 kWh/m2a; the final heating demands is 50–75 kWh/m2a and the final cooling demand in residential buildings is 25–60 kWh/m2a [ 19 ]. Renewable energy sources must cover at least 30% of the annual site energy [ 19 ].

According to the Statistical Office of the Republic of Serbia [ 20 ], the gross primary energy consumption in 2021 was: 0.013516 TWh solar photovoltaic, 1.084541 TWh wind energy, 11.984227 TWh hydroenergy and 0.650913 TWh electricity. The overall energy production by transformation was 38.235523 TWh (0.013516 TWh solar photovoltaic, 1.084541 TWh wind turbines, 11.984227 TWh hydroenergy, 23.733678 TWh thermal power plants and 1.419561 TWh other types of energy production) [ 20 ]. According to the International Renewable Energy Agency (IRENA), the overall energy import amounted to 229 476 TJ (Terra Joules) in 2015 and 256 531 TJ in 2020—37% and 39% of the supply, respectively [ 21 ]. Unfortunately, the overall growth of the Total Energy Supply (TES) for non-renewable energy was 531,780 TJ in 2015 and 553,035 TJ in 2020, while the TES for renewable energy was only 82,681 TJ in 2015 and 112,804 TJ in 2020. Although there is a small increase in renewable energy production between 2015 and 2020, it is still insignificant compared to the non-renewable production growth [ 21 ]. In 2015, the Republic of Serbia submitted the Intended National Determined Contribution (INDC) to the United Nations Framework for the Convention on Climate Change (UNFCCC), while in 2022, the second National Determined Contribution (NDC) was submitted. It puts forward the intention to reduce greenhouse gas (GHG) emissions by 2030—by 13.2% compared to the 2010 level and by 33.3% compared to the 1990 level [ 22 ]. According to the Long-Term Strategy for Encouraging Investment in the Renovation of the National Building Stock of the Republic of Serbia by 2050, residential and non-residential buildings, both public and private, will be provided with financial support to improve energy performance and ensure energy modernisation [ 22 ].

Nature-based solutions (NBSs) should play a crucial role in decreasing the energy demand of buildings, decarbonising cities, fostering urban biodiversity, improving biometeorology conditions, and helping achieve a higher quality of well-being for the urban population [ 23 , 24 ]. To support natural processes in cities, NBS interventions, as an act of intervening in existing ecosystems by applying various techniques, should be enforced [ 24 ]. Therefore, NBSs can provide effective solutions for: the cooling of ‘hot spots’ in cities; the regulation of outdoor and indoor thermal conditions during hot days and tropical nights; the reduction of greenhouse gases and pollutants (particularly CO 2 and PM2.5 particles); the improvement of the energy efficiency of public and private facilities and of the public health, particularly in terms of reducing cardio and respiratory diseases. Generally speaking, NBS can be part of sustainable approaches and ecosystem services in cities [ 23 , 25 , 26 , 27 , 28 , 29 ].

As stated in the Research and Innovation concept [ 30 ], by working with nature, rather than against it, communities can develop and implement solutions that pave the way towards a resilient, resource-efficient and green economy. Since the direct carbon emissions of buildings account for a significant proportion of total carbon emissions, while energy efficiency investment incentives through building materials have weakened, NBSs have emerged as an alternative approach for reducing building energy demands [ 31 ]. Several projects have presented green façade solutions that not only contribute to the energy efficiency of the buildings, but also improve their thermal comfort and aesthetic appeal [ 32 ]. NBSs applied in building industry have the potential to be cost-efficient, i.e. they can yield good results without huge costs, and resource-efficient using building materials, natural resources and energy in a sustainable way, while minimizing impacts on the environment [ 33 ].

Studies show that NBS interventions and expected contributions from the NBS infrastructure are in accordance with the European Green Deal [ 34 ] and the New European Bauhaus [ 35 ] concepts, with the overarching goal of making Europe climate-neutral by 2050. These concepts foster the transformation of economy and society towards sustainable development by creating a revolution in green industry (4.5 million green jobs in the European economy were opened from 2001 to 2019); rising the ratio of clean energy systems that produce renewable energy (by 2030 the target is 42.5% of new renewable energy); renovating buildings for greener lifestyles with the goal to improve the energy performance of buildings across Europe; working with nature to provide a high level of public health and to capture more greenhouse gases.

According to the CORDIS database, created by the European Commission, there are more than 2,000 projects (finished or ongoing) dealing with the topics related to urban biodiversity, renewable energy, decarbonization of cities, greening of cities, urban climate and bioclimate, and similar urban environment issues. The projects that stand out by activities and proposed solutions related to NBS and the urban environments include: (a) ThinkNature—with the main goal to develop a multi-stakeholder communication platform that provides support and ensures the promotion of NBS at the local, regional and international levels; (b) Nature4Cities, which develops complementary and interactive modules (the N4C platform) for engaging stakeholders in the process of collective education on urban greening, the development and circulation of new businesses, financial and management models for nature-based projects; (c) UNaLaB, which seeks to establish the so-called “Living Laboratories” in cooperation with stakeholders and implement demonstration areas, develop a comprehensive base of examples and a European framework of innovative, replicable and locally oriented NBSs to improve the resilience of cities to climate and hydrological change; (d) URBAN GreenUP, which aims to establish an adaptable methodology that will support the development of urban greening plans focused on climate change adaptation and efficient water management; and (e) CONNECTING Nature, seeking to position Europe as a leader in the innovation and implementation of NBSs [ 23 , 36 ]. Another project funded by the EU, which is the topic of this study, is GReENERGY, tasked with fostering the implementation of NBSs in public facilities. The main goals of the project are: (a) to encourage the production and use of renewable energy while reducing energy consumption from the conventional sources that are the major emitters of CO 2 and (b) to emphasize the installation of green roofs and green walls on public buildings as one of the NBSs that ensure additional energy efficiency, to help preserve the urban ecosystem by improving the outdoor thermal comfort conditions on a micro-scale. GReENERGY project activities were focused on the implementation of green roofs (total area of 640 m 2 ) and a green wall (total area of 80 m 2 ), and the production of 213 kW of additional renewable energy through solar power plants installed on both selected buildings in Novi Sad and Osijek [ 37 ]. The entire infrastructure provided through the GReENERGY project will remain the property of respective institutions after the project officially ends. As far as future maintenance after that period is concerned, each institution will be responsible for its own NBS/monitoring implementation.

The research presented in this study was focused on the multifunctional importance and positive impacts of NBSs towards making cities carbon–neutral and climate optimal. Therefore, the main goal was to monitor the positive impacts of NBSs and answer the following research questions: SQ1—to what extent implementing an extensive green roof (in Novi Sad, Republic of Serbia) on public buildings can contribute to the mitigation of outdoor thermal discomfort, especially on days with extremely high temperatures, as well as during tropical nights?; SQ2—to what extent green infrastructure placed on public buildings (extensive green roof in Osijek, Republic of Croatia) can contribute to the reduction of heating energy consumption in buildings during the heating season, helping cities become carbon–neutral in the future?

