What is the current level of PM10 in Wickersley, South Yorkshire?

Wickersley, South Yorkshire currently has a PM10 concentration of 11.252 μg/m3.

What is the current level of sulfur dioxide (SO2) in Wickersley, South Yorkshire?

The current sulfur dioxide (SO2) concentration in Wickersley, South Yorkshire is 0.517 ppb.

What is the current level of ozone (O3) in Wickersley, South Yorkshire?

Wickersley, South Yorkshire currently has an ozone (O3) concentration of 16.915 ppm.

What is the current level of nitrogen dioxide (NO2) in Wickersley, South Yorkshire?

The current level of nitrogen dioxide (NO2) in Wickersley, South Yorkshire is 13.522 ppb.

Current air quality index in Wickersley, South Yorkshire today

Name: Live air pollution levels in Wickersley, South Yorkshire today
Creator: Ambee

Stay updated with real-time air quality in Wickersley, South Yorkshire featuring accurate data on AQI, PM_2.5, PM₁₀, O₃, NO₂, SO₂, and CO levels. Use our interactive map and detailed forecasts to monitor pollution trends, manage health risks, and plan your daily activities with confidence.

Live AQI (Air Quality Index)

Good

Wickersley, South Yorkshire

Last updated: ... (Local time)

Common air pollutants in Wickersley, South Yorkshire

Good

Fine

Moderate

Poor

Very poor

Hazardous

Particulate Matter_2.5 (PM_2.5)

0.40 μg/m³

12.1

35.5

55.5

250.5

500.5+

Particulate Matter₁₀ (PM₁₀)

2.92 μg/m³

155

255

425

605+

Ozone (O₃)

25.60 ppb

201

201+

Sulfur Dioxide (SO₂)

0.46 ppb

186

605

1005+

Nitrogen Dioxide (NO₂)

2.25 ppb

101

361

1250

2050+

Carbon Monoxide (CO)

