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Mapped: Life Expectancy Gains From Breathing Cleaner Air

Published

2 years ago

December 24, 2023

Aarsh Batra

Featured Creator

Article/Editing:

Pallavi Rao

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Map of Life Expectancy Gains From Breathing Cleaner Air

The health impact of something as pervasive as air pollution can be hard to communicate due to the complex nature of its effects on humans. This makes it a challenge to convey the full extent of its consequences to the general public.

However, satellite-derived data from from the 2023 Air Quality Life Index (AQLI) shows how exposure to particulate matter in the air can impact average life expectancy of residents in different cities.

Using this data, Aarsh Batra visualizes a map of life expectancy gains (the deeper the hue, the higher the gain) if all people around the world breathed cleaner air.

Top 500 Cities By Life Expectancy Gains From Cleaner Air

Consistent exposure to particulate matter in the air with a width of 2.5 micrometers, or PM2.5, can lead to strokes, heart attacks, and an increased risk of lung disease. The WHO recommended guideline for annual average PM2.5 levels is below 5 micrograms per cubic meter (µg/m³).

If particle pollution levels in 2021 had matched WHO guidelines around the world, life expectancy on average on the planet would have increased by more than 2 years.

In some cities however, gains are much higher, indicating how much worse their air quality was.

Rank	City/District	Country	Population	PM 2.5 Levels (2021)	Life Expectancy Gain (With Cleaner Air)
1	NCT of Delhi	🇮🇳 India	18,030,054	126.51	11.91
2	Gautam Buddha Nagar	🇮🇳 India	2,604,177	119.99	11.27
3	Gurugram	🇮🇳 India	1,746,628	119.50	11.22
4	Faridabad	🇮🇳 India	2,443,079	115.56	10.83
5	Ghaziabad	🇮🇳 India	3,882,065	113.65	10.65
6	Hathras	🇮🇳 India	1,698,569	109.26	10.22
7	Sonipat	🇮🇳 India	1,630,727	109.28	10.22
8	Aligarh	🇮🇳 India	4,152,828	109.07	10.20
9	Mathura	🇮🇳 India	2,863,039	108.62	10.15
10	Palwal	🇮🇳 India	869,785	108.38	10.13
11	Jaunpur	🇮🇳 India	5,086,963	107.91	10.09
12	Azamgarh	🇮🇳 India	4,501,783	107.43	10.04
13	Etah	🇮🇳 India	1,979,047	107.41	10.04
14	Mainpuri	🇮🇳 India	2,105,322	106.89	9.99
15	Jhajjar	🇮🇳 India	1,111,303	106.20	9.92
16	Firozabad	🇮🇳 India	3,535,204	106.16	9.91
17	Unnao	🇮🇳 India	3,499,247	106.08	9.91
18	Mau	🇮🇳 India	3,146,042	106.05	9.90
19	Ghazipur	🇮🇳 India	4,052,326	105.50	9.85
20	Pratapgarh	🇮🇳 India	3,615,621	105.35	9.83
21	Agra	🇮🇳 India	4,253,657	104.91	9.79
22	Ambedkar Nagar	🇮🇳 India	2,692,878	104.77	9.78
23	Lucknow	🇮🇳 India	5,155,721	104.39	9.74
24	Kanpur Nagar	🇮🇳 India	5,121,237	104.22	9.72
25	Baghpat	🇮🇳 India	1,456,640	104.12	9.71
26	Etawah	🇮🇳 India	1,758,602	103.90	9.69
27	Rae Bareli	🇮🇳 India	2,764,725	103.89	9.69
28	Mewat	🇮🇳 India	1,209,627	103.72	9.67
29	Amethi	🇮🇳 India	2,859,643	102.96	9.60
30	Farrukhabad	🇮🇳 India	2,113,678	102.91	9.60
31	Sultanpur	🇮🇳 India	2,480,449	102.82	9.59
32	Rohtak	🇮🇳 India	1,181,579	102.69	9.57
33	Siwan	🇮🇳 India	3,820,774	102.69	9.57
34	Gopalganj	🇮🇳 India	3,001,323	102.57	9.56
35	Kasganj	🇮🇳 India	1,576,882	102.58	9.56
36	Ballia	🇮🇳 India	3,651,870	102.47	9.55
37	Barabanki	🇮🇳 India	4,286,133	102.10	9.52
38	Sant Kabir Nagar	🇮🇳 India	1,640,454	102.01	9.51
39	Gorakhpur	🇮🇳 India	4,757,213	101.84	9.49
40	Kannauj	🇮🇳 India	1,862,255	101.45	9.45