Research locations

Osijek is the fourth largest city in the Republic of Croatia, with 60 km 2 of built-up and urban green/blue areas and a population of 97,000 people (data from 2021). The city is located in the Pannonian Plain between the Drava and Danube rivers in Central Europe (45° 33′ N, 18° 41′ E). The average absolute elevation of the city is 94 m (Fig.  1 A). According to the Köppen–Geiger climate classification system [ 38 ], Osijek has a Cfb climate (temperate climate, fully humid, warm summers, with at least 4 months of the average air temperature above 10 °C). The mean monthly air temperature ranges from − 0.2 °C in January to 21.3 °C in July, and the mean annual precipitation is 655 mm (based on data between 1971 and 2000) [ 39 ].

figure 1

A Geographical location of Osijek in the Republic of Croatia and Europe. https://www.worldometers.info/img/maps/croatia_physical_map.gif ; B Sports and Recreational Complex of the High School Playground with the implementation of a green roof (160 m 2 ) and a solar power plant (93 kW); C geographical location of Novi Sad in the Republic of Serbia and Europe; Source: https://www.worldometers.info/img/maps/serbia_physical_map.gif ; D SPSE "Milan Petrović" with the implementation of a green roof (480 m 2 ) and a solar power plant (120 kW)

The selected public object in Osijek was the Sports and Recreational Complex of the High School Playground (Fig.  1 B). Through the GReENERGY project, an extensive green roof with an area of 160 m 2 and a solar power plant with the power of 93 kW were installed on this facility. The building was erected in 1964, with a gross area of 1045.65 m 2 and a usable area of 878.85 m 2 . The Sports and Recreational Complex of the High School Playground consists of two heated floors—the ground floor and the first floor. The building uses remote heating with a boiler room connected to the city’s hot water system. The facility is locally supplied with hot water from electric boilers. The building does not have air conditioning, mechanical ventilation and cooling systems. Cooling devices (split system) have been installed for the local cooling of individual rooms. In general, the facility’s energy consumption was high. Using funds provided by the GReENERGY project, the insulation was reconstructed in the whole building [ 40 ].

Novi Sad is the second largest city in the Republic of Serbia, with 102 km 2 of built-up and urban green/blue areas and a population of 325,000 [ 41 ]. The city is located near the Danube River in the Pannonian Plain in Central Europe (45° 16′ N, 19° 50′ E); accordingly, the most of the urban area is flat with an absolute elevation between 72 and 80 m [ 42 ] (Fig.  1 C). Novi Sad has a Cfb climate according to the Köppen–Geiger climate classification system [ 38 ]. The mean monthly air temperature ranges from − 0.3 °C in January to 21.8 °C in July, and the mean annual precipitation is 623 mm (based on data between 1949 and 2015) [ 43 ].

The selected public facility in Novi Sad was the School for Primary and Secondary Education (SPSE) "Milan Petrović" (Fig.  1 D). On this building, the NBS was implemented by installing an extensive green roof with an area of 480 m 2 above the physical training hall, a small green wall with an area of 80 m 2 , and a solar power plant with the power of 120 kW on the roof of the school. The SPSE "Milan Petrović" school is the largest building in Novi Sad housing an education institution. It was built in 2010 as a detached building on a rectangular plot with a total area of 11,538 m 2 . The gross area of the building is 7244.64 m 2 , while the net area is 6034.15 m 2 ; where the ground floor area is 4175 m 2 , and the total heating area is 5719 m 2 . The size of the building and its multiple purposes required complex construction solutions, and it was divided into several parts, with different purposes and functionalities and thus with different thermal zones [ 40 , 42 ].

Monitoring methodologies and data sets

Monitoring thermal micro-scale conditions around a facility in novi sad.

As one of the GReENERGY project outcomes, four static Davis Vantage Pro2 automatic weather stations (AWS) equipped with Globe sensors, were deployed around the SPSE "Milan Petrović" building in Novi Sad (Republic of Serbia). This AWS network was used for the comprehensive monitoring of climate and outdoor thermal comfort conditions on a micro-scale. The criteria for the selection of sites included their suitability for data acquisition and the availability of electricity and security requirements. All stations were mounted on building walls of different heights (Fig.  2 ). Each station was equipped with a Davis Vantage Pro2 sensor set, sensors for measuring air temperature, air humidity, wind speed and direction and solar radiation, and with a Testo Globe sensor. The Tg is referred to as the globe temperature or black globe temperature and it resembles the thermal values of the environment, simulating the thermal conditions felt by the human body [ 44 ]. AWSs measure new data every 10 min and each measurement time is recorded as UTC. Based on previous research [ 45 , 46 , 47 ], the 10-min interval used for measuring of the environmental variables proved to be sufficiently frequent for climate and bioclimate analysis.

figure 2

Locations of the AWSs installed around the SPSE "Milan Petrović" building in Novi Sad (Republic of Serbia)

This study is based on the analysis of a 10-min interval data set from all four AWS: 301—roof/street side; 302—schoolyard/solar panels; 303—green roof; and 304—schoolyard/garages (Fig.  2 ). Furthermore, the research period covered the year 2022, with the focus on heatwaves and "hot day" conditions during the summer season. “Heatwave” is defined as a period with a minimum of three consecutive days with maximum air temperatures higher by 5 °C or more than the average temperature for a particular period of the year. According to the generally accepted definition, "hot day" is a day when the maximum air temperature is at least 30 °C [ 48 ]. This "hot day" threshold is representative of the climate conditions in Germany and can, therefore, be considered as representative of Central Europe and a part of Southeast Europe, which have similar climate characteristics. Finally, for spatial and temporal thermal assessments, the air temperature ( Ta ) data set was used together with the globe temperature ( Tg ) data sets.

Monitoring the thermal transmittance of the facility in Osijek

This research used the heat flow meter (HFM) method to measure the U value of a flat concrete roof before the energy refurbishment of the building, after the application of a thermal insulation layer on the roof and finally, the U value of the green roof measurement. This method is a non-destructive, standardized procedure, often used to estimate the thermal transmission properties of plane building components. It is based on creating a minimal temperature gradient between the indoor and outdoor temperatures to guarantee adequate heat transfer. It is particularly useful for flat building elements with opaque layers that are perpendicular to the heat flow and do not have significant lateral heat transfer [ 49 ]. The first ISO 9869 standard providing the guidelines for the HFM in situ measurement of thermal transmittance and thermal resistance was introduced back in 1994 and, subsequently, in 2014 it was technically revised according to ISO 9869-1:2014 [ 49 ]. The ISO 9869-1:2014 standard outlines that the procedure for measuring thermal transmittance involves the direct measuring of heat flow rate and temperatures on both sides of the building element under steady-state conditions. To obtain the U value of the tested element, at least one heat flow meter should be positioned on the surface of the element that is in contact with a more stable temperature, in addition to two ambient temperature sensors. According to ISO 9869-1:2014 [ 49 ], it is necessary to conduct measurements for at least 3 days to estimate the U value of the element if the temperature around the HFM is stable. If the measurement cannot be completed within 7 days, the time interval should be extended accordingly.

Figure  3 A shows the layout of measurement devices placed in the building during the measurement process. The position of the heat flux sensor was determined using infrared thermography, which helped avoid errors resulting from thermal bridges, cracks, construction joints and other similar factors of the roof, Fig. 3 B and C. According to Albatici et al. [ 50 ], site-related factors that can affect thermal performance include weather conditions before and during the test, such as wind speed, solar radiation, precipitation, and humidity, particularly in relation to the site's typical climate. Building-related factors, such as the aging of materials and proper installation during construction, have a significant impact. Lastly, the operating conditions, such as building user management and maintenance work, are considered the most influential factors. In general, the level of agreement between measured and calculated U values varies considerably and the degree of discrepancy depends very much on the type of the examined structure [ 51 ]. In this research, the calculated U values are not presented since the research goal was to determine the in situ difference of the U values for different conditions of the flat roof and to determine the contribution of the green roof installation to the reduction of U values. According to the ISO 9869-1:2014 standard, the uncertainty of in situ measurements performed by HFM ranges from 14% to 28% [ 49 ].

figure 3

A Layout of measurement devices during measurements; B positioning the heat flow metres on the surface of the element using infrared thermography, before; C and after energy refurbishment

Throughout the measurement process, data must be recorded continuously at predetermined intervals. In this research, a 10-min interval was applied. To obtain accurate measurements, the impact of heating/cooling systems, rain, snow, and solar radiation was minimized in the following way: (a) the first measurements lasted for 13 days (further labelled as Measurement M1 ) for the concrete flat roof before the energy refurbishment of the building (Fig.  4 A); (b) the second measurement (Measurement M2 ) lasted for 23 days after the application of thermal insulation (20 cm of mineral wool) (Fig.  4 B); and (c) the third measurement (Measurement M3 ) lasted for 13 days after the green roof installation (added 8 cm of substrate at the top of the building) (Fig.  4 C). The three measurement campaigns were performed between December 2019 and February 2023.

figure 4

A Concrete flat roof before energy refurbishment; B construction work in progress during the application of thermal insulation on the flat roof; C green roof after the completion of energy refurbishment

The assessment of thermal outdoor conditions on a micro-scale

The AWSs around the school building in Novi Sad were in function from 2021, but during the monitoring time, there were different technical and software issues due to which a certain amount of data was missing. Therefore, to provide relevant thermal assessments, a shorter research period was used in this study and it was limited to the data sets from the summer season when hot days were detected. The overall effect of the assessment can be explained logically because the goal of the research is to present possible effects of NBSs during hot thermal events—in this case during periods/days with very high air temperatures.