0.25 ppm

4.5

9.5

12.5

230.5

50.5+

Pollen Level

Moderate

Wickersley, South Yorkshire

Get Live Pollen Counts

Wickersley, South Yorkshire

Scroll To Air Quality Map

Track live Wickersley, South Yorkshire air quality forecast and history

Time	AQI	PM_2.5	PM₁₀	O₃	SO₂	NO₂	CO
2025-09-16T04:00:00.000Z	23 \| good	3.656 \| good	9.639 \| good	25.181 \| good	0.613 \| good	1.58 \| good	0.268 \| good
2025-09-16T05:00:00.000Z	23 \| good	3.697 \| good	9.756 \| good	25.32 \| good	0.447 \| good	2.077 \| good	0.271 \| good
2025-09-16T06:00:00.000Z	24 \| good	3.746 \| good	8.874 \| good	26.029 \| good	0.382 \| good	2.416 \| good	0.088 \| good
2025-09-16T07:00:00.000Z	23 \| good	3.981 \| good	9.109 \| good	25.113 \| good	0.384 \| good	4.956 \| good	0.094 \| good
2025-09-16T08:00:00.000Z	23 \| good	4.409 \| good	9.461 \| good	25.348 \| good	0.382 \| good	8.662 \| good	0.086 \| good
2025-09-16T09:00:00.000Z	27 \| good	4.879 \| good	9.373 \| good	24.991 \| good	0.612 \| good	8.685 \| good	0.082 \| good
2025-09-16T10:00:00.000Z	27 \| good	4.879 \| good	9.373 \| good	25.226 \| good	0.609 \| good	6.338 \| good	0.097 \| good
2025-09-16T11:00:00.000Z	22 \| good	3.199 \| good	9.026 \| good	24.481 \| good	0.547 \| good	5.527 \| good	0.079 \| good
2025-09-16T12:00:00.000Z	23 \| good	3.215 \| good	9.223 \| good	25.18 \| good	0.635 \| good	5.061 \| good	0.073 \| good
2025-09-16T13:00:00.000Z	23 \| good	3.199 \| good	8.901 \| good	25.386 \| good	0.635 \| good	5.599 \| good	0.071 \| good
2025-09-16T14:00:00.000Z	23 \| good	3.199 \| good	8.668 \| good	25.144 \| good	0.382 \| good	4.768 \| good	0.072 \| good
2025-09-16T15:00:00.000Z	23 \| good	3.218 \| good	9.134 \| good	25.264 \| good	0.521 \| good	5.064 \| good	0.074 \| good
2025-09-16T16:00:00.000Z	24 \| good	3.21 \| good	8.991 \| good	25.876 \| good	0.448 \| good	7.043 \| good	0.07 \| good
2025-09-16T17:00:00.000Z	24 \| good	3.226 \| good	9.342 \| good	26.417 \| good	0.487 \| good	8.734 \| good	0.071 \| good
2025-09-16T18:00:00.000Z	25 \| good	3.186 \| good	8.885 \| good	26.526 \| good	0.487 \| good	7.931 \| good	0.078 \| good
2025-09-16T19:00:00.000Z	25 \| good	3.211 \| good	9.169 \| good	27.027 \| good	0.448 \| good	9.389 \| good	0.082 \| good
2025-09-16T20:00:00.000Z	24 \| good	3.227 \| good	9.592 \| good	25.832 \| good	0.49 \| good	12.301 \| good	0.081 \| good
2025-09-16T21:00:00.000Z	23 \| good	3.236 \| good	9.864 \| good	24.57 \| good	0.42 \| good	13.97 \| good	0.081 \| good
2025-09-16T22:00:00.000Z	22 \| good	3.507 \| good	10.525 \| good	23.26 \| good	0.382 \| good	18.406 \| good	0.067 \| good
2025-09-16T23:00:00.000Z	20 \| good	3.486 \| good	11.125 \| good	21.705 \| good	0.382 \| good	14.102 \| good	0.069 \| good
2025-09-17T00:00:00.000Z	19 \| good	3.479 \| good	11.507 \| good	20.511 \| good	0.49 \| good	10.703 \| good	0.189 \| good
2025-09-17T01:00:00.000Z	18 \| good	3.489 \| good	10.824 \| good	18.753 \| good	0.481 \| good	9.128 \| good	0.24 \| good
2025-09-17T02:00:00.000Z	22 \| good	3.523 \| good	11.064 \| good	18.078 \| good	0.449 \| good	5.216 \| good	0.247 \| good
2025-09-17T03:00:00.000Z	22 \| good	3.564 \| good	11.857 \| good	17.931 \| good	0.448 \| good	5.216 \| good	0.243 \| good
2025-09-17T04:00:00.000Z	16 \| good	3.485 \| good	11.795 \| good	16.503 \| good	0.385 \| good	3.276 \| good	0.242 \| good
2025-09-17T05:00:00.000Z	22 \| good	3.69 \| good	12.659 \| good	16.004 \| good	0.382 \| good	4.877 \| good	0.25 \| good
2025-09-17T06:00:00.000Z	22 \| good	3.714 \| good	12.561 \| good	16.614 \| good	0.416 \| good	7.602 \| good	0.067 \| good
2025-09-17T07:00:00.000Z	22 \| good	3.662 \| good	12.822 \| good	16.464 \| good	0.486 \| good	10.389 \| good	0.073 \| good
2025-09-17T08:00:00.000Z	22 \| good	3.957 \| good	13.47 \| good	16.196 \| good	0.453 \| good	10.508 \| good	0.068 \| good
2025-09-17T09:00:00.000Z	27 \| good	4.664 \| good	17.295 \| good	16.625 \| good	0.521 \| good	12.275 \| good	0.065 \| good
2025-09-17T10:00:00.000Z	27 \| good	4.799 \| good	17.69 \| good	17.061 \| good	0.685 \| good	12.686 \| good	0.063 \| good
2025-09-17T11:00:00.000Z	27 \| good	4.629 \| good	16.989 \| good	17.136 \| good	0.684 \| good	11.467 \| good	0.08 \| good
2025-09-17T12:00:00.000Z	27 \| good	4.532 \| good	16.954 \| good	16.301 \| good	0.693 \| good	9.646 \| good	0.064 \| good
2025-09-17T13:00:00.000Z	22 \| good	4.247 \| good	16.461 \| good	15.715 \| good	0.695 \| good	8.123 \| good	0.065 \| good
2025-09-17T14:00:00.000Z	27 \| good	4.668 \| good	14.232 \| good	16.741 \| good	0.76 \| good	7.159 \| good	0.062 \| good
2025-09-17T15:00:00.000Z	22 \| good	4.406 \| good	14.172 \| good	17.302 \| good	0.693 \| good	6.14 \| good	0.062 \| good
2025-09-17T16:00:00.000Z	22 \| good	4.13 \| good	15.585 \| good	17.171 \| good	0.616 \| good	6.72 \| good	0.064 \| good
2025-09-17T17:00:00.000Z	22 \| good	4.137 \| good	14.217 \| good	17.959 \| good	0.521 \| good	6.066 \| good	0.07 \| good
2025-09-17T18:00:00.000Z	22 \| good	4.132 \| good	13.766 \| good	19.435 \| good	0.455 \| good	7.668 \| good	0.068 \| good
2025-09-17T19:00:00.000Z	22 \| good	4.169 \| good	14.183 \| good	20.03 \| good	0.518 \| good	7.018 \| good	0.067 \| good
2025-09-17T20:00:00.000Z	22 \| good	4.174 \| good	13.791 \| good	20.783 \| good	0.452 \| good	7.529 \| good	0.07 \| good
2025-09-17T21:00:00.000Z	22 \| good	3.526 \| good	13.308 \| good	20.464 \| good	0.488 \| good	6.276 \| good	0.079 \| good
2025-09-17T22:00:00.000Z	22 \| good	3.501 \| good	12.625 \| good	21.327 \| good	0.489 \| good	6.501 \| good	0.049 \| good
2025-09-17T23:00:00.000Z	20 \| good	3.478 \| good	12.644 \| good	21.691 \| good	0.485 \| good	5.456 \| good	0.048 \| good
2025-09-18T00:00:00.000Z	20 \| good	3.234 \| good	12.031 \| good	21.953 \| good	0.484 \| good	4.159 \| good	0.286 \| good
2025-09-18T01:00:00.000Z	21 \| good	3.227 \| good	13.612 \| good	22.976 \| good	0.485 \| good	3.273 \| good	0.206 \| good
2025-09-18T02:00:00.000Z	21 \| good	3.204 \| good	13.515 \| good	23.206 \| good	0.447 \| good	1.985 \| good	0.247 \| good