41	Saran	🇮🇳 India	4,615,182	101.07	9.42
42	Varanasi	🇮🇳 India	4,052,825	100.85	9.39
43	Faizabad	🇮🇳 India	2,153,545	100.47	9.36
44	Hardoi	🇮🇳 India	4,581,753	100.47	9.36
45	Basti	🇮🇳 India	2,406,653	100.32	9.34
46	Fatehpur	🇮🇳 India	2,968,289	100.23	9.33
47	Deoria	🇮🇳 India	3,490,772	100.15	9.32
48	Vaishali	🇮🇳 India	4,005,909	100.05	9.31
49	Kaushambi	🇮🇳 India	2,990,143	99.07	9.22
50	Auraiya	🇮🇳 India	1,599,592	98.90	9.20
51	Bhadohi	🇮🇳 India	1,751,436	98.89	9.20
52	Bulandshahr	🇮🇳 India	3,895,220	98.75	9.19
53	Sitapur	🇮🇳 India	5,028,006	98.72	9.18
54	Gonda	🇮🇳 India	3,810,975	98.48	9.16
55	Muzaffarpur	🇮🇳 India	5,529,068	98.32	9.15
56	Kanpur Dehat	🇮🇳 India	1,986,566	98.00	9.11
57	Buxar	🇮🇳 India	1,958,634	97.57	9.07
58	Samastipur	🇮🇳 India	4,911,121	96.96	9.01
59	Bhind	🇮🇳 India	1,916,992	95.99	8.92
60	Panipat	🇮🇳 India	1,349,731	95.80	8.90
61	Hapur	🇮🇳 India	1,480,746	95.54	8.87
62	Bharatpur	🇮🇳 India	2,882,439	95.17	8.84
63	Kushinagar	🇮🇳 India	3,981,771	94.87	8.81
64	Prayagraj	🇮🇳 India	5,415,602	94.77	8.80
65	Purba Champaran	🇮🇳 India	5,844,764	94.83	8.80
66	Rewari	🇮🇳 India	896,708	94.54	8.77
67	Budaun	🇮🇳 India	3,474,058	94.07	8.73
68	Sheohar	🇮🇳 India	1,283,274	94.07	8.73
69	Shahjahanpur	🇮🇳 India	3,370,212	93.99	8.72
70	Bhojpur	🇮🇳 India	3,180,135	93.86	8.71
71	Patna	🇮🇳 India	6,718,984	93.36	8.66
72	Dhaulpur	🇮🇳 India	1,358,477	92.50	8.57
73	Sitamarhi	🇮🇳 India	3,423,369	91.68	8.49
74	Chandauli	🇮🇳 India	2,257,550	91.41	8.47
75	Darbhanga	🇮🇳 India	4,595,227	91.10	8.44
76	Begusarai	🇮🇳 India	3,464,719	90.51	8.38
77	Morena	🇮🇳 India	2,195,456	90.23	8.35
78	Gazipur	🇧🇩 Bangladesh	3,989,975	89.85	8.31
79	Jind	🇮🇳 India	1,519,442	89.28	8.26
80	Meerut	🇮🇳 India	3,847,662	88.82	8.21
81	Noakhali	🇧🇩 Bangladesh	3,540,247	88.74	8.21
82	Feni	🇧🇩 Bangladesh	1,630,831	88.65	8.20
83	Comilla	🇧🇩 Bangladesh	6,124,075	88.21	8.16
84	Narsingdi	🇧🇩 Bangladesh	2,547,066	88.25	8.16
85	Khagaria	🇮🇳 India	1,922,426	87.87	8.12
86	Chandpur	🇧🇩 Bangladesh	2,731,438	87.79	8.11
87	Lakshmipur	🇧🇩 Bangladesh	1,986,786	87.59	8.09
88	Sambhal	🇮🇳 India	2,372,466	87.44	8.08
89	Jalaun	🇮🇳 India	1,896,350	87.34	8.07
90	Dhaka	🇧🇩 Bangladesh	13,791,222	87.23	8.06
91	Munshiganj	🇧🇩 Bangladesh	1,634,793	87.24	8.06
92	Arwal	🇮🇳 India	821,007	86.95	8.03
93	Narayanganj	🇧🇩 Bangladesh	3,159,730	86.90	8.03
94	Nalanda	🇮🇳 India	3,327,893	86.68	8.00
95	Siddharth Nagar	🇮🇳 India	3,485,912	86.66	8.00
96	Jehanabad	🇮🇳 India	1,297,183	86.39	7.98
97	Raipur	🇮🇳 India	2,575,952	86.26	7.96
98	Bahraich	🇮🇳 India	2,839,622	86.08	7.95
99	Pashchim Champaran	🇮🇳 India	4,549,547	85.47	7.89
100	Saharsa	🇮🇳 India	2,186,832	85.46	7.88
101	Maharajganj	🇮🇳 India	3,255,113	85.07	7.85
102	Charkhi Dadri	🇧🇩 Bangladesh	541,560	84.70	7.81
103	Manikganj	🇮🇳 India	1,571,422	84.74	7.81
104	Durg	🇮🇳 India	2,265,907	84.08	7.75
105	Hisar	🇮🇳 India	1,938,571	83.57	7.70
106	Lakhimpur Kheri	🇮🇳 India	4,506,473	83.57	7.70
107	Shamli	🇧🇩 Bangladesh	1,332,901	83.12	7.66
108	Brahamanbaria	🇮🇳 India	3,252,020	83.06	7.65
109	Alwar	🇮🇳 India	4,163,936	82.97	7.64
110	Banda	🇮🇳 India	2,004,848	82.63	7.61
111	Tarn Taran	🇮🇳 India	1,162,164	82.54	7.60
112	Hamirpur	🇮🇳 India	1,239,827	82.30	7.58
113	Madhubani	🇮🇳 India	5,166,527	82.30	7.58
114	Shravasti	🇧🇩 Bangladesh	2,313,893	82.35	7.58
115	Shariatpur	🇮🇳 India	1,330,690	82.18	7.56
116	Sheikhpura	🇧🇩 Bangladesh	724,935	82.16	7.56
117	Kishoreganj	🇵🇰 Pakistan	3,328,837	81.99	7.55
118	Lahore	🇳🇵 Nepal	9,317,108	81.81	7.53