Table 1 presents very small differences in Ta values between AWSs during both selected heatwaves in the summer of 2022. In general, the lowest values appeared at AWS 303, and compared to other AWSs, the differences ranged from 0.0 °C (June/Max, July/Average) to 1.5 °C (July/Max—303/302), particularly for Average and Max values . The situation is clearer for Tg values, where in all cases, the temperatures from AWS 303 were lower than those collected at other stations, and the most notable differences were for Average and Min values . Tg differences reach up to 3.3 °C (July/Min—303/302) and only in one case the lowest Tg value appeared at AWS 304 (July/Max) (Table  1 ).

Table 2 presents Ta and Tg differences between AWSs on the hottest day (July 23rd) during the heatwave period in July 2022. Thermal assessments were done for daytime (9.00–17.00 UTC) and night-time (19.00–5.00 UTC), respectively. Again, Ta differences were in both cases (daytime and night-time) quite small—in most cases less than 1 °C, and the minimum values were captured at AWSs 303 or 304. In the case of Tg values, differences were more prominent, particularly during night-time. During daytime, the lowest Tg values were captured at AWS 304, and the highest values came from AWS 302. The highest value for Minindex came from AWS 303 (44.8 °C). During night-time, the lowest Tg values in all cases were captured at AWS 303 and differences ranged from 2 °C (Min 303/304) to 3.8 °C (Max 303/302) (Table  2 ).

Figures  5 and 6 graphically present Ta and Tg changes during daytime (Fig.  5 ) and night-time (Fig.  6 ) on July 23rd 2022. According to Fig.  5 A, Ta values at AWS 303 were constantly lower than those at AWSs 301 and 302 between 9.00 UTC and 15.00 UTC, and these differences reached almost up to 3 °C. After 15.00 UTC, the Ta values were higher at AWS 303 than at AWS 302, and the difference reached up to 1 °C. The situation was different as regards the values obtained at AWS 303 and AWS 304, where Ta differences were around 0 °C, and in a few cases, Ta was higher at AWS 303. Similar tendencies can be observed for Tg differences between AWS 303, AWSs 302 and 304 (Fig.  5 B). The results show that from 9.00 UTC to 14.00 UTC, Tg was constantly lower at AWS 303 (from 0 °C to 16.5 °C) than at AWS 302, or similar (from -3 °C to 5.8 °C) to AWS 304. However, after 14.00 UTC, until late afternoon, the Ta values were in both cases higher at AWS 303 with thresholds up to 14.8 °C (AWS 302) and 12.5 °C (AWS 304). Figure  6 A presents the Ta differences between AWSs during night-time, and the results show minimal differences to AWS 303, i.e. they mostly range from 0 °C to ± 1 °C. Greater Ta differences between AWS 303 and other AWSs started to appear with the sunrise time. Figure  6 B shows the Tg differences during night-time, when the values captured at AWS 303 were constantly lower than those obtained at AWSs 302 and 304. The Tg values captured at AWS 303 were lower by 2 °C, with a tendency for the difference to increase to 10 °C after the sunrise time.

figure 5

Thermal differences (in °C) between AWSs during the hottest daytime (July 23rd, from 9:00 to 17:00 UTC) during the heatwave in July 2022, A Ta differences; B Tg differences

figure 6

Thermal differences (in °C) between AWSs during the hottest night-time (July 23rd/24th, from 19:00 to 5:00 UTC) during the heatwave in July 2022, A Ta differences; B Tg differences

Thermal transmittance results for green roofs

All three measurements ( M1 , M2 and M3 ) were carried out during the winter season, when heating was provided, so as to reach the minimal temperature difference required (15 °C or higher) between indoor and outdoor air. Two sets of heat flux sensors were used to determine the U value.

Since this research aimed to determine the influence of additional roof layers on the U value, the following conclusions have been made from the results presented in Table  3 : (a) by applying a 20 cm thick insulation layer on the non-isolated flat roof, the U values decreased from 75% to 78% (Fig.  7 ); (b) by applying a green roof with a 8 cm thick substrate at the top of a refurbished flat roof, more savings could be achieved because the U values decreased from 50% to 69%, as registered by two different heat flux sensors; (c) since the U value of building elements indicates energy loss, the insulation layer and the green roof can significantly prevent heat loss through flat roofs; (d) the differences in the U values from two sensors during the last measurement can be easily explained by the position of the sensors, as the roof was heavily isolated during the last measurement ( M3 ), and therefore, thermal bridges were not visible when using infrared thermography (Fig.  3 C); on the other hand, they can be easily avoided on non-insulated roofs (Fig.  3 B).

figure 7

Decreased initial U values ( M1 ) after the application of the insulation layer ( M2 ) and the green roof ( M3 )

In this study, the influence of NBSs on the improvement of thermal conditions on a micro-scale and the energy demand of buildings was assessed using extensive green roofs as an example. AWSs were placed around the school building in Novi Sad with the intention of identifying thermal influences from different types of surfaces and materials, i.e. they were deployed to monitor microclimate characteristics near or above the green surface, solar cells, walls and concrete. The focus of this study is to identify the impact of different green or artificial surfaces on thermal conditions, particularly during hot days and heatwaves. The Ta and especially Tg values were lower (by about 1 °C to 2 °C) at AWS 303 (above the green roof) than at other AWSs, particularly in case of the Min and Average indices (Table  1 ). Furthermore, the thermal assessment during daytime and night-time on very hot days shows more significant differences in Ta and Tg (Table  2 , Figs. 5 and 6 ). Interestingly, the Ta and Tg differences between AWS 303 and other AWSs during daytime vary from negative to positive values depending on the daytime period, but constant negative difference values ( Tg , lower values on the AWS 303) were captured during night-time, and they ranged from − 0.5 °C to − 4 °C (Fig.  6 b). These results indicate that an extensive green roof (with a 7.5 cm thick soil substrate and low vegetation—sedum mix), could contribute to better microclimate conditions, especially in terms of reducing thermal discomfort events during hot days, and even more during tropical nights. The daytime Ta and Tg results indicate that thermal differences between micro-locations are due to the direct influence of shadow or sunlight. As shown in Fig.  5 a, AWSs 301 and 302 were exposed to sunlight from the morning (9.00 UTC) to the afternoon (15.00 UTC), and AWSs 303 and 304 were in the shadow of the buildings and trees for most of the period. After 15.00 UTC, AWSs 301, 302 and 304 were in the shadow of trees and buildings on the south and west sides, while AWS 303 was still exposed to sunlight until sunset because of its relative height. The constantly lower Tg values from AWS 303 (above the green roof) throughout night-time can be explained by the different capacity of heat absorption and the upward longwave radiation intensities of various surfaces. Obviously, the outcomes of this study are generally in line with the literature data [ 52 , 53 ], confirming that various artificial surfaces, green/blue surfaces and urban designs can lead to different climate/thermal situations on a local- and micro-scale in cities. Therefore, it can be confirmed that a green infrastructure could have a positive impact on thermal comfort conditions on the micro-environmental level [ 26 , 27 , 28 ]. Based on a multi-type green infrastructure evaluation in Toronto (Canada) based on monitoring over two summers, green roof systems ensure an average reduction of the near surface air temperature by 0.8 °C [ 6 ]. Another study conducted in the same city (Toronto) shows a general reduction of CO 2 near a green infrastructure of up to 6% [ 3 ]. The results of this study are generally consistent with the previous works confirming the cooling potential of heat mitigation and the thermal energy reduction in buildings in Singapore [ 54 ], Utrecht [ 55 ], Beijing [ 56 ], Baltimore–Washington metropolitan area [ 57 ], particularly during extreme heat conditions. In addition, previous studies focusing on micro-environmental areas in Novi Sad, confirm that green infrastructures, as well as building shadows, could contribute to preventing outdoor thermal discomfort conditions [ 58 , 59 , 60 ]. Likewise, some studies show that urban trees and intensive green infrastructures are more effective in reducing outdoor thermal values than green roofs or green walls [ 61 , 62 ].