2025-09-18T03:00:00.000Z	24 \| good	0.4 \| good	2.92 \| good	25.599 \| good	0.46 \| good	2.247 \| good	0.247 \| good
2025-09-17T09:00:00.000Z	23 \| good	2.218 \| good	2.763 \| good	25.08 \| good	0.138 \| good	5.55 \| good	0.125 \| good
2025-09-17T10:00:00.000Z	25 \| good	2.594 \| good	3.306 \| good	26.942 \| good	0.142 \| good	4.982 \| good	0.125 \| good
2025-09-17T11:00:00.000Z	28 \| good	2.936 \| good	4.135 \| good	29.662 \| good	0.132 \| good	3.575 \| good	0.122 \| good
2025-09-17T12:00:00.000Z	28 \| good	2.756 \| good	4.551 \| good	29.898 \| good	0.119 \| good	2.415 \| good	0.118 \| good
2025-09-17T13:00:00.000Z	29 \| good	2.274 \| good	5.502 \| good	30.768 \| good	0.122 \| good	1.7 \| good	0.113 \| good
2025-09-17T14:00:00.000Z	29 \| good	3.274 \| good	7.056 \| good	31.104 \| good	0.129 \| good	1.681 \| good	0.108 \| good
2025-09-17T15:00:00.000Z	29 \| good	3.541 \| good	6.606 \| good	31.458 \| good	0.125 \| good	1.844 \| good	0.106 \| good
2025-09-17T16:00:00.000Z	31 \| good	3.348 \| good	6.261 \| good	32.571 \| good	0.13 \| good	2.454 \| good	0.106 \| good
2025-09-17T17:00:00.000Z	30 \| good	3.607 \| good	6.683 \| good	32.222 \| good	0.147 \| good	3.198 \| good	0.107 \| good
2025-09-17T18:00:00.000Z	31 \| good	3.487 \| good	6.682 \| good	32.829 \| good	0.201 \| good	3.498 \| good	0.109 \| good
2025-09-17T19:00:00.000Z	30 \| good	3.679 \| good	7.305 \| good	32.44 \| good	0.22 \| good	3.202 \| good	0.108 \| good
2025-09-17T20:00:00.000Z	31 \| good	3.901 \| good	7.707 \| good	33.385 \| good	0.186 \| good	2.876 \| good	0.108 \| good
2025-09-17T21:00:00.000Z	31 \| good	4.085 \| good	8.487 \| good	32.612 \| good	0.187 \| good	2.626 \| good	0.11 \| good
2025-09-17T22:00:00.000Z	30 \| good	4.011 \| good	8.462 \| good	32.154 \| good	0.172 \| good	2.523 \| good	0.11 \| good
2025-09-17T23:00:00.000Z	31 \| good	3.882 \| good	8.167 \| good	33.139 \| good	0.145 \| good	2.249 \| good	0.11 \| good
2025-09-18T00:00:00.000Z	31 \| good	3.882 \| good	7.913 \| good	33.301 \| good	0.132 \| good	1.991 \| good	0.11 \| good
2025-09-18T01:00:00.000Z	31 \| good	3.827 \| good	7.721 \| good	33.364 \| good	0.125 \| good	1.799 \| good	0.11 \| good
2025-09-18T02:00:00.000Z	30 \| good	3.684 \| good	7.204 \| good	32.016 \| good	0.122 \| good	1.745 \| good	0.109 \| good
2025-09-18T03:00:00.000Z	28 \| good	3.404 \| good	6.354 \| good	30.337 \| good	0.109 \| good	1.748 \| good	0.109 \| good
2025-09-18T04:00:00.000Z	25 \| good	3.502 \| good	5.722 \| good	26.847 \| good	0.091 \| good	1.796 \| good	0.108 \| good
2025-09-18T05:00:00.000Z	23 \| good	3.188 \| good	5.858 \| good	24.751 \| good	0.098 \| good	2.285 \| good	0.105 \| good
2025-09-18T06:00:00.000Z	20 \| good	3.369 \| good	5.937 \| good	22.045 \| good	0.125 \| good	3.353 \| good	0.105 \| good
2025-09-18T07:00:00.000Z	22 \| good	3.403 \| good	6.074 \| good	23.856 \| good	0.162 \| good	4.248 \| good	0.108 \| good
2025-09-18T08:00:00.000Z	23 \| good	3.361 \| good	6.197 \| good	25.13 \| good	0.157 \| good	3.684 \| good	0.105 \| good
2025-09-18T09:00:00.000Z	25 \| good	3.113 \| good	5.577 \| good	27.203 \| good	0.14 \| good	2.781 \| good	0.104 \| good
2025-09-18T10:00:00.000Z	27 \| good	2.878 \| good	5.361 \| good	28.663 \| good	0.125 \| good	2.394 \| good	0.105 \| good
2025-09-18T11:00:00.000Z	27 \| good	2.958 \| good	5.453 \| good	28.955 \| good	0.114 \| good	2.144 \| good	0.104 \| good
2025-09-18T12:00:00.000Z	27 \| good	2.941 \| good	5.508 \| good	28.713 \| good	0.1 \| good	1.991 \| good	0.102 \| good
2025-09-18T13:00:00.000Z	26 \| good	2.771 \| good	5.505 \| good	27.605 \| good	0.096 \| good	1.923 \| good	0.102 \| good
2025-09-18T14:00:00.000Z	25 \| good	2.6 \| good	5.181 \| good	27.248 \| good	0.093 \| good	1.976 \| good	0.103 \| good
2025-09-18T15:00:00.000Z	25 \| good	2.314 \| good	5.469 \| good	26.962 \| good	0.101 \| good	2.186 \| good	0.103 \| good
2025-09-18T16:00:00.000Z	26 \| good	2.189 \| good	5.401 \| good	27.574 \| good	0.103 \| good	2.666 \| good	0.103 \| good
2025-09-18T17:00:00.000Z	25 \| good	2.433 \| good	5.187 \| good	26.548 \| good	0.117 \| good	3.411 \| good	0.104 \| good
2025-09-18T18:00:00.000Z	23 \| good	2.434 \| good	5.073 \| good	25.326 \| good	0.145 \| good	3.733 \| good	0.105 \| good
2025-09-18T19:00:00.000Z	24 \| good	2.603 \| good	5.167 \| good	25.934 \| good	0.161 \| good	3.346 \| good	0.104 \| good
2025-09-18T20:00:00.000Z	25 \| good	2.545 \| good	5.047 \| good	27.242 \| good	0.144 \| good	2.638 \| good	0.101 \| good
2025-09-18T21:00:00.000Z	26 \| good	2.691 \| good	4.921 \| good	28.1 \| good	0.126 \| good	2.343 \| good	0.099 \| good
2025-09-18T22:00:00.000Z	26 \| good	2.621 \| good	4.843 \| good	27.814 \| good	0.106 \| good	2.166 \| good	0.098 \| good
2025-09-18T23:00:00.000Z	25 \| good	2.965 \| good	4.621 \| good	27.319 \| good	0.086 \| good	1.921 \| good	0.097 \| good
2025-09-19T00:00:00.000Z	24 \| good	3.038 \| good	4.811 \| good	25.924 \| good	0.089 \| good	1.749 \| good	0.097 \| good
2025-09-19T01:00:00.000Z	25 \| good	2.909 \| good	4.971 \| good	26.7 \| good	0.077 \| good	1.58 \| good	0.099 \| good
2025-09-19T02:00:00.000Z	25 \| good	2.696 \| good	4.909 \| good	26.686 \| good	0.061 \| good	1.596 \| good	0.1 \| good
2025-09-19T03:00:00.000Z	24 \| good	2.9 \| good	5.159 \| good	26.3 \| good	0.07 \| good	1.849 \| good	0.1 \| good
2025-09-19T04:00:00.000Z	24 \| good	3.019 \| good	5.317 \| good	25.989 \| good	0.084 \| good	2.05 \| good	0.1 \| good
2025-09-19T05:00:00.000Z	23 \| good	3.288 \| good	5.449 \| good	25.128 \| good	0.127 \| good	2.303 \| good	0.1 \| good
2025-09-19T06:00:00.000Z	21 \| good	3.499 \| good	5.834 \| good	23.279 \| good	0.182 \| good	3.452 \| good	0.102 \| good
2025-09-19T07:00:00.000Z	22 \| good	3.859 \| good	6.176 \| good	21.339 \| good	0.196 \| good	5.675 \| good	0.111 \| good
2025-09-19T08:00:00.000Z	22 \| good	4.085 \| good	6.233 \| good	21.251 \| good	0.225 \| good	6.278 \| good	0.114 \| good