119	Mahottari	🇮🇳 India	735,769	81.69	7.52
120	Mansa	🇮🇳 India	854,726	81.71	7.52
121	Fatehabad	🇮🇳 India	1,052,288	81.65	7.51
122	Bhiwani	🇧🇩 Bangladesh	1,281,849	81.25	7.47
123	Tangail	🇮🇳 India	4,122,304	80.97	7.45
124	Karnal	🇳🇵 Nepal	1,665,277	80.89	7.44
125	Rautahat	🇮🇳 India	791,972	80.77	7.43
126	Madhepura	🇮🇳 India	2,322,286	80.65	7.41
127	Bathinda	🇮🇳 India	1,524,742	80.40	7.39
128	Puruliya	🇮🇳 India	3,178,490	80.27	7.38
129	Kaithal	🇳🇵 Nepal	1,233,024	80.20	7.37
130	Dhanusha	🇮🇳 India	874,036	80.00	7.35
131	Balrampur	🇮🇳 India	2,412,972	79.78	7.33
132	Bareilly	🇧🇩 Bangladesh	4,971,744	79.17	7.27
133	Madaripur	🇳🇵 Nepal	1,320,624	79.04	7.26
134	Bara	🇮🇳 India	800,202	78.74	7.23
135	Amritsar	🇧🇩 Bangladesh	2,636,765	78.62	7.22
136	Gopalganj	🇧🇩 Bangladesh	1,342,230	78.64	7.22
137	Barisal	🇮🇳 India	2,621,581	78.55	7.21
138	Lakhisarai	🇮🇳 India	1,200,365	78.33	7.19
139	Dhanbad	🇮🇳 India	3,031,911	78.24	7.18
140	Katihar	🇳🇵 Nepal	3,543,450	78.31	7.18
141	Parsa	🇮🇳 India	694,050	78.12	7.17
142	Mahendragarh	🇳🇵 Nepal	1,045,728	78.10	7.16
143	Sarlahi	🇮🇳 India	888,611	78.04	7.16
144	Rohtas	🇮🇳 India	3,449,308	77.96	7.15
145	Sepahijala	🇮🇳 India	404,754	77.84	7.14
146	Bhagalpur	🇮🇳 India	3,540,537	77.72	7.13
147	Kaimur	🇮🇳 India	1,869,285	77.77	7.13
148	Munger	🇮🇳 India	1,521,105	77.80	7.13
149	Chitrakoot	🇮🇳 India	1,110,002	77.42	7.10
150	Faridkot	🇮🇳 India	658,814	77.47	7.10
151	Faridpur	🇧🇩 Bangladesh	2,181,053	77.42	7.10
152	South Tripura	🇮🇳 India	375,754	77.25	7.08
153	Gwalior	🇮🇳 India	2,149,777	77.11	7.07
154	Mirzapur	🇮🇳 India	2,835,466	77.17	7.07
155	Sri Muktsar Sahib	🇮🇳 India	943,831	77.19	7.07
156	Sirsa	🇮🇳 India	1,448,417	77.03	7.06
157	Bhola	🇧🇩 Bangladesh	2,007,259	76.90	7.05
158	Bankura	🇮🇳 India	3,867,370	76.88	7.04
159	Bokaro	🇮🇳 India	2,395,637	76.78	7.03
160	Sangrur	🇮🇳 India	1,759,762	76.49	7.01
161	Magura	🇧🇩 Bangladesh	1,054,682	76.07	6.97
162	Bemetara	🇮🇳 India	836,256	76.05	6.96
163	Sirajganj	🇧🇩 Bangladesh	3,519,019	76.01	6.96
164	Barnala	🇮🇳 India	632,391	75.77	6.94
165	Rajbari	🇧🇩 Bangladesh	1,200,635	75.79	6.94
166	Moga	🇮🇳 India	1,066,611	75.71	6.93
167	Chittagong	🇧🇩 Bangladesh	8,657,012	75.54	6.91
168	Purnia	🇮🇳 India	3,765,574	75.28	6.89
169	Narail	🇧🇩 Bangladesh	832,039	75.08	6.87
170	Firozpur	🇮🇳 India	1,111,585	74.70	6.83
171	Nawada	🇮🇳 India	2,589,681	74.74	6.83
172	Baloda Bazar	🇮🇳 India	1,451,746	74.54	6.81
173	Ludhiana	🇮🇳 India	3,748,900	74.41	6.80
174	Supaul	🇮🇳 India	2,580,752	74.22	6.78
175	Muzaffarnagar	🇮🇳 India	3,303,410	74.04	6.77
176	Purbi Singhbhum	🇳🇵 Nepal	2,635,476	74.13	6.77
177	Siraha	🇮🇳 India	739,781	73.54	6.72
178	West Tripura	🇮🇳 India	999,367	73.58	6.72
179	Aurangabad	🇧🇩 Bangladesh	2,918,688	73.47	6.71
180	Mymensingh	🇮🇳 India	5,815,595	73.52	6.71
181	Barddhaman	🇮🇳 India	8,343,103	73.23	6.69
182	Datia	🇧🇩 Bangladesh	991,340	73.29	6.69
183	Bagerhat	🇮🇳 India	1,670,296	73.15	6.68
184	Kapurthala	🇧🇩 Bangladesh	860,156	73.03	6.67
185	Khulna	🇮🇳 India	2,636,746	72.92	6.66
186	Amroha	🇮🇳 India	2,354,366	72.90	6.65
187	Hooghly	🇧🇩 Bangladesh	5,980,019	72.83	6.65
188	Jhenaidah	🇧🇩 Bangladesh	1,997,294	72.64	6.63
189	Pabna	🇮🇳 India	2,879,661	72.45	6.61
190	Maldah	🇵🇰 Pakistan	4,321,272	72.25	6.59
191	Sheikhupura	🇮🇳 India	2,953,596	72.23	6.59
192	Ramgarh	🇮🇳 India	1,068,341	72.12	6.58
193	Janjgir-Champa	🇮🇳 India	1,857,077	71.79	6.55
194	Saraikela-kharsawan	🇮🇳 India	1,182,937	71.73	6.54
195	Kurukshetra	🇮🇳 India	1,287,013	71.42	6.51
