Citation: Hassan, S.; Mushinski,
R.M.; Amede, T.; Bending, G.D.;
Covington, J.A. Integrated Probe
System for Measuring Soil Carbon
Dioxide Concentrations. Sensors 2023,
23, 2580. https://doi.org/10.3390/
s23052580
Academic Editor: Dawei Han
Received: 8 December 2022
Revised: 9 February 2023
Accepted: 15 February 2023
Published: 26 February 2023
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Article
Integrated Probe System for Measuring Soil Carbon
Dioxide Concentrations
Sammy Hassan
1,
* , Ryan M. Mushinski
2
, Tilahun Amede
3
, Gary D. Bending
2
and James A. Covington
1
1
School of Engineering, University of Warwick, Coventry CV4 7AL, UK
2
School of Life Sciences, University of Warwick, Coventry CV4 7AL, UK
3
International Crops Research Institute for the Semi-Arid Tropics (ICRISAT),
Addis Ababa P.O. Box 5689, Ethiopia
* Correspondence: sammy.hassan@warwick.ac.uk
Abstract:
This article outlines the design and implementation of an internet-of-things (IoT) platform
for the monitoring of soil carbon dioxide (CO
2
) concentrations. As atmospheric CO
2
continues to rise,
accurate accounting of major carbon sources, such as soil, is essential to inform land management
and government policy. Thus, a batch of IoT-connected CO
2
sensor probes were developed for soil
measurement. These sensors were designed to capture spatial distribution of CO
2
concentrations
across a site and communicate to a central gateway using LoRa. CO
2
concentration and other environ-
mental parameters, including temperature, humidity and volatile organic compound concentration,
were logged locally and communicated to the user through a mobile (GSM) connection to a hosted
website. Following three field deployments in summer and autumn, we observed clear depth and
diurnal variation of soil CO
2
concentration within woodland systems. We determined that the unit
had the capacity to log data continuously for a maximum of 14 days. These low-cost systems have
great potential for better accounting of soil CO
2
sources over temporal and spatial gradients and
possibly flux estimations. Future testing will focus on divergent landscapes and soil conditions.
Keywords:
soil measurements; Wireless Sensor Networks (WSNs); environmental monitoring;
internet-of-things (IoT)
1. Introduction
Anthropogenic activities, including intensive agriculture and land-use changes, have
contributed to the exponential rise in atmospheric carbon dioxide (CO
2
) [
1
]. Evidence
suggests that these two factors may account for 25% of all CO
2
emissions since 2007 [
2
].
Gross soil respiration, which is the positive flux of CO
2
from the soil to the atmosphere, is
estimated at 60 Gt CO
2
-C yr
−1
—representing one of the largest carbon sources. Between
60–90% of this CO
2
is sourced from microbial activity in soil [3]. Practices that lead to soil
disturbance, such as tillage for crop production and deforestation, can stimulate microbial
activity, leading to pulses of CO
2
flux. Current methods for measuring soil respiration com-
monly utilise headspace sampling of small chambers placed on the soil surface. Air within
the headspace is sampled over a set period of time, analysed using a gas chromatograph
or infrared gas analyser, and then the concentration is regressed over sampling time to
calculate flux [
4
]. More modern systems utilise headspace recirculation to automatically
calculate CO
2
flux [
5
]. While well-represented in the literature, these methods are time-
intensive and generally lack spatial resolution. Furthermore, the analytical components can
be cost-prohibitive. Thus, there is a pressing need to develop systems that are cost-effective,
can provide spatial and temporal resolution, can be utilized for flux estimation, and have
data acquisition programs that are easily accessible.
The increased development and availability of the internet has spawned the technol-
ogy of connected devices and the Internet of Things (IOT). IOT describes the integration
and communication between intelligent objects, commonly referred to as “Things” [
6
].
Sensors 2023, 23, 2580. https://doi.org/10.3390/s23052580 https://www.mdpi.com/journal/sensors