The measurements carried out in Osijek focused mainly on the thermal transmittance properties of the flat roof. The accurate identification of the thermal properties of existing building components can be challenging, especially for historic and heritage buildings, due to their technological complexity and heterogeneity of material deterioration [ 63 ]. Thermal transmittance properties can be influenced by occupant activities and behaviour, changes to the material and design, ageing, construction defects, technological performance, building operation and maintenance [ 63 , 64 , 65 , 66 ]. Studies have demonstrated that minor alterations in thermal transmittance ( U value, W/m2K), which is a significant parameter for forecasting energy usage, can lead to a substantial shift in heating requirements [ 67 , 68 ]. As expected, the actions taken on the building in Osijek led to an decreased energy demand, i.e. a decreased U value of the flat roof due to the implementation of thermal insulation and later a green roof. By reducing the U values of building elements, energy demands are reduced, leading to reduced operational building costs and CO 2 emissions. According to the study “Estimation of benefits and costs from the GReENERGY project” [ 69 ], the general reduction of CO 2 emission from both public objects in Novi Sad (Republic of Serbia) and Osijek (Republic of Croatia) amounted to 298.6 t/per year, and the cost savings ranged from 12.000 EUR in 2021 to 18.000 EUR in 2034.

To conclude, the averaged U value from two sensor sets can be used. The average U value for the flat roof before the energy refurbishment of the building was 1,5689 W/m 2 K; for the flat roof after thermal insulation, the U value was 0,3676 W/m 2 K and 0,1490 W/m 2 K for the flat green roof. That means that the U value for the flat green roof is by 59% lower than the value for the insulated roof, and it is by 91% lower than the value for the flat roof before energy refurbishment. The values presented here can be multiplied by the surface of the flat roof (160 m 2 ), with respect to the average temperature difference during the measurement, and can be used to calculate energy savings (in kW or kWh if multiplied by numbers of the building’s operational hours) for 1 year.

The feasibility and future of applying nature-based solutions to decrease the energy demand in public buildings

The implementation of NBSs requires an in-depth feasibility study to evaluate the economic, ecological and energetic benefits of the applied solutions. Before applying adaptations on the two public buildings in Osijek and Novi Sad, a feasibility study was carried out to prove that an actual decrease in the overall amount of required electricity and CO 2 emissions would occur. This decrease was made possible by implementing two principles in both facilities: (a) decreasing energy demand by reconstructing buildings and (b) generating own energy per se, using photovoltaic power plants. In a public building in Osijek, the required amount of electricity per year, according to its energy certificate, was 382.111.60 kWh. After the adaptations (building reconstruction + green roof implementation), the amount decreased to 171.202.80 kWh, which is less than half of the initial requirements.

According to the energy certificate for the same building, the usable surface of the heated area is 878.65 m 2 with the specific emission of CO 2 of 121 kg/(m 2 a) per year, or 106.32 t per year. Since the surface area after the reconstruction (building reconstruction + green roof implementation) remained the same, the amount of the specific emission of CO 2 decreased to 50 kg/(m 2 a), which is equal to 43 t per year (instead of the initial 106.32 t) [ 69 ].

Although this paper presents the results of specific examples of NBS implementation, there are still topics that could be discussed in future adaptations of this kind. The problem that should be addressed is power plant selection. At the moment, there is no information about whether the current power plant can reach its maximum potential, or a more suitable one would be a better choice. To provide information about the best choice per specific micro-location, additional measurements and analysis should be performed. To achieve this, additional monitoring data from the current power plant data-loggers should be combined with micro-meteorological measurements provided from AWSs, bringing together the results regarding the financially most suitable type and the power of solar panels for specific micro-climate locations.

This study presents the results of the assessments of microclimate conditions and the thermal transmittance of/around public buildings in Novi Sad (Republic of Serbia) and Osijek (Republic of Croatia) based upon multi-year monitoring data sets from different seasons. Based upon its outcomes, it can be concluded that green infrastructure, known as NBS—in this case, an extensive green roof—has an impact on diverse aspects of urban environments and the energy conditions of buildings. The positive effects are visible both in summer periods and during the winter season. The results show that extensive green roofs can slightly improve thermal conditions on a micro-scale during hot days, as well as that the green infrastructure is particularly effective during tropical nights. In addition, the 8 cm thick extensive green roof can contribute to energy efficiency during the winter season by improving the thermal transmittance of building walls and ceilings. In both cases, the green infrastructure is helpful in improving the outdoor thermal comfort conditions, urban biodiversity, using less heating energy and preventing increased CO 2 emissions (public buildings use gas or oil and in some cases coal or electric power for heating).

Therefore, this kind of monitoring and assessment can help local communities in their struggle against carbon emissions, which endanger the urban environment, and it can serve as a good example of the implementation of NBSs on the local or micro level. In addition, this research is in line with the Agenda 2030, which defines 17 different Sustainable Development Goals (SDGs), but it primarily focuses on the following: SDG 3—an increased awareness of the necessity of improving public healthcare through the monitoring and improvement of thermal outdoor comfort conditions; SDG 11—contributing to a better implementation of climate-conscious urbanisation that can improve the quality of life, microclimate conditions and contribute to the development of carbon–neutral cities; and SDG 13—work on further measures towards the adaptation to climate change, especially in urban areas where the microclimate and local climate are additionally modified due to the impact of urbanisation.

Availability of data and materials

Not applicable.

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Acknowledgements

The authors would like to thank Milica Ševkušić from the Institute of Technical Sciences of the Serbian Academy of Sciences and Arts for proofreading this manuscript.

The implementation of green infrastructures (green roofs) on public objects was supported by the Interreg-IPA CBC Croatia-Serbia program through the GReENERGY project (no. HR-RS290).The research and assessments were supported by the project entitled: "Improving the environment in Vojvodina to adapt to climate change and reduce the risk of natural disasters" (no. 142-451-3485/2023-01), funded by the Autonomous Province of Vojvodina (regional government).

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Savić, S., Krstić, H., Šećerov, I. et al. Decreasing the energy demand in public buildings using nature-based solutions: case studies from Novi Sad (Republic of Serbia) and Osijek (Republic of Croatia). Energ Sustain Soc 14 , 23 (2024). https://doi.org/10.1186/s13705-024-00455-2

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Energy, Sustainability and Society

ISSN: 2192-0567

case study weather monitoring system

Case study: reducing heating energy consumption in a high tunnel greenhouse with renewable energy and microclimate control by bench-top root-zone heating, bench covers, and under-bench insulation

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  • Published: 11 May 2024
  • Volume 5 , article number  86 , ( 2024 )

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case study weather monitoring system

  • Hei-Young Kim   ORCID: orcid.org/0009-0005-8490-9565 1 ,
  • Ok-Youn Yu 2 &
  • Jeremy Ferrell 2  

Appalachian State University's Nexus project designed an efficient greenhouse heating system that integrated renewable energy and root zone heating technology to reduce the greenhouse heating energy burden on local farmers and installed it at local cooperative farms. This study analyzed 5 years of data from 2018 to 2022 to investigate the energy savings and microclimate control effectiveness of the Nexus heating system installed at Springhouse Farm in North Carolina, USA. By varying bench cover materials, bottom insulation, and the number of loops of root zone tubing, the different soil temperatures required for plant types and growth stages were achieved with a single temperature controller. A root zone heating fluid of 32.2 ℃ satisfactorily maintained the germination soil between 20 and 25 ℃ in March 2019 with an average outside temperature of 4.8 ℃ and an average low temperature of − 0.4 ℃. Growing soil maintained an average temperature of 15 ℃ with bottom insulation and an average of 11–12 ℃ without bottom insulation. Compared to the conventional heating system (a forced-air propane unit heater alone), weather-adjusted propane consumption (propane usage divided by heating degree days) was reduced by 65% with the Nexus system alone and 45% with the Nexus system and unit heater together. It shows that the Nexus system has significantly reduced greenhouse heating energy consumption and maintained productive conditions. The renewable energy fraction ranged only 9–13% of the total thermal energy used due to the high inlet temperature entering the solar thermal collector. This can be improved by separating the heat storage and backup heat source.