196	Gaya	🇧🇩 Bangladesh	5,063,630	71.37	6.50
197	Jhalokati	🇧🇩 Bangladesh	770,500	71.22	6.49
198	Habiganj	🇧🇩 Bangladesh	2,373,769	71.16	6.48
199	Chuadanga	🇮🇳 India	1,308,928	70.79	6.45
200	Jalandhar	🇵🇰 Pakistan	2,364,897	70.75	6.44
201	Kasur	🇧🇩 Bangladesh	3,295,626	70.45	6.41
202	Kushtia	🇧🇩 Bangladesh	2,188,126	70.42	6.41
203	Jessore	🇧🇩 Bangladesh	3,143,329	70.16	6.39
204	Pirojpur	🇧🇩 Bangladesh	1,273,248	70.20	6.39
205	Natore	🇧🇩 Bangladesh	1,922,037	69.79	6.35
206	Naogaon	🇮🇳 India	2,970,897	69.70	6.34
207	Gomati	🇮🇳 India	583,499	69.59	6.33
208	Mungeli	🇧🇩 Bangladesh	823,853	69.62	6.33
209	Meherpur	🇮🇳 India	745,202	69.31	6.30
210	Mahoba	🇧🇩 Bangladesh	971,958	69.20	6.29
211	Bogra	🇳🇵 Nepal	3,873,077	69.13	6.28
212	Nawalparasi West	🇮🇳 India	383,219	69.13	6.28
213	Dakshin Dinajpur	🇮🇳 India	1,753,778	68.84	6.26
214	Karauli	🇧🇩 Bangladesh	1,697,579	68.75	6.25
215	Patuakhali	🇳🇵 Nepal	1,741,154	68.66	6.24
216	Rupandehi	🇮🇳 India	1,011,004	68.43	6.22
217	Dausa	🇮🇳 India	1,883,851	68.25	6.20
218	Jamtara	🇮🇳 India	888,658	68.19	6.19
219	Banka	🇳🇵 Nepal	2,351,874	67.93	6.17
220	Saptari	🇮🇳 India	740,836	67.98	6.17
221	Pashchimi Singhbhum	🇧🇩 Bangladesh	1,700,885	67.86	6.16
222	Jamalpur	🇮🇳 India	2,630,068	67.73	6.15
223	Jamui	🇧🇩 Bangladesh	2,054,451	67.77	6.15
224	Joypurhat	🇮🇳 India	1,036,252	67.60	6.14
225	Mahasamund	🇳🇵 Nepal	1,191,325	67.61	6.14
226	Kapilbastu	🇧🇩 Bangladesh	659,389	67.59	6.13
227	Rajshahi	🇮🇳 India	2,973,646	67.52	6.13
228	Araria	🇮🇳 India	3,280,698	67.22	6.10
229	Nadia	🇮🇳 India	5,654,066	67.21	6.10
230	Godda	🇮🇳 India	1,490,512	67.00	6.08
231	Pilibhit	🇮🇳 India	2,311,365	67.05	6.08
232	Dhamtari	🇮🇳 India	917,922	66.97	6.07
233	Hanumangarh	🇮🇳 India	1,815,270	66.93	6.07
234	Saharanpur	🇮🇳 India	3,818,439	66.93	6.07
235	Rajnandgaon	🇧🇩 Bangladesh	1,735,370	66.84	6.06
236	Satkhira	🇧🇩 Bangladesh	2,258,751	66.79	6.06
237	Khagrachhari	🇮🇳 India	678,444	66.58	6.03
238	Bilaspur	🇮🇳 India	2,211,061	66.43	6.02
239	Fazilka	🇮🇳 India	1,063,160	66.42	6.02
240	Jhansi	🇮🇳 India	2,259,633	66.31	6.01
241	Nawabganj	🇧🇩 Bangladesh	1,868,195	66.20	6.00
242	Sahibganj	🇮🇳 India	1,331,999	66.05	5.98
243	Moradabad	🇮🇳 India	3,267,062	65.71	5.95
244	Patiala	🇮🇳 India	2,045,209	65.65	5.94
245	Fatehgarh Sahib	🇮🇳 India	656,825	65.55	5.93
246	Birbhum	🇮🇳 India	3,777,754	65.15	5.89
247	Balod	🇮🇳 India	712,346	64.96	5.88
248	Peshawar	🇵🇰 Pakistan	4,795,827	64.76	5.86
249	Gaibandha	🇧🇩 Bangladesh	2,706,023	64.60	5.84
250	Gurdaspur	🇮🇳 India	1,912,105	64.44	5.83
251	Pashchim Medinipur	🇮🇳 India	6,372,521	64.34	5.82
252	Rampur	🇮🇳 India	2,661,235	64.36	5.82
253	Bargarh	🇮🇳 India	1,597,870	64.26	5.81
254	Uttar Dinajpur	🇮🇳 India	3,367,379	64.33	5.81
255	Rewa	🇮🇳 India	2,669,379	64.23	5.80
256	Dinajpur	🇧🇩 Bangladesh	3,416,688	63.98	5.78
257	Kabirdham	🇮🇳 India	907,766	63.87	5.77
258	Murshidabad	🇮🇳 India	7,711,949	63.89	5.77
259	Sawai Madhopur	🇮🇳 India	1,423,001	63.73	5.76
260	Khowai	🇮🇳 India	477,965	63.71	5.75
261	Sherpur	🇧🇩 Bangladesh	1,541,333	63.66	5.75
262	Nankana Sahib	🇵🇰 Pakistan	1,267,144	63.35	5.72
263	Barguna	🇧🇩 Bangladesh	995,933	63.20	5.70
264	Khunti	🇮🇳 India	615,993	63.16	5.70
265	Cox'S Bazar	🇧🇩 Bangladesh	3,452,970	62.69	5.65
266	Yamunanagar	🇮🇳 India	1,081,123	62.70	5.65
267	Gujranwala	🇵🇰 Pakistan	4,481,732	62.45	5.63
268	Rangamati	🇧🇩 Bangladesh	687,439	62.20	5.61
269	Ulan Bator	🇲🇳 Mongolia	1,477,064	62.29	5.61
270	Giridih	🇮🇳 India	2,759,940	62.12	5.60
271	Netrakona	🇧🇩 Bangladesh	2,537,434	62.19	5.60
