diff --git a/README.md b/README.md
index 31281e5..808b50a 100644
--- a/README.md
+++ b/README.md
@@ -1,9 +1,10 @@
 <h1 style="text-align: center; font-size:1vw">Environmental Insights</h1>
 
 <p align="center">
-  <img src="_static/environmental_insights.png" />
+  <img src="https://github.com/berrli/Environmental-Insights/raw/main/_static/environmental_insights.png" alt="Environmental Insights" />
 </p>
 
+
 Environmental Insights is a Python package for downloading and visualising air pollution concentration data in the UK and globally. Alongside the downloaded data, a set of functions have also been provided to manipulate the air pollution concentrations and explore air pollution futures. The Python package is a companion to the paper entitled "Environmental Insights: Democratizing Access to Ambient Air Pollution Data and Predictive Analytics with an Open-Source Python Package", with the following abstract:
 \
 Ambient air pollution is a pervasive issue with wide-ranging effects on human health, ecosystem vitality, and economic structures. Utilizing data on ambient air pollution concentrations, researchers can perform comprehensive analyses to uncover the multifaceted impacts of air pollution across society. To this end, we introduce Environmental Insights, an open-source Python package designed to democratize access to air pollution concentration data. This tool enables users to easily retrieve historical air pollution data and employ a Machine Learning model for forecasting potential future conditions. Moreover, Environmental Insights includes a suite of tools aimed at facilitating the dissemination of analytical findings and enhancing user engagement through dynamic visualizations. This comprehensive approach ensures that the package caters to the diverse needs of individuals looking to explore and understand air pollution trends and their implications.
@@ -82,6 +83,4 @@ The documentation for the project is included within the directory "Documentatio
 
 ## Pypip
 
-Using `python -m build` will use the `pyproject.toml` file to locally build the package and store it within the `dist` directory. This can then be installed using `pip install dist/*.whl`. The final `dist` files can be uploaded to PyPI via twine. 
-
-## Conda
+Using `python -m build` will use the `pyproject.toml` file to locally build the package and store it within the `dist` directory. This can then be installed using `pip install dist/*.whl`. The final `dist` files can be uploaded to PyPI via twine. 
\ No newline at end of file
diff --git a/meta.yaml b/meta.yaml
deleted file mode 100644
index 7f2c784..0000000
--- a/meta.yaml
+++ /dev/null
@@ -1,48 +0,0 @@
-package:
-  name: environmental-insights
-  version: 0.1.0-beta
-
-source:
-  # If hosted on GitHub
-  git_url: https://github.com/berrli/Environmental-Insights.git
-  git_tag: v0.1.0-beta  # or use a specific commit SHA
-
-build:
-  noarch: python
-  script: {{ PYTHON }} -m pip install .
-
-requirements:
-  host:
-    - python >=3.6
-    - pip
-
-  run:
-    - python >=3.6
-    - lightgbm ==3.3.3
-    - geopandas ==0.14.1
-    - pandas ==2.1.3
-    - scipy ==1.11.4
-    - matplotlib ==3.8.2
-    - overpy ==0.6
-    - shapely ==2.0.2
-    - pyarrow ==14.0.1
-    - pyogrio ==0.7.2
-
-test:
-  imports:
-    - environmental_insights
-
-  commands:
-    - insights --help
-
-about:
-  home: https://github.com/berrli/Environmental-Insights
-  license: GPL-3.0
-  license_family: GPL
-  summary: A Python package for democratizing access to ambient air pollution data and predictive analytics.
-  description: |
-    Environmental Insights provides tools to access and analyze ambient air pollution data, enabling predictive analytics and insights into environmental impacts.
-
-extra:
-  recipe-maintainers:
-    - berrli
diff --git a/pyproject.toml b/pyproject.toml
index 1de6988..463c50f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "environmental-insights"
-version = "0.1.0-beta"
+version = "0.1.3_beta"
 description = "A Python package for democratizing access to ambient air pollution data and predictive analytics."
 readme = "README.md"
 requires-python = ">=3.6"