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1 Introduction

Research conducted by the Appalachian Sustainable Agriculture Project (ASAP) revealed that demand for locally grown produce exceeds current spending by 260% in western North Carolina (NC) [ 1 ]. This unmet demand for locally grown food indicates that the potential exists for increasing rural farmers’ income in the region [ 1 , 2 ]. However, regional barriers, including a relatively short growing season and mountainous terrain, hinder this benefit by limiting the availability of locally grown produce along with consistency and access [ 3 , 4 ]. Many farmers in the region are small-scale, family-owned, and struggle to maintain profitability with limited resources, resulting in low farming income and high rates of off-farm income sources [ 4 , 5 , 6 ]. In Southern Central Appalachia, which includes the area this study focuses on, 64% of farms had an average net loss of $10,734 per farm in 2017 [ 4 ].

Growing season extension through greenhouse production has been proposed as a key solution that simultaneously meets the demand for productivity improvement and local produce in the region [ 1 , 2 ]. High tunnels’ relatively inexpensive installation cost ($32–47/m 2 ) attracts small-scale farmers, so they are commonly used for growing season extension either by passive means or with active heating and ventilation systems [ 7 ]. However, the high heat loss rate (U-value: 6.4 W/m 2 ·K) of polyethylene, the main material of the high tunnel, does not assure its envelope thermal insulation [ 8 , 9 ]. In addition, the requisite energy costs exclude many rural farmers from being able to afford a heated greenhouse [ 10 , 11 ]. Therefore, farmers in this region, with the late frost/freeze and cold snaps in spring, struggle to balance the economic viability of high tunnel crop production with energy costs.

Heating energy is one of the main overhead costs in greenhouse production in temperate climate regions and thus serves as a key factor in increasing agricultural productivity [ 12 , 13 ]. Forced-air unit heaters are chosen by many growers because they are easy to install and have low initial costs, but the heated air rises upward, increasing the temperature difference between the inside and outside of the greenhouse ceiling, causing large heat loss [ 13 ]. Additionally, unit heaters are frequently installed high up in the greenhouse to secure cultivation space, and energy is wasted by heating the entire greenhouse rather than the plant areas.

Local heating and temperature control are efficient ways to save energy. Because each organ of a plant has a different sensitivity to heat, uniform temperature control of the entire greenhouse is not necessary [ 14 ]. Root zone heating (RZH) has been suggested as an effective heating method that simultaneously enhances plant health and saves heating energy [ 14 ]. Maintaining root zone temperatures within the optimal range, even at low greenhouse air temperatures, promotes root growth, activity, and nutrient uptake, leading to improved aboveground biomass and increased yields with reduced disease risk in studies of tomato crops [ 15 , 16 ]. On the other hand, because root growth is sensitive to temperature, low root zone temperature restricts the growth of the entire plant even when optimal greenhouse air temperatures are provided [ 14 , 17 , 18 ].

Compared to conventional heating systems that heat air, RZH lowers the temperature difference between the greenhouse surface and the outside air, resulting in reduced conductive heat loss through the greenhouse plastic [ 19 ]. As warm roots allow lower ambient temperature, nighttime air temperature can be lowered by 2.8 to 5.6 ℃ when using RZH [ 13 , 15 , 20 ]. Several RZH methods, such as carbon crystal electrothermal film, hydronic tubing system, electric heating mats, and heated hydroponic system, have been investigated by researchers, demonstrating that RZH effectively controls soil temperature and provides a favorable environment [ 15 , 16 , 21 , 22 ].

Another effort to save greenhouse energy is the application of renewable energy. Due to the rising cost, depletion, and negative environmental impact of fossil fuels, interest in the application of renewable energy in greenhouse production has increased, and technologies such as solar thermal systems and earth-air heat exchangers (EAHE) have been investigated for greenhouse [ 11 , 23 , 24 ]. These technologies include heat exchangers and heat storage such as soil, water, or phase change materials to increase greenhouse air temperature and maintain the appropriate temperature required for crops during the night [ 11 , 23 , 25 ]. Mehmet Esen [ 11 ] conducted an experimental study by designing a heating system that integrated biogas, solar thermal energy, and ground source heat pump under the winter climate conditions of eastern Turkey, and presented its potential as an efficient heating system [ 11 ]. However, most studies in greenhouse heating have been conducted in experimental greenhouses for short periods (usually less than a year) or through simulations, and few studies have been conducted on commercial greenhouses to demonstrate the effectiveness of their system design in a real production environment. In addition, only a few studies have investigated RZH performance in terms of greenhouse energy saving [ 14 ].

Appalachian State University’s sustainable energy project, the Nexus, developed an unique greenhouse heating system by integrating renewable energy and RZH to enhance energy savings and installed it at two local cooperative farms [ 26 ]. The heating system collects thermal energy from a solar thermal collector and a small-scale pyrolysis system (biochar kiln) and efficiently delivers heat to crops in a greenhouse through RZH system. We designed a biochar kiln and integrated it into the Nexus system. This innovative approach allows us to harness woody biomass, which is abundant in our region, for dual purposes: producing biochar as a valuable soil amendment and supplying heat energy during periods when solar energy is unavailable. [ 26 ]. This system was designed to be practical and capable of being added to an existing greenhouse.

The purpose of this study is to investigate the performance of the Nexus greenhouse heating system at Springhouse Farm in North Carolina, USA on microclimate conditions in terms of soil temperature and energy savings over 5 years of operation. The effectiveness of the under-bench insulation and bench covers installed in reducing heat loss from RZH was explored. Energy savings (propane consumption) were compared considering weather conditions each year. This study holds significant importance as it conducted a long-term evaluation of the RZH system, which integrates renewable energy within a commercial greenhouse. The evaluation focused on energy savings, with adjustments made based on weather conditions.

2 Research questions

To evaluate the system in terms of energy savings and productive microclimate conditions, the following questions were established:

How efficient are RZH systems compared to conventional forced air heating?

What is the share of renewable energy in the energy saved through the Nexus pilot system?

Can the heating system with improved bench covers maintain productive growing conditions without running forced air heating?

How does the heat loss, which depends on the material of the bench cover, affect the soil temperature?

How does under-bench insulation affect soil temperature?

3 Methodology

3.1 description of greenhouse at springhouse farm and nexus heating system.

Springhouse Farm has a 6.1 m by 9.1 m high tunnel greenhouse consisting of double polyethylene (PE) film and air-inflated between the layers. Inside the greenhouse, there are four growing benches and one germination bench. The greenhouse is used primarily for germination and propagation with work beginning in late January to early March. Before the proposed heating system was installed, they used a propane forced-air unit heater and electric heat mats for early germination.