Wickersley

Empower business decisions with accurate air quality data

Real-time air quality map: Monitor AQI near Wickersley, South Yorkshire

0.07ppm

How accurate is South Yorkshire, UK air quality data?

The air quality data for South Yorkshire, UK is gathered from reliable sources such as satellites and monitoring stations, adhering to US EPA guidelines. With the help of advanced algorithms and machine learning, factors like traffic and population density are analyzed to deliver accurate and dependable results.

Source: Ambee Data Sources

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Frequently asked questions

How frequently does the air quality data for Wickersley, South Yorkshire get updated?

Air quality updates for Wickersley, South Yorkshire are available every hour.

What time in the past 24 hours saw the poorest air quality in Wickersley, South Yorkshire?

Wickersley, South Yorkshire experienced its worst air quality at 10:00:00, 2025-09-16.

When was air quality in Wickersley, South Yorkshire the best over the past 24 hours?

The best air quality in Wickersley, South Yorkshire was observed at 07:00:00 on 2025-09-17.

What is the air quality in Wickersley, South Yorkshire right now?

The air quality in Wickersley, South Yorkshire right now is Good, with an AQI of 16.

What pollutant is most frequently found in Wickersley, South Yorkshire?

In Wickersley, South Yorkshire, O3 is the most frequently found pollutant.

What can I do if the air quality in Wickersley, South Yorkshire is poor?