272	North 24 Parganas	🇮🇳 India	11,094,091	62.17	5.60
273	Ranchi	🇮🇳 India	3,274,251	62.00	5.59
274	Banke	🇳🇵 Nepal	565,005	61.80	5.57
275	Pakur	🇮🇳 India	997,908	61.77	5.56
276	Jharsuguda	🇮🇳 India	625,924	61.60	5.55
277	Jhunjhunu	🇮🇳 India	2,388,813	61.55	5.54
278	Howrah	🇮🇳 India	5,178,193	61.36	5.52
279	Morang	🇳🇵 Nepal	1,122,303	61.32	5.52
280	Sunsari	🇳🇵 Nepal	857,275	61.36	5.52
281	Phuentsholing	🇧🇹 Bhutan	29,158	60.85	5.47
282	Raigarh	🇮🇳 India	1,710,339	60.77	5.47
283	Shahid Bhagat Singh Nagar	🇮🇳 India	681,192	60.79	5.47
284	Deoghar	🇮🇳 India	1,692,622	60.48	5.44
285	Purba Medinipur	🇮🇳 India	5,537,027	60.48	5.44
286	Kishanganj	🇮🇳 India	1,986,137	60.32	5.42
287	Bardiya	🇳🇵 Nepal	492,390	60.17	5.41
288	Hauts Plateaux	🇨🇲 Cameroon	116,568	60.06	5.40
289	Jaipur	🇮🇳 India	7,480,292	60.15	5.40
290	Kodarma	🇮🇳 India	479,641	59.76	5.37
291	Nowshera	🇵🇰 Pakistan	1,817,314	59.67	5.36
292	Satna	🇮🇳 India	2,488,784	59.73	5.36
293	Sialkot	🇵🇰 Pakistan	3,559,383	59.59	5.35
294	Thakurgaon	🇧🇩 Bangladesh	1,586,640	59.53	5.34
295	Hazaribagh	🇮🇳 India	2,325,639	59.36	5.33
296	South 24 Parganas	🇮🇳 India	8,750,991	59.26	5.32
297	Rangpur	🇧🇩 Bangladesh	3,320,617	59.17	5.31
298	Kolkata	🇮🇳 India	4,508,259	58.89	5.28
299	Mayurbhanj	🇮🇳 India	2,723,504	58.86	5.28
300	Jhapa	🇳🇵 Nepal	933,761	58.74	5.27
301	Narowal	🇵🇰 Pakistan	1,743,880	58.69	5.26
302	Sambalpur	🇮🇳 India	1,129,855	58.69	5.26
303	Koung Khi	🇨🇲 Cameroon	95,973	58.60	5.25
304	Yoeseltse	🇧🇹 Bhutan	2,335	58.60	5.25
305	Charsadda	🇵🇰 Pakistan	1,914,699	58.51	5.24
306	Dhalai	🇮🇳 India	415,644	58.48	5.24
307	Hardwar	🇮🇳 India	2,152,031	58.44	5.24
308	Ambala	🇮🇳 India	1,356,523	58.22	5.22
309	Dumka	🇮🇳 India	1,526,726	58.30	5.22
310	Menoua	🇨🇲 Cameroon	410,985	58.26	5.22
311	Bandarban	🇧🇩 Bangladesh	468,571	58.21	5.21
312	Sundargarh	🇮🇳 India	2,264,207	58.14	5.21
313	Maulvibazar	🇧🇩 Bangladesh	2,169,514	57.80	5.17
314	Tonk	🇮🇳 India	1,609,971	57.63	5.16
315	Ugentse	🇧🇹 Bhutan	1,604	57.58	5.15
316	Kendujhar	🇮🇳 India	1,943,855	57.40	5.14
317	Jalpaiguri	🇮🇳 India	2,858,453	57.37	5.13
318	Bhandara	🇮🇳 India	1,561,052	57.04	5.10
319	Chhatarpur	🇮🇳 India	1,989,140	57.00	5.10
320	Bundi	🇮🇳 India	1,198,331	56.81	5.08
321	Swabi	🇮🇳 India	1,586,444	56.79	5.08
322	Mardan	🇵🇰 Pakistan	2,414,561	56.28	5.03
323	Norbugang	🇧🇹 Bhutan	5,064	56.37	5.03
324	Samtse	🇧🇹 Bhutan	10,802	56.31	5.03
325	Simdega	🇮🇳 India	682,501	56.25	5.02
326	Alipurduar	🇮🇳 India	1,368,534	55.88	4.99
327	Nawalparasi East	🇳🇵 Nepal	358,958	55.95	4.99
328	Nilphamari	🇧🇩 Bangladesh	2,023,687	55.96	4.99
329	Bijnor	🇮🇳 India	4,095,135	55.83	4.98
330	Gondiya	🇮🇳 India	1,199,307	55.77	4.98
331	Tikamgarh	🇮🇳 India	1,639,570	55.86	4.98
332	Tashicholing	🇧🇹 Bhutan	3,976	55.72	4.97
333	Unokoti	🇮🇳 India	472,728	55.67	4.97
334	Subarnapur	🇮🇳 India	662,158	55.61	4.96
335	Korba	🇮🇳 India	1,381,578	55.51	4.95
336	Sangngagchhoeling	🇧🇹 Bhutan	4,254	55.52	4.95
337	Balangir	🇮🇳 India	1,784,135	55.44	4.94
338	Chitawan	🇳🇵 Nepal	660,759	55.39	4.94
339	Sheopur	🇮🇳 India	782,116	55.16	4.92
340	Bamboutos	🇨🇲 Cameroon	419,785	55.08	4.91
341	Mifi	🇨🇲 Cameroon	430,147	55.07	4.91
342	Chatra	🇮🇳 India	1,170,688	55.00	4.90
343	Okara	🇵🇰 Pakistan	2,909,813	55.00	4.90
344	Sittwe	🇲🇲 Myanmar	655,680	55.02	4.90
345	Kailali	🇳🇵 Nepal	892,709	54.93	4.89
346	Hafizabad	🇵🇰 Pakistan	1,276,369	54.77	4.88
347	Phuentshogpelri	🇧🇹 Bhutan	8,932	54.83	4.88
348	South West Garo Hills	🇮🇳 India	188,946	54.73	4.87