In late 2017, the Nexus team designed and installed a greenhouse heating system to reduce propane consumption through renewable energy and efficient RZH heat distribution [ 26 ]. The system includes a solar collector, a biochar kiln, a food dehydrator, heat storage, and an RZH system (Fig.  1 ).

figure 1

Nexus pilot system at Springhouse farm, Vilas, NC. a solar thermal collector and food dehydrator; b biochar kiln; c main plumbing and water heater (heat storage)

A heat transfer fluid, 50% propylene glycol–water solution, flows through the system to collect heat and deliver it to the plant rooting zone inside the greenhouse. The thermal collection components include a 30 evacuated-tube-solar thermal collector and a biochar kiln with a built-in heat exchanger. A differential controller controls circulation pumps to collect heat from renewable sources (e.g., sun or biomass) and delivers the heat to the heat storage, a 151.4-L propane water heater located inside the greenhouse. The propane water heater is a storage of heat collected from renewable energy system and is also used as a backup heat source.

The stored heat is distributed to crops on a germination bench and four growing benches through the RZH system (Figs.  2 and 3 ). All benches are 1.2 m wide and 2.4 m long. Christenbury’s report was referred for the RZH piping design of the Nexus system [ 20 ]. Manifold and main pipe were built with 25 mm, 19 mm, and 13 mm PVC pipes and fittings. The 25 mm main pipe was buried 0.3-m-deep in the ground. To distribute heat to the crop root zone (soil) on the benches, 6.35 mm PE drip irrigation tubing was installed due to its ease of acquisition and installation. The RZH tubing and the benches are connected in parallel to provide even flow rate (Fig.  3 ).

figure 2

a RZH tubing on growing benches; b RZH thermal image

figure 3

Schematic of the Nexus heating system at Springhouse Farm [ 26 ]

For sufficient heat transfer, the velocity must be kept below 2 m/s [ 20 ]. Flow rate is the product of velocity and pipe cross-sectional area, so a flow rate of 0.53 l/min or less in 6.35 mm PE tubing (4.32 mm ID) provides adequate heat to the soil. Based on the overall piping design, the total flow rate and friction loss were calculated to select a pump of an appropriate size for RZH circulation. Through preliminary experiments, we found that 37.8 ℃ water through 9 loops (4.9 m per loop) of 6.35 mm PE drip irrigation tubing on a 1.2 m by 2.4 m bench, the temperature of the soil in seedling trays were maintained at 12.8–15.6 ℃ evenly. Based on it, 9 loops of PE tubing were placed on each growing bench and 18 loops on the germination bench for a higher soil temperature.

The RZH circulation pump is regulated by the thermostat that senses the germination soil temperature. A mixing valve mixes the higher-temperature fluid from the heat storage (a 151.4-L propane water heater) with the lower-temperature fluid from the RZH return pipe to discharge the 32.2 ℃ mixed fluid to the RZH supply pipe. When all the heat collected from the renewable energy system is used up and the temperature of the fluid in the heat storage (water heater) drops below 32.2 ℃, the propane gas burner of the water heater ignites to maintain the temperature of the fluid above 32.2 ℃. The water heater has only two setpoints, 32.2 ℃ and 48.9 ℃, and it was set to the lower temperature of 32.2 ℃. During the warm season when heating is not needed in the greenhouse, the collected heat bypasses the water heater and is instead dumped into the food dehydrator where the heat can be used to dry food (Fig.  3 ).

3.2 Weather indicators and energy (propane gas) savings

Weather and propane gas usage data from 2016 through 2022 were compared. To compare each year’s weather conditions, heating degree days (HDDs) were calculated, and the number of days with freezing temperatures (below 0 ℃) was recorded. The HDDs is a measure of how much the outside temperature is below a certain level (base temperature) in degrees for given days and used to estimate the demand of heating energy in a building [ 27 ]. It is relative to a base temperature and obtained by subtracting the average temperature of the day from a base temperature:

where, HDDs is the sum of the differences between average temperature of day n (T n-a ) and a base temperature (T base ) over given days. In this study, the unit heater’s setpoint temperature of 12.8 ℃ in 2016 and 2017 before using the Nexus system was set as a base temperature. All the HDDs from the day the greenhouse heating started to the end of May were summed to measure how cold the temperature was during the heating system operation. Because the weather varies every year as well as the period of the greenhouse heating, we compared the total propane consumption of each year by dividing it by HDDs.

3.3 Overall renewable energy gains

The overall heat gain from the Nexus system’s collection components (the solar thermal collector and the biochar kiln) was calculated in kJs from 2018 through 2022. All the heat energy gained from the solar collector and the biochar kiln is stored in the water heater (heat storage). Therefore, the temperature rise of the water heater during daytime (or biochar kiln operation) was used to calculate the amount of renewable energy gained. We looked at the days with no solar energy gained, such as cloudy and rainy days, and then averaged the water heater temperature on those days. This was the baseline water heater temperature, whereby only propane was used to heat the fluid.

The difference between the baseline temperature and the maximum water heater temperature of each day is the temperature rise by solar radiation or biochar kiln burn. Therefore, the thermal energy gained from the renewable energy system can be calculated by multiplying the total degrees of rise, mass, and specific heat of 50% propylene glycol–water solution. Total heat gains for renewable energy system can be calculated as follows:

where, Q total is total heat gains for renewable energy system; m is a mass of 50% propylene glycol–water solution; C P50 is the specific heat of the solution; t n,max is maximum temperature of the water heater of day n; and t 0 is a baseline temperature of the water heater. We turned off the propane water heater when the daily low temperature outside was constantly above 10 ℃: May 8 in 2018, May 16 in 2019, May 14 in 2020, May 27 in 2021, and May 25 in 2022. After turning off the water heater, the water heater is not a backup heat source, and the soil is heated only with renewable energy at night. The minimum temperature of the water heater on each day was the baseline temperature after turning off the water heater.

The amount of thermal energy generated by a biochar kiln is influenced by many variables such as moisture content of the combustion chamber and biomass, so we refrained from using the biochar kiln during the greenhouse heating period to focus on the system’s solar energy collection for the reliable results.

3.4 Heat loss reduction with a lower U-value bench cover

Bench covers were used to trap heat. The bench cover used in 2018 was made of 0.15 mm thick polyethylene film. In 2019, we upgraded the bench covers to reduce heat loss (Fig.  4 ). We built zippered growing bench covers using 0.15 mm-thick polyethylene film for easy opening and closing, and they were placed over gable frames made of PVC pipes. The germination bench cover was constructed using wood frames and four 0.6 m by 1.2 m, 8 mm double wall polycarbonate panels. U-value, the overall heat transfer coefficient, of an 8 mm double wall polycarbonate panel is 3.03 W/m 2 ·K, which is smaller than half of the U-value of single polyethylene film, 6.4 W/m 2 ·K [ 8 , 9 ].

figure 4

Upgraded bench covers in 2019: a germination bench with polycarbonate cover; b growing bench with zippered polyethylene cover

The effect of the improved germination bench cover was evaluated by three methods: (1) the germination soil temperature, (2) the ignition time interval of the propane water heater, and (3) temperature difference between germination soil and greenhouse air. We compared the germination bench soil temperatures in March 2018 and March 2019. The temperature data collected every minute for March each year were converted into a daily distribution and depicted in one chart.

Since the RZH system is controlled by the germination soil temperature, we anticipated that the lower U-value of the upgraded germination cover would result in longer intervals between propane ignition in the water heater. We recorded the number of minutes that it took from one peak temperature to the next in the water heater between midnight and 8 a.m. on cold nights in March 2018 and March 2019.

3.5 Under-bench insulation

Heat transfer occurs through conduction, convection, and radiation and can be reduced by insulation and reflective film. Different insulators were installed under the RZH tubing (Fig.  5 ) of each bench using extruded polystyrene board (XPS) and reflective bubble insulation. XPS is a common insulation material for buildings that provides good resistance to thermal conduction and convection. The R-value, a measure of insulation ability, of the 1-inch XPS used in the project is rated 0.88 K m 2 /W [ 16 ]. The R-value of reflective bubble insulation varies depending on the installation location and conditions [ 28 ]. It has a small R-value in the material itself with air bubble wrap, but the level of insulation can be increased by minimizing convection and radiation with its low-emittance and almost leak-free reflective surface [ 29 ]. In addition, since there are reflective surfaces on both sides of the air layer, another reflective airspace can be formed when installed, which can enhance the overall insulation [ 28 , 29 ]. Reflective surfaces reflect heat radiated from surrounding heat sources. Thus, the reflective bubble insulation installed below the RZH tubing reflects radiant heat toward the plants located above the tubing.

figure 5

Growing bench insulation: a bench 1 with XPS and reflective bubble insulation; b bench 2 without insulation; c bench 3 with reflective bubble insulation; d bench 4 with XPS

The tubing on growing bench 1 is placed over both XPS and reflective bubble insulation, while bench 3 and bench 4 contain only reflective bubble insulation and XPS, respectively. Bench 2 has no insulation.