When air quality in Wickersley, South Yorkshire is compromised, staying indoors and wearing a mask can reduce health risks.

What is the PM_2.5 concentration in Wickersley, South Yorkshire right now?

Wickersley, South Yorkshire currently has a PM_2.5 concentration of 3.158 μg/m³.

What is the current level of PM₁₀ in Wickersley, South Yorkshire?

Wickersley, South Yorkshire currently has a PM₁₀ concentration of 11.252 μg/m³.

What is the current level of carbon monoxide (CO) in Wickersley, South Yorkshire?

The current carbon monoxide (CO) level in Wickersley, South Yorkshire is 0.071 ppm.

What is the current level of sulfur dioxide (SO₂) in Wickersley, South Yorkshire?

The current sulfur dioxide (SO₂) concentration in Wickersley, South Yorkshire is 0.517 ppb.

What is the current level of ozone (O₃) in Wickersley, South Yorkshire?

Wickersley, South Yorkshire currently has an ozone (O₃) concentration of 16.915 ppm.

What is the current level of nitrogen dioxide (NO₂) in Wickersley, South Yorkshire?

The current level of nitrogen dioxide (NO₂) in Wickersley, South Yorkshire is 13.522 ppb.

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Time	AQI	PM_2.5	PM₁₀	O₃	SO₂	NO₂	CO
2025-09-16T04:00:00.000Z	23 \| good	3.656 \| good	9.639 \| good	25.181 \| good	0.613 \| good	1.58 \| good	0.268 \| good
2025-09-16T05:00:00.000Z	23 \| good	3.697 \| good	9.756 \| good	25.32 \| good	0.447 \| good	2.077 \| good	0.271 \| good
2025-09-16T06:00:00.000Z	24 \| good	3.746 \| good	8.874 \| good	26.029 \| good	0.382 \| good	2.416 \| good	0.088 \| good
2025-09-16T07:00:00.000Z	23 \| good	3.981 \| good	9.109 \| good	25.113 \| good	0.384 \| good	4.956 \| good	0.094 \| good
2025-09-16T08:00:00.000Z	23 \| good	4.409 \| good	9.461 \| good	25.348 \| good	0.382 \| good	8.662 \| good	0.086 \| good
2025-09-16T09:00:00.000Z	27 \| good	4.879 \| good	9.373 \| good	24.991 \| good	0.612 \| good	8.685 \| good	0.082 \| good
2025-09-16T10:00:00.000Z	27 \| good	4.879 \| good	9.373 \| good	25.226 \| good	0.609 \| good	6.338 \| good	0.097 \| good
2025-09-16T11:00:00.000Z	22 \| good	3.199 \| good	9.026 \| good	24.481 \| good	0.547 \| good	5.527 \| good	0.079 \| good
2025-09-16T12:00:00.000Z	23 \| good	3.215 \| good	9.223 \| good	25.18 \| good	0.635 \| good	5.061 \| good	0.073 \| good
2025-09-16T13:00:00.000Z	23 \| good	3.199 \| good	8.901 \| good	25.386 \| good	0.635 \| good	5.599 \| good	0.071 \| good
2025-09-16T14:00:00.000Z	23 \| good	3.199 \| good	8.668 \| good	25.144 \| good	0.382 \| good	4.768 \| good	0.072 \| good
2025-09-16T15:00:00.000Z	23 \| good	3.218 \| good	9.134 \| good	25.264 \| good	0.521 \| good	5.064 \| good	0.074 \| good
2025-09-16T16:00:00.000Z	24 \| good	3.21 \| good	8.991 \| good	25.876 \| good	0.448 \| good	7.043 \| good	0.07 \| good
2025-09-16T17:00:00.000Z	24 \| good	3.226 \| good	9.342 \| good	26.417 \| good	0.487 \| good	8.734 \| good	0.071 \| good
2025-09-16T18:00:00.000Z	25 \| good	3.186 \| good	8.885 \| good	26.526 \| good	0.487 \| good	7.931 \| good	0.078 \| good
2025-09-16T19:00:00.000Z	25 \| good	3.211 \| good	9.169 \| good	27.027 \| good	0.448 \| good	9.389 \| good	0.082 \| good
2025-09-16T20:00:00.000Z	24 \| good	3.227 \| good	9.592 \| good	25.832 \| good	0.49 \| good	12.301 \| good	0.081 \| good
2025-09-16T21:00:00.000Z	23 \| good	3.236 \| good	9.864 \| good	24.57 \| good	0.42 \| good	13.97 \| good	0.081 \| good
2025-09-16T22:00:00.000Z	22 \| good	3.507 \| good	10.525 \| good	23.26 \| good	0.382 \| good	18.406 \| good	0.067 \| good
2025-09-16T23:00:00.000Z	20 \| good	3.486 \| good	11.125 \| good	21.705 \| good	0.382 \| good	14.102 \| good	0.069 \| good
2025-09-17T00:00:00.000Z	19 \| good	3.479 \| good	11.507 \| good	20.511 \| good	0.49 \| good	10.703 \| good	0.189 \| good
2025-09-17T01:00:00.000Z	18 \| good	3.489 \| good	10.824 \| good	18.753 \| good	0.481 \| good	9.128 \| good	0.24 \| good
2025-09-17T02:00:00.000Z	22 \| good	3.523 \| good	11.064 \| good	18.078 \| good	0.449 \| good	5.216 \| good	0.247 \| good
2025-09-17T03:00:00.000Z	22 \| good	3.564 \| good	11.857 \| good	17.931 \| good	0.448 \| good	5.216 \| good	0.243 \| good
2025-09-17T04:00:00.000Z	16 \| good	3.485 \| good	11.795 \| good	16.503 \| good	0.385 \| good	3.276 \| good	0.242 \| good