349	Sikar	🇮🇳 India	3,012,667	54.62	4.86
350	Kurigram	🇧🇩 Bangladesh	2,357,408	54.50	4.85
351	Udayapur	🇳🇵 Nepal	365,638	54.37	4.84
352	Kota	🇮🇳 India	2,248,274	54.15	4.82
353	Samphelling	🇧🇹 Bhutan	7,819	54.09	4.81
354	Sunamganj	🇧🇩 Bangladesh	2,798,538	53.92	4.79
355	Hoshiarpur	🇮🇳 India	1,737,017	53.80	4.78
356	Ganganagar	🇮🇳 India	2,389,908	53.72	4.77
357	Nagpur	🇮🇳 India	5,094,050	53.66	4.77
358	Jabalpur	🇮🇳 India	2,427,332	53.45	4.75
359	Maungdaw	🇲🇲 Myanmar	116,245	53.38	4.74
360	Nuapada	🇮🇳 India	642,845	53.16	4.72
361	Panchagarh	🇧🇩 Bangladesh	1,164,095	53.12	4.72
362	Shompangkha	🇧🇹 Bhutan	2,067	53.18	4.72
363	Gariaband	🇮🇳 India	596,091	52.98	4.70
364	Palamu	🇮🇳 India	2,201,776	52.97	4.70
365	Sahibzada Ajit Singh Nagar	🇮🇳 India	1,024,166	52.80	4.68
366	Kanchanpur	🇳🇵 Nepal	522,868	52.69	4.67
367	Pakpattan	🇵🇰 Pakistan	1,976,068	52.62	4.67
368	Sergelen	🇲🇳 Mongolia	19,790	52.67	4.67
369	Akola	🇮🇳 India	2,021,846	52.52	4.66
370	Churu	🇮🇳 India	2,633,046	52.55	4.66
371	Deogarh	🇮🇳 India	339,476	52.50	4.66
372	Sidhi	🇮🇳 India	1,267,065	52.59	4.66
373	Lalitpur	🇮🇳 India	1,354,546	52.28	4.63
374	Mezam	🇨🇲 Cameroon	766,082	52.24	4.63
375	Lalmonirhat	🇧🇩 Bangladesh	1,441,377	51.93	4.60
376	Balaghat	🇮🇳 India	1,908,869	51.73	4.58
377	Gumla	🇮🇳 India	1,164,751	51.69	4.58
378	Nichula	🇧🇹 Bhutan	801	51.78	4.58
379	Jalgaon	🇮🇳 India	4,619,083	51.59	4.57
380	Lohardaga	🇮🇳 India	522,373	51.65	4.57
381	Dhenkanal	🇮🇳 India	1,289,362	51.41	4.55
382	Lhamoi Zingkha	🇧🇹 Bhutan	3,744	51.46	4.55
383	Senggey	🇧🇹 Bhutan	3,904	51.44	4.55
384	Katni	🇮🇳 India	1,790,495	51.36	4.54
385	Anugul	🇮🇳 India	1,372,767	51.25	4.53
386	Panna	🇮🇳 India	1,146,621	51.27	4.53
387	Baleshwar	🇮🇳 India	2,484,448	51.08	4.52
388	Baran	🇮🇳 India	1,401,375	51.16	4.52
389	Mandi Bahauddin	🇵🇰 Pakistan	2,086,078	51.12	4.52
390	Ndé	🇨🇲 Cameroon	135,543	51.10	4.52
391	Islamabad	🇵🇰 Pakistan	2,930,804	50.97	4.51
392	North Tripura	🇮🇳 India	289,307	50.93	4.50
393	Darjeeling	🇮🇳 India	1,920,808	50.79	4.49
394	Momo	🇨🇲 Cameroon	204,616	50.79	4.49
395	Haut Nkam	🇨🇲 Cameroon	207,959	50.70	4.48
396	Damoh	🇮🇳 India	1,434,975	50.57	4.47
397	Buldhana	🇮🇳 India	2,788,165	50.46	4.46
398	Lawangtlai	🇮🇳 India	131,595	50.52	4.46
399	Narsimhapur	🇮🇳 India	1,236,623	50.52	4.46
400	Uttar Bastar Kanker	🇮🇳 India	865,701	50.50	4.46
401	Mixco	🇬🇹 Guatemala	545,151	50.29	4.44
402	Pemaling	🇧🇹 Bhutan	3,741	50.31	4.44
403	Rahim Yar Khan	🇵🇰 Pakistan	5,044,208	50.32	4.44
404	Sonbhadra	🇮🇳 India	2,086,251	50.17	4.43
405	Magdalena Milpas Altas	🇬🇹 Guatemala	16,259	50.13	4.42
406	Burhanpur	🇮🇳 India	847,005	50.02	4.41
407	San Lucas Sacatepéquez	🇬🇹 Guatemala	34,603	49.99	4.41
408	Sindhuli	🇳🇵 Nepal	339,642	50.01	4.41
409	Wardha	🇮🇳 India	1,436,022	50.03	4.41
410	Latehar	🇮🇳 India	832,653	49.88	4.40
411	Nagaur	🇮🇳 India	3,740,764	49.92	4.40
412	Amravati	🇮🇳 India	3,137,975	49.79	4.39
413	Santa María de Jesús	🇬🇹 Guatemala	25,059	49.77	4.39
414	Tando Allahyar	🇵🇰 Pakistan	664,646	49.76	4.39
415	Garhwa	🇮🇳 India	1,501,173	49.66	4.38
416	Mangai	🇨🇩 DRC	7,806	49.72	4.38
417	Shivpuri	🇮🇳 India	1,929,599	49.67	4.38
418	Bhadrak	🇮🇳 India	1,638,192	49.56	4.37
419	Bui	🇨🇲 Cameroon	470,134	49.54	4.37
420	Udham Singh Nagar	🇮🇳 India	1,919,016	49.56	4.37
421	Vidisha	🇮🇳 India	1,636,489	49.64	4.37
422	Matiari	🇵🇰 Pakistan	508,161	49.48	4.36
423	Bhopal	🇮🇳 India	2,656,340	49.42	4.35
424	East Nimar	🇮🇳 India	1,468,738	49.44	4.35
425	Khargone	🇮🇳 India	2,101,956	49.36	4.35