4 Results and discussion

4.1 setpoints of control systems.

Table 1 summarizes the setpoint temperatures of the unit heater, the RZH system, and the ventilation fan used from 2016 to 2022 to maintain the appropriate growing conditions at Springhouse Farm. In 2016 and 2017, before the Nexus system was installed, the unit heater was set to 12.8 ℃. RZH allows for lower greenhouse air temperature, we reduced unit heater setpoints [ 13 , 15 , 20 ]. After the Nexus system was installed, the unit heater was not operated (2019 and 2020) or was set to 8.9 ℃ (2018, 2021 and 2022), which is 3.9 ℃ lower than previous settings.

4.2 Weather indicators and energy (propane gas) savings

Table 2 shows each year’s HDDs the number of days when the outside temperature is below 0 ℃, and propane usage. Because the weather varies every year as well as the period of the greenhouse heating, the total propane consumption of each year was divided by HDDs (propane usage/HDDs) to compare the weather-adjusted propane gas consumption.

Since 2018, the year when the Nexus system started operation, weather-adjusted propane gas consumption has decreased significantly compared to 2016 and 2017. The average weather-adjusted propane gas consumption was 1.72 for the unit heater only (2016 and 2017), 0.6 for the Nexus system only (2019 and 2020), and 0.95 for both uses (2018, 2021, and 2022). It decreased by more than 65% when only using the Nexus system and by more than 45% when using both the Nexus system and the unit heater.

4.3 Overall renewable energy gains

Table 3 shows the properties of 50% propylene glycol–water solution and the renewable energy harvest (kJ) during the operation of the heating system. The renewable energy fraction, which represents the share of renewable energy in total thermal energy consumption, varies based on several factors. These factors include solar irradiation, the renewable energy collection period, and propane consumption, all of which are influenced by the weather conditions during the year. On average, this fraction ranged from 9 to 13% annually.

4.4 Heat loss reduction with a lower U-value bench cover

4.4.1 germination soil temperature.

Figure  6 plots the daily temperature distribution of germination soil in March 2018 and March 2019. The average outside temperature and average low temperature were 3.9 ℃ and − 0.2 ℃ in March 2018 and 4.8 ℃ and − 0.4 ℃ in March 2019, respectively.

figure 6

Comparison of daily temperature distribution of germination soil according to differences in bench covering materials (polyethylene in 2018 and polycarbonate double wall in 2019)

The RZH system is controlled by the germination soil temperature. It turns on when the germination soil temperature falls below the low bound of the controller and turns off when it reaches the high bound. Each year’s RZH setpoint temperatures are shown in Table  1 . To germinate various types of crops such as tomatoes, peppers, beans, peas, cucumbers, etc. on the germination table, the farmer requested to maintain soil temperature above 20 ℃ during the night. Despite the setpoint temperatures in 2018 being set at 23.3 ℃/25.6 ℃ (low bound/high bound), it frequently dropped below 20 ℃ due to heat loss through polyethylene film cover. In 2019, the overall germination soil temperature remained above 20 ℃ with the upgraded cover made of 8 mm double wall polycarbonate panels even with lower setpoints at 22.2 ℃/23.9 ℃ (low bound/high bound).

Note that the midday soil temperature is affected by the ventilation fan, as the temperature inside the greenhouse rises rapidly during the day. Because the farmer set the ventilation fan temperature to 32.2 ℃ in 2018 and 23.9 ℃ in 2019, the midday soil temperature in 2018 was relatively high.

4.4.2 Propane water heater ignition time intervals

For design simplicity, we designed a propane water heater as a renewable energy storage and backup heat source. In-tank water heaters heat and store fluid by igniting a propane burner to maintain the setpoint temperature. Therefore, the ignition time interval of the burner is an indicator of how much propane (backup heat) is consumed.

The ignition intervals of the propane burners were recorded to evaluate the effect of the upgraded covers on energy savings. The ignition interval is the number of minutes that it takes from one peak temperature to the next in the propane water heater between midnight and 8 a.m. Table 4 presents the comparison of the ignition intervals of the propane burner on cold nights in 2018 and 2019. Compared to 2018, the average intervals were longer in 2019 despite lower outside temperatures, meaning that the upgraded covers can maintain the germination bench temperature above 20 ℃ while burning less propane.

4.4.3 Temperature difference between soil and greenhouse air

Figure  7 plots how much the temperature of the germination soil remained higher than the air inside the greenhouse overnight (midnight to 7 a.m.). Two nights with similar outside temperatures were compared: March 7, 2018, and March 25, 2019. The average outside temperature and greenhouse air temperature during this period were − 0.9 ℃ and 5.3 ℃ on March 7, 2018, and 0.1 ℃ and 6.7 ℃ on March 25, 2019, respectively. On both days, the unit heater was turned off. On average, the germination soil was 16.5 ℃ higher than the greenhouse air with the ungraded covers, while it was 13.7 ℃ higher with the polyethylene film cover.

figure 7

Temperature differences between the germination soil and greenhouse interior on two nights (Mar 7, 2018 and Mar 25, 2019) when the outside temperatures were similar

4.5 Effects of under-bench insulation on soil temperature

Nighttime (midnight to 7 a.m.) soil temperature on the growing benches varied depending on whether an insulator was installed under the RZH tubing. Figure  8 shows average soil temperatures of the growing benches in March of 2018 and 2019. The average outside temperature and average low temperature were 3.9 ℃ and − 0.2 ℃ in March 2018, and 4.8 ℃ and − 0.4 ℃ in March 2019, respectively. In 2018, the unit heater was set to 8.9 degrees, and the unit heater was not used in 2019.

figure 8

Average soil temperatures on growing benches: a March in 2018; b March in 2019

In 2018, the average nighttime soil temperatures of benches 1, 2, and 3 were 15.4 ℃, 13 ℃, and 14.7 ℃, respectively. In 2019, they were 15 ℃, 11,5 ℃, and 15,4 ℃, respectively. The nighttime soil temperatures with no bottom insulation (bench 2) presented the lowest average temperature both with the unit heater running in 2018 and without running in 2019, compared to the other two benches with insulation (Fig.  8 ). Bench 2, which is open below the RZH tubing, undergoes convective heat loss due to the inflow of relatively cold greenhouse air and radiant heat transfer in the downward direction, resulting in greater heat loss compared to the other two benches where the bottom of the tubing is closed with insulation.

Single insulation (bench 1) and multi-layer insulation (bench 3) performed similarly. The thermal resistance of the single bubble insulation is assumed to be sufficient to prevent downward conductive heat transfer from the RZH tubing. On both benches, bottom insulation prevents the inflow of cold greenhouse air, reducing convective heat loss. The reflective surface reflects the radiant heat coming down from the RZH tubing and directs it towards the soil.

Running the unit heater did not significantly affect the nighttime soil temperature on benches with bottom insulation (benches 1&3). On the other hand, bench 2 (no insulation) had lower temperatures without the unit heater running in 2019 than in 2018 when greenhouse air temperature was maintained above 8.9 ℃ by the unit heater. Benches 2 and 3, where the convective inflow of greenhouse air is blocked by bottom insulation, are less affected by greenhouse air temperature. Note that bench 4 with XPS is excluded in this study since bench 4 was occasionally under different conditions according to the farmer’s needs.