2025-09-17T05:00:00.000Z	22 \| good	3.69 \| good	12.659 \| good	16.004 \| good	0.382 \| good	4.877 \| good	0.25 \| good
2025-09-17T06:00:00.000Z	22 \| good	3.714 \| good	12.561 \| good	16.614 \| good	0.416 \| good	7.602 \| good	0.067 \| good
2025-09-17T07:00:00.000Z	22 \| good	3.662 \| good	12.822 \| good	16.464 \| good	0.486 \| good	10.389 \| good	0.073 \| good
2025-09-17T08:00:00.000Z	22 \| good	3.957 \| good	13.47 \| good	16.196 \| good	0.453 \| good	10.508 \| good	0.068 \| good
2025-09-17T09:00:00.000Z	27 \| good	4.664 \| good	17.295 \| good	16.625 \| good	0.521 \| good	12.275 \| good	0.065 \| good
2025-09-17T10:00:00.000Z	27 \| good	4.799 \| good	17.69 \| good	17.061 \| good	0.685 \| good	12.686 \| good	0.063 \| good
2025-09-17T11:00:00.000Z	27 \| good	4.629 \| good	16.989 \| good	17.136 \| good	0.684 \| good	11.467 \| good	0.08 \| good
2025-09-17T12:00:00.000Z	27 \| good	4.532 \| good	16.954 \| good	16.301 \| good	0.693 \| good	9.646 \| good	0.064 \| good
2025-09-17T13:00:00.000Z	22 \| good	4.247 \| good	16.461 \| good	15.715 \| good	0.695 \| good	8.123 \| good	0.065 \| good
2025-09-17T14:00:00.000Z	27 \| good	4.668 \| good	14.232 \| good	16.741 \| good	0.76 \| good	7.159 \| good	0.062 \| good
2025-09-17T15:00:00.000Z	22 \| good	4.406 \| good	14.172 \| good	17.302 \| good	0.693 \| good	6.14 \| good	0.062 \| good
2025-09-17T16:00:00.000Z	22 \| good	4.13 \| good	15.585 \| good	17.171 \| good	0.616 \| good	6.72 \| good	0.064 \| good
2025-09-17T17:00:00.000Z	22 \| good	4.137 \| good	14.217 \| good	17.959 \| good	0.521 \| good	6.066 \| good	0.07 \| good
2025-09-17T18:00:00.000Z	22 \| good	4.132 \| good	13.766 \| good	19.435 \| good	0.455 \| good	7.668 \| good	0.068 \| good
2025-09-17T19:00:00.000Z	22 \| good	4.169 \| good	14.183 \| good	20.03 \| good	0.518 \| good	7.018 \| good	0.067 \| good
2025-09-17T20:00:00.000Z	22 \| good	4.174 \| good	13.791 \| good	20.783 \| good	0.452 \| good	7.529 \| good	0.07 \| good
2025-09-17T21:00:00.000Z	22 \| good	3.526 \| good	13.308 \| good	20.464 \| good	0.488 \| good	6.276 \| good	0.079 \| good
2025-09-17T22:00:00.000Z	22 \| good	3.501 \| good	12.625 \| good	21.327 \| good	0.489 \| good	6.501 \| good	0.049 \| good
2025-09-17T23:00:00.000Z	20 \| good	3.478 \| good	12.644 \| good	21.691 \| good	0.485 \| good	5.456 \| good	0.048 \| good
2025-09-18T00:00:00.000Z	20 \| good	3.234 \| good	12.031 \| good	21.953 \| good	0.484 \| good	4.159 \| good	0.286 \| good
2025-09-18T01:00:00.000Z	21 \| good	3.227 \| good	13.612 \| good	22.976 \| good	0.485 \| good	3.273 \| good	0.206 \| good
2025-09-18T02:00:00.000Z	21 \| good	3.204 \| good	13.515 \| good	23.206 \| good	0.447 \| good	1.985 \| good	0.247 \| good
2025-09-18T03:00:00.000Z	24 \| good	0.4 \| good	2.92 \| good	25.599 \| good	0.46 \| good	2.247 \| good	0.247 \| good
2025-09-17T09:00:00.000Z	23 \| good	2.218 \| good	2.763 \| good	25.08 \| good	0.138 \| good	5.55 \| good	0.125 \| good
2025-09-17T10:00:00.000Z	25 \| good	2.594 \| good	3.306 \| good	26.942 \| good	0.142 \| good	4.982 \| good	0.125 \| good
2025-09-17T11:00:00.000Z	28 \| good	2.936 \| good	4.135 \| good	29.662 \| good	0.132 \| good	3.575 \| good	0.122 \| good
2025-09-17T12:00:00.000Z	28 \| good	2.756 \| good	4.551 \| good	29.898 \| good	0.119 \| good	2.415 \| good	0.118 \| good
2025-09-17T13:00:00.000Z	29 \| good	2.274 \| good	5.502 \| good	30.768 \| good	0.122 \| good	1.7 \| good	0.113 \| good
2025-09-17T14:00:00.000Z	29 \| good	3.274 \| good	7.056 \| good	31.104 \| good	0.129 \| good	1.681 \| good	0.108 \| good
2025-09-17T15:00:00.000Z	29 \| good	3.541 \| good	6.606 \| good	31.458 \| good	0.125 \| good	1.844 \| good	0.106 \| good
2025-09-17T16:00:00.000Z	31 \| good	3.348 \| good	6.261 \| good	32.571 \| good	0.13 \| good	2.454 \| good	0.106 \| good
2025-09-17T17:00:00.000Z	30 \| good	3.607 \| good	6.683 \| good	32.222 \| good	0.147 \| good	3.198 \| good	0.107 \| good
2025-09-17T18:00:00.000Z	31 \| good	3.487 \| good	6.682 \| good	32.829 \| good	0.201 \| good	3.498 \| good	0.109 \| good
2025-09-17T19:00:00.000Z	30 \| good	3.679 \| good	7.305 \| good	32.44 \| good	0.22 \| good	3.202 \| good	0.108 \| good
2025-09-17T20:00:00.000Z	31 \| good	3.901 \| good	7.707 \| good	33.385 \| good	0.186 \| good	2.876 \| good	0.108 \| good
2025-09-17T21:00:00.000Z	31 \| good	4.085 \| good	8.487 \| good	32.612 \| good	0.187 \| good	2.626 \| good	0.11 \| good