426	Hoshangabad	🇮🇳 India	1,410,240	49.29	4.34
427	Mandsaur	🇮🇳 India	1,492,717	49.28	4.34
428	Mrauk-U	🇲🇲 Myanmar	823,866	49.30	4.34
429	Raisen	🇮🇳 India	1,508,510	49.17	4.33
430	Sagar	🇮🇳 India	2,673,555	49.19	4.33
431	Rawalpindi	🇵🇰 Pakistan	5,905,278	49.10	4.32
432	Santa Catarina Pinula	🇬🇹 Guatemala	70,527	48.97	4.31
433	Shijiazhuang	🇨🇳 China	10,674,480	49.00	4.31
434	Zone 19, Guatemala City	🇬🇹 Guatemala	11,669	48.99	4.31
435	Ghotki	🇵🇰 Pakistan	1,479,552	48.91	4.30
436	Jajapur	🇮🇳 India	1,964,648	48.86	4.30
437	Ahmadabad	🇮🇳 India	8,114,639	48.80	4.29
438	Jhalawar	🇮🇳 India	1,620,719	48.78	4.29
439	Santiago Sacatepéquez	🇬🇹 Guatemala	35,299	48.78	4.29
440	Chandigarh	🇮🇳 India	1,166,507	48.65	4.28
441	Sehore	🇮🇳 India	1,452,468	48.70	4.28
442	Bahawalnagar	🇵🇰 Pakistan	3,895,468	48.56	4.27
443	Harda	🇮🇳 India	655,244	48.58	4.27
444	San Bartolomé Milpas Altas	🇬🇹 Guatemala	11,637	48.56	4.27
445	Sylhet	🇧🇩 Bangladesh	3,903,758	48.52	4.27
446	Lodhran	🇵🇰 Pakistan	2,265,233	48.35	4.25
447	Muzaffargarh	🇵🇰 Pakistan	4,850,114	48.32	4.25
448	Ashoknagar	🇮🇳 India	957,807	48.29	4.24
449	Rajgarh	🇮🇳 India	1,732,705	48.30	4.24
450	Seoni	🇮🇳 India	1,547,462	48.24	4.24
451	Dekiling	🇧🇹 Bhutan	4,535	48.11	4.23
452	Ciudad Vieja	🇬🇹 Guatemala	36,973	48.01	4.22
453	Gelephu	🇧🇹 Bhutan	18,144	48.02	4.22
454	Luebo (ville)	🇨🇩 DRC	26,520	48.02	4.22
455	Multan	🇵🇰 Pakistan	5,764,769	48.09	4.22
456	Rupnagar	🇮🇳 India	755,595	48.10	4.22
457	Koch Bihar	🇮🇳 India	3,037,219	47.95	4.21
458	Umaria	🇮🇳 India	591,381	47.87	4.20
459	Makawanpur	🇳🇵 Nepal	481,797	47.76	4.19
460	Rajanpur	🇵🇰 Pakistan	1,840,129	47.75	4.19
461	Ajmer	🇮🇳 India	2,938,947	47.70	4.18
462	Agar Malwa	🇮🇳 India	734,877	47.50	4.17
463	Attock	🇵🇰 Pakistan	3,028,390	47.56	4.17
464	Gujrat	🇵🇰 Pakistan	3,446,394	47.59	4.17
465	Ilebo	🇨🇩 DRC	501,407	47.54	4.17
466	Liaocheng	🇨🇳 China	6,045,858	47.52	4.17
467	Santa Lucía Milpas Altas	🇬🇹 Guatemala	19,667	47.52	4.17
468	Shaheed Benazir Abad	🇵🇰 Pakistan	1,296,630	47.59	4.17
469	Oshwe	🇨🇩 DRC	318,099	47.44	4.16
470	Boudh	🇮🇳 India	480,376	47.40	4.15
471	Shajapur	🇮🇳 India	955,085	47.30	4.15
472	Shikarpur	🇵🇰 Pakistan	722,634	47.30	4.15
473	Chhuzagang	🇧🇹 Bhutan	1,822	47.22	4.14
474	Kashmore	🇵🇰 Pakistan	809,600	47.21	4.14
475	Namgaychhoeling	🇧🇹 Bhutan	3,109	47.20	4.14
476	Naushahro Feroze	🇵🇰 Pakistan	1,350,500	47.27	4.14
477	Zone 7, Guatemala City	🇬🇹 Guatemala	112,441	47.25	4.14
478	San Antonio Aguas Calientes	🇬🇹 Guatemala	13,945	47.18	4.13
479	Ilebo (ville)	🇨🇩 DRC	96,367	47.01	4.12
480	Jocotenango	🇬🇹 Guatemala	24,135	47.04	4.12
481	Kutu	🇨🇩 DRC	744,416	46.99	4.12
482	Ngo Ketunjia	🇨🇲 Cameroon	274,429	47.06	4.12
483	Nioki	🇨🇩 DRC	73,902	47.06	4.12
484	Luebo	🇨🇩 DRC	295,887	46.89	4.11
485	Pastores	🇬🇹 Guatemala	21,379	46.88	4.10
486	Jalna	🇮🇳 India	2,140,052	46.69	4.09
487	Pune	🇮🇳 India	10,338,864	46.69	4.09
488	South Garo Hills	🇮🇳 India	163,681	46.76	4.09
489	Sahiwal	🇵🇰 Pakistan	2,688,960	46.67	4.08
490	Samtenling	🇧🇹 Bhutan	2,175	46.61	4.08
491	Santa Catarina Barahona	🇬🇹 Guatemala	3,438	46.65	4.08
492	Sumpango	🇬🇹 Guatemala	42,564	46.61	4.08
493	Vehari	🇵🇰 Pakistan	3,242,853	46.62	4.08
494	Cuttack	🇮🇳 India	2,903,817	46.58	4.07
495	Hyderabad	🇵🇰 Pakistan	1,446,968	46.50	4.07
496	Tading	🇧🇹 Bhutan	4,314	46.50	4.07
497	Chandrapur	🇮🇳 India	2,414,695	46.41	4.06
498	Fraijanes	🇬🇹 Guatemala	67,417	46.38	4.06
499	Gandhinagar	🇮🇳 India	1,312,495	46.46	4.06
500	Yumbi	🇨🇩 DRC	138,552	46.45	4.06