4.6 Effect of bench covers on soil temperature

The bench cover forms a small greenhouse within the greenhouse, increasing the energy efficiency of the RZH system at night. Figure  9 compares the nighttime temperature difference between the soil and the greenhouse air on March 6 and 29, 2018. The average nighttime air temperature inside the greenhouse was 11.9 ℃ on both days. The benches were heated with RZH, but the unit heater was not running. Bench 1 was covered on both days. Benches 2 and 3 were covered on March 6 but uncovered on March 29.

figure 9

Temperature differences between soil and air inside the greenhouse on Mar 6, 2018, and Mar 29, 2018: a bench 1—covered on both days; b bench 2—covered on Mar 6 but uncovered on Mar 29; c bench 3—covered on Mar 6 but uncovered on Mar 29

The average temperature differences on covered bench 1 (XPS and reflective insulation) remained close on both days: 5.1 ℃ and 5.3 ℃. The soil temperature on bench 2 (no insulation) was on average 3.1 ℃ higher than the greenhouse air temperature when it was covered, while it was only 1.1 ℃ higher when it was not covered. Likewise, the soil temperature on bench 3 (reflective insulation) was on average 4.6 ℃ higher when covered but only 2.2 ℃ higher when uncovered. Because the bench cover prevents heat loss from the soil, the temperature difference between the soil and the air inside the greenhouse is greater when the bench is covered.

4.7 Temperature distributions during nighttime

The RZH, covers, and insulation on the benches create a microclimate of small greenhouses within the larger greenhouse. Figure  10 shows the temperatures of both the air and soil on benches 1 and 2, the greenhouse air, and the outside air during the nighttime (midnight to 7 a.m.) in March 2018 (from the 9th to the 31st) and March 2019 (from 1 to 31st). In 2018, data after the unit heater thermostat was replaced on March 8th was analyzed. The sensors were placed 0.2 m above the bench RZH tubing and 1.8 m above the ground, both inside and outside the greenhouse, to measure air temperature every minute. In 2018, the unit heater was set to 8.9 ℃, while it remained unused in 2019.

figure 10

Nighttime soil and air temperature distributions in March 2018 a and March 2019 b

In 2018, the average nighttime temperatures for the soil and air on benches 1 and 2, the greenhouse air, and the outside were 15.4 ℃, 15 ℃, 13 ℃, 12.3 ℃, 10.7 ℃, and 2.6 ℃, respectively. In 2019, these temperatures were 15 ℃, 12.3 ℃, 11.5 ℃, 10.5 ℃, 6.8 ℃, and 0.8 ℃, respectively. Notably, in 2019, when the unit heater was not used, the greenhouse air was influenced by the outside temperature. It increases the temperature difference between the bench cover surface and the greenhouse air, leading to increased conductive heat loss through the covers. As a result, the average nighttime bench temperatures were lower, and the temperature distribution was wider compared to 2018, except for the soil temperature of bench 1 with bottom insulation.

5 Conclusion

Appalachian State University’s Nexus Project has developed a sustainable greenhouse heating system that integrates renewable energy (solar thermal energy and biomass energy) and RZH as a solution to increase profitability. The Nexus system was installed and demonstrated at a local cooperative farm, Springhouse Farm in North Carolina, U.S.A. System performance was studied by analyzing data for 5 years (from 2018 to 2022). The system has been successfully operated without major defects while maintaining productive microclimate conditions. Because this study was conducted in a commercial greenhouse, we were unable to conduct quantitative studies comparing crop biomass or yield under rigorous experimental conditions, but feedback from Springhouse farmers supports that conditions were for healthy crop production: " The greenhouse has performed wonderfully over the years since changing our system. Our plant health and vitality have increased. I attribute it to the benefits associated with bottom heating. We sell some of our plant starts and the feedback has been very positive. Most customers comment that our plants surpass other big box store-bought plants in health and productivity. Saving money on propane is just an added bonus!".

The conclusion and recommendations drawn from this study are summarized as follows:

The Nexus system significantly reduced greenhouse heating energy consumption. Compared to the conventional heating system (a forced-air propane unit heater alone), weather-adjusted propane consumption (propane usage/HDDs) was reduced by 65% when using the Nexus system alone and 45% when using the Nexus system and unit heater together.

The double-wall polycarbonate cover, which has lower thermal conductivity, maintained the temperature of the germination soil stably compared to the polyethylene film cover. Analysis of propane water heater ignition intervals confirmed that the upgraded germination bench cover reduced overall fuel consumption as RZH was controlled by the temperature of the germination soil.

Under-bench insulation helps reduce heat transfer between RZH tubing and greenhouse air through the bench bottom. However, the soil temperatures of the growing bench with single-layer reflective bubble insulation and the bench with multi-layer insulation with added XPS were similar when 32.2 ℃ fluid flowed through RZH tubing.

The combination of RZH, bench covers, and insulation creates a microclimate on small greenhouses within the larger greenhouse. This microclimate remains warm overnight, effectively reducing energy consumption. However, when the temperature inside the greenhouse was not maintained with the unit heater, heat loss through the bench cover increases, leading to more fluctuations in soil and air temperatures.

Varying the cover material, the presence of bottom insulation, and the number of RZH tubing loops resulted in different nighttime soil temperatures. When the soil temperature of the germination bench (double-wall polycarbonate cover, bottom insulation, and 18 loops) was maintained at 20–25 ℃, the growing bench (polyethylene film cover, insulation, and 9 loops) had about 15 ℃. On the growing bench without insulation, the soil was maintained at 11–12 ℃ in March 2019 with an average outside temperature of 4.8 ℃ and low temperature of − 0.4 ℃. The RZH benches at different temperatures can be filled with plants suited to those temperatures.

The bench covers helped the soil temperature higher. When uncovered, the soil temperature was only 1 to 2 ℃ higher than the greenhouse air, but when covered, the soil temperature was higher by 3 to 5 ℃.

The share of renewable energy used to heat the greenhouse ranged from 9 to 13% of the total thermal energy used. The amount of solar energy actually collected through the Nexus system was less than 50% of the harvestable solar energy in the region calculated through modeling. This is a limitation caused by the design of the system where heat storage is also used as a backup energy source, keeping the collector inlet temperature high. It can be improved by separating the backup heat source from heat storage (e.g., adding an on-demand water heater as a backup).

Parallel arrangement of RZH tubing loops and benches ensures uniform fluid flow rates on each bench. Scale-up can be achieved by adding identical RZH units to larger greenhouses.

Data availability

All data supporting the findings of this study are provided within the paper, and the corresponding raw data is available upon request.

Code availability

Not applicable.

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Acknowledgements

The authors would like to thank local farmers for their assistance with this research, particularly Ms. Amy Fiedler, owner of Springhouse Farm. The information contained in this paper is part of the research projects entitled “Demonstration of root zone heating supported by the developed greenhouse heating system” sponsored by the USDA Southern SARE On-Farm research program (Project number OS18-123) and “Promoting Biomass Greenhouse Heating Systems” sponsored by the Bioenergy Research Initiative—North Carolina Department of Agriculture and Consumer Services (Contract 17-078-4003). The authors thank all of the sponsors.

The information contained in this paper is part of the research projects sponsored by the USDA Southern SARE On-Farm research program (Project number OS18-123) and the Bioenergy Research Initiative—North Carolina Department of Agriculture and Consumer Services (Contract 17-078-4003).

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All authors contributed to conceptualization, investigation, and design. H.K. performed methodology, data curation, analysis, visualization, and writing (original draft). O.Y. performed funding acquisition, project administration, supervision, methodology, and writing (review and editing). J.F. performed project administration, supervision, and writing (review and editing). All authors read and approved the final manuscript.

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Kim, HY., Yu, OY. & Ferrell, J. Case study: reducing heating energy consumption in a high tunnel greenhouse with renewable energy and microclimate control by bench-top root-zone heating, bench covers, and under-bench insulation. Discov Sustain 5 , 86 (2024). https://doi.org/10.1007/s43621-024-00276-5

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