2025-09-17T22:00:00.000Z	30 \| good	4.011 \| good	8.462 \| good	32.154 \| good	0.172 \| good	2.523 \| good	0.11 \| good
2025-09-17T23:00:00.000Z	31 \| good	3.882 \| good	8.167 \| good	33.139 \| good	0.145 \| good	2.249 \| good	0.11 \| good
2025-09-18T00:00:00.000Z	31 \| good	3.882 \| good	7.913 \| good	33.301 \| good	0.132 \| good	1.991 \| good	0.11 \| good
2025-09-18T01:00:00.000Z	31 \| good	3.827 \| good	7.721 \| good	33.364 \| good	0.125 \| good	1.799 \| good	0.11 \| good
2025-09-18T02:00:00.000Z	30 \| good	3.684 \| good	7.204 \| good	32.016 \| good	0.122 \| good	1.745 \| good	0.109 \| good
2025-09-18T03:00:00.000Z	28 \| good	3.404 \| good	6.354 \| good	30.337 \| good	0.109 \| good	1.748 \| good	0.109 \| good
2025-09-18T04:00:00.000Z	25 \| good	3.502 \| good	5.722 \| good	26.847 \| good	0.091 \| good	1.796 \| good	0.108 \| good
2025-09-18T05:00:00.000Z	23 \| good	3.188 \| good	5.858 \| good	24.751 \| good	0.098 \| good	2.285 \| good	0.105 \| good
2025-09-18T06:00:00.000Z	20 \| good	3.369 \| good	5.937 \| good	22.045 \| good	0.125 \| good	3.353 \| good	0.105 \| good
2025-09-18T07:00:00.000Z	22 \| good	3.403 \| good	6.074 \| good	23.856 \| good	0.162 \| good	4.248 \| good	0.108 \| good
2025-09-18T08:00:00.000Z	23 \| good	3.361 \| good	6.197 \| good	25.13 \| good	0.157 \| good	3.684 \| good	0.105 \| good
2025-09-18T09:00:00.000Z	25 \| good	3.113 \| good	5.577 \| good	27.203 \| good	0.14 \| good	2.781 \| good	0.104 \| good
2025-09-18T10:00:00.000Z	27 \| good	2.878 \| good	5.361 \| good	28.663 \| good	0.125 \| good	2.394 \| good	0.105 \| good
2025-09-18T11:00:00.000Z	27 \| good	2.958 \| good	5.453 \| good	28.955 \| good	0.114 \| good	2.144 \| good	0.104 \| good
2025-09-18T12:00:00.000Z	27 \| good	2.941 \| good	5.508 \| good	28.713 \| good	0.1 \| good	1.991 \| good	0.102 \| good
2025-09-18T13:00:00.000Z	26 \| good	2.771 \| good	5.505 \| good	27.605 \| good	0.096 \| good	1.923 \| good	0.102 \| good
2025-09-18T14:00:00.000Z	25 \| good	2.6 \| good	5.181 \| good	27.248 \| good	0.093 \| good	1.976 \| good	0.103 \| good
2025-09-18T15:00:00.000Z	25 \| good	2.314 \| good	5.469 \| good	26.962 \| good	0.101 \| good	2.186 \| good	0.103 \| good
2025-09-18T16:00:00.000Z	26 \| good	2.189 \| good	5.401 \| good	27.574 \| good	0.103 \| good	2.666 \| good	0.103 \| good
2025-09-18T17:00:00.000Z	25 \| good	2.433 \| good	5.187 \| good	26.548 \| good	0.117 \| good	3.411 \| good	0.104 \| good
2025-09-18T18:00:00.000Z	23 \| good	2.434 \| good	5.073 \| good	25.326 \| good	0.145 \| good	3.733 \| good	0.105 \| good
2025-09-18T19:00:00.000Z	24 \| good	2.603 \| good	5.167 \| good	25.934 \| good	0.161 \| good	3.346 \| good	0.104 \| good
2025-09-18T20:00:00.000Z	25 \| good	2.545 \| good	5.047 \| good	27.242 \| good	0.144 \| good	2.638 \| good	0.101 \| good
2025-09-18T21:00:00.000Z	26 \| good	2.691 \| good	4.921 \| good	28.1 \| good	0.126 \| good	2.343 \| good	0.099 \| good
2025-09-18T22:00:00.000Z	26 \| good	2.621 \| good	4.843 \| good	27.814 \| good	0.106 \| good	2.166 \| good	0.098 \| good
2025-09-18T23:00:00.000Z	25 \| good	2.965 \| good	4.621 \| good	27.319 \| good	0.086 \| good	1.921 \| good	0.097 \| good
2025-09-19T00:00:00.000Z	24 \| good	3.038 \| good	4.811 \| good	25.924 \| good	0.089 \| good	1.749 \| good	0.097 \| good
2025-09-19T01:00:00.000Z	25 \| good	2.909 \| good	4.971 \| good	26.7 \| good	0.077 \| good	1.58 \| good	0.099 \| good
2025-09-19T02:00:00.000Z	25 \| good	2.696 \| good	4.909 \| good	26.686 \| good	0.061 \| good	1.596 \| good	0.1 \| good
2025-09-19T03:00:00.000Z	24 \| good	2.9 \| good	5.159 \| good	26.3 \| good	0.07 \| good	1.849 \| good	0.1 \| good
2025-09-19T04:00:00.000Z	24 \| good	3.019 \| good	5.317 \| good	25.989 \| good	0.084 \| good	2.05 \| good	0.1 \| good
2025-09-19T05:00:00.000Z	23 \| good	3.288 \| good	5.449 \| good	25.128 \| good	0.127 \| good	2.303 \| good	0.1 \| good
2025-09-19T06:00:00.000Z	21 \| good	3.499 \| good	5.834 \| good	23.279 \| good	0.182 \| good	3.452 \| good	0.102 \| good
2025-09-19T07:00:00.000Z	22 \| good	3.859 \| good	6.176 \| good	21.339 \| good	0.196 \| good	5.675 \| good	0.111 \| good
2025-09-19T08:00:00.000Z	22 \| good	4.085 \| good	6.233 \| good	21.251 \| good	0.225 \| good	6.278 \| good	0.114 \| good