Note: Data for some cities in the DRC and Egypt is mislabeled in the source and has been omitted from this table.

For instance, residents of the national capital region of India could live nearly 12 years longer if they had cleaner air. In fact the top 78 cities with the most to gain from better air quality are all in India, located in and around the north and northwest regions of the country.

Cities in the broader South Asian region—Bangladesh, Nepal, Pakistan—also feature in the top 500 cities list.

Greater industrialization, economic activity, and rapid population growth in the last two decades have combined to make South Asia a global hotspot for air pollution. Other unique practices in the region that exacerbate the problem include: solid fuel combustion for cooking, burning agricultural waste, and cremation.

Only a few cities, like Melbourne, Australia, meet the WHO guideline. The AQLI report found that 98.4% of the world’s population lives in regions whose air quality is worse than recommended standards.

There is also a significant correlation between a country’s per capita GDP and their air quality; richer countries have cleaner air and vice-versa.

Air Pollution Has the Biggest Impact on Life Expectancy

But perhaps most surprising is how much worse air pollution is to human health, compared to other causes of disease and death. Measured in terms of life expectancy, the AQLI finds that ambient particulate pollution is consistently the world’s greatest external risk to human health.

Click to view this graphic in a higher-resolution.

Globally, particulate pollution reduces average life expectancy the most, worse than tobacco use (2.2 years), unsafe water, sanitation and handwashing (0.6 years), and nutritional deficiencies (0.1 years).

Thus, the impact of particulate pollution on life expectancy is 3.8 times that of exposure to unsafe water, and 23 times that of nutritional deficiencies.

This article was published as a part of Visual Capitalist's Creator Program, which features data-driven visuals from some of our favorite Creators around the world.

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Green

Ranked: Top 15 Countries by Carbon Emissions

This graphic is a revamped look at the top 15 countries by carbon emissions in 2023, visually comparing them to each other for better insights.

Published

6 days ago

July 13, 2025

Pallavi Rao

This cropped graphic compares the top 15 countries by carbon emissions in 2023.

Ranked: Top 15 Countries by Carbon Emissions in 2023

This was originally posted on our Voronoi app. Download the app for free on iOS or Android and discover incredible data-driven charts from a variety of trusted sources.

Key Takeaways

China ranks first by a large margin in the list of top countries by carbon emissions in 2023.
It accounts for nearly one-third of global carbon emissions at 15.9 GtCO₂e in 2023.
But this also reflects China’s extensive manufacturing industry that produces much of the world’s goods.

Despite countries pivoting and investing in clean energy sources in the last decade, global greenhouse gas emissions still hit new highs in 2023.

This infographic ranks the top 15 countries by carbon emissions, based on 2023 data from The Emissions Database for Global Atmospheric Research. It shows national-level greenhouse gas emissions in gigatonnes of CO₂ equivalent (GtCO₂e).

Together, these nations account for nearly 80% of global emissions.

China vs the World: Carbon Emissions Edition

China leads the world in emissions with 15.9 GtCO₂e, representing 30.1% of the global total in 2023.

Rank	Country	GHG Emissions (2023)	Share of Global Emissions
1	🇨🇳 China	15.9 GtCO₂e	30.1%
2	🇺🇸 U.S.	6.0 GtCO₂e	11.3%
3	🇮🇳 India	4.1 GtCO₂e	7.8%
4	🇪🇺 EU	3.2 GtCO₂e	6.1%
5	🇷🇺 Russia	2.7 GtCO₂e	5.0%
6	🇧🇷 Brazil	1.3 GtCO₂e	2.5%
7	🇮🇩 Indonesia	1.2 GtCO₂e	2.3%
8	🇯🇵 Japan	1.0 GtCO₂e	2.0%
9	🇮🇷 Iran	1.0 GtCO₂e	1.9%
10	🇸🇦 Saudi Arabia	0.8 GtCO₂e	1.5%
11	🇨🇦 Canada	0.7 GtCO₂e	1.4%
12	🇲🇽 Mexico	0.7 GtCO₂e	1.3%
13	🇰🇷 South Korea	0.7 GtCO₂e	1.2%
14	🇹🇷 Türkiye	0.6 GtCO₂e	1.1%
15	🇦🇺 Australia	0.6 GtCO₂e	1.1%
N/A	Top 15	41.0 GtCO₂e	76.6%

This reflects its role as the world’s manufacturing hub, with heavy reliance on coal and high industrial output.

In fact, China’s share of global manufacturing is also about the same (27%) showing the direct consequence of becoming the world’s production base.

The country has committed to peaking emissions before 2030, but its growth trajectory poses challenges.

This also means any progress on climate will hinge heavily both on China’s policy decisions and global consumer behavior.

U.S. and India Round Out the Top Three Carbon Emissions

The U.S. is the second-largest emitter at 6.0 GtCO₂e (11.3% of global emissions).

And this is with around 330 million people, or one-fourth of China’s population. It’s per capita emissions (15 tCO₂e) is also top-15 in the world.

In stark contrast, India ranks third with 4.1 GtCO₂e (7.8%), lower than the U.S., with four times the number of people. However, its emissions are rising as its economy and population grow, following a similar path Western industrialized countries took to prosperity.