Current air quality index in Wickersley, South Yorkshire today

Common air pollutants in Wickersley, South Yorkshire

Particulate Matter2.5 (PM2.5)

Particulate Matter10 (PM10)

Ozone (O3)

Sulfur Dioxide (SO2)

Nitrogen Dioxide (NO2)

Carbon Monoxide (CO)

Track live Wickersley, South Yorkshire air quality forecast and history

Empower business decisions with accurate air quality data

Real-time air quality map: Monitor AQI near Wickersley, South Yorkshire

Air quality in nearby cities

Maltby, South Yorkshire

Rotherham, South Yorkshire

Rawmarsh, South Yorkshire

Conisbrough, South Yorkshire

Swallownest, South Yorkshire

Dinnington, South Yorkshire

How accurate is South Yorkshire, UK air quality data?

Air quality levels in UK

Frequently asked questions

How frequently does the air quality data for Wickersley, South Yorkshire get updated?

What time in the past 24 hours saw the poorest air quality in Wickersley, South Yorkshire?

When was air quality in Wickersley, South Yorkshire the best over the past 24 hours?

What is the air quality in Wickersley, South Yorkshire right now?

What pollutant is most frequently found in Wickersley, South Yorkshire?

What can I do if the air quality in Wickersley, South Yorkshire is poor?

What is the PM2.5 concentration in Wickersley, South Yorkshire right now?

What is the current level of PM10 in Wickersley, South Yorkshire?

What is the current level of carbon monoxide (CO) in Wickersley, South Yorkshire?

What is the current level of sulfur dioxide (SO2) in Wickersley, South Yorkshire?

What is the current level of ozone (O3) in Wickersley, South Yorkshire?

What is the current level of nitrogen dioxide (NO2) in Wickersley, South Yorkshire?

Particulate Matter_2.5 (PM_2.5)

Particulate Matter₁₀ (PM₁₀)

Ozone (O₃)

Sulfur Dioxide (SO₂)

Nitrogen Dioxide (NO₂)

What is the PM_2.5 concentration in Wickersley, South Yorkshire right now?

What is the current level of PM₁₀ in Wickersley, South Yorkshire?

What is the current level of sulfur dioxide (SO₂) in Wickersley, South Yorkshire?

What is the current level of ozone (O₃) in Wickersley, South Yorkshire?

What is the current level of nitrogen dioxide (NO₂) in Wickersley, South Yorkshire?